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mode 100644 doc/releases/0.1.0/steps/webvowl/license.txt create mode 100755 doc/run_full_build.sh diff --git a/doc/releases/0.1.0/base/index.html b/doc/releases/0.1.0/base/index.html new file mode 100644 index 0000000..767fff9 --- /dev/null +++ b/doc/releases/0.1.0/base/index.html @@ -0,0 +1,962 @@ + + + Neuroelectrophysiology Analysis Ontology - Base classes + + + + + + + + + +
+
+
language en
+

Neuroelectrophysiology Analysis Ontology - Base classes

+

Release: 2024-12-06

+ + +
+
This version:
+
http://purl.org/neao/0.1.0/base#
+
Latest version:
+
http://purl.org/neao/base#
+
Revision:
+
0.1.0
+
Issued on:
+
2024-12-06
+
Authors:
+
Cristiano Köhler, Forschungszentrum Jülich
Michael Denker, Forschungszentrum Jülich
+ +
License:
https://creativecommons.org/licenses/by/4.0/ +
Visualization:
Visualize with WebVowl
+
+ +Provenance of this page
+
+
+
+Ontology Specification Draft +
+
+
+ + +

Introduction back to ToC

+

Thist module defines the core classes and properties used in the Neuroelectrophysiology Analysis Ontology (NEAO).

 +
+

Namespace declarations

+
+ + + + + + + + + + + + + + +
Table 1: Namespaces used in the document
biro<http://purl.org/spar/biro/>
dcterms<http://purl.org/dc/terms/>
neao_base<http://purl.org/neao/base#>
owl<http://www.w3.org/2002/07/owl#>
rdf<http://www.w3.org/1999/02/22-rdf-syntax-ns#>
rdfs<http://www.w3.org/2000/01/rdf-schema#>
skos<http://www.w3.org/2004/02/skos/core#>
vann<http://purl.org/vocab/vann/>
xml<http://www.w3.org/XML/1998/namespace>
xsd<http://www.w3.org/2001/XMLSchema#>
+
+
+
+ + + +

NEAO Base classes: Overview back to ToC

+ +This ontology has the following classes and properties. +

Classes

+

Object Properties

Data Properties

Annotation Properties

+
+ + + +

NEAO Base classes: Description back to ToC

+ +

An overview of the main relationships is depicted in the diagram below:

+ +

+ +

The NEAO ontology model is constructed upon the central AnalysisStep class, that represents any process that generates new data entities (e.g., generating artificial spike trains) or performs specific operations aimed at extracting additional information during the analysis using existing data entities. For example, a time series with the raw signal recorded from an electrode can be low-pass filtered to extract the local field potential (LFP) component (the step produces transformed data). Additionaly, this new time series with the LFP data can be used in another step to compute the power spectral density (the step produces new, derived data). Therefore, every stage of the analysis generates new data or applies particular operations to data entities.

+ +

The inputs and outputs of the analysis steps are represented by the Data class. This represents any entity storing information needed throughout the analysis. It might represent the data created or transformed by an analysis step, or it can represent data from an electrophysiological recording obtained from neural tissue (or comparable data generated by a simulation). For example, the raw signal time series saved by the recording apparatus, the filtered LFP time series, and the array holding the power spectral density estimates are instances of the Data class.

+ +

An information entity that regulates the behavior of the analysis step is a parameter, and is represented by the AnalysisParameter class. A parameter does not provide data that is used by the step to produce the output. For example, in a low-pass filtering step in the analysis to produce the LFP, the time series with the raw wideband signal is the data input, and the low-pass frequency cutoff frequency value is a parameter.

+ +

The three core classes are related by the object properties hasInput, hasOutput, and usesParameter. Furthermore, several annotation properties are used to provide clear and unambiguous descriptions of the entities represented by the classes. These include abbreviations (abbreviation property), bibliographic references (hasBibliographicReference), labels (skos:prefLabel and skos:altLabel properties) and the class description (using rdfs:comment property).

+ +

For the disambiguation, the skos:prefLabel annotation property provides the preferred label to refer to the entity, and the rdfs:comment annotation provides details to understand the entity (e.g., details of the computation, inputs, and outputs involved in an analysis step). Synonyms are provided by the skos:altLabel property. The NEAO abbreviation annotation property provides suggested abbreviations.

+ +

The specific analysis method used in a step of the analysis can be implemented by different software codes, such as distinct open-source toolboxes that are available to analyze electrophysiology data. The core NEAO model has two classes describing the software implementation of the analysis step:

+ +
    +

  • The main source of the code used to execute the operations involved in the analysis step is represented by the SoftwareImplementation class. This is the code that take any given data input, transform it, and produce the desired results.

    • +

  • The SoftwarePackage class is used to describe collections of software, such as toolboxes with many functionality for neuroelectrophysiology data analysis (i.e., that bundle together different pieces of code).

    • +
+ +

The relationship between SoftwareImplementation and SoftwarePackage is established with the property isImplementedInPackage. The relationship between the AnalysisStep and SoftwareImplementation is defined using the isImplementedIn property. The details of the individuals of each class are provided by distinct properties. The version property of SoftwareImplementation is used to define the version of the software. The packageName and packageVersion properties of SoftwarePackage specify the package name and version, respectively.

+ +

Program and Function are two subclasses of SoftwareImplementation that correspond to the two main approaches used to implement the code for an analysis step:

+ +
    +

  • The entity represented by Program is an executable that has been compiled or a complete script that the operating system can call to perform the analysis step (for example, an executable that reads a file, computes the power spectral density using the Welch technique, and saves a file containing the power spectral density).

    • +

  • The entity represented by Function is a small, reusable code that is used as a building block in larger programs that execute several steps in the analysis.

    • +
+ +

Specific details of these two forms of implementing software are defined using additional properties. The nameInDefinition property in Function specifies the name that is used in the function declaration and in applications that utilize the function code. The programName property of Program specifies the name of the program as published.

+
+ + + +

Cross-reference for NEAO Base classes classes, object properties and data properties back to ToC

+This section provides details for each class and property defined by NEAO Base classes. +
+

Classes

+ +
+

analysis stepc + back to ToC or Class ToC + +

+

+ IRI: http://purl.org/neao/base#AnalysisStep

+
+ A process that generates new data entities or performs specific operations (clean, select, transform, or inspect/visualize) using existing data entities. Ultimately, the goal is to obtain useful information from the data. An analysis step can take zero or more data inputs and can generate one or more data outputs. The behavior of the operation can optionally be controlled by one or more parameters. A complete analysis is composed by one or more analysis steps. +
+
+
is in domain of
+
+ has input + op, has output + op, has substep + op, is implemented in + op, uses parameter + op +
+
is in range of
+
+ has substep + op +
+
is disjoint with
+
+ parameter + c, data + c +
+
+
+
+

datac + back to ToC or Class ToC + +

+

+ IRI: http://purl.org/neao/base#Data

+
+ An entity that represents a piece of data, i.e., relevant information, during the analysis. It can be recorded from a biological entity or from a simulation yielding comparable data, or it can be generated/transformed by other analysis step processes. +
+
+
is in domain of
+
+ has source + op, is represented as + op +
+
is in range of
+
+ has input + op, has output + op +
+
is disjoint with
+
+ parameter + c, analysis step + c +
+
+
+
+

data representationc + back to ToC or Class ToC + +

+

+ IRI: http://purl.org/neao/base#DataRepresentation

+
+ Defines the formal structure to represent a piece of data. +
+
+
is in range of
+
+ is represented as + op +
+
+
+
+

electrophysiology signal sourcec + back to ToC or Class ToC + +

+

+ IRI: http://purl.org/neao/base#ElectrophysiologySignalSource

+
+ Defines the source of a recorded piece of electrophysiology data, i.e., the recorded signals. This is a general concept, that can be expanded to incorporate the anatomical/tissue description from where the signal was recorded, as well as the recording technique. + +For example, voltage potentials can be acquired from extracellular electrodes situtated on the scalp (electroencephalogram), directly on the cortical surface (electrocorticogram) or implanted deep into a specific brain region (multielectrode array). +
+
+
is in range of
+
+ has source + op +
+
+
+
+

functionc + back to ToC or Class ToC + +

+

+ IRI: http://purl.org/neao/base#Function

+
+ A reusable set of instructions that can be used when writing computer programs. A function performs specific tasks, and can be implemented as part of a single computer program or in a software package (library) so that it can be reused across several programs. +
+
+
has super-classes
+
+ software implementation + c +
+
is in domain of
+
+ name in definition + dp +
+
+
+
+

parameterc + back to ToC or Class ToC + +

+

+ IRI: http://purl.org/neao/base#AnalysisParameter

+
+ An information entity that controls the behavior of an analysis step. It does not provide data, but rather changes how the computations operate when transforming or generating new data. +
+
+
is in range of
+
+ uses parameter + op +
+
is disjoint with
+
+ analysis step + c, data + c +
+
+
+
+

programc + back to ToC or Class ToC + +

+

+ IRI: http://purl.org/neao/base#Program

+
+ A set of instructions that is executed by a computer. The instructions of the program can be executed by an interpreter or compiled to machine code. The program instructs the computer to perform tasks and it is called by the operating system. +
+
+
has super-classes
+
+ software implementation + c +
+
is in domain of
+
+ program name + dp +
+
+
+
+

software implementationc + back to ToC or Class ToC + +

+

+ IRI: http://purl.org/neao/base#SoftwareImplementation

+
+ Describes the details for the execution of the analysis step using a computer. The software contains a sequence or set of instructions that is used by the computer to perform all the computations required to execute the analysis step. +
+
+
has sub-classes
+
+ function + c, program + c +
+
is in domain of
+
+ is implemented in package + op, version + dp +
+
is in range of
+
+ is implemented in + op +
+
is disjoint with
+
+ software package + c +
+
+
+
+

software packagec + back to ToC or Class ToC + +

+

+ IRI: http://purl.org/neao/base#SoftwarePackage

+
+ A collection of one or more programs that can be executed by a computer and/or one or more functions that can be imported and used when writing programs. +
+
+
is in domain of
+
+ package version + dp, package version + dp +
+
is in range of
+
+ is implemented in package + op +
+
is disjoint with
+
+ software implementation + c +
+
+
+
+

Object Properties

+ +
+

has inputop + back to ToC or Object Property ToC + +

+

+ IRI: http://purl.org/neao/base#hasInput

+
+ Defines a data entity that is used to provide information for one analysis step. The analysis step will make use of this information and produce zero or more data entities as outputs. +
+
+
+
has domain
+
+ analysis step + c +
+
has range
+
+ data + c +
+
+
+
+
+

has outputop + back to ToC or Object Property ToC + +

+

+ IRI: http://purl.org/neao/base#hasOutput

+
+ Defines a data entity that was produced by an analysis step. This can be newly data generated by the analysis step, or derived data, based on one or more data inputs. +
+
+
+
has domain
+
+ analysis step + c +
+
has range
+
+ data + c +
+
+
+
+
+

has sourceop + back to ToC or Object Property ToC + +

+

+ IRI: http://purl.org/neao/base#hasSource

+
+ Defines the electrophysiology signal source associated with the data entity. One example of use is to define if the data holds a signal obtained by extracellular recordings, or a more specific description involving anatomical structures together with the recording technique. +
+
+
+
has domain
+
+ data + c +
+
has range
+
+ electrophysiology signal source + c +
+
+
+
+
+

has substepop + back to ToC or Object Property ToC + +

+

+ IRI: http://purl.org/neao/base#hasSubstep

+
+ Points to an analysis step that is part of a (larger) compound analysis, represented by the subject with the property. +
+
+
+
has domain
+
+ analysis step + c +
+
has range
+
+ analysis step + c +
+
+
+
+
+

is implemented inop + back to ToC or Object Property ToC + +

+

+ IRI: http://purl.org/neao/base#isImplementedIn

+
+ Defines the code source that implemented the analysis step. +
+
+
+
has domain
+
+ analysis step + c +
+
has range
+
+ software implementation + c +
+
+
+
+
+

is implemented in packageop + back to ToC or Object Property ToC + +

+

+ IRI: http://purl.org/neao/base#isImplementedInPackage

+
+ Defines the software package that contains a particular code. +
+
+
+
has domain
+
+ software implementation + c +
+
has range
+
+ software package + c +
+
+
+
+
+

is represented asop + back to ToC or Object Property ToC + +

+

+ IRI: http://purl.org/neao/base#isRepresentedAs

+
+ Defines how the data entity is represented to be used by software (e.g., data array, list, file) +
+
+
+
has domain
+
+ data + c +
+
has range
+
+ data representation + c +
+
+
+
+
+

uses parameterop + back to ToC or Object Property ToC + +

+

+ IRI: http://purl.org/neao/base#usesParameter

+
+ Defines a parameter used by the analysis step. +
+
+
+
has domain
+
+ analysis step + c +
+
has range
+
+ parameter + c +
+
+
+
+
+

Data Properties

+ +
+

name in definitiondp + back to ToC or Data Property ToC + +

+

+ IRI: http://purl.org/neao/base#nameInDefinition

+
+ Specifies the name of the function as it is defined in the code that implemented it. For example, for Python functions, this is what is specified in the 'def' statement (i.e., def function_name(arg), the value of this property is function_name). +
+
+
+
has domain
+
+ function + c +
+
has range
+
+ string +
+
+
+
+
+

package versiondp + back to ToC or Data Property ToC + +

+

+ IRI: http://purl.org/neao/base#packageName

+
+ Version of the software package. +
+
+
+
has domain
+
+ software package + c +
+
has range
+
+ literal +
+
+
+
+
+

package versiondp + back to ToC or Data Property ToC + +

+

+ IRI: http://purl.org/neao/base#packageVersion

+
+ Specifies the version of the package, as defined by the string used when it was released. +
+
+
+
has domain
+
+ software package + c +
+
has range
+
+ literal +
+
+
+
+
+

program namedp + back to ToC or Data Property ToC + +

+

+ IRI: http://purl.org/neao/base#programName

+
+ Defines the name of the program. +
+
+
+
has domain
+
+ program + c +
+
has range
+
+ string +
+
+
+
+
+

versiondp + back to ToC or Data Property ToC + +

+

+ IRI: http://purl.org/neao/base#version

+
+ Version of the code for a specific program or function. This can be used to define a specific version for the code of a single function or program within a software package. +
+
+
+
has domain
+
+ software implementation + c +
+
has range
+
+ literal +
+
+
+
+
+

Annotation Properties

+ +
+

abbreviationap + back to ToC or Annotation Property ToC + +

+

+ IRI: http://purl.org/neao/base#abbreviation

+
+ A string defining an abbreviation that is frequently used to refer to individuals represented by the class. +
+
+
+
has range
+
+ string +
+
+
+
+ + +
+

has bibliographic referenceap + back to ToC or Annotation Property ToC + +

+

+ IRI: http://purl.org/neao/base#hasBibliographicReference

+
+ Defines the bibliographic reference associated with the entity. The bibliographic reference should contain the details represented by the entity (e.g., method description, software publication). +
+
+
+
has range
+
+ bibliographic reference + c +
+
+
+
+ + + + +
+

Legend back to ToC

+
+c: Classes
+op: Object Properties
+dp: Data Properties
+
+
+
+ + + + +
+

Acknowledgments back to ToC

+

This work was performed as part of the Helmholtz School for Data Science in Life, Earth and Energy (HDS-LEE) and received funding from the Helmholtz Association of German Research Centres. This project has received funding from the European Union’s Horizon 2020 Framework Programme for Research and Innovation under Specific Grant Agreement No. 945539 (Human Brain Project SGA3), the European Union’s Horizon Europe Programme under the Specific Grant Agreement No. 101147319 (EBRAINS 2.0 Project), the Ministry of Culture and Science of the State of North Rhine-Westphalia, Germany (NRW-network "iBehave", grant number: NW21-049), and the Joint Lab "Supercomputing and Modeling for the Human Brain."

+ +

The authors would like to thank Silvio Peroni for developing LODE, a Live OWL Documentation Environment, which is used for representing the Cross Referencing Section of this document and Daniel Garijo for developing Widoco, the program used to create the template used in this documentation.

 +
+ + +
+ + + + + + + diff --git a/doc/releases/0.1.0/base/provenance/provenance-en.html b/doc/releases/0.1.0/base/provenance/provenance-en.html new file mode 100644 index 0000000..5a02036 --- /dev/null +++ b/doc/releases/0.1.0/base/provenance/provenance-en.html @@ -0,0 +1,18 @@ + + + + + + + + +
+

Provenance for Neuroelectrophysiology Analysis Ontology - Base classes Documentation (http://purl.org/neao/0.1.0/base#)

+
    +
  • Ontology created by: Cristiano Köhler (Forschungszentrum Jülich), Michael Denker (Forschungszentrum Jülich)
  • http://purl.org/neao/0.1.0/base# is a specialization of the generic URI http://purl.org/neao/base#
    • +
  • The ontology documentation was the result of using the Widoco tool (which itself uses LODE for generating the crossreference section).
    • +
  • The documentation was generated at 2024-12-06
+
+

back to documentation. TTL format

+ + \ No newline at end of file diff --git a/doc/releases/0.1.0/base/provenance/provenance-en.ttl b/doc/releases/0.1.0/base/provenance/provenance-en.ttl new file mode 100644 index 0000000..897e78c --- /dev/null +++ b/doc/releases/0.1.0/base/provenance/provenance-en.ttl @@ -0,0 +1,14 @@ +@prefix prov: . +@prefix dc: . +@prefix foaf: . +@prefix : <> . + a prov:Entity; + dc:title "Neuroelectrophysiology Analysis Ontology - Base classes"; + prov:wasAttributedTo ; + dc:creator ; + prov:wasAttributedTo ; + dc:creator ; + prov:wasAttributedTo ,; + prov:specializationOf ; + prov:wasGeneratedAt "2024-12-06"; +. diff --git a/doc/releases/0.1.0/base/resources/extra.css b/doc/releases/0.1.0/base/resources/extra.css new file mode 100644 index 0000000..16689d3 --- /dev/null +++ b/doc/releases/0.1.0/base/resources/extra.css @@ -0,0 +1,124 @@ +body { + text-align: justify; +} + +h1 { + line-height: 110%; +} + +.hlist { + border: 1px solid navy; + padding:5px; + background-color: #F4FFFF; +} + +.hlist 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text-align:right; + float:right; + color:black; + padding: 2px; + border: 1px dotted navy; + background-color: #F4FFFF; +} + +.imageblock { + text-align: center; +} + +.imageblock img { + border:1px solid gray; +} + +.endnote { + margin-top: 40px; + border-top: 1px solid gray; + padding-top: 10px; + text-align: center; + color:gray; + font-size:70%; +} + +.literal { + color:green; + font-style:italic; +} \ No newline at end of file diff --git a/doc/releases/0.1.0/base/resources/jquery.js b/doc/releases/0.1.0/base/resources/jquery.js new file mode 100644 index 0000000..48590ec --- /dev/null +++ b/doc/releases/0.1.0/base/resources/jquery.js @@ -0,0 +1,18 @@ +/*! + * jQuery JavaScript Library v1.6.2 + * http://jquery.com/ + * + * Copyright 2011, John Resig + * Dual licensed under the MIT or GPL Version 2 licenses. + * http://jquery.org/license + * + * Includes Sizzle.js + * http://sizzlejs.com/ + * Copyright 2011, The Dojo Foundation + * Released under the MIT, BSD, and GPL Licenses. + * 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r=n[1]||n[2]||"";if(!r||""===u||this.rules.inline.punctuation.exec(u)){var i=n[0].length-1,s=i,l=0,a="*"===n[0][0]?this.rules.inline.emStrong.rDelimAst:this.rules.inline.emStrong.rDelimUnd;for(a.lastIndex=0,t=t.slice(-1*e.length+i);null!=(n=a.exec(t));)if(o=n[1]||n[2]||n[3]||n[4]||n[5]||n[6])if(o=o.length,n[3]||n[4])s+=o;else if((n[5]||n[6])&&i%3&&!((i+o)%3))l+=o;else if(!(0<(s-=o))){var o=Math.min(o,o+s+l);if(Math.min(i,o)%2)return D=e.slice(1,i+n.index+o),{type:"em",raw:e.slice(0,i+n.index+o+1),text:D,tokens:this.lexer.inlineTokens(D,[])};var D=e.slice(2,i+n.index+o-1);return{type:"strong",raw:e.slice(0,i+n.index+o+1),text:D,tokens:this.lexer.inlineTokens(D,[])}}}}},t.codespan=function(e){var t,u,n,e=this.rules.inline.code.exec(e);if(e)return n=e[2].replace(/\n/g," "),t=/[^ ]/.test(n),u=/^ /.test(n)&&/ 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Slightly larger */ + width: 26em; + height: 26em; + z-index: -1; + opacity: 0.8; + + /** From http://stackoverflow.com/questions/1080792/how-to-draw-vertical-text-with-css-cross-browser */ + + -webkit-transform: rotate(-90deg); + -moz-transform: rotate(-90deg); + -ms-transform: rotate(-90deg); + -o-transform: rotate(-90deg); + transform: rotate(-90deg); + /* also accepts left, right, top, bottom coordinates; not + * required, but a good idea for styling */ + -webkit-transform-origin: 50% 50%; + -moz-transform-origin: 50% 50%; + -ms-transform-origin: 50% 50%; + -o-transform-origin: 50% 50%; + transform-origin: 50% 50%; + + /* Should be unset in IE9+ I think. */ + filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=3); +} + +/* The actual status box */ + .status div { + display: block; + background: rgb(0, 90, 156); + color: white; + width: 24em; + padding-top: 0.3em; + padding-left: 0em; + padding-right: 5em; + padding-bottom: 0.3em; + /* Enable for debugging + border: red thin solid; + */ +} + +/* And text inside, don't confuse fonts as it breaks em above */ +.status div span { + font-family: "Tauri"; + font-size: larger; +} \ No newline at end of file diff --git a/doc/releases/0.1.0/base/resources/rdf.icon b/doc/releases/0.1.0/base/resources/rdf.icon new file mode 100644 index 0000000000000000000000000000000000000000..d54310fe20cc6b76fb0aff73bb6d208449383a25 GIT binary patch literal 421 zcmV;W0b2e?Nk%w1VI2S<0K^{vg`>{#^!YhzuNqUMXN>BW*@J zA`Biv9dKI*F$G2>5f4KUX|yqk1!f2uS!02}lx7{JW5GSZW*L7;&$lB24u2k>F$6}2 z9|sD|ao{A8dL-W3NSo?M0}Lb=Tbc$83Fs{c7y=Ux8ZuC@K!AjS1ONaeKqcb9fGD~; zJU~-qN*OvvCfI!Gf5V9$CtYa?E2W PV+=hSSm&XEyAS|7t>CRw literal 0 HcmV?d00001 diff --git a/doc/releases/0.1.0/base/resources/rec.css b/doc/releases/0.1.0/base/resources/rec.css new file mode 100644 index 0000000..d8a1ff2 --- /dev/null +++ b/doc/releases/0.1.0/base/resources/rec.css @@ -0,0 +1,88 @@ +/* Style for a "Recommendation" */ + +/* + Copyright 1997-2003 W3C (MIT, ERCIM, Keio). All Rights Reserved. + The following software licensing rules apply: + http://www.w3.org/Consortium/Legal/copyright-software */ + +/* $Id: base.css,v 1.25 2006/04/18 08:42:53 bbos Exp $ */ + +body { + padding: 2em 1em 2em 70px; + margin: 0; + font-family: sans-serif; + color: black; + background: white; + background-position: top left; + background-attachment: fixed; + background-repeat: no-repeat; + counter-reset:section; +} +:link { color: #00C; background: transparent } +:visited { color: #609; background: transparent } +a:active { color: #C00; background: transparent } + +a:link img, a:visited img { border-style: none } /* no border on img links */ + +a img { color: white; } /* trick to hide the border in Netscape 4 */ +@media all { /* hide the next rule from Netscape 4 */ + a img { color: inherit; } /* undo the color change above */ +} + +th, td { /* ns 4 */ + font-family: sans-serif; +} + +h1, h2, h3, h4, h5, h6 { text-align: left } +h2.list{counter-reset:subsection } +h2.list:before{counter-increment:section;content: counter(section) ". ";} +h3.list:before{counter-increment:subsection;content: counter(section) "." counter(subsection) ". "; + } +h3.list{margin-top: 20px; + border-bottom: 0px; } +/* background should be transparent, but WebTV has a bug */ +h1, h2, h3 { color: #005A9C; background: white } +h1 { font: 170% sans-serif } +h2 { font: 140% sans-serif } +h3 { font: 120% sans-serif } +h4 { font: bold 100% sans-serif } +h5 { font: italic 100% sans-serif } +h6 { font: small-caps 100% sans-serif } + +.hide { display: none } + +div.head { margin-bottom: 1em } +div.head h1 { margin-top: 2em; clear: both } +div.head table { margin-left: 2em; margin-top: 2em } + +p.copyright { font-size: small } +p.copyright small { font-size: small } + +@media screen { /* hide from IE3 */ +a[href]:hover { background: #ffa } +} + +pre { margin-left: 2em } +/* +p { + margin-top: 0.6em; + margin-bottom: 0.6em; +} +*/ +dt, dd { margin-top: 0; margin-bottom: 0 } /* opera 3.50 */ +dt { font-weight: bold } + +pre, code { font-family: monospace } /* navigator 4 requires this */ + +ul.toc, ol.toc { + list-style: disc; /* Mac NS has problem with 'none' */ + list-style: none; +} + +@media aural { + h1, h2, h3 { stress: 20; richness: 90 } + .hide { speak: none } + p.copyright { volume: x-soft; speech-rate: x-fast } + dt { pause-before: 20% } + pre { speak-punctuation: code } +} diff --git a/doc/releases/0.1.0/base/webvowl/css/webvowl.app.css b/doc/releases/0.1.0/base/webvowl/css/webvowl.app.css new file mode 100644 index 0000000..1c350ab --- /dev/null +++ b/doc/releases/0.1.0/base/webvowl/css/webvowl.app.css @@ -0,0 +1,2477 @@ +@import url(https://fonts.googleapis.com/css?family=Open+Sans);/*---------------------------------------------- + WebVOWL page +----------------------------------------------*/ +html { + -ms-content-zooming: none; +} + + + +#loading-progress { + width: 50%; + margin: 10px 0; +} + +#drag_dropOverlay{ + width: 100%; + height:100%; + position:absolute; + top:0; + opacity: 0.5; + background-color: #3071a9; + pointer-events: none; + +} + +#dragDropContainer{ + width: 100%; + height:100%; + position:absolute; + top:0; + pointer-events: none; +} +#drag_icon_group{ + + +} + +#drag_msg{ + width: 50%; + background-color: #fefefe; + height: 50%; + border: black 2px solid; + border-radius: 20px; + left: 25%; + position: absolute; + top: 25%; + vertical-align: middle; + line-height: 10px; + text-align: center; + pointer-events: none; + padding: 10px; + font-size: 1.5em; + white-space: nowrap; + overflow: hidden; + text-overflow: ellipsis; +} + + +#layoutLoadingProgressBarContainer { + height: 50px; + text-align: left; + line-height: 1.5; +} + +#FPS_Statistics { + /*position : absolute;*/ + /*top : 10px;*/ + /*right: 50px;*/ + padding-left: 60px; + padding-top: 60px; +} + +#reloadCachedOntology { + /*position : absolute;*/ + /*top : 10px;*/ + /*right: 50px;*/ +} + +#additionalInformationContainer { + position: absolute; + top: 10px; + right: 50px; +} + +#modeOfOperationString { + /*position: absolute;*/ + /*right: 50px;*/ + /*top : 60px;*/ + padding-left: 34px; +} + +#direct-text-input { + border: 1px solid #34495e; + width: 100%; + margin-top: 5px; + cursor: pointer; +} + +#directUploadBtn, #close_directUploadBtn { + border: 1px solid #34495e; + width: 100%; + margin-top: 5px; + cursor: pointer +} + +#di_controls { + +} + +#di_controls > ul { + list-style: none; + margin: 0; + padding: 5px 0 0 5px; + +} + +#progressBarContext { + border-radius: 10px; + background-color: #bdc3c7; + height: 25px; + border: solid 1px black; + + margin: auto; + +} + +#progressBarValue { + border-radius: 9px; + width: 0%; + background-color: #2980b9; + height: 25px; + line-height: 1.5; + text-align: center; +} + +/** adding searching Styles **/ +.dbEntry { + background-color: #ffffff; + color: #2980b9; + padding: 10px; + font-size: 14px; + border: none; + cursor: pointer; +} + +.debugOption { + +} + +.dbEntrySelected { + background-color: #bdc3c7; + color: #2980b9; + padding: 10px; + font-size: 14px; + border: none; + cursor: pointer; +} + +.dbEntry:hover, .dbEntry:focus { + background-color: #bdc3c7; +} + +.searchMenuEntry { + background-color: #ffffff; + bottom: 0; + font-size: 14px; + min-width: 50px; + margin: 0; + padding: 0; + z-index: 99; + border-radius: 4px 4px 0 0; + border: 1px solid rgba(0, 0, 0, 0.15); + -webkit-box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175); + box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175); + box-sizing: border-box; + border-bottom: none; + display: none; + position: absolute; + list-style: none; +} + +.searchInputText { + background-color: #ffffff; + color: black; + border: black; + text-decoration: none; + max-width: 150px; + overflow: hidden; + text-overflow: ellipsis; + /*height: 20px;*/ + margin: 0; +} + +img, iframe { + border: none; +} + +.hidden { + display: none !important; +} + +.clear { + clear: both; +} + +a { + color: #69c; + text-decoration: none; +} + +a:hover { + color: #3498db; +} + +#optionsArea a { + color: #2980b9; +} + +#optionsArea a.highlighted { + background-color: #d90; +} + +.toolTipMenu li.highlighted { + background-color: #feb; +} + +#browserCheck { + /* checking for IE where WebVOWL is not working */ + background-color: #f00; + padding: 5px 0; + position: absolute; + text-align: center; + width: 100%; +} + +#browserCheck a { + color: #fff; +} + +#browserCheck a:hover { + text-decoration: underline; +} + +/*---------------------------------------------- + SideBar Animation Class; +----------------------------------------------- */ +@-webkit-keyframes sbExpandAnimation { + 0% { + width: 78%; + } + 100% { + width: 100%; + } +} + +@-moz-keyframes sbExpandAnimation { + 0% { + width: 78%; + } + 100% { + width: 100%; + } +} + +@-o-keyframes sbExpandAnimation { + 0% { + width: 78%; + } + 100% { + width: 100%; + } +} + +@keyframes sbExpandAnimation { + 0% { + width: 78%; + } + 100% { + width: 100%; + } +} + +/*Collapse Animation*/ +@-webkit-keyframes sbCollapseAnimation { + 0% { + width: 100%; + } + 100% { + width: 78%; + } +} + +@-moz-keyframes sbCollapseAnimation { + 0% { + width: 100%; + } + 100% { + width: 78%; + } +} + +@-o-keyframes sbCollapseAnimation { + 0% { + width: 100%; + } + 100% { + width: 78%; + } +} + +@keyframes sbCollapseAnimation { + 0% { + width: 100%; + } + 100% { + width: 78%; + } +} + +/*---------------------------------------------- + SideBar Animation Class; +----------------------------------------------- */ +@-webkit-keyframes l_sbExpandAnimation { + 0% { + width: 0px; + } + 100% { + width: 200px; + } +} + +@-moz-keyframes l_sbExpandAnimation { + 0% { + width: 0px; + } + 100% { + width: 200px; + } +} + +@-o-keyframes l_sbExpandAnimation { + 0% { + width: 0px; + } + 100% { + width: 200px; + } +} + +@keyframes l_sbExpandAnimation { + 0% { + width: 0px; + } + 100% { + width: 200px; + } +} + +/*Collapse Animation*/ +@-webkit-keyframes l_sbCollapseAnimation { + 0% { + width: 200px; + } + 100% { + width: 0px; + } +} + +@-moz-keyframes l_sbCollapseAnimation { + 0% { + width: 200px; + } + 100% { + width: 0px; + } +} + +@-o-keyframes l_sbCollapseAnimation { + 0% { + width: 200px; + } + 100% { + width: 0px; + } +} + +@keyframes l_sbCollapseAnimation { + 0% { + width: 200px; + } + 100% { + width: 0px; + } +} + +/*----------------- WARNING ANIMATIONS-------------*/ + +/*---------------------------------------------- + SideBar Animation Class; +----------------------------------------------- */ +@-webkit-keyframes warn_ExpandAnimation { + 0% { + top: -500px; + } + 100% { + top: 0; + } +} + +@-moz-keyframes warn_ExpandAnimation { + 0% { + top: -500px; + } + 100% { + top: 0; + } +} + +@-o-keyframes warn_ExpandAnimation { + 0% { + top: -500px; + } + 100% { + top: 0; + } +} + +@keyframes warn_ExpandAnimation { + 0% { + top: -500px; + } + 100% { + top: 0; + } +} + +/*Collapse Animation*/ +@-webkit-keyframes warn_CollapseAnimation { + 0% { + top: 0; + } + 100% { + top: -400px; + } +} + +@-moz-keyframes warn_CollapseAnimation { + 0% { + top: 0; + } + 100% { + top: -400px; + } +} + +@-o-keyframes warn_CollapseAnimation { + 0% { + top: 0; + } + 100% { + top: -400px; + } +} + +@keyframes warn_CollapseAnimation { + 0% { + top: 0; + } + 100% { + top: -400px; + } +} + +@keyframes msg_CollapseAnimation { + 0% { + top: 0; + } + 100% { + top: -400px; + } +} + +/*// add expand and collaps width for the warn module*/ +@-webkit-keyframes warn_ExpandLeftBarAnimation { + 0% { + left: 0; + } + 100% { + left: 100px; + } +} + +@-moz-keyframes warn_ExpandLeftBarAnimation { + 0% { + left: 0; + } + 100% { + left: 100px; + } +} + +@-o-keyframes warn_ExpandLeftBarAnimation { + 0% { + left: 0; + } + 100% { + left: 100px; + } +} + +@keyframes warn_ExpandLeftBarAnimation { + 0% { + left: 0; + } + 100% { + left: 100px; + } +} + +/*Collapse Animation*/ +@-webkit-keyframes warn_CollapseLeftBarAnimation { + 0% { + left: 100px; + } + 100% { + left: 0; + } +} + +@-moz-keyframes warn_CollapseLeftBarAnimation { + 0% { + left: 100px; + } + 100% { + left: 0; + } +} + +@-o-keyframes warn_CollapseLeftBarAnimation { + 0% { + left: 100px; + } + 100% { + left: 0; + } +} + +@keyframes warn_CollapseLeftBarAnimation { + 0% { + left: 100px; + } + 100% { + left: 0; + } +} + +/*// same for the right side expansion*/ + +/*// add expand and collaps width for the warn module*/ +@-webkit-keyframes warn_ExpandRightBarAnimation { + 0% { + width: 100%; + } + 100% { + width: 78%; + } +} + +@-moz-keyframes warn_ExpandRightBarAnimation { + 0% { + width: 100%; + } + 100% { + width: 78%; + } +} + +@-o-keyframes warn_ExpandRightBarAnimation { + 0% { + width: 100%; + } + 100% { + width: 78%; + } +} + +@keyframes warn_ExpandRightBarAnimation { + 0% { + width: 100%; + } + 100% { + width: 78%; + } + +} + +/*Collapse Animation*/ +@-webkit-keyframes warn_CollapseRightBarAnimation { + 0% { + width: 78%; + } + 100% { + width: 100%; + } +} + +@-moz-keyframes warn_CollapseRightBarAnimation { + 0% { + width: 78%; + } + 100% { + width: 100%; + } +} + +@-o-keyframes warn_CollapseRightBarAnimation { + 0% { + width: 78%; + } + 100% { + width: 100%; + } +} + +@keyframes warn_CollapseRightBarAnimation { + 0% { + width: 78%; + } + 100% { + width: 100%; + } +} + +/*---------------------------------------------- + LAYOUT +----------------------------------------------*/ +body { + background: rgb(24, 32, 42); + height: 100%; + font-size: 14px; + font-family: 'Open Sans', Helvetica, Arial, sans-serif; + line-height: 1; + margin: 0; + overflow: hidden; + padding: 0; + position: fixed; + width: 100%; +} + +main { + height: 100%; + margin: 0; + padding: 0; + position: relative; + width: 100%; +} + +#canvasArea { + position: relative; + margin: 0; + padding: 0; + width: 78%; +} + +#canvasArea #graph { + box-sizing: border-box; + margin: 0 0 2px 0; + background-color: #ecf0f1; + overflow: hidden; + padding: 0; + width: 100%; +} + +#canvasArea svg { + box-sizing: border-box; + margin: 0; + overflow: hidden; + padding: 0; +} + +#logo { + position: fixed; + /*padding: 10px;*/ + pointer-events: none; + /*border: solid 1px red;*/ +} + +#logo h2 { + color: #3498db; + margin: 0; + line-height: 0.7; + text-align: center; + font-size: 24px; +} + +#logo h2 span { + color: #34495E; + /*font-size: min(2vmin, 24px);*/ + font-size: 16px; +} + +@media screen and (max-device-height: 800px) { + #logo h2 { + font-size: calc(8px + 1.0vmin); + } + + #logo h2 span { + font-size: calc(3px + 1.0vmin); + } +} + +@media screen and (max-height: 800px) { + #logo h2 { + font-size: calc(8px + 1.0vmin); + } + + #logo h2 span { + font-size: calc(3px + 1.0vmin); + } +} + +@media screen and (max-device-width: 1200px) { + #logo h2 { + font-size: calc(8px + 1.0vmin); + } + + #logo h2 span { + font-size: calc(3px + 1.0vmin); + } +} + +@media screen and (max-width: 1200px) { + #logo h2 { + font-size: calc(8px + 1.0vmin); + } + + #logo h2 span { + font-size: calc(3px + 1.0vmin); + } +} + +.checkboxContainer input, .checkboxContainer label { + vertical-align: middle; +} + +.selected-ontology { + background-color: #eee; +} + +#credits { + border-top: solid 1px #bdc3c7; + font-size: 0.9em; +} + +.slideOption { + position: relative; + padding: 8px 5px; + outline: none; +} + +.slideOption .value { + float: right; + outline: none; +} + +.slideOption input[type="range"] { + box-sizing: border-box; + margin: 0; + outline: none; + -webkit-appearance: none; + -moz-appearance: none; + border-radius: 3px; + height: 12px; + width: 100%; + box-shadow: none; + left: 0; + position: relative; + transition: all 0.5s ease; + background-color: #eee; +} + +/*TRACK*/ +.slideOption input[type=range]::-webkit-slider-runnable-track { + -webkit-appearance: none; + background-color: #3071a9; + height: 3px; +} + +.slideOption input[type=range]::-moz-range-track { + -webkit-appearance: none; + background-color: #3071a9; + height: 3px; +} + +.slideOption input[type="range"]:hover { + outline: none; +} + +/*THUMB*/ +.slideOption input[type="range"]::-webkit-slider-thumb { + -webkit-appearance: none; + background-color: white; + border-radius: 3px; + border: solid 1px black; + transition: all 0.5s ease; + height: 10px; + width: 30px; + outline: none; + margin-top: -3px; +} + +.slideOption input[type="range"]::-moz-range-thumb { + -webkit-appearance: none; + background-color: white; + border-radius: 3px; + border: solid 1px black; + transition: all 0.5s ease; + height: 10px; + width: 30px; + outline: none; +} + +.slideOption input[type="range"]::-moz-range-thumb:hover { + background-color: #d90; + outline: none; +} + +.slideOption input[type="range"]::-webkit-slider-thumb:hover { + background-color: #d90; + /*color: #d90;*/ + outline: none; +} + +/*focus : remove border*/ +.slideOption input[type="range"]:focus { + outline: none; +} + +.slideOption input[type="range"]:active { + outline: none; +} + +.slideOption input[type="range"]::-moz-range-thumb:focus { + outline: none; +} + +.slideOption input[type="range"]::-moz-range-thumb:active { + outline: none; +} + +.slideOption input[type="range"]::-webkit-slider-thumb:focus { + outline: none; +} + +.slideOption input[type="range"]::-webkit-slider-thumb:active { + outline: none; +} + +.slideOption input[type="range"]:disabled { + box-sizing: border-box; + margin: 0; + outline: none; + -webkit-appearance: none; + -moz-appearance: none; + border-radius: 3px; + height: 12px; + width: 100%; + box-shadow: none; + left: 0; + position: relative; + transition: all 0.5s ease; + background-color: #787878; +} + +/*TRACK*/ +.slideOption input[type=range]:disabled::-webkit-slider-runnable-track { + -webkit-appearance: none; + background-color: #373737; + height: 3px; +} + +.slideOption input[type=range]:disabled::-moz-range-track { + -webkit-appearance: none; + background-color: #373737; + height: 3px; +} + +.slideOption input[type="range"]:disabled { + outline: none; +} + +/*THUMB*/ +.slideOption input[type="range"]:disabled::-webkit-slider-thumb { + -webkit-appearance: none; + background-color: #363636; + border-radius: 3px; + border: solid 1px #aaaaaa; + transition: all 0.5s ease; + height: 10px; + width: 30px; + outline: none; + margin-top: -3px; +} + +.slideOption input[type="range"]:disabled::-moz-range-thumb { + -webkit-appearance: none; + background-color: #aaaaaa; + border-radius: 3px; + border: solid 1px black; + transition: all 0.5s ease; + height: 10px; + width: 30px; + outline: none; +} + +.slideOption input[type="range"]:disabled::-moz-range-thumb { + background-color: #aaaaaa; + outline: none; +} + +.slideOption input[type="range"]:disabled::-webkit-slider-thumb { + background-color: #aaaaaa; + /*color: #d90;*/ + outline: none; +} + +.slideOption input[type="range"]:disabled:hover::-moz-range-thumb { + background-color: #404040; + outline: none; +} + +.slideOption input[type="range"]:disabled:hover::-webkit-slider-thumb { + background-color: #404040; + /*color: #d90;*/ + outline: none; +} + +#detailsArea { + top: 0; + right: 0; + bottom: 0; + color: #bdc3c7; + height: 100%; + width: 22%; + overflow-y: auto; + overflow-x: hidden; + position: fixed; + border-left: 1px solid #34495E; +} + +#detailsArea h1 { + border-bottom: solid 1px #34495e; + color: #ecf0f1; + display: block; + font-weight: 100; + font-size: 1.5em; + margin: 0; + padding: 10px 0; + text-align: center; +} + +#generalDetails { + width: auto; + box-sizing: border-box; + height: 100%; +} + +#generalDetails span #about { + border-bottom: solid 1px #34495e; + display: block; + padding: 10px; + text-align: center; + word-wrap: break-word; + color: #69c; +} + +#generalDetails h4 { + background: rgb(27, 37, 46); + color: #ecf0f1; + display: block; + font-size: 1.1em; + font-weight: 100; + margin: 0; + padding: 10px 0; + text-align: center; +} + +#detailsArea #generalDetails h5 { + border-bottom: solid 1px #34495e; + font-size: 0.9em; + font-weight: 100; + margin: 0; + padding: 5px; + text-align: center; +} + +#description { + text-align: justify; +} + +.accordion-container p { + font-size: 0.9em; + line-height: 1.3; + margin: 5px 10px; +} + +.statisticDetails span { + font-weight: 100; + font-style: italic; + margin: 10px 0; + padding: 10px; +} + +.statisticDetails div { + font-weight: 100; + font-style: italic; + margin: 10px 0; + padding: 0 10px; + display: inline; +} + +#selection-details .propDetails a { + color: #69c; +} + +#selection-details .propDetails > span { + font-weight: 100; + font-style: italic; + padding: 0 10px; +} + +#selection-details #classEquivUri span, #selection-details #disjointNodes span { + padding: 0; +} + +#selection-details .propDetails div { + font-weight: 100; + font-style: italic; + margin: 10px 0; + padding: 0 10px; + display: inline; +} + +#selection-details .propDetails div span { + padding: 0; +} + +/* give subclass property the same background color as the canvas */ +.subclass { + fill: #ecf0f1; +} + +.accordion-trigger { + background: #24323e; + cursor: pointer; + padding: .5em; +} + +.accordion-trigger.accordion-trigger-active:before { + padding-right: 4px; + content: "\25BC" +} + +.accordion-trigger:not(.accordion-trigger-active):before { + padding-right: 4px; + content: "\25BA" +} + +.accordion-container.scrollable { + max-height: 40%; + overflow: auto; +} + +.small-whitespace-separator { + height: 3px; +} + +#language { + background: transparent; + border: 1px solid #34495E; + color: #ecf0f1; +} + +#language option { + background-color: #24323e; +} + +.converter-form:not(:first-child) { + margin-top: 5px; +} + +.converter-form label { + display: inline-block; + line-height: normal; +} + +.converter-form input { + box-sizing: border-box; + height: 20px; + width: 74%; + border: 1px solid #34495E; +} + +.converter-form button { + cursor: pointer; + float: right; + height: 20px; + padding: 0; + width: 25%; + border: 1px solid #34495E; + background-color: #ecf0f1; +} + +#file-converter-label { + border: 1px solid #34495E; + box-sizing: border-box; + cursor: pointer; + height: 20px; + width: 74%; +} + +#killWarning { + cursor: pointer; + color: #ffffff; + font-weight: bold; +} + +/*#copyBt{*/ +/*box-sizing: border-box;*/ +/*color: #000000;*/ +/*float:right;*/ +/*position:absolute;*/ +/*right:2px;*/ +/*padding: 2px 7px 3px 7px;*/ +/*border: 1px solid #000000;*/ +/*background-color: #ecf0f1;*/ +/*cursor: pointer;*/ +/*}*/ + +#copyBt { + box-sizing: border-box; + height: 20px; + width: 31%; + border: 1px solid #34495E; +} + +#sidebarExpandButton { + height: 24px; + width: 24px; + /*background-color: white;*/ + /*box-shadow: 0px 1px 1px grey;*/ + box-sizing: border-box; + top: 10px; + color: #000000; + float: right; + position: absolute; + right: 0; + border: 1px solid #000000; + + text-align: center; + font-size: 1.5em; + cursor: pointer; +} + +.dropdownMenuClass { + height: 20px; + /*width: 69%;*/ + float: right; + border: 1px solid #34495E; + background-color: #34495E; + color: white; + /*border-bottom: 1px solid #d90;*/ + text-align: left; + width: auto; +} + +#typeEditForm_datatype { + padding-top: 5px; +} + +#typeEditor { + width: 165px; +} + +#typeEditor_datatype { + width: 165px; +} + +#leftSideBarCollapseButton { + box-sizing: border-box; + top: 50px; + /*padding:5px;*/ + color: #000000; + position: absolute; + left: 200px; + border: 1px solid #000000; + /*background-color: #ecf0f1;*/ + cursor: pointer; + width: 24px; + height: 24px; + font-size: 1.5em; + text-align: center; +} + +#leftSideBarCollapseButton:hover { + background-color: #d90; +} + +#sidebarExpandButton:hover { + background-color: #d90; +} + +.spanForCharSelection { + padding-left: 25px; +} + +.nodeEditSpan { + color: #000; + background-color: #fff; + text-align: center; + /*overflow: auto;*/ + border: none; + padding-top: 6px; +} + +.nodeEditSpan:focus { + outline: none; + border: none; +} + +.foreignelements { + /*width: 80px;*/ + /*height: 3px;*/ + border: none; +} + +.foreignelements:focus { + outline: none; + border: none; +} + +#leftSideBarContent { + color: #000000; + float: left; + position: absolute; + left: 0; + /*border: 1px solid #000000;*/ + background-color: rgb(24, 32, 42); + width: 100%; + height: 100%; +} + +#leftSideBarContent > h3 { + color: #ecf0f1; + display: block; + font-size: 1.1em; + font-weight: 100; + margin: 0 0 5px 0; + padding: 10px 0; + text-align: left; +} + +#generalDetailsEdit { + /*color: #ecf0f1;*/ + color: #ecf0f1; +} + +#generalDetailsEdit > div { + padding: 5px; +} + +#generalDetailsEdit > h3 { + color: #ecf0f1; + display: block; + font-size: 1.1em; + font-weight: 100; + margin: 0 0 5px 0; + padding: 10px 0; + text-align: left; +} + +.subAccordion { + color: #ecf0f1; + display: block; + font-size: 0.8em; + font-weight: 100; + margin: 0; + padding: 5px; + text-align: left; +} + +.subAccordionDescription { + padding: 0 5px; +} + +.boxed { + padding: 0 5px; +} + +.separatorLineRight { + border-right: 1px solid #f00; +} + +.editPrefixButton:hover { + color: #ff972d; + cursor: pointer; +} + +.editPrefixIcon:hover { + stroke: #ff972d; + stroke-width: 1px; + cursor: pointer; +} + +.editPrefixIcon { + stroke: #fffff; + stroke-width: 1px; + cursor: pointer; +} + +.deletePrefixButton:hover { + color: #ff972d; + cursor: pointer; +} + +.deletePrefixButton { + color: #ff0000; + cursor: pointer; +} + +.invisiblePrefixButton { + cursor: default; + color: rgb(24, 32, 42); +} + +#containerForAddPrefixButton { + width: 100%; + margin-top: 5px; +} + +.roundedButton { + border: 1px solid #000000; + border-radius: 20px; + padding: 0 5px; + background: #fff; + cursor: pointer; + color: black; + outline: none; +} + +.roundedButton:hover { + background: #318638; + cursor: pointer; + color: #fff; + outline: none; +} + +#prefixURL_Description { + padding: 5px 0 0 0; +} + +.prefixIRIElements { + display: inline-block; + padding: 3px; + border-bottom: 1px solid #34495E; + width: 100% +} + +.prefixInput { + width: 30px; + display: inline-block; + margin-right: 5px; +} + +.prefixURL { + width: 100px; + display: inline-block; + paddig-left: 5px; +} + +.selectedDefaultElement { + text-align: left; + white-space: nowrap; + overflow: hidden; + text-overflow: ellipsis; + display: inline-block; + max-width: 200px; +} + +#editHeader { + color: #ecf0f1; + background-color: #394f5a; + display: block; + font-size: 1.1em; + font-weight: 100; + text-align: center; +} + +#leftHeader { + color: #ecf0f1; + background-color: #394f5a; + display: block; + font-size: 1.1em; + font-weight: 100; + text-align: center; + padding: 10px 0; + margin: 0; +} + +.containerForDefaultSelection { + color: #ecf0f1; + display: block; + font-size: 1.1em; + font-weight: 100; + margin: 0; + padding: 10px 20px; + text-align: left; +} + +.defaultSelected { + color: #a15d05; + background-color: #283943; +} + +.containerForDefaultSelection:hover { + color: #f19505; + background-color: #394f5a; + display: block; + cursor: pointer; +} + +#containerForLeftSideBar { + top: 50px; + float: left; + position: absolute; + background-color: #1b252e; + left: 0; + width: 200px; + height: 200px; + overflow-y: auto; + overflow-x: hidden; +} + +#leftSideBar { + width: 100%; + background-color: rgb(24, 32, 42); +} + +#loading-info { + box-sizing: border-box; + position: absolute; + text-align: center; + + width: 100%; + height: 80%; + top: 0; +} + +#loading-info > div { + display: inline-block; + color: #ffffff; + background-color: #18202A; + border-bottom-left-radius: 2px; + border-bottom-right-radius: 2px; +} + +#loading-info > * > * { + padding: 5px; +} + +#loading-info { + pointer-events: none; +} + +#loading-progress { + pointer-events: auto; + min-width: 220px; + border-radius: 10px; +} + +#show-loadingInfo-button { + font-size: 12px; + color: #fff; + cursor: pointer; + text-align: center; +} + +#loadingIndicator_closeButton:hover { + color: #ff972d; + cursor: pointer; + +} + +#loadingIndicator_closeButton { + color: #ffe30f; + cursor: pointer; + padding-bottom: 5px; + float: right; +} + +.busyProgressBar { + background-color: #000; + height: 25px; + position: relative; + animation: busy 2s linear infinite; +} + +@-webkit-keyframes busy { + 0% { + left: 0%; + } + 50% { + left: 80%; + } + 100% { + left: 0%; + } +} + +#bulletPoint_container { + padding-left: 15px; + margin-top: 0px; + margin-bottom: 0px; +} + +#bulletPoint_container > div { + margin-left: -15px; +} + +#loadingInfo-container { + box-sizing: border-box; + text-align: left; + line-height: 1.2; + padding-top: 5px; + overflow: auto; + /*white-space: nowrap;*/ + /*min-width: 250px;*/ + height: 120px; + min-height: 40px; + background-color: #3c3c3c; + +} + +#error-description-button { + margin: 5px 0 0 0; + font-size: 12px; + color: #69c; + cursor: pointer; + text-align: center; +} + +#error-description-container { + box-sizing: border-box; + text-align: left; +} + +#error-description-container pre { + background-color: #34495E; + padding: 2px; + margin: 0; + white-space: pre-wrap; + max-height: calc(100vh - 125px); + max-width: 75vw; + overflow: auto; +} + +.spin { + display: inline-block; + -webkit-animation: spin 2s infinite linear; + animation: spin 2s infinite linear; +} + +@-webkit-keyframes spin { + 0% { + -webkit-transform: rotate(0deg); + transform: rotate(0deg); + } + 100% { + -webkit-transform: rotate(359deg); + transform: rotate(359deg); + } +} + +@keyframes spin { + 0% { + -webkit-transform: rotate(0deg); + transform: rotate(0deg); + } + 100% { + -webkit-transform: rotate(359deg); + transform: rotate(359deg); + } +} + +.truncate { + max-width: 250px; + white-space: nowrap; + overflow: hidden; + text-overflow: ellipsis; +} + +.color-mode-switch { + float: right; + width: 90px; + cursor: pointer; + height: 20px; + padding: 0; + border: 0; + color: #555; + background-color: #ECEEEF; + box-shadow: 0 1px 4px rgba(0, 0, 0, 0.2), inset 0 0 3px rgba(0, 0, 0, 0.1); +} + +.color-mode-switch:focus { + outline-width: 0; +} + +.color-mode-switch.active { + color: #FFF; + background-color: #32CD32; + box-shadow: inset 0 1px 4px rgba(0, 0, 0, 0.2), inset 0 0 3px rgba(0, 0, 0, 0.1); +} + +/* adding button pulse animation*/ +.filterMenuButtonHighlight { + background-color: #d90; +} + +@-webkit-keyframes buttonAnimation { + 0% { + background-color: unset; + } + 100% { + background-color: #d90; + } +} + +@-moz-keyframes buttonAnimation { + 0% { + background-color: unset; + } + 100% { + background-color: #d90; + } +} + +@-o-keyframes buttonAnimation { + 0% { + background-color: unset; + } + 100% { + background-color: #d90; + } +} + +@keyframes buttonAnimation { + 0% { + background-color: unset; + } + 100% { + background-color: #d90; + } +} + +.buttonPulse { + -webkit-animation-name: buttonAnimation; + -moz-animation-name: buttonAnimation; + -o-animation-name: buttonAnimation; + animation-name: buttonAnimation; + + -webkit-animation-duration: 0.5s; + -moz-animation-duration: 0.5s; + -o-animation-duration: 0.5s; + animation-duration: 0.5s; + + -webkit-animation-iteration-count: 3; + -moz-animation-iteration-count: 3; + -o-animation-iteration-count: 3; + animation-iteration-count: 3; + + -webkit-animation-timing-function: linear; + -moz-animation-timing-function: linear; + -o-animation-timing-function: linear; + animation-timing-function: linear; + + +} + +/*swipe bar definition*/ + +/*Overwriting individual menu widths*/ +#m_about { + max-width: 200px; + width: 200px; + position: absolute; + +} + +#m_modes { + max-width: 160px; + width: 160px; + position: absolute; +} + +#m_filter { + max-width: 170px; + width: 170px; + position: absolute; +} + +#m_gravity { + max-width: 180px; + width: 180px; + position: absolute; +} + +#m_export { + max-width: 160px; + width: 160px; + position: absolute; + +} + +#exportedUrl { + width: 100px; +} + +#m_select { + max-width: 300px; + width: 300px; + position: absolute; +} + +#m_config { + max-width: 240px; + width: 240px; + position: absolute; +} + +#m_search { + max-width: 250px; + white-space: nowrap; + overflow: hidden; + text-overflow: ellipsis; +} + +/***************** REWRITING MENU ELEMENT CONTAINERS ***********************/ +/*Container which holds the swipeBar*/ +#swipeBarContainer { + position: fixed; + width: 77.8%; + height: 40px; + margin: 0; + padding: 0; + bottom: 0; +} + +/*Scroll-able container for the menu entries */ +#menuElementContainer { + margin: 0; + padding: 0; + overflow-x: auto; + overflow-y: hidden; + white-space: nowrap; + text-align: right; + list-style-type: none; +} + +/*Style for the individual menu entries*/ +#menuElementContainer > li { + display: inline-block; + box-sizing: border-box; + text-align: left; + position: relative; + height: 40px; + font-size: 14px; + color: #ffffff; + padding: 12px 0 0; + margin-left: -4px; +} + +/*Font-color Style for menu entries */ +#menuElementContainer > li > a { + color: #fff; + padding: 9px 12px 12px 30px; +} + +.menuElementSvgElement { + height: 20px; + width: 20px; + display: block; + position: absolute; + top: 10px; + left: 8px; +} + +.btn_shadowed { + background-color: #fefefe; + box-shadow: 1px 1px 1px gray; +} + +.reloadCachedOntologyIcon { + height: 20px; + width: 108px; + display: block; + position: absolute; + top: 20px; + left: 3px; + /*background: #ecf0f1;;*/ + border: solid 1px black; + border-radius: 10px; + cursor: pointer; +} + +.reloadCachedOntologyIcon:disabled { + background: #f4f4f4; + cursor: auto; + border: solid 1px darkgray; + +} + +.reloadCachedOntologyIcon:hover { + background: #d90; + cursor: pointer; +} + +.disabledReloadElement { + cursor: auto; + background: #F4F4F4; + pointer-events: auto; + border: solid 1px darkgray; + color: #bbbbbb; +} + +.disabledReloadElement:hover { + cursor: auto; + background: #EEEEEE; + pointer-events: auto; +} + +#menuElementContainer > li > input { + color: #000; + /*padding : 0 0.3em 0 1.5em;*/ + padding: 0.1em .3em 0.1em 1.5em; + white-space: nowrap; + overflow: hidden; + text-overflow: ellipsis; + width: 120px; +} + +/*Hovered behavior for the menu entries*/ +#menuElementContainer > li > a:hover { + box-sizing: border-box; + background: #1B252E; + /*background : #d90;*/ + color: #bdc3c7; + +} + +#empty:hover { + box-sizing: border-box; + background: #e1e1e1; + /*background : #d90;*/ + color: #2980b9; +} + +#empty.disabled { + pointer-events: none; + cursor: default; + color: #979797; +} + +.disabled { + pointer-events: none; + cursor: default; + color: #979797; +} + +/*ToolTip Menu Definition*/ +.toolTipMenu { + -webkit-box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175); + box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175); + box-sizing: border-box; + background-color: #ffffff; + border: 1px solid rgba(0, 0, 0, 0.15); + border-bottom: none; + border-radius: 4px 4px 0 0; + bottom: 0; + display: none; + font-size: 14px; + list-style: none; + /*max-width: 300px;*/ + margin: 0; + padding: 0; + white-space: normal; + position: absolute; + z-index: 99; +} + +.toolTipMenu > li:first-of-type { + border: none; +} + +.toolTipMenu a { + color: #2980b9; +} + +.toolTipMenu > li { + border-top: solid 1px #bdc3c7; +} + +.toolTipMenu li { + color: #2980b9; + display: block; +} + +/*MenuElement hovering enables the toolTip of the corresponding menu*/ +#menuElementContainer > li:hover .toolTipMenu { + display: block; +} + +#menuElementContainer li > ul.toolTipMenu li a:hover { + background: #e1e1e1; +} + +/****************************************************************************/ +/*ScrollButton behavior*/ +#scrollLeftButton { + height: 30px; + width: 30px; + padding: 5px 0 5px 10px; + color: #fff; + cursor: pointer; + position: absolute; + margin-top: -2px; + font-size: 2em; + background-color: #24323e; + left: 0; +} + +#scrollLeftButton:focus { + outline: none; +} + +#scrollLeftButton:before { + content: "<"; +} + +/*Right Scroll Button*/ +#scrollRightButton { + height: 30px; + width: 30px; + padding: 5px 0 5px 10px; + color: #fff; + cursor: pointer; + position: absolute; + margin-top: -2px; + font-size: 2em; + background-color: #24323e; + right: 0; +} + +#scrollRightButton:focus { + outline: none; +} + +#scrollRightButton:hover { + color: #bdc3c7; +} + +#scrollLeftButton:hover { + color: #bdc3c7; +} + +#scrollRightButton:before { + content: ">"; +} + +#centerGraphButton, #zoomInButton, #zoomOutButton { + border: 1px solid #000000; + text-align: center; + margin: -1px 0 0 0; + font-size: 1.5em; + padding: 0; + height: 28px; +} + +.noselect { + -webkit-touch-callout: none; /* iOS Safari */ + -webkit-user-select: none; /* Safari */ + -khtml-user-select: none; /* Konqueror HTML */ + -moz-user-select: none; /* Firefox */ + -ms-user-select: none; /* Internet Explorer/Edge */ + user-select: none; + /* Non-prefixed version, currently + supported by Chrome and Opera */ +} + +#zoomOutButton { + line-height: 22px; +} + +#centerGraphButton { + line-height: 25px; +} + +#zoomInButton { + line-height: 25px; +} + +#zoomSlider > p:hover { + background-color: #d90; +} + +#zoomSliderParagraph { + color: #000000; + padding-top: 5px; + margin: -1px 0 0 0; + border: 1px solid #000000; + /*background-color: #ecf0f1;*/ + /*width: 28px;*/ + height: 150px; +} + +p#zoomSliderParagraph:hover { + background-color: #fff; +} + +/*todo put this in a proper position*/ +#zoomSlider { + width: 28px; + margin-top: -2px; + padding: 0; + font-size: 1.5em; + cursor: pointer; + position: absolute; + right: 20px; + bottom: 20px; + color: #000; + /*background-color: #ecf0f1;*/ + box-sizing: border-box; +} + +/****************************************************************************/ +/*Definition for the Icons before*/ +#menuElementContainer > li > a::before { + font-size: 1em; + margin: 0; + padding: 0 6px 0 0; +} + +#menuElementContainer a.highlighted { + background-color: #d90; +} + +/*#search-input-text.searchInputText {*/ +/*!*padding: 0 0.2em;*!*/ +/*color: black;*/ +/*}*/ + +.inner-addon { + position: relative; +} + +.searchIcon { + position: absolute; + /*padding: 0.15em 0;*/ + width: 17px; + height: 17px; + + pointer-events: none; +} + +.gearIcon { + position: absolute; + width: 17px; + height: 17px; + pointer-events: none; + left: -5px; +} + +/*#search-input-text::before {*/ +/*!*padding: 0 0.2em;*!*/ +/*!*color: black;*!*/ +/*font-size: 1.4em; !* todo : test this *!*/ +/*!*content: "\2315";*!*/ +/*content: "⚲";*/ +/*color: white;*/ +/*padding: 0;*/ +/*-webkit-transform: rotate(-45deg);*/ +/*!*content: "\2315" or "\1F50D"*!;*/ +/*display: inline-block;*/ +/*position: relative;*/ +/*top: 2px;*/ +/*left:-5px;*/ +/*}*/ + +li#c_search { + padding: 0 5px; + margin-left: 5px; + height: 20px; +} + +/*Menu icons before the links selection */ +/*#c_select > a::before { content: "\2263"; }*/ +/*#c_export > a::before { content: "\21E4"; }*/ +/*#c_gravity > a::before { content: "\2299"; }*/ +/*#c_filter > a::before { content: "\25BD"; }*/ +/*#c_modes > a::before { content: "\2606"; }*/ +/*#c_reset > a::before { content: "\21BB"; }*/ +/*#c_about > a::before { content: "\00A9"; }*/ + +li#c_locate { + padding: 0; +} + +#c_locate > a { + font-size: 2em; + padding: 0; +} + +a#pause-button { + padding: 12px 12px; +} + +/*Pause Button has a different behavior*/ +a#pause-button.paused::before { + content: "\25BA"; +} + +a#pause-button.paused:hover { + background-color: #d90; + color: #fff; +} + +a#pause-button:not(.paused)::before { + content: "II"; +} + +.toolTipMenu li:hover { + background-color: #e1e1e1; +} + +#emptyLiHover { + background-color: #FFFFFF; +} + +#emptyLiHover:hover { + background-color: #FFFFFF; +} + +.toggleOption li:hover { + background-color: #e1e1e1; +} + +.toggleOption { + padding: 8px 5px; +} + +#converter-option:hover { + background-color: #ffffff; +} + +.toolTipMenu li a:only-child, .option { + display: block; + float: none; + padding: 8px 5px; +} + +.customLocate { + padding: 0; + background-color: #32CD32; +} + +a#locateSearchResult { + padding-bottom: 0; + padding-top: 50px; + position: relative; + top: 5px; +} + +/*#sliderRange{*/ +/*padding: 0;*/ +/*margin: 7px 0 0 0;*/ +/*width:100%;*/ +/*height:5px;*/ +/*-webkit-appearance: none;*/ +/*outline: none;*/ +/*}*/ + +#zoomSliderElement { + color: #000; + position: relative; + padding-top: 0; + width: 155px; + height: 24px; + background-color: transparent; + -webkit-transform-origin-x: 73px; + -webkit-transform-origin-y: 73px; + -webkit-transform: rotate(-90deg); + -moz-transform-origin: 73px 73px; + transform: rotate(-90deg); + transform-origin: 73px 73px; + -webkit-appearance: none; + outline: none; + margin: 4px 0; +} + +/* ------------------ Zoom Slider styles --------------------------*/ +#zoomSliderElement::-webkit-scrollbar { + height: 0; +} + +#zoomSliderElement:hover { + cursor: crosshair; +} + +/*TRACK*/ +#zoomSliderElement::-webkit-slider-runnable-track { + width: 100%; + height: 5px; + cursor: pointer; + background: #3071a9; +} + +#zoomSliderElement::-moz-range-track { + width: 100%; + height: 5px; + cursor: pointer; + background: #3071a9; +} + +/*Thumb*/ +#zoomSliderElement::-webkit-slider-thumb { + -webkit-appearance: none; + border: 1px solid #000000; + height: 10px; + width: 30px; + margin-right: 50px; + border-radius: 3px; + background: #fff; + cursor: pointer; + outline: none; + margin-top: -3px; +} + +#zoomSliderElement::-ms-thumb { + -webkit-appearance: none; + border: 1px solid #000000; + height: 10px; + width: 30px; + margin-right: 50px; + border-radius: 3px; + background: #fff; + cursor: pointer; + outline: none; + margin-top: -3px; +} + +#zoomSliderElement::-ms-thumb:hover { + -webkit-appearance: none; + border: 1px solid #000000; + height: 10px; + width: 30px; + margin-right: 50px; + border-radius: 3px; + background: #d90; + cursor: pointer; + outline: none; + margin-top: -3px; +} + +#zoomSliderElement::-webkit-slider-thumb:hover { + -webkit-appearance: none; + border: 1px solid #000000; + height: 10px; + width: 30px; + margin-right: 50px; + border-radius: 3px; + background: #d90; + cursor: pointer; + outline: none; + margin-top: -3px; +} + +#zoomSliderElement::-moz-range-thumb { + border: 1px solid #000000; + height: 10px; + width: 30px; + border-radius: 3px; + /*background: #ffffff;*/ + cursor: pointer; + outline: none; +} + +#zoomSliderElement::-moz-range-thumb:hover { + border: 1px solid #000000; + height: 10px; + width: 30px; + border-radius: 3px; + background: #d90; + cursor: pointer; + outline: none; +} + +#zoomSliderElement::-moz-focus-outer { + border: 0; +} + +#locateSearchResult:focus { + outline: none; + +} + +a#locateSearchResult.highlighted:hover { + background-color: #d90; + color: red; +} + +a#locateSearchResult { + outline: none; + padding-bottom: 0; + padding-top: 0; + position: relative; + top: 5px; +} + +/*Editor hints*/ +#editorHint { + padding: 5px 5px; + position: absolute; + text-align: center; + width: 100%; + pointer-events: none; +} + +#editorHint label { + pointer-events: auto; + float: right; + padding: 5px 5px; + color: #ffdd00; +} + +#editorHint label:hover { + text-decoration: underline; + cursor: pointer; +} + +#editorHint > div { + pointer-events: auto; + text-align: left; + display: inline-block; + color: #ffffff; + font-size: 0.8em; + background-color: #18202A; + padding: 5px 5px; + border-radius: 5px; + +} + +#WarningErrorMessagesContainer { + position: absolute; + text-align: center; + top: 0; + pointer-events: none; +} + +/*Editor hints*/ +#WarningErrorMessages { + position: relative; + /*text-align: center;*/ + width: 50%; + pointer-events: auto; + margin: 10px 0; + padding-right: 12px; + overflow-y: auto; + overflow-x: hidden; +} + +#WarningErrorMessages label { + pointer-events: auto; + float: right; + padding: 5px 5px; + color: #ffdd00; +} + +#WarningErrorMessages span { + pointer-events: auto; + float: right; + padding: 5px 5px; +} + +#WarningErrorMessages label:hover { + text-decoration: underline; + cursor: pointer; +} + +#WarningErrorMessages > div { + pointer-events: auto; + text-align: left; + display: inline-block; + color: #ffffff; + font-size: 0.8em; + background-color: #18202A; + padding: 5px 5px; + border-radius: 10px; + border: solid 1px #ecf0f1; + width: 70%; + +} + +#WarningErrorMessagesContent > ul { + -webkit-padding-start: 20px; + padding: 0 16px; + +} + +#WarningErrorMessagesContent > ul > li { + padding: 5px; +} + +.converter-form-Editor { + /*display: inline-block;*/ +} + +.textLineEditWithLabel { + display: inline-block; + width: 100%; + border-bottom: 1px solid #34495E; + padding: 2px 0; + +} + +.converter-form-Editor label { + /*//display: inline-block;*/ + line-height: normal; +} + +.descriptionTextClass { + background-color: #34495E; + color: white; +} + +.prefixIRIElements input { + border: 1px solid #34495E; + background-color: #34495E; + color: white; +} + +.prefixIRIElements input:disabled { + background-color: rgb(24, 32, 42); + border: 1px solid rgb(24, 32, 42); + color: white; +} + +.converter-form-Editor input { + /*box-sizing: border-box;*/ + /*height: 18px;*/ + /*width: 69%;*/ + float: right; + border: 1px solid #34495E; + background-color: #34495E; + color: white; + /*border-bottom: 1px solid #d90;*/ + /*text-align: center;*/ + /*display: inline-block;*/ +} + +.converter-form-Editor input:disabled { + background-color: #545350; + border: 1px solid #34495E; + color: #939798; +} + +.disabledLabelForSlider { + color: #808080; +} diff --git a/doc/releases/0.1.0/base/webvowl/css/webvowl.css b/doc/releases/0.1.0/base/webvowl/css/webvowl.css new file mode 100644 index 0000000..bd06623 --- /dev/null +++ b/doc/releases/0.1.0/base/webvowl/css/webvowl.css @@ -0,0 +1,296 @@ +/*----------------------------------------------------------------- + VOWL graphical elements (part of spec) - mixed CSS and SVG styles +-----------------------------------------------------------------*/ + +/*-------- Text --------*/ +.text { + font-family: Helvetica, Arial, sans-serif; + font-size: 12px; +} + +.subtext { + font-size: 9px; +} + +.text.instance-count { + fill: #666; +} + +.external + text .instance-count { + fill: #aaa; +} + +.cardinality { + font-size: 10px; +} + +.text, .embedded { + pointer-events: none; +} + +/*------- Colors ------*/ +.class, .object, .disjoint, .objectproperty, .disjointwith, .equivalentproperty, .transitiveproperty, .functionalproperty, .inversefunctionalproperty, .symmetricproperty, .allvaluesfromproperty, .somevaluesfromproperty { + fill: #acf; +} + +.label .datatype, .datatypeproperty { + fill: #9c6; +} + +.rdf, .rdfproperty { + fill: #c9c; +} + +.literal, .node .datatype { + fill: #fc3; +} + +.deprecated, .deprecatedproperty { + fill: #ccc; +} + +.external, .externalproperty { + /*fill: #36c;*/ +} + +path, .nofill { + fill: none; +} + +marker path { + fill: #000; +} + +.class, path, line, .fineline { + stroke: #000; +} + +.white, .subclass, .subclassproperty, .external + text { + fill: #fff; +} + +.class.hovered, .property.hovered, .cardinality.hovered, .cardinality.focused, .filled.hovered, .filled.focused, .values-from.filled.hovered { + fill: #f00 !important; + cursor: pointer; +} + +.hoveredForEditing { + fill: #f00 !important; + cursor: pointer; +} + +.feature { + fill: #f00; + cursor: pointer; +} + +@-webkit-keyframes pulseAnimation { + 0% { + -webkit-transform: scale(1.5); + stroke-width: 3.33; + } + 50% { + stroke-width: 4; + } + 100% { + -webkit-transform: scale(1.0); + stroke-width: 5; + } +} + +@-moz-keyframes pulseAnimation { + 0% { + -webkit-transform: scale(1.5); + stroke-width: 3.33; + } + 50% { + stroke-width: 4; + } + 100% { + -webkit-transform: scale(1.0); + stroke-width: 5; + } +} + +@-o-keyframes pulseAnimation { + 0% { + -webkit-transform: scale(1.5); + stroke-width: 3.33; + } + 50% { + stroke-width: 4; + } + 100% { + -webkit-transform: scale(1.0); + stroke-width: 5; + } +} + +@keyframes pulseAnimation { + 0% { + -webkit-transform: scale(1.5); + stroke-width: 3.33; + } + 50% { + stroke-width: 4; + } + 100% { + -webkit-transform: scale(1.0); + stroke-width: 5; + } +} + +.searchResultA { + fill: none; + stroke-width: 5; + stroke: #f00; + -webkit-animation-name: pulseAnimation; + -moz-animation-name: pulseAnimation; + -o-animation-name: pulseAnimation; + animation-name: pulseAnimation; + + -webkit-animation-duration: 0.8s; + -moz-animation-duration: 0.8s; + -o-animation-duration: 0.8s; + animation-duration: 0.8s; + + -webkit-transform: translateZ(0); + -o-transform: translateZ(0); + -webkit-animation-iteration-count: 3; + -moz-animation-iteration-count: 3; + -o-animation-iteration-count: 3; + animation-iteration-count: 3; + + -webkit-animation-timing-function: linear; + -moz-animation-timing-function: linear; + -o-animation-timing-function: linear; + animation-timing-function: linear; + +} + +/* a class for not animated search results (hovered over node)*/ +.searchResultB { + fill: none; + stroke-width: 5; + stroke: #f00; +} + +.hovered-MathSymbol { + fill: none; + stroke: #f00 !important; +} + +.focused, path.hovered { + stroke: #f00 !important; +} + +.indirect-highlighting, .feature:hover { + fill: #f90; + cursor: pointer; +} + +.feature_hover { + fill: #f90; + cursor: pointer; +} + +.values-from { + stroke: #69c; +} + +.symbol, .values-from.filled { + fill: #69c; +} + +/*------- Strokes ------*/ +.class, path, line { + stroke-width: 2; +} + +.fineline { + stroke-width: 1; +} + +.dashed, .anonymous { + stroke-dasharray: 8; +} + +.dotted { + stroke-dasharray: 3; +} + +rect.focused, circle.focused { + stroke-width: 4px; +} + +.nostroke { + stroke: none; +} + +/*----------------------------------------------------------------- + Additional elements for the WebVOWL demo (NOT part of spec) +-----------------------------------------------------------------*/ + +.addDataPropertyElement { + fill: #9c6 !important; + cursor: pointer; + stroke-width: 2; + stroke: black; +} + +.addDataPropertyElement:hover { + fill: #f90 !important; + cursor: pointer; + stroke-width: 2; + stroke: black; +} + +.superHiddenElement { + fill: rgba(255, 153, 0, 0.4); + cursor: pointer; + stroke-width: 0; + stroke: black; + /*opacity:0;*/ +} + +.superOpacityElement { + opacity: 0; +} + +.deleteParentElement:hover { + fill: #f90; + cursor: pointer; + stroke-width: 2; + stroke: black; +} + +.deleteParentElement { + fill: #f00; + cursor: pointer; + stroke-width: 2; + stroke: black; +} + +.classNodeDragPath { + stroke: black; + stroke-width: 2px; +} + +.classDraggerNodeHovered { + fill: #f90; + stroke: black; + stroke-width: 2px; + cursor: pointer; +} + +.classDraggerNode { + fill: #acf; + stroke: black; + stroke-width: 2px; +} + +marker path { + /* Safari and Chrome workaround for inheriting the style of its link. + Use any value that is larger than the length of the marker path. */ + stroke-dasharray: 100; +} diff --git a/doc/releases/0.1.0/base/webvowl/data/foaf.json b/doc/releases/0.1.0/base/webvowl/data/foaf.json new file mode 100644 index 0000000..4897985 --- /dev/null +++ b/doc/releases/0.1.0/base/webvowl/data/foaf.json @@ -0,0 +1,2894 @@ +{ + "_comment" : "Created with OWL2VOWL (version 0.3.7), http://vowl.visualdataweb.org", + "header" : { + "languages" : [ "undefined" ], + "baseIris" : [ "http://schema.org", "http://www.w3.org/2000/01/rdf-schema", "http://www.w3.org/2003/01/geo/wgs84_pos", "http://purl.org/dc/terms", "http://www.w3.org/2001/XMLSchema", "http://xmlns.com/foaf/0.1", "http://www.w3.org/2000/10/swap/pim/contact", "http://www.w3.org/2004/02/skos/core" ], + "prefixList" : { + "owl" : "http://www.w3.org/2002/07/owl#", + "rdf" : "http://www.w3.org/1999/02/22-rdf-syntax-ns#", + "wot" : "http://xmlns.com/wot/0.1/", + "xsd" : "http://www.w3.org/2001/XMLSchema#", + "dc" : "http://purl.org/dc/elements/1.1/", + "xml" : "http://www.w3.org/XML/1998/namespace", + "vs" : "http://www.w3.org/2003/06/sw-vocab-status/ns#", + "foaf" : "http://xmlns.com/foaf/0.1/", + "rdfs" : "http://www.w3.org/2000/01/rdf-schema#" + }, + "title" : { + "undefined" : "Friend of a Friend (FOAF) vocabulary" + }, + "iri" : "http://xmlns.com/foaf/0.1/", + "description" : { + "undefined" : "The Friend of a Friend (FOAF) RDF vocabulary, described using W3C RDF Schema and the Web Ontology Language." + }, + "other" : { + "title" : [ { + "identifier" : "title", + "language" : "undefined", + "value" : "Friend of a Friend (FOAF) vocabulary", + "type" : "label" + } ] + } + }, + "namespace" : [ ], + "class" : [ { + "id" : "3", + "type" : "owl:Thing" + }, { + "id" : "9", + "type" : "owl:Class" + }, { + "id" : "1", + "type" : "owl:equivalentClass" + }, { + "id" : "18", + "type" : "owl:Thing" + }, { + "id" : "19", + "type" : "owl:Thing" + }, { + "id" : "5", + "type" : "owl:Thing" + }, { + "id" : "20", + "type" : "rdfs:Literal" + }, { + "id" : "8", + "type" : "rdfs:Literal" + }, { + "id" : "11", + "type" : "owl:Class" + }, { + "id" : "21", + "type" : "owl:Thing" + }, { + "id" : "22", + "type" : "rdfs:Literal" + }, { + "id" : "24", + "type" : "rdfs:Literal" + }, { + "id" : "26", + "type" : "rdfs:Literal" + }, { + "id" : "27", + "type" : "rdfs:Literal" + }, { + "id" : "37", + "type" : "owl:equivalentClass" + }, { + "id" : "45", + "type" : "rdfs:Literal" + }, { + "id" : "46", + "type" : "rdfs:Literal" + }, { + "id" : "53", + "type" : "rdfs:Literal" + }, { + "id" : "56", + "type" : "rdfs:Literal" + }, { + "id" : "59", + "type" : "rdfs:Literal" + }, { + "id" : "60", + "type" : "owl:Class" + }, { + "id" : "61", + "type" : "rdfs:Literal" + }, { + "id" : "6", + "type" : "rdfs:Literal" + }, { + "id" : "62", + "type" : "rdfs:Literal" + }, { + "id" : "12", + "type" : "owl:equivalentClass" + }, { + "id" : "55", + "type" : "rdfs:Literal" + }, { + "id" : "69", + "type" : "rdfs:Literal" + }, { + "id" : "71", + "type" : "owl:Class" + }, { + "id" : "36", + "type" : "owl:Class" + }, { + "id" : "86", + "type" : "owl:Class" + }, { + "id" : "83", + "type" : "owl:Class" + }, { + "id" : "94", + "type" : "owl:Class" + }, { + "id" : "73", + "type" : "rdfs:Literal" + }, { + "id" : "68", + "type" : "rdfs:Literal" + }, { + "id" : "93", + "type" : "rdfs:Literal" + }, { + "id" : "33", + "type" : "owl:Thing" + }, { + "id" : "49", + "type" : "rdfs:Literal" + }, { + "id" : "29", + "type" : "owl:Thing" + }, { + "id" : "101", + "type" : "rdfs:Literal" + }, { + "id" : "39", + "type" : "owl:Thing" + }, { + "id" : "63", + "type" : "owl:equivalentClass" + }, { + "id" : "64", + "type" : "owl:equivalentClass" + }, { + "id" : "102", + "type" : "owl:equivalentClass" + }, { + "id" : "78", + "type" : "owl:Class" + }, { + "id" : "77", + "type" : "owl:Class" + }, { + "id" : "13", + "type" : "owl:equivalentClass" + }, { + "id" : "58", + "type" : "rdfs:Literal" + }, { + "id" : "100", + "type" : "rdfs:Literal" + }, { + "id" : "106", + "type" : "rdfs:Literal" + }, { + "id" : "52", + "type" : "rdfs:Literal" + }, { + "id" : "88", + "type" : "rdfs:Literal" + }, { + "id" : "118", + "type" : "rdfs:Literal" + }, { + "id" : "126", + "type" : "owl:Class" + }, { + "id" : "2", + "type" : "owl:equivalentClass" + }, { + "id" : "32", + "type" : "owl:equivalentClass" + }, { + "id" : "10", + "type" : "owl:Class" + } ], + "classAttribute" : [ { + "iri" : "http://www.w3.org/2002/07/owl#Thing", + "baseIri" : "http://owl2vowl.de", + "id" : "3", + "label" : { + "undefined" : "Thing" + } + }, { + "iri" : "http://www.w3.org/2004/02/skos/core#Concept", + "baseIri" : "http://www.w3.org/2004/02/skos/core", + "instances" : 0, + "label" : { + "IRI-based" : "Concept", + "undefined" : "Concept" + }, + "attributes" : [ "external" ], + "id" : "9" + }, { + "iri" : "http://xmlns.com/foaf/0.1/Agent", + "equivalent" : [ "13" ], + "baseIri" : "http://xmlns.com/foaf/0.1", + "instances" : 0, + "annotations" : { + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "Agent", + "undefined" : "Agent" + }, + "subClasses" : [ "10", "11", "12" ], + "comment" : { + "undefined" : "An agent (eg. person, group, software or physical artifact)." + }, + "attributes" : [ "equivalent" ], + "id" : "1" + }, { + 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+ }, { + "id" : "81", + "type" : "owl:objectProperty" + }, { + "id" : "82", + "type" : "rdfs:SubClassOf" + }, { + "id" : "34", + "type" : "owl:objectProperty" + }, { + "id" : "85", + "type" : "rdfs:SubClassOf" + }, { + "id" : "87", + "type" : "owl:datatypeProperty" + }, { + "id" : "89", + "type" : "rdfs:SubClassOf" + }, { + "id" : "90", + "type" : "rdfs:SubClassOf" + }, { + "id" : "91", + "type" : "owl:objectProperty" + }, { + "id" : "92", + "type" : "owl:datatypeProperty" + }, { + "id" : "95", + "type" : "owl:datatypeProperty" + }, { + "id" : "96", + "type" : "owl:objectProperty" + }, { + "id" : "97", + "type" : "owl:datatypeProperty" + }, { + "id" : "98", + "type" : "rdfs:SubClassOf" + }, { + "id" : "99", + "type" : "owl:datatypeProperty" + }, { + "id" : "43", + "type" : "owl:objectProperty" + }, { + "id" : "42", + "type" : "owl:objectProperty" + }, { + "id" : "103", + "type" : "owl:datatypeProperty" + }, { + "id" : "104", + "type" : "owl:objectProperty" + }, { + "id" : "105", + "type" : "owl:datatypeProperty" + }, { + "id" : "107", + "type" : "owl:objectProperty" + }, { + "id" : "108", + "type" : "owl:datatypeProperty" + }, { + "id" : "109", + "type" : "owl:objectProperty" + }, { + "id" : "110", + "type" : "owl:objectProperty" + }, { + "id" : "40", + "type" : "owl:objectProperty" + }, { + "id" : "41", + "type" : "owl:objectProperty" + }, { + "id" : "84", + "type" : "owl:objectProperty" + }, { + "id" : "111", + "type" : "owl:datatypeProperty" + }, { + "id" : "112", + "type" : "owl:datatypeProperty" + }, { + "id" : "113", + "type" : "owl:datatypeProperty" + }, { + "id" : "114", + "type" : "owl:objectProperty" + }, { + "id" : "116", + "type" : "owl:disjointWith" + }, { + "id" : "117", + "type" : "owl:disjointWith" + }, { + "id" : "119", + "type" : "owl:datatypeProperty" + }, { + "id" : "120", + "type" : "owl:disjointWith" + }, { + "id" : "121", + "type" : "owl:disjointWith" + }, { + "id" : "122", + "type" : "owl:objectProperty" + }, { + "id" : "123", + "type" : "owl:datatypeProperty" + }, { + "id" : "124", + "type" : "owl:objectProperty" + }, { + "id" : "125", + "type" : "owl:datatypeProperty" + }, { + "id" : "127", + "type" : "owl:datatypeProperty" + }, { + "id" : "115", + "type" : "owl:objectProperty" + }, { + "id" : "128", + "type" : "owl:objectProperty" + }, { + "id" : "129", + "type" : "owl:objectProperty" + } ], + "propertyAttribute" : [ { + "iri" : "http://xmlns.com/foaf/0.1/interest", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "interest", + "undefined" : "interest" + }, + "domain" : "1", + "comment" : { + "undefined" : "A page about a topic of interest to this person." + }, + "attributes" : [ "object" ], + "id" : "0" + }, { + "iri" : "http://xmlns.com/foaf/0.1/mbox_sha1sum", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "6", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "mbox_sha1sum", + "undefined" : "sha1sum of a personal mailbox URI name" + }, + "domain" : "5", + "comment" : { + "undefined" : "The sha1sum of the URI of an Internet mailbox associated with exactly one owner, the first owner of the mailbox." + }, + "attributes" : [ "datatype" ], + "id" : "4" + }, { + "iri" : "http://xmlns.com/foaf/0.1/nick", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "8", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "nick", + "undefined" : "nickname" + }, + "domain" : "5", + "comment" : { + "undefined" : "A short informal nickname characterising an agent (includes login identifiers, IRC and other chat nicknames)." + }, + "attributes" : [ "datatype" ], + "id" : "7" + }, { + "iri" : "http://xmlns.com/foaf/0.1/openid", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "openid", + "undefined" : "openid" + }, + "superproperty" : [ "15" ], + "domain" : "1", + "comment" : { + "undefined" : "An OpenID for an Agent." + }, + "attributes" : [ "inverse functional", "object" ], + "id" : "14" + }, { + "iri" : "http://xmlns.com/foaf/0.1/workInfoHomepage", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "workInfoHomepage", + "undefined" : "work info homepage" + }, + "domain" : "12", + "comment" : { + "undefined" : "A work info homepage of some person; a page about their work for some organization." + }, + "attributes" : [ "object" ], + "id" : "16" + }, { + "iri" : "http://xmlns.com/foaf/0.1/pastProject", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "3", + "annotations" : { + "isDefinedBy" : [ { 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"comment" : { + "undefined" : "A theme." + }, + "attributes" : [ "object" ], + "id" : "23" + }, { + "iri" : "http://xmlns.com/foaf/0.1/knows", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "12", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "knows", + "undefined" : "knows" + }, + "domain" : "12", + "comment" : { + "undefined" : "A person known by this person (indicating some level of reciprocated interaction between the parties)." + }, + "attributes" : [ "object" ], + "id" : "25" + }, { + "iri" : "http://xmlns.com/foaf/0.1/focus", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "29", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + 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specified using fully qualified tel: URI scheme (refs: http://www.w3.org/Addressing/schemes.html#tel)." + }, + "attributes" : [ "object" ], + "id" : "30" + }, { + "iri" : "http://xmlns.com/foaf/0.1/depicts", + "inverse" : "34", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "33", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "depicts", + "undefined" : "depicts" + }, + "domain" : "32", + "comment" : { + "undefined" : "A thing depicted in this representation." + }, + "attributes" : [ "object" ], + "id" : "31" + }, { + "iri" : "http://xmlns.com/foaf/0.1/based_near", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "36", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", 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"undefined" : "DNA checksum" + }, + "domain" : "19", + "comment" : { + "undefined" : "A checksum for the DNA of some thing. 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"identifier" : "term_status", + "language" : "undefined", + "value" : "unstable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "status", + "undefined" : "status" + }, + "domain" : "1", + "comment" : { + "undefined" : "A string expressing what the user is happy for the general public (normally) to know about their current activity." + }, + "attributes" : [ "datatype" ], + "id" : "65" + }, { + "iri" : "http://xmlns.com/foaf/0.1/yahooChatID", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "46", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "yahooChatID", + "undefined" : "Yahoo chat ID" + }, + "domain" : "19", + "comment" : { + "undefined" : "A Yahoo chat ID" + }, + "attributes" : [ 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"undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "icqChatID", + "undefined" : "ICQ chat ID" + }, + "domain" : "19", + "comment" : { + "undefined" : "An ICQ chat ID" + }, + "attributes" : [ "datatype" ], + "id" : "70" + }, { + "iri" : "http://xmlns.com/foaf/0.1/givenname", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "73", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "archaic", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "givenname", + "undefined" : "Given name" + }, + "domain" : "19", + "comment" : { + "undefined" : "The given name of some person." + }, + "attributes" : [ "datatype" ], + "id" : "72" + }, { + "iri" : "http://xmlns.com/foaf/0.1/isPrimaryTopicOf", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "isPrimaryTopicOf", + "undefined" : "is primary topic of" + }, + "superproperty" : [ "38" ], + "domain" : "39", + "subproperty" : [ "14", "43" ], + "comment" : { + "undefined" : "A document that this thing is the primary topic of." + }, + "attributes" : [ "inverse functional", "object" ], + "id" : "15" + }, { + "range" : "2", + "domain" : "32", + "attributes" : [ "anonymous", "object" ], + "id" : "74" + }, { + "range" : "2", + "domain" : "71", + "attributes" : [ "anonymous", "object" ], + "id" : "75" + }, { + "range" : "78", + "domain" : "77", + "attributes" : [ "anonymous", "object" ], + "id" : "76" + }, { + "range" : "36", + "domain" : "12", + "attributes" : [ "anonymous", "object" ], + "id" : "79" + }, { + "iri" : "http://xmlns.com/foaf/0.1/accountServiceHomepage", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "accountServiceHomepage", + "undefined" : "account service homepage" + }, + "domain" : "78", + "comment" : { + "undefined" : "Indicates a homepage of the service provide for this online account." + }, + "attributes" : [ "object" ], + "id" : "80" + }, { + "iri" : "http://xmlns.com/foaf/0.1/logo", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "19", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "logo", + "undefined" : "logo" + }, + "domain" : "19", + "comment" : { + "undefined" : "A logo representing some thing." + }, + "attributes" : [ "inverse functional", "object" ], + "id" : "81" + }, { + "range" : "78", + "domain" : "83", + "attributes" : [ "anonymous", "object" ], + "id" : "82" + }, { + "iri" : "http://xmlns.com/foaf/0.1/depiction", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "32", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "depiction", + "undefined" : "depiction" + }, + "domain" : "33", + "subproperty" : [ "84" ], + "comment" : { + "undefined" : "A depiction of some thing." + }, + "attributes" : [ "object" ], + "id" : "34" + }, { + "range" : "78", + "domain" : "86", + "attributes" : [ "anonymous", "object" ], + "id" : "85" + }, { + "iri" : "http://xmlns.com/foaf/0.1/family_name", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "88", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "archaic", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "family_name", + "undefined" : "family_name" + }, + "domain" : "12", + "comment" : { + "undefined" : "The family name of some person." + }, + "attributes" : [ "datatype" ], + "id" : "87" + }, { + "range" : "1", + "domain" : "12", + "attributes" : [ "anonymous", "object" ], + "id" : "89" + }, { + "range" : "1", + "domain" : "11", + "attributes" : [ "anonymous", "object" ], + "id" : "90" + }, { + "iri" : "http://xmlns.com/foaf/0.1/fundedBy", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "19", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "archaic", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "fundedBy", + "undefined" : "funded by" + }, + "domain" : "19", + "comment" : { + "undefined" : "An organization funding a project or person." + }, + "attributes" : [ "object" ], + "id" : "91" + }, { + "iri" : "http://xmlns.com/foaf/0.1/title", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "93", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "title", + "undefined" : "title" + }, + "domain" : "19", + "comment" : { + "undefined" : "Title (Mr, Mrs, Ms, Dr. etc)" + }, + "attributes" : [ "datatype" ], + "id" : "92" + }, { + "iri" : "http://xmlns.com/foaf/0.1/accountName", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "59", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "accountName", + "undefined" : "account name" + }, + "domain" : "78", + "comment" : { + "undefined" : "Indicates the name (identifier) associated with this online account." + }, + "attributes" : [ "datatype" ], + "id" : "95" + }, { + "iri" : "http://xmlns.com/foaf/0.1/account", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "78", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "account", + "undefined" : "account" + }, + "domain" : "1", + "comment" : { + "undefined" : "Indicates an account held by this agent." + }, + "attributes" : [ "object" ], + "id" : "96" + }, { + "iri" : "http://xmlns.com/foaf/0.1/jabberID", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "69", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "jabberID", + "undefined" : "jabber ID" + }, + "domain" : "19", + "comment" : { + "undefined" : "A jabber ID for something." + }, + "attributes" : [ "datatype" ], + "id" : "97" + }, { + "range" : "1", + "domain" : "10", + "attributes" : [ "anonymous", "object" ], + "id" : "98" + }, { + "iri" : "http://xmlns.com/foaf/0.1/age", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "100", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "unstable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "age", + "undefined" : "age" + }, + "domain" : "1", + "comment" : { + "undefined" : "The age in years of some agent." + }, + "attributes" : [ "datatype", "functional" ], + "id" : "99" + }, { + "iri" : "http://xmlns.com/foaf/0.1/homepage", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "homepage", + "undefined" : "homepage" + }, + "superproperty" : [ "15", "38" ], + "domain" : "39", + "comment" : { + "undefined" : "A homepage for some thing." + }, + "attributes" : [ "inverse functional", "object" ], + "id" : "43" + }, { + "iri" : "http://xmlns.com/foaf/0.1/tipjar", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "tipjar", + "undefined" : "tipjar" + }, + "superproperty" : [ "38" ], + "domain" : "1", + "comment" : { + "undefined" : "A tipjar document for this agent, describing means for payment and reward." + }, + "attributes" : [ "object" ], + "id" : "42" + }, { + "iri" : "http://xmlns.com/foaf/0.1/msnChatID", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "61", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "msnChatID", + "undefined" : "MSN chat ID" + }, + "domain" : "5", + "comment" : { + "undefined" : "An MSN chat ID" + }, + "attributes" : [ "datatype" ], + "id" : "103" + }, { + "iri" : "http://xmlns.com/foaf/0.1/topic_interest", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "18", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "topic_interest", + "undefined" : "topic_interest" + }, + "domain" : "1", + "comment" : { + "undefined" : "A thing of interest to this person." + }, + "attributes" : [ "object" ], + "id" : "104" + }, { + "iri" : "http://xmlns.com/foaf/0.1/aimChatID", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "106", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "aimChatID", + "undefined" : "AIM chat ID" + }, + "domain" : "19", + "comment" : { + "undefined" : "An AIM chat ID" + }, + "attributes" : [ "datatype" ], + "id" : "105" + }, { + "iri" : "http://xmlns.com/foaf/0.1/currentProject", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "3", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "currentProject", + "undefined" : "current project" + }, + "domain" : "12", + "comment" : { + "undefined" : "A current project this person works on." + }, + "attributes" : [ "object" ], + "id" : "107" + }, { + "iri" : "http://xmlns.com/foaf/0.1/skypeID", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "20", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "skypeID", + "undefined" : "Skype ID" + }, + "domain" : "1", + "comment" : { + "undefined" : "A Skype ID" + }, + "attributes" : [ "datatype" ], + "id" : "108" + }, { + "iri" : "http://xmlns.com/foaf/0.1/holdsAccount", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "78", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "archaic", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "holdsAccount", + "undefined" : "account" + }, + "domain" : "1", + "comment" : { + "undefined" : "Indicates an account held by this agent." + }, + "attributes" : [ "object" ], + "id" : "109" + }, { + "iri" : "http://xmlns.com/foaf/0.1/thumbnail", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "32", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "thumbnail", + "undefined" : "thumbnail" + }, + "domain" : "32", + "comment" : { + "undefined" : "A derived thumbnail image." + }, + "attributes" : [ "object" ], + "id" : "110" + }, { + "iri" : "http://xmlns.com/foaf/0.1/topic", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "39", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "topic", + "undefined" : "topic" + }, + "domain" : "2", + "comment" : { + "undefined" : "A topic of some page or document." + }, + "attributes" : [ "object" ], + "id" : "40" + }, { + "iri" : "http://xmlns.com/foaf/0.1/weblog", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "weblog", + "undefined" : "weblog" + }, + "superproperty" : [ "38" ], + "domain" : "1", + "comment" : { + "undefined" : "A weblog of some thing (whether person, group, company etc.)." + }, + "attributes" : [ "inverse functional", "object" ], + "id" : "41" + }, { + "iri" : "http://xmlns.com/foaf/0.1/img", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "32", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "img", + "undefined" : "image" + }, + "superproperty" : [ "34" ], + "domain" : "12", + "comment" : { + "undefined" : "An image that can be used to represent some thing (ie. those depictions which are particularly representative of something, eg. one's photo on a homepage)." + }, + "attributes" : [ "object" ], + "id" : "84" + }, { + "iri" : "http://xmlns.com/foaf/0.1/birthday", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "56", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "unstable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "birthday", + "undefined" : "birthday" + }, + "domain" : "1", + "comment" : { + "undefined" : "The birthday of this Agent, represented in mm-dd string form, eg. '12-31'." + }, + "attributes" : [ "datatype", "functional" ], + "id" : "111" + }, { + "iri" : "http://xmlns.com/foaf/0.1/sha1", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "101", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "unstable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "sha1", + "undefined" : "sha1sum (hex)" + }, + "domain" : "2", + "comment" : { + "undefined" : "A sha1sum hash, in hex." + }, + "attributes" : [ "datatype" ], + "id" : "112" + }, { + "iri" : "http://xmlns.com/foaf/0.1/firstName", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "24", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "firstName", + "undefined" : "firstName" + }, + "domain" : "12", + "comment" : { + "undefined" : "The first name of a person." + }, + "attributes" : [ "datatype" ], + "id" : "113" + }, { + "iri" : "http://xmlns.com/foaf/0.1/made", + "inverse" : "115", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "18", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "made", + "undefined" : "made" + }, + "domain" : "1", + "comment" : { + "undefined" : "Something that was made by this agent." + }, + "attributes" : [ "object" ], + "id" : "114" + }, { + "range" : "60", + "domain" : "2", + "attributes" : [ "anonymous", "object" ], + "id" : "116" + }, { + "range" : "12", + "domain" : "60", + "attributes" : [ "anonymous", "object" ], + "id" : "117" + }, { + "iri" : "http://xmlns.com/foaf/0.1/familyName", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "62", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "familyName", + "undefined" : "familyName" + }, + "domain" : "12", + "comment" : { + "undefined" : "The family name of some person." + }, + "attributes" : [ "datatype" ], + "id" : "119" + }, { + "range" : "2", + "domain" : "11", + "attributes" : [ "anonymous", "object" ], + "id" : "120" + }, { + "range" : "12", + "domain" : "11", + "attributes" : [ "anonymous", "object" ], + "id" : "121" + }, { + "iri" : "http://xmlns.com/foaf/0.1/member", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "1", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "member", + "undefined" : "member" + }, + "domain" : "10", + "comment" : { + "undefined" : "Indicates a member of a Group" + }, + "attributes" : [ "object" ], + "id" : "122" + }, { + "iri" : "http://xmlns.com/foaf/0.1/plan", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "27", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "plan", + "undefined" : "plan" + }, + "domain" : "12", + "comment" : { + "undefined" : "A .plan comment, in the tradition of finger and '.plan' files." + }, + "attributes" : [ "datatype" ], + "id" : "123" + }, { + "iri" : "http://xmlns.com/foaf/0.1/mbox", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "18", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "mbox", + "undefined" : "personal mailbox" + }, + "domain" : "1", + "comment" : { + "undefined" : "A personal mailbox, ie. an Internet mailbox associated with exactly one owner, the first owner of this mailbox. This is a 'static inverse functional property', in that there is (across time and change) at most one individual that ever has any particular value for foaf:mbox." + }, + "attributes" : [ "inverse functional", "object" ], + "id" : "124" + }, { + "iri" : "http://xmlns.com/foaf/0.1/surname", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "118", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "archaic", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "surname", + "undefined" : "Surname" + }, + "domain" : "12", + "comment" : { + "undefined" : "The surname of some person." + }, + "attributes" : [ "datatype" ], + "id" : "125" + }, { + "iri" : "http://xmlns.com/foaf/0.1/myersBriggs", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "22", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "myersBriggs", + "undefined" : "myersBriggs" + }, + "domain" : "12", + "comment" : { + "undefined" : "A Myers Briggs (MBTI) personality classification." + }, + "attributes" : [ "datatype" ], + "id" : "127" + }, { + "iri" : "http://xmlns.com/foaf/0.1/maker", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "1", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "maker", + "undefined" : "maker" + }, + "domain" : "18", + "comment" : { + "undefined" : "An agent that made this thing." + }, + "attributes" : [ "object" ], + "id" : "115" + }, { + "iri" : "http://xmlns.com/foaf/0.1/publications", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "publications", + "undefined" : "publications" + }, + "domain" : "12", + "comment" : { + "undefined" : "A link to the publications of this person." + }, + "attributes" : [ "object" ], + "id" : "128" + }, { + "iri" : "http://xmlns.com/foaf/0.1/workplaceHomepage", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "workplaceHomepage", + "undefined" : "workplace homepage" + }, + "domain" : "12", + "comment" : { + "undefined" : "A workplace homepage of some person; the homepage of an organization they work for." + }, + "attributes" : [ "object" ], + "id" : "129" + } ] +} \ No newline at end of file diff --git a/doc/releases/0.1.0/base/webvowl/data/ontology.json b/doc/releases/0.1.0/base/webvowl/data/ontology.json new file mode 100644 index 0000000..57fea9f --- /dev/null +++ b/doc/releases/0.1.0/base/webvowl/data/ontology.json @@ -0,0 +1,690 @@ +{ + "_comment" : "Created with OWL2VOWL (version 0.3.5), http://vowl.visualdataweb.org", + "header" : { + "languages" : [ "en", "undefined" ], + "baseIris" : [ "http://www.w3.org/1999/02/22-rdf-syntax-ns", "http://www.w3.org/2000/01/rdf-schema", "http://www.w3.org/2001/XMLSchema", "http://purl.org/neao/base", "http://purl.org/spar/biro" ], + "iri" : "http://purl.org/neao/base#", + "version" : "0.1.0", + "author" : [ "Michael Denker (ORCID: 0000-0003-1255-7300)", "Cristiano Köhler (ORCID: 0000-0003-0503-5264)" ], + "labels" : { + "en" : "Neuroelectrophysiology Analysis Ontology - Base classes" + }, + "comments" : { + "en" : "This module contains the core classes of the Neuroelectrophysiology Analysis Ontology (NEAO) model.\n\nThe NEAO ontology model is constructed upon the central AnalysisStep class, that represents any process that generates new data entities (e.g., generating artificial spike trains) or performs specific operations aimed at extracting additional information during the analysis using existing data entities. For example, a time series with the raw signal recorded from an electrode can be low-pass filtered to extract the local field potential (LFP) component (the step produces transformed data). Additionaly, this new time series with the LFP data can be used in another step to compute the power spectral density (the step produces new, derived data). Therefore, every stage of the analysis generates new data or applies particular operations to data entities.\n\nThe inputs and outputs of the analysis steps are represented by the Data class. This represents any entity storing information needed throughout the analysis. It might represent the data created or transformed by an analysis step, or it can represent data from an electrophysiological recording obtained from neural tissue (or comparable data generated by a simulation). For example, the raw signal time series saved by the recording apparatus, the filtered LFP time series, and the array holding the power spectral density estimates are instances of the Data class.\n\nAn information entity that regulates the behavior of the analysis step is a parameter, and is represented by the AnalysisParameter class. A parameter does not provide data that is used by the step to produce the output. For example, in a low-pass filtering step in the analysis to produce the LFP, the time series with the raw wideband signal is the data input, and the low-pass frequency cutoff frequency value is a parameter.\n\nThe three core classes are related by the object properties hasInput, hasOutput, and usesParameter. Furthermore, several annotation properties are used to provide clear and unambiguous descriptions of the entities represented by the classes. These include abbreviations (abbreviation property), bibliographic references (hasBibliographicReference), labels (SKOS prefLabel and altLabel properties) and the class description (using RDFS comment property).\n\nThe specific analysis method used in a step of the analysis can be implemented by different software codes, such as distinct open-source toolboxes that are available to analyze electrophysiology data. The core NEAO model has two classes describing the software implementation of the analysis step. The main source of the code used to execute the operations involved in the analysis step is represented by the SoftwareImplementation class. This is the code that take any given data input, transform it, and produce the desired results. The SoftwarePackage class is used to describe collections of software, such as toolboxes with many functionality for neuroelectrophysiology data analysis (i.e., that bundle together different pieces of code). The relationship between SoftwareImplementation and SoftwarePackage is established with the property isImplementedInPackage. The relationship between the AnalysisStep and SoftwareImplementation is defined using the isImplementedIn property. The details of the individuals of each class are provided by distinct properties. The version property of SoftwareImplementation is used to define the version of the software. The packageName and packageVersion properties of SoftwarePackage specify the package name and version, respectively. \n\nProgram and Function are two subclasses of SoftwareImplementation that correspond to the two main approaches used to implement the code for an analysis step. The entity represented by Program is an executable that has been compiled or a complete script that the operating system can call to perform the analysis step (for example, an executable that reads a file, computes the power spectral density using the Welch technique, and saves a file containing the power spectral density). The entity represented by Function is a small, reusable code that is used as a building block in larger programs that execute several steps in the analysis. Specific details of these two forms of implementing software are defined using additional properties. The nameInDefinition property in Function specifies the name that is used in the function declaration and in applications that utilize the function code. The programName property of Program specifies the name of the program as published.\n\nFinally, although NEAO does not aim to model the data acquisition or to give more details of the source and format of the data utilized in the analysis, two classes are defined as abstractions to organize additional information on the entities of the Data class. Data source information can be defined with the ElectrophysiologySignalSource class. For example, this could be used to describe the recording channel, the anatomical features, or the recording technique (e.g., extracellular recording or EEG). Details on the data's structure, which are important for understanding the analysis, can described with the DataRepresentation class. For example, when computing the Pearson correlation coefficient between two binned spike trains, one scalar value is obtained if the input is a pair of spike trains. However, if that analysis step takes a set of binned spike trains, the output could contain a matrix with all the pairwise coefficients computed. These classes are related to the AnalysisStep class using the hasSource and isRepresentedAs properties." + }, + "other" : { + "license" : [ { + "identifier" : "license", + "language" : "undefined", + "value" : "https://creativecommons.org/licenses/by/4.0/", + "type" : "iri" + } ], + "creator" : [ { + "identifier" : "creator", + "language" : "undefined", + "value" : "Michael Denker (ORCID: 0000-0003-1255-7300)", + "type" : "label" + }, { + "identifier" : "creator", + "language" : "undefined", + "value" : "Cristiano Köhler (ORCID: 0000-0003-0503-5264)", + "type" : "label" + } ], + "created" : [ { + "identifier" : "created", + "language" : "undefined", + "value" : "2022-01-19", + "type" : "label" + } ], + "preferredNamespacePrefix" : [ { + "identifier" : "preferredNamespacePrefix", + "language" : "undefined", + "value" : "neao_base", + "type" : "label" + } ], + "preferredNamespaceUri" : [ { + "identifier" : "preferredNamespaceUri", + "language" : "undefined", + "value" : "http://purl.org/neao/base#", + "type" : "label" + } ], + "versionInfo" : [ { + "identifier" : "versionInfo", + "language" : "undefined", + "value" : "0.1.0", + "type" : "label" + } ] + } + }, + "namespace" : [ ], + "class" : [ { + "id" : "7", + "type" : "owl:Class" + }, { + "id" : "1", + "type" : "owl:Class" + }, { + "id" : "11", + "type" : "owl:Class" + }, { + "id" : "14", + "type" : "rdfs:Datatype" + }, { + "id" : "15", + "type" : "rdfs:Literal" + }, { + "id" : "12", + "type" : "rdfs:Literal" + }, { + "id" : "16", + "type" : "owl:Class" + }, { + "id" : "17", + "type" : "rdfs:Datatype" + }, { + "id" : "9", + "type" : "owl:Class" + }, { + "id" : "2", + "type" : "rdfs:Literal" + }, { + "id" : "23", + "type" : "owl:Class" + }, { + "id" : "8", + "type" : "owl:Class" + }, { + "id" : "20", + "type" : "owl:Class" + }, { + "id" : "5", + "type" : "owl:Class" + }, { + "id" : "4", + "type" : "owl:Class" + } ], + "classAttribute" : [ { + "iri" : "http://purl.org/neao/base#Data", + "baseIri" : "http://purl.org/neao/base", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "data", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "Data" + }, + "comment" : { + "en" : "An entity that represents a piece of data, i.e., relevant information, during the analysis. It can be recorded from a biological entity or from a simulation yielding comparable data, or it can be generated/transformed by other analysis step processes." + }, + "id" : "7" + }, { + "iri" : "http://purl.org/neao/base#SoftwareImplementation", + "baseIri" : "http://purl.org/neao/base", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "software implementation", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "SoftwareImplementation" + }, + "subClasses" : [ "8", "9" ], + "comment" : { + "en" : "Describes the details for the execution of the analysis step using a computer. The software contains a sequence or set of instructions that is used by the computer to perform all the computations required to execute the analysis step." + }, + "id" : "1" + }, { + "iri" : "http://purl.org/neao/base#SoftwarePackage", + "baseIri" : "http://purl.org/neao/base", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "software package", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "SoftwarePackage" + }, + "comment" : { + "en" : "A collection of one or more programs that can be executed by a computer and/or one or more functions that can be imported and used when writing programs." + }, + "id" : "11" + }, { + "iri" : "http://www.w3.org/2001/XMLSchema#string", + "baseIri" : "http://www.w3.org/2001/XMLSchema", + "id" : "14", + "label" : { + "IRI-based" : "string" + } + }, { + "iri" : "http://www.w3.org/2000/01/rdf-schema#Literal", + "baseIri" : "http://www.w3.org/2000/01/rdf-schema", + "id" : "15", + "label" : { + "IRI-based" : "Literal", + "undefined" : "Literal" + } + }, { + "iri" : "http://www.w3.org/2000/01/rdf-schema#Literal", + "baseIri" : "http://www.w3.org/2000/01/rdf-schema", + "id" : "12", + "label" : { + "IRI-based" : "Literal", + "undefined" : "Literal" + } + }, { + "iri" : "http://purl.org/spar/biro/BibliographicReference", + "baseIri" : "http://purl.org/spar/biro", + "instances" : 0, + "label" : { + "IRI-based" : "BibliographicReference" + }, + "attributes" : [ "external" ], + "id" : "16" + }, { + "iri" : "http://www.w3.org/2001/XMLSchema#string", + "baseIri" : "http://www.w3.org/2001/XMLSchema", + "id" : "17", + "label" : { + "IRI-based" : "string" + } + }, { + "iri" : "http://purl.org/neao/base#Program", + "baseIri" : "http://purl.org/neao/base", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "program", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "Program" + }, + "comment" : { + "en" : "A set of instructions that is executed by a computer. The instructions of the program can be executed by an interpreter or compiled to machine code. The program instructs the computer to perform tasks and it is called by the operating system." + }, + "id" : "9", + "superClasses" : [ "1" ] + }, { + "iri" : "http://www.w3.org/2000/01/rdf-schema#Literal", + "baseIri" : "http://www.w3.org/2000/01/rdf-schema", + "id" : "2", + "label" : { + "IRI-based" : "Literal", + "undefined" : "Literal" + } + }, { + "iri" : "http://purl.org/neao/base#DataRepresentation", + "baseIri" : "http://purl.org/neao/base", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "data representation", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "DataRepresentation" + }, + "comment" : { + "en" : "Defines the formal structure to represent a piece of data." + }, + "id" : "23" + }, { + "iri" : "http://purl.org/neao/base#Function", + "baseIri" : "http://purl.org/neao/base", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "function", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "Function" + }, + "comment" : { + "en" : "A reusable set of instructions that can be used when writing computer programs. A function performs specific tasks, and can be implemented as part of a single computer program or in a software package (library) so that it can be reused across several programs." + }, + "id" : "8", + "superClasses" : [ "1" ] + }, { + "iri" : "http://purl.org/neao/base#ElectrophysiologySignalSource", + "baseIri" : "http://purl.org/neao/base", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "electrophysiology signal source", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ElectrophysiologySignalSource" + }, + "comment" : { + "en" : "Defines the source of a recorded piece of electrophysiology data, i.e., the recorded signals. This is a general concept, that can be expanded to incorporate the anatomical/tissue description from where the signal was recorded, as well as the recording technique.\n\nFor example, voltage potentials can be acquired from extracellular electrodes situtated on the scalp (electroencephalogram), directly on the cortical surface (electrocorticogram) or implanted deep into a specific brain region (multielectrode array)." + }, + "id" : "20" + }, { + "iri" : "http://purl.org/neao/base#AnalysisParameter", + "baseIri" : "http://purl.org/neao/base", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "parameter", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "AnalysisParameter" + }, + "comment" : { + "en" : "An information entity that controls the behavior of an analysis step. 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the modules object (__webpack_modules__) +/******/ __webpack_require__.m = modules; + +/******/ // expose the module cache +/******/ __webpack_require__.c = installedModules; + +/******/ // __webpack_public_path__ +/******/ __webpack_require__.p = ""; + +/******/ // Load entry module and return exports +/******/ return __webpack_require__(0); +/******/ }) +/************************************************************************/ +/******/ ({ + +/***/ 0: +/***/ (function(module, exports, __webpack_require__) { + + __webpack_require__(319); + __webpack_require__(321); + + module.exports = __webpack_require__(322); + + +/***/ }), + +/***/ 6: +/***/ (function(module, exports) { + + module.exports = d3; + +/***/ }), + +/***/ 91: +/***/ (function(module, exports, __webpack_require__) { + + var Symbol = __webpack_require__(92), + getRawTag = __webpack_require__(95), + objectToString = __webpack_require__(96); + + /** `Object#toString` result references. */ + var nullTag = '[object Null]', + undefinedTag = '[object Undefined]'; + + /** Built-in value references. */ + var symToStringTag = Symbol ? Symbol.toStringTag : undefined; + + /** + * The base implementation of `getTag` without fallbacks for buggy environments. + * + * @private + * @param {*} value The value to query. + * @returns {string} Returns the `toStringTag`. + */ + function baseGetTag(value) { + if (value == null) { + return value === undefined ? undefinedTag : nullTag; + } + return (symToStringTag && symToStringTag in Object(value)) + ? getRawTag(value) + : objectToString(value); + } + + module.exports = baseGetTag; + + +/***/ }), + +/***/ 92: +/***/ (function(module, exports, __webpack_require__) { + + var root = __webpack_require__(93); + + /** Built-in value references. */ + var Symbol = root.Symbol; + + module.exports = Symbol; + + +/***/ }), + +/***/ 93: +/***/ (function(module, exports, __webpack_require__) { + + var freeGlobal = __webpack_require__(94); + + /** Detect free variable `self`. */ + var freeSelf = typeof self == 'object' && self && self.Object === Object && self; + + /** Used as a reference to the global object. */ + var root = freeGlobal || freeSelf || Function('return this')(); + + module.exports = root; + + +/***/ }), + +/***/ 94: +/***/ (function(module, exports) { + + /* WEBPACK VAR INJECTION */(function(global) {/** Detect free variable `global` from Node.js. */ + var freeGlobal = typeof global == 'object' && global && global.Object === Object && global; + + module.exports = freeGlobal; + + /* WEBPACK VAR INJECTION */}.call(exports, (function() { return this; }()))) + +/***/ }), + +/***/ 95: +/***/ (function(module, exports, __webpack_require__) { + + var Symbol = __webpack_require__(92); + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * Used to resolve the + * [`toStringTag`](http://ecma-international.org/ecma-262/7.0/#sec-object.prototype.tostring) + * of values. + */ + var nativeObjectToString = objectProto.toString; + + /** Built-in value references. */ + var symToStringTag = Symbol ? Symbol.toStringTag : undefined; + + /** + * A specialized version of `baseGetTag` which ignores `Symbol.toStringTag` values. + * + * @private + * @param {*} value The value to query. + * @returns {string} Returns the raw `toStringTag`. + */ + function getRawTag(value) { + var isOwn = hasOwnProperty.call(value, symToStringTag), + tag = value[symToStringTag]; + + try { + value[symToStringTag] = undefined; + var unmasked = true; + } catch (e) {} + + var result = nativeObjectToString.call(value); + if (unmasked) { + if (isOwn) { + value[symToStringTag] = tag; + } else { + delete value[symToStringTag]; + } + } + return result; + } + + module.exports = getRawTag; + + +/***/ }), + +/***/ 96: +/***/ (function(module, exports) { + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** + * Used to resolve the + * [`toStringTag`](http://ecma-international.org/ecma-262/7.0/#sec-object.prototype.tostring) + * of values. + */ + var nativeObjectToString = objectProto.toString; + + /** + * Converts `value` to a string using `Object.prototype.toString`. + * + * @private + * @param {*} value The value to convert. + * @returns {string} Returns the converted string. + */ + function objectToString(value) { + return nativeObjectToString.call(value); + } + + module.exports = objectToString; + + +/***/ }), + +/***/ 103: +/***/ (function(module, exports, __webpack_require__) { + + var baseGetTag = __webpack_require__(91), + isObjectLike = __webpack_require__(104); + + /** `Object#toString` result references. */ + var symbolTag = '[object Symbol]'; + + /** + * Checks if `value` is classified as a `Symbol` primitive or object. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a symbol, else `false`. + * @example + * + * _.isSymbol(Symbol.iterator); + * // => true + * + * _.isSymbol('abc'); + * // => false + */ + function isSymbol(value) { + return typeof value == 'symbol' || + (isObjectLike(value) && baseGetTag(value) == symbolTag); + } + + module.exports = isSymbol; + + +/***/ }), + +/***/ 104: +/***/ (function(module, exports) { + + /** + * Checks if `value` is object-like. A value is object-like if it's not `null` + * and has a `typeof` result of "object". + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is object-like, else `false`. + * @example + * + * _.isObjectLike({}); + * // => true + * + * _.isObjectLike([1, 2, 3]); + * // => true + * + * _.isObjectLike(_.noop); + * // => false + * + * _.isObjectLike(null); + * // => false + */ + function isObjectLike(value) { + return value != null && typeof value == 'object'; + } + + module.exports = isObjectLike; + + +/***/ }), + +/***/ 112: +/***/ (function(module, exports) { + + /** + * Checks if `value` is classified as an `Array` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an array, else `false`. + * @example + * + * _.isArray([1, 2, 3]); + * // => true + * + * _.isArray(document.body.children); + * // => false + * + * _.isArray('abc'); + * // => false + * + * _.isArray(_.noop); + * // => false + */ + var isArray = Array.isArray; + + module.exports = isArray; + + +/***/ }), + +/***/ 154: +/***/ (function(module, exports) { + + /** + * A specialized version of `_.map` for arrays without support for iteratee + * shorthands. + * + * @private + * @param {Array} [array] The array to iterate over. + * @param {Function} iteratee The function invoked per iteration. + * @returns {Array} Returns the new mapped array. + */ + function arrayMap(array, iteratee) { + var index = -1, + length = array == null ? 0 : array.length, + result = Array(length); + + while (++index < length) { + result[index] = iteratee(array[index], index, array); + } + return result; + } + + module.exports = arrayMap; + + +/***/ }), + +/***/ 219: +/***/ (function(module, exports, __webpack_require__) { + + var baseToString = __webpack_require__(220); + + /** + * Converts `value` to a string. An empty string is returned for `null` + * and `undefined` values. The sign of `-0` is preserved. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to convert. + * @returns {string} Returns the converted string. + * @example + * + * _.toString(null); + * // => '' + * + * _.toString(-0); + * // => '-0' + * + * _.toString([1, 2, 3]); + * // => '1,2,3' + */ + function toString(value) { + return value == null ? '' : baseToString(value); + } + + module.exports = toString; + + +/***/ }), + +/***/ 220: +/***/ (function(module, exports, __webpack_require__) { + + var Symbol = __webpack_require__(92), + arrayMap = __webpack_require__(154), + isArray = __webpack_require__(112), + isSymbol = __webpack_require__(103); + + /** Used as references for various `Number` constants. */ + var INFINITY = 1 / 0; + + /** Used to convert symbols to primitives and strings. */ + var symbolProto = Symbol ? Symbol.prototype : undefined, + symbolToString = symbolProto ? symbolProto.toString : undefined; + + /** + * The base implementation of `_.toString` which doesn't convert nullish + * values to empty strings. + * + * @private + * @param {*} value The value to process. + * @returns {string} Returns the string. + */ + function baseToString(value) { + // Exit early for strings to avoid a performance hit in some environments. + if (typeof value == 'string') { + return value; + } + if (isArray(value)) { + // Recursively convert values (susceptible to call stack limits). + return arrayMap(value, baseToString) + ''; + } + if (isSymbol(value)) { + return symbolToString ? symbolToString.call(value) : ''; + } + var result = (value + ''); + return (result == '0' && (1 / value) == -INFINITY) ? '-0' : result; + } + + module.exports = baseToString; + + +/***/ }), + +/***/ 319: +/***/ (function(module, exports) { + + // removed by extract-text-webpack-plugin + +/***/ }), + +/***/ 321: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/* Taken from here: http://stackoverflow.com/a/17907562 */ + function getInternetExplorerVersion(){ + var ua, + re, + rv = -1; + + // check for edge + var isEdge = /(?:\b(MS)?IE\s+|\bTrident\/7\.0;.*\s+rv:|\bEdge\/)(\d+)/.test(navigator.userAgent); + if ( isEdge ) { + rv = parseInt("12"); + return rv; + } + + var isIE11 = /Trident.*rv[ :]*11\./.test(navigator.userAgent); + if ( isIE11 ) { + rv = parseInt("11"); + return rv; + } + if ( navigator.appName === "Microsoft Internet Explorer" ) { + ua = navigator.userAgent; + re = new RegExp("MSIE ([0-9]{1,}[\\.0-9]{0,})"); + if ( re.exec(ua) !== null ) { + rv = parseFloat(RegExp.$1); + } + } else if ( navigator.appName === "Netscape" ) { + ua = navigator.userAgent; + re = new RegExp("Trident/.*rv:([0-9]{1,}[\\.0-9]{0,})"); + if ( re.exec(ua) !== null ) { + rv = parseFloat(RegExp.$1); + } + } + return rv; + } + + function showBrowserWarningIfRequired(){ + var version = getInternetExplorerVersion(); + console.log("Browser Version =" + version); + if ( version > 0 && version <= 11 ) { + d3.select("#browserCheck").classed("hidden", false); + d3.select("#killWarning").classed("hidden", true); + d3.select("#optionsArea").classed("hidden", true); + d3.select("#logo").classed("hidden", true); + } + if ( version == 12 ) { + d3.select("#logo").classed("hidden", false); + d3.select("#browserCheck").classed("hidden", false); + // connect the button; + var pb_kill = d3.select("#killWarning"); + pb_kill.on("click", function (){ + console.log("hide the warning please"); + d3.select("#browserCheck").classed("hidden", true); + d3.select("#logo").style("padding", "10px"); + }); + } + else { + d3.select("#logo").classed("hidden", false); + d3.select("#browserCheck").classed("hidden", true); + } + + } + + module.exports = showBrowserWarningIfRequired; + showBrowserWarningIfRequired(); + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 322: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {String.prototype.replaceAll = function ( search, replacement ){ + var target = this; + return target.split(search).join(replacement); + }; + module.exports = function (){ + var newOntologyCounter = 1; + var app = {}, + graph = webvowl.graph(), + options = graph.graphOptions(), + languageTools = webvowl.util.languageTools(), + GRAPH_SELECTOR = "#graph", + // Modules for the webvowl app + exportMenu = __webpack_require__(323)(graph), + filterMenu = __webpack_require__(325)(graph), + gravityMenu = __webpack_require__(326)(graph), + modeMenu = __webpack_require__(327)(graph), + debugMenu = __webpack_require__(328)(graph), + ontologyMenu = __webpack_require__(329)(graph), + pauseMenu = __webpack_require__(333)(graph), + resetMenu = __webpack_require__(334)(graph), + searchMenu = __webpack_require__(335)(graph), + navigationMenu = __webpack_require__(336)(graph), + zoomSlider = __webpack_require__(337)(graph), + sidebar = __webpack_require__(338)(graph), + leftSidebar = __webpack_require__(339)(graph), + editSidebar = __webpack_require__(340)(graph), + configMenu = __webpack_require__(341)(graph), + loadingModule = __webpack_require__(342)(graph), + warningModule = __webpack_require__(343)(graph), + directInputMod = __webpack_require__(344)(graph), + + + // Graph modules + colorExternalsSwitch = webvowl.modules.colorExternalsSwitch(graph), + compactNotationSwitch = webvowl.modules.compactNotationSwitch(graph), + datatypeFilter = webvowl.modules.datatypeFilter(), + disjointFilter = webvowl.modules.disjointFilter(), + focuser = webvowl.modules.focuser(graph), + emptyLiteralFilter = webvowl.modules.emptyLiteralFilter(), + nodeDegreeFilter = webvowl.modules.nodeDegreeFilter(filterMenu), + nodeScalingSwitch = webvowl.modules.nodeScalingSwitch(graph), + objectPropertyFilter = webvowl.modules.objectPropertyFilter(), + pickAndPin = webvowl.modules.pickAndPin(), + selectionDetailDisplayer = webvowl.modules.selectionDetailsDisplayer(sidebar.updateSelectionInformation), + statistics = webvowl.modules.statistics(), + subclassFilter = webvowl.modules.subclassFilter(), + setOperatorFilter = webvowl.modules.setOperatorFilter(); + + + app.getOptions = function (){ + return webvowl.opts; + }; + app.getGraph = function (){ + return webvowl.gr; + }; + // app.afterInitializationCallback=undefined; + + + var executeFileDrop = false; + var wasMessageToShow = false; + var firstTime = false; + + function addFileDropEvents( selector ){ + var node = d3.select(selector); + + node.node().ondragover = function ( e ){ + e.preventDefault(); + + d3.select("#dragDropContainer").classed("hidden", false); + // get svg size + var w = graph.options().width(); + var h = graph.options().height(); + + // get event position; (using clientX and clientY); + var cx = e.clientX; + var cy = e.clientY; + + if ( firstTime === false ) { + var state = d3.select("#loading-info").classed("hidden"); + wasMessageToShow = !state; + firstTime = true; + d3.select("#loading-info").classed("hidden", true); // hide it so it does not conflict with drop event + var bb=d3.select("#drag_msg").node().getBoundingClientRect(); + var hs = bb.height; + var ws = bb.width; + + var icon_scale=Math.min(hs,ws); + icon_scale/=100; + + d3.select("#drag_icon_group").attr("transform", "translate ( " + 0.25 * ws + " " + 0.25 * hs + ")"); + d3.select("#drag_icon").attr("transform","matrix ("+icon_scale+",0,0,"+icon_scale+",0,0)"); + d3.select("#drag_icon_drop").attr("transform","matrix ("+icon_scale+",0,0,"+icon_scale+",0,0)"); + } + + + if ( (cx > 0.25 * w && cx < 0.75 * w) && (cy > 0.25 * h && cy < 0.75 * h) ) { + + d3.select("#drag_msg_text").node().innerHTML = "Drop it here."; + d3.select("#drag_msg").style("background-color", "#67bc0f"); + d3.select("#drag_msg").style("color", "#000000"); + executeFileDrop = true; + // d3.select("#drag_svg").transition() + // .duration(100) + // // .attr("-webkit-transform", "rotate(90)") + // // .attr("-moz-transform", "rotate(90)") + // // .attr("-o-transform", "rotate(90)") + // .attr("transform", "rotate(90)"); + + d3.select("#drag_icon").classed("hidden",true); + d3.select("#drag_icon_drop").classed("hidden",false); + + + } else { + d3.select("#drag_msg_text").node().innerHTML = "Drag ontology file here."; + d3.select("#drag_msg").style("background-color", "#fefefe"); + d3.select("#drag_msg").style("color", "#000000"); + executeFileDrop = false; + + d3.select("#drag_icon").classed("hidden",false); + d3.select("#drag_icon_drop").classed("hidden",true); + + + // d3.select("#drag_svg").transition() + // .duration(100) + // // .attr("-webkit-transform", "rotate(0)") + // // .attr("-moz-transform", "rotate(0)") + // // .attr("-o-transform", "rotate(0)") + // .attr("transform", "rotate(0)"); + // + } + + }; + node.node().ondrop = function ( ev ){ + ev.preventDefault(); + firstTime = false; + if ( executeFileDrop ) { + if ( ev.dataTransfer.items ) { + if ( ev.dataTransfer.items.length === 1 ) { + if ( ev.dataTransfer.items[0].kind === 'file' ) { + var file = ev.dataTransfer.items[0].getAsFile(); + graph.options().loadingModule().fromFileDrop(file.name, file); + } + } + else { + // >> WARNING not multiple file uploaded; + graph.options().warningModule().showMultiFileUploadWarning(); + } + } + } + d3.select("#dragDropContainer").classed("hidden", true); + }; + + node.node().ondragleave = function ( e ){ + var w = graph.options().width(); + var h = graph.options().height(); + + // get event position; (using clientX and clientY); + var cx = e.clientX; + var cy = e.clientY; + + var hidden = false; + firstTime = false; + + if ( cx < 0.1 * w || cx > 0.9 * w ) hidden = true; + if ( cy < 0.1 * h || cy > 0.9 * h ) hidden = true; + d3.select("#dragDropContainer").classed("hidden", hidden); + + d3.select("#loading-info").classed("hidden", !wasMessageToShow); // show it again + // check if it should be visible + var should_show=graph.options().loadingModule().getMessageVisibilityStatus(); + if (should_show===false){ + d3.select("#loading-info").classed("hidden", true); // hide it + } + }; + + } + + + app.initialize = function (){ + addFileDropEvents(GRAPH_SELECTOR); + + window.requestAnimationFrame = window.requestAnimationFrame || window.mozRequestAnimationFrame || window.webkitRequestAnimationFrame || window.msRequestAnimationFrame || function ( f ){ + return setTimeout(f, 1000 / 60); + }; // simulate calling code 60 + window.cancelAnimationFrame = window.cancelAnimationFrame || window.mozCancelAnimationFrame || function ( requestID ){ + clearTimeout(requestID); + }; //fall back + + options.graphContainerSelector(GRAPH_SELECTOR); + options.selectionModules().push(focuser); + options.selectionModules().push(selectionDetailDisplayer); + options.selectionModules().push(pickAndPin); + + options.filterModules().push(emptyLiteralFilter); + options.filterModules().push(statistics); + + options.filterModules().push(nodeDegreeFilter); + options.filterModules().push(datatypeFilter); + options.filterModules().push(objectPropertyFilter); + options.filterModules().push(subclassFilter); + options.filterModules().push(disjointFilter); + options.filterModules().push(setOperatorFilter); + options.filterModules().push(nodeScalingSwitch); + options.filterModules().push(compactNotationSwitch); + options.filterModules().push(colorExternalsSwitch); + + d3.select(window).on("resize", adjustSize); + + exportMenu.setup(); + gravityMenu.setup(); + filterMenu.setup(datatypeFilter, objectPropertyFilter, subclassFilter, disjointFilter, setOperatorFilter, nodeDegreeFilter); + modeMenu.setup(pickAndPin, nodeScalingSwitch, compactNotationSwitch, colorExternalsSwitch); + pauseMenu.setup(); + sidebar.setup(); + loadingModule.setup(); + leftSidebar.setup(); + editSidebar.setup(); + debugMenu.setup(); + var agentVersion = getInternetExplorerVersion(); + if ( agentVersion > 0 && agentVersion <= 11 ) { + console.log("Agent version " + agentVersion); + console.log("This agent is not supported"); + d3.select("#browserCheck").classed("hidden", false); + d3.select("#killWarning").classed("hidden", true); + d3.select("#optionsArea").classed("hidden", true); + d3.select("#logo").classed("hidden", true); + } else { + d3.select("#logo").classed("hidden", false); + if ( agentVersion === 12 ) { + // allow Mircosoft Edge Browser but with warning + d3.select("#browserCheck").classed("hidden", false); + d3.select("#killWarning").classed("hidden", false); + } else { + d3.select("#browserCheck").classed("hidden", true); + } + + resetMenu.setup([gravityMenu, filterMenu, modeMenu, focuser, selectionDetailDisplayer, pauseMenu]); + searchMenu.setup(); + navigationMenu.setup(); + zoomSlider.setup(); + + // give the options the pointer to the some menus for import and export + options.literalFilter(emptyLiteralFilter); + options.nodeDegreeFilter(nodeDegreeFilter); + options.loadingModule(loadingModule); + options.filterMenu(filterMenu); + options.modeMenu(modeMenu); + options.gravityMenu(gravityMenu); + options.pausedMenu(pauseMenu); + options.pickAndPinModule(pickAndPin); + options.resetMenu(resetMenu); + options.searchMenu(searchMenu); + options.ontologyMenu(ontologyMenu); + options.navigationMenu(navigationMenu); + options.sidebar(sidebar); + options.leftSidebar(leftSidebar); + options.editSidebar(editSidebar); + options.exportMenu(exportMenu); + options.graphObject(graph); + options.zoomSlider(zoomSlider); + options.warningModule(warningModule); + options.directInputModule(directInputMod); + options.datatypeFilter(datatypeFilter); + options.objectPropertyFilter(objectPropertyFilter); + options.subclassFilter(subclassFilter); + options.setOperatorFilter(setOperatorFilter); + options.disjointPropertyFilter(disjointFilter); + options.focuserModule(focuser); + options.colorExternalsModule(colorExternalsSwitch); + options.compactNotationModule(compactNotationSwitch); + + ontologyMenu.setup(loadOntologyFromText); + configMenu.setup(); + + leftSidebar.showSidebar(0); + leftSidebar.hideCollapseButton(true); + + + graph.start(); + + var modeOp = d3.select("#modeOfOperationString"); + modeOp.style("font-size", "0.6em"); + modeOp.style("font-style", "italic"); + + adjustSize(); + var defZoom; + var w = graph.options().width(); + var h = graph.options().height(); + defZoom = Math.min(w, h) / 1000; + + var hideDebugOptions = true; + if ( hideDebugOptions === false ) { + graph.setForceTickFunctionWithFPS(); + } + + graph.setDefaultZoom(defZoom); + d3.selectAll(".debugOption").classed("hidden", hideDebugOptions); + + // prevent backspace reloading event + var htmlBody = d3.select("body"); + d3.select(document).on("keydown", function ( e ){ + if ( d3.event.keyCode === 8 && d3.event.target === htmlBody.node() ) { + // we could add here an alert + d3.event.preventDefault(); + } + // using ctrl+Shift+d as debug option + if ( d3.event.ctrlKey && d3.event.shiftKey && d3.event.keyCode === 68 ) { + graph.options().executeHiddenDebugFeatuers(); + d3.event.preventDefault(); + } + }); + if ( d3.select("#maxLabelWidthSliderOption") ) { + var setValue = !graph.options().dynamicLabelWidth(); + d3.select("#maxLabelWidthSlider").node().disabled = setValue; + d3.select("#maxLabelWidthvalueLabel").classed("disabledLabelForSlider", setValue); + d3.select("#maxLabelWidthDescriptionLabel").classed("disabledLabelForSlider", setValue); + } + + d3.select("#blockGraphInteractions").style("position", "absolute") + .style("top", "0") + .style("background-color", "#bdbdbd") + .style("opacity", "0.5") + .style("pointer-events", "auto") + .style("width", graph.options().width() + "px") + .style("height", graph.options().height() + "px") + .on("click", function (){ + d3.event.preventDefault(); + d3.event.stopPropagation(); + }) + .on("dblclick", function (){ + d3.event.preventDefault(); + d3.event.stopPropagation(); + }); + + d3.select("#direct-text-input").on("click", function (){ + directInputMod.setDirectInputMode(); + }); + d3.select("#blockGraphInteractions").node().draggable = false; + options.prefixModule(webvowl.util.prefixTools(graph)); + adjustSize(); + sidebar.updateOntologyInformation(undefined, statistics); + loadingModule.parseUrlAndLoadOntology(); // loads automatically the ontology provided by the parameters + options.debugMenu(debugMenu); + debugMenu.updateSettings(); + + // connect the reloadCachedVersionButton + d3.select("#reloadSvgIcon").on("click", function (){ + if ( d3.select("#reloadSvgIcon").node().disabled === true ) { + graph.options().ontologyMenu().clearCachedVersion(); + return; + } + d3.select("#reloadCachedOntology").classed("hidden", true); + graph.options().ontologyMenu().reloadCachedOntology(); + + }); + // add the initialized objects + webvowl.opts = options; + webvowl.gr = graph; + + } + }; + + + function loadOntologyFromText( jsonText, filename, alternativeFilename ){ + d3.select("#reloadCachedOntology").classed("hidden", true); + pauseMenu.reset(); + graph.options().navigationMenu().hideAllMenus(); + + if ( (jsonText === undefined && filename === undefined) || (jsonText.length === 0) ) { + loadingModule.notValidJsonFile(); + return; + } + graph.editorMode(); // updates the checkbox + var data; + if ( jsonText ) { + // validate JSON FILE + var validJSON; + try { + data = JSON.parse(jsonText); + validJSON = true; + } catch ( e ) { + validJSON = false; + } + if ( validJSON === false ) { + // the server output is not a valid json file + loadingModule.notValidJsonFile(); + return; + } + + if ( !filename ) { + // First look if an ontology title exists, otherwise take the alternative filename + var ontologyNames = data.header ? data.header.title : undefined; + var ontologyName = languageTools.textInLanguage(ontologyNames); + + if ( ontologyName ) { + filename = ontologyName; + } else { + filename = alternativeFilename; + } + } + } + + + // check if we have graph data + var classCount = 0; + if ( data.class !== undefined ) { + classCount = data.class.length; + } + + var loadEmptyOntologyForEditing = false; + if ( location.hash.indexOf("#new_ontology") !== -1 ) { + loadEmptyOntologyForEditing = true; + newOntologyCounter++; + d3.select("#empty").node().href = "#opts=editorMode=true;#new_ontology" + newOntologyCounter; + } + if ( classCount === 0 && graph.editorMode() === false && loadEmptyOntologyForEditing === false ) { + // generate message for the user; + loadingModule.emptyGraphContentError(); + } else { + loadingModule.validJsonFile(); + ontologyMenu.setCachedOntology(filename, jsonText); + exportMenu.setJsonText(jsonText); + options.data(data); + graph.options().loadingModule().setPercentMode(); + if ( loadEmptyOntologyForEditing === true ) { + graph.editorMode(true); + + } + graph.load(); + sidebar.updateOntologyInformation(data, statistics); + exportMenu.setFilename(filename); + graph.updateZoomSliderValueFromOutside(); + adjustSize(); + + var flagOfCheckBox = d3.select("#editorModeModuleCheckbox").node().checked; + graph.editorMode(flagOfCheckBox);// update gui + + } + } + + function adjustSize(){ + var graphContainer = d3.select(GRAPH_SELECTOR), + svg = graphContainer.select("svg"), + height = window.innerHeight - 40, + width = window.innerWidth - (window.innerWidth * 0.22); + + if ( sidebar.getSidebarVisibility() === "0" ) { + height = window.innerHeight - 40; + width = window.innerWidth; + } + + directInputMod.updateLayout(); + d3.select("#blockGraphInteractions").style("width", window.innerWidth + "px"); + d3.select("#blockGraphInteractions").style("height", window.innerHeight + "px"); + + d3.select("#WarningErrorMessagesContainer").style("width", width + "px"); + d3.select("#WarningErrorMessagesContainer").style("height", height + "px"); + + d3.select("#WarningErrorMessages").style("max-height", (height - 12) + "px"); + + graphContainer.style("height", height + "px"); + svg.attr("width", width) + .attr("height", height); + + options.width(width) + .height(height); + + graph.updateStyle(); + + if ( isTouchDevice() === true ) { + if ( graph.isEditorMode() === true ) + d3.select("#modeOfOperationString").node().innerHTML = "touch able device detected"; + graph.setTouchDevice(true); + + } else { + if ( graph.isEditorMode() === true ) + d3.select("#modeOfOperationString").node().innerHTML = "point & click device detected"; + graph.setTouchDevice(false); + } + + d3.select("#loadingInfo-container").style("height", 0.5 * (height - 80) + "px"); + loadingModule.checkForScreenSize(); + + adjustSliderSize(); + // update also the padding options of loading and the logo positions; + var warningDiv = d3.select("#browserCheck"); + if ( warningDiv.classed("hidden") === false ) { + var offset = 10 + warningDiv.node().getBoundingClientRect().height; + d3.select("#logo").style("padding", offset + "px 10px"); + } else { + // remove the dynamic padding from the logo element; + d3.select("#logo").style("padding", "10px"); + } + + // scrollbar tests; + var element = d3.select("#menuElementContainer").node(); + var maxScrollLeft = element.scrollWidth - element.clientWidth; + var leftButton = d3.select("#scrollLeftButton"); + var rightButton = d3.select("#scrollRightButton"); + if ( maxScrollLeft > 0 ) { + // show both and then check how far is bar; + rightButton.classed("hidden", false); + leftButton.classed("hidden", false); + navigationMenu.updateScrollButtonVisibility(); + } else { + // hide both; + rightButton.classed("hidden", true); + leftButton.classed("hidden", true); + } + + // adjust height of the leftSidebar element; + editSidebar.updateElementWidth(); + + + var hs = d3.select("#drag_msg").node().getBoundingClientRect().height; + var ws = d3.select("#drag_msg").node().getBoundingClientRect().width; + d3.select("#drag_icon_group").attr("transform", "translate ( " + 0.25 * ws + " " + 0.25 * hs + ")"); + + } + + function adjustSliderSize(){ + // TODO: refactor and put this into the slider it self + var height = window.innerHeight - 40; + var fullHeight = height; + var zoomOutPos = height - 30; + var sliderHeight = 150; + + // assuming DOM elements are generated in the index.html + // todo: refactor for independent usage of graph and app + if ( fullHeight < 150 ) { + // hide the slider button; + d3.select("#zoomSliderParagraph").classed("hidden", true); + d3.select("#zoomOutButton").classed("hidden", true); + d3.select("#zoomInButton").classed("hidden", true); + d3.select("#centerGraphButton").classed("hidden", true); + return; + } + d3.select("#zoomSliderParagraph").classed("hidden", false); + d3.select("#zoomOutButton").classed("hidden", false); + d3.select("#zoomInButton").classed("hidden", false); + d3.select("#centerGraphButton").classed("hidden", false); + + var zoomInPos = zoomOutPos - 20; + var centerPos = zoomInPos - 20; + if ( fullHeight < 280 ) { + // hide the slider button; + d3.select("#zoomSliderParagraph").classed("hidden", true);//var sliderPos=zoomOutPos-sliderHeight; + d3.select("#zoomOutButton").style("top", zoomOutPos + "px"); + d3.select("#zoomInButton").style("top", zoomInPos + "px"); + d3.select("#centerGraphButton").style("top", centerPos + "px"); + return; + } + + var sliderPos = zoomOutPos - sliderHeight; + zoomInPos = sliderPos - 20; + centerPos = zoomInPos - 20; + d3.select("#zoomSliderParagraph").classed("hidden", false); + d3.select("#zoomOutButton").style("top", zoomOutPos + "px"); + d3.select("#zoomInButton").style("top", zoomInPos + "px"); + d3.select("#centerGraphButton").style("top", centerPos + "px"); + d3.select("#zoomSliderParagraph").style("top", sliderPos + "px"); + } + + function isTouchDevice(){ + try { + document.createEvent("TouchEvent"); + return true; + } catch ( e ) { + return false; + } + } + + + function getInternetExplorerVersion(){ + var ua, + re, + rv = -1; + + // check for edge + var isEdge = /(?:\b(MS)?IE\s+|\bTrident\/7\.0;.*\s+rv:|\bEdge\/)(\d+)/.test(navigator.userAgent); + if ( isEdge ) { + rv = parseInt("12"); + return rv; + } + + var isIE11 = /Trident.*rv[ :]*11\./.test(navigator.userAgent); + if ( isIE11 ) { + rv = parseInt("11"); + return rv; + } + if ( navigator.appName === "Microsoft Internet Explorer" ) { + ua = navigator.userAgent; + re = new RegExp("MSIE ([0-9]{1,}[\\.0-9]{0,})"); + if ( re.exec(ua) !== null ) { + rv = parseFloat(RegExp.$1); + } + } else if ( navigator.appName === "Netscape" ) { + ua = navigator.userAgent; + re = new RegExp("Trident/.*rv:([0-9]{1,}[\\.0-9]{0,})"); + if ( re.exec(ua) !== null ) { + rv = parseFloat(RegExp.$1); + } + } + return rv; + } + + return app; + } + ; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 323: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for the export button. + * @returns {{}} + */ + module.exports = function ( graph ){ + + var exportMenu = {}, + exportSvgButton, + exportFilename, + exportJsonButton, + exportTurtleButton, + exportTexButton, + copyButton, + exportableJsonText; + + var exportTTLModule = __webpack_require__(324)(graph); + + + String.prototype.replaceAll = function ( search, replacement ){ + var target = this; + return target.split(search).join(replacement); + }; + + + /** + * Adds the export button to the website. + */ + exportMenu.setup = function (){ + exportSvgButton = d3.select("#exportSvg") + .on("click", exportSvg); + exportJsonButton = d3.select("#exportJson") + .on("click", exportJson); + + copyButton = d3.select("#copyBt") + .on("click", copyUrl); + + exportTexButton = d3.select("#exportTex") + .on("click", exportTex); + + exportTurtleButton = d3.select("#exportTurtle") + .on("click", exportTurtle); + + var menuEntry = d3.select("#m_export"); + menuEntry.on("mouseover", function (){ + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + exportMenu.exportAsUrl(); + }); + }; + function exportTurtle(){ + var success = exportTTLModule.requestExport(); + var result = exportTTLModule.resultingTTL_Content(); + var ontoTitle = "NewOntology"; + console.log("Exporter was successful: " + success); + if ( success ) { + // console.log("The result is : " + result); + // var ontoTitle=graph.options().getGeneralMetaObjectProperty('title'); + // if (ontoTitle===undefined || ontoTitle.length===0) + // ontoTitle="NewOntology"; + // else{ + // // language object -.- + // ontoTitle.replace(" ","_") + // } + + // TODO: show TEXT in warning module? + + + // // write the data + var dataURI = "data:text/json;charset=utf-8," + encodeURIComponent(result); + + exportTurtleButton.attr("href", dataURI) + .attr("download", ontoTitle + ".ttl"); + + // okay restore old href? + // exportTurtleButton.attr("href", oldHref); + } else { + console.log("ShowWarning!"); + graph.options().warningModule().showExporterWarning(); + console.log("Stay on the page! " + window.location.href); + exportTurtleButton.attr("href", window.location.href); + d3.event.preventDefault(); // prevent the href to be called ( reloads the page otherwise ) + } + } + + exportMenu.setFilename = function ( filename ){ + exportFilename = filename || "export"; + }; + + exportMenu.setJsonText = function ( jsonText ){ + exportableJsonText = jsonText; + }; + + function copyUrl(){ + d3.select("#exportedUrl").node().focus(); + d3.select("#exportedUrl").node().select(); + document.execCommand("copy"); + graph.options().navigationMenu().hideAllMenus(); + d3.event.preventDefault(); // prevent the href to be called ( reloads the page otherwise ) + } + + function prepareOptionString( defOpts, currOpts ){ + var setOptions = 0; + var optsString = "opts="; + + for ( var name in defOpts ) { + // define key and value ; + if ( defOpts.hasOwnProperty(name) ) {// for travis warning + var def_value = defOpts[name]; + var cur_value = currOpts[name]; + if ( def_value !== cur_value ) { + optsString += name + "=" + cur_value + ";"; + setOptions++; + } + } + } + optsString += ""; + if ( setOptions === 0 ) { + return ""; + } + return optsString; + } + + exportMenu.exportAsUrl = function (){ + var currObj = {}; + currObj.sidebar = graph.options().sidebar().getSidebarVisibility(); + + // identify default value given by ontology; + var defOntValue = graph.options().filterMenu().getDefaultDegreeValue(); + var currentValue = graph.options().filterMenu().getDegreeSliderValue(); + if ( parseInt(defOntValue) === parseInt(currentValue) ) { + currObj.doc = -1; + } else { + currObj.doc = currentValue; + } + + currObj.cd = graph.options().classDistance(); + currObj.dd = graph.options().datatypeDistance(); + if ( graph.editorMode() === true ) { + currObj.editorMode = "true"; + } else { + currObj.editorMode = "false"; + } + currObj.filter_datatypes = String(graph.options().filterMenu().getCheckBoxValue("datatypeFilterCheckbox")); + currObj.filter_sco = String(graph.options().filterMenu().getCheckBoxValue("subclassFilterCheckbox")); + currObj.filter_disjoint = String(graph.options().filterMenu().getCheckBoxValue("disjointFilterCheckbox")); + currObj.filter_setOperator = String(graph.options().filterMenu().getCheckBoxValue("setoperatorFilterCheckbox")); + currObj.filter_objectProperties = String(graph.options().filterMenu().getCheckBoxValue("objectPropertyFilterCheckbox")); + currObj.mode_dynamic = String(graph.options().dynamicLabelWidth()); + currObj.mode_scaling = String(graph.options().modeMenu().getCheckBoxValue("nodescalingModuleCheckbox")); + currObj.mode_compact = String(graph.options().modeMenu().getCheckBoxValue("compactnotationModuleCheckbox")); + currObj.mode_colorExt = String(graph.options().modeMenu().getCheckBoxValue("colorexternalsModuleCheckbox")); + currObj.mode_multiColor = String(graph.options().modeMenu().colorModeState()); + currObj.mode_pnp = String(graph.options().modeMenu().getCheckBoxValue("pickandpinModuleCheckbox")); + currObj.debugFeatures = String(!graph.options().getHideDebugFeatures()); + currObj.rect = 0; + + var defObj = graph.options().initialConfig(); + var optsString = prepareOptionString(defObj, currObj); + var urlString = String(location); + var htmlElement; + // when everything is default then there is nothing to write + if ( optsString.length === 0 ) { + // building up parameter list; + + // remove the all options form location + var hashCode = location.hash; + urlString = urlString.split(hashCode)[0]; + + var lPos = hashCode.lastIndexOf("#"); + if ( lPos === -1 ) { + htmlElement = d3.select("#exportedUrl").node(); + htmlElement.value = String(location); + htmlElement.title = String(location); + return; // nothing to change in the location String + } + var newURL = hashCode.slice(lPos, hashCode.length); + htmlElement = d3.select("#exportedUrl").node(); + htmlElement.value = urlString + newURL; + htmlElement.title = urlString + newURL; + return; + } + + // generate the options string; + var numParameters = (urlString.match(/#/g) || []).length; + var newUrlString; + if ( numParameters === undefined || numParameters === 0 ) { + newUrlString = urlString + "#" + optsString; + } + if ( numParameters > 0 ) { + var tokens = urlString.split("#"); + var i; + if ( tokens[1].indexOf("opts=") >= 0 ) { + tokens[1] = optsString; + newUrlString = tokens[0]; + } else { + newUrlString = tokens[0] + "#"; + newUrlString += optsString; + } + // append parameters + for ( i = 1; i < tokens.length; i++ ) { + if ( tokens[i].length > 0 ) { + newUrlString += "#" + tokens[i]; + } + } + } + // building up parameter list; + htmlElement = d3.select("#exportedUrl").node(); + htmlElement.value = newUrlString; + htmlElement.title = newUrlString; + + }; + + function exportSvg(){ + graph.options().navigationMenu().hideAllMenus(); + // Get the d3js SVG element + var graphSvg = d3.select(graph.options().graphContainerSelector()).select("svg"), + graphSvgCode, + escapedGraphSvgCode, + dataURI; + + // inline the styles, so that the exported svg code contains the css rules + inlineVowlStyles(); + hideNonExportableElements(); + + graphSvgCode = graphSvg.attr("version", 1.1) + .attr("xmlns", "http://www.w3.org/2000/svg") + .node().parentNode.innerHTML; + + // Insert the reference to VOWL + graphSvgCode = "\n" + graphSvgCode; + + escapedGraphSvgCode = escapeUnicodeCharacters(graphSvgCode); + //btoa(); Creates a base-64 encoded ASCII string from a "string" of binary data. + dataURI = "data:image/svg+xml;base64," + btoa(escapedGraphSvgCode); + + + exportSvgButton.attr("href", dataURI) + .attr("download", exportFilename + ".svg"); + + // remove graphic styles for interaction to go back to normal + removeVowlInlineStyles(); + showNonExportableElements(); + graph.lazyRefresh(); + } + + function escapeUnicodeCharacters( text ){ + var textSnippets = [], + i, textLength = text.length, + character, + charCode; + + for ( i = 0; i < textLength; i++ ) { + character = text.charAt(i); + charCode = character.charCodeAt(0); + + if ( charCode < 128 ) { + textSnippets.push(character); + } else { + textSnippets.push("&#" + charCode + ";"); + } + } + + return textSnippets.join(""); + } + + function inlineVowlStyles(){ + setStyleSensitively(".text", [{ name: "font-family", value: "Helvetica, Arial, sans-serif" }, { + name: "font-size", + value: "12px" + }]); + setStyleSensitively(".subtext", [{ name: "font-size", value: "9px" }]); + setStyleSensitively(".text.instance-count", [{ name: "fill", value: "#666" }]); + setStyleSensitively(".external + text .instance-count", [{ name: "fill", value: "#aaa" }]); + setStyleSensitively(".cardinality", [{ name: "font-size", value: "10px" }]); + setStyleSensitively(".text, .embedded", [{ name: "pointer-events", value: "none" }]); + setStyleSensitively(".class, .object, .disjoint, .objectproperty, .disjointwith, .equivalentproperty, .transitiveproperty, .functionalproperty, .inversefunctionalproperty, .symmetricproperty, .allvaluesfromproperty, .somevaluesfromproperty", [{ + name: "fill", + value: "#acf" + }]); + setStyleSensitively(".label .datatype, .datatypeproperty", [{ name: "fill", value: "#9c6" }]); + setStyleSensitively(".rdf, .rdfproperty", [{ name: "fill", value: "#c9c" }]); + setStyleSensitively(".literal, .node .datatype", [{ name: "fill", value: "#fc3" }]); + setStyleSensitively(".deprecated, .deprecatedproperty", [{ name: "fill", value: "#ccc" }]); + setStyleSensitively(".external, .externalproperty", [{ name: "fill", value: "#36c" }]); + setStyleSensitively("path, .nofill", [{ name: "fill", value: "none" }]); + setStyleSensitively("marker path", [{ name: "fill", value: "#000" }]); + setStyleSensitively(".class, path, line, .fineline", [{ name: "stroke", value: "#000" }]); + setStyleSensitively(".white, .subclass, .subclassproperty, .external + text", [{ name: "fill", value: "#fff" }]); + setStyleSensitively(".class.hovered, .property.hovered, .cardinality.hovered, .cardinality.focused, circle.pin, .filled.hovered, .filled.focused", [{ + name: "fill", + value: "#f00" + }, { name: "cursor", value: "pointer" }]); + setStyleSensitively(".focused, path.hovered", [{ name: "stroke", value: "#f00" }]); + setStyleSensitively(".indirect-highlighting, .feature:hover", [{ name: "fill", value: "#f90" }]); + setStyleSensitively(".values-from", [{ name: "stroke", value: "#69c" }]); + setStyleSensitively(".symbol, .values-from.filled", [{ name: "fill", value: "#69c" }]); + setStyleSensitively(".class, path, line", [{ name: "stroke-width", value: "2" }]); + setStyleSensitively(".fineline", [{ name: "stroke-width", value: "1" }]); + setStyleSensitively(".dashed, .anonymous", [{ name: "stroke-dasharray", value: "8" }]); + setStyleSensitively(".dotted", [{ name: "stroke-dasharray", value: "3" }]); + setStyleSensitively("rect.focused, circle.focused", [{ name: "stroke-width", value: "4px" }]); + setStyleSensitively(".nostroke", [{ name: "stroke", value: "none" }]); + setStyleSensitively("marker path", [{ name: "stroke-dasharray", value: "100" }]); + } + + function setStyleSensitively( selector, styles ){ + var elements = d3.selectAll(selector); + if ( elements.empty() ) { + return; + } + + styles.forEach(function ( style ){ + elements.each(function (){ + var element = d3.select(this); + if ( !shouldntChangeInlineCss(element, style.name) ) { + element.style(style.name, style.value); + } + }); + }); + } + + function shouldntChangeInlineCss( element, style ){ + return style === "fill" && hasBackgroundColorSet(element); + } + + function hasBackgroundColorSet( element ){ + var data = element.datum(); + if ( data === undefined ) { + return false; + } + return data.backgroundColor && !!data.backgroundColor(); + } + + /** + * For example the pin of the pick&pin module should be invisible in the exported graphic. + */ + function hideNonExportableElements(){ + d3.selectAll(".hidden-in-export").style("display", "none"); + } + + function removeVowlInlineStyles(){ + d3.selectAll(".text, .subtext, .text.instance-count, .external + text .instance-count, .cardinality, .text, .embedded, .class, .object, .disjoint, .objectproperty, .disjointwith, .equivalentproperty, .transitiveproperty, .functionalproperty, .inversefunctionalproperty, .symmetricproperty, .allvaluesfromproperty, .somevaluesfromproperty, .label .datatype, .datatypeproperty, .rdf, .rdfproperty, .literal, .node .datatype, .deprecated, .deprecatedproperty, .external, .externalproperty, path, .nofill, .symbol, .values-from.filled, marker path, .class, path, line, .fineline, .white, .subclass, .subclassproperty, .external + text, .class.hovered, .property.hovered, .cardinality.hovered, .cardinality.focused, circle.pin, .filled.hovered, .filled.focused, .focused, path.hovered, .indirect-highlighting, .feature:hover, .values-from, .class, path, line, .fineline, .dashed, .anonymous, .dotted, rect.focused, circle.focused, .nostroke, marker path") + .each(function (){ + var element = d3.select(this); + + var inlineStyles = element.node().style; + for ( var styleName in inlineStyles ) { + if ( inlineStyles.hasOwnProperty(styleName) ) { + if ( shouldntChangeInlineCss(element, styleName) ) { + continue; + } + element.style(styleName, null); + } + } + + if ( element.datum && element.datum() !== undefined && element.datum().type ) { + if ( element.datum().type() === "rdfs:subClassOf" ) { + element.style("fill", null); + } + } + }); + + // repair svg icons in the menu; + var scrollContainer = d3.select("#menuElementContainer").node(); + var controlElements = scrollContainer.children; + var numEntries = controlElements.length; + + for ( var i = 0; i < numEntries; i++ ) { + var currentMenu = controlElements[i].id; + d3.select("#" + currentMenu).select("path").style("stroke-width", "0"); + d3.select("#" + currentMenu).select("path").style("fill", "#fff"); + } + + d3.select("#magnifyingGlass").style("stroke-width", "0"); + d3.select("#magnifyingGlass").style("fill", "#666"); + + } + + function showNonExportableElements(){ + d3.selectAll(".hidden-in-export").style("display", null); + } + + exportMenu.createJSON_exportObject = function (){ + var i, j, k; // an index variable for the for-loops + + /** get data for exporter **/ + if (!graph.options().data()) {return {};} // return an empty json object + // extract onotology information; + var unfilteredData = graph.getUnfilteredData(); + var ontologyComment = graph.options().data()._comment; + var metaObj = graph.options().getGeneralMetaObject(); + var header = graph.options().data().header; + + if ( metaObj.iri && metaObj.iri !== header.iri ) { + header.iri = metaObj.iri; + } + if ( metaObj.title && metaObj.title !== header.title ) { + header.title = metaObj.title; + } + if ( metaObj.version && metaObj.version !== header.version ) { + header.version = metaObj.version; + } + if ( metaObj.author && metaObj.author !== header.author ) { + header.author = metaObj.author; + } + if ( metaObj.description && metaObj.description !== header.description ) { + header.description = metaObj.description; + } + + + var exportText = {}; + exportText._comment = ontologyComment; + exportText.header = header; + exportText.namespace = graph.options().data().namespace; + if ( exportText.namespace === undefined ) { + exportText.namespace = []; // just an empty namespace array + } + // we do have now the unfiltered data which needs to be transfered to class/classAttribute and property/propertyAttribute + + + // var classAttributeString='classAttribute:[ \n'; + var nodes = unfilteredData.nodes; + var nLen = nodes.length; // hope for compiler unroll + var classObjects = []; + var classAttributeObjects = []; + for ( i = 0; i < nLen; i++ ) { + var classObj = {}; + var classAttr = {}; + classObj.id = nodes[i].id(); + classObj.type = nodes[i].type(); + classObjects.push(classObj); + + // define the attributes object + classAttr.id = nodes[i].id(); + classAttr.iri = nodes[i].iri(); + classAttr.baseIri = nodes[i].baseIri(); + classAttr.label = nodes[i].label(); + + if ( nodes[i].attributes().length > 0 ) { + classAttr.attributes = nodes[i].attributes(); + } + if ( nodes[i].comment() ) { + classAttr.comment = nodes[i].comment(); + } + if ( nodes[i].annotations() ) { + classAttr.annotations = nodes[i].annotations(); + } + if ( nodes[i].description() ) { + classAttr.description = nodes[i].description(); + } + + + if ( nodes[i].individuals().length > 0 ) { + var classIndividualElements = []; + var nIndividuals = nodes[i].individuals(); + for ( j = 0; j < nIndividuals.length; j++ ) { + var indObj = {}; + indObj.iri = nIndividuals[j].iri(); + indObj.baseIri = nIndividuals[j].baseIri(); + indObj.labels = nIndividuals[j].label(); + if ( nIndividuals[j].annotations() ) { + indObj.annotations = nIndividuals[j].annotations(); + } + if ( nIndividuals[j].description() ) { + indObj.description = nIndividuals[j].description(); + } + if ( nIndividuals[j].comment() ) { + indObj.comment = nIndividuals[j].comment(); + } + classIndividualElements.push(indObj); + } + classAttr.individuals = classIndividualElements; + } + + var equalsForAttributes = undefined; + if ( nodes[i].equivalents().length > 0 ) { + equalsForAttributes = []; + var equals = nodes[i].equivalents(); + for ( j = 0; j < equals.length; j++ ) { + var eqObj = {}; + var eqAttr = {}; + eqObj.id = equals[j].id(); + equalsForAttributes.push(equals[j].id()); + eqObj.type = equals[j].type(); + classObjects.push(eqObj); + + eqAttr.id = equals[j].id(); + eqAttr.iri = equals[j].iri(); + eqAttr.baseIri = equals[j].baseIri(); + eqAttr.label = equals[j].label(); + + if ( equals[j].attributes().length > 0 ) { + eqAttr.attributes = equals[j].attributes(); + } + if ( equals[j].comment() ) { + eqAttr.comment = equals[j].comment(); + } + if ( equals[j].individuals().length > 0 ) { + eqAttr.individuals = equals[j].individuals(); + } + if ( equals[j].annotations() ) { + eqAttr.annotations = equals[j].annotations(); + } + if ( equals[j].description() ) { + eqAttr.description = equals[j].description(); + } + + if ( equals[j].individuals().length > 0 ) { + var e_classIndividualElements = []; + var e_nIndividuals = equals[i].individuals(); + for ( k = 0; k < e_nIndividuals.length; k++ ) { + var e_indObj = {}; + e_indObj.iri = e_nIndividuals[k].iri(); + e_indObj.baseIri = e_nIndividuals[k].baseIri(); + e_indObj.labels = e_nIndividuals[k].label(); + + if ( e_nIndividuals[k].annotations() ) { + e_indObj.annotations = e_nIndividuals[k].annotations(); + } + if ( e_nIndividuals[k].description() ) { + e_indObj.description = e_nIndividuals[k].description(); + } + if ( e_nIndividuals[k].comment() ) { + e_indObj.comment = e_nIndividuals[k].comment(); + } + e_classIndividualElements.push(e_indObj); + } + eqAttr.individuals = e_classIndividualElements; + } + + classAttributeObjects.push(eqAttr); + } + } + if ( equalsForAttributes && equalsForAttributes.length > 0 ) { + classAttr.equivalent = equalsForAttributes; + } + + // classAttr.subClasses=nodes[i].subClasses(); // not needed + // classAttr.instances=nodes[i].instances(); + + // + // .complement(element.complement) + // .disjointUnion(element.disjointUnion) + // .description(element.description) + // .equivalents(element.equivalent) + // .intersection(element.intersection) + // .type(element.type) Ignore, because we predefined it + // .union(element.union) + classAttributeObjects.push(classAttr); + } + + /** -- properties -- **/ + var properties = unfilteredData.properties; + var pLen = properties.length; // hope for compiler unroll + var propertyObjects = []; + var propertyAttributeObjects = []; + + for ( i = 0; i < pLen; i++ ) { + var pObj = {}; + var pAttr = {}; + pObj.id = properties[i].id(); + pObj.type = properties[i].type(); + propertyObjects.push(pObj); + + // // define the attributes object + pAttr.id = properties[i].id(); + pAttr.iri = properties[i].iri(); + pAttr.baseIri = properties[i].baseIri(); + pAttr.label = properties[i].label(); + + if ( properties[i].attributes().length > 0 ) { + pAttr.attributes = properties[i].attributes(); + } + if ( properties[i].comment() ) { + pAttr.comment = properties[i].comment(); + } + + if ( properties[i].annotations() ) { + pAttr.annotations = properties[i].annotations(); + } + if ( properties[i].maxCardinality() ) { + pAttr.maxCardinality = properties[i].maxCardinality(); + } + if ( properties[i].minCardinality() ) { + pAttr.minCardinality = properties[i].minCardinality(); + } + if ( properties[i].cardinality() ) { + pAttr.cardinality = properties[i].cardinality(); + } + if ( properties[i].description() ) { + pAttr.description = properties[i].description(); + } + + pAttr.domain = properties[i].domain().id(); + pAttr.range = properties[i].range().id(); + // sub properties; + if ( properties[i].subproperties() ) { + var subProps = properties[i].subproperties(); + var subPropsIdArray = []; + for ( j = 0; j < subProps.length; j++ ) { + if ( subProps[j].id ) + subPropsIdArray.push(subProps[j].id()); + } + pAttr.subproperty = subPropsIdArray; + } + + // super properties + if ( properties[i].superproperties() ) { + var superProps = properties[i].superproperties(); + var superPropsIdArray = []; + for ( j = 0; j < superProps.length; j++ ) { + if ( superProps[j].id ) + superPropsIdArray.push(superProps[j].id()); + } + pAttr.superproperty = superPropsIdArray; + } + + // check for inverse element + if ( properties[i].inverse() ) { + if ( properties[i].inverse().id ) + pAttr.inverse = properties[i].inverse().id(); + } + propertyAttributeObjects.push(pAttr); + } + + exportText.class = classObjects; + exportText.classAttribute = classAttributeObjects; + exportText.property = propertyObjects; + exportText.propertyAttribute = propertyAttributeObjects; + + + var nodeElements = graph.graphNodeElements(); // get visible nodes + var propElements = graph.graphLabelElements(); // get visible labels + // var jsonObj = JSON.parse(exportableJsonText); // reparse the original input json + + /** modify comment **/ + var comment = exportText._comment; + var additionalString = " [Additional Information added by WebVOWL Exporter Version: " + "1.1.7" + "]"; + // adding new string to comment only if it does not exist + if ( comment.indexOf(additionalString) === -1 ) { + exportText._comment = comment + " [Additional Information added by WebVOWL Exporter Version: " + "1.1.7" + "]"; + } + + var classAttribute = exportText.classAttribute; + var propAttribute = exportText.propertyAttribute; + /** remove previously stored variables **/ + for ( i = 0; i < classAttribute.length; i++ ) { + var classObj_del = classAttribute[i]; + delete classObj_del.pos; + delete classObj_del.pinned; + } + var propertyObj; + for ( i = 0; i < propAttribute.length; i++ ) { + propertyObj = propAttribute[i]; + delete propertyObj.pos; + delete propertyObj.pinned; + } + /** add new variables to jsonObj **/ + // class attribute variables + nodeElements.each(function ( node ){ + var nodeId = node.id(); + for ( i = 0; i < classAttribute.length; i++ ) { + var classObj = classAttribute[i]; + if ( classObj.id === nodeId ) { + // store relative positions + classObj.pos = [parseFloat(node.x.toFixed(2)), parseFloat(node.y.toFixed(2))]; + if ( node.pinned() ) + classObj.pinned = true; + break; + } + } + }); + // property attribute variables + for ( j = 0; j < propElements.length; j++ ) { + var correspondingProp = propElements[j].property(); + for ( i = 0; i < propAttribute.length; i++ ) { + propertyObj = propAttribute[i]; + if ( propertyObj.id === correspondingProp.id() ) { + propertyObj.pos = [parseFloat(propElements[j].x.toFixed(2)), parseFloat(propElements[j].y.toFixed(2))]; + if ( propElements[j].pinned() ) + propertyObj.pinned = true; + break; + } + } + } + /** create the variable for settings and set their values **/ + exportText.settings = {}; + + // Global Settings + var zoom = graph.scaleFactor(); + var paused = graph.paused(); + var translation = [parseFloat(graph.translation()[0].toFixed(2)), parseFloat(graph.translation()[1].toFixed(2))]; + exportText.settings.global = {}; + exportText.settings.global.zoom = zoom.toFixed(2); + exportText.settings.global.translation = translation; + exportText.settings.global.paused = paused; + + // shared variable declaration + var cb_text; + var isEnabled; + var cb_obj; + + // Gravity Settings + var classDistance = graph.options().classDistance(); + var datatypeDistance = graph.options().datatypeDistance(); + exportText.settings.gravity = {}; + exportText.settings.gravity.classDistance = classDistance; + exportText.settings.gravity.datatypeDistance = datatypeDistance; + + // Filter Settings + var fMenu = graph.options().filterMenu(); + var fContainer = fMenu.getCheckBoxContainer(); + var cbCont = []; + for ( i = 0; i < fContainer.length; i++ ) { + cb_text = fContainer[i].checkbox.attr("id"); + isEnabled = fContainer[i].checkbox.property("checked"); + cb_obj = {}; + cb_obj.id = cb_text; + cb_obj.checked = isEnabled; + cbCont.push(cb_obj); + } + var degreeSliderVal = fMenu.getDegreeSliderValue(); + exportText.settings.filter = {}; + exportText.settings.filter.checkBox = cbCont; + exportText.settings.filter.degreeSliderValue = degreeSliderVal; + + // Modes Settings + var mMenu = graph.options().modeMenu(); + var mContainer = mMenu.getCheckBoxContainer(); + var cb_modes = []; + for ( i = 0; i < mContainer.length; i++ ) { + cb_text = mContainer[i].attr("id"); + isEnabled = mContainer[i].property("checked"); + cb_obj = {}; + cb_obj.id = cb_text; + cb_obj.checked = isEnabled; + cb_modes.push(cb_obj); + } + var colorSwitchState = mMenu.colorModeState(); + exportText.settings.modes = {}; + exportText.settings.modes.checkBox = cb_modes; + exportText.settings.modes.colorSwitchState = colorSwitchState; + + var exportObj = {}; + // todo: [ ] find better way for ordering the objects + // hack for ordering of objects, so settings is after metrics + exportObj._comment = exportText._comment; + exportObj.header = exportText.header; + exportObj.namespace = exportText.namespace; + exportObj.metrics = exportText.metrics; + exportObj.settings = exportText.settings; + exportObj.class = exportText.class; + exportObj.classAttribute = exportText.classAttribute; + exportObj.property = exportText.property; + exportObj.propertyAttribute = exportText.propertyAttribute; + + return exportObj; + }; + + function exportJson(){ + graph.options().navigationMenu().hideAllMenus(); + /** check if there is data **/ + if ( !exportableJsonText ) { + alert("No graph data available."); + // Stop the redirection to the path of the href attribute + d3.event.preventDefault(); + return; + } + + var exportObj = exportMenu.createJSON_exportObject(); + + // make a string again; + var exportText = JSON.stringify(exportObj, null, ' '); + // write the data + var dataURI = "data:text/json;charset=utf-8," + encodeURIComponent(exportText); + var jsonExportFileName = exportFilename; + + if ( !jsonExportFileName.endsWith(".json") ) + jsonExportFileName += ".json"; + exportJsonButton.attr("href", dataURI) + .attr("download", jsonExportFileName); + } + + var curveFunction = d3.svg.line() + .x(function ( d ){ + return d.x; + }) + .y(function ( d ){ + return d.y; + }) + .interpolate("cardinal"); + var loopFunction = d3.svg.line() + .x(function ( d ){ + return d.x; + }) + .y(function ( d ){ + return d.y; + }) + .interpolate("cardinal") + .tension(-1); + + function exportTex(){ + var zoom = graph.scaleFactor(); + var grTranslate = graph.translation(); + var bbox = graph.getBoundingBoxForTex(); + var comment = " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n"; + comment += " % Generated with the experimental alpha version of the TeX exporter of WebVOWL (version 1.1.3) %%% \n"; + comment += " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n\n"; + comment += " % The content can be used as import in other TeX documents. \n"; + comment += " % Parent document has to use the following packages \n"; + comment += " % \\usepackage{tikz} \n"; + comment += " % \\usepackage{helvet} \n"; + comment += " % \\usetikzlibrary{decorations.markings,decorations.shapes,decorations,arrows,automata,backgrounds,petri,shapes.geometric} \n"; + comment += " % \\usepackage{xcolor} \n\n"; + comment += " %%%%%%%%%%%%%%% Example Parent Document %%%%%%%%%%%%%%%%%%%%%%%\n"; + comment += " %\\documentclass{article} \n"; + comment += " %\\usepackage{tikz} \n"; + comment += " %\\usepackage{helvet} \n"; + comment += " %\\usetikzlibrary{decorations.markings,decorations.shapes,decorations,arrows,automata,backgrounds,petri,shapes.geometric} \n"; + comment += " %\\usepackage{xcolor} \n\n"; + comment += " %\\begin{document} \n"; + comment += " %\\section{Example} \n"; + comment += " % This is an example. \n"; + comment += " % \\begin{figure} \n"; + comment += " % \\input{} % << tex file name for the graph \n"; + comment += " % \\caption{A generated graph with TKIZ using alpha version of the TeX exporter of WebVOWL (version 1.1.3) } \n"; + comment += " % \\end{figure} \n"; + comment += " %\\end{document} \n"; + comment += " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n\n"; + + + var texString = comment + "\\definecolor{imageBGCOLOR}{HTML}{FFFFFF} \n" + + "\\definecolor{owlClassColor}{HTML}{AACCFF}\n" + + "\\definecolor{owlObjectPropertyColor}{HTML}{AACCFF}\n" + + "\\definecolor{owlExternalClassColor}{HTML}{AACCFF}\n" + + "\\definecolor{owlDatatypePropertyColor}{HTML}{99CC66}\n" + + "\\definecolor{owlDatatypeColor}{HTML}{FFCC33}\n" + + "\\definecolor{owlThingColor}{HTML}{FFFFFF}\n" + + "\\definecolor{valuesFrom}{HTML}{6699CC}\n" + + "\\definecolor{rdfPropertyColor}{HTML}{CC99CC}\n" + + "\\definecolor{unionColor}{HTML}{6699cc}\n" + + "\\begin{center} \n" + + "\\resizebox{\\linewidth}{!}{\n" + + + "\\begin{tikzpicture}[framed]\n" + + "\\clip (" + bbox[0] + "pt , " + bbox[1] + "pt ) rectangle (" + bbox[2] + "pt , " + bbox[3] + "pt);\n" + + "\\tikzstyle{dashed}=[dash pattern=on 4pt off 4pt] \n" + + "\\tikzstyle{dotted}=[dash pattern=on 2pt off 2pt] \n" + + "\\fontfamily{sans-serif}{\\fontsize{12}{12}\\selectfont}\n \n"; + + + texString += "\\tikzset{triangleBlack/.style = {fill=black, draw=black, line width=1pt,scale=0.7,regular polygon, regular polygon sides=3} }\n"; + texString += "\\tikzset{triangleWhite/.style = {fill=white, draw=black, line width=1pt,scale=0.7,regular polygon, regular polygon sides=3} }\n"; + texString += "\\tikzset{triangleBlue/.style = {fill=valuesFrom, draw=valuesFrom, line width=1pt,scale=0.7,regular polygon, regular polygon sides=3} }\n"; + + texString += "\\tikzset{Diamond/.style = {fill=white, draw=black, line width=2pt,scale=1.2,regular polygon, regular polygon sides=4} }\n"; + + + texString += "\\tikzset{Literal/.style={rectangle,align=center,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "black, draw=black, dashed, line width=1pt, fill=owlDatatypeColor, minimum width=80pt,\n" + + "minimum height = 20pt}}\n\n"; + + texString += "\\tikzset{Datatype/.style={rectangle,align=center,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "black, draw=black, line width=1pt, fill=owlDatatypeColor, minimum width=80pt,\n" + + "minimum height = 20pt}}\n\n"; + + + texString += "\\tikzset{owlClass/.style={circle, inner sep=0mm,align=center, \n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "black, draw=black, line width=1pt, fill=owlClassColor, minimum size=101pt}}\n\n"; + + texString += "\\tikzset{anonymousClass/.style={circle, inner sep=0mm,align=center, \n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "black, dashed, draw=black, line width=1pt, fill=owlClassColor, minimum size=101pt}}\n\n"; + + + texString += "\\tikzset{owlThing/.style={circle, inner sep=0mm,align=center,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "black, dashed, draw=black, line width=1pt, fill=owlThingColor, minimum size=62pt}}\n\n"; + + + texString += "\\tikzset{owlObjectProperty/.style={rectangle,align=center,\n" + + "inner sep=0mm,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "fill=owlObjectPropertyColor, minimum width=80pt,\n" + + "minimum height = 25pt}}\n\n"; + + texString += "\\tikzset{rdfProperty/.style={rectangle,align=center,\n" + + "inner sep=0mm,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "fill=rdfPropertyColor, minimum width=80pt,\n" + + "minimum height = 25pt}}\n\n"; + + + texString += "\\tikzset{owlDatatypeProperty/.style={rectangle,align=center,\n" + + "fill=owlDatatypePropertyColor, minimum width=80pt,\n" + + "inner sep=0mm,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "minimum height = 25pt}}\n\n"; + + texString += "\\tikzset{rdfsSubClassOf/.style={rectangle,align=center,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "inner sep=0mm,\n" + + "fill=imageBGCOLOR, minimum width=80pt,\n" + + "minimum height = 25pt}}\n\n"; + + texString += "\\tikzset{unionOf/.style={circle, inner sep=0mm,align=center,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "black, draw=black, line width=1pt, fill=unionColor, minimum size=25pt}}\n\n"; + + texString += "\\tikzset{disjointWith/.style={circle, inner sep=0mm,align=center,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "black, draw=black, line width=1pt, fill=unionColor, minimum size=20pt}}\n\n"; + + + texString += "\\tikzset{owlEquivalentClass/.style={circle,align=center,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "inner sep=0mm,\n" + + "black, solid, draw=black, line width=3pt, fill=owlExternalClassColor, minimum size=101pt,\n" + + "postaction = {draw,line width=1pt, white}}}\n\n"; + + // draw a bounding box; + + // get bbox coordinates; + + + graph.options().navigationMenu().hideAllMenus(); + /** check if there is data **/ + if ( !exportableJsonText ) { + alert("No graph data available."); + // Stop the redirection to the path of the href attribute + d3.event.preventDefault(); + return; + } + + var i = 0, identifier; + + /** get data for exporter **/ + var nodeElements = graph.graphNodeElements(); // get visible nodes + var propElements = graph.graphLabelElements(); // get visible labels + var links = graph.graphLinkElements(); + + // export only nodes; + // draw Links; + for ( i = 0; i < links.length; i++ ) { + var link = links[i]; + // console.log("\n****************\nInverstigating Link for property "+link.property().labelForCurrentLanguage()); + + var prop = link.property(); + var dx, dy, px, py, rx, ry; + var colorStr = "black"; + var linkDomainIntersection; + var linkRangeIntersection; + var center; + var linkStyle = ""; + var isLoop = ""; + var curvePoint; + var pathStart; + var pathEnd; + var controlPoints; + var len; + var ahAngle; + var pathLen; + var markerOffset = 7; + + var arrowType = "triangleBlack"; + var linkWidth = ",line width=2pt"; + if ( prop.linkType ) { + if ( prop.linkType() === "dotted" ) { + //stroke-dasharray: 3; + linkStyle = ", dotted "; + arrowType = "triangleWhite"; + } + if ( prop.linkType() === "dashed" ) { + //stroke-dasharray: 3; + linkStyle = ", dashed "; + } + + if ( prop.linkType() === "values-from" ) { + colorStr = "valuesFrom"; + } + + } + + var startX, startY, endX, endY, normX, normY, lg; + + if ( link.layers().length === 1 && !link.loops() ) { + + linkDomainIntersection = graph.math().calculateIntersection(link.range(), link.domain(), 1); + linkRangeIntersection = graph.math().calculateIntersection(link.domain(), link.range(), 1); + center = graph.math().calculateCenter(linkDomainIntersection, linkRangeIntersection); + dx = linkDomainIntersection.x; + dy = -linkDomainIntersection.y; + px = center.x; + py = -center.y; + rx = linkRangeIntersection.x; + ry = -linkRangeIntersection.y; + + + pathStart = linkDomainIntersection; + curvePoint = center; + pathEnd = linkRangeIntersection; + + var nx = rx - px; + var ny = ry - py; + + // normalize ; + len = Math.sqrt(nx * nx + ny * ny); + + nx = nx / len; + ny = ny / len; + + ahAngle = Math.atan2(ny, nx) * (180 / Math.PI); + normX = nx; + normY = ny; + } + else { + if ( link.isLoop() ) { + isLoop = ", tension=3"; + controlPoints = graph.math().calculateLoopPoints(link); + pathStart = controlPoints[0]; + curvePoint = controlPoints[1]; + pathEnd = controlPoints[2]; + } else { + curvePoint = link.label(); + pathStart = graph.math().calculateIntersection(curvePoint, link.domain(), 1); + pathEnd = graph.math().calculateIntersection(curvePoint, link.range(), 1); + } + dx = pathStart.x; + dy = -pathStart.y; + px = curvePoint.x; + py = -curvePoint.y; + rx = pathEnd.x; + ry = -pathEnd.y; + } + + texString += "\\draw [" + colorStr + linkStyle + linkWidth + isLoop + "] plot [smooth] coordinates {(" + + dx + "pt, " + dy + "pt) (" + px + "pt, " + py + "pt) (" + rx + "pt, " + ry + "pt)};\n"; + + + if ( link.property().markerElement() === undefined ) continue; + + // add arrow head; + + + if ( link.property().type() === "owl:someValuesFrom" || link.property().type() === "owl:allValuesFrom" ) { + arrowType = "triangleBlue"; + } + + lg = link.pathObj(); + pathLen = Math.floor(lg.node().getTotalLength()); + var p1 = lg.node().getPointAtLength(pathLen - 4); + var p2 = lg.node().getPointAtLength(pathLen); + var markerCenter = lg.node().getPointAtLength(pathLen - 6); + + if ( link.property().type() === "setOperatorProperty" ) { + p1 = lg.node().getPointAtLength(4); + p2 = lg.node().getPointAtLength(0); + markerCenter = lg.node().getPointAtLength(8); + arrowType = "Diamond"; + } + + startX = p1.x; + startY = p1.y; + endX = p2.x; + endY = p2.y; + normX = endX - startX; + normY = endY - startY; + len = Math.sqrt(normX * normX + normY * normY); + normX = normX / len; + normY = normY / len; + + ahAngle = -1.0 * Math.atan2(normY, normX) * (180 / Math.PI); + ahAngle -= 90; + if ( link.property().type() === "setOperatorProperty" ) { + ahAngle -= 45; + } + // console.log(link.property().labelForCurrentLanguage()+ ": "+normX+ " "+normY +" "+ahAngle); + rx = markerCenter.x; + ry = markerCenter.y; + if ( link.layers().length === 1 && !link.loops() ) { + // markerOffset=-1*m + ry = -1 * ry; + texString += "\\node[" + arrowType + ", rotate=" + ahAngle + "] at (" + rx + "pt, " + ry + "pt) (single_marker" + i + ") {};\n "; + } else { + ry = -1 * ry; + texString += "\\node[" + arrowType + ", rotate=" + ahAngle + "] at (" + rx + "pt, " + ry + "pt) (marker" + i + ") {};\n "; + } + + // if (link.isLoop()){ + // rotAngle=-10+angle * (180 / Math.PI); + // } + + // add cardinality; + var cardinalityText = link.property().generateCardinalityText(); + if ( cardinalityText && cardinalityText.length > 0 ) { + var cardinalityCenter = lg.node().getPointAtLength(pathLen - 18); + var cx = cardinalityCenter.x - (10 * normY); + var cy = cardinalityCenter.y + (10 * normX); // using orthonormal y Coordinate + cy *= -1.0; + var textColor = "black"; + if ( cardinalityText.indexOf("A") > -1 ) { + cardinalityText = "$\\forall$"; + } + if ( cardinalityText.indexOf("E") > -1 ) { + cardinalityText = "$\\exists$"; + } + + + texString += "\\node[font={\\fontsize{12pt}{12}\\selectfont \\sffamily },text=" + textColor + "] at (" + cx + "pt, " + cy + "pt) (cardinalityText" + i + ") {" + cardinalityText + "};\n "; + } + + + if ( link.property().inverse() ) { + lg = link.pathObj(); + pathLen = Math.floor(lg.node().getTotalLength()); + var p1_inv = lg.node().getPointAtLength(4); + var p2_inv = lg.node().getPointAtLength(0); + var markerCenter_inv = lg.node().getPointAtLength(6); + startX = p1_inv.x; + startY = p1_inv.y; + endX = p2_inv.x; + endY = p2_inv.y; + normX = endX - startX; + normY = endY - startY; + len = Math.sqrt(normX * normX + normY * normY); + normX = normX / len; + normY = normY / len; + + ahAngle = -1.0 * Math.atan2(normY, normX) * (180 / Math.PI); + ahAngle -= 90; + // console.log("INV>>\n "+link.property().inverse().labelForCurrentLanguage()+ ": "+normX+ " "+normY +" "+ahAngle); + rx = markerCenter_inv.x; + ry = markerCenter_inv.y; + if ( link.layers().length === 1 && !link.loops() ) { + // markerOffset=-1*m + ry = -1 * ry; + texString += "\\node[" + arrowType + ", rotate=" + ahAngle + "] at (" + rx + "pt, " + ry + "pt) (INV_single_marker" + i + ") {};\n "; + } else { + ry = -1 * ry; + texString += "\\node[" + arrowType + ", rotate=" + ahAngle + "] at (" + rx + "pt, " + ry + "pt) (INV_marker" + i + ") {};\n "; + } + } + + + } + + + nodeElements.each(function ( node ){ + + px = node.x; + py = -node.y; + identifier = node.labelForCurrentLanguage(); + // console.log("Writing : "+ identifier); + if ( identifier === undefined ) identifier = ""; + var qType = "owlClass"; + if ( node.type() === "owl:Thing" || node.type() === "owl:Nothing" ) + qType = "owlThing"; + + if ( node.type() === "owl:equivalentClass" ) { + qType = "owlEquivalentClass"; + } + var textColorStr = ""; + if ( node.textBlock ) { + var txtColor = node.textBlock()._textBlock().style("fill"); + if ( txtColor === "rgb(0, 0, 0)" ) { + textColorStr = ", text=black"; + } + if ( txtColor === "rgb(255, 255, 255)" ) { + textColorStr = ", text=white"; + } + + + var tspans = node.textBlock()._textBlock().node().children; + if ( tspans[0] ) { + identifier = tspans[0].innerHTML; + if ( node.individuals() && node.individuals().length === parseInt(tspans[0].innerHTML) ) { + identifier = "{\\color{gray} " + tspans[0].innerHTML + " }"; + } + for ( var t = 1; t < tspans.length; t++ ) { + if ( node.individuals() && node.individuals().length === parseInt(tspans[t].innerHTML) ) { + identifier += "\\\\ {\\color{gray} " + tspans[t].innerHTML + " }"; + } else { + identifier += "\\\\ {\\small " + tspans[t].innerHTML + " }"; + } + } + } + } + if ( node.type() === "rdfs:Literal" ) { + qType = "Literal"; + } + if ( node.type() === "rdfs:Datatype" ) { + qType = "Datatype"; + } + if ( node.attributes().indexOf("anonymous") !== -1 ) { + qType = "anonymousClass"; + } + + + if ( node.type() === "owl:unionOf" || node.type() === "owl:complementOf" || node.type() === "owl:disjointUnionOf" || node.type() === "owl:intersectionOf" ) + qType = "owlClass"; + + var bgColorStr = ""; + var widthString = ""; + + if ( node.type() === "rdfs:Literal" || node.type() === "rdfs:Datatype" ) { + var width = node.width(); + widthString = ",minimum width=" + width + "pt"; + } + else { + widthString = ",minimum size=" + 2 * node.actualRadius() + "pt"; + + } + if ( node.backgroundColor() ) { + var bgColor = node.backgroundColor(); + bgColor.toUpperCase(); + bgColor = bgColor.slice(1, bgColor.length); + texString += "\\definecolor{Node" + i + "_COLOR}{HTML}{" + bgColor + "} \n "; + bgColorStr = ", fill=Node" + i + "_COLOR "; + } + if ( node.attributes().indexOf("deprecated") > -1 ) { + texString += "\\definecolor{Node" + i + "_COLOR}{HTML}{CCCCCC} \n "; + bgColorStr = ", fill=Node" + i + "_COLOR "; + } + + var leftPos = px - 7; + var rightPos = px + 7; + var txtOffset = py + 20; + if ( node.type() !== "owl:unionOf" || node.type() !== "owl:disjointUnionOf" ) { + texString += "\\node[" + qType + " " + widthString + " " + bgColorStr + " " + textColorStr + "] at (" + px + "pt, " + py + "pt) (Node" + i + ") {" + identifier.replaceAll("_", "\\_ ") + "};\n"; + } + if ( node.type() === "owl:unionOf" ) { + // add symbol to it; + texString += "\\node[" + qType + " " + widthString + " " + bgColorStr + " " + textColorStr + "] at (" + px + "pt, " + py + "pt) (Node" + i + ") {};\n"; + texString += "\\node[unionOf , text=black] at (" + leftPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[unionOf , text=black] at (" + rightPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[unionOf ,fill=none , text=black] at (" + leftPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[text=black] at (" + px + "pt, " + py + "pt) (unionText13) {$\\mathbf{\\cup}$};\n"; + texString += "\\node[font={\\fontsize{12pt}{12}\\selectfont \\sffamily }" + textColorStr + "] at (" + px + "pt, " + txtOffset + "pt) (Node_text" + i + ") {" + identifier.replaceAll("_", "\\_ ") + "};\n"; + } + // OWL DISJOINT UNION OF + if ( node.type() === "owl:disjointUnionOf" ) { + texString += "\\node[" + qType + " " + widthString + " " + bgColorStr + " " + textColorStr + "] at (" + px + "pt, " + py + "pt) (Node" + i + ") {};\n"; + texString += "\\node[unionOf , text=black] at (" + leftPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[unionOf , text=black] at (" + rightPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[unionOf ,fill=none , text=black] at (" + leftPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[font={\\fontsize{12pt}{12}\\selectfont \\sffamily }" + textColorStr + "] at (" + px + "pt, " + py + "pt) (disjointUnoinText" + i + ") {1};\n"; + texString += "\\node[font={\\fontsize{12pt}{12}\\selectfont \\sffamily }" + textColorStr + "] at (" + px + "pt, " + txtOffset + "pt) (Node_text" + i + ") {" + identifier.replaceAll("_", "\\_ ") + "};\n"; + } + // OWL COMPLEMENT OF + if ( node.type() === "owl:complementOf" ) { + // add symbol to it; + texString += "\\node[" + qType + " " + widthString + " " + bgColorStr + " " + textColorStr + "] at (" + px + "pt, " + py + "pt) (Node" + i + ") {};\n"; + texString += "\\node[unionOf , text=black] at (" + px + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[font={\\fontsize{18pt}{18}\\selectfont \\sffamily }" + textColorStr + "] at (" + px + "pt, " + py + "pt) (unionText13) {$\\neg$};\n"; + texString += "\\node[font={\\fontsize{12pt}{12}\\selectfont \\sffamily }" + textColorStr + "] at (" + px + "pt, " + txtOffset + "pt) (Node_text" + i + ") {" + identifier.replaceAll("_", "\\_ ") + "};\n"; + } + // OWL INTERSECTION OF + if ( node.type() === "owl:intersectionOf" ) { + texString += "\\node[" + qType + " " + widthString + " " + bgColorStr + " " + textColorStr + "] at (" + px + "pt, " + py + "pt) (Node" + i + ") {};\n"; + texString += "\\node[unionOf , text=black] at (" + leftPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[unionOf , text=black] at (" + rightPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[unionOf ,fill=none , text=black] at (" + leftPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + + // add now the outer colors; + texString += "\\filldraw[even odd rule,fill=owlClassColor,line width=1pt] (" + leftPos + "pt, " + py + "pt) circle (12.5pt) (" + rightPos + "pt, " + py + "pt) circle (12.5pt);\n "; + + // add texts + texString += "\\node[font={\\fontsize{12pt}{12}\\selectfont \\sffamily }" + textColorStr + "] at (" + px + "pt, " + py + "pt) (intersectionText" + i + ") {$\\cap$};\n"; + texString += "\\node[font={\\fontsize{12pt}{12}\\selectfont \\sffamily }" + textColorStr + "] at (" + px + "pt, " + txtOffset + "pt) (Node_text" + i + ") {" + identifier.replaceAll("_", "\\_ ") + "};\n"; + + } + + + i++; + + }); + for ( i = 0; i < propElements.length; i++ ) { + var correspondingProp = propElements[i].property(); + var p_px = propElements[i].x; + var p_py = -propElements[i].y; + identifier = correspondingProp.labelForCurrentLanguage(); + if ( identifier === undefined ) identifier = ""; + var textColorStr = ""; + if ( correspondingProp.textBlock && correspondingProp.textBlock() ) { + var txtColor = correspondingProp.textBlock()._textBlock().style("fill"); + // console.log("PropertyTextColor="+txtColor); + if ( txtColor === "rgb(0, 0, 0)" ) { + textColorStr = ", text=black"; + } + if ( txtColor === "rgb(255, 255, 255)" ) { + textColorStr = ", text=white"; + } + var tspans = correspondingProp.textBlock()._textBlock().node().children; + + // identifier=node.textBlock()._textBlock().text(); + // console.log(tspans); + if ( tspans[0] ) { + identifier = tspans[0].innerHTML; + + for ( var t = 1; t < tspans.length; t++ ) { + var spanText = tspans[t].innerHTML; + if ( spanText.indexOf("(") > -1 ) { + identifier += "\\\\ {\\small " + tspans[t].innerHTML + " }"; + } + else { + identifier += "\\\\ " + tspans[t].innerHTML; + } + } + } + else { + } + } + if ( correspondingProp.type() === "setOperatorProperty" ) { + continue; // this property does not have a label + } + var qType = "owlObjectProperty"; + if ( correspondingProp.type() === "owl:DatatypeProperty" ) { + qType = "owlDatatypeProperty"; + } + if ( correspondingProp.type() === "rdfs:subClassOf" ) { + qType = "rdfsSubClassOf"; + } + if ( correspondingProp.type() === "rdf:Property" ) { + qType = "rdfProperty"; + } + + + var bgColorStr = ""; + if ( correspondingProp.backgroundColor() ) { + // console.log("Found backGround color"); + var bgColor = correspondingProp.backgroundColor(); + //console.log(bgColor); + bgColor.toUpperCase(); + bgColor = bgColor.slice(1, bgColor.length); + texString += "\\definecolor{property" + i + "_COLOR}{HTML}{" + bgColor + "} \n "; + bgColorStr = ", fill=property" + i + "_COLOR "; + } + if ( correspondingProp.attributes().indexOf("deprecated") > -1 ) { + texString += "\\definecolor{property" + i + "_COLOR}{HTML}{CCCCCC} \n "; + bgColorStr = ", fill=property" + i + "_COLOR "; + } + + var widthString = ""; + var width = correspondingProp.textWidth(); + widthString = ",minimum width=" + width + "pt"; + + + // OWL INTERSECTION OF + if ( correspondingProp.type() === "owl:disjointWith" ) { + var leftPos = p_px - 12; + var rightPos = p_px + 12; + var txtOffset = p_py - 20; + texString += "\\node[" + qType + " " + widthString + " " + bgColorStr + " " + textColorStr + "] at (" + p_px + "pt, " + p_py + "pt) (Node" + i + ") {};\n"; + texString += "\\node[disjointWith , text=black] at (" + leftPos + "pt, " + p_py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[disjointWith , text=black] at (" + rightPos + "pt, " + p_py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[font={\\fontsize{12pt}{12}\\selectfont \\sffamily }" + textColorStr + "] at (" + p_px + "pt, " + txtOffset + "pt) (Node_text" + i + ") {"; + if ( graph.options().compactNotation() === false ) { + texString += "(disjoint)"; + } + texString += "};\n"; + continue; + } + + + if ( correspondingProp.inverse() ) { + var inv_correspondingProp = correspondingProp.inverse(); + // create the rendering element for the inverse property; + var inv_identifier = inv_correspondingProp.labelForCurrentLanguage(); + if ( inv_identifier === undefined ) inv_identifier = ""; + var inv_textColorStr = ""; + //console.log(inv_correspondingProp); + //console.log(inv_correspondingProp.textBlock()); + + if ( inv_correspondingProp.textBlock && inv_correspondingProp.textBlock() ) { + + var inv_txtColor = inv_correspondingProp.textBlock()._textBlock().style("fill"); + // console.log("PropertyTextColor="+inv_txtColor); + if ( inv_txtColor === "rgb(0, 0, 0)" ) { + inv_textColorStr = ", text=black"; + } + if ( inv_txtColor === "rgb(255, 255, 255)" ) { + inv_textColorStr = ", text=white"; + } + var inv_tspans = inv_correspondingProp.textBlock()._textBlock().node().children; + + // identifier=node.textBlock()._textBlock().text(); + // console.log(inv_tspans); + if ( inv_tspans[0] ) { + inv_identifier = inv_tspans[0].innerHTML; + + for ( var inv_t = 1; inv_t < inv_tspans.length; inv_t++ ) { + var ispanText = inv_tspans[inv_t].innerHTML; + if ( ispanText.indexOf("(") > -1 ) { + inv_identifier += "\\\\ {\\small " + inv_tspans[inv_t].innerHTML + " }"; + } else { + inv_identifier += "\\\\ " + inv_tspans[inv_t].innerHTML; + } + } + } + } + var inv_qType = "owlObjectProperty"; + var inv_bgColorStr = ""; + + if ( inv_correspondingProp.backgroundColor() ) { + // console.log("Found backGround color"); + var inv_bgColor = inv_correspondingProp.backgroundColor(); + // console.log(inv_bgColor); + inv_bgColor.toUpperCase(); + inv_bgColor = inv_bgColor.slice(1, inv_bgColor.length); + texString += "\\definecolor{inv_property" + i + "_COLOR}{HTML}{" + inv_bgColor + "} \n "; + inv_bgColorStr = ", fill=inv_property" + i + "_COLOR "; + } + if ( inv_correspondingProp.attributes().indexOf("deprecated") > -1 ) { + texString += "\\definecolor{inv_property" + i + "_COLOR}{HTML}{CCCCCC} \n "; + inv_bgColorStr = ", fill=inv_property" + i + "_COLOR "; + } + + var inv_widthString = ""; + var inv_width = inv_correspondingProp.textWidth(); + + var pOY1 = p_py - 14; + var pOY2 = p_py + 14; + inv_widthString = ",minimum width=" + inv_width + "pt"; + texString += "% Createing Inverse Property \n"; + texString += "\\node[" + inv_qType + " " + inv_widthString + " " + inv_bgColorStr + " " + inv_textColorStr + "] at (" + p_px + "pt, " + pOY1 + "pt) (property" + i + ") {" + inv_identifier.replaceAll("_", "\\_ ") + "};\n"; + texString += "% " + inv_qType + " vs " + qType + "\n"; + texString += "% " + inv_widthString + " vs " + widthString + "\n"; + texString += "% " + inv_bgColorStr + " vs " + bgColorStr + "\n"; + texString += "% " + inv_textColorStr + " vs " + textColorStr + "\n"; + + texString += "\\node[" + qType + " " + widthString + " " + bgColorStr + " " + textColorStr + "] at (" + p_px + "pt, " + pOY2 + "pt) (property" + i + ") {" + identifier.replaceAll("_", "\\_ ") + "};\n"; + + } else { + texString += "\\node[" + qType + " " + widthString + " " + bgColorStr + " " + textColorStr + "] at (" + p_px + "pt, " + p_py + "pt) (property" + i + ") {" + identifier.replaceAll("_", "\\_ ") + "};\n"; + } + } + + texString += "\\end{tikzpicture}\n}\n \\end{center}\n"; + + // console.log("Tex Output\n"+ texString); + var dataURI = "data:text/json;charset=utf-8," + encodeURIComponent(texString); + exportTexButton.attr("href", dataURI) + .attr("download", exportFilename + ".tex"); + + + } + + function calculateRadian( angle ){ + angle = angle % 360; + if ( angle < 0 ) { + angle = angle + 360; + } + return (Math.PI * angle) / 180; + } + + function calculateAngle( radian ){ + return radian * (180 / Math.PI); + } + + return exportMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 324: +/***/ (function(module, exports) { + + /** + * Contains the logic for the export button. + * @returns {{}} + */ + module.exports = function ( graph ){ + var exportTTLModule = {}; + var resultingTTLContent = ""; + var currentNodes; + var currentProperties; + var currentAxioms; + var Map_ID2Node = {}; + var Map_ID2Prop = {}; + var prefixModule = webvowl.util.prefixTools(graph); + + exportTTLModule.requestExport = function (){ + prefixModule.updatePrefixModel(); + resultingTTLContent = ""; + currentNodes = graph.getClassDataForTtlExport(); + var i; + for ( i = 0; i < currentNodes.length; i++ ) { + Map_ID2Node[currentNodes[i].id()] = currentNodes[i]; + } + currentProperties = graph.getPropertyDataForTtlExport(); + + for ( i = 0; i < currentProperties.length; i++ ) { + Map_ID2Prop[currentProperties[i].id()] = currentProperties[i]; + } + + + prepareHeader(); + preparePrefixList(); + prepareOntologyDef(); + resultingTTLContent += "#################################################################\r\n\r\n"; + preparePrefixRepresentation(); + var property_success = exportProperties(); + var class_success = exportClasses(); + currentNodes = null; + currentProperties = null; + Map_ID2Node = {}; + Map_ID2Prop = {}; + if ( property_success === false || class_success === false ) + return false; + return true; + + }; + + function preparePrefixRepresentation(){ + var i; + var allNodes = graph.getUnfilteredData().nodes; + var allProps = graph.getUnfilteredData().properties; + for ( i = 0; i < allNodes.length; i++ ) { + var nodeIRI = prefixModule.getPrefixRepresentationForFullURI(allNodes[i].iri()); + if ( prefixModule.validURL(nodeIRI) === true ) + allNodes[i].prefixRepresentation = "<" + nodeIRI + ">"; + else + allNodes[i].prefixRepresentation = nodeIRI; + } + for ( i = 0; i < allProps.length; i++ ) { + var propIRI = prefixModule.getPrefixRepresentationForFullURI(allProps[i].iri()); + if ( prefixModule.validURL(propIRI) === true ) + allProps[i].prefixRepresentation = "<" + propIRI + ">"; + else + allProps[i].prefixRepresentation = propIRI; + } + } + + function exportProperties(){ + if ( currentProperties.length === 0 ) return; // we dont need to write that + resultingTTLContent += "### Property Definitions (Number of Property) " + currentProperties.length + " ###\r\n"; + for ( var i = 0; i < currentProperties.length; i++ ) { + + resultingTTLContent += "# --------------------------- Property " + i + "------------------------- \r\n"; + var addedElement = extractPropertyDescription(currentProperties[i]); + resultingTTLContent += addedElement; + //@ workaround for not supported elements + if ( addedElement.indexOf("WHYEMPTYNAME") !== -1 ) { + return false; + } + } + return true; + } + + + function exportClasses(){ + if ( currentNodes.length === 0 ) return; // we dont need to write that + resultingTTLContent += "### Class Definitions (Number of Classes) " + currentNodes.length + " ###\r\n"; + for ( var i = 0; i < currentNodes.length; i++ ) { + // check for node type here and return false + resultingTTLContent += "# --------------------------- Class " + i + "------------------------- \r\n"; + var addedElement = extractClassDescription(currentNodes[i]); + resultingTTLContent += addedElement; + + if ( addedElement.indexOf("WHYEMPTYNAME") !== -1 ) { + return false; + } + } + return true; + } + + function getPresentAttribute( selectedElement, element ){ + var attr = selectedElement.attributes(); + return (attr.indexOf(element) >= 0); + } + + function extractClassDescription( node ){ + var subject = node.prefixRepresentation; + var predicate = "rdf:type"; + var object = node.type(); + if ( node.type() === "owl:equivalentClass" ) + object = "owl:Class"; + if ( node.type() === "owl:disjointUnionOf" ) + object = "owl:Class"; + if ( node.type() === "owl:unionOf" ) + object = "owl:Class"; + var arrayOfNodes = []; + var arrayOfUnionNodes = []; + + if ( node.union() ) { + var union = node.union(); + for ( var u = 0; u < union.length; u++ ) { + var u_node = Map_ID2Node[union[u]]; + arrayOfUnionNodes.push(u_node); + } + } + + if ( node.disjointUnion() ) { + var distUnion = node.disjointUnion(); + for ( var du = 0; du < distUnion.length; du++ ) { + var du_node = Map_ID2Node[distUnion[du]]; + arrayOfNodes.push(du_node); + } + } + + var objectDef = subject + " " + predicate + " " + object; + if ( getPresentAttribute(node, "deprecated") === true ) { + objectDef += ", owl:DeprecatedProperty"; + } + // equivalent class handeled using type itself! + + // check for equivalent classes; + var indent = getIndent(subject); + objectDef += "; \r\n"; + for ( var e = 0; e < node.equivalents().length; e++ ) { + var eqIRI = prefixModule.getPrefixRepresentationForFullURI(node.equivalents()[e].iri()); + var eqNode_prefRepresentation = ""; + if ( prefixModule.validURL(eqIRI) === true ) + eqNode_prefRepresentation = "<" + eqIRI + ">"; + else + eqNode_prefRepresentation = eqIRI; + objectDef += indent + " owl:equivalentClass " + eqNode_prefRepresentation + " ;\r\n"; + } + + // if (getPresentAttribute(node,"equivalent")===true){ + // objectDef+=", owl:EquivalentClass"; + // } + + // add Comments + + if ( node.commentForCurrentLanguage() ) { + + objectDef += indent + " rdfs:comment \"" + node.commentForCurrentLanguage() + "\" ;\r\n"; + } + + if ( node.annotations() ) { + var annotations = node.annotations(); + for ( var an in annotations ) { + if ( annotations.hasOwnProperty(an) ) { + var anArrayObj = annotations[an]; + var anObj = anArrayObj[0]; + var an_ident = anObj.identifier; + var an_val = anObj.value; + + if ( an_ident === "isDefinedBy" ) { + objectDef += indent + " rdfs:isDefinedBy <" + an_val + "> ;\r\n"; + } + if ( an_ident === "term_status" ) { + objectDef += indent + " vs:term_status \"" + an_val + "\" ;\r\n"; + } + } + } + } + + + if ( arrayOfNodes.length > 0 ) { + // add disjoint unionOf + objectDef += indent + " owl:disjointUnionOf ("; + for ( var duE = 0; duE < arrayOfNodes.length; duE++ ) { + var duIri = prefixModule.getPrefixRepresentationForFullURI(arrayOfNodes[duE].iri()); + var duNode_prefRepresentation = ""; + if ( prefixModule.validURL(duIri) === true ) + duNode_prefRepresentation = "<" + duIri + ">"; + else + duNode_prefRepresentation = duIri; + objectDef += indent + indent + duNode_prefRepresentation + " \n"; + } + objectDef += ") ;\r\n"; + } + + if ( arrayOfUnionNodes.length > 0 ) { + // add disjoint unionOf + objectDef += indent + " rdfs:subClassOf [ rdf:type owl:Class ; \r\n"; + objectDef += indent + indent + " owl:unionOf ( "; + + for ( var uE = 0; uE < arrayOfUnionNodes.length; uE++ ) { + + if ( arrayOfUnionNodes[uE] && arrayOfUnionNodes[uE].iri() ) { + var uIri = prefixModule.getPrefixRepresentationForFullURI(arrayOfUnionNodes[uE].iri()); + var uNode_prefRepresentation = ""; + if ( prefixModule.validURL(uIri) === true ) + uNode_prefRepresentation = "<" + uIri + ">"; + else + uNode_prefRepresentation = uIri; + objectDef += indent + indent + indent + uNode_prefRepresentation + " \n"; + } + } + objectDef += ") ;\r\n"; + + + } + + + var allProps = graph.getUnfilteredData().properties; + var myProperties = []; + var i; + for ( i = 0; i < allProps.length; i++ ) { + if ( allProps[i].domain() === node && + ( allProps[i].type() === "rdfs:subClassOf" || + allProps[i].type() === "owl:allValuesFrom" || + allProps[i].type() === "owl:someValuesFrom") + ) { + myProperties.push(allProps[i]); + } + // special case disjoint with>> both domain and range get that property + if ( (allProps[i].domain() === node) && + allProps[i].type() === "owl:disjointWith" ) { + myProperties.push(allProps[i]); + } + + } + for ( i = 0; i < myProperties.length; i++ ) { + // depending on the property we have to do some things; + + // special case + if ( myProperties[i].type() === "owl:someValuesFrom" ) { + objectDef += indent + " rdfs:subClassOf [ rdf:type owl:Restriction ; \r\n"; + objectDef += indent + " owl:onProperty " + myProperties[i].prefixRepresentation + ";\r\n"; + if ( myProperties[i].range().type() !== "owl:Thing" ) { + objectDef += indent + " owl:someValuesFrom " + myProperties[i].range().prefixRepresentation + "\r\n"; + } + objectDef += indent + " ];\r\n"; + continue; + } + + if ( myProperties[i].type() === "owl:allValuesFrom" ) { + objectDef += indent + " rdfs:subClassOf [ rdf:type owl:Restriction ; \r\n"; + objectDef += indent + " owl:onProperty " + myProperties[i].prefixRepresentation + ";\r\n"; + if ( myProperties[i].range().type() !== "owl:Thing" ) { + objectDef += indent + " owl:allValuesFrom " + myProperties[i].range().prefixRepresentation + "\r\n"; + } + objectDef += indent + " ];\r\n"; + continue; + } + + if ( myProperties[i].range().type() !== "owl:Thing" ) { + objectDef += indent + " " + myProperties[i].prefixRepresentation + + " " + myProperties[i].range().prefixRepresentation + " ;\r\n"; + + + } + } + + + objectDef += general_Label_languageExtractor(indent, node.label(), "rdfs:label", true); + return objectDef; + + } + + function extractPropertyDescription( property ){ + var subject = property.prefixRepresentation; + if ( subject.length === 0 ) { + console.log("THIS SHOULD NOT HAPPEN"); + var propIRI = prefixModule.getPrefixRepresentationForFullURI(property.iri()); + console.log("FOUND " + propIRI); + + + } + var predicate = "rdf:type"; + var object = property.type(); + + var objectDef = subject + " " + predicate + " " + object; + if ( getPresentAttribute(property, "deprecated") === true ) { + objectDef += ", owl:DeprecatedProperty"; + } + if ( getPresentAttribute(property, "functional") === true ) { + objectDef += ", owl:FunctionalProperty"; + } + if ( getPresentAttribute(property, "inverse functional") === true ) { + objectDef += ", owl:InverseFunctionalProperty"; + } + if ( getPresentAttribute(property, "symmetric") === true ) { + objectDef += ", owl:SymmetricProperty"; + } + if ( getPresentAttribute(property, "transitive") === true ) { + objectDef += ", owl:TransitiveProperty"; + } + var indent = getIndent(subject); + + if ( property.inverse() ) { + objectDef += "; \r\n"; + objectDef += indent + " owl:inverseOf " + property.inverse().prefixRepresentation; + } + + // check for domain and range; + + + var closeStatement = false; + var domain = property.domain(); + var range = property.range(); + + + objectDef += " ;\r\n"; + + + if ( property.commentForCurrentLanguage() ) { + + objectDef += indent + " rdfs:comment \"" + property.commentForCurrentLanguage() + "\" ;\r\n"; + } + + if ( property.superproperties() ) { + var superProps = property.superproperties(); + for ( var sP = 0; sP < superProps.length; sP++ ) { + var sPelement = superProps[sP]; + objectDef += indent + "rdfs:subPropertyOf " + sPelement.prefixRepresentation + ";\r\n"; + } + // for (var an in annotations){ + // if (annotations.hasOwnProperty(an)){ + // var anArrayObj=annotations[an]; + // var anObj=anArrayObj[0]; + // var an_ident=anObj.identifier; + // var an_val=anObj.value; + // console.log(an_ident + " "+ an_val); + // + // if (an_ident==="isDefinedBy"){ + // objectDef+=indent+" rdfs:isDefinedBy <"+an_val+"> ;\r\n"; + // } + // if (an_ident==="term_status"){ + // objectDef+=indent+" vs:term_status \""+an_val+"\" ;\r\n"; + // } + // } + // } + + } + + if ( property.annotations() ) { + var annotations = property.annotations(); + for ( var an in annotations ) { + if ( annotations.hasOwnProperty(an) ) { + var anArrayObj = annotations[an]; + var anObj = anArrayObj[0]; + var an_ident = anObj.identifier; + var an_val = anObj.value; + + if ( an_ident === "isDefinedBy" ) { + objectDef += indent + " rdfs:isDefinedBy <" + an_val + "> ;\r\n"; + } + if ( an_ident === "term_status" ) { + objectDef += indent + " vs:term_status \"" + an_val + "\" ;\r\n"; + } + } + } + } + + + if ( domain.type() === "owl:Thing" && range.type() === "owl:Thing" ) { + // we do not write domain and range + if ( typeof property.label() !== "object" && property.label().length === 0 ) { + closeStatement = true; + } + } + + + if ( closeStatement === true ) { + var uobjectDef = objectDef.substring(0, objectDef.length - 2); + objectDef = uobjectDef + " . \r\n"; + return objectDef; + } + // objectDef+="; \r\n"; + var labelDescription; + + + if ( domain.type() === "owl:Thing" && range.type() === "owl:Thing" ) { + labelDescription = general_Label_languageExtractor(indent, property.label(), "rdfs:label", true); + objectDef += labelDescription; + } + else { + // do not close the statement; + labelDescription = general_Label_languageExtractor(indent, property.label(), "rdfs:label"); + objectDef += labelDescription; + if ( domain.type() !== "owl:Thing" ) { + objectDef += indent + " rdfs:domain " + domain.prefixRepresentation + ";\r\n"; + } + if ( range.type() !== "owl:Thing" ) { + objectDef += indent + " rdfs:range " + range.prefixRepresentation + ";\r\n"; + } + + // close statement now; + + var s_needUpdate = objectDef; + var s_lastPtr = s_needUpdate.lastIndexOf(";"); + objectDef = s_needUpdate.substring(0, s_lastPtr) + " . \r\n"; + } + + return objectDef; + + } + + + exportTTLModule.resultingTTL_Content = function (){ + return resultingTTLContent; + }; + + function getIndent( name ){ + if ( name === undefined ) { + return "WHYEMPTYNAME?"; + } + return new Array(name.length + 1).join(" "); + } + + function prepareHeader(){ + resultingTTLContent += "#################################################################\r\n"; + resultingTTLContent += "### Generated with the experimental alpha version of the TTL exporter of WebVOWL (version 1.1.7) " + + " http://visualdataweb.de/webvowl/ ###\r\n"; + resultingTTLContent += "#################################################################\r\n\r\n"; + + } + + function preparePrefixList(){ + var ontoIri = graph.options().getGeneralMetaObjectProperty('iri'); + var prefixList = graph.options().prefixList(); + var prefixDef = []; + prefixDef.push('@prefix : \t\t<' + ontoIri + '> .'); + for ( var name in prefixList ) { + if ( prefixList.hasOwnProperty(name) ) { + prefixDef.push('@prefix ' + name + ': \t\t<' + prefixList[name] + '> .'); + } + } + prefixDef.push('@base \t\t\t<' + ontoIri + '> .\r\n'); + + for ( var i = 0; i < prefixDef.length; i++ ) { + resultingTTLContent += prefixDef[i] + '\r\n'; + } + } + + function prepareOntologyDef(){ + var ontoIri = graph.options().getGeneralMetaObjectProperty('iri'); + var indent = getIndent('<' + ontoIri + '>'); + resultingTTLContent += '<' + ontoIri + '> rdf:type owl:Ontology ;\r\n' + + getOntologyTitle(indent) + + getOntologyDescription(indent) + + getOntologyVersion(indent) + + getOntologyAuthor(indent); + + // close the statement; + var s_needUpdate = resultingTTLContent; + var s_lastPtr = s_needUpdate.lastIndexOf(";"); + resultingTTLContent = s_needUpdate.substring(0, s_lastPtr) + " . \r\n"; + } + + function getOntologyTitle( indent ){ + return general_languageExtractor(indent, "title", "dc:title"); + } + + function getOntologyDescription( indent ){ + return general_languageExtractor(indent, "description", "dc:description"); + } + + function getOntologyAuthor( indent ){ + var languageElement = graph.options().getGeneralMetaObjectProperty('author'); + if ( languageElement ) { + if ( typeof languageElement !== "object" ) { + if ( languageElement.length === 0 ) + return ""; // an empty string + var aString = indent + " dc:creator " + '"' + languageElement + '";\r\n'; + return aString; + } + // we assume this thing is an array; + var authorString = indent + " dc:creator " + '"'; + for ( var i = 0; i < languageElement.length - 1; i++ ) { + authorString += languageElement[i] + ", "; + } + authorString += languageElement[languageElement.length - 1] + '";\r\n'; + return authorString; + } else { + return ""; // an empty string + } + } + + function getOntologyVersion( indent ){ + var languageElement = graph.options().getGeneralMetaObjectProperty('version'); + if ( languageElement ) { + if ( typeof languageElement !== "object" ) { + if ( languageElement.length === 0 ) + return ""; // an empty string + } + return general_languageExtractor(indent, "version", "owl:versionInfo"); + } else return ""; // an empty string + } + + function general_languageExtractor( indent, metaObjectDescription, annotationDescription, endStatement ){ + var languageElement = graph.options().getGeneralMetaObjectProperty(metaObjectDescription); + + if ( typeof languageElement === 'object' ) { + + var resultingLanguages = []; + for ( var name in languageElement ) { + if ( languageElement.hasOwnProperty(name) ) { + var content = languageElement[name]; + if ( name === "undefined" ) { + resultingLanguages.push(indent + " " + annotationDescription + ' "' + content + '"@en; \r\n'); + } + else { + resultingLanguages.push(indent + " " + annotationDescription + ' "' + content + '"@' + name + '; \r\n'); + } + } + } + // create resulting titles; + + var resultingString = ""; + for ( var i = 0; i < resultingLanguages.length; i++ ) { + resultingString += resultingLanguages[i]; + } + if ( endStatement && endStatement === true ) { + var needUpdate = resultingString; + var lastPtr = needUpdate.lastIndexOf(";"); + return needUpdate.substring(0, lastPtr) + ". \r\n"; + } else { + return resultingString; + } + + } else { + if ( endStatement && endStatement === true ) { + var s_needUpdate = indent + " " + annotationDescription + ' "' + languageElement + '"@en; \r\n'; + var s_lastPtr = s_needUpdate.lastIndexOf(";"); + return s_needUpdate.substring(0, s_lastPtr) + " . \r\n"; + } + return indent + " " + annotationDescription + ' "' + languageElement + '"@en;\r\n'; + } + } + + function general_Label_languageExtractor( indent, label, annotationDescription, endStatement ){ + var languageElement = label; + + if ( typeof languageElement === 'object' ) { + var resultingLanguages = []; + for ( var name in languageElement ) { + if ( languageElement.hasOwnProperty(name) ) { + var content = languageElement[name]; + if ( name === "undefined" ) { + resultingLanguages.push(indent + " " + annotationDescription + ' "' + content + '"@en; \r\n'); + } + else { + resultingLanguages.push(indent + " " + annotationDescription + ' "' + content + '"@' + name + '; \r\n'); + } + } + } + // create resulting titles; + var resultingString = ""; + for ( var i = 0; i < resultingLanguages.length; i++ ) { + resultingString += resultingLanguages[i]; + } + if ( endStatement && endStatement === true ) { + var needUpdate = resultingString; + var lastPtr = needUpdate.lastIndexOf(";"); + return needUpdate.substring(0, lastPtr) + " . \r\n"; + } else { + return resultingString; + } + + } else { + if ( endStatement && endStatement === true ) { + var s_needUpdate = indent + " " + annotationDescription + ' "' + languageElement + '"@en; \r\n'; + var s_lastPtr = s_needUpdate.lastIndexOf(";"); + return s_needUpdate.substring(0, s_lastPtr) + " . \r\n"; + } + return indent + " " + annotationDescription + ' "' + languageElement + '"@en; \r\n'; + } + } + + return exportTTLModule; + }; + + +/***/ }), + +/***/ 325: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for connecting the filters with the website. + * + * @param graph required for calling a refresh after a filter change + * @returns {{}} + */ + module.exports = function ( graph ){ + + var filterMenu = {}, + checkboxData = [], + menuElement = d3.select("#m_filter"), + menuControl = d3.select("#c_filter a"), + nodeDegreeContainer = d3.select("#nodeDegreeFilteringOption"), + graphDegreeLevel, + defaultDegreeValue = 0, + degreeSlider; + + filterMenu.setDefaultDegreeValue = function ( val ){ + defaultDegreeValue = val; + }; + filterMenu.getDefaultDegreeValue = function (){ + return defaultDegreeValue; + }; + + filterMenu.getGraphObject = function (){ + return graph; + }; + /** some getter function **/ + filterMenu.getCheckBoxContainer = function (){ + return checkboxData; + }; + + filterMenu.getDegreeSliderValue = function (){ + return degreeSlider.property("value"); + }; + /** + * Connects the website with graph filters. + * @param datatypeFilter filter for all datatypes + * @param objectPropertyFilter filter for all object properties + * @param subclassFilter filter for all subclasses + * @param disjointFilter filter for all disjoint with properties + * @param setOperatorFilter filter for all set operators with properties + * @param nodeDegreeFilter filters nodes by their degree + */ + filterMenu.setup = function ( datatypeFilter, objectPropertyFilter, subclassFilter, disjointFilter, setOperatorFilter, nodeDegreeFilter ){ + // TODO: is this here really necessarry? << new menu visualization style? + menuControl.on("mouseover", function (){ + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + }); + menuControl.on("mouseleave", function (){ + filterMenu.highlightForDegreeSlider(false); + }); + + addFilterItem(datatypeFilter, "datatype", "Datatype properties", "#datatypeFilteringOption"); + addFilterItem(objectPropertyFilter, "objectProperty", "Object properties", "#objectPropertyFilteringOption"); + addFilterItem(subclassFilter, "subclass", "Solitary subclasses", "#subclassFilteringOption"); + addFilterItem(disjointFilter, "disjoint", "Class disjointness", "#disjointFilteringOption"); + addFilterItem(setOperatorFilter, "setoperator", "Set operators", "#setOperatorFilteringOption"); + + addNodeDegreeFilter(nodeDegreeFilter, nodeDegreeContainer); + addAnimationFinishedListener(); + }; + + + function addFilterItem( filter, identifier, pluralNameOfFilteredItems, selector ){ + var filterContainer, + filterCheckbox; + + filterContainer = d3.select(selector) + .append("div") + .classed("checkboxContainer", true); + + filterCheckbox = filterContainer.append("input") + .classed("filterCheckbox", true) + .attr("id", identifier + "FilterCheckbox") + .attr("type", "checkbox") + .property("checked", filter.enabled()); + + // Store for easier resetting + checkboxData.push({ checkbox: filterCheckbox, defaultState: filter.enabled() }); + + filterCheckbox.on("click", function ( silent ){ + // There might be no parameters passed because of a manual + // invocation when resetting the filters + var isEnabled = filterCheckbox.property("checked"); + filter.enabled(isEnabled); + if ( silent !== true ) { + // updating graph when silent is false or the parameter is not given. + graph.update(); + } + }); + + filterContainer.append("label") + .attr("for", identifier + "FilterCheckbox") + .text(pluralNameOfFilteredItems); + } + + function addNodeDegreeFilter( nodeDegreeFilter, container ){ + nodeDegreeFilter.setMaxDegreeSetter(function ( maxDegree ){ + degreeSlider.attr("max", maxDegree); + setSliderValue(degreeSlider, Math.min(maxDegree, degreeSlider.property("value"))); + }); + + nodeDegreeFilter.setDegreeGetter(function (){ + return degreeSlider.property("value"); + }); + + nodeDegreeFilter.setDegreeSetter(function ( value ){ + setSliderValue(degreeSlider, value); + }); + + var sliderContainer, + sliderValueLabel; + + sliderContainer = container.append("div") + .classed("distanceSliderContainer", true); + + degreeSlider = sliderContainer.append("input") + .attr("id", "nodeDegreeDistanceSlider") + .attr("type", "range") + .attr("min", 0) + .attr("step", 1); + + sliderContainer.append("label") + .classed("description", true) + .attr("for", "nodeDegreeDistanceSlider") + .text("Degree of collapsing"); + + sliderValueLabel = sliderContainer.append("label") + .classed("value", true) + .attr("for", "nodeDegreeDistanceSlider") + .text(0); + + + degreeSlider.on("change", function ( silent ){ + if ( silent !== true ) { + graph.update(); + graphDegreeLevel = degreeSlider.property("value"); + } + }); + + + degreeSlider.on("input", function (){ + var degree = degreeSlider.property("value"); + sliderValueLabel.text(degree); + }); + + + // adding wheel events + degreeSlider.on("wheel", handleWheelEvent); + degreeSlider.on("focusout", function (){ + if ( degreeSlider.property("value") !== graphDegreeLevel ) { + graph.update(); + } + }); + } + + function handleWheelEvent(){ + var wheelEvent = d3.event; + + var offset; + if ( wheelEvent.deltaY < 0 ) offset = 1; + if ( wheelEvent.deltaY > 0 ) offset = -1; + var maxDeg = parseInt(degreeSlider.attr("max")); + var oldVal = parseInt(degreeSlider.property("value")); + var newSliderValue = oldVal + offset; + if ( oldVal !== newSliderValue && (newSliderValue >= 0 && newSliderValue <= maxDeg) ) { + // only update when they are different [reducing redundant updates] + // set the new value and emit an update signal + degreeSlider.property("value", newSliderValue); + degreeSlider.on("input")();// <<-- sets the text value + graph.update(); + } + d3.event.preventDefault(); + } + + function setSliderValue( slider, value ){ + slider.property("value", value).on("input")(); + } + + /** + * Resets the filters (and also filtered elements) to their default. + */ + filterMenu.reset = function (){ + checkboxData.forEach(function ( checkboxData ){ + var checkbox = checkboxData.checkbox, + enabledByDefault = checkboxData.defaultState, + isChecked = checkbox.property("checked"); + + if ( isChecked !== enabledByDefault ) { + checkbox.property("checked", enabledByDefault); + // Call onclick event handlers programmatically + checkbox.on("click")(); + } + }); + + setSliderValue(degreeSlider, 0); + degreeSlider.on("change")(); + }; + + function addAnimationFinishedListener(){ + menuControl.node().addEventListener("animationend", function (){ + menuControl.classed("buttonPulse", false); + menuControl.classed("filterMenuButtonHighlight", true); + + }); + } + + filterMenu.killButtonAnimation = function (){ + menuControl.classed("buttonPulse", false); + menuControl.classed("filterMenuButtonHighlight", false); + }; + + + filterMenu.highlightForDegreeSlider = function ( enable ){ + if ( !arguments.length ) { + enable = true; + } + menuControl.classed("highlighted", enable); + nodeDegreeContainer.classed("highlighted", enable); + // pulse button handling + if ( menuControl.classed("buttonPulse") === true && enable === true ) { + menuControl.classed("buttonPulse", false); + var timer = setTimeout(function (){ + menuControl.classed("buttonPulse", enable); + clearTimeout(timer); + // after the time is done, remove the pulse but stay highlighted + }, 100); + } else { + menuControl.classed("buttonPulse", enable); + menuControl.classed("filterMenuButtonHighlight", enable); + } + }; + + + /** importer functions **/ + // setting manually the values of the filter + // no update of the gui settings, these are updated in updateSettings + filterMenu.setCheckBoxValue = function ( id, checked ){ + for ( var i = 0; i < checkboxData.length; i++ ) { + var cbdId = checkboxData[i].checkbox.attr("id"); + if ( cbdId === id ) { + checkboxData[i].checkbox.property("checked", checked); + break; + } + } + }; + + filterMenu.getCheckBoxValue = function ( id ){ + for ( var i = 0; i < checkboxData.length; i++ ) { + var cbdId = checkboxData[i].checkbox.attr("id"); + if ( cbdId === id ) { + return checkboxData[i].checkbox.property("checked"); + + } + } + }; + // set the value of the slider + filterMenu.setDegreeSliderValue = function ( val ){ + degreeSlider.property("value", val); + }; + + filterMenu.getDegreeSliderValue = function (){ + return degreeSlider.property("value"); + }; + + // update the gui without invoking graph update (calling silent onclick function) + filterMenu.updateSettings = function (){ + var silent = true; + var sliderValue = degreeSlider.property("value"); + if ( sliderValue > 0 ) { + filterMenu.highlightForDegreeSlider(true); + } else { + filterMenu.highlightForDegreeSlider(false); + } + checkboxData.forEach(function ( checkboxData ){ + var checkbox = checkboxData.checkbox; + checkbox.on("click")(silent); + }); + + degreeSlider.on("input")(); + degreeSlider.on("change")(); + + }; + + return filterMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 326: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for setting up the gravity sliders. + * + * @param graph the associated webvowl graph + * @returns {{}} + */ + module.exports = function ( graph ){ + + var gravityMenu = {}, + sliders = [], + options = graph.graphOptions(), + defaultCharge = options.charge(); + + + /** + * Adds the gravity sliders to the website. + */ + gravityMenu.setup = function (){ + var menuEntry = d3.select("#m_gravity"); + menuEntry.on("mouseover", function (){ + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + }); + addDistanceSlider("#classSliderOption", "class", "Class distance", options.classDistance); + addDistanceSlider("#datatypeSliderOption", "datatype", "Datatype distance", options.datatypeDistance); + }; + + function addDistanceSlider( selector, identifier, label, distanceFunction ){ + var defaultLinkDistance = distanceFunction(); + + var sliderContainer, + sliderValueLabel; + + sliderContainer = d3.select(selector) + .append("div") + .datum({ distanceFunction: distanceFunction }) // connect the options-function with the slider + .classed("distanceSliderContainer", true); + + var slider = sliderContainer.append("input") + .attr("id", identifier + "DistanceSlider") + .attr("type", "range") + .attr("min", 10) + .attr("max", 600) + .attr("value", distanceFunction()) + .attr("step", 10); + + sliderContainer.append("label") + .classed("description", true) + .attr("for", identifier + "DistanceSlider") + .text(label); + + sliderValueLabel = sliderContainer.append("label") + .classed("value", true) + .attr("for", identifier + "DistanceSlider") + .text(distanceFunction()); + + // Store slider for easier resetting + sliders.push(slider); + + slider.on("focusout", function (){ + graph.updateStyle(); + }); + + slider.on("input", function (){ + var distance = slider.property("value"); + distanceFunction(distance); + adjustCharge(defaultLinkDistance); + sliderValueLabel.text(distance); + graph.updateStyle(); + }); + + // add wheel event to the slider + slider.on("wheel", function (){ + var wheelEvent = d3.event; + var offset; + if ( wheelEvent.deltaY < 0 ) offset = 10; + if ( wheelEvent.deltaY > 0 ) offset = -10; + var oldVal = parseInt(slider.property("value")); + var newSliderValue = oldVal + offset; + if ( newSliderValue !== oldVal ) { + slider.property("value", newSliderValue); + distanceFunction(newSliderValue); + slider.on("input")(); // << set text and update the graphStyles + } + d3.event.preventDefault(); + }); + } + + function adjustCharge( defaultLinkDistance ){ + var greaterDistance = Math.max(options.classDistance(), options.datatypeDistance()), + ratio = greaterDistance / defaultLinkDistance, + newCharge = defaultCharge * ratio; + + options.charge(newCharge); + } + + /** + * Resets the gravity sliders to their default. + */ + gravityMenu.reset = function (){ + sliders.forEach(function ( slider ){ + slider.property("value", function ( d ){ + // Simply reload the distance from the options + return d.distanceFunction(); + }); + slider.on("input")(); + }); + }; + + + return gravityMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 327: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for connecting the modes with the website. + * + * @param graph the graph that belongs to these controls + * @returns {{}} + */ + module.exports = function ( graph ){ + + var SAME_COLOR_MODE = { text: "Multicolor", type: "same" }; + var GRADIENT_COLOR_MODE = { text: "Multicolor", type: "gradient" }; + + var modeMenu = {}, + checkboxes = [], + colorModeSwitch; + + var dynamicLabelWidthCheckBox; + // getter and setter for the state of color modes + modeMenu.colorModeState = function ( s ){ + if ( !arguments.length ) return colorModeSwitch.datum().active; + colorModeSwitch.datum().active = s; + return modeMenu; + }; + + + modeMenu.setDynamicLabelWidth = function ( val ){ + dynamicLabelWidthCheckBox.property("checked", val); + }; + // getter for checkboxes + modeMenu.getCheckBoxContainer = function (){ + return checkboxes; + }; + // getter for the color switch [needed? ] + modeMenu.colorModeSwitch = function (){ + return colorModeSwitch; + }; + + /** + * Connects the website with the available graph modes. + */ + modeMenu.setup = function ( pickAndPin, nodeScaling, compactNotation, colorExternals ){ + var menuEntry = d3.select("#m_modes"); + menuEntry.on("mouseover", function (){ + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + }); + addCheckBoxD("labelWidth", "Dynamic label width", "#dynamicLabelWidth", graph.options().dynamicLabelWidth, 1); + addCheckBox("editorMode", "Editing ", "#editMode", graph.editorMode); + addModeItem(pickAndPin, "pickandpin", "Pick & pin", "#pickAndPinOption", false); + addModeItem(nodeScaling, "nodescaling", "Node scaling", "#nodeScalingOption", true); + addModeItem(compactNotation, "compactnotation", "Compact notation", "#compactNotationOption", true); + var container = addModeItem(colorExternals, "colorexternals", "Color externals", "#colorExternalsOption", true); + colorModeSwitch = addExternalModeSelection(container, colorExternals); + }; + function addCheckBoxD( identifier, modeName, selector, onChangeFunc, updateLvl ){ + var moduleOptionContainer = d3.select(selector) + .append("div") + .classed("checkboxContainer", true); + + var moduleCheckbox = moduleOptionContainer.append("input") + .classed("moduleCheckbox", true) + .attr("id", identifier + "ModuleCheckbox") + .attr("type", "checkbox") + .property("checked", onChangeFunc()); + + moduleCheckbox.on("click", function ( d ){ + var isEnabled = moduleCheckbox.property("checked"); + onChangeFunc(isEnabled); + d3.select("#maxLabelWidthSlider").node().disabled = !isEnabled; + d3.select("#maxLabelWidthvalueLabel").classed("disabledLabelForSlider", !isEnabled); + d3.select("#maxLabelWidthDescriptionLabel").classed("disabledLabelForSlider", !isEnabled); + + if ( updateLvl > 0 ) { + graph.animateDynamicLabelWidth(); + // graph.lazyRefresh(); + } + }); + moduleOptionContainer.append("label") + .attr("for", identifier + "ModuleCheckbox") + .text(modeName); + if ( identifier === "editorMode" ) { + moduleOptionContainer.append("label") + .attr("style", "font-size:10px;padding-top:3px") + .text("(experimental)"); + } + + dynamicLabelWidthCheckBox = moduleCheckbox; + } + + function addCheckBox( identifier, modeName, selector, onChangeFunc ){ + var moduleOptionContainer = d3.select(selector) + .append("div") + .classed("checkboxContainer", true); + + var moduleCheckbox = moduleOptionContainer.append("input") + .classed("moduleCheckbox", true) + .attr("id", identifier + "ModuleCheckbox") + .attr("type", "checkbox") + .property("checked", onChangeFunc()); + + moduleCheckbox.on("click", function ( d ){ + var isEnabled = moduleCheckbox.property("checked"); + onChangeFunc(isEnabled); + if ( isEnabled === true ) + graph.showEditorHintIfNeeded(); + }); + moduleOptionContainer.append("label") + .attr("for", identifier + "ModuleCheckbox") + .text(modeName); + if ( identifier === "editorMode" ) { + moduleOptionContainer.append("label") + .attr("style", "font-size:10px;padding-top:3px") + .text(" (experimental)"); + } + } + + function addModeItem( module, identifier, modeName, selector, updateGraphOnClick ){ + var moduleOptionContainer, + moduleCheckbox; + + moduleOptionContainer = d3.select(selector) + .append("div") + .classed("checkboxContainer", true) + .datum({ module: module, defaultState: module.enabled() }); + + moduleCheckbox = moduleOptionContainer.append("input") + .classed("moduleCheckbox", true) + .attr("id", identifier + "ModuleCheckbox") + .attr("type", "checkbox") + .property("checked", module.enabled()); + + // Store for easier resetting all modes + checkboxes.push(moduleCheckbox); + + moduleCheckbox.on("click", function ( d, silent ){ + var isEnabled = moduleCheckbox.property("checked"); + d.module.enabled(isEnabled); + if ( updateGraphOnClick && silent !== true ) { + graph.executeColorExternalsModule(); + graph.executeCompactNotationModule(); + graph.lazyRefresh(); + } + }); + + moduleOptionContainer.append("label") + .attr("for", identifier + "ModuleCheckbox") + .text(modeName); + + return moduleOptionContainer; + } + + function addExternalModeSelection( container, colorExternalsMode ){ + var button = container.append("button").datum({ active: false }).classed("color-mode-switch", true); + applyColorModeSwitchState(button, colorExternalsMode); + + button.on("click", function ( silent ){ + var data = button.datum(); + data.active = !data.active; + applyColorModeSwitchState(button, colorExternalsMode); + if ( colorExternalsMode.enabled() && silent !== true ) { + graph.executeColorExternalsModule(); + graph.lazyRefresh(); + } + }); + + return button; + } + + function applyColorModeSwitchState( element, colorExternalsMode ){ + var isActive = element.datum().active; + var activeColorMode = getColorModeByState(isActive); + + element.classed("active", isActive) + .text(activeColorMode.text); + + if ( colorExternalsMode ) { + colorExternalsMode.colorModeType(activeColorMode.type); + } + } + + function getColorModeByState( isActive ){ + return isActive ? GRADIENT_COLOR_MODE : SAME_COLOR_MODE; + } + + /** + * Resets the modes to their default. + */ + modeMenu.reset = function (){ + checkboxes.forEach(function ( checkbox ){ + var defaultState = checkbox.datum().defaultState, + isChecked = checkbox.property("checked"); + + if ( isChecked !== defaultState ) { + checkbox.property("checked", defaultState); + // Call onclick event handlers programmatically + checkbox.on("click")(checkbox.datum()); + } + + // Reset the module that is connected with the checkbox + checkbox.datum().module.reset(); + }); + + // set the switch to active and simulate disabling + colorModeSwitch.datum().active = true; + colorModeSwitch.on("click")(); + }; + + /** importer functions **/ + // setting manually the values of the filter + // no update of the gui settings, these are updated in updateSettings + modeMenu.setCheckBoxValue = function ( id, checked ){ + for ( var i = 0; i < checkboxes.length; i++ ) { + var cbdId = checkboxes[i].attr("id"); + + if ( cbdId === id ) { + checkboxes[i].property("checked", checked); + break; + } + } + }; + modeMenu.getCheckBoxValue = function ( id ){ + for ( var i = 0; i < checkboxes.length; i++ ) { + var cbdId = checkboxes[i].attr("id"); + if ( cbdId === id ) { + return checkboxes[i].property("checked"); + } + } + }; + + modeMenu.setColorSwitchState = function ( state ){ + // need the !state because we simulate later a click + modeMenu.colorModeState(!state); + }; + modeMenu.setColorSwitchStateUsingURL = function ( state ){ + // need the !state because we simulate later a click + modeMenu.colorModeState(!state); + colorModeSwitch.on("click")(true); + }; + + + modeMenu.updateSettingsUsingURL = function (){ + var silent = true; + checkboxes.forEach(function ( checkbox ){ + checkbox.on("click")(checkbox.datum(), silent); + }); + }; + + modeMenu.updateSettings = function (){ + var silent = true; + checkboxes.forEach(function ( checkbox ){ + checkbox.on("click")(checkbox.datum(), silent); + }); + // this simulates onclick and inverts its state + colorModeSwitch.on("click")(silent); + }; + return modeMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 328: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( graph ){ + var debugMenu = {}, + checkboxes = []; + + + var hoverFlag = false; + var specialCbx; + debugMenu.setup = function (){ + var menuEntry = d3.select("#debugMenuHref"); + + menuEntry.on("mouseover", function (){ + if ( hoverFlag === false ) { + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + specialCbx.on("click")(true); + if ( graph.editorMode() === false ) { + d3.select("#useAccuracyHelper").style("color", "#979797"); + d3.select("#useAccuracyHelper").style("pointer-events", "none"); + + // regardless the state on which useAccuracyHelper is , we are not in editing mode -> disable it + d3.select("#showDraggerObject").style("color", "#979797"); + d3.select("#showDraggerObject").style("pointer-events", "none"); + } else { + d3.select("#useAccuracyHelper").style("color", "#2980b9"); + d3.select("#useAccuracyHelper").style("pointer-events", "auto"); + } + hoverFlag = true; + } + }); + menuEntry.on("mouseout", function (){ + hoverFlag = false; + }); + + + specialCbx = addCheckBox("useAccuracyHelper", "Use accuracy helper", "#useAccuracyHelper", graph.options().useAccuracyHelper, + function ( enabled, silent ){ + if ( !enabled ) { + d3.select("#showDraggerObject").style("color", "#979797"); + d3.select("#showDraggerObject").style("pointer-events", "none"); + d3.select("#showDraggerObjectConfigCheckbox").node().checked = false; + } else { + d3.select("#showDraggerObject").style("color", "#2980b9"); + d3.select("#showDraggerObject").style("pointer-events", "auto"); + } + + if ( silent === true ) return; + graph.lazyRefresh(); + graph.updateDraggerElements(); + } + ); + addCheckBox("showDraggerObject", "Show accuracy helper", "#showDraggerObject", graph.options().showDraggerObject, + function ( enabled, silent ){ + if ( silent === true ) return; + graph.lazyRefresh(); + graph.updateDraggerElements(); + }); + addCheckBox("showFPS_Statistics", "Show rendering statistics", "#showFPS_Statistics", graph.options().showRenderingStatistic, + function ( enabled, silent ){ + + if ( graph.options().getHideDebugFeatures() === false ) { + d3.select("#FPS_Statistics").classed("hidden", !enabled); + } else { + d3.select("#FPS_Statistics").classed("hidden", true); + } + + + }); + addCheckBox("showModeOfOperation", "Show input modality", "#showModeOfOperation", graph.options().showInputModality, + function ( enabled ){ + if ( graph.options().getHideDebugFeatures() === false ) { + d3.select("#modeOfOperationString").classed("hidden", !enabled); + } else { + d3.select("#modeOfOperationString").classed("hidden", true); + } + }); + + + }; + + + function addCheckBox( identifier, modeName, selector, onChangeFunc, _callbackFunction ){ + var configOptionContainer = d3.select(selector) + .append("div") + .classed("checkboxContainer", true); + var configCheckbox = configOptionContainer.append("input") + .classed("moduleCheckbox", true) + .attr("id", identifier + "ConfigCheckbox") + .attr("type", "checkbox") + .property("checked", onChangeFunc()); + + + configCheckbox.on("click", function ( silent ){ + var isEnabled = configCheckbox.property("checked"); + onChangeFunc(isEnabled); + _callbackFunction(isEnabled, silent); + + }); + checkboxes.push(configCheckbox); + configOptionContainer.append("label") + .attr("for", identifier + "ConfigCheckbox") + .text(modeName); + + return configCheckbox; + } + + debugMenu.setCheckBoxValue = function ( identifier, value ){ + for ( var i = 0; i < checkboxes.length; i++ ) { + var cbdId = checkboxes[i].attr("id"); + if ( cbdId === identifier ) { + checkboxes[i].property("checked", value); + break; + } + } + }; + + debugMenu.getCheckBoxValue = function ( id ){ + for ( var i = 0; i < checkboxes.length; i++ ) { + var cbdId = checkboxes[i].attr("id"); + if ( cbdId === id ) { + return checkboxes[i].property("checked"); + } + } + }; + + debugMenu.updateSettings = function (){ + d3.selectAll(".debugOption").classed("hidden", graph.options().getHideDebugFeatures()); + + var silent = true; + checkboxes.forEach(function ( checkbox ){ + checkbox.on("click")(silent); + }); + if ( graph.editorMode() === false ) { + + d3.select("#useAccuracyHelper").style("color", "#979797"); + d3.select("#useAccuracyHelper").style("pointer-events", "none"); + + // regardless the state on which useAccuracyHelper is , we are not in editing mode -> disable it + d3.select("#showDraggerObject").style("color", "#979797"); + d3.select("#showDraggerObject").style("pointer-events", "none"); + } else { + + d3.select("#useAccuracyHelper").style("color", "#2980b9"); + d3.select("#useAccuracyHelper").style("pointer-events", "auto"); + } + + }; + + return debugMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 329: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var unescape = __webpack_require__(330); + + module.exports = function ( graph ){ + + var ontologyMenu = {}, + loadingInfo = d3.select("#loading-info"), + loadingProgress = d3.select("#loading-progress"), + + ontologyMenuTimeout, + fileToLoad, + stopTimer = false, + loadingError = false, + loadingStatusTimer, + conversion_sessionId, + cachedConversions = {}, + loadingModule, + loadOntologyFromText; + var currentLoadedOntologyName = ""; + + String.prototype.beginsWith = function ( string ){ + return (this.indexOf(string) === 0); + }; + + ontologyMenu.getLoadingFunction = function (){ + return loadOntologyFromText; + }; + + ontologyMenu.clearCachedVersion = function (){ + if ( cachedConversions[currentLoadedOntologyName] ) { + cachedConversions[currentLoadedOntologyName] = undefined; + } + }; + + + ontologyMenu.reloadCachedOntology = function (){ + ontologyMenu.clearCachedVersion(); + graph.clearGraphData(); + loadingModule.parseUrlAndLoadOntology(false); + }; + + ontologyMenu.cachedOntology = function ( ontoName ){ + currentLoadedOntologyName = ontoName; + if ( cachedConversions[ontoName] ) { + var locStr = String(location.hash); + d3.select("#reloadSvgIcon").node().disabled = false; + graph.showReloadButtonAfterLayoutOptimization(true); + if ( locStr.indexOf("#file") > -1 ) { + d3.select("#reloadSvgIcon").node().disabled = true; + d3.select("#reloadCachedOntology").node().title = "reloading original version not possible, please reload the file"; + d3.select("#reloadSvgIcon").classed("disabledReloadElement", true); + d3.select("#svgStringText").style("fill", "gray"); + d3.select("#svgStringText").classed("noselect", true); + } + else { + d3.select("#reloadCachedOntology").node().title = "generate new visualization and overwrite cached ontology"; + d3.select("#reloadSvgIcon").classed("disabledReloadElement", false); + d3.select("#svgStringText").style("fill", "black"); + d3.select("#svgStringText").classed("noselect", true); + } + } else { + graph.showReloadButtonAfterLayoutOptimization(false); + + } + return cachedConversions[ontoName]; + }; + ontologyMenu.setCachedOntology = function ( ontoName, ontoContent ){ + cachedConversions[ontoName] = ontoContent; + currentLoadedOntologyName = ontoName; + }; + + ontologyMenu.getErrorStatus = function (){ + return loadingError; + }; + + ontologyMenu.setup = function ( _loadOntologyFromText ){ + loadOntologyFromText = _loadOntologyFromText; + loadingModule = graph.options().loadingModule(); + var menuEntry = d3.select("#m_select"); + menuEntry.on("mouseover", function (){ + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + }); + + setupConverterButtons(); + setupUploadButton(); + + var descriptionButton = d3.select("#error-description-button").datum({ open: false }); + descriptionButton.on("click", function ( data ){ + var errorContainer = d3.select("#error-description-container"); + var errorDetailsButton = d3.select(this); + + // toggle the state + data.open = !data.open; + var descriptionVisible = data.open; + if ( descriptionVisible ) { + errorDetailsButton.text("Hide error details"); + } else { + errorDetailsButton.text("Show error details"); + } + errorContainer.classed("hidden", !descriptionVisible); + }); + + setupUriListener(); + loadingModule.setOntologyMenu(ontologyMenu); + }; + + + function setupUriListener(){ + // reload ontology when hash parameter gets changed manually + d3.select(window).on("hashchange", function (){ + var oldURL = d3.event.oldURL, newURL = d3.event.newURL; + if ( oldURL !== newURL ) { + // don't reload when just the hash parameter gets appended + if ( newURL === oldURL + "#" ) { + return; + } + updateNavigationHrefs(); + loadingModule.parseUrlAndLoadOntology(); + } + }); + updateNavigationHrefs(); + } + + ontologyMenu.stopLoadingTimer = function (){ + stopTimer = true; + clearTimeout(loadingStatusTimer); + }; + + /** + * Quick fix: update all anchor tags that are used as buttons because a click on them + * changes the url and this will load an other ontology. + */ + function updateNavigationHrefs(){ + d3.selectAll("#menuElementContainer > li > a").attr("href", location.hash || "#"); + } + + ontologyMenu.setIriText = function ( text ){ + d3.select("#iri-converter-input").node().value = text; + d3.select("#iri-converter-button").attr("disabled", false); + d3.select("#iri-converter-form").on("submit")(); + }; + + ontologyMenu.clearDetailInformation = function (){ + var bpContainer = d3.select("#bulletPoint_container"); + var htmlCollection = bpContainer.node().children; + var numEntries = htmlCollection.length; + + for ( var i = 0; i < numEntries; i++ ) { + htmlCollection[0].remove(); + } + }; + ontologyMenu.append_message = function ( msg ){ + // forward call + append_message(msg); + }; + function append_message( msg ){ + var bpContainer = d3.select("#bulletPoint_container"); + var div = bpContainer.append("div"); + div.node().innerHTML = msg; + loadingModule.scrollDownDetails(); + } + + ontologyMenu.append_message_toLastBulletPoint = function ( msg ){ + // forward call + append_message_toLastBulletPoint(msg); + }; + + ontologyMenu.append_bulletPoint = function ( msg ){ + // forward call + append_bulletPoint(msg); + }; + function append_message_toLastBulletPoint( msg ){ + var bpContainer = d3.select("#bulletPoint_container"); + var htmlCollection = bpContainer.node().getElementsByTagName("LI"); + var lastItem = htmlCollection.length - 1; + if ( lastItem >= 0 ) { + var oldText = htmlCollection[lastItem].innerHTML; + htmlCollection[lastItem].innerHTML = oldText + msg; + } + loadingModule.scrollDownDetails(); + } + + function append_bulletPoint( msg ){ + var bp_container = d3.select("#bulletPoint_container"); + var bp = bp_container.append("li"); + bp.node().innerHTML = msg; + d3.select("#currentLoadingStep").node().innerHTML = msg; + loadingModule.scrollDownDetails(); + } + + + function setupConverterButtons(){ + var iriConverterButton = d3.select("#iri-converter-button"); + var iriConverterInput = d3.select("#iri-converter-input"); + + iriConverterInput.on("input", function (){ + keepOntologySelectionOpenShortly(); + + var inputIsEmpty = iriConverterInput.property("value") === ""; + iriConverterButton.attr("disabled", inputIsEmpty || undefined); + }).on("click", function (){ + keepOntologySelectionOpenShortly(); + }); + + d3.select("#iri-converter-form").on("submit", function (){ + var inputName = iriConverterInput.property("value"); + + // remove first spaces + var clearedName = inputName.replace(/%20/g, " "); + while ( clearedName.beginsWith(" ") ) { + clearedName = clearedName.substr(1, clearedName.length); + } + // remove ending spaces + while ( clearedName.endsWith(" ") ) { + clearedName = clearedName.substr(0, clearedName.length - 1); + } + // check if iri is actually an url for a json file (ends with .json) + // create lowercase filenames; + inputName = clearedName; + var lc_iri = inputName.toLowerCase(); + if ( lc_iri.endsWith(".json") ) { + location.hash = "url=" + inputName; + iriConverterInput.property("value", ""); + iriConverterInput.on("input")(); + } else { + location.hash = "iri=" + inputName; + iriConverterInput.property("value", ""); + iriConverterInput.on("input")(); + } + d3.event.preventDefault(); + return false; + }); + } + + function setupUploadButton(){ + var input = d3.select("#file-converter-input"), + inputLabel = d3.select("#file-converter-label"), + uploadButton = d3.select("#file-converter-button"); + + input.on("change", function (){ + var selectedFiles = input.property("files"); + if ( selectedFiles.length <= 0 ) { + inputLabel.text("Select ontology file"); + uploadButton.property("disabled", true); + } else { + inputLabel.text(selectedFiles[0].name); + fileToLoad = selectedFiles[0].name; + uploadButton.property("disabled", false); + uploadButton.node().click(); + // close menu; + graph.options().navigationMenu().hideAllMenus(); + } + }); + + uploadButton.on("click", function (){ + var selectedFile = input.property("files")[0]; + if ( !selectedFile ) { + return false; + } + var newHashParameter = "file=" + selectedFile.name; + // Trigger the reupload manually, because the iri is not changing + if ( location.hash === "#" + newHashParameter ) { + loadingModule.parseUrlAndLoadOntology(); + } else { + location.hash = newHashParameter; + } + }); + } + + function setLoadingStatusInfo( message ){ + // check if there is a owl2vowl li item; + var o2vConverterContainer = d3.select("#o2vConverterContainer"); + if ( !o2vConverterContainer.node() ) { + var bp_container = d3.select("#bulletPoint_container"); + var div = bp_container.append("div"); + o2vConverterContainer = div.append("ul"); + o2vConverterContainer.attr("id", "o2vConverterContainer"); + o2vConverterContainer.style("margin-left", "-25px"); + } + // clear o2vConverterContainer; + var htmlCollection = o2vConverterContainer.node().children; + var numEntries = htmlCollection.length; + for ( var i = 0; i < numEntries; i++ ) { + htmlCollection[0].remove(); + } + // split tokens provided by o2v messages + var tokens = message.split("* "); + var liForToken; + for ( var t = 0; t < tokens.length; t++ ) { + var tokenMessage = tokens[t]; + // create li for tokens; + if ( tokenMessage.length > 0 ) { + liForToken = o2vConverterContainer.append("li"); + liForToken.attr("type", "disc"); + liForToken.node().innerHTML = tokenMessage.replace(/\n/g, "
    "); + } + } + if ( liForToken ) + liForToken.node().innerHTML += "
    "; + + loadingModule.scrollDownDetails(); + } + + ontologyMenu.setLoadingStatusInfo = function ( message ){ + // forward call + setLoadingStatusInfo(message); + }; + + function getLoadingStatusOnceCallBacked( callback, parameter ){ + d3.xhr("loadingStatus?sessionId=" + conversion_sessionId, "application/text", function ( error, request ){ + if ( error ) { + console.log("ontologyMenu getLoadingStatusOnceCallBacked throws error"); + console.log("---------Error -----------"); + console.log(error); + console.log("---------Request -----------"); + console.log(request); + } + setLoadingStatusInfo(request.responseText); + callback(parameter); + }); + } + + function getLoadingStatusTimeLooped(){ + d3.xhr("loadingStatus?sessionId=" + conversion_sessionId, "application/text", function ( error, request ){ + if ( error ) { + console.log("ontologyMenu getLoadingStatusTimeLooped throws error"); + console.log("---------Error -----------"); + console.log(error); + console.log("---------Request -----------"); + console.log(request); + } + if ( stopTimer === false ) { + setLoadingStatusInfo(request.responseText); + timedLoadingStatusLogger(); + } + }); + } + + function timedLoadingStatusLogger(){ + clearTimeout(loadingStatusTimer); + if ( stopTimer === false ) { + loadingStatusTimer = setTimeout(function (){ + getLoadingStatusTimeLooped(); + }, 1000); + } + } + + function callbackUpdateLoadingMessage( msg ){ + d3.xhr("loadingStatus", "application/text", function ( error, request ){ + if ( request !== undefined ) { + setLoadingStatusInfo(request.responseText + "
    " + msg); + } else { + append_message(msg); + } + }); + } + + ontologyMenu.setConversionID = function ( id ){ + conversion_sessionId = id; + }; + + ontologyMenu.callbackLoad_Ontology_FromIRI = function ( parameter ){ + var relativePath = parameter[0]; + var ontoName = parameter[1]; + var localThreadId = parameter[2]; + stopTimer = false; + timedLoadingStatusLogger(); + d3.xhr(relativePath, "application/json", function ( error, request ){ + var loadingSuccessful = !error; + // check if error occurred or responseText is empty + if ( (error !== null && error.status === 500) || (request && request.responseText.length === 0) ) { + clearTimeout(loadingStatusTimer); + stopTimer = true; + getLoadingStatusOnceCallBacked(callbackFromIRI_URL_ERROR, [error, request, localThreadId]); + } + var jsonText; + if ( loadingSuccessful ) { + clearTimeout(loadingStatusTimer); + stopTimer = true; + jsonText = request.responseText; + getLoadingStatusOnceCallBacked(callbackFromIRI_Success, [jsonText, ontoName, localThreadId]); + } + }); + }; + + + ontologyMenu.callbackLoad_Ontology_From_DirectInput = function ( text, parameter ){ + var input = text; + var sessionId = parameter[1]; + stopTimer = false; + timedLoadingStatusLogger(); + + var formData = new FormData(); + formData.append("input", input); + formData.append("sessionId", sessionId); + var xhr = new XMLHttpRequest(); + + xhr.open("POST", "directInput", true); + xhr.onload = function (){ + clearTimeout(loadingStatusTimer); + stopTimer = true; + getLoadingStatusOnceCallBacked(callbackForConvert, [xhr, input, sessionId]); + }; + timedLoadingStatusLogger(); + xhr.send(formData); + + }; + function callbackFromIRI_Success( parameter ){ + var local_conversionId = parameter[2]; + if ( local_conversionId !== conversion_sessionId ) { + console.log("The conversion process for file:" + parameter[1] + " has been canceled!"); + ontologyMenu.conversionFinished(local_conversionId); + return; + } + loadingModule.loadFromOWL2VOWL(parameter[0], parameter[1]); + ontologyMenu.conversionFinished(); + + } + + function callbackFromDirectInput_Success( parameter ){ + var local_conversionId = parameter[1]; + if ( local_conversionId !== conversion_sessionId ) { + console.log("The conversion process for file:" + parameter[1] + " has been canceled!"); + ontologyMenu.conversionFinished(local_conversionId); + return; + } + loadingModule.loadFromOWL2VOWL(parameter[0], "DirectInputConversionID" + local_conversionId); + ontologyMenu.conversionFinished(); + + } + + ontologyMenu.getConversionId = function (){ + return conversion_sessionId; + }; + + ontologyMenu.callbackLoad_JSON_FromURL = function ( parameter ){ + var relativePath = parameter[0]; + var ontoName = parameter[1]; + var local_conversionId = parameter[2]; + stopTimer = false; + timedLoadingStatusLogger(); + d3.xhr(relativePath, "application/json", function ( error, request ){ + var loadingSuccessful = !error; + // check if error occurred or responseText is empty + if ( (error !== null && error.status === 500) || (request && request.responseText.length === 0) ) { + clearTimeout(loadingStatusTimer); + stopTimer = true; + loadingSuccessful = false; + console.log(request); + console.log(request.responseText.length); + getLoadingStatusOnceCallBacked(callbackFromJSON_URL_ERROR, [error, request, local_conversionId]); + } + if ( loadingSuccessful ) { + clearTimeout(loadingStatusTimer); + stopTimer = true; + var jsonText = request.responseText; + getLoadingStatusOnceCallBacked(callbackFromJSON_Success, [jsonText, ontoName, local_conversionId]); + } + }); + }; + + function callbackFromJSON_Success( parameter ){ + var local_conversionId = parameter[2]; + if ( local_conversionId !== conversion_sessionId ) { + console.log("The conversion process for file:" + parameter[1] + " has been canceled!"); + return; + } + loadingModule.loadFromOWL2VOWL(parameter[0], parameter[1]); + } + + function callbackFromJSON_URL_ERROR( parameter ){ + var error = parameter[0]; + var request = parameter[1]; + var local_conversionId = parameter[2]; + if ( local_conversionId !== conversion_sessionId ) { + console.log("This thread has been canceled!!"); + ontologyMenu.conversionFinished(local_conversionId); + return; + } + callbackUpdateLoadingMessage("
    Failed to convert the file. " + + " Ontology could not be loaded.
    Is it a valid OWL ontology? Please check with OWL Validator"); + + if ( error !== null && error.status === 500 ) { + append_message("Could not find ontology at the URL"); + } + if ( request && request.responseText.length === 0 ) { + append_message("Received empty graph"); + } + graph.handleOnLoadingError(); + ontologyMenu.conversionFinished(); + } + + + function callbackFromIRI_URL_ERROR( parameter ){ + var error = parameter[0]; + var request = parameter[1]; + var local_conversionId = parameter[2]; + if ( local_conversionId !== conversion_sessionId ) { + console.log("This thread has been canceled!!"); + ontologyMenu.conversionFinished(local_conversionId); + return; + } + callbackUpdateLoadingMessage("
    Failed to convert the file. " + + " Ontology could not be loaded.
    Is it a valid OWL ontology? Please check with OWL Validator"); + + if ( error !== null && error.status === 500 ) { + append_message("Could not find ontology at the URL"); + } + if ( request && request.responseText.length === 0 ) { + append_message("Received empty graph"); + } + graph.handleOnLoadingError(); + ontologyMenu.conversionFinished(); + } + + function callbackFromDirectInput_ERROR( parameter ){ + + var error = parameter[0]; + var request = parameter[1]; + var local_conversionId = parameter[2]; + if ( local_conversionId !== conversion_sessionId ) { + console.log("The loading process for direct input has been canceled!"); + return; + } + // callbackUpdateLoadingMessage("
    Failed to convert the file. "+ + // "Ontology could not be loaded.
    Is it a valid OWL ontology? Please check with OWL Validator"); + if ( error !== null && error.status === 500 ) { + append_message("Could not convert direct input"); + } + if ( request && request.responseText.length === 0 ) { + append_message("Received empty graph"); + } + + graph.handleOnLoadingError(); + ontologyMenu.conversionFinished(); + } + + ontologyMenu.callbackLoadFromOntology = function ( selectedFile, filename, local_threadId ){ + callbackLoadFromOntology(selectedFile, filename, local_threadId); + }; + + function callbackLoadFromOntology( selectedFile, filename, local_threadId ){ + stopTimer = false; + timedLoadingStatusLogger(); + + var formData = new FormData(); + formData.append("ontology", selectedFile); + formData.append("sessionId", local_threadId); + var xhr = new XMLHttpRequest(); + + xhr.open("POST", "convert", true); + xhr.onload = function (){ + clearTimeout(loadingStatusTimer); + stopTimer = true; + console.log(xhr); + getLoadingStatusOnceCallBacked(callbackForConvert, [xhr, filename, local_threadId]); + }; + timedLoadingStatusLogger(); + xhr.send(formData); + } + + function callbackForConvert( parameter ){ + var xhr = parameter[0]; + var filename = parameter[1]; + var local_threadId = parameter[2]; + if ( local_threadId !== conversion_sessionId ) { + console.log("The conversion process for file:" + filename + " has been canceled!"); + ontologyMenu.conversionFinished(local_threadId); + return; + } + if ( xhr.status === 200 ) { + loadingModule.loadFromOWL2VOWL(xhr.responseText, filename); + ontologyMenu.conversionFinished(); + } else { + var uglyJson=xhr.responseText; + var jsonResut=JSON.parse(uglyJson); + var niceJSON=JSON.stringify(jsonResut, 'null', ' '); + niceJSON= niceJSON.replace(new RegExp('\r?\n','g'), '
    '); + callbackUpdateLoadingMessage("Failed to convert the file. " + + "
    Server answer:
    "+ + "
    "+niceJSON+ "
    "+ + "Ontology could not be loaded.
    Is it a valid OWL ontology? Please check with OWL Validator"); + + graph.handleOnLoadingError(); + ontologyMenu.conversionFinished(); + } + } + + ontologyMenu.conversionFinished = function ( id ){ + var local_id = conversion_sessionId; + if ( id ) { + local_id = id; + } + d3.xhr("conversionDone?sessionId=" + local_id, "application/text", function ( error, request ){ + if ( error ) { + console.log("ontologyMenu conversionFinished throws error"); + console.log("---------Error -----------"); + console.log(error); + console.log("---------Request -----------"); + console.log(request); + } + }); + }; + + function keepOntologySelectionOpenShortly(){ + // Events in the menu should not be considered + var ontologySelection = d3.select("#select .toolTipMenu"); + ontologySelection.on("click", function (){ + d3.event.stopPropagation(); + }).on("keydown", function (){ + d3.event.stopPropagation(); + }); + + ontologySelection.style("display", "block"); + + function disableKeepingOpen(){ + ontologySelection.style("display", undefined); + + clearTimeout(ontologyMenuTimeout); + d3.select(window).on("click", undefined).on("keydown", undefined); + ontologySelection.on("mouseover", undefined); + } + + // Clear the timeout to handle fast calls of this function + clearTimeout(ontologyMenuTimeout); + ontologyMenuTimeout = setTimeout(function (){ + disableKeepingOpen(); + }, 3000); + + // Disable forced open selection on interaction + d3.select(window).on("click", function (){ + disableKeepingOpen(); + }).on("keydown", function (){ + disableKeepingOpen(); + }); + + ontologySelection.on("mouseover", function (){ + disableKeepingOpen(); + }); + } + + ontologyMenu.showLoadingStatus = function ( visible ){ + if ( visible === true ) { + displayLoadingIndicators(); + } + else { + hideLoadingInformations(); + } + }; + + function displayLoadingIndicators(){ + d3.select("#layoutLoadingProgressBarContainer").classed("hidden", false); + loadingInfo.classed("hidden", false); + loadingProgress.classed("hidden", false); + } + + function hideLoadingInformations(){ + loadingInfo.classed("hidden", true); + } + + return ontologyMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 330: +/***/ (function(module, exports, __webpack_require__) { + + var toString = __webpack_require__(219), + unescapeHtmlChar = __webpack_require__(331); + + /** Used to match HTML entities and HTML characters. */ + var reEscapedHtml = /&(?:amp|lt|gt|quot|#39);/g, + reHasEscapedHtml = RegExp(reEscapedHtml.source); + + /** + * The inverse of `_.escape`; this method converts the HTML entities + * `&`, `<`, `>`, `"`, and `'` in `string` to + * their corresponding characters. + * + * **Note:** No other HTML entities are unescaped. To unescape additional + * HTML entities use a third-party library like [_he_](https://mths.be/he). + * + * @static + * @memberOf _ + * @since 0.6.0 + * @category String + * @param {string} [string=''] The string to unescape. + * @returns {string} Returns the unescaped string. + * @example + * + * _.unescape('fred, barney, & pebbles'); + * // => 'fred, barney, & pebbles' + */ + function unescape(string) { + string = toString(string); + return (string && reHasEscapedHtml.test(string)) + ? string.replace(reEscapedHtml, unescapeHtmlChar) + : string; + } + + module.exports = unescape; + + +/***/ }), + +/***/ 331: +/***/ (function(module, exports, __webpack_require__) { + + var basePropertyOf = __webpack_require__(332); + + /** Used to map HTML entities to characters. */ + var htmlUnescapes = { + '&': '&', + '<': '<', + '>': '>', + '"': '"', + ''': "'" + }; + + /** + * Used by `_.unescape` to convert HTML entities to characters. + * + * @private + * @param {string} chr The matched character to unescape. + * @returns {string} Returns the unescaped character. + */ + var unescapeHtmlChar = basePropertyOf(htmlUnescapes); + + module.exports = unescapeHtmlChar; + + +/***/ }), + +/***/ 332: +/***/ (function(module, exports) { + + /** + * The base implementation of `_.propertyOf` without support for deep paths. + * + * @private + * @param {Object} object The object to query. + * @returns {Function} Returns the new accessor function. + */ + function basePropertyOf(object) { + return function(key) { + return object == null ? undefined : object[key]; + }; + } + + module.exports = basePropertyOf; + + +/***/ }), + +/***/ 333: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for the pause and resume button. + * + * @param graph the associated webvowl graph + * @returns {{}} + */ + module.exports = function ( graph ){ + + var pauseMenu = {}, + pauseButton; + + + /** + * Adds the pause button to the website. + */ + pauseMenu.setup = function (){ + var menuEntry = d3.select("#pauseOption"); + menuEntry.on("mouseover", function (){ + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + }); + pauseButton = d3.select("#pause-button") + .datum({ paused: false }) + .on("click", function ( d ){ + graph.paused(!d.paused); + d.paused = !d.paused; + updatePauseButton(); + pauseButton.classed("highlighted", d.paused); + }); + // Set these properties the first time manually + updatePauseButton(); + }; + + pauseMenu.setPauseValue = function ( value ){ + pauseButton.datum().paused = value; + graph.paused(value); + pauseButton.classed("highlighted", value); + updatePauseButton(); + }; + + function updatePauseButton(){ + updatePauseButtonClass(); + updatePauseButtonText(); + } + + function updatePauseButtonClass(){ + pauseButton.classed("paused", function ( d ){ + return d.paused; + }); + } + + function updatePauseButtonText(){ + if ( pauseButton.datum().paused ) { + pauseButton.text("Resume"); + } else { + pauseButton.text("Pause"); + } + } + + pauseMenu.reset = function (){ + // resuming + pauseMenu.setPauseValue(false); + }; + + + return pauseMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 334: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for the reset button. + * + * @param graph the associated webvowl graph + * @returns {{}} + */ + module.exports = function ( graph ){ + + var resetMenu = {}, + options = graph.graphOptions(), + resettableModules, + untouchedOptions = webvowl.options(); + + + /** + * Adds the reset button to the website. + * @param _resettableModules modules that can be resetted + */ + resetMenu.setup = function ( _resettableModules ){ + resettableModules = _resettableModules; + d3.select("#reset-button").on("click", resetGraph); + var menuEntry = d3.select("#resetOption"); + menuEntry.on("mouseover", function (){ + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + }); + }; + + function resetGraph(){ + graph.resetSearchHighlight(); + graph.options().searchMenu().clearText(); + options.classDistance(untouchedOptions.classDistance()); + options.datatypeDistance(untouchedOptions.datatypeDistance()); + options.charge(untouchedOptions.charge()); + options.gravity(untouchedOptions.gravity()); + options.linkStrength(untouchedOptions.linkStrength()); + graph.reset(); + + resettableModules.forEach(function ( module ){ + module.reset(); + }); + + graph.updateStyle(); + } + + + return resetMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 335: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the search "engine" + * + * @param graph the associated webvowl graph + * @returns {{}} + */ + module.exports = function ( graph ){ + var searchMenu = {}, + dictionary = [], + entryNames = [], + searchLineEdit, + mergedStringsList, + mergedIdList, + maxEntries = 6, + dictionaryUpdateRequired = true, + labelDictionary, + inputText, + viewStatusOfSearchEntries = false; + + var results = []; + var resultID = []; + var c_locate = d3.select("#locateSearchResult"); + var c_search = d3.select("#c_search"); + var m_search = d3.select("#m_search"); // << dropdown container; + + + String.prototype.beginsWith = function ( string ){ + return (this.indexOf(string) === 0); + }; + + searchMenu.requestDictionaryUpdate = function (){ + dictionaryUpdateRequired = true; + // clear possible pre searched entries + var htmlCollection = m_search.node().children; + var numEntries = htmlCollection.length; + + for ( var i = 0; i < numEntries; i++ ) + htmlCollection[0].remove(); + searchLineEdit.node().value = ""; + }; + + + function updateSearchDictionary(){ + labelDictionary = graph.getUpdateDictionary(); + dictionaryUpdateRequired = false; + dictionary = []; + entryNames = []; + var idList = []; + var stringList = []; + + var i; + for ( i = 0; i < labelDictionary.length; i++ ) { + var lEntry = labelDictionary[i].labelForCurrentLanguage(); + idList.push(labelDictionary[i].id()); + stringList.push(lEntry); + // add all equivalents to the search space; + if ( labelDictionary[i].equivalents && labelDictionary[i].equivalents().length > 0 ) { + var eqs = labelDictionary[i].equivalentsString(); + var eqsLabels = eqs.split(", "); + for ( var e = 0; e < eqsLabels.length; e++ ) { + idList.push(labelDictionary[i].id()); + stringList.push(eqsLabels[e]); + } + } + } + + mergedStringsList = []; + mergedIdList = []; + var indexInStringList = -1; + var currentString; + var currentObjectId; + + for ( i = 0; i < stringList.length; i++ ) { + if ( i === 0 ) { + // just add the elements + mergedStringsList.push(stringList[i]); + mergedIdList.push([]); + mergedIdList[0].push(idList[i]); + continue; + } + else { + currentString = stringList[i]; + currentObjectId = idList[i]; + indexInStringList = mergedStringsList.indexOf(currentString); + } + if ( indexInStringList === -1 ) { + mergedStringsList.push(stringList[i]); + mergedIdList.push([]); + var lastEntry = mergedIdList.length; + mergedIdList[lastEntry - 1].push(currentObjectId); + } else { + mergedIdList[indexInStringList].push(currentObjectId); + } + } + + for ( i = 0; i < mergedStringsList.length; i++ ) { + var aString = mergedStringsList[i]; + var correspondingIdList = mergedIdList[i]; + var idListResult = "[ "; + for ( var j = 0; j < correspondingIdList.length; j++ ) { + idListResult = idListResult + correspondingIdList[j].toString(); + idListResult = idListResult + ", "; + } + idListResult = idListResult.substring(0, idListResult.length - 2); + idListResult = idListResult + " ]"; + + dictionary.push(aString); + entryNames.push(aString); + } + } + + searchMenu.setup = function (){ + // clear dictionary; + dictionary = []; + searchLineEdit = d3.select("#search-input-text"); + searchLineEdit.on("input", userInput); + searchLineEdit.on("keydown", userNavigation); + searchLineEdit.on("click", toggleSearchEntryView); + searchLineEdit.on("mouseover", hoverSearchEntryView); + + c_locate.on("click", function (){ + graph.locateSearchResult(); + }); + + c_locate.on("mouseover", function (){ + searchMenu.hideSearchEntries(); + }); + + }; + + function hoverSearchEntryView(){ + updateSelectionStatusFlags(); + searchMenu.showSearchEntries(); + } + + function toggleSearchEntryView(){ + if ( viewStatusOfSearchEntries ) { + searchMenu.hideSearchEntries(); + } else { + searchMenu.showSearchEntries(); + } + } + + searchMenu.hideSearchEntries = function (){ + m_search.style("display", "none"); + viewStatusOfSearchEntries = false; + }; + + searchMenu.showSearchEntries = function (){ + m_search.style("display", "block"); + viewStatusOfSearchEntries = true; + }; + + function ValidURL( str ){ + var urlregex = /^(https?|ftp):\/\/([a-zA-Z0-9.-]+(:[a-zA-Z0-9.&%$-]+)*@)*((25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9][0-9]?)(\.(25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9]?[0-9])){3}|([a-zA-Z0-9-]+\.)*[a-zA-Z0-9-]+\.(com|edu|gov|int|mil|net|org|biz|arpa|info|name|pro|aero|coop|museum|[a-zA-Z]{2}))(:[0-9]+)*(\/($|[a-zA-Z0-9.,?'\\+&%$#=~_-]+))*$/; + return urlregex.test(str); + + } + + + function updateSelectionStatusFlags(){ + if ( searchLineEdit.node().value.length === 0 ) { + createSearchEntries(); + return; + } + handleAutoCompletion(); + } + + function userNavigation(){ + if ( dictionaryUpdateRequired ) { + updateSearchDictionary(); + } + + var htmlCollection = m_search.node().children; + var numEntries = htmlCollection.length; + + + var move = 0; + var i; + var selectedEntry = -1; + for ( i = 0; i < numEntries; i++ ) { + var atr = htmlCollection[i].getAttribute('class'); + if ( atr === "dbEntrySelected" ) { + selectedEntry = i; + } + } + if ( d3.event.keyCode === 13 ) { + if ( selectedEntry >= 0 && selectedEntry < numEntries ) { + // simulate onClick event + htmlCollection[selectedEntry].onclick(); + searchMenu.hideSearchEntries(); + } + else if ( numEntries === 0 ) { + inputText = searchLineEdit.node().value; + // check if input text ends or begins with with space + // remove first spaces + var clearedText = inputText.replace(/%20/g, " "); + while ( clearedText.beginsWith(" ") ) { + clearedText = clearedText.substr(1, clearedText.length); + } + // remove ending spaces + while ( clearedText.endsWith(" ") ) { + clearedText = clearedText.substr(0, clearedText.length - 1); + } + var iri = clearedText.replace(/ /g, "%20"); + + var valid = ValidURL(iri); + // validate url: + if ( valid ) { + var ontM = graph.options().ontologyMenu(); + ontM.setIriText(iri); + searchLineEdit.node().value = ""; + } + else { + console.log(iri + " is not a valid URL!"); + } + } + } + if ( d3.event.keyCode === 38 ) { + move = -1; + searchMenu.showSearchEntries(); + } + if ( d3.event.keyCode === 40 ) { + move = +1; + searchMenu.showSearchEntries(); + } + + var newSelection = selectedEntry + move; + if ( newSelection !== selectedEntry ) { + + if ( newSelection < 0 && selectedEntry <= 0 ) { + htmlCollection[0].setAttribute('class', "dbEntrySelected"); + } + + if ( newSelection >= numEntries ) { + htmlCollection[selectedEntry].setAttribute('class', "dbEntrySelected"); + } + if ( newSelection >= 0 && newSelection < numEntries ) { + htmlCollection[newSelection].setAttribute('class', "dbEntrySelected"); + if ( selectedEntry >= 0 ) + htmlCollection[selectedEntry].setAttribute('class', "dbEntry"); + } + } + } + + searchMenu.getSearchString = function (){ + return searchLineEdit.node().value; + }; + + + function clearSearchEntries(){ + var htmlCollection = m_search.node().children; + var numEntries = htmlCollection.length; + for ( var i = 0; i < numEntries; i++ ) { + htmlCollection[0].remove(); + } + results = []; + resultID = []; + + } + + function createSearchEntries(){ + inputText = searchLineEdit.node().value; + var i; + var lc_text = inputText.toLowerCase(); + var token; + + for ( i = 0; i < dictionary.length; i++ ) { + var tokenElement = dictionary[i]; + if ( tokenElement === undefined ) { + //@WORKAROUND : nodes with undefined labels are skipped + //@FIX: these nodes are now not added to the dictionary + continue; + } + token = dictionary[i].toLowerCase(); + if ( token.indexOf(lc_text) > -1 ) { + results.push(dictionary[i]); + resultID.push(i); + } + } + } + + function measureTextWidth( text, textStyle ){ + // Set a default value + if ( !textStyle ) { + textStyle = "text"; + } + var d = d3.select("body") + .append("div") + .attr("class", textStyle) + .attr("id", "width-test") // tag this element to identify it + .attr("style", "position:absolute; float:left; white-space:nowrap; visibility:hidden;") + .text(text), + w = document.getElementById("width-test").offsetWidth; + d.remove(); + return w; + } + + function cropText( input ){ + var maxWidth = 250; + var textStyle = "dbEntry"; + var truncatedText = input; + var textWidth; + var ratio; + var newTruncatedTextLength; + while ( true ) { + textWidth = measureTextWidth(truncatedText, textStyle); + if ( textWidth <= maxWidth ) { + break; + } + + ratio = textWidth / maxWidth; + newTruncatedTextLength = Math.floor(truncatedText.length / ratio); + + // detect if nothing changes + if ( truncatedText.length === newTruncatedTextLength ) { + break; + } + + truncatedText = truncatedText.substring(0, newTruncatedTextLength); + } + + if ( input.length > truncatedText.length ) { + return input.substring(0, truncatedText.length - 6); + } + return input; + } + + function createDropDownElements(){ + var numEntries; + var copyRes = results; + var i; + var token; + var newResults = []; + var newResultsIds = []; + + var lc_text = searchLineEdit.node().value.toLowerCase(); + // set the number of shown results to be maxEntries or less; + numEntries = results.length; + if ( numEntries > maxEntries ) + numEntries = maxEntries; + + + for ( i = 0; i < numEntries; i++ ) { + // search for the best entry + var indexElement = 1000000; + var lengthElement = 1000000; + var bestElement = -1; + for ( var j = 0; j < copyRes.length; j++ ) { + token = copyRes[j].toLowerCase(); + var tIe = token.indexOf(lc_text); + var tLe = token.length; + if ( tIe > -1 && tIe <= indexElement && tLe <= lengthElement ) { + bestElement = j; + indexElement = tIe; + lengthElement = tLe; + } + } + newResults.push(copyRes[bestElement]); + newResultsIds.push(resultID[bestElement]); + copyRes[bestElement] = ""; + } + + // add the results to the entry menu + //****************************************** + numEntries = results.length; + if ( numEntries > maxEntries ) + numEntries = maxEntries; + + var filteredOutElements = 0; + for ( i = 0; i < numEntries; i++ ) { + //add results to the dropdown menu + var testEntry = document.createElement('li'); + testEntry.setAttribute('elementID', newResultsIds[i]); + testEntry.onclick = handleClick(newResultsIds[i]); + testEntry.setAttribute('class', "dbEntry"); + + var entries = mergedIdList[newResultsIds[i]]; + var eLen = entries.length; + + var croppedText = cropText(newResults[i]); + + var el0 = entries[0]; + var allSame = true; + var nodeMap = graph.getNodeMapForSearch(); + var visible = eLen; + if ( eLen > 1 ) { + for ( var q = 0; q < eLen; q++ ) { + if ( nodeMap[entries[q]] === undefined ) { + visible--; + } + } + } + + for ( var a = 0; a < eLen; a++ ) { + if ( el0 !== entries[a] ) { + allSame = false; + } + } + if ( croppedText !== newResults[i] ) { + // append ...(#numElements) if needed + if ( eLen > 1 && allSame === false ) { + if ( eLen !== visible ) + croppedText += "... (" + visible + "/" + eLen + ")"; + } + else { + croppedText += "..."; + } + testEntry.title = newResults[i]; + } + else { + if ( eLen > 1 && allSame === false ) { + if ( eLen !== visible ) + croppedText += " (" + visible + "/" + eLen + ")"; + else + croppedText += " (" + eLen + ")"; + } + } + + var searchEntryNode = d3.select(testEntry); + if ( eLen === 1 || allSame === true ) { + if ( nodeMap[entries[0]] === undefined ) { + searchEntryNode.style("color", "#979797"); + testEntry.title = newResults[i] + "\nElement is filtered out."; + testEntry.onclick = function (){ + }; + d3.select(testEntry).style("cursor", "default"); + filteredOutElements++; + } + } else { + if ( visible < 1 ) { + searchEntryNode.style("color", "#979797"); + testEntry.onclick = function (){ + }; + testEntry.title = newResults[i] + "\nAll elements are filtered out."; + d3.select(testEntry).style("cursor", "default"); + filteredOutElements++; + } else { + searchEntryNode.style("color", ""); + } + if ( visible < eLen && visible > 1 ) { + testEntry.title = newResults[i] + "\n" + visible + "/" + eLen + " elements are visible."; + } + } + searchEntryNode.node().innerHTML = croppedText; + m_search.node().appendChild(testEntry); + } + } + + + function handleAutoCompletion(){ + /** pre condition: autoCompletion has already a valid text**/ + clearSearchEntries(); + createSearchEntries(); + createDropDownElements(); + } + + function userInput(){ + c_locate.classed("highlighted", false); + c_locate.node().title = "Nothing to locate"; + + if ( dictionaryUpdateRequired ) { + updateSearchDictionary(); + } + graph.resetSearchHighlight(); + + if ( dictionary.length === 0 ) { + console.log("dictionary is empty"); + return; + } + inputText = searchLineEdit.node().value; + + clearSearchEntries(); + if ( inputText.length !== 0 ) { + createSearchEntries(); + createDropDownElements(); + } + + searchMenu.showSearchEntries(); + } + + function handleClick( elementId ){ + + return function (){ + var id = elementId; + var correspondingIds = mergedIdList[id]; + + // autoComplete the text for the user + var autoComStr = entryNames[id]; + searchLineEdit.node().value = autoComStr; + + graph.resetSearchHighlight(); + graph.highLightNodes(correspondingIds); + c_locate.node().title = "Locate search term"; + if ( autoComStr !== inputText ) { + handleAutoCompletion(); + } + searchMenu.hideSearchEntries(); + }; + } + + searchMenu.clearText = function (){ + searchLineEdit.node().value = ""; + c_locate.classed("highlighted", false); + c_locate.node().title = "Nothing to locate"; + var htmlCollection = m_search.node().children; + var numEntries = htmlCollection.length; + for ( var i = 0; i < numEntries; i++ ) { + htmlCollection[0].remove(); + } + }; + + return searchMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 336: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the navigation "engine" + * + * @param graph the associated webvowl graph + * @returns {{}} + */ + module.exports = function ( graph ){ + var navigationMenu = {}, + scrollContainer = d3.select("#menuElementContainer").node(), + menuContainer = d3.select("#menuContainer").node(), + leftButton = d3.select("#scrollLeftButton"), + rightButton = d3.select("#scrollRightButton"), + scrolLeftValue, + scrollMax, + currentlyVisibleMenu, + currentlyHoveredEntry, + touchedElement = false, + t_scrollLeft, + t_scrollRight, + c_select = [], + m_select = []; + + + function clearAllTimers(){ + cancelAnimationFrame(t_scrollLeft); + cancelAnimationFrame(t_scrollRight); + } + + function timed_scrollRight(){ + scrolLeftValue += 5; + scrollContainer.scrollLeft = scrolLeftValue; + navigationMenu.updateScrollButtonVisibility(); + if ( scrolLeftValue >= scrollMax ) { + clearAllTimers(); + return; + } + t_scrollRight = requestAnimationFrame(timed_scrollRight); + + } + + function timed_scrollLeft(){ + scrolLeftValue -= 5; + scrollContainer.scrollLeft = scrolLeftValue; + navigationMenu.updateScrollButtonVisibility(); + if ( scrolLeftValue <= 0 ) { + clearAllTimers(); + return; + } + t_scrollRight = requestAnimationFrame(timed_scrollLeft); + } + + // collect all menu entries and stuff; + function setupControlsAndMenus(){ + // HEURISTIC : to match the menus and their controllers we remove the first 2 letters and match + c_select = []; + m_select = []; + + var c_temp = []; + var m_temp = []; + var i; + var controlElements = scrollContainer.children; + var numEntries = controlElements.length; + + for ( i = 0; i < numEntries; i++ ) { + c_temp.push(controlElements[i].id.slice(2)); + } + + var menuElements = menuContainer.children; + numEntries = menuElements.length; + for ( i = 0; i < numEntries; i++ ) { + m_temp.push(menuElements[i].id.slice(2)); + } + + numEntries = controlElements.length; + for ( i = 0; i < numEntries; i++ ) { + c_select[i] = "c_" + c_temp[i]; + if ( m_temp.indexOf(c_temp[i]) > -1 ) { + m_select[i] = "m_" + c_temp[i]; + } else { + m_select[i] = undefined; + } + // create custom behavior for click, touch, and hover + d3.select("#" + c_select[i]).on("mouseover", menuElementOnHovered); + d3.select("#" + c_select[i]).on("mouseout", menuElementOutHovered); + + d3.select("#" + c_select[i]).on("click", menuElementClicked); + d3.select("#" + c_select[i]).on("touchstart", menuElementTouched); + + } + + // connect to mouseWheel + d3.select("#menuElementContainer").on("wheel", function (){ + var wheelEvent = d3.event; + var offset; + if ( wheelEvent.deltaY < 0 ) offset = 20; + if ( wheelEvent.deltaY > 0 ) offset = -20; + scrollContainer.scrollLeft += offset; + navigationMenu.hideAllMenus(); + navigationMenu.updateScrollButtonVisibility(); + }); + + // connect scrollIndicator Buttons; + d3.select("#scrollRightButton").on("mousedown", function (){ + scrolLeftValue = scrollContainer.scrollLeft; + navigationMenu.hideAllMenus(); + t_scrollRight = requestAnimationFrame(timed_scrollRight); + + }).on("touchstart", function (){ + scrolLeftValue = scrollContainer.scrollLeft; + navigationMenu.hideAllMenus(); + t_scrollRight = requestAnimationFrame(timed_scrollRight); + }).on("mouseup", clearAllTimers) + .on("touchend", clearAllTimers) + .on("touchcancel", clearAllTimers); + + d3.select("#scrollLeftButton").on("mousedown", function (){ + scrolLeftValue = scrollContainer.scrollLeft; + navigationMenu.hideAllMenus(); + t_scrollLeft = requestAnimationFrame(timed_scrollLeft); + }).on("touchstart", function (){ + scrolLeftValue = scrollContainer.scrollLeft; + navigationMenu.hideAllMenus(); + t_scrollLeft = requestAnimationFrame(timed_scrollLeft); + }).on("mouseup", clearAllTimers) + .on("touchend", clearAllTimers) + .on("touchcancel", clearAllTimers); + + // connect the scroll functionality; + d3.select("#menuElementContainer").on("scroll", function (){ + navigationMenu.updateScrollButtonVisibility(); + navigationMenu.hideAllMenus(); + }); + } + + function menuElementOnHovered(){ + navigationMenu.hideAllMenus(); + if ( touchedElement ) { + return; + } + showSingleMenu(this.id); + } + + function menuElementOutHovered(){ + hoveroutedControMenu(this.id); + } + + function menuElementClicked(){ + var m_element = m_select[c_select.indexOf(this.id)]; + if ( m_element ) { + var menuElement = d3.select("#" + m_element); + if ( menuElement ) { + if ( menuElement.style("display") === "block" ) { + menuElement.style("display", "none");// hide it + } else { + showSingleMenu(this.id); + } + } + } + } + + function menuElementTouched(){ + // it sets a flag that we have touched it, + // since d3. propagates the event for touch as hover and then click, we block the hover event + touchedElement = true; + } + + + function hoveroutedControMenu( controllerID ){ + currentlyHoveredEntry = d3.select("#" + controllerID); + if ( controllerID !== "c_search" ) { + d3.select("#" + controllerID).select("path").style("stroke-width", "0"); + d3.select("#" + controllerID).select("path").style("fill", "#fff"); + } + + } + + function showSingleMenu( controllerID ){ + currentlyHoveredEntry = d3.select("#" + controllerID).node(); + // get the corresponding menu element for this controller + var m_element = m_select[c_select.indexOf(controllerID)]; + if ( m_element ) { + if ( controllerID !== "c_search" ) { + + d3.select("#" + controllerID).select("path").style("stroke-width", "0"); + d3.select("#" + controllerID).select("path").style("fill", "#bdc3c7"); + } + // show it if we have a menu + currentlyVisibleMenu = d3.select("#" + m_element); + currentlyVisibleMenu.style("display", "block"); + if ( m_element === "m_export" ) + graph.options().exportMenu().exportAsUrl(); + updateMenuPosition(); + } + } + + function updateMenuPosition(){ + if ( currentlyHoveredEntry ) { + var leftOffset = currentlyHoveredEntry.offsetLeft; + var scrollOffset = scrollContainer.scrollLeft; + var totalOffset = leftOffset - scrollOffset; + var finalOffset = Math.max(0, totalOffset); + var fullContainer_width = scrollContainer.getBoundingClientRect().width; + var elementWidth = currentlyVisibleMenu.node().getBoundingClientRect().width; + // make priority > first check if we are right + if ( finalOffset + elementWidth > fullContainer_width ) { + finalOffset = fullContainer_width - elementWidth; + } + // fix priority; + finalOffset = Math.max(0, finalOffset); + currentlyVisibleMenu.style("left", finalOffset + "px"); + + // // check if outside the viewport + // var menuWidth=currentlyHoveredEntry.getBoundingClientRect().width; + // var bt_width=36; + // if (totalOffset+menuWidthfullContainer_width){ + // navigationMenu.hideAllMenus(); + // currentlyHoveredEntry=undefined; + // } + } + } + + navigationMenu.hideAllMenus = function (){ + d3.selectAll(".toolTipMenu").style("display", "none"); // hiding all menus + }; + + navigationMenu.updateScrollButtonVisibility = function (){ + scrollMax = scrollContainer.scrollWidth - scrollContainer.clientWidth - 2; + if ( scrollContainer.scrollLeft === 0 ) { + leftButton.classed("hidden", true); + } else { + leftButton.classed("hidden", false); + } + + if ( scrollContainer.scrollLeft > scrollMax ) { + rightButton.classed("hidden", true); + } else { + rightButton.classed("hidden", false); + } + + }; + + navigationMenu.setup = function (){ + setupControlsAndMenus(); + // make sure that the menu elements follow their controller and also their restrictions + // some hovering behavior -- lets the menu disappear when hovered in graph or sidebar; + d3.select("#graph").on("mouseover", function (){ + navigationMenu.hideAllMenus(); + }); + d3.select("#generalDetails").on("mouseover", function (){ + navigationMenu.hideAllMenus(); + }); + }; + + return navigationMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 337: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** The zoom Slider **/ + module.exports = function ( graph ){ + var zoomSlider = {}; + var minMag = graph.options().minMagnification(), + maxMag = graph.options().maxMagnification(), + defZoom, + t_zoomOut, + t_zoomIn, + zoomValue, + showSlider = true, + w = graph.options().width(), + h = graph.options().height(), + slider; + + defZoom = Math.min(w, h) / 1000; + + function clearAllTimers(){ + cancelAnimationFrame(t_zoomOut); + cancelAnimationFrame(t_zoomIn); + } + + function timed_zoomOut(){ + zoomValue = 0.98 * zoomValue; + // fail saves + if ( zoomValue < minMag ) { + zoomValue = minMag; + } + graph.setSliderZoom(zoomValue); + t_zoomOut = requestAnimationFrame(timed_zoomOut); + } + + function timed_zoomIn(){ + zoomValue = 1.02 * zoomValue; + // fail saves + if ( zoomValue > maxMag ) { + zoomValue = maxMag; + } + graph.setSliderZoom(zoomValue); + t_zoomIn = requestAnimationFrame(timed_zoomIn); + } + + zoomSlider.setup = function (){ + slider = d3.select("#zoomSliderParagraph").append("input") + .datum({}) + .attr("id", "zoomSliderElement") + .attr("type", "range") + .attr("value", defZoom) + .attr("min", minMag) + .attr("max", maxMag) + .attr("step", (maxMag - minMag) / 40) + .attr("title", "zoom factor") + .on("input", function (){ + zoomSlider.zooming(); + }); + + d3.select("#zoomOutButton").on("mousedown", function (){ + graph.options().navigationMenu().hideAllMenus(); + zoomValue = graph.scaleFactor(); + t_zoomOut = requestAnimationFrame(timed_zoomOut); + }) + .on("touchstart", function (){ + graph.options().navigationMenu().hideAllMenus(); + zoomValue = graph.scaleFactor(); + t_zoomOut = requestAnimationFrame(timed_zoomOut); + }) + .on("mouseup", clearAllTimers) + .on("touchend", clearAllTimers) + .on("touchcancel", clearAllTimers) + .attr("title", "zoom out"); + + d3.select("#zoomInButton").on("mousedown", function (){ + graph.options().navigationMenu().hideAllMenus(); + zoomValue = graph.scaleFactor(); + t_zoomIn = requestAnimationFrame(timed_zoomIn); + }) + .on("touchstart", function (){ + graph.options().navigationMenu().hideAllMenus(); + zoomValue = graph.scaleFactor(); + t_zoomIn = requestAnimationFrame(timed_zoomIn); + }) + .on("mouseup", clearAllTimers) + .on("touchend", clearAllTimers) + .on("touchcancel", clearAllTimers) + .attr("title", "zoom in"); + + d3.select("#centerGraphButton").on("click", function (){ + graph.options().navigationMenu().hideAllMenus(); + graph.forceRelocationEvent(); + }).attr("title", "center graph"); + + }; + + zoomSlider.showSlider = function ( val ){ + if ( !arguments.length ) return showSlider; + d3.select("#zoomSlider").classed("hidden", !val); + showSlider = val; + }; + + zoomSlider.zooming = function (){ + graph.options().navigationMenu().hideAllMenus(); + var zoomValue = slider.property("value"); + slider.attr("value", zoomValue); + graph.setSliderZoom(zoomValue); + }; + + zoomSlider.updateZoomSliderValue = function ( val ){ + if ( slider ) { + slider.attr("value", val); + slider.property("value", val); + } + }; + + return zoomSlider; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 338: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for the sidebar. + * @param graph the graph that belongs to these controls + * @returns {{}} + */ + module.exports = function ( graph ){ + + var sidebar = {}, + languageTools = webvowl.util.languageTools(), + elementTools = webvowl.util.elementTools(), + // Required for reloading when the language changes + ontologyInfo, + visibleSidebar = 1, + lastSelectedElement, + + detailArea = d3.select("#detailsArea"), + graphArea = d3.select("#canvasArea"), + menuArea = d3.select("#swipeBarContainer"), + collapseButton = d3.select("#sidebarExpandButton"); + + /** + * Setup the menu bar. + */ + + + function setupCollapsing(){ + // adapted version of this example: http://www.normansblog.de/simple-jquery-accordion/ + function collapseContainers( containers ){ + containers.classed("hidden", true); + } + + function expandContainers( containers ){ + containers.classed("hidden", false); + } + + var triggers = d3.selectAll(".accordion-trigger"); + + // Collapse all inactive triggers on startup + collapseContainers(d3.selectAll(".accordion-trigger:not(.accordion-trigger-active) + div")); + + triggers.on("click", function (){ + var selectedTrigger = d3.select(this), + activeTriggers = d3.selectAll(".accordion-trigger-active"); + + if ( selectedTrigger.classed("accordion-trigger-active") ) { + // Collapse the active (which is also the selected) trigger + collapseContainers(d3.select(selectedTrigger.node().nextElementSibling)); + selectedTrigger.classed("accordion-trigger-active", false); + } else { + // Collapse the other trigger ... + collapseContainers(d3.selectAll(".accordion-trigger-active + div")); + activeTriggers.classed("accordion-trigger-active", false); + // ... and expand the selected one + expandContainers(d3.select(selectedTrigger.node().nextElementSibling)); + selectedTrigger.classed("accordion-trigger-active", true); + } + }); + } + + sidebar.clearOntologyInformation = function (){ + + d3.select("#title").text("No title available"); + d3.select("#about").attr("href", "#").attr("target", "_blank").text("not given"); + d3.select("#version").text("--"); + d3.select("#authors").text("--"); + d3.select("#description").text("No description available."); + var container = d3.select("#ontology-metadata"); + container.selectAll("*").remove(); + d3.select("#classCount") + .text("0"); + d3.select("#objectPropertyCount") + .text("0"); + d3.select("#datatypePropertyCount") + .text("0"); + d3.select("#individualCount") + .text("0"); + d3.select("#nodeCount") + .text("0"); + d3.select("#edgeCount") + .text("0"); + + // clear selectedNode info + var isTriggerActive = d3.select("#selection-details-trigger").classed("accordion-trigger-active"); + if ( isTriggerActive ) { + // close accordion + d3.select("#selection-details-trigger").node().click(); + } + showSelectionAdvice(); + + }; + + /** + * Updates the information of the passed ontology. + * @param data the graph data + * @param statistics the statistics module + */ + sidebar.updateOntologyInformation = function ( data, statistics ){ + data = data || {}; + ontologyInfo = data.header || {}; + + updateGraphInformation(); + displayGraphStatistics(undefined, statistics); + displayMetadata(ontologyInfo.other); + + // Reset the sidebar selection + sidebar.updateSelectionInformation(undefined); + + setLanguages(ontologyInfo.languages); + }; + + function setLanguages( languages ){ + languages = languages || []; + + // Put the default and unset label on top of the selection labels + languages.sort(function ( a, b ){ + if ( a === webvowl.util.constants().LANG_IRIBASED ) { + return -1; + } else if ( b === webvowl.util.constants().LANG_IRIBASED ) { + return 1; + } + if ( a === webvowl.util.constants().LANG_UNDEFINED ) { + return -1; + } else if ( b === webvowl.util.constants().LANG_UNDEFINED ) { + return 1; + } + return a.localeCompare(b); + }); + + var languageSelection = d3.select("#language") + .on("change", function (){ + graph.language(d3.event.target.value); + updateGraphInformation(); + sidebar.updateSelectionInformation(lastSelectedElement); + }); + + languageSelection.selectAll("option").remove(); + languageSelection.selectAll("option") + .data(languages) + .enter().append("option") + .attr("value", function ( d ){ + return d; + }) + .text(function ( d ){ + return d; + }); + + if ( !trySelectDefaultLanguage(languageSelection, languages, "en") ) { + if ( !trySelectDefaultLanguage(languageSelection, languages, webvowl.util.constants().LANG_UNDEFINED) ) { + trySelectDefaultLanguage(languageSelection, languages, webvowl.util.constants().LANG_IRIBASED); + } + } + } + + function trySelectDefaultLanguage( selection, languages, language ){ + var langIndex = languages.indexOf(language); + if ( langIndex >= 0 ) { + selection.property("selectedIndex", langIndex); + graph.language(language); + return true; + } + + return false; + } + + function updateGraphInformation(){ + var title = languageTools.textInLanguage(ontologyInfo.title, graph.language()); + d3.select("#title").text(title || "No title available"); + d3.select("#about").attr("href", ontologyInfo.iri).attr("target", "_blank").text(ontologyInfo.iri); + d3.select("#version").text(ontologyInfo.version || "--"); + var authors = ontologyInfo.author; + if ( typeof authors === "string" ) { + // Stay compatible with author info as strings after change in january 2015 + d3.select("#authors").text(authors); + } else if ( authors instanceof Array ) { + d3.select("#authors").text(authors.join(", ")); + } else { + d3.select("#authors").text("--"); + } + + var description = languageTools.textInLanguage(ontologyInfo.description, graph.language()); + d3.select("#description").text(description || "No description available."); + } + + function displayGraphStatistics( deliveredMetrics, statistics ){ + // Metrics are optional and may be undefined + deliveredMetrics = deliveredMetrics || {}; + + d3.select("#classCount") + .text(deliveredMetrics.classCount || statistics.classCount()); + d3.select("#objectPropertyCount") + .text(deliveredMetrics.objectPropertyCount || statistics.objectPropertyCount()); + d3.select("#datatypePropertyCount") + .text(deliveredMetrics.datatypePropertyCount || statistics.datatypePropertyCount()); + d3.select("#individualCount") + .text(deliveredMetrics.totalIndividualCount || statistics.totalIndividualCount()); + d3.select("#nodeCount") + .text(statistics.nodeCount()); + d3.select("#edgeCount") + .text(statistics.edgeCount()); + } + + function displayMetadata( metadata ){ + var container = d3.select("#ontology-metadata"); + container.selectAll("*").remove(); + + listAnnotations(container, metadata); + + if ( container.selectAll(".annotation").size() <= 0 ) { + container.append("p").text("No annotations available."); + } + } + + function listAnnotations( container, annotationObject ){ + annotationObject = annotationObject || {}; //todo + + // Collect the annotations in an array for simpler processing + var annotations = []; + for ( var annotation in annotationObject ) { + if ( annotationObject.hasOwnProperty(annotation) ) { + annotations.push(annotationObject[annotation][0]); + } + } + + container.selectAll(".annotation").remove(); + container.selectAll(".annotation").data(annotations).enter().append("p") + .classed("annotation", true) + .classed("statisticDetails", true) + .text(function ( d ){ + return d.identifier + ":"; + }) + .append("span") + .each(function ( d ){ + appendIriLabel(d3.select(this), d.value, d.type === "iri" ? d.value : undefined); + }); + } + + /** + * Update the information of the selected node. + * @param selectedElement the selection or null if nothing is selected + */ + sidebar.updateSelectionInformation = function ( selectedElement ){ + lastSelectedElement = selectedElement; + + // Click event was prevented when dragging + if ( d3.event && d3.event.defaultPrevented ) { + return; + } + + var isTriggerActive = d3.select("#selection-details-trigger").classed("accordion-trigger-active"); + if ( selectedElement && !isTriggerActive ) { + d3.select("#selection-details-trigger").node().click(); + } else if ( !selectedElement && isTriggerActive ) { + showSelectionAdvice(); + return; + } + + if ( elementTools.isProperty(selectedElement) ) { + displayPropertyInformation(selectedElement); + } else if ( elementTools.isNode(selectedElement) ) { + displayNodeInformation(selectedElement); + } + }; + + function showSelectionAdvice(){ + setSelectionInformationVisibility(false, false, true); + } + + function setSelectionInformationVisibility( showClasses, showProperties, showAdvice ){ + d3.select("#classSelectionInformation").classed("hidden", !showClasses); + d3.select("#propertySelectionInformation").classed("hidden", !showProperties); + d3.select("#noSelectionInformation").classed("hidden", !showAdvice); + } + + function displayPropertyInformation( property ){ + showPropertyInformations(); + + setIriLabel(d3.select("#propname"), property.labelForCurrentLanguage(), property.iri()); + d3.select("#typeProp").text(property.type()); + + if ( property.inverse() !== undefined ) { + d3.select("#inverse").classed("hidden", false); + setIriLabel(d3.select("#inverse span"), property.inverse().labelForCurrentLanguage(), property.inverse().iri()); + } else { + d3.select("#inverse").classed("hidden", true); + } + + var equivalentIriSpan = d3.select("#propEquivUri"); + listNodeArray(equivalentIriSpan, property.equivalents()); + + listNodeArray(d3.select("#subproperties"), property.subproperties()); + listNodeArray(d3.select("#superproperties"), property.superproperties()); + + if ( property.minCardinality() !== undefined ) { + d3.select("#infoCardinality").classed("hidden", true); + d3.select("#minCardinality").classed("hidden", false); + d3.select("#minCardinality span").text(property.minCardinality()); + d3.select("#maxCardinality").classed("hidden", false); + + if ( property.maxCardinality() !== undefined ) { + d3.select("#maxCardinality span").text(property.maxCardinality()); + } else { + d3.select("#maxCardinality span").text("*"); + } + + } else if ( property.cardinality() !== undefined ) { + d3.select("#minCardinality").classed("hidden", true); + d3.select("#maxCardinality").classed("hidden", true); + d3.select("#infoCardinality").classed("hidden", false); + d3.select("#infoCardinality span").text(property.cardinality()); + } else { + d3.select("#infoCardinality").classed("hidden", true); + d3.select("#minCardinality").classed("hidden", true); + d3.select("#maxCardinality").classed("hidden", true); + } + + setIriLabel(d3.select("#domain"), property.domain().labelForCurrentLanguage(), property.domain().iri()); + setIriLabel(d3.select("#range"), property.range().labelForCurrentLanguage(), property.range().iri()); + + displayAttributes(property.attributes(), d3.select("#propAttributes")); + + setTextAndVisibility(d3.select("#propDescription"), property.descriptionForCurrentLanguage()); + setTextAndVisibility(d3.select("#propComment"), property.commentForCurrentLanguage()); + + listAnnotations(d3.select("#propertySelectionInformation"), property.annotations()); + } + + function showPropertyInformations(){ + setSelectionInformationVisibility(false, true, false); + } + + function setIriLabel( element, name, iri ){ + var parent = d3.select(element.node().parentNode); + + if ( name ) { + element.selectAll("*").remove(); + appendIriLabel(element, name, iri); + parent.classed("hidden", false); + } else { + parent.classed("hidden", true); + } + } + + function appendIriLabel( element, name, iri ){ + var tag; + + if ( iri ) { + tag = element.append("a") + .attr("href", iri) + .attr("title", iri) + .attr("target", "_blank"); + } else { + tag = element.append("span"); + } + tag.text(name); + } + + function displayAttributes( attributes, textSpan ){ + var spanParent = d3.select(textSpan.node().parentNode); + + if ( attributes && attributes.length > 0 ) { + // Remove redundant redundant attributes for sidebar + removeElementFromArray("object", attributes); + removeElementFromArray("datatype", attributes); + removeElementFromArray("rdf", attributes); + } + + if ( attributes && attributes.length > 0 ) { + textSpan.text(attributes.join(", ")); + + spanParent.classed("hidden", false); + } else { + spanParent.classed("hidden", true); + } + } + + function removeElementFromArray( element, array ){ + var index = array.indexOf(element); + if ( index > -1 ) { + array.splice(index, 1); + } + } + + function displayNodeInformation( node ){ + showClassInformations(); + + setIriLabel(d3.select("#name"), node.labelForCurrentLanguage(), node.iri()); + + /* Equivalent stuff. */ + var equivalentIriSpan = d3.select("#classEquivUri"); + listNodeArray(equivalentIriSpan, node.equivalents()); + + d3.select("#typeNode").text(node.type()); + listNodeArray(d3.select("#individuals"), node.individuals()); + + /* Disjoint stuff. */ + var disjointNodes = d3.select("#disjointNodes"); + var disjointNodesParent = d3.select(disjointNodes.node().parentNode); + + if ( node.disjointWith() !== undefined ) { + disjointNodes.selectAll("*").remove(); + + node.disjointWith().forEach(function ( element, index ){ + if ( index > 0 ) { + disjointNodes.append("span").text(", "); + } + appendIriLabel(disjointNodes, element.labelForCurrentLanguage(), element.iri()); + }); + + disjointNodesParent.classed("hidden", false); + } else { + disjointNodesParent.classed("hidden", true); + } + + displayAttributes(node.attributes(), d3.select("#classAttributes")); + + setTextAndVisibility(d3.select("#nodeDescription"), node.descriptionForCurrentLanguage()); + setTextAndVisibility(d3.select("#nodeComment"), node.commentForCurrentLanguage()); + + listAnnotations(d3.select("#classSelectionInformation"), node.annotations()); + } + + function showClassInformations(){ + setSelectionInformationVisibility(true, false, false); + } + + function listNodeArray( textSpan, nodes ){ + var spanParent = d3.select(textSpan.node().parentNode); + + if ( nodes && nodes.length ) { + textSpan.selectAll("*").remove(); + nodes.forEach(function ( element, index ){ + if ( index > 0 ) { + textSpan.append("span").text(", "); + } + appendIriLabel(textSpan, element.labelForCurrentLanguage(), element.iri()); + }); + + spanParent.classed("hidden", false); + } else { + spanParent.classed("hidden", true); + } + } + + function setTextAndVisibility( label, value ){ + var parentNode = d3.select(label.node().parentNode); + var hasValue = !!value; + if ( value ) { + label.text(value); + } + parentNode.classed("hidden", !hasValue); + } + + /** Collapsible Sidebar functions; **/ + + sidebar.showSidebar = function ( val, init ){ + // make val to bool + if ( val === 1 ) { + visibleSidebar = true; + collapseButton.node().innerHTML = ">"; + detailArea.classed("hidden", true); + if ( init === true ) { + detailArea.classed("hidden", !visibleSidebar); + graphArea.style("width", "78%"); + graphArea.style("-webkit-animation-name", "none"); + + menuArea.style("width", "78%"); + menuArea.style("-webkit-animation-name", "none"); + + d3.select("#WarningErrorMessagesContainer").style("width", "78%"); + d3.select("#WarningErrorMessagesContainer").style("-webkit-animation-name", "none"); + } else { + graphArea.style("width", "78%"); + graphArea.style("-webkit-animation-name", "sbCollapseAnimation"); + graphArea.style("-webkit-animation-duration", "0.5s"); + + menuArea.style("width", "78%"); + menuArea.style("-webkit-animation-name", "sbCollapseAnimation"); + menuArea.style("-webkit-animation-duration", "0.5s"); + + d3.select("#WarningErrorMessagesContainer").style("width", "78%"); + d3.select("#WarningErrorMessagesContainer").style("-webkit-animation-name", "warn_ExpandRightBarAnimation"); + d3.select("#WarningErrorMessagesContainer").style("-webkit-animation-duration", "0.5s"); + } + graph.options().width(window.innerWidth - (window.innerWidth * 0.22)); + graph.options().navigationMenu().updateScrollButtonVisibility(); + } + if ( val === 0 ) { + visibleSidebar = false; + detailArea.classed("hidden", true); + + collapseButton.node().innerHTML = "<"; + // adjust the layout + if ( init === true ) { + graphArea.style("width", "100%"); + graphArea.style("-webkit-animation-name", "none"); + + menuArea.style("width", "100%"); + menuArea.style("-webkit-animation-name", "none"); + + d3.select("#WarningErrorMessagesContainer").style("width", "100%"); + d3.select("#WarningErrorMessagesContainer").style("-webkit-animation-name", "none"); + } else { + graphArea.style("width", "100%"); + graphArea.style("-webkit-animation-name", "sbExpandAnimation"); + graphArea.style("-webkit-animation-duration", "0.5s"); + + menuArea.style("width", "100%"); + menuArea.style("-webkit-animation-name", "sbExpandAnimation"); + menuArea.style("-webkit-animation-duration", "0.5s"); + + d3.select("#WarningErrorMessagesContainer").style("width", "100%"); + d3.select("#WarningErrorMessagesContainer").style("-webkit-animation-name", "warn_CollapseRightBarAnimation"); + d3.select("#WarningErrorMessagesContainer").style("-webkit-animation-duration", "0.5s"); + + } + graph.options().width(window.innerWidth); + graph.updateCanvasContainerSize(); + graph.options().navigationMenu().updateScrollButtonVisibility(); + } + }; + + sidebar.isSidebarVisible = function (){ + return visibleSidebar; + }; + + sidebar.updateSideBarVis = function ( init ){ + var vis = sidebar.getSidebarVisibility(); + sidebar.showSidebar(parseInt(vis), init); + }; + + sidebar.getSidebarVisibility = function (){ + var isHidden = detailArea.classed("hidden"); + if ( isHidden === false ) return String(1); + if ( isHidden === true ) return String(0); + }; + + sidebar.initSideBarAnimation = function (){ + graphArea.node().addEventListener("animationend", function (){ + detailArea.classed("hidden", !visibleSidebar); + graph.updateCanvasContainerSize(); + graph.options().navigationMenu().updateScrollButtonVisibility(); + }); + }; + + sidebar.setup = function (){ + setupCollapsing(); + sidebar.initSideBarAnimation(); + + collapseButton.on("click", function (){ + graph.options().navigationMenu().hideAllMenus(); + var settingValue = parseInt(sidebar.getSidebarVisibility()); + if ( settingValue === 1 ) sidebar.showSidebar(0); + else sidebar.showSidebar(1); + }); + }; + + + sidebar.updateShowedInformation = function (){ + var editMode = graph.editorMode(); + d3.select("#generalDetails").classed("hidden", editMode); + d3.select("#generalDetailsEdit").classed("hidden", !editMode); + + // store the meta information in graph.options() + + // todo: update edit meta info + graph.options().editSidebar().updateGeneralOntologyInfo(); + + // todo: update showed meta info; + graph.options().sidebar().updateGeneralOntologyInfo(); + + }; + + sidebar.updateGeneralOntologyInfo = function (){ + // get it from graph.options + var generalMetaObj = graph.options().getGeneralMetaObject(); + var preferredLanguage = graph && graph.language ? graph.language() : null; + if ( generalMetaObj.hasOwnProperty("title") ) { + // title has language to it -.- + if ( typeof generalMetaObj.title === "object" ) { + d3.select("#title").node().value = languageTools.textInLanguage(generalMetaObj.title, preferredLanguage); + } else { + d3.select("#title").node().innerHTML = generalMetaObj.title; + } + + } + if ( generalMetaObj.hasOwnProperty("iri") ) d3.select("#about").node().innerHTML = generalMetaObj.iri; + if ( generalMetaObj.hasOwnProperty("iri") ) d3.select("#about").node().href = generalMetaObj.iri; + if ( generalMetaObj.hasOwnProperty("version") ) d3.select("#version").node().innerHTML = generalMetaObj.version; + if ( generalMetaObj.hasOwnProperty("author") ) d3.select("#authors").node().innerHTML = generalMetaObj.author; + // this could also be an object >> + if ( generalMetaObj.hasOwnProperty("description") ) { + if ( typeof generalMetaObj.description === "object" ) { + d3.select("#description").node().innerHTML = languageTools.textInLanguage(generalMetaObj.description, preferredLanguage); + } + else { + d3.select("#description").node().innerHTML = generalMetaObj.description; + } + } + }; + + + return sidebar; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 339: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for the sidebar. + * @param graph the graph that belongs to these controls + * @returns {{}} + */ + module.exports = function ( graph ){ + + var leftSidebar = {}, + languageTools = webvowl.util.languageTools(), + elementTools = webvowl.util.elementTools(); + var collapseButton = d3.select("#leftSideBarCollapseButton"); + var visibleSidebar = 0; + var backupVisibility = 0; + var sideBarContent = d3.select("#leftSideBarContent"); + var sideBarContainer = d3.select("#containerForLeftSideBar"); + var defaultClassSelectionContainers = []; + var defaultDatatypeSelectionContainers = []; + var defaultPropertySelectionContainers = []; + + leftSidebar.setup = function (){ + setupCollapsing(); + leftSidebar.initSideBarAnimation(); + + collapseButton.on("click", function (){ + graph.options().navigationMenu().hideAllMenus(); + var settingValue = parseInt(leftSidebar.getSidebarVisibility()); + if ( settingValue === 0 ) leftSidebar.showSidebar(1); + else leftSidebar.showSidebar(0); + backupVisibility = settingValue; + }); + + setupSelectionContainers(); + d3.select("#WarningErrorMessages").node().addEventListener("animationend", function (){ + d3.select("#WarningErrorMessages").style("-webkit-animation-name", "none"); + }); + + }; + + leftSidebar.hideCollapseButton = function ( val ){ + sideBarContainer.classed("hidden", val); + }; + + + function unselectAllElements( container ){ + for ( var i = 0; i < container.length; i++ ) + container[i].classed("defaultSelected", false); + } + + function selectThisDefaultElement( element ){ + d3.select(element).classed("defaultSelected", true); + } + + function updateDefaultNameInAccordion( element, identifier ){ + var elementDescription = ""; + if ( identifier === "defaultClass" ) elementDescription = "Class: "; + if ( identifier === "defaultDatatype" ) elementDescription = "Datatype: "; + if ( identifier === "defaultProperty" ) elementDescription = "Property: "; + + d3.select("#" + identifier).node().innerHTML = elementDescription + element.innerHTML; + d3.select("#" + identifier).node().title = element.innerHTML; + } + + function classSelectorFunction(){ + unselectAllElements(defaultClassSelectionContainers); + selectThisDefaultElement(this); + updateDefaultNameInAccordion(this, "defaultClass"); + } + + function datatypeSelectorFunction(){ + unselectAllElements(defaultDatatypeSelectionContainers); + selectThisDefaultElement(this); + updateDefaultNameInAccordion(this, "defaultDatatype"); + } + + function propertySelectorFunction(){ + unselectAllElements(defaultPropertySelectionContainers); + selectThisDefaultElement(this); + updateDefaultNameInAccordion(this, "defaultProperty"); + } + + + function setupSelectionContainers(){ + var classContainer = d3.select("#classContainer"); + var datatypeContainer = d3.select("#datatypeContainer"); + var propertyContainer = d3.select("#propertyContainer"); + // create the supported elements + + var defaultClass = "owl:Class"; + var defaultDatatype = "rdfs:Literal"; + var defaultProperty = "owl:objectProperty"; + + var supportedClasses = graph.options().supportedClasses(); + var supportedDatatypes = graph.options().supportedDatatypes(); + var supportedProperties = graph.options().supportedProperties(); + var i; + + for ( i = 0; i < supportedClasses.length; i++ ) { + var aClassSelectionContainer; + aClassSelectionContainer = classContainer.append("div"); + aClassSelectionContainer.classed("containerForDefaultSelection", true); + aClassSelectionContainer.classed("noselect", true); + aClassSelectionContainer.node().id = "selectedClass" + supportedClasses[i]; + aClassSelectionContainer.node().innerHTML = supportedClasses[i]; + + if ( supportedClasses[i] === defaultClass ) { + selectThisDefaultElement(aClassSelectionContainer.node()); + } + aClassSelectionContainer.on("click", classSelectorFunction); + defaultClassSelectionContainers.push(aClassSelectionContainer); + } + + for ( i = 0; i < supportedDatatypes.length; i++ ) { + var aDTSelectionContainer = datatypeContainer.append("div"); + aDTSelectionContainer.classed("containerForDefaultSelection", true); + aDTSelectionContainer.classed("noselect", true); + aDTSelectionContainer.node().id = "selectedDatatype" + supportedDatatypes[i]; + aDTSelectionContainer.node().innerHTML = supportedDatatypes[i]; + + if ( supportedDatatypes[i] === defaultDatatype ) { + selectThisDefaultElement(aDTSelectionContainer.node()); + } + aDTSelectionContainer.on("click", datatypeSelectorFunction); + defaultDatatypeSelectionContainers.push(aDTSelectionContainer); + } + for ( i = 0; i < supportedProperties.length; i++ ) { + var aPropSelectionContainer = propertyContainer.append("div"); + aPropSelectionContainer.classed("containerForDefaultSelection", true); + aPropSelectionContainer.classed("noselect", true); + aPropSelectionContainer.node().id = "selectedClass" + supportedProperties[i]; + aPropSelectionContainer.node().innerHTML = supportedProperties[i]; + aPropSelectionContainer.on("click", propertySelectorFunction); + if ( supportedProperties[i] === defaultProperty ) { + selectThisDefaultElement(aPropSelectionContainer.node()); + } + defaultPropertySelectionContainers.push(aPropSelectionContainer); + } + } + + function setupCollapsing(){ + // adapted version of this example: http://www.normansblog.de/simple-jquery-accordion/ + function collapseContainers( containers ){ + containers.classed("hidden", true); + } + + function expandContainers( containers ){ + containers.classed("hidden", false); + } + + var triggers = d3.selectAll(".accordion-trigger"); + + // Collapse all inactive triggers on startup + // collapseContainers(d3.selectAll(".accordion-trigger:not(.accordion-trigger-active) + div")); + + triggers.on("click", function (){ + var selectedTrigger = d3.select(this); + if ( selectedTrigger.classed("accordion-trigger-active") ) { + // Collapse the active (which is also the selected) trigger + collapseContainers(d3.select(selectedTrigger.node().nextElementSibling)); + selectedTrigger.classed("accordion-trigger-active", false); + } else { + // Collapse the other trigger ... + // collapseContainers(d3.selectAll(".accordion-trigger-active + div")); + // activeTriggers.classed("accordion-trigger-active", false); + // ... and expand the selected one + expandContainers(d3.select(selectedTrigger.node().nextElementSibling)); + selectedTrigger.classed("accordion-trigger-active", true); + } + }); + } + + + leftSidebar.isSidebarVisible = function (){ + return visibleSidebar; + }; + + leftSidebar.updateSideBarVis = function ( init ){ + var vis = leftSidebar.getSidebarVisibility(); + leftSidebar.showSidebar(parseInt(vis), init); + }; + + leftSidebar.initSideBarAnimation = function (){ + sideBarContainer.node().addEventListener("animationend", function (){ + sideBarContent.classed("hidden", !visibleSidebar); + if ( visibleSidebar === true ) { + sideBarContainer.style("width", "200px"); + sideBarContent.classed("hidden", false); + d3.select("#leftSideBarCollapseButton").style("left", "200px"); + d3.select("#leftSideBarCollapseButton").classed("hidden", false); + d3.select("#WarningErrorMessages").style("left", "100px"); + } + else { + sideBarContainer.style("width", "0px"); + d3.select("#leftSideBarCollapseButton").style("left", "0px"); + d3.select("#WarningErrorMessages").style("left", "0px"); + d3.select("#leftSideBarCollapseButton").classed("hidden", false); + + } + graph.updateCanvasContainerSize(); + graph.options().navigationMenu().updateScrollButtonVisibility(); + }); + }; + + leftSidebar.showSidebar = function ( val, init ){ + // make val to bool + var collapseButton = d3.select("#leftSideBarCollapseButton"); + if ( init === true ) { + visibleSidebar = (backupVisibility === 0); + sideBarContent.classed("hidden", !visibleSidebar); + sideBarContainer.style("-webkit-animation-name", "none"); + d3.select("#WarningErrorMessages").style("-webkit-animation-name", "none"); + if ( visibleSidebar === true ) { + sideBarContainer.style("width", "200px"); + sideBarContent.classed("hidden", false); + d3.select("#leftSideBarCollapseButton").style("left", "200px"); + d3.select("#leftSideBarCollapseButton").classed("hidden", false); + d3.select("#WarningErrorMessages").style("left", "100px"); + collapseButton.node().innerHTML = "<"; + } + + else { + sideBarContainer.style("width", "0px"); + d3.select("#WarningErrorMessages").style("left", "0px"); + d3.select("#leftSideBarCollapseButton").style("left", "0px"); + d3.select("#leftSideBarCollapseButton").classed("hidden", false); + collapseButton.node().innerHTML = ">"; + } + + graph.updateCanvasContainerSize(); + graph.options().navigationMenu().updateScrollButtonVisibility(); + return; + } + + d3.select("#leftSideBarCollapseButton").classed("hidden", true); + + if ( val === 1 ) { + visibleSidebar = true; + collapseButton.node().innerHTML = "<"; + // call expand animation; + sideBarContainer.style("-webkit-animation-name", "l_sbExpandAnimation"); + sideBarContainer.style("-webkit-animation-duration", "0.5s"); + // prepare the animation; + + d3.select("#WarningErrorMessages").style("-webkit-animation-name", "warn_ExpandLeftBarAnimation"); + d3.select("#WarningErrorMessages").style("-webkit-animation-duration", "0.5s"); + + } + if ( val === 0 ) { + visibleSidebar = false; + sideBarContent.classed("hidden", true); + collapseButton.node().innerHTML = ">"; + // call collapse animation + sideBarContainer.style("-webkit-animation-name", "l_sbCollapseAnimation"); + sideBarContainer.style("-webkit-animation-duration", "0.5s"); + d3.select("#WarningErrorMessages").style("-webkit-animation-name", "warn_CollapseLeftBarAnimation"); + d3.select("#WarningErrorMessages").style("-webkit-animation-duration", "0.5s"); + d3.select("#WarningErrorMessages").style("left", "0"); + } + + }; + + leftSidebar.getSidebarVisibility = function (){ + var isHidden = sideBarContent.classed("hidden"); + if ( isHidden === false ) return String(1); + if ( isHidden === true ) return String(0); + }; + + return leftSidebar; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 340: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for the sidebar. + * @param graph the graph that belongs to these controls + * @returns {{}} + */ + module.exports = function ( graph ){ + + var editSidebar = {}, + languageTools = webvowl.util.languageTools(), + elementTools = webvowl.util.elementTools(); + + var prefixModule = webvowl.util.prefixTools(graph); + var selectedElementForCharacteristics; + var oldPrefix, oldPrefixURL; + var prefix_editMode = false; + + + editSidebar.clearMetaObjectValue = function (){ + d3.select("#titleEditor").node().value = ""; + d3.select("#iriEditor").node().value = ""; + d3.select("#versionEditor").node().value = ""; + d3.select("#authorsEditor").node().value = ""; + d3.select("#descriptionEditor").node().value = ""; + // todo add clear description; + }; + + + editSidebar.updatePrefixUi = function (){ + editSidebar.updateElementWidth(); + var prefixListContainer = d3.select("#prefixURL_Container"); + while ( prefixListContainer.node().firstChild ) { + prefixListContainer.node().removeChild(prefixListContainer.node().firstChild); + } + setupPrefixList(); + }; + + editSidebar.setup = function (){ + setupCollapsing(); + setupPrefixList(); + setupAddPrefixButton(); + setupSupportedDatatypes(); + + + d3.select("#titleEditor") + .on("change", function (){ + graph.options().addOrUpdateGeneralObjectEntry("title", d3.select("#titleEditor").node().value); + }) + .on("keydown", function (){ + d3.event.stopPropagation(); + if ( d3.event.keyCode === 13 ) { + d3.event.preventDefault(); + graph.options().addOrUpdateGeneralObjectEntry("title", d3.select("#titleEditor").node().value); + } + }); + d3.select("#iriEditor") + .on("change", function (){ + if ( graph.options().addOrUpdateGeneralObjectEntry("iri", d3.select("#iriEditor").node().value) === false ) { + // restore value + d3.select("#iriEditor").node().value = graph.options().getGeneralMetaObjectProperty('iri'); + } + }) + .on("keydown", function (){ + d3.event.stopPropagation(); + if ( d3.event.keyCode === 13 ) { + d3.event.preventDefault(); + if ( graph.options().addOrUpdateGeneralObjectEntry("iri", d3.select("#iriEditor").node().value) === false ) { + // restore value + d3.select("#iriEditor").node().value = graph.options().getGeneralMetaObjectProperty('iri'); + } + } + }); + d3.select("#versionEditor") + .on("change", function (){ + graph.options().addOrUpdateGeneralObjectEntry("version", d3.select("#versionEditor").node().value); + }) + .on("keydown", function (){ + d3.event.stopPropagation(); + if ( d3.event.keyCode === 13 ) { + d3.event.preventDefault(); + graph.options().addOrUpdateGeneralObjectEntry("version", d3.select("#versionEditor").node().value); + } + }); + d3.select("#authorsEditor") + .on("change", function (){ + graph.options().addOrUpdateGeneralObjectEntry("author", d3.select("#authorsEditor").node().value); + }) + .on("keydown", function (){ + d3.event.stopPropagation(); + if ( d3.event.keyCode === 13 ) { + d3.event.preventDefault(); + graph.options().addOrUpdateGeneralObjectEntry("author", d3.select("#authorsEditor").node().value); + } + }); + d3.select("#descriptionEditor") + .on("change", function (){ + graph.options().addOrUpdateGeneralObjectEntry("description", d3.select("#descriptionEditor").node().value); + }); + + editSidebar.updateElementWidth(); + + }; + + function setupSupportedDatatypes(){ + var datatypeEditorSelection = d3.select("#typeEditor_datatype").node(); + var supportedDatatypes = ["undefined", "xsd:boolean", "xsd:double", "xsd:integer", "xsd:string"]; + for ( var i = 0; i < supportedDatatypes.length; i++ ) { + var optB = document.createElement('option'); + optB.innerHTML = supportedDatatypes[i]; + datatypeEditorSelection.appendChild(optB); + } + } + + function highlightDeleteButton( enable, name ){ + var deletePath = d3.select("#del_pathFor_" + name); + var deleteRect = d3.select("#del_rectFor_" + name); + + if ( enable === false ) { + deletePath.node().style = "stroke: #f00;"; + deleteRect.style("cursor", "auto"); + } else { + deletePath.node().style = "stroke: #ff972d;"; + deleteRect.style("cursor", "pointer"); + } + } + + + function highlightEditButton( enable, name, fill ){ + var editPath = d3.select("#pathFor_" + name); + var editRect = d3.select("#rectFor_" + name); + + if ( enable === false ) { + if ( fill ) + editPath.node().style = "fill: #fff; stroke : #fff; stroke-width : 1px"; + else + editPath.node().style = " stroke : #fff; stroke-width : 1px"; + + editRect.style("cursor", "auto"); + } else { + if ( fill ) + editPath.node().style = "fill: #ff972d; stroke : #ff972d; stroke-width : 1px"; + else + editPath.node().style = "stroke : #ff972d; stroke-width : 1px"; + editRect.style("cursor", "pointer"); + } + + } + + function setupAddPrefixButton(){ + var btn = d3.select("#addPrefixButton"); + btn.on("click", function (){ + + // check if we are still in editMode? + if ( prefix_editMode === false ) { + // create new line entry; + var name = "emptyPrefixEntry"; + var prefixListContainer = d3.select("#prefixURL_Container"); + var prefixEditContainer = prefixListContainer.append("div"); + prefixEditContainer.classed("prefixIRIElements", true); + prefixEditContainer.node().id = "prefixContainerFor_" + name; + + var IconContainer = prefixEditContainer.append("div"); + IconContainer.style("position", "absolute"); + IconContainer.node().id = "containerFor_" + name; + var editButton = IconContainer.append("svg"); + editButton.style("width", "14px"); + editButton.style("height", "20px"); + // editButton.classed("editPrefixButton", true); + editButton.classed("noselect", true); + //editButton.node().innerHTML = "\u2714"; + editButton.node().id = "editButtonFor_" + name; + + editButton.node().elementStyle = "save"; + editButton.node().selectorName = name; + var editIcon = editButton.append("g"); + var editRect = editIcon.append("rect"); + var editPath = editIcon.append("path"); + editIcon.node().id = "iconFor_" + name; + editPath.node().id = "pathFor_" + name; + editRect.node().id = "rectFor_" + name; + + editIcon.node().selectorName = name; + editPath.node().selectorName = name; + editRect.node().selectorName = name; + IconContainer.node().title = "Save new prefix and IRI"; + + editPath.classed("editPrefixIcon"); + editPath.style("stroke", "#fff"); + editPath.style("stroke-width", "1px"); + editPath.style("fill", "#fff"); + editRect.attr("width", "14px"); + editRect.attr("height", "14px"); + editRect.style("fill", "#18202A"); + editRect.attr("transform", "matrix(1,0,0,1,-3,4)"); + + editButton.selectAll("g").on("mouseover", function (){ + highlightEditButton(true, this.selectorName, true); + }); + editButton.selectAll("g").on("mouseout", function (){ + highlightEditButton(false, this.selectorName, true); + }); + // Check mark + // M9 16.2L4.8 12l-1.4 1.4L9 19 21 7l-1.4-1.4L9 16.2z + // pencil + // M3 17.25V21h3.75L17.81 9.94l-3.75-3.75L3 17.25zM20.71 7.04c.39-.39.39-1.02 0-1.41l-2.34-2.34c-.39-.39-1.02-.39-1.41 0l-1.83 1.83 3.75 3.75 1.83-1.83z + editPath.attr("d", "M9 16.2L4.8 12l-1.4 1.4L9 19 21 7l-1.4-1.4L9 16.2z"); + editPath.attr("transform", "matrix(0.45,0,0,0.45,0,5)"); + + var prefInput = prefixEditContainer.append("input"); + prefInput.classed("prefixInput", true); + prefInput.node().type = "text"; + prefInput.node().id = "prefixInputFor_" + name; + prefInput.node().autocomplete = "off"; + prefInput.node().value = ""; + prefInput.style("margin-left", "14px"); + + var prefURL = prefixEditContainer.append("input"); + prefURL.classed("prefixURL", true); + prefURL.node().type = "text"; + prefURL.node().id = "prefixURLFor_" + name; + prefURL.node().autocomplete = "off"; + prefURL.node().value = ""; + + prefInput.node().disabled = false; + prefURL.node().disabled = false; + prefix_editMode = true; + var deleteContainer = prefixEditContainer.append("div"); + deleteContainer.style("float", "right"); + var deleteButton = deleteContainer.append("svg"); + deleteButton.node().id = "deleteButtonFor_" + name; + deleteContainer.node().title = "Delete prefix and IRI"; + deleteButton.style("width", "10px"); + deleteButton.style("height", "20px"); + var deleteIcon = deleteButton.append("g"); + var deleteRect = deleteIcon.append("rect"); + var deletePath = deleteIcon.append("path"); + deleteIcon.node().id = "del_iconFor_" + name; + deletePath.node().id = "del_pathFor_" + name; + deleteRect.node().id = "del_rectFor_" + name; + + deleteIcon.node().selectorName = name; + deletePath.node().selectorName = name; + deleteRect.node().selectorName = name; + + + deletePath.style("stroke", "#f00"); + deleteRect.attr("width", "10px"); + deleteRect.attr("height", "14px"); + deleteRect.style("fill", "#18202A"); + deleteRect.attr("transform", "matrix(1,0,0,1,-3,4)"); + + + deletePath.attr("d", "M19 6.41L17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12z"); + deletePath.attr("transform", "matrix(0.45,0,0,0.45,0,5)"); + + deleteButton.selectAll("g").on("mouseover", function (){ + highlightDeleteButton(true, this.selectorName); + }); + deleteButton.selectAll("g").on("mouseout", function (){ + highlightDeleteButton(false, this.selectorName); + }); + + + // connect the buttons; + editButton.on("click", enablePrefixEdit); + deleteButton.on("click", deletePrefixLine); + + editSidebar.updateElementWidth(); + // swap focus to prefixInput + prefInput.node().focus(); + oldPrefix = name; + oldPrefixURL = ""; + d3.select("#addPrefixButton").node().innerHTML = "Save Prefix"; + } else { + d3.select("#editButtonFor_emptyPrefixEntry").on("click")(d3.select("#editButtonFor_emptyPrefixEntry").node()); + } + + }); + + } + + function setupPrefixList(){ + if ( graph.isEditorMode() === false ) return; + var prefixListContainer = d3.select("#prefixURL_Container"); + var prefixElements = graph.options().prefixList(); + for ( var name in prefixElements ) { + if ( prefixElements.hasOwnProperty(name) ) { + var prefixEditContainer = prefixListContainer.append("div"); + prefixEditContainer.classed("prefixIRIElements", true); + prefixEditContainer.node().id = "prefixContainerFor_" + name; + + // create edit button which enables the input fields + var IconContainer = prefixEditContainer.append("div"); + IconContainer.style("position", "absolute"); + IconContainer.node().id = "containerFor_" + name; + var editButton = IconContainer.append("svg"); + editButton.style("width", "14px"); + editButton.style("height", "20px"); + editButton.classed("noselect", true); + editButton.node().id = "editButtonFor_" + name; + IconContainer.node().title = "Edit prefix and IRI"; + editButton.node().elementStyle = "save"; + editButton.node().selectorName = name; + + editButton.node().id = "editButtonFor_" + name; + editButton.node().elementStyle = "edit"; + var editIcon = editButton.append("g"); + var editRect = editIcon.append("rect"); + var editPath = editIcon.append("path"); + editIcon.node().id = "iconFor_" + name; + editPath.node().id = "pathFor_" + name; + editRect.node().id = "rectFor_" + name; + + editIcon.node().selectorName = name; + editPath.node().selectorName = name; + editRect.node().selectorName = name; + + + editPath.classed("editPrefixIcon"); + editPath.style("stroke", "#fff"); + editPath.style("stroke-width", "1px"); + editRect.attr("width", "14px"); + editRect.attr("height", "14px"); + editRect.style("fill", "#18202A"); + editRect.attr("transform", "matrix(1,0,0,1,-3,4)"); + + editButton.selectAll("g").on("mouseover", function (){ + var sender = this; + var fill = false; + var enable = true; + var f_editPath = d3.select("#pathFor_" + sender.selectorName); + var f_editRect = d3.select("#rectFor_" + sender.selectorName); + + if ( enable === false ) { + if ( fill ) + f_editPath.node().style = "fill: #fff; stroke : #fff; stroke-width : 1px"; + else + f_editPath.node().style = " stroke : #fff; stroke-width : 1px"; + + f_editRect.style("cursor", "auto"); + } else { + if ( fill ) + f_editPath.node().style = "fill: #ff972d; stroke : #ff972d; stroke-width : 1px"; + else + f_editPath.node().style = "stroke : #ff972d; stroke-width : 1px"; + f_editRect.style("cursor", "pointer"); + } + }); + editButton.selectAll("g").on("mouseout", function (){ + var sender = this; + var fill = false; + var enable = false; + var f_editPath = d3.select("#pathFor_" + sender.selectorName); + var f_editRect = d3.select("#rectFor_" + sender.selectorName); + + if ( enable === false ) { + if ( fill ) + f_editPath.node().style = "fill: #fff; stroke : #fff; stroke-width : 1px"; + else + f_editPath.node().style = " stroke : #fff; stroke-width : 1px"; + + f_editRect.style("cursor", "auto"); + } else { + if ( fill ) + f_editPath.node().style = "fill: #ff972d; stroke : #ff972d; stroke-width : 1px"; + else + f_editPath.node().style = "stroke : #ff972d; stroke-width : 1px"; + f_editRect.style("cursor", "pointer"); + } + }); + + editPath.attr("d", "M3 17.25V21h3.75L17.81 9.94l-3.75-3.75L3 17.25zM20.71 7.04c.39-.39.39-1.02 0-1.41l-2.34-2.34c-.39-.39-1.02-.39-1.41 0l-1.83 1.83 3.75 3.75 1.83-1.83z"); + editPath.attr("transform", "matrix(-0.45,0,0,0.45,10,5)"); + + // create input field for prefix + var prefInput = prefixEditContainer.append("input"); + prefInput.classed("prefixInput", true); + prefInput.node().type = "text"; + prefInput.node().id = "prefixInputFor_" + name; + prefInput.node().autocomplete = "off"; + prefInput.node().value = name; + prefInput.style("margin-left", "14px"); + + // create input field for prefix url + var prefURL = prefixEditContainer.append("input"); + prefURL.classed("prefixURL", true); + prefURL.node().type = "text"; + prefURL.node().id = "prefixURLFor_" + name; + prefURL.node().autocomplete = "off"; + prefURL.node().value = prefixElements[name]; + prefURL.node().title = prefixElements[name]; + // disable the input fields (already defined elements can be edited later) + prefInput.node().disabled = true; + prefURL.node().disabled = true; + + // create the delete button + var deleteContainer = prefixEditContainer.append("div"); + deleteContainer.style("float", "right"); + var deleteButton = deleteContainer.append("svg"); + deleteButton.node().id = "deleteButtonFor_" + name; + deleteContainer.node().title = "Delete prefix and IRI"; + deleteButton.style("width", "10px"); + deleteButton.style("height", "20px"); + var deleteIcon = deleteButton.append("g"); + var deleteRect = deleteIcon.append("rect"); + var deletePath = deleteIcon.append("path"); + deleteIcon.node().id = "del_iconFor_" + name; + deletePath.node().id = "del_pathFor_" + name; + deleteRect.node().id = "del_rectFor_" + name; + + deleteIcon.node().selectorName = name; + deletePath.node().selectorName = name; + deleteRect.node().selectorName = name; + + + deletePath.style("stroke", "#f00"); + deleteRect.attr("width", "10px"); + deleteRect.attr("height", "14px"); + deleteRect.style("fill", "#18202A"); + deleteRect.attr("transform", "matrix(1,0,0,1,-3,4)"); + + + deletePath.attr("d", "M19 6.41L17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12z"); + deletePath.attr("transform", "matrix(0.45,0,0,0.45,0,5)"); + + deleteButton.selectAll("g").on("mouseover", function (){ + var selector = this; + var enable = true; + var f_deletePath = d3.select("#del_pathFor_" + selector.selectorName); + var f_deleteRect = d3.select("#del_rectFor_" + selector.selectorName); + + if ( enable === false ) { + f_deletePath.node().style = "stroke: #f00;"; + f_deleteRect.style("cursor", "auto"); + } else { + f_deletePath.node().style = "stroke: #ff972d;"; + f_deleteRect.style("cursor", "pointer"); + } + }); + deleteButton.selectAll("g").on("mouseout", function (){ + var selector = this; + var enable = false; + var f_deletePath = d3.select("#del_pathFor_" + selector.selectorName); + var f_deleteRect = d3.select("#del_rectFor_" + selector.selectorName); + + if ( enable === false ) { + f_deletePath.node().style = "stroke: #f00;"; + f_deleteRect.style("cursor", "auto"); + } else { + f_deletePath.node().style = "stroke: #ff972d;"; + f_deleteRect.style("cursor", "pointer"); + } + }); + + + editButton.on("click", enablePrefixEdit); + deleteButton.on("click", deletePrefixLine); + + // EXPERIMENTAL + + if ( name === "rdf" || + name === "rdfs" || + name === "xsd" || name === "dc" || + name === "owl" + ) { + // make them invis so the spacing does not change + IconContainer.classed("hidden", true); + deleteContainer.classed("hidden", true); + } + } + } + prefixModule.updatePrefixModel(); + } + + function deletePrefixLine(){ + if ( this.disabled === true ) return; + d3.select("#addPrefixButton").node().innerHTML = "Add Prefix"; + var selector = this.id.split("_")[1]; + d3.select("#prefixContainerFor_" + selector).remove(); + graph.options().removePrefix(selector); + prefix_editMode = false; // < 0 ) { + var basePref = graph.options().prefixList()[pr]; + if ( basePref === undefined ) { + console.log("ERROR __________________"); + graph.options().warningModule().showWarning("Invalid Element IRI", + "Could not resolve prefix '" + basePref + "'", + "Restoring previous IRI for Element" + element.iri(), 1, false); + d3.select("#element_iriEditor").node().value = element.iri(); + return; + + } + // check if url is not empty + + if ( name.length === 0 ) { + graph.options().warningModule().showWarning("Invalid Element IRI", + "Input IRI is EMPTY", + "Restoring previous IRI for Element" + element.iri(), 1, false); + console.log("NO INPUT PROVIDED"); + d3.select("#element_iriEditor").node().value = element.iri(); + return; + + } + url = basePref + name; + } + else { + url = base + name; + } + } else { + if ( url.length === 0 ) { + // + console.log("NO INPUT PROVIDED"); + d3.select("#element_iriEditor").node().value = element.iri(); + return; + } + // failed to identify anything useful + console.log("Tryig to use the input!"); + url = base + url; + } + } + return url; + } + + function changeIriForElement( element ){ + var url = getURLFROMPrefixedVersion(element); + var base = graph.options().getGeneralMetaObjectProperty("iri"); + var sanityCheckResult; + if ( elementTools.isNode(element) ) { + + sanityCheckResult = graph.checkIfIriClassAlreadyExist(url); + if ( sanityCheckResult === false ) { + element.iri(url); + } else { + // throw warnign + graph.options().warningModule().showWarning("Already seen this class", + "Input IRI: " + url + " for element: " + element.labelForCurrentLanguage() + " already been set", + "Restoring previous IRI for Element : " + element.iri(), 2, false, sanityCheckResult); + + editSidebar.updateSelectionInformation(element); + return; + + } + } + if ( elementTools.isProperty(element) === true ) { + sanityCheckResult = editSidebar.checkProperIriChange(element, url); + if ( sanityCheckResult !== false ) { + graph.options().warningModule().showWarning("Already seen this property", + "Input IRI: " + url + " for element: " + element.labelForCurrentLanguage() + " already been set", + "Restoring previous IRI for Element : " + element.iri(), 1, false, sanityCheckResult); + + editSidebar.updateSelectionInformation(element); + return; + } + } + + // if (element.existingPropertyIRI(url)===true){ + // console.log("I Have seen this Particular URL already "+url); + // graph.options().warningModule().showWarning("Already Seen This one ", + // "Input IRI For Element"+ element.labelForCurrentLanguage()+" already been set ", + // "Restoring previous IRI for Element"+element.iri(),1,false); + // d3.select("#element_iriEditor").node().value=graph.options().prefixModule().getPrefixRepresentationForFullURI(element.iri()); + // editSidebar.updateSelectionInformation(element); + // return; + // } + + element.iri(url); + if ( identifyExternalCharacteristicForElement(base, url) === true ) { + addAttribute(element, "external"); + // background color for external element; + element.backgroundColor("#36C"); + element.redrawElement(); + element.redrawLabelText(); + // handle visual selection + + } else { + removeAttribute(element, "external"); + // background color for external element; + element.backgroundColor(undefined); + element.redrawElement(); + element.redrawLabelText(); + + } + + if ( element.focused() ) { + graph.options().focuserModule().handle(element, true); // unfocus + graph.options().focuserModule().handle(element, true); // focus + } + // graph.options().focuserModule().handle(undefined); + + + d3.select("#element_iriEditor").node().value = prefixModule.getPrefixRepresentationForFullURI(url); + editSidebar.updateSelectionInformation(element); + } + + function validURL( str ){ + var urlregex = /^(https?|ftp):\/\/([a-zA-Z0-9.-]+(:[a-zA-Z0-9.&%$-]+)*@)*((25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9][0-9]?)(\.(25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9]?[0-9])){3}|([a-zA-Z0-9-]+\.)*[a-zA-Z0-9-]+\.(com|edu|gov|int|mil|net|org|biz|arpa|info|name|pro|aero|coop|museum|[a-zA-Z]{2}))(:[0-9]+)*(\/($|[a-zA-Z0-9.,?'\\+&%$#=~_-]+))*$/; + return urlregex.test(str); + } + + + function changeLabelForElement( element ){ + element.label(d3.select("#element_labelEditor").node().value); + element.redrawLabelText(); + } + + editSidebar.updateEditDeleteButtonIds = function ( oldPrefix, newPrefix ){ + d3.select("#prefixInputFor_" + oldPrefix).node().id = "prefixInputFor_" + newPrefix; + d3.select("#prefixURLFor_" + oldPrefix).node().id = "prefixURLFor_" + newPrefix; + d3.select("#deleteButtonFor_" + oldPrefix).node().id = "deleteButtonFor_" + newPrefix; + d3.select("#editButtonFor_" + oldPrefix).node().id = "editButtonFor_" + newPrefix; + + d3.select("#prefixContainerFor_" + oldPrefix).node().id = "prefixContainerFor_" + newPrefix; + }; + + editSidebar.checkForExistingURL = function ( url ){ + var i; + var allProps = graph.getUnfilteredData().properties; + for ( i = 0; i < allProps.length; i++ ) { + if ( allProps[i].iri() === url ) return true; + } + return false; + + }; + editSidebar.checkProperIriChange = function ( element, url ){ + console.log("Element changed Label"); + console.log("Testing URL " + url); + if ( element.type() === "rdfs:subClassOf" || element.type() === "owl:disjointWith" ) { + console.log("ignore this for now, already handled in the type and domain range changer"); + } else { + var i; + var allProps = graph.getUnfilteredData().properties; + for ( i = 0; i < allProps.length; i++ ) { + if ( allProps[i] === element ) continue; + if ( allProps[i].iri() === url ) return allProps[i]; + } + } + return false; + }; + + editSidebar.updateSelectionInformation = function ( element ){ + + if ( element === undefined ) { + // show hint; + d3.select("#selectedElementProperties").classed("hidden", true); + d3.select("#selectedElementPropertiesEmptyHint").classed("hidden", false); + selectedElementForCharacteristics = null; + editSidebar.updateElementWidth(); + } + else { + d3.select("#selectedElementProperties").classed("hidden", false); + d3.select("#selectedElementPropertiesEmptyHint").classed("hidden", true); + d3.select("#typeEditForm_datatype").classed("hidden", true); + + // set the element IRI, and labels + d3.select("#element_iriEditor").node().value = element.iri(); + d3.select("#element_labelEditor").node().value = element.labelForCurrentLanguage(); + d3.select("#element_iriEditor").node().title = element.iri(); + + d3.select("#element_iriEditor") + .on("change", function (){ + var elementIRI = element.iri(); + var prefixed = graph.options().prefixModule().getPrefixRepresentationForFullURI(elementIRI); + if ( prefixed === d3.select("#element_iriEditor").node().value ) { + console.log("Iri is identical, nothing has changed!"); + return; + } + + changeIriForElement(element); + }) + .on("keydown", function (){ + d3.event.stopPropagation(); + if ( d3.event.keyCode === 13 ) { + d3.event.preventDefault(); + console.log("IRI CHANGED Via ENTER pressed"); + changeIriForElement(element); + d3.select("#element_iriEditor").node().title = element.iri(); + } + }); + + var forceIRISync = defaultIriValue(element); + d3.select("#element_labelEditor") + .on("change", function (){ + var sanityCheckResult; + console.log("Element changed Label"); + var url = getURLFROMPrefixedVersion(element); + if ( element.iri() !== url ) { + if ( elementTools.isProperty(element) === true ) { + sanityCheckResult = editSidebar.checkProperIriChange(element, url); + if ( sanityCheckResult !== false ) { + graph.options().warningModule().showWarning("Already seen this property", + "Input IRI: " + url + " for element: " + element.labelForCurrentLanguage() + " already been set", + "Continuing with duplicate property!", 1, false, sanityCheckResult); + editSidebar.updateSelectionInformation(element); + return; + } + } + + if ( elementTools.isNode(element) === true ) { + sanityCheckResult = graph.checkIfIriClassAlreadyExist(url); + if ( sanityCheckResult !== false ) { + graph.options().warningModule().showWarning("Already seen this Class", + "Input IRI: " + url + " for element: " + element.labelForCurrentLanguage() + " already been set", + "Restoring previous IRI for Element : " + element.iri(), 2, false, sanityCheckResult); + + editSidebar.updateSelectionInformation(element); + return; + } + } + element.iri(url); + } + changeLabelForElement(element); + editSidebar.updateSelectionInformation(element); // prevents that it will be changed if node is still active + }) + .on("keydown", function (){ + d3.event.stopPropagation(); + if ( d3.event.keyCode === 13 ) { + d3.event.preventDefault(); + var sanityCheckResult; + console.log("Element changed Label"); + var url = getURLFROMPrefixedVersion(element); + if ( element.iri() !== url ) { + if ( elementTools.isProperty(element) === true ) { + sanityCheckResult = editSidebar.checkProperIriChange(element, url); + if ( sanityCheckResult !== false ) { + graph.options().warningModule().showWarning("Already seen this property", + "Input IRI: " + url + " for element: " + element.labelForCurrentLanguage() + " already been set", + "Continuing with duplicate property!", 1, false, sanityCheckResult); + + editSidebar.updateSelectionInformation(element); + return; + } + } + + if ( elementTools.isNode(element) === true ) { + sanityCheckResult = graph.checkIfIriClassAlreadyExist(url); + if ( sanityCheckResult !== false ) { + graph.options().warningModule().showWarning("Already seen this Class", + "Input IRI: " + url + " for element: " + element.labelForCurrentLanguage() + " already been set", + "Restoring previous IRI for Element : " + element.iri(), 2, false, sanityCheckResult); + + editSidebar.updateSelectionInformation(element); + return; + } + } + element.iri(url); + } + changeLabelForElement(element); + } + }) + .on("keyup", function (){ + if ( forceIRISync ) { + var labelName = d3.select("#element_labelEditor").node().value; + var resourceName = labelName.replaceAll(" ", "_"); + var syncedIRI = element.baseIri() + resourceName; + + //element.iri(syncedIRI); + d3.select("#element_iriEditor").node().title = element.iri(); + d3.select("#element_iriEditor").node().value = prefixModule.getPrefixRepresentationForFullURI(syncedIRI); + } + }); + // check if we are allowed to change IRI OR LABEL + d3.select("#element_iriEditor").node().disabled = false; + d3.select("#element_labelEditor").node().disabled = false; + + if ( element.type() === "rdfs:subClassOf" ) { + d3.select("#element_iriEditor").node().value = "http://www.w3.org/2000/01/rdf-schema#subClassOf"; + d3.select("#element_iriEditor").node().title = "http://www.w3.org/2000/01/rdf-schema#subClassOf"; + d3.select("#element_labelEditor").node().value = "Subclass of"; + d3.select("#element_iriEditor").node().disabled = true; + d3.select("#element_labelEditor").node().disabled = true; + } + if ( element.type() === "owl:Thing" ) { + d3.select("#element_iriEditor").node().value = "http://www.w3.org/2002/07/owl#Thing"; + d3.select("#element_iriEditor").node().title = "http://www.w3.org/2002/07/owl#Thing"; + d3.select("#element_labelEditor").node().value = "Thing"; + d3.select("#element_iriEditor").node().disabled = true; + d3.select("#element_labelEditor").node().disabled = true; + } + + if ( element.type() === "owl:disjointWith" ) { + d3.select("#element_iriEditor").node().value = "http://www.w3.org/2002/07/owl#disjointWith"; + d3.select("#element_iriEditor").node().title = "http://www.w3.org/2002/07/owl#disjointWith"; + d3.select("#element_iriEditor").node().disabled = true; + d3.select("#element_labelEditor").node().disabled = true; + } + + if ( element.type() === "rdfs:Literal" ) { + d3.select("#element_iriEditor").node().value = "http://www.w3.org/2000/01/rdf-schema#Literal"; + d3.select("#element_iriEditor").node().title = "http://www.w3.org/2000/01/rdf-schema#Literal"; + d3.select("#element_iriEditor").node().disabled = true; + d3.select("#element_labelEditor").node().disabled = true; + element.iri("http://www.w3.org/2000/01/rdf-schema#Literal"); + } + if ( element.type() === "rdfs:Datatype" ) { + var datatypeEditorSelection = d3.select("#typeEditor_datatype"); + d3.select("#typeEditForm_datatype").classed("hidden", false); + element.iri("http://www.w3.org/2000/01/rdf-schema#Datatype"); + d3.select("#element_iriEditor").node().value = "http://www.w3.org/2000/01/rdf-schema#Datatype"; + d3.select("#element_iriEditor").node().title = "http://www.w3.org/2000/01/rdf-schema#Datatype"; + d3.select("#element_iriEditor").node().disabled = true; + d3.select("#element_labelEditor").node().disabled = true; + + datatypeEditorSelection.node().value = element.dType(); + if ( datatypeEditorSelection.node().value === "undefined" ) { + d3.select("#element_iriEditor").node().disabled = true; // always prevent IRI modifications + d3.select("#element_labelEditor").node().disabled = false; + } + // reconnect the element + datatypeEditorSelection.on("change", function (){ + changeDatatypeType(element); + }); + } + + // add type selector + var typeEditorSelection = d3.select("#typeEditor").node(); + var htmlCollection = typeEditorSelection.children; + var numEntries = htmlCollection.length; + var i; + var elementPrototypes = getElementPrototypes(element); + for ( i = 0; i < numEntries; i++ ) + typeEditorSelection.removeChild(htmlCollection[0]); + + for ( i = 0; i < elementPrototypes.length; i++ ) { + var optA = document.createElement('option'); + optA.innerHTML = elementPrototypes[i]; + typeEditorSelection.appendChild(optA); + } + // set the proper value in the selection + typeEditorSelection.value = element.type(); + d3.select("#typeEditor").on("change", function (){ + elementTypeSelectionChanged(element); + }); + + + // add characteristics selection + var needChar = elementNeedsCharacteristics(element); + d3.select("#property_characteristics_Container").classed("hidden", !needChar); + if ( needChar === true ) { + addElementsCharacteristics(element); + } + var fullURI = d3.select("#element_iriEditor").node().value; + d3.select("#element_iriEditor").node().value = prefixModule.getPrefixRepresentationForFullURI(fullURI); + d3.select("#element_iriEditor").node().title = fullURI; + editSidebar.updateElementWidth(); + } + + }; + + editSidebar.updateGeneralOntologyInfo = function (){ + var preferredLanguage = graph && graph.language ? graph.language() : null; + + // get it from graph.options + var generalMetaObj = graph.options().getGeneralMetaObject(); + if ( generalMetaObj.hasOwnProperty("title") ) { + // title has language to it -.- + if ( typeof generalMetaObj.title === "object" ) { + d3.select("#titleEditor").node().value = languageTools.textInLanguage(generalMetaObj.title, preferredLanguage); + } else + d3.select("#titleEditor").node().value = generalMetaObj.title; + } + if ( generalMetaObj.hasOwnProperty("iri") ) d3.select("#iriEditor").node().value = generalMetaObj.iri; + if ( generalMetaObj.hasOwnProperty("version") ) d3.select("#versionEditor").node().value = generalMetaObj.version; + if ( generalMetaObj.hasOwnProperty("author") ) d3.select("#authorsEditor").node().value = generalMetaObj.author; + + + if ( generalMetaObj.hasOwnProperty("description") ) { + + if ( typeof generalMetaObj.description === "object" ) + d3.select("#descriptionEditor").node().value = + languageTools.textInLanguage(generalMetaObj.description, preferredLanguage); + else + d3.select("#descriptionEditor").node().value = generalMetaObj.description; + } + else + d3.select("#descriptionEditor").node().value = "No Description"; + }; + + editSidebar.updateElementWidth = function (){ + var height = window.innerHeight - 40; + var lsb_offset = d3.select("#logo").node().getBoundingClientRect().height + 5; + var lsb_height = height - lsb_offset; + d3.select("#containerForLeftSideBar").style("top", lsb_offset + "px"); + d3.select("#leftSideBarCollapseButton").style("top", lsb_offset + "px"); + d3.select("#containerForLeftSideBar").style("height", lsb_height + "px"); + + var div_width = d3.select("#generalDetailsEdit").node().getBoundingClientRect().width; + div_width += 10; + + var title_labelWidth = d3.select("#titleEditor-label").node().getBoundingClientRect().width + 20; + var iri_labelWidth = d3.select("#iriEditor-label").node().getBoundingClientRect().width + 20; + var version_labelWidth = d3.select("#versionEditor-label").node().getBoundingClientRect().width + 20; + var author_labelWidth = d3.select("#authorsEditor-label").node().getBoundingClientRect().width + 20; + //find max width; + var maxW = 0; + maxW = Math.max(maxW, title_labelWidth); + maxW = Math.max(maxW, iri_labelWidth); + maxW = Math.max(maxW, version_labelWidth); + maxW = Math.max(maxW, author_labelWidth); + + var meta_inputWidth = div_width - maxW - 10; + + d3.select("#titleEditor").style("width", meta_inputWidth + "px"); + d3.select("#iriEditor").style("width", meta_inputWidth + "px"); + d3.select("#versionEditor").style("width", meta_inputWidth + "px"); + d3.select("#authorsEditor").style("width", meta_inputWidth + "px"); + + + var elementIri_width = d3.select("#element_iriEditor-label").node().getBoundingClientRect().width + 20; + var elementLabel_width = d3.select("#element_labelEditor-label").node().getBoundingClientRect().width + 20; + var elementType_width = d3.select("#typeEditor-label").node().getBoundingClientRect().width + 20; + var elementDType_width = d3.select("#typeEditor_datatype-label").node().getBoundingClientRect().width + 20; + + maxW = 0; + maxW = Math.max(maxW, elementIri_width); + maxW = Math.max(maxW, elementLabel_width); + maxW = Math.max(maxW, elementType_width); + maxW = Math.max(maxW, elementDType_width); + var selectedElement_inputWidth = div_width - maxW - 10; + + d3.select("#element_iriEditor").style("width", selectedElement_inputWidth + "px"); + d3.select("#element_labelEditor").style("width", selectedElement_inputWidth + "px"); + d3.select("#typeEditor").style("width", selectedElement_inputWidth + 4 + "px"); + d3.select("#typeEditor_datatype").style("width", selectedElement_inputWidth + 4 + "px"); + + // update prefix Element width; + var containerWidth = d3.select("#containerForPrefixURL").node().getBoundingClientRect().width; + if ( containerWidth !== 0 ) { + var inputs = d3.selectAll(".prefixInput"); + if ( inputs.node() ) { + var prefixWidth = d3.selectAll(".prefixInput").node().getBoundingClientRect().width; + d3.selectAll(".prefixURL").style("width", containerWidth - prefixWidth - 45 + "px"); + } + } + }; + + function addElementsCharacteristics( element ){ + // save selected element for checkbox handler + selectedElementForCharacteristics = element; + var i; + // KILL old elements + var charSelectionNode = d3.select("#property_characteristics_Selection"); + var htmlCollection = charSelectionNode.node().children; + if ( htmlCollection ) { + var numEntries = htmlCollection.length; + for ( var q = 0; q < numEntries; q++ ) { + charSelectionNode.node().removeChild(htmlCollection[0]); + } + } + // datatypes kind of ignored by the elementsNeedCharacteristics function + // so we need to check if we are a node or not + if ( element.attributes().indexOf("external") > -1 ) { + // add external span to the div; + var externalCharSpan = charSelectionNode.append("span"); + externalCharSpan.classed("spanForCharSelection", true); + externalCharSpan.node().innerHTML = "external"; + } + var filterContainer, + filterCheckbox; + if ( elementTools.isNode(element) === true ) { + // add the deprecated characteristic; + var arrayOfNodeChars = ["deprecated"]; + for ( i = 0; i < arrayOfNodeChars.length; i++ ) { + filterContainer = charSelectionNode + .append("div") + .classed("checkboxContainer", true) + .style("padding-top", "2px"); + + filterCheckbox = filterContainer.append("input") + .classed("filterCheckbox", true) + .attr("id", "CharacteristicsCheckbox" + i) + .attr("type", "checkbox") + .attr("characteristics", arrayOfNodeChars[i]) + .property("checked", getPresentAttribute(element, arrayOfNodeChars[i])); + // + filterContainer.append("label") + .attr("for", "CharacteristicsCheckbox" + i) + .text(arrayOfNodeChars[i]); + + filterCheckbox.on("click", handleCheckBoxClick); + + } + } + + else { + // add the deprecated characteristic; + var arrayOfPropertyChars = ["deprecated", "inverse functional", "functional", "transitive"]; + if ( elementTools.isDatatypeProperty(element) === true ) { + arrayOfPropertyChars = ["deprecated", "functional"]; + } + for ( i = 0; i < arrayOfPropertyChars.length; i++ ) { + filterContainer = charSelectionNode + .append("div") + .classed("checkboxContainer", true) + .style("padding-top", "2px"); + + filterCheckbox = filterContainer.append("input") + .classed("filterCheckbox", true) + .attr("id", "CharacteristicsCheckbox" + i) + .attr("type", "checkbox") + .attr("characteristics", arrayOfPropertyChars[i]) + .property("checked", getPresentAttribute(element, arrayOfPropertyChars[i])); + // + filterContainer.append("label") + .attr("for", "CharacteristicsCheckbox" + i) + .text(arrayOfPropertyChars[i]); + + filterCheckbox.on("click", handleCheckBoxClick); + + } + } + + + } + + function getPresentAttribute( selectedElement, element ){ + return (selectedElement.attributes().indexOf(element) >= 0); + } + + function handleCheckBoxClick(){ + var checked = this.checked; + var char = this.getAttribute("characteristics"); + if ( checked === true ) { + addAttribute(selectedElementForCharacteristics, char); + } else { + removeAttribute(selectedElementForCharacteristics, char); + } + // graph.executeColorExternalsModule(); + selectedElementForCharacteristics.redrawElement(); + // workaround to have the node still be focused as rendering element + selectedElementForCharacteristics.focused(false); + selectedElementForCharacteristics.toggleFocus(); + + } + + + function addAttribute( selectedElement, char ){ + if ( selectedElement.attributes().indexOf(char) === -1 ) { + // not found add it + var attr = selectedElement.attributes(); + attr.push(char); + selectedElement.attributes(attr); + }// indications string update; + if ( selectedElement.indications().indexOf(char) === -1 ) { + var indications = selectedElement.indications(); + indications.push(char); + selectedElement.indications(indications); + } + // add visual attributes + var visAttr; + if ( selectedElement.visualAttributes().indexOf(char) === -1 ) { + visAttr = selectedElement.visualAttributes(); + visAttr.push(char); + selectedElement.visualAttributes(visAttr); + } + if ( getPresentAttribute(selectedElement, "external") && getPresentAttribute(selectedElement, "deprecated") ) { + visAttr = selectedElement.visualAttributes(); + var visInd = visAttr.indexOf("external"); + if ( visInd > -1 ) { + visAttr.splice(visInd, 1); + } + selectedElement.visualAttributes(visAttr); + } + + } + + function removeAttribute( selectedElement, element ){ + var attr = selectedElement.attributes(); + var indications = selectedElement.indications(); + var visAttr = selectedElement.visualAttributes(); + var attrInd = attr.indexOf(element); + if ( attrInd >= 0 ) { + attr.splice(attrInd, 1); + } + var indInd = indications.indexOf(element); + if ( indInd > -1 ) { + indications.splice(indInd, 1); + } + var visInd = visAttr.indexOf(element); + if ( visInd > -1 ) { + visAttr.splice(visInd, 1); + } + selectedElement.attributes(attr); + selectedElement.indications(indications); + selectedElement.visualAttributes(visAttr); + if ( element === "deprecated" ) { + // set its to its original Style + //typeBaseThign + // todo : fix all different types + if ( selectedElement.type() === "owl:Class" ) selectedElement.styleClass("class"); + if ( selectedElement.type() === "owl:DatatypeProperty" ) selectedElement.styleClass("datatypeproperty"); + if ( selectedElement.type() === "owl:ObjectProperty" ) selectedElement.styleClass("objectproperty"); + if ( selectedElement.type() === "owl:disjointWith" ) selectedElement.styleClass("disjointwith"); + } + } + + + function elementNeedsCharacteristics( element ){ + //TODO: Add more types + if ( element.type() === "owl:Thing" || + element.type() === "rdfs:subClassOf" || + element.type() === "rdfs:Literal" || + element.type() === "rdfs:Datatype" || + element.type() === "rdfs:disjointWith" ) + return false; + + // if (element.attributes().indexOf("external")|| + // element.attributes().indexOf("deprecated")) + // return true; + return true; + + } + + function elementTypeSelectionChanged( element ){ + if ( elementTools.isNode(element) ) { + if ( graph.changeNodeType(element) === false ) { + //restore old value + + if ( elementTools.isDatatype(element) === true ) { + + } + editSidebar.updateSelectionInformation(element); + } + } + + if ( elementTools.isProperty(element) ) { + if ( graph.changePropertyType(element) === false ) { + //restore old value + editSidebar.updateSelectionInformation(element); + + } + } + + } + + function getElementPrototypes( selectedElement ){ + var availiblePrototypes = []; + // TODO the text should be also complied with the prefixes loaded into the ontology + if ( elementTools.isProperty(selectedElement) ) { + if ( selectedElement.type() === "owl:DatatypeProperty" ) + availiblePrototypes.push("owl:DatatypeProperty"); + else { + availiblePrototypes.push("owl:ObjectProperty"); + // handling loops ! + if ( selectedElement.domain() !== selectedElement.range() ) { + availiblePrototypes.push("rdfs:subClassOf"); + } + availiblePrototypes.push("owl:disjointWith"); + availiblePrototypes.push("owl:allValuesFrom"); + availiblePrototypes.push("owl:someValuesFrom"); + } + return availiblePrototypes; + } + if ( selectedElement.renderType() === "rect" ) { + availiblePrototypes.push("rdfs:Literal"); + availiblePrototypes.push("rdfs:Datatype"); + } else { + availiblePrototypes.push("owl:Class"); + availiblePrototypes.push("owl:Thing"); + // TODO: ADD MORE TYPES + // availiblePrototypes.push("owl:complementOf"); + // availiblePrototypes.push("owl:disjointUnionOf"); + } + return availiblePrototypes; + } + + + function setupCollapsing(){ + // TODO : Decision , for now I want to have the control over the collapse expand operation of the + // TODO : elements, otherwise the old approach will also randomly collapse other containers + + // adapted version of this example: http://www.normansblog.de/simple-jquery-accordion/ + function collapseContainers( containers ){ + containers.classed("hidden", true); + } + + function expandContainers( containers ){ + containers.classed("hidden", false); + } + + var triggers = d3.selectAll(".accordion-trigger"); + + // Collapse all inactive triggers on startup + // collapseContainers(d3.selectAll(".accordion-trigger:not(.accordion-trigger-active) + div")); + + triggers.on("click", function (){ + var selectedTrigger = d3.select(this); + if ( selectedTrigger.classed("accordion-trigger-active") ) { + // Collapse the active (which is also the selected) trigger + collapseContainers(d3.select(selectedTrigger.node().nextElementSibling)); + selectedTrigger.classed("accordion-trigger-active", false); + } else { + // Collapse the other trigger ... + // collapseContainers(d3.selectAll(".accordion-trigger-active + div")); + + // ... and expand the selected one + expandContainers(d3.select(selectedTrigger.node().nextElementSibling)); + selectedTrigger.classed("accordion-trigger-active", true); + } + editSidebar.updateElementWidth(); + }); + } + + return editSidebar; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 341: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( graph ){ + var configMenu = {}, + checkboxes = []; + + + configMenu.setup = function (){ + var menuEntry = d3.select("#m_modes"); + menuEntry.on("mouseover", function (){ + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + }); + + addCheckBox("showZoomSlider", "Zoom controls", "#zoomSliderOption", graph.options().zoomSlider().showSlider, 0); + addLabelWidthSlider("#maxLabelWidthSliderOption", "maxLabelWidth", "Max label width", graph.options().maxLabelWidth); + }; + + + function addLabelWidthSlider( selector, identifier, label, onChangeFunction ){ + var sliderContainer, + sliderValueLabel; + + sliderContainer = d3.select(selector) + .append("div") + .classed("distanceSliderContainer", true); + + var slider = sliderContainer.append("input") + .attr("id", identifier + "Slider") + .attr("type", "range") + .attr("min", 20) + .attr("max", 600) + .attr("value", onChangeFunction()) + .attr("step", 10); + sliderContainer.append("label") + .classed("description", true) + .attr("for", identifier + "Slider") + .attr("id", identifier + "DescriptionLabel") + .text(label); + sliderValueLabel = sliderContainer.append("label") + .classed("value", true) + .attr("for", identifier + "Slider") + .attr("id", identifier + "valueLabel") + .text(onChangeFunction()); + + slider.on("input", function (){ + var value = slider.property("value"); + onChangeFunction(value); + sliderValueLabel.text(value); + if ( graph.options().dynamicLabelWidth() === true ) + graph.animateDynamicLabelWidth(); + }); + + // add wheel event to the slider + slider.on("wheel", function (){ + if ( slider.node().disabled === true ) return; + var wheelEvent = d3.event; + var offset; + if ( wheelEvent.deltaY < 0 ) offset = 10; + if ( wheelEvent.deltaY > 0 ) offset = -10; + var oldVal = parseInt(slider.property("value")); + var newSliderValue = oldVal + offset; + if ( newSliderValue !== oldVal ) { + slider.property("value", newSliderValue); + onChangeFunction(newSliderValue); + slider.on("input")(); // << set text and update the graphStyles + } + d3.event.preventDefault(); + }); + } + + function addCheckBox( identifier, modeName, selector, onChangeFunc, updateLvl ){ + var configOptionContainer = d3.select(selector) + .append("div") + .classed("checkboxContainer", true); + var configCheckbox = configOptionContainer.append("input") + .classed("moduleCheckbox", true) + .attr("id", identifier + "ConfigCheckbox") + .attr("type", "checkbox") + .property("checked", onChangeFunc()); + + + configCheckbox.on("click", function ( silent ){ + var isEnabled = configCheckbox.property("checked"); + onChangeFunc(isEnabled); + if ( silent !== true ) { + // updating graph when silent is false or the parameter is not given. + if ( updateLvl === 1 ) { + graph.lazyRefresh(); + //graph.redrawWithoutForce + } + if ( updateLvl === 2 ) { + graph.update(); + } + + if ( updateLvl === 3 ) { + graph.updateDraggerElements(); + } + } + + }); + checkboxes.push(configCheckbox); + configOptionContainer.append("label") + .attr("for", identifier + "ConfigCheckbox") + .text(modeName); + } + + configMenu.setCheckBoxValue = function ( identifier, value ){ + for ( var i = 0; i < checkboxes.length; i++ ) { + var cbdId = checkboxes[i].attr("id"); + if ( cbdId === identifier ) { + checkboxes[i].property("checked", value); + break; + } + } + }; + + configMenu.getCheckBoxValue = function ( id ){ + for ( var i = 0; i < checkboxes.length; i++ ) { + var cbdId = checkboxes[i].attr("id"); + if ( cbdId === id ) { + return checkboxes[i].property("checked"); + } + } + }; + + configMenu.updateSettings = function (){ + var silent = true; + checkboxes.forEach(function ( checkbox ){ + checkbox.on("click")(silent); + }); + }; + + return configMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 342: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( graph ){ + /** some constants **/ + var PREDEFINED = 0, + FILE_UPLOAD = 1, + JSON_URL = 2, + IRI_URL = 3; + + var PROGRESS_BAR_ERROR = 0, + PROGRESS_BAR_BUSY = 1, + PROGRESS_BAR_PERCENT = 2, + progressBarMode = 1; + + var loadingWasSuccessFul = false; + var missingImportsWarning = false; + var showLoadingDetails = false; + var visibilityStatus = true; + + var DEFAULT_JSON_NAME = "ontology"; // This file is loaded by default + var conversion_sessionId; + + /** variable defs **/ + var loadingModule = {}, + menuContainer = d3.select("#loading-info"), + loadingInfoContainer = d3.select("#loadingInfo-container"), + detailsButton = d3.select("#show-loadingInfo-button"), + closeButton = d3.select("#loadingIndicator_closeButton"), + ontologyMenu, + ontologyIdentifierFromURL; + + /** functon defs **/ + loadingModule.checkForScreenSize = function (){ + // checks for window size and adjusts the loading indicator + var w = graph.options().width(), + h = graph.options().height(); + + if ( w < 270 ) { + d3.select("#loading-info").classed("hidden", true); + } else { + // check if it should be visible + if ( visibilityStatus === true ) { + d3.select("#loading-info").classed("hidden", false); + } else { + d3.select("#loading-info").classed("hidden", true); + } + } + if ( h < 150 ) { + d3.select("#loadingInfo_msgBox").classed("hidden", true); + } else { + d3.select("#loadingInfo_msgBox").classed("hidden", false); + } + if ( h < 80 ) { + d3.select("#progressBarContext").classed("hidden", true); + d3.select("#layoutLoadingProgressBarContainer").style("height", "20px"); + } else { + d3.select("#progressBarContext").classed("hidden", false); + d3.select("#layoutLoadingProgressBarContainer").style("height", "50px"); + } + }; + + loadingModule.getMessageVisibilityStatus = function (){ + return visibilityStatus; + }; + + loadingModule.getProgressBarMode = function (){ + return progressBarMode; + }; + + loadingModule.successfullyLoadedOntology = function (){ + return loadingWasSuccessFul; + }; + + loadingModule.missingImportsWarning = function (){ + return missingImportsWarning; + }; + + loadingModule.setOntologyMenu = function ( m ){ + ontologyMenu = m; + }; + + loadingModule.showErrorDetailsMessage = function (){ + loadingModule.showLoadingIndicator(); + loadingModule.expandDetails(); + d3.select("#loadingIndicator_closeButton").classed("hidden", true); + loadingModule.scrollDownDetails(); + }; + + loadingModule.showWarningDetailsMessage = function (){ + d3.select("#currentLoadingStep").style("color", "#ff0"); + loadingModule.showLoadingIndicator(); + loadingModule.expandDetails(); + d3.select("#loadingIndicator_closeButton").classed("hidden", false); + loadingModule.scrollDownDetails(); + }; + + loadingModule.scrollDownDetails = function (){ + var scrollingElement = d3.select("#loadingInfo-container").node(); + scrollingElement.scrollTop = scrollingElement.scrollHeight; + }; + + loadingModule.hideLoadingIndicator = function (){ + d3.select("#loading-info").classed("hidden", true); + visibilityStatus = false; + }; + + loadingModule.showLoadingIndicator = function (){ + d3.select("#loading-info").classed("hidden", false); + visibilityStatus = true; + + }; + + /** -- SETUP -- **/ + loadingModule.setup = function (){ + // create connections for close and details button; + loadingInfoContainer.classed("hidden", !showLoadingDetails); + detailsButton.on("click", function (){ + showLoadingDetails = !showLoadingDetails; + loadingInfoContainer.classed("hidden", !showLoadingDetails); + detailsButton.classed("accordion-trigger-active", showLoadingDetails); + }); + + closeButton.on("click", function (){ + menuContainer.classed("hidden", true); + }); + loadingModule.setBusyMode(); + }; + + loadingModule.updateSize = function (){ + showLoadingDetails = !(loadingInfoContainer.classed("hidden")); + loadingInfoContainer.classed("hidden", !showLoadingDetails); + detailsButton.classed("accordion-trigger-active", showLoadingDetails); + }; + + loadingModule.getDetailsState = function (){ + return showLoadingDetails; + }; + + loadingModule.expandDetails = function (){ + showLoadingDetails = true; + loadingInfoContainer.classed("hidden", !showLoadingDetails); + detailsButton.classed("accordion-trigger-active", showLoadingDetails); + }; + + loadingModule.collapseDetails = function (){ + showLoadingDetails = false; + loadingInfoContainer.classed("hidden", !showLoadingDetails); + detailsButton.classed("accordion-trigger-active", showLoadingDetails); + }; + + loadingModule.setBusyMode = function (){ + d3.select("#currentLoadingStep").style("color", "#fff"); + d3.select("#progressBarValue").node().innherHTML = ""; + d3.select("#progressBarValue").style("width", "20%"); + d3.select("#progressBarValue").classed("busyProgressBar", true); + progressBarMode = PROGRESS_BAR_BUSY; + }; + + loadingModule.setSuccessful = function (){ + d3.select("#currentLoadingStep").style("color", "#0f0"); + }; + + loadingModule.setErrorMode = function (){ + d3.select("#currentLoadingStep").style("color", "#f00"); + d3.select("#progressBarValue").style("width", "0%"); + d3.select("#progressBarValue").classed("busyProgressBar", false); + d3.select("#progressBarValue").node().innherHTML = ""; + progressBarMode = PROGRESS_BAR_ERROR; + }; + + loadingModule.setPercentMode = function (){ + d3.select("#currentLoadingStep").style("color", "#fff"); + d3.select("#progressBarValue").classed("busyProgressBar", false); + d3.select("#progressBarValue").node().innherHTML = "0%"; + d3.select("#progressBarValue").style("width", "0%"); + progressBarMode = PROGRESS_BAR_PERCENT; + }; + + loadingModule.setPercentValue = function ( val ){ + d3.select("#progressBarValue").node().innherHTML = val; + }; + + loadingModule.emptyGraphContentError = function (){ + graph.clearGraphData(); + ontologyMenu.append_message_toLastBulletPoint("failed"); + ontologyMenu.append_message_toLastBulletPoint("
    Error: Received empty graph"); + loadingWasSuccessFul = false; + graph.handleOnLoadingError(); + loadingModule.setErrorMode(); + }; + + loadingModule.isThreadCanceled = function (){ + + }; + + loadingModule.initializeLoader = function ( storeCache ){ + if ( storeCache === true && graph.getCachedJsonObj() !== null ) { + // save cached ontology; + var cachedContent = JSON.stringify(graph.getCachedJsonObj()); + var cachedName = ontologyIdentifierFromURL; + ontologyMenu.setCachedOntology(cachedName, cachedContent); + } + conversion_sessionId = -10000; + ontologyMenu.setConversionID(conversion_sessionId); + ontologyMenu.stopLoadingTimer(); + graph.clearGraphData(); + loadingModule.setBusyMode(); + loadingModule.showLoadingIndicator(); + loadingModule.collapseDetails(); + missingImportsWarning = false; + d3.select("#loadingIndicator_closeButton").classed("hidden", true); + ontologyMenu.clearDetailInformation(); + }; + + /** ------------------ URL Interpreter -------------- **/ + loadingModule.parseUrlAndLoadOntology = function ( storeCache ){ + var autoStore = true; + if ( storeCache === false ) { + autoStore = false; + } + + graph.clearAllGraphData(); + loadingModule.initializeLoader(autoStore); + var urlString = String(location); + var parameterArray = identifyParameter(urlString); + ontologyIdentifierFromURL = DEFAULT_JSON_NAME; + loadGraphOptions(parameterArray); // identifies and loads configuration values + var loadingMethod = identifyOntologyLoadingMethod(ontologyIdentifierFromURL); + d3.select("#progressBarValue").node().innerHTML = " "; + switch ( loadingMethod ) { + case 0: + loadingModule.from_presetOntology(ontologyIdentifierFromURL); + break; + case 1: + loadingModule.from_FileUpload(ontologyIdentifierFromURL); + break; + case 2: + loadingModule.from_JSON_URL(ontologyIdentifierFromURL); + break; + case 3: + loadingModule.from_IRI_URL(ontologyIdentifierFromURL); + break; + default: + console.log("Could not identify loading method , or not IMPLEMENTED YET"); + } + }; + + /** ------------------- LOADING --------------------- **/ + // the loading module splits into 3 branches + // 1] PresetOntology Loading + // 2] File Upload + // 3] Load From URL / IRI + + loadingModule.from_JSON_URL = function ( fileName ){ + var filename = decodeURIComponent(fileName.slice("url=".length)); + ontologyIdentifierFromURL = filename; + + var ontologyContent = ""; + if ( ontologyMenu.cachedOntology(filename) ) { + ontologyMenu.append_bulletPoint("Loading already cached ontology: " + filename); + ontologyContent = ontologyMenu.cachedOntology(filename); + loadingWasSuccessFul = true; // cached Ontology should be true; + parseOntologyContent(ontologyContent); + + } else { + // involve the o2v conveter; + ontologyMenu.append_message("Retrieving ontology from JSON URL " + filename); + requestServerTimeStampForJSON_URL(ontologyMenu.callbackLoad_JSON_FromURL, ["read?json=" + filename, filename]); + } + }; + + function requestServerTimeStampForJSON_URL( callback, parameter ){ + d3.xhr("serverTimeStamp", "application/text", function ( error, request ){ + if ( error ) { + // could not get server timestamp -> no connection to owl2vowl + ontologyMenu.append_bulletPoint("Could not establish connection to OWL2VOWL service"); + fallbackForJSON_URL(callback, parameter); + } else { + conversion_sessionId = request.responseText; + ontologyMenu.setConversionID(conversion_sessionId); + parameter.push(conversion_sessionId); + callback(parameter); + } + }); + + } + + loadingModule.requestServerTimeStampForDirectInput = function ( callback, text ){ + d3.xhr("serverTimeStamp", "application/text", function ( error, request ){ + if ( error ) { + // could not get server timestamp -> no connection to owl2vowl + ontologyMenu.append_bulletPoint("Could not establish connection to OWL2VOWL service"); + loadingModule.setErrorMode(); + ontologyMenu.append_message_toLastBulletPoint("
    Could not connect to OWL2VOWL service "); + loadingModule.showErrorDetailsMessage(); + d3.select("#progressBarValue").style("width", "0%"); + d3.select("#progressBarValue").classed("busyProgressBar", false); + d3.select("#progressBarValue").text("0%"); + + } else { + conversion_sessionId = request.responseText; + ontologyMenu.setConversionID(conversion_sessionId); + callback(text, ["conversionID" + conversion_sessionId, conversion_sessionId]); + } + }); + }; + + loadingModule.from_IRI_URL = function ( fileName ){ + // owl2vowl converters the given ontology url and returns json file; + var filename = decodeURIComponent(fileName.slice("iri=".length)); + ontologyIdentifierFromURL = filename; + + var ontologyContent = ""; + if ( ontologyMenu.cachedOntology(filename) ) { + ontologyMenu.append_bulletPoint("Loading already cached ontology: " + filename); + ontologyContent = ontologyMenu.cachedOntology(filename); + loadingWasSuccessFul = true; // cached Ontology should be true; + parseOntologyContent(ontologyContent); + } else { + // involve the o2v conveter; + var encoded = encodeURIComponent(filename); + ontologyMenu.append_bulletPoint("Retrieving ontology from IRI: " + filename); + requestServerTimeStampForIRI_Converte(ontologyMenu.callbackLoad_Ontology_FromIRI, ["convert?iri=" + encoded, filename]); + } + }; + + loadingModule.fromFileDrop = function ( fileName, file ){ + d3.select("#progressBarValue").node().innerHTML = " "; + loadingModule.initializeLoader(false); + + ontologyMenu.append_bulletPoint("Retrieving ontology from dropped file: " + fileName); + var ontologyContent = ""; + + // two options here + //1] Direct Json Upload + if ( fileName.match(/\.json$/) ) { + ontologyMenu.setConversionID(-10000); + var reader = new FileReader(); + reader.readAsText(file); + reader.onload = function (){ + ontologyContent = reader.result; + ontologyIdentifierFromURL = fileName; + parseOntologyContent(ontologyContent); + }; + } else { + //2] File Upload to OWL2VOWL Converter + // 1) check if we can get a timeStamp; + var parameterArray = [file, fileName]; + requestServerTimeStamp(ontologyMenu.callbackLoadFromOntology, parameterArray); + } + }; + + + loadingModule.from_FileUpload = function ( fileName ){ + loadingModule.setBusyMode(); + var filename = decodeURIComponent(fileName.slice("file=".length)); + ontologyIdentifierFromURL = filename; + var ontologyContent = ""; + if ( ontologyMenu.cachedOntology(filename) ) { + ontologyMenu.append_bulletPoint("Loading already cached ontology: " + filename); + ontologyContent = ontologyMenu.cachedOntology(filename); + loadingWasSuccessFul = true; // cached Ontology should be true; + parseOntologyContent(ontologyContent); + + } else { + // d3.select("#currentLoadingStep").node().innerHTML="Loading ontology from file "+ filename; + ontologyMenu.append_bulletPoint("Retrieving ontology from file: " + filename); + // get the file + var selectedFile = d3.select("#file-converter-input").property("files")[0]; + // No selection -> this was triggered by the iri. Unequal names -> reuploading another file + if ( !selectedFile || (filename && (filename !== selectedFile.name)) ) { + ontologyMenu.append_message_toLastBulletPoint("
    No cached version of \"" + filename + "\" was found.
    Please reupload the file."); + loadingModule.setErrorMode(); + d3.select("#progressBarValue").classed("busyProgressBar", false); + graph.handleOnLoadingError(); + return; + } else { + filename = selectedFile.name; + } + + + // two options here + //1] Direct Json Upload + if ( filename.match(/\.json$/) ) { + ontologyMenu.setConversionID(-10000); + var reader = new FileReader(); + reader.readAsText(selectedFile); + reader.onload = function (){ + ontologyContent = reader.result; + ontologyIdentifierFromURL = filename; + parseOntologyContent(ontologyContent); + }; + } else { + //2] File Upload to OWL2VOWL Converter + // 1) check if we can get a timeStamp; + var parameterArray = [selectedFile, filename]; + requestServerTimeStamp(ontologyMenu.callbackLoadFromOntology, parameterArray); + } + } + }; + + function fallbackForJSON_URL( callback, parameter ){ + ontologyMenu.append_message_toLastBulletPoint("
    Trying to convert with other communication protocol."); + callback(parameter); + + } + + function fallbackConversion( parameter ){ + ontologyMenu.append_message_toLastBulletPoint("
    Trying to convert with other communication protocol."); + var file = parameter[0]; + var name = parameter[1]; + var formData = new FormData(); + formData.append("ontology", file); + + var xhr = new XMLHttpRequest(); + xhr.open("POST", "convert", true); + var ontologyContent = ""; + xhr.onload = function (){ + if ( xhr.status === 200 ) { + ontologyContent = xhr.responseText; + ontologyMenu.setCachedOntology(name, ontologyContent); + ontologyIdentifierFromURL = name; + missingImportsWarning = true; // using this variable for warnings + ontologyMenu.append_message_toLastBulletPoint("
    Success, but you are using a deprecated OWL2VOWL service!"); + parseOntologyContent(ontologyContent); + } + }; + + // check what this thing is doing; + xhr.onreadystatechange = function (){ + if ( xhr.readyState === 4 && xhr.status === 0 ) { + ontologyMenu.append_message_toLastBulletPoint("
    Old protocol also failed to establish connection to OWL2VOWL service!"); + loadingModule.setErrorMode(); + ontologyMenu.append_bulletPoint("Failed to load ontology"); + ontologyMenu.append_message_toLastBulletPoint("
    Could not connect to OWL2VOWL service "); + loadingModule.showErrorDetailsMessage(); + } + }; + xhr.send(formData); + } + + function requestServerTimeStampForIRI_Converte( callback, parameterArray ){ + d3.xhr("serverTimeStamp", "application/text", function ( error, request ){ + loadingModule.setBusyMode(); + if ( error ) { + // could not get server timestamp -> no connection to owl2vowl + ontologyMenu.append_bulletPoint("Could not establish connection to OWL2VOWL service"); + loadingModule.setErrorMode(); + ontologyMenu.append_bulletPoint("Failed to load ontology"); + ontologyMenu.append_message_toLastBulletPoint("
    Could not connect to OWL2VOWL service "); + loadingModule.showErrorDetailsMessage(); + } else { + conversion_sessionId = request.responseText; + ontologyMenu.setConversionID(conversion_sessionId); + // update paramater for new communication paradigm + parameterArray[0] = parameterArray[0] + "&sessionId=" + conversion_sessionId; + parameterArray.push(conversion_sessionId); + callback(parameterArray); + } + }); + } + + function requestServerTimeStamp( callback, parameterArray ){ + d3.xhr("serverTimeStamp", "application/text", function ( error, request ){ + if ( error ) { + // could not get server timestamp -> no connection to owl2vowl + ontologyMenu.append_bulletPoint("Could not establish connection to OWL2VOWL service"); + fallbackConversion(parameterArray); // tries o2v version0.3.4 communication + } else { + conversion_sessionId = request.responseText; + ontologyMenu.setConversionID(conversion_sessionId); + console.log("Request Session ID:" + conversion_sessionId); + callback(parameterArray[0], parameterArray[1], conversion_sessionId); + } + }); + } + + loadingModule.directInput = function ( text ){ + ontologyMenu.clearDetailInformation(); + parseOntologyContent(text); + }; + + loadingModule.loadFromOWL2VOWL = function ( ontoContent, filename ){ + loadingWasSuccessFul = false; + + var old = d3.select("#bulletPoint_container").node().innerHTML; + if ( old.indexOf("(with warnings)") !== -1 ) { + missingImportsWarning = true; + } + + if ( ontologyMenu.cachedOntology(ontoContent) ) { + ontologyMenu.append_bulletPoint("Loading already cached ontology: " + filename); + parseOntologyContent(ontoContent); + } else { // set parse the ontology content; + parseOntologyContent(ontoContent); + } + }; + + loadingModule.from_presetOntology = function ( selectedOntology ){ + ontologyMenu.append_bulletPoint("Retrieving ontology: " + selectedOntology); + loadPresetOntology(selectedOntology); + }; + + function loadPresetOntology( ontology ){ + // check if already cached in ontology menu? + var f2r; + var loadingNewOntologyForEditor=false; + if ( ontology.indexOf("new_ontology") !== -1 ) { + loadingModule.hideLoadingIndicator(); + graph.showEditorHintIfNeeded(); + f2r = "./data/new_ontology.json"; + loadingNewOntologyForEditor=true; + } + + loadingWasSuccessFul = false; + var ontologyContent = ""; + if ( ontologyMenu.cachedOntology(ontology) ) { + ontologyMenu.append_bulletPoint("Loading already cached ontology: " + ontology); + ontologyContent = ontologyMenu.cachedOntology(ontology); + loadingWasSuccessFul = true; // cached Ontology should be true; + loadingModule.showLoadingIndicator(); + parseOntologyContent(ontologyContent); + + } else { + // read the file name + + var fileToRead = "./data/" + ontology + ".json"; + if ( f2r ) { + fileToRead = f2r; + } // overwrite the newOntology Index + // read file + d3.xhr(fileToRead, "application/json", function ( error, request ){ + var loadingSuccessful = !error; + if ( loadingSuccessful ) { + ontologyContent = request.responseText; + parseOntologyContent(ontologyContent); + } else { + + if (loadingNewOntologyForEditor){ + ontologyContent = '{\n' + + ' "_comment": "Empty ontology for WebVOWL Editor",\n' + + ' "header": {\n' + + ' "languages": [\n' + + ' "en"\n' + + ' ],\n' + + ' "baseIris": [\n' + + ' "http://www.w3.org/2000/01/rdf-schema"\n' + + ' ],\n' + + ' "iri": "http://visualdataweb.org/newOntology/",\n' + + ' "title": {\n' + + ' "en": "New ontology"\n' + + ' },\n' + + ' "description": {\n' + + ' "en": "New ontology description"\n' + + ' }\n' + + ' },\n' + + ' "namespace": [],\n' + + ' "metrics": {\n' + + ' "classCount": 0,\n' + + ' "datatypeCount": 0,\n' + + ' "objectPropertyCount": 0,\n' + + ' "datatypePropertyCount": 0,\n' + + ' "propertyCount": 0,\n' + + ' "nodeCount": 0,\n' + + ' "individualCount": 0\n' + + ' }\n' + + '}\n'; + parseOntologyContent(ontologyContent); + }else{ + // some error occurred + ontologyMenu.append_bulletPoint("Failed to load: " + ontology); + if (error.status===0){ // assumption this is CORS error when running locally (error status == 0) + ontologyMenu.append_message_toLastBulletPoint(" ERROR STATUS: " + error.status); + if (window.location.toString().startsWith("file:/")){ + ontologyMenu.append_message_toLastBulletPoint("

    WebVOWL runs in a local instance.

    "); + ontologyMenu.append_message_toLastBulletPoint("

    CORS prevents to automatically load files on host system.

    "); + ontologyMenu.append_message_toLastBulletPoint("

    You can load preprocessed ontologies (i.e. VOWL-JSON files) using the upload feature in the ontology menu or by dragging the files and dropping them on the canvas.

    "); + ontologyMenu.append_message_toLastBulletPoint("

    Hint: Note that the conversion of ontologies into the VOWL-JSON format is not part of WebVOWL but requires an additional converter such as OWL2VOWL.

    "); + ontologyMenu.append_message_toLastBulletPoint("

    Ontologies can be created using the editor mode (i.e. activate editing mode in Modes menu and create a new ontology using the Ontology menu.

    "); + } + }else { + ontologyMenu.append_message_toLastBulletPoint(" ERROR STATUS: " + error.status); + } + + + + graph.handleOnLoadingError(); + loadingModule.setErrorMode(); + } + } + }); + } + } + + + /** -- PARSE JSON CONTENT -- **/ + function parseOntologyContent( content ){ + + ontologyMenu.append_bulletPoint("Reading ontology graph ... "); + var _loader = ontologyMenu.getLoadingFunction(); + _loader(content, ontologyIdentifierFromURL, "noAlternativeNameYet"); + } + + loadingModule.notValidJsonFile = function (){ + graph.clearGraphData(); + ontologyMenu.append_message_toLastBulletPoint(" failed"); + ontologyMenu.append_message_toLastBulletPoint("
    Error: Received empty graph"); + loadingWasSuccessFul = false; + graph.handleOnLoadingError(); + + }; + + loadingModule.validJsonFile = function (){ + ontologyMenu.append_message_toLastBulletPoint("done"); + loadingWasSuccessFul = true; + }; + + + /** --- HELPER FUNCTIONS **/ + + function identifyParameter( url ){ + var numParameters = (url.match(/#/g) || []).length; + // create parameters array + var paramArray = []; + if ( numParameters > 0 ) { + var tokens = url.split("#"); + // skip the first token since it is the address of the server + for ( var i = 1; i < tokens.length; i++ ) { + if ( tokens[i].length === 0 ) { + // this token belongs actually to the last paramArray + paramArray[paramArray.length - 1] = paramArray[paramArray.length - 1] + "#"; + } else { + paramArray.push(tokens[i]); + } + } + } + return paramArray; + } + + + function loadGraphOptions( parameterArray ){ + var optString = "opts="; + + function loadDefaultConfig(){ + graph.options().setOptionsFromURL(graph.options().defaultConfig(), false); + } + + function loadCustomConfig( opts ){ + var changeEditingFlag = false; + var defObj = graph.options().defaultConfig(); + for ( var i = 0; i < opts.length; i++ ) { + var keyVal = opts[i].split('='); + if ( keyVal[0] === "editorMode" ) { + changeEditingFlag = true; + } + defObj[keyVal[0]] = keyVal[1]; + } + graph.options().setOptionsFromURL(defObj, changeEditingFlag); + } + + function identifyOptions( paramArray ){ + if ( paramArray[0].indexOf(optString) >= 0 ) { + // parse the parameters; + var parameterLength = paramArray[0].length; + var givenOptionsStr = paramArray[0].substr(5, parameterLength - 6); + var optionsArray = givenOptionsStr.split(';'); + loadCustomConfig(optionsArray); + } else { + ontologyIdentifierFromURL = paramArray[0]; + loadDefaultConfig(); + } + } + + function identifyOptionsAndOntology( paramArray ){ + + if ( paramArray[0].indexOf(optString) >= 0 ) { + // parse the parameters; + var parameterLength = paramArray[0].length; + var givenOptionsStr = paramArray[0].substr(5, parameterLength - 6); + var optionsArray = givenOptionsStr.split(';'); + loadCustomConfig(optionsArray); + } else { + loadDefaultConfig(); + } + ontologyIdentifierFromURL = paramArray[1]; + } + + switch ( parameterArray.length ) { + case 0: + loadDefaultConfig(); + break; + case 1: + identifyOptions(parameterArray); + break; + case 2: + identifyOptionsAndOntology(parameterArray); + break; + default : + console.log("To many input parameters , loading default config"); + loadDefaultConfig(); + ontologyIdentifierFromURL = "ERROR_TO_MANY_INPUT_PARAMETERS"; + } + } + + + function identifyOntologyLoadingMethod( url ){ + var iriKey = "iri="; + var urlKey = "url="; + var fileKey = "file="; + + var method = -1; + if ( url.substr(0, fileKey.length) === fileKey ) { + method = FILE_UPLOAD; + } else if ( url.substr(0, urlKey.length) === urlKey ) { + method = JSON_URL; + } else if ( url.substr(0, iriKey.length) === iriKey ) { + method = IRI_URL; + } else { + method = PREDEFINED; + } + return method; + } + + return loadingModule; + } + ; + + + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 343: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( graph ){ + /** variable defs **/ + var warningModule = {}; + var superContainer = d3.select("#WarningErrorMessages"); + var _messageContainers = []; + var _messageContext = []; + var _visibleStatus = []; + + var _filterHintId; + var _editorHintId; + var _messageId = -1; + superContainer.style("display", "inline-block"); + var cssStyleIndex = 0; + var styleSelectorIndex = 2; + + + // helper for standalone webvowl in chrome + function createCSSSelector( name, rules ){ + var style = document.createElement('style'); + style.type = 'text/css'; + document.getElementsByTagName('head')[0].appendChild(style); + if ( !(style.sheet || {}).insertRule ) + (style.styleSheet || style.sheet).addRule(name, rules); + else + style.sheet.insertRule(name + "{" + rules + "}", 0); + } + + + function findCSS_Index(){ + createCSSSelector("@keyframes msg_CollapseAnimation", " 0% { top: 0; } 100% { top: -400px;}"); + console.log(document.styleSheets ); + } + + findCSS_Index(); + + warningModule.addMessageBox = function (){ + + // add a container; + _messageId++; + var messageContainer = d3.select("#WarningErrorMessages").append("div"); + messageContainer.node().id = "messageContainerId_" + _messageId; + + var messageContext = messageContainer.append("div"); + messageContext.node().id = "messageContextId_" + _messageId; + messageContext.style("top", "0"); + messageContainer.style("position", "relative"); + messageContainer.style("width", "100%"); + //save in array + _messageContainers.push(messageContainer); + _messageContext.push(messageContext); + + // add animation to the container + messageContainer.node().addEventListener("animationend", _msgContainer_animationEnd); + + // set visible flag that is used in end of animation + _visibleStatus[_messageId] = true; + return _messageId; + }; + + function _msgContainer_animationEnd(){ + var containerId = this.id; + var tokens = containerId.split("_")[1]; + var mContainer = d3.select("#" + containerId); + // get number of children + mContainer.classed("hidden", !_visibleStatus[tokens]); + // clean up DOM + if ( !_visibleStatus[tokens] ) { + mContainer.remove(); + _messageContext[tokens] = null; + _messageContainers[tokens] = null; + } + // remove event listener + var c = d3.select(this); + // c.node().removeEventListener("animationend",_msgContainer_animationEnd); + } + + warningModule.createMessageContext = function ( id ){ + var warningContainer = _messageContext[id]; + var moduleContainer = _messageContainers[id]; + var generalHint = warningContainer.append('div'); + generalHint.node().innerHTML = ""; + _editorHintId = id; + /** Editing mode activated. You can now modify an existing ontology or create a new one via the ontology menu. You can save any ontology using the export menu (and exporting it as TTL file).**/ + generalHint.node().innerHTML += "Editing mode activated.
    " + + "You can now modify an existing ontology or create a new one via the ontology menu.
    " + + "You can save any ontology using the export menu (and exporting it as TTL file)."; + + generalHint.style("padding", "5px"); + generalHint.style("line-height", "1.2em"); + generalHint.style("font-size", "1.2em"); + + + var ul = warningContainer.append('ul'); + ul.append('li').node().innerHTML = "Create a class with double click / tap on empty canvas area."; + ul.append('li').node().innerHTML = "Edit names with double click / tap on element."; + ul.append('li').node().innerHTML = "Selection of default constructors is provided in the left sidebar."; + ul.append('li').node().innerHTML = "Additional editing functionality is provided in the right sidebar."; + + + var gotItButton = warningContainer.append("label"); + gotItButton.node().id = "killWarningErrorMessages_" + id; + gotItButton.node().innerHTML = "Got It"; + gotItButton.on("click", warningModule.closeMessage); + + moduleContainer.classed("hidden", false); + moduleContainer.style("-webkit-animation-name", "warn_ExpandAnimation"); + moduleContainer.style("-webkit-animation-duration", "0.5s"); + }; + + warningModule.showMessage = function ( id ){ + var moduleContainer = _messageContainers[id]; + moduleContainer.classed("hidden", false); + moduleContainer.style("-webkit-animation-name", "warn_ExpandAnimation"); + moduleContainer.style("-webkit-animation-duration", "0.5s"); + }; + + warningModule.closeMessage = function ( id ){ + var nId; + if ( id === undefined ) { + var givenId = this.id; + nId = givenId.split("_")[1]; + } else { + nId = id; + } + if ( id && id.indexOf("_") !== -1 ) { + nId = id.split("_")[1]; + } + _visibleStatus[nId] = false; + // get module; + var moduleContainer = _messageContainers[nId]; + moduleContainer.style("-webkit-animation-name", "warn_CollapseAnimation"); + moduleContainer.style("-webkit-animation-duration", "0.5s"); + + var m_height = moduleContainer.node().getBoundingClientRect().height; + + // find my id in the children + var pNode = moduleContainer.node().parentNode; + + var followingChildren = []; + var pChild = pNode.children; + var pChild_len = pChild.length; + var containerId = moduleContainer.node().id; + var found_me = false; + for ( var i = 0; i < pChild_len; i++ ) { + if ( found_me === true ) { + followingChildren.push(pChild[i].id); + } + + if ( containerId === pChild[i].id ) { + found_me = true; + } + } + + for ( var fc = 0; fc < followingChildren.length; fc++ ) { + var child = d3.select("#" + followingChildren[fc]); + // get the document style and overwrite it; + var superCss = document.styleSheets[styleSelectorIndex].cssRules[cssStyleIndex]; + // remove the existing 0% and 100% rules + superCss.deleteRule("0%"); + superCss.deleteRule("100%"); + + superCss.appendRule("0% {top: 0;}"); + superCss.appendRule("100% {top: -" + m_height + "px;"); + + child.style("-webkit-animation-name", "msg_CollapseAnimation"); + child.style("-webkit-animation-duration", "0.5s"); + child.node().addEventListener("animationend", _child_animationEnd); + } + }; + + function _child_animationEnd(){ + var c = d3.select(this); + c.style("-webkit-animation-name", ""); + c.style("-webkit-animation-duration", ""); + c.node().removeEventListener("animationend", _child_animationEnd); + } + + warningModule.closeFilterHint = function (){ + if ( _messageContainers[_filterHintId] ) { + _messageContainers[_filterHintId].classed("hidden", true); + _messageContainers[_filterHintId].remove(); + _messageContainers[_filterHintId] = null; + _messageContext[_filterHintId] = null; + _visibleStatus[_filterHintId] = false; + } + }; + + warningModule.showEditorHint = function (){ + var id = warningModule.addMessageBox(); + warningModule.createMessageContext(id); + }; + + warningModule.showExporterWarning=function (){ + warningModule.showWarning("Can not export ontology", "Detected unsupported ontology axioms, (e.g. owl:Union)", "Ontology is not exported", 1, false); + }; + + + + warningModule.responseWarning = function ( header, reason, action, callback, parameterArray, forcedWarning ){ + var id = warningModule.addMessageBox(); + var warningContainer = _messageContext[id]; + var moduleContainer = _messageContainers[id]; + _visibleStatus[id] = true; + d3.select("#blockGraphInteractions").classed("hidden", false); + var graphWidth = 0.5 * graph.options().width(); + + if ( header.length > 0 ) { + var head = warningContainer.append("div"); + head.style("padding", "5px"); + var titleHeader = head.append("div"); + // some classes + titleHeader.style("display", "inline-flex"); + titleHeader.node().innerHTML = "Warning:"; + titleHeader.style("padding-right", "3px"); + var msgHeader = head.append("div"); + // some classes + msgHeader.style("display", "inline-flex"); + msgHeader.style("max-width", graphWidth + "px"); + + msgHeader.node().innerHTML = header; + } + if ( reason.length > 0 ) { + var reasonContainer = warningContainer.append("div"); + reasonContainer.style("padding", "5px"); + var reasonHeader = reasonContainer.append("div"); + // some classes + reasonHeader.style("display", "inline-flex"); + reasonHeader.style("padding-right", "3px"); + + reasonHeader.node().innerHTML = "Reason:"; + var msgReason = reasonContainer.append("div"); + // some classes + msgReason.style("display", "inline-flex"); + msgReason.style("max-width", graphWidth + "px"); + msgReason.node().innerHTML = reason; + } + if ( action.length > 0 ) { + var actionContainer = warningContainer.append("div"); + actionContainer.style("padding", "5px"); + var actionHeader = actionContainer.append("div"); + // some classes + actionHeader.style("display", "inline-flex"); + actionHeader.style("padding-right", "8px"); + actionHeader.node().innerHTML = "Action:"; + var msgAction = actionContainer.append("div"); + // some classes + msgAction.style("display", "inline-flex"); + msgAction.style("max-width", graphWidth + "px"); + msgAction.node().innerHTML = action; + } + + var gotItButton = warningContainer.append("label"); + gotItButton.node().id = "killWarningErrorMessages_" + id; + gotItButton.node().innerHTML = "Continue"; + gotItButton.on("click", function (){ + warningModule.closeMessage(this.id); + d3.select("#blockGraphInteractions").classed("hidden", true); + callback(parameterArray[0], parameterArray[1], parameterArray[2], parameterArray[3]); + }); + warningContainer.append("span").node().innerHTML = "|"; + var cancelButton = warningContainer.append("label"); + cancelButton.node().id = "cancelButton_" + id; + cancelButton.node().innerHTML = "Cancel"; + cancelButton.on("click", function (){ + warningModule.closeMessage(this.id); + d3.select("#blockGraphInteractions").classed("hidden", true); + }); + moduleContainer.classed("hidden", false); + moduleContainer.style("-webkit-animation-name", "warn_ExpandAnimation"); + moduleContainer.style("-webkit-animation-duration", "0.5s"); + }; + + warningModule.showFilterHint = function (){ + var id = warningModule.addMessageBox(); + var warningContainer = _messageContext[id]; + var moduleContainer = _messageContainers[id]; + _visibleStatus[id] = true; + + _filterHintId = id; + var generalHint = warningContainer.append('div'); + /** Editing mode activated. You can now modify an existing ontology or create a new one via the ontology menu. You can save any ontology using the export menu (and exporting it as TTL file).**/ + generalHint.node().innerHTML = "Collapsing filter activated.
    " + + "The number of visualized elements has been automatically reduced.
    " + + "Use the degree of collapsing slider in the filter menu to adjust the visualization.

    " + + "Note: A performance decrease could be experienced with a growing amount of visual elements in the graph."; + + + generalHint.style("padding", "5px"); + generalHint.style("line-height", "1.2em"); + generalHint.style("font-size", "1.2em"); + + var gotItButton = warningContainer.append("label"); + gotItButton.node().id = "killFilterMessages_" + id; + gotItButton.node().innerHTML = "Got It"; + gotItButton.on("click", warningModule.closeMessage); + + moduleContainer.classed("hidden", false); + moduleContainer.style("-webkit-animation-name", "warn_ExpandAnimation"); + moduleContainer.style("-webkit-animation-duration", "0.5s"); + }; + + warningModule.showMultiFileUploadWarning = function (){ + var id = warningModule.addMessageBox(); + var warningContainer = _messageContext[id]; + var moduleContainer = _messageContainers[id]; + _visibleStatus[id] = true; + + _filterHintId = id; + var generalHint = warningContainer.append('div'); + + generalHint.node().innerHTML = "Uploading multiple files is not supported.
    "; + + generalHint.style("padding", "5px"); + generalHint.style("line-height", "1.2em"); + generalHint.style("font-size", "1.2em"); + + var gotItButton = warningContainer.append("label"); + gotItButton.node().id = "killFilterMessages_" + id; + gotItButton.node().innerHTML = "Got It"; + gotItButton.on("click", warningModule.closeMessage); + + moduleContainer.classed("hidden", false); + moduleContainer.style("-webkit-animation-name", "warn_ExpandAnimation"); + moduleContainer.style("-webkit-animation-duration", "0.5s"); + }; + + warningModule.showWarning = function ( header, reason, action, type, forcedWarning, additionalOpts ){ + var id = warningModule.addMessageBox(); + var warningContainer = _messageContext[id]; + var moduleContainer = _messageContainers[id]; + _visibleStatus[id] = true; + + // add new one; + var graphWidth = 0.5 * graph.options().width(); + + if ( header.length > 0 ) { + var head = warningContainer.append("div"); + head.style("padding", "5px"); + var titleHeader = head.append("div"); + // some classes + titleHeader.style("display", "inline-flex"); + titleHeader.node().innerHTML = "Warning:"; + titleHeader.style("padding-right", "3px"); + var msgHeader = head.append("div"); + // some classes + msgHeader.style("display", "inline-flex"); + msgHeader.style("max-width", graphWidth + "px"); + + msgHeader.node().innerHTML = header; + } + if ( reason.length > 0 ) { + var reasonContainer = warningContainer.append("div"); + reasonContainer.style("padding", "5px"); + var reasonHeader = reasonContainer.append("div"); + // some classes + reasonHeader.style("display", "inline-flex"); + reasonHeader.style("padding-right", "3px"); + + reasonHeader.node().innerHTML = "Reason:"; + var msgReason = reasonContainer.append("div"); + // some classes + msgReason.style("display", "inline-flex"); + msgReason.style("max-width", graphWidth + "px"); + msgReason.node().innerHTML = reason; + } + if ( action.length > 0 ) { + var actionContainer = warningContainer.append("div"); + actionContainer.style("padding", "5px"); + var actionHeader = actionContainer.append("div"); + // some classes + actionHeader.style("display", "inline-flex"); + actionHeader.style("padding-right", "8px"); + actionHeader.node().innerHTML = "Action:"; + var msgAction = actionContainer.append("div"); + // some classes + msgAction.style("display", "inline-flex"); + msgAction.style("max-width", graphWidth + "px"); + msgAction.node().innerHTML = action; + } + + var gotItButton; + if ( type === 1 ) { + gotItButton = warningContainer.append("label"); + gotItButton.node().id = "killWarningErrorMessages_" + id; + gotItButton.node().innerHTML = "Got It"; + gotItButton.on("click", warningModule.closeMessage); + } + + if ( type === 2 ) { + gotItButton = warningContainer.append("label"); + gotItButton.node().id = "killWarningErrorMessages_" + id; + gotItButton.node().innerHTML = "Got It"; + gotItButton.on("click", warningModule.closeMessage); + warningContainer.append("span").node().innerHTML = "|"; + var zoomToElementButton = warningContainer.append("label"); + zoomToElementButton.node().id = "zoomElementThing_" + id; + zoomToElementButton.node().innerHTML = "Zoom to element "; + zoomToElementButton.on("click", function (){ + // assume the additional Element is for halo; + graph.zoomToElementInGraph(additionalOpts); + }); + warningContainer.append("span").node().innerHTML = "|"; + var ShowElementButton = warningContainer.append("label"); + ShowElementButton.node().id = "showElementThing_" + id; + ShowElementButton.node().innerHTML = "Indicate element"; + ShowElementButton.on("click", function (){ + // assume the additional Element is for halo; + if ( additionalOpts.halo() === false ) { + additionalOpts.drawHalo(); + graph.updatePulseIds([additionalOpts.id()]); + } else { + additionalOpts.removeHalo(); + additionalOpts.drawHalo(); + graph.updatePulseIds([additionalOpts.id()]); + } + }); + } + moduleContainer.classed("hidden", false); + moduleContainer.style("-webkit-animation-name", "warn_ExpandAnimation"); + moduleContainer.style("-webkit-animation-duration", "0.5s"); + moduleContainer.classed("hidden", false); + }; + + return warningModule; + }; + + + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 344: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( graph ){ + /** variable defs **/ + var directInputModule = {}; + var inputContainer = d3.select("#DirectInputContent"); + inputContainer.style("top", "0"); + inputContainer.style("position", "absolute"); + var textArea = d3.select("#directInputTextArea"); + var visibleContainer = false; + + inputContainer.style("border", "1px solid black"); + inputContainer.style("padding", "5px"); + inputContainer.style("background", "#fff"); + + + // connect upload and close button; + directInputModule.handleDirectUpload = function (){ + + var text = textArea.node().value; + var jsonOBJ; + try { + jsonOBJ = JSON.parse(text); + graph.options().loadingModule().directInput(text); + // close if successful + if ( jsonOBJ.class.length > 0 ) { + directInputModule.setDirectInputMode(false); + } + } + catch ( e ) { + try { + // Initialize; + graph.options().loadingModule().initializeLoader(); + graph.options().loadingModule().requestServerTimeStampForDirectInput( + graph.options().ontologyMenu().callbackLoad_Ontology_From_DirectInput, text + ); + } catch ( error2 ) { + console.log("Error " + error2); + d3.select("#Error_onLoad").classed("hidden", false); + d3.select("#Error_onLoad").node().innerHTML = "Failed to convert the input!"; + } + } + }; + + directInputModule.handleCloseButton = function (){ + directInputModule.setDirectInputMode(false); + }; + + directInputModule.updateLayout = function (){ + var w = graph.options().width(); + var h = graph.options().height(); + textArea.style("width", 0.4 * w + "px"); + textArea.style("height", 0.7 * h + "px"); + }; + + directInputModule.setDirectInputMode = function ( val ){ + if ( !val ) { + visibleContainer = !visibleContainer; + } + else { + visibleContainer = val; + } + // update visibility; + directInputModule.updateLayout(); + d3.select("#Error_onLoad").classed("hidden", true); + inputContainer.classed("hidden", !visibleContainer); + }; + + + d3.select("#directUploadBtn").on("click", directInputModule.handleDirectUpload); + d3.select("#close_directUploadBtn").on("click", directInputModule.handleCloseButton); + + return directInputModule; + }; + + + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }) + +/******/ }); diff --git a/doc/releases/0.1.0/base/webvowl/js/webvowl.js b/doc/releases/0.1.0/base/webvowl/js/webvowl.js new file mode 100644 index 0000000..1aba35e --- /dev/null +++ b/doc/releases/0.1.0/base/webvowl/js/webvowl.js @@ -0,0 +1,25345 @@ +webvowl = +/******/ (function(modules) { // webpackBootstrap +/******/ // The module cache +/******/ var installedModules = {}; + +/******/ // The require function +/******/ function __webpack_require__(moduleId) { + +/******/ // Check if module is in cache +/******/ if(installedModules[moduleId]) +/******/ return installedModules[moduleId].exports; + +/******/ // Create a new module (and put it into the cache) +/******/ var module = installedModules[moduleId] = { +/******/ exports: {}, +/******/ id: moduleId, +/******/ loaded: false +/******/ }; + +/******/ // Execute the module function +/******/ modules[moduleId].call(module.exports, module, module.exports, __webpack_require__); + +/******/ // Flag the module as loaded +/******/ module.loaded = true; + +/******/ // Return the exports of the module +/******/ return module.exports; +/******/ } + + +/******/ // expose the modules object (__webpack_modules__) +/******/ __webpack_require__.m = modules; + +/******/ // expose the module cache +/******/ __webpack_require__.c = installedModules; + +/******/ // __webpack_public_path__ +/******/ __webpack_require__.p = ""; + +/******/ // Load entry module and return exports +/******/ return __webpack_require__(0); +/******/ }) +/************************************************************************/ +/******/ ([ +/* 0 */ +/***/ (function(module, exports, __webpack_require__) { + + __webpack_require__(1); + + var nodeMap = __webpack_require__(5)(); + var propertyMap = __webpack_require__(40)(); + + + var webvowl = {}; + webvowl.graph = __webpack_require__(57); + webvowl.options = __webpack_require__(64); + webvowl.version = "1.1.7"; + + webvowl.util = {}; + webvowl.util.constants = __webpack_require__(12); + webvowl.util.languageTools = __webpack_require__(11); + webvowl.util.elementTools = __webpack_require__(63); + webvowl.util.prefixTools = __webpack_require__(72); + webvowl.modules = {}; + webvowl.modules.colorExternalsSwitch = __webpack_require__(73); + webvowl.modules.compactNotationSwitch = __webpack_require__(74); + webvowl.modules.datatypeFilter = __webpack_require__(75); + webvowl.modules.disjointFilter = __webpack_require__(77); + webvowl.modules.focuser = __webpack_require__(78); + webvowl.modules.emptyLiteralFilter = __webpack_require__(79); + webvowl.modules.nodeDegreeFilter = __webpack_require__(80); + webvowl.modules.nodeScalingSwitch = __webpack_require__(81); + webvowl.modules.objectPropertyFilter = __webpack_require__(82); + webvowl.modules.pickAndPin = __webpack_require__(83); + webvowl.modules.selectionDetailsDisplayer = __webpack_require__(315); + webvowl.modules.setOperatorFilter = __webpack_require__(316); + webvowl.modules.statistics = __webpack_require__(317); + webvowl.modules.subclassFilter = __webpack_require__(318); + + + webvowl.nodes = {}; + nodeMap.entries().forEach(function ( entry ){ + mapEntryToIdentifier(webvowl.nodes, entry); + }); + + webvowl.properties = {}; + propertyMap.entries().forEach(function ( entry ){ + mapEntryToIdentifier(webvowl.properties, entry); + }); + + function mapEntryToIdentifier( map, entry ){ + var identifier = entry.key.replace(":", "").toLowerCase(); + map[identifier] = entry.value; + } + + + module.exports = webvowl; + + +/***/ }), +/* 1 */ +/***/ (function(module, exports) { + + // removed by extract-text-webpack-plugin + +/***/ }), +/* 2 */, +/* 3 */, +/* 4 */, +/* 5 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var nodes = []; + nodes.push(__webpack_require__(7)); + nodes.push(__webpack_require__(18)); + nodes.push(__webpack_require__(19)); + nodes.push(__webpack_require__(26)); + nodes.push(__webpack_require__(27)); + nodes.push(__webpack_require__(28)); + nodes.push(__webpack_require__(29)); + nodes.push(__webpack_require__(30)); + nodes.push(__webpack_require__(31)); + nodes.push(__webpack_require__(32)); + nodes.push(__webpack_require__(33)); + nodes.push(__webpack_require__(34)); + nodes.push(__webpack_require__(38)); + nodes.push(__webpack_require__(39)); + + var map = d3.map(nodes, function ( Prototype ){ + return new Prototype().type(); + }); + + module.exports = function (){ + return map; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 6 */ +/***/ (function(module, exports) { + + module.exports = d3; + +/***/ }), +/* 7 */ +/***/ (function(module, exports, __webpack_require__) { + + var RoundNode = __webpack_require__(8); + + module.exports = (function (){ + + var o = function ( graph ){ + RoundNode.apply(this, arguments); + + this.attributes(["external"]) + .type("ExternalClass"); + }; + o.prototype = Object.create(RoundNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 8 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseNode = __webpack_require__(9); + var CenteringTextElement = __webpack_require__(14); + var drawTools = __webpack_require__(17)(); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseNode.apply(this, arguments); + + var that = this, + collapsible = false, + radius = 50, + collapsingGroupElement, + pinGroupElement, + haloGroupElement = null, + rectangularRepresentation = false, + renderingElement, + textBlock; + + this.setRectangularRepresentation = function ( val ){ + rectangularRepresentation = val; + }; + this.getRectangularRepresentation = function (){ + return rectangularRepresentation; + }; + + this.getHalos = function (){ + return haloGroupElement; + }; + + // Properties + this.collapsible = function ( p ){ + if ( !arguments.length ) return collapsible; + collapsible = p; + return this; + }; + + this.textBlock = function ( p ){ + if ( !arguments.length ) return textBlock; + textBlock = p; + return this; + }; + + /** + * This might not be equal to the actual radius, because the instance count is used for its calculation. + * @param p + * @returns {*} + */ + this.radius = function ( p ){ + if ( !arguments.length ) return radius; + radius = p; + return this; + }; + + + // Functions + this.setHoverHighlighting = function ( enable ){ + that.nodeElement().selectAll("circle").classed("hovered", enable); + }; + + this.textWidth = function ( yOffset ){ + var availableWidth = this.actualRadius() * 2; + + // if the text is not placed in the center of the circle, it can't have the full width + if ( yOffset ) { + var relativeOffset = Math.abs(yOffset) / this.actualRadius(); + var isOffsetInsideOfNode = relativeOffset <= 1; + + if ( isOffsetInsideOfNode ) { + availableWidth = Math.cos(relativeOffset) * availableWidth; + } else { + availableWidth = 0; + } + } + + return availableWidth; + }; + + this.toggleFocus = function (){ + that.focused(!that.focused()); + if ( that.nodeElement() ) + that.nodeElement().select("circle").classed("focused", that.focused()); + graph.resetSearchHighlight(); + graph.options().searchMenu().clearText(); + + }; + + this.actualRadius = function (){ + if ( !graph.options().scaleNodesByIndividuals() || that.individuals().length <= 0 ) { + return that.radius(); + } else { + // we could "listen" for radius and maxIndividualCount changes, but this is easier + var MULTIPLIER = 8, + additionalRadius = Math.log(that.individuals().length + 1) * MULTIPLIER + 5; + + return that.radius() + additionalRadius; + } + }; + + this.distanceToBorder = function (){ + return that.actualRadius(); + }; + + this.removeHalo = function (){ + if ( that.halo() ) { + that.halo(false); + if ( haloGroupElement ) { + haloGroupElement.remove(); + } + } + }; + + this.drawHalo = function ( pulseAnimation ){ + that.halo(true); + if ( rectangularRepresentation === true ) { + haloGroupElement = drawTools.drawRectHalo(that.nodeElement(), 80, 80, 5); + } else { + haloGroupElement = drawTools.drawHalo(that.nodeElement(), that.actualRadius(), this.removeHalo); + } + if ( pulseAnimation === false ) { + var pulseItem = haloGroupElement.selectAll(".searchResultA"); + pulseItem.classed("searchResultA", false); + pulseItem.classed("searchResultB", true); + pulseItem.attr("animationRunning", false); + } + }; + + /** + * Draws the pin on a round node on a position depending on its radius. + */ + this.drawPin = function (){ + that.pinned(true); + var dx = (-3.5 / 5) * that.actualRadius(), + dy = (-7 / 10) * that.actualRadius(); + pinGroupElement = drawTools.drawPin(that.nodeElement(), dx, dy, this.removePin, graph.options().showDraggerObject, graph.options().useAccuracyHelper()); + + + }; + + /** + * Removes the pin and refreshs the graph to update the force layout. + */ + this.removePin = function (){ + that.pinned(false); + if ( pinGroupElement ) { + pinGroupElement.remove(); + } + graph.updateStyle(); + }; + + this.drawCollapsingButton = function (){ + + collapsingGroupElement = that.nodeElement() + .append("g") + .classed("hidden-in-export", true) + .attr("transform", function (){ + var dx = (-2 / 5) * that.actualRadius(), + dy = (1 / 2) * that.actualRadius(); + return "translate(" + dx + "," + dy + ")"; + }); + + collapsingGroupElement.append("rect") + .classed("class pin feature", true) + .attr("x", 0) + .attr("y", 0) + .attr("width", 40) + .attr("height", 24); + + collapsingGroupElement.append("line") + .attr("x1", 13) + .attr("y1", 12) + .attr("x2", 27) + .attr("y2", 12); + + collapsingGroupElement.append("line") + .attr("x1", 20) + .attr("y1", 6) + .attr("x2", 20) + .attr("y2", 18); + }; + + /** + * Draws a circular node. + * @param parentElement the element to which this node will be appended + * @param [additionalCssClasses] additional css classes + */ + this.draw = function ( parentElement, additionalCssClasses ){ + var cssClasses = that.collectCssClasses(); + that.nodeElement(parentElement); + + var bgColor = that.backgroundColor(); + if ( bgColor === null ) bgColor = undefined; + if ( that.attributes().indexOf("deprecated") > -1 ) { + bgColor = undefined; + } + if ( additionalCssClasses instanceof Array ) { + cssClasses = cssClasses.concat(additionalCssClasses); + } + if ( rectangularRepresentation === true ) { + renderingElement = drawTools.appendRectangularClass(parentElement, 80, 80, cssClasses, that.labelForCurrentLanguage(), bgColor); + } else { + renderingElement = drawTools.appendCircularClass(parentElement, that.actualRadius(), cssClasses, that.labelForCurrentLanguage(), bgColor); + } + that.postDrawActions(parentElement); + }; + + this.redrawElement = function (){ + renderingElement.remove(); + textBlock.remove(); + var bgColor = that.backgroundColor(); + if ( that.attributes().indexOf("deprecated") > -1 ) { + bgColor = undefined; + } + + var cssClasses = that.collectCssClasses(); + + if ( rectangularRepresentation === true ) { + renderingElement = drawTools.appendRectangularClass(that.nodeElement(), 80, 80, cssClasses, that.labelForCurrentLanguage(), bgColor); + } else { + renderingElement = drawTools.appendCircularClass(that.nodeElement(), that.actualRadius(), cssClasses, that.labelForCurrentLanguage(), bgColor); + } + that.postDrawActions(that.nodeElement()); + }; + /** + * Common actions that should be invoked after drawing a node. + */ + this.postDrawActions = function (){ + that.textBlock(createTextBlock()); + + that.addMouseListeners(); + if ( that.pinned() ) { + that.drawPin(); + } + if ( that.halo() ) { + that.drawHalo(false); + } + if ( that.collapsible() ) { + that.drawCollapsingButton(); + } + }; + + this.redrawLabelText = function (){ + that.textBlock().remove(); + that.textBlock(createTextBlock()); + renderingElement.select("title").text(that.labelForCurrentLanguage()); + }; + function createTextBlock(){ + var bgColor = that.backgroundColor(); + if ( that.attributes().indexOf("deprecated") > -1 ) + bgColor = undefined; + + var textBlock = new CenteringTextElement(that.nodeElement(), bgColor); + + var equivalentsString = that.equivalentsString(); + var suffixForFollowingEquivalents = equivalentsString ? "," : ""; + + textBlock.addText(that.labelForCurrentLanguage(), "", suffixForFollowingEquivalents); + textBlock.addEquivalents(equivalentsString); + if ( !graph.options().compactNotation() ) { + textBlock.addSubText(that.indicationString()); + } + textBlock.addInstanceCount(that.individuals().length); + + return textBlock; + } + + this.equivalentsString = function (){ + var equivalentClasses = that.equivalents(); + if ( !equivalentClasses ) { + return; + } + + return equivalentClasses + .map(function ( node ){ + return node.labelForCurrentLanguage(); + }) + .join(", "); + }; + }; + o.prototype = Object.create(BaseNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 9 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var BaseElement = __webpack_require__(10); + var forceLayoutNodeFunctions = __webpack_require__(13)(); + + module.exports = (function (){ + + var Base = function ( graph ){ + BaseElement.apply(this, arguments); + + var that = this, + // Basic attributes + complement, + disjointUnion, + disjointWith, + individuals = [], + intersection, + union, + links, + rendertype = "round", + // Additional attributes + maxIndividualCount, + fobj, // foreigner object for editing + ignoreLocalHoverEvents = false, + backupFullIri, + // Element containers + nodeElement; + + // array to store my properties; // we will need this also later for semantic zooming stuff + var assignedProperties = []; + that.editingTextElement = false; + + this.isPropertyAssignedToThisElement = function ( property ){ + // this goes via IRIS + console.log("Element IRI :" + property.iri()); + if ( property.type() === "rdfs:subClassOf" ) + for ( var i = 0; i < assignedProperties.length; i++ ) { + var iriEl = assignedProperties[i].iri(); + if ( property.iri() === iriEl ) { + return true; + } + if ( property.type() === "rdfs:subClassOf" && assignedProperties[i].type() === "rdfs:subClassOf" ) + return true; + if ( property.type() === "owl:disjointWith" && assignedProperties[i].type() === "owl:disjointWith" ) + return true; + + } + return false; + }; + + + this.existingPropertyIRI = function ( url ){ + // this goes via IRIS + for ( var i = 0; i < assignedProperties.length; i++ ) { + var iriEl = assignedProperties[i].iri(); + if ( iriEl === url ) { + return true; + } + } + return false; + }; + + this.addProperty = function ( property ){ + if ( assignedProperties.indexOf(property) === -1 ) { + assignedProperties.push(property); + } + }; + + this.removePropertyElement = function ( property ){ + // console.log("Calling removing old property!"+ property.iri()); + if ( assignedProperties.indexOf(property) !== -1 ) { + // console.log("Found it!"); + assignedProperties.splice(assignedProperties.indexOf(property), 1); + } + }; + this.getMyProperties = function (){ + return assignedProperties; + }; + this.copyOtherProperties = function ( otherProperties ){ + assignedProperties = otherProperties; + }; + + this.copyInformation = function ( other ){ + console.log(other.labelForCurrentLanguage()); + if ( other.type() !== "owl:Thing" ) + that.label(other.label()); + that.complement(other.complement()); + that.iri(other.iri()); + that.copyOtherProperties(other.getMyProperties()); + that.baseIri(other.baseIri()); + if ( other.type() === "owl:Class" ) { + that.backupLabel(other.label()); + // console.log("copied backup label"+that.backupLabel()); + } + if ( other.backupLabel() !== undefined ) { + that.backupLabel(other.backupLabel()); + } + }; + + this.enableEditing = function ( autoEditing ){ + if ( autoEditing === false ) + return; + that.raiseDoubleClickEdit(true); + }; + + this.raiseDoubleClickEdit = function ( forceIRISync ){ + d3.selectAll(".foreignelements").remove(); + if ( nodeElement === undefined || this.type() === "owl:Thing" || this.type() === "rdfs:Literal" ) { + console.log("No Container found"); + return; + } + if ( fobj !== undefined ) { + nodeElement.selectAll(".foreignelements").remove(); + } + + backupFullIri = undefined; + graph.options().focuserModule().handle(undefined); + graph.options().focuserModule().handle(that); + // add again the editing elements to that one + if ( graph.isTouchDevice() === true ) { + graph.activateHoverElements(true, that, true); + } + that.editingTextElement = true; + ignoreLocalHoverEvents = true; + that.nodeElement().selectAll("circle").classed("hoveredForEditing", true); + graph.killDelayedTimer(); + graph.ignoreOtherHoverEvents(false); + fobj = nodeElement.append("foreignObject") + .attr("x", -0.5 * (that.textWidth() - 2)) + .attr("y", -12) + .attr("height", 30) + .attr("class", "foreignelements") + .on("dragstart", function (){ + return false; + }) // remove drag operations of text element) + .attr("width", that.textWidth() - 2); + + var editText = fobj.append("xhtml:input") + .attr("class", "nodeEditSpan") + .attr("id", that.id()) + .attr("align", "center") + .attr("contentEditable", "true") + .on("dragstart", function (){ + return false; + }); // remove drag operations of text element) + + var bgColor = '#f00'; + var txtWidth = that.textWidth() - 2; + editText.style({ + + 'align': 'center', + 'color': 'black', + 'width': txtWidth + "px", + 'height': '15px', + 'background-color': bgColor, + 'border-bottom': '2px solid black' + }); + var txtNode = editText.node(); + txtNode.value = that.labelForCurrentLanguage(); + txtNode.focus(); + txtNode.select(); + that.frozen(true); // << releases the not after selection + that.locked(true); + + + d3.event.stopPropagation(); + // ignoreNodeHoverEvent=true; + // // add some events that relate to this object + editText.on("click", function (){ + d3.event.stopPropagation(); + }); + // // remove hover Events for now; + editText.on("mouseout", function (){ + d3.event.stopPropagation(); + + + }); + editText.on("mousedown", function (){ + d3.event.stopPropagation(); + }) + .on("keydown", function (){ + d3.event.stopPropagation(); + if ( d3.event.keyCode === 13 ) { + this.blur(); + that.frozen(false); // << releases the not after selection + that.locked(false); + } + }) + .on("keyup", function (){ + if ( forceIRISync ) { + var labelName = editText.node().value; + var resourceName = labelName.replaceAll(" ", "_"); + var syncedIRI = that.baseIri() + resourceName; + backupFullIri = syncedIRI; + + d3.select("#element_iriEditor").node().title = syncedIRI; + d3.select("#element_iriEditor").node().value = graph.options().prefixModule().getPrefixRepresentationForFullURI(syncedIRI); + } + d3.select("#element_labelEditor").node().value = editText.node().value; + + }) + .on("blur", function (){ + that.editingTextElement = false; + ignoreLocalHoverEvents = false; + that.nodeElement().selectAll("circle").classed("hoveredForEditing", false); + var newLabel = editText.node().value; + nodeElement.selectAll(".foreignelements").remove(); + // that.setLabelForCurrentLanguage(classNameConvention(editText.node().value)); + that.label(newLabel); + that.backupLabel(newLabel); + that.redrawLabelText(); + that.frozen(graph.paused()); + that.locked(graph.paused()); + graph.ignoreOtherHoverEvents(false); + // console.log("Calling blur on Node!"); + if ( backupFullIri ) { + var sanityCheckResult = graph.checkIfIriClassAlreadyExist(backupFullIri); + if ( sanityCheckResult === false ) { + that.iri(backupFullIri); + } else { + // throw warnign + graph.options().warningModule().showWarning("Already seen this class", + "Input IRI: " + backupFullIri + " for element: " + that.labelForCurrentLanguage() + " already been set", + "Restoring previous IRI for Element : " + that.iri(), 2, false, sanityCheckResult); + + } + } + if ( graph.isADraggerActive() === false ) { + graph.options().focuserModule().handle(undefined); + graph.options().focuserModule().handle(that); + } + }); // add a foreiner element to this thing; + }; + + + this.renderType = function ( t ){ + if ( !arguments.length ) return rendertype; + rendertype = t; + return this; + }; + // Properties + this.complement = function ( p ){ + if ( !arguments.length ) return complement; + complement = p; + return this; + }; + + this.disjointUnion = function ( p ){ + if ( !arguments.length ) return disjointUnion; + disjointUnion = p; + return this; + }; + + this.disjointWith = function ( p ){ + if ( !arguments.length ) return disjointWith; + disjointWith = p; + return this; + }; + + this.individuals = function ( p ){ + if ( !arguments.length ) return individuals; + individuals = p || []; + return this; + }; + + this.intersection = function ( p ){ + if ( !arguments.length ) return intersection; + intersection = p; + return this; + }; + + this.links = function ( p ){ + if ( !arguments.length ) return links; + links = p; + return this; + }; + + this.maxIndividualCount = function ( p ){ + if ( !arguments.length ) return maxIndividualCount; + maxIndividualCount = p; + return this; + }; + + this.nodeElement = function ( p ){ + if ( !arguments.length ) return nodeElement; + nodeElement = p; + return this; + }; + + this.union = function ( p ){ + if ( !arguments.length ) return union; + union = p; + return this; + }; + + + /** + * Returns css classes generated from the data of this object. + * @returns {Array} + */ + that.collectCssClasses = function (){ + var cssClasses = []; + + if ( typeof that.styleClass() === "string" ) { + cssClasses.push(that.styleClass()); + } + + cssClasses = cssClasses.concat(that.visualAttributes()); + + return cssClasses; + }; + + + // Reused functions TODO refactor + this.addMouseListeners = function (){ + // Empty node + if ( !that.nodeElement() ) { + console.warn(this); + return; + } + + that.nodeElement().selectAll("*") + .on("mouseover", onMouseOver) + .on("mouseout", onMouseOut); + }; + + this.animationProcess = function (){ + var animRuns = false; + if ( that.getHalos() ) { + var haloGr = that.getHalos(); + var haloEls = haloGr.selectAll(".searchResultA"); + animRuns = haloGr.attr("animationRunning"); + if ( typeof animRuns !== "boolean" ) { + // parse this to a boolean value + animRuns = (animRuns === 'true'); + } + if ( animRuns === false ) { + haloEls.classed("searchResultA", false); + haloEls.classed("searchResultB", true); + } + } + return animRuns; + }; + + this.foreground = function (){ + var selectedNode = that.nodeElement().node(), + nodeContainer = selectedNode.parentNode; + // check if the halo is present and an animation is running + if ( that.animationProcess() === false ) { + // Append hovered element as last child to the container list. + nodeContainer.appendChild(selectedNode); + } + + }; + + function onMouseOver(){ + if ( that.mouseEntered() || ignoreLocalHoverEvents === true ) { + return; + } + + var selectedNode = that.nodeElement().node(), + nodeContainer = selectedNode.parentNode; + + // Append hovered element as last child to the container list. + if ( that.animationProcess() === false ) { + nodeContainer.appendChild(selectedNode); + } + if ( graph.isTouchDevice() === false ) { + that.setHoverHighlighting(true); + that.mouseEntered(true); + if ( graph.editorMode() === true && graph.ignoreOtherHoverEvents() === false ) { + graph.activateHoverElements(true, that); + } + } else { + if ( graph.editorMode() === true && graph.ignoreOtherHoverEvents() === false ) { + graph.activateHoverElements(true, that, true); + } + + } + + + } + + function onMouseOut(){ + that.setHoverHighlighting(false); + that.mouseEntered(false); + if ( graph.editorMode() === true && graph.ignoreOtherHoverEvents() === false ) { + graph.activateHoverElements(false); + } + } + + + forceLayoutNodeFunctions.addTo(this); + }; + + Base.prototype = Object.create(BaseElement.prototype); + Base.prototype.constructor = Base; + + + return Base; + }()); + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 10 */ +/***/ (function(module, exports, __webpack_require__) { + + /** + * The base element for all visual elements of webvowl. + */ + module.exports = (function (){ + + var Base = function ( graph ){ + // Basic attributes + var equivalents = [], + id, + label, + type, + iri, + baseIri, + // Additional attributes + annotations, + attributes = [], + backgroundColor, + comment, + description, + equivalentBase, + visualAttributes = [], + // Style attributes + focused = false, + indications = [], + mouseEntered = false, + styleClass, + visible = true, + + backupLabel, + // Other + languageTools = __webpack_require__(11)(); + + + this.backupLabel = function ( label ){ + if ( !arguments.length ) return backupLabel; + backupLabel = label; + }; + // Properties + this.attributes = function ( p ){ + if ( !arguments.length ) return attributes; + attributes = p; + return this; + }; + + this.annotations = function ( p ){ + if ( !arguments.length ) return annotations; + annotations = p; + return this; + }; + + this.redrawElement = function (){ + // TODO: OVERLOADED BY INDIVIDUAL ELEMENTS + }; + + this.backgroundColor = function ( p ){ + if ( !arguments.length ) return backgroundColor; + backgroundColor = p; + return this; + }; + + this.baseIri = function ( p ){ + if ( !arguments.length ) return baseIri; + baseIri = p; + return this; + }; + + this.comment = function ( p ){ + if ( !arguments.length ) return comment; + comment = p; + return this; + }; + + this.description = function ( p ){ + if ( !arguments.length ) return description; + description = p; + return this; + }; + + this.equivalents = function ( p ){ + if ( !arguments.length ) return equivalents; + equivalents = p || []; + return this; + }; + + this.equivalentBase = function ( p ){ + if ( !arguments.length ) return equivalentBase; + equivalentBase = p; + return this; + }; + + this.focused = function ( p ){ + if ( !arguments.length ) return focused; + focused = p; + return this; + }; + + this.id = function ( p ){ + if ( !arguments.length ) return id; + id = p; + return this; + }; + + this.indications = function ( p ){ + if ( !arguments.length ) return indications; + indications = p; + return this; + }; + + this.iri = function ( p ){ + if ( !arguments.length ) return iri; + iri = p; + return this; + }; + + this.label = function ( p ){ + if ( !arguments.length ) return label; + label = p; + return this; + }; + + this.mouseEntered = function ( p ){ + if ( !arguments.length ) return mouseEntered; + mouseEntered = p; + return this; + }; + + this.styleClass = function ( p ){ + if ( !arguments.length ) return styleClass; + styleClass = p; + return this; + }; + + this.type = function ( p ){ + if ( !arguments.length ) return type; + type = p; + return this; + }; + + this.visible = function ( p ){ + if ( !arguments.length ) return visible; + visible = p; + return this; + }; + + this.visualAttributes = function ( p ){ + if ( !arguments.length ) return visualAttributes; + visualAttributes = p; + return this; + }; + + + this.commentForCurrentLanguage = function (){ + return languageTools.textInLanguage(this.comment(), graph.language()); + }; + + /** + * @returns {string} the css class of this node.. + */ + this.cssClassOfNode = function (){ + return "node" + this.id(); + }; + + this.descriptionForCurrentLanguage = function (){ + return languageTools.textInLanguage(this.description(), graph.language()); + }; + + this.defaultLabel = function (){ + return languageTools.textInLanguage(this.label(), "default"); + }; + + this.indicationString = function (){ + return this.indications().join(", "); + }; + + this.labelForCurrentLanguage = function (){ + var preferredLanguage = graph && graph.language ? graph.language() : null; + return languageTools.textInLanguage(this.label(), preferredLanguage); + }; + }; + + Base.prototype.constructor = Base; + + Base.prototype.equals = function ( other ){ + return other instanceof Base && this.id() === other.id(); + }; + + Base.prototype.toString = function (){ + return this.labelForCurrentLanguage() + " (" + this.type() + ")"; + }; + + + return Base; + }()); + + +/***/ }), +/* 11 */ +/***/ (function(module, exports, __webpack_require__) { + + var constants = __webpack_require__(12)(); + + /** + * Encapsulates methods which return a label in a specific language for a preferred language. + */ + module.exports = (function (){ + + var languageTools = {}; + + + languageTools.textInLanguage = function ( textObject, preferredLanguage ){ + if ( typeof textObject === "undefined" ) { + return undefined; + } + + if ( typeof textObject === "string" ) { + return textObject; + } + + if ( preferredLanguage && textObject.hasOwnProperty(preferredLanguage) ) { + return textObject[preferredLanguage]; + } + + var textForLanguage = searchLanguage(textObject, "en"); + if ( textForLanguage ) { + return textForLanguage; + } + textForLanguage = searchLanguage(textObject, constants.LANG_UNDEFINED); + if ( textForLanguage ) { + return textForLanguage; + } + + return textObject[constants.LANG_IRIBASED]; + }; + + + function searchLanguage( textObject, preferredLanguage ){ + for ( var language in textObject ) { + if ( language === preferredLanguage && textObject.hasOwnProperty(language) ) { + return textObject[language]; + } + } + } + + return function (){ + /* Use a function here to keep a consistent style like webvowl.path.to.module() + * despite having just a single languageTools object. */ + return languageTools; + }; + })(); + + +/***/ }), +/* 12 */ +/***/ (function(module, exports) { + + module.exports = (function (){ + + var constants = {}; + + constants.LANG_IRIBASED = "IRI-based"; + constants.LANG_UNDEFINED = "undefined"; + + return function (){ + /* Use a function here to keep a consistent style like webvowl.path.to.module() + * despite having just a single object. */ + return constants; + }; + })(); + + +/***/ }), +/* 13 */ +/***/ (function(module, exports) { + + /** + * The functions for controlling attributes of nodes of the force layout can't be modelled to the element hierarchy, + * which is used for inheriting visual and OWL-like attributes. + * + * To reduce code redundancy the common functions for controlling the force layout node attributes are excluded into this + * module, which can add them to the node objects. + * + * @type {{}} + */ + var nodeFunctions = {}; + module.exports = function (){ + return nodeFunctions; + }; + + + nodeFunctions.addTo = function ( node ){ + addFixedLocationFunctions(node); + }; + + function addFixedLocationFunctions( node ){ + var locked = false, + frozen = false, + halo = false, + pinned = false; + + node.locked = function ( p ){ + if ( !arguments.length ) { + return locked; + } + locked = p; + applyFixedLocationAttributes(); + return node; + }; + + node.frozen = function ( p ){ + if ( !arguments.length ) { + return frozen; + } + frozen = p; + applyFixedLocationAttributes(); + return node; + }; + + node.halo = function ( p ){ + if ( !arguments.length ) { + return halo; + } + halo = p; + applyFixedLocationAttributes(); + return node; + }; + + node.pinned = function ( p ){ + if ( !arguments.length ) { + return pinned; + } + pinned = p; + applyFixedLocationAttributes(); + return node; + }; + + function applyFixedLocationAttributes(){ + if ( node.locked() || node.frozen() || node.pinned() ) { + node.fixed = true; + } else { + node.fixed = false; + } + } + } + + +/***/ }), +/* 14 */ +/***/ (function(module, exports, __webpack_require__) { + + var textTools = __webpack_require__(15)(); + var AbstractTextElement = __webpack_require__(16); + + module.exports = CenteringTextElement; + function CenteringTextElement( container, backgroundColor ){ + AbstractTextElement.apply(this, arguments); + this.storedFullTextLines = []; + this.storedSpanArrays = []; + this.storedStyle = []; + + } + + CenteringTextElement.prototype = Object.create(AbstractTextElement.prototype); + CenteringTextElement.prototype.constructor = CenteringTextElement; + + CenteringTextElement.prototype.addText = function ( text, prefix, suffix ){ + if ( text ) { + this.addTextline(text, this.CSS_CLASSES.default, prefix, suffix); + } + }; + + CenteringTextElement.prototype.addSubText = function ( text ){ + if ( text ) { + this.addTextline(text, this.CSS_CLASSES.subtext, "(", ")"); + } + }; + + CenteringTextElement.prototype.addEquivalents = function ( text ){ + if ( text ) { + this.addTextline(text, this.CSS_CLASSES.default); + } + }; + + CenteringTextElement.prototype.addInstanceCount = function ( instanceCount ){ + if ( instanceCount ) { + this.addTextline(instanceCount.toString(), this.CSS_CLASSES.instanceCount); + } + }; + CenteringTextElement.prototype.saveCorrespondingSpan = function ( correspondingSpan ){ + this.storedSpanArrays.push(correspondingSpan); + }; + CenteringTextElement.prototype.saveFullTextLine = function ( fullText ){ + this.storedFullTextLines.push(fullText); + }; + CenteringTextElement.prototype.saveStyle = function ( style ){ + this.storedStyle.push(style); + }; + + CenteringTextElement.prototype.updateAllTextElements = function (){ + // TODO : TEST THIS postPrefix >>> _applyPreAndPostFix + for ( var i = 0; i < this.storedSpanArrays.length; i++ ) { + var truncatedText = textTools.truncate(this.storedFullTextLines[i], this._textBlock().datum().textWidth(), this.storedStyle[i]); + this.storedSpanArrays[i].text(truncatedText); + } + }; + + + CenteringTextElement.prototype.addTextline = function ( text, style, prefix, postfix ){ + var truncatedText = textTools.truncate(text, this._textBlock().datum().textWidth(), style); + this.saveFullTextLine(text); + this.saveStyle(style); + var tspan = this._textBlock().append("tspan") + .classed(this.CSS_CLASSES.default, true) + .classed(style, true) + .text(this._applyPreAndPostFix(truncatedText, prefix, postfix)) + .attr("x", 0); + this._repositionTextLine(tspan); + this.saveCorrespondingSpan(tspan); + + this._repositionTextBlock(); + }; + + CenteringTextElement.prototype._repositionTextLine = function ( tspan ){ + var fontSizeProperty = window.getComputedStyle(tspan.node()).getPropertyValue("font-size"); + var fontSize = parseFloat(fontSizeProperty); + + var siblingCount = this._lineCount() - 1; + var lineDistance = siblingCount > 0 ? this.LINE_DISTANCE : 0; + + tspan.attr("dy", fontSize + lineDistance + "px"); + }; + + CenteringTextElement.prototype.getTextBox = function (){ + return this._textBlock(); + }; + + + CenteringTextElement.prototype._repositionTextBlock = function (){ + // Nothing to do if no child elements exist + var lineCount = this._lineCount(); + if ( lineCount < 1 ) { + this._textBlock().attr("y", 0); + return; + } + + var textBlockHeight = this._textBlock().node().getBBox().height; + this._textBlock().attr("y", -textBlockHeight * 0.5 + "px"); + }; + + CenteringTextElement.prototype._lineCount = function (){ + return this._textBlock().property("childElementCount"); + }; + + +/***/ }), +/* 15 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var ADDITIONAL_TEXT_SPACE = 4; + + var tools = {}; + + function measureTextWidth( text, textStyle ){ + // Set a default value + if ( !textStyle ) { + textStyle = "text"; + } + var d = d3.select("body") + .append("div") + .attr("class", textStyle) + .attr("id", "width-test") // tag this element to identify it + .attr("style", "position:absolute; float:left; white-space:nowrap; visibility:hidden;") + .text(text), + w = document.getElementById("width-test").offsetWidth; + d.remove(); + return w; + } + + tools.truncate = function ( text, maxWidth, textStyle, additionalTextSpace ){ + maxWidth -= isNaN(additionalTextSpace) ? ADDITIONAL_TEXT_SPACE : additionalTextSpace; + if ( isNaN(maxWidth) || maxWidth <= 0 ) { + return text; + } + + var truncatedText = text, + newTruncatedTextLength, + textWidth, + ratio; + + while ( true ) { + textWidth = measureTextWidth(truncatedText, textStyle); + if ( textWidth <= maxWidth ) { + break; + } + + ratio = textWidth / maxWidth; + newTruncatedTextLength = Math.floor(truncatedText.length / ratio); + + // detect if nothing changes + if ( truncatedText.length === newTruncatedTextLength ) { + break; + } + + truncatedText = truncatedText.substring(0, newTruncatedTextLength); + } + + if ( text.length > truncatedText.length ) { + return text.substring(0, truncatedText.length - 3) + "..."; + } + return text; + }; + + + module.exports = function (){ + return tools; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 16 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = AbstractTextElement; + + function AbstractTextElement( container, backgroundColor ){ + var textBlock = container.append("text") + .classed("text", true) + .style("fill", this._getTextColor(backgroundColor)) + .attr("text-anchor", "middle"); + + this._textBlock = function (){ + return textBlock; + }; + } + + AbstractTextElement.prototype.LINE_DISTANCE = 1; + AbstractTextElement.prototype.CSS_CLASSES = { + default: "text", + subtext: "subtext", + instanceCount: "instance-count" + }; + AbstractTextElement.prototype.DARK_TEXT_COLOR = "#000"; + AbstractTextElement.prototype.LIGHT_TEXT_COLOR = "#fff"; + + AbstractTextElement.prototype.translation = function ( x, y ){ + this._textBlock().attr("transform", "translate(" + x + ", " + y + ")"); + return this; + }; + + AbstractTextElement.prototype.remove = function (){ + this._textBlock().remove(); + return this; + }; + + AbstractTextElement.prototype._applyPreAndPostFix = function ( text, prefix, postfix ){ + if ( prefix ) { + text = prefix + text; + } + if ( postfix ) { + text += postfix; + } + return text; + }; + + AbstractTextElement.prototype._getTextColor = function ( rawBackgroundColor ){ + if ( !rawBackgroundColor ) { + return AbstractTextElement.prototype.DARK_TEXT_COLOR; + } + + var backgroundColor = d3.rgb(rawBackgroundColor); + if ( calculateLuminance(backgroundColor) > 0.5 ) { + return AbstractTextElement.prototype.DARK_TEXT_COLOR; + } else { + return AbstractTextElement.prototype.LIGHT_TEXT_COLOR; + } + }; + + function calculateLuminance( color ){ + return 0.3 * (color.r / 255) + 0.59 * (color.g / 255) + 0.11 * (color.b / 255); + } + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 17 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains reusable function for drawing nodes. + */ + module.exports = (function (){ + + var tools = {}; + + /** + * Append a circular class node with the passed attributes. + * @param parent the parent element to which the circle will be appended + * @param radius + * @param [cssClasses] an array of additional css classes + * @param [tooltip] + * @param [backgroundColor] + * @returns {*} + */ + tools.appendCircularClass = function ( parent, radius, cssClasses, tooltip, backgroundColor ){ + var circle = parent.append("circle") + .classed("class", true) + .attr("r", radius); + + addCssClasses(circle, cssClasses); + addToolTip(circle, tooltip); + addBackgroundColor(circle, backgroundColor); + + return circle; + }; + + function addCssClasses( element, cssClasses ){ + if ( cssClasses instanceof Array ) { + cssClasses.forEach(function ( cssClass ){ + element.classed(cssClass, true); + }); + } + } + + function addToolTip( element, tooltip ){ + if ( tooltip ) { + element.append("title").text(tooltip); + } + } + + function addBackgroundColor( element, backgroundColor ){ + if ( backgroundColor ) { + element.style("fill", backgroundColor); + } + } + + /** + * Appends a rectangular class node with the passed attributes. + * @param parent the parent element to which the rectangle will be appended + * @param width + * @param height + * @param [cssClasses] an array of additional css classes + * @param [tooltip] + * @param [backgroundColor] + * @returns {*} + */ + tools.appendRectangularClass = function ( parent, width, height, cssClasses, tooltip, backgroundColor ){ + var rectangle = parent.append("rect") + .classed("class", true) + .attr("x", -width / 2) + .attr("y", -height / 2) + .attr("width", width) + .attr("height", height); + + addCssClasses(rectangle, cssClasses); + addToolTip(rectangle, tooltip); + addBackgroundColor(rectangle, backgroundColor); + + return rectangle; + }; + + tools.drawPin = function ( container, dx, dy, onClick, accuraciesHelperFunction, useAccuracyHelper ){ + var pinGroupElement = container + .append("g") + .classed("hidden-in-export", true) + .attr("transform", "translate(" + dx + "," + dy + ")"); + + var base = pinGroupElement.append("circle") + .classed("class pin feature", true) + .attr("r", 12) + .on("click", function (){ + if ( onClick ) { + onClick(); + } + d3.event.stopPropagation(); + }); + + pinGroupElement.append("line") + .attr("x1", 0) + .attr("x2", 0) + .attr("y1", 12) + .attr("y2", 16); + + if ( useAccuracyHelper === true ) { + pinGroupElement.append("circle") + .attr("r", 15) + .attr("cx", -7) + .attr("cy", -7) + .classed("superHiddenElement ", true) + .classed("superOpacityElement", !accuraciesHelperFunction()) + .on("click", function (){ + if ( onClick ) { + onClick(); + } + d3.event.stopPropagation(); + }) + .on("mouseover", function (){ + base.classed("feature_hover", true); + }) + .on("mouseout", function (){ + base.classed("feature_hover", false); + }) + ; + + } + + + return pinGroupElement; + }; + + tools.drawRectHalo = function ( node, width, height, offset ){ + var container; + if ( node.nodeElement ) + container = node.nodeElement(); + else + container = node.labelElement(); + + if ( !container ) { + // console.log("no container found"); + return; + } + + var haloGroupElement = container + .append("g") + .classed("hidden-in-export", true); + + haloGroupElement.append("rect") + .classed("searchResultA", true) + .attr("x", (-width - offset) / 2) + .attr("y", (-offset - height) / 2) + .attr("width", width + offset) + .attr("height", height + offset); + haloGroupElement.attr("animationRunning", true); + + haloGroupElement.node().addEventListener("webkitAnimationEnd", function (){ + var test = haloGroupElement.selectAll(".searchResultA"); + test.classed("searchResultA", false) + .classed("searchResultB", true); + haloGroupElement.attr("animationRunning", false); + }); + haloGroupElement.node().addEventListener("animationend", function (){ + var test = haloGroupElement.selectAll(".searchResultA"); + test.classed("searchResultA", false) + .classed("searchResultB", true); + haloGroupElement.attr("animationRunning", false); + }); + + + return haloGroupElement; + + }; + tools.drawHalo = function ( container, radius ){ + if ( container === undefined ) { + return null; + // there is no element to add the halo to; + // this means the node was not rendered previously + } + + var haloGroupElement = container + .append("g") + .classed("hidden-in-export", true); + + + haloGroupElement.append("circle", ":first-child") + .classed("searchResultA", true) + .attr("r", radius + 15); + haloGroupElement.attr("animationRunning", true); + + + haloGroupElement.node().addEventListener("webkitAnimationEnd", function (){ + var test = haloGroupElement.selectAll(".searchResultA"); + test.classed("searchResultA", false) + .classed("searchResultB", true) + .attr("animationRunning", false); + haloGroupElement.attr("animationRunning", false); + }); + haloGroupElement.node().addEventListener("animationend", function (){ + var test = haloGroupElement.selectAll(".searchResultA"); + test.classed("searchResultA", false) + .classed("searchResultB", true) + .attr("animationRunning", false); + haloGroupElement.attr("animationRunning", false); + }); + + return haloGroupElement; + }; + + return function (){ + // Encapsulate into function to maintain default.module.path() + return tools; + }; + })(); + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 18 */ +/***/ (function(module, exports, __webpack_require__) { + + var RoundNode = __webpack_require__(8); + + module.exports = (function (){ + + var o = function ( graph ){ + RoundNode.apply(this, arguments); + + this.type("owl:Class"); + }; + o.prototype = Object.create(RoundNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 19 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetOperatorNode = __webpack_require__(20); + + module.exports = (function (){ + + var o = function ( graph ){ + SetOperatorNode.apply(this, arguments); + + var that = this, + superDrawFunction = that.draw; + + this.styleClass("complementof") + .type("owl:complementOf"); + + this.draw = function ( element ){ + superDrawFunction(element); + + var symbol = element.append("g").classed("embedded", true); + + symbol.append("circle") + .attr("class", "symbol") + .classed("fineline", true) + .attr("r", 10); + symbol.append("path") + .attr("class", "nofill") + .attr("d", "m -7,-1.5 12,0 0,6") + .attr("transform", "scale(.5)"); + + symbol.attr("transform", + "translate(-" + (that.radius() - 15) / 100 + ",-" + (that.radius() - 15) / 100 + ")"); + + that.postDrawActions(); + }; + }; + o.prototype = Object.create(SetOperatorNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 20 */ +/***/ (function(module, exports, __webpack_require__) { + + var AbsoluteTextElement = __webpack_require__(21); + var BoxArrowLink = __webpack_require__(22); + var RoundNode = __webpack_require__(8); + var drawTools = __webpack_require__(17)(); + + module.exports = (function (){ + + var o = function ( graph ){ + RoundNode.apply(this, arguments); + + var that = this, + superHoverHighlightingFunction = that.setHoverHighlighting, + superPostDrawActions = that.postDrawActions; + + this.setHoverHighlighting = function ( enable ){ + superHoverHighlightingFunction(enable); + + // Highlight links pointing to included nodes when hovering the set operator + that.links() + .filter(function ( link ){ + return link instanceof BoxArrowLink; + }) + .filter(function ( link ){ + return link.domain().equals(that); + }) + .forEach(function ( link ){ + link.property().setHighlighting(enable); + }); + }; + + this.draw = function ( element ){ + that.nodeElement(element); + + drawTools.appendCircularClass(element, that.actualRadius(), + that.collectCssClasses().join(" "), + that.labelForCurrentLanguage(), that.backgroundColor()); + }; + + this.postDrawActions = function (){ + superPostDrawActions(); + that.textBlock().remove(); + + var textElement = new AbsoluteTextElement(that.nodeElement(), that.backgroundColor()); + + var equivalentsString = that.equivalentsString(); + var offsetForFollowingEquivalents = equivalentsString ? -30 : -17; + var suffixForFollowingEquivalents = equivalentsString ? "," : ""; + textElement.addText(that.labelForCurrentLanguage(), offsetForFollowingEquivalents, "", + suffixForFollowingEquivalents); + + textElement.addEquivalents(equivalentsString, -17); + + + if ( !graph.options().compactNotation() ) { + + if ( that.indicationString().length > 0 ) { + textElement.addSubText(that.indicationString(), 17); + textElement.addInstanceCount(that.individuals().length, 30); + } else { + textElement.addInstanceCount(that.individuals().length, 17); + } + } else { + textElement.addInstanceCount(that.individuals().length, 17); + } + + that.textBlock(textElement); + }; + }; + o.prototype = Object.create(RoundNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 21 */ +/***/ (function(module, exports, __webpack_require__) { + + var textTools = __webpack_require__(15)(); + var AbstractTextElement = __webpack_require__(16); + + module.exports = AbsoluteTextElement; + function AbsoluteTextElement( container, backgroundColor ){ + AbstractTextElement.apply(this, arguments); + } + + AbsoluteTextElement.prototype = Object.create(AbstractTextElement.prototype); + AbsoluteTextElement.prototype.constructor = AbsoluteTextElement; + + AbsoluteTextElement.prototype.addText = function ( text, yShift, prefix, suffix ){ + if ( text ) { + this.addTextline(text, this.CSS_CLASSES.default, yShift, prefix, suffix); + } + }; + + AbsoluteTextElement.prototype.addSubText = function ( text, yShift ){ + if ( text ) { + this.addTextline(text, this.CSS_CLASSES.subtext, yShift, "(", ")"); + } + }; + + AbsoluteTextElement.prototype.addEquivalents = function ( text, yShift ){ + if ( text ) { + this.addTextline(text, this.CSS_CLASSES.default, yShift); + } + }; + + AbsoluteTextElement.prototype.addInstanceCount = function ( instanceCount, yShift ){ + if ( instanceCount ) { + this.addTextline(instanceCount.toString(), this.CSS_CLASSES.instanceCount, yShift); + } + }; + + + AbsoluteTextElement.prototype.addTextline = function ( text, style, yShift, prefix, postfix ){ + var truncatedText = textTools.truncate(text, this._textBlock().datum().textWidth(yShift), style); + + var tspan = this._textBlock().append("tspan") + .classed(this.CSS_CLASSES.default, true) + .classed(style, true) + .text(this._applyPreAndPostFix(truncatedText, prefix, postfix)) + .attr("x", 0); + this._repositionTextLine(tspan, yShift); + }; + + AbsoluteTextElement.prototype._repositionTextLine = function ( tspan, yShift ){ + var fontSizeProperty = window.getComputedStyle(tspan.node()).getPropertyValue("font-size"); + var fontSize = parseFloat(fontSizeProperty); + + /* BBox height is not supported in Firefox for tspans and dominant-baseline doesn't work in some SVG editors */ + var approximatedShiftForVerticalCentering = (1 / 3) * fontSize; + + tspan.attr("y", approximatedShiftForVerticalCentering + (yShift || 0) + "px"); + }; + + +/***/ }), +/* 22 */ +/***/ (function(module, exports, __webpack_require__) { + + var PlainLink = __webpack_require__(23); + + + module.exports = BoxArrowLink; + + function BoxArrowLink( domain, range, property ){ + PlainLink.apply(this, arguments); + } + + BoxArrowLink.prototype = Object.create(PlainLink.prototype); + BoxArrowLink.prototype.constructor = BoxArrowLink; + + + BoxArrowLink.prototype.draw = function ( linkGroup, markerContainer ){ + var property = this.label().property(); + var inverse = this.label().inverse(); + + createPropertyMarker(markerContainer, property); + if ( inverse ) { + createInverseMarker(markerContainer, inverse); + } + + PlainLink.prototype.draw.apply(this, arguments); + + // attach the markers to the link + linkGroup.attr("marker-start", "url(#" + property.markerId() + ")"); + if ( inverse ) { + linkGroup.attr("marker-end", "url(#" + inverse.markerId() + ")"); + } + }; + + + function createPropertyMarker( markerContainer, inverse ){ + var inverseMarker = appendBasicMarker(markerContainer, inverse); + inverseMarker.attr("refX", -8); + inverseMarker.append("path") + .attr("d", "M0,-8L8,0L0,8L-8,0L0,-8L8,0") + .classed(inverse.markerType(), true); + + inverse.markerElement(inverseMarker); + } + + function createInverseMarker( markerContainer, property ){ + var marker = appendBasicMarker(markerContainer, property); + marker.attr("refX", 8); + marker.append("path") + .attr("d", "M0,-8L8,0L0,8L-8,0L0,-8L8,0") + .classed(property.markerType(), true); + + property.markerElement(marker); + } + + function appendBasicMarker( markerContainer, property ){ + return markerContainer.append("marker") + .datum(property) + .attr("id", property.markerId()) + .attr("viewBox", "-10 -10 20 20") + .attr("markerWidth", 20) + .attr("markerHeight", 20) + .attr("markerUnits", "userSpaceOnUse") + .attr("orient", "auto"); + } + + +/***/ }), +/* 23 */ +/***/ (function(module, exports, __webpack_require__) { + + var Label = __webpack_require__(24); + + + module.exports = PlainLink; + + /** + * A link connects at least two VOWL nodes. + * The properties connecting the VOWL nodes are stored separately into the label. + * @param domain + * @param range + * @param property + */ + function PlainLink( domain, range, property ){ + var layers, + layerIndex, + loops, + loopIndex, + pathEl, + label = new Label(property, this); + + var backPart = __webpack_require__(25)(domain, label, this), + frontPart = __webpack_require__(25)(label, range, this); + + + this.layers = function ( p ){ + if ( !arguments.length ) return layers; + layers = p; + return this; + }; + + this.layerIndex = function ( p ){ + if ( !arguments.length ) return layerIndex; + layerIndex = p; + return this; + }; + + this.loops = function ( p ){ + if ( !arguments.length ) return loops; + loops = p; + return this; + }; + + this.loopIndex = function ( p ){ + if ( !arguments.length ) return loopIndex; + loopIndex = p; + return this; + }; + + + this.domain = function (){ + return domain; + }; + + this.label = function (){ + return label; + }; + + this.linkParts = function (){ + return [frontPart, backPart]; + }; + + this.range = function (){ + return range; + }; + this.pathObj = function ( pE ){ + if ( !arguments.length ) { + return pathEl; + } + pathEl = pE; + }; + } + + + PlainLink.prototype.draw = function ( linkGroup ){ + var property = this.label().property(); + var inverse = this.label().inverse(); + + property.linkGroup(linkGroup); + if ( inverse ) { + inverse.linkGroup(linkGroup); + } + + var pathElement = linkGroup.append("path"); + pathElement.classed("link-path", true) + .classed(this.domain().cssClassOfNode(), true) + .classed(this.range().cssClassOfNode(), true) + .classed(property.linkType(), true); + this.pathObj(pathElement); + + }; + + + PlainLink.prototype.inverse = function (){ + return this.label().inverse(); + }; + + PlainLink.prototype.isLoop = function (){ + return this.domain().equals(this.range()); + }; + + PlainLink.prototype.property = function (){ + return this.label().property(); + }; + + + +/***/ }), +/* 24 */ +/***/ (function(module, exports) { + + module.exports = Label; + + /** + * A label represents the element(s) which further describe a link. + * It encapsulates the property and its inverse property. + * @param property the property; the inverse is inferred + * @param link the link this label belongs to + */ + function Label( property, link ){ + this.link = function (){ + return link; + }; + + this.property = function (){ + return property; + }; + + // "Forward" the fixed value set on the property to avoid having to access this container + Object.defineProperty(this, "fixed", { + get: function (){ + var inverseFixed = property.inverse() ? property.inverse().fixed : false; + return property.fixed || inverseFixed; + }, + set: function ( v ){ + property.fixed = v; + if ( property.inverse() ) property.inverse().fixed = v; + } + }); + this.frozen = property.frozen; + this.locked = property.locked; + this.pinned = property.pinned; + } + + Label.prototype.actualRadius = function (){ + return this.property().actualRadius(); + }; + + Label.prototype.draw = function ( container ){ + return this.property().draw(container); + }; + + Label.prototype.inverse = function (){ + return this.property().inverse(); + }; + + Label.prototype.equals = function ( other ){ + if ( !other ) { + return false; + } + + var instance = other instanceof Label; + var equalProperty = this.property().equals(other.property()); + + var equalInverse = false; + if ( this.inverse() ) { + equalInverse = this.inverse().equals(other.inverse()); + } else if ( !other.inverse() ) { + equalInverse = true; + } + + return instance && equalProperty && equalInverse; + }; + + +/***/ }), +/* 25 */ +/***/ (function(module, exports) { + + /** + * A linkPart connects two force layout nodes. + * It reprents a link which can be used in d3's force layout. + * @param _domain + * @param _range + * @param _link + */ + module.exports = function ( _domain, _range, _link ){ + var linkPart = {}, + domain = _domain, + link = _link, + range = _range; + + // Define d3 properties + Object.defineProperties(linkPart, { + "source": { value: domain, writable: true }, + "target": { value: range, writable: true } + }); + + + linkPart.domain = function (){ + return domain; + }; + + linkPart.link = function (){ + return link; + }; + + linkPart.range = function (){ + return range; + }; + + + return linkPart; + }; + + +/***/ }), +/* 26 */ +/***/ (function(module, exports, __webpack_require__) { + + var RoundNode = __webpack_require__(8); + + module.exports = (function (){ + + var o = function ( graph ){ + RoundNode.apply(this, arguments); + + this.attributes(["deprecated"]) + .type("owl:DeprecatedClass") + .styleClass("deprecated") + .indications(["deprecated"]); + }; + o.prototype = Object.create(RoundNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 27 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetOperatorNode = __webpack_require__(20); + + module.exports = (function (){ + + var o = function ( graph ){ + SetOperatorNode.apply(this, arguments); + + var that = this, + superDrawFunction = that.draw; + + this.styleClass("disjointunionof") + .type("owl:disjointUnionOf"); + + this.draw = function ( element ){ + superDrawFunction(element); + + var symbol = element.append("g").classed("embedded", true); + + var symbolRadius = 10; + symbol.append("circle") + .attr("class", "symbol") + .attr("r", symbolRadius); + symbol.append("circle") + .attr("cx", 10) + .attr("class", "symbol") + .classed("fineline", true) + .attr("r", symbolRadius); + symbol.append("circle") + .attr("class", "nofill") + .classed("fineline", true) + .attr("r", symbolRadius); + symbol.append("text") + .attr("class", "link") + .text("1") + .attr("transform", "scale(.7)translate(3,5)"); + + symbol.attr("transform", "translate(-" + (that.radius() - 15) / 7 + ",-" + (that.radius() - 15) / 100 + ")"); + + that.postDrawActions(); + }; + }; + o.prototype = Object.create(SetOperatorNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 28 */ +/***/ (function(module, exports, __webpack_require__) { + + var RoundNode = __webpack_require__(8); + var drawTools = __webpack_require__(17)(); + + module.exports = (function (){ + + var o = function ( graph ){ + RoundNode.apply(this, arguments); + + var CIRCLE_SIZE_DIFFERENCE = 4; + var renderingElement; + var that = this, + superActualRadiusFunction = that.actualRadius; + + this.styleClass("equivalentclass") + .type("owl:equivalentClass"); + + this.actualRadius = function (){ + return superActualRadiusFunction() + CIRCLE_SIZE_DIFFERENCE; + }; + + this.redrawElement = function (){ + renderingElement.remove(); + that.textBlock().remove(); + var bgColor = that.backgroundColor(); + + if ( that.attributes().indexOf("deprecated") > -1 ) { + bgColor = undefined; + } + var cssClasses = that.collectCssClasses(); + renderingElement = that.nodeElement().append("g"); + + if ( that.getRectangularRepresentation() === true ) { + drawTools.appendRectangularClass(renderingElement, 84, 84, ["white", "embedded"]); + drawTools.appendRectangularClass(renderingElement, 80 - CIRCLE_SIZE_DIFFERENCE, 80 - CIRCLE_SIZE_DIFFERENCE, cssClasses, that.labelForCurrentLanguage(), bgColor); + } else { + drawTools.appendCircularClass(renderingElement, that.actualRadius(), ["white", "embedded"]); + console.log(cssClasses); + console.log(that.attributes()); + console.log("what is bgColor" + bgColor); + drawTools.appendCircularClass(renderingElement, that.actualRadius() - CIRCLE_SIZE_DIFFERENCE, cssClasses, that.labelForCurrentLanguage(), bgColor); + + } + that.postDrawActions(that.nodeElement()); + + }; + this.draw = function ( parentElement ){ + var cssClasses = that.collectCssClasses(); + + that.nodeElement(parentElement); + renderingElement = parentElement.append("g"); + var bgColor = that.backgroundColor(); + if ( that.attributes().indexOf("deprecated") > -1 ) { + bgColor = undefined; + } + // draw the outer circle at first and afterwards the inner circle + if ( that.getRectangularRepresentation() === true ) { + drawTools.appendRectangularClass(renderingElement, 84, 84, ["white", "embedded"]); + drawTools.appendRectangularClass(renderingElement, 80 - CIRCLE_SIZE_DIFFERENCE, 80 - CIRCLE_SIZE_DIFFERENCE, cssClasses, that.labelForCurrentLanguage(), bgColor); + } else { + drawTools.appendCircularClass(renderingElement, that.actualRadius(), ["white", "embedded"]); + drawTools.appendCircularClass(renderingElement, that.actualRadius() - CIRCLE_SIZE_DIFFERENCE, cssClasses, that.labelForCurrentLanguage(), bgColor); + + } + + that.postDrawActions(); + }; + + /** + * Sets the hover highlighting of this node. + * @param enable + */ + that.setHoverHighlighting = function ( enable ){ + that.nodeElement().selectAll("circle:last-of-type").classed("hovered", enable); + }; + }; + o.prototype = Object.create(RoundNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 29 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetOperatorNode = __webpack_require__(20); + + module.exports = (function (){ + + var o = function ( graph ){ + SetOperatorNode.apply(this, arguments); + + var that = this, + superDrawFunction = that.draw, + INTERSECTION_BACKGROUND_PATH = createIntersectionPath(); + + this.styleClass("intersectionof") + .type("owl:intersectionOf"); + + this.draw = function ( element ){ + superDrawFunction(element); + + var symbol = element.append("g").classed("embedded", true); + + var symbolRadius = 10; + symbol.append("path") + .attr("class", "nostroke") + .classed("symbol", true) + .attr("d", INTERSECTION_BACKGROUND_PATH); + symbol.append("circle") + .attr("class", "nofill") + .classed("fineline", true) + .attr("r", symbolRadius); + symbol.append("circle") + .attr("cx", 10) + .attr("class", "nofill") + .classed("fineline", true) + .attr("r", symbolRadius); + symbol.append("path") + .attr("class", "nofill") + .attr("d", "m 9,5 c 0,-2 0,-4 0,-6 0,0 0,0 0,0 0,0 0,-1.8 -1,-2.3 -0.7,-0.6 -1.7,-0.8 -2.9," + + "-0.8 -1.2,0 -2,0 -3,0.8 -0.7,0.5 -1,1.4 -1,2.3 0,2 0,4 0,6") + .attr("transform", "scale(.5)translate(5,0)"); + + symbol.attr("transform", + "translate(-" + (that.radius() - 15) / 7 + ",-" + (that.radius() - 15) / 100 + ")"); + + that.postDrawActions(); + }; + + function createIntersectionPath(){ + var height = 18; + + var offsetX = 5; + var offsetY = -(height / 2); + + var bezierX = 7; + var bezierY = 5; + var bottomBezierY = height - bezierY; + + var startPosition = "M" + offsetX + "," + offsetY; + var rightSide = "c" + bezierX + "," + bezierY + " " + bezierX + "," + bottomBezierY + " 0," + height; + var leftSide = "c" + -bezierX + "," + -bezierY + " " + -bezierX + "," + -bottomBezierY + " 0," + -height; + + return startPosition + rightSide + leftSide; + } + }; + o.prototype = Object.create(SetOperatorNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 30 */ +/***/ (function(module, exports, __webpack_require__) { + + var OwlThing = __webpack_require__(31); + + module.exports = (function (){ + + var o = function ( graph ){ + OwlThing.apply(this, arguments); + + this.label("Nothing") + .type("owl:Nothing") + .iri("http://www.w3.org/2002/07/owl#Nothing"); + }; + o.prototype = Object.create(OwlThing.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 31 */ +/***/ (function(module, exports, __webpack_require__) { + + var RoundNode = __webpack_require__(8); + + module.exports = (function (){ + + var o = function ( graph ){ + RoundNode.apply(this, arguments); + + var superDrawFunction = this.draw; + + this.label("Thing") + .type("owl:Thing") + .iri("http://www.w3.org/2002/07/owl#Thing") + .radius(30); + + this.draw = function ( element ){ + superDrawFunction(element, ["white", "dashed"]); + }; + }; + o.prototype = Object.create(RoundNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 32 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetOperatorNode = __webpack_require__(20); + + module.exports = (function (){ + + var o = function ( graph ){ + SetOperatorNode.apply(this, arguments); + + var that = this, + superDrawFunction = that.draw; + + this.styleClass("unionof") + .type("owl:unionOf"); + + this.draw = function ( element ){ + superDrawFunction(element); + + var symbol = element.append("g").classed("embedded", true); + + var symbolRadius = 10; + symbol.append("circle") + .attr("class", "symbol") + .attr("r", symbolRadius); + symbol.append("circle") + .attr("cx", 10) + .attr("class", "symbol") + .classed("fineline", true) + .attr("r", symbolRadius); + symbol.append("circle") + .attr("class", "nofill") + .classed("fineline", true) + .attr("r", symbolRadius); + symbol.append("path") + .attr("class", "link") + .attr("d", "m 1,-3 c 0,2 0,4 0,6 0,0 0,0 0,0 0,2 2,3 4,3 2,0 4,-1 4,-3 0,-2 0,-4 0,-6") + .attr("transform", "scale(.5)translate(5,0)"); + + symbol.attr("transform", "translate(-" + (that.radius() - 15) / 7 + ",-" + (that.radius() - 15) / 100 + ")"); + + that.postDrawActions(); + }; + }; + o.prototype = Object.create(SetOperatorNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 33 */ +/***/ (function(module, exports, __webpack_require__) { + + var RoundNode = __webpack_require__(8); + + module.exports = (function (){ + + var o = function ( graph ){ + RoundNode.apply(this, arguments); + + this.attributes(["rdf"]) + .type("rdfs:Class"); + }; + o.prototype = Object.create(RoundNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 34 */ +/***/ (function(module, exports, __webpack_require__) { + + var DatatypeNode = __webpack_require__(35); + + module.exports = (function (){ + + var o = function ( graph ){ + DatatypeNode.apply(this, arguments); + var dTypeString = "undefined"; + this.attributes(["datatype"]) + .type("rdfs:Datatype") + .styleClass("datatype"); + this.dType = function ( val ){ + if ( !arguments.length ) return dTypeString; + dTypeString = val; + + }; + }; + o.prototype = Object.create(DatatypeNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 35 */ +/***/ (function(module, exports, __webpack_require__) { + + var RectangularNode = __webpack_require__(36); + + module.exports = (function (){ + + var o = function ( graph ){ + RectangularNode.apply(this, arguments); + }; + o.prototype = Object.create(RectangularNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 36 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var BaseNode = __webpack_require__(9); + var CenteringTextElement = __webpack_require__(14); + var drawTools = __webpack_require__(17)(); + var rectangularElementTools = __webpack_require__(37)(); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseNode.apply(this, arguments); + + var that = this, + height = 20, + width = 60, + pinGroupElement, + haloGroupElement, + labelWidth = 80, + myWidth = 80, + defaultWidth = 80, + shapeElement, + textBlock, + smallestRadius = height / 2; + + that.renderType("rect"); + // Properties + this.height = function ( p ){ + if ( !arguments.length ) return height; + height = p; + return this; + }; + + this.width = function ( p ){ + if ( !arguments.length ) return width; + width = p; + return this; + }; + + this.getHalos = function (){ + return haloGroupElement; + }; + + // Functions + // for compatibility reasons // TODO resolve + this.actualRadius = function (){ + return smallestRadius; + }; + + this.distanceToBorder = function ( dx, dy ){ + return rectangularElementTools.distanceToBorder(that, dx, dy); + }; + + this.setHoverHighlighting = function ( enable ){ + that.nodeElement().selectAll("rect").classed("hovered", enable); + + var haloGroup = that.getHalos(); + if ( haloGroup ) { + var test = haloGroup.selectAll(".searchResultA"); + test.classed("searchResultA", false); + test.classed("searchResultB", true); + } + + }; + + + // overwrite the labelWith; + + + this.textWidth = function (){ + return labelWidth; + }; + this.width = function (){ + return labelWidth; + }; + + this.getMyWidth = function (){ + // use a simple heuristic + var text = that.labelForCurrentLanguage(); + myWidth = measureTextWidth(text, "text") + 20; + + // check for sub names; + var indicatorText = that.indicationString(); + var indicatorWidth = measureTextWidth(indicatorText, "subtext") + 20; + if ( indicatorWidth > myWidth ) + myWidth = indicatorWidth; + + return myWidth; + }; + + this.textWidth = function (){ + return that.width(); + }; + function measureTextWidth( text, textStyle ){ + // Set a default value + if ( !textStyle ) { + textStyle = "text"; + } + var d = d3.select("body") + .append("div") + .attr("class", textStyle) + .attr("id", "width-test") // tag this element to identify it + .attr("style", "position:absolute; float:left; white-space:nowrap; visibility:hidden;") + .text(text), + w = document.getElementById("width-test").offsetWidth; + d.remove(); + return w; + } + + this.toggleFocus = function (){ + that.focused(!that.focused()); + that.nodeElement().select("rect").classed("focused", that.focused()); + graph.resetSearchHighlight(); + graph.options().searchMenu().clearText(); + }; + + /** + * Draws the rectangular node. + * @param parentElement the element to which this node will be appended + * @param [additionalCssClasses] additional css classes + */ + this.draw = function ( parentElement, additionalCssClasses ){ + var cssClasses = that.collectCssClasses(); + + that.nodeElement(parentElement); + + if ( additionalCssClasses instanceof Array ) { + cssClasses = cssClasses.concat(additionalCssClasses); + } + + // set the value for that.width() + // update labelWidth Value; + if ( graph.options().dynamicLabelWidth() === true ) labelWidth = Math.min(that.getMyWidth(), graph.options().maxLabelWidth()); + else labelWidth = defaultWidth; + + width = labelWidth; + shapeElement = drawTools.appendRectangularClass(parentElement, that.width(), that.height(), cssClasses, that.labelForCurrentLanguage(), that.backgroundColor()); + + textBlock = new CenteringTextElement(parentElement, that.backgroundColor()); + textBlock.addText(that.labelForCurrentLanguage()); + + that.addMouseListeners(); + + if ( that.pinned() ) { + that.drawPin(); + } + if ( that.halo() ) { + that.drawHalo(false); + } + }; + + this.drawPin = function (){ + that.pinned(true); + // if (graph.options().dynamicLabelWidth()===true) labelWidth=that.getMyWidth(); + // else labelWidth=defaultWidth; + // width=labelWidth; + // console.log("this element label Width is "+labelWidth); + var dx = -0.5 * labelWidth + 5, + dy = -1.1 * height; + + pinGroupElement = drawTools.drawPin(that.nodeElement(), dx, dy, this.removePin, graph.options().showDraggerObject, graph.options().useAccuracyHelper()); + + }; + + this.removePin = function (){ + that.pinned(false); + if ( pinGroupElement ) { + pinGroupElement.remove(); + } + graph.updateStyle(); + }; + + this.removeHalo = function (){ + that.halo(false); + if ( haloGroupElement ) { + haloGroupElement.remove(); + haloGroupElement = null; + } + }; + + this.drawHalo = function ( pulseAnimation ){ + that.halo(true); + + var offset = 0; + haloGroupElement = drawTools.drawRectHalo(that, this.width(), this.height(), offset); + + if ( pulseAnimation === false ) { + var pulseItem = haloGroupElement.selectAll(".searchResultA"); + pulseItem.classed("searchResultA", false); + pulseItem.classed("searchResultB", true); + pulseItem.attr("animationRunning", false); + } + + if ( that.pinned() ) { + var selectedNode = pinGroupElement.node(); + var nodeContainer = selectedNode.parentNode; + nodeContainer.appendChild(selectedNode); + } + + }; + + this.updateTextElement = function (){ + textBlock.updateAllTextElements(); + + }; + + this.textBlock = function (){ + return textBlock; + }; + + this.redrawLabelText = function (){ + textBlock.remove(); + textBlock = new CenteringTextElement(that.nodeElement(), that.backgroundColor()); + textBlock.addText(that.labelForCurrentLanguage()); + that.animateDynamicLabelWidth(graph.options().dynamicLabelWidth()); + shapeElement.select("title").text(that.labelForCurrentLanguage()); + }; + + this.animateDynamicLabelWidth = function ( dynamic ){ + that.removeHalo(); + var height = that.height(); + if ( dynamic === true ) { + labelWidth = Math.min(that.getMyWidth(), graph.options().maxLabelWidth()); + shapeElement.transition().tween("attr", function (){ + }) + .ease('linear') + .duration(100) + .attr({ x: -labelWidth / 2, y: -height / 2, width: labelWidth, height: height }) + .each("end", function (){ + that.updateTextElement(); + }); + + } else { + labelWidth = defaultWidth; + that.updateTextElement(); + shapeElement.transition().tween("attr", function (){ + }) + .ease('linear') + .duration(100) + .attr({ x: -labelWidth / 2, y: -height / 2, width: labelWidth, height: height }); + + } + + // for the pin we dont need to differ between different widths -- they are already set + if ( that.pinned() === true && pinGroupElement ) { + + var dx = 0.5 * labelWidth - 10, + dy = -1.1 * height; + + pinGroupElement.transition() + .tween("attr.translate", function (){ + }) + .attr("transform", "translate(" + dx + "," + dy + ")") + .ease('linear') + .duration(100); + } + }; + + this.addTextLabelElement = function (){ + var parentElement = that.nodeElement(); + textBlock = new CenteringTextElement(parentElement, this.backgroundColor()); + textBlock.addText(that.labelForCurrentLanguage()); + }; + + + }; + o.prototype = Object.create(BaseNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 37 */ +/***/ (function(module, exports) { + + var tools = {}; + module.exports = function (){ + return tools; + }; + + tools.distanceToBorder = function ( rect, dx, dy ){ + var width = rect.width(), + height = rect.height(); + + var innerDistance, + m_link = Math.abs(dy / dx), + m_rect = height / width; + + if ( m_link <= m_rect ) { + var timesX = dx / (width / 2), + rectY = dy / timesX; + innerDistance = Math.sqrt(Math.pow(width / 2, 2) + Math.pow(rectY, 2)); + } else { + var timesY = dy / (height / 2), + rectX = dx / timesY; + innerDistance = Math.sqrt(Math.pow(height / 2, 2) + Math.pow(rectX, 2)); + } + + return innerDistance; + }; + + +/***/ }), +/* 38 */ +/***/ (function(module, exports, __webpack_require__) { + + var DatatypeNode = __webpack_require__(35); + + module.exports = (function (){ + + var o = function ( graph ){ + DatatypeNode.apply(this, arguments); + + var superDrawFunction = this.draw, + superLabelFunction = this.label; + + this.attributes(["datatype"]) + .label("Literal") + .styleClass("literal") + .type("rdfs:Literal") + .iri("http://www.w3.org/2000/01/rdf-schema#Literal"); + + this.draw = function ( element ){ + superDrawFunction(element, ["dashed"]); + }; + + this.label = function ( p ){ + if ( !arguments.length ) return superLabelFunction(); + return this; + }; + }; + o.prototype = Object.create(DatatypeNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 39 */ +/***/ (function(module, exports, __webpack_require__) { + + var RoundNode = __webpack_require__(8); + + module.exports = (function (){ + + var o = function ( graph ){ + RoundNode.apply(this, arguments); + + var superDrawFunction = this.draw; + + this.attributes(["rdf"]) + .label("Resource") + .radius(30) + .styleClass("rdfsresource") + .type("rdfs:Resource"); + + this.draw = function ( element ){ + superDrawFunction(element, ["rdf", "dashed"]); + }; + }; + o.prototype = Object.create(RoundNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 40 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var properties = []; + properties.push(__webpack_require__(41)); + properties.push(__webpack_require__(44)); + properties.push(__webpack_require__(45)); + properties.push(__webpack_require__(46)); + properties.push(__webpack_require__(47)); + properties.push(__webpack_require__(48)); + properties.push(__webpack_require__(49)); + properties.push(__webpack_require__(50)); + properties.push(__webpack_require__(51)); + properties.push(__webpack_require__(52)); + properties.push(__webpack_require__(53)); + properties.push(__webpack_require__(54)); + properties.push(__webpack_require__(55)); + properties.push(__webpack_require__(56)); + + var map = d3.map(properties, function ( Prototype ){ + return new Prototype().type(); + }); + + module.exports = function (){ + return map; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 41 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + var superGenerateCardinalityText = this.generateCardinalityText; + + this.linkType("values-from") + .markerType("filled values-from") + .styleClass("allvaluesfromproperty") + .type("owl:allValuesFrom"); + + this.generateCardinalityText = function (){ + var cardinalityText = "A"; + + var superCardinalityText = superGenerateCardinalityText(); + if ( superCardinalityText ) { + cardinalityText += ", " + superCardinalityText; + } + + return cardinalityText; + }; + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + + + +/***/ }), +/* 42 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var BaseElement = __webpack_require__(10); + var CenteringTextElement = __webpack_require__(14); + var drawTools = __webpack_require__(17)(); + var forceLayoutNodeFunctions = __webpack_require__(13)(); + var rectangularElementTools = __webpack_require__(37)(); + var math = __webpack_require__(43)(); + + module.exports = (function (){ + + // Static variables + var labelHeight = 28, + labelWidth = 80, + smallestRadius = labelHeight / 2; + + + // Constructor, private variables and privileged methods + var Base = function ( graph ){ + BaseElement.apply(this, arguments); + + var that = this, + // Basic attributes + cardinality, + domain, + inverse, + link, + minCardinality, + maxCardinality, + range, + subproperties, + superproperties, + // Style attributes + linkType = "normal", + markerType = "filled", + labelVisible = true, + // Element containers + cardinalityElement, + labelElement, + linkGroup, + markerElement, + // Other + ignoreLocalHoverEvents, + fobj, + pinGroupElement, + haloGroupElement, + myWidth = 80, + defaultWidth = 80, + shapeElement, + textElement, + parent_labelObject, + backupFullIri, + + redundantProperties = []; + + + this.existingPropertyIRI = function ( url ){ + return graph.options().editSidebar().checkForExistingURL(url); + }; + + this.getHalos = function (){ + return haloGroupElement; + }; + + this.getPin = function (){ + return pinGroupElement; + }; + this.labelObject = function ( lo, once ){ + if ( !arguments.length ) { + return parent_labelObject; + } + else { + parent_labelObject = lo; + if ( that.inverse() && once !== true ) { + that.inverse().labelObject(lo, true); + } + + } + }; + this.hide = function ( val ){ + that.labelElement().classed("hidden", val); + that.linkGroup().classed("hidden", val); + if ( that.cardinalityElement() ) + that.cardinalityElement().classed("hidden", val); + }; + + // Properties + this.cardinality = function ( p ){ + if ( !arguments.length ) return cardinality; + cardinality = p; + return this; + }; + + this.cardinalityElement = function ( p ){ + if ( !arguments.length ) return cardinalityElement; + cardinalityElement = p; + return this; + }; + + this.domain = function ( p ){ + if ( !arguments.length ) return domain; + domain = p; + return this; + }; + + this.inverse = function ( p ){ + if ( !arguments.length ) return inverse; + inverse = p; + return this; + }; + + this.labelElement = function ( p ){ + if ( !arguments.length ) return labelElement; + labelElement = p; + return this; + }; + + this.labelVisible = function ( p ){ + if ( !arguments.length ) return labelVisible; + labelVisible = p; + return this; + }; + + this.link = function ( p ){ + if ( !arguments.length ) return link; + link = p; + return this; + }; + + this.linkGroup = function ( p ){ + if ( !arguments.length ) return linkGroup; + linkGroup = p; + return this; + }; + + this.linkType = function ( p ){ + if ( !arguments.length ) return linkType; + linkType = p; + return this; + }; + + this.markerElement = function ( p ){ + if ( !arguments.length ) return markerElement; + markerElement = p; + return this; + }; + + this.markerType = function ( p ){ + if ( !arguments.length ) return markerType; + markerType = p; + return this; + }; + + this.maxCardinality = function ( p ){ + if ( !arguments.length ) return maxCardinality; + maxCardinality = p; + return this; + }; + + this.minCardinality = function ( p ){ + if ( !arguments.length ) return minCardinality; + minCardinality = p; + return this; + }; + + this.range = function ( p ){ + if ( !arguments.length ) return range; + range = p; + return this; + }; + + this.redundantProperties = function ( p ){ + if ( !arguments.length ) return redundantProperties; + redundantProperties = p; + return this; + }; + + this.subproperties = function ( p ){ + if ( !arguments.length ) return subproperties; + subproperties = p; + return this; + }; + + this.superproperties = function ( p ){ + if ( !arguments.length ) return superproperties; + superproperties = p; + return this; + }; + + + // Functions + this.distanceToBorder = function ( dx, dy ){ + return rectangularElementTools.distanceToBorder(that, dx, dy); + }; + + this.linkHasMarker = function (){ + return linkType !== "dashed"; + }; + + this.markerId = function (){ + return "marker" + that.id(); + }; + + this.toggleFocus = function (){ + that.focused(!that.focused()); + labelElement.select("rect").classed("focused", that.focused()); + graph.resetSearchHighlight(); + graph.options().searchMenu().clearText(); + }; + this.getShapeElement = function (){ + return shapeElement; + }; + + this.textBlock = function (){ + return textElement; + }; + + this.redrawElement = function (){ + shapeElement.remove(); + textElement.remove(); + + that.drawLabel(that.labelElement()); + that.animateDynamicLabelWidth(graph.options().dynamicLabelWidth()); + + + // shapeElement=this.addRect(that.labelElement()); + // + // var equivalentsString = that.equivalentsString(); + // var suffixForFollowingEquivalents = equivalentsString ? "," : ""; + // + // textElement = new CenteringTextElement(labelContainer, this.backgroundColor()); + // textElement.addText(this.labelForCurrentLanguage(), "", suffixForFollowingEquivalents); + // textElement.addEquivalents(equivalentsString); + // textElement.addSubText(this.indicationString()); + + }; + + // Reused functions TODO refactor + this.draw = function ( labelGroup ){ + function attachLabel( property ){ + var labelContainer = labelGroup.append("g") + .datum(property) + .classed("label", true) + .attr("id", property.id()); + + property.drawLabel(labelContainer); + return labelContainer; + } + + if ( !that.labelVisible() ) { + return undefined; + } + if ( graph.options().dynamicLabelWidth() === true ) myWidth = Math.min(that.getMyWidth(), graph.options().maxLabelWidth()); + else myWidth = defaultWidth; + + that.labelElement(attachLabel(that)); + // Draw an inverse label and reposition both labels if necessary + if ( that.inverse() ) { + var yTransformation = (that.height() / 2) + 1 /* additional space */; + that.inverse() + .labelElement(attachLabel(that.inverse())); + + that.labelElement() + .attr("transform", "translate(" + 0 + ",-" + yTransformation + ")"); + that.inverse() + .labelElement() + .attr("transform", "translate(" + 0 + "," + yTransformation + ")"); + } + + if ( that.pinned() ) { + that.drawPin(); + } else if ( that.inverse() && that.inverse().pinned() ) { + that.inverse().drawPin(); + } + + if ( that.halo() ) + that.drawHalo(false); + + return that.labelElement(); + }; + + this.addRect = function ( labelContainer ){ + var rect = labelContainer.append("rect") + .classed(that.styleClass(), true) + .classed("property", true) + .attr("x", -that.width() / 2) + .attr("y", -that.height() / 2) + .attr("width", that.width()) + .attr("height", that.height()) + .on("mouseover", function (){ + onMouseOver(); + }) + .on("mouseout", function (){ + onMouseOut(); + }); + + rect.append("title") + .text(that.labelForCurrentLanguage()); + + if ( that.visualAttributes() ) { + rect.classed(that.visualAttributes(), true); + } + + var bgColor = that.backgroundColor(); + + if ( that.attributes().indexOf("deprecated") > -1 ) { + bgColor = undefined; + rect.classed("deprecatedproperty", true); + } else { + rect.classed("deprecatedproperty", false); + } + rect.style("fill", bgColor); + + return rect; + }; + this.drawLabel = function ( labelContainer ){ + shapeElement = this.addRect(labelContainer); + + var equivalentsString = that.equivalentsString(); + var suffixForFollowingEquivalents = equivalentsString ? "," : ""; + + var bgColor = that.backgroundColor(); + if ( that.attributes().indexOf("deprecated") > -1 ) { + bgColor = undefined; + } + textElement = new CenteringTextElement(labelContainer, bgColor); + textElement.addText(this.labelForCurrentLanguage(), "", suffixForFollowingEquivalents); + textElement.addEquivalents(equivalentsString); + textElement.addSubText(this.indicationString()); + }; + + this.equivalentsString = function (){ + var equivalentProperties = that.equivalents(); + if ( !equivalentProperties ) { + return; + } + + return equivalentProperties + .map(function ( property ){ + if ( property === undefined || typeof(property) === "string" ) { // @WORKAROUND + return "ERROR"; + } + return property.labelForCurrentLanguage(); + }) + .join(", "); + }; + + this.drawCardinality = function ( container ){ + var cardinalityText = this.generateCardinalityText(); + + if ( cardinalityText ) { + that.cardinalityElement(container); + if ( cardinalityText.indexOf("A") === 0 && cardinalityText.length === 1 ) { + + // replacing text elements to svg elements; + container.classed("cardinality", true) + .attr("text-anchor", "middle") + .append("path") + .classed("cardinality", true) + .attr("d", "m -8.8832678,-11.303355 -7.97e-4,0 0.717374,1.833297 8.22987151,21.371761 8.66826659,-21.2123526 0.797082,-1.9927054 0.02471,0 -0.8218553,1.9927054 -2.2517565,5.4201577 -12.4444429,8e-6 -2.2019394,-5.5795821 z") + .style("fill", "none") + .attr("transform", "matrix(0.5,0,0,0.5,0.5,0.5)"); + return true; + } else if ( cardinalityText.indexOf("E") === 0 && cardinalityText.length === 1 ) { + container.classed("cardinality", true) + .attr("text-anchor", "middle") + .append("path") + .classed("cardinality", true) + .attr("d", "m -5.5788451,-8.0958763 10.8749368,0 0,8.34681523 -9.5707468,0.040132 9.5707468,-0.040132 0,8.42707237 -10.9150654,0") + .style("fill", "none") + .attr("transform", "matrix(0.5,0,0,0.5,0.5,0.5)"); + return true; + } + else { + container.append("text") + .classed("cardinality", true) + .attr("text-anchor", "middle") + .attr("dy", "0.5ex") + .text(cardinalityText); + return true; // drawing successful + } + } else { + return false; + } + }; + + this.generateCardinalityText = function (){ + if ( that.cardinality() ) { + return that.cardinality(); + } else if ( that.minCardinality() || that.maxCardinality() ) { + var minBoundary = that.minCardinality() || "*"; + var maxBoundary = that.maxCardinality() || "*"; + return minBoundary + ".." + maxBoundary; + } + }; + + that.setHighlighting = function ( enable ){ + if ( that.labelElement && that.labelElement() ) { + that.labelElement().select("rect").classed("hovered", enable); + } + that.linkGroup().selectAll("path, text").classed("hovered", enable); + if ( that.markerElement() ) { + that.markerElement().select("path").classed("hovered", enable); + if ( that.cardinalityElement() ) { + that.cardinalityElement().selectAll("path").classed("hovered-MathSymbol", enable); + that.cardinalityElement().classed("hovered", enable); + } + } + var subAndSuperProperties = getSubAndSuperProperties(); + subAndSuperProperties.forEach(function ( property ){ + + if ( property.labelElement && property.labelElement() ) { + property.labelElement().select("rect") + .classed("indirect-highlighting", enable); + } + + }); + var inversed = false; + + if ( graph.ignoreOtherHoverEvents() === false ) { + if ( that.inverse() ) { + inversed = true; + } + + if ( graph.isTouchDevice() === false ) { + graph.activateHoverElementsForProperties(enable, that, inversed); + } + else { + that.labelElement().select("rect").classed("hovered", false); + that.linkGroup().selectAll("path, text").classed("hovered", false); + if ( that.markerElement() ) { + that.markerElement().select("path").classed("hovered", false); + if ( that.cardinalityElement() ) { + that.cardinalityElement().classed("hovered", false); + } + } + graph.activateHoverElementsForProperties(enable, that, inversed, true); + } + } + }; + + /** + * Combines the sub- and superproperties into a single array, because + * they're often used equivalently. + * @returns {Array} + */ + function getSubAndSuperProperties(){ + var properties = []; + + if ( that.subproperties() ) { + properties = properties.concat(that.subproperties()); + } + if ( that.superproperties() ) { + properties = properties.concat(that.superproperties()); + } + + return properties; + } + + /** + * Foregrounds the property, its inverse and the link. + */ + this.foreground = function (){ + // check for additional objects that we can highlight + if ( !that.labelElement() ) + return; + if ( that.labelElement().node().parentNode === null ) { + return; + } + var selectedLabelGroup = that.labelElement().node().parentNode, + labelContainer = selectedLabelGroup.parentNode, + selectedLinkGroup = that.linkGroup().node(), + linkContainer = that.linkGroup().node().parentNode; + if ( that.animationProcess() === false ) { + labelContainer.appendChild(selectedLabelGroup); + } + linkContainer.appendChild(selectedLinkGroup); + }; + + /** + * Foregrounds the sub- and superproperties of this property. + * This is separated from the foreground-function to prevent endless loops. + */ + function foregroundSubAndSuperProperties(){ + var subAndSuperProperties = getSubAndSuperProperties(); + + subAndSuperProperties.forEach(function ( property ){ + if ( property.foreground ) property.foreground(); + }); + } + + function onMouseOver(){ + if ( that.mouseEntered() || ignoreLocalHoverEvents === true ) { + return; + } + that.mouseEntered(true); + that.setHighlighting(true); + that.foreground(); + foregroundSubAndSuperProperties(); + } + + function onMouseOut(){ + that.mouseEntered(false); + that.setHighlighting(false); + } + + this.drawPin = function (){ + that.pinned(true); + if ( graph.options().dynamicLabelWidth() === true ) myWidth = that.getMyWidth(); + else myWidth = defaultWidth; + + if ( that.inverse() ) { + // check which element is rendered on top and add a pin to it + var tr_that = that.labelElement().attr("transform"); + var tr_inv = that.inverse().labelElement().attr("transform"); + + var thatY = /translate\(\s*([^\s,)]+)[ ,]([^\s,)]+)/.exec(tr_that)[2]; + var invY = /translate\(\s*([^\s,)]+)[ ,]([^\s,)]+)/.exec(tr_inv)[2]; + + if ( thatY < invY ) + pinGroupElement = drawTools.drawPin(that.labelElement(), -0.5 * that.width() + 10, -25, this.removePin, graph.options().showDraggerObject, graph.options().useAccuracyHelper()); + else + pinGroupElement = drawTools.drawPin(that.inverse().labelElement(), -0.5 * that.inverse().width() + 10, -25, this.removePin, graph.options().showDraggerObject, graph.options().useAccuracyHelper()); + + } + else { + pinGroupElement = drawTools.drawPin(that.labelElement(), -0.5 * that.width() + 10, -25, this.removePin, graph.options().showDraggerObject, graph.options().useAccuracyHelper()); + } + + + }; + + /** + * Removes the pin and refreshs the graph to update the force layout. + */ + this.removePin = function (){ + that.pinned(false); + if ( pinGroupElement ) { + pinGroupElement.remove(); + } + graph.updateStyle(); + }; + + this.removeHalo = function (){ + that.halo(false); + if ( haloGroupElement ) { + haloGroupElement.remove(); + haloGroupElement = null; + } + }; + + this.animationProcess = function (){ + var animRuns = false; + if ( that.getHalos() ) { + var haloGr = that.getHalos(); + var haloEls = haloGr.selectAll(".searchResultA"); + animRuns = haloGr.attr("animationRunning"); + + if ( typeof animRuns !== "boolean" ) { + // parse this to a boolean value + animRuns = (animRuns === 'true'); + } + if ( animRuns === false ) { + haloEls.classed("searchResultA", false); + haloEls.classed("searchResultB", true); + } + } + return animRuns; + }; + + this.drawHalo = function ( pulseAnimation ){ + that.halo(true); + var offset = 0; + if ( that.labelElement() && that.labelElement().node() ) { + var labelNode = that.labelElement().node(); + var labelContainer = labelNode.parentNode; + // do this only if animation is not running + if ( that.animationProcess() === false ) + labelContainer.appendChild(labelNode); + } + haloGroupElement = drawTools.drawRectHalo(that, that.width(), that.height(), offset); + if ( haloGroupElement ) { + var haloNode = haloGroupElement.node(); + var haloContainer = haloNode.parentNode; + haloContainer.appendChild(haloNode); + } + var selectedNode; + var nodeContainer; + if ( that.pinned() ) { + selectedNode = pinGroupElement.node(); + nodeContainer = selectedNode.parentNode; + nodeContainer.appendChild(selectedNode); + } + if ( that.inverse() && that.inverse().pinned() ) { + if ( that.inverse().getPin() ) { + selectedNode = that.inverse().getPin().node(); + nodeContainer = selectedNode.parentNode; + nodeContainer.appendChild(selectedNode); + } + } + if ( pulseAnimation === false ) { + var pulseItem = haloGroupElement.selectAll(".searchResultA"); + pulseItem.classed("searchResultA", false); + pulseItem.classed("searchResultB", true); + pulseItem.attr("animationRunning", false); + } + }; + + this.getMyWidth = function (){ + var text = that.labelForCurrentLanguage(); + myWidth = measureTextWidth(text, "text") + 20; + // check for sub names; + var indicatorText = that.indicationString(); + var indicatorWidth = measureTextWidth(indicatorText, "subtext") + 20; + if ( indicatorWidth > myWidth ) + myWidth = indicatorWidth; + + return myWidth; + }; + + function measureTextWidth( text, textStyle ){ + // Set a default value + if ( !textStyle ) { + textStyle = "text"; + } + var d = d3.select("body") + .append("div") + .attr("class", textStyle) + .attr("id", "width-test") // tag this element to identify it + .attr("style", "position:absolute; float:left; white-space:nowrap; visibility:hidden;") + .text(text), + w = document.getElementById("width-test").offsetWidth; + d.remove(); + return w; + } + + this.textWidth = function (){ + return myWidth; + }; + this.width = function (){ + return myWidth; + }; + + this.animateDynamicLabelWidth = function ( dynamic ){ + that.removeHalo(); + if ( shapeElement === undefined ) {// this handles setOperatorProperties which dont have a shapeElement! + return; + } + + var h = that.height(); + if ( dynamic === true ) { + myWidth = Math.min(that.getMyWidth(), graph.options().maxLabelWidth()); + shapeElement.transition().tween("attr", function (){ + }) + .ease('linear') + .duration(100) + .attr({ x: -myWidth / 2, y: -h / 2, width: myWidth, height: h }) + .each("end", function (){ + that.updateTextElement(); + }); + } else { + // Static width for property labels = 80 + myWidth = defaultWidth; + that.updateTextElement(); + shapeElement.transition().tween("attr", function (){ + }) + .ease('linear') + .duration(100) + .attr({ x: -myWidth / 2, y: -h / 2, width: myWidth, height: h }); + } + if ( that.pinned() === true && pinGroupElement ) { + var dx = -0.5 * myWidth + 10, + dy = -25; + pinGroupElement.transition() + .tween("attr.translate", function (){ + }) + .attr("transform", "translate(" + dx + "," + dy + ")") + .ease('linear') + .duration(100); + } + }; + + this.redrawLabelText = function (){ + textElement.remove(); + that.addTextLabelElement(); + that.animateDynamicLabelWidth(graph.options().dynamicLabelWidth()); + shapeElement.select("title").text(that.labelForCurrentLanguage()); + }; + + this.addTextLabelElement = function (){ + var labelContainer = that.labelElement(); + + var equivalentsString = that.equivalentsString(); + var suffixForFollowingEquivalents = equivalentsString ? "," : ""; + + textElement = new CenteringTextElement(labelContainer, this.backgroundColor()); + textElement.addText(this.labelForCurrentLanguage(), "", suffixForFollowingEquivalents); + textElement.addEquivalents(equivalentsString); + textElement.addSubText(this.indicationString()); + }; + + this.updateTextElement = function (){ + textElement.updateAllTextElements(); + }; + this.enableEditing = function ( autoEditing ){ + if ( autoEditing === false ) + return; + that.raiseDoubleClickEdit(true); + }; + + this.raiseDoubleClickEdit = function ( forceIRISync ){ + d3.selectAll(".foreignelements").remove(); + if ( that.labelElement() === undefined || this.type() === "owl:disjointWith" || this.type() === "rdfs:subClassOf" ) { + console.log("No Container found"); + return; + } + if ( fobj !== undefined ) { + that.labelElement().selectAll(".foreignelements").remove(); + } + backupFullIri = undefined; + graph.options().focuserModule().handle(undefined); + graph.options().focuserModule().handle(that); + that.editingTextElement = true; + ignoreLocalHoverEvents = true; + that.labelElement().selectAll("rect").classed("hoveredForEditing", true); + that.frozen(true); + graph.killDelayedTimer(); + graph.ignoreOtherHoverEvents(false); + fobj = that.labelElement().append("foreignObject") + .attr("x", -0.5 * that.textWidth()) + .attr("y", -13) + .attr("height", 25) + .attr("class", "foreignelements") + .on("dragstart", function (){ + return false; + }) // remove drag operations of text element) + .attr("width", that.textWidth() - 2); + // adding a Style to the fObject + // + // + // + var editText = fobj.append("xhtml:input") + .attr("class", "nodeEditSpan") + .attr("id", that.id()) + .attr("align", "center") + .attr("contentEditable", "true") + .on("dragstart", function (){ + return false; + }); // remove drag operations of text element) + + var bgColor = '#f00'; + var txtWidth = that.textWidth() - 2; + editText.style({ + // 'line-height': '30px', + 'align': 'center', + 'color': 'black', + 'width': txtWidth + "px", + 'background-color': bgColor, + 'border-bottom': '2px solid black' + }); + var txtNode = editText.node(); + txtNode.value = that.labelForCurrentLanguage(); + txtNode.focus(); + txtNode.select(); + if ( d3.event.stopPropagation ) d3.event.stopPropagation(); + if ( d3.event.sourceEvent && d3.event.sourceEvent.stopPropagation ) d3.event.sourceEvent.stopPropagation(); + + // add some events that relate to this object + editText.on("click", function (){ + if ( d3.event.stopPropagation ) d3.event.stopPropagation(); + if ( d3.event.sourceEvent && d3.event.sourceEvent.stopPropagation ) d3.event.sourceEvent.stopPropagation(); + + }); + // // remove hover Events for now; + editText.on("mouseout", function (){ + if ( d3.event.stopPropagation ) d3.event.stopPropagation(); + if ( d3.event.sourceEvent && d3.event.sourceEvent.stopPropagation ) d3.event.sourceEvent.stopPropagation(); + }); + editText.on("mousedown", function (){ + if ( d3.event.stopPropagation ) d3.event.stopPropagation(); + if ( d3.event.sourceEvent && d3.event.sourceEvent.stopPropagation ) d3.event.sourceEvent.stopPropagation(); + }) + .on("keydown", function (){ + + if ( d3.event.keyCode === 13 ) { + this.blur(); + that.frozen(false); // << releases the not after selection + that.locked(false); + } + }) + .on("keyup", function (){ + if ( forceIRISync ) { + var labelName = editText.node().value; + var resourceName = labelName.replaceAll(" ", "_"); + var syncedIRI = that.baseIri() + resourceName; + backupFullIri = syncedIRI; + + d3.select("#element_iriEditor").node().title = syncedIRI; + d3.select("#element_iriEditor").node().value = graph.options().prefixModule().getPrefixRepresentationForFullURI(syncedIRI); + } + d3.select("#element_labelEditor").node().value = editText.node().value; + + }) + .on("blur", function (){ + + + that.editingTextElement = false; + ignoreLocalHoverEvents = false; + that.labelElement().selectAll("rect").classed("hoveredForEditing", false); + var newLabel = editText.node().value; + that.labelElement().selectAll(".foreignelements").remove(); + // that.setLabelForCurrentLanguage(classNameConvention(editText.node().value)); + that.label(newLabel); + that.backupLabel(newLabel); + that.redrawLabelText(); + updateHoverElements(true); + graph.showHoverElementsAfterAnimation(that, false); + graph.ignoreOtherHoverEvents(false); + + + that.frozen(graph.paused()); + that.locked(graph.paused()); + that.domain().frozen(graph.paused()); + that.domain().locked(graph.paused()); + that.range().frozen(graph.paused()); + that.range().locked(graph.paused()); + graph.removeEditElements(); + if ( backupFullIri ) { + // console.log("Checking if element is Identical ?"); + var sanityCheckResult = graph.options().editSidebar().checkProperIriChange(that, backupFullIri); + if ( sanityCheckResult !== false ) { + graph.options().warningModule().showWarning("Already seen this property", + "Input IRI: " + backupFullIri + " for element: " + that.labelForCurrentLanguage() + " already been set", + "Continuing with duplicate property!", 1, false, sanityCheckResult); + } + that.iri(backupFullIri); + } + graph.options().focuserModule().handle(undefined); + graph.options().focuserModule().handle(that); + graph.updatePropertyDraggerElements(that); + + + }); // add a foreiner element to this thing; + + }; + + // update hover elements + function updateHoverElements( enable ){ + if ( graph.ignoreOtherHoverEvents() === false ) { + var inversed = false; + if ( that.inverse() ) { + inversed = true; + } + if ( enable === true ) { + graph.activateHoverElementsForProperties(enable, that, inversed); + } + } + } + + that.copyInformation = function ( other ){ + that.label(other.label()); + that.iri(other.iri()); + that.baseIri(other.baseIri()); + if ( other.type() === "owl:ObjectProperty" || + other.type() === "owl:DatatypeProperty" ) { + that.backupLabel(other.label()); + // console.log("copied backup label"+that.backupLabel()); + } + if ( other.backupLabel() !== undefined ) { + that.backupLabel(other.backupLabel()); + } + }; + + forceLayoutNodeFunctions.addTo(this); + }; + + Base.prototype = Object.create(BaseElement.prototype); + Base.prototype.constructor = Base; + + Base.prototype.height = function (){ + return labelHeight; + }; + + Base.prototype.width = function (){ + return labelWidth; + }; + + Base.prototype.actualRadius = function (){ + return smallestRadius; + }; + + Base.prototype.textWidth = Base.prototype.width; + + + return Base; + }()); + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 43 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains a collection of mathematical functions with some additional data + * used for WebVOWL. + */ + module.exports = (function (){ + + var math = {}, + loopFunction = d3.svg.line() + .x(function ( d ){ + return d.x; + }) + .y(function ( d ){ + return d.y; + }) + .interpolate("cardinal") + .tension(-1); + + + /** + * Calculates the normal vector of the path between the two nodes. + * @param source the first node + * @param target the second node + * @param length the length of the calculated normal vector + * @returns {{x: number, y: number}} + */ + math.calculateNormalVector = function ( source, target, length ){ + var dx = target.x - source.x, + dy = target.y - source.y; + + var nx = -dy, + ny = dx; + + var vlength = Math.sqrt(nx * nx + ny * ny); + + var ratio = vlength !== 0 ? length / vlength : 0; + + return { "x": nx * ratio, "y": ny * ratio }; + }; + + /** + * Calculates the path for a link, if it is a loop. Currently only working for circlular nodes. + * @param link the link + * @returns {*} + */ + + + + math.getLoopPoints = function ( link ){ + var node = link.domain(), + label = link.label(); + + var fairShareLoopAngle = 360 / link.loops().length, + fairShareLoopAngleWithMargin = fairShareLoopAngle * 0.8, + loopAngle = Math.min(60, fairShareLoopAngleWithMargin); + + if ( label.increasedLoopAngle === true ) + loopAngle = 120; + + + var dx = label.x - node.x, + dy = label.y - node.y, + labelRadian = Math.atan2(dy, dx), + labelAngle = calculateAngle(labelRadian); + + var startAngle = labelAngle - loopAngle / 2, + endAngle = labelAngle + loopAngle / 2; + + + var arcFrom = calculateRadian(startAngle), + arcTo = calculateRadian(endAngle), + + x1 = Math.cos(arcFrom) * node.actualRadius(), + y1 = Math.sin(arcFrom) * node.actualRadius(), + + x2 = Math.cos(arcTo) * node.actualRadius(), + y2 = Math.sin(arcTo) * node.actualRadius(), + + fixPoint1 = { "x": node.x + x1, "y": node.y + y1 }, + fixPoint2 = { "x": node.x + x2, "y": node.y + y2 }; + + return [fixPoint1, fixPoint2]; + }; + math.calculateLoopPath = function ( link ){ + var node = link.domain(), + label = link.label(); + + + var fairShareLoopAngle = 360 / link.loops().length, + fairShareLoopAngleWithMargin = fairShareLoopAngle * 0.8, + loopAngle = Math.min(60, fairShareLoopAngleWithMargin); + + if ( label.increasedLoopAngle === true ) + loopAngle = 120; + + var dx = label.x - node.x, + dy = label.y - node.y, + labelRadian = Math.atan2(dy, dx), + labelAngle = calculateAngle(labelRadian); + + var startAngle = labelAngle - loopAngle / 2, + endAngle = labelAngle + loopAngle / 2; + + var arcFrom = calculateRadian(startAngle), + arcTo = calculateRadian(endAngle), + + x1 = Math.cos(arcFrom) * node.actualRadius(), + y1 = Math.sin(arcFrom) * node.actualRadius(), + + x2 = Math.cos(arcTo) * node.actualRadius(), + y2 = Math.sin(arcTo) * node.actualRadius(), + + fixPoint1 = { "x": node.x + x1, "y": node.y + y1 }, + fixPoint2 = { "x": node.x + x2, "y": node.y + y2 }; + + return loopFunction([fixPoint1, link.label(), fixPoint2]); + }; + + math.calculateLoopPoints = function ( link ){ + var node = link.domain(), + label = link.label(); + + var fairShareLoopAngle = 360 / link.loops().length, + fairShareLoopAngleWithMargin = fairShareLoopAngle * 0.8, + loopAngle = Math.min(60, fairShareLoopAngleWithMargin); + + var dx = label.x - node.x, + dy = label.y - node.y, + labelRadian = Math.atan2(dy, dx), + labelAngle = calculateAngle(labelRadian); + + var startAngle = labelAngle - loopAngle / 2, + endAngle = labelAngle + loopAngle / 2; + + var arcFrom = calculateRadian(startAngle), + arcTo = calculateRadian(endAngle), + + x1 = Math.cos(arcFrom) * node.actualRadius(), + y1 = Math.sin(arcFrom) * node.actualRadius(), + + x2 = Math.cos(arcTo) * (node.actualRadius()), + y2 = Math.sin(arcTo) * (node.actualRadius()), + + fixPoint1 = { "x": node.x + x1, "y": node.y + y1 }, + fixPoint2 = { "x": node.x + x2, "y": node.y + y2 }; + + return [fixPoint1, link.label(), fixPoint2]; + }; + + /** + * @param angle + * @returns {number} the radian of the angle + */ + function calculateRadian( angle ){ + angle = angle % 360; + if ( angle < 0 ) { + angle = angle + 360; + } + return (Math.PI * angle) / 180; + } + + /** + * @param radian + * @returns {number} the angle of the radian + */ + function calculateAngle( radian ){ + return radian * (180 / Math.PI); + } + + /** + * Calculates the point where the link between the source and target node + * intersects the border of the target node. + * @param source the source node + * @param target the target node + * @param additionalDistance additional distance the + * @returns {{x: number, y: number}} + */ + math.calculateIntersection = function ( source, target, additionalDistance ){ + var dx = target.x - source.x, + dy = target.y - source.y, + length = Math.sqrt(dx * dx + dy * dy); + + if ( length === 0 ) { + return { x: source.x, y: source.y }; + } + + var innerDistance = target.distanceToBorder(dx, dy); + + var ratio = (length - (innerDistance + additionalDistance)) / length, + x = dx * ratio + source.x, + y = dy * ratio + source.y; + + return { x: x, y: y }; + }; + + /** + * Calculates the position between the two points. + * @param firstPoint + * @param secondPoint + * @returns {{x: number, y: number}} + */ + math.calculateCenter = function ( firstPoint, secondPoint ){ + return { + x: (firstPoint.x + secondPoint.x) / 2, + y: (firstPoint.y + secondPoint.y) / 2 + }; + }; + + + return function (){ + /* Use a function here to keep a consistent style like webvowl.path.to.module() + * despite having just a single math object. */ + return math; + }; + })(); + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 44 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.attributes(["datatype"]) + .styleClass("datatypeproperty") + .type("owl:DatatypeProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 45 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.attributes(["deprecated"]) + .styleClass("deprecatedproperty") + .type("owl:DeprecatedProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 46 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + var CenteringTextElement = __webpack_require__(14); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + var label = "Disjoint With"; + var shapeElement; + // Disallow overwriting the label + this.label = function ( p ){ + if ( !arguments.length ) return label; + return this; + }; + + this.linkType("dashed") + .styleClass("disjointwith") + .type("owl:disjointWith"); + + this.drawLabel = function ( labelContainer ){ + shapeElement = this.addRect(labelContainer); + + labelContainer.append("circle") + .classed("symbol", true) + .classed("fineline", true) + .classed("embedded", true) + .attr("cx", -12.5) + .attr("r", 10); + + labelContainer.append("circle") + .classed("symbol", true) + .classed("fineline", true) + .classed("embedded", true) + .attr("cx", 12.5) + .attr("r", 10); + + var textElement = new CenteringTextElement(labelContainer, this.backgroundColor()); + if ( !graph.options().compactNotation() ) { + textElement.addSubText("disjoint"); + } + textElement.translation(0, 20); + }; + this.getShapeElement = function (){ + return shapeElement; + }; + this.markerElement = function (){ + return undefined; + }; + + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 47 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.styleClass("equivalentproperty") + .type("owl:equivalentProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 48 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.attributes(["functional"]) + .styleClass("functionalproperty") + .type("owl:FunctionalProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 49 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.attributes(["inverse functional"]) + .styleClass("inversefunctionalproperty") + .type("owl:InverseFunctionalProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 50 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.attributes(["object"]) + .styleClass("objectproperty") + .type("owl:ObjectProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + + + +/***/ }), +/* 51 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + var superGenerateCardinalityText = this.generateCardinalityText; + + this.linkType("values-from") + .markerType("filled values-from") + .styleClass("somevaluesfromproperty") + .type("owl:someValuesFrom"); + + this.generateCardinalityText = function (){ + var cardinalityText = "E"; + + var superCardinalityText = superGenerateCardinalityText(); + if ( superCardinalityText ) { + cardinalityText += ", " + superCardinalityText; + } + + return cardinalityText; + }; + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + + + +/***/ }), +/* 52 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.attributes(["symmetric"]) + .styleClass("symmetricproperty") + .type("owl:SymmetricProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 53 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.attributes(["transitive"]) + .styleClass("transitiveproperty") + .type("owl:TransitiveProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 54 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.attributes(["rdf"]) + .styleClass("rdfproperty") + .type("rdf:Property"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 55 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + var that = this, + superDrawFunction = that.draw, + label = "Subclass of"; + + this.draw = function ( labelGroup ){ + that.labelVisible(!graph.options().compactNotation()); + return superDrawFunction(labelGroup); + }; + + // Disallow overwriting the label + this.label = function ( p ){ + if ( !arguments.length ) return label; + return this; + }; + + this.linkType("dotted") + .markerType("white") + .styleClass("subclass") + .type("rdfs:subClassOf"); + + that.baseIri("http://www.w3.org/2000/01/rdf-schema#"); + that.iri("http://www.w3.org/2000/01/rdf-schema#subClassOf"); + + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 56 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.labelVisible(false) + .linkType("dashed") + .markerType("white") + .styleClass("setoperatorproperty") + .type("setOperatorProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 57 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var _ = __webpack_require__(58); + var math = __webpack_require__(43)(); + var linkCreator = __webpack_require__(60)(); + var elementTools = __webpack_require__(63)(); + // add some maps for nodes and properties -- used for object generation + var nodePrototypeMap = __webpack_require__(5)(); + var propertyPrototypeMap = __webpack_require__(40)(); + + + module.exports = function ( graphContainerSelector ){ + var graph = {}, + CARDINALITY_HDISTANCE = 20, + CARDINALITY_VDISTANCE = 10, + curveFunction = d3.svg.line() + .x(function ( d ){ + return d.x; + }) + .y(function ( d ){ + return d.y; + }) + .interpolate("cardinal"), + options = __webpack_require__(64)(), + parser = __webpack_require__(65)(graph), + language = "default", + paused = false, + // Container for visual elements + graphContainer, + nodeContainer, + labelContainer, + cardinalityContainer, + linkContainer, + // Visual elements + nodeElements, + initialLoad = true, + updateRenderingDuringSimulation = false, + labelGroupElements, + linkGroups, + linkPathElements, + cardinalityElements, + // Internal data + classNodes, + labelNodes, + links, + properties, + unfilteredData, + // Graph behaviour + force, + dragBehaviour, + zoomFactor = 1.0, + centerGraphViewOnLoad = false, + transformAnimation = false, + graphTranslation = [0, 0], + graphUpdateRequired = false, + pulseNodeIds = [], + nodeArrayForPulse = [], + nodeMap = [], + locationId = 0, + defaultZoom = 1.0, + defaultTargetZoom = 0.8, + global_dof = -1, + touchDevice = false, + last_touch_time, + originalD3_dblClickFunction = null, + originalD3_touchZoomFunction = null, + + // editing elements + deleteGroupElement, + addDataPropertyGroupElement, + editContainer, + draggerLayer = null, + draggerObjectsArray = [], + delayedHider, + nodeFreezer, + hoveredNodeElement = null, + currentlySelectedNode = null, + hoveredPropertyElement = null, + draggingStarted = false, + frozenDomainForPropertyDragger, + frozenRangeForPropertyDragger, + + eP = 0, // id for new properties + eN = 0, // id for new Nodes + editMode = true, + debugContainer = d3.select("#FPS_Statistics"), + finishedLoadingSequence = false, + + ignoreOtherHoverEvents = false, + forceNotZooming = false, + now, then, // used for fps computation + showFPS = false, + seenEditorHint = false, + seenFilterWarning = false, + showFilterWarning = false, + + keepDetailsCollapsedOnLoading = true, + adjustingGraphSize = false, + showReloadButtonAfterLayoutOptimization = false, + zoom; + //var prefixModule=require("./prefixRepresentationModule")(graph); + var NodePrototypeMap = createLowerCasePrototypeMap(nodePrototypeMap); + var PropertyPrototypeMap = createLowerCasePrototypeMap(propertyPrototypeMap); + var classDragger = __webpack_require__(68)(graph); + var rangeDragger = __webpack_require__(69)(graph); + var domainDragger = __webpack_require__(70)(graph); + var shadowClone = __webpack_require__(71)(graph); + + graph.math = function (){ + return math; + }; + /** --------------------------------------------------------- **/ + /** -- getter and setter definitions -- **/ + /** --------------------------------------------------------- **/ + graph.isEditorMode = function (){ + return editMode; + }; + graph.getGlobalDOF = function (){ + return global_dof; + }; + graph.setGlobalDOF = function ( val ){ + global_dof = val; + }; + + graph.updateZoomSliderValueFromOutside = function (){ + graph.options().zoomSlider().updateZoomSliderValue(zoomFactor); + }; + + graph.setDefaultZoom = function ( val ){ + defaultZoom = val; + graph.reset(); + graph.options().zoomSlider().updateZoomSliderValue(defaultZoom); + }; + graph.setTargetZoom = function ( val ){ + defaultTargetZoom = val; + }; + graph.graphOptions = function (){ + return options; + }; + + graph.scaleFactor = function (){ + return zoomFactor; + }; + graph.translation = function (){ + return graphTranslation; + }; + + // Returns the visible nodes + graph.graphNodeElements = function (){ + return nodeElements; + }; + // Returns the visible Label Nodes + graph.graphLabelElements = function (){ + return labelNodes; + }; + + graph.graphLinkElements = function (){ + return links; + }; + + graph.setSliderZoom = function ( val ){ + + var cx = 0.5 * graph.options().width(); + var cy = 0.5 * graph.options().height(); + var cp = getWorldPosFromScreen(cx, cy, graphTranslation, zoomFactor); + var sP = [cp.x, cp.y, graph.options().height() / zoomFactor]; + var eP = [cp.x, cp.y, graph.options().height() / val]; + var pos_intp = d3.interpolateZoom(sP, eP); + + graphContainer.attr("transform", transform(sP, cx, cy)) + .transition() + .duration(1) + .attrTween("transform", function (){ + return function ( t ){ + return transform(pos_intp(t), cx, cy); + }; + }) + .each("end", function (){ + graphContainer.attr("transform", "translate(" + graphTranslation + ")scale(" + zoomFactor + ")"); + zoom.translate(graphTranslation); + zoom.scale(zoomFactor); + graph.options().zoomSlider().updateZoomSliderValue(zoomFactor); + }); + }; + + + graph.setZoom = function ( value ){ + zoom.scale(value); + }; + + graph.setTranslation = function ( translation ){ + zoom.translate([translation[0], translation[1]]); + }; + + graph.options = function (){ + return options; + }; + // search functionality + graph.getUpdateDictionary = function (){ + return parser.getDictionary(); + }; + + graph.language = function ( newLanguage ){ + if ( !arguments.length ) return language; + + // Just update if the language changes + if ( language !== newLanguage ) { + language = newLanguage || "default"; + redrawContent(); + recalculatePositions(); + graph.options().searchMenu().requestDictionaryUpdate(); + graph.resetSearchHighlight(); + } + return graph; + }; + + + /** --------------------------------------------------------- **/ + /** graph / rendering related functions **/ + /** --------------------------------------------------------- **/ + + // Initializes the graph. + function initializeGraph(){ + + options.graphContainerSelector(graphContainerSelector); + var moved = false; + force = d3.layout.force() + .on("tick", hiddenRecalculatePositions); + + dragBehaviour = d3.behavior.drag() + .origin(function ( d ){ + return d; + }) + .on("dragstart", function ( d ){ + d3.event.sourceEvent.stopPropagation(); // Prevent panning + graph.ignoreOtherHoverEvents(true); + if ( d.type && d.type() === "Class_dragger" ) { + classDragger.mouseButtonPressed = true; + clearTimeout(delayedHider); + classDragger.selectedViaTouch(true); + d.parentNode().locked(true); + draggingStarted = true; + } else if ( d.type && d.type() === "Range_dragger" ) { + graph.ignoreOtherHoverEvents(true); + clearTimeout(delayedHider); + frozenDomainForPropertyDragger = shadowClone.parentNode().domain(); + frozenRangeForPropertyDragger = shadowClone.parentNode().range(); + shadowClone.setInitialPosition(); + shadowClone.hideClone(false); + shadowClone.hideParentProperty(true); + shadowClone.updateElement(); + deleteGroupElement.classed("hidden", true); + addDataPropertyGroupElement.classed("hidden", true); + frozenDomainForPropertyDragger.frozen(true); + frozenDomainForPropertyDragger.locked(true); + frozenRangeForPropertyDragger.frozen(true); + frozenRangeForPropertyDragger.locked(true); + domainDragger.updateElement(); + domainDragger.mouseButtonPressed = true; + rangeDragger.updateElement(); + rangeDragger.mouseButtonPressed = true; + // shadowClone.setPosition(d.x, d.y); + + + } else if ( d.type && d.type() === "Domain_dragger" ) { + graph.ignoreOtherHoverEvents(true); + clearTimeout(delayedHider); + frozenDomainForPropertyDragger = shadowClone.parentNode().domain(); + frozenRangeForPropertyDragger = shadowClone.parentNode().range(); + shadowClone.setInitialPosition(); + shadowClone.hideClone(false); + shadowClone.hideParentProperty(true); + shadowClone.updateElement(); + deleteGroupElement.classed("hidden", true); + addDataPropertyGroupElement.classed("hidden", true); + + frozenDomainForPropertyDragger.frozen(true); + frozenDomainForPropertyDragger.locked(true); + frozenRangeForPropertyDragger.frozen(true); + frozenRangeForPropertyDragger.locked(true); + domainDragger.updateElement(); + domainDragger.mouseButtonPressed = true; + rangeDragger.updateElement(); + rangeDragger.mouseButtonPressed = true; + } + else { + d.locked(true); + moved = false; + } + }) + .on("drag", function ( d ){ + + if ( d.type && d.type() === "Class_dragger" ) { + clearTimeout(delayedHider); + classDragger.setPosition(d3.event.x, d3.event.y); + } else if ( d.type && d.type() === "Range_dragger" ) { + clearTimeout(delayedHider); + rangeDragger.setPosition(d3.event.x, d3.event.y); + shadowClone.setPosition(d3.event.x, d3.event.y); + domainDragger.updateElementViaRangeDragger(d3.event.x, d3.event.y); + } + else if ( d.type && d.type() === "Domain_dragger" ) { + clearTimeout(delayedHider); + domainDragger.setPosition(d3.event.x, d3.event.y); + shadowClone.setPositionDomain(d3.event.x, d3.event.y); + rangeDragger.updateElementViaDomainDragger(d3.event.x, d3.event.y); + } + + else { + d.px = d3.event.x; + d.py = d3.event.y; + force.resume(); + updateHaloRadius(); + moved = true; + if ( d.renderType && d.renderType() === "round" ) { + classDragger.setParentNode(d); + } + + } + }) + .on("dragend", function ( d ){ + graph.ignoreOtherHoverEvents(false); + if ( d.type && d.type() === "Class_dragger" ) { + var nX = classDragger.x; + var nY = classDragger.y; + clearTimeout(delayedHider); + classDragger.mouseButtonPressed = false; + classDragger.selectedViaTouch(false); + d.setParentNode(d.parentNode()); + + var draggerEndPos = [nX, nY]; + var targetNode = graph.getTargetNode(draggerEndPos); + if ( targetNode ) { + createNewObjectProperty(d.parentNode(), targetNode, draggerEndPos); + } + if ( touchDevice === false ) { + editElementHoverOut(); + } + draggingStarted = false; + } else if ( d.type && d.type() === "Range_dragger" ) { + graph.ignoreOtherHoverEvents(false); + frozenDomainForPropertyDragger.frozen(false); + frozenDomainForPropertyDragger.locked(false); + frozenRangeForPropertyDragger.frozen(false); + frozenRangeForPropertyDragger.locked(false); + rangeDragger.mouseButtonPressed = false; + domainDragger.mouseButtonPressed = false; + domainDragger.updateElement(); + rangeDragger.updateElement(); + shadowClone.hideClone(true); + var rX = rangeDragger.x; + var rY = rangeDragger.y; + var rangeDraggerEndPos = [rX, rY]; + var targetRangeNode = graph.getTargetNode(rangeDraggerEndPos); + if ( elementTools.isDatatype(targetRangeNode) === true ) { + targetRangeNode = null; + console.log("---------------TARGET NODE IS A DATATYPE/ LITERAL ------------"); + } + + if ( targetRangeNode === null ) { + d.reDrawEverthing(); + shadowClone.hideParentProperty(false); + } + else { + d.updateRange(targetRangeNode); + graph.update(); + shadowClone.hideParentProperty(false); + } + } else if ( d.type && d.type() === "Domain_dragger" ) { + graph.ignoreOtherHoverEvents(false); + frozenDomainForPropertyDragger.frozen(false); + frozenDomainForPropertyDragger.locked(false); + frozenRangeForPropertyDragger.frozen(false); + frozenRangeForPropertyDragger.locked(false); + rangeDragger.mouseButtonPressed = false; + domainDragger.mouseButtonPressed = false; + domainDragger.updateElement(); + rangeDragger.updateElement(); + shadowClone.hideClone(true); + + var dX = domainDragger.x; + var dY = domainDragger.y; + var domainDraggerEndPos = [dX, dY]; + var targetDomainNode = graph.getTargetNode(domainDraggerEndPos); + if ( elementTools.isDatatype(targetDomainNode) === true ) { + targetDomainNode = null; + console.log("---------------TARGET NODE IS A DATATYPE/ LITERAL ------------"); + } + shadowClone.hideClone(true); + if ( targetDomainNode === null ) { + d.reDrawEverthing(); + shadowClone.hideParentProperty(false); + } + else { + d.updateDomain(targetDomainNode); + graph.update(); + shadowClone.hideParentProperty(false); + } + } + + else { + d.locked(false); + var pnp = graph.options().pickAndPinModule(); + if ( pnp.enabled() === true && moved === true ) { + if ( d.id ) { // node + pnp.handle(d, true); + } + if ( d.property ) { + pnp.handle(d.property(), true); + } + } + } + }); + + // Apply the zooming factor. + zoom = d3.behavior.zoom() + .duration(150) + .scaleExtent([options.minMagnification(), options.maxMagnification()]) + .on("zoom", zoomed); + + draggerObjectsArray.push(classDragger); + draggerObjectsArray.push(rangeDragger); + draggerObjectsArray.push(domainDragger); + draggerObjectsArray.push(shadowClone); + force.stop(); + } + + graph.lazyRefresh = function (){ + redrawContent(); + recalculatePositions(); + }; + + graph.adjustingGraphSize = function ( val ){ + adjustingGraphSize = val; + }; + + graph.showReloadButtonAfterLayoutOptimization = function ( show ){ + showReloadButtonAfterLayoutOptimization = show; + }; + + + function hiddenRecalculatePositions(){ + finishedLoadingSequence = false; + if ( graph.options().loadingModule().successfullyLoadedOntology() === false ) { + force.stop(); + d3.select("#progressBarValue").node().innerHTML = ""; + graph.updateProgressBarMode(); + graph.options().loadingModule().showErrorDetailsMessage(hiddenRecalculatePositions); + if ( keepDetailsCollapsedOnLoading && adjustingGraphSize === false ) { + graph.options().loadingModule().collapseDetails("hiddenRecalculatePositions"); + } + return; + } + if ( updateRenderingDuringSimulation === false ) { + var value = 1.0 - 10 * force.alpha(); + var percent = parseInt(200 * value) + "%"; + graph.options().loadingModule().setPercentValue(percent); + d3.select("#progressBarValue").style("width", percent); + d3.select("#progressBarValue").node().innerHTML = percent; + + if ( value > 0.49 ) { + updateRenderingDuringSimulation = true; + // show graph container; + if ( graphContainer ) { + graphContainer.style("opacity", "1"); + percent = "100%"; + d3.select("#progressBarValue").style("width", percent); + d3.select("#progressBarValue").node().innerHTML = percent; + graph.options().ontologyMenu().append_message_toLastBulletPoint("done"); + d3.select("#reloadCachedOntology").classed("hidden", !showReloadButtonAfterLayoutOptimization); + if ( showFilterWarning === true && seenFilterWarning === false ) { + graph.options().warningModule().showFilterHint(); + seenFilterWarning = true; + } + } + + if ( initialLoad ) { + if ( graph.paused() === false ) + force.resume(); // resume force + initialLoad = false; + + } + + + finishedLoadingSequence = true; + if ( showFPS === true ) { + force.on("tick", recalculatePositionsWithFPS); + recalculatePositionsWithFPS(); + } + else { + force.on("tick", recalculatePositions); + recalculatePositions(); + } + + if ( centerGraphViewOnLoad === true && force.nodes().length > 0 ) { + if ( force.nodes().length < 10 ) graph.forceRelocationEvent(true); // uses dynamic zoomer; + else graph.forceRelocationEvent(); + centerGraphViewOnLoad = false; + // console.log("--------------------------------------") + } + + + graph.showEditorHintIfNeeded(); + + if ( graph.options().loadingModule().missingImportsWarning() === false ) { + graph.options().loadingModule().hideLoadingIndicator(); + graph.options().ontologyMenu().append_bulletPoint("Successfully loaded ontology"); + graph.options().loadingModule().setSuccessful(); + } else { + graph.options().loadingModule().showWarningDetailsMessage(); + graph.options().ontologyMenu().append_bulletPoint("Loaded ontology with warnings"); + } + } + } + } + + graph.showEditorHintIfNeeded = function (){ + if ( seenEditorHint === false && editMode === true ) { + seenEditorHint = true; + graph.options().warningModule().showEditorHint(); + } + }; + + graph.setForceTickFunctionWithFPS = function (){ + showFPS = true; + if ( force && finishedLoadingSequence === true ) { + force.on("tick", recalculatePositionsWithFPS); + } + + }; + graph.setDefaultForceTickFunction = function (){ + showFPS = false; + if ( force && finishedLoadingSequence === true ) { + force.on("tick", recalculatePositions); + } + }; + function recalculatePositionsWithFPS(){ + // compute the fps + + recalculatePositions(); + now = Date.now(); + var diff = now - then; + var fps = (1000 / (diff)).toFixed(2); + + debugContainer.node().innerHTML = "FPS: " + fps + "
    " + "Nodes: " + force.nodes().length + "
    " + "Links: " + force.links().length; + then = Date.now(); + + } + + function recalculatePositions(){ + // Set node positions + + + // add switch for edit mode to make this faster; + if ( !editMode ) { + nodeElements.attr("transform", function ( node ){ + return "translate(" + node.x + "," + node.y + ")"; + }); + + // Set label group positions + labelGroupElements.attr("transform", function ( label ){ + var position; + + // force centered positions on single-layered links + var link = label.link(); + if ( link.layers().length === 1 && !link.loops() ) { + var linkDomainIntersection = math.calculateIntersection(link.range(), link.domain(), 0); + var linkRangeIntersection = math.calculateIntersection(link.domain(), link.range(), 0); + position = math.calculateCenter(linkDomainIntersection, linkRangeIntersection); + label.x = position.x; + label.y = position.y; + } + return "translate(" + label.x + "," + label.y + ")"; + }); + // Set link paths and calculate additional information + linkPathElements.attr("d", function ( l ){ + if ( l.isLoop() ) { + return math.calculateLoopPath(l); + } + var curvePoint = l.label(); + var pathStart = math.calculateIntersection(curvePoint, l.domain(), 1); + var pathEnd = math.calculateIntersection(curvePoint, l.range(), 1); + + return curveFunction([pathStart, curvePoint, pathEnd]); + }); + + // Set cardinality positions + cardinalityElements.attr("transform", function ( property ){ + + var label = property.link().label(), + pos = math.calculateIntersection(label, property.range(), CARDINALITY_HDISTANCE), + normalV = math.calculateNormalVector(label, property.range(), CARDINALITY_VDISTANCE); + + return "translate(" + (pos.x + normalV.x) + "," + (pos.y + normalV.y) + ")"; + }); + + + updateHaloRadius(); + return; + } + + // TODO: this is Editor redraw function // we need to make this faster!! + + + nodeElements.attr("transform", function ( node ){ + return "translate(" + node.x + "," + node.y + ")"; + }); + + // Set label group positions + labelGroupElements.attr("transform", function ( label ){ + var position; + + // force centered positions on single-layered links + var link = label.link(); + if ( link.layers().length === 1 && !link.loops() ) { + var linkDomainIntersection = math.calculateIntersection(link.range(), link.domain(), 0); + var linkRangeIntersection = math.calculateIntersection(link.domain(), link.range(), 0); + position = math.calculateCenter(linkDomainIntersection, linkRangeIntersection); + label.x = position.x; + label.y = position.y; + label.linkRangeIntersection = linkRangeIntersection; + label.linkDomainIntersection = linkDomainIntersection; + if ( link.property().focused() === true || hoveredPropertyElement !== undefined ) { + rangeDragger.updateElement(); + domainDragger.updateElement(); + // shadowClone.setPosition(link.property().range().x,link.property().range().y); + // shadowClone.setPositionDomain(link.property().domain().x,link.property().domain().y); + } + } else { + label.linkDomainIntersection = math.calculateIntersection(link.label(), link.domain(), 0); + label.linkRangeIntersection = math.calculateIntersection(link.label(), link.range(), 0); + if ( link.property().focused() === true || hoveredPropertyElement !== undefined ) { + rangeDragger.updateElement(); + domainDragger.updateElement(); + // shadowClone.setPosition(link.property().range().x,link.property().range().y); + // shadowClone.setPositionDomain(link.property().domain().x,link.property().domain().y); + } + + } + return "translate(" + label.x + "," + label.y + ")"; + }); + // Set link paths and calculate additional information + linkPathElements.attr("d", function ( l ){ + if ( l.isLoop() ) { + + var ptrAr = math.getLoopPoints(l); + l.label().linkRangeIntersection = ptrAr[1]; + l.label().linkDomainIntersection = ptrAr[0]; + + if ( l.property().focused() === true || hoveredPropertyElement !== undefined ) { + rangeDragger.updateElement(); + domainDragger.updateElement(); + } + return math.calculateLoopPath(l); + } + var curvePoint = l.label(); + var pathStart = math.calculateIntersection(curvePoint, l.domain(), 1); + var pathEnd = math.calculateIntersection(curvePoint, l.range(), 1); + l.linkRangeIntersection = pathStart; + l.linkDomainIntersection = pathEnd; + if ( l.property().focused() === true || hoveredPropertyElement !== undefined ) { + domainDragger.updateElement(); + rangeDragger.updateElement(); + // shadowClone.setPosition(l.property().range().x,l.property().range().y); + // shadowClone.setPositionDomain(l.property().domain().x,l.property().domain().y); + } + return curveFunction([pathStart, curvePoint, pathEnd]); + }); + + // Set cardinality positions + cardinalityElements.attr("transform", function ( property ){ + + var label = property.link().label(), + pos = math.calculateIntersection(label, property.range(), CARDINALITY_HDISTANCE), + normalV = math.calculateNormalVector(label, property.range(), CARDINALITY_VDISTANCE); + + return "translate(" + (pos.x + normalV.x) + "," + (pos.y + normalV.y) + ")"; + }); + + if ( hoveredNodeElement ) { + setDeleteHoverElementPosition(hoveredNodeElement); + setAddDataPropertyHoverElementPosition(hoveredNodeElement); + if ( draggingStarted === false ) { + classDragger.setParentNode(hoveredNodeElement); + } + } + if ( hoveredPropertyElement ) { + setDeleteHoverElementPositionProperty(hoveredPropertyElement); + } + + updateHaloRadius(); + } + + graph.updatePropertyDraggerElements = function ( property ){ + if ( property.type() !== "owl:DatatypeProperty" ) { + + shadowClone.setParentProperty(property); + rangeDragger.setParentProperty(property); + rangeDragger.hideDragger(false); + rangeDragger.addMouseEvents(); + domainDragger.setParentProperty(property); + domainDragger.hideDragger(false); + domainDragger.addMouseEvents(); + + } + else { + rangeDragger.hideDragger(true); + domainDragger.hideDragger(true); + shadowClone.hideClone(true); + } + }; + + function addClickEvents(){ + function executeModules( selectedElement ){ + options.selectionModules().forEach(function ( module ){ + module.handle(selectedElement); + }); + } + + nodeElements.on("click", function ( clickedNode ){ + + // manaual double clicker // helper for iphone 6 etc... + if ( touchDevice === true && doubletap() === true ) { + d3.event.stopPropagation(); + if ( editMode === true ) { + clickedNode.raiseDoubleClickEdit(defaultIriValue(clickedNode)); + } + } + else { + executeModules(clickedNode); + } + }); + + nodeElements.on("dblclick", function ( clickedNode ){ + + d3.event.stopPropagation(); + if ( editMode === true ) { + clickedNode.raiseDoubleClickEdit(defaultIriValue(clickedNode)); + } + }); + + labelGroupElements.selectAll(".label").on("click", function ( clickedProperty ){ + executeModules(clickedProperty); + + // this is for enviroments that do not define dblClick function; + if ( touchDevice === true && doubletap() === true ) { + d3.event.stopPropagation(); + if ( editMode === true ) { + clickedProperty.raiseDoubleClickEdit(defaultIriValue(clickedProperty)); + } + } + + // currently removed the selection of an element to invoke the dragger + // if (editMode===true && clickedProperty.editingTextElement!==true) { + // return; + // // We say that Datatype properties are not allowed to have domain range draggers + // if (clickedProperty.focused() && clickedProperty.type() !== "owl:DatatypeProperty") { + // shadowClone.setParentProperty(clickedProperty); + // rangeDragger.setParentProperty(clickedProperty); + // rangeDragger.hideDragger(false); + // rangeDragger.addMouseEvents(); + // domainDragger.setParentProperty(clickedProperty); + // domainDragger.hideDragger(false); + // domainDragger.addMouseEvents(); + // + // if (clickedProperty.domain()===clickedProperty.range()){ + // clickedProperty.labelObject().increasedLoopAngle=true; + // recalculatePositions(); + // + // } + // + // } else if (clickedProperty.focused() && clickedProperty.type() === "owl:DatatypeProperty") { + // shadowClone.setParentProperty(clickedProperty); + // rangeDragger.setParentProperty(clickedProperty); + // rangeDragger.hideDragger(true); + // rangeDragger.addMouseEvents(); + // domainDragger.setParentProperty(clickedProperty); + // domainDragger.hideDragger(false); + // domainDragger.addMouseEvents(); + // + // } + // else { + // rangeDragger.hideDragger(true); + // domainDragger.hideDragger(true); + // if (clickedProperty.domain()===clickedProperty.range()){ + // clickedProperty.labelObject().increasedLoopAngle=false; + // recalculatePositions(); + // + // } + // } + // } + }); + labelGroupElements.selectAll(".label").on("dblclick", function ( clickedProperty ){ + d3.event.stopPropagation(); + if ( editMode === true ) { + clickedProperty.raiseDoubleClickEdit(defaultIriValue(clickedProperty)); + } + + }); + } + + function defaultIriValue( element ){ + // get the iri of that element; + if ( graph.options().getGeneralMetaObject().iri ) { + var str2Compare = graph.options().getGeneralMetaObject().iri + element.id(); + return element.iri() === str2Compare; + } + return false; + } + + /** Adjusts the containers current scale and position. */ + function zoomed(){ + if ( forceNotZooming === true ) { + zoom.translate(graphTranslation); + zoom.scale(zoomFactor); + return; + } + + + var zoomEventByMWheel = false; + if ( d3.event.sourceEvent ) { + if ( d3.event.sourceEvent.deltaY ) zoomEventByMWheel = true; + } + if ( zoomEventByMWheel === false ) { + if ( transformAnimation === true ) { + return; + } + zoomFactor = d3.event.scale; + graphTranslation = d3.event.translate; + graphContainer.attr("transform", "translate(" + graphTranslation + ")scale(" + zoomFactor + ")"); + updateHaloRadius(); + graph.options().zoomSlider().updateZoomSliderValue(zoomFactor); + return; + } + /** animate the transition **/ + zoomFactor = d3.event.scale; + graphTranslation = d3.event.translate; + graphContainer.transition() + .tween("attr.translate", function (){ + return function ( t ){ + transformAnimation = true; + var tr = d3.transform(graphContainer.attr("transform")); + graphTranslation[0] = tr.translate[0]; + graphTranslation[1] = tr.translate[1]; + zoomFactor = tr.scale[0]; + updateHaloRadius(); + graph.options().zoomSlider().updateZoomSliderValue(zoomFactor); + }; + }) + .each("end", function (){ + transformAnimation = false; + }) + .attr("transform", "translate(" + graphTranslation + ")scale(" + zoomFactor + ")") + .ease('linear') + .duration(250); + }// end of zoomed function + + function redrawGraph(){ + remove(); + + graphContainer = d3.selectAll(options.graphContainerSelector()) + .append("svg") + .classed("vowlGraph", true) + .attr("width", options.width()) + .attr("height", options.height()) + .call(zoom) + .append("g"); + // add touch and double click functions + + var svgGraph = d3.selectAll(".vowlGraph"); + originalD3_dblClickFunction = svgGraph.on("dblclick.zoom"); + originalD3_touchZoomFunction = svgGraph.on("touchstart"); + svgGraph.on("touchstart", touchzoomed); + if ( editMode === true ) { + svgGraph.on("dblclick.zoom", graph.modified_dblClickFunction); + } + else { + svgGraph.on("dblclick.zoom", originalD3_dblClickFunction); + } + + } + + function generateEditElements(){ + addDataPropertyGroupElement = editContainer.append('g') + .classed("hidden-in-export", true) + .classed("hidden", true) + .classed("addDataPropertyElement", true) + .attr("transform", "translate(" + 0 + "," + 0 + ")"); + + + addDataPropertyGroupElement.append("circle") + // .classed("deleteElement", true) + .attr("r", 12) + .attr("cx", 0) + .attr("cy", 0) + .append("title").text("Add Datatype Property"); + + addDataPropertyGroupElement.append("line") + // .classed("deleteElementIcon ",true) + .attr("x1", -8) + .attr("y1", 0) + .attr("x2", 8) + .attr("y2", 0) + .append("title").text("Add Datatype Property"); + + addDataPropertyGroupElement.append("line") + // .classed("deleteElementIcon",true) + .attr("x1", 0) + .attr("y1", -8) + .attr("x2", 0) + .attr("y2", 8) + .append("title").text("Add Datatype Property"); + + if ( graph.options().useAccuracyHelper() ) { + addDataPropertyGroupElement.append("circle") + .attr("r", 15) + .attr("cx", -7) + .attr("cy", 7) + .classed("superHiddenElement", true) + .classed("superOpacityElement", !graph.options().showDraggerObject()); + } + + + deleteGroupElement = editContainer.append('g') + .classed("hidden-in-export", true) + .classed("hidden", true) + .classed("deleteParentElement", true) + .attr("transform", "translate(" + 0 + "," + 0 + ")"); + + deleteGroupElement.append("circle") + .attr("r", 12) + .attr("cx", 0) + .attr("cy", 0) + .append("title").text("Delete This Node"); + + var crossLen = 5; + deleteGroupElement.append("line") + .attr("x1", -crossLen) + .attr("y1", -crossLen) + .attr("x2", crossLen) + .attr("y2", crossLen) + .append("title").text("Delete This Node"); + + deleteGroupElement.append("line") + .attr("x1", crossLen) + .attr("y1", -crossLen) + .attr("x2", -crossLen) + .attr("y2", crossLen) + .append("title").text("Delete This Node"); + + if ( graph.options().useAccuracyHelper() ) { + deleteGroupElement.append("circle") + .attr("r", 15) + .attr("cx", 7) + .attr("cy", -7) + .classed("superHiddenElement", true) + .classed("superOpacityElement", !graph.options().showDraggerObject()); + } + + + } + + graph.getUnfilteredData = function (){ + return unfilteredData; + }; + + graph.getClassDataForTtlExport = function (){ + var allNodes = unfilteredData.nodes; + var nodeData = []; + for ( var i = 0; i < allNodes.length; i++ ) { + if ( allNodes[i].type() !== "rdfs:Literal" && + allNodes[i].type() !== "rdfs:Datatype" && + allNodes[i].type() !== "owl:Thing" ) { + nodeData.push(allNodes[i]); + } + } + return nodeData; + }; + + graph.getPropertyDataForTtlExport = function (){ + var propertyData = []; + var allProperties = unfilteredData.properties; + for ( var i = 0; i < allProperties.length; i++ ) { + // currently using only the object properties + if ( allProperties[i].type() === "owl:ObjectProperty" || + allProperties[i].type() === "owl:DatatypeProperty" || + allProperties[i].type() === "owl:ObjectProperty" + + ) { + propertyData.push(allProperties[i]); + } else { + if ( allProperties[i].type() === "rdfs:subClassOf" ) { + allProperties[i].baseIri("http://www.w3.org/2000/01/rdf-schema#"); + allProperties[i].iri("http://www.w3.org/2000/01/rdf-schema#subClassOf"); + } + if ( allProperties[i].type() === "owl:disjointWith" ) { + allProperties[i].baseIri("http://www.w3.org/2002/07/owl#"); + allProperties[i].iri("http://www.w3.org/2002/07/owl#disjointWith"); + } + } + } + return propertyData; + }; + + graph.getAxiomsForTtlExport = function (){ + var axioms = []; + var allProperties = unfilteredData.properties; + for ( var i = 0; i < allProperties.length; i++ ) { + // currently using only the object properties + if ( allProperties[i].type() === "owl:ObjectProperty" || + allProperties[i].type() === "owl:DatatypeProperty" || + allProperties[i].type() === "owl:ObjectProperty" || + allProperties[i].type() === "rdfs:subClassOf" + ) { + } else { + } + } + return axioms; + }; + + + graph.getUnfilteredData = function (){ + return unfilteredData; + }; + + graph.getClassDataForTtlExport = function (){ + var allNodes = unfilteredData.nodes; + var nodeData = []; + for ( var i = 0; i < allNodes.length; i++ ) { + if ( allNodes[i].type() !== "rdfs:Literal" && + allNodes[i].type() !== "rdfs:Datatype" && + allNodes[i].type() !== "owl:Thing" ) { + nodeData.push(allNodes[i]); + } + } + return nodeData; + }; + + + function redrawContent(){ + var markerContainer; + + if ( !graphContainer ) { + return; + } + + // Empty the graph container + graphContainer.selectAll("*").remove(); + + // Last container -> elements of this container overlap others + linkContainer = graphContainer.append("g").classed("linkContainer", true); + cardinalityContainer = graphContainer.append("g").classed("cardinalityContainer", true); + labelContainer = graphContainer.append("g").classed("labelContainer", true); + nodeContainer = graphContainer.append("g").classed("nodeContainer", true); + + // adding editing Elements + var draggerPathLayer = graphContainer.append("g").classed("linkContainer", true); + draggerLayer = graphContainer.append("g").classed("editContainer", true); + editContainer = graphContainer.append("g").classed("editContainer", true); + + draggerPathLayer.classed("hidden-in-export", true); + editContainer.classed("hidden-in-export", true); + draggerLayer.classed("hidden-in-export", true); + + // Add an extra container for all markers + markerContainer = linkContainer.append("defs"); + var drElement = draggerLayer.selectAll(".node") + .data(draggerObjectsArray).enter() + .append("g") + .classed("node", true) + .classed("hidden-in-export", true) + .attr("id", function ( d ){ + return d.id(); + }) + .call(dragBehaviour); + drElement.each(function ( node ){ + node.svgRoot(d3.select(this)); + node.svgPathLayer(draggerPathLayer); + if ( node.type() === "shadowClone" ) { + node.drawClone(); + node.hideClone(true); + } else { + node.drawNode(); + node.hideDragger(true); + } + }); + generateEditElements(); + + + // Add an extra container for all markers + markerContainer = linkContainer.append("defs"); + + // Draw nodes + + if ( classNodes === undefined ) classNodes = []; + + nodeElements = nodeContainer.selectAll(".node") + .data(classNodes).enter() + .append("g") + .classed("node", true) + .attr("id", function ( d ){ + return d.id(); + }) + .call(dragBehaviour); + nodeElements.each(function ( node ){ + node.draw(d3.select(this)); + }); + + + if ( labelNodes === undefined ) labelNodes = []; + + // Draw label groups (property + inverse) + labelGroupElements = labelContainer.selectAll(".labelGroup") + .data(labelNodes).enter() + .append("g") + .classed("labelGroup", true) + .call(dragBehaviour); + + labelGroupElements.each(function ( label ){ + var success = label.draw(d3.select(this)); + label.property().labelObject(label); + // Remove empty groups without a label. + if ( !success ) { + d3.select(this).remove(); + } + }); + // Place subclass label groups on the bottom of all labels + labelGroupElements.each(function ( label ){ + // the label might be hidden e.g. in compact notation + if ( !this.parentNode ) { + return; + } + + if ( elementTools.isRdfsSubClassOf(label.property()) ) { + var parentNode = this.parentNode; + parentNode.insertBefore(this, parentNode.firstChild); + } + }); + if ( properties === undefined ) properties = []; + // Draw cardinality elements + cardinalityElements = cardinalityContainer.selectAll(".cardinality") + .data(properties).enter() + .append("g") + .classed("cardinality", true); + + cardinalityElements.each(function ( property ){ + var success = property.drawCardinality(d3.select(this)); + + // Remove empty groups without a label. + if ( !success ) { + d3.select(this).remove(); + } + }); + // Draw links + if ( links === undefined ) links = []; + linkGroups = linkContainer.selectAll(".link") + .data(links).enter() + .append("g") + .classed("link", true); + + linkGroups.each(function ( link ){ + link.draw(d3.select(this), markerContainer); + }); + linkPathElements = linkGroups.selectAll("path"); + // Select the path for direct access to receive a better performance + addClickEvents(); + } + + function remove(){ + if ( graphContainer ) { + // Select the parent element because the graph container is a group (e.g. for zooming) + d3.select(graphContainer.node().parentNode).remove(); + } + } + + initializeGraph(); // << call the initialization function + + graph.updateCanvasContainerSize = function (){ + if ( graphContainer ) { + var svgElement = d3.selectAll(".vowlGraph"); + svgElement.attr("width", options.width()); + svgElement.attr("height", options.height()); + graphContainer.attr("transform", "translate(" + graphTranslation + ")scale(" + zoomFactor + ")"); + } + }; + + // Loads all settings, removes the old graph (if it exists) and draws a new one. + graph.start = function (){ + force.stop(); + loadGraphData(true); + redrawGraph(); + graph.update(true); + + if ( graph.options().loadingModule().successfullyLoadedOntology() === false ) { + graph.options().loadingModule().setErrorMode(); + } + + }; + + // Updates only the style of the graph. + graph.updateStyle = function (){ + refreshGraphStyle(); + if ( graph.options().loadingModule().successfullyLoadedOntology() === false ) { + force.stop(); + } else { + force.start(); + } + }; + + graph.reload = function (){ + loadGraphData(); + graph.update(); + + }; + + graph.load = function (){ + force.stop(); + loadGraphData(); + refreshGraphData(); + for ( var i = 0; i < labelNodes.length; i++ ) { + var label = labelNodes[i]; + if ( label.property().x && label.property().y ) { + label.x = label.property().x; + label.y = label.property().y; + // also set the prev position of the label + label.px = label.x; + label.py = label.y; + } + } + graph.update(); + }; + + graph.fastUpdate = function (){ + // fast update function for editor calls; + // -- experimental ; + quick_refreshGraphData(); + updateNodeMap(); + force.start(); + redrawContent(); + graph.updatePulseIds(nodeArrayForPulse); + refreshGraphStyle(); + updateHaloStyles(); + + }; + + graph.getNodeMapForSearch = function (){ + return nodeMap; + }; + function updateNodeMap(){ + nodeMap = []; + var node; + for ( var j = 0; j < force.nodes().length; j++ ) { + node = force.nodes()[j]; + if ( node.id ) { + nodeMap[node.id()] = j; + // check for equivalents + var eqs = node.equivalents(); + if ( eqs.length > 0 ) { + for ( var e = 0; e < eqs.length; e++ ) { + var eqObject = eqs[e]; + nodeMap[eqObject.id()] = j; + } + } + } + if ( node.property ) { + nodeMap[node.property().id()] = j; + var inverse = node.inverse(); + if ( inverse ) { + nodeMap[inverse.id()] = j; + } + } + } + } + + function updateHaloStyles(){ + var haloElement; + var halo; + var node; + for ( var j = 0; j < force.nodes().length; j++ ) { + node = force.nodes()[j]; + if ( node.id ) { + haloElement = node.getHalos(); + if ( haloElement ) { + halo = haloElement.selectAll(".searchResultA"); + halo.classed("searchResultA", false); + halo.classed("searchResultB", true); + } + } + + if ( node.property ) { + haloElement = node.property().getHalos(); + if ( haloElement ) { + halo = haloElement.selectAll(".searchResultA"); + halo.classed("searchResultA", false); + halo.classed("searchResultB", true); + } + } + } + } + + // Updates the graphs displayed data and style. + graph.update = function ( init ){ + var validOntology = graph.options().loadingModule().successfullyLoadedOntology(); + if ( validOntology === false && (init && init === true) ) { + graph.options().loadingModule().collapseDetails(); + return; + } + if ( validOntology === false ) { + return; + } + + keepDetailsCollapsedOnLoading = false; + refreshGraphData(); + // update node map + updateNodeMap(); + + force.start(); + redrawContent(); + graph.updatePulseIds(nodeArrayForPulse); + refreshGraphStyle(); + updateHaloStyles(); + }; + + graph.paused = function ( p ){ + if ( !arguments.length ) return paused; + paused = p; + graph.updateStyle(); + return graph; + }; + // resetting the graph + graph.reset = function (){ + // window size + var w = 0.5 * graph.options().width(); + var h = 0.5 * graph.options().height(); + // computing initial translation for the graph due tue the dynamic default zoom level + var tx = w - defaultZoom * w; + var ty = h - defaultZoom * h; + zoom.translate([tx, ty]) + .scale(defaultZoom); + }; + + + graph.zoomOut = function (){ + + var minMag = options.minMagnification(), + maxMag = options.maxMagnification(); + var stepSize = (maxMag - minMag) / 10; + var val = zoomFactor - stepSize; + if ( val < minMag ) val = minMag; + + var cx = 0.5 * graph.options().width(); + var cy = 0.5 * graph.options().height(); + var cp = getWorldPosFromScreen(cx, cy, graphTranslation, zoomFactor); + var sP = [cp.x, cp.y, graph.options().height() / zoomFactor]; + var eP = [cp.x, cp.y, graph.options().height() / val]; + var pos_intp = d3.interpolateZoom(sP, eP); + + graphContainer.attr("transform", transform(sP, cx, cy)) + .transition() + .duration(250) + .attrTween("transform", function (){ + return function ( t ){ + return transform(pos_intp(t), cx, cy); + }; + }) + .each("end", function (){ + graphContainer.attr("transform", "translate(" + graphTranslation + ")scale(" + zoomFactor + ")"); + zoom.translate(graphTranslation); + zoom.scale(zoomFactor); + updateHaloRadius(); + options.zoomSlider().updateZoomSliderValue(zoomFactor); + }); + + }; + + graph.zoomIn = function (){ + var minMag = options.minMagnification(), + maxMag = options.maxMagnification(); + var stepSize = (maxMag - minMag) / 10; + var val = zoomFactor + stepSize; + if ( val > maxMag ) val = maxMag; + var cx = 0.5 * graph.options().width(); + var cy = 0.5 * graph.options().height(); + var cp = getWorldPosFromScreen(cx, cy, graphTranslation, zoomFactor); + var sP = [cp.x, cp.y, graph.options().height() / zoomFactor]; + var eP = [cp.x, cp.y, graph.options().height() / val]; + var pos_intp = d3.interpolateZoom(sP, eP); + + graphContainer.attr("transform", transform(sP, cx, cy)) + .transition() + .duration(250) + .attrTween("transform", function (){ + return function ( t ){ + return transform(pos_intp(t), cx, cy); + }; + }) + .each("end", function (){ + graphContainer.attr("transform", "translate(" + graphTranslation + ")scale(" + zoomFactor + ")"); + zoom.translate(graphTranslation); + zoom.scale(zoomFactor); + updateHaloRadius(); + options.zoomSlider().updateZoomSliderValue(zoomFactor); + }); + + + }; + + /** --------------------------------------------------------- **/ + /** -- data related handling -- **/ + /** --------------------------------------------------------- **/ + + var cachedJsonOBJ = null; + graph.clearAllGraphData = function (){ + if ( graph.graphNodeElements() && graph.graphNodeElements().length > 0 ) { + cachedJsonOBJ = graph.options().exportMenu().createJSON_exportObject(); + } else { + cachedJsonOBJ = null; + } + force.stop(); + if ( unfilteredData ) { + unfilteredData.nodes = []; + unfilteredData.properties = []; + } + }; + graph.getCachedJsonObj = function (){ + return cachedJsonOBJ; + }; + + // removes data when data could not be loaded + graph.clearGraphData = function (){ + force.stop(); + var sidebar = graph.options().sidebar(); + if ( sidebar ) + sidebar.clearOntologyInformation(); + if ( graphContainer ) + redrawGraph(); + }; + + function generateDictionary( data ){ + var i; + var originalDictionary = []; + var nodes = data.nodes; + for ( i = 0; i < nodes.length; i++ ) { + // check if node has a label + if ( nodes[i].labelForCurrentLanguage() !== undefined ) + originalDictionary.push(nodes[i]); + } + var props = data.properties; + for ( i = 0; i < props.length; i++ ) { + if ( props[i].labelForCurrentLanguage() !== undefined ) + originalDictionary.push(props[i]); + } + parser.setDictionary(originalDictionary); + + var literFilter = graph.options().literalFilter(); + var idsToRemove = literFilter.removedNodes(); + var originalDict = parser.getDictionary(); + var newDict = []; + + // go through the dictionary and remove the ids; + for ( i = 0; i < originalDict.length; i++ ) { + var dictElement = originalDict[i]; + var dictElementId; + if ( dictElement.property ) + dictElementId = dictElement.property().id(); + else + dictElementId = dictElement.id(); + // compare against the removed ids; + var addToDictionary = true; + for ( var j = 0; j < idsToRemove.length; j++ ) { + var currentId = idsToRemove[j]; + if ( currentId === dictElementId ) { + addToDictionary = false; + } + } + if ( addToDictionary === true ) { + newDict.push(dictElement); + } + } + // tell the parser that the dictionary is updated + parser.setDictionary(newDict); + + } + + graph.updateProgressBarMode = function (){ + var loadingModule = graph.options().loadingModule(); + + var state = loadingModule.getProgressBarMode(); + switch ( state ) { + case 0: + loadingModule.setErrorMode(); + break; + case 1: + loadingModule.setBusyMode(); + break; + case 2: + loadingModule.setPercentMode(); + break; + default: + loadingModule.setPercentMode(); + } + }; + + graph.setFilterWarning = function ( val ){ + showFilterWarning = val; + }; + function loadGraphData( init ){ + // reset the locate button and previously selected locations and other variables + + var loadingModule = graph.options().loadingModule(); + force.stop(); + + force.nodes([]); + force.links([]); + nodeArrayForPulse = []; + pulseNodeIds = []; + locationId = 0; + d3.select("#locateSearchResult").classed("highlighted", false); + d3.select("#locateSearchResult").node().title = "Nothing to locate"; + graph.clearGraphData(); + + if ( init ) { + force.stop(); + return; + } + + showFilterWarning = false; + parser.parse(options.data()); + unfilteredData = { + nodes: parser.nodes(), + properties: parser.properties() + }; + // fixing class and property id counter for the editor + eN = unfilteredData.nodes.length + 1; + eP = unfilteredData.properties.length + 1; + + initialLoad = true; + graph.options().warningModule().closeFilterHint(); + + // loading handler + updateRenderingDuringSimulation = true; + var validOntology = graph.options().loadingModule().successfullyLoadedOntology(); + if ( graphContainer && validOntology === true ) { + + updateRenderingDuringSimulation = false; + graph.options().ontologyMenu().append_bulletPoint("Generating visualization ... "); + loadingModule.setPercentMode(); + + if ( unfilteredData.nodes.length > 0 ) { + graphContainer.style("opacity", "0"); + force.on("tick", hiddenRecalculatePositions); + } else { + graphContainer.style("opacity", "1"); + if ( showFPS === true ) { + force.on("tick", recalculatePositionsWithFPS); + } + else { + force.on("tick", recalculatePositions); + } + } + + force.start(); + } else { + force.stop(); + graph.options().ontologyMenu().append_bulletPoint("Failed to load ontology"); + loadingModule.setErrorMode(); + } + // update prefixList( + // update general MetaOBJECT + graph.options().clearMetaObject(); + graph.options().clearGeneralMetaObject(); + graph.options().editSidebar().clearMetaObjectValue(); + if ( options.data() !== undefined ) { + var header = options.data().header; + if ( header ) { + if ( header.iri ) { + graph.options().addOrUpdateGeneralObjectEntry("iri", header.iri); + } + if ( header.title ) { + graph.options().addOrUpdateGeneralObjectEntry("title", header.title); + } + if ( header.author ) { + graph.options().addOrUpdateGeneralObjectEntry("author", header.author); + } + if ( header.version ) { + graph.options().addOrUpdateGeneralObjectEntry("version", header.version); + } + if ( header.description ) { + graph.options().addOrUpdateGeneralObjectEntry("description", header.description); + } + if ( header.prefixList ) { + var pL = header.prefixList; + for ( var pr in pL ) { + if ( pL.hasOwnProperty(pr) ) { + var val = pL[pr]; + graph.options().addPrefix(pr, val); + } + } + } + // get other metadata; + if ( header.other ) { + var otherObjects = header.other; + for ( var name in otherObjects ) { + if ( otherObjects.hasOwnProperty(name) ) { + var otherObj = otherObjects[name]; + if ( otherObj.hasOwnProperty("identifier") && otherObj.hasOwnProperty("value") ) { + graph.options().addOrUpdateMetaObjectEntry(otherObj.identfier, otherObj.value); + } + } + } + } + } + } + // update more meta OBJECT + // Initialize filters with data to replicate consecutive filtering + var initializationData = _.clone(unfilteredData); + options.filterModules().forEach(function ( module ){ + initializationData = filterFunction(module, initializationData, true); + }); + // generate dictionary here ; + generateDictionary(unfilteredData); + + parser.parseSettings(); + graphUpdateRequired = parser.settingsImported(); + centerGraphViewOnLoad = true; + if ( parser.settingsImportGraphZoomAndTranslation() === true ) { + centerGraphViewOnLoad = false; + } + graph.options().searchMenu().requestDictionaryUpdate(); + graph.options().editSidebar().updateGeneralOntologyInfo(); + graph.options().editSidebar().updatePrefixUi(); + graph.options().editSidebar().updateElementWidth(); + } + + graph.handleOnLoadingError = function (){ + force.stop(); + graph.clearGraphData(); + graph.options().ontologyMenu().append_bulletPoint("Failed to load ontology"); + d3.select("#progressBarValue").node().innherHTML = ""; + d3.select("#progressBarValue").classed("busyProgressBar", false); + graph.options().loadingModule().setErrorMode(); + graph.options().loadingModule().showErrorDetailsMessage(); + }; + + function quick_refreshGraphData(){ + links = linkCreator.createLinks(properties); + labelNodes = links.map(function ( link ){ + return link.label(); + }); + + storeLinksOnNodes(classNodes, links); + setForceLayoutData(classNodes, labelNodes, links); + } + + //Applies the data of the graph options object and parses it. The graph is not redrawn. + function refreshGraphData(){ + var shouldExecuteEmptyFilter = options.literalFilter().enabled(); + graph.executeEmptyLiteralFilter(); + options.literalFilter().enabled(shouldExecuteEmptyFilter); + + var preprocessedData = _.clone(unfilteredData); + + // Filter the data + options.filterModules().forEach(function ( module ){ + preprocessedData = filterFunction(module, preprocessedData); + }); + options.focuserModule().handle(undefined, true); + classNodes = preprocessedData.nodes; + properties = preprocessedData.properties; + links = linkCreator.createLinks(properties); + labelNodes = links.map(function ( link ){ + return link.label(); + }); + storeLinksOnNodes(classNodes, links); + setForceLayoutData(classNodes, labelNodes, links); + // for (var i = 0; i < classNodes.length; i++) { + // if (classNodes[i].setRectangularRepresentation) + // classNodes[i].setRectangularRepresentation(graph.options().rectangularRepresentation()); + // } + } + + function filterFunction( module, data, initializing ){ + links = linkCreator.createLinks(data.properties); + storeLinksOnNodes(data.nodes, links); + + if ( initializing ) { + if ( module.initialize ) { + module.initialize(data.nodes, data.properties); + } + } + module.filter(data.nodes, data.properties); + return { + nodes: module.filteredNodes(), + properties: module.filteredProperties() + }; + } + + + /** --------------------------------------------------------- **/ + /** -- force-layout related functions -- **/ + /** --------------------------------------------------------- **/ + function storeLinksOnNodes( nodes, links ){ + for ( var i = 0, nodesLength = nodes.length; i < nodesLength; i++ ) { + var node = nodes[i], + connectedLinks = []; + + // look for properties where this node is the domain or range + for ( var j = 0, linksLength = links.length; j < linksLength; j++ ) { + var link = links[j]; + + if ( link.domain() === node || link.range() === node ) { + connectedLinks.push(link); + } + } + node.links(connectedLinks); + } + } + + function setForceLayoutData( classNodes, labelNodes, links ){ + var d3Links = []; + links.forEach(function ( link ){ + d3Links = d3Links.concat(link.linkParts()); + }); + + var d3Nodes = [].concat(classNodes).concat(labelNodes); + setPositionOfOldLabelsOnNewLabels(force.nodes(), labelNodes); + + force.nodes(d3Nodes) + .links(d3Links); + } + + // The label nodes are positioned randomly, because they are created from scratch if the data changes and lose + // their position information. With this hack the position of old labels is copied to the new labels. + function setPositionOfOldLabelsOnNewLabels( oldLabelNodes, labelNodes ){ + labelNodes.forEach(function ( labelNode ){ + for ( var i = 0; i < oldLabelNodes.length; i++ ) { + var oldNode = oldLabelNodes[i]; + if ( oldNode.equals(labelNode) ) { + labelNode.x = oldNode.x; + labelNode.y = oldNode.y; + labelNode.px = oldNode.px; + labelNode.py = oldNode.py; + break; + } + } + }); + } + + // Applies all options that don't change the graph data. + function refreshGraphStyle(){ + zoom = zoom.scaleExtent([options.minMagnification(), options.maxMagnification()]); + if ( graphContainer ) { + zoom.event(graphContainer); + } + + force.charge(function ( element ){ + var charge = options.charge(); + if ( elementTools.isLabel(element) ) { + charge *= 0.8; + } + return charge; + }) + .size([options.width(), options.height()]) + .linkDistance(calculateLinkPartDistance) + .gravity(options.gravity()) + .linkStrength(options.linkStrength()); // Flexibility of links + + force.nodes().forEach(function ( n ){ + n.frozen(paused); + }); + } + + function calculateLinkPartDistance( linkPart ){ + var link = linkPart.link(); + + if ( link.isLoop() ) { + return options.loopDistance(); + } + + // divide by 2 to receive the length for a single link part + var linkPartDistance = getVisibleLinkDistance(link) / 2; + linkPartDistance += linkPart.domain().actualRadius(); + linkPartDistance += linkPart.range().actualRadius(); + return linkPartDistance; + } + + function getVisibleLinkDistance( link ){ + if ( elementTools.isDatatype(link.domain()) || elementTools.isDatatype(link.range()) ) { + return options.datatypeDistance(); + } else { + return options.classDistance(); + } + } + + /** --------------------------------------------------------- **/ + /** -- animation functions for the nodes -- **/ + /** --------------------------------------------------------- **/ + + graph.animateDynamicLabelWidth = function (){ + var wantedWidth = options.dynamicLabelWidth(); + var i; + for ( i = 0; i < classNodes.length; i++ ) { + var nodeElement = classNodes[i]; + if ( elementTools.isDatatype(nodeElement) ) { + nodeElement.animateDynamicLabelWidth(wantedWidth); + } + } + for ( i = 0; i < properties.length; i++ ) { + properties[i].animateDynamicLabelWidth(wantedWidth); + } + }; + + + /** --------------------------------------------------------- **/ + /** -- halo and localization functions -- **/ + /** --------------------------------------------------------- **/ + function updateHaloRadius(){ + if ( pulseNodeIds && pulseNodeIds.length > 0 ) { + var forceNodes = force.nodes(); + for ( var i = 0; i < pulseNodeIds.length; i++ ) { + var node = forceNodes[pulseNodeIds[i]]; + if ( node ) { + if ( node.property ) { + // match search strings with property label + if ( node.property().inverse ) { + var searchString = graph.options().searchMenu().getSearchString().toLowerCase(); + var name = node.property().labelForCurrentLanguage().toLowerCase(); + if ( name === searchString ) computeDistanceToCenter(node); + else { + node.property().removeHalo(); + if ( node.property().inverse() ) { + if ( !node.property().inverse().getHalos() ) + node.property().inverse().drawHalo(); + computeDistanceToCenter(node, true); + } + if ( node.property().equivalents() ) { + var eq = node.property().equivalents(); + for ( var e = 0; e < eq.length; e++ ) { + if ( !eq[e].getHalos() ) + eq[e].drawHalo(); + } + if ( !node.property().getHalos() ) + node.property().drawHalo(); + computeDistanceToCenter(node, false); + + } + } + } + } + computeDistanceToCenter(node); + } + } + } + } + + function getScreenCoords( x, y, translate, scale ){ + var xn = translate[0] + x * scale; + var yn = translate[1] + y * scale; + return { x: xn, y: yn }; + } + + function getClickedScreenCoords( x, y, translate, scale ){ + var xn = (x - translate[0]) / scale; + var yn = (y - translate[1]) / scale; + return { x: xn, y: yn }; + } + + + function computeDistanceToCenter( node, inverse ){ + var container = node; + var w = graph.options().width(); + var h = graph.options().height(); + var posXY = getScreenCoords(node.x, node.y, graphTranslation, zoomFactor); + + var highlightOfInv = false; + + if ( inverse && inverse === true ) { + highlightOfInv = true; + posXY = getScreenCoords(node.x, node.y + 20, graphTranslation, zoomFactor); + } + var x = posXY.x; + var y = posXY.y; + var nodeIsRect = false; + var halo; + var roundHalo; + var rectHalo; + var borderPoint_x = 0; + var borderPoint_y = 0; + var defaultRadius; + var offset = 15; + var radius; + + if ( node.property && highlightOfInv === true ) { + if ( node.property().inverse() ) { + rectHalo = node.property().inverse().getHalos().select("rect"); + + } else { + if ( node.property().getHalos() ) + rectHalo = node.property().getHalos().select("rect"); + else { + node.property().drawHalo(); + rectHalo = node.property().getHalos().select("rect"); + } + } + rectHalo.classed("hidden", true); + if ( node.property().inverse() ) { + if ( node.property().inverse().getHalos() ) { + roundHalo = node.property().inverse().getHalos().select("circle"); + } + } else { + roundHalo = node.property().getHalos().select("circle"); + } + if ( roundHalo.node() === null ) { + radius = node.property().inverse().width() + 15; + + roundHalo = node.property().inverse().getHalos().append("circle") + .classed("searchResultB", true) + .classed("searchResultA", false) + .attr("r", radius + 15); + + } + halo = roundHalo; // swap the halo to be round + nodeIsRect = true; + container = node.property().inverse(); + } + + if ( node.id ) { + if ( !node.getHalos() ) return; // something went wrong before + halo = node.getHalos().select("rect"); + if ( halo.node() === null ) { + // this is a round node + nodeIsRect = false; + roundHalo = node.getHalos().select("circle"); + defaultRadius = node.actualRadius(); + roundHalo.attr("r", defaultRadius + offset); + halo = roundHalo; + } else { // this is a rect node + nodeIsRect = true; + rectHalo = node.getHalos().select("rect"); + rectHalo.classed("hidden", true); + roundHalo = node.getHalos().select("circle"); + if ( roundHalo.node() === null ) { + radius = node.width(); + roundHalo = node.getHalos().append("circle") + .classed("searchResultB", true) + .classed("searchResultA", false) + .attr("r", radius + offset); + } + halo = roundHalo; + } + } + if ( node.property && !inverse ) { + if ( !node.property().getHalos() ) return; // something went wrong before + rectHalo = node.property().getHalos().select("rect"); + rectHalo.classed("hidden", true); + + roundHalo = node.property().getHalos().select("circle"); + if ( roundHalo.node() === null ) { + radius = node.property().width(); + + roundHalo = node.property().getHalos().append("circle") + .classed("searchResultB", true) + .classed("searchResultA", false) + .attr("r", radius + 15); + + } + halo = roundHalo; // swap the halo to be round + nodeIsRect = true; + container = node.property(); + } + + if ( x < 0 || x > w || y < 0 || y > h ) { + // node outside viewport; + // check for quadrant and get the correct boarder point (intersection with viewport) + if ( x < 0 && y < 0 ) { + borderPoint_x = 0; + borderPoint_y = 0; + } else if ( x > 0 && x < w && y < 0 ) { + borderPoint_x = x; + borderPoint_y = 0; + } else if ( x > w && y < 0 ) { + borderPoint_x = w; + borderPoint_y = 0; + } else if ( x > w && y > 0 && y < h ) { + borderPoint_x = w; + borderPoint_y = y; + } else if ( x > w && y > h ) { + borderPoint_x = w; + borderPoint_y = h; + } else if ( x > 0 && x < w && y > h ) { + borderPoint_x = x; + borderPoint_y = h; + } else if ( x < 0 && y > h ) { + borderPoint_x = 0; + borderPoint_y = h; + } else if ( x < 0 && y > 0 && y < h ) { + borderPoint_x = 0; + borderPoint_y = y; + } + // kill all pulses of nodes that are outside the viewport + container.getHalos().select("rect").classed("searchResultA", false); + container.getHalos().select("circle").classed("searchResultA", false); + container.getHalos().select("rect").classed("searchResultB", true); + container.getHalos().select("circle").classed("searchResultB", true); + halo.classed("hidden", false); + // compute in pixel coordinates length of difference vector + var borderRadius_x = borderPoint_x - x; + var borderRadius_y = borderPoint_y - y; + + var len = borderRadius_x * borderRadius_x + borderRadius_y * borderRadius_y; + len = Math.sqrt(len); + + var normedX = borderRadius_x / len; + var normedY = borderRadius_y / len; + + len = len + 20; // add 20 px; + + // re-normalized vector + var newVectorX = normedX * len + x; + var newVectorY = normedY * len + y; + // compute world coordinates of this point + var wX = (newVectorX - graphTranslation[0]) / zoomFactor; + var wY = (newVectorY - graphTranslation[1]) / zoomFactor; + + // compute distance in world coordinates + var dx = wX - node.x; + var dy = wY - node.y; + if ( highlightOfInv === true ) + dy = wY - node.y - 20; + + if ( highlightOfInv === false && node.property && node.property().inverse() ) + dy = wY - node.y + 20; + + var newRadius = Math.sqrt(dx * dx + dy * dy); + halo = container.getHalos().select("circle"); + // sanity checks and setting new halo radius + if ( !nodeIsRect ) { + defaultRadius = node.actualRadius() + offset; + if ( newRadius < defaultRadius ) { + newRadius = defaultRadius; + } + halo.attr("r", newRadius); + } else { + defaultRadius = 0.5 * container.width(); + if ( newRadius < defaultRadius ) + newRadius = defaultRadius; + halo.attr("r", newRadius); + } + } else { // node is in viewport , render original; + // reset the halo to original radius + defaultRadius = node.actualRadius() + 15; + if ( !nodeIsRect ) { + halo.attr("r", defaultRadius); + } else { // this is rectangular node render as such + halo = container.getHalos().select("rect"); + halo.classed("hidden", false); + //halo.classed("searchResultB", true); + //halo.classed("searchResultA", false); + var aCircHalo = container.getHalos().select("circle"); + aCircHalo.classed("hidden", true); + + container.getHalos().select("rect").classed("hidden", false); + container.getHalos().select("circle").classed("hidden", true); + } + } + } + + function transform( p, cx, cy ){ + // one iteration step for the locate target animation + zoomFactor = graph.options().height() / p[2]; + graphTranslation = [(cx - p[0] * zoomFactor), (cy - p[1] * zoomFactor)]; + updateHaloRadius(); + // update the values in case the user wants to break the animation + zoom.translate(graphTranslation); + zoom.scale(zoomFactor); + graph.options().zoomSlider().updateZoomSliderValue(zoomFactor); + return "translate(" + graphTranslation[0] + "," + graphTranslation[1] + ")scale(" + zoomFactor + ")"; + } + + graph.zoomToElementInGraph = function ( element ){ + targetLocationZoom(element); + }; + graph.updateHaloRadius = function ( element ){ + computeDistanceToCenter(element); + }; + + function targetLocationZoom( target ){ + // store the original information + var cx = 0.5 * graph.options().width(); + var cy = 0.5 * graph.options().height(); + var cp = getWorldPosFromScreen(cx, cy, graphTranslation, zoomFactor); + var sP = [cp.x, cp.y, graph.options().height() / zoomFactor]; + + var zoomLevel = Math.max(defaultZoom + 0.5 * defaultZoom, defaultTargetZoom); + var eP = [target.x, target.y, graph.options().height() / zoomLevel]; + var pos_intp = d3.interpolateZoom(sP, eP); + + var lenAnimation = pos_intp.duration; + if ( lenAnimation > 2500 ) { + lenAnimation = 2500; + } + + graphContainer.attr("transform", transform(sP, cx, cy)) + .transition() + .duration(lenAnimation) + .attrTween("transform", function (){ + return function ( t ){ + return transform(pos_intp(t), cx, cy); + }; + }) + .each("end", function (){ + graphContainer.attr("transform", "translate(" + graphTranslation + ")scale(" + zoomFactor + ")"); + zoom.translate(graphTranslation); + zoom.scale(zoomFactor); + updateHaloRadius(); + }); + } + + function getWorldPosFromScreen( x, y, translate, scale ){ + var temp = scale[0], xn, yn; + if ( temp ) { + xn = (x - translate[0]) / temp; + yn = (y - translate[1]) / temp; + } else { + xn = (x - translate[0]) / scale; + yn = (y - translate[1]) / scale; + } + return { x: xn, y: yn }; + } + + graph.locateSearchResult = function (){ + if ( pulseNodeIds && pulseNodeIds.length > 0 ) { + // move the center of the viewport to this location + if ( transformAnimation === true ) return; // << prevents incrementing the location id if we are in an animation + var node = force.nodes()[pulseNodeIds[locationId]]; + locationId++; + locationId = locationId % pulseNodeIds.length; + if ( node.id ) node.foreground(); + if ( node.property ) node.property().foreground(); + + targetLocationZoom(node); + } + }; + + graph.resetSearchHighlight = function (){ + // get all nodes (handle also already filtered nodes ) + pulseNodeIds = []; + nodeArrayForPulse = []; + // clear from stored nodes + var nodes = unfilteredData.nodes; + var props = unfilteredData.properties; + var j; + for ( j = 0; j < nodes.length; j++ ) { + var node = nodes[j]; + if ( node.removeHalo ) + node.removeHalo(); + } + for ( j = 0; j < props.length; j++ ) { + var prop = props[j]; + if ( prop.removeHalo ) + prop.removeHalo(); + } + }; + + graph.updatePulseIds = function ( nodeIdArray ){ + pulseNodeIds = []; + for ( var i = 0; i < nodeIdArray.length; i++ ) { + var selectedId = nodeIdArray[i]; + var forceId = nodeMap[selectedId]; + if ( forceId !== undefined ) { + var le_node = force.nodes()[forceId]; + if ( le_node.id ) { + if ( pulseNodeIds.indexOf(forceId) === -1 ) { + pulseNodeIds.push(forceId); + } + } + if ( le_node.property ) { + if ( pulseNodeIds.indexOf(forceId) === -1 ) { + pulseNodeIds.push(forceId); + } + } + } + } + locationId = 0; + if ( pulseNodeIds.length > 0 ) { + d3.select("#locateSearchResult").classed("highlighted", true); + d3.select("#locateSearchResult").node().title = "Locate search term"; + } + else { + d3.select("#locateSearchResult").classed("highlighted", false); + d3.select("#locateSearchResult").node().title = "Nothing to locate"; + } + + }; + + graph.highLightNodes = function ( nodeIdArray ){ + if ( nodeIdArray.length === 0 ) { + return; // nothing to highlight + } + pulseNodeIds = []; + nodeArrayForPulse = nodeIdArray; + var missedIds = []; + + // identify the force id to highlight + for ( var i = 0; i < nodeIdArray.length; i++ ) { + var selectedId = nodeIdArray[i]; + var forceId = nodeMap[selectedId]; + if ( forceId !== undefined ) { + var le_node = force.nodes()[forceId]; + if ( le_node.id ) { + if ( pulseNodeIds.indexOf(forceId) === -1 ) { + pulseNodeIds.push(forceId); + le_node.foreground(); + le_node.drawHalo(); + } + } + if ( le_node.property ) { + if ( pulseNodeIds.indexOf(forceId) === -1 ) { + pulseNodeIds.push(forceId); + le_node.property().foreground(); + le_node.property().drawHalo(); + } + } + } + else { + missedIds.push(selectedId); + } + } + + if ( missedIds.length === nodeIdArray.length ) { + + } + // store the highlight on the missed nodes; + var s_nodes = unfilteredData.nodes; + var s_props = unfilteredData.properties; + for ( i = 0; i < missedIds.length; i++ ) { + var missedId = missedIds[i]; + // search for this in the nodes; + for ( var n = 0; n < s_nodes.length; n++ ) { + var nodeId = s_nodes[n].id(); + if ( nodeId === missedId ) { + s_nodes[n].drawHalo(); + } + } + for ( var p = 0; p < s_props.length; p++ ) { + var propId = s_props[p].id(); + if ( propId === missedId ) { + s_props[p].drawHalo(); + } + } + } + if ( missedIds.length === nodeIdArray.length ) { + d3.select("#locateSearchResult").classed("highlighted", false); + } + else { + d3.select("#locateSearchResult").classed("highlighted", true); + } + locationId = 0; + updateHaloRadius(); + }; + + graph.hideHalos = function (){ + var haloElements = d3.selectAll(".searchResultA,.searchResultB"); + haloElements.classed("hidden", true); + return haloElements; + }; + + function nodeInViewport( node, property ){ + + var w = graph.options().width(); + var h = graph.options().height(); + var posXY = getScreenCoords(node.x, node.y, graphTranslation, zoomFactor); + var x = posXY.x; + var y = posXY.y; + + var retVal = !(x < 0 || x > w || y < 0 || y > h); + return retVal; + } + + graph.getBoundingBoxForTex = function (){ + var halos = graph.hideHalos(); + var bbox = graphContainer.node().getBoundingClientRect(); + halos.classed("hidden", false); + var w = graph.options().width(); + var h = graph.options().height(); + + // get the graph coordinates + var topLeft = getWorldPosFromScreen(0, 0, graphTranslation, zoomFactor); + var botRight = getWorldPosFromScreen(w, h, graphTranslation, zoomFactor); + + + var t_topLeft = getWorldPosFromScreen(bbox.left, bbox.top, graphTranslation, zoomFactor); + var t_botRight = getWorldPosFromScreen(bbox.right, bbox.bottom, graphTranslation, zoomFactor); + + // tighten up the bounding box; + + var tX = Math.max(t_topLeft.x, topLeft.x); + var tY = Math.max(t_topLeft.y, topLeft.y); + + var bX = Math.min(t_botRight.x, botRight.x); + var bY = Math.min(t_botRight.y, botRight.y); + + + // tighten further; + var allForceNodes = force.nodes(); + var numNodes = allForceNodes.length; + var visibleNodes = []; + var bbx; + + + var contentBBox = { tx: 1000000000000, ty: 1000000000000, bx: -1000000000000, by: -1000000000000 }; + + for ( var i = 0; i < numNodes; i++ ) { + var node = allForceNodes[i]; + if ( node ) { + if ( node.property ) { + if ( nodeInViewport(node, true) ) { + if ( node.property().labelElement() === undefined ) continue; + bbx = node.property().labelElement().node().getBoundingClientRect(); + if ( bbx ) { + contentBBox.tx = Math.min(contentBBox.tx, bbx.left); + contentBBox.bx = Math.max(contentBBox.bx, bbx.right); + contentBBox.ty = Math.min(contentBBox.ty, bbx.top); + contentBBox.by = Math.max(contentBBox.by, bbx.bottom); + } + } + } else { + if ( nodeInViewport(node, false) ) { + bbx = node.nodeElement().node().getBoundingClientRect(); + if ( bbx ) { + contentBBox.tx = Math.min(contentBBox.tx, bbx.left); + contentBBox.bx = Math.max(contentBBox.bx, bbx.right); + contentBBox.ty = Math.min(contentBBox.ty, bbx.top); + contentBBox.by = Math.max(contentBBox.by, bbx.bottom); + } + } + } + } + } + + var tt_topLeft = getWorldPosFromScreen(contentBBox.tx, contentBBox.ty, graphTranslation, zoomFactor); + var tt_botRight = getWorldPosFromScreen(contentBBox.bx, contentBBox.by, graphTranslation, zoomFactor); + + tX = Math.max(tX, tt_topLeft.x); + tY = Math.max(tY, tt_topLeft.y); + + bX = Math.min(bX, tt_botRight.x); + bY = Math.min(bY, tt_botRight.y); + // y axis flip for tex + return [tX, -tY, bX, -bY]; + + }; + + var updateTargetElement = function (){ + var bbox = graphContainer.node().getBoundingClientRect(); + + + // get the graph coordinates + var bboxOffset = 50; // default radius of a node; + var topLeft = getWorldPosFromScreen(bbox.left, bbox.top, graphTranslation, zoomFactor); + var botRight = getWorldPosFromScreen(bbox.right, bbox.bottom, graphTranslation, zoomFactor); + + var w = graph.options().width(); + if ( graph.options().leftSidebar().isSidebarVisible() === true ) + w -= 200; + var h = graph.options().height(); + topLeft.x += bboxOffset; + topLeft.y -= bboxOffset; + botRight.x -= bboxOffset; + botRight.y += bboxOffset; + + var g_w = botRight.x - topLeft.x; + var g_h = botRight.y - topLeft.y; + + // endpoint position calculations + var posX = 0.5 * (topLeft.x + botRight.x); + var posY = 0.5 * (topLeft.y + botRight.y); + var cx = 0.5 * w, + cy = 0.5 * h; + + if ( graph.options().leftSidebar().isSidebarVisible() === true ) + cx += 200; + var cp = getWorldPosFromScreen(cx, cy, graphTranslation, zoomFactor); + + // zoom factor calculations and fail safes; + var newZoomFactor = 1.0; // fail save if graph and window are squares + //get the smaller one + var a = w / g_w; + var b = h / g_h; + if ( a < b ) newZoomFactor = a; + else newZoomFactor = b; + + + // fail saves + if ( newZoomFactor > zoom.scaleExtent()[1] ) { + newZoomFactor = zoom.scaleExtent()[1]; + } + if ( newZoomFactor < zoom.scaleExtent()[0] ) { + newZoomFactor = zoom.scaleExtent()[0]; + } + + // apply Zooming + var sP = [cp.x, cp.y, h / zoomFactor]; + var eP = [posX, posY, h / newZoomFactor]; + + + var pos_intp = d3.interpolateZoom(sP, eP); + return [pos_intp, cx, cy]; + + }; + + graph.forceRelocationEvent = function ( dynamic ){ + // we need to kill the halo to determine the bounding box; + var halos = graph.hideHalos(); + var bbox = graphContainer.node().getBoundingClientRect(); + halos.classed("hidden", false); + + // get the graph coordinates + var bboxOffset = 50; // default radius of a node; + var topLeft = getWorldPosFromScreen(bbox.left, bbox.top, graphTranslation, zoomFactor); + var botRight = getWorldPosFromScreen(bbox.right, bbox.bottom, graphTranslation, zoomFactor); + + var w = graph.options().width(); + if ( graph.options().leftSidebar().isSidebarVisible() === true ) + w -= 200; + var h = graph.options().height(); + topLeft.x += bboxOffset; + topLeft.y -= bboxOffset; + botRight.x -= bboxOffset; + botRight.y += bboxOffset; + + var g_w = botRight.x - topLeft.x; + var g_h = botRight.y - topLeft.y; + + // endpoint position calculations + var posX = 0.5 * (topLeft.x + botRight.x); + var posY = 0.5 * (topLeft.y + botRight.y); + var cx = 0.5 * w, + cy = 0.5 * h; + + if ( graph.options().leftSidebar().isSidebarVisible() === true ) + cx += 200; + var cp = getWorldPosFromScreen(cx, cy, graphTranslation, zoomFactor); + + // zoom factor calculations and fail safes; + var newZoomFactor = 1.0; // fail save if graph and window are squares + //get the smaller one + var a = w / g_w; + var b = h / g_h; + if ( a < b ) newZoomFactor = a; + else newZoomFactor = b; + + + // fail saves + if ( newZoomFactor > zoom.scaleExtent()[1] ) { + newZoomFactor = zoom.scaleExtent()[1]; + } + if ( newZoomFactor < zoom.scaleExtent()[0] ) { + newZoomFactor = zoom.scaleExtent()[0]; + } + + // apply Zooming + var sP = [cp.x, cp.y, h / zoomFactor]; + var eP = [posX, posY, h / newZoomFactor]; + + + var pos_intp = d3.interpolateZoom(sP, eP); + var lenAnimation = pos_intp.duration; + if ( lenAnimation > 2500 ) { + lenAnimation = 2500; + } + graphContainer.attr("transform", transform(sP, cx, cy)) + .transition() + .duration(lenAnimation) + .attrTween("transform", function (){ + return function ( t ){ + if ( dynamic ) { + var param = updateTargetElement(); + var nV = param[0](t); + return transform(nV, cx, cy); + } + return transform(pos_intp(t), cx, cy); + }; + }) + .each("end", function (){ + if ( dynamic ) { + return; + } + + graphContainer.attr("transform", "translate(" + graphTranslation + ")scale(" + zoomFactor + ")"); + zoom.translate(graphTranslation); + zoom.scale(zoomFactor); + graph.options().zoomSlider().updateZoomSliderValue(zoomFactor); + + + }); + }; + + + graph.isADraggerActive = function (){ + if ( classDragger.mouseButtonPressed === true || + domainDragger.mouseButtonPressed === true || + rangeDragger.mouseButtonPressed === true ) { + return true; + } + return false; + }; + + /** --------------------------------------------------------- **/ + /** -- VOWL EDITOR create/ edit /delete functions -- **/ + /** --------------------------------------------------------- **/ + + graph.changeNodeType = function ( element ){ + + var typeString = d3.select("#typeEditor").node().value; + + if ( graph.classesSanityCheck(element, typeString) === false ) { + // call reselection to restore previous type selection + graph.options().editSidebar().updateSelectionInformation(element); + return; + } + + var prototype = NodePrototypeMap.get(typeString.toLowerCase()); + var aNode = new prototype(graph); + + aNode.x = element.x; + aNode.y = element.y; + aNode.px = element.x; + aNode.py = element.y; + aNode.id(element.id()); + aNode.copyInformation(element); + + if ( typeString === "owl:Thing" ) { + aNode.label("Thing"); + } + else if ( elementTools.isDatatype(element) === false ) { + if ( element.backupLabel() !== undefined ) { + aNode.label(element.backupLabel()); + } else if ( aNode.backupLabel() !== undefined ) { + aNode.label(aNode.backupLabel()); + } else { + aNode.label("NewClass"); + } + } + + if ( typeString === "rdfs:Datatype" ) { + if ( aNode.dType() === "undefined" ) + aNode.label("undefined"); + else { + var identifier = aNode.dType().split(":")[1]; + aNode.label(identifier); + } + } + var i; + // updates the property domain and range + for ( i = 0; i < unfilteredData.properties.length; i++ ) { + if ( unfilteredData.properties[i].domain() === element ) { + // unfilteredData.properties[i].toString(); + unfilteredData.properties[i].domain(aNode); + } + if ( unfilteredData.properties[i].range() === element ) { + unfilteredData.properties[i].range(aNode); + // unfilteredData.properties[i].toString(); + } + } + + // update for fastUpdate: + for ( i = 0; i < properties.length; i++ ) { + if ( properties[i].domain() === element ) { + // unfilteredData.properties[i].toString(); + properties[i].domain(aNode); + } + if ( properties[i].range() === element ) { + properties[i].range(aNode); + // unfilteredData.properties[i].toString(); + } + } + + var remId = unfilteredData.nodes.indexOf(element); + if ( remId !== -1 ) + unfilteredData.nodes.splice(remId, 1); + remId = classNodes.indexOf(element); + if ( remId !== -1 ) + classNodes.splice(remId, 1); + // very important thing for selection!; + addNewNodeElement(aNode); + // handle focuser! + options.focuserModule().handle(aNode); + generateDictionary(unfilteredData); + graph.getUpdateDictionary(); + element = null; + }; + + + graph.changePropertyType = function ( element ){ + var typeString = d3.select("#typeEditor").node().value; + + // create warning + if ( graph.sanityCheckProperty(element.domain(), element.range(), typeString) === false ) return false; + + var propPrototype = PropertyPrototypeMap.get(typeString.toLowerCase()); + var aProp = new propPrototype(graph); + aProp.copyInformation(element); + aProp.id(element.id()); + + element.domain().removePropertyElement(element); + element.range().removePropertyElement(element); + aProp.domain(element.domain()); + aProp.range(element.range()); + + if ( element.backupLabel() !== undefined ) { + aProp.label(element.backupLabel()); + } else { + aProp.label("newObjectProperty"); + } + + if ( aProp.type() === "rdfs:subClassOf" ) { + aProp.iri("http://www.w3.org/2000/01/rdf-schema#subClassOf"); + } else { + if ( element.iri() === "http://www.w3.org/2000/01/rdf-schema#subClassOf" ) + aProp.iri(graph.options().getGeneralMetaObjectProperty('iri') + aProp.id()); + + } + + + if ( graph.propertyCheckExistenceChecker(aProp, element.domain(), element.range()) === false ) { + graph.options().editSidebar().updateSelectionInformation(element); + return; + } + // // TODO: change its base IRI to proper value + // var ontoIRI="http://someTest.de"; + // aProp.baseIri(ontoIRI); + // aProp.iri(aProp.baseIri()+aProp.id()); + + + // add this to the data; + unfilteredData.properties.push(aProp); + if ( properties.indexOf(aProp) === -1 ) + properties.push(aProp); + var remId = unfilteredData.properties.indexOf(element); + if ( remId !== -1 ) + unfilteredData.properties.splice(remId, 1); + if ( properties.indexOf(aProp) === -1 ) + properties.push(aProp); + remId = properties.indexOf(element); + if ( remId !== -1 ) + properties.splice(remId, 1); + graph.fastUpdate(); + aProp.domain().addProperty(aProp); + aProp.range().addProperty(aProp); + if ( element.labelObject() && aProp.labelObject() ) { + aProp.labelObject().x = element.labelObject().x; + aProp.labelObject().px = element.labelObject().px; + aProp.labelObject().y = element.labelObject().y; + aProp.labelObject().py = element.labelObject().py; + } + + options.focuserModule().handle(aProp); + element = null; + }; + + graph.removeEditElements = function (){ + // just added to be called form outside + removeEditElements(); + }; + + function removeEditElements(){ + rangeDragger.hideDragger(true); + domainDragger.hideDragger(true); + shadowClone.hideClone(true); + + classDragger.hideDragger(true); + if ( addDataPropertyGroupElement ) + addDataPropertyGroupElement.classed("hidden", true); + if ( deleteGroupElement ) + deleteGroupElement.classed("hidden", true); + + + if ( hoveredNodeElement ) { + if ( hoveredNodeElement.pinned() === false ) { + hoveredNodeElement.locked(graph.paused()); + hoveredNodeElement.frozen(graph.paused()); + } + } + if ( hoveredPropertyElement ) { + if ( hoveredPropertyElement.pinned() === false ) { + hoveredPropertyElement.locked(graph.paused()); + hoveredPropertyElement.frozen(graph.paused()); + } + } + + + } + + graph.editorMode = function ( val ){ + var create_entry = d3.select("#empty"); + var create_container = d3.select("#emptyContainer"); + + var modeOfOpString = d3.select("#modeOfOperationString").node(); + if ( !arguments.length ) { + create_entry.node().checked = editMode; + if ( editMode === false ) { + create_container.node().title = "Enable editing in modes menu to create a new ontology"; + create_entry.node().title = "Enable editing in modes menu to create a new ontology"; + create_entry.style("pointer-events", "none"); + } else { + create_container.node().title = "Creates a new empty ontology"; + create_entry.node().title = "Creates a new empty ontology"; + d3.select("#useAccuracyHelper").style("color", "#2980b9"); + d3.select("#useAccuracyHelper").style("pointer-events", "auto"); + create_entry.node().disabled = false; + create_entry.style("pointer-events", "auto"); + } + + return editMode; + } + graph.options().setEditorModeForDefaultObject(val); + + // if (seenEditorHint===false && val===true){ + // seenEditorHint=true; + // graph.options().warningModule().showEditorHint(); + // } + editMode = val; + + if ( create_entry ) { + create_entry.classed("disabled", !editMode); + if ( !editMode ) { + create_container.node().title = "Enable editing in modes menu to create a new ontology"; + create_entry.node().title = "Enable editing in modes menu to create a new ontology"; + create_entry.node().disabled = true; + d3.select("#useAccuracyHelper").style("color", "#979797"); + d3.select("#useAccuracyHelper").style("pointer-events", "none"); + create_entry.style("pointer-events", "none"); + } else { + create_container.node().title = "Creates a new empty ontology"; + create_entry.node().title = "Creates a new empty ontology"; + d3.select("#useAccuracyHelper").style("color", "#2980b9"); + d3.select("#useAccuracyHelper").style("pointer-events", "auto"); + create_entry.style("pointer-events", "auto"); + } + } + + // adjust compact notation + // selector = compactNotationOption; + // box =ModuleCheckbox + var compactNotationContainer = d3.select("#compactnotationModuleCheckbox"); + if ( compactNotationContainer ) { + compactNotationContainer.classed("disabled", !editMode); + if ( !editMode ) { + compactNotationContainer.node().title = ""; + compactNotationContainer.node().disabled = false; + compactNotationContainer.style("pointer-events", "auto"); + d3.select("#compactNotationOption").style("color", ""); + d3.select("#compactNotationOption").node().title = ""; + options.literalFilter().enabled(true); + graph.update(); + } else { + // if editor Mode + //1) uncheck the element + d3.select("#compactNotationOption").node().title = "Compact notation can only be used in view mode"; + compactNotationContainer.node().disabled = true; + compactNotationContainer.node().checked = false; + options.compactNotationModule().enabled(false); + options.literalFilter().enabled(false); + graph.executeCompactNotationModule(); + graph.executeEmptyLiteralFilter(); + graph.lazyRefresh(); + compactNotationContainer.style("pointer-events", "none"); + d3.select("#compactNotationOption").style("color", "#979797"); + } + } + + if ( modeOfOpString ) { + if ( touchDevice === true ) { + modeOfOpString.innerHTML = "touch able device detected"; + } else { + modeOfOpString.innerHTML = "point & click device detected"; + } + } + var svgGraph = d3.selectAll(".vowlGraph"); + + if ( editMode === true ) { + options.leftSidebar().showSidebar(options.leftSidebar().getSidebarVisibility(), true); + options.leftSidebar().hideCollapseButton(false); + graph.options().editSidebar().updatePrefixUi(); + graph.options().editSidebar().updateElementWidth(); + svgGraph.on("dblclick.zoom", graph.modified_dblClickFunction); + + } else { + svgGraph.on("dblclick.zoom", originalD3_dblClickFunction); + options.leftSidebar().showSidebar(0); + options.leftSidebar().hideCollapseButton(true); + // hide hovered edit elements + removeEditElements(); + } + options.sidebar().updateShowedInformation(); + options.editSidebar().updateElementWidth(); + + }; + + function createLowerCasePrototypeMap( prototypeMap ){ + return d3.map(prototypeMap.values(), function ( Prototype ){ + return new Prototype().type().toLowerCase(); + }); + } + + function createNewNodeAtPosition( pos ){ + var aNode, prototype; + var forceUpdate = true; + // create a node of that id; + + var typeToCreate = d3.select("#defaultClass").node().title; + prototype = NodePrototypeMap.get(typeToCreate.toLowerCase()); + aNode = new prototype(graph); + var autoEditElement = false; + if ( typeToCreate === "owl:Thing" ) { + aNode.label("Thing"); + } + else { + aNode.label("NewClass"); + autoEditElement = true; + } + aNode.x = pos.x; + aNode.y = pos.y; + aNode.px = aNode.x; + aNode.py = aNode.y; + aNode.id("Class" + eN++); + // aNode.paused(true); + + aNode.baseIri(d3.select("#iriEditor").node().value); + aNode.iri(aNode.baseIri() + aNode.id()); + addNewNodeElement(aNode, forceUpdate); + options.focuserModule().handle(aNode, true); + aNode.frozen(graph.paused()); + aNode.locked(graph.paused()); + aNode.enableEditing(autoEditElement); + } + + + function addNewNodeElement( element ){ + unfilteredData.nodes.push(element); + if ( classNodes.indexOf(element) === -1 ) + classNodes.push(element); + + generateDictionary(unfilteredData); + graph.getUpdateDictionary(); + graph.fastUpdate(); + } + + graph.getTargetNode = function ( position ){ + var dx = position[0]; + var dy = position[1]; + var tN = null; + var minDist = 1000000000000; + // This is a bit OVERKILL for the computation of one node >> TODO: KD-TREE SEARCH + unfilteredData.nodes.forEach(function ( el ){ + var cDist = Math.sqrt((el.x - dx) * (el.x - dx) + (el.y - dy) * (el.y - dy)); + if ( cDist < minDist ) { + minDist = cDist; + tN = el; + } + }); + if ( hoveredNodeElement ) { + var offsetDist = hoveredNodeElement.actualRadius() + 30; + if ( minDist > offsetDist ) return null; + if ( tN.renderType() === "rect" ) return null; + if ( tN === hoveredNodeElement && minDist <= hoveredNodeElement.actualRadius() ) { + return tN; + } else if ( tN === hoveredNodeElement && minDist > hoveredNodeElement.actualRadius() ) { + return null; + } + return tN; + } + else { + + if ( minDist > (tN.actualRadius() + 30) ) + return null; + else return tN; + + } + }; + + graph.genericPropertySanityCheck = function ( domain, range, typeString, header, action ){ + if ( domain === range && typeString === "rdfs:subClassOf" ) { + graph.options().warningModule().showWarning(header, + "rdfs:subClassOf can not be created as loops (domain == range)", + action, 1, false); + return false; + } + if ( domain === range && typeString === "owl:disjointWith" ) { + graph.options().warningModule().showWarning(header, + "owl:disjointWith can not be created as loops (domain == range)", + action, 1, false); + return false; + } + // allProps[i].type()==="owl:allValuesFrom" || + // allProps[i].type()==="owl:someValuesFrom" + if ( domain.type() === "owl:Thing" && typeString === "owl:allValuesFrom" ) { + graph.options().warningModule().showWarning(header, + "owl:allValuesFrom can not originate from owl:Thing", + action, 1, false); + return false; + } + if ( domain.type() === "owl:Thing" && typeString === "owl:someValuesFrom" ) { + graph.options().warningModule().showWarning(header, + "owl:someValuesFrom can not originate from owl:Thing", + action, 1, false); + return false; + } + + if ( range.type() === "owl:Thing" && typeString === "owl:allValuesFrom" ) { + graph.options().warningModule().showWarning(header, + "owl:allValuesFrom can not be connected to owl:Thing", + action, 1, false); + return false; + } + if ( range.type() === "owl:Thing" && typeString === "owl:someValuesFrom" ) { + graph.options().warningModule().showWarning(header, + "owl:someValuesFrom can not be connected to owl:Thing", + action, 1, false); + return false; + } + + return true; // we can Change the domain or range + }; + + graph.checkIfIriClassAlreadyExist = function ( url ){ + // search for a class node with this url + var allNodes = unfilteredData.nodes; + for ( var i = 0; i < allNodes.length; i++ ) { + if ( elementTools.isDatatype(allNodes[i]) === true || allNodes[i].type() === "owl:Thing" ) + continue; + + // now we are a real class; + //get class IRI + var classIRI = allNodes[i].iri(); + + // this gives me the node for halo + if ( url === classIRI ) { + return allNodes[i]; + } + } + return false; + }; + + graph.classesSanityCheck = function ( classElement, targetType ){ + // this is added due to someValuesFrom properties + // we should not be able to change a classElement to a owl:Thing + // when it has a property attached to it that uses these restrictions + // + + if ( targetType === "owl:Class" ) return true; + + else { + // collect all properties which have that one as a domain or range + var allProps = unfilteredData.properties; + for ( var i = 0; i < allProps.length; i++ ) { + if ( allProps[i].range() === classElement || allProps[i].domain() === classElement ) { + // check for the type of that property + if ( allProps[i].type() === "owl:someValuesFrom" ) { + graph.options().warningModule().showWarning("Can not change class type", + "The element has a property that is of type owl:someValuesFrom", + "Element type not changed!", 1, true); + return false; + } + if ( allProps[i].type() === "owl:allValuesFrom" ) { + graph.options().warningModule().showWarning("Can not change class type", + "The element has a property that is of type owl:allValuesFrom", + "Element type not changed!", 1, true); + return false; + } + } + } + + + } + return true; + }; + + graph.propertyCheckExistenceChecker = function ( property, domain, range ){ + var allProps = unfilteredData.properties; + var i; + if ( property.type() === "rdfs:subClassOf" || property.type() === "owl:disjointWith" ) { + + for ( i = 0; i < allProps.length; i++ ) { + if ( allProps[i] === property ) continue; + if ( allProps[i].domain() === domain && allProps[i].range() === range && allProps[i].type() === property.type() ) { + graph.options().warningModule().showWarning("Warning", + "This triple already exist!", + "Element not created!", 1, false); + return false; + } + if ( allProps[i].domain() === range && allProps[i].range() === domain && allProps[i].type() === property.type() ) { + graph.options().warningModule().showWarning("Warning", + "Inverse assignment already exist! ", + "Element not created!", 1, false); + return false; + } + } + return true; + } + return true; + }; + + // graph.checkForTripleDuplicate=function(property){ + // var domain=property.domain(); + // var range=property.range(); + // console.log("checking for duplicates"); + // var b1= domain.isPropertyAssignedToThisElement(property); + // var b2= range.isPropertyAssignedToThisElement(property); + // + // console.log("test domain results in "+ b1); + // console.log("test range results in "+ b1); + // + // if (b1 && b2 ){ + // graph.options().warningModule().showWarning("Warning", + // "This triple already exist!", + // "Element not created!",1,false); + // return false; + // } + // return true; + // }; + + graph.sanityCheckProperty = function ( domain, range, typeString ){ + + // check for duplicate triple in the element; + + + if ( typeString === "owl:objectProperty" && graph.options().objectPropertyFilter().enabled() === true ) { + graph.options().warningModule().showWarning("Warning", + "Object properties are filtered out in the visualization!", + "Element not created!", 1, false); + return false; + } + + if ( typeString === "owl:disjointWith" && graph.options().disjointPropertyFilter().enabled() === true ) { + graph.options().warningModule().showWarning("Warning", + "owl:disjointWith properties are filtered out in the visualization!", + "Element not created!", 1, false); + return false; + } + + + if ( domain === range && typeString === "rdfs:subClassOf" ) { + graph.options().warningModule().showWarning("Warning", + "rdfs:subClassOf can not be created as loops (domain == range)", + "Element not created!", 1, false); + return false; + } + if ( domain === range && typeString === "owl:disjointWith" ) { + graph.options().warningModule().showWarning("Warning", + "owl:disjointWith can not be created as loops (domain == range)", + "Element not created!", 1, false); + return false; + } + + if ( domain.type() === "owl:Thing" && typeString === "owl:someValuesFrom" ) { + graph.options().warningModule().showWarning("Warning", + "owl:someValuesFrom can not originate from owl:Thing", + "Element not created!", 1, false); + return false; + } + if ( domain.type() === "owl:Thing" && typeString === "owl:allValuesFrom" ) { + graph.options().warningModule().showWarning("Warning", + "owl:allValuesFrom can not originate from owl:Thing", + "Element not created!", 1, false); + return false; + } + + if ( range.type() === "owl:Thing" && typeString === "owl:allValuesFrom" ) { + graph.options().warningModule().showWarning("Warning", + "owl:allValuesFrom can not be connected to owl:Thing", + "Element not created!", 1, false); + return false; + } + if ( range.type() === "owl:Thing" && typeString === "owl:someValuesFrom" ) { + graph.options().warningModule().showWarning("Warning", + "owl:someValuesFrom can not be connected to owl:Thing", + "Element not created!", 1, false); + return false; + } + return true; // we can create a property + }; + + function createNewObjectProperty( domain, range, draggerEndposition ){ + // check type of the property that we want to create; + + var defaultPropertyName = d3.select("#defaultProperty").node().title; + + // check if we are allow to create that property + if ( graph.sanityCheckProperty(domain, range, defaultPropertyName) === false ) return false; + + + var propPrototype = PropertyPrototypeMap.get(defaultPropertyName.toLowerCase()); + var aProp = new propPrototype(graph); + aProp.id("objectProperty" + eP++); + aProp.domain(domain); + aProp.range(range); + aProp.label("newObjectProperty"); + aProp.baseIri(d3.select("#iriEditor").node().value); + aProp.iri(aProp.baseIri() + aProp.id()); + + // check for duplicate; + if ( graph.propertyCheckExistenceChecker(aProp, domain, range) === false ) { + // delete aProp; + // hope for garbage collection here -.- + return false; + } + + var autoEditElement = false; + + if ( defaultPropertyName === "owl:objectProperty" ) { + autoEditElement = true; + } + var pX = 0.49 * (domain.x + range.x); + var pY = 0.49 * (domain.y + range.y); + + if ( domain === range ) { + // we use the dragger endposition to determine an angle to put the loop there; + var dirD_x = draggerEndposition[0] - domain.x; + var dirD_y = draggerEndposition[1] - domain.y; + + // normalize; + var len = Math.sqrt(dirD_x * dirD_x + dirD_y * dirD_y); + // it should be very hard to set the position on the same sport but why not handling this + var nx = dirD_x / len; + var ny = dirD_y / len; + // is Nan in javascript like in c len==len returns false when it is not a number? + if ( isNaN(len) ) { + nx = 0; + ny = -1; + } + + // get domain actual raidus + var offset = 2 * domain.actualRadius() + 50; + pX = domain.x + offset * nx; + pY = domain.y + offset * ny; + } + + // add this property to domain and range; + domain.addProperty(aProp); + range.addProperty(aProp); + + + // add this to the data; + unfilteredData.properties.push(aProp); + if ( properties.indexOf(aProp) === -1 ) + properties.push(aProp); + graph.fastUpdate(); + aProp.labelObject().x = pX; + aProp.labelObject().px = pX; + aProp.labelObject().y = pY; + aProp.labelObject().py = pY; + + aProp.frozen(graph.paused()); + aProp.locked(graph.paused()); + domain.frozen(graph.paused()); + domain.locked(graph.paused()); + range.frozen(graph.paused()); + range.locked(graph.paused()); + + + generateDictionary(unfilteredData); + graph.getUpdateDictionary(); + + options.focuserModule().handle(aProp); + graph.activateHoverElementsForProperties(true, aProp, false, touchDevice); + aProp.labelObject().increasedLoopAngle = true; + aProp.enableEditing(autoEditElement); + } + + graph.createDataTypeProperty = function ( node ){ + // random postion issues; + clearTimeout(nodeFreezer); + // tells user when element is filtered out + if ( graph.options().datatypeFilter().enabled() === true ) { + graph.options().warningModule().showWarning("Warning", + "Datatype properties are filtered out in the visualization!", + "Element not created!", 1, false); + return; + } + + + var aNode, prototype; + + // create a default datatype Node >> HERE LITERAL; + var defaultDatatypeName = d3.select("#defaultDatatype").node().title; + if ( defaultDatatypeName === "rdfs:Literal" ) { + prototype = NodePrototypeMap.get("rdfs:literal"); + aNode = new prototype(graph); + aNode.label("Literal"); + aNode.iri("http://www.w3.org/2000/01/rdf-schema#Literal"); + aNode.baseIri("http://www.w3.org/2000/01/rdf-schema#"); + } else { + prototype = NodePrototypeMap.get("rdfs:datatype"); + aNode = new prototype(graph); + var identifier = ""; + if ( defaultDatatypeName === "undefined" ) { + identifier = "undefined"; + + aNode.label(identifier); + // TODO : HANDLER FOR UNDEFINED DATATYPES!!<<<>>>>>>>>>>>.. + aNode.iri("http://www.undefinedDatatype.org/#" + identifier); + aNode.baseIri("http://www.undefinedDatatype.org/#"); + aNode.dType(defaultDatatypeName); + } else { + identifier = defaultDatatypeName.split(":")[1]; + aNode.label(identifier); + aNode.dType(defaultDatatypeName); + aNode.iri("http://www.w3.org/2001/XMLSchema#" + identifier); + aNode.baseIri("http://www.w3.org/2001/XMLSchema#"); + } + } + + + var nX = node.x - node.actualRadius() - 100; + var nY = node.y + node.actualRadius() + 100; + + aNode.x = nX; + aNode.y = nY; + aNode.px = aNode.x; + aNode.py = aNode.y; + aNode.id("NodeId" + eN++); + // add this property to the nodes; + unfilteredData.nodes.push(aNode); + if ( classNodes.indexOf(aNode) === -1 ) + classNodes.push(aNode); + + + // add also the datatype Property to it + var propPrototype = PropertyPrototypeMap.get("owl:datatypeproperty"); + var aProp = new propPrototype(graph); + aProp.id("datatypeProperty" + eP++); + + // create the connection + aProp.domain(node); + aProp.range(aNode); + aProp.label("newDatatypeProperty"); + + + // TODO: change its base IRI to proper value + var ontoIri = d3.select("#iriEditor").node().value; + aProp.baseIri(ontoIri); + aProp.iri(ontoIri + aProp.id()); + // add this to the data; + unfilteredData.properties.push(aProp); + if ( properties.indexOf(aProp) === -1 ) + properties.push(aProp); + graph.fastUpdate(); + generateDictionary(unfilteredData); + graph.getUpdateDictionary(); + + nodeFreezer = setTimeout(function (){ + if ( node && node.frozen() === true && node.pinned() === false && graph.paused() === false ) { + node.frozen(graph.paused()); + node.locked(graph.paused()); + } + }, 1000); + options.focuserModule().handle(undefined); + if ( node ) { + node.frozen(true); + node.locked(true); + } + }; + + graph.removeNodesViaResponse = function ( nodesToRemove, propsToRemove ){ + var i, remId; + // splice them; + for ( i = 0; i < propsToRemove.length; i++ ) { + remId = unfilteredData.properties.indexOf(propsToRemove[i]); + if ( remId !== -1 ) + unfilteredData.properties.splice(remId, 1); + remId = properties.indexOf(propsToRemove[i]); + if ( remId !== -1 ) + properties.splice(remId, 1); + propsToRemove[i] = null; + } + for ( i = 0; i < nodesToRemove.length; i++ ) { + remId = unfilteredData.nodes.indexOf(nodesToRemove[i]); + if ( remId !== -1 ) { + unfilteredData.nodes.splice(remId, 1); + } + remId = classNodes.indexOf(nodesToRemove[i]); + if ( remId !== -1 ) + classNodes.splice(remId, 1); + nodesToRemove[i] = null; + } + graph.fastUpdate(); + generateDictionary(unfilteredData); + graph.getUpdateDictionary(); + options.focuserModule().handle(undefined); + nodesToRemove = null; + propsToRemove = null; + + }; + + graph.removeNodeViaEditor = function ( node ){ + var propsToRemove = []; + var nodesToRemove = []; + var datatypes = 0; + + var remId; + + nodesToRemove.push(node); + for ( var i = 0; i < unfilteredData.properties.length; i++ ) { + if ( unfilteredData.properties[i].domain() === node || unfilteredData.properties[i].range() === node ) { + propsToRemove.push(unfilteredData.properties[i]); + if ( unfilteredData.properties[i].type().toLocaleLowerCase() === "owl:datatypeproperty" && + unfilteredData.properties[i].range() !== node ) { + nodesToRemove.push(unfilteredData.properties[i].range()); + datatypes++; + } + } + } + var removedItems = propsToRemove.length + nodesToRemove.length; + if ( removedItems > 2 ) { + var text = "You are about to delete 1 class and " + propsToRemove.length + " properties"; + if ( datatypes !== 0 ) { + text = "You are about to delete 1 class, " + datatypes + " datatypes and " + propsToRemove.length + " properties"; + } + + + graph.options().warningModule().responseWarning( + "Removing elements", + text, + "Awaiting response!", graph.removeNodesViaResponse, [nodesToRemove, propsToRemove], false); + + + // + // if (confirm("Remove :\n"+propsToRemove.length + " properties\n"+nodesToRemove.length+" classes? ")===false){ + // return; + // }else{ + // // todo : store for undo delete button ; + // } + } else { + // splice them; + for ( i = 0; i < propsToRemove.length; i++ ) { + remId = unfilteredData.properties.indexOf(propsToRemove[i]); + if ( remId !== -1 ) + unfilteredData.properties.splice(remId, 1); + remId = properties.indexOf(propsToRemove[i]); + if ( remId !== -1 ) + properties.splice(remId, 1); + propsToRemove[i] = null; + } + for ( i = 0; i < nodesToRemove.length; i++ ) { + remId = unfilteredData.nodes.indexOf(nodesToRemove[i]); + if ( remId !== -1 ) + unfilteredData.nodes.splice(remId, 1); + remId = classNodes.indexOf(nodesToRemove[i]); + if ( remId !== -1 ) + classNodes.splice(remId, 1); + nodesToRemove[i] = null; + } + graph.fastUpdate(); + generateDictionary(unfilteredData); + graph.getUpdateDictionary(); + options.focuserModule().handle(undefined); + nodesToRemove = null; + propsToRemove = null; + } + }; + + graph.removePropertyViaEditor = function ( property ){ + property.domain().removePropertyElement(property); + property.range().removePropertyElement(property); + var remId; + + if ( property.type().toLocaleLowerCase() === "owl:datatypeproperty" ) { + var datatype = property.range(); + remId = unfilteredData.nodes.indexOf(property.range()); + if ( remId !== -1 ) + unfilteredData.nodes.splice(remId, 1); + remId = classNodes.indexOf(property.range()); + if ( remId !== -1 ) + classNodes.splice(remId, 1); + datatype = null; + } + remId = unfilteredData.properties.indexOf(property); + if ( remId !== -1 ) + unfilteredData.properties.splice(remId, 1); + remId = properties.indexOf(property); + if ( remId !== -1 ) + properties.splice(remId, 1); + if ( property.inverse() ) { + // so we have inverse + property.inverse().inverse(0); + + } + + + hoveredPropertyElement = undefined; + graph.fastUpdate(); + generateDictionary(unfilteredData); + graph.getUpdateDictionary(); + options.focuserModule().handle(undefined); + property = null; + }; + + graph.executeColorExternalsModule = function (){ + options.colorExternalsModule().filter(unfilteredData.nodes, unfilteredData.properties); + }; + + graph.executeCompactNotationModule = function (){ + if ( unfilteredData ) { + options.compactNotationModule().filter(unfilteredData.nodes, unfilteredData.properties); + } + + }; + graph.executeEmptyLiteralFilter = function (){ + + if ( unfilteredData && unfilteredData.nodes.length > 1 ) { + options.literalFilter().filter(unfilteredData.nodes, unfilteredData.properties); + unfilteredData.nodes = options.literalFilter().filteredNodes(); + unfilteredData.properties = options.literalFilter().filteredProperties(); + } + + }; + + + /** --------------------------------------------------------- **/ + /** -- animation functions for the nodes -- **/ + /** --------------------------------------------------------- **/ + + graph.animateDynamicLabelWidth = function (){ + var wantedWidth = options.dynamicLabelWidth(); + var i; + for ( i = 0; i < classNodes.length; i++ ) { + var nodeElement = classNodes[i]; + if ( elementTools.isDatatype(nodeElement) ) { + nodeElement.animateDynamicLabelWidth(wantedWidth); + } + } + for ( i = 0; i < properties.length; i++ ) { + properties[i].animateDynamicLabelWidth(wantedWidth); + } + }; + + + /** --------------------------------------------------------- **/ + /** -- Touch behaviour functions -- **/ + /** --------------------------------------------------------- **/ + + graph.setTouchDevice = function ( val ){ + touchDevice = val; + }; + + graph.isTouchDevice = function (){ + return touchDevice; + }; + + graph.modified_dblClickFunction = function (){ + + d3.event.stopPropagation(); + d3.event.preventDefault(); + // get position where we want to add the node; + var grPos = getClickedScreenCoords(d3.event.clientX, d3.event.clientY, graph.translation(), graph.scaleFactor()); + createNewNodeAtPosition(grPos); + }; + + function doubletap(){ + var touch_time = d3.event.timeStamp; + var numTouchers = 1; + if ( d3.event && d3.event.touches && d3.event.touches.length ) + numTouchers = d3.event.touches.length; + + if ( touch_time - last_touch_time < 300 && numTouchers === 1 ) { + d3.event.stopPropagation(); + if ( editMode === true ) { + //graph.modified_dblClickFunction(); + d3.event.preventDefault(); + d3.event.stopPropagation(); + last_touch_time = touch_time; + return true; + } + } + last_touch_time = touch_time; + return false; + } + + + function touchzoomed(){ + forceNotZooming = true; + + + var touch_time = d3.event.timeStamp; + if ( touch_time - last_touch_time < 300 && d3.event.touches.length === 1 ) { + d3.event.stopPropagation(); + + if ( editMode === true ) { + //graph.modified_dblClickFunction(); + d3.event.preventDefault(); + d3.event.stopPropagation(); + zoom.translate(graphTranslation); + zoom.scale(zoomFactor); + graph.modified_dblTouchFunction(); + } + else { + forceNotZooming = false; + if ( originalD3_touchZoomFunction ) + originalD3_touchZoomFunction(); + } + return; + } + forceNotZooming = false; + last_touch_time = touch_time; + // TODO: WORK AROUND TO CHECK FOR ORIGINAL FUNCTION + if ( originalD3_touchZoomFunction ) + originalD3_touchZoomFunction(); + } + + graph.modified_dblTouchFunction = function ( d ){ + d3.event.stopPropagation(); + d3.event.preventDefault(); + var xy; + if ( editMode === true ) { + xy = d3.touches(d3.selectAll(".vowlGraph").node()); + } + var grPos = getClickedScreenCoords(xy[0][0], xy[0][1], graph.translation(), graph.scaleFactor()); + createNewNodeAtPosition(grPos); + }; + + /** --------------------------------------------------------- **/ + /** -- Hover and Selection functions, adding edit elements -- **/ + /** --------------------------------------------------------- **/ + + graph.ignoreOtherHoverEvents = function ( val ){ + if ( !arguments.length ) { + return ignoreOtherHoverEvents; + } + else ignoreOtherHoverEvents = val; + }; + + function delayedHiddingHoverElements( tbh ){ + if ( tbh === true ) return; + if ( hoveredNodeElement ) { + if ( hoveredNodeElement.editingTextElement === true ) return; + delayedHider = setTimeout(function (){ + deleteGroupElement.classed("hidden", true); + addDataPropertyGroupElement.classed("hidden", true); + classDragger.hideDragger(true); + if ( hoveredNodeElement && hoveredNodeElement.pinned() === false && graph.paused() === false && hoveredNodeElement.editingTextElement === false ) { + hoveredNodeElement.frozen(false); + hoveredNodeElement.locked(false); + } + }, 1000); + } + if ( hoveredPropertyElement ) { + if ( hoveredPropertyElement.editingTextElement === true ) return; + delayedHider = setTimeout(function (){ + deleteGroupElement.classed("hidden", true); + addDataPropertyGroupElement.classed("hidden", true); + classDragger.hideDragger(true); + rangeDragger.hideDragger(true); + domainDragger.hideDragger(true); + shadowClone.hideClone(true); + if ( hoveredPropertyElement && hoveredPropertyElement.focused() === true && graph.options().drawPropertyDraggerOnHover() === true ) { + hoveredPropertyElement.labelObject().increasedLoopAngle = false; + // lazy update + recalculatePositions(); + } + + if ( hoveredPropertyElement && hoveredPropertyElement.pinned() === false && graph.paused() === false && hoveredPropertyElement.editingTextElement === false ) { + hoveredPropertyElement.frozen(false); + hoveredPropertyElement.locked(false); + } + }, 1000); + } + + } + + + // TODO : experimental code for updating dynamic label with and its hover element + graph.hideHoverPropertyElementsForAnimation = function (){ + deleteGroupElement.classed("hidden", true); + }; + graph.showHoverElementsAfterAnimation = function ( property, inversed ){ + setDeleteHoverElementPositionProperty(property, inversed); + deleteGroupElement.classed("hidden", false); + + }; + + function editElementHoverOnHidden(){ + classDragger.nodeElement.classed("classDraggerNodeHovered", true); + classDragger.nodeElement.classed("classDraggerNode", false); + editElementHoverOn(); + } + + function editElementHoverOutHidden(){ + classDragger.nodeElement.classed("classDraggerNodeHovered", false); + classDragger.nodeElement.classed("classDraggerNode", true); + editElementHoverOut(); + } + + function editElementHoverOn( touch ){ + if ( touch === true ) return; + clearTimeout(delayedHider); // ignore touch behaviour + + } + + graph.killDelayedTimer = function (){ + clearTimeout(delayedHider); + clearTimeout(nodeFreezer); + }; + + + function editElementHoverOut( tbh ){ + if ( hoveredNodeElement ) { + if ( graph.ignoreOtherHoverEvents() === true || tbh === true || hoveredNodeElement.editingTextElement === true ) return; + delayedHider = setTimeout(function (){ + if ( graph.isADraggerActive() === true ) return; + deleteGroupElement.classed("hidden", true); + addDataPropertyGroupElement.classed("hidden", true); + classDragger.hideDragger(true); + if ( hoveredNodeElement && hoveredNodeElement.pinned() === false && graph.paused() === false ) { + hoveredNodeElement.frozen(false); + hoveredNodeElement.locked(false); + } + + }, 1000); + } + if ( hoveredPropertyElement ) { + if ( graph.ignoreOtherHoverEvents() === true || tbh === true || hoveredPropertyElement.editingTextElement === true ) return; + delayedHider = setTimeout(function (){ + if ( graph.isADraggerActive() === true ) return; + deleteGroupElement.classed("hidden", true); + addDataPropertyGroupElement.classed("hidden", true); + classDragger.hideDragger(true); + if ( hoveredPropertyElement && hoveredPropertyElement.pinned() === false && graph.paused() === false ) { + hoveredPropertyElement.frozen(false); + hoveredPropertyElement.locked(false); + } + + }, 1000); + } + } + + graph.activateHoverElementsForProperties = function ( val, property, inversed, touchBehaviour ){ + if ( editMode === false ) return; // nothing to do; + + if ( touchBehaviour === undefined ) + touchBehaviour = false; + + if ( val === true ) { + clearTimeout(delayedHider); + if ( hoveredPropertyElement ) { + if ( hoveredPropertyElement.domain() === hoveredPropertyElement.range() ) { + hoveredPropertyElement.labelObject().increasedLoopAngle = false; + recalculatePositions(); + } + } + + hoveredPropertyElement = property; + if ( graph.options().drawPropertyDraggerOnHover() === true ) { + + + if ( property.type() !== "owl:DatatypeProperty" ) { + if ( property.domain() === property.range() ) { + property.labelObject().increasedLoopAngle = true; + recalculatePositions(); + } + shadowClone.setParentProperty(property, inversed); + rangeDragger.setParentProperty(property, inversed); + rangeDragger.hideDragger(false); + rangeDragger.addMouseEvents(); + domainDragger.setParentProperty(property, inversed); + domainDragger.hideDragger(false); + domainDragger.addMouseEvents(); + + + } else if ( property.type() === "owl:DatatypeProperty" ) { + shadowClone.setParentProperty(property, inversed); + rangeDragger.setParentProperty(property, inversed); + rangeDragger.hideDragger(true); + rangeDragger.addMouseEvents(); + domainDragger.setParentProperty(property, inversed); + domainDragger.hideDragger(false); + domainDragger.addMouseEvents(); + } + } + else { // hide when we dont want that option + if ( graph.options().drawPropertyDraggerOnHover() === true ) { + rangeDragger.hideDragger(true); + domainDragger.hideDragger(true); + shadowClone.hideClone(true); + if ( property.domain() === property.range() ) { + property.labelObject().increasedLoopAngle = false; + recalculatePositions(); + } + } + } + + if ( hoveredNodeElement ) { + if ( hoveredNodeElement && hoveredNodeElement.pinned() === false && graph.paused() === false ) { + hoveredNodeElement.frozen(false); + hoveredNodeElement.locked(false); + } + } + hoveredNodeElement = undefined; + deleteGroupElement.classed("hidden", false); + setDeleteHoverElementPositionProperty(property, inversed); + deleteGroupElement.selectAll("*").on("click", function (){ + if ( touchBehaviour && property.focused() === false ) { + graph.options().focuserModule().handle(property); + return; + } + graph.removePropertyViaEditor(property); + d3.event.stopPropagation(); + }); + classDragger.hideDragger(true); + addDataPropertyGroupElement.classed("hidden", true); + } else { + delayedHiddingHoverElements(); + } + }; + + graph.updateDraggerElements = function (){ + + // set opacity style for all elements + + rangeDragger.draggerObject.classed("superOpacityElement", !graph.options().showDraggerObject()); + domainDragger.draggerObject.classed("superOpacityElement", !graph.options().showDraggerObject()); + classDragger.draggerObject.classed("superOpacityElement", !graph.options().showDraggerObject()); + + nodeContainer.selectAll(".superHiddenElement").classed("superOpacityElement", !graph.options().showDraggerObject()); + labelContainer.selectAll(".superHiddenElement").classed("superOpacityElement", !graph.options().showDraggerObject()); + + deleteGroupElement.selectAll(".superHiddenElement").classed("superOpacityElement", !graph.options().showDraggerObject()); + addDataPropertyGroupElement.selectAll(".superHiddenElement").classed("superOpacityElement", !graph.options().showDraggerObject()); + + + }; + + function setAddDataPropertyHoverElementPosition( node ){ + var delX, delY = 0; + if ( node.renderType() === "round" ) { + var scale = 0.5 * Math.sqrt(2.0); + var oX = scale * node.actualRadius(); + var oY = scale * node.actualRadius(); + delX = node.x - oX; + delY = node.y + oY; + addDataPropertyGroupElement.attr("transform", "translate(" + delX + "," + delY + ")"); + } + } + + function setDeleteHoverElementPosition( node ){ + var delX, delY = 0; + if ( node.renderType() === "round" ) { + var scale = 0.5 * Math.sqrt(2.0); + var oX = scale * node.actualRadius(); + var oY = scale * node.actualRadius(); + delX = node.x + oX; + delY = node.y - oY; + } else { + delX = node.x + 0.5 * node.width() + 6; + delY = node.y - 0.5 * node.height() - 6; + } + deleteGroupElement.attr("transform", "translate(" + delX + "," + delY + ")"); + } + + function setDeleteHoverElementPositionProperty( property, inversed ){ + if ( property && property.labelElement() ) { + var pos = [property.labelObject().x, property.labelObject().y]; + var widthElement = parseFloat(property.getShapeElement().attr("width")); + var heightElement = parseFloat(property.getShapeElement().attr("height")); + var delX = pos[0] + 0.5 * widthElement + 6; + var delY = pos[1] - 0.5 * heightElement - 6; + // this is the lower element + if ( property.labelElement().attr("transform") === "translate(0,15)" ) + delY += 15; + // this is upper element + if ( property.labelElement().attr("transform") === "translate(0,-15)" ) + delY -= 15; + deleteGroupElement.attr("transform", "translate(" + delX + "," + delY + ")"); + } else { + deleteGroupElement.classed("hidden", true);// hide when there is no property + } + + + } + + graph.activateHoverElements = function ( val, node, touchBehaviour ){ + if ( editMode === false ) { + return; // nothing to do; + } + if ( touchBehaviour === undefined ) touchBehaviour = false; + if ( val === true ) { + if ( graph.options().drawPropertyDraggerOnHover() === true ) { + rangeDragger.hideDragger(true); + domainDragger.hideDragger(true); + shadowClone.hideClone(true); + } + // make them visible + clearTimeout(delayedHider); + clearTimeout(nodeFreezer); + if ( hoveredNodeElement && node.pinned() === false && graph.paused() === false ) { + hoveredNodeElement.frozen(false); + hoveredNodeElement.locked(false); + } + hoveredNodeElement = node; + if ( node && node.frozen() === false && node.pinned() === false ) { + node.frozen(true); + node.locked(false); + } + if ( hoveredPropertyElement && hoveredPropertyElement.focused() === false ) { + hoveredPropertyElement.labelObject().increasedLoopAngle = false; + recalculatePositions(); + // update the loopAngles; + + } + hoveredPropertyElement = undefined; + deleteGroupElement.classed("hidden", false); + setDeleteHoverElementPosition(node); + + + deleteGroupElement.selectAll("*").on("click", function (){ + if ( touchBehaviour && node.focused() === false ) { + graph.options().focuserModule().handle(node); + return; + } + graph.removeNodeViaEditor(node); + d3.event.stopPropagation(); + }) + .on("mouseover", function (){ + editElementHoverOn(node, touchBehaviour); + }) + .on("mouseout", function (){ + editElementHoverOut(node, touchBehaviour); + }); + + addDataPropertyGroupElement.classed("hidden", true); + classDragger.nodeElement.on("mouseover", editElementHoverOn) + .on("mouseout", editElementHoverOut); + classDragger.draggerObject.on("mouseover", editElementHoverOnHidden) + .on("mouseout", editElementHoverOutHidden); + + // add the dragger element; + if ( node.renderType() === "round" ) { + classDragger.svgRoot(draggerLayer); + classDragger.setParentNode(node); + classDragger.hideDragger(false); + addDataPropertyGroupElement.classed("hidden", false); + setAddDataPropertyHoverElementPosition(node); + addDataPropertyGroupElement.selectAll("*").on("click", function (){ + if ( touchBehaviour && node.focused() === false ) { + graph.options().focuserModule().handle(node); + return; + } + graph.createDataTypeProperty(node); + d3.event.stopPropagation(); + }) + .on("mouseover", function (){ + editElementHoverOn(node, touchBehaviour); + }) + .on("mouseout", function (){ + editElementHoverOut(node, touchBehaviour); + }); + } else { + classDragger.hideDragger(true); + + } + + } else { + delayedHiddingHoverElements(node, touchBehaviour); + + } + }; + + + return graph; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 58 */ +/***/ (function(module, exports, __webpack_require__) { + + var __WEBPACK_AMD_DEFINE_RESULT__;/* WEBPACK VAR INJECTION */(function(global, module) {/** + * @license + * Lodash (Custom Build) + * Build: `lodash core -o ./dist/lodash.core.js` + * Copyright OpenJS Foundation and other contributors + * Released under MIT license + * Based on Underscore.js 1.8.3 + * Copyright Jeremy Ashkenas, DocumentCloud and Investigative Reporters & Editors + */ + ;(function() { + + /** Used as a safe reference for `undefined` in pre-ES5 environments. */ + var undefined; + + /** Used as the semantic version number. */ + var VERSION = '4.17.15'; + + /** Error message constants. */ + var FUNC_ERROR_TEXT = 'Expected a function'; + + /** Used to compose bitmasks for value comparisons. */ + var COMPARE_PARTIAL_FLAG = 1, + COMPARE_UNORDERED_FLAG = 2; + + /** Used to compose bitmasks for function metadata. */ + var WRAP_BIND_FLAG = 1, + WRAP_PARTIAL_FLAG = 32; + + /** Used as references for various `Number` constants. */ + var INFINITY = 1 / 0, + MAX_SAFE_INTEGER = 9007199254740991; + + /** `Object#toString` result references. */ + var argsTag = '[object Arguments]', + arrayTag = '[object Array]', + asyncTag = '[object AsyncFunction]', + boolTag = '[object Boolean]', + dateTag = '[object Date]', + errorTag = '[object Error]', + funcTag = '[object Function]', + genTag = '[object GeneratorFunction]', + numberTag = '[object Number]', + objectTag = '[object Object]', + proxyTag = '[object Proxy]', + regexpTag = '[object RegExp]', + stringTag = '[object String]'; + + /** Used to match HTML entities and HTML characters. */ + var reUnescapedHtml = /[&<>"']/g, + reHasUnescapedHtml = RegExp(reUnescapedHtml.source); + + /** Used to detect unsigned integer values. */ + var reIsUint = /^(?:0|[1-9]\d*)$/; + + /** Used to map characters to HTML entities. */ + var htmlEscapes = { + '&': '&', + '<': '<', + '>': '>', + '"': '"', + "'": ''' + }; + + /** Detect free variable `global` from Node.js. */ + var freeGlobal = typeof global == 'object' && global && global.Object === Object && global; + + /** Detect free variable `self`. */ + var freeSelf = typeof self == 'object' && self && self.Object === Object && self; + + /** Used as a reference to the global object. */ + var root = freeGlobal || freeSelf || Function('return this')(); + + /** Detect free variable `exports`. */ + var freeExports = typeof exports == 'object' && exports && !exports.nodeType && exports; + + /** Detect free variable `module`. */ + var freeModule = freeExports && typeof module == 'object' && module && !module.nodeType && module; + + /*--------------------------------------------------------------------------*/ + + /** + * Appends the elements of `values` to `array`. + * + * @private + * @param {Array} array The array to modify. + * @param {Array} values The values to append. + * @returns {Array} Returns `array`. + */ + function arrayPush(array, values) { + array.push.apply(array, values); + return array; + } + + /** + * The base implementation of `_.findIndex` and `_.findLastIndex` without + * support for iteratee shorthands. + * + * @private + * @param {Array} array The array to inspect. + * @param {Function} predicate The function invoked per iteration. + * @param {number} fromIndex The index to search from. + * @param {boolean} [fromRight] Specify iterating from right to left. + * @returns {number} Returns the index of the matched value, else `-1`. + */ + function baseFindIndex(array, predicate, fromIndex, fromRight) { + var length = array.length, + index = fromIndex + (fromRight ? 1 : -1); + + while ((fromRight ? index-- : ++index < length)) { + if (predicate(array[index], index, array)) { + return index; + } + } + return -1; + } + + /** + * The base implementation of `_.property` without support for deep paths. + * + * @private + * @param {string} key The key of the property to get. + * @returns {Function} Returns the new accessor function. + */ + function baseProperty(key) { + return function(object) { + return object == null ? undefined : object[key]; + }; + } + + /** + * The base implementation of `_.propertyOf` without support for deep paths. + * + * @private + * @param {Object} object The object to query. + * @returns {Function} Returns the new accessor function. + */ + function basePropertyOf(object) { + return function(key) { + return object == null ? undefined : object[key]; + }; + } + + /** + * The base implementation of `_.reduce` and `_.reduceRight`, without support + * for iteratee shorthands, which iterates over `collection` using `eachFunc`. + * + * @private + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} iteratee The function invoked per iteration. + * @param {*} accumulator The initial value. + * @param {boolean} initAccum Specify using the first or last element of + * `collection` as the initial value. + * @param {Function} eachFunc The function to iterate over `collection`. + * @returns {*} Returns the accumulated value. + */ + function baseReduce(collection, iteratee, accumulator, initAccum, eachFunc) { + eachFunc(collection, function(value, index, collection) { + accumulator = initAccum + ? (initAccum = false, value) + : iteratee(accumulator, value, index, collection); + }); + return accumulator; + } + + /** + * The base implementation of `_.values` and `_.valuesIn` which creates an + * array of `object` property values corresponding to the property names + * of `props`. + * + * @private + * @param {Object} object The object to query. + * @param {Array} props The property names to get values for. + * @returns {Object} Returns the array of property values. + */ + function baseValues(object, props) { + return baseMap(props, function(key) { + return object[key]; + }); + } + + /** + * Used by `_.escape` to convert characters to HTML entities. + * + * @private + * @param {string} chr The matched character to escape. + * @returns {string} Returns the escaped character. + */ + var escapeHtmlChar = basePropertyOf(htmlEscapes); + + /** + * Creates a unary function that invokes `func` with its argument transformed. + * + * @private + * @param {Function} func The function to wrap. + * @param {Function} transform The argument transform. + * @returns {Function} Returns the new function. + */ + function overArg(func, transform) { + return function(arg) { + return func(transform(arg)); + }; + } + + /*--------------------------------------------------------------------------*/ + + /** Used for built-in method references. */ + var arrayProto = Array.prototype, + objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** Used to generate unique IDs. */ + var idCounter = 0; + + /** + * Used to resolve the + * [`toStringTag`](http://ecma-international.org/ecma-262/7.0/#sec-object.prototype.tostring) + * of values. + */ + var nativeObjectToString = objectProto.toString; + + /** Used to restore the original `_` reference in `_.noConflict`. */ + var oldDash = root._; + + /** Built-in value references. */ + var objectCreate = Object.create, + propertyIsEnumerable = objectProto.propertyIsEnumerable; + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeIsFinite = root.isFinite, + nativeKeys = overArg(Object.keys, Object), + nativeMax = Math.max; + + /*------------------------------------------------------------------------*/ + + /** + * Creates a `lodash` object which wraps `value` to enable implicit method + * chain sequences. Methods that operate on and return arrays, collections, + * and functions can be chained together. Methods that retrieve a single value + * or may return a primitive value will automatically end the chain sequence + * and return the unwrapped value. Otherwise, the value must be unwrapped + * with `_#value`. + * + * Explicit chain sequences, which must be unwrapped with `_#value`, may be + * enabled using `_.chain`. + * + * The execution of chained methods is lazy, that is, it's deferred until + * `_#value` is implicitly or explicitly called. + * + * Lazy evaluation allows several methods to support shortcut fusion. + * Shortcut fusion is an optimization to merge iteratee calls; this avoids + * the creation of intermediate arrays and can greatly reduce the number of + * iteratee executions. Sections of a chain sequence qualify for shortcut + * fusion if the section is applied to an array and iteratees accept only + * one argument. The heuristic for whether a section qualifies for shortcut + * fusion is subject to change. + * + * Chaining is supported in custom builds as long as the `_#value` method is + * directly or indirectly included in the build. + * + * In addition to lodash methods, wrappers have `Array` and `String` methods. + * + * The wrapper `Array` methods are: + * `concat`, `join`, `pop`, `push`, `shift`, `sort`, `splice`, and `unshift` + * + * The wrapper `String` methods are: + * `replace` and `split` + * + * The wrapper methods that support shortcut fusion are: + * `at`, `compact`, `drop`, `dropRight`, `dropWhile`, `filter`, `find`, + * `findLast`, `head`, `initial`, `last`, `map`, `reject`, `reverse`, `slice`, + * `tail`, `take`, `takeRight`, `takeRightWhile`, `takeWhile`, and `toArray` + * + * The chainable wrapper methods are: + * `after`, `ary`, `assign`, `assignIn`, `assignInWith`, `assignWith`, `at`, + * `before`, `bind`, `bindAll`, `bindKey`, `castArray`, `chain`, `chunk`, + * `commit`, `compact`, `concat`, `conforms`, `constant`, `countBy`, `create`, + * `curry`, `debounce`, `defaults`, `defaultsDeep`, `defer`, `delay`, + * `difference`, `differenceBy`, `differenceWith`, `drop`, `dropRight`, + * `dropRightWhile`, `dropWhile`, `extend`, `extendWith`, `fill`, `filter`, + * `flatMap`, `flatMapDeep`, `flatMapDepth`, `flatten`, `flattenDeep`, + * `flattenDepth`, `flip`, `flow`, `flowRight`, `fromPairs`, `functions`, + * `functionsIn`, `groupBy`, `initial`, `intersection`, `intersectionBy`, + * `intersectionWith`, `invert`, `invertBy`, `invokeMap`, `iteratee`, `keyBy`, + * `keys`, `keysIn`, `map`, `mapKeys`, `mapValues`, `matches`, `matchesProperty`, + * `memoize`, `merge`, `mergeWith`, `method`, `methodOf`, `mixin`, `negate`, + * `nthArg`, `omit`, `omitBy`, `once`, `orderBy`, `over`, `overArgs`, + * `overEvery`, `overSome`, `partial`, `partialRight`, `partition`, `pick`, + * `pickBy`, `plant`, `property`, `propertyOf`, `pull`, `pullAll`, `pullAllBy`, + * `pullAllWith`, `pullAt`, `push`, `range`, `rangeRight`, `rearg`, `reject`, + * `remove`, `rest`, `reverse`, `sampleSize`, `set`, `setWith`, `shuffle`, + * `slice`, `sort`, `sortBy`, `splice`, `spread`, `tail`, `take`, `takeRight`, + * `takeRightWhile`, `takeWhile`, `tap`, `throttle`, `thru`, `toArray`, + * `toPairs`, `toPairsIn`, `toPath`, `toPlainObject`, `transform`, `unary`, + * `union`, `unionBy`, `unionWith`, `uniq`, `uniqBy`, `uniqWith`, `unset`, + * `unshift`, `unzip`, `unzipWith`, `update`, `updateWith`, `values`, + * `valuesIn`, `without`, `wrap`, `xor`, `xorBy`, `xorWith`, `zip`, + * `zipObject`, `zipObjectDeep`, and `zipWith` + * + * The wrapper methods that are **not** chainable by default are: + * `add`, `attempt`, `camelCase`, `capitalize`, `ceil`, `clamp`, `clone`, + * `cloneDeep`, `cloneDeepWith`, `cloneWith`, `conformsTo`, `deburr`, + * `defaultTo`, `divide`, `each`, `eachRight`, `endsWith`, `eq`, `escape`, + * `escapeRegExp`, `every`, `find`, `findIndex`, `findKey`, `findLast`, + * `findLastIndex`, `findLastKey`, `first`, `floor`, `forEach`, `forEachRight`, + * `forIn`, `forInRight`, `forOwn`, `forOwnRight`, `get`, `gt`, `gte`, `has`, + * `hasIn`, `head`, `identity`, `includes`, `indexOf`, `inRange`, `invoke`, + * `isArguments`, `isArray`, `isArrayBuffer`, `isArrayLike`, `isArrayLikeObject`, + * `isBoolean`, `isBuffer`, `isDate`, `isElement`, `isEmpty`, `isEqual`, + * `isEqualWith`, `isError`, `isFinite`, `isFunction`, `isInteger`, `isLength`, + * `isMap`, `isMatch`, `isMatchWith`, `isNaN`, `isNative`, `isNil`, `isNull`, + * `isNumber`, `isObject`, `isObjectLike`, `isPlainObject`, `isRegExp`, + * `isSafeInteger`, `isSet`, `isString`, `isUndefined`, `isTypedArray`, + * `isWeakMap`, `isWeakSet`, `join`, `kebabCase`, `last`, `lastIndexOf`, + * `lowerCase`, `lowerFirst`, `lt`, `lte`, `max`, `maxBy`, `mean`, `meanBy`, + * `min`, `minBy`, `multiply`, `noConflict`, `noop`, `now`, `nth`, `pad`, + * `padEnd`, `padStart`, `parseInt`, `pop`, `random`, `reduce`, `reduceRight`, + * `repeat`, `result`, `round`, `runInContext`, `sample`, `shift`, `size`, + * `snakeCase`, `some`, `sortedIndex`, `sortedIndexBy`, `sortedLastIndex`, + * `sortedLastIndexBy`, `startCase`, `startsWith`, `stubArray`, `stubFalse`, + * `stubObject`, `stubString`, `stubTrue`, `subtract`, `sum`, `sumBy`, + * `template`, `times`, `toFinite`, `toInteger`, `toJSON`, `toLength`, + * `toLower`, `toNumber`, `toSafeInteger`, `toString`, `toUpper`, `trim`, + * `trimEnd`, `trimStart`, `truncate`, `unescape`, `uniqueId`, `upperCase`, + * `upperFirst`, `value`, and `words` + * + * @name _ + * @constructor + * @category Seq + * @param {*} value The value to wrap in a `lodash` instance. + * @returns {Object} Returns the new `lodash` wrapper instance. + * @example + * + * function square(n) { + * return n * n; + * } + * + * var wrapped = _([1, 2, 3]); + * + * // Returns an unwrapped value. + * wrapped.reduce(_.add); + * // => 6 + * + * // Returns a wrapped value. + * var squares = wrapped.map(square); + * + * _.isArray(squares); + * // => false + * + * _.isArray(squares.value()); + * // => true + */ + function lodash(value) { + return value instanceof LodashWrapper + ? value + : new LodashWrapper(value); + } + + /** + * The base implementation of `_.create` without support for assigning + * properties to the created object. + * + * @private + * @param {Object} proto The object to inherit from. + * @returns {Object} Returns the new object. + */ + var baseCreate = (function() { + function object() {} + return function(proto) { + if (!isObject(proto)) { + return {}; + } + if (objectCreate) { + return objectCreate(proto); + } + object.prototype = proto; + var result = new object; + object.prototype = undefined; + return result; + }; + }()); + + /** + * The base constructor for creating `lodash` wrapper objects. + * + * @private + * @param {*} value The value to wrap. + * @param {boolean} [chainAll] Enable explicit method chain sequences. + */ + function LodashWrapper(value, chainAll) { + this.__wrapped__ = value; + this.__actions__ = []; + this.__chain__ = !!chainAll; + } + + LodashWrapper.prototype = baseCreate(lodash.prototype); + LodashWrapper.prototype.constructor = LodashWrapper; + + /*------------------------------------------------------------------------*/ + + /** + * Assigns `value` to `key` of `object` if the existing value is not equivalent + * using [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. + * + * @private + * @param {Object} object The object to modify. + * @param {string} key The key of the property to assign. + * @param {*} value The value to assign. + */ + function assignValue(object, key, value) { + var objValue = object[key]; + if (!(hasOwnProperty.call(object, key) && eq(objValue, value)) || + (value === undefined && !(key in object))) { + baseAssignValue(object, key, value); + } + } + + /** + * The base implementation of `assignValue` and `assignMergeValue` without + * value checks. + * + * @private + * @param {Object} object The object to modify. + * @param {string} key The key of the property to assign. + * @param {*} value The value to assign. + */ + function baseAssignValue(object, key, value) { + object[key] = value; + } + + /** + * The base implementation of `_.delay` and `_.defer` which accepts `args` + * to provide to `func`. + * + * @private + * @param {Function} func The function to delay. + * @param {number} wait The number of milliseconds to delay invocation. + * @param {Array} args The arguments to provide to `func`. + * @returns {number|Object} Returns the timer id or timeout object. + */ + function baseDelay(func, wait, args) { + if (typeof func != 'function') { + throw new TypeError(FUNC_ERROR_TEXT); + } + return setTimeout(function() { func.apply(undefined, args); }, wait); + } + + /** + * The base implementation of `_.forEach` without support for iteratee shorthands. + * + * @private + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} iteratee The function invoked per iteration. + * @returns {Array|Object} Returns `collection`. + */ + var baseEach = createBaseEach(baseForOwn); + + /** + * The base implementation of `_.every` without support for iteratee shorthands. + * + * @private + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} predicate The function invoked per iteration. + * @returns {boolean} Returns `true` if all elements pass the predicate check, + * else `false` + */ + function baseEvery(collection, predicate) { + var result = true; + baseEach(collection, function(value, index, collection) { + result = !!predicate(value, index, collection); + return result; + }); + return result; + } + + /** + * The base implementation of methods like `_.max` and `_.min` which accepts a + * `comparator` to determine the extremum value. + * + * @private + * @param {Array} array The array to iterate over. + * @param {Function} iteratee The iteratee invoked per iteration. + * @param {Function} comparator The comparator used to compare values. + * @returns {*} Returns the extremum value. + */ + function baseExtremum(array, iteratee, comparator) { + var index = -1, + length = array.length; + + while (++index < length) { + var value = array[index], + current = iteratee(value); + + if (current != null && (computed === undefined + ? (current === current && !false) + : comparator(current, computed) + )) { + var computed = current, + result = value; + } + } + return result; + } + + /** + * The base implementation of `_.filter` without support for iteratee shorthands. + * + * @private + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} predicate The function invoked per iteration. + * @returns {Array} Returns the new filtered array. + */ + function baseFilter(collection, predicate) { + var result = []; + baseEach(collection, function(value, index, collection) { + if (predicate(value, index, collection)) { + result.push(value); + } + }); + return result; + } + + /** + * The base implementation of `_.flatten` with support for restricting flattening. + * + * @private + * @param {Array} array The array to flatten. + * @param {number} depth The maximum recursion depth. + * @param {boolean} [predicate=isFlattenable] The function invoked per iteration. + * @param {boolean} [isStrict] Restrict to values that pass `predicate` checks. + * @param {Array} [result=[]] The initial result value. + * @returns {Array} Returns the new flattened array. + */ + function baseFlatten(array, depth, predicate, isStrict, result) { + var index = -1, + length = array.length; + + predicate || (predicate = isFlattenable); + result || (result = []); + + while (++index < length) { + var value = array[index]; + if (depth > 0 && predicate(value)) { + if (depth > 1) { + // Recursively flatten arrays (susceptible to call stack limits). + baseFlatten(value, depth - 1, predicate, isStrict, result); + } else { + arrayPush(result, value); + } + } else if (!isStrict) { + result[result.length] = value; + } + } + return result; + } + + /** + * The base implementation of `baseForOwn` which iterates over `object` + * properties returned by `keysFunc` and invokes `iteratee` for each property. + * Iteratee functions may exit iteration early by explicitly returning `false`. + * + * @private + * @param {Object} object The object to iterate over. + * @param {Function} iteratee The function invoked per iteration. + * @param {Function} keysFunc The function to get the keys of `object`. + * @returns {Object} Returns `object`. + */ + var baseFor = createBaseFor(); + + /** + * The base implementation of `_.forOwn` without support for iteratee shorthands. + * + * @private + * @param {Object} object The object to iterate over. + * @param {Function} iteratee The function invoked per iteration. + * @returns {Object} Returns `object`. + */ + function baseForOwn(object, iteratee) { + return object && baseFor(object, iteratee, keys); + } + + /** + * The base implementation of `_.functions` which creates an array of + * `object` function property names filtered from `props`. + * + * @private + * @param {Object} object The object to inspect. + * @param {Array} props The property names to filter. + * @returns {Array} Returns the function names. + */ + function baseFunctions(object, props) { + return baseFilter(props, function(key) { + return isFunction(object[key]); + }); + } + + /** + * The base implementation of `getTag` without fallbacks for buggy environments. + * + * @private + * @param {*} value The value to query. + * @returns {string} Returns the `toStringTag`. + */ + function baseGetTag(value) { + return objectToString(value); + } + + /** + * The base implementation of `_.gt` which doesn't coerce arguments. + * + * @private + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @returns {boolean} Returns `true` if `value` is greater than `other`, + * else `false`. + */ + function baseGt(value, other) { + return value > other; + } + + /** + * The base implementation of `_.isArguments`. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an `arguments` object, + */ + var baseIsArguments = noop; + + /** + * The base implementation of `_.isDate` without Node.js optimizations. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a date object, else `false`. + */ + function baseIsDate(value) { + return isObjectLike(value) && baseGetTag(value) == dateTag; + } + + /** + * The base implementation of `_.isEqual` which supports partial comparisons + * and tracks traversed objects. + * + * @private + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @param {boolean} bitmask The bitmask flags. + * 1 - Unordered comparison + * 2 - Partial comparison + * @param {Function} [customizer] The function to customize comparisons. + * @param {Object} [stack] Tracks traversed `value` and `other` objects. + * @returns {boolean} Returns `true` if the values are equivalent, else `false`. + */ + function baseIsEqual(value, other, bitmask, customizer, stack) { + if (value === other) { + return true; + } + if (value == null || other == null || (!isObjectLike(value) && !isObjectLike(other))) { + return value !== value && other !== other; + } + return baseIsEqualDeep(value, other, bitmask, customizer, baseIsEqual, stack); + } + + /** + * A specialized version of `baseIsEqual` for arrays and objects which performs + * deep comparisons and tracks traversed objects enabling objects with circular + * references to be compared. + * + * @private + * @param {Object} object The object to compare. + * @param {Object} other The other object to compare. + * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. + * @param {Function} customizer The function to customize comparisons. + * @param {Function} equalFunc The function to determine equivalents of values. + * @param {Object} [stack] Tracks traversed `object` and `other` objects. + * @returns {boolean} Returns `true` if the objects are equivalent, else `false`. + */ + function baseIsEqualDeep(object, other, bitmask, customizer, equalFunc, stack) { + var objIsArr = isArray(object), + othIsArr = isArray(other), + objTag = objIsArr ? arrayTag : baseGetTag(object), + othTag = othIsArr ? arrayTag : baseGetTag(other); + + objTag = objTag == argsTag ? objectTag : objTag; + othTag = othTag == argsTag ? objectTag : othTag; + + var objIsObj = objTag == objectTag, + othIsObj = othTag == objectTag, + isSameTag = objTag == othTag; + + stack || (stack = []); + var objStack = find(stack, function(entry) { + return entry[0] == object; + }); + var othStack = find(stack, function(entry) { + return entry[0] == other; + }); + if (objStack && othStack) { + return objStack[1] == other; + } + stack.push([object, other]); + stack.push([other, object]); + if (isSameTag && !objIsObj) { + var result = (objIsArr) + ? equalArrays(object, other, bitmask, customizer, equalFunc, stack) + : equalByTag(object, other, objTag, bitmask, customizer, equalFunc, stack); + stack.pop(); + return result; + } + if (!(bitmask & COMPARE_PARTIAL_FLAG)) { + var objIsWrapped = objIsObj && hasOwnProperty.call(object, '__wrapped__'), + othIsWrapped = othIsObj && hasOwnProperty.call(other, '__wrapped__'); + + if (objIsWrapped || othIsWrapped) { + var objUnwrapped = objIsWrapped ? object.value() : object, + othUnwrapped = othIsWrapped ? other.value() : other; + + var result = equalFunc(objUnwrapped, othUnwrapped, bitmask, customizer, stack); + stack.pop(); + return result; + } + } + if (!isSameTag) { + return false; + } + var result = equalObjects(object, other, bitmask, customizer, equalFunc, stack); + stack.pop(); + return result; + } + + /** + * The base implementation of `_.isRegExp` without Node.js optimizations. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a regexp, else `false`. + */ + function baseIsRegExp(value) { + return isObjectLike(value) && baseGetTag(value) == regexpTag; + } + + /** + * The base implementation of `_.iteratee`. + * + * @private + * @param {*} [value=_.identity] The value to convert to an iteratee. + * @returns {Function} Returns the iteratee. + */ + function baseIteratee(func) { + if (typeof func == 'function') { + return func; + } + if (func == null) { + return identity; + } + return (typeof func == 'object' ? baseMatches : baseProperty)(func); + } + + /** + * The base implementation of `_.lt` which doesn't coerce arguments. + * + * @private + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @returns {boolean} Returns `true` if `value` is less than `other`, + * else `false`. + */ + function baseLt(value, other) { + return value < other; + } + + /** + * The base implementation of `_.map` without support for iteratee shorthands. + * + * @private + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} iteratee The function invoked per iteration. + * @returns {Array} Returns the new mapped array. + */ + function baseMap(collection, iteratee) { + var index = -1, + result = isArrayLike(collection) ? Array(collection.length) : []; + + baseEach(collection, function(value, key, collection) { + result[++index] = iteratee(value, key, collection); + }); + return result; + } + + /** + * The base implementation of `_.matches` which doesn't clone `source`. + * + * @private + * @param {Object} source The object of property values to match. + * @returns {Function} Returns the new spec function. + */ + function baseMatches(source) { + var props = nativeKeys(source); + return function(object) { + var length = props.length; + if (object == null) { + return !length; + } + object = Object(object); + while (length--) { + var key = props[length]; + if (!(key in object && + baseIsEqual(source[key], object[key], COMPARE_PARTIAL_FLAG | COMPARE_UNORDERED_FLAG) + )) { + return false; + } + } + return true; + }; + } + + /** + * The base implementation of `_.pick` without support for individual + * property identifiers. + * + * @private + * @param {Object} object The source object. + * @param {string[]} paths The property paths to pick. + * @returns {Object} Returns the new object. + */ + function basePick(object, props) { + object = Object(object); + return reduce(props, function(result, key) { + if (key in object) { + result[key] = object[key]; + } + return result; + }, {}); + } + + /** + * The base implementation of `_.rest` which doesn't validate or coerce arguments. + * + * @private + * @param {Function} func The function to apply a rest parameter to. + * @param {number} [start=func.length-1] The start position of the rest parameter. + * @returns {Function} Returns the new function. + */ + function baseRest(func, start) { + return setToString(overRest(func, start, identity), func + ''); + } + + /** + * The base implementation of `_.slice` without an iteratee call guard. + * + * @private + * @param {Array} array The array to slice. + * @param {number} [start=0] The start position. + * @param {number} [end=array.length] The end position. + * @returns {Array} Returns the slice of `array`. + */ + function baseSlice(array, start, end) { + var index = -1, + length = array.length; + + if (start < 0) { + start = -start > length ? 0 : (length + start); + } + end = end > length ? length : end; + if (end < 0) { + end += length; + } + length = start > end ? 0 : ((end - start) >>> 0); + start >>>= 0; + + var result = Array(length); + while (++index < length) { + result[index] = array[index + start]; + } + return result; + } + + /** + * Copies the values of `source` to `array`. + * + * @private + * @param {Array} source The array to copy values from. + * @param {Array} [array=[]] The array to copy values to. + * @returns {Array} Returns `array`. + */ + function copyArray(source) { + return baseSlice(source, 0, source.length); + } + + /** + * The base implementation of `_.some` without support for iteratee shorthands. + * + * @private + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} predicate The function invoked per iteration. + * @returns {boolean} Returns `true` if any element passes the predicate check, + * else `false`. + */ + function baseSome(collection, predicate) { + var result; + + baseEach(collection, function(value, index, collection) { + result = predicate(value, index, collection); + return !result; + }); + return !!result; + } + + /** + * The base implementation of `wrapperValue` which returns the result of + * performing a sequence of actions on the unwrapped `value`, where each + * successive action is supplied the return value of the previous. + * + * @private + * @param {*} value The unwrapped value. + * @param {Array} actions Actions to perform to resolve the unwrapped value. + * @returns {*} Returns the resolved value. + */ + function baseWrapperValue(value, actions) { + var result = value; + return reduce(actions, function(result, action) { + return action.func.apply(action.thisArg, arrayPush([result], action.args)); + }, result); + } + + /** + * Compares values to sort them in ascending order. + * + * @private + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @returns {number} Returns the sort order indicator for `value`. + */ + function compareAscending(value, other) { + if (value !== other) { + var valIsDefined = value !== undefined, + valIsNull = value === null, + valIsReflexive = value === value, + valIsSymbol = false; + + var othIsDefined = other !== undefined, + othIsNull = other === null, + othIsReflexive = other === other, + othIsSymbol = false; + + if ((!othIsNull && !othIsSymbol && !valIsSymbol && value > other) || + (valIsSymbol && othIsDefined && othIsReflexive && !othIsNull && !othIsSymbol) || + (valIsNull && othIsDefined && othIsReflexive) || + (!valIsDefined && othIsReflexive) || + !valIsReflexive) { + return 1; + } + if ((!valIsNull && !valIsSymbol && !othIsSymbol && value < other) || + (othIsSymbol && valIsDefined && valIsReflexive && !valIsNull && !valIsSymbol) || + (othIsNull && valIsDefined && valIsReflexive) || + (!othIsDefined && valIsReflexive) || + !othIsReflexive) { + return -1; + } + } + return 0; + } + + /** + * Copies properties of `source` to `object`. + * + * @private + * @param {Object} source The object to copy properties from. + * @param {Array} props The property identifiers to copy. + * @param {Object} [object={}] The object to copy properties to. + * @param {Function} [customizer] The function to customize copied values. + * @returns {Object} Returns `object`. + */ + function copyObject(source, props, object, customizer) { + var isNew = !object; + object || (object = {}); + + var index = -1, + length = props.length; + + while (++index < length) { + var key = props[index]; + + var newValue = customizer + ? customizer(object[key], source[key], key, object, source) + : undefined; + + if (newValue === undefined) { + newValue = source[key]; + } + if (isNew) { + baseAssignValue(object, key, newValue); + } else { + assignValue(object, key, newValue); + } + } + return object; + } + + /** + * Creates a function like `_.assign`. + * + * @private + * @param {Function} assigner The function to assign values. + * @returns {Function} Returns the new assigner function. + */ + function createAssigner(assigner) { + return baseRest(function(object, sources) { + var index = -1, + length = sources.length, + customizer = length > 1 ? sources[length - 1] : undefined; + + customizer = (assigner.length > 3 && typeof customizer == 'function') + ? (length--, customizer) + : undefined; + + object = Object(object); + while (++index < length) { + var source = sources[index]; + if (source) { + assigner(object, source, index, customizer); + } + } + return object; + }); + } + + /** + * Creates a `baseEach` or `baseEachRight` function. + * + * @private + * @param {Function} eachFunc The function to iterate over a collection. + * @param {boolean} [fromRight] Specify iterating from right to left. + * @returns {Function} Returns the new base function. + */ + function createBaseEach(eachFunc, fromRight) { + return function(collection, iteratee) { + if (collection == null) { + return collection; + } + if (!isArrayLike(collection)) { + return eachFunc(collection, iteratee); + } + var length = collection.length, + index = fromRight ? length : -1, + iterable = Object(collection); + + while ((fromRight ? index-- : ++index < length)) { + if (iteratee(iterable[index], index, iterable) === false) { + break; + } + } + return collection; + }; + } + + /** + * Creates a base function for methods like `_.forIn` and `_.forOwn`. + * + * @private + * @param {boolean} [fromRight] Specify iterating from right to left. + * @returns {Function} Returns the new base function. + */ + function createBaseFor(fromRight) { + return function(object, iteratee, keysFunc) { + var index = -1, + iterable = Object(object), + props = keysFunc(object), + length = props.length; + + while (length--) { + var key = props[fromRight ? length : ++index]; + if (iteratee(iterable[key], key, iterable) === false) { + break; + } + } + return object; + }; + } + + /** + * Creates a function that produces an instance of `Ctor` regardless of + * whether it was invoked as part of a `new` expression or by `call` or `apply`. + * + * @private + * @param {Function} Ctor The constructor to wrap. + * @returns {Function} Returns the new wrapped function. + */ + function createCtor(Ctor) { + return function() { + // Use a `switch` statement to work with class constructors. See + // http://ecma-international.org/ecma-262/7.0/#sec-ecmascript-function-objects-call-thisargument-argumentslist + // for more details. + var args = arguments; + var thisBinding = baseCreate(Ctor.prototype), + result = Ctor.apply(thisBinding, args); + + // Mimic the constructor's `return` behavior. + // See https://es5.github.io/#x13.2.2 for more details. + return isObject(result) ? result : thisBinding; + }; + } + + /** + * Creates a `_.find` or `_.findLast` function. + * + * @private + * @param {Function} findIndexFunc The function to find the collection index. + * @returns {Function} Returns the new find function. + */ + function createFind(findIndexFunc) { + return function(collection, predicate, fromIndex) { + var iterable = Object(collection); + if (!isArrayLike(collection)) { + var iteratee = baseIteratee(predicate, 3); + collection = keys(collection); + predicate = function(key) { return iteratee(iterable[key], key, iterable); }; + } + var index = findIndexFunc(collection, predicate, fromIndex); + return index > -1 ? iterable[iteratee ? collection[index] : index] : undefined; + }; + } + + /** + * Creates a function that wraps `func` to invoke it with the `this` binding + * of `thisArg` and `partials` prepended to the arguments it receives. + * + * @private + * @param {Function} func The function to wrap. + * @param {number} bitmask The bitmask flags. See `createWrap` for more details. + * @param {*} thisArg The `this` binding of `func`. + * @param {Array} partials The arguments to prepend to those provided to + * the new function. + * @returns {Function} Returns the new wrapped function. + */ + function createPartial(func, bitmask, thisArg, partials) { + if (typeof func != 'function') { + throw new TypeError(FUNC_ERROR_TEXT); + } + var isBind = bitmask & WRAP_BIND_FLAG, + Ctor = createCtor(func); + + function wrapper() { + var argsIndex = -1, + argsLength = arguments.length, + leftIndex = -1, + leftLength = partials.length, + args = Array(leftLength + argsLength), + fn = (this && this !== root && this instanceof wrapper) ? Ctor : func; + + while (++leftIndex < leftLength) { + args[leftIndex] = partials[leftIndex]; + } + while (argsLength--) { + args[leftIndex++] = arguments[++argsIndex]; + } + return fn.apply(isBind ? thisArg : this, args); + } + return wrapper; + } + + /** + * A specialized version of `baseIsEqualDeep` for arrays with support for + * partial deep comparisons. + * + * @private + * @param {Array} array The array to compare. + * @param {Array} other The other array to compare. + * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. + * @param {Function} customizer The function to customize comparisons. + * @param {Function} equalFunc The function to determine equivalents of values. + * @param {Object} stack Tracks traversed `array` and `other` objects. + * @returns {boolean} Returns `true` if the arrays are equivalent, else `false`. + */ + function equalArrays(array, other, bitmask, customizer, equalFunc, stack) { + var isPartial = bitmask & COMPARE_PARTIAL_FLAG, + arrLength = array.length, + othLength = other.length; + + if (arrLength != othLength && !(isPartial && othLength > arrLength)) { + return false; + } + var index = -1, + result = true, + seen = (bitmask & COMPARE_UNORDERED_FLAG) ? [] : undefined; + + // Ignore non-index properties. + while (++index < arrLength) { + var arrValue = array[index], + othValue = other[index]; + + var compared; + if (compared !== undefined) { + if (compared) { + continue; + } + result = false; + break; + } + // Recursively compare arrays (susceptible to call stack limits). + if (seen) { + if (!baseSome(other, function(othValue, othIndex) { + if (!indexOf(seen, othIndex) && + (arrValue === othValue || equalFunc(arrValue, othValue, bitmask, customizer, stack))) { + return seen.push(othIndex); + } + })) { + result = false; + break; + } + } else if (!( + arrValue === othValue || + equalFunc(arrValue, othValue, bitmask, customizer, stack) + )) { + result = false; + break; + } + } + return result; + } + + /** + * A specialized version of `baseIsEqualDeep` for comparing objects of + * the same `toStringTag`. + * + * **Note:** This function only supports comparing values with tags of + * `Boolean`, `Date`, `Error`, `Number`, `RegExp`, or `String`. + * + * @private + * @param {Object} object The object to compare. + * @param {Object} other The other object to compare. + * @param {string} tag The `toStringTag` of the objects to compare. + * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. + * @param {Function} customizer The function to customize comparisons. + * @param {Function} equalFunc The function to determine equivalents of values. + * @param {Object} stack Tracks traversed `object` and `other` objects. + * @returns {boolean} Returns `true` if the objects are equivalent, else `false`. + */ + function equalByTag(object, other, tag, bitmask, customizer, equalFunc, stack) { + switch (tag) { + + case boolTag: + case dateTag: + case numberTag: + // Coerce booleans to `1` or `0` and dates to milliseconds. + // Invalid dates are coerced to `NaN`. + return eq(+object, +other); + + case errorTag: + return object.name == other.name && object.message == other.message; + + case regexpTag: + case stringTag: + // Coerce regexes to strings and treat strings, primitives and objects, + // as equal. See http://www.ecma-international.org/ecma-262/7.0/#sec-regexp.prototype.tostring + // for more details. + return object == (other + ''); + + } + return false; + } + + /** + * A specialized version of `baseIsEqualDeep` for objects with support for + * partial deep comparisons. + * + * @private + * @param {Object} object The object to compare. + * @param {Object} other The other object to compare. + * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. + * @param {Function} customizer The function to customize comparisons. + * @param {Function} equalFunc The function to determine equivalents of values. + * @param {Object} stack Tracks traversed `object` and `other` objects. + * @returns {boolean} Returns `true` if the objects are equivalent, else `false`. + */ + function equalObjects(object, other, bitmask, customizer, equalFunc, stack) { + var isPartial = bitmask & COMPARE_PARTIAL_FLAG, + objProps = keys(object), + objLength = objProps.length, + othProps = keys(other), + othLength = othProps.length; + + if (objLength != othLength && !isPartial) { + return false; + } + var index = objLength; + while (index--) { + var key = objProps[index]; + if (!(isPartial ? key in other : hasOwnProperty.call(other, key))) { + return false; + } + } + var result = true; + + var skipCtor = isPartial; + while (++index < objLength) { + key = objProps[index]; + var objValue = object[key], + othValue = other[key]; + + var compared; + // Recursively compare objects (susceptible to call stack limits). + if (!(compared === undefined + ? (objValue === othValue || equalFunc(objValue, othValue, bitmask, customizer, stack)) + : compared + )) { + result = false; + break; + } + skipCtor || (skipCtor = key == 'constructor'); + } + if (result && !skipCtor) { + var objCtor = object.constructor, + othCtor = other.constructor; + + // Non `Object` object instances with different constructors are not equal. + if (objCtor != othCtor && + ('constructor' in object && 'constructor' in other) && + !(typeof objCtor == 'function' && objCtor instanceof objCtor && + typeof othCtor == 'function' && othCtor instanceof othCtor)) { + result = false; + } + } + return result; + } + + /** + * A specialized version of `baseRest` which flattens the rest array. + * + * @private + * @param {Function} func The function to apply a rest parameter to. + * @returns {Function} Returns the new function. + */ + function flatRest(func) { + return setToString(overRest(func, undefined, flatten), func + ''); + } + + /** + * Checks if `value` is a flattenable `arguments` object or array. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is flattenable, else `false`. + */ + function isFlattenable(value) { + return isArray(value) || isArguments(value); + } + + /** + * Checks if `value` is a valid array-like index. + * + * @private + * @param {*} value The value to check. + * @param {number} [length=MAX_SAFE_INTEGER] The upper bounds of a valid index. + * @returns {boolean} Returns `true` if `value` is a valid index, else `false`. + */ + function isIndex(value, length) { + var type = typeof value; + length = length == null ? MAX_SAFE_INTEGER : length; + + return !!length && + (type == 'number' || + (type != 'symbol' && reIsUint.test(value))) && + (value > -1 && value % 1 == 0 && value < length); + } + + /** + * Checks if the given arguments are from an iteratee call. + * + * @private + * @param {*} value The potential iteratee value argument. + * @param {*} index The potential iteratee index or key argument. + * @param {*} object The potential iteratee object argument. + * @returns {boolean} Returns `true` if the arguments are from an iteratee call, + * else `false`. + */ + function isIterateeCall(value, index, object) { + if (!isObject(object)) { + return false; + } + var type = typeof index; + if (type == 'number' + ? (isArrayLike(object) && isIndex(index, object.length)) + : (type == 'string' && index in object) + ) { + return eq(object[index], value); + } + return false; + } + + /** + * This function is like + * [`Object.keys`](http://ecma-international.org/ecma-262/7.0/#sec-object.keys) + * except that it includes inherited enumerable properties. + * + * @private + * @param {Object} object The object to query. + * @returns {Array} Returns the array of property names. + */ + function nativeKeysIn(object) { + var result = []; + if (object != null) { + for (var key in Object(object)) { + result.push(key); + } + } + return result; + } + + /** + * Converts `value` to a string using `Object.prototype.toString`. + * + * @private + * @param {*} value The value to convert. + * @returns {string} Returns the converted string. + */ + function objectToString(value) { + return nativeObjectToString.call(value); + } + + /** + * A specialized version of `baseRest` which transforms the rest array. + * + * @private + * @param {Function} func The function to apply a rest parameter to. + * @param {number} [start=func.length-1] The start position of the rest parameter. + * @param {Function} transform The rest array transform. + * @returns {Function} Returns the new function. + */ + function overRest(func, start, transform) { + start = nativeMax(start === undefined ? (func.length - 1) : start, 0); + return function() { + var args = arguments, + index = -1, + length = nativeMax(args.length - start, 0), + array = Array(length); + + while (++index < length) { + array[index] = args[start + index]; + } + index = -1; + var otherArgs = Array(start + 1); + while (++index < start) { + otherArgs[index] = args[index]; + } + otherArgs[start] = transform(array); + return func.apply(this, otherArgs); + }; + } + + /** + * Sets the `toString` method of `func` to return `string`. + * + * @private + * @param {Function} func The function to modify. + * @param {Function} string The `toString` result. + * @returns {Function} Returns `func`. + */ + var setToString = identity; + + /*------------------------------------------------------------------------*/ + + /** + * Creates an array with all falsey values removed. The values `false`, `null`, + * `0`, `""`, `undefined`, and `NaN` are falsey. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to compact. + * @returns {Array} Returns the new array of filtered values. + * @example + * + * _.compact([0, 1, false, 2, '', 3]); + * // => [1, 2, 3] + */ + function compact(array) { + return baseFilter(array, Boolean); + } + + /** + * Creates a new array concatenating `array` with any additional arrays + * and/or values. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to concatenate. + * @param {...*} [values] The values to concatenate. + * @returns {Array} Returns the new concatenated array. + * @example + * + * var array = [1]; + * var other = _.concat(array, 2, [3], [[4]]); + * + * console.log(other); + * // => [1, 2, 3, [4]] + * + * console.log(array); + * // => [1] + */ + function concat() { + var length = arguments.length; + if (!length) { + return []; + } + var args = Array(length - 1), + array = arguments[0], + index = length; + + while (index--) { + args[index - 1] = arguments[index]; + } + return arrayPush(isArray(array) ? copyArray(array) : [array], baseFlatten(args, 1)); + } + + /** + * This method is like `_.find` except that it returns the index of the first + * element `predicate` returns truthy for instead of the element itself. + * + * @static + * @memberOf _ + * @since 1.1.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @param {number} [fromIndex=0] The index to search from. + * @returns {number} Returns the index of the found element, else `-1`. + * @example + * + * var users = [ + * { 'user': 'barney', 'active': false }, + * { 'user': 'fred', 'active': false }, + * { 'user': 'pebbles', 'active': true } + * ]; + * + * _.findIndex(users, function(o) { return o.user == 'barney'; }); + * // => 0 + * + * // The `_.matches` iteratee shorthand. + * _.findIndex(users, { 'user': 'fred', 'active': false }); + * // => 1 + * + * // The `_.matchesProperty` iteratee shorthand. + * _.findIndex(users, ['active', false]); + * // => 0 + * + * // The `_.property` iteratee shorthand. + * _.findIndex(users, 'active'); + * // => 2 + */ + function findIndex(array, predicate, fromIndex) { + var length = array == null ? 0 : array.length; + if (!length) { + return -1; + } + var index = fromIndex == null ? 0 : toInteger(fromIndex); + if (index < 0) { + index = nativeMax(length + index, 0); + } + return baseFindIndex(array, baseIteratee(predicate, 3), index); + } + + /** + * Flattens `array` a single level deep. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to flatten. + * @returns {Array} Returns the new flattened array. + * @example + * + * _.flatten([1, [2, [3, [4]], 5]]); + * // => [1, 2, [3, [4]], 5] + */ + function flatten(array) { + var length = array == null ? 0 : array.length; + return length ? baseFlatten(array, 1) : []; + } + + /** + * Recursively flattens `array`. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to flatten. + * @returns {Array} Returns the new flattened array. + * @example + * + * _.flattenDeep([1, [2, [3, [4]], 5]]); + * // => [1, 2, 3, 4, 5] + */ + function flattenDeep(array) { + var length = array == null ? 0 : array.length; + return length ? baseFlatten(array, INFINITY) : []; + } + + /** + * Gets the first element of `array`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @alias first + * @category Array + * @param {Array} array The array to query. + * @returns {*} Returns the first element of `array`. + * @example + * + * _.head([1, 2, 3]); + * // => 1 + * + * _.head([]); + * // => undefined + */ + function head(array) { + return (array && array.length) ? array[0] : undefined; + } + + /** + * Gets the index at which the first occurrence of `value` is found in `array` + * using [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. If `fromIndex` is negative, it's used as the + * offset from the end of `array`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @param {number} [fromIndex=0] The index to search from. + * @returns {number} Returns the index of the matched value, else `-1`. + * @example + * + * _.indexOf([1, 2, 1, 2], 2); + * // => 1 + * + * // Search from the `fromIndex`. + * _.indexOf([1, 2, 1, 2], 2, 2); + * // => 3 + */ + function indexOf(array, value, fromIndex) { + var length = array == null ? 0 : array.length; + if (typeof fromIndex == 'number') { + fromIndex = fromIndex < 0 ? nativeMax(length + fromIndex, 0) : fromIndex; + } else { + fromIndex = 0; + } + var index = (fromIndex || 0) - 1, + isReflexive = value === value; + + while (++index < length) { + var other = array[index]; + if ((isReflexive ? other === value : other !== other)) { + return index; + } + } + return -1; + } + + /** + * Gets the last element of `array`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to query. + * @returns {*} Returns the last element of `array`. + * @example + * + * _.last([1, 2, 3]); + * // => 3 + */ + function last(array) { + var length = array == null ? 0 : array.length; + return length ? array[length - 1] : undefined; + } + + /** + * Creates a slice of `array` from `start` up to, but not including, `end`. + * + * **Note:** This method is used instead of + * [`Array#slice`](https://mdn.io/Array/slice) to ensure dense arrays are + * returned. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to slice. + * @param {number} [start=0] The start position. + * @param {number} [end=array.length] The end position. + * @returns {Array} Returns the slice of `array`. + */ + function slice(array, start, end) { + var length = array == null ? 0 : array.length; + start = start == null ? 0 : +start; + end = end === undefined ? length : +end; + return length ? baseSlice(array, start, end) : []; + } + + /*------------------------------------------------------------------------*/ + + /** + * Creates a `lodash` wrapper instance that wraps `value` with explicit method + * chain sequences enabled. The result of such sequences must be unwrapped + * with `_#value`. + * + * @static + * @memberOf _ + * @since 1.3.0 + * @category Seq + * @param {*} value The value to wrap. + * @returns {Object} Returns the new `lodash` wrapper instance. + * @example + * + * var users = [ + * { 'user': 'barney', 'age': 36 }, + * { 'user': 'fred', 'age': 40 }, + * { 'user': 'pebbles', 'age': 1 } + * ]; + * + * var youngest = _ + * .chain(users) + * .sortBy('age') + * .map(function(o) { + * return o.user + ' is ' + o.age; + * }) + * .head() + * .value(); + * // => 'pebbles is 1' + */ + function chain(value) { + var result = lodash(value); + result.__chain__ = true; + return result; + } + + /** + * This method invokes `interceptor` and returns `value`. The interceptor + * is invoked with one argument; (value). The purpose of this method is to + * "tap into" a method chain sequence in order to modify intermediate results. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Seq + * @param {*} value The value to provide to `interceptor`. + * @param {Function} interceptor The function to invoke. + * @returns {*} Returns `value`. + * @example + * + * _([1, 2, 3]) + * .tap(function(array) { + * // Mutate input array. + * array.pop(); + * }) + * .reverse() + * .value(); + * // => [2, 1] + */ + function tap(value, interceptor) { + interceptor(value); + return value; + } + + /** + * This method is like `_.tap` except that it returns the result of `interceptor`. + * The purpose of this method is to "pass thru" values replacing intermediate + * results in a method chain sequence. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Seq + * @param {*} value The value to provide to `interceptor`. + * @param {Function} interceptor The function to invoke. + * @returns {*} Returns the result of `interceptor`. + * @example + * + * _(' abc ') + * .chain() + * .trim() + * .thru(function(value) { + * return [value]; + * }) + * .value(); + * // => ['abc'] + */ + function thru(value, interceptor) { + return interceptor(value); + } + + /** + * Creates a `lodash` wrapper instance with explicit method chain sequences enabled. + * + * @name chain + * @memberOf _ + * @since 0.1.0 + * @category Seq + * @returns {Object} Returns the new `lodash` wrapper instance. + * @example + * + * var users = [ + * { 'user': 'barney', 'age': 36 }, + * { 'user': 'fred', 'age': 40 } + * ]; + * + * // A sequence without explicit chaining. + * _(users).head(); + * // => { 'user': 'barney', 'age': 36 } + * + * // A sequence with explicit chaining. + * _(users) + * .chain() + * .head() + * .pick('user') + * .value(); + * // => { 'user': 'barney' } + */ + function wrapperChain() { + return chain(this); + } + + /** + * Executes the chain sequence to resolve the unwrapped value. + * + * @name value + * @memberOf _ + * @since 0.1.0 + * @alias toJSON, valueOf + * @category Seq + * @returns {*} Returns the resolved unwrapped value. + * @example + * + * _([1, 2, 3]).value(); + * // => [1, 2, 3] + */ + function wrapperValue() { + return baseWrapperValue(this.__wrapped__, this.__actions__); + } + + /*------------------------------------------------------------------------*/ + + /** + * Checks if `predicate` returns truthy for **all** elements of `collection`. + * Iteration is stopped once `predicate` returns falsey. The predicate is + * invoked with three arguments: (value, index|key, collection). + * + * **Note:** This method returns `true` for + * [empty collections](https://en.wikipedia.org/wiki/Empty_set) because + * [everything is true](https://en.wikipedia.org/wiki/Vacuous_truth) of + * elements of empty collections. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Collection + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. + * @returns {boolean} Returns `true` if all elements pass the predicate check, + * else `false`. + * @example + * + * _.every([true, 1, null, 'yes'], Boolean); + * // => false + * + * var users = [ + * { 'user': 'barney', 'age': 36, 'active': false }, + * { 'user': 'fred', 'age': 40, 'active': false } + * ]; + * + * // The `_.matches` iteratee shorthand. + * _.every(users, { 'user': 'barney', 'active': false }); + * // => false + * + * // The `_.matchesProperty` iteratee shorthand. + * _.every(users, ['active', false]); + * // => true + * + * // The `_.property` iteratee shorthand. + * _.every(users, 'active'); + * // => false + */ + function every(collection, predicate, guard) { + predicate = guard ? undefined : predicate; + return baseEvery(collection, baseIteratee(predicate)); + } + + /** + * Iterates over elements of `collection`, returning an array of all elements + * `predicate` returns truthy for. The predicate is invoked with three + * arguments: (value, index|key, collection). + * + * **Note:** Unlike `_.remove`, this method returns a new array. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Collection + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @returns {Array} Returns the new filtered array. + * @see _.reject + * @example + * + * var users = [ + * { 'user': 'barney', 'age': 36, 'active': true }, + * { 'user': 'fred', 'age': 40, 'active': false } + * ]; + * + * _.filter(users, function(o) { return !o.active; }); + * // => objects for ['fred'] + * + * // The `_.matches` iteratee shorthand. + * _.filter(users, { 'age': 36, 'active': true }); + * // => objects for ['barney'] + * + * // The `_.matchesProperty` iteratee shorthand. + * _.filter(users, ['active', false]); + * // => objects for ['fred'] + * + * // The `_.property` iteratee shorthand. + * _.filter(users, 'active'); + * // => objects for ['barney'] + */ + function filter(collection, predicate) { + return baseFilter(collection, baseIteratee(predicate)); + } + + /** + * Iterates over elements of `collection`, returning the first element + * `predicate` returns truthy for. The predicate is invoked with three + * arguments: (value, index|key, collection). + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Collection + * @param {Array|Object} collection The collection to inspect. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @param {number} [fromIndex=0] The index to search from. + * @returns {*} Returns the matched element, else `undefined`. + * @example + * + * var users = [ + * { 'user': 'barney', 'age': 36, 'active': true }, + * { 'user': 'fred', 'age': 40, 'active': false }, + * { 'user': 'pebbles', 'age': 1, 'active': true } + * ]; + * + * _.find(users, function(o) { return o.age < 40; }); + * // => object for 'barney' + * + * // The `_.matches` iteratee shorthand. + * _.find(users, { 'age': 1, 'active': true }); + * // => object for 'pebbles' + * + * // The `_.matchesProperty` iteratee shorthand. + * _.find(users, ['active', false]); + * // => object for 'fred' + * + * // The `_.property` iteratee shorthand. + * _.find(users, 'active'); + * // => object for 'barney' + */ + var find = createFind(findIndex); + + /** + * Iterates over elements of `collection` and invokes `iteratee` for each element. + * The iteratee is invoked with three arguments: (value, index|key, collection). + * Iteratee functions may exit iteration early by explicitly returning `false`. + * + * **Note:** As with other "Collections" methods, objects with a "length" + * property are iterated like arrays. To avoid this behavior use `_.forIn` + * or `_.forOwn` for object iteration. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @alias each + * @category Collection + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} [iteratee=_.identity] The function invoked per iteration. + * @returns {Array|Object} Returns `collection`. + * @see _.forEachRight + * @example + * + * _.forEach([1, 2], function(value) { + * console.log(value); + * }); + * // => Logs `1` then `2`. + * + * _.forEach({ 'a': 1, 'b': 2 }, function(value, key) { + * console.log(key); + * }); + * // => Logs 'a' then 'b' (iteration order is not guaranteed). + */ + function forEach(collection, iteratee) { + return baseEach(collection, baseIteratee(iteratee)); + } + + /** + * Creates an array of values by running each element in `collection` thru + * `iteratee`. The iteratee is invoked with three arguments: + * (value, index|key, collection). + * + * Many lodash methods are guarded to work as iteratees for methods like + * `_.every`, `_.filter`, `_.map`, `_.mapValues`, `_.reject`, and `_.some`. + * + * The guarded methods are: + * `ary`, `chunk`, `curry`, `curryRight`, `drop`, `dropRight`, `every`, + * `fill`, `invert`, `parseInt`, `random`, `range`, `rangeRight`, `repeat`, + * `sampleSize`, `slice`, `some`, `sortBy`, `split`, `take`, `takeRight`, + * `template`, `trim`, `trimEnd`, `trimStart`, and `words` + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Collection + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} [iteratee=_.identity] The function invoked per iteration. + * @returns {Array} Returns the new mapped array. + * @example + * + * function square(n) { + * return n * n; + * } + * + * _.map([4, 8], square); + * // => [16, 64] + * + * _.map({ 'a': 4, 'b': 8 }, square); + * // => [16, 64] (iteration order is not guaranteed) + * + * var users = [ + * { 'user': 'barney' }, + * { 'user': 'fred' } + * ]; + * + * // The `_.property` iteratee shorthand. + * _.map(users, 'user'); + * // => ['barney', 'fred'] + */ + function map(collection, iteratee) { + return baseMap(collection, baseIteratee(iteratee)); + } + + /** + * Reduces `collection` to a value which is the accumulated result of running + * each element in `collection` thru `iteratee`, where each successive + * invocation is supplied the return value of the previous. If `accumulator` + * is not given, the first element of `collection` is used as the initial + * value. The iteratee is invoked with four arguments: + * (accumulator, value, index|key, collection). + * + * Many lodash methods are guarded to work as iteratees for methods like + * `_.reduce`, `_.reduceRight`, and `_.transform`. + * + * The guarded methods are: + * `assign`, `defaults`, `defaultsDeep`, `includes`, `merge`, `orderBy`, + * and `sortBy` + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Collection + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} [iteratee=_.identity] The function invoked per iteration. + * @param {*} [accumulator] The initial value. + * @returns {*} Returns the accumulated value. + * @see _.reduceRight + * @example + * + * _.reduce([1, 2], function(sum, n) { + * return sum + n; + * }, 0); + * // => 3 + * + * _.reduce({ 'a': 1, 'b': 2, 'c': 1 }, function(result, value, key) { + * (result[value] || (result[value] = [])).push(key); + * return result; + * }, {}); + * // => { '1': ['a', 'c'], '2': ['b'] } (iteration order is not guaranteed) + */ + function reduce(collection, iteratee, accumulator) { + return baseReduce(collection, baseIteratee(iteratee), accumulator, arguments.length < 3, baseEach); + } + + /** + * Gets the size of `collection` by returning its length for array-like + * values or the number of own enumerable string keyed properties for objects. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Collection + * @param {Array|Object|string} collection The collection to inspect. + * @returns {number} Returns the collection size. + * @example + * + * _.size([1, 2, 3]); + * // => 3 + * + * _.size({ 'a': 1, 'b': 2 }); + * // => 2 + * + * _.size('pebbles'); + * // => 7 + */ + function size(collection) { + if (collection == null) { + return 0; + } + collection = isArrayLike(collection) ? collection : nativeKeys(collection); + return collection.length; + } + + /** + * Checks if `predicate` returns truthy for **any** element of `collection`. + * Iteration is stopped once `predicate` returns truthy. The predicate is + * invoked with three arguments: (value, index|key, collection). + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Collection + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. + * @returns {boolean} Returns `true` if any element passes the predicate check, + * else `false`. + * @example + * + * _.some([null, 0, 'yes', false], Boolean); + * // => true + * + * var users = [ + * { 'user': 'barney', 'active': true }, + * { 'user': 'fred', 'active': false } + * ]; + * + * // The `_.matches` iteratee shorthand. + * _.some(users, { 'user': 'barney', 'active': false }); + * // => false + * + * // The `_.matchesProperty` iteratee shorthand. + * _.some(users, ['active', false]); + * // => true + * + * // The `_.property` iteratee shorthand. + * _.some(users, 'active'); + * // => true + */ + function some(collection, predicate, guard) { + predicate = guard ? undefined : predicate; + return baseSome(collection, baseIteratee(predicate)); + } + + /** + * Creates an array of elements, sorted in ascending order by the results of + * running each element in a collection thru each iteratee. This method + * performs a stable sort, that is, it preserves the original sort order of + * equal elements. The iteratees are invoked with one argument: (value). + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Collection + * @param {Array|Object} collection The collection to iterate over. + * @param {...(Function|Function[])} [iteratees=[_.identity]] + * The iteratees to sort by. + * @returns {Array} Returns the new sorted array. + * @example + * + * var users = [ + * { 'user': 'fred', 'age': 48 }, + * { 'user': 'barney', 'age': 36 }, + * { 'user': 'fred', 'age': 40 }, + * { 'user': 'barney', 'age': 34 } + * ]; + * + * _.sortBy(users, [function(o) { return o.user; }]); + * // => objects for [['barney', 36], ['barney', 34], ['fred', 48], ['fred', 40]] + * + * _.sortBy(users, ['user', 'age']); + * // => objects for [['barney', 34], ['barney', 36], ['fred', 40], ['fred', 48]] + */ + function sortBy(collection, iteratee) { + var index = 0; + iteratee = baseIteratee(iteratee); + + return baseMap(baseMap(collection, function(value, key, collection) { + return { 'value': value, 'index': index++, 'criteria': iteratee(value, key, collection) }; + }).sort(function(object, other) { + return compareAscending(object.criteria, other.criteria) || (object.index - other.index); + }), baseProperty('value')); + } + + /*------------------------------------------------------------------------*/ + + /** + * Creates a function that invokes `func`, with the `this` binding and arguments + * of the created function, while it's called less than `n` times. Subsequent + * calls to the created function return the result of the last `func` invocation. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Function + * @param {number} n The number of calls at which `func` is no longer invoked. + * @param {Function} func The function to restrict. + * @returns {Function} Returns the new restricted function. + * @example + * + * jQuery(element).on('click', _.before(5, addContactToList)); + * // => Allows adding up to 4 contacts to the list. + */ + function before(n, func) { + var result; + if (typeof func != 'function') { + throw new TypeError(FUNC_ERROR_TEXT); + } + n = toInteger(n); + return function() { + if (--n > 0) { + result = func.apply(this, arguments); + } + if (n <= 1) { + func = undefined; + } + return result; + }; + } + + /** + * Creates a function that invokes `func` with the `this` binding of `thisArg` + * and `partials` prepended to the arguments it receives. + * + * The `_.bind.placeholder` value, which defaults to `_` in monolithic builds, + * may be used as a placeholder for partially applied arguments. + * + * **Note:** Unlike native `Function#bind`, this method doesn't set the "length" + * property of bound functions. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Function + * @param {Function} func The function to bind. + * @param {*} thisArg The `this` binding of `func`. + * @param {...*} [partials] The arguments to be partially applied. + * @returns {Function} Returns the new bound function. + * @example + * + * function greet(greeting, punctuation) { + * return greeting + ' ' + this.user + punctuation; + * } + * + * var object = { 'user': 'fred' }; + * + * var bound = _.bind(greet, object, 'hi'); + * bound('!'); + * // => 'hi fred!' + * + * // Bound with placeholders. + * var bound = _.bind(greet, object, _, '!'); + * bound('hi'); + * // => 'hi fred!' + */ + var bind = baseRest(function(func, thisArg, partials) { + return createPartial(func, WRAP_BIND_FLAG | WRAP_PARTIAL_FLAG, thisArg, partials); + }); + + /** + * Defers invoking the `func` until the current call stack has cleared. Any + * additional arguments are provided to `func` when it's invoked. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Function + * @param {Function} func The function to defer. + * @param {...*} [args] The arguments to invoke `func` with. + * @returns {number} Returns the timer id. + * @example + * + * _.defer(function(text) { + * console.log(text); + * }, 'deferred'); + * // => Logs 'deferred' after one millisecond. + */ + var defer = baseRest(function(func, args) { + return baseDelay(func, 1, args); + }); + + /** + * Invokes `func` after `wait` milliseconds. Any additional arguments are + * provided to `func` when it's invoked. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Function + * @param {Function} func The function to delay. + * @param {number} wait The number of milliseconds to delay invocation. + * @param {...*} [args] The arguments to invoke `func` with. + * @returns {number} Returns the timer id. + * @example + * + * _.delay(function(text) { + * console.log(text); + * }, 1000, 'later'); + * // => Logs 'later' after one second. + */ + var delay = baseRest(function(func, wait, args) { + return baseDelay(func, toNumber(wait) || 0, args); + }); + + /** + * Creates a function that negates the result of the predicate `func`. The + * `func` predicate is invoked with the `this` binding and arguments of the + * created function. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Function + * @param {Function} predicate The predicate to negate. + * @returns {Function} Returns the new negated function. + * @example + * + * function isEven(n) { + * return n % 2 == 0; + * } + * + * _.filter([1, 2, 3, 4, 5, 6], _.negate(isEven)); + * // => [1, 3, 5] + */ + function negate(predicate) { + if (typeof predicate != 'function') { + throw new TypeError(FUNC_ERROR_TEXT); + } + return function() { + var args = arguments; + return !predicate.apply(this, args); + }; + } + + /** + * Creates a function that is restricted to invoking `func` once. Repeat calls + * to the function return the value of the first invocation. The `func` is + * invoked with the `this` binding and arguments of the created function. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Function + * @param {Function} func The function to restrict. + * @returns {Function} Returns the new restricted function. + * @example + * + * var initialize = _.once(createApplication); + * initialize(); + * initialize(); + * // => `createApplication` is invoked once + */ + function once(func) { + return before(2, func); + } + + /*------------------------------------------------------------------------*/ + + /** + * Creates a shallow clone of `value`. + * + * **Note:** This method is loosely based on the + * [structured clone algorithm](https://mdn.io/Structured_clone_algorithm) + * and supports cloning arrays, array buffers, booleans, date objects, maps, + * numbers, `Object` objects, regexes, sets, strings, symbols, and typed + * arrays. The own enumerable properties of `arguments` objects are cloned + * as plain objects. An empty object is returned for uncloneable values such + * as error objects, functions, DOM nodes, and WeakMaps. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to clone. + * @returns {*} Returns the cloned value. + * @see _.cloneDeep + * @example + * + * var objects = [{ 'a': 1 }, { 'b': 2 }]; + * + * var shallow = _.clone(objects); + * console.log(shallow[0] === objects[0]); + * // => true + */ + function clone(value) { + if (!isObject(value)) { + return value; + } + return isArray(value) ? copyArray(value) : copyObject(value, nativeKeys(value)); + } + + /** + * Performs a + * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * comparison between two values to determine if they are equivalent. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @returns {boolean} Returns `true` if the values are equivalent, else `false`. + * @example + * + * var object = { 'a': 1 }; + * var other = { 'a': 1 }; + * + * _.eq(object, object); + * // => true + * + * _.eq(object, other); + * // => false + * + * _.eq('a', 'a'); + * // => true + * + * _.eq('a', Object('a')); + * // => false + * + * _.eq(NaN, NaN); + * // => true + */ + function eq(value, other) { + return value === other || (value !== value && other !== other); + } + + /** + * Checks if `value` is likely an `arguments` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an `arguments` object, + * else `false`. + * @example + * + * _.isArguments(function() { return arguments; }()); + * // => true + * + * _.isArguments([1, 2, 3]); + * // => false + */ + var isArguments = baseIsArguments(function() { return arguments; }()) ? baseIsArguments : function(value) { + return isObjectLike(value) && hasOwnProperty.call(value, 'callee') && + !propertyIsEnumerable.call(value, 'callee'); + }; + + /** + * Checks if `value` is classified as an `Array` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an array, else `false`. + * @example + * + * _.isArray([1, 2, 3]); + * // => true + * + * _.isArray(document.body.children); + * // => false + * + * _.isArray('abc'); + * // => false + * + * _.isArray(_.noop); + * // => false + */ + var isArray = Array.isArray; + + /** + * Checks if `value` is array-like. A value is considered array-like if it's + * not a function and has a `value.length` that's an integer greater than or + * equal to `0` and less than or equal to `Number.MAX_SAFE_INTEGER`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is array-like, else `false`. + * @example + * + * _.isArrayLike([1, 2, 3]); + * // => true + * + * _.isArrayLike(document.body.children); + * // => true + * + * _.isArrayLike('abc'); + * // => true + * + * _.isArrayLike(_.noop); + * // => false + */ + function isArrayLike(value) { + return value != null && isLength(value.length) && !isFunction(value); + } + + /** + * Checks if `value` is classified as a boolean primitive or object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a boolean, else `false`. + * @example + * + * _.isBoolean(false); + * // => true + * + * _.isBoolean(null); + * // => false + */ + function isBoolean(value) { + return value === true || value === false || + (isObjectLike(value) && baseGetTag(value) == boolTag); + } + + /** + * Checks if `value` is classified as a `Date` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a date object, else `false`. + * @example + * + * _.isDate(new Date); + * // => true + * + * _.isDate('Mon April 23 2012'); + * // => false + */ + var isDate = baseIsDate; + + /** + * Checks if `value` is an empty object, collection, map, or set. + * + * Objects are considered empty if they have no own enumerable string keyed + * properties. + * + * Array-like values such as `arguments` objects, arrays, buffers, strings, or + * jQuery-like collections are considered empty if they have a `length` of `0`. + * Similarly, maps and sets are considered empty if they have a `size` of `0`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is empty, else `false`. + * @example + * + * _.isEmpty(null); + * // => true + * + * _.isEmpty(true); + * // => true + * + * _.isEmpty(1); + * // => true + * + * _.isEmpty([1, 2, 3]); + * // => false + * + * _.isEmpty({ 'a': 1 }); + * // => false + */ + function isEmpty(value) { + if (isArrayLike(value) && + (isArray(value) || isString(value) || + isFunction(value.splice) || isArguments(value))) { + return !value.length; + } + return !nativeKeys(value).length; + } + + /** + * Performs a deep comparison between two values to determine if they are + * equivalent. + * + * **Note:** This method supports comparing arrays, array buffers, booleans, + * date objects, error objects, maps, numbers, `Object` objects, regexes, + * sets, strings, symbols, and typed arrays. `Object` objects are compared + * by their own, not inherited, enumerable properties. Functions and DOM + * nodes are compared by strict equality, i.e. `===`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @returns {boolean} Returns `true` if the values are equivalent, else `false`. + * @example + * + * var object = { 'a': 1 }; + * var other = { 'a': 1 }; + * + * _.isEqual(object, other); + * // => true + * + * object === other; + * // => false + */ + function isEqual(value, other) { + return baseIsEqual(value, other); + } + + /** + * Checks if `value` is a finite primitive number. + * + * **Note:** This method is based on + * [`Number.isFinite`](https://mdn.io/Number/isFinite). + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a finite number, else `false`. + * @example + * + * _.isFinite(3); + * // => true + * + * _.isFinite(Number.MIN_VALUE); + * // => true + * + * _.isFinite(Infinity); + * // => false + * + * _.isFinite('3'); + * // => false + */ + function isFinite(value) { + return typeof value == 'number' && nativeIsFinite(value); + } + + /** + * Checks if `value` is classified as a `Function` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a function, else `false`. + * @example + * + * _.isFunction(_); + * // => true + * + * _.isFunction(/abc/); + * // => false + */ + function isFunction(value) { + if (!isObject(value)) { + return false; + } + // The use of `Object#toString` avoids issues with the `typeof` operator + // in Safari 9 which returns 'object' for typed arrays and other constructors. + var tag = baseGetTag(value); + return tag == funcTag || tag == genTag || tag == asyncTag || tag == proxyTag; + } + + /** + * Checks if `value` is a valid array-like length. + * + * **Note:** This method is loosely based on + * [`ToLength`](http://ecma-international.org/ecma-262/7.0/#sec-tolength). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a valid length, else `false`. + * @example + * + * _.isLength(3); + * // => true + * + * _.isLength(Number.MIN_VALUE); + * // => false + * + * _.isLength(Infinity); + * // => false + * + * _.isLength('3'); + * // => false + */ + function isLength(value) { + return typeof value == 'number' && + value > -1 && value % 1 == 0 && value <= MAX_SAFE_INTEGER; + } + + /** + * Checks if `value` is the + * [language type](http://www.ecma-international.org/ecma-262/7.0/#sec-ecmascript-language-types) + * of `Object`. (e.g. arrays, functions, objects, regexes, `new Number(0)`, and `new String('')`) + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an object, else `false`. + * @example + * + * _.isObject({}); + * // => true + * + * _.isObject([1, 2, 3]); + * // => true + * + * _.isObject(_.noop); + * // => true + * + * _.isObject(null); + * // => false + */ + function isObject(value) { + var type = typeof value; + return value != null && (type == 'object' || type == 'function'); + } + + /** + * Checks if `value` is object-like. A value is object-like if it's not `null` + * and has a `typeof` result of "object". + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is object-like, else `false`. + * @example + * + * _.isObjectLike({}); + * // => true + * + * _.isObjectLike([1, 2, 3]); + * // => true + * + * _.isObjectLike(_.noop); + * // => false + * + * _.isObjectLike(null); + * // => false + */ + function isObjectLike(value) { + return value != null && typeof value == 'object'; + } + + /** + * Checks if `value` is `NaN`. + * + * **Note:** This method is based on + * [`Number.isNaN`](https://mdn.io/Number/isNaN) and is not the same as + * global [`isNaN`](https://mdn.io/isNaN) which returns `true` for + * `undefined` and other non-number values. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is `NaN`, else `false`. + * @example + * + * _.isNaN(NaN); + * // => true + * + * _.isNaN(new Number(NaN)); + * // => true + * + * isNaN(undefined); + * // => true + * + * _.isNaN(undefined); + * // => false + */ + function isNaN(value) { + // An `NaN` primitive is the only value that is not equal to itself. + // Perform the `toStringTag` check first to avoid errors with some + // ActiveX objects in IE. + return isNumber(value) && value != +value; + } + + /** + * Checks if `value` is `null`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is `null`, else `false`. + * @example + * + * _.isNull(null); + * // => true + * + * _.isNull(void 0); + * // => false + */ + function isNull(value) { + return value === null; + } + + /** + * Checks if `value` is classified as a `Number` primitive or object. + * + * **Note:** To exclude `Infinity`, `-Infinity`, and `NaN`, which are + * classified as numbers, use the `_.isFinite` method. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a number, else `false`. + * @example + * + * _.isNumber(3); + * // => true + * + * _.isNumber(Number.MIN_VALUE); + * // => true + * + * _.isNumber(Infinity); + * // => true + * + * _.isNumber('3'); + * // => false + */ + function isNumber(value) { + return typeof value == 'number' || + (isObjectLike(value) && baseGetTag(value) == numberTag); + } + + /** + * Checks if `value` is classified as a `RegExp` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a regexp, else `false`. + * @example + * + * _.isRegExp(/abc/); + * // => true + * + * _.isRegExp('/abc/'); + * // => false + */ + var isRegExp = baseIsRegExp; + + /** + * Checks if `value` is classified as a `String` primitive or object. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a string, else `false`. + * @example + * + * _.isString('abc'); + * // => true + * + * _.isString(1); + * // => false + */ + function isString(value) { + return typeof value == 'string' || + (!isArray(value) && isObjectLike(value) && baseGetTag(value) == stringTag); + } + + /** + * Checks if `value` is `undefined`. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is `undefined`, else `false`. + * @example + * + * _.isUndefined(void 0); + * // => true + * + * _.isUndefined(null); + * // => false + */ + function isUndefined(value) { + return value === undefined; + } + + /** + * Converts `value` to an array. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Lang + * @param {*} value The value to convert. + * @returns {Array} Returns the converted array. + * @example + * + * _.toArray({ 'a': 1, 'b': 2 }); + * // => [1, 2] + * + * _.toArray('abc'); + * // => ['a', 'b', 'c'] + * + * _.toArray(1); + * // => [] + * + * _.toArray(null); + * // => [] + */ + function toArray(value) { + if (!isArrayLike(value)) { + return values(value); + } + return value.length ? copyArray(value) : []; + } + + /** + * Converts `value` to an integer. + * + * **Note:** This method is loosely based on + * [`ToInteger`](http://www.ecma-international.org/ecma-262/7.0/#sec-tointeger). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to convert. + * @returns {number} Returns the converted integer. + * @example + * + * _.toInteger(3.2); + * // => 3 + * + * _.toInteger(Number.MIN_VALUE); + * // => 0 + * + * _.toInteger(Infinity); + * // => 1.7976931348623157e+308 + * + * _.toInteger('3.2'); + * // => 3 + */ + var toInteger = Number; + + /** + * Converts `value` to a number. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to process. + * @returns {number} Returns the number. + * @example + * + * _.toNumber(3.2); + * // => 3.2 + * + * _.toNumber(Number.MIN_VALUE); + * // => 5e-324 + * + * _.toNumber(Infinity); + * // => Infinity + * + * _.toNumber('3.2'); + * // => 3.2 + */ + var toNumber = Number; + + /** + * Converts `value` to a string. An empty string is returned for `null` + * and `undefined` values. The sign of `-0` is preserved. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to convert. + * @returns {string} Returns the converted string. + * @example + * + * _.toString(null); + * // => '' + * + * _.toString(-0); + * // => '-0' + * + * _.toString([1, 2, 3]); + * // => '1,2,3' + */ + function toString(value) { + if (typeof value == 'string') { + return value; + } + return value == null ? '' : (value + ''); + } + + /*------------------------------------------------------------------------*/ + + /** + * Assigns own enumerable string keyed properties of source objects to the + * destination object. Source objects are applied from left to right. + * Subsequent sources overwrite property assignments of previous sources. + * + * **Note:** This method mutates `object` and is loosely based on + * [`Object.assign`](https://mdn.io/Object/assign). + * + * @static + * @memberOf _ + * @since 0.10.0 + * @category Object + * @param {Object} object The destination object. + * @param {...Object} [sources] The source objects. + * @returns {Object} Returns `object`. + * @see _.assignIn + * @example + * + * function Foo() { + * this.a = 1; + * } + * + * function Bar() { + * this.c = 3; + * } + * + * Foo.prototype.b = 2; + * Bar.prototype.d = 4; + * + * _.assign({ 'a': 0 }, new Foo, new Bar); + * // => { 'a': 1, 'c': 3 } + */ + var assign = createAssigner(function(object, source) { + copyObject(source, nativeKeys(source), object); + }); + + /** + * This method is like `_.assign` except that it iterates over own and + * inherited source properties. + * + * **Note:** This method mutates `object`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @alias extend + * @category Object + * @param {Object} object The destination object. + * @param {...Object} [sources] The source objects. + * @returns {Object} Returns `object`. + * @see _.assign + * @example + * + * function Foo() { + * this.a = 1; + * } + * + * function Bar() { + * this.c = 3; + * } + * + * Foo.prototype.b = 2; + * Bar.prototype.d = 4; + * + * _.assignIn({ 'a': 0 }, new Foo, new Bar); + * // => { 'a': 1, 'b': 2, 'c': 3, 'd': 4 } + */ + var assignIn = createAssigner(function(object, source) { + copyObject(source, nativeKeysIn(source), object); + }); + + /** + * Creates an object that inherits from the `prototype` object. If a + * `properties` object is given, its own enumerable string keyed properties + * are assigned to the created object. + * + * @static + * @memberOf _ + * @since 2.3.0 + * @category Object + * @param {Object} prototype The object to inherit from. + * @param {Object} [properties] The properties to assign to the object. + * @returns {Object} Returns the new object. + * @example + * + * function Shape() { + * this.x = 0; + * this.y = 0; + * } + * + * function Circle() { + * Shape.call(this); + * } + * + * Circle.prototype = _.create(Shape.prototype, { + * 'constructor': Circle + * }); + * + * var circle = new Circle; + * circle instanceof Circle; + * // => true + * + * circle instanceof Shape; + * // => true + */ + function create(prototype, properties) { + var result = baseCreate(prototype); + return properties == null ? result : assign(result, properties); + } + + /** + * Assigns own and inherited enumerable string keyed properties of source + * objects to the destination object for all destination properties that + * resolve to `undefined`. Source objects are applied from left to right. + * Once a property is set, additional values of the same property are ignored. + * + * **Note:** This method mutates `object`. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Object + * @param {Object} object The destination object. + * @param {...Object} [sources] The source objects. + * @returns {Object} Returns `object`. + * @see _.defaultsDeep + * @example + * + * _.defaults({ 'a': 1 }, { 'b': 2 }, { 'a': 3 }); + * // => { 'a': 1, 'b': 2 } + */ + var defaults = baseRest(function(object, sources) { + object = Object(object); + + var index = -1; + var length = sources.length; + var guard = length > 2 ? sources[2] : undefined; + + if (guard && isIterateeCall(sources[0], sources[1], guard)) { + length = 1; + } + + while (++index < length) { + var source = sources[index]; + var props = keysIn(source); + var propsIndex = -1; + var propsLength = props.length; + + while (++propsIndex < propsLength) { + var key = props[propsIndex]; + var value = object[key]; + + if (value === undefined || + (eq(value, objectProto[key]) && !hasOwnProperty.call(object, key))) { + object[key] = source[key]; + } + } + } + + return object; + }); + + /** + * Checks if `path` is a direct property of `object`. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Object + * @param {Object} object The object to query. + * @param {Array|string} path The path to check. + * @returns {boolean} Returns `true` if `path` exists, else `false`. + * @example + * + * var object = { 'a': { 'b': 2 } }; + * var other = _.create({ 'a': _.create({ 'b': 2 }) }); + * + * _.has(object, 'a'); + * // => true + * + * _.has(object, 'a.b'); + * // => true + * + * _.has(object, ['a', 'b']); + * // => true + * + * _.has(other, 'a'); + * // => false + */ + function has(object, path) { + return object != null && hasOwnProperty.call(object, path); + } + + /** + * Creates an array of the own enumerable property names of `object`. + * + * **Note:** Non-object values are coerced to objects. See the + * [ES spec](http://ecma-international.org/ecma-262/7.0/#sec-object.keys) + * for more details. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Object + * @param {Object} object The object to query. + * @returns {Array} Returns the array of property names. + * @example + * + * function Foo() { + * this.a = 1; + * this.b = 2; + * } + * + * Foo.prototype.c = 3; + * + * _.keys(new Foo); + * // => ['a', 'b'] (iteration order is not guaranteed) + * + * _.keys('hi'); + * // => ['0', '1'] + */ + var keys = nativeKeys; + + /** + * Creates an array of the own and inherited enumerable property names of `object`. + * + * **Note:** Non-object values are coerced to objects. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Object + * @param {Object} object The object to query. + * @returns {Array} Returns the array of property names. + * @example + * + * function Foo() { + * this.a = 1; + * this.b = 2; + * } + * + * Foo.prototype.c = 3; + * + * _.keysIn(new Foo); + * // => ['a', 'b', 'c'] (iteration order is not guaranteed) + */ + var keysIn = nativeKeysIn; + + /** + * Creates an object composed of the picked `object` properties. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Object + * @param {Object} object The source object. + * @param {...(string|string[])} [paths] The property paths to pick. + * @returns {Object} Returns the new object. + * @example + * + * var object = { 'a': 1, 'b': '2', 'c': 3 }; + * + * _.pick(object, ['a', 'c']); + * // => { 'a': 1, 'c': 3 } + */ + var pick = flatRest(function(object, paths) { + return object == null ? {} : basePick(object, paths); + }); + + /** + * This method is like `_.get` except that if the resolved value is a + * function it's invoked with the `this` binding of its parent object and + * its result is returned. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Object + * @param {Object} object The object to query. + * @param {Array|string} path The path of the property to resolve. + * @param {*} [defaultValue] The value returned for `undefined` resolved values. + * @returns {*} Returns the resolved value. + * @example + * + * var object = { 'a': [{ 'b': { 'c1': 3, 'c2': _.constant(4) } }] }; + * + * _.result(object, 'a[0].b.c1'); + * // => 3 + * + * _.result(object, 'a[0].b.c2'); + * // => 4 + * + * _.result(object, 'a[0].b.c3', 'default'); + * // => 'default' + * + * _.result(object, 'a[0].b.c3', _.constant('default')); + * // => 'default' + */ + function result(object, path, defaultValue) { + var value = object == null ? undefined : object[path]; + if (value === undefined) { + value = defaultValue; + } + return isFunction(value) ? value.call(object) : value; + } + + /** + * Creates an array of the own enumerable string keyed property values of `object`. + * + * **Note:** Non-object values are coerced to objects. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Object + * @param {Object} object The object to query. + * @returns {Array} Returns the array of property values. + * @example + * + * function Foo() { + * this.a = 1; + * this.b = 2; + * } + * + * Foo.prototype.c = 3; + * + * _.values(new Foo); + * // => [1, 2] (iteration order is not guaranteed) + * + * _.values('hi'); + * // => ['h', 'i'] + */ + function values(object) { + return object == null ? [] : baseValues(object, keys(object)); + } + + /*------------------------------------------------------------------------*/ + + /** + * Converts the characters "&", "<", ">", '"', and "'" in `string` to their + * corresponding HTML entities. + * + * **Note:** No other characters are escaped. To escape additional + * characters use a third-party library like [_he_](https://mths.be/he). + * + * Though the ">" character is escaped for symmetry, characters like + * ">" and "/" don't need escaping in HTML and have no special meaning + * unless they're part of a tag or unquoted attribute value. See + * [Mathias Bynens's article](https://mathiasbynens.be/notes/ambiguous-ampersands) + * (under "semi-related fun fact") for more details. + * + * When working with HTML you should always + * [quote attribute values](http://wonko.com/post/html-escaping) to reduce + * XSS vectors. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category String + * @param {string} [string=''] The string to escape. + * @returns {string} Returns the escaped string. + * @example + * + * _.escape('fred, barney, & pebbles'); + * // => 'fred, barney, & pebbles' + */ + function escape(string) { + string = toString(string); + return (string && reHasUnescapedHtml.test(string)) + ? string.replace(reUnescapedHtml, escapeHtmlChar) + : string; + } + + /*------------------------------------------------------------------------*/ + + /** + * This method returns the first argument it receives. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Util + * @param {*} value Any value. + * @returns {*} Returns `value`. + * @example + * + * var object = { 'a': 1 }; + * + * console.log(_.identity(object) === object); + * // => true + */ + function identity(value) { + return value; + } + + /** + * Creates a function that invokes `func` with the arguments of the created + * function. If `func` is a property name, the created function returns the + * property value for a given element. If `func` is an array or object, the + * created function returns `true` for elements that contain the equivalent + * source properties, otherwise it returns `false`. + * + * @static + * @since 4.0.0 + * @memberOf _ + * @category Util + * @param {*} [func=_.identity] The value to convert to a callback. + * @returns {Function} Returns the callback. + * @example + * + * var users = [ + * { 'user': 'barney', 'age': 36, 'active': true }, + * { 'user': 'fred', 'age': 40, 'active': false } + * ]; + * + * // The `_.matches` iteratee shorthand. + * _.filter(users, _.iteratee({ 'user': 'barney', 'active': true })); + * // => [{ 'user': 'barney', 'age': 36, 'active': true }] + * + * // The `_.matchesProperty` iteratee shorthand. + * _.filter(users, _.iteratee(['user', 'fred'])); + * // => [{ 'user': 'fred', 'age': 40 }] + * + * // The `_.property` iteratee shorthand. + * _.map(users, _.iteratee('user')); + * // => ['barney', 'fred'] + * + * // Create custom iteratee shorthands. + * _.iteratee = _.wrap(_.iteratee, function(iteratee, func) { + * return !_.isRegExp(func) ? iteratee(func) : function(string) { + * return func.test(string); + * }; + * }); + * + * _.filter(['abc', 'def'], /ef/); + * // => ['def'] + */ + var iteratee = baseIteratee; + + /** + * Creates a function that performs a partial deep comparison between a given + * object and `source`, returning `true` if the given object has equivalent + * property values, else `false`. + * + * **Note:** The created function is equivalent to `_.isMatch` with `source` + * partially applied. + * + * Partial comparisons will match empty array and empty object `source` + * values against any array or object value, respectively. See `_.isEqual` + * for a list of supported value comparisons. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Util + * @param {Object} source The object of property values to match. + * @returns {Function} Returns the new spec function. + * @example + * + * var objects = [ + * { 'a': 1, 'b': 2, 'c': 3 }, + * { 'a': 4, 'b': 5, 'c': 6 } + * ]; + * + * _.filter(objects, _.matches({ 'a': 4, 'c': 6 })); + * // => [{ 'a': 4, 'b': 5, 'c': 6 }] + */ + function matches(source) { + return baseMatches(assign({}, source)); + } + + /** + * Adds all own enumerable string keyed function properties of a source + * object to the destination object. If `object` is a function, then methods + * are added to its prototype as well. + * + * **Note:** Use `_.runInContext` to create a pristine `lodash` function to + * avoid conflicts caused by modifying the original. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Util + * @param {Function|Object} [object=lodash] The destination object. + * @param {Object} source The object of functions to add. + * @param {Object} [options={}] The options object. + * @param {boolean} [options.chain=true] Specify whether mixins are chainable. + * @returns {Function|Object} Returns `object`. + * @example + * + * function vowels(string) { + * return _.filter(string, function(v) { + * return /[aeiou]/i.test(v); + * }); + * } + * + * _.mixin({ 'vowels': vowels }); + * _.vowels('fred'); + * // => ['e'] + * + * _('fred').vowels().value(); + * // => ['e'] + * + * _.mixin({ 'vowels': vowels }, { 'chain': false }); + * _('fred').vowels(); + * // => ['e'] + */ + function mixin(object, source, options) { + var props = keys(source), + methodNames = baseFunctions(source, props); + + if (options == null && + !(isObject(source) && (methodNames.length || !props.length))) { + options = source; + source = object; + object = this; + methodNames = baseFunctions(source, keys(source)); + } + var chain = !(isObject(options) && 'chain' in options) || !!options.chain, + isFunc = isFunction(object); + + baseEach(methodNames, function(methodName) { + var func = source[methodName]; + object[methodName] = func; + if (isFunc) { + object.prototype[methodName] = function() { + var chainAll = this.__chain__; + if (chain || chainAll) { + var result = object(this.__wrapped__), + actions = result.__actions__ = copyArray(this.__actions__); + + actions.push({ 'func': func, 'args': arguments, 'thisArg': object }); + result.__chain__ = chainAll; + return result; + } + return func.apply(object, arrayPush([this.value()], arguments)); + }; + } + }); + + return object; + } + + /** + * Reverts the `_` variable to its previous value and returns a reference to + * the `lodash` function. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Util + * @returns {Function} Returns the `lodash` function. + * @example + * + * var lodash = _.noConflict(); + */ + function noConflict() { + if (root._ === this) { + root._ = oldDash; + } + return this; + } + + /** + * This method returns `undefined`. + * + * @static + * @memberOf _ + * @since 2.3.0 + * @category Util + * @example + * + * _.times(2, _.noop); + * // => [undefined, undefined] + */ + function noop() { + // No operation performed. + } + + /** + * Generates a unique ID. If `prefix` is given, the ID is appended to it. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Util + * @param {string} [prefix=''] The value to prefix the ID with. + * @returns {string} Returns the unique ID. + * @example + * + * _.uniqueId('contact_'); + * // => 'contact_104' + * + * _.uniqueId(); + * // => '105' + */ + function uniqueId(prefix) { + var id = ++idCounter; + return toString(prefix) + id; + } + + /*------------------------------------------------------------------------*/ + + /** + * Computes the maximum value of `array`. If `array` is empty or falsey, + * `undefined` is returned. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Math + * @param {Array} array The array to iterate over. + * @returns {*} Returns the maximum value. + * @example + * + * _.max([4, 2, 8, 6]); + * // => 8 + * + * _.max([]); + * // => undefined + */ + function max(array) { + return (array && array.length) + ? baseExtremum(array, identity, baseGt) + : undefined; + } + + /** + * Computes the minimum value of `array`. If `array` is empty or falsey, + * `undefined` is returned. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Math + * @param {Array} array The array to iterate over. + * @returns {*} Returns the minimum value. + * @example + * + * _.min([4, 2, 8, 6]); + * // => 2 + * + * _.min([]); + * // => undefined + */ + function min(array) { + return (array && array.length) + ? baseExtremum(array, identity, baseLt) + : undefined; + } + + /*------------------------------------------------------------------------*/ + + // Add methods that return wrapped values in chain sequences. + lodash.assignIn = assignIn; + lodash.before = before; + lodash.bind = bind; + lodash.chain = chain; + lodash.compact = compact; + lodash.concat = concat; + lodash.create = create; + lodash.defaults = defaults; + lodash.defer = defer; + lodash.delay = delay; + lodash.filter = filter; + lodash.flatten = flatten; + lodash.flattenDeep = flattenDeep; + lodash.iteratee = iteratee; + lodash.keys = keys; + lodash.map = map; + lodash.matches = matches; + lodash.mixin = mixin; + lodash.negate = negate; + lodash.once = once; + lodash.pick = pick; + lodash.slice = slice; + lodash.sortBy = sortBy; + lodash.tap = tap; + lodash.thru = thru; + lodash.toArray = toArray; + lodash.values = values; + + // Add aliases. + lodash.extend = assignIn; + + // Add methods to `lodash.prototype`. + mixin(lodash, lodash); + + /*------------------------------------------------------------------------*/ + + // Add methods that return unwrapped values in chain sequences. + lodash.clone = clone; + lodash.escape = escape; + lodash.every = every; + lodash.find = find; + lodash.forEach = forEach; + lodash.has = has; + lodash.head = head; + lodash.identity = identity; + lodash.indexOf = indexOf; + lodash.isArguments = isArguments; + lodash.isArray = isArray; + lodash.isBoolean = isBoolean; + lodash.isDate = isDate; + lodash.isEmpty = isEmpty; + lodash.isEqual = isEqual; + lodash.isFinite = isFinite; + lodash.isFunction = isFunction; + lodash.isNaN = isNaN; + lodash.isNull = isNull; + lodash.isNumber = isNumber; + lodash.isObject = isObject; + lodash.isRegExp = isRegExp; + lodash.isString = isString; + lodash.isUndefined = isUndefined; + lodash.last = last; + lodash.max = max; + lodash.min = min; + lodash.noConflict = noConflict; + lodash.noop = noop; + lodash.reduce = reduce; + lodash.result = result; + lodash.size = size; + lodash.some = some; + lodash.uniqueId = uniqueId; + + // Add aliases. + lodash.each = forEach; + lodash.first = head; + + mixin(lodash, (function() { + var source = {}; + baseForOwn(lodash, function(func, methodName) { + if (!hasOwnProperty.call(lodash.prototype, methodName)) { + source[methodName] = func; + } + }); + return source; + }()), { 'chain': false }); + + /*------------------------------------------------------------------------*/ + + /** + * The semantic version number. + * + * @static + * @memberOf _ + * @type {string} + */ + lodash.VERSION = VERSION; + + // Add `Array` methods to `lodash.prototype`. + baseEach(['pop', 'join', 'replace', 'reverse', 'split', 'push', 'shift', 'sort', 'splice', 'unshift'], function(methodName) { + var func = (/^(?:replace|split)$/.test(methodName) ? String.prototype : arrayProto)[methodName], + chainName = /^(?:push|sort|unshift)$/.test(methodName) ? 'tap' : 'thru', + retUnwrapped = /^(?:pop|join|replace|shift)$/.test(methodName); + + lodash.prototype[methodName] = function() { + var args = arguments; + if (retUnwrapped && !this.__chain__) { + var value = this.value(); + return func.apply(isArray(value) ? value : [], args); + } + return this[chainName](function(value) { + return func.apply(isArray(value) ? value : [], args); + }); + }; + }); + + // Add chain sequence methods to the `lodash` wrapper. + lodash.prototype.toJSON = lodash.prototype.valueOf = lodash.prototype.value = wrapperValue; + + /*--------------------------------------------------------------------------*/ + + // Some AMD build optimizers, like r.js, check for condition patterns like: + if (true) { + // Expose Lodash on the global object to prevent errors when Lodash is + // loaded by a script tag in the presence of an AMD loader. + // See http://requirejs.org/docs/errors.html#mismatch for more details. + // Use `_.noConflict` to remove Lodash from the global object. + root._ = lodash; + + // Define as an anonymous module so, through path mapping, it can be + // referenced as the "underscore" module. + !(__WEBPACK_AMD_DEFINE_RESULT__ = function() { + return lodash; + }.call(exports, __webpack_require__, exports, module), __WEBPACK_AMD_DEFINE_RESULT__ !== undefined && (module.exports = __WEBPACK_AMD_DEFINE_RESULT__)); + } + // Check for `exports` after `define` in case a build optimizer adds it. + else if (freeModule) { + // Export for Node.js. + (freeModule.exports = lodash)._ = lodash; + // Export for CommonJS support. + freeExports._ = lodash; + } + else { + // Export to the global object. + root._ = lodash; + } + }.call(this)); + + /* WEBPACK VAR INJECTION */}.call(exports, (function() { return this; }()), __webpack_require__(59)(module))) + +/***/ }), +/* 59 */ +/***/ (function(module, exports) { + + module.exports = function(module) { + if(!module.webpackPolyfill) { + module.deprecate = function() {}; + module.paths = []; + // module.parent = undefined by default + module.children = []; + module.webpackPolyfill = 1; + } + return module; + } + + +/***/ }), +/* 60 */ +/***/ (function(module, exports, __webpack_require__) { + + var ArrowLink = __webpack_require__(61); + var BoxArrowLink = __webpack_require__(22); + var PlainLink = __webpack_require__(23); + var OwlDisjointWith = __webpack_require__(46); + var SetOperatorProperty = __webpack_require__(56); + + /** + * Stores the passed properties in links. + * @returns {Function} + */ + module.exports = (function (){ + var linkCreator = {}; + + /** + * Creates links from the passed properties. + * @param properties + */ + linkCreator.createLinks = function ( properties ){ + var links = groupPropertiesToLinks(properties); + + for ( var i = 0, l = links.length; i < l; i++ ) { + var link = links[i]; + + countAndSetLayers(link, links); + countAndSetLoops(link, links); + } + + return links; + }; + + /** + * Creates links of properties and - if existing - their inverses. + * @param properties the properties + * @returns {Array} + */ + function groupPropertiesToLinks( properties ){ + var links = [], + property, + addedProperties = __webpack_require__(62)(); + + for ( var i = 0, l = properties.length; i < l; i++ ) { + property = properties[i]; + + if ( !addedProperties.has(property) ) { + var link = createLink(property); + + property.link(link); + if ( property.inverse() ) { + property.inverse().link(link); + } + + links.push(link); + + addedProperties.add(property); + if ( property.inverse() ) { + addedProperties.add(property.inverse()); + } + } + } + + return links; + } + + function countAndSetLayers( link, allLinks ){ + var layer, + layers, + i, l; + + if ( typeof link.layers() === "undefined" ) { + layers = []; + + // Search for other links that are another layer + for ( i = 0, l = allLinks.length; i < l; i++ ) { + var otherLink = allLinks[i]; + if ( link.domain() === otherLink.domain() && link.range() === otherLink.range() || + link.domain() === otherLink.range() && link.range() === otherLink.domain() ) { + layers.push(otherLink); + } + } + + // Set the results on each of the layers + for ( i = 0, l = layers.length; i < l; ++i ) { + layer = layers[i]; + + layer.layerIndex(i); + layer.layers(layers); + } + } + } + + function countAndSetLoops( link, allLinks ){ + var loop, + loops, + i, l; + + if ( typeof link.loops() === "undefined" ) { + loops = []; + + // Search for other links that are also loops of the same node + for ( i = 0, l = allLinks.length; i < l; i++ ) { + var otherLink = allLinks[i]; + if ( link.domain() === otherLink.domain() && link.domain() === otherLink.range() ) { + loops.push(otherLink); + } + } + + // Set the results on each of the loops + for ( i = 0, l = loops.length; i < l; ++i ) { + loop = loops[i]; + + loop.loopIndex(i); + loop.loops(loops); + } + } + } + + function createLink( property ){ + var domain = property.domain(); + var range = property.range(); + + if ( property instanceof OwlDisjointWith ) { + return new PlainLink(domain, range, property); + } else if ( property instanceof SetOperatorProperty ) { + return new BoxArrowLink(domain, range, property); + } + return new ArrowLink(domain, range, property); + } + + return function (){ + // Return a function to keep module interfaces consistent + return linkCreator; + }; + })(); + + +/***/ }), +/* 61 */ +/***/ (function(module, exports, __webpack_require__) { + + var PlainLink = __webpack_require__(23); + + + module.exports = ArrowLink; + + function ArrowLink( domain, range, property ){ + PlainLink.apply(this, arguments); + } + + ArrowLink.prototype = Object.create(PlainLink.prototype); + ArrowLink.prototype.constructor = ArrowLink; + + + ArrowLink.prototype.draw = function ( linkGroup, markerContainer ){ + var property = this.label().property(); + var inverse = this.label().inverse(); + + createPropertyMarker(markerContainer, property); + if ( inverse ) { + createInverseMarker(markerContainer, inverse); + } + + PlainLink.prototype.draw.apply(this, arguments); + + // attach the markers to the link + linkGroup.attr("marker-end", "url(#" + property.markerId() + ")"); + if ( inverse ) { + linkGroup.attr("marker-start", "url(#" + inverse.markerId() + ")"); + } + }; + + function createPropertyMarker( markerContainer, property ){ + var marker = appendBasicMarker(markerContainer, property); + //marker.attr("refX", 12); + var m1X = -12; + var m1Y = 8; + var m2X = -12; + var m2Y = -8; + marker.append("path") + //.attr("d", "M0,-8L12,0L0,8Z") + .attr("d", "M0,0L " + m1X + "," + m1Y + "L" + m2X + "," + m2Y + "L" + 0 + "," + 0) + .classed(property.markerType(), true); + + property.markerElement(marker); + } + + function createInverseMarker( markerContainer, inverse ){ + var m1X = -12; + var m1Y = 8; + var m2X = -12; + var m2Y = -8; + var inverseMarker = appendBasicMarker(markerContainer, inverse); + inverseMarker.append("path") + //.attr("d", "M12,-8L0,0L12,8Z") + .attr("d", "M0,0L " + -m1X + "," + -m1Y + "L" + -m2X + "," + -m2Y + "L" + 0 + "," + 0) + .classed(inverse.markerType(), true); + + inverse.markerElement(inverseMarker); + } + + function appendBasicMarker( markerContainer, property ){ + return markerContainer.append("marker") + .datum(property) + .attr("id", property.markerId()) + + .attr("viewBox", "-14 -10 28 20") + .attr("markerWidth", 10) + .attr("markerHeight", 10) + //.attr("markerUnits", "userSpaceOnUse") + .attr("orient", "auto"); + } + + +/***/ }), +/* 62 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * A simple incomplete encapsulation of the d3 set, which is able to store webvowl + * elements by using their id. + */ + module.exports = function ( array ){ + + var set = {}, + d3Set = d3.set(array); + + set.has = function ( webvowlElement ){ + return d3Set.has(webvowlElement.id()); + }; + + set.add = function ( webvowlElement ){ + return d3Set.add(webvowlElement.id()); + }; + + set.remove = function ( webvowlElement ){ + return d3Set.remove(webvowlElement.id()); + }; + + set.empty = function (){ + return d3Set.empty(); + }; + + set.size = function (){ + return d3Set.size(); + }; + + return set; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 63 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + var BaseNode = __webpack_require__(9); + var DatatypeNode = __webpack_require__(35); + var Thing = __webpack_require__(31); + var ObjectProperty = __webpack_require__(50); + var DatatypeProperty = __webpack_require__(44); + var RdfsSubClassOf = __webpack_require__(55); + var Label = __webpack_require__(24); + + + var tools = {}; + module.exports = function (){ + return tools; + }; + + tools.isLabel = function ( element ){ + return element instanceof Label; + }; + + tools.isNode = function ( element ){ + return element instanceof BaseNode; + }; + + tools.isDatatype = function ( node ){ + return node instanceof DatatypeNode; + }; + + tools.isThing = function ( node ){ + return node instanceof Thing; + }; + + tools.isProperty = function ( element ){ + return element instanceof BaseProperty; + }; + + tools.isObjectProperty = function ( element ){ + return element instanceof ObjectProperty; + }; + + tools.isDatatypeProperty = function ( element ){ + return element instanceof DatatypeProperty; + }; + + tools.isRdfsSubClassOf = function ( property ){ + return property instanceof RdfsSubClassOf; + }; + + +/***/ }), +/* 64 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function (){ + var options = {}, + data, + graphContainerSelector, + classDistance = 200, + datatypeDistance = 120, + loopDistance = 150, + charge = -500, + gravity = 0.025, + linkStrength = 1, + height = 600, + width = 800, + selectionModules = [], + filterModules = [], + minMagnification = 0.01, + maxMagnification = 4, + compactNotation = false, + dynamicLabelWidth = true, + // some filters + literalFilter, + // menus + gravityMenu, + filterMenu, + loadingModule, + modeMenu, + pausedMenu, + pickAndPinModule, + resetMenu, + searchMenu, + ontologyMenu, + sidebar, + leftSidebar, + editSidebar, + navigationMenu, + exportMenu, + graphObject, + zoomSlider, + datatypeFilter, + focuserModule, + colorExternalsModule, + compactNotationModule, + objectPropertyFilter, + subclassFilter, + setOperatorFilter, + maxLabelWidth = 120, + metadataObject = {}, + generalOntologyMetaData = {}, + disjointPropertyFilter, + rectangularRep = false, + warningModule, + prefixModule, + drawPropertyDraggerOnHover = true, + showDraggerObject = false, + directInputModule, + scaleNodesByIndividuals = true, + useAccuracyHelper = true, + showRenderingStatistic = true, + showInputModality = false, + hideDebugOptions = true, + nodeDegreeFilter, + debugMenu, + + supportedDatatypes = ["rdfs:Literal", "xsd:boolean", "xsd:double", "xsd:integer", "xsd:string", "undefined"], + supportedClasses = ["owl:Thing", "owl:Class", "owl:DeprecatedClass"], + supportedProperties = ["owl:objectProperty", + "rdfs:subClassOf", + "owl:disjointWith", + "owl:allValuesFrom", + "owl:someValuesFrom" + ], + prefixList = { + rdf: 'http://www.w3.org/1999/02/22-rdf-syntax-ns#', + rdfs: 'http://www.w3.org/2000/01/rdf-schema#', + owl: 'http://www.w3.org/2002/07/owl#', + xsd: 'http://www.w3.org/2001/XMLSchema#', + dc: 'http://purl.org/dc/elements/1.1/#', + xml: 'http://www.w3.org/XML/1998/namespace' + }; + + options.clearMetaObject = function (){ + generalOntologyMetaData = {}; + }; + options.clearGeneralMetaObject = function (){ + generalOntologyMetaData = {}; + }; + + options.debugMenu = function ( val ){ + if ( !arguments.length ) return debugMenu; + debugMenu = val; + }; + + options.getHideDebugFeatures = function (){ + return hideDebugOptions; + }; + options.executeHiddenDebugFeatuers = function (){ + hideDebugOptions = !hideDebugOptions; + d3.selectAll(".debugOption").classed("hidden", hideDebugOptions); + if ( hideDebugOptions === false ) { + graphObject.setForceTickFunctionWithFPS(); + } + else { + graphObject.setDefaultForceTickFunction(); + } + if ( debugMenu ) { + debugMenu.updateSettings(); + } + options.setHideDebugFeaturesForDefaultObject(hideDebugOptions); + }; + + + options.addOrUpdateGeneralObjectEntry = function ( property, value ){ + if ( generalOntologyMetaData.hasOwnProperty(property) ) { + //console.log("Updating Property:"+ property); + if ( property === "iri" ) { + if ( validURL(value) === false ) { + warningModule.showWarning("Invalid Ontology IRI", "Input IRI does not represent an URL", "Restoring previous IRI for ontology", 1, false); + return false; + } + } + generalOntologyMetaData[property] = value; + } else { + generalOntologyMetaData[property] = value; + } + return true; + }; + + options.getGeneralMetaObjectProperty = function ( property ){ + if ( generalOntologyMetaData.hasOwnProperty(property) ) { + return generalOntologyMetaData[property]; + } + }; + + options.getGeneralMetaObject = function (){ + return generalOntologyMetaData; + }; + + options.addOrUpdateMetaObjectEntry = function ( property, value ){ + + if ( metadataObject.hasOwnProperty(property) ) { + metadataObject[property] = value; + } else { + metadataObject[property] = value; + } + }; + + options.getMetaObjectProperty = function ( property ){ + if ( metadataObject.hasOwnProperty(property) ) { + return metadataObject[property]; + } + }; + options.getMetaObject = function (){ + return metadataObject; + }; + + + options.prefixList = function (){ + return prefixList; + }; + options.addPrefix = function ( prefix, url ){ + prefixList[prefix] = url; + }; + + function validURL( str ){ + var urlregex = /^(https?|ftp):\/\/([a-zA-Z0-9.-]+(:[a-zA-Z0-9.&%$-]+)*@)*((25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9][0-9]?)(\.(25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9]?[0-9])){3}|([a-zA-Z0-9-]+\.)*[a-zA-Z0-9-]+\.(com|edu|gov|int|mil|net|org|biz|arpa|info|name|pro|aero|coop|museum|[a-zA-Z]{2}))(:[0-9]+)*(\/($|[a-zA-Z0-9.,?'\\+&%$#=~_-]+))*$/; + return urlregex.test(str); + } + + options.updatePrefix = function ( oldPrefix, newPrefix, oldURL, newURL ){ + if ( oldPrefix === newPrefix && oldURL === newURL ) { + // console.log("Nothing to update"); + return true; + } + if ( oldPrefix === newPrefix && oldURL !== newURL && validURL(newURL) === true ) { + // console.log("Update URL"); + prefixList[oldPrefix] = newURL; + } else if ( oldPrefix === newPrefix && oldURL !== newURL && validURL(newURL) === false ) { + if ( validURL(newURL) === false ) { + warningModule.showWarning("Invalid Prefix IRI", "Input IRI does not represent an IRI", "You should enter a valid IRI in form of a URL", 1, false); + return false; + } + + return false; + } + if ( oldPrefix !== newPrefix && validURL(newURL) === true ) { + + // sanity check + if ( prefixList.hasOwnProperty(newPrefix) ) { + // console.log("Already have this prefix!"); + warningModule.showWarning("Prefix Already Exist", "Prefix: " + newPrefix + " is already defined", "You should use an other one", 1, false); + return false; + } + options.removePrefix(oldPrefix); + options.addPrefix(newPrefix, newURL); + editSidebar.updateEditDeleteButtonIds(oldPrefix, newPrefix); + return true; + } + + // console.log("Is new URL ("+newURL+") valid? >> "+validURL(newURL)); + if ( validURL(newURL) === false ) { + warningModule.showWarning("Invalid Prefix IRI", "Input IRI does not represent an URL", "You should enter a valid URL", 1, false); + + } + return false; + }; + + options.removePrefix = function ( prefix ){ + delete prefixList[prefix]; + }; + + + options.supportedDatatypes = function (){ + return supportedDatatypes; + }; + options.supportedClasses = function (){ + return supportedClasses; + }; + options.supportedProperties = function (){ + return supportedProperties; + }; + + options.datatypeFilter = function ( val ){ + if ( !arguments.length ) return datatypeFilter; + datatypeFilter = val; + }; + + options.showDraggerObject = function ( val ){ + if ( !arguments.length ) { + return showDraggerObject; + } + showDraggerObject = val; + }; + options.useAccuracyHelper = function ( val ){ + if ( !arguments.length ) { + return useAccuracyHelper; + } + useAccuracyHelper = val; + }; + options.showAccuracyHelper = function ( val ){ + if ( !arguments.length ) { + return options.showDraggerObject(); + } + options.showDraggerObject(val); + }; + options.showRenderingStatistic = function ( val ){ + if ( !arguments.length ) { + return showRenderingStatistic; + } + showRenderingStatistic = val; + }; + options.showInputModality = function ( val ){ + if ( !arguments.length ) { + return showInputModality; + } + showInputModality = val; + }; + + options.drawPropertyDraggerOnHover = function ( val ){ + if ( !arguments.length ) return drawPropertyDraggerOnHover; + drawPropertyDraggerOnHover = val; + }; + + options.warningModule = function ( val ){ + if ( !arguments.length ) return warningModule; + warningModule = val; + }; + options.directInputModule = function ( val ){ + if ( !arguments.length ) return directInputModule; + directInputModule = val; + }; + options.prefixModule = function ( val ){ + if ( !arguments.length ) return prefixModule; + prefixModule = val; + }; + + options.focuserModule = function ( val ){ + if ( !arguments.length ) return focuserModule; + focuserModule = val; + }; + options.colorExternalsModule = function ( val ){ + if ( !arguments.length ) return colorExternalsModule; + colorExternalsModule = val; + }; + options.compactNotationModule = function ( val ){ + if ( !arguments.length ) return compactNotationModule; + compactNotationModule = val; + }; + + options.maxLabelWidth = function ( val ){ + if ( !arguments.length ) return maxLabelWidth; + maxLabelWidth = val; + }; + options.objectPropertyFilter = function ( val ){ + if ( !arguments.length ) return objectPropertyFilter; + objectPropertyFilter = val; + }; + options.disjointPropertyFilter = function ( val ){ + if ( !arguments.length ) return disjointPropertyFilter; + disjointPropertyFilter = val; + }; + options.subclassFilter = function ( val ){ + if ( !arguments.length ) return subclassFilter; + subclassFilter = val; + }; + options.setOperatorFilter = function ( val ){ + if ( !arguments.length ) return setOperatorFilter; + setOperatorFilter = val; + }; + options.leftSidebar = function ( val ){ + if ( !arguments.length ) return leftSidebar; + leftSidebar = val; + }; + options.editSidebar = function ( val ){ + if ( !arguments.length ) return editSidebar; + editSidebar = val; + }; + + options.zoomSlider = function ( val ){ + if ( !arguments.length ) return zoomSlider; + zoomSlider = val; + }; + + options.graphObject = function ( val ){ + if ( !arguments.length ) return graphObject; + graphObject = val; + }; + + + var defaultOptionsConfig = {}; + defaultOptionsConfig.sidebar = "1"; + defaultOptionsConfig.doc = -1; + defaultOptionsConfig.cd = 200; + defaultOptionsConfig.dd = 120; + defaultOptionsConfig.editorMode = "false"; + defaultOptionsConfig.filter_datatypes = "false"; + defaultOptionsConfig.filter_objectProperties = "false"; + defaultOptionsConfig.filter_sco = "false"; + defaultOptionsConfig.filter_disjoint = "true"; + defaultOptionsConfig.filter_setOperator = "false"; + defaultOptionsConfig.mode_dynamic = "true"; + defaultOptionsConfig.mode_scaling = "true"; + defaultOptionsConfig.mode_compact = "false"; + defaultOptionsConfig.mode_colorExt = "true"; + defaultOptionsConfig.mode_multiColor = "false"; + defaultOptionsConfig.debugFeatures = "false"; + defaultOptionsConfig.rect = 0; + + + options.initialConfig = function (){ + var initCfg = {}; + initCfg.sidebar = "1"; + initCfg.doc = -1; + initCfg.cd = 200; + initCfg.dd = 120; + initCfg.editorMode = "false"; + initCfg.filter_datatypes = "false"; + initCfg.filter_objectProperties = "false"; + initCfg.filter_sco = "false"; + initCfg.filter_disjoint = "true"; + initCfg.filter_setOperator = "false"; + initCfg.mode_dynamic = "true"; + initCfg.mode_scaling = "true"; + initCfg.mode_compact = "false"; + initCfg.mode_colorExt = "true"; + initCfg.mode_multiColor = "false"; + initCfg.mode_pnp = "false"; + initCfg.debugFeatures = "false"; + initCfg.rect = 0; + return initCfg; + }; + + options.setEditorModeForDefaultObject = function ( val ){ + defaultOptionsConfig.editorMode = String(val); + }; + options.setHideDebugFeaturesForDefaultObject = function ( val ){ + defaultOptionsConfig.debugFeatures = String(!val); + }; + + function updateConfigObject(){ + defaultOptionsConfig.sidebar = options.sidebar().getSidebarVisibility(); + defaultOptionsConfig.cd = options.classDistance(); + defaultOptionsConfig.dd = options.datatypeDistance(); + defaultOptionsConfig.filter_datatypes = String(options.filterMenu().getCheckBoxValue("datatypeFilterCheckbox")); + defaultOptionsConfig.filter_sco = String(options.filterMenu().getCheckBoxValue("subclassFilterCheckbox")); + defaultOptionsConfig.filter_disjoint = String(options.filterMenu().getCheckBoxValue("disjointFilterCheckbox")); + defaultOptionsConfig.filter_setOperator = String(options.filterMenu().getCheckBoxValue("setoperatorFilterCheckbox")); + defaultOptionsConfig.filter_objectProperties = String(options.filterMenu().getCheckBoxValue("objectPropertyFilterCheckbox")); + defaultOptionsConfig.mode_dynamic = String(options.dynamicLabelWidth()); + defaultOptionsConfig.mode_scaling = String(options.modeMenu().getCheckBoxValue("nodescalingModuleCheckbox")); + defaultOptionsConfig.mode_compact = String(options.modeMenu().getCheckBoxValue("compactnotationModuleCheckbox")); + defaultOptionsConfig.mode_colorExt = String(options.modeMenu().getCheckBoxValue("colorexternalsModuleCheckbox")); + defaultOptionsConfig.mode_multiColor = String(options.modeMenu().colorModeState()); + defaultOptionsConfig.mode_pnp = String(options.modeMenu().getCheckBoxValue("pickandpinModuleCheckbox")); + defaultOptionsConfig.rect = 0; + } + + options.defaultConfig = function (){ + updateConfigObject(); + return defaultOptionsConfig; + }; + + options.exportMenu = function ( val ){ + if ( !arguments.length ) return exportMenu; + exportMenu = val; + }; + + options.rectangularRepresentation = function ( val ){ + if ( !arguments.length ) { + return rectangularRep; + } else { + var intVal = parseInt(val); + if ( intVal === 0 ) { + rectangularRep = false; + } else { + rectangularRep = true; + } + } + }; + + options.dynamicLabelWidth = function ( val ){ + if ( !arguments.length ) + return dynamicLabelWidth; + else { + dynamicLabelWidth = val; + } + }; + options.sidebar = function ( s ){ + if ( !arguments.length ) return sidebar; + sidebar = s; + return options; + + }; + + options.navigationMenu = function ( m ){ + if ( !arguments.length ) return navigationMenu; + navigationMenu = m; + return options; + + }; + + options.ontologyMenu = function ( m ){ + if ( !arguments.length ) return ontologyMenu; + ontologyMenu = m; + return options; + }; + + options.searchMenu = function ( m ){ + if ( !arguments.length ) return searchMenu; + searchMenu = m; + return options; + }; + + options.resetMenu = function ( m ){ + if ( !arguments.length ) return resetMenu; + resetMenu = m; + return options; + }; + + options.pausedMenu = function ( m ){ + if ( !arguments.length ) return pausedMenu; + pausedMenu = m; + return options; + }; + + options.pickAndPinModule = function ( m ){ + if ( !arguments.length ) return pickAndPinModule; + pickAndPinModule = m; + return options; + }; + + options.gravityMenu = function ( m ){ + if ( !arguments.length ) return gravityMenu; + gravityMenu = m; + return options; + }; + + options.filterMenu = function ( m ){ + if ( !arguments.length ) return filterMenu; + filterMenu = m; + return options; + }; + + options.modeMenu = function ( m ){ + if ( !arguments.length ) return modeMenu; + modeMenu = m; + return options; + }; + + options.charge = function ( p ){ + if ( !arguments.length ) return charge; + charge = +p; + return options; + }; + + options.classDistance = function ( p ){ + if ( !arguments.length ) return classDistance; + classDistance = +p; + return options; + }; + + options.compactNotation = function ( p ){ + + if ( !arguments.length ) return compactNotation; + compactNotation = p; + return options; + }; + + options.data = function ( p ){ + if ( !arguments.length ) return data; + data = p; + return options; + }; + + options.datatypeDistance = function ( p ){ + if ( !arguments.length ) return datatypeDistance; + datatypeDistance = +p; + return options; + }; + + options.filterModules = function ( p ){ + if ( !arguments.length ) return filterModules; + filterModules = p; + return options; + }; + + options.graphContainerSelector = function ( p ){ + if ( !arguments.length ) return graphContainerSelector; + graphContainerSelector = p; + return options; + }; + + options.gravity = function ( p ){ + if ( !arguments.length ) return gravity; + gravity = +p; + return options; + }; + + options.height = function ( p ){ + if ( !arguments.length ) return height; + height = +p; + return options; + }; + + options.linkStrength = function ( p ){ + if ( !arguments.length ) return linkStrength; + linkStrength = +p; + return options; + }; + + options.loopDistance = function ( p ){ + if ( !arguments.length ) return loopDistance; + loopDistance = p; + return options; + }; + + options.minMagnification = function ( p ){ + if ( !arguments.length ) return minMagnification; + minMagnification = +p; + return options; + }; + + options.maxMagnification = function ( p ){ + if ( !arguments.length ) return maxMagnification; + maxMagnification = +p; + return options; + }; + + options.scaleNodesByIndividuals = function ( p ){ + if ( !arguments.length ) return scaleNodesByIndividuals; + scaleNodesByIndividuals = p; + return options; + }; + + options.selectionModules = function ( p ){ + if ( !arguments.length ) return selectionModules; + selectionModules = p; + return options; + }; + + options.width = function ( p ){ + if ( !arguments.length ) return width; + width = +p; + return options; + }; + + options.literalFilter = function ( p ){ + if ( !arguments.length ) return literalFilter; + literalFilter = p; + return options; + }; + options.nodeDegreeFilter = function ( p ){ + if ( !arguments.length ) return nodeDegreeFilter; + nodeDegreeFilter = p; + return options; + }; + + options.loadingModule = function ( p ){ + if ( !arguments.length ) return loadingModule; + loadingModule = p; + return options; + }; + + // define url loadable options; + // update all set values in the default object + options.setOptionsFromURL = function ( opts, changeEditFlag ){ + if ( opts.sidebar !== undefined ) sidebar.showSidebar(parseInt(opts.sidebar), true); + if ( opts.doc ) { + var asInt = parseInt(opts.doc); + filterMenu.setDegreeSliderValue(asInt); + graphObject.setGlobalDOF(asInt); + // reset the value to be -1; + defaultOptionsConfig.doc = -1; + } + var settingFlag = false; + if ( opts.editorMode ) { + if ( opts.editorMode === "true" ) settingFlag = true; + d3.select("#editorModeModuleCheckbox").node().checked = settingFlag; + + if ( changeEditFlag && changeEditFlag === true ) { + graphObject.editorMode(settingFlag); + } + + // update config object + defaultOptionsConfig.editorMode = opts.editorMode; + + } + if ( opts.cd ) { // class distance + options.classDistance(opts.cd); // class distance + defaultOptionsConfig.cd = opts.cd; + } + if ( opts.dd ) { // data distance + options.datatypeDistance(opts.dd); + defaultOptionsConfig.cd = opts.cd; + } + if ( opts.cd || opts.dd ) options.gravityMenu().reset(); // reset the values so the slider is updated; + + + settingFlag = false; + if ( opts.filter_datatypes ) { + if ( opts.filter_datatypes === "true" ) settingFlag = true; + filterMenu.setCheckBoxValue("datatypeFilterCheckbox", settingFlag); + defaultOptionsConfig.filter_datatypes = opts.filter_datatypes; + } + if ( opts.debugFeatures ) { + if ( opts.debugFeatures === "true" ) settingFlag = true; + hideDebugOptions = settingFlag; + if ( options.getHideDebugFeatures() === false ) { + options.executeHiddenDebugFeatuers(); + } + defaultOptionsConfig.debugFeatures = opts.debugFeatures; + } + + settingFlag = false; + if ( opts.filter_objectProperties ) { + if ( opts.filter_objectProperties === "true" ) settingFlag = true; + filterMenu.setCheckBoxValue("objectPropertyFilterCheckbox", settingFlag); + defaultOptionsConfig.filter_objectProperties = opts.filter_objectProperties; + } + settingFlag = false; + if ( opts.filter_sco ) { + if ( opts.filter_sco === "true" ) settingFlag = true; + filterMenu.setCheckBoxValue("subclassFilterCheckbox", settingFlag); + defaultOptionsConfig.filter_sco = opts.filter_sco; + } + settingFlag = false; + if ( opts.filter_disjoint ) { + if ( opts.filter_disjoint === "true" ) settingFlag = true; + filterMenu.setCheckBoxValue("disjointFilterCheckbox", settingFlag); + defaultOptionsConfig.filter_disjoint = opts.filter_disjoint; + } + settingFlag = false; + if ( opts.filter_setOperator ) { + if ( opts.filter_setOperator === "true" ) settingFlag = true; + filterMenu.setCheckBoxValue("setoperatorFilterCheckbox", settingFlag); + defaultOptionsConfig.filter_setOperator = opts.filter_setOperator; + } + filterMenu.updateSettings(); + + // modesMenu + settingFlag = false; + if ( opts.mode_dynamic ) { + if ( opts.mode_dynamic === "true" ) settingFlag = true; + modeMenu.setDynamicLabelWidth(settingFlag); + dynamicLabelWidth = settingFlag; + defaultOptionsConfig.mode_dynamic = opts.mode_dynamic; + } + // settingFlag=false; + // THIS SHOULD NOT BE SET USING THE OPTIONS ON THE URL + // if (opts.mode_picnpin) { + // graph.options().filterMenu().setCheckBoxValue("pickandpin ModuleCheckbox", settingFlag); + // } + + settingFlag = false; + if ( opts.mode_pnp ) { + if ( opts.mode_pnp === "true" ) settingFlag = true; + modeMenu.setCheckBoxValue("pickandpinModuleCheckbox", settingFlag); + defaultOptionsConfig.mode_pnp = opts.mode_pnp; + } + + settingFlag = false; + if ( opts.mode_scaling ) { + if ( opts.mode_scaling === "true" ) settingFlag = true; + modeMenu.setCheckBoxValue("nodescalingModuleCheckbox", settingFlag); + defaultOptionsConfig.mode_scaling = opts.mode_scaling; + } + + settingFlag = false; + if ( opts.mode_compact ) { + if ( opts.mode_compact === "true" ) settingFlag = true; + modeMenu.setCheckBoxValue("compactnotationModuleCheckbox", settingFlag); + defaultOptionsConfig.mode_compact = opts.mode_compact; + } + + settingFlag = false; + if ( opts.mode_colorExt ) { + if ( opts.mode_colorExt === "true" ) settingFlag = true; + modeMenu.setCheckBoxValue("colorexternalsModuleCheckbox", settingFlag); + defaultOptionsConfig.mode_colorExt = opts.mode_colorExt; + } + + settingFlag = false; + if ( opts.mode_multiColor ) { + if ( opts.mode_multiColor === "true" ) settingFlag = true; + modeMenu.setColorSwitchStateUsingURL(settingFlag); + defaultOptionsConfig.mode_multiColor = opts.mode_multiColor; + } + modeMenu.updateSettingsUsingURL(); + options.rectangularRepresentation(opts.rect); + }; + + return options; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 65 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var OwlDisjointWith = __webpack_require__(46); + var attributeParser = __webpack_require__(66)(); + var equivalentPropertyMerger = __webpack_require__(67)(); + var nodePrototypeMap = __webpack_require__(5)(); + var propertyPrototypeMap = __webpack_require__(40)(); + + /** + * Encapsulates the parsing and preparation logic of the input data. + * @param graph the graph object that will be passed to the elements + * @returns {{}} + */ + module.exports = function ( graph ){ + var parser = {}, + nodes, + properties, + classMap, + settingsData, + settingsImported = false, + settingsImportGraphZoomAndTranslation = false, + dictionary = [], + propertyMap; + + parser.getDictionary = function (){ + return dictionary; + }; + + parser.setDictionary = function ( d ){ + dictionary = d; + }; + + parser.settingsImported = function (){ + return settingsImported; + }; + parser.settingsImportGraphZoomAndTranslation = function (){ + return settingsImportGraphZoomAndTranslation; + }; + + parser.parseSettings = function (){ + settingsImported = true; + settingsImportGraphZoomAndTranslation = false; + + if ( !settingsData ) { + settingsImported = false; + return; + } + /** global settings **********************************************************/ + if ( settingsData.global ) { + if ( settingsData.global.zoom ) { + var zoomFactor = settingsData.global.zoom; + graph.setZoom(zoomFactor); + settingsImportGraphZoomAndTranslation = true; + } + + if ( settingsData.global.translation ) { + var translation = settingsData.global.translation; + graph.setTranslation(translation); + settingsImportGraphZoomAndTranslation = true; + } + + if ( settingsData.global.paused ) { + var paused = settingsData.global.paused; + graph.options().pausedMenu().setPauseValue(paused); + } + } + /** Gravity Settings **********************************************************/ + if ( settingsData.gravity ) { + if ( settingsData.gravity.classDistance ) { + var classDistance = settingsData.gravity.classDistance; + graph.options().classDistance(classDistance); + } + if ( settingsData.gravity.datatypeDistance ) { + var datatypeDistance = settingsData.gravity.datatypeDistance; + graph.options().datatypeDistance(datatypeDistance); + } + graph.options().gravityMenu().reset(); // reads the options values and sets the gui values + } + + + // shared variable declaration + + var i; + var id; + var checked; + /** Filter Settings **********************************************************/ + if ( settingsData.filter ) { + // checkbox settings + if ( settingsData.filter.checkBox ) { + var filter_cb = settingsData.filter.checkBox; + for ( i = 0; i < filter_cb.length; i++ ) { + id = filter_cb[i].id; + checked = filter_cb[i].checked; + graph.options().filterMenu().setCheckBoxValue(id, checked); + } + } + // node degree filter settings + if ( settingsData.filter.degreeSliderValue ) { + var degreeSliderValue = settingsData.filter.degreeSliderValue; + graph.options().filterMenu().setDegreeSliderValue(degreeSliderValue); + } + graph.options().filterMenu().updateSettings(); + } + + /** Modes Setting **********************************************************/ + if ( settingsData.modes ) { + // checkbox settings + if ( settingsData.modes.checkBox ) { + var modes_cb = settingsData.modes.checkBox; + for ( i = 0; i < modes_cb.length; i++ ) { + id = modes_cb[i].id; + checked = modes_cb[i].checked; + graph.options().modeMenu().setCheckBoxValue(id, checked); + } + } + // color switch settings + var state = settingsData.modes.colorSwitchState; + // state could be undefined + if ( state === true || state === false ) { + graph.options().modeMenu().setColorSwitchState(state); + } + graph.options().modeMenu().updateSettings(); + } + graph.updateStyle(); // updates graph representation(setting charges and distances) + }; + + + /** + * Parses the ontology data and preprocesses it (e.g. connecting inverse properties and so on). + * @param ontologyData the loaded ontology json file + */ + parser.parse = function ( ontologyData ){ + if ( !ontologyData ) { + nodes = []; + properties = []; + dictionary = []; + return; + } + dictionary = []; + if ( ontologyData.settings ) settingsData = ontologyData.settings; + else settingsData = undefined; + + var classes = combineClasses(ontologyData.class, ontologyData.classAttribute), + datatypes = combineClasses(ontologyData.datatype, ontologyData.datatypeAttribute), + combinedClassesAndDatatypes = classes.concat(datatypes), + unparsedProperties = ontologyData.property || [], + combinedProperties; + + // Inject properties for unions, intersections, ... + addSetOperatorProperties(combinedClassesAndDatatypes, unparsedProperties); + combinedProperties = combineProperties(unparsedProperties, ontologyData.propertyAttribute); + classMap = mapElements(combinedClassesAndDatatypes); + propertyMap = mapElements(combinedProperties); + mergeRangesOfEquivalentProperties(combinedProperties, combinedClassesAndDatatypes); + + // Process the graph data + convertTypesToIris(combinedClassesAndDatatypes, ontologyData.namespace); + convertTypesToIris(combinedProperties, ontologyData.namespace); + nodes = createNodeStructure(combinedClassesAndDatatypes, classMap); + properties = createPropertyStructure(combinedProperties, classMap, propertyMap); + }; + + /** + * @return {Array} the preprocessed nodes + */ + parser.nodes = function (){ + return nodes; + }; + + /** + * @returns {Array} the preprocessed properties + */ + parser.properties = function (){ + return properties; + }; + + /** + * Combines the passed objects with its attributes and prototypes. This also applies + * attributes defined in the base of the prototype. + */ + function combineClasses( baseObjects, attributes ){ + var combinations = []; + var prototypeMap = createLowerCasePrototypeMap(nodePrototypeMap); + + if ( baseObjects ) { + baseObjects.forEach(function ( element ){ + var matchingAttribute; + + if ( attributes ) { + // Look for an attribute with the same id and merge them + for ( var i = 0; i < attributes.length; i++ ) { + var attribute = attributes[i]; + if ( element.id === attribute.id ) { + matchingAttribute = attribute; + break; + } + } + addAdditionalAttributes(element, matchingAttribute); + } + + // Then look for a prototype to add its properties + var Prototype = prototypeMap.get(element.type.toLowerCase()); + + if ( Prototype ) { + addAdditionalAttributes(element, Prototype); // TODO might be unnecessary + + var node = new Prototype(graph); + node.annotations(element.annotations) + .baseIri(element.baseIri) + .comment(element.comment) + .complement(element.complement) + .disjointUnion(element.disjointUnion) + .description(element.description) + .equivalents(element.equivalent) + .id(element.id) + .intersection(element.intersection) + .label(element.label) + // .type(element.type) Ignore, because we predefined it + .union(element.union) + .iri(element.iri); + if ( element.pos ) { + node.x = element.pos[0]; + node.y = element.pos[1]; + node.px = node.x; + node.py = node.y; + } + //class element pin + var elementPinned = element.pinned; + if ( elementPinned === true ) { + node.pinned(true); + graph.options().pickAndPinModule().addPinnedElement(node); + } + // Create node objects for all individuals + if ( element.individuals ) { + element.individuals.forEach(function ( individual ){ + var individualNode = new Prototype(graph); + individualNode.label(individual.labels) + .iri(individual.iri); + + node.individuals().push(individualNode); + }); + } + + if ( element.attributes ) { + var deduplicatedAttributes = d3.set(element.attributes.concat(node.attributes())); + node.attributes(deduplicatedAttributes.values()); + } + combinations.push(node); + } else { + console.error("Unknown element type: " + element.type); + } + }); + } + + return combinations; + } + + function combineProperties( baseObjects, attributes ){ + var combinations = []; + var prototypeMap = createLowerCasePrototypeMap(propertyPrototypeMap); + + if ( baseObjects ) { + baseObjects.forEach(function ( element ){ + var matchingAttribute; + + if ( attributes ) { + // Look for an attribute with the same id and merge them + for ( var i = 0; i < attributes.length; i++ ) { + var attribute = attributes[i]; + if ( element.id === attribute.id ) { + matchingAttribute = attribute; + break; + } + } + addAdditionalAttributes(element, matchingAttribute); + } + + // Then look for a prototype to add its properties + var Prototype = prototypeMap.get(element.type.toLowerCase()); + + if ( Prototype ) { + // Create the matching object and set the properties + var property = new Prototype(graph); + property.annotations(element.annotations) + .baseIri(element.baseIri) + .cardinality(element.cardinality) + .comment(element.comment) + .domain(element.domain) + .description(element.description) + .equivalents(element.equivalent) + .id(element.id) + .inverse(element.inverse) + .label(element.label) + .minCardinality(element.minCardinality) + .maxCardinality(element.maxCardinality) + .range(element.range) + .subproperties(element.subproperty) + .superproperties(element.superproperty) + // .type(element.type) Ignore, because we predefined it + .iri(element.iri); + + // adding property position + if ( element.pos ) { + property.x = element.pos[0]; + property.y = element.pos[1]; + property.px = element.pos[0]; + property.py = element.pos[1]; + } + var elementPinned = element.pinned; + if ( elementPinned === true ) { + property.pinned(true); + graph.options().pickAndPinModule().addPinnedElement(property); + } + + + if ( element.attributes ) { + var deduplicatedAttributes = d3.set(element.attributes.concat(property.attributes())); + property.attributes(deduplicatedAttributes.values()); + } + combinations.push(property); + } else { + console.error("Unknown element type: " + element.type); + } + + }); + } + + return combinations; + } + + function createLowerCasePrototypeMap( prototypeMap ){ + return d3.map(prototypeMap.values(), function ( Prototype ){ + return new Prototype().type().toLowerCase(); + }); + } + + function mergeRangesOfEquivalentProperties( properties, nodes ){ + // pass clones of arrays into the merger to keep the current functionality of this module + var newNodes = equivalentPropertyMerger.merge(properties.slice(), nodes.slice(), propertyMap, classMap, graph); + + // replace all the existing nodes and map the nodes again + nodes.length = 0; + Array.prototype.push.apply(nodes, newNodes); + classMap = mapElements(nodes); + } + + /** + * Checks all attributes which have to be rewritten. + * For example: + * equivalent is filled with only ID's of the corresponding nodes. It would be better to used the + * object instead of the ID so we swap the ID's with the correct object reference and can delete it from drawing + * because it is not necessary. + */ + function createNodeStructure( rawNodes, classMap ){ + var nodes = []; + + // Set the default values + var maxIndividualCount = 0; + rawNodes.forEach(function ( node ){ + maxIndividualCount = Math.max(maxIndividualCount, node.individuals().length); + node.visible(true); + }); + + rawNodes.forEach(function ( node ){ + // Merge and connect the equivalent nodes + processEquivalentIds(node, classMap); + + attributeParser.parseClassAttributes(node); + + node.maxIndividualCount(maxIndividualCount); + }); + + // Collect all nodes that should be displayed + rawNodes.forEach(function ( node ){ + if ( node.visible() ) { + nodes.push(node); + } + }); + + return nodes; + } + + /** + * Sets the disjoint attribute of the nodes if a disjoint label is found. + * @param property + */ + function processDisjoints( property ){ + if ( property instanceof OwlDisjointWith === false ) { + return; + } + + var domain = property.domain(), + range = property.range(); + + // Check the domain. + if ( !domain.disjointWith() ) { + domain.disjointWith([]); + } + + // Check the range. + if ( !range.disjointWith() ) { + range.disjointWith([]); + } + + domain.disjointWith().push(property.range()); + range.disjointWith().push(property.domain()); + } + + /** + * Connect all properties and also their sub- and superproperties. + * We iterate over the rawProperties array because it is way faster than iterating + * over an object and its attributes. + * + * @param rawProperties the properties + * @param classMap a map of all classes + * @param propertyMap the properties in a map + */ + function createPropertyStructure( rawProperties, classMap, propertyMap ){ + var properties = []; + // Set default values + rawProperties.forEach(function ( property ){ + property.visible(true); + }); + + // Connect properties + rawProperties.forEach(function ( property ){ + var domain, + range, + domainObject, + rangeObject, + inverse; + + /* Skip properties that have no information about their domain and range, like + inverse properties with optional inverse and optional domain and range attributes */ + if ( (property.domain() && property.range()) || property.inverse() ) { + + var inversePropertyId = findId(property.inverse()); + // Look if an inverse property exists + if ( inversePropertyId ) { + inverse = propertyMap[inversePropertyId]; + if ( !inverse ) { + console.warn("No inverse property was found for id: " + inversePropertyId); + property.inverse(undefined); + } + } + + // Either domain and range are set on this property or at the inverse + if ( typeof property.domain() !== "undefined" && typeof property.range() !== "undefined" ) { + domain = findId(property.domain()); + range = findId(property.range()); + + domainObject = classMap[domain]; + rangeObject = classMap[range]; + } else if ( inverse ) { + // Domain and range need to be switched + domain = findId(inverse.range()); + range = findId(inverse.domain()); + + domainObject = classMap[domain]; + rangeObject = classMap[range]; + } else { + console.warn("Domain and range not found for property: " + property.id()); + } + + // Set the references on this property + property.domain(domainObject); + property.range(rangeObject); + + // Also set the attributes of the inverse property + if ( inverse ) { + property.inverse(inverse); + inverse.inverse(property); + + // Switch domain and range + inverse.domain(rangeObject); + inverse.range(domainObject); + } + } + // Reference sub- and superproperties + referenceSubOrSuperProperties(property.subproperties()); + referenceSubOrSuperProperties(property.superproperties()); + }); + + // Merge equivalent properties and process disjoints. + rawProperties.forEach(function ( property ){ + processEquivalentIds(property, propertyMap); + processDisjoints(property); + + attributeParser.parsePropertyAttributes(property); + }); + // Add additional information to the properties + rawProperties.forEach(function ( property ){ + // Properties of merged classes should point to/from the visible equivalent class + var propertyWasRerouted = false; + + if ( property.domain() === undefined ) { + console.warn("No Domain was found for id:" + property.id()); + return; + } + + if ( wasNodeMerged(property.domain()) ) { + property.domain(property.domain().equivalentBase()); + propertyWasRerouted = true; + } + if ( property.range() === undefined ) { + console.warn("No range was found for id:" + property.id()); + return; + } + if ( wasNodeMerged(property.range()) ) { + property.range(property.range().equivalentBase()); + propertyWasRerouted = true; + } + // But there should not be two equal properties between the same domain and range + var equalProperty = getOtherEqualProperty(rawProperties, property); + + if ( propertyWasRerouted && equalProperty ) { + property.visible(false); + + equalProperty.redundantProperties().push(property); + } + + // Hide property if source or target node is hidden + if ( !property.domain().visible() || !property.range().visible() ) { + property.visible(false); + } + + // Collect all properties that should be displayed + if ( property.visible() ) { + properties.push(property); + } + }); + return properties; + } + + function referenceSubOrSuperProperties( subOrSuperPropertiesArray ){ + var i, l; + + if ( !subOrSuperPropertiesArray ) { + return; + } + + for ( i = 0, l = subOrSuperPropertiesArray.length; i < l; ++i ) { + var subOrSuperPropertyId = findId(subOrSuperPropertiesArray[i]); + var subOrSuperProperty = propertyMap[subOrSuperPropertyId]; + + if ( subOrSuperProperty ) { + // Replace id with object + subOrSuperPropertiesArray[i] = subOrSuperProperty; + } else { + console.warn("No sub-/superproperty was found for id: " + subOrSuperPropertyId); + } + } + } + + function wasNodeMerged( node ){ + return !node.visible() && node.equivalentBase(); + } + + function getOtherEqualProperty( properties, referenceProperty ){ + var i, l, property; + + for ( i = 0, l = properties.length; i < l; i++ ) { + property = properties[i]; + + if ( referenceProperty === property ) { + continue; + } + if ( referenceProperty.domain() !== property.domain() || + referenceProperty.range() !== property.range() ) { + continue; + } + + // Check for an equal IRI, if non existent compare label and type + if ( referenceProperty.iri() && property.iri() ) { + if ( referenceProperty.iri() === property.iri() ) { + return property; + } + } else if ( referenceProperty.type() === property.type() && + referenceProperty.defaultLabel() === property.defaultLabel() ) { + return property; + } + } + + return undefined; + } + + /** + * Generates and adds properties for links to set operators. + * @param classes unprocessed classes + * @param properties unprocessed properties + */ + function addSetOperatorProperties( classes, properties ){ + function addProperties( domainId, rangeIds, operatorType ){ + if ( !rangeIds ) { + return; + } + + rangeIds.forEach(function ( rangeId, index ){ + var property = { + id: "GENERATED-" + operatorType + "-" + domainId + "-" + rangeId + "-" + index, + type: "setOperatorProperty", + domain: domainId, + range: rangeId + }; + + properties.push(property); + }); + } + + classes.forEach(function ( clss ){ + addProperties(clss.id(), clss.complement(), "COMPLEMENT"); + addProperties(clss.id(), clss.intersection(), "INTERSECTION"); + addProperties(clss.id(), clss.union(), "UNION"); + addProperties(clss.id(), clss.disjointUnion(), "DISJOINTUNION"); + }); + } + + /** + * Replaces the ids of equivalent nodes/properties with the matching objects, cross references them + * and tags them as processed. + * @param element a node or a property + * @param elementMap a map where nodes/properties can be looked up + */ + function processEquivalentIds( element, elementMap ){ + var eqIds = element.equivalents(); + + if ( !eqIds || element.equivalentBase() ) { + return; + } + + // Replace ids with the corresponding objects + for ( var i = 0, l = eqIds.length; i < l; ++i ) { + var eqId = findId(eqIds[i]); + var eqObject = elementMap[eqId]; + + if ( eqObject ) { + // Cross reference both objects + eqObject.equivalents(eqObject.equivalents()); + eqObject.equivalents().push(element); + eqObject.equivalentBase(element); + eqIds[i] = eqObject; + + // Hide other equivalent nodes + eqObject.visible(false); + } else { + console.warn("No class/property was found for equivalent id: " + eqId); + } + } + } + + /** + * Tries to convert the type to an iri and sets it. + * @param elements classes or properties + * @param namespaces an array of namespaces + */ + function convertTypesToIris( elements, namespaces ){ + elements.forEach(function ( element ){ + if ( typeof element.iri() === "string" ) { + element.iri(replaceNamespace(element.iri(), namespaces)); + } + }); + } + + /** + * Creates a map by mapping the array with the passed function. + * @param array the array + * @returns {{}} + */ + function mapElements( array ){ + var map = {}; + for ( var i = 0, length = array.length; i < length; i++ ) { + var element = array[i]; + map[element.id()] = element; + } + return map; + } + + /** + * Adds the attributes of the additional object to the base object, but doesn't + * overwrite existing ones. + * + * @param base the base object + * @param addition the object with additional data + * @returns the combination is also returned + */ + function addAdditionalAttributes( base, addition ){ + // Check for an undefined value + addition = addition || {}; + + for ( var addAttribute in addition ) { + // Add the attribute if it doesn't exist + if ( !(addAttribute in base) && addition.hasOwnProperty(addAttribute) ) { + base[addAttribute] = addition[addAttribute]; + } + } + return base; + } + + /** + * Replaces the namespace (and the separator) if one exists and returns the new value. + * @param address the address with a namespace in it + * @param namespaces an array of namespaces + * @returns {string} the processed address with the (possibly) replaced namespace + */ + function replaceNamespace( address, namespaces ){ + var separatorIndex = address.indexOf(":"); + if ( separatorIndex === -1 ) { + return address; + } + var namespaceName = address.substring(0, separatorIndex); + + for ( var i = 0, length = namespaces.length; i < length; ++i ) { + var namespace = namespaces[i]; + if ( namespaceName === namespace.name ) { + return namespace.iri + address.substring(separatorIndex + 1); + } + } + + return address; + } + + /** + * Looks whether the passed object is already the id or if it was replaced + * with the object that belongs to the id. + * @param object an id, a class or a property + * @returns {string} the id of the passed object or undefined + */ + function findId( object ){ + if ( !object ) { + return undefined; + } else if ( typeof object === "string" ) { + return object; + } else if ( "id" in object ) { + return object.id(); + } else { + console.warn("No Id was found for this object: " + object); + return undefined; + } + } + + return parser; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 66 */ +/***/ (function(module, exports) { + + /** + * Parses the attributes an element has and sets the corresponding attributes. + * @returns {Function} + */ + module.exports = (function (){ + var attributeParser = {}, + // Style + ANONYMOUS = "anonymous", + DATATYPE = "datatype", + DEPRECATED = "deprecated", + EXTERNAL = "external", + OBJECT = "object", + RDF = "rdf", + // Representations + ASYMMETRIC = "asymmetric", + FUNCTIONAL = "functional", + INVERSE_FUNCTIONAL = "inverse functional", + IRREFLEXIVE = "irreflexive", + KEY = "key", + REFLEXIVE = "reflexive", + SYMMETRIC = "symmetric", + TRANSITIVE = "transitive", + // Attribute groups + VISUAL_ATTRIBUTE_GROUPS = [ + [DEPRECATED, DATATYPE, OBJECT, RDF], + [ANONYMOUS] + ], + CLASS_INDICATIONS = [DEPRECATED, EXTERNAL], + PROPERTY_INDICATIONS = [ASYMMETRIC, FUNCTIONAL, INVERSE_FUNCTIONAL, IRREFLEXIVE, KEY, REFLEXIVE, SYMMETRIC, + TRANSITIVE]; + + /** + * Parses and sets the attributes of a class. + * @param clazz + */ + attributeParser.parseClassAttributes = function ( clazz ){ + if ( !(clazz.attributes() instanceof Array) ) { + return; + } + + parseVisualAttributes(clazz); + parseClassIndications(clazz); + }; + + function parseVisualAttributes( element ){ + VISUAL_ATTRIBUTE_GROUPS.forEach(function ( attributeGroup ){ + setVisualAttributeOfGroup(element, attributeGroup); + }); + } + + function setVisualAttributeOfGroup( element, group ){ + var i, l, attribute; + + for ( i = 0, l = group.length; i < l; i++ ) { + attribute = group[i]; + if ( element.attributes().indexOf(attribute) >= 0 ) { + element.visualAttributes().push(attribute); + + // Just a single attribute is possible + break; + } + } + } + + function parseClassIndications( clazz ){ + var i, l, indication; + + for ( i = 0, l = CLASS_INDICATIONS.length; i < l; i++ ) { + indication = CLASS_INDICATIONS[i]; + + if ( clazz.attributes().indexOf(indication) >= 0 ) { + clazz.indications().push(indication); + } + } + } + + /** + * Parses and sets the attributes of a property. + * @param property + */ + attributeParser.parsePropertyAttributes = function ( property ){ + if ( !(property.attributes() instanceof Array) ) { + return; + } + + parseVisualAttributes(property); + parsePropertyIndications(property); + }; + + function parsePropertyIndications( property ){ + var i, l, indication; + + for ( i = 0, l = PROPERTY_INDICATIONS.length; i < l; i++ ) { + indication = PROPERTY_INDICATIONS[i]; + + if ( property.attributes().indexOf(indication) >= 0 ) { + property.indications().push(indication); + } + } + } + + + return function (){ + // Return a function to keep module interfaces consistent + return attributeParser; + }; + })(); + + +/***/ }), +/* 67 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var OwlThing = __webpack_require__(31); + var RdfsLiteral = __webpack_require__(38); + var elementTools = __webpack_require__(63)(); + + var equivalentPropertyMerger = {}; + module.exports = function (){ + return equivalentPropertyMerger; + }; + + var PREFIX = "GENERATED-MERGED_RANGE-"; + var OBJECT_PROPERTY_DEFAULT_RANGE_TYPE = "owl:Thing"; + var DATA_PROPERTY_DEFAULT_RANGE_TYPE = "rdfs:Literal"; + + + equivalentPropertyMerger.merge = function ( properties, nodes, propertyMap, nodeMap, graph ){ + var totalNodeIdsToHide = d3.set(); + var processedPropertyIds = d3.set(); + var mergeNodes = []; + + for ( var i = 0; i < properties.length; i++ ) { + var property = properties[i]; + var equivalents = property.equivalents().map(createIdToPropertyMapper(propertyMap)); + + if ( equivalents.length === 0 || processedPropertyIds.has(property.id()) ) { + continue; + } + + var propertyWithEquivalents = equivalents.concat(property); + + var mergeNode = findMergeNode(propertyWithEquivalents, nodeMap); + if ( !mergeNode ) { + if ( mergeNode !== undefined ) { + mergeNode = createDefaultMergeNode(property, graph); + mergeNodes.push(mergeNode); + } + } + + var nodeIdsToHide = replaceRangesAndCollectNodesToHide(propertyWithEquivalents, mergeNode, properties, + processedPropertyIds); + for ( var j = 0; j < nodeIdsToHide.length; j++ ) { + totalNodeIdsToHide.add(nodeIdsToHide[j]); + } + } + + return filterVisibleNodes(nodes.concat(mergeNodes), totalNodeIdsToHide); + }; + + + function createIdToPropertyMapper( propertyMap ){ + return function ( id ){ + return propertyMap[id]; + }; + } + + function findMergeNode( propertyWithEquivalents, nodeMap ){ + var typeMap = mapPropertiesRangesToType(propertyWithEquivalents, nodeMap); + var typeSet = d3.set(typeMap.keys()); + + // default types are the fallback values and should be ignored for the type determination + typeSet.remove(OBJECT_PROPERTY_DEFAULT_RANGE_TYPE); + typeSet.remove(DATA_PROPERTY_DEFAULT_RANGE_TYPE); + + // exactly one type to chose from -> take the node of this type as range + if ( typeSet.size() === 1 ) { + var type = typeSet.values()[0]; + var ranges = typeMap.get(type); + + if ( ranges.length === 1 ) { + return ranges[0]; + } + } + } + + function mapPropertiesRangesToType( properties, nodeMap ){ + var typeMap = d3.map(); + + properties.forEach(function ( property ){ + if ( property === undefined ) //@ WORKAROUND + return; + + var range = nodeMap[property.range()]; + var type = range.type(); + + if ( !typeMap.has(type) ) { + typeMap.set(type, []); + } + + typeMap.get(type).push(range); + }); + + return typeMap; + } + + function createDefaultMergeNode( property, graph ){ + var range; + + if ( elementTools.isDatatypeProperty(property) ) { + range = new RdfsLiteral(graph); + } else { + range = new OwlThing(graph); + } + range.id(PREFIX + property.id()); + + return range; + } + + function replaceRangesAndCollectNodesToHide( propertyWithEquivalents, mergeNode, properties, processedPropertyIds ){ + var nodesToHide = []; + + propertyWithEquivalents.forEach(function ( property ){ + + if ( property === undefined || mergeNode === undefined ) // @ WORKAROUND + return; + var oldRangeId = property.range(); + property.range(mergeNode.id()); + if ( !isDomainOrRangeOfOtherProperty(oldRangeId, properties) ) { + nodesToHide.push(oldRangeId); + } + + processedPropertyIds.add(property.id()); + }); + + return nodesToHide; + } + + function isDomainOrRangeOfOtherProperty( nodeId, properties ){ + for ( var i = 0; i < properties.length; i++ ) { + var property = properties[i]; + if ( property.domain() === nodeId || property.range() === nodeId ) { + return true; + } + } + + return false; + } + + function filterVisibleNodes( nodes, nodeIdsToHide ){ + var filteredNodes = []; + + nodes.forEach(function ( node ){ + if ( !nodeIdsToHide.has(node.id()) ) { + filteredNodes.push(node); + } + }); + + return filteredNodes; + } + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 68 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( graph ){ + /** variable defs **/ + var Class_dragger = {}; + Class_dragger.nodeId = 10001; + Class_dragger.parent = undefined; + Class_dragger.x = 0; + Class_dragger.y = 0; + Class_dragger.rootElement = undefined; + Class_dragger.rootNodeLayer = undefined; + Class_dragger.pathLayer = undefined; + Class_dragger.mouseEnteredVar = false; + Class_dragger.mouseButtonPressed = false; + Class_dragger.nodeElement = undefined; + Class_dragger.draggerObject = undefined; + Class_dragger.pathElement = undefined; + Class_dragger.typus = "Class_dragger"; + + Class_dragger.type = function (){ + return Class_dragger.typus; + }; + + Class_dragger.parentNode = function (){ + return Class_dragger.parent; + }; + + Class_dragger.hideClass_dragger = function ( val ){ + Class_dragger.pathElement.classed("hidden", val); + Class_dragger.nodeElement.classed("hidden", val); + Class_dragger.draggerObject.classed("hidden", val); + }; + + Class_dragger.setParentNode = function ( parentNode ){ + Class_dragger.parent = parentNode; + + if ( Class_dragger.mouseButtonPressed === false ) { + if ( Class_dragger.parent.actualRadius && Class_dragger.parent.actualRadius() ) { + Class_dragger.x = Class_dragger.parent.x + 10 + Class_dragger.parent.actualRadius(); + Class_dragger.y = Class_dragger.parent.y + 10 + Class_dragger.parent.actualRadius(); + } else { + Class_dragger.x = Class_dragger.parent.x + 60; + Class_dragger.y = Class_dragger.parent.y + 60; + } + } + Class_dragger.updateElement(); + }; + + Class_dragger.hideDragger = function ( val ){ + if ( Class_dragger.pathElement ) Class_dragger.pathElement.classed("hidden", val); + if ( Class_dragger.nodeElement ) Class_dragger.nodeElement.classed("hidden", val); + if ( Class_dragger.draggerObject ) Class_dragger.draggerObject.classed("hidden", val); + + }; + /** BASE HANDLING FUNCTIONS ------------------------------------------------- **/ + Class_dragger.id = function ( index ){ + if ( !arguments.length ) { + return Class_dragger.nodeId; + } + Class_dragger.nodeId = index; + }; + + Class_dragger.svgPathLayer = function ( layer ){ + Class_dragger.pathLayer = layer.append('g'); + }; + + Class_dragger.svgRoot = function ( root ){ + if ( !arguments.length ) + return Class_dragger.rootElement; + Class_dragger.rootElement = root; + Class_dragger.rootNodeLayer = Class_dragger.rootElement.append('g'); + Class_dragger.addMouseEvents(); + }; + + /** DRAWING FUNCTIONS ------------------------------------------------- **/ + Class_dragger.drawNode = function (){ + Class_dragger.pathElement = Class_dragger.pathLayer.append('line') + .classed("classNodeDragPath", true); + Class_dragger.pathElement.attr("x1", 0) + .attr("y1", 0) + .attr("x2", 0) + .attr("y2", 0); + + // var lineData = [ + // {"x": 0, "y": 0}, + // {"x": 0, "y": 40}, + // {"x": -40, "y": 0}, + // {"x": 0, "y": -40}, + // {"x": 0, "y": 0} + // ]; + + var lineData = [ + { "x": -40, "y": 0 }, // start + { "x": -20, "y": -10 }, + { "x": 20, "y": -50 }, + { "x": -10, "y": 0 }, // center + { "x": 20, "y": 50 }, + { "x": -20, "y": 10 }, + { "x": -40, "y": 0 } + ]; + + + var lineFunction = d3.svg.line() + .x(function ( d ){ + return d.x; + }) + .y(function ( d ){ + return d.y; + }) + .interpolate("basis-closed"); + var pathData = "M 20,40 C 0,15 0,-15 20,-40 L -40,0 Z"; + // var pathData="M 20,40 C 0,15 0,-15 20,-40 20,-40 -35.22907,-23.905556 -45.113897,0.06313453 -35.22907,20.095453 20,40 20,40 Z"; + // var pathData="M 39.107144,51.25 C 0,17.362169 0,-13.75 39.285715,-49.821429 c 0,0 -69.58321,34.511175 -100.714286,50.35714329 C -22.96643,20.324376 39.107144,51.25 39.107144,51.25 Z"; + + Class_dragger.nodeElement = Class_dragger.rootNodeLayer.append('path').attr("d", pathData); + Class_dragger.nodeElement.classed("classDraggerNode", true); + Class_dragger.draggerObject = Class_dragger.rootNodeLayer.append("circle"); + if ( graph.options().useAccuracyHelper() ) { + Class_dragger.draggerObject.attr("r", 40) + .attr("cx", 0) + .attr("cy", 0) + .classed("superHiddenElement", true); + Class_dragger.draggerObject.classed("superOpacityElement", !graph.options().showDraggerObject()); + } + + + }; + + Class_dragger.updateElement = function (){ + + // Class_dragger.pathLayer.attr("transform", "translate(" + Class_dragger.x + "," + Class_dragger.y + ")"); + // Class_dragger.rootElement.attr("transform", "translate(" + Class_dragger.x + "," + Class_dragger.y + ")"); + if ( Class_dragger.pathElement ) { + + // compute start point ; + + + var sX = Class_dragger.parent.x, + sY = Class_dragger.parent.y, + eX = Class_dragger.x, + eY = Class_dragger.y; + + + // this is used only when you dont have a proper layout ordering; + var dirX = eX - sX; + var dirY = eY - sY; + var len = Math.sqrt((dirX * dirX) + (dirY * dirY)); + + var nX = dirX / len; + var nY = dirY / len; + + var ppX = sX + nX * Class_dragger.parent.actualRadius(); + var ppY = sY + nY * Class_dragger.parent.actualRadius(); + + var ncx = nX * 15; + var ncy = nY * 15; + Class_dragger.draggerObject.attr("cx", ncx) + .attr("cy", ncy); + + Class_dragger.pathElement.attr("x1", ppX) + .attr("y1", ppY) + .attr("x2", eX) + .attr("y2", eY); + } + var angle = Math.atan2(Class_dragger.parent.y - Class_dragger.y, Class_dragger.parent.x - Class_dragger.x) * 180 / Math.PI; + + Class_dragger.nodeElement.attr("transform", "translate(" + Class_dragger.x + "," + Class_dragger.y + ")" + "rotate(" + angle + ")"); + Class_dragger.draggerObject.attr("transform", "translate(" + Class_dragger.x + "," + Class_dragger.y + ")"); + // console.log("update Elmenent root element"+Class_dragger.x + "," + Class_dragger.y ); + // + // Class_dragger.nodeElement.attr("transform", function (d) { + // return "rotate(" + angle + ")"; + // }); + }; + + /** MOUSE HANDLING FUNCTIONS ------------------------------------------------- **/ + + Class_dragger.addMouseEvents = function (){ + // console.log("adding mouse events"); + Class_dragger.rootNodeLayer.selectAll("*").on("mouseover", Class_dragger.onMouseOver) + .on("mouseout", Class_dragger.onMouseOut) + .on("click", function (){ + }) + .on("dblclick", function (){ + }) + .on("mousedown", Class_dragger.mouseDown) + .on("mouseup", Class_dragger.mouseUp); + }; + + Class_dragger.mouseDown = function (){ + Class_dragger.nodeElement.style("cursor", "move"); + Class_dragger.nodeElement.classed("classDraggerNodeHovered", true); + Class_dragger.mouseButtonPressed = true; + console.log("Mouse DOWN from Dragger"); + }; + + Class_dragger.mouseUp = function (){ + Class_dragger.nodeElement.style("cursor", "auto"); + Class_dragger.mouseButtonPressed = false; + console.log("Mouse UP from Dragger"); + }; + + + Class_dragger.mouseEntered = function ( p ){ + if ( !arguments.length ) return Class_dragger.mouseEnteredVar; + Class_dragger.mouseEnteredVar = p; + return Class_dragger; + }; + + Class_dragger.selectedViaTouch = function ( val ){ + Class_dragger.nodeElement.classed("classDraggerNode", !val); + Class_dragger.nodeElement.classed("classDraggerNodeHovered", val); + + }; + + Class_dragger.onMouseOver = function (){ + if ( Class_dragger.mouseEntered() ) { + return; + } + Class_dragger.nodeElement.classed("classDraggerNode", false); + Class_dragger.nodeElement.classed("classDraggerNodeHovered", true); + var selectedNode = Class_dragger.rootElement.node(), + nodeContainer = selectedNode.parentNode; + nodeContainer.appendChild(selectedNode); + + Class_dragger.mouseEntered(true); + + }; + Class_dragger.onMouseOut = function (){ + if ( Class_dragger.mouseButtonPressed === true ) + return; + Class_dragger.nodeElement.classed("classDraggerNodeHovered", false); + Class_dragger.nodeElement.classed("classDraggerNode", true); + Class_dragger.mouseEntered(false); + }; + + Class_dragger.setPosition = function ( x, y ){ + + Class_dragger.x = x; + Class_dragger.y = y; + Class_dragger.updateElement(); + }; + + Class_dragger.setAdditionalClassForClass_dragger = function ( name, val ){ + // console.log("Class_dragger should sett the class here") + // Class_dragger.nodeElement.classed(name,val); + + }; + return Class_dragger; + }; + + + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 69 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( graph ){ + /** variable defs **/ + var Range_dragger = {}; + Range_dragger.nodeId = 10002; + Range_dragger.parent = undefined; + Range_dragger.x = 0; + Range_dragger.y = 0; + Range_dragger.rootElement = undefined; + Range_dragger.rootNodeLayer = undefined; + Range_dragger.pathLayer = undefined; + Range_dragger.mouseEnteredVar = false; + Range_dragger.mouseButtonPressed = false; + Range_dragger.nodeElement = undefined; + Range_dragger.draggerObject = undefined; + + Range_dragger.pathElement = undefined; + Range_dragger.typus = "Range_dragger"; + + Range_dragger.type = function (){ + return Range_dragger.typus; + }; + + // TODO: We need the endPoint of the Link here! + Range_dragger.parentNode = function (){ + return Range_dragger.parent; + }; + + Range_dragger.hide_dragger = function ( val ){ + Range_dragger.pathElement.classed("hidden", val); + Range_dragger.nodeElement.classed("hidden", val); + Range_dragger.draggerObject.classed("hidden", val); + }; + Range_dragger.hideDragger = function ( val ){ + if ( Range_dragger.pathElement ) Range_dragger.pathElement.classed("hidden", val); + if ( Range_dragger.nodeElement ) Range_dragger.nodeElement.classed("hidden", val); + if ( Range_dragger.draggerObject ) Range_dragger.draggerObject.classed("hidden", val); + + + }; + + Range_dragger.reDrawEverthing = function (){ + Range_dragger.setParentProperty(Range_dragger.parent); + }; + Range_dragger.updateRange = function ( newRange ){ + + if ( graph.genericPropertySanityCheck(Range_dragger.parent.domain(), newRange, + Range_dragger.parent.type(), + "Could not update range", "Restoring previous range") === false ) return; + + // check for triple duplicates! + + if ( graph.propertyCheckExistenceChecker(Range_dragger.parent, Range_dragger.parent.domain(), newRange) === false ) + return; + if ( Range_dragger.parent.labelElement() === undefined ) return; + if ( Range_dragger.parent.labelElement().attr("transform") === "translate(0,15)" || + Range_dragger.parent.labelElement().attr("transform") === "translate(0,-15)" ) { + var prop = Range_dragger.parent; + Range_dragger.parent.inverse().inverse(null); + Range_dragger.parent.inverse(null); + prop.range(newRange); + } + + else { + Range_dragger.parent.range(newRange); + } + // update the position of the new range + var rX = newRange.x; + var rY = newRange.y; + + var dX = Range_dragger.parent.domain().x; + var dY = Range_dragger.parent.domain().y; + + + // center + var cX = 0.49 * (dX + rX); + var cY = 0.49 * (dY + rY); + // put position there; + Range_dragger.parent.labelElement().x = cX; + Range_dragger.parent.labelElement().px = cX; + Range_dragger.parent.labelElement().y = cY; + Range_dragger.parent.labelElement().py = cY; + + }; + + Range_dragger.setParentProperty = function ( parentProperty, inversed ){ + Range_dragger.parent = parentProperty; + var iP; + var renElem; + Range_dragger.isLoopProperty = false; + if ( parentProperty.domain() === parentProperty.range() ) Range_dragger.isLoopProperty = true; + Range_dragger.parent = parentProperty; + renElem = parentProperty.labelObject(); + if ( inversed === true ) { + if ( parentProperty.labelElement() && parentProperty.labelElement().attr("transform") === "translate(0,15)" ) { + iP = renElem.linkDomainIntersection; + if ( renElem.linkDomainIntersection ) { + Range_dragger.x = iP.x; + Range_dragger.y = iP.y; + } + } else { + iP = renElem.linkRangeIntersection; + if ( renElem.linkRangeIntersection ) { + Range_dragger.x = iP.x; + Range_dragger.y = iP.y; + } + } + } + else { + iP = renElem.linkRangeIntersection; + if ( renElem.linkRangeIntersection ) { + Range_dragger.x = iP.x; + Range_dragger.y = iP.y; + } + } + + Range_dragger.updateElement(); + }; + + + /** BASE HANDLING FUNCTIONS ------------------------------------------------- **/ + Range_dragger.id = function ( index ){ + if ( !arguments.length ) { + return Range_dragger.nodeId; + } + Range_dragger.nodeId = index; + }; + + Range_dragger.svgPathLayer = function ( layer ){ + Range_dragger.pathLayer = layer.append('g'); + }; + + Range_dragger.svgRoot = function ( root ){ + if ( !arguments.length ) + return Range_dragger.rootElement; + Range_dragger.rootElement = root; + Range_dragger.rootNodeLayer = Range_dragger.rootElement.append('g'); + Range_dragger.addMouseEvents(); + }; + + /** DRAWING FUNCTIONS ------------------------------------------------- **/ + Range_dragger.drawNode = function (){ + Range_dragger.pathElement = Range_dragger.pathLayer.append('line') + .classed("classNodeDragPath", true); + Range_dragger.pathElement.attr("x1", 0) + .attr("y1", 0) + .attr("x2", 0) + .attr("y2", 0); + + // var lineData = [ + // {"x": 0, "y": 0}, + // {"x": 0, "y": 40}, + // {"x": -40, "y": 0}, + // {"x": 0, "y": -40}, + // {"x": 0, "y": 0} + // ]; + + var lineData = [ + { "x": -40, "y": 0 }, // start + { "x": -20, "y": -10 }, + { "x": 20, "y": -50 }, + { "x": -10, "y": 0 }, // center + { "x": 20, "y": 50 }, + { "x": -20, "y": 10 }, + { "x": -40, "y": 0 } + ]; + + + var lineFunction = d3.svg.line() + .x(function ( d ){ + return d.x; + }) + .y(function ( d ){ + return d.y; + }) + .interpolate("basis-closed"); + var pathData = "M 61,40 C 41,15 41,-15 61,-40 L 1,0 Z"; + + Range_dragger.nodeElement = Range_dragger.rootNodeLayer.append('path').attr("d", pathData); + Range_dragger.nodeElement.classed("classDraggerNode", true); + if ( graph.options().useAccuracyHelper() ) { + Range_dragger.draggerObject = Range_dragger.rootNodeLayer.append("circle"); + Range_dragger.draggerObject.attr("r", 40) + .attr("cx", 0) + .attr("cy", 0) + .classed("superHiddenElement", true); + Range_dragger.draggerObject.classed("superOpacityElement", !graph.options().showDraggerObject()); + } + + + }; + + Range_dragger.updateElementViaDomainDragger = function ( x, y ){ + + var range_x = x; + var range_y = y; + + var dex = Range_dragger.parent.range().x; + var dey = Range_dragger.parent.range().y; + + var dir_X = x - dex; + var dir_Y = y - dey; + + var len = Math.sqrt(dir_X * dir_X + dir_Y * dir_Y); + + var nX = dir_X / len; + var nY = dir_Y / len; + + + var ep_range_x = dex + nX * Range_dragger.parent.range().actualRadius(); + var ep_range_y = dey + nY * Range_dragger.parent.range().actualRadius(); + + + var dx = range_x - ep_range_x; + var dy = range_y - ep_range_y; + len = Math.sqrt(dx * dx + dy * dy); + nX = dx / len; + nY = dy / len; + + var angle = Math.atan2(ep_range_y - range_y, ep_range_x - range_x) * 180 / Math.PI + 180; + Range_dragger.nodeElement.attr("transform", "translate(" + ep_range_x + "," + ep_range_y + ")" + "rotate(" + angle + ")"); + var doX = ep_range_x + nX * 40; + var doY = ep_range_y + nY * 40; + Range_dragger.draggerObject.attr("transform", "translate(" + doX + "," + doY + ")"); + + }; + + + Range_dragger.updateElement = function (){ + if ( Range_dragger.mouseButtonPressed === true || Range_dragger.parent === undefined ) return; + + var range = Range_dragger.parent.range(); + var iP = Range_dragger.parent.labelObject().linkRangeIntersection; + if ( Range_dragger.parent.labelElement() === undefined ) return; + var offsetForLoop = 48; + if ( Range_dragger.parent.labelElement().attr("transform") === "translate(0,15)" ) { + range = Range_dragger.parent.inverse().domain(); + iP = Range_dragger.parent.labelObject().linkDomainIntersection; + offsetForLoop = -48; + } + + if ( iP === undefined ) return; + var range_x = range.x; + var range_y = range.y; + + var ep_range_x = iP.x; + var ep_range_y = iP.y; + // offset for dragger object + var dx = range_x - ep_range_x; + var dy = range_y - ep_range_y; + var len = Math.sqrt(dx * dx + dy * dy); + var nX = dx / len; + var nY = dy / len; + var angle = Math.atan2(ep_range_y - range_y, ep_range_x - range_x) * 180 / Math.PI; + + var doX = ep_range_x - nX * 40; + var doY = ep_range_y - nY * 40; + + if ( Range_dragger.isLoopProperty === true ) + angle -= offsetForLoop; + + + Range_dragger.nodeElement.attr("transform", "translate(" + ep_range_x + "," + ep_range_y + ")" + "rotate(" + angle + ")"); + Range_dragger.draggerObject.attr("transform", "translate(" + doX + "," + doY + ")"); + + + }; + + /** MOUSE HANDLING FUNCTIONS ------------------------------------------------- **/ + + Range_dragger.addMouseEvents = function (){ + var rootLayer = Range_dragger.rootNodeLayer.selectAll("*"); + rootLayer.on("mouseover", Range_dragger.onMouseOver) + .on("mouseout", Range_dragger.onMouseOut) + .on("click", function (){ + }) + .on("dblclick", function (){ + }) + .on("mousedown", Range_dragger.mouseDown) + .on("mouseup", Range_dragger.mouseUp); + }; + + Range_dragger.mouseDown = function (){ + Range_dragger.nodeElement.style("cursor", "move"); + Range_dragger.nodeElement.classed("classDraggerNodeHovered", true); + Range_dragger.mouseButtonPressed = true; + }; + + Range_dragger.mouseUp = function (){ + Range_dragger.nodeElement.style("cursor", "auto"); + Range_dragger.nodeElement.classed("classDraggerNodeHovered", false); + Range_dragger.mouseButtonPressed = false; + }; + + + Range_dragger.mouseEntered = function ( p ){ + if ( !arguments.length ) return Range_dragger.mouseEnteredVar; + Range_dragger.mouseEnteredVar = p; + return Range_dragger; + }; + + Range_dragger.selectedViaTouch = function ( val ){ + Range_dragger.nodeElement.classed("classDraggerNode", !val); + Range_dragger.nodeElement.classed("classDraggerNodeHovered", val); + + }; + + Range_dragger.onMouseOver = function (){ + if ( Range_dragger.mouseEntered() ) { + return; + } + Range_dragger.nodeElement.classed("classDraggerNode", false); + Range_dragger.nodeElement.classed("classDraggerNodeHovered", true); + var selectedNode = Range_dragger.rootElement.node(), + nodeContainer = selectedNode.parentNode; + nodeContainer.appendChild(selectedNode); + + Range_dragger.mouseEntered(true); + + }; + Range_dragger.onMouseOut = function (){ + if ( Range_dragger.mouseButtonPressed === true ) + return; + Range_dragger.nodeElement.classed("classDraggerNodeHovered", false); + Range_dragger.nodeElement.classed("classDraggerNode", true); + Range_dragger.mouseEntered(false); + }; + + Range_dragger.setPosition = function ( x, y ){ + var range_x = Range_dragger.parent.domain().x; + var range_y = Range_dragger.parent.domain().y; + + // var position of the rangeEndPoint + var ep_range_x = x; + var ep_range_y = y; + + // offset for dragger object + var dx = range_x - ep_range_x; + var dy = range_y - ep_range_y; + + var len = Math.sqrt(dx * dx + dy * dy); + + var nX = dx / len; + var nY = dy / len; + + + var angle = Math.atan2(dy, dx) * 180 / Math.PI; + var doX = ep_range_x + nX * 40; + var doY = ep_range_y + nY * 40; + Range_dragger.nodeElement.attr("transform", "translate(" + ep_range_x + "," + ep_range_y + ")" + "rotate(" + angle + ")"); + Range_dragger.draggerObject.attr("transform", "translate(" + doX + "," + doY + ")"); + Range_dragger.x = x; + Range_dragger.y = y; + + }; + + Range_dragger.setAdditionalClassForClass_dragger = function ( name, val ){ + + }; + return Range_dragger; + }; + + + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 70 */ +/***/ (function(module, exports) { + + module.exports = function ( graph ){ + /** variable defs **/ + var Domain_dragger = {}; + Domain_dragger.nodeId = 10002; + Domain_dragger.parent = undefined; + Domain_dragger.x = 0; + Domain_dragger.y = 0; + Domain_dragger.rootElement = undefined; + Domain_dragger.rootNodeLayer = undefined; + Domain_dragger.pathLayer = undefined; + Domain_dragger.mouseEnteredVar = false; + Domain_dragger.mouseButtonPressed = false; + Domain_dragger.nodeElement = undefined; + Domain_dragger.draggerObject = undefined; + + Domain_dragger.pathElement = undefined; + Domain_dragger.typus = "Domain_dragger"; + + Domain_dragger.type = function (){ + return Domain_dragger.typus; + }; + + + // TODO: We need the endPoint of the Link here! + Domain_dragger.parentNode = function (){ + return Domain_dragger.parent; + }; + + Domain_dragger.hide_dragger = function ( val ){ + Domain_dragger.pathElement.classed("hidden", val); + Domain_dragger.nodeElement.classed("hidden", val); + Domain_dragger.draggerObject.classed("hidden", val); + }; + + Domain_dragger.reDrawEverthing = function (){ + Domain_dragger.setParentProperty(Domain_dragger.parent); + }; + Domain_dragger.updateDomain = function ( newDomain ){ + + if ( graph.genericPropertySanityCheck(Domain_dragger.parent.range(), newDomain, Domain_dragger.parent.type(), + "Could not update domain", "Restoring previous domain") === false ) { + Domain_dragger.updateElement(); + return; + } + + if ( graph.propertyCheckExistenceChecker(Domain_dragger.parent, newDomain, Domain_dragger.parent.range()) === false ) + return; + + + if ( Domain_dragger.parent.labelElement() === undefined ) { + Domain_dragger.updateElement(); + return; + } + if ( Domain_dragger.parent.labelElement().attr("transform") === "translate(0,15)" || + Domain_dragger.parent.labelElement().attr("transform") === "translate(0,-15)" ) { + var prop = Domain_dragger.parent; + Domain_dragger.parent.inverse().inverse(null); + Domain_dragger.parent.inverse(null); + console.log("SPLITTING ITEMS!"); + prop.domain(newDomain); + } + else { + Domain_dragger.parent.domain(newDomain); + } + + // update the position of the new range + var rX = Domain_dragger.parent.range().x; + var rY = Domain_dragger.parent.range().y; + var dX = newDomain.x; + var dY = newDomain.y; + + // center + var cX = 0.49 * (dX + rX); + var cY = 0.49 * (dY + rY); + // put position there; + Domain_dragger.parent.labelObject().x = cX; + Domain_dragger.parent.labelObject().px = cX; + Domain_dragger.parent.labelObject().y = cY; + Domain_dragger.parent.labelObject().py = cY; + Domain_dragger.updateElement(); + + }; + + Domain_dragger.setParentProperty = function ( parentProperty, inverted ){ + Domain_dragger.invertedProperty = inverted; + var renElem; + var iP; + Domain_dragger.isLoopProperty = false; + if ( parentProperty.domain() === parentProperty.range() ) + Domain_dragger.isLoopProperty = true; + + Domain_dragger.parent = parentProperty; + renElem = parentProperty.labelObject(); + if ( inverted === true ) { + + // this is the lower element + if ( parentProperty.labelElement() && parentProperty.labelElement().attr("transform") === "translate(0,15)" ) { + // console.log("This is the lower element!"); + iP = renElem.linkRangeIntersection; + if ( renElem.linkRangeIntersection ) { + Domain_dragger.x = iP.x; + Domain_dragger.y = iP.y; + } + } + else { + // console.log("This is the upper element"); + iP = renElem.linkDomainIntersection; + if ( renElem.linkDomainIntersection ) { + Domain_dragger.x = iP.x; + Domain_dragger.y = iP.y; + } + } + } + else { + // console.log("This is single element"); + iP = renElem.linkDomainIntersection; + if ( renElem.linkDomainIntersection ) { + Domain_dragger.x = iP.x; + Domain_dragger.y = iP.y; + } + } + Domain_dragger.updateElement(); + + }; + + Domain_dragger.hideDragger = function ( val ){ + if ( Domain_dragger.pathElement ) Domain_dragger.pathElement.classed("hidden", val); + if ( Domain_dragger.nodeElement ) Domain_dragger.nodeElement.classed("hidden", val); + if ( Domain_dragger.draggerObject ) Domain_dragger.draggerObject.classed("hidden", val); + + + }; + /** BASE HANDLING FUNCTIONS ------------------------------------------------- **/ + Domain_dragger.id = function ( index ){ + if ( !arguments.length ) { + return Domain_dragger.nodeId; + } + Domain_dragger.nodeId = index; + }; + + Domain_dragger.svgPathLayer = function ( layer ){ + Domain_dragger.pathLayer = layer.append('g'); + }; + + Domain_dragger.svgRoot = function ( root ){ + if ( !arguments.length ) + return Domain_dragger.rootElement; + Domain_dragger.rootElement = root; + Domain_dragger.rootNodeLayer = Domain_dragger.rootElement.append('g'); + Domain_dragger.addMouseEvents(); + }; + + /** DRAWING FUNCTIONS ------------------------------------------------- **/ + Domain_dragger.drawNode = function (){ + Domain_dragger.pathElement = Domain_dragger.pathLayer.append('line') + .classed("classNodeDragPath", true); + Domain_dragger.pathElement.attr("x1", 0) + .attr("y1", 0) + .attr("x2", 0) + .attr("y2", 0); + + var pathData = "M 10,40 C -10,15 -10,-15 10,-40 -8.8233455,-13.641384 -36.711107,-5.1228436 -50,0 -36.696429,4.9079017 -8.6403157,13.745728 10,40 Z"; + Domain_dragger.nodeElement = Domain_dragger.rootNodeLayer.append('path').attr("d", pathData); + Domain_dragger.nodeElement.classed("classDraggerNode", true); + if ( graph.options().useAccuracyHelper() ) { + Domain_dragger.draggerObject = Domain_dragger.rootNodeLayer.append("circle"); + Domain_dragger.draggerObject.attr("r", 40) + .attr("cx", 0) + .attr("cy", 0) + .classed("superHiddenElement", true); + Domain_dragger.draggerObject.classed("superOpacityElement", !graph.options().showDraggerObject()); + } + + + }; + Domain_dragger.updateElementViaRangeDragger = function ( x, y ){ + var range_x = x; + var range_y = y; + + var dex = Domain_dragger.parent.domain().x; + var dey = Domain_dragger.parent.domain().y; + + var dir_X = x - dex; + var dir_Y = y - dey; + + var len = Math.sqrt(dir_X * dir_X + dir_Y * dir_Y); + + var nX = dir_X / len; + var nY = dir_Y / len; + + + var ep_range_x = dex + nX * Domain_dragger.parent.domain().actualRadius(); + var ep_range_y = dey + nY * Domain_dragger.parent.domain().actualRadius(); + + var angle = Math.atan2(ep_range_y - range_y, ep_range_x - range_x) * 180 / Math.PI; + + Domain_dragger.nodeElement.attr("transform", "translate(" + ep_range_x + "," + ep_range_y + ")" + "rotate(" + angle + ")"); + var dox = ep_range_x + nX * 20; + var doy = ep_range_y + nY * 20; + Domain_dragger.draggerObject.attr("transform", "translate(" + dox + "," + doy + ")"); + }; + + + Domain_dragger.updateElement = function (){ + if ( Domain_dragger.mouseButtonPressed === true || Domain_dragger.parent === undefined ) return; + + var domain = Domain_dragger.parent.domain(); + var iP = Domain_dragger.parent.labelObject().linkDomainIntersection; + if ( Domain_dragger.parent.labelElement() === undefined ) return; + if ( Domain_dragger.parent.labelElement().attr("transform") === "translate(0,15)" ) { + Domain_dragger.parent.inverse().domain(); + iP = Domain_dragger.parent.labelObject().linkRangeIntersection; + + } + var range_x = domain.x; + var range_y = domain.y; + + + if ( iP === undefined ) return; + var ep_range_x = iP.x; + var ep_range_y = iP.y; + + var dx = range_x - ep_range_x; + var dy = range_y - ep_range_y; + var len = Math.sqrt(dx * dx + dy * dy); + + var nX = dx / len; + var nY = dy / len; + + var dox = ep_range_x - nX * 20; + var doy = ep_range_y - nY * 20; + var angle = Math.atan2(ep_range_y - range_y, ep_range_x - range_x) * 180 / Math.PI + 180; + + Domain_dragger.nodeElement.attr("transform", "translate(" + ep_range_x + "," + ep_range_y + ")" + "rotate(" + angle + ")"); + Domain_dragger.draggerObject.attr("transform", "translate(" + dox + "," + doy + ")"); + }; + + /** MOUSE HANDLING FUNCTIONS ------------------------------------------------- **/ + + Domain_dragger.addMouseEvents = function (){ + var rootLayer = Domain_dragger.rootNodeLayer.selectAll("*"); + rootLayer.on("mouseover", Domain_dragger.onMouseOver) + .on("mouseout", Domain_dragger.onMouseOut) + .on("click", function (){ + }) + .on("dblclick", function (){ + }) + .on("mousedown", Domain_dragger.mouseDown) + .on("mouseup", Domain_dragger.mouseUp); + }; + + Domain_dragger.mouseDown = function (){ + Domain_dragger.nodeElement.style("cursor", "move"); + Domain_dragger.nodeElement.classed("classDraggerNodeHovered", true); + Domain_dragger.mouseButtonPressed = true; + }; + + Domain_dragger.mouseUp = function (){ + Domain_dragger.nodeElement.style("cursor", "auto"); + Domain_dragger.nodeElement.classed("classDraggerNodeHovered", false); + Domain_dragger.mouseButtonPressed = false; + }; + + + Domain_dragger.mouseEntered = function ( p ){ + if ( !arguments.length ) return Domain_dragger.mouseEnteredVar; + Domain_dragger.mouseEnteredVar = p; + return Domain_dragger; + }; + + Domain_dragger.selectedViaTouch = function ( val ){ + Domain_dragger.nodeElement.classed("classDraggerNode", !val); + Domain_dragger.nodeElement.classed("classDraggerNodeHovered", val); + + }; + + Domain_dragger.onMouseOver = function (){ + if ( Domain_dragger.mouseEntered() ) { + return; + } + Domain_dragger.nodeElement.classed("classDraggerNode", false); + Domain_dragger.nodeElement.classed("classDraggerNodeHovered", true); + var selectedNode = Domain_dragger.rootElement.node(), + nodeContainer = selectedNode.parentNode; + nodeContainer.appendChild(selectedNode); + + Domain_dragger.mouseEntered(true); + + }; + Domain_dragger.onMouseOut = function (){ + if ( Domain_dragger.mouseButtonPressed === true ) + return; + Domain_dragger.nodeElement.classed("classDraggerNodeHovered", false); + Domain_dragger.nodeElement.classed("classDraggerNode", true); + Domain_dragger.mouseEntered(false); + }; + + Domain_dragger.setPosition = function ( x, y ){ + var range_x = Domain_dragger.parent.range().x; + var range_y = Domain_dragger.parent.range().y; + + // var position of the rangeEndPoint + var ep_range_x = x; + var ep_range_y = y; + + // offset for dragger object + var dx = range_x - ep_range_x; + var dy = range_y - ep_range_y; + + var len = Math.sqrt(dx * dx + dy * dy); + + var nX = dx / len; + var nY = dy / len; + var dox = ep_range_x + nX * 20; + var doy = ep_range_y + nY * 20; + + var angle = Math.atan2(range_y - ep_range_y, range_x - ep_range_x) * 180 / Math.PI + 180; + + Domain_dragger.nodeElement.attr("transform", "translate(" + ep_range_x + "," + ep_range_y + ")" + "rotate(" + angle + ")"); + Domain_dragger.draggerObject.attr("transform", "translate(" + dox + "," + doy + ")"); + + Domain_dragger.x = x; + Domain_dragger.y = y; + + }; + + Domain_dragger.setAdditionalClassForClass_dragger = function ( name, val ){ + // console.log("Class_dragger should sett the class here") + // Class_dragger.nodeElement.classed(name,val); + + }; + return Domain_dragger; + }; + + + + +/***/ }), +/* 71 */ +/***/ (function(module, exports, __webpack_require__) { + + var CenteringTextElement = __webpack_require__(14); + var elementTools = __webpack_require__(63)(); + var math = __webpack_require__(43)(); + module.exports = function ( graph ){ + /** variable defs **/ + var ShadowClone = {}; + ShadowClone.nodeId = 10003; + ShadowClone.parent = undefined; + ShadowClone.s_x = 0; + ShadowClone.s_y = 0; + ShadowClone.e_x = 0; + ShadowClone.e_y = 0; + ShadowClone.rootElement = undefined; + ShadowClone.rootNodeLayer = undefined; + ShadowClone.pathLayer = undefined; + ShadowClone.nodeElement = undefined; + ShadowClone.pathElement = undefined; + ShadowClone.typus = "shadowClone"; + + + ShadowClone.type = function (){ + return ShadowClone.typus; + }; + + // TODO: We need the endPoint of the Link here! + ShadowClone.parentNode = function (){ + return ShadowClone.parent; + }; + + ShadowClone.setParentProperty = function ( parentProperty, inverted ){ + ShadowClone.invertedProperty = inverted; + ShadowClone.parent = parentProperty; + var renElment; + if ( inverted === true ) { + renElment = parentProperty.inverse().labelObject(); + if ( renElment.linkRangeIntersection && renElment.linkDomainIntersection ) { + var iiP_range = renElment.linkDomainIntersection; + var iiP_domain = renElment.linkRangeIntersection; + ShadowClone.s_x = iiP_domain.x; + ShadowClone.s_y = iiP_domain.y; + ShadowClone.e_x = iiP_range.x; + ShadowClone.e_y = iiP_range.y; + } + } + else { + renElment = parentProperty.labelObject(); + + if ( renElment.linkRangeIntersection && renElment.linkDomainIntersection ) { + var iP_range = renElment.linkRangeIntersection; + var iP_domain = renElment.linkDomainIntersection; + ShadowClone.s_x = iP_domain.x; + ShadowClone.s_y = iP_domain.y; + ShadowClone.e_x = iP_range.x; + ShadowClone.e_y = iP_range.y; + } + + } + + ShadowClone.rootNodeLayer.remove(); + ShadowClone.rootNodeLayer = ShadowClone.rootElement.append('g'); + ShadowClone.rootNodeLayer.datum(parentProperty); + + // ShadowClone.pathElement.remove(); + // ShadowClone.pathElement = ShadowClone.pathLayer.append('line'); + // + // ShadowClone.pathElement.attr("x1", ShadowClone.s_x) + // .attr("y1", ShadowClone.s_y) + // .attr("x2", ShadowClone.e_x) + // .attr("y2", ShadowClone.e_y); + ShadowClone.pathElement.remove(); + ShadowClone.pathElement = ShadowClone.pathLayer.append('line'); + ShadowClone.markerElement = ShadowClone.pathLayer.append("marker"); + ShadowClone.markerElement.attr("id", "shadowCloneMarker"); + ShadowClone.pathElement.attr("x1", ShadowClone.e_x) + .attr("y1", ShadowClone.e_y) + .attr("x2", ShadowClone.s_x) + .attr("y2", ShadowClone.s_y); + ShadowClone.pathElement.classed(parentProperty.linkType(), true); + + if ( parentProperty.markerElement() ) { + ShadowClone.markerElement.attr("viewBox", parentProperty.markerElement().attr("viewBox")) + .attr("markerWidth", parentProperty.markerElement().attr("markerWidth")) + .attr("markerHeight", parentProperty.markerElement().attr("markerHeight")) + .attr("orient", parentProperty.markerElement().attr("orient")); + + var markerPath = parentProperty.markerElement().select("path"); + ShadowClone.markerElement.append("path") + .attr("d", markerPath.attr("d")) + .classed(parentProperty.markerType(), true); + + ShadowClone.pathElement.attr("marker-end", "url(#" + "shadowCloneMarker" + ")"); + ShadowClone.markerElement.classed("hidden", !elementTools.isDatatypeProperty(parentProperty)); + } + var rect = ShadowClone.rootNodeLayer.append("rect") + .classed(parentProperty.styleClass(), true) + .classed("property", true) + .attr("x", -parentProperty.width() / 2) + .attr("y", -parentProperty.height() / 2) + .attr("width", parentProperty.width()) + .attr("height", parentProperty.height()); + + if ( parentProperty.visualAttributes() ) { + rect.classed(parentProperty.visualAttributes(), true); + } + rect.classed("datatype", false); + var bgColor = parentProperty.backgroundColor(); + + if ( parentProperty.attributes().indexOf("deprecated") > -1 ) { + bgColor = undefined; + rect.classed("deprecatedproperty", true); + } else { + rect.classed("deprecatedproperty", false); + } + rect.style("fill", bgColor); + + // add Text; + var equivalentsString = parentProperty.equivalentsString(); + var suffixForFollowingEquivalents = equivalentsString ? "," : ""; + + + var textElement = new CenteringTextElement(ShadowClone.rootNodeLayer, bgColor); + textElement.addText(parentProperty.labelForCurrentLanguage(), "", suffixForFollowingEquivalents); + textElement.addEquivalents(equivalentsString); + textElement.addSubText(parentProperty.indicationString()); + + + var cx = 0.5 * (ShadowClone.s_x + ShadowClone.e_x); + var cy = 0.5 * (ShadowClone.s_y + ShadowClone.e_y); + ShadowClone.rootNodeLayer.attr("transform", "translate(" + cx + "," + cy + ")"); + ShadowClone.rootNodeLayer.classed("hidden", true); + ShadowClone.pathElement.classed("hidden", true); + + + }; + + ShadowClone.hideClone = function ( val ){ + if ( ShadowClone.rootNodeLayer ) ShadowClone.rootNodeLayer.classed("hidden", val); + if ( ShadowClone.pathElement ) ShadowClone.pathElement.classed("hidden", val); + }; + + ShadowClone.hideParentProperty = function ( val ){ + + var labelObj = ShadowClone.parent.labelObject(); + if ( labelObj ) { + if ( ShadowClone.parent.labelElement().attr("transform") === "translate(0,15)" || + ShadowClone.parent.labelElement().attr("transform") === "translate(0,-15)" ) + ShadowClone.parent.inverse().hide(val); + + + } + ShadowClone.parent.hide(val); + + + }; + + /** BASE HANDLING FUNCTIONS ------------------------------------------------- **/ + ShadowClone.id = function ( index ){ + if ( !arguments.length ) { + return ShadowClone.nodeId; + } + ShadowClone.nodeId = index; + }; + + ShadowClone.svgPathLayer = function ( layer ){ + ShadowClone.pathLayer = layer.append('g'); + }; + + ShadowClone.svgRoot = function ( root ){ + if ( !arguments.length ) + return ShadowClone.rootElement; + ShadowClone.rootElement = root; + ShadowClone.rootNodeLayer = ShadowClone.rootElement.append('g'); + + }; + + /** DRAWING FUNCTIONS ------------------------------------------------- **/ + ShadowClone.drawClone = function (){ + ShadowClone.pathElement = ShadowClone.pathLayer.append('line'); + + ShadowClone.pathElement.attr("x1", 0) + .attr("y1", 0) + .attr("x2", 0) + .attr("y2", 0); + + }; + + + ShadowClone.updateElement = function (){ + ShadowClone.pathElement.attr("x1", ShadowClone.e_x) + .attr("y1", ShadowClone.e_y) + .attr("x2", ShadowClone.s_x) + .attr("y2", ShadowClone.s_y); + + var cx = 0.5 * (ShadowClone.s_x + ShadowClone.e_x); + var cy = 0.5 * (ShadowClone.s_y + ShadowClone.e_y); + ShadowClone.rootNodeLayer.attr("transform", "translate(" + cx + "," + cy + ")"); + }; + + ShadowClone.setInitialPosition = function (){ + + var renElment = ShadowClone.parent.labelObject(); + if ( renElment.linkRangeIntersection && renElment.linkDomainIntersection ) { + var iP_range = renElment.linkRangeIntersection; + var iP_domain = renElment.linkDomainIntersection; + ShadowClone.e_x = iP_domain.x; + ShadowClone.e_y = iP_domain.y; + ShadowClone.s_x = iP_range.x; + ShadowClone.s_y = iP_range.y; + } + ShadowClone.updateElement(); + return; + // + // var rex=ShadowClone.parent.range().x; + // var rey=ShadowClone.parent.range().y; + // + // + // var dex=ShadowClone.parent.domain().x; + // var dey=ShadowClone.parent.domain().y; + // + // + // var dir_X= rex-dex; + // var dir_Y= rey-dey; + // + // var len=Math.sqrt(dir_X*dir_X+dir_Y*dir_Y); + // var nX=dir_X/len; + // var nY=dir_Y/len; + // ShadowClone.s_x=rex-nX*ShadowClone.parent.range().actualRadius(); + // ShadowClone.s_y=rey-nY*ShadowClone.parent.range().actualRadius(); + // + // ShadowClone.e_x=dex+nX*ShadowClone.parent.domain().actualRadius(); + // ShadowClone.e_y=dey+nY*ShadowClone.parent.domain().actualRadius(); + // ShadowClone.updateElement(); + + }; + ShadowClone.setPositionDomain = function ( e_x, e_y ){ + + var rex = ShadowClone.parent.range().x; + var rey = ShadowClone.parent.range().y; + + + if ( elementTools.isDatatype(ShadowClone.parent.range()) === true ) { + var intersection = math.calculateIntersection({ x: e_x, y: e_y }, ShadowClone.parent.range(), 0); + ShadowClone.s_x = intersection.x; + ShadowClone.s_y = intersection.y; + } else { + var dir_X = rex - e_x; + var dir_Y = rey - e_y; + + var len = Math.sqrt(dir_X * dir_X + dir_Y * dir_Y); + + var nX = dir_X / len; + var nY = dir_Y / len; + ShadowClone.s_x = rex - nX * ShadowClone.parent.range().actualRadius(); + ShadowClone.s_y = rey - nY * ShadowClone.parent.range().actualRadius(); + + } + + + ShadowClone.e_x = e_x; + ShadowClone.e_y = e_y; + ShadowClone.updateElement(); + }; + + ShadowClone.setPosition = function ( s_x, s_y ){ + ShadowClone.s_x = s_x; + ShadowClone.s_y = s_y; + + // add normalized dir; + + var dex = ShadowClone.parent.domain().x; + var dey = ShadowClone.parent.domain().y; + + var dir_X = s_x - dex; + var dir_Y = s_y - dey; + + var len = Math.sqrt(dir_X * dir_X + dir_Y * dir_Y); + + var nX = dir_X / len; + var nY = dir_Y / len; + + + ShadowClone.e_x = dex + nX * ShadowClone.parent.domain().actualRadius(); + ShadowClone.e_y = dey + nY * ShadowClone.parent.domain().actualRadius(); + + + ShadowClone.updateElement(); + + + }; + + + /** MOUSE HANDLING FUNCTIONS ------------------------------------------------- **/ + + return ShadowClone; + }; + + + + +/***/ }), +/* 72 */ +/***/ (function(module, exports) { + + module.exports = function ( graph ){ + /** variable defs **/ + var prefixRepresentationModule = {}; + + var currentPrefixModel; + + prefixRepresentationModule.updatePrefixModel = function (){ + currentPrefixModel = graph.options().prefixList(); + }; + + + prefixRepresentationModule.validURL = function ( url ){ + return validURL(url); + }; + function validURL( str ){ + var urlregex = /^(https?|ftp):\/\/([a-zA-Z0-9.-]+(:[a-zA-Z0-9.&%$-]+)*@)*((25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9][0-9]?)(\.(25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9]?[0-9])){3}|([a-zA-Z0-9-]+\.)*[a-zA-Z0-9-]+\.(com|edu|gov|int|mil|net|org|biz|arpa|info|name|pro|aero|coop|museum|[a-zA-Z]{2}))(:[0-9]+)*(\/($|[a-zA-Z0-9.,?'\\+&%$#=~_-]+))*$/; + return urlregex.test(str); + } + + function splitURLIntoBaseAndResource( fullURL ){ + var splitedURL = { base: "", resource: "" }; + if ( fullURL === undefined ) { + splitedURL = { base: "ERROR", resource: "NOT FOUND" }; + return splitedURL; + } + + var resource, base; + // check if there is a last hashTag + if ( fullURL.indexOf("#") > -1 ) { + resource = fullURL.substring(fullURL.lastIndexOf('#') + 1); + base = fullURL.substring(0, fullURL.length - resource.length); + // overwrite base if it is ontologyIri; + if ( base === graph.options().getGeneralMetaObjectProperty('iri') ) { + base = ":"; + } + splitedURL.base = base; + splitedURL.resource = resource; + } else { + resource = fullURL.substring(fullURL.lastIndexOf('/') + 1); + base = fullURL.substring(0, fullURL.length - resource.length); + // overwrite base if it is ontologyIri; + if ( base === graph.options().getGeneralMetaObjectProperty('iri') ) { + base = ":"; + } + splitedURL.base = base; + splitedURL.resource = resource; + } + return splitedURL; + } + + prefixRepresentationModule.getPrefixRepresentationForFullURI = function ( fullURL ){ + prefixRepresentationModule.updatePrefixModel(); + var splittedURL = splitURLIntoBaseAndResource(fullURL); + + // lazy approach , for + // loop over prefix model + for ( var name in currentPrefixModel ) { + if ( currentPrefixModel.hasOwnProperty(name) ) { + // THIS IS CASE SENSITIVE! + if ( currentPrefixModel[name] === splittedURL.base ) { + return name + ":" + splittedURL.resource; + } + } + } + + if ( splittedURL.base === ":" ) { + return ":" + splittedURL.resource; + } + + return fullURL; + }; + + + return prefixRepresentationModule; + }; + + + + +/***/ }), +/* 73 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var _ = __webpack_require__(58); + + module.exports = function (){ + + var DEFAULT_STATE = true; + var COLOR_MODES = [ + { type: "same", range: [d3.rgb("#36C"), d3.rgb("#36C")] }, + { type: "gradient", range: [d3.rgb("#36C"), d3.rgb("#EE2867")] } // taken from LD-VOWL + ]; + + var filter = {}, + nodes, + properties, + enabled = DEFAULT_STATE, + filteredNodes, + filteredProperties, + colorModeType = "same"; + + + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + + var externalElements = filterExternalElements(nodes.concat(properties)); + + if ( enabled ) { + setColorsForExternals(externalElements); + } else { + resetBackgroundColors(externalElements); + } + + filteredNodes = nodes; + filteredProperties = properties; + }; + + function filterExternalElements( elements ){ + return elements.filter(function ( element ){ + if ( element.visualAttributes().indexOf("deprecated") >= 0 ) { + // deprecated is the only attribute which has preference over external + return false; + } + + return element.attributes().indexOf("external") >= 0; + }); + } + + function setColorsForExternals( elements ){ + var iriMap = mapExternalsToBaseUri(elements); + var entries = iriMap.entries(); + + var colorScale = d3.scale.linear() + .domain([0, entries.length - 1]) + .range(_.find(COLOR_MODES, { type: colorModeType }).range) + .interpolate(d3.interpolateHsl); + + for ( var i = 0; i < entries.length; i++ ) { + var groupedElements = entries[i].value; + setBackgroundColorForElements(groupedElements, colorScale(i)); + } + } + + function mapExternalsToBaseUri( elements ){ + var map = d3.map(); + + elements.forEach(function ( element ){ + var baseIri = element.baseIri(); + + if ( !map.has(baseIri) ) { + map.set(baseIri, []); + } + map.get(baseIri).push(element); + }); + + return map; + } + + function setBackgroundColorForElements( elements, backgroundColor ){ + elements.forEach(function ( element ){ + element.backgroundColor(backgroundColor); + }); + } + + function resetBackgroundColors( elements ){ + console.log("Resetting color"); + elements.forEach(function ( element ){ + element.backgroundColor(null); + }); + } + + filter.colorModeType = function ( p ){ + if ( !arguments.length ) return colorModeType; + colorModeType = p; + return filter; + }; + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + filter.reset = function (){ + enabled = DEFAULT_STATE; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 74 */ +/***/ (function(module, exports) { + + /** + * This module abuses the filter function a bit like the statistics module. Nothing is filtered. + * + * @returns {{}} + */ + + + module.exports = function ( graph ){ + + var DEFAULT_STATE = false; + + var filter = {}, + nodes, + properties, + enabled = DEFAULT_STATE, + filteredNodes, + filteredProperties; + + + /** + * If enabled, redundant details won't be drawn anymore. + * @param untouchedNodes + * @param untouchedProperties + */ + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + graph.options().compactNotation(enabled); + filteredNodes = nodes; + filteredProperties = properties; + }; + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + filter.reset = function (){ + enabled = DEFAULT_STATE; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }), +/* 75 */ +/***/ (function(module, exports, __webpack_require__) { + + var elementTools = __webpack_require__(63)(); + var filterTools = __webpack_require__(76)(); + + module.exports = function (){ + + var filter = {}, + nodes, + properties, + enabled = false, + filteredNodes, + filteredProperties; + + + /** + * If enabled, all datatypes and literals including connected properties are filtered. + * @param untouchedNodes + * @param untouchedProperties + */ + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + + if ( this.enabled() ) { + removeDatatypesAndLiterals(); + } + + filteredNodes = nodes; + filteredProperties = properties; + }; + + function removeDatatypesAndLiterals(){ + var filteredData = filterTools.filterNodesAndTidy(nodes, properties, isNoDatatypeOrLiteral); + + nodes = filteredData.nodes; + properties = filteredData.properties; + } + + function isNoDatatypeOrLiteral( node ){ + return !elementTools.isDatatype(node); + } + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }), +/* 76 */ +/***/ (function(module, exports, __webpack_require__) { + + var elementTools = __webpack_require__(63)(); + + module.exports = (function (){ + + var tools = {}; + + /** + * Filters the passed nodes and removes dangling properties. + * @param nodes + * @param properties + * @param shouldKeepNode function that returns true if the node should be kept + * @returns {{nodes: Array, properties: Array}} the filtered nodes and properties + */ + tools.filterNodesAndTidy = function ( nodes, properties, shouldKeepNode ){ + var removedNodes = __webpack_require__(62)(), + cleanedNodes = [], + cleanedProperties = []; + + nodes.forEach(function ( node ){ + if ( shouldKeepNode(node) ) { + cleanedNodes.push(node); + } else { + removedNodes.add(node); + } + }); + + properties.forEach(function ( property ){ + if ( propertyHasVisibleNodes(removedNodes, property) ) { + cleanedProperties.push(property); + } else if ( elementTools.isDatatypeProperty(property) ) { + // Remove floating datatypes/literals, because they belong to their datatype property + var index = cleanedNodes.indexOf(property.range()); + if ( index >= 0 ) { + cleanedNodes.splice(index, 1); + } + } + }); + + return { + nodes: cleanedNodes, + properties: cleanedProperties + }; + }; + + /** + * Returns true, if the domain and the range of this property have not been removed. + * @param removedNodes + * @param property + * @returns {boolean} true if property isn't dangling + */ + function propertyHasVisibleNodes( removedNodes, property ){ + return !removedNodes.has(property.domain()) && !removedNodes.has(property.range()); + } + + + return function (){ + return tools; + }; + })(); + + +/***/ }), +/* 77 */ +/***/ (function(module, exports, __webpack_require__) { + + var OwlDisjointWith = __webpack_require__(46); + + module.exports = function (){ + + var filter = {}, + nodes, + properties, + // According to the specification enabled by default + enabled = true, + filteredNodes, + filteredProperties; + + + /** + * If enabled, all disjoint with properties are filtered. + * @param untouchedNodes + * @param untouchedProperties + */ + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + + if ( this.enabled() ) { + removeDisjointWithProperties(); + } + + filteredNodes = nodes; + filteredProperties = properties; + }; + + function removeDisjointWithProperties(){ + var cleanedProperties = [], + i, l, property; + + for ( i = 0, l = properties.length; i < l; i++ ) { + property = properties[i]; + + if ( !(property instanceof OwlDisjointWith) ) { + cleanedProperties.push(property); + } + } + + properties = cleanedProperties; + } + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }), +/* 78 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( graph ){ + var focuser = {}, + focusedElement; + var elementTools = webvowl.util.elementTools(); + focuser.handle = function ( selectedElement, forced ){ + // Don't display details on a drag event, which will be prevented + if ( d3.event && d3.event.defaultPrevented && forced === undefined ) { + return; + } + + if ( focusedElement !== undefined ) { + focusedElement.toggleFocus(); + } + + if ( focusedElement !== selectedElement && selectedElement ) { + selectedElement.toggleFocus(); + focusedElement = selectedElement; + } else { + focusedElement = undefined; + } + if ( focusedElement && focusedElement.focused() ) { + graph.options().editSidebar().updateSelectionInformation(focusedElement); + if ( elementTools.isProperty(selectedElement) === true ) { + var inversed = false; + if ( selectedElement.inverse() ) { + inversed = true; + } + graph.activateHoverElementsForProperties(true, selectedElement, inversed, graph.isTouchDevice()); + } + else { + graph.activateHoverElements(true, selectedElement, graph.isTouchDevice()); + } + } + else { + graph.options().editSidebar().updateSelectionInformation(undefined); + graph.removeEditElements(); + } + }; + + /** + * Removes the focus if an element is focussed. + */ + focuser.reset = function (){ + if ( focusedElement ) { + focusedElement.toggleFocus(); + focusedElement = undefined; + } + }; + + return focuser; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 79 */ +/***/ (function(module, exports) { + + /** @WORKAROUND CODE: + * clears empty literals that are provided by owl2vowl: 0.2.2x*/ + + + module.exports = function (){ + + var filter = {}, + enabled = true, + filteredNodes, + removedNodes, + filteredProperties; + + filter.enabled = function ( val ){ + if ( !arguments.length ) { + return enabled; + } + enabled = val; + }; + + filter.filter = function ( nodes, properties ){ + if ( enabled === false ) { + filteredNodes = nodes; + filteredProperties = properties; + removedNodes = []; + return; + } + var literalUsageMap = []; + var thingUsageMap = []; + var node; + for ( var i = 0; i < properties.length; i++ ) { + // get property range; + var prop = properties[i]; + + // checking for literals + if ( prop.range() ) { + node = prop.range(); + if ( node.type() === "rdfs:Literal" ) { + literalUsageMap[node.id()] = 1; + } + } + // checking for thing + if ( prop.range() ) { + node = prop.range(); + if ( node.type() === "owl:Thing" ) { + thingUsageMap[node.id()] = 1; + } + } + if ( prop.domain() ) { + node = prop.domain(); + if ( node.type() === "owl:Thing" ) { + thingUsageMap[node.id()] = 1; + } + } + + } + var nodesToRemove = []; + var newNodes = []; + // todo: test and make it faster + for ( i = 0; i < nodes.length; i++ ) { + var nodeId = nodes[i].id(); + if ( nodes[i].type() === "rdfs:Literal" ) { + if ( literalUsageMap[nodeId] === undefined ) { + nodesToRemove.push(nodeId); + } + else { + newNodes.push(nodes[i]); + } + // check for node type == OWL:THING + } else if ( nodes[i].type() === "owl:Thing" ) { + if ( thingUsageMap[nodeId] === undefined ) { + nodesToRemove.push(nodeId); + } + else { + newNodes.push(nodes[i]); + } + } else { + newNodes.push(nodes[i]); + } + } + + filteredNodes = newNodes; + filteredProperties = properties; + removedNodes = nodesToRemove; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.removedNodes = function (){ + return removedNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }), +/* 80 */ +/***/ (function(module, exports, __webpack_require__) { + + var elementTools = __webpack_require__(63)(); + var filterTools = __webpack_require__(76)(); + + module.exports = function ( menu ){ + + var filter = {}, + nodes, + properties, + enabled = true, + filteredNodes, + filteredProperties, + maxDegreeSetter, + degreeGetter, + lastFiltedDegree, + degreeSetter; + + + var NODE_COUNT_LIMIT_FOR_AUTO_ENABLING = 50; + + + filter.initialize = function ( nodes, properties ){ + lastFiltedDegree = -1; + var maxLinkCount = findMaxLinkCount(nodes); + if ( maxDegreeSetter instanceof Function ) { + maxDegreeSetter(maxLinkCount); + } + + menu.setDefaultDegreeValue(findAutoDefaultDegree(nodes, properties, maxLinkCount)); + var defaultDegree = findDefaultDegree(maxLinkCount); + if ( degreeSetter instanceof Function ) { + degreeSetter(defaultDegree); + if ( defaultDegree > 0 ) { + menu.highlightForDegreeSlider(true); + menu.getGraphObject().setFilterWarning(true); + + } + } else { + console.error("No degree setter function set."); + } + }; + + function findAutoDefaultDegree( nodes, properties, maxDegree ){ + for ( var degree = 0; degree < maxDegree; degree++ ) { + var filteredData = filterByNodeDegree(nodes, properties, degree); + + if ( filteredData.nodes.length <= NODE_COUNT_LIMIT_FOR_AUTO_ENABLING ) { + return degree; + } + } + return 0; + } + + function findDefaultDegree( maxDegree ){ + var globalDegOfFilter = menu.getGraphObject().getGlobalDOF(); + if ( globalDegOfFilter >= 0 ) { + if ( globalDegOfFilter <= maxDegree ) { + return globalDegOfFilter; + } else { + menu.getGraphObject().setGlobalDOF(maxDegree); + return maxDegree; + } + } + return menu.getDefaultDegreeValue(); + } + + /** + * If enabled, all nodes are filter by their node degree. + * @param untouchedNodes + * @param untouchedProperties + */ + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + + if ( this.enabled() ) { + if ( degreeGetter instanceof Function ) { + filterByNodeDegreeAndApply(degreeGetter()); + } else { + console.error("No degree query function set."); + } + } + + filteredNodes = nodes; + filteredProperties = properties; + + if ( filteredNodes.length === 0 ) { + degreeSetter(0); + filteredNodes = untouchedNodes; + filteredProperties = untouchedProperties; + } + lastFiltedDegree = degreeGetter(); + }; + + function findMaxLinkCount( nodes ){ + var maxLinkCount = 0; + for ( var i = 0, l = nodes.length; i < l; i++ ) { + var linksWithoutDatatypes = filterOutDatatypes(nodes[i].links()); + + maxLinkCount = Math.max(maxLinkCount, linksWithoutDatatypes.length); + } + return maxLinkCount; + } + + function filterOutDatatypes( links ){ + return links.filter(function ( link ){ + return !elementTools.isDatatypeProperty(link.property()); + }); + } + + function filterByNodeDegreeAndApply( minDegree ){ + var filteredData = filterByNodeDegree(nodes, properties, minDegree); + nodes = filteredData.nodes; + properties = filteredData.properties; + } + + function filterByNodeDegree( nodes, properties, minDegree ){ + return filterTools.filterNodesAndTidy(nodes, properties, hasRequiredDegree(minDegree)); + } + + function hasRequiredDegree( minDegree ){ + return function ( node ){ + return filterOutDatatypes(node.links()).length >= minDegree; + }; + } + + filter.setMaxDegreeSetter = function ( _maxDegreeSetter ){ + maxDegreeSetter = _maxDegreeSetter; + }; + + filter.setDegreeGetter = function ( _degreeGetter ){ + degreeGetter = _degreeGetter; + }; + + filter.setDegreeSetter = function ( _degreeSetter ){ + degreeSetter = _degreeSetter; + }; + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }), +/* 81 */ +/***/ (function(module, exports) { + + /** + * This module abuses the filter function a bit like the statistics module. Nothing is filtered. + * + * @returns {{}} + */ + module.exports = function ( graph ){ + + var DEFAULT_STATE = true; + + var filter = {}, + nodes, + properties, + enabled = DEFAULT_STATE, + filteredNodes, + filteredProperties; + + + /** + * If enabled, the scaling of nodes according to individuals will be enabled. + * @param untouchedNodes + * @param untouchedProperties + */ + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + + graph.options().scaleNodesByIndividuals(enabled); + + filteredNodes = nodes; + filteredProperties = properties; + }; + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + filter.reset = function (){ + enabled = DEFAULT_STATE; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }), +/* 82 */ +/***/ (function(module, exports, __webpack_require__) { + + var elementTools = __webpack_require__(63)(); + + + module.exports = function (){ + + var filter = {}, + nodes, + properties, + enabled = false, + filteredNodes, + filteredProperties; + + + /** + * If enabled, all object properties and things without any other property are filtered. + * @param untouchedNodes + * @param untouchedProperties + */ + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + + if ( this.enabled() ) { + removeObjectProperties(); + } + + filteredNodes = nodes; + filteredProperties = properties; + }; + + function removeObjectProperties(){ + properties = properties.filter(isNoObjectProperty); + nodes = nodes.filter(isNoFloatingThing); + } + + function isNoObjectProperty( property ){ + return !elementTools.isObjectProperty(property); + } + + function isNoFloatingThing( node ){ + var isNoThing = !elementTools.isThing(node); + var hasNonFilteredProperties = hasPropertiesOtherThanObjectProperties(node, properties); + return isNoThing || hasNonFilteredProperties; + } + + function hasPropertiesOtherThanObjectProperties( node, properties ){ + for ( var i = 0; i < properties.length; i++ ) { + var property = properties[i]; + if ( property.domain() !== node && property.range() !== node ) { + continue; + } + + if ( isNoObjectProperty(property) ) { + return true; + } + } + + return false; + } + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }), +/* 83 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var _ = __webpack_require__(84); + var elementTools = __webpack_require__(63)(); + + module.exports = function (){ + var pap = {}, + enabled = false, + pinnedElements = []; + + pap.addPinnedElement = function ( element ){ + // check if element is already in list + var indexInArray = pinnedElements.indexOf(element); + if ( indexInArray === -1 ) { + pinnedElements.push(element); + } + }; + + pap.handle = function ( selection, forced ){ + if ( !enabled ) { + return; + } + + if ( !forced ) { + if ( wasNotDragged() ) { + return; + } + } + if ( elementTools.isProperty(selection) ) { + if ( selection.inverse() && selection.inverse().pinned() ) { + return; + } else if ( hasNoParallelProperties(selection) ) { + return; + } + } + + if ( !selection.pinned() ) { + selection.drawPin(); + pap.addPinnedElement(selection); + } + }; + + function wasNotDragged(){ + return !d3.event.defaultPrevented; + } + + function hasNoParallelProperties( property ){ + return _.intersection(property.domain().links(), property.range().links()).length === 1; + } + + pap.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return pap; + }; + + pap.reset = function (){ + pinnedElements.forEach(function ( element ){ + element.removePin(); + }); + // Clear the array of stored nodes + pinnedElements.length = 0; + }; + + return pap; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 84 */ +/***/ (function(module, exports, __webpack_require__) { + + module.exports = { + 'chunk': __webpack_require__(85), + 'compact': __webpack_require__(105), + 'concat': __webpack_require__(106), + 'difference': __webpack_require__(114), + 'differenceBy': __webpack_require__(167), + 'differenceWith': __webpack_require__(229), + 'drop': __webpack_require__(230), + 'dropRight': __webpack_require__(231), + 'dropRightWhile': __webpack_require__(232), + 'dropWhile': __webpack_require__(234), + 'fill': __webpack_require__(235), + 'findIndex': __webpack_require__(239), + 'findLastIndex': __webpack_require__(240), + 'first': __webpack_require__(241), + 'flatten': __webpack_require__(243), + 'flattenDeep': __webpack_require__(244), + 'flattenDepth': __webpack_require__(245), + 'fromPairs': __webpack_require__(246), + 'head': __webpack_require__(242), + 'indexOf': __webpack_require__(247), + 'initial': __webpack_require__(248), + 'intersection': __webpack_require__(249), + 'intersectionBy': __webpack_require__(252), + 'intersectionWith': __webpack_require__(253), + 'join': __webpack_require__(254), + 'last': __webpack_require__(228), + 'lastIndexOf': __webpack_require__(255), + 'nth': __webpack_require__(257), + 'pull': __webpack_require__(259), + 'pullAll': __webpack_require__(260), + 'pullAllBy': __webpack_require__(263), + 'pullAllWith': __webpack_require__(264), + 'pullAt': __webpack_require__(265), + 'remove': __webpack_require__(272), + 'reverse': __webpack_require__(273), + 'slice': __webpack_require__(274), + 'sortedIndex': __webpack_require__(275), + 'sortedIndexBy': __webpack_require__(278), + 'sortedIndexOf': __webpack_require__(279), + 'sortedLastIndex': __webpack_require__(280), + 'sortedLastIndexBy': __webpack_require__(281), + 'sortedLastIndexOf': __webpack_require__(282), + 'sortedUniq': __webpack_require__(283), + 'sortedUniqBy': __webpack_require__(285), + 'tail': __webpack_require__(286), + 'take': __webpack_require__(287), + 'takeRight': __webpack_require__(288), + 'takeRightWhile': __webpack_require__(289), + 'takeWhile': __webpack_require__(290), + 'union': __webpack_require__(291), + 'unionBy': __webpack_require__(295), + 'unionWith': __webpack_require__(296), + 'uniq': __webpack_require__(297), + 'uniqBy': __webpack_require__(298), + 'uniqWith': __webpack_require__(299), + 'unzip': __webpack_require__(300), + 'unzipWith': __webpack_require__(301), + 'without': __webpack_require__(302), + 'xor': __webpack_require__(303), + 'xorBy': __webpack_require__(305), + 'xorWith': __webpack_require__(306), + 'zip': __webpack_require__(307), + 'zipObject': __webpack_require__(308), + 'zipObjectDeep': __webpack_require__(312), + 'zipWith': __webpack_require__(314) + }; + + +/***/ }), +/* 85 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86), + isIterateeCall = __webpack_require__(87), + toInteger = __webpack_require__(100); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeCeil = Math.ceil, + nativeMax = Math.max; + + /** + * Creates an array of elements split into groups the length of `size`. + * If `array` can't be split evenly, the final chunk will be the remaining + * elements. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to process. + * @param {number} [size=1] The length of each chunk + * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. + * @returns {Array} Returns the new array of chunks. + * @example + * + * _.chunk(['a', 'b', 'c', 'd'], 2); + * // => [['a', 'b'], ['c', 'd']] + * + * _.chunk(['a', 'b', 'c', 'd'], 3); + * // => [['a', 'b', 'c'], ['d']] + */ + function chunk(array, size, guard) { + if ((guard ? isIterateeCall(array, size, guard) : size === undefined)) { + size = 1; + } else { + size = nativeMax(toInteger(size), 0); + } + var length = array == null ? 0 : array.length; + if (!length || size < 1) { + return []; + } + var index = 0, + resIndex = 0, + result = Array(nativeCeil(length / size)); + + while (index < length) { + result[resIndex++] = baseSlice(array, index, (index += size)); + } + return result; + } + + module.exports = chunk; + + +/***/ }), +/* 86 */ +/***/ (function(module, exports) { + + /** + * The base implementation of `_.slice` without an iteratee call guard. + * + * @private + * @param {Array} array The array to slice. + * @param {number} [start=0] The start position. + * @param {number} [end=array.length] The end position. + * @returns {Array} Returns the slice of `array`. + */ + function baseSlice(array, start, end) { + var index = -1, + length = array.length; + + if (start < 0) { + start = -start > length ? 0 : (length + start); + } + end = end > length ? length : end; + if (end < 0) { + end += length; + } + length = start > end ? 0 : ((end - start) >>> 0); + start >>>= 0; + + var result = Array(length); + while (++index < length) { + result[index] = array[index + start]; + } + return result; + } + + module.exports = baseSlice; + + +/***/ }), +/* 87 */ +/***/ (function(module, exports, __webpack_require__) { + + var eq = __webpack_require__(88), + isArrayLike = __webpack_require__(89), + isIndex = __webpack_require__(99), + isObject = __webpack_require__(97); + + /** + * Checks if the given arguments are from an iteratee call. + * + * @private + * @param {*} value The potential iteratee value argument. + * @param {*} index The potential iteratee index or key argument. + * @param {*} object The potential iteratee object argument. + * @returns {boolean} Returns `true` if the arguments are from an iteratee call, + * else `false`. + */ + function isIterateeCall(value, index, object) { + if (!isObject(object)) { + return false; + } + var type = typeof index; + if (type == 'number' + ? (isArrayLike(object) && isIndex(index, object.length)) + : (type == 'string' && index in object) + ) { + return eq(object[index], value); + } + return false; + } + + module.exports = isIterateeCall; + + +/***/ }), +/* 88 */ +/***/ (function(module, exports) { + + /** + * Performs a + * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * comparison between two values to determine if they are equivalent. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @returns {boolean} Returns `true` if the values are equivalent, else `false`. + * @example + * + * var object = { 'a': 1 }; + * var other = { 'a': 1 }; + * + * _.eq(object, object); + * // => true + * + * _.eq(object, other); + * // => false + * + * _.eq('a', 'a'); + * // => true + * + * _.eq('a', Object('a')); + * // => false + * + * _.eq(NaN, NaN); + * // => true + */ + function eq(value, other) { + return value === other || (value !== value && other !== other); + } + + module.exports = eq; + + +/***/ }), +/* 89 */ +/***/ (function(module, exports, __webpack_require__) { + + var isFunction = __webpack_require__(90), + isLength = __webpack_require__(98); + + /** + * Checks if `value` is array-like. A value is considered array-like if it's + * not a function and has a `value.length` that's an integer greater than or + * equal to `0` and less than or equal to `Number.MAX_SAFE_INTEGER`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is array-like, else `false`. + * @example + * + * _.isArrayLike([1, 2, 3]); + * // => true + * + * _.isArrayLike(document.body.children); + * // => true + * + * _.isArrayLike('abc'); + * // => true + * + * _.isArrayLike(_.noop); + * // => false + */ + function isArrayLike(value) { + return value != null && isLength(value.length) && !isFunction(value); + } + + module.exports = isArrayLike; + + +/***/ }), +/* 90 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseGetTag = __webpack_require__(91), + isObject = __webpack_require__(97); + + /** `Object#toString` result references. */ + var asyncTag = '[object AsyncFunction]', + funcTag = '[object Function]', + genTag = '[object GeneratorFunction]', + proxyTag = '[object Proxy]'; + + /** + * Checks if `value` is classified as a `Function` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a function, else `false`. + * @example + * + * _.isFunction(_); + * // => true + * + * _.isFunction(/abc/); + * // => false + */ + function isFunction(value) { + if (!isObject(value)) { + return false; + } + // The use of `Object#toString` avoids issues with the `typeof` operator + // in Safari 9 which returns 'object' for typed arrays and other constructors. + var tag = baseGetTag(value); + return tag == funcTag || tag == genTag || tag == asyncTag || tag == proxyTag; + } + + module.exports = isFunction; + + +/***/ }), +/* 91 */ +/***/ (function(module, exports, __webpack_require__) { + + var Symbol = __webpack_require__(92), + getRawTag = __webpack_require__(95), + objectToString = __webpack_require__(96); + + /** `Object#toString` result references. */ + var nullTag = '[object Null]', + undefinedTag = '[object Undefined]'; + + /** Built-in value references. */ + var symToStringTag = Symbol ? Symbol.toStringTag : undefined; + + /** + * The base implementation of `getTag` without fallbacks for buggy environments. + * + * @private + * @param {*} value The value to query. + * @returns {string} Returns the `toStringTag`. + */ + function baseGetTag(value) { + if (value == null) { + return value === undefined ? undefinedTag : nullTag; + } + return (symToStringTag && symToStringTag in Object(value)) + ? getRawTag(value) + : objectToString(value); + } + + module.exports = baseGetTag; + + +/***/ }), +/* 92 */ +/***/ (function(module, exports, __webpack_require__) { + + var root = __webpack_require__(93); + + /** Built-in value references. */ + var Symbol = root.Symbol; + + module.exports = Symbol; + + +/***/ }), +/* 93 */ +/***/ (function(module, exports, __webpack_require__) { + + var freeGlobal = __webpack_require__(94); + + /** Detect free variable `self`. */ + var freeSelf = typeof self == 'object' && self && self.Object === Object && self; + + /** Used as a reference to the global object. */ + var root = freeGlobal || freeSelf || Function('return this')(); + + module.exports = root; + + +/***/ }), +/* 94 */ +/***/ (function(module, exports) { + + /* WEBPACK VAR INJECTION */(function(global) {/** Detect free variable `global` from Node.js. */ + var freeGlobal = typeof global == 'object' && global && global.Object === Object && global; + + module.exports = freeGlobal; + + /* WEBPACK VAR INJECTION */}.call(exports, (function() { return this; }()))) + +/***/ }), +/* 95 */ +/***/ (function(module, exports, __webpack_require__) { + + var Symbol = __webpack_require__(92); + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * Used to resolve the + * [`toStringTag`](http://ecma-international.org/ecma-262/7.0/#sec-object.prototype.tostring) + * of values. + */ + var nativeObjectToString = objectProto.toString; + + /** Built-in value references. */ + var symToStringTag = Symbol ? Symbol.toStringTag : undefined; + + /** + * A specialized version of `baseGetTag` which ignores `Symbol.toStringTag` values. + * + * @private + * @param {*} value The value to query. + * @returns {string} Returns the raw `toStringTag`. + */ + function getRawTag(value) { + var isOwn = hasOwnProperty.call(value, symToStringTag), + tag = value[symToStringTag]; + + try { + value[symToStringTag] = undefined; + var unmasked = true; + } catch (e) {} + + var result = nativeObjectToString.call(value); + if (unmasked) { + if (isOwn) { + value[symToStringTag] = tag; + } else { + delete value[symToStringTag]; + } + } + return result; + } + + module.exports = getRawTag; + + +/***/ }), +/* 96 */ +/***/ (function(module, exports) { + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** + * Used to resolve the + * [`toStringTag`](http://ecma-international.org/ecma-262/7.0/#sec-object.prototype.tostring) + * of values. + */ + var nativeObjectToString = objectProto.toString; + + /** + * Converts `value` to a string using `Object.prototype.toString`. + * + * @private + * @param {*} value The value to convert. + * @returns {string} Returns the converted string. + */ + function objectToString(value) { + return nativeObjectToString.call(value); + } + + module.exports = objectToString; + + +/***/ }), +/* 97 */ +/***/ (function(module, exports) { + + /** + * Checks if `value` is the + * [language type](http://www.ecma-international.org/ecma-262/7.0/#sec-ecmascript-language-types) + * of `Object`. (e.g. arrays, functions, objects, regexes, `new Number(0)`, and `new String('')`) + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an object, else `false`. + * @example + * + * _.isObject({}); + * // => true + * + * _.isObject([1, 2, 3]); + * // => true + * + * _.isObject(_.noop); + * // => true + * + * _.isObject(null); + * // => false + */ + function isObject(value) { + var type = typeof value; + return value != null && (type == 'object' || type == 'function'); + } + + module.exports = isObject; + + +/***/ }), +/* 98 */ +/***/ (function(module, exports) { + + /** Used as references for various `Number` constants. */ + var MAX_SAFE_INTEGER = 9007199254740991; + + /** + * Checks if `value` is a valid array-like length. + * + * **Note:** This method is loosely based on + * [`ToLength`](http://ecma-international.org/ecma-262/7.0/#sec-tolength). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a valid length, else `false`. + * @example + * + * _.isLength(3); + * // => true + * + * _.isLength(Number.MIN_VALUE); + * // => false + * + * _.isLength(Infinity); + * // => false + * + * _.isLength('3'); + * // => false + */ + function isLength(value) { + return typeof value == 'number' && + value > -1 && value % 1 == 0 && value <= MAX_SAFE_INTEGER; + } + + module.exports = isLength; + + +/***/ }), +/* 99 */ +/***/ (function(module, exports) { + + /** Used as references for various `Number` constants. */ + var MAX_SAFE_INTEGER = 9007199254740991; + + /** Used to detect unsigned integer values. */ + var reIsUint = /^(?:0|[1-9]\d*)$/; + + /** + * Checks if `value` is a valid array-like index. + * + * @private + * @param {*} value The value to check. + * @param {number} [length=MAX_SAFE_INTEGER] The upper bounds of a valid index. + * @returns {boolean} Returns `true` if `value` is a valid index, else `false`. + */ + function isIndex(value, length) { + var type = typeof value; + length = length == null ? MAX_SAFE_INTEGER : length; + + return !!length && + (type == 'number' || + (type != 'symbol' && reIsUint.test(value))) && + (value > -1 && value % 1 == 0 && value < length); + } + + module.exports = isIndex; + + +/***/ }), +/* 100 */ +/***/ (function(module, exports, __webpack_require__) { + + var toFinite = __webpack_require__(101); + + /** + * Converts `value` to an integer. + * + * **Note:** This method is loosely based on + * [`ToInteger`](http://www.ecma-international.org/ecma-262/7.0/#sec-tointeger). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to convert. + * @returns {number} Returns the converted integer. + * @example + * + * _.toInteger(3.2); + * // => 3 + * + * _.toInteger(Number.MIN_VALUE); + * // => 0 + * + * _.toInteger(Infinity); + * // => 1.7976931348623157e+308 + * + * _.toInteger('3.2'); + * // => 3 + */ + function toInteger(value) { + var result = toFinite(value), + remainder = result % 1; + + return result === result ? (remainder ? result - remainder : result) : 0; + } + + module.exports = toInteger; + + +/***/ }), +/* 101 */ +/***/ (function(module, exports, __webpack_require__) { + + var toNumber = __webpack_require__(102); + + /** Used as references for various `Number` constants. */ + var INFINITY = 1 / 0, + MAX_INTEGER = 1.7976931348623157e+308; + + /** + * Converts `value` to a finite number. + * + * @static + * @memberOf _ + * @since 4.12.0 + * @category Lang + * @param {*} value The value to convert. + * @returns {number} Returns the converted number. + * @example + * + * _.toFinite(3.2); + * // => 3.2 + * + * _.toFinite(Number.MIN_VALUE); + * // => 5e-324 + * + * _.toFinite(Infinity); + * // => 1.7976931348623157e+308 + * + * _.toFinite('3.2'); + * // => 3.2 + */ + function toFinite(value) { + if (!value) { + return value === 0 ? value : 0; + } + value = toNumber(value); + if (value === INFINITY || value === -INFINITY) { + var sign = (value < 0 ? -1 : 1); + return sign * MAX_INTEGER; + } + return value === value ? value : 0; + } + + module.exports = toFinite; + + +/***/ }), +/* 102 */ +/***/ (function(module, exports, __webpack_require__) { + + var isObject = __webpack_require__(97), + isSymbol = __webpack_require__(103); + + /** Used as references for various `Number` constants. */ + var NAN = 0 / 0; + + /** Used to match leading and trailing whitespace. */ + var reTrim = /^\s+|\s+$/g; + + /** Used to detect bad signed hexadecimal string values. */ + var reIsBadHex = /^[-+]0x[0-9a-f]+$/i; + + /** Used to detect binary string values. */ + var reIsBinary = /^0b[01]+$/i; + + /** Used to detect octal string values. */ + var reIsOctal = /^0o[0-7]+$/i; + + /** Built-in method references without a dependency on `root`. */ + var freeParseInt = parseInt; + + /** + * Converts `value` to a number. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to process. + * @returns {number} Returns the number. + * @example + * + * _.toNumber(3.2); + * // => 3.2 + * + * _.toNumber(Number.MIN_VALUE); + * // => 5e-324 + * + * _.toNumber(Infinity); + * // => Infinity + * + * _.toNumber('3.2'); + * // => 3.2 + */ + function toNumber(value) { + if (typeof value == 'number') { + return value; + } + if (isSymbol(value)) { + return NAN; + } + if (isObject(value)) { + var other = typeof value.valueOf == 'function' ? value.valueOf() : value; + value = isObject(other) ? (other + '') : other; + } + if (typeof value != 'string') { + return value === 0 ? value : +value; + } + value = value.replace(reTrim, ''); + var isBinary = reIsBinary.test(value); + return (isBinary || reIsOctal.test(value)) + ? freeParseInt(value.slice(2), isBinary ? 2 : 8) + : (reIsBadHex.test(value) ? NAN : +value); + } + + module.exports = toNumber; + + +/***/ }), +/* 103 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseGetTag = __webpack_require__(91), + isObjectLike = __webpack_require__(104); + + /** `Object#toString` result references. */ + var symbolTag = '[object Symbol]'; + + /** + * Checks if `value` is classified as a `Symbol` primitive or object. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a symbol, else `false`. + * @example + * + * _.isSymbol(Symbol.iterator); + * // => true + * + * _.isSymbol('abc'); + * // => false + */ + function isSymbol(value) { + return typeof value == 'symbol' || + (isObjectLike(value) && baseGetTag(value) == symbolTag); + } + + module.exports = isSymbol; + + +/***/ }), +/* 104 */ +/***/ (function(module, exports) { + + /** + * Checks if `value` is object-like. A value is object-like if it's not `null` + * and has a `typeof` result of "object". + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is object-like, else `false`. + * @example + * + * _.isObjectLike({}); + * // => true + * + * _.isObjectLike([1, 2, 3]); + * // => true + * + * _.isObjectLike(_.noop); + * // => false + * + * _.isObjectLike(null); + * // => false + */ + function isObjectLike(value) { + return value != null && typeof value == 'object'; + } + + module.exports = isObjectLike; + + +/***/ }), +/* 105 */ +/***/ (function(module, exports) { + + /** + * Creates an array with all falsey values removed. The values `false`, `null`, + * `0`, `""`, `undefined`, and `NaN` are falsey. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to compact. + * @returns {Array} Returns the new array of filtered values. + * @example + * + * _.compact([0, 1, false, 2, '', 3]); + * // => [1, 2, 3] + */ + function compact(array) { + var index = -1, + length = array == null ? 0 : array.length, + resIndex = 0, + result = []; + + while (++index < length) { + var value = array[index]; + if (value) { + result[resIndex++] = value; + } + } + return result; + } + + module.exports = compact; + + +/***/ }), +/* 106 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayPush = __webpack_require__(107), + baseFlatten = __webpack_require__(108), + copyArray = __webpack_require__(113), + isArray = __webpack_require__(112); + + /** + * Creates a new array concatenating `array` with any additional arrays + * and/or values. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to concatenate. + * @param {...*} [values] The values to concatenate. + * @returns {Array} Returns the new concatenated array. + * @example + * + * var array = [1]; + * var other = _.concat(array, 2, [3], [[4]]); + * + * console.log(other); + * // => [1, 2, 3, [4]] + * + * console.log(array); + * // => [1] + */ + function concat() { + var length = arguments.length; + if (!length) { + return []; + } + var args = Array(length - 1), + array = arguments[0], + index = length; + + while (index--) { + args[index - 1] = arguments[index]; + } + return arrayPush(isArray(array) ? copyArray(array) : [array], baseFlatten(args, 1)); + } + + module.exports = concat; + + +/***/ }), +/* 107 */ +/***/ (function(module, exports) { + + /** + * Appends the elements of `values` to `array`. + * + * @private + * @param {Array} array The array to modify. + * @param {Array} values The values to append. + * @returns {Array} Returns `array`. + */ + function arrayPush(array, values) { + var index = -1, + length = values.length, + offset = array.length; + + while (++index < length) { + array[offset + index] = values[index]; + } + return array; + } + + module.exports = arrayPush; + + +/***/ }), +/* 108 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayPush = __webpack_require__(107), + isFlattenable = __webpack_require__(109); + + /** + * The base implementation of `_.flatten` with support for restricting flattening. + * + * @private + * @param {Array} array The array to flatten. + * @param {number} depth The maximum recursion depth. + * @param {boolean} [predicate=isFlattenable] The function invoked per iteration. + * @param {boolean} [isStrict] Restrict to values that pass `predicate` checks. + * @param {Array} [result=[]] The initial result value. + * @returns {Array} Returns the new flattened array. + */ + function baseFlatten(array, depth, predicate, isStrict, result) { + var index = -1, + length = array.length; + + predicate || (predicate = isFlattenable); + result || (result = []); + + while (++index < length) { + var value = array[index]; + if (depth > 0 && predicate(value)) { + if (depth > 1) { + // Recursively flatten arrays (susceptible to call stack limits). + baseFlatten(value, depth - 1, predicate, isStrict, result); + } else { + arrayPush(result, value); + } + } else if (!isStrict) { + result[result.length] = value; + } + } + return result; + } + + module.exports = baseFlatten; + + +/***/ }), +/* 109 */ +/***/ (function(module, exports, __webpack_require__) { + + var Symbol = __webpack_require__(92), + isArguments = __webpack_require__(110), + isArray = __webpack_require__(112); + + /** Built-in value references. */ + var spreadableSymbol = Symbol ? Symbol.isConcatSpreadable : undefined; + + /** + * Checks if `value` is a flattenable `arguments` object or array. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is flattenable, else `false`. + */ + function isFlattenable(value) { + return isArray(value) || isArguments(value) || + !!(spreadableSymbol && value && value[spreadableSymbol]); + } + + module.exports = isFlattenable; + + +/***/ }), +/* 110 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIsArguments = __webpack_require__(111), + isObjectLike = __webpack_require__(104); + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** Built-in value references. */ + var propertyIsEnumerable = objectProto.propertyIsEnumerable; + + /** + * Checks if `value` is likely an `arguments` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an `arguments` object, + * else `false`. + * @example + * + * _.isArguments(function() { return arguments; }()); + * // => true + * + * _.isArguments([1, 2, 3]); + * // => false + */ + var isArguments = baseIsArguments(function() { return arguments; }()) ? baseIsArguments : function(value) { + return isObjectLike(value) && hasOwnProperty.call(value, 'callee') && + !propertyIsEnumerable.call(value, 'callee'); + }; + + module.exports = isArguments; + + +/***/ }), +/* 111 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseGetTag = __webpack_require__(91), + isObjectLike = __webpack_require__(104); + + /** `Object#toString` result references. */ + var argsTag = '[object Arguments]'; + + /** + * The base implementation of `_.isArguments`. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an `arguments` object, + */ + function baseIsArguments(value) { + return isObjectLike(value) && baseGetTag(value) == argsTag; + } + + module.exports = baseIsArguments; + + +/***/ }), +/* 112 */ +/***/ (function(module, exports) { + + /** + * Checks if `value` is classified as an `Array` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an array, else `false`. + * @example + * + * _.isArray([1, 2, 3]); + * // => true + * + * _.isArray(document.body.children); + * // => false + * + * _.isArray('abc'); + * // => false + * + * _.isArray(_.noop); + * // => false + */ + var isArray = Array.isArray; + + module.exports = isArray; + + +/***/ }), +/* 113 */ +/***/ (function(module, exports) { + + /** + * Copies the values of `source` to `array`. + * + * @private + * @param {Array} source The array to copy values from. + * @param {Array} [array=[]] The array to copy values to. + * @returns {Array} Returns `array`. + */ + function copyArray(source, array) { + var index = -1, + length = source.length; + + array || (array = Array(length)); + while (++index < length) { + array[index] = source[index]; + } + return array; + } + + module.exports = copyArray; + + +/***/ }), +/* 114 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseDifference = __webpack_require__(115), + baseFlatten = __webpack_require__(108), + baseRest = __webpack_require__(157), + isArrayLikeObject = __webpack_require__(166); + + /** + * Creates an array of `array` values not included in the other given arrays + * using [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. The order and references of result values are + * determined by the first array. + * + * **Note:** Unlike `_.pullAll`, this method returns a new array. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {...Array} [values] The values to exclude. + * @returns {Array} Returns the new array of filtered values. + * @see _.without, _.xor + * @example + * + * _.difference([2, 1], [2, 3]); + * // => [1] + */ + var difference = baseRest(function(array, values) { + return isArrayLikeObject(array) + ? baseDifference(array, baseFlatten(values, 1, isArrayLikeObject, true)) + : []; + }); + + module.exports = difference; + + +/***/ }), +/* 115 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetCache = __webpack_require__(116), + arrayIncludes = __webpack_require__(148), + arrayIncludesWith = __webpack_require__(153), + arrayMap = __webpack_require__(154), + baseUnary = __webpack_require__(155), + cacheHas = __webpack_require__(156); + + /** Used as the size to enable large array optimizations. */ + var LARGE_ARRAY_SIZE = 200; + + /** + * The base implementation of methods like `_.difference` without support + * for excluding multiple arrays or iteratee shorthands. + * + * @private + * @param {Array} array The array to inspect. + * @param {Array} values The values to exclude. + * @param {Function} [iteratee] The iteratee invoked per element. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new array of filtered values. + */ + function baseDifference(array, values, iteratee, comparator) { + var index = -1, + includes = arrayIncludes, + isCommon = true, + length = array.length, + result = [], + valuesLength = values.length; + + if (!length) { + return result; + } + if (iteratee) { + values = arrayMap(values, baseUnary(iteratee)); + } + if (comparator) { + includes = arrayIncludesWith; + isCommon = false; + } + else if (values.length >= LARGE_ARRAY_SIZE) { + includes = cacheHas; + isCommon = false; + values = new SetCache(values); + } + outer: + while (++index < length) { + var value = array[index], + computed = iteratee == null ? value : iteratee(value); + + value = (comparator || value !== 0) ? value : 0; + if (isCommon && computed === computed) { + var valuesIndex = valuesLength; + while (valuesIndex--) { + if (values[valuesIndex] === computed) { + continue outer; + } + } + result.push(value); + } + else if (!includes(values, computed, comparator)) { + result.push(value); + } + } + return result; + } + + module.exports = baseDifference; + + +/***/ }), +/* 116 */ +/***/ (function(module, exports, __webpack_require__) { + + var MapCache = __webpack_require__(117), + setCacheAdd = __webpack_require__(146), + setCacheHas = __webpack_require__(147); + + /** + * + * Creates an array cache object to store unique values. + * + * @private + * @constructor + * @param {Array} [values] The values to cache. + */ + function SetCache(values) { + var index = -1, + length = values == null ? 0 : values.length; + + this.__data__ = new MapCache; + while (++index < length) { + this.add(values[index]); + } + } + + // Add methods to `SetCache`. + SetCache.prototype.add = SetCache.prototype.push = setCacheAdd; + SetCache.prototype.has = setCacheHas; + + module.exports = SetCache; + + +/***/ }), +/* 117 */ +/***/ (function(module, exports, __webpack_require__) { + + var mapCacheClear = __webpack_require__(118), + mapCacheDelete = __webpack_require__(140), + mapCacheGet = __webpack_require__(143), + mapCacheHas = __webpack_require__(144), + mapCacheSet = __webpack_require__(145); + + /** + * Creates a map cache object to store key-value pairs. + * + * @private + * @constructor + * @param {Array} [entries] The key-value pairs to cache. + */ + function MapCache(entries) { + var index = -1, + length = entries == null ? 0 : entries.length; + + this.clear(); + while (++index < length) { + var entry = entries[index]; + this.set(entry[0], entry[1]); + } + } + + // Add methods to `MapCache`. + MapCache.prototype.clear = mapCacheClear; + MapCache.prototype['delete'] = mapCacheDelete; + MapCache.prototype.get = mapCacheGet; + MapCache.prototype.has = mapCacheHas; + MapCache.prototype.set = mapCacheSet; + + module.exports = MapCache; + + +/***/ }), +/* 118 */ +/***/ (function(module, exports, __webpack_require__) { + + var Hash = __webpack_require__(119), + ListCache = __webpack_require__(132), + Map = __webpack_require__(139); + + /** + * Removes all key-value entries from the map. + * + * @private + * @name clear + * @memberOf MapCache + */ + function mapCacheClear() { + this.size = 0; + this.__data__ = { + 'hash': new Hash, + 'map': new (Map || ListCache), + 'string': new Hash + }; + } + + module.exports = mapCacheClear; + + +/***/ }), +/* 119 */ +/***/ (function(module, exports, __webpack_require__) { + + var hashClear = __webpack_require__(120), + hashDelete = __webpack_require__(128), + hashGet = __webpack_require__(129), + hashHas = __webpack_require__(130), + hashSet = __webpack_require__(131); + + /** + * Creates a hash object. + * + * @private + * @constructor + * @param {Array} [entries] The key-value pairs to cache. + */ + function Hash(entries) { + var index = -1, + length = entries == null ? 0 : entries.length; + + this.clear(); + while (++index < length) { + var entry = entries[index]; + this.set(entry[0], entry[1]); + } + } + + // Add methods to `Hash`. + Hash.prototype.clear = hashClear; + Hash.prototype['delete'] = hashDelete; + Hash.prototype.get = hashGet; + Hash.prototype.has = hashHas; + Hash.prototype.set = hashSet; + + module.exports = Hash; + + +/***/ }), +/* 120 */ +/***/ (function(module, exports, __webpack_require__) { + + var nativeCreate = __webpack_require__(121); + + /** + * Removes all key-value entries from the hash. + * + * @private + * @name clear + * @memberOf Hash + */ + function hashClear() { + this.__data__ = nativeCreate ? nativeCreate(null) : {}; + this.size = 0; + } + + module.exports = hashClear; + + +/***/ }), +/* 121 */ +/***/ (function(module, exports, __webpack_require__) { + + var getNative = __webpack_require__(122); + + /* Built-in method references that are verified to be native. */ + var nativeCreate = getNative(Object, 'create'); + + module.exports = nativeCreate; + + +/***/ }), +/* 122 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIsNative = __webpack_require__(123), + getValue = __webpack_require__(127); + + /** + * Gets the native function at `key` of `object`. + * + * @private + * @param {Object} object The object to query. + * @param {string} key The key of the method to get. + * @returns {*} Returns the function if it's native, else `undefined`. + */ + function getNative(object, key) { + var value = getValue(object, key); + return baseIsNative(value) ? value : undefined; + } + + module.exports = getNative; + + +/***/ }), +/* 123 */ +/***/ (function(module, exports, __webpack_require__) { + + var isFunction = __webpack_require__(90), + isMasked = __webpack_require__(124), + isObject = __webpack_require__(97), + toSource = __webpack_require__(126); + + /** + * Used to match `RegExp` + * [syntax characters](http://ecma-international.org/ecma-262/7.0/#sec-patterns). + */ + var reRegExpChar = /[\\^$.*+?()[\]{}|]/g; + + /** Used to detect host constructors (Safari). */ + var reIsHostCtor = /^\[object .+?Constructor\]$/; + + /** Used for built-in method references. */ + var funcProto = Function.prototype, + objectProto = Object.prototype; + + /** Used to resolve the decompiled source of functions. */ + var funcToString = funcProto.toString; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** Used to detect if a method is native. */ + var reIsNative = RegExp('^' + + funcToString.call(hasOwnProperty).replace(reRegExpChar, '\\$&') + .replace(/hasOwnProperty|(function).*?(?=\\\()| for .+?(?=\\\])/g, '$1.*?') + '$' + ); + + /** + * The base implementation of `_.isNative` without bad shim checks. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a native function, + * else `false`. + */ + function baseIsNative(value) { + if (!isObject(value) || isMasked(value)) { + return false; + } + var pattern = isFunction(value) ? reIsNative : reIsHostCtor; + return pattern.test(toSource(value)); + } + + module.exports = baseIsNative; + + +/***/ }), +/* 124 */ +/***/ (function(module, exports, __webpack_require__) { + + var coreJsData = __webpack_require__(125); + + /** Used to detect methods masquerading as native. */ + var maskSrcKey = (function() { + var uid = /[^.]+$/.exec(coreJsData && coreJsData.keys && coreJsData.keys.IE_PROTO || ''); + return uid ? ('Symbol(src)_1.' + uid) : ''; + }()); + + /** + * Checks if `func` has its source masked. + * + * @private + * @param {Function} func The function to check. + * @returns {boolean} Returns `true` if `func` is masked, else `false`. + */ + function isMasked(func) { + return !!maskSrcKey && (maskSrcKey in func); + } + + module.exports = isMasked; + + +/***/ }), +/* 125 */ +/***/ (function(module, exports, __webpack_require__) { + + var root = __webpack_require__(93); + + /** Used to detect overreaching core-js shims. */ + var coreJsData = root['__core-js_shared__']; + + module.exports = coreJsData; + + +/***/ }), +/* 126 */ +/***/ (function(module, exports) { + + /** Used for built-in method references. */ + var funcProto = Function.prototype; + + /** Used to resolve the decompiled source of functions. */ + var funcToString = funcProto.toString; + + /** + * Converts `func` to its source code. + * + * @private + * @param {Function} func The function to convert. + * @returns {string} Returns the source code. + */ + function toSource(func) { + if (func != null) { + try { + return funcToString.call(func); + } catch (e) {} + try { + return (func + ''); + } catch (e) {} + } + return ''; + } + + module.exports = toSource; + + +/***/ }), +/* 127 */ +/***/ (function(module, exports) { + + /** + * Gets the value at `key` of `object`. + * + * @private + * @param {Object} [object] The object to query. + * @param {string} key The key of the property to get. + * @returns {*} Returns the property value. + */ + function getValue(object, key) { + return object == null ? undefined : object[key]; + } + + module.exports = getValue; + + +/***/ }), +/* 128 */ +/***/ (function(module, exports) { + + /** + * Removes `key` and its value from the hash. + * + * @private + * @name delete + * @memberOf Hash + * @param {Object} hash The hash to modify. + * @param {string} key The key of the value to remove. + * @returns {boolean} Returns `true` if the entry was removed, else `false`. + */ + function hashDelete(key) { + var result = this.has(key) && delete this.__data__[key]; + this.size -= result ? 1 : 0; + return result; + } + + module.exports = hashDelete; + + +/***/ }), +/* 129 */ +/***/ (function(module, exports, __webpack_require__) { + + var nativeCreate = __webpack_require__(121); + + /** Used to stand-in for `undefined` hash values. */ + var HASH_UNDEFINED = '__lodash_hash_undefined__'; + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * Gets the hash value for `key`. + * + * @private + * @name get + * @memberOf Hash + * @param {string} key The key of the value to get. + * @returns {*} Returns the entry value. + */ + function hashGet(key) { + var data = this.__data__; + if (nativeCreate) { + var result = data[key]; + return result === HASH_UNDEFINED ? undefined : result; + } + return hasOwnProperty.call(data, key) ? data[key] : undefined; + } + + module.exports = hashGet; + + +/***/ }), +/* 130 */ +/***/ (function(module, exports, __webpack_require__) { + + var nativeCreate = __webpack_require__(121); + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * Checks if a hash value for `key` exists. + * + * @private + * @name has + * @memberOf Hash + * @param {string} key The key of the entry to check. + * @returns {boolean} Returns `true` if an entry for `key` exists, else `false`. + */ + function hashHas(key) { + var data = this.__data__; + return nativeCreate ? (data[key] !== undefined) : hasOwnProperty.call(data, key); + } + + module.exports = hashHas; + + +/***/ }), +/* 131 */ +/***/ (function(module, exports, __webpack_require__) { + + var nativeCreate = __webpack_require__(121); + + /** Used to stand-in for `undefined` hash values. */ + var HASH_UNDEFINED = '__lodash_hash_undefined__'; + + /** + * Sets the hash `key` to `value`. + * + * @private + * @name set + * @memberOf Hash + * @param {string} key The key of the value to set. + * @param {*} value The value to set. + * @returns {Object} Returns the hash instance. + */ + function hashSet(key, value) { + var data = this.__data__; + this.size += this.has(key) ? 0 : 1; + data[key] = (nativeCreate && value === undefined) ? HASH_UNDEFINED : value; + return this; + } + + module.exports = hashSet; + + +/***/ }), +/* 132 */ +/***/ (function(module, exports, __webpack_require__) { + + var listCacheClear = __webpack_require__(133), + listCacheDelete = __webpack_require__(134), + listCacheGet = __webpack_require__(136), + listCacheHas = __webpack_require__(137), + listCacheSet = __webpack_require__(138); + + /** + * Creates an list cache object. + * + * @private + * @constructor + * @param {Array} [entries] The key-value pairs to cache. + */ + function ListCache(entries) { + var index = -1, + length = entries == null ? 0 : entries.length; + + this.clear(); + while (++index < length) { + var entry = entries[index]; + this.set(entry[0], entry[1]); + } + } + + // Add methods to `ListCache`. + ListCache.prototype.clear = listCacheClear; + ListCache.prototype['delete'] = listCacheDelete; + ListCache.prototype.get = listCacheGet; + ListCache.prototype.has = listCacheHas; + ListCache.prototype.set = listCacheSet; + + module.exports = ListCache; + + +/***/ }), +/* 133 */ +/***/ (function(module, exports) { + + /** + * Removes all key-value entries from the list cache. + * + * @private + * @name clear + * @memberOf ListCache + */ + function listCacheClear() { + this.__data__ = []; + this.size = 0; + } + + module.exports = listCacheClear; + + +/***/ }), +/* 134 */ +/***/ (function(module, exports, __webpack_require__) { + + var assocIndexOf = __webpack_require__(135); + + /** Used for built-in method references. */ + var arrayProto = Array.prototype; + + /** Built-in value references. */ + var splice = arrayProto.splice; + + /** + * Removes `key` and its value from the list cache. + * + * @private + * @name delete + * @memberOf ListCache + * @param {string} key The key of the value to remove. + * @returns {boolean} Returns `true` if the entry was removed, else `false`. + */ + function listCacheDelete(key) { + var data = this.__data__, + index = assocIndexOf(data, key); + + if (index < 0) { + return false; + } + var lastIndex = data.length - 1; + if (index == lastIndex) { + data.pop(); + } else { + splice.call(data, index, 1); + } + --this.size; + return true; + } + + module.exports = listCacheDelete; + + +/***/ }), +/* 135 */ +/***/ (function(module, exports, __webpack_require__) { + + var eq = __webpack_require__(88); + + /** + * Gets the index at which the `key` is found in `array` of key-value pairs. + * + * @private + * @param {Array} array The array to inspect. + * @param {*} key The key to search for. + * @returns {number} Returns the index of the matched value, else `-1`. + */ + function assocIndexOf(array, key) { + var length = array.length; + while (length--) { + if (eq(array[length][0], key)) { + return length; + } + } + return -1; + } + + module.exports = assocIndexOf; + + +/***/ }), +/* 136 */ +/***/ (function(module, exports, __webpack_require__) { + + var assocIndexOf = __webpack_require__(135); + + /** + * Gets the list cache value for `key`. + * + * @private + * @name get + * @memberOf ListCache + * @param {string} key The key of the value to get. + * @returns {*} Returns the entry value. + */ + function listCacheGet(key) { + var data = this.__data__, + index = assocIndexOf(data, key); + + return index < 0 ? undefined : data[index][1]; + } + + module.exports = listCacheGet; + + +/***/ }), +/* 137 */ +/***/ (function(module, exports, __webpack_require__) { + + var assocIndexOf = __webpack_require__(135); + + /** + * Checks if a list cache value for `key` exists. + * + * @private + * @name has + * @memberOf ListCache + * @param {string} key The key of the entry to check. + * @returns {boolean} Returns `true` if an entry for `key` exists, else `false`. + */ + function listCacheHas(key) { + return assocIndexOf(this.__data__, key) > -1; + } + + module.exports = listCacheHas; + + +/***/ }), +/* 138 */ +/***/ (function(module, exports, __webpack_require__) { + + var assocIndexOf = __webpack_require__(135); + + /** + * Sets the list cache `key` to `value`. + * + * @private + * @name set + * @memberOf ListCache + * @param {string} key The key of the value to set. + * @param {*} value The value to set. + * @returns {Object} Returns the list cache instance. + */ + function listCacheSet(key, value) { + var data = this.__data__, + index = assocIndexOf(data, key); + + if (index < 0) { + ++this.size; + data.push([key, value]); + } else { + data[index][1] = value; + } + return this; + } + + module.exports = listCacheSet; + + +/***/ }), +/* 139 */ +/***/ (function(module, exports, __webpack_require__) { + + var getNative = __webpack_require__(122), + root = __webpack_require__(93); + + /* Built-in method references that are verified to be native. */ + var Map = getNative(root, 'Map'); + + module.exports = Map; + + +/***/ }), +/* 140 */ +/***/ (function(module, exports, __webpack_require__) { + + var getMapData = __webpack_require__(141); + + /** + * Removes `key` and its value from the map. + * + * @private + * @name delete + * @memberOf MapCache + * @param {string} key The key of the value to remove. + * @returns {boolean} Returns `true` if the entry was removed, else `false`. + */ + function mapCacheDelete(key) { + var result = getMapData(this, key)['delete'](key); + this.size -= result ? 1 : 0; + return result; + } + + module.exports = mapCacheDelete; + + +/***/ }), +/* 141 */ +/***/ (function(module, exports, __webpack_require__) { + + var isKeyable = __webpack_require__(142); + + /** + * Gets the data for `map`. + * + * @private + * @param {Object} map The map to query. + * @param {string} key The reference key. + * @returns {*} Returns the map data. + */ + function getMapData(map, key) { + var data = map.__data__; + return isKeyable(key) + ? data[typeof key == 'string' ? 'string' : 'hash'] + : data.map; + } + + module.exports = getMapData; + + +/***/ }), +/* 142 */ +/***/ (function(module, exports) { + + /** + * Checks if `value` is suitable for use as unique object key. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is suitable, else `false`. + */ + function isKeyable(value) { + var type = typeof value; + return (type == 'string' || type == 'number' || type == 'symbol' || type == 'boolean') + ? (value !== '__proto__') + : (value === null); + } + + module.exports = isKeyable; + + +/***/ }), +/* 143 */ +/***/ (function(module, exports, __webpack_require__) { + + var getMapData = __webpack_require__(141); + + /** + * Gets the map value for `key`. + * + * @private + * @name get + * @memberOf MapCache + * @param {string} key The key of the value to get. + * @returns {*} Returns the entry value. + */ + function mapCacheGet(key) { + return getMapData(this, key).get(key); + } + + module.exports = mapCacheGet; + + +/***/ }), +/* 144 */ +/***/ (function(module, exports, __webpack_require__) { + + var getMapData = __webpack_require__(141); + + /** + * Checks if a map value for `key` exists. + * + * @private + * @name has + * @memberOf MapCache + * @param {string} key The key of the entry to check. + * @returns {boolean} Returns `true` if an entry for `key` exists, else `false`. + */ + function mapCacheHas(key) { + return getMapData(this, key).has(key); + } + + module.exports = mapCacheHas; + + +/***/ }), +/* 145 */ +/***/ (function(module, exports, __webpack_require__) { + + var getMapData = __webpack_require__(141); + + /** + * Sets the map `key` to `value`. + * + * @private + * @name set + * @memberOf MapCache + * @param {string} key The key of the value to set. + * @param {*} value The value to set. + * @returns {Object} Returns the map cache instance. + */ + function mapCacheSet(key, value) { + var data = getMapData(this, key), + size = data.size; + + data.set(key, value); + this.size += data.size == size ? 0 : 1; + return this; + } + + module.exports = mapCacheSet; + + +/***/ }), +/* 146 */ +/***/ (function(module, exports) { + + /** Used to stand-in for `undefined` hash values. */ + var HASH_UNDEFINED = '__lodash_hash_undefined__'; + + /** + * Adds `value` to the array cache. + * + * @private + * @name add + * @memberOf SetCache + * @alias push + * @param {*} value The value to cache. + * @returns {Object} Returns the cache instance. + */ + function setCacheAdd(value) { + this.__data__.set(value, HASH_UNDEFINED); + return this; + } + + module.exports = setCacheAdd; + + +/***/ }), +/* 147 */ +/***/ (function(module, exports) { + + /** + * Checks if `value` is in the array cache. + * + * @private + * @name has + * @memberOf SetCache + * @param {*} value The value to search for. + * @returns {number} Returns `true` if `value` is found, else `false`. + */ + function setCacheHas(value) { + return this.__data__.has(value); + } + + module.exports = setCacheHas; + + +/***/ }), +/* 148 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIndexOf = __webpack_require__(149); + + /** + * A specialized version of `_.includes` for arrays without support for + * specifying an index to search from. + * + * @private + * @param {Array} [array] The array to inspect. + * @param {*} target The value to search for. + * @returns {boolean} Returns `true` if `target` is found, else `false`. + */ + function arrayIncludes(array, value) { + var length = array == null ? 0 : array.length; + return !!length && baseIndexOf(array, value, 0) > -1; + } + + module.exports = arrayIncludes; + + +/***/ }), +/* 149 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFindIndex = __webpack_require__(150), + baseIsNaN = __webpack_require__(151), + strictIndexOf = __webpack_require__(152); + + /** + * The base implementation of `_.indexOf` without `fromIndex` bounds checks. + * + * @private + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @param {number} fromIndex The index to search from. + * @returns {number} Returns the index of the matched value, else `-1`. + */ + function baseIndexOf(array, value, fromIndex) { + return value === value + ? strictIndexOf(array, value, fromIndex) + : baseFindIndex(array, baseIsNaN, fromIndex); + } + + module.exports = baseIndexOf; + + +/***/ }), +/* 150 */ +/***/ (function(module, exports) { + + /** + * The base implementation of `_.findIndex` and `_.findLastIndex` without + * support for iteratee shorthands. + * + * @private + * @param {Array} array The array to inspect. + * @param {Function} predicate The function invoked per iteration. + * @param {number} fromIndex The index to search from. + * @param {boolean} [fromRight] Specify iterating from right to left. + * @returns {number} Returns the index of the matched value, else `-1`. + */ + function baseFindIndex(array, predicate, fromIndex, fromRight) { + var length = array.length, + index = fromIndex + (fromRight ? 1 : -1); + + while ((fromRight ? index-- : ++index < length)) { + if (predicate(array[index], index, array)) { + return index; + } + } + return -1; + } + + module.exports = baseFindIndex; + + +/***/ }), +/* 151 */ +/***/ (function(module, exports) { + + /** + * The base implementation of `_.isNaN` without support for number objects. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is `NaN`, else `false`. + */ + function baseIsNaN(value) { + return value !== value; + } + + module.exports = baseIsNaN; + + +/***/ }), +/* 152 */ +/***/ (function(module, exports) { + + /** + * A specialized version of `_.indexOf` which performs strict equality + * comparisons of values, i.e. `===`. + * + * @private + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @param {number} fromIndex The index to search from. + * @returns {number} Returns the index of the matched value, else `-1`. + */ + function strictIndexOf(array, value, fromIndex) { + var index = fromIndex - 1, + length = array.length; + + while (++index < length) { + if (array[index] === value) { + return index; + } + } + return -1; + } + + module.exports = strictIndexOf; + + +/***/ }), +/* 153 */ +/***/ (function(module, exports) { + + /** + * This function is like `arrayIncludes` except that it accepts a comparator. + * + * @private + * @param {Array} [array] The array to inspect. + * @param {*} target The value to search for. + * @param {Function} comparator The comparator invoked per element. + * @returns {boolean} Returns `true` if `target` is found, else `false`. + */ + function arrayIncludesWith(array, value, comparator) { + var index = -1, + length = array == null ? 0 : array.length; + + while (++index < length) { + if (comparator(value, array[index])) { + return true; + } + } + return false; + } + + module.exports = arrayIncludesWith; + + +/***/ }), +/* 154 */ +/***/ (function(module, exports) { + + /** + * A specialized version of `_.map` for arrays without support for iteratee + * shorthands. + * + * @private + * @param {Array} [array] The array to iterate over. + * @param {Function} iteratee The function invoked per iteration. + * @returns {Array} Returns the new mapped array. + */ + function arrayMap(array, iteratee) { + var index = -1, + length = array == null ? 0 : array.length, + result = Array(length); + + while (++index < length) { + result[index] = iteratee(array[index], index, array); + } + return result; + } + + module.exports = arrayMap; + + +/***/ }), +/* 155 */ +/***/ (function(module, exports) { + + /** + * The base implementation of `_.unary` without support for storing metadata. + * + * @private + * @param {Function} func The function to cap arguments for. + * @returns {Function} Returns the new capped function. + */ + function baseUnary(func) { + return function(value) { + return func(value); + }; + } + + module.exports = baseUnary; + + +/***/ }), +/* 156 */ +/***/ (function(module, exports) { + + /** + * Checks if a `cache` value for `key` exists. + * + * @private + * @param {Object} cache The cache to query. + * @param {string} key The key of the entry to check. + * @returns {boolean} Returns `true` if an entry for `key` exists, else `false`. + */ + function cacheHas(cache, key) { + return cache.has(key); + } + + module.exports = cacheHas; + + +/***/ }), +/* 157 */ +/***/ (function(module, exports, __webpack_require__) { + + var identity = __webpack_require__(158), + overRest = __webpack_require__(159), + setToString = __webpack_require__(161); + + /** + * The base implementation of `_.rest` which doesn't validate or coerce arguments. + * + * @private + * @param {Function} func The function to apply a rest parameter to. + * @param {number} [start=func.length-1] The start position of the rest parameter. + * @returns {Function} Returns the new function. + */ + function baseRest(func, start) { + return setToString(overRest(func, start, identity), func + ''); + } + + module.exports = baseRest; + + +/***/ }), +/* 158 */ +/***/ (function(module, exports) { + + /** + * This method returns the first argument it receives. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Util + * @param {*} value Any value. + * @returns {*} Returns `value`. + * @example + * + * var object = { 'a': 1 }; + * + * console.log(_.identity(object) === object); + * // => true + */ + function identity(value) { + return value; + } + + module.exports = identity; + + +/***/ }), +/* 159 */ +/***/ (function(module, exports, __webpack_require__) { + + var apply = __webpack_require__(160); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeMax = Math.max; + + /** + * A specialized version of `baseRest` which transforms the rest array. + * + * @private + * @param {Function} func The function to apply a rest parameter to. + * @param {number} [start=func.length-1] The start position of the rest parameter. + * @param {Function} transform The rest array transform. + * @returns {Function} Returns the new function. + */ + function overRest(func, start, transform) { + start = nativeMax(start === undefined ? (func.length - 1) : start, 0); + return function() { + var args = arguments, + index = -1, + length = nativeMax(args.length - start, 0), + array = Array(length); + + while (++index < length) { + array[index] = args[start + index]; + } + index = -1; + var otherArgs = Array(start + 1); + while (++index < start) { + otherArgs[index] = args[index]; + } + otherArgs[start] = transform(array); + return apply(func, this, otherArgs); + }; + } + + module.exports = overRest; + + +/***/ }), +/* 160 */ +/***/ (function(module, exports) { + + /** + * A faster alternative to `Function#apply`, this function invokes `func` + * with the `this` binding of `thisArg` and the arguments of `args`. + * + * @private + * @param {Function} func The function to invoke. + * @param {*} thisArg The `this` binding of `func`. + * @param {Array} args The arguments to invoke `func` with. + * @returns {*} Returns the result of `func`. + */ + function apply(func, thisArg, args) { + switch (args.length) { + case 0: return func.call(thisArg); + case 1: return func.call(thisArg, args[0]); + case 2: return func.call(thisArg, args[0], args[1]); + case 3: return func.call(thisArg, args[0], args[1], args[2]); + } + return func.apply(thisArg, args); + } + + module.exports = apply; + + +/***/ }), +/* 161 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSetToString = __webpack_require__(162), + shortOut = __webpack_require__(165); + + /** + * Sets the `toString` method of `func` to return `string`. + * + * @private + * @param {Function} func The function to modify. + * @param {Function} string The `toString` result. + * @returns {Function} Returns `func`. + */ + var setToString = shortOut(baseSetToString); + + module.exports = setToString; + + +/***/ }), +/* 162 */ +/***/ (function(module, exports, __webpack_require__) { + + var constant = __webpack_require__(163), + defineProperty = __webpack_require__(164), + identity = __webpack_require__(158); + + /** + * The base implementation of `setToString` without support for hot loop shorting. + * + * @private + * @param {Function} func The function to modify. + * @param {Function} string The `toString` result. + * @returns {Function} Returns `func`. + */ + var baseSetToString = !defineProperty ? identity : function(func, string) { + return defineProperty(func, 'toString', { + 'configurable': true, + 'enumerable': false, + 'value': constant(string), + 'writable': true + }); + }; + + module.exports = baseSetToString; + + +/***/ }), +/* 163 */ +/***/ (function(module, exports) { + + /** + * Creates a function that returns `value`. + * + * @static + * @memberOf _ + * @since 2.4.0 + * @category Util + * @param {*} value The value to return from the new function. + * @returns {Function} Returns the new constant function. + * @example + * + * var objects = _.times(2, _.constant({ 'a': 1 })); + * + * console.log(objects); + * // => [{ 'a': 1 }, { 'a': 1 }] + * + * console.log(objects[0] === objects[1]); + * // => true + */ + function constant(value) { + return function() { + return value; + }; + } + + module.exports = constant; + + +/***/ }), +/* 164 */ +/***/ (function(module, exports, __webpack_require__) { + + var getNative = __webpack_require__(122); + + var defineProperty = (function() { + try { + var func = getNative(Object, 'defineProperty'); + func({}, '', {}); + return func; + } catch (e) {} + }()); + + module.exports = defineProperty; + + +/***/ }), +/* 165 */ +/***/ (function(module, exports) { + + /** Used to detect hot functions by number of calls within a span of milliseconds. */ + var HOT_COUNT = 800, + HOT_SPAN = 16; + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeNow = Date.now; + + /** + * Creates a function that'll short out and invoke `identity` instead + * of `func` when it's called `HOT_COUNT` or more times in `HOT_SPAN` + * milliseconds. + * + * @private + * @param {Function} func The function to restrict. + * @returns {Function} Returns the new shortable function. + */ + function shortOut(func) { + var count = 0, + lastCalled = 0; + + return function() { + var stamp = nativeNow(), + remaining = HOT_SPAN - (stamp - lastCalled); + + lastCalled = stamp; + if (remaining > 0) { + if (++count >= HOT_COUNT) { + return arguments[0]; + } + } else { + count = 0; + } + return func.apply(undefined, arguments); + }; + } + + module.exports = shortOut; + + +/***/ }), +/* 166 */ +/***/ (function(module, exports, __webpack_require__) { + + var isArrayLike = __webpack_require__(89), + isObjectLike = __webpack_require__(104); + + /** + * This method is like `_.isArrayLike` except that it also checks if `value` + * is an object. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an array-like object, + * else `false`. + * @example + * + * _.isArrayLikeObject([1, 2, 3]); + * // => true + * + * _.isArrayLikeObject(document.body.children); + * // => true + * + * _.isArrayLikeObject('abc'); + * // => false + * + * _.isArrayLikeObject(_.noop); + * // => false + */ + function isArrayLikeObject(value) { + return isObjectLike(value) && isArrayLike(value); + } + + module.exports = isArrayLikeObject; + + +/***/ }), +/* 167 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseDifference = __webpack_require__(115), + baseFlatten = __webpack_require__(108), + baseIteratee = __webpack_require__(168), + baseRest = __webpack_require__(157), + isArrayLikeObject = __webpack_require__(166), + last = __webpack_require__(228); + + /** + * This method is like `_.difference` except that it accepts `iteratee` which + * is invoked for each element of `array` and `values` to generate the criterion + * by which they're compared. The order and references of result values are + * determined by the first array. The iteratee is invoked with one argument: + * (value). + * + * **Note:** Unlike `_.pullAllBy`, this method returns a new array. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {...Array} [values] The values to exclude. + * @param {Function} [iteratee=_.identity] The iteratee invoked per element. + * @returns {Array} Returns the new array of filtered values. + * @example + * + * _.differenceBy([2.1, 1.2], [2.3, 3.4], Math.floor); + * // => [1.2] + * + * // The `_.property` iteratee shorthand. + * _.differenceBy([{ 'x': 2 }, { 'x': 1 }], [{ 'x': 1 }], 'x'); + * // => [{ 'x': 2 }] + */ + var differenceBy = baseRest(function(array, values) { + var iteratee = last(values); + if (isArrayLikeObject(iteratee)) { + iteratee = undefined; + } + return isArrayLikeObject(array) + ? baseDifference(array, baseFlatten(values, 1, isArrayLikeObject, true), baseIteratee(iteratee, 2)) + : []; + }); + + module.exports = differenceBy; + + +/***/ }), +/* 168 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseMatches = __webpack_require__(169), + baseMatchesProperty = __webpack_require__(211), + identity = __webpack_require__(158), + isArray = __webpack_require__(112), + property = __webpack_require__(225); + + /** + * The base implementation of `_.iteratee`. + * + * @private + * @param {*} [value=_.identity] The value to convert to an iteratee. + * @returns {Function} Returns the iteratee. + */ + function baseIteratee(value) { + // Don't store the `typeof` result in a variable to avoid a JIT bug in Safari 9. + // See https://bugs.webkit.org/show_bug.cgi?id=156034 for more details. + if (typeof value == 'function') { + return value; + } + if (value == null) { + return identity; + } + if (typeof value == 'object') { + return isArray(value) + ? baseMatchesProperty(value[0], value[1]) + : baseMatches(value); + } + return property(value); + } + + module.exports = baseIteratee; + + +/***/ }), +/* 169 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIsMatch = __webpack_require__(170), + getMatchData = __webpack_require__(208), + matchesStrictComparable = __webpack_require__(210); + + /** + * The base implementation of `_.matches` which doesn't clone `source`. + * + * @private + * @param {Object} source The object of property values to match. + * @returns {Function} Returns the new spec function. + */ + function baseMatches(source) { + var matchData = getMatchData(source); + if (matchData.length == 1 && matchData[0][2]) { + return matchesStrictComparable(matchData[0][0], matchData[0][1]); + } + return function(object) { + return object === source || baseIsMatch(object, source, matchData); + }; + } + + module.exports = baseMatches; + + +/***/ }), +/* 170 */ +/***/ (function(module, exports, __webpack_require__) { + + var Stack = __webpack_require__(171), + baseIsEqual = __webpack_require__(177); + + /** Used to compose bitmasks for value comparisons. */ + var COMPARE_PARTIAL_FLAG = 1, + COMPARE_UNORDERED_FLAG = 2; + + /** + * The base implementation of `_.isMatch` without support for iteratee shorthands. + * + * @private + * @param {Object} object The object to inspect. + * @param {Object} source The object of property values to match. + * @param {Array} matchData The property names, values, and compare flags to match. + * @param {Function} [customizer] The function to customize comparisons. + * @returns {boolean} Returns `true` if `object` is a match, else `false`. + */ + function baseIsMatch(object, source, matchData, customizer) { + var index = matchData.length, + length = index, + noCustomizer = !customizer; + + if (object == null) { + return !length; + } + object = Object(object); + while (index--) { + var data = matchData[index]; + if ((noCustomizer && data[2]) + ? data[1] !== object[data[0]] + : !(data[0] in object) + ) { + return false; + } + } + while (++index < length) { + data = matchData[index]; + var key = data[0], + objValue = object[key], + srcValue = data[1]; + + if (noCustomizer && data[2]) { + if (objValue === undefined && !(key in object)) { + return false; + } + } else { + var stack = new Stack; + if (customizer) { + var result = customizer(objValue, srcValue, key, object, source, stack); + } + if (!(result === undefined + ? baseIsEqual(srcValue, objValue, COMPARE_PARTIAL_FLAG | COMPARE_UNORDERED_FLAG, customizer, stack) + : result + )) { + return false; + } + } + } + return true; + } + + module.exports = baseIsMatch; + + +/***/ }), +/* 171 */ +/***/ (function(module, exports, __webpack_require__) { + + var ListCache = __webpack_require__(132), + stackClear = __webpack_require__(172), + stackDelete = __webpack_require__(173), + stackGet = __webpack_require__(174), + stackHas = __webpack_require__(175), + stackSet = __webpack_require__(176); + + /** + * Creates a stack cache object to store key-value pairs. + * + * @private + * @constructor + * @param {Array} [entries] The key-value pairs to cache. + */ + function Stack(entries) { + var data = this.__data__ = new ListCache(entries); + this.size = data.size; + } + + // Add methods to `Stack`. + Stack.prototype.clear = stackClear; + Stack.prototype['delete'] = stackDelete; + Stack.prototype.get = stackGet; + Stack.prototype.has = stackHas; + Stack.prototype.set = stackSet; + + module.exports = Stack; + + +/***/ }), +/* 172 */ +/***/ (function(module, exports, __webpack_require__) { + + var ListCache = __webpack_require__(132); + + /** + * Removes all key-value entries from the stack. + * + * @private + * @name clear + * @memberOf Stack + */ + function stackClear() { + this.__data__ = new ListCache; + this.size = 0; + } + + module.exports = stackClear; + + +/***/ }), +/* 173 */ +/***/ (function(module, exports) { + + /** + * Removes `key` and its value from the stack. + * + * @private + * @name delete + * @memberOf Stack + * @param {string} key The key of the value to remove. + * @returns {boolean} Returns `true` if the entry was removed, else `false`. + */ + function stackDelete(key) { + var data = this.__data__, + result = data['delete'](key); + + this.size = data.size; + return result; + } + + module.exports = stackDelete; + + +/***/ }), +/* 174 */ +/***/ (function(module, exports) { + + /** + * Gets the stack value for `key`. + * + * @private + * @name get + * @memberOf Stack + * @param {string} key The key of the value to get. + * @returns {*} Returns the entry value. + */ + function stackGet(key) { + return this.__data__.get(key); + } + + module.exports = stackGet; + + +/***/ }), +/* 175 */ +/***/ (function(module, exports) { + + /** + * Checks if a stack value for `key` exists. + * + * @private + * @name has + * @memberOf Stack + * @param {string} key The key of the entry to check. + * @returns {boolean} Returns `true` if an entry for `key` exists, else `false`. + */ + function stackHas(key) { + return this.__data__.has(key); + } + + module.exports = stackHas; + + +/***/ }), +/* 176 */ +/***/ (function(module, exports, __webpack_require__) { + + var ListCache = __webpack_require__(132), + Map = __webpack_require__(139), + MapCache = __webpack_require__(117); + + /** Used as the size to enable large array optimizations. */ + var LARGE_ARRAY_SIZE = 200; + + /** + * Sets the stack `key` to `value`. + * + * @private + * @name set + * @memberOf Stack + * @param {string} key The key of the value to set. + * @param {*} value The value to set. + * @returns {Object} Returns the stack cache instance. + */ + function stackSet(key, value) { + var data = this.__data__; + if (data instanceof ListCache) { + var pairs = data.__data__; + if (!Map || (pairs.length < LARGE_ARRAY_SIZE - 1)) { + pairs.push([key, value]); + this.size = ++data.size; + return this; + } + data = this.__data__ = new MapCache(pairs); + } + data.set(key, value); + this.size = data.size; + return this; + } + + module.exports = stackSet; + + +/***/ }), +/* 177 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIsEqualDeep = __webpack_require__(178), + isObjectLike = __webpack_require__(104); + + /** + * The base implementation of `_.isEqual` which supports partial comparisons + * and tracks traversed objects. + * + * @private + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @param {boolean} bitmask The bitmask flags. + * 1 - Unordered comparison + * 2 - Partial comparison + * @param {Function} [customizer] The function to customize comparisons. + * @param {Object} [stack] Tracks traversed `value` and `other` objects. + * @returns {boolean} Returns `true` if the values are equivalent, else `false`. + */ + function baseIsEqual(value, other, bitmask, customizer, stack) { + if (value === other) { + return true; + } + if (value == null || other == null || (!isObjectLike(value) && !isObjectLike(other))) { + return value !== value && other !== other; + } + return baseIsEqualDeep(value, other, bitmask, customizer, baseIsEqual, stack); + } + + module.exports = baseIsEqual; + + +/***/ }), +/* 178 */ +/***/ (function(module, exports, __webpack_require__) { + + var Stack = __webpack_require__(171), + equalArrays = __webpack_require__(179), + equalByTag = __webpack_require__(181), + equalObjects = __webpack_require__(185), + getTag = __webpack_require__(203), + isArray = __webpack_require__(112), + isBuffer = __webpack_require__(194), + isTypedArray = __webpack_require__(196); + + /** Used to compose bitmasks for value comparisons. */ + var COMPARE_PARTIAL_FLAG = 1; + + /** `Object#toString` result references. */ + var argsTag = '[object Arguments]', + arrayTag = '[object Array]', + objectTag = '[object Object]'; + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * A specialized version of `baseIsEqual` for arrays and objects which performs + * deep comparisons and tracks traversed objects enabling objects with circular + * references to be compared. + * + * @private + * @param {Object} object The object to compare. + * @param {Object} other The other object to compare. + * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. + * @param {Function} customizer The function to customize comparisons. + * @param {Function} equalFunc The function to determine equivalents of values. + * @param {Object} [stack] Tracks traversed `object` and `other` objects. + * @returns {boolean} Returns `true` if the objects are equivalent, else `false`. + */ + function baseIsEqualDeep(object, other, bitmask, customizer, equalFunc, stack) { + var objIsArr = isArray(object), + othIsArr = isArray(other), + objTag = objIsArr ? arrayTag : getTag(object), + othTag = othIsArr ? arrayTag : getTag(other); + + objTag = objTag == argsTag ? objectTag : objTag; + othTag = othTag == argsTag ? objectTag : othTag; + + var objIsObj = objTag == objectTag, + othIsObj = othTag == objectTag, + isSameTag = objTag == othTag; + + if (isSameTag && isBuffer(object)) { + if (!isBuffer(other)) { + return false; + } + objIsArr = true; + objIsObj = false; + } + if (isSameTag && !objIsObj) { + stack || (stack = new Stack); + return (objIsArr || isTypedArray(object)) + ? equalArrays(object, other, bitmask, customizer, equalFunc, stack) + : equalByTag(object, other, objTag, bitmask, customizer, equalFunc, stack); + } + if (!(bitmask & COMPARE_PARTIAL_FLAG)) { + var objIsWrapped = objIsObj && hasOwnProperty.call(object, '__wrapped__'), + othIsWrapped = othIsObj && hasOwnProperty.call(other, '__wrapped__'); + + if (objIsWrapped || othIsWrapped) { + var objUnwrapped = objIsWrapped ? object.value() : object, + othUnwrapped = othIsWrapped ? other.value() : other; + + stack || (stack = new Stack); + return equalFunc(objUnwrapped, othUnwrapped, bitmask, customizer, stack); + } + } + if (!isSameTag) { + return false; + } + stack || (stack = new Stack); + return equalObjects(object, other, bitmask, customizer, equalFunc, stack); + } + + module.exports = baseIsEqualDeep; + + +/***/ }), +/* 179 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetCache = __webpack_require__(116), + arraySome = __webpack_require__(180), + cacheHas = __webpack_require__(156); + + /** Used to compose bitmasks for value comparisons. */ + var COMPARE_PARTIAL_FLAG = 1, + COMPARE_UNORDERED_FLAG = 2; + + /** + * A specialized version of `baseIsEqualDeep` for arrays with support for + * partial deep comparisons. + * + * @private + * @param {Array} array The array to compare. + * @param {Array} other The other array to compare. + * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. + * @param {Function} customizer The function to customize comparisons. + * @param {Function} equalFunc The function to determine equivalents of values. + * @param {Object} stack Tracks traversed `array` and `other` objects. + * @returns {boolean} Returns `true` if the arrays are equivalent, else `false`. + */ + function equalArrays(array, other, bitmask, customizer, equalFunc, stack) { + var isPartial = bitmask & COMPARE_PARTIAL_FLAG, + arrLength = array.length, + othLength = other.length; + + if (arrLength != othLength && !(isPartial && othLength > arrLength)) { + return false; + } + // Assume cyclic values are equal. + var stacked = stack.get(array); + if (stacked && stack.get(other)) { + return stacked == other; + } + var index = -1, + result = true, + seen = (bitmask & COMPARE_UNORDERED_FLAG) ? new SetCache : undefined; + + stack.set(array, other); + stack.set(other, array); + + // Ignore non-index properties. + while (++index < arrLength) { + var arrValue = array[index], + othValue = other[index]; + + if (customizer) { + var compared = isPartial + ? customizer(othValue, arrValue, index, other, array, stack) + : customizer(arrValue, othValue, index, array, other, stack); + } + if (compared !== undefined) { + if (compared) { + continue; + } + result = false; + break; + } + // Recursively compare arrays (susceptible to call stack limits). + if (seen) { + if (!arraySome(other, function(othValue, othIndex) { + if (!cacheHas(seen, othIndex) && + (arrValue === othValue || equalFunc(arrValue, othValue, bitmask, customizer, stack))) { + return seen.push(othIndex); + } + })) { + result = false; + break; + } + } else if (!( + arrValue === othValue || + equalFunc(arrValue, othValue, bitmask, customizer, stack) + )) { + result = false; + break; + } + } + stack['delete'](array); + stack['delete'](other); + return result; + } + + module.exports = equalArrays; + + +/***/ }), +/* 180 */ +/***/ (function(module, exports) { + + /** + * A specialized version of `_.some` for arrays without support for iteratee + * shorthands. + * + * @private + * @param {Array} [array] The array to iterate over. + * @param {Function} predicate The function invoked per iteration. + * @returns {boolean} Returns `true` if any element passes the predicate check, + * else `false`. + */ + function arraySome(array, predicate) { + var index = -1, + length = array == null ? 0 : array.length; + + while (++index < length) { + if (predicate(array[index], index, array)) { + return true; + } + } + return false; + } + + module.exports = arraySome; + + +/***/ }), +/* 181 */ +/***/ (function(module, exports, __webpack_require__) { + + var Symbol = __webpack_require__(92), + Uint8Array = __webpack_require__(182), + eq = __webpack_require__(88), + equalArrays = __webpack_require__(179), + mapToArray = __webpack_require__(183), + setToArray = __webpack_require__(184); + + /** Used to compose bitmasks for value comparisons. */ + var COMPARE_PARTIAL_FLAG = 1, + COMPARE_UNORDERED_FLAG = 2; + + /** `Object#toString` result references. */ + var boolTag = '[object Boolean]', + dateTag = '[object Date]', + errorTag = '[object Error]', + mapTag = '[object Map]', + numberTag = '[object Number]', + regexpTag = '[object RegExp]', + setTag = '[object Set]', + stringTag = '[object String]', + symbolTag = '[object Symbol]'; + + var arrayBufferTag = '[object ArrayBuffer]', + dataViewTag = '[object DataView]'; + + /** Used to convert symbols to primitives and strings. */ + var symbolProto = Symbol ? Symbol.prototype : undefined, + symbolValueOf = symbolProto ? symbolProto.valueOf : undefined; + + /** + * A specialized version of `baseIsEqualDeep` for comparing objects of + * the same `toStringTag`. + * + * **Note:** This function only supports comparing values with tags of + * `Boolean`, `Date`, `Error`, `Number`, `RegExp`, or `String`. + * + * @private + * @param {Object} object The object to compare. + * @param {Object} other The other object to compare. + * @param {string} tag The `toStringTag` of the objects to compare. + * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. + * @param {Function} customizer The function to customize comparisons. + * @param {Function} equalFunc The function to determine equivalents of values. + * @param {Object} stack Tracks traversed `object` and `other` objects. + * @returns {boolean} Returns `true` if the objects are equivalent, else `false`. + */ + function equalByTag(object, other, tag, bitmask, customizer, equalFunc, stack) { + switch (tag) { + case dataViewTag: + if ((object.byteLength != other.byteLength) || + (object.byteOffset != other.byteOffset)) { + return false; + } + object = object.buffer; + other = other.buffer; + + case arrayBufferTag: + if ((object.byteLength != other.byteLength) || + !equalFunc(new Uint8Array(object), new Uint8Array(other))) { + return false; + } + return true; + + case boolTag: + case dateTag: + case numberTag: + // Coerce booleans to `1` or `0` and dates to milliseconds. + // Invalid dates are coerced to `NaN`. + return eq(+object, +other); + + case errorTag: + return object.name == other.name && object.message == other.message; + + case regexpTag: + case stringTag: + // Coerce regexes to strings and treat strings, primitives and objects, + // as equal. See http://www.ecma-international.org/ecma-262/7.0/#sec-regexp.prototype.tostring + // for more details. + return object == (other + ''); + + case mapTag: + var convert = mapToArray; + + case setTag: + var isPartial = bitmask & COMPARE_PARTIAL_FLAG; + convert || (convert = setToArray); + + if (object.size != other.size && !isPartial) { + return false; + } + // Assume cyclic values are equal. + var stacked = stack.get(object); + if (stacked) { + return stacked == other; + } + bitmask |= COMPARE_UNORDERED_FLAG; + + // Recursively compare objects (susceptible to call stack limits). + stack.set(object, other); + var result = equalArrays(convert(object), convert(other), bitmask, customizer, equalFunc, stack); + stack['delete'](object); + return result; + + case symbolTag: + if (symbolValueOf) { + return symbolValueOf.call(object) == symbolValueOf.call(other); + } + } + return false; + } + + module.exports = equalByTag; + + +/***/ }), +/* 182 */ +/***/ (function(module, exports, __webpack_require__) { + + var root = __webpack_require__(93); + + /** Built-in value references. */ + var Uint8Array = root.Uint8Array; + + module.exports = Uint8Array; + + +/***/ }), +/* 183 */ +/***/ (function(module, exports) { + + /** + * Converts `map` to its key-value pairs. + * + * @private + * @param {Object} map The map to convert. + * @returns {Array} Returns the key-value pairs. + */ + function mapToArray(map) { + var index = -1, + result = Array(map.size); + + map.forEach(function(value, key) { + result[++index] = [key, value]; + }); + return result; + } + + module.exports = mapToArray; + + +/***/ }), +/* 184 */ +/***/ (function(module, exports) { + + /** + * Converts `set` to an array of its values. + * + * @private + * @param {Object} set The set to convert. + * @returns {Array} Returns the values. + */ + function setToArray(set) { + var index = -1, + result = Array(set.size); + + set.forEach(function(value) { + result[++index] = value; + }); + return result; + } + + module.exports = setToArray; + + +/***/ }), +/* 185 */ +/***/ (function(module, exports, __webpack_require__) { + + var getAllKeys = __webpack_require__(186); + + /** Used to compose bitmasks for value comparisons. */ + var COMPARE_PARTIAL_FLAG = 1; + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * A specialized version of `baseIsEqualDeep` for objects with support for + * partial deep comparisons. + * + * @private + * @param {Object} object The object to compare. + * @param {Object} other The other object to compare. + * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. + * @param {Function} customizer The function to customize comparisons. + * @param {Function} equalFunc The function to determine equivalents of values. + * @param {Object} stack Tracks traversed `object` and `other` objects. + * @returns {boolean} Returns `true` if the objects are equivalent, else `false`. + */ + function equalObjects(object, other, bitmask, customizer, equalFunc, stack) { + var isPartial = bitmask & COMPARE_PARTIAL_FLAG, + objProps = getAllKeys(object), + objLength = objProps.length, + othProps = getAllKeys(other), + othLength = othProps.length; + + if (objLength != othLength && !isPartial) { + return false; + } + var index = objLength; + while (index--) { + var key = objProps[index]; + if (!(isPartial ? key in other : hasOwnProperty.call(other, key))) { + return false; + } + } + // Assume cyclic values are equal. + var stacked = stack.get(object); + if (stacked && stack.get(other)) { + return stacked == other; + } + var result = true; + stack.set(object, other); + stack.set(other, object); + + var skipCtor = isPartial; + while (++index < objLength) { + key = objProps[index]; + var objValue = object[key], + othValue = other[key]; + + if (customizer) { + var compared = isPartial + ? customizer(othValue, objValue, key, other, object, stack) + : customizer(objValue, othValue, key, object, other, stack); + } + // Recursively compare objects (susceptible to call stack limits). + if (!(compared === undefined + ? (objValue === othValue || equalFunc(objValue, othValue, bitmask, customizer, stack)) + : compared + )) { + result = false; + break; + } + skipCtor || (skipCtor = key == 'constructor'); + } + if (result && !skipCtor) { + var objCtor = object.constructor, + othCtor = other.constructor; + + // Non `Object` object instances with different constructors are not equal. + if (objCtor != othCtor && + ('constructor' in object && 'constructor' in other) && + !(typeof objCtor == 'function' && objCtor instanceof objCtor && + typeof othCtor == 'function' && othCtor instanceof othCtor)) { + result = false; + } + } + stack['delete'](object); + stack['delete'](other); + return result; + } + + module.exports = equalObjects; + + +/***/ }), +/* 186 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseGetAllKeys = __webpack_require__(187), + getSymbols = __webpack_require__(188), + keys = __webpack_require__(191); + + /** + * Creates an array of own enumerable property names and symbols of `object`. + * + * @private + * @param {Object} object The object to query. + * @returns {Array} Returns the array of property names and symbols. + */ + function getAllKeys(object) { + return baseGetAllKeys(object, keys, getSymbols); + } + + module.exports = getAllKeys; + + +/***/ }), +/* 187 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayPush = __webpack_require__(107), + isArray = __webpack_require__(112); + + /** + * The base implementation of `getAllKeys` and `getAllKeysIn` which uses + * `keysFunc` and `symbolsFunc` to get the enumerable property names and + * symbols of `object`. + * + * @private + * @param {Object} object The object to query. + * @param {Function} keysFunc The function to get the keys of `object`. + * @param {Function} symbolsFunc The function to get the symbols of `object`. + * @returns {Array} Returns the array of property names and symbols. + */ + function baseGetAllKeys(object, keysFunc, symbolsFunc) { + var result = keysFunc(object); + return isArray(object) ? result : arrayPush(result, symbolsFunc(object)); + } + + module.exports = baseGetAllKeys; + + +/***/ }), +/* 188 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayFilter = __webpack_require__(189), + stubArray = __webpack_require__(190); + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Built-in value references. */ + var propertyIsEnumerable = objectProto.propertyIsEnumerable; + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeGetSymbols = Object.getOwnPropertySymbols; + + /** + * Creates an array of the own enumerable symbols of `object`. + * + * @private + * @param {Object} object The object to query. + * @returns {Array} Returns the array of symbols. + */ + var getSymbols = !nativeGetSymbols ? stubArray : function(object) { + if (object == null) { + return []; + } + object = Object(object); + return arrayFilter(nativeGetSymbols(object), function(symbol) { + return propertyIsEnumerable.call(object, symbol); + }); + }; + + module.exports = getSymbols; + + +/***/ }), +/* 189 */ +/***/ (function(module, exports) { + + /** + * A specialized version of `_.filter` for arrays without support for + * iteratee shorthands. + * + * @private + * @param {Array} [array] The array to iterate over. + * @param {Function} predicate The function invoked per iteration. + * @returns {Array} Returns the new filtered array. + */ + function arrayFilter(array, predicate) { + var index = -1, + length = array == null ? 0 : array.length, + resIndex = 0, + result = []; + + while (++index < length) { + var value = array[index]; + if (predicate(value, index, array)) { + result[resIndex++] = value; + } + } + return result; + } + + module.exports = arrayFilter; + + +/***/ }), +/* 190 */ +/***/ (function(module, exports) { + + /** + * This method returns a new empty array. + * + * @static + * @memberOf _ + * @since 4.13.0 + * @category Util + * @returns {Array} Returns the new empty array. + * @example + * + * var arrays = _.times(2, _.stubArray); + * + * console.log(arrays); + * // => [[], []] + * + * console.log(arrays[0] === arrays[1]); + * // => false + */ + function stubArray() { + return []; + } + + module.exports = stubArray; + + +/***/ }), +/* 191 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayLikeKeys = __webpack_require__(192), + baseKeys = __webpack_require__(199), + isArrayLike = __webpack_require__(89); + + /** + * Creates an array of the own enumerable property names of `object`. + * + * **Note:** Non-object values are coerced to objects. See the + * [ES spec](http://ecma-international.org/ecma-262/7.0/#sec-object.keys) + * for more details. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Object + * @param {Object} object The object to query. + * @returns {Array} Returns the array of property names. + * @example + * + * function Foo() { + * this.a = 1; + * this.b = 2; + * } + * + * Foo.prototype.c = 3; + * + * _.keys(new Foo); + * // => ['a', 'b'] (iteration order is not guaranteed) + * + * _.keys('hi'); + * // => ['0', '1'] + */ + function keys(object) { + return isArrayLike(object) ? arrayLikeKeys(object) : baseKeys(object); + } + + module.exports = keys; + + +/***/ }), +/* 192 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseTimes = __webpack_require__(193), + isArguments = __webpack_require__(110), + isArray = __webpack_require__(112), + isBuffer = __webpack_require__(194), + isIndex = __webpack_require__(99), + isTypedArray = __webpack_require__(196); + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * Creates an array of the enumerable property names of the array-like `value`. + * + * @private + * @param {*} value The value to query. + * @param {boolean} inherited Specify returning inherited property names. + * @returns {Array} Returns the array of property names. + */ + function arrayLikeKeys(value, inherited) { + var isArr = isArray(value), + isArg = !isArr && isArguments(value), + isBuff = !isArr && !isArg && isBuffer(value), + isType = !isArr && !isArg && !isBuff && isTypedArray(value), + skipIndexes = isArr || isArg || isBuff || isType, + result = skipIndexes ? baseTimes(value.length, String) : [], + length = result.length; + + for (var key in value) { + if ((inherited || hasOwnProperty.call(value, key)) && + !(skipIndexes && ( + // Safari 9 has enumerable `arguments.length` in strict mode. + key == 'length' || + // Node.js 0.10 has enumerable non-index properties on buffers. + (isBuff && (key == 'offset' || key == 'parent')) || + // PhantomJS 2 has enumerable non-index properties on typed arrays. + (isType && (key == 'buffer' || key == 'byteLength' || key == 'byteOffset')) || + // Skip index properties. + isIndex(key, length) + ))) { + result.push(key); + } + } + return result; + } + + module.exports = arrayLikeKeys; + + +/***/ }), +/* 193 */ +/***/ (function(module, exports) { + + /** + * The base implementation of `_.times` without support for iteratee shorthands + * or max array length checks. + * + * @private + * @param {number} n The number of times to invoke `iteratee`. + * @param {Function} iteratee The function invoked per iteration. + * @returns {Array} Returns the array of results. + */ + function baseTimes(n, iteratee) { + var index = -1, + result = Array(n); + + while (++index < n) { + result[index] = iteratee(index); + } + return result; + } + + module.exports = baseTimes; + + +/***/ }), +/* 194 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(module) {var root = __webpack_require__(93), + stubFalse = __webpack_require__(195); + + /** Detect free variable `exports`. */ + var freeExports = typeof exports == 'object' && exports && !exports.nodeType && exports; + + /** Detect free variable `module`. */ + var freeModule = freeExports && typeof module == 'object' && module && !module.nodeType && module; + + /** Detect the popular CommonJS extension `module.exports`. */ + var moduleExports = freeModule && freeModule.exports === freeExports; + + /** Built-in value references. */ + var Buffer = moduleExports ? root.Buffer : undefined; + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeIsBuffer = Buffer ? Buffer.isBuffer : undefined; + + /** + * Checks if `value` is a buffer. + * + * @static + * @memberOf _ + * @since 4.3.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a buffer, else `false`. + * @example + * + * _.isBuffer(new Buffer(2)); + * // => true + * + * _.isBuffer(new Uint8Array(2)); + * // => false + */ + var isBuffer = nativeIsBuffer || stubFalse; + + module.exports = isBuffer; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(59)(module))) + +/***/ }), +/* 195 */ +/***/ (function(module, exports) { + + /** + * This method returns `false`. + * + * @static + * @memberOf _ + * @since 4.13.0 + * @category Util + * @returns {boolean} Returns `false`. + * @example + * + * _.times(2, _.stubFalse); + * // => [false, false] + */ + function stubFalse() { + return false; + } + + module.exports = stubFalse; + + +/***/ }), +/* 196 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIsTypedArray = __webpack_require__(197), + baseUnary = __webpack_require__(155), + nodeUtil = __webpack_require__(198); + + /* Node.js helper references. */ + var nodeIsTypedArray = nodeUtil && nodeUtil.isTypedArray; + + /** + * Checks if `value` is classified as a typed array. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a typed array, else `false`. + * @example + * + * _.isTypedArray(new Uint8Array); + * // => true + * + * _.isTypedArray([]); + * // => false + */ + var isTypedArray = nodeIsTypedArray ? baseUnary(nodeIsTypedArray) : baseIsTypedArray; + + module.exports = isTypedArray; + + +/***/ }), +/* 197 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseGetTag = __webpack_require__(91), + isLength = __webpack_require__(98), + isObjectLike = __webpack_require__(104); + + /** `Object#toString` result references. */ + var argsTag = '[object Arguments]', + arrayTag = '[object Array]', + boolTag = '[object Boolean]', + dateTag = '[object Date]', + errorTag = '[object Error]', + funcTag = '[object Function]', + mapTag = '[object Map]', + numberTag = '[object Number]', + objectTag = '[object Object]', + regexpTag = '[object RegExp]', + setTag = '[object Set]', + stringTag = '[object String]', + weakMapTag = '[object WeakMap]'; + + var arrayBufferTag = '[object ArrayBuffer]', + dataViewTag = '[object DataView]', + float32Tag = '[object Float32Array]', + float64Tag = '[object Float64Array]', + int8Tag = '[object Int8Array]', + int16Tag = '[object Int16Array]', + int32Tag = '[object Int32Array]', + uint8Tag = '[object Uint8Array]', + uint8ClampedTag = '[object Uint8ClampedArray]', + uint16Tag = '[object Uint16Array]', + uint32Tag = '[object Uint32Array]'; + + /** Used to identify `toStringTag` values of typed arrays. */ + var typedArrayTags = {}; + typedArrayTags[float32Tag] = typedArrayTags[float64Tag] = + typedArrayTags[int8Tag] = typedArrayTags[int16Tag] = + typedArrayTags[int32Tag] = typedArrayTags[uint8Tag] = + typedArrayTags[uint8ClampedTag] = typedArrayTags[uint16Tag] = + typedArrayTags[uint32Tag] = true; + typedArrayTags[argsTag] = typedArrayTags[arrayTag] = + typedArrayTags[arrayBufferTag] = typedArrayTags[boolTag] = + typedArrayTags[dataViewTag] = typedArrayTags[dateTag] = + typedArrayTags[errorTag] = typedArrayTags[funcTag] = + typedArrayTags[mapTag] = typedArrayTags[numberTag] = + typedArrayTags[objectTag] = typedArrayTags[regexpTag] = + typedArrayTags[setTag] = typedArrayTags[stringTag] = + typedArrayTags[weakMapTag] = false; + + /** + * The base implementation of `_.isTypedArray` without Node.js optimizations. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a typed array, else `false`. + */ + function baseIsTypedArray(value) { + return isObjectLike(value) && + isLength(value.length) && !!typedArrayTags[baseGetTag(value)]; + } + + module.exports = baseIsTypedArray; + + +/***/ }), +/* 198 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(module) {var freeGlobal = __webpack_require__(94); + + /** Detect free variable `exports`. */ + var freeExports = typeof exports == 'object' && exports && !exports.nodeType && exports; + + /** Detect free variable `module`. */ + var freeModule = freeExports && typeof module == 'object' && module && !module.nodeType && module; + + /** Detect the popular CommonJS extension `module.exports`. */ + var moduleExports = freeModule && freeModule.exports === freeExports; + + /** Detect free variable `process` from Node.js. */ + var freeProcess = moduleExports && freeGlobal.process; + + /** Used to access faster Node.js helpers. */ + var nodeUtil = (function() { + try { + // Use `util.types` for Node.js 10+. + var types = freeModule && freeModule.require && freeModule.require('util').types; + + if (types) { + return types; + } + + // Legacy `process.binding('util')` for Node.js < 10. + return freeProcess && freeProcess.binding && freeProcess.binding('util'); + } catch (e) {} + }()); + + module.exports = nodeUtil; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(59)(module))) + +/***/ }), +/* 199 */ +/***/ (function(module, exports, __webpack_require__) { + + var isPrototype = __webpack_require__(200), + nativeKeys = __webpack_require__(201); + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * The base implementation of `_.keys` which doesn't treat sparse arrays as dense. + * + * @private + * @param {Object} object The object to query. + * @returns {Array} Returns the array of property names. + */ + function baseKeys(object) { + if (!isPrototype(object)) { + return nativeKeys(object); + } + var result = []; + for (var key in Object(object)) { + if (hasOwnProperty.call(object, key) && key != 'constructor') { + result.push(key); + } + } + return result; + } + + module.exports = baseKeys; + + +/***/ }), +/* 200 */ +/***/ (function(module, exports) { + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** + * Checks if `value` is likely a prototype object. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a prototype, else `false`. + */ + function isPrototype(value) { + var Ctor = value && value.constructor, + proto = (typeof Ctor == 'function' && Ctor.prototype) || objectProto; + + return value === proto; + } + + module.exports = isPrototype; + + +/***/ }), +/* 201 */ +/***/ (function(module, exports, __webpack_require__) { + + var overArg = __webpack_require__(202); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeKeys = overArg(Object.keys, Object); + + module.exports = nativeKeys; + + +/***/ }), +/* 202 */ +/***/ (function(module, exports) { + + /** + * Creates a unary function that invokes `func` with its argument transformed. + * + * @private + * @param {Function} func The function to wrap. + * @param {Function} transform The argument transform. + * @returns {Function} Returns the new function. + */ + function overArg(func, transform) { + return function(arg) { + return func(transform(arg)); + }; + } + + module.exports = overArg; + + +/***/ }), +/* 203 */ +/***/ (function(module, exports, __webpack_require__) { + + var DataView = __webpack_require__(204), + Map = __webpack_require__(139), + Promise = __webpack_require__(205), + Set = __webpack_require__(206), + WeakMap = __webpack_require__(207), + baseGetTag = __webpack_require__(91), + toSource = __webpack_require__(126); + + /** `Object#toString` result references. */ + var mapTag = '[object Map]', + objectTag = '[object Object]', + promiseTag = '[object Promise]', + setTag = '[object Set]', + weakMapTag = '[object WeakMap]'; + + var dataViewTag = '[object DataView]'; + + /** Used to detect maps, sets, and weakmaps. */ + var dataViewCtorString = toSource(DataView), + mapCtorString = toSource(Map), + promiseCtorString = toSource(Promise), + setCtorString = toSource(Set), + weakMapCtorString = toSource(WeakMap); + + /** + * Gets the `toStringTag` of `value`. + * + * @private + * @param {*} value The value to query. + * @returns {string} Returns the `toStringTag`. + */ + var getTag = baseGetTag; + + // Fallback for data views, maps, sets, and weak maps in IE 11 and promises in Node.js < 6. + if ((DataView && getTag(new DataView(new ArrayBuffer(1))) != dataViewTag) || + (Map && getTag(new Map) != mapTag) || + (Promise && getTag(Promise.resolve()) != promiseTag) || + (Set && getTag(new Set) != setTag) || + (WeakMap && getTag(new WeakMap) != weakMapTag)) { + getTag = function(value) { + var result = baseGetTag(value), + Ctor = result == objectTag ? value.constructor : undefined, + ctorString = Ctor ? toSource(Ctor) : ''; + + if (ctorString) { + switch (ctorString) { + case dataViewCtorString: return dataViewTag; + case mapCtorString: return mapTag; + case promiseCtorString: return promiseTag; + case setCtorString: return setTag; + case weakMapCtorString: return weakMapTag; + } + } + return result; + }; + } + + module.exports = getTag; + + +/***/ }), +/* 204 */ +/***/ (function(module, exports, __webpack_require__) { + + var getNative = __webpack_require__(122), + root = __webpack_require__(93); + + /* Built-in method references that are verified to be native. */ + var DataView = getNative(root, 'DataView'); + + module.exports = DataView; + + +/***/ }), +/* 205 */ +/***/ (function(module, exports, __webpack_require__) { + + var getNative = __webpack_require__(122), + root = __webpack_require__(93); + + /* Built-in method references that are verified to be native. */ + var Promise = getNative(root, 'Promise'); + + module.exports = Promise; + + +/***/ }), +/* 206 */ +/***/ (function(module, exports, __webpack_require__) { + + var getNative = __webpack_require__(122), + root = __webpack_require__(93); + + /* Built-in method references that are verified to be native. */ + var Set = getNative(root, 'Set'); + + module.exports = Set; + + +/***/ }), +/* 207 */ +/***/ (function(module, exports, __webpack_require__) { + + var getNative = __webpack_require__(122), + root = __webpack_require__(93); + + /* Built-in method references that are verified to be native. */ + var WeakMap = getNative(root, 'WeakMap'); + + module.exports = WeakMap; + + +/***/ }), +/* 208 */ +/***/ (function(module, exports, __webpack_require__) { + + var isStrictComparable = __webpack_require__(209), + keys = __webpack_require__(191); + + /** + * Gets the property names, values, and compare flags of `object`. + * + * @private + * @param {Object} object The object to query. + * @returns {Array} Returns the match data of `object`. + */ + function getMatchData(object) { + var result = keys(object), + length = result.length; + + while (length--) { + var key = result[length], + value = object[key]; + + result[length] = [key, value, isStrictComparable(value)]; + } + return result; + } + + module.exports = getMatchData; + + +/***/ }), +/* 209 */ +/***/ (function(module, exports, __webpack_require__) { + + var isObject = __webpack_require__(97); + + /** + * Checks if `value` is suitable for strict equality comparisons, i.e. `===`. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` if suitable for strict + * equality comparisons, else `false`. + */ + function isStrictComparable(value) { + return value === value && !isObject(value); + } + + module.exports = isStrictComparable; + + +/***/ }), +/* 210 */ +/***/ (function(module, exports) { + + /** + * A specialized version of `matchesProperty` for source values suitable + * for strict equality comparisons, i.e. `===`. + * + * @private + * @param {string} key The key of the property to get. + * @param {*} srcValue The value to match. + * @returns {Function} Returns the new spec function. + */ + function matchesStrictComparable(key, srcValue) { + return function(object) { + if (object == null) { + return false; + } + return object[key] === srcValue && + (srcValue !== undefined || (key in Object(object))); + }; + } + + module.exports = matchesStrictComparable; + + +/***/ }), +/* 211 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIsEqual = __webpack_require__(177), + get = __webpack_require__(212), + hasIn = __webpack_require__(222), + isKey = __webpack_require__(215), + isStrictComparable = __webpack_require__(209), + matchesStrictComparable = __webpack_require__(210), + toKey = __webpack_require__(221); + + /** Used to compose bitmasks for value comparisons. */ + var COMPARE_PARTIAL_FLAG = 1, + COMPARE_UNORDERED_FLAG = 2; + + /** + * The base implementation of `_.matchesProperty` which doesn't clone `srcValue`. + * + * @private + * @param {string} path The path of the property to get. + * @param {*} srcValue The value to match. + * @returns {Function} Returns the new spec function. + */ + function baseMatchesProperty(path, srcValue) { + if (isKey(path) && isStrictComparable(srcValue)) { + return matchesStrictComparable(toKey(path), srcValue); + } + return function(object) { + var objValue = get(object, path); + return (objValue === undefined && objValue === srcValue) + ? hasIn(object, path) + : baseIsEqual(srcValue, objValue, COMPARE_PARTIAL_FLAG | COMPARE_UNORDERED_FLAG); + }; + } + + module.exports = baseMatchesProperty; + + +/***/ }), +/* 212 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseGet = __webpack_require__(213); + + /** + * Gets the value at `path` of `object`. If the resolved value is + * `undefined`, the `defaultValue` is returned in its place. + * + * @static + * @memberOf _ + * @since 3.7.0 + * @category Object + * @param {Object} object The object to query. + * @param {Array|string} path The path of the property to get. + * @param {*} [defaultValue] The value returned for `undefined` resolved values. + * @returns {*} Returns the resolved value. + * @example + * + * var object = { 'a': [{ 'b': { 'c': 3 } }] }; + * + * _.get(object, 'a[0].b.c'); + * // => 3 + * + * _.get(object, ['a', '0', 'b', 'c']); + * // => 3 + * + * _.get(object, 'a.b.c', 'default'); + * // => 'default' + */ + function get(object, path, defaultValue) { + var result = object == null ? undefined : baseGet(object, path); + return result === undefined ? defaultValue : result; + } + + module.exports = get; + + +/***/ }), +/* 213 */ +/***/ (function(module, exports, __webpack_require__) { + + var castPath = __webpack_require__(214), + toKey = __webpack_require__(221); + + /** + * The base implementation of `_.get` without support for default values. + * + * @private + * @param {Object} object The object to query. + * @param {Array|string} path The path of the property to get. + * @returns {*} Returns the resolved value. + */ + function baseGet(object, path) { + path = castPath(path, object); + + var index = 0, + length = path.length; + + while (object != null && index < length) { + object = object[toKey(path[index++])]; + } + return (index && index == length) ? object : undefined; + } + + module.exports = baseGet; + + +/***/ }), +/* 214 */ +/***/ (function(module, exports, __webpack_require__) { + + var isArray = __webpack_require__(112), + isKey = __webpack_require__(215), + stringToPath = __webpack_require__(216), + toString = __webpack_require__(219); + + /** + * Casts `value` to a path array if it's not one. + * + * @private + * @param {*} value The value to inspect. + * @param {Object} [object] The object to query keys on. + * @returns {Array} Returns the cast property path array. + */ + function castPath(value, object) { + if (isArray(value)) { + return value; + } + return isKey(value, object) ? [value] : stringToPath(toString(value)); + } + + module.exports = castPath; + + +/***/ }), +/* 215 */ +/***/ (function(module, exports, __webpack_require__) { + + var isArray = __webpack_require__(112), + isSymbol = __webpack_require__(103); + + /** Used to match property names within property paths. */ + var reIsDeepProp = /\.|\[(?:[^[\]]*|(["'])(?:(?!\1)[^\\]|\\.)*?\1)\]/, + reIsPlainProp = /^\w*$/; + + /** + * Checks if `value` is a property name and not a property path. + * + * @private + * @param {*} value The value to check. + * @param {Object} [object] The object to query keys on. + * @returns {boolean} Returns `true` if `value` is a property name, else `false`. + */ + function isKey(value, object) { + if (isArray(value)) { + return false; + } + var type = typeof value; + if (type == 'number' || type == 'symbol' || type == 'boolean' || + value == null || isSymbol(value)) { + return true; + } + return reIsPlainProp.test(value) || !reIsDeepProp.test(value) || + (object != null && value in Object(object)); + } + + module.exports = isKey; + + +/***/ }), +/* 216 */ +/***/ (function(module, exports, __webpack_require__) { + + var memoizeCapped = __webpack_require__(217); + + /** Used to match property names within property paths. */ + var rePropName = /[^.[\]]+|\[(?:(-?\d+(?:\.\d+)?)|(["'])((?:(?!\2)[^\\]|\\.)*?)\2)\]|(?=(?:\.|\[\])(?:\.|\[\]|$))/g; + + /** Used to match backslashes in property paths. */ + var reEscapeChar = /\\(\\)?/g; + + /** + * Converts `string` to a property path array. + * + * @private + * @param {string} string The string to convert. + * @returns {Array} Returns the property path array. + */ + var stringToPath = memoizeCapped(function(string) { + var result = []; + if (string.charCodeAt(0) === 46 /* . */) { + result.push(''); + } + string.replace(rePropName, function(match, number, quote, subString) { + result.push(quote ? subString.replace(reEscapeChar, '$1') : (number || match)); + }); + return result; + }); + + module.exports = stringToPath; + + +/***/ }), +/* 217 */ +/***/ (function(module, exports, __webpack_require__) { + + var memoize = __webpack_require__(218); + + /** Used as the maximum memoize cache size. */ + var MAX_MEMOIZE_SIZE = 500; + + /** + * A specialized version of `_.memoize` which clears the memoized function's + * cache when it exceeds `MAX_MEMOIZE_SIZE`. + * + * @private + * @param {Function} func The function to have its output memoized. + * @returns {Function} Returns the new memoized function. + */ + function memoizeCapped(func) { + var result = memoize(func, function(key) { + if (cache.size === MAX_MEMOIZE_SIZE) { + cache.clear(); + } + return key; + }); + + var cache = result.cache; + return result; + } + + module.exports = memoizeCapped; + + +/***/ }), +/* 218 */ +/***/ (function(module, exports, __webpack_require__) { + + var MapCache = __webpack_require__(117); + + /** Error message constants. */ + var FUNC_ERROR_TEXT = 'Expected a function'; + + /** + * Creates a function that memoizes the result of `func`. If `resolver` is + * provided, it determines the cache key for storing the result based on the + * arguments provided to the memoized function. By default, the first argument + * provided to the memoized function is used as the map cache key. The `func` + * is invoked with the `this` binding of the memoized function. + * + * **Note:** The cache is exposed as the `cache` property on the memoized + * function. Its creation may be customized by replacing the `_.memoize.Cache` + * constructor with one whose instances implement the + * [`Map`](http://ecma-international.org/ecma-262/7.0/#sec-properties-of-the-map-prototype-object) + * method interface of `clear`, `delete`, `get`, `has`, and `set`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Function + * @param {Function} func The function to have its output memoized. + * @param {Function} [resolver] The function to resolve the cache key. + * @returns {Function} Returns the new memoized function. + * @example + * + * var object = { 'a': 1, 'b': 2 }; + * var other = { 'c': 3, 'd': 4 }; + * + * var values = _.memoize(_.values); + * values(object); + * // => [1, 2] + * + * values(other); + * // => [3, 4] + * + * object.a = 2; + * values(object); + * // => [1, 2] + * + * // Modify the result cache. + * values.cache.set(object, ['a', 'b']); + * values(object); + * // => ['a', 'b'] + * + * // Replace `_.memoize.Cache`. + * _.memoize.Cache = WeakMap; + */ + function memoize(func, resolver) { + if (typeof func != 'function' || (resolver != null && typeof resolver != 'function')) { + throw new TypeError(FUNC_ERROR_TEXT); + } + var memoized = function() { + var args = arguments, + key = resolver ? resolver.apply(this, args) : args[0], + cache = memoized.cache; + + if (cache.has(key)) { + return cache.get(key); + } + var result = func.apply(this, args); + memoized.cache = cache.set(key, result) || cache; + return result; + }; + memoized.cache = new (memoize.Cache || MapCache); + return memoized; + } + + // Expose `MapCache`. + memoize.Cache = MapCache; + + module.exports = memoize; + + +/***/ }), +/* 219 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseToString = __webpack_require__(220); + + /** + * Converts `value` to a string. An empty string is returned for `null` + * and `undefined` values. The sign of `-0` is preserved. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to convert. + * @returns {string} Returns the converted string. + * @example + * + * _.toString(null); + * // => '' + * + * _.toString(-0); + * // => '-0' + * + * _.toString([1, 2, 3]); + * // => '1,2,3' + */ + function toString(value) { + return value == null ? '' : baseToString(value); + } + + module.exports = toString; + + +/***/ }), +/* 220 */ +/***/ (function(module, exports, __webpack_require__) { + + var Symbol = __webpack_require__(92), + arrayMap = __webpack_require__(154), + isArray = __webpack_require__(112), + isSymbol = __webpack_require__(103); + + /** Used as references for various `Number` constants. */ + var INFINITY = 1 / 0; + + /** Used to convert symbols to primitives and strings. */ + var symbolProto = Symbol ? Symbol.prototype : undefined, + symbolToString = symbolProto ? symbolProto.toString : undefined; + + /** + * The base implementation of `_.toString` which doesn't convert nullish + * values to empty strings. + * + * @private + * @param {*} value The value to process. + * @returns {string} Returns the string. + */ + function baseToString(value) { + // Exit early for strings to avoid a performance hit in some environments. + if (typeof value == 'string') { + return value; + } + if (isArray(value)) { + // Recursively convert values (susceptible to call stack limits). + return arrayMap(value, baseToString) + ''; + } + if (isSymbol(value)) { + return symbolToString ? symbolToString.call(value) : ''; + } + var result = (value + ''); + return (result == '0' && (1 / value) == -INFINITY) ? '-0' : result; + } + + module.exports = baseToString; + + +/***/ }), +/* 221 */ +/***/ (function(module, exports, __webpack_require__) { + + var isSymbol = __webpack_require__(103); + + /** Used as references for various `Number` constants. */ + var INFINITY = 1 / 0; + + /** + * Converts `value` to a string key if it's not a string or symbol. + * + * @private + * @param {*} value The value to inspect. + * @returns {string|symbol} Returns the key. + */ + function toKey(value) { + if (typeof value == 'string' || isSymbol(value)) { + return value; + } + var result = (value + ''); + return (result == '0' && (1 / value) == -INFINITY) ? '-0' : result; + } + + module.exports = toKey; + + +/***/ }), +/* 222 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseHasIn = __webpack_require__(223), + hasPath = __webpack_require__(224); + + /** + * Checks if `path` is a direct or inherited property of `object`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Object + * @param {Object} object The object to query. + * @param {Array|string} path The path to check. + * @returns {boolean} Returns `true` if `path` exists, else `false`. + * @example + * + * var object = _.create({ 'a': _.create({ 'b': 2 }) }); + * + * _.hasIn(object, 'a'); + * // => true + * + * _.hasIn(object, 'a.b'); + * // => true + * + * _.hasIn(object, ['a', 'b']); + * // => true + * + * _.hasIn(object, 'b'); + * // => false + */ + function hasIn(object, path) { + return object != null && hasPath(object, path, baseHasIn); + } + + module.exports = hasIn; + + +/***/ }), +/* 223 */ +/***/ (function(module, exports) { + + /** + * The base implementation of `_.hasIn` without support for deep paths. + * + * @private + * @param {Object} [object] The object to query. + * @param {Array|string} key The key to check. + * @returns {boolean} Returns `true` if `key` exists, else `false`. + */ + function baseHasIn(object, key) { + return object != null && key in Object(object); + } + + module.exports = baseHasIn; + + +/***/ }), +/* 224 */ +/***/ (function(module, exports, __webpack_require__) { + + var castPath = __webpack_require__(214), + isArguments = __webpack_require__(110), + isArray = __webpack_require__(112), + isIndex = __webpack_require__(99), + isLength = __webpack_require__(98), + toKey = __webpack_require__(221); + + /** + * Checks if `path` exists on `object`. + * + * @private + * @param {Object} object The object to query. + * @param {Array|string} path The path to check. + * @param {Function} hasFunc The function to check properties. + * @returns {boolean} Returns `true` if `path` exists, else `false`. + */ + function hasPath(object, path, hasFunc) { + path = castPath(path, object); + + var index = -1, + length = path.length, + result = false; + + while (++index < length) { + var key = toKey(path[index]); + if (!(result = object != null && hasFunc(object, key))) { + break; + } + object = object[key]; + } + if (result || ++index != length) { + return result; + } + length = object == null ? 0 : object.length; + return !!length && isLength(length) && isIndex(key, length) && + (isArray(object) || isArguments(object)); + } + + module.exports = hasPath; + + +/***/ }), +/* 225 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseProperty = __webpack_require__(226), + basePropertyDeep = __webpack_require__(227), + isKey = __webpack_require__(215), + toKey = __webpack_require__(221); + + /** + * Creates a function that returns the value at `path` of a given object. + * + * @static + * @memberOf _ + * @since 2.4.0 + * @category Util + * @param {Array|string} path The path of the property to get. + * @returns {Function} Returns the new accessor function. + * @example + * + * var objects = [ + * { 'a': { 'b': 2 } }, + * { 'a': { 'b': 1 } } + * ]; + * + * _.map(objects, _.property('a.b')); + * // => [2, 1] + * + * _.map(_.sortBy(objects, _.property(['a', 'b'])), 'a.b'); + * // => [1, 2] + */ + function property(path) { + return isKey(path) ? baseProperty(toKey(path)) : basePropertyDeep(path); + } + + module.exports = property; + + +/***/ }), +/* 226 */ +/***/ (function(module, exports) { + + /** + * The base implementation of `_.property` without support for deep paths. + * + * @private + * @param {string} key The key of the property to get. + * @returns {Function} Returns the new accessor function. + */ + function baseProperty(key) { + return function(object) { + return object == null ? undefined : object[key]; + }; + } + + module.exports = baseProperty; + + +/***/ }), +/* 227 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseGet = __webpack_require__(213); + + /** + * A specialized version of `baseProperty` which supports deep paths. + * + * @private + * @param {Array|string} path The path of the property to get. + * @returns {Function} Returns the new accessor function. + */ + function basePropertyDeep(path) { + return function(object) { + return baseGet(object, path); + }; + } + + module.exports = basePropertyDeep; + + +/***/ }), +/* 228 */ +/***/ (function(module, exports) { + + /** + * Gets the last element of `array`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to query. + * @returns {*} Returns the last element of `array`. + * @example + * + * _.last([1, 2, 3]); + * // => 3 + */ + function last(array) { + var length = array == null ? 0 : array.length; + return length ? array[length - 1] : undefined; + } + + module.exports = last; + + +/***/ }), +/* 229 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseDifference = __webpack_require__(115), + baseFlatten = __webpack_require__(108), + baseRest = __webpack_require__(157), + isArrayLikeObject = __webpack_require__(166), + last = __webpack_require__(228); + + /** + * This method is like `_.difference` except that it accepts `comparator` + * which is invoked to compare elements of `array` to `values`. The order and + * references of result values are determined by the first array. The comparator + * is invoked with two arguments: (arrVal, othVal). + * + * **Note:** Unlike `_.pullAllWith`, this method returns a new array. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {...Array} [values] The values to exclude. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new array of filtered values. + * @example + * + * var objects = [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }]; + * + * _.differenceWith(objects, [{ 'x': 1, 'y': 2 }], _.isEqual); + * // => [{ 'x': 2, 'y': 1 }] + */ + var differenceWith = baseRest(function(array, values) { + var comparator = last(values); + if (isArrayLikeObject(comparator)) { + comparator = undefined; + } + return isArrayLikeObject(array) + ? baseDifference(array, baseFlatten(values, 1, isArrayLikeObject, true), undefined, comparator) + : []; + }); + + module.exports = differenceWith; + + +/***/ }), +/* 230 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86), + toInteger = __webpack_require__(100); + + /** + * Creates a slice of `array` with `n` elements dropped from the beginning. + * + * @static + * @memberOf _ + * @since 0.5.0 + * @category Array + * @param {Array} array The array to query. + * @param {number} [n=1] The number of elements to drop. + * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. + * @returns {Array} Returns the slice of `array`. + * @example + * + * _.drop([1, 2, 3]); + * // => [2, 3] + * + * _.drop([1, 2, 3], 2); + * // => [3] + * + * _.drop([1, 2, 3], 5); + * // => [] + * + * _.drop([1, 2, 3], 0); + * // => [1, 2, 3] + */ + function drop(array, n, guard) { + var length = array == null ? 0 : array.length; + if (!length) { + return []; + } + n = (guard || n === undefined) ? 1 : toInteger(n); + return baseSlice(array, n < 0 ? 0 : n, length); + } + + module.exports = drop; + + +/***/ }), +/* 231 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86), + toInteger = __webpack_require__(100); + + /** + * Creates a slice of `array` with `n` elements dropped from the end. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to query. + * @param {number} [n=1] The number of elements to drop. + * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. + * @returns {Array} Returns the slice of `array`. + * @example + * + * _.dropRight([1, 2, 3]); + * // => [1, 2] + * + * _.dropRight([1, 2, 3], 2); + * // => [1] + * + * _.dropRight([1, 2, 3], 5); + * // => [] + * + * _.dropRight([1, 2, 3], 0); + * // => [1, 2, 3] + */ + function dropRight(array, n, guard) { + var length = array == null ? 0 : array.length; + if (!length) { + return []; + } + n = (guard || n === undefined) ? 1 : toInteger(n); + n = length - n; + return baseSlice(array, 0, n < 0 ? 0 : n); + } + + module.exports = dropRight; + + +/***/ }), +/* 232 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + baseWhile = __webpack_require__(233); + + /** + * Creates a slice of `array` excluding elements dropped from the end. + * Elements are dropped until `predicate` returns falsey. The predicate is + * invoked with three arguments: (value, index, array). + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to query. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @returns {Array} Returns the slice of `array`. + * @example + * + * var users = [ + * { 'user': 'barney', 'active': true }, + * { 'user': 'fred', 'active': false }, + * { 'user': 'pebbles', 'active': false } + * ]; + * + * _.dropRightWhile(users, function(o) { return !o.active; }); + * // => objects for ['barney'] + * + * // The `_.matches` iteratee shorthand. + * _.dropRightWhile(users, { 'user': 'pebbles', 'active': false }); + * // => objects for ['barney', 'fred'] + * + * // The `_.matchesProperty` iteratee shorthand. + * _.dropRightWhile(users, ['active', false]); + * // => objects for ['barney'] + * + * // The `_.property` iteratee shorthand. + * _.dropRightWhile(users, 'active'); + * // => objects for ['barney', 'fred', 'pebbles'] + */ + function dropRightWhile(array, predicate) { + return (array && array.length) + ? baseWhile(array, baseIteratee(predicate, 3), true, true) + : []; + } + + module.exports = dropRightWhile; + + +/***/ }), +/* 233 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86); + + /** + * The base implementation of methods like `_.dropWhile` and `_.takeWhile` + * without support for iteratee shorthands. + * + * @private + * @param {Array} array The array to query. + * @param {Function} predicate The function invoked per iteration. + * @param {boolean} [isDrop] Specify dropping elements instead of taking them. + * @param {boolean} [fromRight] Specify iterating from right to left. + * @returns {Array} Returns the slice of `array`. + */ + function baseWhile(array, predicate, isDrop, fromRight) { + var length = array.length, + index = fromRight ? length : -1; + + while ((fromRight ? index-- : ++index < length) && + predicate(array[index], index, array)) {} + + return isDrop + ? baseSlice(array, (fromRight ? 0 : index), (fromRight ? index + 1 : length)) + : baseSlice(array, (fromRight ? index + 1 : 0), (fromRight ? length : index)); + } + + module.exports = baseWhile; + + +/***/ }), +/* 234 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + baseWhile = __webpack_require__(233); + + /** + * Creates a slice of `array` excluding elements dropped from the beginning. + * Elements are dropped until `predicate` returns falsey. The predicate is + * invoked with three arguments: (value, index, array). + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to query. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @returns {Array} Returns the slice of `array`. + * @example + * + * var users = [ + * { 'user': 'barney', 'active': false }, + * { 'user': 'fred', 'active': false }, + * { 'user': 'pebbles', 'active': true } + * ]; + * + * _.dropWhile(users, function(o) { return !o.active; }); + * // => objects for ['pebbles'] + * + * // The `_.matches` iteratee shorthand. + * _.dropWhile(users, { 'user': 'barney', 'active': false }); + * // => objects for ['fred', 'pebbles'] + * + * // The `_.matchesProperty` iteratee shorthand. + * _.dropWhile(users, ['active', false]); + * // => objects for ['pebbles'] + * + * // The `_.property` iteratee shorthand. + * _.dropWhile(users, 'active'); + * // => objects for ['barney', 'fred', 'pebbles'] + */ + function dropWhile(array, predicate) { + return (array && array.length) + ? baseWhile(array, baseIteratee(predicate, 3), true) + : []; + } + + module.exports = dropWhile; + + +/***/ }), +/* 235 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFill = __webpack_require__(236), + isIterateeCall = __webpack_require__(87); + + /** + * Fills elements of `array` with `value` from `start` up to, but not + * including, `end`. + * + * **Note:** This method mutates `array`. + * + * @static + * @memberOf _ + * @since 3.2.0 + * @category Array + * @param {Array} array The array to fill. + * @param {*} value The value to fill `array` with. + * @param {number} [start=0] The start position. + * @param {number} [end=array.length] The end position. + * @returns {Array} Returns `array`. + * @example + * + * var array = [1, 2, 3]; + * + * _.fill(array, 'a'); + * console.log(array); + * // => ['a', 'a', 'a'] + * + * _.fill(Array(3), 2); + * // => [2, 2, 2] + * + * _.fill([4, 6, 8, 10], '*', 1, 3); + * // => [4, '*', '*', 10] + */ + function fill(array, value, start, end) { + var length = array == null ? 0 : array.length; + if (!length) { + return []; + } + if (start && typeof start != 'number' && isIterateeCall(array, value, start)) { + start = 0; + end = length; + } + return baseFill(array, value, start, end); + } + + module.exports = fill; + + +/***/ }), +/* 236 */ +/***/ (function(module, exports, __webpack_require__) { + + var toInteger = __webpack_require__(100), + toLength = __webpack_require__(237); + + /** + * The base implementation of `_.fill` without an iteratee call guard. + * + * @private + * @param {Array} array The array to fill. + * @param {*} value The value to fill `array` with. + * @param {number} [start=0] The start position. + * @param {number} [end=array.length] The end position. + * @returns {Array} Returns `array`. + */ + function baseFill(array, value, start, end) { + var length = array.length; + + start = toInteger(start); + if (start < 0) { + start = -start > length ? 0 : (length + start); + } + end = (end === undefined || end > length) ? length : toInteger(end); + if (end < 0) { + end += length; + } + end = start > end ? 0 : toLength(end); + while (start < end) { + array[start++] = value; + } + return array; + } + + module.exports = baseFill; + + +/***/ }), +/* 237 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseClamp = __webpack_require__(238), + toInteger = __webpack_require__(100); + + /** Used as references for the maximum length and index of an array. */ + var MAX_ARRAY_LENGTH = 4294967295; + + /** + * Converts `value` to an integer suitable for use as the length of an + * array-like object. + * + * **Note:** This method is based on + * [`ToLength`](http://ecma-international.org/ecma-262/7.0/#sec-tolength). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to convert. + * @returns {number} Returns the converted integer. + * @example + * + * _.toLength(3.2); + * // => 3 + * + * _.toLength(Number.MIN_VALUE); + * // => 0 + * + * _.toLength(Infinity); + * // => 4294967295 + * + * _.toLength('3.2'); + * // => 3 + */ + function toLength(value) { + return value ? baseClamp(toInteger(value), 0, MAX_ARRAY_LENGTH) : 0; + } + + module.exports = toLength; + + +/***/ }), +/* 238 */ +/***/ (function(module, exports) { + + /** + * The base implementation of `_.clamp` which doesn't coerce arguments. + * + * @private + * @param {number} number The number to clamp. + * @param {number} [lower] The lower bound. + * @param {number} upper The upper bound. + * @returns {number} Returns the clamped number. + */ + function baseClamp(number, lower, upper) { + if (number === number) { + if (upper !== undefined) { + number = number <= upper ? number : upper; + } + if (lower !== undefined) { + number = number >= lower ? number : lower; + } + } + return number; + } + + module.exports = baseClamp; + + +/***/ }), +/* 239 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFindIndex = __webpack_require__(150), + baseIteratee = __webpack_require__(168), + toInteger = __webpack_require__(100); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeMax = Math.max; + + /** + * This method is like `_.find` except that it returns the index of the first + * element `predicate` returns truthy for instead of the element itself. + * + * @static + * @memberOf _ + * @since 1.1.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @param {number} [fromIndex=0] The index to search from. + * @returns {number} Returns the index of the found element, else `-1`. + * @example + * + * var users = [ + * { 'user': 'barney', 'active': false }, + * { 'user': 'fred', 'active': false }, + * { 'user': 'pebbles', 'active': true } + * ]; + * + * _.findIndex(users, function(o) { return o.user == 'barney'; }); + * // => 0 + * + * // The `_.matches` iteratee shorthand. + * _.findIndex(users, { 'user': 'fred', 'active': false }); + * // => 1 + * + * // The `_.matchesProperty` iteratee shorthand. + * _.findIndex(users, ['active', false]); + * // => 0 + * + * // The `_.property` iteratee shorthand. + * _.findIndex(users, 'active'); + * // => 2 + */ + function findIndex(array, predicate, fromIndex) { + var length = array == null ? 0 : array.length; + if (!length) { + return -1; + } + var index = fromIndex == null ? 0 : toInteger(fromIndex); + if (index < 0) { + index = nativeMax(length + index, 0); + } + return baseFindIndex(array, baseIteratee(predicate, 3), index); + } + + module.exports = findIndex; + + +/***/ }), +/* 240 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFindIndex = __webpack_require__(150), + baseIteratee = __webpack_require__(168), + toInteger = __webpack_require__(100); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeMax = Math.max, + nativeMin = Math.min; + + /** + * This method is like `_.findIndex` except that it iterates over elements + * of `collection` from right to left. + * + * @static + * @memberOf _ + * @since 2.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @param {number} [fromIndex=array.length-1] The index to search from. + * @returns {number} Returns the index of the found element, else `-1`. + * @example + * + * var users = [ + * { 'user': 'barney', 'active': true }, + * { 'user': 'fred', 'active': false }, + * { 'user': 'pebbles', 'active': false } + * ]; + * + * _.findLastIndex(users, function(o) { return o.user == 'pebbles'; }); + * // => 2 + * + * // The `_.matches` iteratee shorthand. + * _.findLastIndex(users, { 'user': 'barney', 'active': true }); + * // => 0 + * + * // The `_.matchesProperty` iteratee shorthand. + * _.findLastIndex(users, ['active', false]); + * // => 2 + * + * // The `_.property` iteratee shorthand. + * _.findLastIndex(users, 'active'); + * // => 0 + */ + function findLastIndex(array, predicate, fromIndex) { + var length = array == null ? 0 : array.length; + if (!length) { + return -1; + } + var index = length - 1; + if (fromIndex !== undefined) { + index = toInteger(fromIndex); + index = fromIndex < 0 + ? nativeMax(length + index, 0) + : nativeMin(index, length - 1); + } + return baseFindIndex(array, baseIteratee(predicate, 3), index, true); + } + + module.exports = findLastIndex; + + +/***/ }), +/* 241 */ +/***/ (function(module, exports, __webpack_require__) { + + module.exports = __webpack_require__(242); + + +/***/ }), +/* 242 */ +/***/ (function(module, exports) { + + /** + * Gets the first element of `array`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @alias first + * @category Array + * @param {Array} array The array to query. + * @returns {*} Returns the first element of `array`. + * @example + * + * _.head([1, 2, 3]); + * // => 1 + * + * _.head([]); + * // => undefined + */ + function head(array) { + return (array && array.length) ? array[0] : undefined; + } + + module.exports = head; + + +/***/ }), +/* 243 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFlatten = __webpack_require__(108); + + /** + * Flattens `array` a single level deep. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to flatten. + * @returns {Array} Returns the new flattened array. + * @example + * + * _.flatten([1, [2, [3, [4]], 5]]); + * // => [1, 2, [3, [4]], 5] + */ + function flatten(array) { + var length = array == null ? 0 : array.length; + return length ? baseFlatten(array, 1) : []; + } + + module.exports = flatten; + + +/***/ }), +/* 244 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFlatten = __webpack_require__(108); + + /** Used as references for various `Number` constants. */ + var INFINITY = 1 / 0; + + /** + * Recursively flattens `array`. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to flatten. + * @returns {Array} Returns the new flattened array. + * @example + * + * _.flattenDeep([1, [2, [3, [4]], 5]]); + * // => [1, 2, 3, 4, 5] + */ + function flattenDeep(array) { + var length = array == null ? 0 : array.length; + return length ? baseFlatten(array, INFINITY) : []; + } + + module.exports = flattenDeep; + + +/***/ }), +/* 245 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFlatten = __webpack_require__(108), + toInteger = __webpack_require__(100); + + /** + * Recursively flatten `array` up to `depth` times. + * + * @static + * @memberOf _ + * @since 4.4.0 + * @category Array + * @param {Array} array The array to flatten. + * @param {number} [depth=1] The maximum recursion depth. + * @returns {Array} Returns the new flattened array. + * @example + * + * var array = [1, [2, [3, [4]], 5]]; + * + * _.flattenDepth(array, 1); + * // => [1, 2, [3, [4]], 5] + * + * _.flattenDepth(array, 2); + * // => [1, 2, 3, [4], 5] + */ + function flattenDepth(array, depth) { + var length = array == null ? 0 : array.length; + if (!length) { + return []; + } + depth = depth === undefined ? 1 : toInteger(depth); + return baseFlatten(array, depth); + } + + module.exports = flattenDepth; + + +/***/ }), +/* 246 */ +/***/ (function(module, exports) { + + /** + * The inverse of `_.toPairs`; this method returns an object composed + * from key-value `pairs`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} pairs The key-value pairs. + * @returns {Object} Returns the new object. + * @example + * + * _.fromPairs([['a', 1], ['b', 2]]); + * // => { 'a': 1, 'b': 2 } + */ + function fromPairs(pairs) { + var index = -1, + length = pairs == null ? 0 : pairs.length, + result = {}; + + while (++index < length) { + var pair = pairs[index]; + result[pair[0]] = pair[1]; + } + return result; + } + + module.exports = fromPairs; + + +/***/ }), +/* 247 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIndexOf = __webpack_require__(149), + toInteger = __webpack_require__(100); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeMax = Math.max; + + /** + * Gets the index at which the first occurrence of `value` is found in `array` + * using [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. If `fromIndex` is negative, it's used as the + * offset from the end of `array`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @param {number} [fromIndex=0] The index to search from. + * @returns {number} Returns the index of the matched value, else `-1`. + * @example + * + * _.indexOf([1, 2, 1, 2], 2); + * // => 1 + * + * // Search from the `fromIndex`. + * _.indexOf([1, 2, 1, 2], 2, 2); + * // => 3 + */ + function indexOf(array, value, fromIndex) { + var length = array == null ? 0 : array.length; + if (!length) { + return -1; + } + var index = fromIndex == null ? 0 : toInteger(fromIndex); + if (index < 0) { + index = nativeMax(length + index, 0); + } + return baseIndexOf(array, value, index); + } + + module.exports = indexOf; + + +/***/ }), +/* 248 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86); + + /** + * Gets all but the last element of `array`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to query. + * @returns {Array} Returns the slice of `array`. + * @example + * + * _.initial([1, 2, 3]); + * // => [1, 2] + */ + function initial(array) { + var length = array == null ? 0 : array.length; + return length ? baseSlice(array, 0, -1) : []; + } + + module.exports = initial; + + +/***/ }), +/* 249 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayMap = __webpack_require__(154), + baseIntersection = __webpack_require__(250), + baseRest = __webpack_require__(157), + castArrayLikeObject = __webpack_require__(251); + + /** + * Creates an array of unique values that are included in all given arrays + * using [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. The order and references of result values are + * determined by the first array. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @returns {Array} Returns the new array of intersecting values. + * @example + * + * _.intersection([2, 1], [2, 3]); + * // => [2] + */ + var intersection = baseRest(function(arrays) { + var mapped = arrayMap(arrays, castArrayLikeObject); + return (mapped.length && mapped[0] === arrays[0]) + ? baseIntersection(mapped) + : []; + }); + + module.exports = intersection; + + +/***/ }), +/* 250 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetCache = __webpack_require__(116), + arrayIncludes = __webpack_require__(148), + arrayIncludesWith = __webpack_require__(153), + arrayMap = __webpack_require__(154), + baseUnary = __webpack_require__(155), + cacheHas = __webpack_require__(156); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeMin = Math.min; + + /** + * The base implementation of methods like `_.intersection`, without support + * for iteratee shorthands, that accepts an array of arrays to inspect. + * + * @private + * @param {Array} arrays The arrays to inspect. + * @param {Function} [iteratee] The iteratee invoked per element. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new array of shared values. + */ + function baseIntersection(arrays, iteratee, comparator) { + var includes = comparator ? arrayIncludesWith : arrayIncludes, + length = arrays[0].length, + othLength = arrays.length, + othIndex = othLength, + caches = Array(othLength), + maxLength = Infinity, + result = []; + + while (othIndex--) { + var array = arrays[othIndex]; + if (othIndex && iteratee) { + array = arrayMap(array, baseUnary(iteratee)); + } + maxLength = nativeMin(array.length, maxLength); + caches[othIndex] = !comparator && (iteratee || (length >= 120 && array.length >= 120)) + ? new SetCache(othIndex && array) + : undefined; + } + array = arrays[0]; + + var index = -1, + seen = caches[0]; + + outer: + while (++index < length && result.length < maxLength) { + var value = array[index], + computed = iteratee ? iteratee(value) : value; + + value = (comparator || value !== 0) ? value : 0; + if (!(seen + ? cacheHas(seen, computed) + : includes(result, computed, comparator) + )) { + othIndex = othLength; + while (--othIndex) { + var cache = caches[othIndex]; + if (!(cache + ? cacheHas(cache, computed) + : includes(arrays[othIndex], computed, comparator)) + ) { + continue outer; + } + } + if (seen) { + seen.push(computed); + } + result.push(value); + } + } + return result; + } + + module.exports = baseIntersection; + + +/***/ }), +/* 251 */ +/***/ (function(module, exports, __webpack_require__) { + + var isArrayLikeObject = __webpack_require__(166); + + /** + * Casts `value` to an empty array if it's not an array like object. + * + * @private + * @param {*} value The value to inspect. + * @returns {Array|Object} Returns the cast array-like object. + */ + function castArrayLikeObject(value) { + return isArrayLikeObject(value) ? value : []; + } + + module.exports = castArrayLikeObject; + + +/***/ }), +/* 252 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayMap = __webpack_require__(154), + baseIntersection = __webpack_require__(250), + baseIteratee = __webpack_require__(168), + baseRest = __webpack_require__(157), + castArrayLikeObject = __webpack_require__(251), + last = __webpack_require__(228); + + /** + * This method is like `_.intersection` except that it accepts `iteratee` + * which is invoked for each element of each `arrays` to generate the criterion + * by which they're compared. The order and references of result values are + * determined by the first array. The iteratee is invoked with one argument: + * (value). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @param {Function} [iteratee=_.identity] The iteratee invoked per element. + * @returns {Array} Returns the new array of intersecting values. + * @example + * + * _.intersectionBy([2.1, 1.2], [2.3, 3.4], Math.floor); + * // => [2.1] + * + * // The `_.property` iteratee shorthand. + * _.intersectionBy([{ 'x': 1 }], [{ 'x': 2 }, { 'x': 1 }], 'x'); + * // => [{ 'x': 1 }] + */ + var intersectionBy = baseRest(function(arrays) { + var iteratee = last(arrays), + mapped = arrayMap(arrays, castArrayLikeObject); + + if (iteratee === last(mapped)) { + iteratee = undefined; + } else { + mapped.pop(); + } + return (mapped.length && mapped[0] === arrays[0]) + ? baseIntersection(mapped, baseIteratee(iteratee, 2)) + : []; + }); + + module.exports = intersectionBy; + + +/***/ }), +/* 253 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayMap = __webpack_require__(154), + baseIntersection = __webpack_require__(250), + baseRest = __webpack_require__(157), + castArrayLikeObject = __webpack_require__(251), + last = __webpack_require__(228); + + /** + * This method is like `_.intersection` except that it accepts `comparator` + * which is invoked to compare elements of `arrays`. The order and references + * of result values are determined by the first array. The comparator is + * invoked with two arguments: (arrVal, othVal). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new array of intersecting values. + * @example + * + * var objects = [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }]; + * var others = [{ 'x': 1, 'y': 1 }, { 'x': 1, 'y': 2 }]; + * + * _.intersectionWith(objects, others, _.isEqual); + * // => [{ 'x': 1, 'y': 2 }] + */ + var intersectionWith = baseRest(function(arrays) { + var comparator = last(arrays), + mapped = arrayMap(arrays, castArrayLikeObject); + + comparator = typeof comparator == 'function' ? comparator : undefined; + if (comparator) { + mapped.pop(); + } + return (mapped.length && mapped[0] === arrays[0]) + ? baseIntersection(mapped, undefined, comparator) + : []; + }); + + module.exports = intersectionWith; + + +/***/ }), +/* 254 */ +/***/ (function(module, exports) { + + /** Used for built-in method references. */ + var arrayProto = Array.prototype; + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeJoin = arrayProto.join; + + /** + * Converts all elements in `array` into a string separated by `separator`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to convert. + * @param {string} [separator=','] The element separator. + * @returns {string} Returns the joined string. + * @example + * + * _.join(['a', 'b', 'c'], '~'); + * // => 'a~b~c' + */ + function join(array, separator) { + return array == null ? '' : nativeJoin.call(array, separator); + } + + module.exports = join; + + +/***/ }), +/* 255 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFindIndex = __webpack_require__(150), + baseIsNaN = __webpack_require__(151), + strictLastIndexOf = __webpack_require__(256), + toInteger = __webpack_require__(100); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeMax = Math.max, + nativeMin = Math.min; + + /** + * This method is like `_.indexOf` except that it iterates over elements of + * `array` from right to left. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @param {number} [fromIndex=array.length-1] The index to search from. + * @returns {number} Returns the index of the matched value, else `-1`. + * @example + * + * _.lastIndexOf([1, 2, 1, 2], 2); + * // => 3 + * + * // Search from the `fromIndex`. + * _.lastIndexOf([1, 2, 1, 2], 2, 2); + * // => 1 + */ + function lastIndexOf(array, value, fromIndex) { + var length = array == null ? 0 : array.length; + if (!length) { + return -1; + } + var index = length; + if (fromIndex !== undefined) { + index = toInteger(fromIndex); + index = index < 0 ? nativeMax(length + index, 0) : nativeMin(index, length - 1); + } + return value === value + ? strictLastIndexOf(array, value, index) + : baseFindIndex(array, baseIsNaN, index, true); + } + + module.exports = lastIndexOf; + + +/***/ }), +/* 256 */ +/***/ (function(module, exports) { + + /** + * A specialized version of `_.lastIndexOf` which performs strict equality + * comparisons of values, i.e. `===`. + * + * @private + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @param {number} fromIndex The index to search from. + * @returns {number} Returns the index of the matched value, else `-1`. + */ + function strictLastIndexOf(array, value, fromIndex) { + var index = fromIndex + 1; + while (index--) { + if (array[index] === value) { + return index; + } + } + return index; + } + + module.exports = strictLastIndexOf; + + +/***/ }), +/* 257 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseNth = __webpack_require__(258), + toInteger = __webpack_require__(100); + + /** + * Gets the element at index `n` of `array`. If `n` is negative, the nth + * element from the end is returned. + * + * @static + * @memberOf _ + * @since 4.11.0 + * @category Array + * @param {Array} array The array to query. + * @param {number} [n=0] The index of the element to return. + * @returns {*} Returns the nth element of `array`. + * @example + * + * var array = ['a', 'b', 'c', 'd']; + * + * _.nth(array, 1); + * // => 'b' + * + * _.nth(array, -2); + * // => 'c'; + */ + function nth(array, n) { + return (array && array.length) ? baseNth(array, toInteger(n)) : undefined; + } + + module.exports = nth; + + +/***/ }), +/* 258 */ +/***/ (function(module, exports, __webpack_require__) { + + var isIndex = __webpack_require__(99); + + /** + * The base implementation of `_.nth` which doesn't coerce arguments. + * + * @private + * @param {Array} array The array to query. + * @param {number} n The index of the element to return. + * @returns {*} Returns the nth element of `array`. + */ + function baseNth(array, n) { + var length = array.length; + if (!length) { + return; + } + n += n < 0 ? length : 0; + return isIndex(n, length) ? array[n] : undefined; + } + + module.exports = baseNth; + + +/***/ }), +/* 259 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseRest = __webpack_require__(157), + pullAll = __webpack_require__(260); + + /** + * Removes all given values from `array` using + * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. + * + * **Note:** Unlike `_.without`, this method mutates `array`. Use `_.remove` + * to remove elements from an array by predicate. + * + * @static + * @memberOf _ + * @since 2.0.0 + * @category Array + * @param {Array} array The array to modify. + * @param {...*} [values] The values to remove. + * @returns {Array} Returns `array`. + * @example + * + * var array = ['a', 'b', 'c', 'a', 'b', 'c']; + * + * _.pull(array, 'a', 'c'); + * console.log(array); + * // => ['b', 'b'] + */ + var pull = baseRest(pullAll); + + module.exports = pull; + + +/***/ }), +/* 260 */ +/***/ (function(module, exports, __webpack_require__) { + + var basePullAll = __webpack_require__(261); + + /** + * This method is like `_.pull` except that it accepts an array of values to remove. + * + * **Note:** Unlike `_.difference`, this method mutates `array`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to modify. + * @param {Array} values The values to remove. + * @returns {Array} Returns `array`. + * @example + * + * var array = ['a', 'b', 'c', 'a', 'b', 'c']; + * + * _.pullAll(array, ['a', 'c']); + * console.log(array); + * // => ['b', 'b'] + */ + function pullAll(array, values) { + return (array && array.length && values && values.length) + ? basePullAll(array, values) + : array; + } + + module.exports = pullAll; + + +/***/ }), +/* 261 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayMap = __webpack_require__(154), + baseIndexOf = __webpack_require__(149), + baseIndexOfWith = __webpack_require__(262), + baseUnary = __webpack_require__(155), + copyArray = __webpack_require__(113); + + /** Used for built-in method references. */ + var arrayProto = Array.prototype; + + /** Built-in value references. */ + var splice = arrayProto.splice; + + /** + * The base implementation of `_.pullAllBy` without support for iteratee + * shorthands. + * + * @private + * @param {Array} array The array to modify. + * @param {Array} values The values to remove. + * @param {Function} [iteratee] The iteratee invoked per element. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns `array`. + */ + function basePullAll(array, values, iteratee, comparator) { + var indexOf = comparator ? baseIndexOfWith : baseIndexOf, + index = -1, + length = values.length, + seen = array; + + if (array === values) { + values = copyArray(values); + } + if (iteratee) { + seen = arrayMap(array, baseUnary(iteratee)); + } + while (++index < length) { + var fromIndex = 0, + value = values[index], + computed = iteratee ? iteratee(value) : value; + + while ((fromIndex = indexOf(seen, computed, fromIndex, comparator)) > -1) { + if (seen !== array) { + splice.call(seen, fromIndex, 1); + } + splice.call(array, fromIndex, 1); + } + } + return array; + } + + module.exports = basePullAll; + + +/***/ }), +/* 262 */ +/***/ (function(module, exports) { + + /** + * This function is like `baseIndexOf` except that it accepts a comparator. + * + * @private + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @param {number} fromIndex The index to search from. + * @param {Function} comparator The comparator invoked per element. + * @returns {number} Returns the index of the matched value, else `-1`. + */ + function baseIndexOfWith(array, value, fromIndex, comparator) { + var index = fromIndex - 1, + length = array.length; + + while (++index < length) { + if (comparator(array[index], value)) { + return index; + } + } + return -1; + } + + module.exports = baseIndexOfWith; + + +/***/ }), +/* 263 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + basePullAll = __webpack_require__(261); + + /** + * This method is like `_.pullAll` except that it accepts `iteratee` which is + * invoked for each element of `array` and `values` to generate the criterion + * by which they're compared. The iteratee is invoked with one argument: (value). + * + * **Note:** Unlike `_.differenceBy`, this method mutates `array`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to modify. + * @param {Array} values The values to remove. + * @param {Function} [iteratee=_.identity] The iteratee invoked per element. + * @returns {Array} Returns `array`. + * @example + * + * var array = [{ 'x': 1 }, { 'x': 2 }, { 'x': 3 }, { 'x': 1 }]; + * + * _.pullAllBy(array, [{ 'x': 1 }, { 'x': 3 }], 'x'); + * console.log(array); + * // => [{ 'x': 2 }] + */ + function pullAllBy(array, values, iteratee) { + return (array && array.length && values && values.length) + ? basePullAll(array, values, baseIteratee(iteratee, 2)) + : array; + } + + module.exports = pullAllBy; + + +/***/ }), +/* 264 */ +/***/ (function(module, exports, __webpack_require__) { + + var basePullAll = __webpack_require__(261); + + /** + * This method is like `_.pullAll` except that it accepts `comparator` which + * is invoked to compare elements of `array` to `values`. The comparator is + * invoked with two arguments: (arrVal, othVal). + * + * **Note:** Unlike `_.differenceWith`, this method mutates `array`. + * + * @static + * @memberOf _ + * @since 4.6.0 + * @category Array + * @param {Array} array The array to modify. + * @param {Array} values The values to remove. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns `array`. + * @example + * + * var array = [{ 'x': 1, 'y': 2 }, { 'x': 3, 'y': 4 }, { 'x': 5, 'y': 6 }]; + * + * _.pullAllWith(array, [{ 'x': 3, 'y': 4 }], _.isEqual); + * console.log(array); + * // => [{ 'x': 1, 'y': 2 }, { 'x': 5, 'y': 6 }] + */ + function pullAllWith(array, values, comparator) { + return (array && array.length && values && values.length) + ? basePullAll(array, values, undefined, comparator) + : array; + } + + module.exports = pullAllWith; + + +/***/ }), +/* 265 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayMap = __webpack_require__(154), + baseAt = __webpack_require__(266), + basePullAt = __webpack_require__(267), + compareAscending = __webpack_require__(270), + flatRest = __webpack_require__(271), + isIndex = __webpack_require__(99); + + /** + * Removes elements from `array` corresponding to `indexes` and returns an + * array of removed elements. + * + * **Note:** Unlike `_.at`, this method mutates `array`. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to modify. + * @param {...(number|number[])} [indexes] The indexes of elements to remove. + * @returns {Array} Returns the new array of removed elements. + * @example + * + * var array = ['a', 'b', 'c', 'd']; + * var pulled = _.pullAt(array, [1, 3]); + * + * console.log(array); + * // => ['a', 'c'] + * + * console.log(pulled); + * // => ['b', 'd'] + */ + var pullAt = flatRest(function(array, indexes) { + var length = array == null ? 0 : array.length, + result = baseAt(array, indexes); + + basePullAt(array, arrayMap(indexes, function(index) { + return isIndex(index, length) ? +index : index; + }).sort(compareAscending)); + + return result; + }); + + module.exports = pullAt; + + +/***/ }), +/* 266 */ +/***/ (function(module, exports, __webpack_require__) { + + var get = __webpack_require__(212); + + /** + * The base implementation of `_.at` without support for individual paths. + * + * @private + * @param {Object} object The object to iterate over. + * @param {string[]} paths The property paths to pick. + * @returns {Array} Returns the picked elements. + */ + function baseAt(object, paths) { + var index = -1, + length = paths.length, + result = Array(length), + skip = object == null; + + while (++index < length) { + result[index] = skip ? undefined : get(object, paths[index]); + } + return result; + } + + module.exports = baseAt; + + +/***/ }), +/* 267 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseUnset = __webpack_require__(268), + isIndex = __webpack_require__(99); + + /** Used for built-in method references. */ + var arrayProto = Array.prototype; + + /** Built-in value references. */ + var splice = arrayProto.splice; + + /** + * The base implementation of `_.pullAt` without support for individual + * indexes or capturing the removed elements. + * + * @private + * @param {Array} array The array to modify. + * @param {number[]} indexes The indexes of elements to remove. + * @returns {Array} Returns `array`. + */ + function basePullAt(array, indexes) { + var length = array ? indexes.length : 0, + lastIndex = length - 1; + + while (length--) { + var index = indexes[length]; + if (length == lastIndex || index !== previous) { + var previous = index; + if (isIndex(index)) { + splice.call(array, index, 1); + } else { + baseUnset(array, index); + } + } + } + return array; + } + + module.exports = basePullAt; + + +/***/ }), +/* 268 */ +/***/ (function(module, exports, __webpack_require__) { + + var castPath = __webpack_require__(214), + last = __webpack_require__(228), + parent = __webpack_require__(269), + toKey = __webpack_require__(221); + + /** + * The base implementation of `_.unset`. + * + * @private + * @param {Object} object The object to modify. + * @param {Array|string} path The property path to unset. + * @returns {boolean} Returns `true` if the property is deleted, else `false`. + */ + function baseUnset(object, path) { + path = castPath(path, object); + object = parent(object, path); + return object == null || delete object[toKey(last(path))]; + } + + module.exports = baseUnset; + + +/***/ }), +/* 269 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseGet = __webpack_require__(213), + baseSlice = __webpack_require__(86); + + /** + * Gets the parent value at `path` of `object`. + * + * @private + * @param {Object} object The object to query. + * @param {Array} path The path to get the parent value of. + * @returns {*} Returns the parent value. + */ + function parent(object, path) { + return path.length < 2 ? object : baseGet(object, baseSlice(path, 0, -1)); + } + + module.exports = parent; + + +/***/ }), +/* 270 */ +/***/ (function(module, exports, __webpack_require__) { + + var isSymbol = __webpack_require__(103); + + /** + * Compares values to sort them in ascending order. + * + * @private + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @returns {number} Returns the sort order indicator for `value`. + */ + function compareAscending(value, other) { + if (value !== other) { + var valIsDefined = value !== undefined, + valIsNull = value === null, + valIsReflexive = value === value, + valIsSymbol = isSymbol(value); + + var othIsDefined = other !== undefined, + othIsNull = other === null, + othIsReflexive = other === other, + othIsSymbol = isSymbol(other); + + if ((!othIsNull && !othIsSymbol && !valIsSymbol && value > other) || + (valIsSymbol && othIsDefined && othIsReflexive && !othIsNull && !othIsSymbol) || + (valIsNull && othIsDefined && othIsReflexive) || + (!valIsDefined && othIsReflexive) || + !valIsReflexive) { + return 1; + } + if ((!valIsNull && !valIsSymbol && !othIsSymbol && value < other) || + (othIsSymbol && valIsDefined && valIsReflexive && !valIsNull && !valIsSymbol) || + (othIsNull && valIsDefined && valIsReflexive) || + (!othIsDefined && valIsReflexive) || + !othIsReflexive) { + return -1; + } + } + return 0; + } + + module.exports = compareAscending; + + +/***/ }), +/* 271 */ +/***/ (function(module, exports, __webpack_require__) { + + var flatten = __webpack_require__(243), + overRest = __webpack_require__(159), + setToString = __webpack_require__(161); + + /** + * A specialized version of `baseRest` which flattens the rest array. + * + * @private + * @param {Function} func The function to apply a rest parameter to. + * @returns {Function} Returns the new function. + */ + function flatRest(func) { + return setToString(overRest(func, undefined, flatten), func + ''); + } + + module.exports = flatRest; + + +/***/ }), +/* 272 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + basePullAt = __webpack_require__(267); + + /** + * Removes all elements from `array` that `predicate` returns truthy for + * and returns an array of the removed elements. The predicate is invoked + * with three arguments: (value, index, array). + * + * **Note:** Unlike `_.filter`, this method mutates `array`. Use `_.pull` + * to pull elements from an array by value. + * + * @static + * @memberOf _ + * @since 2.0.0 + * @category Array + * @param {Array} array The array to modify. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @returns {Array} Returns the new array of removed elements. + * @example + * + * var array = [1, 2, 3, 4]; + * var evens = _.remove(array, function(n) { + * return n % 2 == 0; + * }); + * + * console.log(array); + * // => [1, 3] + * + * console.log(evens); + * // => [2, 4] + */ + function remove(array, predicate) { + var result = []; + if (!(array && array.length)) { + return result; + } + var index = -1, + indexes = [], + length = array.length; + + predicate = baseIteratee(predicate, 3); + while (++index < length) { + var value = array[index]; + if (predicate(value, index, array)) { + result.push(value); + indexes.push(index); + } + } + basePullAt(array, indexes); + return result; + } + + module.exports = remove; + + +/***/ }), +/* 273 */ +/***/ (function(module, exports) { + + /** Used for built-in method references. */ + var arrayProto = Array.prototype; + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeReverse = arrayProto.reverse; + + /** + * Reverses `array` so that the first element becomes the last, the second + * element becomes the second to last, and so on. + * + * **Note:** This method mutates `array` and is based on + * [`Array#reverse`](https://mdn.io/Array/reverse). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to modify. + * @returns {Array} Returns `array`. + * @example + * + * var array = [1, 2, 3]; + * + * _.reverse(array); + * // => [3, 2, 1] + * + * console.log(array); + * // => [3, 2, 1] + */ + function reverse(array) { + return array == null ? array : nativeReverse.call(array); + } + + module.exports = reverse; + + +/***/ }), +/* 274 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86), + isIterateeCall = __webpack_require__(87), + toInteger = __webpack_require__(100); + + /** + * Creates a slice of `array` from `start` up to, but not including, `end`. + * + * **Note:** This method is used instead of + * [`Array#slice`](https://mdn.io/Array/slice) to ensure dense arrays are + * returned. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to slice. + * @param {number} [start=0] The start position. + * @param {number} [end=array.length] The end position. + * @returns {Array} Returns the slice of `array`. + */ + function slice(array, start, end) { + var length = array == null ? 0 : array.length; + if (!length) { + return []; + } + if (end && typeof end != 'number' && isIterateeCall(array, start, end)) { + start = 0; + end = length; + } + else { + start = start == null ? 0 : toInteger(start); + end = end === undefined ? length : toInteger(end); + } + return baseSlice(array, start, end); + } + + module.exports = slice; + + +/***/ }), +/* 275 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSortedIndex = __webpack_require__(276); + + /** + * Uses a binary search to determine the lowest index at which `value` + * should be inserted into `array` in order to maintain its sort order. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The sorted array to inspect. + * @param {*} value The value to evaluate. + * @returns {number} Returns the index at which `value` should be inserted + * into `array`. + * @example + * + * _.sortedIndex([30, 50], 40); + * // => 1 + */ + function sortedIndex(array, value) { + return baseSortedIndex(array, value); + } + + module.exports = sortedIndex; + + +/***/ }), +/* 276 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSortedIndexBy = __webpack_require__(277), + identity = __webpack_require__(158), + isSymbol = __webpack_require__(103); + + /** Used as references for the maximum length and index of an array. */ + var MAX_ARRAY_LENGTH = 4294967295, + HALF_MAX_ARRAY_LENGTH = MAX_ARRAY_LENGTH >>> 1; + + /** + * The base implementation of `_.sortedIndex` and `_.sortedLastIndex` which + * performs a binary search of `array` to determine the index at which `value` + * should be inserted into `array` in order to maintain its sort order. + * + * @private + * @param {Array} array The sorted array to inspect. + * @param {*} value The value to evaluate. + * @param {boolean} [retHighest] Specify returning the highest qualified index. + * @returns {number} Returns the index at which `value` should be inserted + * into `array`. + */ + function baseSortedIndex(array, value, retHighest) { + var low = 0, + high = array == null ? low : array.length; + + if (typeof value == 'number' && value === value && high <= HALF_MAX_ARRAY_LENGTH) { + while (low < high) { + var mid = (low + high) >>> 1, + computed = array[mid]; + + if (computed !== null && !isSymbol(computed) && + (retHighest ? (computed <= value) : (computed < value))) { + low = mid + 1; + } else { + high = mid; + } + } + return high; + } + return baseSortedIndexBy(array, value, identity, retHighest); + } + + module.exports = baseSortedIndex; + + +/***/ }), +/* 277 */ +/***/ (function(module, exports, __webpack_require__) { + + var isSymbol = __webpack_require__(103); + + /** Used as references for the maximum length and index of an array. */ + var MAX_ARRAY_LENGTH = 4294967295, + MAX_ARRAY_INDEX = MAX_ARRAY_LENGTH - 1; + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeFloor = Math.floor, + nativeMin = Math.min; + + /** + * The base implementation of `_.sortedIndexBy` and `_.sortedLastIndexBy` + * which invokes `iteratee` for `value` and each element of `array` to compute + * their sort ranking. The iteratee is invoked with one argument; (value). + * + * @private + * @param {Array} array The sorted array to inspect. + * @param {*} value The value to evaluate. + * @param {Function} iteratee The iteratee invoked per element. + * @param {boolean} [retHighest] Specify returning the highest qualified index. + * @returns {number} Returns the index at which `value` should be inserted + * into `array`. + */ + function baseSortedIndexBy(array, value, iteratee, retHighest) { + value = iteratee(value); + + var low = 0, + high = array == null ? 0 : array.length, + valIsNaN = value !== value, + valIsNull = value === null, + valIsSymbol = isSymbol(value), + valIsUndefined = value === undefined; + + while (low < high) { + var mid = nativeFloor((low + high) / 2), + computed = iteratee(array[mid]), + othIsDefined = computed !== undefined, + othIsNull = computed === null, + othIsReflexive = computed === computed, + othIsSymbol = isSymbol(computed); + + if (valIsNaN) { + var setLow = retHighest || othIsReflexive; + } else if (valIsUndefined) { + setLow = othIsReflexive && (retHighest || othIsDefined); + } else if (valIsNull) { + setLow = othIsReflexive && othIsDefined && (retHighest || !othIsNull); + } else if (valIsSymbol) { + setLow = othIsReflexive && othIsDefined && !othIsNull && (retHighest || !othIsSymbol); + } else if (othIsNull || othIsSymbol) { + setLow = false; + } else { + setLow = retHighest ? (computed <= value) : (computed < value); + } + if (setLow) { + low = mid + 1; + } else { + high = mid; + } + } + return nativeMin(high, MAX_ARRAY_INDEX); + } + + module.exports = baseSortedIndexBy; + + +/***/ }), +/* 278 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + baseSortedIndexBy = __webpack_require__(277); + + /** + * This method is like `_.sortedIndex` except that it accepts `iteratee` + * which is invoked for `value` and each element of `array` to compute their + * sort ranking. The iteratee is invoked with one argument: (value). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The sorted array to inspect. + * @param {*} value The value to evaluate. + * @param {Function} [iteratee=_.identity] The iteratee invoked per element. + * @returns {number} Returns the index at which `value` should be inserted + * into `array`. + * @example + * + * var objects = [{ 'x': 4 }, { 'x': 5 }]; + * + * _.sortedIndexBy(objects, { 'x': 4 }, function(o) { return o.x; }); + * // => 0 + * + * // The `_.property` iteratee shorthand. + * _.sortedIndexBy(objects, { 'x': 4 }, 'x'); + * // => 0 + */ + function sortedIndexBy(array, value, iteratee) { + return baseSortedIndexBy(array, value, baseIteratee(iteratee, 2)); + } + + module.exports = sortedIndexBy; + + +/***/ }), +/* 279 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSortedIndex = __webpack_require__(276), + eq = __webpack_require__(88); + + /** + * This method is like `_.indexOf` except that it performs a binary + * search on a sorted `array`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @returns {number} Returns the index of the matched value, else `-1`. + * @example + * + * _.sortedIndexOf([4, 5, 5, 5, 6], 5); + * // => 1 + */ + function sortedIndexOf(array, value) { + var length = array == null ? 0 : array.length; + if (length) { + var index = baseSortedIndex(array, value); + if (index < length && eq(array[index], value)) { + return index; + } + } + return -1; + } + + module.exports = sortedIndexOf; + + +/***/ }), +/* 280 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSortedIndex = __webpack_require__(276); + + /** + * This method is like `_.sortedIndex` except that it returns the highest + * index at which `value` should be inserted into `array` in order to + * maintain its sort order. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The sorted array to inspect. + * @param {*} value The value to evaluate. + * @returns {number} Returns the index at which `value` should be inserted + * into `array`. + * @example + * + * _.sortedLastIndex([4, 5, 5, 5, 6], 5); + * // => 4 + */ + function sortedLastIndex(array, value) { + return baseSortedIndex(array, value, true); + } + + module.exports = sortedLastIndex; + + +/***/ }), +/* 281 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + baseSortedIndexBy = __webpack_require__(277); + + /** + * This method is like `_.sortedLastIndex` except that it accepts `iteratee` + * which is invoked for `value` and each element of `array` to compute their + * sort ranking. The iteratee is invoked with one argument: (value). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The sorted array to inspect. + * @param {*} value The value to evaluate. + * @param {Function} [iteratee=_.identity] The iteratee invoked per element. + * @returns {number} Returns the index at which `value` should be inserted + * into `array`. + * @example + * + * var objects = [{ 'x': 4 }, { 'x': 5 }]; + * + * _.sortedLastIndexBy(objects, { 'x': 4 }, function(o) { return o.x; }); + * // => 1 + * + * // The `_.property` iteratee shorthand. + * _.sortedLastIndexBy(objects, { 'x': 4 }, 'x'); + * // => 1 + */ + function sortedLastIndexBy(array, value, iteratee) { + return baseSortedIndexBy(array, value, baseIteratee(iteratee, 2), true); + } + + module.exports = sortedLastIndexBy; + + +/***/ }), +/* 282 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSortedIndex = __webpack_require__(276), + eq = __webpack_require__(88); + + /** + * This method is like `_.lastIndexOf` except that it performs a binary + * search on a sorted `array`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @returns {number} Returns the index of the matched value, else `-1`. + * @example + * + * _.sortedLastIndexOf([4, 5, 5, 5, 6], 5); + * // => 3 + */ + function sortedLastIndexOf(array, value) { + var length = array == null ? 0 : array.length; + if (length) { + var index = baseSortedIndex(array, value, true) - 1; + if (eq(array[index], value)) { + return index; + } + } + return -1; + } + + module.exports = sortedLastIndexOf; + + +/***/ }), +/* 283 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSortedUniq = __webpack_require__(284); + + /** + * This method is like `_.uniq` except that it's designed and optimized + * for sorted arrays. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @returns {Array} Returns the new duplicate free array. + * @example + * + * _.sortedUniq([1, 1, 2]); + * // => [1, 2] + */ + function sortedUniq(array) { + return (array && array.length) + ? baseSortedUniq(array) + : []; + } + + module.exports = sortedUniq; + + +/***/ }), +/* 284 */ +/***/ (function(module, exports, __webpack_require__) { + + var eq = __webpack_require__(88); + + /** + * The base implementation of `_.sortedUniq` and `_.sortedUniqBy` without + * support for iteratee shorthands. + * + * @private + * @param {Array} array The array to inspect. + * @param {Function} [iteratee] The iteratee invoked per element. + * @returns {Array} Returns the new duplicate free array. + */ + function baseSortedUniq(array, iteratee) { + var index = -1, + length = array.length, + resIndex = 0, + result = []; + + while (++index < length) { + var value = array[index], + computed = iteratee ? iteratee(value) : value; + + if (!index || !eq(computed, seen)) { + var seen = computed; + result[resIndex++] = value === 0 ? 0 : value; + } + } + return result; + } + + module.exports = baseSortedUniq; + + +/***/ }), +/* 285 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + baseSortedUniq = __webpack_require__(284); + + /** + * This method is like `_.uniqBy` except that it's designed and optimized + * for sorted arrays. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {Function} [iteratee] The iteratee invoked per element. + * @returns {Array} Returns the new duplicate free array. + * @example + * + * _.sortedUniqBy([1.1, 1.2, 2.3, 2.4], Math.floor); + * // => [1.1, 2.3] + */ + function sortedUniqBy(array, iteratee) { + return (array && array.length) + ? baseSortedUniq(array, baseIteratee(iteratee, 2)) + : []; + } + + module.exports = sortedUniqBy; + + +/***/ }), +/* 286 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86); + + /** + * Gets all but the first element of `array`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to query. + * @returns {Array} Returns the slice of `array`. + * @example + * + * _.tail([1, 2, 3]); + * // => [2, 3] + */ + function tail(array) { + var length = array == null ? 0 : array.length; + return length ? baseSlice(array, 1, length) : []; + } + + module.exports = tail; + + +/***/ }), +/* 287 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86), + toInteger = __webpack_require__(100); + + /** + * Creates a slice of `array` with `n` elements taken from the beginning. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to query. + * @param {number} [n=1] The number of elements to take. + * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. + * @returns {Array} Returns the slice of `array`. + * @example + * + * _.take([1, 2, 3]); + * // => [1] + * + * _.take([1, 2, 3], 2); + * // => [1, 2] + * + * _.take([1, 2, 3], 5); + * // => [1, 2, 3] + * + * _.take([1, 2, 3], 0); + * // => [] + */ + function take(array, n, guard) { + if (!(array && array.length)) { + return []; + } + n = (guard || n === undefined) ? 1 : toInteger(n); + return baseSlice(array, 0, n < 0 ? 0 : n); + } + + module.exports = take; + + +/***/ }), +/* 288 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86), + toInteger = __webpack_require__(100); + + /** + * Creates a slice of `array` with `n` elements taken from the end. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to query. + * @param {number} [n=1] The number of elements to take. + * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. + * @returns {Array} Returns the slice of `array`. + * @example + * + * _.takeRight([1, 2, 3]); + * // => [3] + * + * _.takeRight([1, 2, 3], 2); + * // => [2, 3] + * + * _.takeRight([1, 2, 3], 5); + * // => [1, 2, 3] + * + * _.takeRight([1, 2, 3], 0); + * // => [] + */ + function takeRight(array, n, guard) { + var length = array == null ? 0 : array.length; + if (!length) { + return []; + } + n = (guard || n === undefined) ? 1 : toInteger(n); + n = length - n; + return baseSlice(array, n < 0 ? 0 : n, length); + } + + module.exports = takeRight; + + +/***/ }), +/* 289 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + baseWhile = __webpack_require__(233); + + /** + * Creates a slice of `array` with elements taken from the end. Elements are + * taken until `predicate` returns falsey. The predicate is invoked with + * three arguments: (value, index, array). + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to query. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @returns {Array} Returns the slice of `array`. + * @example + * + * var users = [ + * { 'user': 'barney', 'active': true }, + * { 'user': 'fred', 'active': false }, + * { 'user': 'pebbles', 'active': false } + * ]; + * + * _.takeRightWhile(users, function(o) { return !o.active; }); + * // => objects for ['fred', 'pebbles'] + * + * // The `_.matches` iteratee shorthand. + * _.takeRightWhile(users, { 'user': 'pebbles', 'active': false }); + * // => objects for ['pebbles'] + * + * // The `_.matchesProperty` iteratee shorthand. + * _.takeRightWhile(users, ['active', false]); + * // => objects for ['fred', 'pebbles'] + * + * // The `_.property` iteratee shorthand. + * _.takeRightWhile(users, 'active'); + * // => [] + */ + function takeRightWhile(array, predicate) { + return (array && array.length) + ? baseWhile(array, baseIteratee(predicate, 3), false, true) + : []; + } + + module.exports = takeRightWhile; + + +/***/ }), +/* 290 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + baseWhile = __webpack_require__(233); + + /** + * Creates a slice of `array` with elements taken from the beginning. Elements + * are taken until `predicate` returns falsey. The predicate is invoked with + * three arguments: (value, index, array). + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to query. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @returns {Array} Returns the slice of `array`. + * @example + * + * var users = [ + * { 'user': 'barney', 'active': false }, + * { 'user': 'fred', 'active': false }, + * { 'user': 'pebbles', 'active': true } + * ]; + * + * _.takeWhile(users, function(o) { return !o.active; }); + * // => objects for ['barney', 'fred'] + * + * // The `_.matches` iteratee shorthand. + * _.takeWhile(users, { 'user': 'barney', 'active': false }); + * // => objects for ['barney'] + * + * // The `_.matchesProperty` iteratee shorthand. + * _.takeWhile(users, ['active', false]); + * // => objects for ['barney', 'fred'] + * + * // The `_.property` iteratee shorthand. + * _.takeWhile(users, 'active'); + * // => [] + */ + function takeWhile(array, predicate) { + return (array && array.length) + ? baseWhile(array, baseIteratee(predicate, 3)) + : []; + } + + module.exports = takeWhile; + + +/***/ }), +/* 291 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFlatten = __webpack_require__(108), + baseRest = __webpack_require__(157), + baseUniq = __webpack_require__(292), + isArrayLikeObject = __webpack_require__(166); + + /** + * Creates an array of unique values, in order, from all given arrays using + * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @returns {Array} Returns the new array of combined values. + * @example + * + * _.union([2], [1, 2]); + * // => [2, 1] + */ + var union = baseRest(function(arrays) { + return baseUniq(baseFlatten(arrays, 1, isArrayLikeObject, true)); + }); + + module.exports = union; + + +/***/ }), +/* 292 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetCache = __webpack_require__(116), + arrayIncludes = __webpack_require__(148), + arrayIncludesWith = __webpack_require__(153), + cacheHas = __webpack_require__(156), + createSet = __webpack_require__(293), + setToArray = __webpack_require__(184); + + /** Used as the size to enable large array optimizations. */ + var LARGE_ARRAY_SIZE = 200; + + /** + * The base implementation of `_.uniqBy` without support for iteratee shorthands. + * + * @private + * @param {Array} array The array to inspect. + * @param {Function} [iteratee] The iteratee invoked per element. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new duplicate free array. + */ + function baseUniq(array, iteratee, comparator) { + var index = -1, + includes = arrayIncludes, + length = array.length, + isCommon = true, + result = [], + seen = result; + + if (comparator) { + isCommon = false; + includes = arrayIncludesWith; + } + else if (length >= LARGE_ARRAY_SIZE) { + var set = iteratee ? null : createSet(array); + if (set) { + return setToArray(set); + } + isCommon = false; + includes = cacheHas; + seen = new SetCache; + } + else { + seen = iteratee ? [] : result; + } + outer: + while (++index < length) { + var value = array[index], + computed = iteratee ? iteratee(value) : value; + + value = (comparator || value !== 0) ? value : 0; + if (isCommon && computed === computed) { + var seenIndex = seen.length; + while (seenIndex--) { + if (seen[seenIndex] === computed) { + continue outer; + } + } + if (iteratee) { + seen.push(computed); + } + result.push(value); + } + else if (!includes(seen, computed, comparator)) { + if (seen !== result) { + seen.push(computed); + } + result.push(value); + } + } + return result; + } + + module.exports = baseUniq; + + +/***/ }), +/* 293 */ +/***/ (function(module, exports, __webpack_require__) { + + var Set = __webpack_require__(206), + noop = __webpack_require__(294), + setToArray = __webpack_require__(184); + + /** Used as references for various `Number` constants. */ + var INFINITY = 1 / 0; + + /** + * Creates a set object of `values`. + * + * @private + * @param {Array} values The values to add to the set. + * @returns {Object} Returns the new set. + */ + var createSet = !(Set && (1 / setToArray(new Set([,-0]))[1]) == INFINITY) ? noop : function(values) { + return new Set(values); + }; + + module.exports = createSet; + + +/***/ }), +/* 294 */ +/***/ (function(module, exports) { + + /** + * This method returns `undefined`. + * + * @static + * @memberOf _ + * @since 2.3.0 + * @category Util + * @example + * + * _.times(2, _.noop); + * // => [undefined, undefined] + */ + function noop() { + // No operation performed. + } + + module.exports = noop; + + +/***/ }), +/* 295 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFlatten = __webpack_require__(108), + baseIteratee = __webpack_require__(168), + baseRest = __webpack_require__(157), + baseUniq = __webpack_require__(292), + isArrayLikeObject = __webpack_require__(166), + last = __webpack_require__(228); + + /** + * This method is like `_.union` except that it accepts `iteratee` which is + * invoked for each element of each `arrays` to generate the criterion by + * which uniqueness is computed. Result values are chosen from the first + * array in which the value occurs. The iteratee is invoked with one argument: + * (value). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @param {Function} [iteratee=_.identity] The iteratee invoked per element. + * @returns {Array} Returns the new array of combined values. + * @example + * + * _.unionBy([2.1], [1.2, 2.3], Math.floor); + * // => [2.1, 1.2] + * + * // The `_.property` iteratee shorthand. + * _.unionBy([{ 'x': 1 }], [{ 'x': 2 }, { 'x': 1 }], 'x'); + * // => [{ 'x': 1 }, { 'x': 2 }] + */ + var unionBy = baseRest(function(arrays) { + var iteratee = last(arrays); + if (isArrayLikeObject(iteratee)) { + iteratee = undefined; + } + return baseUniq(baseFlatten(arrays, 1, isArrayLikeObject, true), baseIteratee(iteratee, 2)); + }); + + module.exports = unionBy; + + +/***/ }), +/* 296 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFlatten = __webpack_require__(108), + baseRest = __webpack_require__(157), + baseUniq = __webpack_require__(292), + isArrayLikeObject = __webpack_require__(166), + last = __webpack_require__(228); + + /** + * This method is like `_.union` except that it accepts `comparator` which + * is invoked to compare elements of `arrays`. Result values are chosen from + * the first array in which the value occurs. The comparator is invoked + * with two arguments: (arrVal, othVal). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new array of combined values. + * @example + * + * var objects = [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }]; + * var others = [{ 'x': 1, 'y': 1 }, { 'x': 1, 'y': 2 }]; + * + * _.unionWith(objects, others, _.isEqual); + * // => [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }, { 'x': 1, 'y': 1 }] + */ + var unionWith = baseRest(function(arrays) { + var comparator = last(arrays); + comparator = typeof comparator == 'function' ? comparator : undefined; + return baseUniq(baseFlatten(arrays, 1, isArrayLikeObject, true), undefined, comparator); + }); + + module.exports = unionWith; + + +/***/ }), +/* 297 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseUniq = __webpack_require__(292); + + /** + * Creates a duplicate-free version of an array, using + * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons, in which only the first occurrence of each element + * is kept. The order of result values is determined by the order they occur + * in the array. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to inspect. + * @returns {Array} Returns the new duplicate free array. + * @example + * + * _.uniq([2, 1, 2]); + * // => [2, 1] + */ + function uniq(array) { + return (array && array.length) ? baseUniq(array) : []; + } + + module.exports = uniq; + + +/***/ }), +/* 298 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + baseUniq = __webpack_require__(292); + + /** + * This method is like `_.uniq` except that it accepts `iteratee` which is + * invoked for each element in `array` to generate the criterion by which + * uniqueness is computed. The order of result values is determined by the + * order they occur in the array. The iteratee is invoked with one argument: + * (value). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {Function} [iteratee=_.identity] The iteratee invoked per element. + * @returns {Array} Returns the new duplicate free array. + * @example + * + * _.uniqBy([2.1, 1.2, 2.3], Math.floor); + * // => [2.1, 1.2] + * + * // The `_.property` iteratee shorthand. + * _.uniqBy([{ 'x': 1 }, { 'x': 2 }, { 'x': 1 }], 'x'); + * // => [{ 'x': 1 }, { 'x': 2 }] + */ + function uniqBy(array, iteratee) { + return (array && array.length) ? baseUniq(array, baseIteratee(iteratee, 2)) : []; + } + + module.exports = uniqBy; + + +/***/ }), +/* 299 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseUniq = __webpack_require__(292); + + /** + * This method is like `_.uniq` except that it accepts `comparator` which + * is invoked to compare elements of `array`. The order of result values is + * determined by the order they occur in the array.The comparator is invoked + * with two arguments: (arrVal, othVal). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new duplicate free array. + * @example + * + * var objects = [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }, { 'x': 1, 'y': 2 }]; + * + * _.uniqWith(objects, _.isEqual); + * // => [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }] + */ + function uniqWith(array, comparator) { + comparator = typeof comparator == 'function' ? comparator : undefined; + return (array && array.length) ? baseUniq(array, undefined, comparator) : []; + } + + module.exports = uniqWith; + + +/***/ }), +/* 300 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayFilter = __webpack_require__(189), + arrayMap = __webpack_require__(154), + baseProperty = __webpack_require__(226), + baseTimes = __webpack_require__(193), + isArrayLikeObject = __webpack_require__(166); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeMax = Math.max; + + /** + * This method is like `_.zip` except that it accepts an array of grouped + * elements and creates an array regrouping the elements to their pre-zip + * configuration. + * + * @static + * @memberOf _ + * @since 1.2.0 + * @category Array + * @param {Array} array The array of grouped elements to process. + * @returns {Array} Returns the new array of regrouped elements. + * @example + * + * var zipped = _.zip(['a', 'b'], [1, 2], [true, false]); + * // => [['a', 1, true], ['b', 2, false]] + * + * _.unzip(zipped); + * // => [['a', 'b'], [1, 2], [true, false]] + */ + function unzip(array) { + if (!(array && array.length)) { + return []; + } + var length = 0; + array = arrayFilter(array, function(group) { + if (isArrayLikeObject(group)) { + length = nativeMax(group.length, length); + return true; + } + }); + return baseTimes(length, function(index) { + return arrayMap(array, baseProperty(index)); + }); + } + + module.exports = unzip; + + +/***/ }), +/* 301 */ +/***/ (function(module, exports, __webpack_require__) { + + var apply = __webpack_require__(160), + arrayMap = __webpack_require__(154), + unzip = __webpack_require__(300); + + /** + * This method is like `_.unzip` except that it accepts `iteratee` to specify + * how regrouped values should be combined. The iteratee is invoked with the + * elements of each group: (...group). + * + * @static + * @memberOf _ + * @since 3.8.0 + * @category Array + * @param {Array} array The array of grouped elements to process. + * @param {Function} [iteratee=_.identity] The function to combine + * regrouped values. + * @returns {Array} Returns the new array of regrouped elements. + * @example + * + * var zipped = _.zip([1, 2], [10, 20], [100, 200]); + * // => [[1, 10, 100], [2, 20, 200]] + * + * _.unzipWith(zipped, _.add); + * // => [3, 30, 300] + */ + function unzipWith(array, iteratee) { + if (!(array && array.length)) { + return []; + } + var result = unzip(array); + if (iteratee == null) { + return result; + } + return arrayMap(result, function(group) { + return apply(iteratee, undefined, group); + }); + } + + module.exports = unzipWith; + + +/***/ }), +/* 302 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseDifference = __webpack_require__(115), + baseRest = __webpack_require__(157), + isArrayLikeObject = __webpack_require__(166); + + /** + * Creates an array excluding all given values using + * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. + * + * **Note:** Unlike `_.pull`, this method returns a new array. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {...*} [values] The values to exclude. + * @returns {Array} Returns the new array of filtered values. + * @see _.difference, _.xor + * @example + * + * _.without([2, 1, 2, 3], 1, 2); + * // => [3] + */ + var without = baseRest(function(array, values) { + return isArrayLikeObject(array) + ? baseDifference(array, values) + : []; + }); + + module.exports = without; + + +/***/ }), +/* 303 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayFilter = __webpack_require__(189), + baseRest = __webpack_require__(157), + baseXor = __webpack_require__(304), + isArrayLikeObject = __webpack_require__(166); + + /** + * Creates an array of unique values that is the + * [symmetric difference](https://en.wikipedia.org/wiki/Symmetric_difference) + * of the given arrays. The order of result values is determined by the order + * they occur in the arrays. + * + * @static + * @memberOf _ + * @since 2.4.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @returns {Array} Returns the new array of filtered values. + * @see _.difference, _.without + * @example + * + * _.xor([2, 1], [2, 3]); + * // => [1, 3] + */ + var xor = baseRest(function(arrays) { + return baseXor(arrayFilter(arrays, isArrayLikeObject)); + }); + + module.exports = xor; + + +/***/ }), +/* 304 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseDifference = __webpack_require__(115), + baseFlatten = __webpack_require__(108), + baseUniq = __webpack_require__(292); + + /** + * The base implementation of methods like `_.xor`, without support for + * iteratee shorthands, that accepts an array of arrays to inspect. + * + * @private + * @param {Array} arrays The arrays to inspect. + * @param {Function} [iteratee] The iteratee invoked per element. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new array of values. + */ + function baseXor(arrays, iteratee, comparator) { + var length = arrays.length; + if (length < 2) { + return length ? baseUniq(arrays[0]) : []; + } + var index = -1, + result = Array(length); + + while (++index < length) { + var array = arrays[index], + othIndex = -1; + + while (++othIndex < length) { + if (othIndex != index) { + result[index] = baseDifference(result[index] || array, arrays[othIndex], iteratee, comparator); + } + } + } + return baseUniq(baseFlatten(result, 1), iteratee, comparator); + } + + module.exports = baseXor; + + +/***/ }), +/* 305 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayFilter = __webpack_require__(189), + baseIteratee = __webpack_require__(168), + baseRest = __webpack_require__(157), + baseXor = __webpack_require__(304), + isArrayLikeObject = __webpack_require__(166), + last = __webpack_require__(228); + + /** + * This method is like `_.xor` except that it accepts `iteratee` which is + * invoked for each element of each `arrays` to generate the criterion by + * which by which they're compared. The order of result values is determined + * by the order they occur in the arrays. The iteratee is invoked with one + * argument: (value). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @param {Function} [iteratee=_.identity] The iteratee invoked per element. + * @returns {Array} Returns the new array of filtered values. + * @example + * + * _.xorBy([2.1, 1.2], [2.3, 3.4], Math.floor); + * // => [1.2, 3.4] + * + * // The `_.property` iteratee shorthand. + * _.xorBy([{ 'x': 1 }], [{ 'x': 2 }, { 'x': 1 }], 'x'); + * // => [{ 'x': 2 }] + */ + var xorBy = baseRest(function(arrays) { + var iteratee = last(arrays); + if (isArrayLikeObject(iteratee)) { + iteratee = undefined; + } + return baseXor(arrayFilter(arrays, isArrayLikeObject), baseIteratee(iteratee, 2)); + }); + + module.exports = xorBy; + + +/***/ }), +/* 306 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayFilter = __webpack_require__(189), + baseRest = __webpack_require__(157), + baseXor = __webpack_require__(304), + isArrayLikeObject = __webpack_require__(166), + last = __webpack_require__(228); + + /** + * This method is like `_.xor` except that it accepts `comparator` which is + * invoked to compare elements of `arrays`. The order of result values is + * determined by the order they occur in the arrays. The comparator is invoked + * with two arguments: (arrVal, othVal). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new array of filtered values. + * @example + * + * var objects = [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }]; + * var others = [{ 'x': 1, 'y': 1 }, { 'x': 1, 'y': 2 }]; + * + * _.xorWith(objects, others, _.isEqual); + * // => [{ 'x': 2, 'y': 1 }, { 'x': 1, 'y': 1 }] + */ + var xorWith = baseRest(function(arrays) { + var comparator = last(arrays); + comparator = typeof comparator == 'function' ? comparator : undefined; + return baseXor(arrayFilter(arrays, isArrayLikeObject), undefined, comparator); + }); + + module.exports = xorWith; + + +/***/ }), +/* 307 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseRest = __webpack_require__(157), + unzip = __webpack_require__(300); + + /** + * Creates an array of grouped elements, the first of which contains the + * first elements of the given arrays, the second of which contains the + * second elements of the given arrays, and so on. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {...Array} [arrays] The arrays to process. + * @returns {Array} Returns the new array of grouped elements. + * @example + * + * _.zip(['a', 'b'], [1, 2], [true, false]); + * // => [['a', 1, true], ['b', 2, false]] + */ + var zip = baseRest(unzip); + + module.exports = zip; + + +/***/ }), +/* 308 */ +/***/ (function(module, exports, __webpack_require__) { + + var assignValue = __webpack_require__(309), + baseZipObject = __webpack_require__(311); + + /** + * This method is like `_.fromPairs` except that it accepts two arrays, + * one of property identifiers and one of corresponding values. + * + * @static + * @memberOf _ + * @since 0.4.0 + * @category Array + * @param {Array} [props=[]] The property identifiers. + * @param {Array} [values=[]] The property values. + * @returns {Object} Returns the new object. + * @example + * + * _.zipObject(['a', 'b'], [1, 2]); + * // => { 'a': 1, 'b': 2 } + */ + function zipObject(props, values) { + return baseZipObject(props || [], values || [], assignValue); + } + + module.exports = zipObject; + + +/***/ }), +/* 309 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseAssignValue = __webpack_require__(310), + eq = __webpack_require__(88); + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * Assigns `value` to `key` of `object` if the existing value is not equivalent + * using [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. + * + * @private + * @param {Object} object The object to modify. + * @param {string} key The key of the property to assign. + * @param {*} value The value to assign. + */ + function assignValue(object, key, value) { + var objValue = object[key]; + if (!(hasOwnProperty.call(object, key) && eq(objValue, value)) || + (value === undefined && !(key in object))) { + baseAssignValue(object, key, value); + } + } + + module.exports = assignValue; + + +/***/ }), +/* 310 */ +/***/ (function(module, exports, __webpack_require__) { + + var defineProperty = __webpack_require__(164); + + /** + * The base implementation of `assignValue` and `assignMergeValue` without + * value checks. + * + * @private + * @param {Object} object The object to modify. + * @param {string} key The key of the property to assign. + * @param {*} value The value to assign. + */ + function baseAssignValue(object, key, value) { + if (key == '__proto__' && defineProperty) { + defineProperty(object, key, { + 'configurable': true, + 'enumerable': true, + 'value': value, + 'writable': true + }); + } else { + object[key] = value; + } + } + + module.exports = baseAssignValue; + + +/***/ }), +/* 311 */ +/***/ (function(module, exports) { + + /** + * This base implementation of `_.zipObject` which assigns values using `assignFunc`. + * + * @private + * @param {Array} props The property identifiers. + * @param {Array} values The property values. + * @param {Function} assignFunc The function to assign values. + * @returns {Object} Returns the new object. + */ + function baseZipObject(props, values, assignFunc) { + var index = -1, + length = props.length, + valsLength = values.length, + result = {}; + + while (++index < length) { + var value = index < valsLength ? values[index] : undefined; + assignFunc(result, props[index], value); + } + return result; + } + + module.exports = baseZipObject; + + +/***/ }), +/* 312 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSet = __webpack_require__(313), + baseZipObject = __webpack_require__(311); + + /** + * This method is like `_.zipObject` except that it supports property paths. + * + * @static + * @memberOf _ + * @since 4.1.0 + * @category Array + * @param {Array} [props=[]] The property identifiers. + * @param {Array} [values=[]] The property values. + * @returns {Object} Returns the new object. + * @example + * + * _.zipObjectDeep(['a.b[0].c', 'a.b[1].d'], [1, 2]); + * // => { 'a': { 'b': [{ 'c': 1 }, { 'd': 2 }] } } + */ + function zipObjectDeep(props, values) { + return baseZipObject(props || [], values || [], baseSet); + } + + module.exports = zipObjectDeep; + + +/***/ }), +/* 313 */ +/***/ (function(module, exports, __webpack_require__) { + + var assignValue = __webpack_require__(309), + castPath = __webpack_require__(214), + isIndex = __webpack_require__(99), + isObject = __webpack_require__(97), + toKey = __webpack_require__(221); + + /** + * The base implementation of `_.set`. + * + * @private + * @param {Object} object The object to modify. + * @param {Array|string} path The path of the property to set. + * @param {*} value The value to set. + * @param {Function} [customizer] The function to customize path creation. + * @returns {Object} Returns `object`. + */ + function baseSet(object, path, value, customizer) { + if (!isObject(object)) { + return object; + } + path = castPath(path, object); + + var index = -1, + length = path.length, + lastIndex = length - 1, + nested = object; + + while (nested != null && ++index < length) { + var key = toKey(path[index]), + newValue = value; + + if (index != lastIndex) { + var objValue = nested[key]; + newValue = customizer ? customizer(objValue, key, nested) : undefined; + if (newValue === undefined) { + newValue = isObject(objValue) + ? objValue + : (isIndex(path[index + 1]) ? [] : {}); + } + } + assignValue(nested, key, newValue); + nested = nested[key]; + } + return object; + } + + module.exports = baseSet; + + +/***/ }), +/* 314 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseRest = __webpack_require__(157), + unzipWith = __webpack_require__(301); + + /** + * This method is like `_.zip` except that it accepts `iteratee` to specify + * how grouped values should be combined. The iteratee is invoked with the + * elements of each group: (...group). + * + * @static + * @memberOf _ + * @since 3.8.0 + * @category Array + * @param {...Array} [arrays] The arrays to process. + * @param {Function} [iteratee=_.identity] The function to combine + * grouped values. + * @returns {Array} Returns the new array of grouped elements. + * @example + * + * _.zipWith([1, 2], [10, 20], [100, 200], function(a, b, c) { + * return a + b + c; + * }); + * // => [111, 222] + */ + var zipWith = baseRest(function(arrays) { + var length = arrays.length, + iteratee = length > 1 ? arrays[length - 1] : undefined; + + iteratee = typeof iteratee == 'function' ? (arrays.pop(), iteratee) : undefined; + return unzipWith(arrays, iteratee); + }); + + module.exports = zipWith; + + +/***/ }), +/* 315 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( handlerFunction ){ + var viewer = {}, + lastSelectedElement; + + viewer.handle = function ( selectedElement ){ + // Don't display details on a drag event, which will be prevented + if ( d3.event.defaultPrevented ) { + return; + } + + var isSelection = true; + + // Deselection of the focused element + if ( lastSelectedElement === selectedElement ) { + isSelection = false; + } + + if ( handlerFunction instanceof Function ) { + if ( isSelection ) { + handlerFunction(selectedElement); + } else { + handlerFunction(undefined); + } + } + + if ( isSelection ) { + lastSelectedElement = selectedElement; + } else { + lastSelectedElement = undefined; + } + }; + + /** + * Resets the displayed information to its default. + */ + viewer.reset = function (){ + if ( lastSelectedElement ) { + handlerFunction(undefined); + lastSelectedElement = undefined; + } + }; + + return viewer; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 316 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetOperatorNode = __webpack_require__(20); + + module.exports = function (){ + + var filter = {}, + nodes, + properties, + enabled = false, + filteredNodes, + filteredProperties, + filterTools = __webpack_require__(76)(); + + + /** + * If enabled, all set operators including connected properties are filtered. + * @param untouchedNodes + * @param untouchedProperties + */ + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + + if ( this.enabled() ) { + removeSetOperators(); + } + + filteredNodes = nodes; + filteredProperties = properties; + }; + + function removeSetOperators(){ + var filteredData = filterTools.filterNodesAndTidy(nodes, properties, isNoSetOperator); + + nodes = filteredData.nodes; + properties = filteredData.properties; + } + + function isNoSetOperator( node ){ + return !(node instanceof SetOperatorNode); + } + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }), +/* 317 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var SetOperatorNode = __webpack_require__(20); + var OwlThing = __webpack_require__(31); + var OwlNothing = __webpack_require__(30); + var elementTools = __webpack_require__(63)(); + + module.exports = function (){ + + var statistics = {}, + nodeCount, + occurencesOfClassAndDatatypeTypes = {}, + edgeCount, + occurencesOfPropertyTypes = {}, + classCount, + datatypeCount, + datatypePropertyCount, + objectPropertyCount, + propertyCount, + totalIndividualCount, + filteredNodes, + filteredProperties; + + + statistics.filter = function ( classesAndDatatypes, properties ){ + resetStoredData(); + + storeTotalCounts(classesAndDatatypes, properties); + storeClassAndDatatypeCount(classesAndDatatypes); + storePropertyCount(properties); + + storeOccurencesOfTypes(classesAndDatatypes, occurencesOfClassAndDatatypeTypes); + storeOccurencesOfTypes(properties, occurencesOfPropertyTypes); + + storeTotalIndividualCount(classesAndDatatypes); + + filteredNodes = classesAndDatatypes; + filteredProperties = properties; + }; + + function resetStoredData(){ + nodeCount = 0; + edgeCount = 0; + classCount = 0; + datatypeCount = 0; + datatypePropertyCount = 0; + objectPropertyCount = 0; + propertyCount = 0; + totalIndividualCount = 0; + } + + function storeTotalCounts( classesAndDatatypes, properties ){ + nodeCount = classesAndDatatypes.length; + + var seenProperties = __webpack_require__(62)(), i, l, property; + for ( i = 0, l = properties.length; i < l; i++ ) { + property = properties[i]; + if ( !seenProperties.has(property) ) { + edgeCount += 1; + } + + seenProperties.add(property); + if ( property.inverse() ) { + seenProperties.add(property.inverse()); + } + } + } + + function storeClassAndDatatypeCount( classesAndDatatypes ){ + // Each datatype should be counted just a single time + var datatypeSet = d3.set(), + hasThing = false, + hasNothing = false; + classCount = 0; + var old = 0, newcc = 0; + classesAndDatatypes.forEach(function ( node ){ + if ( elementTools.isDatatype(node) ) { + datatypeSet.add(node.defaultLabel()); + } else if ( !(node instanceof SetOperatorNode) ) { + if ( node instanceof OwlThing ) { + hasThing = true; + } else if ( node instanceof OwlNothing ) { + hasNothing = true; + } else { + old = classCount; + var adds = 1 + countElementArray(node.equivalents()); + classCount += adds; + newcc = classCount; + } + } else if ( node instanceof SetOperatorNode ) { + old = classCount; + classCount += 1; + newcc = classCount; + } + }); + + // count things and nothings just a single time + // classCount += hasThing ? 1 : 0; + // classCount += hasNothing ? 1 : 0; + + datatypeCount = datatypeSet.size(); + } + + function storePropertyCount( properties ){ + for ( var i = 0, l = properties.length; i < l; i++ ) { + var property = properties[i]; + var attr; + var result = false; + if ( property.attributes ) { + attr = property.attributes(); + if ( attr && attr.indexOf("datatype") !== -1 ) { + result = true; + } + } + if ( result === true ) { + datatypePropertyCount += getExtendedPropertyCount(property); + } else if ( elementTools.isObjectProperty(property) ) { + objectPropertyCount += getExtendedPropertyCount(property); + } + } + propertyCount = objectPropertyCount + datatypePropertyCount; + } + + function getExtendedPropertyCount( property ){ + // count the property itself + var count = 1; + + // and count properties this property represents + count += countElementArray(property.equivalents()); + count += countElementArray(property.redundantProperties()); + + return count; + } + + function countElementArray( properties ){ + if ( properties ) { + return properties.length; + } + return 0; + } + + function storeOccurencesOfTypes( elements, storage ){ + elements.forEach(function ( element ){ + var type = element.type(), + typeCount = storage[type]; + + if ( typeof typeCount === "undefined" ) { + typeCount = 0; + } else { + typeCount += 1; + } + storage[type] = typeCount; + }); + } + + function storeTotalIndividualCount( nodes ){ + var sawIndividuals = {}; + var totalCount = 0; + for ( var i = 0, l = nodes.length; i < l; i++ ) { + var individuals = nodes[i].individuals(); + + var tempCount = 0; + for ( var iA = 0; iA < individuals.length; iA++ ) { + if ( sawIndividuals[individuals[iA].iri()] === undefined ) { + sawIndividuals[individuals[iA].iri()] = 1; // this iri for that individual is now set to 1 >> seen it + tempCount++; + } + } + totalCount += tempCount; + } + totalIndividualCount = totalCount; + sawIndividuals = {}; // clear the object + + } + + + statistics.nodeCount = function (){ + return nodeCount; + }; + + statistics.occurencesOfClassAndDatatypeTypes = function (){ + return occurencesOfClassAndDatatypeTypes; + }; + + statistics.edgeCount = function (){ + return edgeCount; + }; + + statistics.occurencesOfPropertyTypes = function (){ + return occurencesOfPropertyTypes; + }; + + statistics.classCount = function (){ + return classCount; + }; + + statistics.datatypeCount = function (){ + return datatypeCount; + }; + + statistics.datatypePropertyCount = function (){ + return datatypePropertyCount; + }; + + statistics.objectPropertyCount = function (){ + return objectPropertyCount; + }; + + statistics.propertyCount = function (){ + return propertyCount; + }; + + statistics.totalIndividualCount = function (){ + return totalIndividualCount; + }; + + + // Functions a filter must have + statistics.filteredNodes = function (){ + return filteredNodes; + }; + + statistics.filteredProperties = function (){ + return filteredProperties; + }; + + + return statistics; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 318 */ +/***/ (function(module, exports, __webpack_require__) { + + var elementTools = __webpack_require__(63)(); + + module.exports = function (){ + + var filter = {}, + nodes, + properties, + enabled = false, + filteredNodes, + filteredProperties; + + + /** + * If enabled subclasses that have only subclass properties are filtered. + * @param untouchedNodes + * @param untouchedProperties + */ + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + + if ( this.enabled() ) { + hideSubclassesWithoutOwnProperties(); + } + + filteredNodes = nodes; + filteredProperties = properties; + }; + + function hideSubclassesWithoutOwnProperties(){ + var unneededProperties = [], + unneededClasses = [], + subclasses = [], + connectedProperties, + subclass, + property, + i, // index, + l; // length + + + for ( i = 0, l = properties.length; i < l; i++ ) { + property = properties[i]; + if ( elementTools.isRdfsSubClassOf(property) ) { + subclasses.push(property.domain()); + } + } + + for ( i = 0, l = subclasses.length; i < l; i++ ) { + subclass = subclasses[i]; + connectedProperties = findRelevantConnectedProperties(subclass, properties); + + // Only remove the node and its properties, if they're all subclassOf properties + if ( areOnlySubclassProperties(connectedProperties) && + doesNotInheritFromMultipleClasses(subclass, connectedProperties) ) { + + unneededProperties = unneededProperties.concat(connectedProperties); + unneededClasses.push(subclass); + } + } + + nodes = removeUnneededElements(nodes, unneededClasses); + properties = removeUnneededElements(properties, unneededProperties); + } + + /** + * Looks recursively for connected properties. Because just subclasses are relevant, + * we just look recursively for their properties. + * + * @param node + * @param allProperties + * @param visitedNodes a visited nodes which is used on recursive invocation + * @returns {Array} + */ + function findRelevantConnectedProperties( node, allProperties, visitedNodes ){ + var connectedProperties = [], + property, + i, + l; + + for ( i = 0, l = allProperties.length; i < l; i++ ) { + property = allProperties[i]; + if ( property.domain() === node || + property.range() === node ) { + + connectedProperties.push(property); + + + /* Special case: SuperClass <-(1) Subclass <-(2) Subclass ->(3) e.g. Datatype + * We need to find the last property recursively. Otherwise, we would remove the subClassOf + * property (1) because we didn't see the datatype property (3). + */ + + // Look only for subclass properties, because these are the relevant properties + if ( elementTools.isRdfsSubClassOf(property) ) { + var domain = property.domain(); + visitedNodes = visitedNodes || __webpack_require__(62)(); + + // If we have the range, there might be a nested property on the domain + if ( node === property.range() && !visitedNodes.has(domain) ) { + visitedNodes.add(domain); + var nestedConnectedProperties = findRelevantConnectedProperties(domain, allProperties, visitedNodes); + connectedProperties = connectedProperties.concat(nestedConnectedProperties); + } + } + } + } + + return connectedProperties; + } + + function areOnlySubclassProperties( connectedProperties ){ + var onlySubclassProperties = true, + property, + i, + l; + + for ( i = 0, l = connectedProperties.length; i < l; i++ ) { + property = connectedProperties[i]; + + if ( !elementTools.isRdfsSubClassOf(property) ) { + onlySubclassProperties = false; + break; + } + } + + return onlySubclassProperties; + } + + function doesNotInheritFromMultipleClasses( subclass, connectedProperties ){ + var superClassCount = 0; + + for ( var i = 0, l = connectedProperties.length; i < l; i++ ) { + var property = connectedProperties[i]; + + if ( property.domain() === subclass ) { + superClassCount += 1; + } + + if ( superClassCount > 1 ) { + return false; + } + } + + return true; + } + + function removeUnneededElements( array, removableElements ){ + var disjoint = [], + element, + i, + l; + + for ( i = 0, l = array.length; i < l; i++ ) { + element = array[i]; + if ( removableElements.indexOf(element) === -1 ) { + disjoint.push(element); + } + } + return disjoint; + } + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }) +/******/ ]); \ No newline at end of file diff --git a/doc/releases/0.1.0/base/webvowl/license.txt b/doc/releases/0.1.0/base/webvowl/license.txt new file mode 100644 index 0000000..008e54c --- /dev/null +++ b/doc/releases/0.1.0/base/webvowl/license.txt @@ -0,0 +1,21 @@ +The MIT License (MIT) + +Copyright (c) 2014-2019 Vincent Link, Steffen Lohmann, Eduard Marbach, Stefan Negru, Vitalis Wiens + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in +all copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN +THE SOFTWARE. diff --git a/doc/releases/0.1.0/bibliography/index.html b/doc/releases/0.1.0/bibliography/index.html new file mode 100644 index 0000000..f35bade --- /dev/null +++ b/doc/releases/0.1.0/bibliography/index.html @@ -0,0 +1,2613 @@ + + + Neuroelectrophysiology Analysis Ontology - Bibliographic References + + + + + + + + + +
    +
    +
    language en
    +

    Neuroelectrophysiology Analysis Ontology - Bibliographic References

    +

    Release: 2024-12-06

    + + +
    +
    This version:
    +
    http://purl.org/neao/0.1.0/bibliography#
    +
    Latest version:
    +
    http://purl.org/neao/bibliography#
    +
    Revision:
    +
    0.1.0
    +
    Issued on:
    +
    2024-12-06
    +
    Authors:
    +
    Cristiano Köhler, Forschungszentrum Jülich
    Michael Denker, Forschungszentrum Jülich
    + +
    License:
    https://creativecommons.org/licenses/by/4.0/ +
    + +Provenance of this page
    +
    +
    +
    +Ontology Specification Draft +
    +
    +
    + + +

    Introduction back to ToC

    +

    This module contains all individuals representing bibliographic references used throughout the Neuroelectrophysiology Analysis Ontology (NEAO).

     +
    +

    Namespace declarations

    +
    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    Table 1: Namespaces used in the document
    biro<http://purl.org/spar/biro/>
    book<https://isbndb.com/book/9789971502553#>
    dcterms<http://purl.org/dc/terms/>
    doi<https://doi.org/>
    doi1<https://doi.org/10.1016/>
    doi10<https://doi.org/10.1146/>
    doi11<https://doi.org/10.1126/>
    doi12<https://doi.org/10.1073/>
    doi13<https://doi.org/10.3389/>
    doi14<https://doi.org/10.1523/>
    doi15<https://doi.org/10.1007/978-1-4419-5675-0>
    doi16<https://doi.org/10.1214/14->
    doi17<https://doi.org/10.1162/>
    doi18<https://doi.org/10.7554/>
    doi19<https://doi.org/10.1007/978-3-642-68915-4>
    doi2<https://doi.org/10.1016/0165-1684(91)90079->
    doi20<https://doi.org/10.1098/>
    doi21<https://doi.org/10.1088/1741-2552/>
    doi22<https://doi.org/10.1002/>
    doi3<https://doi.org/10.1007/>
    doi4<https://doi.org/10.1007/978-3-540-88853-6>
    doi5<https://doi.org/10.1109/>
    doi6<https://doi.org/10.1038/>
    doi7<https://doi.org/10.1371/>
    doi8<https://doi.org/10.1103/>
    doi9<https://doi.org/10.1152/>
    neao_bib<http://purl.org/neao/bibliography#>
    owl<http://www.w3.org/2002/07/owl#>
    rdf<http://www.w3.org/1999/02/22-rdf-syntax-ns#>
    rdfs<http://www.w3.org/2000/01/rdf-schema#>
    skos<http://www.w3.org/2004/02/skos/core#>
    v54<https://proceedings.mlr.press/v54/>
    vann<http://purl.org/vocab/vann/>
    xml<http://www.w3.org/XML/1998/namespace>
    xsd<http://www.w3.org/2001/XMLSchema#>
    +
    +
    +
    + + + +

    NEAO Bibliography: Overview back to ToC

    + +This ontology has the following classes and properties. +

    Named Individuals

    +
    + + + +

    NEAO Bibliography: Description back to ToC

    + +

    The individuals defined in this module are supposed to be imported by the steps module when inserting bibliographic reference information into the classes. + +

    Each bibliography item is represented as an individual of the biro:BibliographicReference class that is related to the analysis steps (defined in the steps module) through the hasBibliographicReference annotation property. Each individual has a dcterms:bibliographicCitation property defining a string with the human-readable citation, and also a biro:references property pointing to resolvable URIs used to reach the resource.

    + + + +

    Cross-reference for NEAO Bibliography classes, object properties and data properties back to ToC

    +This section provides details for each class and property defined by NEAO Bibliography. +
    +

    Named Individuals

    + +
    +

    Aertsen et al. (1987)ni + back to ToC or Named Individual ToC + +

    +

    + IRI: http://purl.org/neao/bibliography#Aertsen1987_1

    +
    +
    belongs to
    +
    + bibliographic reference + c +
    +
    has facts
    +
    + references + op + aertsen 1 +
    +
    +
    +
    +

    Baccalá & Sameshima (2001)ni + back to ToC or Named Individual ToC + +

    +

    + IRI: http://purl.org/neao/bibliography#Baccala2001_463

    +
    +
    belongs to
    +
    + bibliographic reference + c +
    +
    has facts
    +
    + references + op + p l00007990 +
    +
    +
    +
    +

    Bartlett (1950)ni + back to ToC or Named Individual ToC + +

    +

    + IRI: http://purl.org/neao/bibliography#Bartlett1950_1

    +
    +
    belongs to
    +
    + bibliographic reference + c +
    +
    has facts
    +
    + references + op + 37.1 2.1 +
    +
    +
    +
    +

    Bokil et al. (2010)ni + back to ToC or Named Individual ToC + +

    +

    + IRI: http://purl.org/neao/bibliography#Bokil2010_146

    +
    +
    belongs to
    +
    + bibliographic reference + c +
    +
    has facts
    +
    + references + op + j.jneumeth.2010.06.020 +
    +
    +
    +
    +

    Brovelli et al. (2004)ni + back to ToC or Named Individual ToC + +

    +

    + IRI: http://purl.org/neao/bibliography#Brovelli2004_9849

    +
    +
    belongs to
    +
    + bibliographic reference + c +
    +
    has facts
    +
    + references + op + pnas.0308538101 +
    +
    +
    +
    +

    Brown et al. (2004)ni + back to ToC or Named Individual ToC + +

    +

    + IRI: http://purl.org/neao/bibliography#Brown2004_456

    +
    +
    belongs to
    +
    + bibliographic reference + c +
    +
    has facts
    +
    + references + op + nn1228 +
    +
    +
    +
    +

    Bruña & Maestú (2018)ni + back to ToC or Named Individual ToC + +

    +

    + IRI: http://purl.org/neao/bibliography#Bruna2018_056011

    +
    +
    belongs to
    +
    + bibliographic reference + c +
    +
    has facts
    +
    + references + op + aacfe4 +
    +
    +
    +
    +

    Canolty et al. (2006)ni + back to ToC or Named Individual ToC + +

    +

    + IRI: http://purl.org/neao/bibliography#Canolty2006_1626

    +
    +
    belongs to
    +
    + bibliographic reference + c +
    +
    has facts
    +
    + references + op + science.1128115 +
    +
    +
    +
    +

    Carter (1987)ni + back to ToC or Named Individual ToC + +

    +

    + IRI: http://purl.org/neao/bibliography#Carter1987_236

    +
    +
    belongs to
    +
    + bibliographic reference + c +
    +
    has facts
    +
    + references + op + p r o c.1987.13723 +
    +
    +
    +
    +

    Ciba et al. (2018)ni + back to ToC or Named Individual ToC + +

    +

    + IRI: http://purl.org/neao/bibliography#Ciba2018_136

    +
    +
    belongs to
    +
    + bibliographic reference + c +
    +
    has facts
    +
    + references + op + j.jneumeth.2017.09.008 +
    +
    +
    +
    +

    Cohen & Kohn (2011)ni + back to ToC or Named Individual ToC + +

    +

    + IRI: http://purl.org/neao/bibliography#Cohen2011_811

    +
    +
    belongs to
    +
    + bibliographic reference + c +
    +
    has facts
    +
    + references + op + nn.2842 +
    +
    +
    +
    +

    Cover & Thomas (2012)ni + back to ToC or Named Individual ToC + +

    +

    + IRI: http://purl.org/neao/bibliography#Cover2012

    +
    +
    belongs to
    +
    + bibliographic reference + c +
    +
    has facts
    +
    + references + op + 9781118585771 +
    +
    +
    +
    +

    Cowley et al. (2017)ni + back to ToC or Named Individual ToC + +

    +

    + IRI: http://purl.org/neao/bibliography#Cowley2017_242

    +
    +
    belongs to
    +
    + bibliographic reference + c +
    +
    has facts
    +
    + references + op + cowley17a.html +
    +
    +
    +
    +

    Cutts & Eglen (2014)ni + back to ToC or Named Individual ToC + +

    +

    + IRI: http://purl.org/neao/bibliography#Cutts2014_14288

    +
    +
    belongs to
    +
    + bibliographic reference + c +
    +
    has facts
    +
    + references + op + j n e u r o s c i.2767 14.2014 +
    +
    +
    +
    +

    Deger et al. (2012)ni + back to ToC or Named Individual ToC + +

    +

    + IRI: http://purl.org/neao/bibliography#Deger2012_443

    +
    +
    belongs to
    +
    + bibliographic reference + c +
    +
    has facts
    +
    + references + op + s10827 011 0362 8 +
    +
    +
    +
    +

    Dhamala et al. (2008)ni + back to ToC or Named Individual ToC + +

    +

    + IRI: http://purl.org/neao/bibliography#Dhamala2008_354

    +
    +
    belongs to
    +
    + bibliographic reference + c +
    +
    has facts
    +
    + references + op + j.neuroimage.2008.02.020 +
    +
    +
    +
    +

    Ding et al. (2006)ni + back to ToC or Named Individual ToC + +

    +

    + IRI: http://purl.org/neao/bibliography#Ding2006_0608035

    +
    +
    belongs to
    +
    + bibliographic reference + c +
    +
    has facts
    +
    + references + op + 0608035 +
    +
    +
    +
    +

    Eggermont (2010)ni + back to ToC or Named Individual ToC + +

    +

    + IRI: http://purl.org/neao/bibliography#Eggermont2010_77

    +
    +
    belongs to
    +
    + bibliographic reference + c +
    +
    has facts
    +
    + references + op + 978 1 4419 5675 0 5 +
    +
    +
    +
    +

    Ewald et al. (2012)ni + back to ToC or Named Individual ToC + +

    +

    + IRI: http://purl.org/neao/bibliography#Ewald2012_476

    +
    +
    belongs to
    +
    + bibliographic reference + c +
    +
    has facts
    +
    + references + op + j.neuroimage.2011.11.084 +
    +
    +
    +
    +

    Farge (1992)ni + back to ToC or Named Individual ToC + +

    +

    + IRI: http://purl.org/neao/bibliography#Farge1992_395

    +
    +
    belongs to
    +
    + bibliographic reference + c +
    +
    has facts
    +
    + references + op + annurev.fl.24.010192.002143 +
    +
    +
    +
    +

    Freeman & Nicholson (1975)ni + back to ToC or Named Individual ToC + +

    +

    + IRI: http://purl.org/neao/bibliography#Freeman1975_369

    +
    +
    belongs to
    +
    + bibliographic reference + c +
    +
    has facts
    +
    + references + op + jn.1975.38.2.369 +
    +
    +
    +
    +

    Fries et al. (2001)ni + back to ToC or Named Individual ToC + +

    +

    + IRI: http://purl.org/neao/bibliography#Fries2001_1560

    +
    +
    belongs to
    +
    + bibliographic reference + c +
    +
    has facts
    +
    + references + op + science.1055465 +
    +
    +
    +
    +

    Georgopoulos et al. (1983)ni + back to ToC or Named Individual ToC + +

    +

    + IRI: http://purl.org/neao/bibliography#Georgopoulos1983_327

    +
    +
    belongs to
    +
    + bibliographic reference + c +
    +
    has facts
    +
    + references + op + 978 3 642 68915 4 34 +
    +
    +
    +
    +

    Geweke (1982)ni + back to ToC or Named Individual ToC + +

    +

    + IRI: http://purl.org/neao/bibliography#Geweke1982_304

    +
    +
    belongs to
    +
    + bibliographic reference + c +
    +
    has facts
    +
    + references + op + 01621459.1982.10477803 +
    +
    +
    +
    +

    Grün (2009)ni + back to ToC or Named Individual ToC + +

    +

    + IRI: http://purl.org/neao/bibliography#Gruen2009_1126

    +
    +
    belongs to
    +
    + bibliographic reference + c +
    +
    has facts
    +
    + references + op + jn.00093.2008 +
    +
    +
    +
    +

    Grün et al. (1999)ni + back to ToC or Named Individual ToC + +

    +

    + IRI: http://purl.org/neao/bibliography#Gruen1999_67

    +
    +
    belongs to
    +
    + bibliographic reference + c +
    +
    has facts
    +
    + references + op + s0165 0270(99)00126 0 +
    +
    +
    +
    +

    Grün et al. (2002a)ni + back to ToC or Named Individual ToC + +

    +

    + IRI: http://purl.org/neao/bibliography#Gruen2002_43

    +
    +
    belongs to
    +
    + bibliographic reference + c +
    +
    has facts
    +
    + references + op + 089976602753284455 +
    +
    +
    +
    +

    Grün et al. (2002b)ni + back to ToC or Named Individual ToC + +

    +

    + IRI: http://purl.org/neao/bibliography#Gruen2002_81

    +
    +
    belongs to
    +
    + bibliographic reference + c +
    +
    has facts
    +
    + references + op + 089976602753284464 +
    +
    +
    +
    +

    Grün et al. (2003)ni + back to ToC or Named Individual ToC + +

    +

    + IRI: http://purl.org/neao/bibliography#Gruen2003_335

    +
    +
    belongs to
    +
    + bibliographic reference + c +
    +
    has facts
    +
    + references + op + s00422 002 0386 2 +
    +
    +
    +
    +

    Grün et al. (2007)ni + back to ToC or Named Individual ToC + +

    +

    + IRI: http://purl.org/neao/bibliography#Gruen2007_96

    +
    +
    belongs to
    +
    + bibliographic reference + c +
    +
    has facts
    +
    + references + op + 978 3 540 88853 6 8 +
    +
    +
    +
    +

    Hafner & Herwartz (2008)ni + back to ToC or Named Individual ToC + +

    +

    + IRI: http://purl.org/neao/bibliography#Hafner2008_215

    +
    +
    belongs to
    +
    + bibliographic reference + c +
    +
    has facts
    +
    + references + op + 27715168 +
    +
    +
    +
    +

    Hipp et al. (2012)ni + back to ToC or Named Individual ToC + +

    +

    + IRI: http://purl.org/neao/bibliography#Hipp2012_884

    +
    +
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    Acknowledgments back to ToC

    +

    This work was performed as part of the Helmholtz School for Data Science in Life, Earth and Energy (HDS-LEE) and received funding from the Helmholtz Association of German Research Centres. This project has received funding from the European Union’s Horizon 2020 Framework Programme for Research and Innovation under Specific Grant Agreement No. 945539 (Human Brain Project SGA3), the European Union’s Horizon Europe Programme under the Specific Grant Agreement No. 101147319 (EBRAINS 2.0 Project), the Ministry of Culture and Science of the State of North Rhine-Westphalia, Germany (NRW-network "iBehave", grant number: NW21-049), and the Joint Lab "Supercomputing and Modeling for the Human Brain."

    + +

    The authors would like to thank Silvio Peroni for developing LODE, a Live OWL Documentation Environment, which is used for representing the Cross Referencing Section of this document and Daniel Garijo for developing Widoco, the program used to create the template used in this documentation.

     +
    + + +
    + + + + + + + diff --git a/doc/releases/0.1.0/bibliography/provenance/provenance-en.html b/doc/releases/0.1.0/bibliography/provenance/provenance-en.html new file mode 100644 index 0000000..0ecafef --- /dev/null +++ b/doc/releases/0.1.0/bibliography/provenance/provenance-en.html @@ -0,0 +1,18 @@ + + + + + + + + +
    +

    Provenance for Neuroelectrophysiology Analysis Ontology - Bibliographic References Documentation (http://purl.org/neao/0.1.0/bibliography#)

    +
      +
    • Ontology created by: Cristiano Köhler (Forschungszentrum Jülich), Michael Denker (Forschungszentrum Jülich)
    • http://purl.org/neao/0.1.0/bibliography# is a specialization of the generic URI http://purl.org/neao/bibliography#
      • +
    • The ontology documentation was the result of using the Widoco tool (which itself uses LODE for generating the crossreference section).
      • +
    • The documentation was generated at 2024-12-06
    +
    +

    back to documentation. TTL format

    + + \ No newline at end of file diff --git a/doc/releases/0.1.0/bibliography/provenance/provenance-en.ttl b/doc/releases/0.1.0/bibliography/provenance/provenance-en.ttl new file mode 100644 index 0000000..c7813d8 --- /dev/null +++ b/doc/releases/0.1.0/bibliography/provenance/provenance-en.ttl @@ -0,0 +1,14 @@ +@prefix prov: . +@prefix dc: . +@prefix foaf: . +@prefix : <> . + a prov:Entity; + dc:title "Neuroelectrophysiology Analysis Ontology - Bibliographic References"; + prov:wasAttributedTo ; + dc:creator ; + prov:wasAttributedTo ; + dc:creator ; + prov:wasAttributedTo ,; + prov:specializationOf ; + prov:wasGeneratedAt "2024-12-06"; +. diff --git a/doc/releases/0.1.0/bibliography/resources/extra.css b/doc/releases/0.1.0/bibliography/resources/extra.css new file mode 100644 index 0000000..16689d3 --- /dev/null +++ b/doc/releases/0.1.0/bibliography/resources/extra.css @@ -0,0 +1,124 @@ +body { + text-align: justify; +} + +h1 { + line-height: 110%; +} + +.hlist { + border: 1px solid 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r=n[1]||n[2]||"";if(!r||""===u||this.rules.inline.punctuation.exec(u)){var i=n[0].length-1,s=i,l=0,a="*"===n[0][0]?this.rules.inline.emStrong.rDelimAst:this.rules.inline.emStrong.rDelimUnd;for(a.lastIndex=0,t=t.slice(-1*e.length+i);null!=(n=a.exec(t));)if(o=n[1]||n[2]||n[3]||n[4]||n[5]||n[6])if(o=o.length,n[3]||n[4])s+=o;else if((n[5]||n[6])&&i%3&&!((i+o)%3))l+=o;else if(!(0<(s-=o))){var o=Math.min(o,o+s+l);if(Math.min(i,o)%2)return D=e.slice(1,i+n.index+o),{type:"em",raw:e.slice(0,i+n.index+o+1),text:D,tokens:this.lexer.inlineTokens(D,[])};var D=e.slice(2,i+n.index+o-1);return{type:"strong",raw:e.slice(0,i+n.index+o+1),text:D,tokens:this.lexer.inlineTokens(D,[])}}}}},t.codespan=function(e){var t,u,n,e=this.rules.inline.code.exec(e);if(e)return n=e[2].replace(/\n/g," "),t=/[^ ]/.test(n),u=/^ /.test(n)&&/ 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    +
    + +

    Neuroelectrophysiology Analysis Ontology - Data

    +

    Release: 2024-12-06

    + + +
    +
    This version:
    +
    http://purl.org/neao/0.1.0/data#
    +
    Latest version:
    +
    http://purl.org/neao/data#
    +
    Revision:
    +
    0.1.0
    +
    Issued on:
    +
    2024-12-06
    +
    Authors:
    +
    Cristiano Köhler, Forschungszentrum Jülich
    Michael Denker, Forschungszentrum Jülich
    + +
    License:
    https://creativecommons.org/licenses/by/4.0/ +
    Visualization:
    Visualize with WebVowl
    +
    + +Provenance of this page
    +
    +
    +
    +Ontology Specification Draft +
    +
    +
    + + +

    Introduction back to ToC

    +

    This module in the Neuroelectrophysiology Analysis Ontology (NEAO) contains classes that represent data entities in the analysis of neuroelectrophysiology data.

     +
    +

    Namespace declarations

    +
    + + + + + + + + + + + + + + +
    Table 1: Namespaces used in the document
    dcterms<http://purl.org/dc/terms/>
    neao_base<http://purl.org/neao/base#>
    neao_data<http://purl.org/neao/data#>
    owl<http://www.w3.org/2002/07/owl#>
    rdf<http://www.w3.org/1999/02/22-rdf-syntax-ns#>
    rdfs<http://www.w3.org/2000/01/rdf-schema#>
    skos<http://www.w3.org/2004/02/skos/core#>
    vann<http://purl.org/vocab/vann/>
    xml<http://www.w3.org/XML/1998/namespace>
    xsd<http://www.w3.org/2001/XMLSchema#>
    +
    +
    +
    + + + +

    NEAO Data: Overview back to ToC

    + +This ontology has the following classes and properties. +

    Classes

    +

    Data Properties

    +
    + + + +

    NEAO Data: Description back to ToC

    + +

    The classes in this module are subclasses of the Data base class (defined in the base module), and are associated with the distinct steps throughout the analysis (defined in the steps module) by the hasInput and hasOutput object properties.

    + +

    Additional information on the data entity can be described by using additional classes and properties defined in the base module:

    + +
      +

    • The electrophysiology recording source associated with the data can be defined with the hasSource object property that points to individuals of the ElectrophysiologySignalSource class.

      • +

    • In addition, information on the structure of the data (e.g., matrix, array) can be provided with the isRepresentedAs object property that points to individuals of the DataRepresentation class.

      • +
    + +

    The objective of NEAO is not to model the sources and formats of the data, but these two classes above can be used as abstractions to align other ontologies that are defined with that purpose.

    + +

    Finally, several data properties are also defined to provide extended information on the data entity (e.g., isNormalized or isArtificial). These properties can be used to define additional semantic groupings to make inferences on the data and analysis (e.g., artificial data is defined by the ArtificialData class).

    + + + +

    Cross-reference for NEAO Data classes, object properties and data properties back to ToC

    +This section provides details for each class and property defined by NEAO Data. +
    +

    Classes

    + +
    +

    analytic signalc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#AnalyticSignal

    +
    + The analytic signal obtained from a time series using the Hilbert transform. +
    +
    +
    has super-classes
    +
    + time series + c +
    +
    +
    +
    +

    angular mean of spike phasesc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#AngularMeanSpikePhases

    +
    + The computed angular mean of the spike phases. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    artificial datac + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#ArtificialData

    +
    + Data that is generated programmatically rather than obtained from experimental recordings. +
    +
    +
    is equivalent to
    +
    + is artificial + dp + value true
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    ASSET analysis matrixc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#ASSETAnalysisMatrix

    +
    + Data that contains a matrix computed by one of the ASSET analysis substeps, as part of the execution of the ASSET analysis for the detection of neuronal activity patterns. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    has sub-classes
    +
    + ASSET cluster matrix + c, ASSET intersection matrix + c, ASSET joint probability matrix + c, ASSET mask matrix + c, ASSET probability matrix + c +
    +
    +
    +
    +

    ASSET cluster matrixc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#ASSETClusterMatrix

    +
    + The cluster matrix (CMAT) computed in the ASSET analysis. +
    +
    +
    has super-classes
    +
    + ASSET analysis matrix + c +
    +
    +
    +
    +

    ASSET intersection matrixc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#ASSETIntersectionMatrix

    +
    + The intersection matrix (IMAT) computed in the ASSET analysis. +
    +
    +
    has super-classes
    +
    + ASSET analysis matrix + c +
    +
    +
    +
    +

    ASSET joint probability matrixc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#ASSETJointProbabilityMatrix

    +
    + The joint probability matrix (JMAT) computed in the ASSET analysis. +
    +
    +
    has super-classes
    +
    + ASSET analysis matrix + c +
    +
    +
    +
    +

    ASSET mask matrixc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#ASSETMaskMatrix

    +
    + The mask matrix (MMAT) computed in the ASSET analysis. +
    +
    +
    has super-classes
    +
    + ASSET analysis matrix + c +
    +
    +
    +
    +

    ASSET patternc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#ASSETPattern

    +
    + A neuronal activity pattern obtained by the ASSET analysis. The ASSET patterns are the output of the last substep of the ASSET analysis that identifies the neurons present in each repeated sequence, based on the diagonal structures in the cluster matrix. +
    +
    +
    has super-classes
    +
    + neuronal activity pattern + c +
    +
    +
    +
    +

    ASSET probability matrixc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#ASSETProbabilityMatrix

    +
    + The probability matrix (PMAT) computed in the ASSET analysis. +
    +
    +
    has super-classes
    +
    + ASSET analysis matrix + c +
    +
    +
    +
    +

    autocorrelation functionc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#AutocorrelationFunction

    +
    + The computed estimator of the autocorrelation function. +
    +
    +
    has super-classes
    +
    + autocorrelation measure + c +
    +
    +
    +
    +

    autocorrelation measurec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#AutocorrelationMeasure

    +
    + Data that contains a measure of autocorrelation. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    has sub-classes
    +
    + autocorrelation function + c, spike train autocorrelation histogram + c +
    +
    +
    +
    +

    binned spike trainc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#BinnedSpikeTrain

    +
    + The output of applying binning to the input spike train data. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    canonical coherencec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#CanonicalCoherence

    +
    + The computed canonical coherence (caCOH). +
    +
    +
    has super-classes
    +
    + coherence measure + c +
    +
    +
    +
    +

    Cell Assembly Detection patternc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#CellAssemblyDetectionPattern

    +
    + A neuronal activity pattern obtained by the Cell Assembly Detection (CAD) analysis. +
    +
    +
    has super-classes
    +
    + neuronal activity pattern + c +
    +
    +
    +
    +

    change pointc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#ChangePoint

    +
    + A change point identified by the rate change detection multiple filter test. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    coefficient of variationc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#CV

    +
    + The computed coefficient of variation (CV). +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    coefficient of variation of the interspike intervalsc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#CVInterspikeIntervals

    +
    + The computed coefficient of variation (CV) of the interspike intervals (ISIs). +
    +
    +
    has super-classes
    +
    + interspike interval variability measure + c +
    +
    +
    +
    +

    coherencec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#Coherence

    +
    + The computed magnitude squared coherence. This is the typical output of a computation estimating coherence, and it is frequently referred as just coherence. +
    +
    +
    has super-classes
    +
    + coherence measure + c +
    +
    +
    +
    +

    coherence measurec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#CoherenceMeasure

    +
    + Data that contains a measure of coherence. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    has sub-classes
    +
    + canonical coherence + c, coherence + c, magnitude coherence + c, partial coherence + c +
    +
    +
    +
    +

    coherencyc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#Coherency

    +
    + The computed coherency. +
    +
    +
    has super-classes
    +
    + coherency measure + c +
    +
    +
    +
    +

    coherency measurec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#CoherencyMeasure

    +
    + Data that contains a measure of coherency. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    has sub-classes
    +
    + coherency + c, imaginary coherency + c, maximized imaginary coherency + c +
    +
    +
    +
    +

    complexity distributionc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#ComplexityDistribution

    +
    + The computed complexity distribution across the spike trains. +
    +
    +
    has super-classes
    +
    + spike train synchrony measure + c +
    +
    +
    +
    +

    conditional Granger causalityc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#ConditionalGrangerCausality

    +
    + The computed conditional Granger causality. +
    +
    +
    has super-classes
    +
    + Granger causality measure + c +
    +
    +
    +
    +

    confidence intervalc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#ConfidenceInterval

    +
    + The computed confidence interval (CI), with the lower and upper limits. +
    +
    +
    has super-classes
    +
    + confidence interval measure + c +
    +
    +
    +
    +

    confidence interval measurec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#ConfidenceIntervalMeasure

    +
    + Data that contains the description of a confidence interval (CI). +
    +
    +
    has super-classes
    +
    + data + c +
    +
    has sub-classes
    +
    + confidence interval + c, lower limit of confidence interval + c, upper limit of confidence interval + c +
    +
    +
    +
    +

    corrected imaginary phase locking valuec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#CorrectedImaginaryPhaseLockingValue

    +
    + The computed corrected imaginary phase locking value (ciPLV). +
    +
    +
    has super-classes
    +
    + phase locking value measure + c +
    +
    +
    +
    +

    correlation measurec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#CorrelationMeasure

    +
    + Data that contains a measure of correlation. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    has sub-classes
    +
    + correlation measure + c, orthogonalized power envelope correlation + c +
    +
    +
    +
    +

    correlation measurec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#SpikeTrainCorrelationMeasure

    +
    + Data that contains a measure estimating the correlation between spike trains. +
    +
    +
    has super-classes
    +
    + correlation measure + c +
    +
    has sub-classes
    +
    + noise correlations + c, spike time tiling coefficient + c, spike train Pearson correlation coefficient + c +
    +
    +
    +
    +

    covariancec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#Covariance

    +
    + The computed covariance values between the inputs. +
    +
    +
    has super-classes
    +
    + covariance measure + c +
    +
    has sub-classes
    +
    + regularized covariance + c +
    +
    +
    +
    +

    covariance measurec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#CovarianceMeasure

    +
    + Data that contains a measure of covariance. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    has sub-classes
    +
    + covariance + c, noise covariance + c +
    +
    +
    +
    +

    cross power spectral densityc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#CrossPowerSpectralDensity

    +
    + The computed cross power spectral density (CPSD). +
    +
    +
    has super-classes
    +
    + spectral density + c +
    +
    +
    +
    +

    cross-correlation functionc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#CrossCorrelationFunction

    +
    + The computed estimator of the cross-correlation function. +
    +
    +
    has super-classes
    +
    + cross-correlation measure + c +
    +
    +
    +
    +

    cross-correlation measurec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#CrossCorrelationMeasure

    +
    + Data that contains a measure of cross-correlation. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    has sub-classes
    +
    + cross-correlation function + c, spike train cross-correlation histogram + c +
    +
    +
    +
    +

    cross-spectrogramc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#CrossSpectrogram

    +
    + The computed cross-spectrogram. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    CuBIC analysis resultc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#CubicAnalysisResult

    +
    + The result of the CuBIC analysis. +
    +
    +
    has super-classes
    +
    + spike train synchrony measure + c +
    +
    +
    +
    +

    current source densityc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#CurrentSourceDensity

    +
    + The profile of current densities estimated by a current source density analysis. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    CV2c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#CV2

    +
    + The computed CV2 measure. +
    +
    +
    has super-classes
    +
    + interspike interval variability measure + c +
    +
    +
    +
    +

    debiased squared weighted phase lag indexc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#DebiasedSquaredWeightedPhaseLagIndex

    +
    + The computed debiased squared weighted phase lag index (WPLI). +
    +
    +
    has super-classes
    +
    + phase lag index measure + c +
    +
    is disjoint with
    +
    + directed phase lag index + c, phase lag index + c, unbiased squared phase lag index + c, weighted phase lag index + c +
    +
    +
    +
    +

    dimensionality reduction outputc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#DimensionalityReductionOutput

    +
    + Data that contains an output of applying a dimensionality reduction transformation to the input data. +
    +
    +
    is equivalent to
    +
    + is dimensionality reduction + dp + value true
    +
    has super-classes
    +
    + data + c +
    +
    has sub-classes
    +
    + Fisher linear discriminant + c, distance covariance dimension + c, principal component + c, tensor component + c +
    +
    +
    +
    +

    directed phase lag indexc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#DirectedPhaseLagIndex

    +
    + The computed directed phase lag index (DPLI). +
    +
    +
    has super-classes
    +
    + phase lag index measure + c +
    +
    is disjoint with
    +
    + debiased squared weighted phase lag index + c, phase lag index + c, unbiased squared phase lag index + c, weighted phase lag index + c +
    +
    +
    +
    +

    directed transfer functionc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#DirectedTransferFunction

    +
    + The computed directed transfer function (DTF). +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    directional Granger causalityc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#DirectionalGrangerCausality

    +
    + The computed directional Granger causality from one input to the other. +
    +
    +
    has super-classes
    +
    + Granger causality measure + c +
    +
    +
    +
    +

    discrete Fourier transformc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#DiscreteFourierTransform

    +
    + The complex sinusoid coefficients obtained by applying the Discrete Fourier Transform (DFT) to the input data (e.g., using the FFT algorithm). +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    distance covariance dimensionc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#DistanceCovarianceDimension

    +
    + A dimension identified by applying distance covariance analysis (DCA) to the input data. +
    +
    +
    has super-classes
    +
    + dimensionality reduction output + c +
    +
    +
    +
    +

    epochc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#Epoch

    +
    + Data that represents a finite time interval (window). For example, the interval between the start and end of a behavioral trial in the recording session. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    eventc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#Event

    +
    + Data that contains the time(s) when an event of interest occurred (e.g., a certain behavior or stimulus in an experimental trial). +
    +
    +
    has super-classes
    +
    + data + c +
    +
    is disjoint with
    +
    + spike train + c, spike train surrogate + c, time series + c +
    +
    +
    +
    +

    event-related potentialc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#EventRelatedPotential

    +
    + The computed event-related potential (ERP). +
    +
    +
    has super-classes
    +
    + data + c +
    +
    has sub-classes
    +
    + evoked potential + c +
    +
    +
    +
    +

    event-triggered averagec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#EventTriggeredAverage

    +
    + The computed event-triggered average. +
    +
    +
    has super-classes
    +
    + triggered average measure + c +
    +
    +
    +
    +

    evoked potentialc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#EvokedPotential

    +
    + The computed evoked potential (EP). +
    +
    +
    has super-classes
    +
    + event-related potential + c +
    +
    +
    +
    +

    firing ratec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#FiringRate

    +
    + The computed firing rate. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    has sub-classes
    +
    + instantaneous firing rate + c, mean firing rate + c +
    +
    +
    +
    +

    Fisher linear discriminantc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#FisherLinearDiscriminant

    +
    + A Fisher linear discriminant obtained by applying linear discrimination analysis (LDA) to the input data. +
    +
    +
    has super-classes
    +
    + dimensionality reduction output + c +
    +
    +
    +
    +

    Granger causality measurec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#GrangerCausalityMeasure

    +
    + Data that contains a measure of Granger causality. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    has sub-classes
    +
    + Granger total interdependence + c, conditional Granger causality + c, directional Granger causality + c, instantaneous Granger causality + c +
    +
    +
    +
    +

    Granger total interdependencec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#GrangerTotalInterdependence

    +
    + The computed total interdependence in the Granger causality analysis. +
    +
    +
    has super-classes
    +
    + Granger causality measure + c +
    +
    +
    +
    +

    imaginary coherencyc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#ImaginaryCoherency

    +
    + The computed imaginary part of the coherency. +
    +
    +
    has super-classes
    +
    + coherency measure + c +
    +
    +
    +
    +

    independent componentc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#IndependentComponent

    +
    + Data that contains an independent component produced by applying independent component analysis (ICA) to the input data. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    instantaneous firing ratec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#InstantaneousFiringRate

    +
    + The computed instantaneous firing rate. +
    +
    +
    has super-classes
    +
    + firing rate + c +
    +
    +
    +
    +

    instantaneous Granger causalityc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#InstantaneousGrangerCausality

    +
    + The computed instantaneous Granger causality. +
    +
    +
    has super-classes
    +
    + Granger causality measure + c +
    +
    +
    +
    +

    interquartile rangec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#InterquartileRange

    +
    + The computed interquartile range, with the difference between the 75th and 25th percentile values. +
    +
    +
    has super-classes
    +
    + interquartile range measure + c +
    +
    is disjoint with
    +
    + lower limit of interquartile range + c, upper limit of interquartile range + c +
    +
    +
    +
    +

    interquartile range measurec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#InterquartileRangeMeasure

    +
    + Data that contains the description of an interquartile range (IQR). +
    +
    +
    has super-classes
    +
    + data + c +
    +
    has sub-classes
    +
    + interquartile range + c, lower limit of interquartile range + c, upper limit of interquartile range + c +
    +
    +
    +
    +

    interspike interval histogramc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#InterspikeIntervalHistogram

    +
    + The computed interspike interval histogram (ISIH). +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    interspike interval variability measurec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#InterspikeIntervalVariabilityMeasure

    +
    + Data that contains a measure describing the variability of the interspike intervals. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    has sub-classes
    +
    + CV2 + c, LV + c, LvR + c, coefficient of variation of the interspike intervals + c +
    +
    +
    +
    +

    interspike intervalsc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#InterspikeIntervals

    +
    + The computed interspike intervals (ISIs). +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    ISI-distancec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#ISIDistance

    +
    + The computed ISI-distance. +
    +
    +
    has super-classes
    +
    + spike train distance + c +
    +
    +
    +
    +

    joint peristimulus time histogram matrixc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#JointPeristimulusTimeHistogramMatrix

    +
    + The computed joint peristimulus time histogram (JPSTH) matrix. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    lower limit of confidence intervalc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#ConfidenceIntervalLowerLimit

    +
    + The lower limit value of the computed confidence interval. +
    +
    +
    has super-classes
    +
    + confidence interval measure + c +
    +
    +
    +
    +

    lower limit of interquartile rangec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#InterquartileRangeLowerLimit

    +
    + The lower limit of the computed interquartile range, corresponding to the 25th percentile. +
    +
    +
    has super-classes
    +
    + interquartile range measure + c +
    +
    is disjoint with
    +
    + interquartile range + c, upper limit of interquartile range + c +
    +
    +
    +
    +

    LVc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#LV

    +
    + The computed local variation (LV) measure. +
    +
    +
    has super-classes
    +
    + interspike interval variability measure + c +
    +
    +
    +
    +

    LvRc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#LVR

    +
    + The computed revised local variation (LvR) measure. +
    +
    +
    has super-classes
    +
    + interspike interval variability measure + c +
    +
    +
    +
    +

    magnitude coherencec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#MagnitudeCoherence

    +
    + The computed magnitude coherence. +
    +
    +
    has super-classes
    +
    + coherence measure + c +
    +
    +
    +
    +

    maximized imaginary coherencyc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#MaximizedImaginaryCoherency

    +
    + The computed maximized imaginary coherency (MIC). +
    +
    +
    has super-classes
    +
    + coherency measure + c +
    +
    +
    +
    +

    meanc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#Mean

    +
    + The computed mean. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    mean firing ratec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#MeanFiringRate

    +
    + The computed mean firing rate. +
    +
    +
    has super-classes
    +
    + firing rate + c +
    +
    +
    +
    +

    mean phase vectorc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#MeanPhaseVector

    +
    + The computed mean phase vector (i.e., the angle and length). +
    +
    +
    has super-classes
    +
    + mean phase vector measure + c +
    +
    is disjoint with
    +
    + mean phase vector angle + c, mean phase vector length + c +
    +
    +
    +
    +

    mean phase vector anglec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#MeanPhaseVectorAngle

    +
    + The angle of the computed mean phase vector. +
    +
    +
    has super-classes
    +
    + mean phase vector measure + c +
    +
    is disjoint with
    +
    + mean phase vector + c, mean phase vector length + c +
    +
    +
    +
    +

    mean phase vector lengthc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#MeanPhaseVectorLength

    +
    + The length of the computed mean phase vector. +
    +
    +
    has super-classes
    +
    + mean phase vector measure + c +
    +
    is disjoint with
    +
    + mean phase vector + c, mean phase vector angle + c +
    +
    +
    +
    +

    mean phase vector measurec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#MeanPhaseVectorMeasure

    +
    + Data that contains the description or elements of the mean phase vector. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    has sub-classes
    +
    + mean phase vector + c, mean phase vector angle + c, mean phase vector length + c +
    +
    +
    +
    +

    mean vector lengthc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#MeanVectorLength

    +
    + The computed mean vector length (MVL). +
    +
    +
    has super-classes
    +
    + phase amplitude coupling measure + c +
    +
    +
    +
    +

    medianc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#Median

    +
    + The computed median. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    modulation indexc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#ModulationIndex

    +
    + The computed modulation index (MI). +
    +
    +
    has super-classes
    +
    + phase amplitude coupling measure + c +
    +
    +
    +
    +

    Morlet waveletc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#MorletWavelet

    +
    + Data that contains the generated Morlet wavelet values for a sequence of time points. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    multivariate interaction measurec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#MultivariateInteractionMeasure

    +
    + The computed multivariate interaction measure (MIM). +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    mutual informationc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#MutualInformation

    +
    + The computed mutual information (MI). +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    neural trajectoryc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#NeuralTrajectory

    +
    + A neural trajectory obtained by applying Gaussian process factor analysis (GPFA) to the input data containing multitrial spiking activity of a neuronal population. +
    +
    +
    has super-classes
    +
    + time series + c +
    +
    +
    +
    +

    neuronal activity patternc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#NeuronalActivityPattern

    +
    + Data that contains the description of a neuronal activity pattern, which is obtained from a neuronal activity pattern detection analysis. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    has sub-classes
    +
    + ASSET pattern + c, Cell Assembly Detection pattern + c, SPADE pattern + c, Unitary Event pattern + c +
    +
    +
    +
    +

    neuronal population vectorc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#NeuronalPopulationVector

    +
    + The computed neuronal population vector. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    noise correlationsc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#NoiseCorrelations

    +
    + The computed noise correlations (NC). +
    +
    +
    has super-classes
    +
    + correlation measure + c +
    +
    +
    +
    +

    noise covariancec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#NoiseCovariance

    +
    + The computed noise covariance. +
    +
    +
    has super-classes
    +
    + covariance measure + c +
    +
    +
    +
    +

    orthogonalized power envelope correlationc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#OrthogonalizedPowerEnvelopeCorrelation

    +
    + The computed orthogonalized power envelope correlation. +
    +
    +
    has super-classes
    +
    + correlation measure + c +
    +
    +
    +
    +

    pairwise phase consistencyc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#PairwisePhaseConsistency

    +
    + The computed pairwise phase consistency (PPC) measure. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    partial coherencec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#PartialCoherence

    +
    + The computed partial coherence. +
    +
    +
    has super-classes
    +
    + coherence measure + c +
    +
    +
    +
    +

    partial directed coherencec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#PartialDirectedCoherence

    +
    + The computed partial directed coherence (PDC). +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    peristimulus coincidence histogramc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#PeristimulusCoincidenceHistogram

    +
    + The computed peristimulus coincidence histogram. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    peristimulus time histogramc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#PeristimulusTimeHistogram

    +
    + The computed peristimulus time histogram (PSTH). The stimulus or event of interest can occur at any time point within the interval analyzed. However, if the histogram represents the neuronal activity after the stimulus presentation or event occurrence, this can be referred as post-stimulus time histogram. Conversely, if the histogram shows the activity of the neuron before the stimulus presentation or event, this can be referred as prestimulus time histogram. Finally, if the histogram considers a behavioral event (or an event that is not an externally presented stimulus), the histogram can be referred to as perievent time histogram (PETH). +
    +
    +
    has super-classes
    +
    + time histogram + c +
    +
    +
    +
    +

    phase amplitude coupling measurec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#PhaseAmplitudeCouplingMeasure

    +
    + Data that contains a measure of phase-amplitude coupling (PAC). +
    +
    +
    has super-classes
    +
    + data + c +
    +
    has sub-classes
    +
    + mean vector length + c, modulation index + c +
    +
    +
    +
    +

    phase anglesc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#PhaseAngles

    +
    + A measure of phase defining the angle on the unit circle that corresponds to the current position within the waveform's cycle. The range of angles in a full cycle is from 0 to 2*pi radians or 0 to 360 degrees. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    phase lag indexc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#PhaseLagIndex

    +
    + The computed phase lag index (PLI). +
    +
    +
    has super-classes
    +
    + phase lag index measure + c +
    +
    is disjoint with
    +
    + debiased squared weighted phase lag index + c, directed phase lag index + c, unbiased squared phase lag index + c, weighted phase lag index + c +
    +
    +
    +
    +

    phase lag index measurec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#PhaseLagIndexMeasure

    +
    + Data that contains a measure computed by a phase-lag index analysis. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    has sub-classes
    +
    + debiased squared weighted phase lag index + c, directed phase lag index + c, phase lag index + c, unbiased squared phase lag index + c, weighted phase lag index + c +
    +
    +
    +
    +

    phase locking valuec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#PhaseLockingValue

    +
    + The computed phase locking value (PLV). +
    +
    +
    has super-classes
    +
    + phase locking value measure + c +
    +
    +
    +
    +

    phase locking value measurec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#PhaseLockingValueMeasure

    +
    + Data that contains a phase locking value (PLV) measure. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    has sub-classes
    +
    + corrected imaginary phase locking value + c, phase locking value + c +
    +
    +
    +
    +

    phase slope indexc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#PhaseSlopeIndex

    +
    + The computed phase slope index (PSI). +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    plotc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#Plot

    +
    + A graphical representation of data values. It is used to visually communicate quantitative information, providing intuitive insights that can complement numerical analysis. It is often produced by later steps in the analysis after the computation of measures, to provide the visual representation of the results. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    population histogramc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#PopulationHistogram

    +
    + The computed population histogram. +
    +
    +
    has super-classes
    +
    + time histogram + c +
    +
    +
    +
    +

    power spectral densityc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#PowerSpectralDensity

    +
    + The computed power spectral density (PSD). +
    +
    +
    has super-classes
    +
    + spectral density + c +
    +
    +
    +
    +

    principal componentc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#PrincipalComponent

    +
    + A principal component obtained by applying principal component analysis (PCA) to the input data. +
    +
    +
    has super-classes
    +
    + dimensionality reduction output + c +
    +
    +
    +
    +

    rectified area under the curvec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#RectifiedAreaUnderCurve

    +
    + The computed rectified area under the curve (RAUC). +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    regularized covariancec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#RegularizedCovariance

    +
    + The covariance values computed with regularization techniques for numerical stability. +
    +
    +
    has super-classes
    +
    + covariance + c +
    +
    +
    +
    +

    short-time Fourier transformc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#ShortTimeFourierTransform

    +
    + The complex sinusoid coefficients obtained by applying the short-time Fourier transform (STFT) to the input data. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    SPADE patternc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#SPADEPattern

    +
    + A neuronal activity pattern obtained by the Spatio-temporal PAttern Detection and Evaluation (SPADE) analysis. +
    +
    +
    has super-classes
    +
    + neuronal activity pattern + c +
    +
    +
    +
    +

    spectral densityc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#SpectralDensity

    +
    + Data that contains the density of a measure of the input(s) over the frequency spectrum. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    has sub-classes
    +
    + cross power spectral density + c, power spectral density + c +
    +
    +
    +
    +

    spectrogramc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#Spectrogram

    +
    + The computed spectrogram. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    SPIKE distancec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#SPIKEDistance

    +
    + The computed SPIKE distance. +
    +
    +
    has super-classes
    +
    + spike train distance + c +
    +
    +
    +
    +

    SPIKE synchronizationc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#SPIKESynchronization

    +
    + The computed SPIKE synchronization distance. +
    +
    +
    has super-classes
    +
    + spike train distance + c +
    +
    +
    +
    +

    spike time tiling coefficientc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#SpikeTimeTilingCoefficient

    +
    + The computed spike time tiling coefficient (STTC). +
    +
    +
    has super-classes
    +
    + correlation measure + c +
    +
    +
    +
    +

    spike trainc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#SpikeTrain

    +
    + Data that contains the sequence of time points when an action potential (spike) occurs. A spike train can be obtained by electrophysiological recordings from the neural tissue (i.e., the data contains the times when spikes occur naturally in response to various stimuli or during spontaneous activity) or artificially-generated using specific statistical procedures or simulations of neuronal activity. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    is disjoint with
    +
    + event + c, spike train surrogate + c, time series + c +
    +
    +
    +
    +

    spike train autocorrelation histogramc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#SpikeTrainAutocorrelationHistogram

    +
    + The computed spike train autocorrelation histogram. +
    +
    +
    has super-classes
    +
    + autocorrelation measure + c +
    +
    +
    +
    +

    spike train autocorrelation time scalec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#SpikeTrainAutocorrelationTimeScale

    +
    + The computed spike train autocorrelation time scale. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    spike train cross-correlation histogramc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#SpikeTrainCrossCorrelationHistogram

    +
    + The computed spike train cross-correlation histogram. +
    +
    +
    has super-classes
    +
    + cross-correlation measure + c +
    +
    +
    +
    +

    spike train distancec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#SpikeTrainDistance

    +
    + Data that contains a spike train distance measure. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    has sub-classes
    +
    + ISI-distance + c, SPIKE distance + c, SPIKE synchronization + c, Victor-Purpura distance + c, van Rossum distance + c +
    +
    +
    +
    +

    spike train Fano factorc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#SpikeTrainFanoFactor

    +
    + The computed Fano factor (FF) for a set of input spike trains. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    spike train Pearson correlation coefficientc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#SpikeTrainPearsonCorrelationCoefficient

    +
    + The computed Pearson correlation coefficient between two spike trains. +
    +
    +
    has super-classes
    +
    + correlation measure + c +
    +
    +
    +
    +

    spike train surrogatec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#SpikeTrainSurrogate

    +
    + Data that contains a spike train surrogate. It is generated from spike train inputs using distinct methods to alter the original spike times. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    is disjoint with
    +
    + event + c, spike train + c, time series + c +
    +
    +
    +
    +

    spike train synchrony measurec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#SpikeTrainSynchronyMeasure

    +
    + Data that contains a measure describing synchronization in two or more spike trains containing the activity of different neurons. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    has sub-classes
    +
    + CuBIC analysis result + c, Spike-contrast + c, complexity distribution + c +
    +
    +
    +
    +

    spike train time histogramc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#SpikeTrainTimeHistogram

    +
    + The computed spike train time histogram. +
    +
    +
    has super-classes
    +
    + time histogram + c +
    +
    +
    +
    +

    spike waveformc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#SpikeWaveform

    +
    + Data that contains the characteristic voltage change over time observed in the electrical recording of a neuron's action potential (spike). This waveform represents the rapid depolarization and repolarization of the neuron's membrane potential during the action potential. The data is acquired in a finite number of samples that correspond to a time window around the spike time (i.e., with periods before and after the action potential onset). +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    spike waveform averagec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#SpikeWaveformAverage

    +
    + The computed average across the spike waveforms. +
    +
    +
    has super-classes
    +
    + spike waveform statistic + c +
    +
    +
    +
    +

    spike waveform signal-to-noise ratioc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#SpikeWaveformSNR

    +
    + The computed signal-to-noise ratio of the spike waveforms. +
    +
    +
    has super-classes
    +
    + spike waveform statistic + c +
    +
    +
    +
    +

    spike waveform statisticc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#SpikeWavevormStatistic

    +
    + Data that contains measures used to describe specific characteristics or make inferences from spike waveforms. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    has sub-classes
    +
    + spike waveform average + c, spike waveform signal-to-noise ratio + c, spike waveform variance + c, spike waveform width + c +
    +
    +
    +
    +

    spike waveform variancec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#SpikeWaveformVariance

    +
    + The computed variance across the spike waveforms. +
    +
    +
    has super-classes
    +
    + spike waveform statistic + c +
    +
    +
    +
    +

    spike waveform widthc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#SpikeWaveformWidth

    +
    + The computed spike waveform width. +
    +
    +
    has super-classes
    +
    + spike waveform statistic + c +
    +
    +
    +
    +

    Spike-contrastc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#SpikeContrast

    +
    + The computed Spike-contrast. +
    +
    +
    has super-classes
    +
    + spike train synchrony measure + c +
    +
    +
    +
    +

    spike-field coherencec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#SpikeFieldCoherence

    +
    + The computed spike-field coherence (SFC). +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    spike-triggered averagec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#SpikeTriggeredAverage

    +
    + The computed spike-triggered average (STA). +
    +
    +
    has super-classes
    +
    + triggered average measure + c +
    +
    has sub-classes
    +
    + spike-triggered local field potential average + c +
    +
    +
    +
    +

    spike-triggered local field potential averagec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#SpikeTriggeredLFPAverage

    +
    + The computed spike-triggered average of the local field potential (LFP) signal. +
    +
    +
    has super-classes
    +
    + spike-triggered average + c +
    +
    +
    +
    +

    spike-triggered phasec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#SpikeTriggeredPhase

    +
    + The computed spike-triggered phase angles. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    standard deviationc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#StandardDeviation

    +
    + The computed standard deviation (SD). +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    standard error of the meanc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#StandardErrorMean

    +
    + The computed standard error of the mean (SEM). +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    Stockwell transformc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#StockwellTransform

    +
    + The result of computing the Stockwell transform (S transform). +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    tensor componentc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#TensorComponent

    +
    + A tensor component obtained by applying tensor component analysis (TCA) to the input data. +
    +
    +
    has super-classes
    +
    + dimensionality reduction output + c +
    +
    +
    +
    +

    time histogramc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#TimeHistogram

    +
    + Data that contains a time histogram, i.e., a histogram that shows the distribution of a measure across specified time intervals (bins). +
    +
    +
    has super-classes
    +
    + data + c +
    +
    has sub-classes
    +
    + peristimulus time histogram + c, population histogram + c, spike train time histogram + c +
    +
    +
    +
    +

    time seriesc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#TimeSeries

    +
    + Data that contains values of a specific quantity (e.g., voltage) acquired as a series of successive samples over time. Typically, there is a fixed interval between the samples (sampling period), with each sample representing a distinct time point in the series. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    has sub-classes
    +
    + analytic signal + c, neural trajectory + c +
    +
    is disjoint with
    +
    + event + c, spike train + c, spike train surrogate + c +
    +
    +
    +
    +

    transfer entropyc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#TransferEntropy

    +
    + The computed transfer entropy (TE). +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    triggered average measurec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#TriggeredAverageMeasure

    +
    + Data that contains the output of a triggered average analysis. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    has sub-classes
    +
    + event-triggered average + c, spike-triggered average + c +
    +
    +
    +
    +

    tuning curvec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#TuningCurve

    +
    + The computed tuning curve. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    unbiased squared phase lag indexc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#UnbiasedSquaredPhaseLagIndex

    +
    + The computed unbiased squared phase lag index (PLI). +
    +
    +
    has super-classes
    +
    + phase lag index measure + c +
    +
    is disjoint with
    +
    + debiased squared weighted phase lag index + c, directed phase lag index + c, phase lag index + c, weighted phase lag index + c +
    +
    +
    +
    +

    Unitary Event patternc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#UnitaryEventPattern

    +
    + A neuronal activity pattern obtained by the Unitary Event (UE) analysis. +
    +
    +
    has super-classes
    +
    + neuronal activity pattern + c +
    +
    +
    +
    +

    upper limit of confidence intervalc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#ConfidenceIntervalUpperLimit

    +
    + The upper limit value of the computed confidence interval. +
    +
    +
    has super-classes
    +
    + confidence interval measure + c +
    +
    +
    +
    +

    upper limit of interquartile rangec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#InterquartileRangeUpperLimit

    +
    + The upper limit of the computed interquartile range, corresponding to the 75th percentile. +
    +
    +
    has super-classes
    +
    + interquartile range measure + c +
    +
    is disjoint with
    +
    + interquartile range + c, lower limit of interquartile range + c +
    +
    +
    +
    +

    van Rossum distancec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#VanRossumDistance

    +
    + The computed van Rossum distance. +
    +
    +
    has super-classes
    +
    + spike train distance + c +
    +
    +
    +
    +

    variancec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#Variance

    +
    + The computed variance. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    Victor-Purpura distancec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#VictorPurpuraDistance

    +
    + The computed Victor-Purpura distance. +
    +
    +
    has super-classes
    +
    + spike train distance + c +
    +
    +
    +
    +

    wavelet transformc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#WaveletTransform

    +
    + Data that contains the result of a wavelet transform analysis, i.e., decomposing a time series using a mother wavelet function. +
    +
    +
    has super-classes
    +
    + data + c +
    +
    +
    +
    +

    weighted phase lag indexc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/data#WeightedPhaseLagIndex

    +
    + The computed weighted phase lag index (WPLI). +
    +
    +
    has super-classes
    +
    + phase lag index measure + c +
    +
    is disjoint with
    +
    + debiased squared weighted phase lag index + c, directed phase lag index + c, phase lag index + c, unbiased squared phase lag index + c +
    +
    +
    +
    +

    Data Properties

    + +
    +

    is artificialdp + back to ToC or Data Property ToC + +

    +

    + IRI: http://purl.org/neao/data#isArtificial

    +
    + Defines if the data is artificially-generated (true) or obtained from experimental recordings (false). +
    +
    +
    +
    has super-properties
    +
    + top data property +
    +
    has domain
    +
    + data + c +
    +
    has range
    +
    + boolean +
    +
    +
    +
    +
    +

    is averageddp + back to ToC or Data Property ToC + +

    +

    + IRI: http://purl.org/neao/data#isAveraged

    +
    + Defines if the data is the result of an aggregation to obtain an average estimate from other data (true). +
    +
    +
    +
    has super-properties
    +
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    +
    has domain
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    +
    has range
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    +
    +
    +
    +
    +

    is detrendeddp + back to ToC or Data Property ToC + +

    +

    + IRI: http://purl.org/neao/data#isDetrended

    +
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    +
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    +
    has super-properties
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    has range
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    +

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    +
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    has super-properties
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    +
    +
    +
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    +

    + IRI: http://purl.org/neao/data#isDownsampled

    +
    + Defines if a downsampling transformation was applied to the data (true). +
    +
    +
    +
    has super-properties
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    has domain
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    +
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    +
    +
    +
    +
    +

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    +

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    +

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    is rectifieddp + back to ToC or Data Property ToC + +

    +

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    +
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    +
    +

    is rereferenceddp + back to ToC or Data Property ToC + +

    +

    + IRI: http://purl.org/neao/data#isRereferenced

    +
    + Defines if a transformation to change the reference in the recorded data was applied (true). +
    +
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    +

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    is smootheddp + back to ToC or Data Property ToC + +

    +

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    +
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    +
    +
    +
    +
    +

    is upsampleddp + back to ToC or Data Property ToC + +

    +

    + IRI: http://purl.org/neao/data#isUpsampled

    +
    + Defines if an upsampling transformation was applied to the data (true). +
    +
    +
    +
    has super-properties
    +
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    + boolean +
    +
    +
    +
    +
    +

    Legend back to ToC

    +
    +c: Classes
    +dp: Data Properties
    +
    +
    +
    + + + + +
    +

    Acknowledgments back to ToC

    +

    This work was performed as part of the Helmholtz School for Data Science in Life, Earth and Energy (HDS-LEE) and received funding from the Helmholtz Association of German Research Centres. This project has received funding from the European Union’s Horizon 2020 Framework Programme for Research and Innovation under Specific Grant Agreement No. 945539 (Human Brain Project SGA3), the European Union’s Horizon Europe Programme under the Specific Grant Agreement No. 101147319 (EBRAINS 2.0 Project), the Ministry of Culture and Science of the State of North Rhine-Westphalia, Germany (NRW-network "iBehave", grant number: NW21-049), and the Joint Lab "Supercomputing and Modeling for the Human Brain."

    + +

    The authors would like to thank Silvio Peroni for developing LODE, a Live OWL Documentation Environment, which is used for representing the Cross Referencing Section of this document and Daniel Garijo for developing Widoco, the program used to create the template used in this documentation.

     +
    + + +
    + + + + + + + diff --git a/doc/releases/0.1.0/data/provenance/provenance-en.html b/doc/releases/0.1.0/data/provenance/provenance-en.html new file mode 100644 index 0000000..4ec4922 --- /dev/null +++ b/doc/releases/0.1.0/data/provenance/provenance-en.html @@ -0,0 +1,18 @@ + + + + + + + + +
    +

    Provenance for Neuroelectrophysiology Analysis Ontology - Data Documentation (http://purl.org/neao/0.1.0/data#)

    +
      +
    • Ontology created by: Cristiano Köhler (Forschungszentrum Jülich), Michael Denker (Forschungszentrum Jülich)
    • http://purl.org/neao/0.1.0/data# is a specialization of the generic URI http://purl.org/neao/data#
      • +
    • The ontology documentation was the result of using the Widoco tool (which itself uses LODE for generating the crossreference section).
      • +
    • The documentation was generated at 2024-12-06
    +
    +

    back to documentation. TTL format

    + + \ No newline at end of file diff --git a/doc/releases/0.1.0/data/provenance/provenance-en.ttl b/doc/releases/0.1.0/data/provenance/provenance-en.ttl new file mode 100644 index 0000000..979c143 --- /dev/null +++ b/doc/releases/0.1.0/data/provenance/provenance-en.ttl @@ -0,0 +1,14 @@ +@prefix prov: . +@prefix dc: . +@prefix foaf: . +@prefix : <> . + a prov:Entity; + dc:title "Neuroelectrophysiology Analysis Ontology - Data"; + prov:wasAttributedTo ; + dc:creator ; + prov:wasAttributedTo ; + dc:creator ; + prov:wasAttributedTo ,; + prov:specializationOf ; + prov:wasGeneratedAt "2024-12-06"; +. diff --git a/doc/releases/0.1.0/data/resources/extra.css b/doc/releases/0.1.0/data/resources/extra.css new file mode 100644 index 0000000..16689d3 --- /dev/null +++ b/doc/releases/0.1.0/data/resources/extra.css @@ -0,0 +1,124 @@ +body { + text-align: justify; +} + +h1 { + line-height: 110%; +} + +.hlist { + border: 1px solid navy; + padding:5px; + background-color: #F4FFFF; +} + +.hlist li { 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r=n[1]||n[2]||"";if(!r||""===u||this.rules.inline.punctuation.exec(u)){var i=n[0].length-1,s=i,l=0,a="*"===n[0][0]?this.rules.inline.emStrong.rDelimAst:this.rules.inline.emStrong.rDelimUnd;for(a.lastIndex=0,t=t.slice(-1*e.length+i);null!=(n=a.exec(t));)if(o=n[1]||n[2]||n[3]||n[4]||n[5]||n[6])if(o=o.length,n[3]||n[4])s+=o;else if((n[5]||n[6])&&i%3&&!((i+o)%3))l+=o;else if(!(0<(s-=o))){var o=Math.min(o,o+s+l);if(Math.min(i,o)%2)return D=e.slice(1,i+n.index+o),{type:"em",raw:e.slice(0,i+n.index+o+1),text:D,tokens:this.lexer.inlineTokens(D,[])};var D=e.slice(2,i+n.index+o-1);return{type:"strong",raw:e.slice(0,i+n.index+o+1),text:D,tokens:this.lexer.inlineTokens(D,[])}}}}},t.codespan=function(e){var t,u,n,e=this.rules.inline.code.exec(e);if(e)return n=e[2].replace(/\n/g," "),t=/[^ ]/.test(n),u=/^ /.test(n)&&/ 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Slightly larger */ + width: 26em; + height: 26em; + z-index: -1; + opacity: 0.8; + + /** From http://stackoverflow.com/questions/1080792/how-to-draw-vertical-text-with-css-cross-browser */ + + -webkit-transform: rotate(-90deg); + -moz-transform: rotate(-90deg); + -ms-transform: rotate(-90deg); + -o-transform: rotate(-90deg); + transform: rotate(-90deg); + /* also accepts left, right, top, bottom coordinates; not + * required, but a good idea for styling */ + -webkit-transform-origin: 50% 50%; + -moz-transform-origin: 50% 50%; + -ms-transform-origin: 50% 50%; + -o-transform-origin: 50% 50%; + transform-origin: 50% 50%; + + /* Should be unset in IE9+ I think. */ + filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=3); +} + +/* The actual status box */ + .status div { + display: block; + background: rgb(0, 90, 156); + color: white; + width: 24em; + padding-top: 0.3em; + padding-left: 0em; + padding-right: 5em; + padding-bottom: 0.3em; + /* Enable for debugging + border: red thin solid; + */ +} + +/* And text inside, don't confuse fonts as it breaks em above */ +.status div span { + font-family: "Tauri"; + font-size: larger; +} \ No newline at end of file diff --git a/doc/releases/0.1.0/data/resources/rdf.icon b/doc/releases/0.1.0/data/resources/rdf.icon new file mode 100644 index 0000000000000000000000000000000000000000..d54310fe20cc6b76fb0aff73bb6d208449383a25 GIT binary patch literal 421 zcmV;W0b2e?Nk%w1VI2S<0K^{vg`>{#^!YhzuNqUMXN>BW*@J zA`Biv9dKI*F$G2>5f4KUX|yqk1!f2uS!02}lx7{JW5GSZW*L7;&$lB24u2k>F$6}2 z9|sD|ao{A8dL-W3NSo?M0}Lb=Tbc$83Fs{c7y=Ux8ZuC@K!AjS1ONaeKqcb9fGD~; zJU~-qN*OvvCfI!Gf5V9$CtYa?E2W PV+=hSSm&XEyAS|7t>CRw literal 0 HcmV?d00001 diff --git a/doc/releases/0.1.0/data/resources/rec.css b/doc/releases/0.1.0/data/resources/rec.css new file mode 100644 index 0000000..d8a1ff2 --- /dev/null +++ b/doc/releases/0.1.0/data/resources/rec.css @@ -0,0 +1,88 @@ +/* Style for a "Recommendation" */ + +/* + Copyright 1997-2003 W3C (MIT, ERCIM, Keio). All Rights Reserved. + The following software licensing rules apply: + http://www.w3.org/Consortium/Legal/copyright-software */ + +/* $Id: base.css,v 1.25 2006/04/18 08:42:53 bbos Exp $ */ + +body { + padding: 2em 1em 2em 70px; + margin: 0; + font-family: sans-serif; + color: black; + background: white; + background-position: top left; + background-attachment: fixed; + background-repeat: no-repeat; + counter-reset:section; +} +:link { color: #00C; background: transparent } +:visited { color: #609; background: transparent } +a:active { color: #C00; background: transparent } + +a:link img, a:visited img { border-style: none } /* no border on img links */ + +a img { color: white; } /* trick to hide the border in Netscape 4 */ +@media all { /* hide the next rule from Netscape 4 */ + a img { color: inherit; } /* undo the color change above */ +} + +th, td { /* ns 4 */ + font-family: sans-serif; +} + +h1, h2, h3, h4, h5, h6 { text-align: left } +h2.list{counter-reset:subsection } +h2.list:before{counter-increment:section;content: counter(section) ". ";} +h3.list:before{counter-increment:subsection;content: counter(section) "." counter(subsection) ". "; + } +h3.list{margin-top: 20px; + border-bottom: 0px; } +/* background should be transparent, but WebTV has a bug */ +h1, h2, h3 { color: #005A9C; background: white } +h1 { font: 170% sans-serif } +h2 { font: 140% sans-serif } +h3 { font: 120% sans-serif } +h4 { font: bold 100% sans-serif } +h5 { font: italic 100% sans-serif } +h6 { font: small-caps 100% sans-serif } + +.hide { display: none } + +div.head { margin-bottom: 1em } +div.head h1 { margin-top: 2em; clear: both } +div.head table { margin-left: 2em; margin-top: 2em } + +p.copyright { font-size: small } +p.copyright small { font-size: small } + +@media screen { /* hide from IE3 */ +a[href]:hover { background: #ffa } +} + +pre { margin-left: 2em } +/* +p { + margin-top: 0.6em; + margin-bottom: 0.6em; +} +*/ +dt, dd { margin-top: 0; margin-bottom: 0 } /* opera 3.50 */ +dt { font-weight: bold } + +pre, code { font-family: monospace } /* navigator 4 requires this */ + +ul.toc, ol.toc { + list-style: disc; /* Mac NS has problem with 'none' */ + list-style: none; +} + +@media aural { + h1, h2, h3 { stress: 20; richness: 90 } + .hide { speak: none } + p.copyright { volume: x-soft; speech-rate: x-fast } + dt { pause-before: 20% } + pre { speak-punctuation: code } +} diff --git a/doc/releases/0.1.0/data/webvowl/css/webvowl.app.css b/doc/releases/0.1.0/data/webvowl/css/webvowl.app.css new file mode 100644 index 0000000..1c350ab --- /dev/null +++ b/doc/releases/0.1.0/data/webvowl/css/webvowl.app.css @@ -0,0 +1,2477 @@ +@import url(https://fonts.googleapis.com/css?family=Open+Sans);/*---------------------------------------------- + WebVOWL page +----------------------------------------------*/ +html { + -ms-content-zooming: none; +} + + + +#loading-progress { + width: 50%; + margin: 10px 0; +} + +#drag_dropOverlay{ + width: 100%; + height:100%; + position:absolute; + top:0; + opacity: 0.5; + background-color: #3071a9; + pointer-events: none; + +} + +#dragDropContainer{ + width: 100%; + height:100%; + position:absolute; + top:0; + pointer-events: none; +} +#drag_icon_group{ + + +} + +#drag_msg{ + width: 50%; + background-color: #fefefe; + height: 50%; + border: black 2px solid; + border-radius: 20px; + left: 25%; + position: absolute; + top: 25%; + vertical-align: middle; + line-height: 10px; + text-align: center; + pointer-events: none; + padding: 10px; + font-size: 1.5em; + white-space: nowrap; + overflow: hidden; + text-overflow: ellipsis; +} + + +#layoutLoadingProgressBarContainer { + height: 50px; + text-align: left; + line-height: 1.5; +} + +#FPS_Statistics { + /*position : absolute;*/ + /*top : 10px;*/ + /*right: 50px;*/ + padding-left: 60px; + padding-top: 60px; +} + +#reloadCachedOntology { + /*position : absolute;*/ + /*top : 10px;*/ + /*right: 50px;*/ +} + +#additionalInformationContainer { + position: absolute; + top: 10px; + right: 50px; +} + +#modeOfOperationString { + /*position: absolute;*/ + /*right: 50px;*/ + /*top : 60px;*/ + padding-left: 34px; +} + +#direct-text-input { + border: 1px solid #34495e; + width: 100%; + margin-top: 5px; + cursor: pointer; +} + +#directUploadBtn, #close_directUploadBtn { + border: 1px solid #34495e; + width: 100%; + margin-top: 5px; + cursor: pointer +} + +#di_controls { + +} + +#di_controls > ul { + list-style: none; + margin: 0; + padding: 5px 0 0 5px; + +} + +#progressBarContext { + border-radius: 10px; + background-color: #bdc3c7; + height: 25px; + border: solid 1px black; + + margin: auto; + +} + +#progressBarValue { + border-radius: 9px; + width: 0%; + background-color: #2980b9; + height: 25px; + line-height: 1.5; + text-align: center; +} + +/** adding searching Styles **/ +.dbEntry { + background-color: #ffffff; + color: #2980b9; + padding: 10px; + font-size: 14px; + border: none; + cursor: pointer; +} + +.debugOption { + +} + +.dbEntrySelected { + background-color: #bdc3c7; + color: #2980b9; + padding: 10px; + font-size: 14px; + border: none; + cursor: pointer; +} + +.dbEntry:hover, .dbEntry:focus { + background-color: #bdc3c7; +} + +.searchMenuEntry { + background-color: #ffffff; + bottom: 0; + font-size: 14px; + min-width: 50px; + margin: 0; + padding: 0; + z-index: 99; + border-radius: 4px 4px 0 0; + border: 1px solid rgba(0, 0, 0, 0.15); + -webkit-box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175); + box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175); + box-sizing: border-box; + border-bottom: none; + display: none; + position: absolute; + list-style: none; +} + +.searchInputText { + background-color: #ffffff; + color: black; + border: black; + text-decoration: none; + max-width: 150px; + overflow: hidden; + text-overflow: ellipsis; + /*height: 20px;*/ + margin: 0; +} + +img, iframe { + border: none; +} + +.hidden { + display: none !important; +} + +.clear { + clear: both; +} + +a { + color: #69c; + text-decoration: none; +} + +a:hover { + color: #3498db; +} + +#optionsArea a { + color: #2980b9; +} + +#optionsArea a.highlighted { + background-color: #d90; +} + +.toolTipMenu li.highlighted { + background-color: #feb; +} + +#browserCheck { + /* checking for IE where WebVOWL is not working */ + background-color: #f00; + padding: 5px 0; + position: absolute; + text-align: center; + width: 100%; +} + +#browserCheck a { + color: #fff; +} + +#browserCheck a:hover { + text-decoration: underline; +} + +/*---------------------------------------------- + SideBar Animation Class; +----------------------------------------------- */ +@-webkit-keyframes sbExpandAnimation { + 0% { + width: 78%; + } + 100% { + width: 100%; + } +} + +@-moz-keyframes sbExpandAnimation { + 0% { + width: 78%; + } + 100% { + width: 100%; + } +} + +@-o-keyframes sbExpandAnimation { + 0% { + width: 78%; + } + 100% { + width: 100%; + } +} + +@keyframes sbExpandAnimation { + 0% { + width: 78%; + } + 100% { + width: 100%; + } +} + +/*Collapse Animation*/ +@-webkit-keyframes sbCollapseAnimation { + 0% { + width: 100%; + } + 100% { + width: 78%; + } +} + +@-moz-keyframes sbCollapseAnimation { + 0% { + width: 100%; + } + 100% { + width: 78%; + } +} + +@-o-keyframes sbCollapseAnimation { + 0% { + width: 100%; + } + 100% { + width: 78%; + } +} + +@keyframes sbCollapseAnimation { + 0% { + width: 100%; + } + 100% { + width: 78%; + } +} + +/*---------------------------------------------- + SideBar Animation Class; +----------------------------------------------- */ +@-webkit-keyframes l_sbExpandAnimation { + 0% { + width: 0px; + } + 100% { + width: 200px; + } +} + +@-moz-keyframes l_sbExpandAnimation { + 0% { + width: 0px; + } + 100% { + width: 200px; + } +} + +@-o-keyframes l_sbExpandAnimation { + 0% { + width: 0px; + } + 100% { + width: 200px; + } +} + +@keyframes l_sbExpandAnimation { + 0% { + width: 0px; + } + 100% { + width: 200px; + } +} + +/*Collapse Animation*/ +@-webkit-keyframes l_sbCollapseAnimation { + 0% { + width: 200px; + } + 100% { + width: 0px; + } +} + +@-moz-keyframes l_sbCollapseAnimation { + 0% { + width: 200px; + } + 100% { + width: 0px; + } +} + +@-o-keyframes l_sbCollapseAnimation { + 0% { + width: 200px; + } + 100% { + width: 0px; + } +} + +@keyframes l_sbCollapseAnimation { + 0% { + width: 200px; + } + 100% { + width: 0px; + } +} + +/*----------------- WARNING ANIMATIONS-------------*/ + +/*---------------------------------------------- + SideBar Animation Class; +----------------------------------------------- */ +@-webkit-keyframes warn_ExpandAnimation { + 0% { + top: -500px; + } + 100% { + top: 0; + } +} + +@-moz-keyframes warn_ExpandAnimation { + 0% { + top: -500px; + } + 100% { + top: 0; + } +} + +@-o-keyframes warn_ExpandAnimation { + 0% { + top: -500px; + } + 100% { + top: 0; + } +} + +@keyframes warn_ExpandAnimation { + 0% { + top: -500px; + } + 100% { + top: 0; + } +} + +/*Collapse Animation*/ +@-webkit-keyframes warn_CollapseAnimation { + 0% { + top: 0; + } + 100% { + top: -400px; + } +} + +@-moz-keyframes warn_CollapseAnimation { + 0% { + top: 0; + } + 100% { + top: -400px; + } +} + +@-o-keyframes warn_CollapseAnimation { + 0% { + top: 0; + } + 100% { + top: -400px; + } +} + +@keyframes warn_CollapseAnimation { + 0% { + top: 0; + } + 100% { + top: -400px; + } +} + +@keyframes msg_CollapseAnimation { + 0% { + top: 0; + } + 100% { + top: -400px; + } +} + +/*// add expand and collaps width for the warn module*/ +@-webkit-keyframes warn_ExpandLeftBarAnimation { + 0% { + left: 0; + } + 100% { + left: 100px; + } +} + +@-moz-keyframes warn_ExpandLeftBarAnimation { + 0% { + left: 0; + } + 100% { + left: 100px; + } +} + +@-o-keyframes warn_ExpandLeftBarAnimation { + 0% { + left: 0; + } + 100% { + left: 100px; + } +} + +@keyframes warn_ExpandLeftBarAnimation { + 0% { + left: 0; + } + 100% { + left: 100px; + } +} + +/*Collapse Animation*/ +@-webkit-keyframes warn_CollapseLeftBarAnimation { + 0% { + left: 100px; + } + 100% { + left: 0; + } +} + +@-moz-keyframes warn_CollapseLeftBarAnimation { + 0% { + left: 100px; + } + 100% { + left: 0; + } +} + +@-o-keyframes warn_CollapseLeftBarAnimation { + 0% { + left: 100px; + } + 100% { + left: 0; + } +} + +@keyframes warn_CollapseLeftBarAnimation { + 0% { + left: 100px; + } + 100% { + left: 0; + } +} + +/*// same for the right side expansion*/ + +/*// add expand and collaps width for the warn module*/ +@-webkit-keyframes warn_ExpandRightBarAnimation { + 0% { + width: 100%; + } + 100% { + width: 78%; + } +} + +@-moz-keyframes warn_ExpandRightBarAnimation { + 0% { + width: 100%; + } + 100% { + width: 78%; + } +} + +@-o-keyframes warn_ExpandRightBarAnimation { + 0% { + width: 100%; + } + 100% { + width: 78%; + } +} + +@keyframes warn_ExpandRightBarAnimation { + 0% { + width: 100%; + } + 100% { + width: 78%; + } + +} + +/*Collapse Animation*/ +@-webkit-keyframes warn_CollapseRightBarAnimation { + 0% { + width: 78%; + } + 100% { + width: 100%; + } +} + +@-moz-keyframes warn_CollapseRightBarAnimation { + 0% { + width: 78%; + } + 100% { + width: 100%; + } +} + +@-o-keyframes warn_CollapseRightBarAnimation { + 0% { + width: 78%; + } + 100% { + width: 100%; + } +} + +@keyframes warn_CollapseRightBarAnimation { + 0% { + width: 78%; + } + 100% { + width: 100%; + } +} + +/*---------------------------------------------- + LAYOUT +----------------------------------------------*/ +body { + background: rgb(24, 32, 42); + height: 100%; + font-size: 14px; + font-family: 'Open Sans', Helvetica, Arial, sans-serif; + line-height: 1; + margin: 0; + overflow: hidden; + padding: 0; + position: fixed; + width: 100%; +} + +main { + height: 100%; + margin: 0; + padding: 0; + position: relative; + width: 100%; +} + +#canvasArea { + position: relative; + margin: 0; + padding: 0; + width: 78%; +} + +#canvasArea #graph { + box-sizing: border-box; + margin: 0 0 2px 0; + background-color: #ecf0f1; + overflow: hidden; + padding: 0; + width: 100%; +} + +#canvasArea svg { + box-sizing: border-box; + margin: 0; + overflow: hidden; + padding: 0; +} + +#logo { + position: fixed; + /*padding: 10px;*/ + pointer-events: none; + /*border: solid 1px red;*/ +} + +#logo h2 { + color: #3498db; + margin: 0; + line-height: 0.7; + text-align: center; + font-size: 24px; +} + +#logo h2 span { + color: #34495E; + /*font-size: min(2vmin, 24px);*/ + font-size: 16px; +} + +@media screen and (max-device-height: 800px) { + #logo h2 { + font-size: calc(8px + 1.0vmin); + } + + #logo h2 span { + font-size: calc(3px + 1.0vmin); + } +} + +@media screen and (max-height: 800px) { + #logo h2 { + font-size: calc(8px + 1.0vmin); + } + + #logo h2 span { + font-size: calc(3px + 1.0vmin); + } +} + +@media screen and (max-device-width: 1200px) { + #logo h2 { + font-size: calc(8px + 1.0vmin); + } + + #logo h2 span { + font-size: calc(3px + 1.0vmin); + } +} + +@media screen and (max-width: 1200px) { + #logo h2 { + font-size: calc(8px + 1.0vmin); + } + + #logo h2 span { + font-size: calc(3px + 1.0vmin); + } +} + +.checkboxContainer input, .checkboxContainer label { + vertical-align: middle; +} + +.selected-ontology { + background-color: #eee; +} + +#credits { + border-top: solid 1px #bdc3c7; + font-size: 0.9em; +} + +.slideOption { + position: relative; + padding: 8px 5px; + outline: none; +} + +.slideOption .value { + float: right; + outline: none; +} + +.slideOption input[type="range"] { + box-sizing: border-box; + margin: 0; + outline: none; + -webkit-appearance: none; + -moz-appearance: none; + border-radius: 3px; + height: 12px; + width: 100%; + box-shadow: none; + left: 0; + position: relative; + transition: all 0.5s ease; + background-color: #eee; +} + +/*TRACK*/ +.slideOption input[type=range]::-webkit-slider-runnable-track { + -webkit-appearance: none; + background-color: #3071a9; + height: 3px; +} + +.slideOption input[type=range]::-moz-range-track { + -webkit-appearance: none; + background-color: #3071a9; + height: 3px; +} + +.slideOption input[type="range"]:hover { + outline: none; +} + +/*THUMB*/ +.slideOption input[type="range"]::-webkit-slider-thumb { + -webkit-appearance: none; + background-color: white; + border-radius: 3px; + border: solid 1px black; + transition: all 0.5s ease; + height: 10px; + width: 30px; + outline: none; + margin-top: -3px; +} + +.slideOption input[type="range"]::-moz-range-thumb { + -webkit-appearance: none; + background-color: white; + border-radius: 3px; + border: solid 1px black; + transition: all 0.5s ease; + height: 10px; + width: 30px; + outline: none; +} + +.slideOption input[type="range"]::-moz-range-thumb:hover { + background-color: #d90; + outline: none; +} + +.slideOption input[type="range"]::-webkit-slider-thumb:hover { + background-color: #d90; + /*color: #d90;*/ + outline: none; +} + +/*focus : remove border*/ +.slideOption input[type="range"]:focus { + outline: none; +} + +.slideOption input[type="range"]:active { + outline: none; +} + +.slideOption input[type="range"]::-moz-range-thumb:focus { + outline: none; +} + +.slideOption input[type="range"]::-moz-range-thumb:active { + outline: none; +} + +.slideOption input[type="range"]::-webkit-slider-thumb:focus { + outline: none; +} + +.slideOption input[type="range"]::-webkit-slider-thumb:active { + outline: none; +} + +.slideOption input[type="range"]:disabled { + box-sizing: border-box; + margin: 0; + outline: none; + -webkit-appearance: none; + -moz-appearance: none; + border-radius: 3px; + height: 12px; + width: 100%; + box-shadow: none; + left: 0; + position: relative; + transition: all 0.5s ease; + background-color: #787878; +} + +/*TRACK*/ +.slideOption input[type=range]:disabled::-webkit-slider-runnable-track { + -webkit-appearance: none; + background-color: #373737; + height: 3px; +} + +.slideOption input[type=range]:disabled::-moz-range-track { + -webkit-appearance: none; + background-color: #373737; + height: 3px; +} + +.slideOption input[type="range"]:disabled { + outline: none; +} + +/*THUMB*/ +.slideOption input[type="range"]:disabled::-webkit-slider-thumb { + -webkit-appearance: none; + background-color: #363636; + border-radius: 3px; + border: solid 1px #aaaaaa; + transition: all 0.5s ease; + height: 10px; + width: 30px; + outline: none; + margin-top: -3px; +} + +.slideOption input[type="range"]:disabled::-moz-range-thumb { + -webkit-appearance: none; + background-color: #aaaaaa; + border-radius: 3px; + border: solid 1px black; + transition: all 0.5s ease; + height: 10px; + width: 30px; + outline: none; +} + +.slideOption input[type="range"]:disabled::-moz-range-thumb { + background-color: #aaaaaa; + outline: none; +} + +.slideOption input[type="range"]:disabled::-webkit-slider-thumb { + background-color: #aaaaaa; + /*color: #d90;*/ + outline: none; +} + +.slideOption input[type="range"]:disabled:hover::-moz-range-thumb { + background-color: #404040; + outline: none; +} + +.slideOption input[type="range"]:disabled:hover::-webkit-slider-thumb { + background-color: #404040; + /*color: #d90;*/ + outline: none; +} + +#detailsArea { + top: 0; + right: 0; + bottom: 0; + color: #bdc3c7; + height: 100%; + width: 22%; + overflow-y: auto; + overflow-x: hidden; + position: fixed; + border-left: 1px solid #34495E; +} + +#detailsArea h1 { + border-bottom: solid 1px #34495e; + color: #ecf0f1; + display: block; + font-weight: 100; + font-size: 1.5em; + margin: 0; + padding: 10px 0; + text-align: center; +} + +#generalDetails { + width: auto; + box-sizing: border-box; + height: 100%; +} + +#generalDetails span #about { + border-bottom: solid 1px #34495e; + display: block; + padding: 10px; + text-align: center; + word-wrap: break-word; + color: #69c; +} + +#generalDetails h4 { + background: rgb(27, 37, 46); + color: #ecf0f1; + display: block; + font-size: 1.1em; + font-weight: 100; + margin: 0; + padding: 10px 0; + text-align: center; +} + +#detailsArea #generalDetails h5 { + border-bottom: solid 1px #34495e; + font-size: 0.9em; + font-weight: 100; + margin: 0; + padding: 5px; + text-align: center; +} + +#description { + text-align: justify; +} + +.accordion-container p { + font-size: 0.9em; + line-height: 1.3; + margin: 5px 10px; +} + +.statisticDetails span { + font-weight: 100; + font-style: italic; + margin: 10px 0; + padding: 10px; +} + +.statisticDetails div { + font-weight: 100; + font-style: italic; + margin: 10px 0; + padding: 0 10px; + display: inline; +} + +#selection-details .propDetails a { + color: #69c; +} + +#selection-details .propDetails > span { + font-weight: 100; + font-style: italic; + padding: 0 10px; +} + +#selection-details #classEquivUri span, #selection-details #disjointNodes span { + padding: 0; +} + +#selection-details .propDetails div { + font-weight: 100; + font-style: italic; + margin: 10px 0; + padding: 0 10px; + display: inline; +} + +#selection-details .propDetails div span { + padding: 0; +} + +/* give subclass property the same background color as the canvas */ +.subclass { + fill: #ecf0f1; +} + +.accordion-trigger { + background: #24323e; + cursor: pointer; + padding: .5em; +} + +.accordion-trigger.accordion-trigger-active:before { + padding-right: 4px; + content: "\25BC" +} + +.accordion-trigger:not(.accordion-trigger-active):before { + padding-right: 4px; + content: "\25BA" +} + +.accordion-container.scrollable { + max-height: 40%; + overflow: auto; +} + +.small-whitespace-separator { + height: 3px; +} + +#language { + background: transparent; + border: 1px solid #34495E; + color: #ecf0f1; +} + +#language option { + background-color: #24323e; +} + +.converter-form:not(:first-child) { + margin-top: 5px; +} + +.converter-form label { + display: inline-block; + line-height: normal; +} + +.converter-form input { + box-sizing: border-box; + height: 20px; + width: 74%; + border: 1px solid #34495E; +} + +.converter-form button { + cursor: pointer; + float: right; + height: 20px; + padding: 0; + width: 25%; + border: 1px solid #34495E; + background-color: #ecf0f1; +} + +#file-converter-label { + border: 1px solid #34495E; + box-sizing: border-box; + cursor: pointer; + height: 20px; + width: 74%; +} + +#killWarning { + cursor: pointer; + color: #ffffff; + font-weight: bold; +} + +/*#copyBt{*/ +/*box-sizing: border-box;*/ +/*color: #000000;*/ +/*float:right;*/ +/*position:absolute;*/ +/*right:2px;*/ +/*padding: 2px 7px 3px 7px;*/ +/*border: 1px solid #000000;*/ +/*background-color: #ecf0f1;*/ +/*cursor: pointer;*/ +/*}*/ + +#copyBt { + box-sizing: border-box; + height: 20px; + width: 31%; + border: 1px solid #34495E; +} + +#sidebarExpandButton { + height: 24px; + width: 24px; + /*background-color: white;*/ + /*box-shadow: 0px 1px 1px grey;*/ + box-sizing: border-box; + top: 10px; + color: #000000; + float: right; + position: absolute; + right: 0; + border: 1px solid #000000; + + text-align: center; + font-size: 1.5em; + cursor: pointer; +} + +.dropdownMenuClass { + height: 20px; + /*width: 69%;*/ + float: right; + border: 1px solid #34495E; + background-color: #34495E; + color: white; + /*border-bottom: 1px solid #d90;*/ + text-align: left; + width: auto; +} + +#typeEditForm_datatype { + padding-top: 5px; +} + +#typeEditor { + width: 165px; +} + +#typeEditor_datatype { + width: 165px; +} + +#leftSideBarCollapseButton { + box-sizing: border-box; + top: 50px; + /*padding:5px;*/ + color: #000000; + position: absolute; + left: 200px; + border: 1px solid #000000; + /*background-color: #ecf0f1;*/ + cursor: pointer; + width: 24px; + height: 24px; + font-size: 1.5em; + text-align: center; +} + +#leftSideBarCollapseButton:hover { + background-color: #d90; +} + +#sidebarExpandButton:hover { + background-color: #d90; +} + +.spanForCharSelection { + padding-left: 25px; +} + +.nodeEditSpan { + color: #000; + background-color: #fff; + text-align: center; + /*overflow: auto;*/ + border: none; + padding-top: 6px; +} + +.nodeEditSpan:focus { + outline: none; + border: none; +} + +.foreignelements { + /*width: 80px;*/ + /*height: 3px;*/ + border: none; +} + +.foreignelements:focus { + outline: none; + border: none; +} + +#leftSideBarContent { + color: #000000; + float: left; + position: absolute; + left: 0; + /*border: 1px solid #000000;*/ + background-color: rgb(24, 32, 42); + width: 100%; + height: 100%; +} + +#leftSideBarContent > h3 { + color: #ecf0f1; + display: block; + font-size: 1.1em; + font-weight: 100; + margin: 0 0 5px 0; + padding: 10px 0; + text-align: left; +} + +#generalDetailsEdit { + /*color: #ecf0f1;*/ + color: #ecf0f1; +} + +#generalDetailsEdit > div { + padding: 5px; +} + +#generalDetailsEdit > h3 { + color: #ecf0f1; + display: block; + font-size: 1.1em; + font-weight: 100; + margin: 0 0 5px 0; + padding: 10px 0; + text-align: left; +} + +.subAccordion { + color: #ecf0f1; + display: block; + font-size: 0.8em; + font-weight: 100; + margin: 0; + padding: 5px; + text-align: left; +} + +.subAccordionDescription { + padding: 0 5px; +} + +.boxed { + padding: 0 5px; +} + +.separatorLineRight { + border-right: 1px solid #f00; +} + +.editPrefixButton:hover { + color: #ff972d; + cursor: pointer; +} + +.editPrefixIcon:hover { + stroke: #ff972d; + stroke-width: 1px; + cursor: pointer; +} + +.editPrefixIcon { + stroke: #fffff; + stroke-width: 1px; + cursor: pointer; +} + +.deletePrefixButton:hover { + color: #ff972d; + cursor: pointer; +} + +.deletePrefixButton { + color: #ff0000; + cursor: pointer; +} + +.invisiblePrefixButton { + cursor: default; + color: rgb(24, 32, 42); +} + +#containerForAddPrefixButton { + width: 100%; + margin-top: 5px; +} + +.roundedButton { + border: 1px solid #000000; + border-radius: 20px; + padding: 0 5px; + background: #fff; + cursor: pointer; + color: black; + outline: none; +} + +.roundedButton:hover { + background: #318638; + cursor: pointer; + color: #fff; + outline: none; +} + +#prefixURL_Description { + padding: 5px 0 0 0; +} + +.prefixIRIElements { + display: inline-block; + padding: 3px; + border-bottom: 1px solid #34495E; + width: 100% +} + +.prefixInput { + width: 30px; + display: inline-block; + margin-right: 5px; +} + +.prefixURL { + width: 100px; + display: inline-block; + paddig-left: 5px; +} + +.selectedDefaultElement { + text-align: left; + white-space: nowrap; + overflow: hidden; + text-overflow: ellipsis; + display: inline-block; + max-width: 200px; +} + +#editHeader { + color: #ecf0f1; + background-color: #394f5a; + display: block; + font-size: 1.1em; + font-weight: 100; + text-align: center; +} + +#leftHeader { + color: #ecf0f1; + background-color: #394f5a; + display: block; + font-size: 1.1em; + font-weight: 100; + text-align: center; + padding: 10px 0; + margin: 0; +} + +.containerForDefaultSelection { + color: #ecf0f1; + display: block; + font-size: 1.1em; + font-weight: 100; + margin: 0; + padding: 10px 20px; + text-align: left; +} + +.defaultSelected { + color: #a15d05; + background-color: #283943; +} + +.containerForDefaultSelection:hover { + color: #f19505; + background-color: #394f5a; + display: block; + cursor: pointer; +} + +#containerForLeftSideBar { + top: 50px; + float: left; + position: absolute; + background-color: #1b252e; + left: 0; + width: 200px; + height: 200px; + overflow-y: auto; + overflow-x: hidden; +} + +#leftSideBar { + width: 100%; + background-color: rgb(24, 32, 42); +} + +#loading-info { + box-sizing: border-box; + position: absolute; + text-align: center; + + width: 100%; + height: 80%; + top: 0; +} + +#loading-info > div { + display: inline-block; + color: #ffffff; + background-color: #18202A; + border-bottom-left-radius: 2px; + border-bottom-right-radius: 2px; +} + +#loading-info > * > * { + padding: 5px; +} + +#loading-info { + pointer-events: none; +} + +#loading-progress { + pointer-events: auto; + min-width: 220px; + border-radius: 10px; +} + +#show-loadingInfo-button { + font-size: 12px; + color: #fff; + cursor: pointer; + text-align: center; +} + +#loadingIndicator_closeButton:hover { + color: #ff972d; + cursor: pointer; + +} + +#loadingIndicator_closeButton { + color: #ffe30f; + cursor: pointer; + padding-bottom: 5px; + float: right; +} + +.busyProgressBar { + background-color: #000; + height: 25px; + position: relative; + animation: busy 2s linear infinite; +} + +@-webkit-keyframes busy { + 0% { + left: 0%; + } + 50% { + left: 80%; + } + 100% { + left: 0%; + } +} + +#bulletPoint_container { + padding-left: 15px; + margin-top: 0px; + margin-bottom: 0px; +} + +#bulletPoint_container > div { + margin-left: -15px; +} + +#loadingInfo-container { + box-sizing: border-box; + text-align: left; + line-height: 1.2; + padding-top: 5px; + overflow: auto; + /*white-space: nowrap;*/ + /*min-width: 250px;*/ + height: 120px; + min-height: 40px; + background-color: #3c3c3c; + +} + +#error-description-button { + margin: 5px 0 0 0; + font-size: 12px; + color: #69c; + cursor: pointer; + text-align: center; +} + +#error-description-container { + box-sizing: border-box; + text-align: left; +} + +#error-description-container pre { + background-color: #34495E; + padding: 2px; + margin: 0; + white-space: pre-wrap; + max-height: calc(100vh - 125px); + max-width: 75vw; + overflow: auto; +} + +.spin { + display: inline-block; + -webkit-animation: spin 2s infinite linear; + animation: spin 2s infinite linear; +} + +@-webkit-keyframes spin { + 0% { + -webkit-transform: rotate(0deg); + transform: rotate(0deg); + } + 100% { + -webkit-transform: rotate(359deg); + transform: rotate(359deg); + } +} + +@keyframes spin { + 0% { + -webkit-transform: rotate(0deg); + transform: rotate(0deg); + } + 100% { + -webkit-transform: rotate(359deg); + transform: rotate(359deg); + } +} + +.truncate { + max-width: 250px; + white-space: nowrap; + overflow: hidden; + text-overflow: ellipsis; +} + +.color-mode-switch { + float: right; + width: 90px; + cursor: pointer; + height: 20px; + padding: 0; + border: 0; + color: #555; + background-color: #ECEEEF; + box-shadow: 0 1px 4px rgba(0, 0, 0, 0.2), inset 0 0 3px rgba(0, 0, 0, 0.1); +} + +.color-mode-switch:focus { + outline-width: 0; +} + +.color-mode-switch.active { + color: #FFF; + background-color: #32CD32; + box-shadow: inset 0 1px 4px rgba(0, 0, 0, 0.2), inset 0 0 3px rgba(0, 0, 0, 0.1); +} + +/* adding button pulse animation*/ +.filterMenuButtonHighlight { + background-color: #d90; +} + +@-webkit-keyframes buttonAnimation { + 0% { + background-color: unset; + } + 100% { + background-color: #d90; + } +} + +@-moz-keyframes buttonAnimation { + 0% { + background-color: unset; + } + 100% { + background-color: #d90; + } +} + +@-o-keyframes buttonAnimation { + 0% { + background-color: unset; + } + 100% { + background-color: #d90; + } +} + +@keyframes buttonAnimation { + 0% { + background-color: unset; + } + 100% { + background-color: #d90; + } +} + +.buttonPulse { + -webkit-animation-name: buttonAnimation; + -moz-animation-name: buttonAnimation; + -o-animation-name: buttonAnimation; + animation-name: buttonAnimation; + + -webkit-animation-duration: 0.5s; + -moz-animation-duration: 0.5s; + -o-animation-duration: 0.5s; + animation-duration: 0.5s; + + -webkit-animation-iteration-count: 3; + -moz-animation-iteration-count: 3; + -o-animation-iteration-count: 3; + animation-iteration-count: 3; + + -webkit-animation-timing-function: linear; + -moz-animation-timing-function: linear; + -o-animation-timing-function: linear; + animation-timing-function: linear; + + +} + +/*swipe bar definition*/ + +/*Overwriting individual menu widths*/ +#m_about { + max-width: 200px; + width: 200px; + position: absolute; + +} + +#m_modes { + max-width: 160px; + width: 160px; + position: absolute; +} + +#m_filter { + max-width: 170px; + width: 170px; + position: absolute; +} + +#m_gravity { + max-width: 180px; + width: 180px; + position: absolute; +} + +#m_export { + max-width: 160px; + width: 160px; + position: absolute; + +} + +#exportedUrl { + width: 100px; +} + +#m_select { + max-width: 300px; + width: 300px; + position: absolute; +} + +#m_config { + max-width: 240px; + width: 240px; + position: absolute; +} + +#m_search { + max-width: 250px; + white-space: nowrap; + overflow: hidden; + text-overflow: ellipsis; +} + +/***************** REWRITING MENU ELEMENT CONTAINERS ***********************/ +/*Container which holds the swipeBar*/ +#swipeBarContainer { + position: fixed; + width: 77.8%; + height: 40px; + margin: 0; + padding: 0; + bottom: 0; +} + +/*Scroll-able container for the menu entries */ +#menuElementContainer { + margin: 0; + padding: 0; + overflow-x: auto; + overflow-y: hidden; + white-space: nowrap; + text-align: right; + list-style-type: none; +} + +/*Style for the individual menu entries*/ +#menuElementContainer > li { + display: inline-block; + box-sizing: border-box; + text-align: left; + position: relative; + height: 40px; + font-size: 14px; + color: #ffffff; + padding: 12px 0 0; + margin-left: -4px; +} + +/*Font-color Style for menu entries */ +#menuElementContainer > li > a { + color: #fff; + padding: 9px 12px 12px 30px; +} + +.menuElementSvgElement { + height: 20px; + width: 20px; + display: block; + position: absolute; + top: 10px; + left: 8px; +} + +.btn_shadowed { + background-color: #fefefe; + box-shadow: 1px 1px 1px gray; +} + +.reloadCachedOntologyIcon { + height: 20px; + width: 108px; + display: block; + position: absolute; + top: 20px; + left: 3px; + /*background: #ecf0f1;;*/ + border: solid 1px black; + border-radius: 10px; + cursor: pointer; +} + +.reloadCachedOntologyIcon:disabled { + background: #f4f4f4; + cursor: auto; + border: solid 1px darkgray; + +} + +.reloadCachedOntologyIcon:hover { + background: #d90; + cursor: pointer; +} + +.disabledReloadElement { + cursor: auto; + background: #F4F4F4; + pointer-events: auto; + border: solid 1px darkgray; + color: #bbbbbb; +} + +.disabledReloadElement:hover { + cursor: auto; + background: #EEEEEE; + pointer-events: auto; +} + +#menuElementContainer > li > input { + color: #000; + /*padding : 0 0.3em 0 1.5em;*/ + padding: 0.1em .3em 0.1em 1.5em; + white-space: nowrap; + overflow: hidden; + text-overflow: ellipsis; + width: 120px; +} + +/*Hovered behavior for the menu entries*/ +#menuElementContainer > li > a:hover { + box-sizing: border-box; + background: #1B252E; + /*background : #d90;*/ + color: #bdc3c7; + +} + +#empty:hover { + box-sizing: border-box; + background: #e1e1e1; + /*background : #d90;*/ + color: #2980b9; +} + +#empty.disabled { + pointer-events: none; + cursor: default; + color: #979797; +} + +.disabled { + pointer-events: none; + cursor: default; + color: #979797; +} + +/*ToolTip Menu Definition*/ +.toolTipMenu { + -webkit-box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175); + box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175); + box-sizing: border-box; + background-color: #ffffff; + border: 1px solid rgba(0, 0, 0, 0.15); + border-bottom: none; + border-radius: 4px 4px 0 0; + bottom: 0; + display: none; + font-size: 14px; + list-style: none; + /*max-width: 300px;*/ + margin: 0; + padding: 0; + white-space: normal; + position: absolute; + z-index: 99; +} + +.toolTipMenu > li:first-of-type { + border: none; +} + +.toolTipMenu a { + color: #2980b9; +} + +.toolTipMenu > li { + border-top: solid 1px #bdc3c7; +} + +.toolTipMenu li { + color: #2980b9; + display: block; +} + +/*MenuElement hovering enables the toolTip of the corresponding menu*/ +#menuElementContainer > li:hover .toolTipMenu { + display: block; +} + +#menuElementContainer li > ul.toolTipMenu li a:hover { + background: #e1e1e1; +} + +/****************************************************************************/ +/*ScrollButton behavior*/ +#scrollLeftButton { + height: 30px; + width: 30px; + padding: 5px 0 5px 10px; + color: #fff; + cursor: pointer; + position: absolute; + margin-top: -2px; + font-size: 2em; + background-color: #24323e; + left: 0; +} + +#scrollLeftButton:focus { + outline: none; +} + +#scrollLeftButton:before { + content: "<"; +} + +/*Right Scroll Button*/ +#scrollRightButton { + height: 30px; + width: 30px; + padding: 5px 0 5px 10px; + color: #fff; + cursor: pointer; + position: absolute; + margin-top: -2px; + font-size: 2em; + background-color: #24323e; + right: 0; +} + +#scrollRightButton:focus { + outline: none; +} + +#scrollRightButton:hover { + color: #bdc3c7; +} + +#scrollLeftButton:hover { + color: #bdc3c7; +} + +#scrollRightButton:before { + content: ">"; +} + +#centerGraphButton, #zoomInButton, #zoomOutButton { + border: 1px solid #000000; + text-align: center; + margin: -1px 0 0 0; + font-size: 1.5em; + padding: 0; + height: 28px; +} + +.noselect { + -webkit-touch-callout: none; /* iOS Safari */ + -webkit-user-select: none; /* Safari */ + -khtml-user-select: none; /* Konqueror HTML */ + -moz-user-select: none; /* Firefox */ + -ms-user-select: none; /* Internet Explorer/Edge */ + user-select: none; + /* Non-prefixed version, currently + supported by Chrome and Opera */ +} + +#zoomOutButton { + line-height: 22px; +} + +#centerGraphButton { + line-height: 25px; +} + +#zoomInButton { + line-height: 25px; +} + +#zoomSlider > p:hover { + background-color: #d90; +} + +#zoomSliderParagraph { + color: #000000; + padding-top: 5px; + margin: -1px 0 0 0; + border: 1px solid #000000; + /*background-color: #ecf0f1;*/ + /*width: 28px;*/ + height: 150px; +} + +p#zoomSliderParagraph:hover { + background-color: #fff; +} + +/*todo put this in a proper position*/ +#zoomSlider { + width: 28px; + margin-top: -2px; + padding: 0; + font-size: 1.5em; + cursor: pointer; + position: absolute; + right: 20px; + bottom: 20px; + color: #000; + /*background-color: #ecf0f1;*/ + box-sizing: border-box; +} + +/****************************************************************************/ +/*Definition for the Icons before*/ +#menuElementContainer > li > a::before { + font-size: 1em; + margin: 0; + padding: 0 6px 0 0; +} + +#menuElementContainer a.highlighted { + background-color: #d90; +} + +/*#search-input-text.searchInputText {*/ +/*!*padding: 0 0.2em;*!*/ +/*color: black;*/ +/*}*/ + +.inner-addon { + position: relative; +} + +.searchIcon { + position: absolute; + /*padding: 0.15em 0;*/ + width: 17px; + height: 17px; + + pointer-events: none; +} + +.gearIcon { + position: absolute; + width: 17px; + height: 17px; + pointer-events: none; + left: -5px; +} + +/*#search-input-text::before {*/ +/*!*padding: 0 0.2em;*!*/ +/*!*color: black;*!*/ +/*font-size: 1.4em; !* todo : test this *!*/ +/*!*content: "\2315";*!*/ +/*content: "⚲";*/ +/*color: white;*/ +/*padding: 0;*/ +/*-webkit-transform: rotate(-45deg);*/ +/*!*content: "\2315" or "\1F50D"*!;*/ +/*display: inline-block;*/ +/*position: relative;*/ +/*top: 2px;*/ +/*left:-5px;*/ +/*}*/ + +li#c_search { + padding: 0 5px; + margin-left: 5px; + height: 20px; +} + +/*Menu icons before the links selection */ +/*#c_select > a::before { content: "\2263"; }*/ +/*#c_export > a::before { content: "\21E4"; }*/ +/*#c_gravity > a::before { content: "\2299"; }*/ +/*#c_filter > a::before { content: "\25BD"; }*/ +/*#c_modes > a::before { content: "\2606"; }*/ +/*#c_reset > a::before { content: "\21BB"; }*/ +/*#c_about > a::before { content: "\00A9"; }*/ + +li#c_locate { + padding: 0; +} + +#c_locate > a { + font-size: 2em; + padding: 0; +} + +a#pause-button { + padding: 12px 12px; +} + +/*Pause Button has a different behavior*/ +a#pause-button.paused::before { + content: "\25BA"; +} + +a#pause-button.paused:hover { + background-color: #d90; + color: #fff; +} + +a#pause-button:not(.paused)::before { + content: "II"; +} + +.toolTipMenu li:hover { + background-color: #e1e1e1; +} + +#emptyLiHover { + background-color: #FFFFFF; +} + +#emptyLiHover:hover { + background-color: #FFFFFF; +} + +.toggleOption li:hover { + background-color: #e1e1e1; +} + +.toggleOption { + padding: 8px 5px; +} + +#converter-option:hover { + background-color: #ffffff; +} + +.toolTipMenu li a:only-child, .option { + display: block; + float: none; + padding: 8px 5px; +} + +.customLocate { + padding: 0; + background-color: #32CD32; +} + +a#locateSearchResult { + padding-bottom: 0; + padding-top: 50px; + position: relative; + top: 5px; +} + +/*#sliderRange{*/ +/*padding: 0;*/ +/*margin: 7px 0 0 0;*/ +/*width:100%;*/ +/*height:5px;*/ +/*-webkit-appearance: none;*/ +/*outline: none;*/ +/*}*/ + +#zoomSliderElement { + color: #000; + position: relative; + padding-top: 0; + width: 155px; + height: 24px; + background-color: transparent; + -webkit-transform-origin-x: 73px; + -webkit-transform-origin-y: 73px; + -webkit-transform: rotate(-90deg); + -moz-transform-origin: 73px 73px; + transform: rotate(-90deg); + transform-origin: 73px 73px; + -webkit-appearance: none; + outline: none; + margin: 4px 0; +} + +/* ------------------ Zoom Slider styles --------------------------*/ +#zoomSliderElement::-webkit-scrollbar { + height: 0; +} + +#zoomSliderElement:hover { + cursor: crosshair; +} + +/*TRACK*/ +#zoomSliderElement::-webkit-slider-runnable-track { + width: 100%; + height: 5px; + cursor: pointer; + background: #3071a9; +} + +#zoomSliderElement::-moz-range-track { + width: 100%; + height: 5px; + cursor: pointer; + background: #3071a9; +} + +/*Thumb*/ +#zoomSliderElement::-webkit-slider-thumb { + -webkit-appearance: none; + border: 1px solid #000000; + height: 10px; + width: 30px; + margin-right: 50px; + border-radius: 3px; + background: #fff; + cursor: pointer; + outline: none; + margin-top: -3px; +} + +#zoomSliderElement::-ms-thumb { + -webkit-appearance: none; + border: 1px solid #000000; + height: 10px; + width: 30px; + margin-right: 50px; + border-radius: 3px; + background: #fff; + cursor: pointer; + outline: none; + margin-top: -3px; +} + +#zoomSliderElement::-ms-thumb:hover { + -webkit-appearance: none; + border: 1px solid #000000; + height: 10px; + width: 30px; + margin-right: 50px; + border-radius: 3px; + background: #d90; + cursor: pointer; + outline: none; + margin-top: -3px; +} + +#zoomSliderElement::-webkit-slider-thumb:hover { + -webkit-appearance: none; + border: 1px solid #000000; + height: 10px; + width: 30px; + margin-right: 50px; + border-radius: 3px; + background: #d90; + cursor: pointer; + outline: none; + margin-top: -3px; +} + +#zoomSliderElement::-moz-range-thumb { + border: 1px solid #000000; + height: 10px; + width: 30px; + border-radius: 3px; + /*background: #ffffff;*/ + cursor: pointer; + outline: none; +} + +#zoomSliderElement::-moz-range-thumb:hover { + border: 1px solid #000000; + height: 10px; + width: 30px; + border-radius: 3px; + background: #d90; + cursor: pointer; + outline: none; +} + +#zoomSliderElement::-moz-focus-outer { + border: 0; +} + +#locateSearchResult:focus { + outline: none; + +} + +a#locateSearchResult.highlighted:hover { + background-color: #d90; + color: red; +} + +a#locateSearchResult { + outline: none; + padding-bottom: 0; + padding-top: 0; + position: relative; + top: 5px; +} + +/*Editor hints*/ +#editorHint { + padding: 5px 5px; + position: absolute; + text-align: center; + width: 100%; + pointer-events: none; +} + +#editorHint label { + pointer-events: auto; + float: right; + padding: 5px 5px; + color: #ffdd00; +} + +#editorHint label:hover { + text-decoration: underline; + cursor: pointer; +} + +#editorHint > div { + pointer-events: auto; + text-align: left; + display: inline-block; + color: #ffffff; + font-size: 0.8em; + background-color: #18202A; + padding: 5px 5px; + border-radius: 5px; + +} + +#WarningErrorMessagesContainer { + position: absolute; + text-align: center; + top: 0; + pointer-events: none; +} + +/*Editor hints*/ +#WarningErrorMessages { + position: relative; + /*text-align: center;*/ + width: 50%; + pointer-events: auto; + margin: 10px 0; + padding-right: 12px; + overflow-y: auto; + overflow-x: hidden; +} + +#WarningErrorMessages label { + pointer-events: auto; + float: right; + padding: 5px 5px; + color: #ffdd00; +} + +#WarningErrorMessages span { + pointer-events: auto; + float: right; + padding: 5px 5px; +} + +#WarningErrorMessages label:hover { + text-decoration: underline; + cursor: pointer; +} + +#WarningErrorMessages > div { + pointer-events: auto; + text-align: left; + display: inline-block; + color: #ffffff; + font-size: 0.8em; + background-color: #18202A; + padding: 5px 5px; + border-radius: 10px; + border: solid 1px #ecf0f1; + width: 70%; + +} + +#WarningErrorMessagesContent > ul { + -webkit-padding-start: 20px; + padding: 0 16px; + +} + +#WarningErrorMessagesContent > ul > li { + padding: 5px; +} + +.converter-form-Editor { + /*display: inline-block;*/ +} + +.textLineEditWithLabel { + display: inline-block; + width: 100%; + border-bottom: 1px solid #34495E; + padding: 2px 0; + +} + +.converter-form-Editor label { + /*//display: inline-block;*/ + line-height: normal; +} + +.descriptionTextClass { + background-color: #34495E; + color: white; +} + +.prefixIRIElements input { + border: 1px solid #34495E; + background-color: #34495E; + color: white; +} + +.prefixIRIElements input:disabled { + background-color: rgb(24, 32, 42); + border: 1px solid rgb(24, 32, 42); + color: white; +} + +.converter-form-Editor input { + /*box-sizing: border-box;*/ + /*height: 18px;*/ + /*width: 69%;*/ + float: right; + border: 1px solid #34495E; + background-color: #34495E; + color: white; + /*border-bottom: 1px solid #d90;*/ + /*text-align: center;*/ + /*display: inline-block;*/ +} + +.converter-form-Editor input:disabled { + background-color: #545350; + border: 1px solid #34495E; + color: #939798; +} + +.disabledLabelForSlider { + color: #808080; +} diff --git a/doc/releases/0.1.0/data/webvowl/css/webvowl.css b/doc/releases/0.1.0/data/webvowl/css/webvowl.css new file mode 100644 index 0000000..bd06623 --- /dev/null +++ b/doc/releases/0.1.0/data/webvowl/css/webvowl.css @@ -0,0 +1,296 @@ +/*----------------------------------------------------------------- + VOWL graphical elements (part of spec) - mixed CSS and SVG styles +-----------------------------------------------------------------*/ + +/*-------- Text --------*/ +.text { + font-family: Helvetica, Arial, sans-serif; + font-size: 12px; +} + +.subtext { + font-size: 9px; +} + +.text.instance-count { + fill: #666; +} + +.external + text .instance-count { + fill: #aaa; +} + +.cardinality { + font-size: 10px; +} + +.text, .embedded { + pointer-events: none; +} + +/*------- Colors ------*/ +.class, .object, .disjoint, .objectproperty, .disjointwith, .equivalentproperty, .transitiveproperty, .functionalproperty, .inversefunctionalproperty, .symmetricproperty, .allvaluesfromproperty, .somevaluesfromproperty { + fill: #acf; +} + +.label .datatype, .datatypeproperty { + fill: #9c6; +} + +.rdf, .rdfproperty { + fill: #c9c; +} + +.literal, .node .datatype { + fill: #fc3; +} + +.deprecated, .deprecatedproperty { + fill: #ccc; +} + +.external, .externalproperty { + /*fill: #36c;*/ +} + +path, .nofill { + fill: none; +} + +marker path { + fill: #000; +} + +.class, path, line, .fineline { + stroke: #000; +} + +.white, .subclass, .subclassproperty, .external + text { + fill: #fff; +} + +.class.hovered, .property.hovered, .cardinality.hovered, .cardinality.focused, .filled.hovered, .filled.focused, .values-from.filled.hovered { + fill: #f00 !important; + cursor: pointer; +} + +.hoveredForEditing { + fill: #f00 !important; + cursor: pointer; +} + +.feature { + fill: #f00; + cursor: pointer; +} + +@-webkit-keyframes pulseAnimation { + 0% { + -webkit-transform: scale(1.5); + stroke-width: 3.33; + } + 50% { + stroke-width: 4; + } + 100% { + -webkit-transform: scale(1.0); + stroke-width: 5; + } +} + +@-moz-keyframes pulseAnimation { + 0% { + -webkit-transform: scale(1.5); + stroke-width: 3.33; + } + 50% { + stroke-width: 4; + } + 100% { + -webkit-transform: scale(1.0); + stroke-width: 5; + } +} + +@-o-keyframes pulseAnimation { + 0% { + -webkit-transform: scale(1.5); + stroke-width: 3.33; + } + 50% { + stroke-width: 4; + } + 100% { + -webkit-transform: scale(1.0); + stroke-width: 5; + } +} + +@keyframes pulseAnimation { + 0% { + -webkit-transform: scale(1.5); + stroke-width: 3.33; + } + 50% { + stroke-width: 4; + } + 100% { + -webkit-transform: scale(1.0); + stroke-width: 5; + } +} + +.searchResultA { + fill: none; + stroke-width: 5; + stroke: #f00; + -webkit-animation-name: pulseAnimation; + -moz-animation-name: pulseAnimation; + -o-animation-name: pulseAnimation; + animation-name: pulseAnimation; + + -webkit-animation-duration: 0.8s; + -moz-animation-duration: 0.8s; + -o-animation-duration: 0.8s; + animation-duration: 0.8s; + + -webkit-transform: translateZ(0); + -o-transform: translateZ(0); + -webkit-animation-iteration-count: 3; + -moz-animation-iteration-count: 3; + -o-animation-iteration-count: 3; + animation-iteration-count: 3; + + -webkit-animation-timing-function: linear; + -moz-animation-timing-function: linear; + -o-animation-timing-function: linear; + animation-timing-function: linear; + +} + +/* a class for not animated search results (hovered over node)*/ +.searchResultB { + fill: none; + stroke-width: 5; + stroke: #f00; +} + +.hovered-MathSymbol { + fill: none; + stroke: #f00 !important; +} + +.focused, path.hovered { + stroke: #f00 !important; +} + +.indirect-highlighting, .feature:hover { + fill: #f90; + cursor: pointer; +} + +.feature_hover { + fill: #f90; + cursor: pointer; +} + +.values-from { + stroke: #69c; +} + +.symbol, .values-from.filled { + fill: #69c; +} + +/*------- Strokes ------*/ +.class, path, line { + stroke-width: 2; +} + +.fineline { + stroke-width: 1; +} + +.dashed, .anonymous { + stroke-dasharray: 8; +} + +.dotted { + stroke-dasharray: 3; +} + +rect.focused, circle.focused { + stroke-width: 4px; +} + +.nostroke { + stroke: none; +} + +/*----------------------------------------------------------------- + Additional elements for the WebVOWL demo (NOT part of spec) +-----------------------------------------------------------------*/ + +.addDataPropertyElement { + fill: #9c6 !important; + cursor: pointer; + stroke-width: 2; + stroke: black; +} + +.addDataPropertyElement:hover { + fill: #f90 !important; + cursor: pointer; + stroke-width: 2; + stroke: black; +} + +.superHiddenElement { + fill: rgba(255, 153, 0, 0.4); + cursor: pointer; + stroke-width: 0; + stroke: black; + /*opacity:0;*/ +} + +.superOpacityElement { + opacity: 0; +} + +.deleteParentElement:hover { + fill: #f90; + cursor: pointer; + stroke-width: 2; + stroke: black; +} + +.deleteParentElement { + fill: #f00; + cursor: pointer; + stroke-width: 2; + stroke: black; +} + +.classNodeDragPath { + stroke: black; + stroke-width: 2px; +} + +.classDraggerNodeHovered { + fill: #f90; + stroke: black; + stroke-width: 2px; + cursor: pointer; +} + +.classDraggerNode { + fill: #acf; + stroke: black; + stroke-width: 2px; +} + +marker path { + /* Safari and Chrome workaround for inheriting the style of its link. + Use any value that is larger than the length of the marker path. */ + stroke-dasharray: 100; +} diff --git a/doc/releases/0.1.0/data/webvowl/data/foaf.json b/doc/releases/0.1.0/data/webvowl/data/foaf.json new file mode 100644 index 0000000..4897985 --- /dev/null +++ b/doc/releases/0.1.0/data/webvowl/data/foaf.json @@ -0,0 +1,2894 @@ +{ + "_comment" : "Created with OWL2VOWL (version 0.3.7), http://vowl.visualdataweb.org", + "header" : { + "languages" : [ "undefined" ], + "baseIris" : [ "http://schema.org", "http://www.w3.org/2000/01/rdf-schema", "http://www.w3.org/2003/01/geo/wgs84_pos", "http://purl.org/dc/terms", "http://www.w3.org/2001/XMLSchema", "http://xmlns.com/foaf/0.1", "http://www.w3.org/2000/10/swap/pim/contact", "http://www.w3.org/2004/02/skos/core" ], + "prefixList" : { + "owl" : "http://www.w3.org/2002/07/owl#", + "rdf" : "http://www.w3.org/1999/02/22-rdf-syntax-ns#", + "wot" : "http://xmlns.com/wot/0.1/", + "xsd" : "http://www.w3.org/2001/XMLSchema#", + "dc" : "http://purl.org/dc/elements/1.1/", + "xml" : "http://www.w3.org/XML/1998/namespace", + "vs" : "http://www.w3.org/2003/06/sw-vocab-status/ns#", + "foaf" : "http://xmlns.com/foaf/0.1/", + "rdfs" : "http://www.w3.org/2000/01/rdf-schema#" + }, + "title" : { + "undefined" : "Friend of a Friend (FOAF) vocabulary" + }, + "iri" : "http://xmlns.com/foaf/0.1/", + "description" : { + "undefined" : "The Friend of a Friend (FOAF) RDF vocabulary, described using W3C RDF Schema and the Web Ontology Language." + }, + "other" : { + "title" : [ { + "identifier" : "title", + "language" : "undefined", + "value" : "Friend of a Friend (FOAF) vocabulary", + "type" : "label" + } ] + } + }, + "namespace" : [ ], + "class" : [ { + "id" : "3", + "type" : "owl:Thing" + }, { + "id" : "9", + "type" : "owl:Class" + }, { + "id" : "1", + "type" : "owl:equivalentClass" + }, { + "id" : "18", + "type" : "owl:Thing" + }, { + "id" : "19", + "type" : "owl:Thing" + }, { + "id" : "5", + "type" : "owl:Thing" + }, { + "id" : "20", + "type" : "rdfs:Literal" + }, { + "id" : "8", + "type" : "rdfs:Literal" + }, { + "id" : "11", + "type" : "owl:Class" + }, { + "id" : "21", + "type" : "owl:Thing" + }, { + "id" : "22", + "type" : "rdfs:Literal" + }, { + "id" : "24", + "type" : "rdfs:Literal" + }, { + "id" : "26", + "type" : "rdfs:Literal" + }, { + "id" : "27", + "type" : "rdfs:Literal" + }, { + "id" : "37", + "type" : "owl:equivalentClass" + }, { + "id" : "45", + "type" : "rdfs:Literal" + }, { + "id" : "46", + "type" : "rdfs:Literal" + }, { + "id" : "53", + "type" : "rdfs:Literal" + }, { + "id" : "56", + "type" : "rdfs:Literal" + }, { + "id" : "59", + "type" : "rdfs:Literal" + }, { + "id" : "60", + "type" : "owl:Class" + }, { + "id" : "61", + "type" : "rdfs:Literal" + }, { + "id" : "6", + "type" : "rdfs:Literal" + }, { + "id" : "62", + "type" : "rdfs:Literal" + }, { + "id" : "12", + "type" : "owl:equivalentClass" + }, { + "id" : "55", + "type" : "rdfs:Literal" + }, { + "id" : "69", + "type" : "rdfs:Literal" + }, { + "id" : "71", + "type" : "owl:Class" + }, { + "id" : "36", + "type" : "owl:Class" + }, { + "id" : "86", + "type" : "owl:Class" + }, { + "id" : "83", + "type" : "owl:Class" + }, { + "id" : "94", + "type" : "owl:Class" + }, { + "id" : "73", + "type" : "rdfs:Literal" + }, { + "id" : "68", + "type" : "rdfs:Literal" + }, { + "id" : "93", + "type" : "rdfs:Literal" + }, { + "id" : "33", + "type" : "owl:Thing" + }, { + "id" : "49", + "type" : "rdfs:Literal" + }, { + "id" : "29", + "type" : "owl:Thing" + }, { + "id" : "101", + "type" : "rdfs:Literal" + }, { + "id" : "39", + "type" : "owl:Thing" + }, { + "id" : "63", + "type" : "owl:equivalentClass" + }, { + "id" : "64", + "type" : "owl:equivalentClass" + }, { + "id" : "102", + "type" : "owl:equivalentClass" + }, { + "id" : "78", + "type" : "owl:Class" + }, { + "id" : "77", + "type" : "owl:Class" + }, { + "id" : "13", + "type" : "owl:equivalentClass" + }, { + "id" : "58", + "type" : "rdfs:Literal" + }, { + "id" : "100", + "type" : "rdfs:Literal" + }, { + "id" : "106", + "type" : "rdfs:Literal" + }, { + "id" : "52", + "type" : "rdfs:Literal" + }, { + "id" : "88", + "type" : "rdfs:Literal" + }, { + "id" : "118", + "type" : "rdfs:Literal" + }, { + "id" : "126", + "type" : "owl:Class" + }, { + "id" : "2", + "type" : "owl:equivalentClass" + }, { + "id" : "32", + "type" : "owl:equivalentClass" + }, { + "id" : "10", + "type" : "owl:Class" + } ], + "classAttribute" : [ { + "iri" : "http://www.w3.org/2002/07/owl#Thing", + "baseIri" : "http://owl2vowl.de", + "id" : "3", + "label" : { + "undefined" : "Thing" + } + }, { + "iri" : "http://www.w3.org/2004/02/skos/core#Concept", + "baseIri" : "http://www.w3.org/2004/02/skos/core", + "instances" : 0, + "label" : { + "IRI-based" : "Concept", + "undefined" : "Concept" + }, + "attributes" : [ "external" ], + "id" : "9" + }, { + "iri" : "http://xmlns.com/foaf/0.1/Agent", + "equivalent" : [ "13" ], + "baseIri" : "http://xmlns.com/foaf/0.1", + "instances" : 0, + "annotations" : { + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "Agent", + "undefined" : "Agent" + }, + "subClasses" : [ "10", "11", "12" ], + "comment" : { + "undefined" : "An agent (eg. person, group, software or physical artifact)." + }, + "attributes" : [ "equivalent" ], + "id" : "1" + }, { + 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+ }, { + "id" : "81", + "type" : "owl:objectProperty" + }, { + "id" : "82", + "type" : "rdfs:SubClassOf" + }, { + "id" : "34", + "type" : "owl:objectProperty" + }, { + "id" : "85", + "type" : "rdfs:SubClassOf" + }, { + "id" : "87", + "type" : "owl:datatypeProperty" + }, { + "id" : "89", + "type" : "rdfs:SubClassOf" + }, { + "id" : "90", + "type" : "rdfs:SubClassOf" + }, { + "id" : "91", + "type" : "owl:objectProperty" + }, { + "id" : "92", + "type" : "owl:datatypeProperty" + }, { + "id" : "95", + "type" : "owl:datatypeProperty" + }, { + "id" : "96", + "type" : "owl:objectProperty" + }, { + "id" : "97", + "type" : "owl:datatypeProperty" + }, { + "id" : "98", + "type" : "rdfs:SubClassOf" + }, { + "id" : "99", + "type" : "owl:datatypeProperty" + }, { + "id" : "43", + "type" : "owl:objectProperty" + }, { + "id" : "42", + "type" : "owl:objectProperty" + }, { + "id" : "103", + "type" : "owl:datatypeProperty" + }, { + "id" : "104", + "type" : "owl:objectProperty" + }, { + "id" : "105", + "type" : "owl:datatypeProperty" + }, { + "id" : "107", + "type" : "owl:objectProperty" + }, { + "id" : "108", + "type" : "owl:datatypeProperty" + }, { + "id" : "109", + "type" : "owl:objectProperty" + }, { + "id" : "110", + "type" : "owl:objectProperty" + }, { + "id" : "40", + "type" : "owl:objectProperty" + }, { + "id" : "41", + "type" : "owl:objectProperty" + }, { + "id" : "84", + "type" : "owl:objectProperty" + }, { + "id" : "111", + "type" : "owl:datatypeProperty" + }, { + "id" : "112", + "type" : "owl:datatypeProperty" + }, { + "id" : "113", + "type" : "owl:datatypeProperty" + }, { + "id" : "114", + "type" : "owl:objectProperty" + }, { + "id" : "116", + "type" : "owl:disjointWith" + }, { + "id" : "117", + "type" : "owl:disjointWith" + }, { + "id" : "119", + "type" : "owl:datatypeProperty" + }, { + "id" : "120", + "type" : "owl:disjointWith" + }, { + "id" : "121", + "type" : "owl:disjointWith" + }, { + "id" : "122", + "type" : "owl:objectProperty" + }, { + "id" : "123", + "type" : "owl:datatypeProperty" + }, { + "id" : "124", + "type" : "owl:objectProperty" + }, { + "id" : "125", + "type" : "owl:datatypeProperty" + }, { + "id" : "127", + "type" : "owl:datatypeProperty" + }, { + "id" : "115", + "type" : "owl:objectProperty" + }, { + "id" : "128", + "type" : "owl:objectProperty" + }, { + "id" : "129", + "type" : "owl:objectProperty" + } ], + "propertyAttribute" : [ { + "iri" : "http://xmlns.com/foaf/0.1/interest", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "interest", + "undefined" : "interest" + }, + "domain" : "1", + "comment" : { + "undefined" : "A page about a topic of interest to this person." + }, + "attributes" : [ "object" ], + "id" : "0" + }, { + "iri" : "http://xmlns.com/foaf/0.1/mbox_sha1sum", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "6", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "mbox_sha1sum", + "undefined" : "sha1sum of a personal mailbox URI name" + }, + "domain" : "5", + "comment" : { + "undefined" : "The sha1sum of the URI of an Internet mailbox associated with exactly one owner, the first owner of the mailbox." + }, + "attributes" : [ "datatype" ], + "id" : "4" + }, { + "iri" : "http://xmlns.com/foaf/0.1/nick", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "8", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "nick", + "undefined" : "nickname" + }, + "domain" : "5", + "comment" : { + "undefined" : "A short informal nickname characterising an agent (includes login identifiers, IRC and other chat nicknames)." + }, + "attributes" : [ "datatype" ], + "id" : "7" + }, { + "iri" : "http://xmlns.com/foaf/0.1/openid", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "openid", + "undefined" : "openid" + }, + "superproperty" : [ "15" ], + "domain" : "1", + "comment" : { + "undefined" : "An OpenID for an Agent." + }, + "attributes" : [ "inverse functional", "object" ], + "id" : "14" + }, { + "iri" : "http://xmlns.com/foaf/0.1/workInfoHomepage", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "workInfoHomepage", + "undefined" : "work info homepage" + }, + "domain" : "12", + "comment" : { + "undefined" : "A work info homepage of some person; a page about their work for some organization." + }, + "attributes" : [ "object" ], + "id" : "16" + }, { + "iri" : "http://xmlns.com/foaf/0.1/pastProject", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "3", + "annotations" : { + "isDefinedBy" : [ { 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"comment" : { + "undefined" : "A theme." + }, + "attributes" : [ "object" ], + "id" : "23" + }, { + "iri" : "http://xmlns.com/foaf/0.1/knows", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "12", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "knows", + "undefined" : "knows" + }, + "domain" : "12", + "comment" : { + "undefined" : "A person known by this person (indicating some level of reciprocated interaction between the parties)." + }, + "attributes" : [ "object" ], + "id" : "25" + }, { + "iri" : "http://xmlns.com/foaf/0.1/focus", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "29", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + 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specified using fully qualified tel: URI scheme (refs: http://www.w3.org/Addressing/schemes.html#tel)." + }, + "attributes" : [ "object" ], + "id" : "30" + }, { + "iri" : "http://xmlns.com/foaf/0.1/depicts", + "inverse" : "34", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "33", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "depicts", + "undefined" : "depicts" + }, + "domain" : "32", + "comment" : { + "undefined" : "A thing depicted in this representation." + }, + "attributes" : [ "object" ], + "id" : "31" + }, { + "iri" : "http://xmlns.com/foaf/0.1/based_near", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "36", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", 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"undefined" : "DNA checksum" + }, + "domain" : "19", + "comment" : { + "undefined" : "A checksum for the DNA of some thing. 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"identifier" : "term_status", + "language" : "undefined", + "value" : "unstable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "status", + "undefined" : "status" + }, + "domain" : "1", + "comment" : { + "undefined" : "A string expressing what the user is happy for the general public (normally) to know about their current activity." + }, + "attributes" : [ "datatype" ], + "id" : "65" + }, { + "iri" : "http://xmlns.com/foaf/0.1/yahooChatID", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "46", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "yahooChatID", + "undefined" : "Yahoo chat ID" + }, + "domain" : "19", + "comment" : { + "undefined" : "A Yahoo chat ID" + }, + "attributes" : [ 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"undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "icqChatID", + "undefined" : "ICQ chat ID" + }, + "domain" : "19", + "comment" : { + "undefined" : "An ICQ chat ID" + }, + "attributes" : [ "datatype" ], + "id" : "70" + }, { + "iri" : "http://xmlns.com/foaf/0.1/givenname", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "73", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "archaic", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "givenname", + "undefined" : "Given name" + }, + "domain" : "19", + "comment" : { + "undefined" : "The given name of some person." + }, + "attributes" : [ "datatype" ], + "id" : "72" + }, { + "iri" : "http://xmlns.com/foaf/0.1/isPrimaryTopicOf", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "isPrimaryTopicOf", + "undefined" : "is primary topic of" + }, + "superproperty" : [ "38" ], + "domain" : "39", + "subproperty" : [ "14", "43" ], + "comment" : { + "undefined" : "A document that this thing is the primary topic of." + }, + "attributes" : [ "inverse functional", "object" ], + "id" : "15" + }, { + "range" : "2", + "domain" : "32", + "attributes" : [ "anonymous", "object" ], + "id" : "74" + }, { + "range" : "2", + "domain" : "71", + "attributes" : [ "anonymous", "object" ], + "id" : "75" + }, { + "range" : "78", + "domain" : "77", + "attributes" : [ "anonymous", "object" ], + "id" : "76" + }, { + "range" : "36", + "domain" : "12", + "attributes" : [ "anonymous", "object" ], + "id" : "79" + }, { + "iri" : "http://xmlns.com/foaf/0.1/accountServiceHomepage", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "accountServiceHomepage", + "undefined" : "account service homepage" + }, + "domain" : "78", + "comment" : { + "undefined" : "Indicates a homepage of the service provide for this online account." + }, + "attributes" : [ "object" ], + "id" : "80" + }, { + "iri" : "http://xmlns.com/foaf/0.1/logo", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "19", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "logo", + "undefined" : "logo" + }, + "domain" : "19", + "comment" : { + "undefined" : "A logo representing some thing." + }, + "attributes" : [ "inverse functional", "object" ], + "id" : "81" + }, { + "range" : "78", + "domain" : "83", + "attributes" : [ "anonymous", "object" ], + "id" : "82" + }, { + "iri" : "http://xmlns.com/foaf/0.1/depiction", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "32", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "depiction", + "undefined" : "depiction" + }, + "domain" : "33", + "subproperty" : [ "84" ], + "comment" : { + "undefined" : "A depiction of some thing." + }, + "attributes" : [ "object" ], + "id" : "34" + }, { + "range" : "78", + "domain" : "86", + "attributes" : [ "anonymous", "object" ], + "id" : "85" + }, { + "iri" : "http://xmlns.com/foaf/0.1/family_name", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "88", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "archaic", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "family_name", + "undefined" : "family_name" + }, + "domain" : "12", + "comment" : { + "undefined" : "The family name of some person." + }, + "attributes" : [ "datatype" ], + "id" : "87" + }, { + "range" : "1", + "domain" : "12", + "attributes" : [ "anonymous", "object" ], + "id" : "89" + }, { + "range" : "1", + "domain" : "11", + "attributes" : [ "anonymous", "object" ], + "id" : "90" + }, { + "iri" : "http://xmlns.com/foaf/0.1/fundedBy", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "19", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "archaic", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "fundedBy", + "undefined" : "funded by" + }, + "domain" : "19", + "comment" : { + "undefined" : "An organization funding a project or person." + }, + "attributes" : [ "object" ], + "id" : "91" + }, { + "iri" : "http://xmlns.com/foaf/0.1/title", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "93", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "title", + "undefined" : "title" + }, + "domain" : "19", + "comment" : { + "undefined" : "Title (Mr, Mrs, Ms, Dr. etc)" + }, + "attributes" : [ "datatype" ], + "id" : "92" + }, { + "iri" : "http://xmlns.com/foaf/0.1/accountName", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "59", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "accountName", + "undefined" : "account name" + }, + "domain" : "78", + "comment" : { + "undefined" : "Indicates the name (identifier) associated with this online account." + }, + "attributes" : [ "datatype" ], + "id" : "95" + }, { + "iri" : "http://xmlns.com/foaf/0.1/account", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "78", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "account", + "undefined" : "account" + }, + "domain" : "1", + "comment" : { + "undefined" : "Indicates an account held by this agent." + }, + "attributes" : [ "object" ], + "id" : "96" + }, { + "iri" : "http://xmlns.com/foaf/0.1/jabberID", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "69", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "jabberID", + "undefined" : "jabber ID" + }, + "domain" : "19", + "comment" : { + "undefined" : "A jabber ID for something." + }, + "attributes" : [ "datatype" ], + "id" : "97" + }, { + "range" : "1", + "domain" : "10", + "attributes" : [ "anonymous", "object" ], + "id" : "98" + }, { + "iri" : "http://xmlns.com/foaf/0.1/age", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "100", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "unstable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "age", + "undefined" : "age" + }, + "domain" : "1", + "comment" : { + "undefined" : "The age in years of some agent." + }, + "attributes" : [ "datatype", "functional" ], + "id" : "99" + }, { + "iri" : "http://xmlns.com/foaf/0.1/homepage", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "homepage", + "undefined" : "homepage" + }, + "superproperty" : [ "15", "38" ], + "domain" : "39", + "comment" : { + "undefined" : "A homepage for some thing." + }, + "attributes" : [ "inverse functional", "object" ], + "id" : "43" + }, { + "iri" : "http://xmlns.com/foaf/0.1/tipjar", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "tipjar", + "undefined" : "tipjar" + }, + "superproperty" : [ "38" ], + "domain" : "1", + "comment" : { + "undefined" : "A tipjar document for this agent, describing means for payment and reward." + }, + "attributes" : [ "object" ], + "id" : "42" + }, { + "iri" : "http://xmlns.com/foaf/0.1/msnChatID", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "61", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "msnChatID", + "undefined" : "MSN chat ID" + }, + "domain" : "5", + "comment" : { + "undefined" : "An MSN chat ID" + }, + "attributes" : [ "datatype" ], + "id" : "103" + }, { + "iri" : "http://xmlns.com/foaf/0.1/topic_interest", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "18", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "topic_interest", + "undefined" : "topic_interest" + }, + "domain" : "1", + "comment" : { + "undefined" : "A thing of interest to this person." + }, + "attributes" : [ "object" ], + "id" : "104" + }, { + "iri" : "http://xmlns.com/foaf/0.1/aimChatID", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "106", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "aimChatID", + "undefined" : "AIM chat ID" + }, + "domain" : "19", + "comment" : { + "undefined" : "An AIM chat ID" + }, + "attributes" : [ "datatype" ], + "id" : "105" + }, { + "iri" : "http://xmlns.com/foaf/0.1/currentProject", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "3", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "currentProject", + "undefined" : "current project" + }, + "domain" : "12", + "comment" : { + "undefined" : "A current project this person works on." + }, + "attributes" : [ "object" ], + "id" : "107" + }, { + "iri" : "http://xmlns.com/foaf/0.1/skypeID", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "20", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "skypeID", + "undefined" : "Skype ID" + }, + "domain" : "1", + "comment" : { + "undefined" : "A Skype ID" + }, + "attributes" : [ "datatype" ], + "id" : "108" + }, { + "iri" : "http://xmlns.com/foaf/0.1/holdsAccount", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "78", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "archaic", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "holdsAccount", + "undefined" : "account" + }, + "domain" : "1", + "comment" : { + "undefined" : "Indicates an account held by this agent." + }, + "attributes" : [ "object" ], + "id" : "109" + }, { + "iri" : "http://xmlns.com/foaf/0.1/thumbnail", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "32", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "thumbnail", + "undefined" : "thumbnail" + }, + "domain" : "32", + "comment" : { + "undefined" : "A derived thumbnail image." + }, + "attributes" : [ "object" ], + "id" : "110" + }, { + "iri" : "http://xmlns.com/foaf/0.1/topic", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "39", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "topic", + "undefined" : "topic" + }, + "domain" : "2", + "comment" : { + "undefined" : "A topic of some page or document." + }, + "attributes" : [ "object" ], + "id" : "40" + }, { + "iri" : "http://xmlns.com/foaf/0.1/weblog", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "weblog", + "undefined" : "weblog" + }, + "superproperty" : [ "38" ], + "domain" : "1", + "comment" : { + "undefined" : "A weblog of some thing (whether person, group, company etc.)." + }, + "attributes" : [ "inverse functional", "object" ], + "id" : "41" + }, { + "iri" : "http://xmlns.com/foaf/0.1/img", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "32", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "img", + "undefined" : "image" + }, + "superproperty" : [ "34" ], + "domain" : "12", + "comment" : { + "undefined" : "An image that can be used to represent some thing (ie. those depictions which are particularly representative of something, eg. one's photo on a homepage)." + }, + "attributes" : [ "object" ], + "id" : "84" + }, { + "iri" : "http://xmlns.com/foaf/0.1/birthday", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "56", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "unstable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "birthday", + "undefined" : "birthday" + }, + "domain" : "1", + "comment" : { + "undefined" : "The birthday of this Agent, represented in mm-dd string form, eg. '12-31'." + }, + "attributes" : [ "datatype", "functional" ], + "id" : "111" + }, { + "iri" : "http://xmlns.com/foaf/0.1/sha1", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "101", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "unstable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "sha1", + "undefined" : "sha1sum (hex)" + }, + "domain" : "2", + "comment" : { + "undefined" : "A sha1sum hash, in hex." + }, + "attributes" : [ "datatype" ], + "id" : "112" + }, { + "iri" : "http://xmlns.com/foaf/0.1/firstName", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "24", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "firstName", + "undefined" : "firstName" + }, + "domain" : "12", + "comment" : { + "undefined" : "The first name of a person." + }, + "attributes" : [ "datatype" ], + "id" : "113" + }, { + "iri" : "http://xmlns.com/foaf/0.1/made", + "inverse" : "115", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "18", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "made", + "undefined" : "made" + }, + "domain" : "1", + "comment" : { + "undefined" : "Something that was made by this agent." + }, + "attributes" : [ "object" ], + "id" : "114" + }, { + "range" : "60", + "domain" : "2", + "attributes" : [ "anonymous", "object" ], + "id" : "116" + }, { + "range" : "12", + "domain" : "60", + "attributes" : [ "anonymous", "object" ], + "id" : "117" + }, { + "iri" : "http://xmlns.com/foaf/0.1/familyName", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "62", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "familyName", + "undefined" : "familyName" + }, + "domain" : "12", + "comment" : { + "undefined" : "The family name of some person." + }, + "attributes" : [ "datatype" ], + "id" : "119" + }, { + "range" : "2", + "domain" : "11", + "attributes" : [ "anonymous", "object" ], + "id" : "120" + }, { + "range" : "12", + "domain" : "11", + "attributes" : [ "anonymous", "object" ], + "id" : "121" + }, { + "iri" : "http://xmlns.com/foaf/0.1/member", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "1", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "member", + "undefined" : "member" + }, + "domain" : "10", + "comment" : { + "undefined" : "Indicates a member of a Group" + }, + "attributes" : [ "object" ], + "id" : "122" + }, { + "iri" : "http://xmlns.com/foaf/0.1/plan", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "27", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "plan", + "undefined" : "plan" + }, + "domain" : "12", + "comment" : { + "undefined" : "A .plan comment, in the tradition of finger and '.plan' files." + }, + "attributes" : [ "datatype" ], + "id" : "123" + }, { + "iri" : "http://xmlns.com/foaf/0.1/mbox", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "18", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "mbox", + "undefined" : "personal mailbox" + }, + "domain" : "1", + "comment" : { + "undefined" : "A personal mailbox, ie. an Internet mailbox associated with exactly one owner, the first owner of this mailbox. This is a 'static inverse functional property', in that there is (across time and change) at most one individual that ever has any particular value for foaf:mbox." + }, + "attributes" : [ "inverse functional", "object" ], + "id" : "124" + }, { + "iri" : "http://xmlns.com/foaf/0.1/surname", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "118", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "archaic", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "surname", + "undefined" : "Surname" + }, + "domain" : "12", + "comment" : { + "undefined" : "The surname of some person." + }, + "attributes" : [ "datatype" ], + "id" : "125" + }, { + "iri" : "http://xmlns.com/foaf/0.1/myersBriggs", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "22", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "myersBriggs", + "undefined" : "myersBriggs" + }, + "domain" : "12", + "comment" : { + "undefined" : "A Myers Briggs (MBTI) personality classification." + }, + "attributes" : [ "datatype" ], + "id" : "127" + }, { + "iri" : "http://xmlns.com/foaf/0.1/maker", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "1", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "maker", + "undefined" : "maker" + }, + "domain" : "18", + "comment" : { + "undefined" : "An agent that made this thing." + }, + "attributes" : [ "object" ], + "id" : "115" + }, { + "iri" : "http://xmlns.com/foaf/0.1/publications", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "publications", + "undefined" : "publications" + }, + "domain" : "12", + "comment" : { + "undefined" : "A link to the publications of this person." + }, + "attributes" : [ "object" ], + "id" : "128" + }, { + "iri" : "http://xmlns.com/foaf/0.1/workplaceHomepage", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "workplaceHomepage", + "undefined" : "workplace homepage" + }, + "domain" : "12", + "comment" : { + "undefined" : "A workplace homepage of some person; the homepage of an organization they work for." + }, + "attributes" : [ "object" ], + "id" : "129" + } ] +} \ No newline at end of file diff --git a/doc/releases/0.1.0/data/webvowl/data/ontology.json b/doc/releases/0.1.0/data/webvowl/data/ontology.json new file mode 100644 index 0000000..220a467 --- /dev/null +++ b/doc/releases/0.1.0/data/webvowl/data/ontology.json @@ -0,0 +1,5928 @@ +{ + "_comment" : "Created with OWL2VOWL (version 0.3.5), http://vowl.visualdataweb.org", + "header" : { + "languages" : [ "en", "undefined" ], + "baseIris" : [ "http://www.w3.org/1999/02/22-rdf-syntax-ns", "http://purl.org/neao/data", "http://www.w3.org/2002/07/owl", "http://www.w3.org/2000/01/rdf-schema", "http://www.w3.org/2001/XMLSchema", "http://purl.org/neao/base" ], + "iri" : "http://purl.org/neao/data#", + "version" : "0.1.0", + "author" : [ "Michael Denker (ORCID: 0000-0003-1255-7300)", "Cristiano Köhler (ORCID: 0000-0003-0503-5264)" ], + "labels" : { + "en" : "Neuroelectrophysiology Analysis Ontology - Data" + }, + "comments" : { + "en" : "This module in the Neuroelectrophysiology Analysis Ontology contains classes that represent data entities in the analysis of neuroelectrophysiology data.\n\nThe classes in this module are subclasses of the Data base class, and are associated with the distinct steps throughout the analysis (defined in the steps module) by the hasInput and hasOutput object properties.\n\nAdditional information on the data entity can be described. The electrophysiology recording source associated with the data can be defined with the hasSource object property that points to individuals of the ElectrophysiologySignalSource class. In addition, information on the structure of the data (e.g., matrix, array) can be provided with the isRepresentedAs object property that points to individuals of the DataRepresentation class. The objective of NEAO is not to model the sources and formats of the data, but these classes can be used as abstractions to align other ontologies that are defined with that purpose. These properties and classes are defined in the base module.\n\nFinally, several data properties are also defined to provide extended information on the data entity (e.g., isNormalized or isArtificial). These properties can be used to define additional semantic groupings to make inferences on the data and analysis (e.g., artificial data is defined by the ArtificialData class)." + }, + "other" : { + "license" : [ { + "identifier" : "license", + "language" : "undefined", + "value" : "https://creativecommons.org/licenses/by/4.0/", + "type" : "iri" + } ], + "creator" : [ { + "identifier" : "creator", + "language" : "undefined", + "value" : "Cristiano Köhler (ORCID: 0000-0003-0503-5264)", + "type" : "label" + }, { + "identifier" : "creator", + "language" : "undefined", + "value" : "Michael Denker (ORCID: 0000-0003-1255-7300)", + "type" : "label" + } ], + "created" : [ { + "identifier" : "created", + "language" : "undefined", + "value" : "2022-01-19", + "type" : "label" + } ], + "preferredNamespacePrefix" : [ { + "identifier" : "preferredNamespacePrefix", + "language" : "undefined", + "value" : "neao_data", + "type" : "label" + } ], + "versionInfo" : [ { + "identifier" : "versionInfo", + "language" : "undefined", + "value" : "0.1.0", + "type" : "label" + } ], + "preferredNamespaceUri" : [ { + "identifier" : "preferredNamespaceUri", + "language" : "undefined", + "value" : "http://purl.org/neao/data#", + "type" : "label" + } ] + } + }, + "namespace" : [ ], + "class" : [ { + "id" : "9", + "type" : "owl:Class" + }, { + "id" : "15", + "type" : "owl:Class" + }, { + "id" : "16", + "type" : "owl:Class" + }, { + "id" : "10", + "type" : "owl:Class" + }, { + "id" : "22", + "type" : "owl:Class" + }, { + "id" : "28", + "type" : "owl:Class" + }, { + "id" : "29", + "type" : "owl:Class" + }, { + "id" : "31", + "type" : "owl:Class" + }, { + "id" : "33", + "type" : "owl:Class" + }, { + "id" : "35", + "type" : "owl:Class" + }, { + "id" : "36", + "type" : "owl:Class" + }, { + "id" : "38", + "type" : "owl:Class" + }, { + "id" : "39", + "type" : "owl:Class" + }, { + "id" : "46", + "type" : "owl:Class" + }, { + "id" : "57", + "type" : "owl:Class" + }, { + "id" : "68", + "type" : "owl:Class" 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Symbol.toStringTag : undefined; + + /** + * The base implementation of `getTag` without fallbacks for buggy environments. + * + * @private + * @param {*} value The value to query. + * @returns {string} Returns the `toStringTag`. + */ + function baseGetTag(value) { + if (value == null) { + return value === undefined ? undefinedTag : nullTag; + } + return (symToStringTag && symToStringTag in Object(value)) + ? getRawTag(value) + : objectToString(value); + } + + module.exports = baseGetTag; + + +/***/ }), + +/***/ 92: +/***/ (function(module, exports, __webpack_require__) { + + var root = __webpack_require__(93); + + /** Built-in value references. */ + var Symbol = root.Symbol; + + module.exports = Symbol; + + +/***/ }), + +/***/ 93: +/***/ (function(module, exports, __webpack_require__) { + + var freeGlobal = __webpack_require__(94); + + /** Detect free variable `self`. */ + var freeSelf = typeof self == 'object' && self && self.Object === Object && self; + + /** Used as a reference to the global object. */ + var root = freeGlobal || freeSelf || Function('return this')(); + + module.exports = root; + + +/***/ }), + +/***/ 94: +/***/ (function(module, exports) { + + /* WEBPACK VAR INJECTION */(function(global) {/** Detect free variable `global` from Node.js. */ + var freeGlobal = typeof global == 'object' && global && global.Object === Object && global; + + module.exports = freeGlobal; + + /* WEBPACK VAR INJECTION */}.call(exports, (function() { return this; }()))) + +/***/ }), + +/***/ 95: +/***/ (function(module, exports, __webpack_require__) { + + var Symbol = __webpack_require__(92); + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * Used to resolve the + * [`toStringTag`](http://ecma-international.org/ecma-262/7.0/#sec-object.prototype.tostring) + * of values. + */ + var nativeObjectToString = objectProto.toString; + + /** Built-in value references. */ + var symToStringTag = Symbol ? Symbol.toStringTag : undefined; + + /** + * A specialized version of `baseGetTag` which ignores `Symbol.toStringTag` values. + * + * @private + * @param {*} value The value to query. + * @returns {string} Returns the raw `toStringTag`. + */ + function getRawTag(value) { + var isOwn = hasOwnProperty.call(value, symToStringTag), + tag = value[symToStringTag]; + + try { + value[symToStringTag] = undefined; + var unmasked = true; + } catch (e) {} + + var result = nativeObjectToString.call(value); + if (unmasked) { + if (isOwn) { + value[symToStringTag] = tag; + } else { + delete value[symToStringTag]; + } + } + return result; + } + + module.exports = getRawTag; + + +/***/ }), + +/***/ 96: +/***/ (function(module, exports) { + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** + * Used to resolve the + * [`toStringTag`](http://ecma-international.org/ecma-262/7.0/#sec-object.prototype.tostring) + * of values. + */ + var nativeObjectToString = objectProto.toString; + + /** + * Converts `value` to a string using `Object.prototype.toString`. + * + * @private + * @param {*} value The value to convert. + * @returns {string} Returns the converted string. + */ + function objectToString(value) { + return nativeObjectToString.call(value); + } + + module.exports = objectToString; + + +/***/ }), + +/***/ 103: +/***/ (function(module, exports, __webpack_require__) { + + var baseGetTag = __webpack_require__(91), + isObjectLike = __webpack_require__(104); + + /** `Object#toString` result references. */ + var symbolTag = '[object Symbol]'; + + /** + * Checks if `value` is classified as a `Symbol` primitive or object. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a symbol, else `false`. + * @example + * + * _.isSymbol(Symbol.iterator); + * // => true + * + * _.isSymbol('abc'); + * // => false + */ + function isSymbol(value) { + return typeof value == 'symbol' || + (isObjectLike(value) && baseGetTag(value) == symbolTag); + } + + module.exports = isSymbol; + + +/***/ }), + +/***/ 104: +/***/ (function(module, exports) { + + /** + * Checks if `value` is object-like. A value is object-like if it's not `null` + * and has a `typeof` result of "object". + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is object-like, else `false`. + * @example + * + * _.isObjectLike({}); + * // => true + * + * _.isObjectLike([1, 2, 3]); + * // => true + * + * _.isObjectLike(_.noop); + * // => false + * + * _.isObjectLike(null); + * // => false + */ + function isObjectLike(value) { + return value != null && typeof value == 'object'; + } + + module.exports = isObjectLike; + + +/***/ }), + +/***/ 112: +/***/ (function(module, exports) { + + /** + * Checks if `value` is classified as an `Array` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an array, else `false`. + * @example + * + * _.isArray([1, 2, 3]); + * // => true + * + * _.isArray(document.body.children); + * // => false + * + * _.isArray('abc'); + * // => false + * + * _.isArray(_.noop); + * // => false + */ + var isArray = Array.isArray; + + module.exports = isArray; + + +/***/ }), + +/***/ 154: +/***/ (function(module, exports) { + + /** + * A specialized version of `_.map` for arrays without support for iteratee + * shorthands. + * + * @private + * @param {Array} [array] The array to iterate over. + * @param {Function} iteratee The function invoked per iteration. + * @returns {Array} Returns the new mapped array. + */ + function arrayMap(array, iteratee) { + var index = -1, + length = array == null ? 0 : array.length, + result = Array(length); + + while (++index < length) { + result[index] = iteratee(array[index], index, array); + } + return result; + } + + module.exports = arrayMap; + + +/***/ }), + +/***/ 219: +/***/ (function(module, exports, __webpack_require__) { + + var baseToString = __webpack_require__(220); + + /** + * Converts `value` to a string. An empty string is returned for `null` + * and `undefined` values. The sign of `-0` is preserved. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to convert. + * @returns {string} Returns the converted string. + * @example + * + * _.toString(null); + * // => '' + * + * _.toString(-0); + * // => '-0' + * + * _.toString([1, 2, 3]); + * // => '1,2,3' + */ + function toString(value) { + return value == null ? '' : baseToString(value); + } + + module.exports = toString; + + +/***/ }), + +/***/ 220: +/***/ (function(module, exports, __webpack_require__) { + + var Symbol = __webpack_require__(92), + arrayMap = __webpack_require__(154), + isArray = __webpack_require__(112), + isSymbol = __webpack_require__(103); + + /** Used as references for various `Number` constants. */ + var INFINITY = 1 / 0; + + /** Used to convert symbols to primitives and strings. */ + var symbolProto = Symbol ? Symbol.prototype : undefined, + symbolToString = symbolProto ? symbolProto.toString : undefined; + + /** + * The base implementation of `_.toString` which doesn't convert nullish + * values to empty strings. + * + * @private + * @param {*} value The value to process. + * @returns {string} Returns the string. + */ + function baseToString(value) { + // Exit early for strings to avoid a performance hit in some environments. + if (typeof value == 'string') { + return value; + } + if (isArray(value)) { + // Recursively convert values (susceptible to call stack limits). + return arrayMap(value, baseToString) + ''; + } + if (isSymbol(value)) { + return symbolToString ? symbolToString.call(value) : ''; + } + var result = (value + ''); + return (result == '0' && (1 / value) == -INFINITY) ? 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+ } + + } + + module.exports = showBrowserWarningIfRequired; + showBrowserWarningIfRequired(); + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 322: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {String.prototype.replaceAll = function ( search, replacement ){ + var target = this; + return target.split(search).join(replacement); + }; + module.exports = function (){ + var newOntologyCounter = 1; + var app = {}, + graph = webvowl.graph(), + options = graph.graphOptions(), + languageTools = webvowl.util.languageTools(), + GRAPH_SELECTOR = "#graph", + // Modules for the webvowl app + exportMenu = __webpack_require__(323)(graph), + filterMenu = __webpack_require__(325)(graph), + gravityMenu = __webpack_require__(326)(graph), + modeMenu = __webpack_require__(327)(graph), + debugMenu = __webpack_require__(328)(graph), + ontologyMenu = __webpack_require__(329)(graph), + pauseMenu = __webpack_require__(333)(graph), + resetMenu = __webpack_require__(334)(graph), + searchMenu = __webpack_require__(335)(graph), + navigationMenu = __webpack_require__(336)(graph), + zoomSlider = __webpack_require__(337)(graph), + sidebar = __webpack_require__(338)(graph), + leftSidebar = __webpack_require__(339)(graph), + editSidebar = __webpack_require__(340)(graph), + configMenu = __webpack_require__(341)(graph), + loadingModule = __webpack_require__(342)(graph), + warningModule = __webpack_require__(343)(graph), + directInputMod = __webpack_require__(344)(graph), + + + // Graph modules + colorExternalsSwitch = webvowl.modules.colorExternalsSwitch(graph), + compactNotationSwitch = webvowl.modules.compactNotationSwitch(graph), + datatypeFilter = webvowl.modules.datatypeFilter(), + disjointFilter = webvowl.modules.disjointFilter(), + focuser = webvowl.modules.focuser(graph), + emptyLiteralFilter = webvowl.modules.emptyLiteralFilter(), + nodeDegreeFilter = webvowl.modules.nodeDegreeFilter(filterMenu), + nodeScalingSwitch = webvowl.modules.nodeScalingSwitch(graph), + objectPropertyFilter = webvowl.modules.objectPropertyFilter(), + pickAndPin = webvowl.modules.pickAndPin(), + selectionDetailDisplayer = webvowl.modules.selectionDetailsDisplayer(sidebar.updateSelectionInformation), + statistics = webvowl.modules.statistics(), + subclassFilter = webvowl.modules.subclassFilter(), + setOperatorFilter = webvowl.modules.setOperatorFilter(); + + + app.getOptions = function (){ + return webvowl.opts; + }; + app.getGraph = function (){ + return webvowl.gr; + }; + // app.afterInitializationCallback=undefined; + + + var executeFileDrop = false; + var wasMessageToShow = false; + var firstTime = false; + + function addFileDropEvents( selector ){ + var node = d3.select(selector); + + node.node().ondragover = function ( e ){ + e.preventDefault(); + + d3.select("#dragDropContainer").classed("hidden", false); + // get svg size + var w = graph.options().width(); + var h = graph.options().height(); + + // get event position; (using clientX and clientY); + var cx = e.clientX; + var cy = e.clientY; + + if ( firstTime === false ) { + var state = d3.select("#loading-info").classed("hidden"); + wasMessageToShow = !state; + firstTime = true; + d3.select("#loading-info").classed("hidden", true); // hide it so it does not conflict with drop event + var bb=d3.select("#drag_msg").node().getBoundingClientRect(); + var hs = bb.height; + var ws = bb.width; + + var icon_scale=Math.min(hs,ws); + icon_scale/=100; + + d3.select("#drag_icon_group").attr("transform", "translate ( " + 0.25 * ws + " " + 0.25 * hs + ")"); + d3.select("#drag_icon").attr("transform","matrix ("+icon_scale+",0,0,"+icon_scale+",0,0)"); + d3.select("#drag_icon_drop").attr("transform","matrix ("+icon_scale+",0,0,"+icon_scale+",0,0)"); + } + + + if ( (cx > 0.25 * w && cx < 0.75 * w) && (cy > 0.25 * h && cy < 0.75 * h) ) { + + d3.select("#drag_msg_text").node().innerHTML = "Drop it here."; + d3.select("#drag_msg").style("background-color", "#67bc0f"); + d3.select("#drag_msg").style("color", "#000000"); + executeFileDrop = true; + // d3.select("#drag_svg").transition() + // .duration(100) + // // .attr("-webkit-transform", "rotate(90)") + // // .attr("-moz-transform", "rotate(90)") + // // .attr("-o-transform", "rotate(90)") + // .attr("transform", "rotate(90)"); + + d3.select("#drag_icon").classed("hidden",true); + d3.select("#drag_icon_drop").classed("hidden",false); + + + } else { + d3.select("#drag_msg_text").node().innerHTML = "Drag ontology file here."; + d3.select("#drag_msg").style("background-color", "#fefefe"); + d3.select("#drag_msg").style("color", "#000000"); + executeFileDrop = false; + + d3.select("#drag_icon").classed("hidden",false); + d3.select("#drag_icon_drop").classed("hidden",true); + + + // d3.select("#drag_svg").transition() + // .duration(100) + // // .attr("-webkit-transform", "rotate(0)") + // // .attr("-moz-transform", "rotate(0)") + // // .attr("-o-transform", "rotate(0)") + // .attr("transform", "rotate(0)"); + // + } + + }; + node.node().ondrop = function ( ev ){ + ev.preventDefault(); + firstTime = false; + if ( executeFileDrop ) { + if ( ev.dataTransfer.items ) { + if ( ev.dataTransfer.items.length === 1 ) { + if ( ev.dataTransfer.items[0].kind === 'file' ) { + var file = ev.dataTransfer.items[0].getAsFile(); + graph.options().loadingModule().fromFileDrop(file.name, file); + } + } + else { + // >> WARNING not multiple file uploaded; + graph.options().warningModule().showMultiFileUploadWarning(); + } + } + } + d3.select("#dragDropContainer").classed("hidden", true); + }; + + node.node().ondragleave = function ( e ){ + var w = graph.options().width(); + var h = graph.options().height(); + + // get event position; (using clientX and clientY); + var cx = e.clientX; + var cy = e.clientY; + + var hidden = false; + firstTime = false; + + if ( cx < 0.1 * w || cx > 0.9 * w ) hidden = true; + if ( cy < 0.1 * h || cy > 0.9 * h ) hidden = true; + d3.select("#dragDropContainer").classed("hidden", hidden); + + d3.select("#loading-info").classed("hidden", !wasMessageToShow); // show it again + // check if it should be visible + var should_show=graph.options().loadingModule().getMessageVisibilityStatus(); + if (should_show===false){ + d3.select("#loading-info").classed("hidden", true); // hide it + } + }; + + } + + + app.initialize = function (){ + addFileDropEvents(GRAPH_SELECTOR); + + window.requestAnimationFrame = window.requestAnimationFrame || window.mozRequestAnimationFrame || window.webkitRequestAnimationFrame || window.msRequestAnimationFrame || function ( f ){ + return setTimeout(f, 1000 / 60); + }; // simulate calling code 60 + window.cancelAnimationFrame = window.cancelAnimationFrame || window.mozCancelAnimationFrame || function ( requestID ){ + clearTimeout(requestID); + }; //fall back + + options.graphContainerSelector(GRAPH_SELECTOR); + options.selectionModules().push(focuser); + options.selectionModules().push(selectionDetailDisplayer); + options.selectionModules().push(pickAndPin); + + options.filterModules().push(emptyLiteralFilter); + options.filterModules().push(statistics); + + options.filterModules().push(nodeDegreeFilter); + options.filterModules().push(datatypeFilter); + options.filterModules().push(objectPropertyFilter); + options.filterModules().push(subclassFilter); + options.filterModules().push(disjointFilter); + options.filterModules().push(setOperatorFilter); + options.filterModules().push(nodeScalingSwitch); + options.filterModules().push(compactNotationSwitch); + options.filterModules().push(colorExternalsSwitch); + + d3.select(window).on("resize", adjustSize); + + exportMenu.setup(); + gravityMenu.setup(); + filterMenu.setup(datatypeFilter, objectPropertyFilter, subclassFilter, disjointFilter, setOperatorFilter, nodeDegreeFilter); + modeMenu.setup(pickAndPin, nodeScalingSwitch, compactNotationSwitch, colorExternalsSwitch); + pauseMenu.setup(); + sidebar.setup(); + loadingModule.setup(); + leftSidebar.setup(); + editSidebar.setup(); + debugMenu.setup(); + var agentVersion = getInternetExplorerVersion(); + if ( agentVersion > 0 && agentVersion <= 11 ) { + console.log("Agent version " + agentVersion); + console.log("This agent is not supported"); + d3.select("#browserCheck").classed("hidden", false); + d3.select("#killWarning").classed("hidden", true); + d3.select("#optionsArea").classed("hidden", true); + d3.select("#logo").classed("hidden", true); + } else { + d3.select("#logo").classed("hidden", false); + if ( agentVersion === 12 ) { + // allow Mircosoft Edge Browser but with warning + d3.select("#browserCheck").classed("hidden", false); + d3.select("#killWarning").classed("hidden", false); + } else { + d3.select("#browserCheck").classed("hidden", true); + } + + resetMenu.setup([gravityMenu, filterMenu, modeMenu, focuser, selectionDetailDisplayer, pauseMenu]); + searchMenu.setup(); + navigationMenu.setup(); + zoomSlider.setup(); + + // give the options the pointer to the some menus for import and export + options.literalFilter(emptyLiteralFilter); + options.nodeDegreeFilter(nodeDegreeFilter); + options.loadingModule(loadingModule); + options.filterMenu(filterMenu); + options.modeMenu(modeMenu); + options.gravityMenu(gravityMenu); + options.pausedMenu(pauseMenu); + options.pickAndPinModule(pickAndPin); + options.resetMenu(resetMenu); + options.searchMenu(searchMenu); + options.ontologyMenu(ontologyMenu); + options.navigationMenu(navigationMenu); + options.sidebar(sidebar); + options.leftSidebar(leftSidebar); + options.editSidebar(editSidebar); + options.exportMenu(exportMenu); + options.graphObject(graph); + options.zoomSlider(zoomSlider); + options.warningModule(warningModule); + options.directInputModule(directInputMod); + options.datatypeFilter(datatypeFilter); + options.objectPropertyFilter(objectPropertyFilter); + options.subclassFilter(subclassFilter); + options.setOperatorFilter(setOperatorFilter); + options.disjointPropertyFilter(disjointFilter); + options.focuserModule(focuser); + options.colorExternalsModule(colorExternalsSwitch); + options.compactNotationModule(compactNotationSwitch); + + ontologyMenu.setup(loadOntologyFromText); + configMenu.setup(); + + leftSidebar.showSidebar(0); + leftSidebar.hideCollapseButton(true); + + + graph.start(); + + var modeOp = d3.select("#modeOfOperationString"); + modeOp.style("font-size", "0.6em"); + modeOp.style("font-style", "italic"); + + adjustSize(); + var defZoom; + var w = graph.options().width(); + var h = graph.options().height(); + defZoom = Math.min(w, h) / 1000; + + var hideDebugOptions = true; + if ( hideDebugOptions === false ) { + graph.setForceTickFunctionWithFPS(); + } + + graph.setDefaultZoom(defZoom); + d3.selectAll(".debugOption").classed("hidden", hideDebugOptions); + + // prevent backspace reloading event + var htmlBody = d3.select("body"); + d3.select(document).on("keydown", function ( e ){ + if ( d3.event.keyCode === 8 && d3.event.target === htmlBody.node() ) { + // we could add here an alert + d3.event.preventDefault(); + } + // using ctrl+Shift+d as debug option + if ( d3.event.ctrlKey && d3.event.shiftKey && d3.event.keyCode === 68 ) { + graph.options().executeHiddenDebugFeatuers(); + d3.event.preventDefault(); + } + }); + if ( d3.select("#maxLabelWidthSliderOption") ) { + var setValue = !graph.options().dynamicLabelWidth(); + d3.select("#maxLabelWidthSlider").node().disabled = setValue; + d3.select("#maxLabelWidthvalueLabel").classed("disabledLabelForSlider", setValue); + d3.select("#maxLabelWidthDescriptionLabel").classed("disabledLabelForSlider", setValue); + } + + d3.select("#blockGraphInteractions").style("position", "absolute") + .style("top", "0") + .style("background-color", "#bdbdbd") + .style("opacity", "0.5") + .style("pointer-events", "auto") + .style("width", graph.options().width() + "px") + .style("height", graph.options().height() + "px") + .on("click", function (){ + d3.event.preventDefault(); + d3.event.stopPropagation(); + }) + .on("dblclick", function (){ + d3.event.preventDefault(); + d3.event.stopPropagation(); + }); + + d3.select("#direct-text-input").on("click", function (){ + directInputMod.setDirectInputMode(); + }); + d3.select("#blockGraphInteractions").node().draggable = false; + options.prefixModule(webvowl.util.prefixTools(graph)); + adjustSize(); + sidebar.updateOntologyInformation(undefined, statistics); + loadingModule.parseUrlAndLoadOntology(); // loads automatically the ontology provided by the parameters + options.debugMenu(debugMenu); + debugMenu.updateSettings(); + + // connect the reloadCachedVersionButton + d3.select("#reloadSvgIcon").on("click", function (){ + if ( d3.select("#reloadSvgIcon").node().disabled === true ) { + graph.options().ontologyMenu().clearCachedVersion(); + return; + } + d3.select("#reloadCachedOntology").classed("hidden", true); + graph.options().ontologyMenu().reloadCachedOntology(); + + }); + // add the initialized objects + webvowl.opts = options; + webvowl.gr = graph; + + } + }; + + + function loadOntologyFromText( jsonText, filename, alternativeFilename ){ + d3.select("#reloadCachedOntology").classed("hidden", true); + pauseMenu.reset(); + graph.options().navigationMenu().hideAllMenus(); + + if ( (jsonText === undefined && filename === undefined) || (jsonText.length === 0) ) { + loadingModule.notValidJsonFile(); + return; + } + graph.editorMode(); // updates the checkbox + var data; + if ( jsonText ) { + // validate JSON FILE + var validJSON; + try { + data = JSON.parse(jsonText); + validJSON = true; + } catch ( e ) { + validJSON = false; + } + if ( validJSON === false ) { + // the server output is not a valid json file + loadingModule.notValidJsonFile(); + return; + } + + if ( !filename ) { + // First look if an ontology title exists, otherwise take the alternative filename + var ontologyNames = data.header ? data.header.title : undefined; + var ontologyName = languageTools.textInLanguage(ontologyNames); + + if ( ontologyName ) { + filename = ontologyName; + } else { + filename = alternativeFilename; + } + } + } + + + // check if we have graph data + var classCount = 0; + if ( data.class !== undefined ) { + classCount = data.class.length; + } + + var loadEmptyOntologyForEditing = false; + if ( location.hash.indexOf("#new_ontology") !== -1 ) { + loadEmptyOntologyForEditing = true; + newOntologyCounter++; + d3.select("#empty").node().href = "#opts=editorMode=true;#new_ontology" + newOntologyCounter; + } + if ( classCount === 0 && graph.editorMode() === false && loadEmptyOntologyForEditing === false ) { + // generate message for the user; + loadingModule.emptyGraphContentError(); + } else { + loadingModule.validJsonFile(); + ontologyMenu.setCachedOntology(filename, jsonText); + exportMenu.setJsonText(jsonText); + options.data(data); + graph.options().loadingModule().setPercentMode(); + if ( loadEmptyOntologyForEditing === true ) { + graph.editorMode(true); + + } + graph.load(); + sidebar.updateOntologyInformation(data, statistics); + exportMenu.setFilename(filename); + graph.updateZoomSliderValueFromOutside(); + adjustSize(); + + var flagOfCheckBox = d3.select("#editorModeModuleCheckbox").node().checked; + graph.editorMode(flagOfCheckBox);// update gui + + } + } + + function adjustSize(){ + var graphContainer = d3.select(GRAPH_SELECTOR), + svg = graphContainer.select("svg"), + height = window.innerHeight - 40, + width = window.innerWidth - (window.innerWidth * 0.22); + + if ( sidebar.getSidebarVisibility() === "0" ) { + height = window.innerHeight - 40; + width = window.innerWidth; + } + + directInputMod.updateLayout(); + d3.select("#blockGraphInteractions").style("width", window.innerWidth + "px"); + d3.select("#blockGraphInteractions").style("height", window.innerHeight + "px"); + + d3.select("#WarningErrorMessagesContainer").style("width", width + "px"); + d3.select("#WarningErrorMessagesContainer").style("height", height + "px"); + + d3.select("#WarningErrorMessages").style("max-height", (height - 12) + "px"); + + graphContainer.style("height", height + "px"); + svg.attr("width", width) + .attr("height", height); + + options.width(width) + .height(height); + + graph.updateStyle(); + + if ( isTouchDevice() === true ) { + if ( graph.isEditorMode() === true ) + d3.select("#modeOfOperationString").node().innerHTML = "touch able device detected"; + graph.setTouchDevice(true); + + } else { + if ( graph.isEditorMode() === true ) + d3.select("#modeOfOperationString").node().innerHTML = "point & click device detected"; + graph.setTouchDevice(false); + } + + d3.select("#loadingInfo-container").style("height", 0.5 * (height - 80) + "px"); + loadingModule.checkForScreenSize(); + + adjustSliderSize(); + // update also the padding options of loading and the logo positions; + var warningDiv = d3.select("#browserCheck"); + if ( warningDiv.classed("hidden") === false ) { + var offset = 10 + warningDiv.node().getBoundingClientRect().height; + d3.select("#logo").style("padding", offset + "px 10px"); + } else { + // remove the dynamic padding from the logo element; + d3.select("#logo").style("padding", "10px"); + } + + // scrollbar tests; + var element = d3.select("#menuElementContainer").node(); + var maxScrollLeft = element.scrollWidth - element.clientWidth; + var leftButton = d3.select("#scrollLeftButton"); + var rightButton = d3.select("#scrollRightButton"); + if ( maxScrollLeft > 0 ) { + // show both and then check how far is bar; + rightButton.classed("hidden", false); + leftButton.classed("hidden", false); + navigationMenu.updateScrollButtonVisibility(); + } else { + // hide both; + rightButton.classed("hidden", true); + leftButton.classed("hidden", true); + } + + // adjust height of the leftSidebar element; + editSidebar.updateElementWidth(); + + + var hs = d3.select("#drag_msg").node().getBoundingClientRect().height; + var ws = d3.select("#drag_msg").node().getBoundingClientRect().width; + d3.select("#drag_icon_group").attr("transform", "translate ( " + 0.25 * ws + " " + 0.25 * hs + ")"); + + } + + function adjustSliderSize(){ + // TODO: refactor and put this into the slider it self + var height = window.innerHeight - 40; + var fullHeight = height; + var zoomOutPos = height - 30; + var sliderHeight = 150; + + // assuming DOM elements are generated in the index.html + // todo: refactor for independent usage of graph and app + if ( fullHeight < 150 ) { + // hide the slider button; + d3.select("#zoomSliderParagraph").classed("hidden", true); + d3.select("#zoomOutButton").classed("hidden", true); + d3.select("#zoomInButton").classed("hidden", true); + d3.select("#centerGraphButton").classed("hidden", true); + return; + } + d3.select("#zoomSliderParagraph").classed("hidden", false); + d3.select("#zoomOutButton").classed("hidden", false); + d3.select("#zoomInButton").classed("hidden", false); + d3.select("#centerGraphButton").classed("hidden", false); + + var zoomInPos = zoomOutPos - 20; + var centerPos = zoomInPos - 20; + if ( fullHeight < 280 ) { + // hide the slider button; + d3.select("#zoomSliderParagraph").classed("hidden", true);//var sliderPos=zoomOutPos-sliderHeight; + d3.select("#zoomOutButton").style("top", zoomOutPos + "px"); + d3.select("#zoomInButton").style("top", zoomInPos + "px"); + d3.select("#centerGraphButton").style("top", centerPos + "px"); + return; + } + + var sliderPos = zoomOutPos - sliderHeight; + zoomInPos = sliderPos - 20; + centerPos = zoomInPos - 20; + d3.select("#zoomSliderParagraph").classed("hidden", false); + d3.select("#zoomOutButton").style("top", zoomOutPos + "px"); + d3.select("#zoomInButton").style("top", zoomInPos + "px"); + d3.select("#centerGraphButton").style("top", centerPos + "px"); + d3.select("#zoomSliderParagraph").style("top", sliderPos + "px"); + } + + function isTouchDevice(){ + try { + document.createEvent("TouchEvent"); + return true; + } catch ( e ) { + return false; + } + } + + + function getInternetExplorerVersion(){ + var ua, + re, + rv = -1; + + // check for edge + var isEdge = /(?:\b(MS)?IE\s+|\bTrident\/7\.0;.*\s+rv:|\bEdge\/)(\d+)/.test(navigator.userAgent); + if ( isEdge ) { + rv = parseInt("12"); + return rv; + } + + var isIE11 = /Trident.*rv[ :]*11\./.test(navigator.userAgent); + if ( isIE11 ) { + rv = parseInt("11"); + return rv; + } + if ( navigator.appName === "Microsoft Internet Explorer" ) { + ua = navigator.userAgent; + re = new RegExp("MSIE ([0-9]{1,}[\\.0-9]{0,})"); + if ( re.exec(ua) !== null ) { + rv = parseFloat(RegExp.$1); + } + } else if ( navigator.appName === "Netscape" ) { + ua = navigator.userAgent; + re = new RegExp("Trident/.*rv:([0-9]{1,}[\\.0-9]{0,})"); + if ( re.exec(ua) !== null ) { + rv = parseFloat(RegExp.$1); + } + } + return rv; + } + + return app; + } + ; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 323: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for the export button. + * @returns {{}} + */ + module.exports = function ( graph ){ + + var exportMenu = {}, + exportSvgButton, + exportFilename, + exportJsonButton, + exportTurtleButton, + exportTexButton, + copyButton, + exportableJsonText; + + var exportTTLModule = __webpack_require__(324)(graph); + + + String.prototype.replaceAll = function ( search, replacement ){ + var target = this; + return target.split(search).join(replacement); + }; + + + /** + * Adds the export button to the website. + */ + exportMenu.setup = function (){ + exportSvgButton = d3.select("#exportSvg") + .on("click", exportSvg); + exportJsonButton = d3.select("#exportJson") + .on("click", exportJson); + + copyButton = d3.select("#copyBt") + .on("click", copyUrl); + + exportTexButton = d3.select("#exportTex") + .on("click", exportTex); + + exportTurtleButton = d3.select("#exportTurtle") + .on("click", exportTurtle); + + var menuEntry = d3.select("#m_export"); + menuEntry.on("mouseover", function (){ + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + exportMenu.exportAsUrl(); + }); + }; + function exportTurtle(){ + var success = exportTTLModule.requestExport(); + var result = exportTTLModule.resultingTTL_Content(); + var ontoTitle = "NewOntology"; + console.log("Exporter was successful: " + success); + if ( success ) { + // console.log("The result is : " + result); + // var ontoTitle=graph.options().getGeneralMetaObjectProperty('title'); + // if (ontoTitle===undefined || ontoTitle.length===0) + // ontoTitle="NewOntology"; + // else{ + // // language object -.- + // ontoTitle.replace(" ","_") + // } + + // TODO: show TEXT in warning module? + + + // // write the data + var dataURI = "data:text/json;charset=utf-8," + encodeURIComponent(result); + + exportTurtleButton.attr("href", dataURI) + .attr("download", ontoTitle + ".ttl"); + + // okay restore old href? + // exportTurtleButton.attr("href", oldHref); + } else { + console.log("ShowWarning!"); + graph.options().warningModule().showExporterWarning(); + console.log("Stay on the page! " + window.location.href); + exportTurtleButton.attr("href", window.location.href); + d3.event.preventDefault(); // prevent the href to be called ( reloads the page otherwise ) + } + } + + exportMenu.setFilename = function ( filename ){ + exportFilename = filename || "export"; + }; + + exportMenu.setJsonText = function ( jsonText ){ + exportableJsonText = jsonText; + }; + + function copyUrl(){ + d3.select("#exportedUrl").node().focus(); + d3.select("#exportedUrl").node().select(); + document.execCommand("copy"); + graph.options().navigationMenu().hideAllMenus(); + d3.event.preventDefault(); // prevent the href to be called ( reloads the page otherwise ) + } + + function prepareOptionString( defOpts, currOpts ){ + var setOptions = 0; + var optsString = "opts="; + + for ( var name in defOpts ) { + // define key and value ; + if ( defOpts.hasOwnProperty(name) ) {// for travis warning + var def_value = defOpts[name]; + var cur_value = currOpts[name]; + if ( def_value !== cur_value ) { + optsString += name + "=" + cur_value + ";"; + setOptions++; + } + } + } + optsString += ""; + if ( setOptions === 0 ) { + return ""; + } + return optsString; + } + + exportMenu.exportAsUrl = function (){ + var currObj = {}; + currObj.sidebar = graph.options().sidebar().getSidebarVisibility(); + + // identify default value given by ontology; + var defOntValue = graph.options().filterMenu().getDefaultDegreeValue(); + var currentValue = graph.options().filterMenu().getDegreeSliderValue(); + if ( parseInt(defOntValue) === parseInt(currentValue) ) { + currObj.doc = -1; + } else { + currObj.doc = currentValue; + } + + currObj.cd = graph.options().classDistance(); + currObj.dd = graph.options().datatypeDistance(); + if ( graph.editorMode() === true ) { + currObj.editorMode = "true"; + } else { + currObj.editorMode = "false"; + } + currObj.filter_datatypes = String(graph.options().filterMenu().getCheckBoxValue("datatypeFilterCheckbox")); + currObj.filter_sco = String(graph.options().filterMenu().getCheckBoxValue("subclassFilterCheckbox")); + currObj.filter_disjoint = String(graph.options().filterMenu().getCheckBoxValue("disjointFilterCheckbox")); + currObj.filter_setOperator = String(graph.options().filterMenu().getCheckBoxValue("setoperatorFilterCheckbox")); + currObj.filter_objectProperties = String(graph.options().filterMenu().getCheckBoxValue("objectPropertyFilterCheckbox")); + currObj.mode_dynamic = String(graph.options().dynamicLabelWidth()); + currObj.mode_scaling = String(graph.options().modeMenu().getCheckBoxValue("nodescalingModuleCheckbox")); + currObj.mode_compact = String(graph.options().modeMenu().getCheckBoxValue("compactnotationModuleCheckbox")); + currObj.mode_colorExt = String(graph.options().modeMenu().getCheckBoxValue("colorexternalsModuleCheckbox")); + currObj.mode_multiColor = String(graph.options().modeMenu().colorModeState()); + currObj.mode_pnp = String(graph.options().modeMenu().getCheckBoxValue("pickandpinModuleCheckbox")); + currObj.debugFeatures = String(!graph.options().getHideDebugFeatures()); + currObj.rect = 0; + + var defObj = graph.options().initialConfig(); + var optsString = prepareOptionString(defObj, currObj); + var urlString = String(location); + var htmlElement; + // when everything is default then there is nothing to write + if ( optsString.length === 0 ) { + // building up parameter list; + + // remove the all options form location + var hashCode = location.hash; + urlString = urlString.split(hashCode)[0]; + + var lPos = hashCode.lastIndexOf("#"); + if ( lPos === -1 ) { + htmlElement = d3.select("#exportedUrl").node(); + htmlElement.value = String(location); + htmlElement.title = String(location); + return; // nothing to change in the location String + } + var newURL = hashCode.slice(lPos, hashCode.length); + htmlElement = d3.select("#exportedUrl").node(); + htmlElement.value = urlString + newURL; + htmlElement.title = urlString + newURL; + return; + } + + // generate the options string; + var numParameters = (urlString.match(/#/g) || []).length; + var newUrlString; + if ( numParameters === undefined || numParameters === 0 ) { + newUrlString = urlString + "#" + optsString; + } + if ( numParameters > 0 ) { + var tokens = urlString.split("#"); + var i; + if ( tokens[1].indexOf("opts=") >= 0 ) { + tokens[1] = optsString; + newUrlString = tokens[0]; + } else { + newUrlString = tokens[0] + "#"; + newUrlString += optsString; + } + // append parameters + for ( i = 1; i < tokens.length; i++ ) { + if ( tokens[i].length > 0 ) { + newUrlString += "#" + tokens[i]; + } + } + } + // building up parameter list; + htmlElement = d3.select("#exportedUrl").node(); + htmlElement.value = newUrlString; + htmlElement.title = newUrlString; + + }; + + function exportSvg(){ + graph.options().navigationMenu().hideAllMenus(); + // Get the d3js SVG element + var graphSvg = d3.select(graph.options().graphContainerSelector()).select("svg"), + graphSvgCode, + escapedGraphSvgCode, + dataURI; + + // inline the styles, so that the exported svg code contains the css rules + inlineVowlStyles(); + hideNonExportableElements(); + + graphSvgCode = graphSvg.attr("version", 1.1) + .attr("xmlns", "http://www.w3.org/2000/svg") + .node().parentNode.innerHTML; + + // Insert the reference to VOWL + graphSvgCode = "\n" + graphSvgCode; + + escapedGraphSvgCode = escapeUnicodeCharacters(graphSvgCode); + //btoa(); Creates a base-64 encoded ASCII string from a "string" of binary data. + dataURI = "data:image/svg+xml;base64," + btoa(escapedGraphSvgCode); + + + exportSvgButton.attr("href", dataURI) + .attr("download", exportFilename + ".svg"); + + // remove graphic styles for interaction to go back to normal + removeVowlInlineStyles(); + showNonExportableElements(); + graph.lazyRefresh(); + } + + function escapeUnicodeCharacters( text ){ + var textSnippets = [], + i, textLength = text.length, + character, + charCode; + + for ( i = 0; i < textLength; i++ ) { + character = text.charAt(i); + charCode = character.charCodeAt(0); + + if ( charCode < 128 ) { + textSnippets.push(character); + } else { + textSnippets.push("&#" + charCode + ";"); + } + } + + return textSnippets.join(""); + } + + function inlineVowlStyles(){ + setStyleSensitively(".text", [{ name: "font-family", value: "Helvetica, Arial, sans-serif" }, { + name: "font-size", + value: "12px" + }]); + setStyleSensitively(".subtext", [{ name: "font-size", value: "9px" }]); + setStyleSensitively(".text.instance-count", [{ name: "fill", value: "#666" }]); + setStyleSensitively(".external + text .instance-count", [{ name: "fill", value: "#aaa" }]); + setStyleSensitively(".cardinality", [{ name: "font-size", value: "10px" }]); + setStyleSensitively(".text, .embedded", [{ name: "pointer-events", value: "none" }]); + setStyleSensitively(".class, .object, .disjoint, .objectproperty, .disjointwith, .equivalentproperty, .transitiveproperty, .functionalproperty, .inversefunctionalproperty, .symmetricproperty, .allvaluesfromproperty, .somevaluesfromproperty", [{ + name: "fill", + value: "#acf" + }]); + setStyleSensitively(".label .datatype, .datatypeproperty", [{ name: "fill", value: "#9c6" }]); + setStyleSensitively(".rdf, .rdfproperty", [{ name: "fill", value: "#c9c" }]); + setStyleSensitively(".literal, .node .datatype", [{ name: "fill", value: "#fc3" }]); + setStyleSensitively(".deprecated, .deprecatedproperty", [{ name: "fill", value: "#ccc" }]); + setStyleSensitively(".external, .externalproperty", [{ name: "fill", value: "#36c" }]); + setStyleSensitively("path, .nofill", [{ name: "fill", value: "none" }]); + setStyleSensitively("marker path", [{ name: "fill", value: "#000" }]); + setStyleSensitively(".class, path, line, .fineline", [{ name: "stroke", value: "#000" }]); + setStyleSensitively(".white, .subclass, .subclassproperty, .external + text", [{ name: "fill", value: "#fff" }]); + setStyleSensitively(".class.hovered, .property.hovered, .cardinality.hovered, .cardinality.focused, circle.pin, .filled.hovered, .filled.focused", [{ + name: "fill", + value: "#f00" + }, { name: "cursor", value: "pointer" }]); + setStyleSensitively(".focused, path.hovered", [{ name: "stroke", value: "#f00" }]); + setStyleSensitively(".indirect-highlighting, .feature:hover", [{ name: "fill", value: "#f90" }]); + setStyleSensitively(".values-from", [{ name: "stroke", value: "#69c" }]); + setStyleSensitively(".symbol, .values-from.filled", [{ name: "fill", value: "#69c" }]); + setStyleSensitively(".class, path, line", [{ name: "stroke-width", value: "2" }]); + setStyleSensitively(".fineline", [{ name: "stroke-width", value: "1" }]); + setStyleSensitively(".dashed, .anonymous", [{ name: "stroke-dasharray", value: "8" }]); + setStyleSensitively(".dotted", [{ name: "stroke-dasharray", value: "3" }]); + setStyleSensitively("rect.focused, circle.focused", [{ name: "stroke-width", value: "4px" }]); + setStyleSensitively(".nostroke", [{ name: "stroke", value: "none" }]); + setStyleSensitively("marker path", [{ name: "stroke-dasharray", value: "100" }]); + } + + function setStyleSensitively( selector, styles ){ + var elements = d3.selectAll(selector); + if ( elements.empty() ) { + return; + } + + styles.forEach(function ( style ){ + elements.each(function (){ + var element = d3.select(this); + if ( !shouldntChangeInlineCss(element, style.name) ) { + element.style(style.name, style.value); + } + }); + }); + } + + function shouldntChangeInlineCss( element, style ){ + return style === "fill" && hasBackgroundColorSet(element); + } + + function hasBackgroundColorSet( element ){ + var data = element.datum(); + if ( data === undefined ) { + return false; + } + return data.backgroundColor && !!data.backgroundColor(); + } + + /** + * For example the pin of the pick&pin module should be invisible in the exported graphic. + */ + function hideNonExportableElements(){ + d3.selectAll(".hidden-in-export").style("display", "none"); + } + + function removeVowlInlineStyles(){ + d3.selectAll(".text, .subtext, .text.instance-count, .external + text .instance-count, .cardinality, .text, .embedded, .class, .object, .disjoint, .objectproperty, .disjointwith, .equivalentproperty, .transitiveproperty, .functionalproperty, .inversefunctionalproperty, .symmetricproperty, .allvaluesfromproperty, .somevaluesfromproperty, .label .datatype, .datatypeproperty, .rdf, .rdfproperty, .literal, .node .datatype, .deprecated, .deprecatedproperty, .external, .externalproperty, path, .nofill, .symbol, .values-from.filled, marker path, .class, path, line, .fineline, .white, .subclass, .subclassproperty, .external + text, .class.hovered, .property.hovered, .cardinality.hovered, .cardinality.focused, circle.pin, .filled.hovered, .filled.focused, .focused, path.hovered, .indirect-highlighting, .feature:hover, .values-from, .class, path, line, .fineline, .dashed, .anonymous, .dotted, rect.focused, circle.focused, .nostroke, marker path") + .each(function (){ + var element = d3.select(this); + + var inlineStyles = element.node().style; + for ( var styleName in inlineStyles ) { + if ( inlineStyles.hasOwnProperty(styleName) ) { + if ( shouldntChangeInlineCss(element, styleName) ) { + continue; + } + element.style(styleName, null); + } + } + + if ( element.datum && element.datum() !== undefined && element.datum().type ) { + if ( element.datum().type() === "rdfs:subClassOf" ) { + element.style("fill", null); + } + } + }); + + // repair svg icons in the menu; + var scrollContainer = d3.select("#menuElementContainer").node(); + var controlElements = scrollContainer.children; + var numEntries = controlElements.length; + + for ( var i = 0; i < numEntries; i++ ) { + var currentMenu = controlElements[i].id; + d3.select("#" + currentMenu).select("path").style("stroke-width", "0"); + d3.select("#" + currentMenu).select("path").style("fill", "#fff"); + } + + d3.select("#magnifyingGlass").style("stroke-width", "0"); + d3.select("#magnifyingGlass").style("fill", "#666"); + + } + + function showNonExportableElements(){ + d3.selectAll(".hidden-in-export").style("display", null); + } + + exportMenu.createJSON_exportObject = function (){ + var i, j, k; // an index variable for the for-loops + + /** get data for exporter **/ + if (!graph.options().data()) {return {};} // return an empty json object + // extract onotology information; + var unfilteredData = graph.getUnfilteredData(); + var ontologyComment = graph.options().data()._comment; + var metaObj = graph.options().getGeneralMetaObject(); + var header = graph.options().data().header; + + if ( metaObj.iri && metaObj.iri !== header.iri ) { + header.iri = metaObj.iri; + } + if ( metaObj.title && metaObj.title !== header.title ) { + header.title = metaObj.title; + } + if ( metaObj.version && metaObj.version !== header.version ) { + header.version = metaObj.version; + } + if ( metaObj.author && metaObj.author !== header.author ) { + header.author = metaObj.author; + } + if ( metaObj.description && metaObj.description !== header.description ) { + header.description = metaObj.description; + } + + + var exportText = {}; + exportText._comment = ontologyComment; + exportText.header = header; + exportText.namespace = graph.options().data().namespace; + if ( exportText.namespace === undefined ) { + exportText.namespace = []; // just an empty namespace array + } + // we do have now the unfiltered data which needs to be transfered to class/classAttribute and property/propertyAttribute + + + // var classAttributeString='classAttribute:[ \n'; + var nodes = unfilteredData.nodes; + var nLen = nodes.length; // hope for compiler unroll + var classObjects = []; + var classAttributeObjects = []; + for ( i = 0; i < nLen; i++ ) { + var classObj = {}; + var classAttr = {}; + classObj.id = nodes[i].id(); + classObj.type = nodes[i].type(); + classObjects.push(classObj); + + // define the attributes object + classAttr.id = nodes[i].id(); + classAttr.iri = nodes[i].iri(); + classAttr.baseIri = nodes[i].baseIri(); + classAttr.label = nodes[i].label(); + + if ( nodes[i].attributes().length > 0 ) { + classAttr.attributes = nodes[i].attributes(); + } + if ( nodes[i].comment() ) { + classAttr.comment = nodes[i].comment(); + } + if ( nodes[i].annotations() ) { + classAttr.annotations = nodes[i].annotations(); + } + if ( nodes[i].description() ) { + classAttr.description = nodes[i].description(); + } + + + if ( nodes[i].individuals().length > 0 ) { + var classIndividualElements = []; + var nIndividuals = nodes[i].individuals(); + for ( j = 0; j < nIndividuals.length; j++ ) { + var indObj = {}; + indObj.iri = nIndividuals[j].iri(); + indObj.baseIri = nIndividuals[j].baseIri(); + indObj.labels = nIndividuals[j].label(); + if ( nIndividuals[j].annotations() ) { + indObj.annotations = nIndividuals[j].annotations(); + } + if ( nIndividuals[j].description() ) { + indObj.description = nIndividuals[j].description(); + } + if ( nIndividuals[j].comment() ) { + indObj.comment = nIndividuals[j].comment(); + } + classIndividualElements.push(indObj); + } + classAttr.individuals = classIndividualElements; + } + + var equalsForAttributes = undefined; + if ( nodes[i].equivalents().length > 0 ) { + equalsForAttributes = []; + var equals = nodes[i].equivalents(); + for ( j = 0; j < equals.length; j++ ) { + var eqObj = {}; + var eqAttr = {}; + eqObj.id = equals[j].id(); + equalsForAttributes.push(equals[j].id()); + eqObj.type = equals[j].type(); + classObjects.push(eqObj); + + eqAttr.id = equals[j].id(); + eqAttr.iri = equals[j].iri(); + eqAttr.baseIri = equals[j].baseIri(); + eqAttr.label = equals[j].label(); + + if ( equals[j].attributes().length > 0 ) { + eqAttr.attributes = equals[j].attributes(); + } + if ( equals[j].comment() ) { + eqAttr.comment = equals[j].comment(); + } + if ( equals[j].individuals().length > 0 ) { + eqAttr.individuals = equals[j].individuals(); + } + if ( equals[j].annotations() ) { + eqAttr.annotations = equals[j].annotations(); + } + if ( equals[j].description() ) { + eqAttr.description = equals[j].description(); + } + + if ( equals[j].individuals().length > 0 ) { + var e_classIndividualElements = []; + var e_nIndividuals = equals[i].individuals(); + for ( k = 0; k < e_nIndividuals.length; k++ ) { + var e_indObj = {}; + e_indObj.iri = e_nIndividuals[k].iri(); + e_indObj.baseIri = e_nIndividuals[k].baseIri(); + e_indObj.labels = e_nIndividuals[k].label(); + + if ( e_nIndividuals[k].annotations() ) { + e_indObj.annotations = e_nIndividuals[k].annotations(); + } + if ( e_nIndividuals[k].description() ) { + e_indObj.description = e_nIndividuals[k].description(); + } + if ( e_nIndividuals[k].comment() ) { + e_indObj.comment = e_nIndividuals[k].comment(); + } + e_classIndividualElements.push(e_indObj); + } + eqAttr.individuals = e_classIndividualElements; + } + + classAttributeObjects.push(eqAttr); + } + } + if ( equalsForAttributes && equalsForAttributes.length > 0 ) { + classAttr.equivalent = equalsForAttributes; + } + + // classAttr.subClasses=nodes[i].subClasses(); // not needed + // classAttr.instances=nodes[i].instances(); + + // + // .complement(element.complement) + // .disjointUnion(element.disjointUnion) + // .description(element.description) + // .equivalents(element.equivalent) + // .intersection(element.intersection) + // .type(element.type) Ignore, because we predefined it + // .union(element.union) + classAttributeObjects.push(classAttr); + } + + /** -- properties -- **/ + var properties = unfilteredData.properties; + var pLen = properties.length; // hope for compiler unroll + var propertyObjects = []; + var propertyAttributeObjects = []; + + for ( i = 0; i < pLen; i++ ) { + var pObj = {}; + var pAttr = {}; + pObj.id = properties[i].id(); + pObj.type = properties[i].type(); + propertyObjects.push(pObj); + + // // define the attributes object + pAttr.id = properties[i].id(); + pAttr.iri = properties[i].iri(); + pAttr.baseIri = properties[i].baseIri(); + pAttr.label = properties[i].label(); + + if ( properties[i].attributes().length > 0 ) { + pAttr.attributes = properties[i].attributes(); + } + if ( properties[i].comment() ) { + pAttr.comment = properties[i].comment(); + } + + if ( properties[i].annotations() ) { + pAttr.annotations = properties[i].annotations(); + } + if ( properties[i].maxCardinality() ) { + pAttr.maxCardinality = properties[i].maxCardinality(); + } + if ( properties[i].minCardinality() ) { + pAttr.minCardinality = properties[i].minCardinality(); + } + if ( properties[i].cardinality() ) { + pAttr.cardinality = properties[i].cardinality(); + } + if ( properties[i].description() ) { + pAttr.description = properties[i].description(); + } + + pAttr.domain = properties[i].domain().id(); + pAttr.range = properties[i].range().id(); + // sub properties; + if ( properties[i].subproperties() ) { + var subProps = properties[i].subproperties(); + var subPropsIdArray = []; + for ( j = 0; j < subProps.length; j++ ) { + if ( subProps[j].id ) + subPropsIdArray.push(subProps[j].id()); + } + pAttr.subproperty = subPropsIdArray; + } + + // super properties + if ( properties[i].superproperties() ) { + var superProps = properties[i].superproperties(); + var superPropsIdArray = []; + for ( j = 0; j < superProps.length; j++ ) { + if ( superProps[j].id ) + superPropsIdArray.push(superProps[j].id()); + } + pAttr.superproperty = superPropsIdArray; + } + + // check for inverse element + if ( properties[i].inverse() ) { + if ( properties[i].inverse().id ) + pAttr.inverse = properties[i].inverse().id(); + } + propertyAttributeObjects.push(pAttr); + } + + exportText.class = classObjects; + exportText.classAttribute = classAttributeObjects; + exportText.property = propertyObjects; + exportText.propertyAttribute = propertyAttributeObjects; + + + var nodeElements = graph.graphNodeElements(); // get visible nodes + var propElements = graph.graphLabelElements(); // get visible labels + // var jsonObj = JSON.parse(exportableJsonText); // reparse the original input json + + /** modify comment **/ + var comment = exportText._comment; + var additionalString = " [Additional Information added by WebVOWL Exporter Version: " + "1.1.7" + "]"; + // adding new string to comment only if it does not exist + if ( comment.indexOf(additionalString) === -1 ) { + exportText._comment = comment + " [Additional Information added by WebVOWL Exporter Version: " + "1.1.7" + "]"; + } + + var classAttribute = exportText.classAttribute; + var propAttribute = exportText.propertyAttribute; + /** remove previously stored variables **/ + for ( i = 0; i < classAttribute.length; i++ ) { + var classObj_del = classAttribute[i]; + delete classObj_del.pos; + delete classObj_del.pinned; + } + var propertyObj; + for ( i = 0; i < propAttribute.length; i++ ) { + propertyObj = propAttribute[i]; + delete propertyObj.pos; + delete propertyObj.pinned; + } + /** add new variables to jsonObj **/ + // class attribute variables + nodeElements.each(function ( node ){ + var nodeId = node.id(); + for ( i = 0; i < classAttribute.length; i++ ) { + var classObj = classAttribute[i]; + if ( classObj.id === nodeId ) { + // store relative positions + classObj.pos = [parseFloat(node.x.toFixed(2)), parseFloat(node.y.toFixed(2))]; + if ( node.pinned() ) + classObj.pinned = true; + break; + } + } + }); + // property attribute variables + for ( j = 0; j < propElements.length; j++ ) { + var correspondingProp = propElements[j].property(); + for ( i = 0; i < propAttribute.length; i++ ) { + propertyObj = propAttribute[i]; + if ( propertyObj.id === correspondingProp.id() ) { + propertyObj.pos = [parseFloat(propElements[j].x.toFixed(2)), parseFloat(propElements[j].y.toFixed(2))]; + if ( propElements[j].pinned() ) + propertyObj.pinned = true; + break; + } + } + } + /** create the variable for settings and set their values **/ + exportText.settings = {}; + + // Global Settings + var zoom = graph.scaleFactor(); + var paused = graph.paused(); + var translation = [parseFloat(graph.translation()[0].toFixed(2)), parseFloat(graph.translation()[1].toFixed(2))]; + exportText.settings.global = {}; + exportText.settings.global.zoom = zoom.toFixed(2); + exportText.settings.global.translation = translation; + exportText.settings.global.paused = paused; + + // shared variable declaration + var cb_text; + var isEnabled; + var cb_obj; + + // Gravity Settings + var classDistance = graph.options().classDistance(); + var datatypeDistance = graph.options().datatypeDistance(); + exportText.settings.gravity = {}; + exportText.settings.gravity.classDistance = classDistance; + exportText.settings.gravity.datatypeDistance = datatypeDistance; + + // Filter Settings + var fMenu = graph.options().filterMenu(); + var fContainer = fMenu.getCheckBoxContainer(); + var cbCont = []; + for ( i = 0; i < fContainer.length; i++ ) { + cb_text = fContainer[i].checkbox.attr("id"); + isEnabled = fContainer[i].checkbox.property("checked"); + cb_obj = {}; + cb_obj.id = cb_text; + cb_obj.checked = isEnabled; + cbCont.push(cb_obj); + } + var degreeSliderVal = fMenu.getDegreeSliderValue(); + exportText.settings.filter = {}; + exportText.settings.filter.checkBox = cbCont; + exportText.settings.filter.degreeSliderValue = degreeSliderVal; + + // Modes Settings + var mMenu = graph.options().modeMenu(); + var mContainer = mMenu.getCheckBoxContainer(); + var cb_modes = []; + for ( i = 0; i < mContainer.length; i++ ) { + cb_text = mContainer[i].attr("id"); + isEnabled = mContainer[i].property("checked"); + cb_obj = {}; + cb_obj.id = cb_text; + cb_obj.checked = isEnabled; + cb_modes.push(cb_obj); + } + var colorSwitchState = mMenu.colorModeState(); + exportText.settings.modes = {}; + exportText.settings.modes.checkBox = cb_modes; + exportText.settings.modes.colorSwitchState = colorSwitchState; + + var exportObj = {}; + // todo: [ ] find better way for ordering the objects + // hack for ordering of objects, so settings is after metrics + exportObj._comment = exportText._comment; + exportObj.header = exportText.header; + exportObj.namespace = exportText.namespace; + exportObj.metrics = exportText.metrics; + exportObj.settings = exportText.settings; + exportObj.class = exportText.class; + exportObj.classAttribute = exportText.classAttribute; + exportObj.property = exportText.property; + exportObj.propertyAttribute = exportText.propertyAttribute; + + return exportObj; + }; + + function exportJson(){ + graph.options().navigationMenu().hideAllMenus(); + /** check if there is data **/ + if ( !exportableJsonText ) { + alert("No graph data available."); + // Stop the redirection to the path of the href attribute + d3.event.preventDefault(); + return; + } + + var exportObj = exportMenu.createJSON_exportObject(); + + // make a string again; + var exportText = JSON.stringify(exportObj, null, ' '); + // write the data + var dataURI = "data:text/json;charset=utf-8," + encodeURIComponent(exportText); + var jsonExportFileName = exportFilename; + + if ( !jsonExportFileName.endsWith(".json") ) + jsonExportFileName += ".json"; + exportJsonButton.attr("href", dataURI) + .attr("download", jsonExportFileName); + } + + var curveFunction = d3.svg.line() + .x(function ( d ){ + return d.x; + }) + .y(function ( d ){ + return d.y; + }) + .interpolate("cardinal"); + var loopFunction = d3.svg.line() + .x(function ( d ){ + return d.x; + }) + .y(function ( d ){ + return d.y; + }) + .interpolate("cardinal") + .tension(-1); + + function exportTex(){ + var zoom = graph.scaleFactor(); + var grTranslate = graph.translation(); + var bbox = graph.getBoundingBoxForTex(); + var comment = " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n"; + comment += " % Generated with the experimental alpha version of the TeX exporter of WebVOWL (version 1.1.3) %%% \n"; + comment += " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n\n"; + comment += " % The content can be used as import in other TeX documents. \n"; + comment += " % Parent document has to use the following packages \n"; + comment += " % \\usepackage{tikz} \n"; + comment += " % \\usepackage{helvet} \n"; + comment += " % \\usetikzlibrary{decorations.markings,decorations.shapes,decorations,arrows,automata,backgrounds,petri,shapes.geometric} \n"; + comment += " % \\usepackage{xcolor} \n\n"; + comment += " %%%%%%%%%%%%%%% Example Parent Document %%%%%%%%%%%%%%%%%%%%%%%\n"; + comment += " %\\documentclass{article} \n"; + comment += " %\\usepackage{tikz} \n"; + comment += " %\\usepackage{helvet} \n"; + comment += " %\\usetikzlibrary{decorations.markings,decorations.shapes,decorations,arrows,automata,backgrounds,petri,shapes.geometric} \n"; + comment += " %\\usepackage{xcolor} \n\n"; + comment += " %\\begin{document} \n"; + comment += " %\\section{Example} \n"; + comment += " % This is an example. \n"; + comment += " % \\begin{figure} \n"; + comment += " % \\input{} % << tex file name for the graph \n"; + comment += " % \\caption{A generated graph with TKIZ using alpha version of the TeX exporter of WebVOWL (version 1.1.3) } \n"; + comment += " % \\end{figure} \n"; + comment += " %\\end{document} \n"; + comment += " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n\n"; + + + var texString = comment + "\\definecolor{imageBGCOLOR}{HTML}{FFFFFF} \n" + + "\\definecolor{owlClassColor}{HTML}{AACCFF}\n" + + "\\definecolor{owlObjectPropertyColor}{HTML}{AACCFF}\n" + + "\\definecolor{owlExternalClassColor}{HTML}{AACCFF}\n" + + "\\definecolor{owlDatatypePropertyColor}{HTML}{99CC66}\n" + + "\\definecolor{owlDatatypeColor}{HTML}{FFCC33}\n" + + "\\definecolor{owlThingColor}{HTML}{FFFFFF}\n" + + "\\definecolor{valuesFrom}{HTML}{6699CC}\n" + + "\\definecolor{rdfPropertyColor}{HTML}{CC99CC}\n" + + "\\definecolor{unionColor}{HTML}{6699cc}\n" + + "\\begin{center} \n" + + "\\resizebox{\\linewidth}{!}{\n" + + + "\\begin{tikzpicture}[framed]\n" + + "\\clip (" + bbox[0] + "pt , " + bbox[1] + "pt ) rectangle (" + bbox[2] + "pt , " + bbox[3] + "pt);\n" + + "\\tikzstyle{dashed}=[dash pattern=on 4pt off 4pt] \n" + + "\\tikzstyle{dotted}=[dash pattern=on 2pt off 2pt] \n" + + "\\fontfamily{sans-serif}{\\fontsize{12}{12}\\selectfont}\n \n"; + + + texString += "\\tikzset{triangleBlack/.style = {fill=black, draw=black, line width=1pt,scale=0.7,regular polygon, regular polygon sides=3} }\n"; + texString += "\\tikzset{triangleWhite/.style = {fill=white, draw=black, line width=1pt,scale=0.7,regular polygon, regular polygon sides=3} }\n"; + texString += "\\tikzset{triangleBlue/.style = {fill=valuesFrom, draw=valuesFrom, line width=1pt,scale=0.7,regular polygon, regular polygon sides=3} }\n"; + + texString += "\\tikzset{Diamond/.style = {fill=white, draw=black, line width=2pt,scale=1.2,regular polygon, regular polygon sides=4} }\n"; + + + texString += "\\tikzset{Literal/.style={rectangle,align=center,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "black, draw=black, dashed, line width=1pt, fill=owlDatatypeColor, minimum width=80pt,\n" + + "minimum height = 20pt}}\n\n"; + + texString += "\\tikzset{Datatype/.style={rectangle,align=center,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "black, draw=black, line width=1pt, fill=owlDatatypeColor, minimum width=80pt,\n" + + "minimum height = 20pt}}\n\n"; + + + texString += "\\tikzset{owlClass/.style={circle, inner sep=0mm,align=center, \n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "black, draw=black, line width=1pt, fill=owlClassColor, minimum size=101pt}}\n\n"; + + texString += "\\tikzset{anonymousClass/.style={circle, inner sep=0mm,align=center, \n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "black, dashed, draw=black, line width=1pt, fill=owlClassColor, minimum size=101pt}}\n\n"; + + + texString += "\\tikzset{owlThing/.style={circle, inner sep=0mm,align=center,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "black, dashed, draw=black, line width=1pt, fill=owlThingColor, minimum size=62pt}}\n\n"; + + + texString += "\\tikzset{owlObjectProperty/.style={rectangle,align=center,\n" + + "inner sep=0mm,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "fill=owlObjectPropertyColor, minimum width=80pt,\n" + + "minimum height = 25pt}}\n\n"; + + texString += "\\tikzset{rdfProperty/.style={rectangle,align=center,\n" + + "inner sep=0mm,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "fill=rdfPropertyColor, minimum width=80pt,\n" + + "minimum height = 25pt}}\n\n"; + + + texString += "\\tikzset{owlDatatypeProperty/.style={rectangle,align=center,\n" + + "fill=owlDatatypePropertyColor, minimum width=80pt,\n" + + "inner sep=0mm,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "minimum height = 25pt}}\n\n"; + + texString += "\\tikzset{rdfsSubClassOf/.style={rectangle,align=center,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "inner sep=0mm,\n" + + "fill=imageBGCOLOR, minimum width=80pt,\n" + + "minimum height = 25pt}}\n\n"; + + texString += "\\tikzset{unionOf/.style={circle, inner sep=0mm,align=center,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "black, draw=black, line width=1pt, fill=unionColor, minimum size=25pt}}\n\n"; + + texString += "\\tikzset{disjointWith/.style={circle, inner sep=0mm,align=center,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "black, draw=black, line width=1pt, fill=unionColor, minimum size=20pt}}\n\n"; + + + texString += "\\tikzset{owlEquivalentClass/.style={circle,align=center,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "inner sep=0mm,\n" + + "black, solid, draw=black, line width=3pt, fill=owlExternalClassColor, minimum size=101pt,\n" + + "postaction = {draw,line width=1pt, white}}}\n\n"; + + // draw a bounding box; + + // get bbox coordinates; + + + graph.options().navigationMenu().hideAllMenus(); + /** check if there is data **/ + if ( !exportableJsonText ) { + alert("No graph data available."); + // Stop the redirection to the path of the href attribute + d3.event.preventDefault(); + return; + } + + var i = 0, identifier; + + /** get data for exporter **/ + var nodeElements = graph.graphNodeElements(); // get visible nodes + var propElements = graph.graphLabelElements(); // get visible labels + var links = graph.graphLinkElements(); + + // export only nodes; + // draw Links; + for ( i = 0; i < links.length; i++ ) { + var link = links[i]; + // console.log("\n****************\nInverstigating Link for property "+link.property().labelForCurrentLanguage()); + + var prop = link.property(); + var dx, dy, px, py, rx, ry; + var colorStr = "black"; + var linkDomainIntersection; + var linkRangeIntersection; + var center; + var linkStyle = ""; + var isLoop = ""; + var curvePoint; + var pathStart; + var pathEnd; + var controlPoints; + var len; + var ahAngle; + var pathLen; + var markerOffset = 7; + + var arrowType = "triangleBlack"; + var linkWidth = ",line width=2pt"; + if ( prop.linkType ) { + if ( prop.linkType() === "dotted" ) { + //stroke-dasharray: 3; + linkStyle = ", dotted "; + arrowType = "triangleWhite"; + } + if ( prop.linkType() === "dashed" ) { + //stroke-dasharray: 3; + linkStyle = ", dashed "; + } + + if ( prop.linkType() === "values-from" ) { + colorStr = "valuesFrom"; + } + + } + + var startX, startY, endX, endY, normX, normY, lg; + + if ( link.layers().length === 1 && !link.loops() ) { + + linkDomainIntersection = graph.math().calculateIntersection(link.range(), link.domain(), 1); + linkRangeIntersection = graph.math().calculateIntersection(link.domain(), link.range(), 1); + center = graph.math().calculateCenter(linkDomainIntersection, linkRangeIntersection); + dx = linkDomainIntersection.x; + dy = -linkDomainIntersection.y; + px = center.x; + py = -center.y; + rx = linkRangeIntersection.x; + ry = -linkRangeIntersection.y; + + + pathStart = linkDomainIntersection; + curvePoint = center; + pathEnd = linkRangeIntersection; + + var nx = rx - px; + var ny = ry - py; + + // normalize ; + len = Math.sqrt(nx * nx + ny * ny); + + nx = nx / len; + ny = ny / len; + + ahAngle = Math.atan2(ny, nx) * (180 / Math.PI); + normX = nx; + normY = ny; + } + else { + if ( link.isLoop() ) { + isLoop = ", tension=3"; + controlPoints = graph.math().calculateLoopPoints(link); + pathStart = controlPoints[0]; + curvePoint = controlPoints[1]; + pathEnd = controlPoints[2]; + } else { + curvePoint = link.label(); + pathStart = graph.math().calculateIntersection(curvePoint, link.domain(), 1); + pathEnd = graph.math().calculateIntersection(curvePoint, link.range(), 1); + } + dx = pathStart.x; + dy = -pathStart.y; + px = curvePoint.x; + py = -curvePoint.y; + rx = pathEnd.x; + ry = -pathEnd.y; + } + + texString += "\\draw [" + colorStr + linkStyle + linkWidth + isLoop + "] plot [smooth] coordinates {(" + + dx + "pt, " + dy + "pt) (" + px + "pt, " + py + "pt) (" + rx + "pt, " + ry + "pt)};\n"; + + + if ( link.property().markerElement() === undefined ) continue; + + // add arrow head; + + + if ( link.property().type() === "owl:someValuesFrom" || link.property().type() === "owl:allValuesFrom" ) { + arrowType = "triangleBlue"; + } + + lg = link.pathObj(); + pathLen = Math.floor(lg.node().getTotalLength()); + var p1 = lg.node().getPointAtLength(pathLen - 4); + var p2 = lg.node().getPointAtLength(pathLen); + var markerCenter = lg.node().getPointAtLength(pathLen - 6); + + if ( link.property().type() === "setOperatorProperty" ) { + p1 = lg.node().getPointAtLength(4); + p2 = lg.node().getPointAtLength(0); + markerCenter = lg.node().getPointAtLength(8); + arrowType = "Diamond"; + } + + startX = p1.x; + startY = p1.y; + endX = p2.x; + endY = p2.y; + normX = endX - startX; + normY = endY - startY; + len = Math.sqrt(normX * normX + normY * normY); + normX = normX / len; + normY = normY / len; + + ahAngle = -1.0 * Math.atan2(normY, normX) * (180 / Math.PI); + ahAngle -= 90; + if ( link.property().type() === "setOperatorProperty" ) { + ahAngle -= 45; + } + // console.log(link.property().labelForCurrentLanguage()+ ": "+normX+ " "+normY +" "+ahAngle); + rx = markerCenter.x; + ry = markerCenter.y; + if ( link.layers().length === 1 && !link.loops() ) { + // markerOffset=-1*m + ry = -1 * ry; + texString += "\\node[" + arrowType + ", rotate=" + ahAngle + "] at (" + rx + "pt, " + ry + "pt) (single_marker" + i + ") {};\n "; + } else { + ry = -1 * ry; + texString += "\\node[" + arrowType + ", rotate=" + ahAngle + "] at (" + rx + "pt, " + ry + "pt) (marker" + i + ") {};\n "; + } + + // if (link.isLoop()){ + // rotAngle=-10+angle * (180 / Math.PI); + // } + + // add cardinality; + var cardinalityText = link.property().generateCardinalityText(); + if ( cardinalityText && cardinalityText.length > 0 ) { + var cardinalityCenter = lg.node().getPointAtLength(pathLen - 18); + var cx = cardinalityCenter.x - (10 * normY); + var cy = cardinalityCenter.y + (10 * normX); // using orthonormal y Coordinate + cy *= -1.0; + var textColor = "black"; + if ( cardinalityText.indexOf("A") > -1 ) { + cardinalityText = "$\\forall$"; + } + if ( cardinalityText.indexOf("E") > -1 ) { + cardinalityText = "$\\exists$"; + } + + + texString += "\\node[font={\\fontsize{12pt}{12}\\selectfont \\sffamily },text=" + textColor + "] at (" + cx + "pt, " + cy + "pt) (cardinalityText" + i + ") {" + cardinalityText + "};\n "; + } + + + if ( link.property().inverse() ) { + lg = link.pathObj(); + pathLen = Math.floor(lg.node().getTotalLength()); + var p1_inv = lg.node().getPointAtLength(4); + var p2_inv = lg.node().getPointAtLength(0); + var markerCenter_inv = lg.node().getPointAtLength(6); + startX = p1_inv.x; + startY = p1_inv.y; + endX = p2_inv.x; + endY = p2_inv.y; + normX = endX - startX; + normY = endY - startY; + len = Math.sqrt(normX * normX + normY * normY); + normX = normX / len; + normY = normY / len; + + ahAngle = -1.0 * Math.atan2(normY, normX) * (180 / Math.PI); + ahAngle -= 90; + // console.log("INV>>\n "+link.property().inverse().labelForCurrentLanguage()+ ": "+normX+ " "+normY +" "+ahAngle); + rx = markerCenter_inv.x; + ry = markerCenter_inv.y; + if ( link.layers().length === 1 && !link.loops() ) { + // markerOffset=-1*m + ry = -1 * ry; + texString += "\\node[" + arrowType + ", rotate=" + ahAngle + "] at (" + rx + "pt, " + ry + "pt) (INV_single_marker" + i + ") {};\n "; + } else { + ry = -1 * ry; + texString += "\\node[" + arrowType + ", rotate=" + ahAngle + "] at (" + rx + "pt, " + ry + "pt) (INV_marker" + i + ") {};\n "; + } + } + + + } + + + nodeElements.each(function ( node ){ + + px = node.x; + py = -node.y; + identifier = node.labelForCurrentLanguage(); + // console.log("Writing : "+ identifier); + if ( identifier === undefined ) identifier = ""; + var qType = "owlClass"; + if ( node.type() === "owl:Thing" || node.type() === "owl:Nothing" ) + qType = "owlThing"; + + if ( node.type() === "owl:equivalentClass" ) { + qType = "owlEquivalentClass"; + } + var textColorStr = ""; + if ( node.textBlock ) { + var txtColor = node.textBlock()._textBlock().style("fill"); + if ( txtColor === "rgb(0, 0, 0)" ) { + textColorStr = ", text=black"; + } + if ( txtColor === "rgb(255, 255, 255)" ) { + textColorStr = ", text=white"; + } + + + var tspans = node.textBlock()._textBlock().node().children; + if ( tspans[0] ) { + identifier = tspans[0].innerHTML; + if ( node.individuals() && node.individuals().length === parseInt(tspans[0].innerHTML) ) { + identifier = "{\\color{gray} " + tspans[0].innerHTML + " }"; + } + for ( var t = 1; t < tspans.length; t++ ) { + if ( node.individuals() && node.individuals().length === parseInt(tspans[t].innerHTML) ) { + identifier += "\\\\ {\\color{gray} " + tspans[t].innerHTML + " }"; + } else { + identifier += "\\\\ {\\small " + tspans[t].innerHTML + " }"; + } + } + } + } + if ( node.type() === "rdfs:Literal" ) { + qType = "Literal"; + } + if ( node.type() === "rdfs:Datatype" ) { + qType = "Datatype"; + } + if ( node.attributes().indexOf("anonymous") !== -1 ) { + qType = "anonymousClass"; + } + + + if ( node.type() === "owl:unionOf" || node.type() === "owl:complementOf" || node.type() === "owl:disjointUnionOf" || node.type() === "owl:intersectionOf" ) + qType = "owlClass"; + + var bgColorStr = ""; + var widthString = ""; + + if ( node.type() === "rdfs:Literal" || node.type() === "rdfs:Datatype" ) { + var width = node.width(); + widthString = ",minimum width=" + width + "pt"; + } + else { + widthString = ",minimum size=" + 2 * node.actualRadius() + "pt"; + + } + if ( node.backgroundColor() ) { + var bgColor = node.backgroundColor(); + bgColor.toUpperCase(); + bgColor = bgColor.slice(1, bgColor.length); + texString += "\\definecolor{Node" + i + "_COLOR}{HTML}{" + bgColor + "} \n "; + bgColorStr = ", fill=Node" + i + "_COLOR "; + } + if ( node.attributes().indexOf("deprecated") > -1 ) { + texString += "\\definecolor{Node" + i + "_COLOR}{HTML}{CCCCCC} \n "; + bgColorStr = ", fill=Node" + i + "_COLOR "; + } + + var leftPos = px - 7; + var rightPos = px + 7; + var txtOffset = py + 20; + if ( node.type() !== "owl:unionOf" || node.type() !== "owl:disjointUnionOf" ) { + texString += "\\node[" + qType + " " + widthString + " " + bgColorStr + " " + textColorStr + "] at (" + px + "pt, " + py + "pt) (Node" + i + ") {" + identifier.replaceAll("_", "\\_ ") + "};\n"; + } + if ( node.type() === "owl:unionOf" ) { + // add symbol to it; + texString += "\\node[" + qType + " " + widthString + " " + bgColorStr + " " + textColorStr + "] at (" + px + "pt, " + py + "pt) (Node" + i + ") {};\n"; + texString += "\\node[unionOf , text=black] at (" + leftPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[unionOf , text=black] at (" + rightPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[unionOf ,fill=none , text=black] at (" + leftPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[text=black] at (" + px + "pt, " + py + "pt) (unionText13) {$\\mathbf{\\cup}$};\n"; + texString += "\\node[font={\\fontsize{12pt}{12}\\selectfont \\sffamily }" + textColorStr + "] at (" + px + "pt, " + txtOffset + "pt) (Node_text" + i + ") {" + identifier.replaceAll("_", "\\_ ") + "};\n"; + } + // OWL DISJOINT UNION OF + if ( node.type() === "owl:disjointUnionOf" ) { + texString += "\\node[" + qType + " " + widthString + " " + bgColorStr + " " + textColorStr + "] at (" + px + "pt, " + py + "pt) (Node" + i + ") {};\n"; + texString += "\\node[unionOf , text=black] at (" + leftPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[unionOf , text=black] at (" + rightPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[unionOf ,fill=none , text=black] at (" + leftPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[font={\\fontsize{12pt}{12}\\selectfont \\sffamily }" + textColorStr + "] at (" + px + "pt, " + py + "pt) (disjointUnoinText" + i + ") {1};\n"; + texString += "\\node[font={\\fontsize{12pt}{12}\\selectfont \\sffamily }" + textColorStr + "] at (" + px + "pt, " + txtOffset + "pt) (Node_text" + i + ") {" + identifier.replaceAll("_", "\\_ ") + "};\n"; + } + // OWL COMPLEMENT OF + if ( node.type() === "owl:complementOf" ) { + // add symbol to it; + texString += "\\node[" + qType + " " + widthString + " " + bgColorStr + " " + textColorStr + "] at (" + px + "pt, " + py + "pt) (Node" + i + ") {};\n"; + texString += "\\node[unionOf , text=black] at (" + px + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[font={\\fontsize{18pt}{18}\\selectfont \\sffamily }" + textColorStr + "] at (" + px + "pt, " + py + "pt) (unionText13) {$\\neg$};\n"; + texString += "\\node[font={\\fontsize{12pt}{12}\\selectfont \\sffamily }" + textColorStr + "] at (" + px + "pt, " + txtOffset + "pt) (Node_text" + i + ") {" + identifier.replaceAll("_", "\\_ ") + "};\n"; + } + // OWL INTERSECTION OF + if ( node.type() === "owl:intersectionOf" ) { + texString += "\\node[" + qType + " " + widthString + " " + bgColorStr + " " + textColorStr + "] at (" + px + "pt, " + py + "pt) (Node" + i + ") {};\n"; + texString += "\\node[unionOf , text=black] at (" + leftPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[unionOf , text=black] at (" + rightPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[unionOf ,fill=none , text=black] at (" + leftPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + + // add now the outer colors; + texString += "\\filldraw[even odd rule,fill=owlClassColor,line width=1pt] (" + leftPos + "pt, " + py + "pt) circle (12.5pt) (" + rightPos + "pt, " + py + "pt) circle (12.5pt);\n "; + + // add texts + texString += "\\node[font={\\fontsize{12pt}{12}\\selectfont \\sffamily }" + textColorStr + "] at (" + px + "pt, " + py + "pt) (intersectionText" + i + ") {$\\cap$};\n"; + texString += "\\node[font={\\fontsize{12pt}{12}\\selectfont \\sffamily }" + textColorStr + "] at (" + px + "pt, " + txtOffset + "pt) (Node_text" + i + ") {" + identifier.replaceAll("_", "\\_ ") + "};\n"; + + } + + + i++; + + }); + for ( i = 0; i < propElements.length; i++ ) { + var correspondingProp = propElements[i].property(); + var p_px = propElements[i].x; + var p_py = -propElements[i].y; + identifier = correspondingProp.labelForCurrentLanguage(); + if ( identifier === undefined ) identifier = ""; + var textColorStr = ""; + if ( correspondingProp.textBlock && correspondingProp.textBlock() ) { + var txtColor = correspondingProp.textBlock()._textBlock().style("fill"); + // console.log("PropertyTextColor="+txtColor); + if ( txtColor === "rgb(0, 0, 0)" ) { + textColorStr = ", text=black"; + } + if ( txtColor === "rgb(255, 255, 255)" ) { + textColorStr = ", text=white"; + } + var tspans = correspondingProp.textBlock()._textBlock().node().children; + + // identifier=node.textBlock()._textBlock().text(); + // console.log(tspans); + if ( tspans[0] ) { + identifier = tspans[0].innerHTML; + + for ( var t = 1; t < tspans.length; t++ ) { + var spanText = tspans[t].innerHTML; + if ( spanText.indexOf("(") > -1 ) { + identifier += "\\\\ {\\small " + tspans[t].innerHTML + " }"; + } + else { + identifier += "\\\\ " + tspans[t].innerHTML; + } + } + } + else { + } + } + if ( correspondingProp.type() === "setOperatorProperty" ) { + continue; // this property does not have a label + } + var qType = "owlObjectProperty"; + if ( correspondingProp.type() === "owl:DatatypeProperty" ) { + qType = "owlDatatypeProperty"; + } + if ( correspondingProp.type() === "rdfs:subClassOf" ) { + qType = "rdfsSubClassOf"; + } + if ( correspondingProp.type() === "rdf:Property" ) { + qType = "rdfProperty"; + } + + + var bgColorStr = ""; + if ( correspondingProp.backgroundColor() ) { + // console.log("Found backGround color"); + var bgColor = correspondingProp.backgroundColor(); + //console.log(bgColor); + bgColor.toUpperCase(); + bgColor = bgColor.slice(1, bgColor.length); + texString += "\\definecolor{property" + i + "_COLOR}{HTML}{" + bgColor + "} \n "; + bgColorStr = ", fill=property" + i + "_COLOR "; + } + if ( correspondingProp.attributes().indexOf("deprecated") > -1 ) { + texString += "\\definecolor{property" + i + "_COLOR}{HTML}{CCCCCC} \n "; + bgColorStr = ", fill=property" + i + "_COLOR "; + } + + var widthString = ""; + var width = correspondingProp.textWidth(); + widthString = ",minimum width=" + width + "pt"; + + + // OWL INTERSECTION OF + if ( correspondingProp.type() === "owl:disjointWith" ) { + var leftPos = p_px - 12; + var rightPos = p_px + 12; + var txtOffset = p_py - 20; + texString += "\\node[" + qType + " " + widthString + " " + bgColorStr + " " + textColorStr + "] at (" + p_px + "pt, " + p_py + "pt) (Node" + i + ") {};\n"; + texString += "\\node[disjointWith , text=black] at (" + leftPos + "pt, " + p_py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[disjointWith , text=black] at (" + rightPos + "pt, " + p_py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[font={\\fontsize{12pt}{12}\\selectfont \\sffamily }" + textColorStr + "] at (" + p_px + "pt, " + txtOffset + "pt) (Node_text" + i + ") {"; + if ( graph.options().compactNotation() === false ) { + texString += "(disjoint)"; + } + texString += "};\n"; + continue; + } + + + if ( correspondingProp.inverse() ) { + var inv_correspondingProp = correspondingProp.inverse(); + // create the rendering element for the inverse property; + var inv_identifier = inv_correspondingProp.labelForCurrentLanguage(); + if ( inv_identifier === undefined ) inv_identifier = ""; + var inv_textColorStr = ""; + //console.log(inv_correspondingProp); + //console.log(inv_correspondingProp.textBlock()); + + if ( inv_correspondingProp.textBlock && inv_correspondingProp.textBlock() ) { + + var inv_txtColor = inv_correspondingProp.textBlock()._textBlock().style("fill"); + // console.log("PropertyTextColor="+inv_txtColor); + if ( inv_txtColor === "rgb(0, 0, 0)" ) { + inv_textColorStr = ", text=black"; + } + if ( inv_txtColor === "rgb(255, 255, 255)" ) { + inv_textColorStr = ", text=white"; + } + var inv_tspans = inv_correspondingProp.textBlock()._textBlock().node().children; + + // identifier=node.textBlock()._textBlock().text(); + // console.log(inv_tspans); + if ( inv_tspans[0] ) { + inv_identifier = inv_tspans[0].innerHTML; + + for ( var inv_t = 1; inv_t < inv_tspans.length; inv_t++ ) { + var ispanText = inv_tspans[inv_t].innerHTML; + if ( ispanText.indexOf("(") > -1 ) { + inv_identifier += "\\\\ {\\small " + inv_tspans[inv_t].innerHTML + " }"; + } else { + inv_identifier += "\\\\ " + inv_tspans[inv_t].innerHTML; + } + } + } + } + var inv_qType = "owlObjectProperty"; + var inv_bgColorStr = ""; + + if ( inv_correspondingProp.backgroundColor() ) { + // console.log("Found backGround color"); + var inv_bgColor = inv_correspondingProp.backgroundColor(); + // console.log(inv_bgColor); + inv_bgColor.toUpperCase(); + inv_bgColor = inv_bgColor.slice(1, inv_bgColor.length); + texString += "\\definecolor{inv_property" + i + "_COLOR}{HTML}{" + inv_bgColor + "} \n "; + inv_bgColorStr = ", fill=inv_property" + i + "_COLOR "; + } + if ( inv_correspondingProp.attributes().indexOf("deprecated") > -1 ) { + texString += "\\definecolor{inv_property" + i + "_COLOR}{HTML}{CCCCCC} \n "; + inv_bgColorStr = ", fill=inv_property" + i + "_COLOR "; + } + + var inv_widthString = ""; + var inv_width = inv_correspondingProp.textWidth(); + + var pOY1 = p_py - 14; + var pOY2 = p_py + 14; + inv_widthString = ",minimum width=" + inv_width + "pt"; + texString += "% Createing Inverse Property \n"; + texString += "\\node[" + inv_qType + " " + inv_widthString + " " + inv_bgColorStr + " " + inv_textColorStr + "] at (" + p_px + "pt, " + pOY1 + "pt) (property" + i + ") {" + inv_identifier.replaceAll("_", "\\_ ") + "};\n"; + texString += "% " + inv_qType + " vs " + qType + "\n"; + texString += "% " + inv_widthString + " vs " + widthString + "\n"; + texString += "% " + inv_bgColorStr + " vs " + bgColorStr + "\n"; + texString += "% " + inv_textColorStr + " vs " + textColorStr + "\n"; + + texString += "\\node[" + qType + " " + widthString + " " + bgColorStr + " " + textColorStr + "] at (" + p_px + "pt, " + pOY2 + "pt) (property" + i + ") {" + identifier.replaceAll("_", "\\_ ") + "};\n"; + + } else { + texString += "\\node[" + qType + " " + widthString + " " + bgColorStr + " " + textColorStr + "] at (" + p_px + "pt, " + p_py + "pt) (property" + i + ") {" + identifier.replaceAll("_", "\\_ ") + "};\n"; + } + } + + texString += "\\end{tikzpicture}\n}\n \\end{center}\n"; + + // console.log("Tex Output\n"+ texString); + var dataURI = "data:text/json;charset=utf-8," + encodeURIComponent(texString); + exportTexButton.attr("href", dataURI) + .attr("download", exportFilename + ".tex"); + + + } + + function calculateRadian( angle ){ + angle = angle % 360; + if ( angle < 0 ) { + angle = angle + 360; + } + return (Math.PI * angle) / 180; + } + + function calculateAngle( radian ){ + return radian * (180 / Math.PI); + } + + return exportMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 324: +/***/ (function(module, exports) { + + /** + * Contains the logic for the export button. + * @returns {{}} + */ + module.exports = function ( graph ){ + var exportTTLModule = {}; + var resultingTTLContent = ""; + var currentNodes; + var currentProperties; + var currentAxioms; + var Map_ID2Node = {}; + var Map_ID2Prop = {}; + var prefixModule = webvowl.util.prefixTools(graph); + + exportTTLModule.requestExport = function (){ + prefixModule.updatePrefixModel(); + resultingTTLContent = ""; + currentNodes = graph.getClassDataForTtlExport(); + var i; + for ( i = 0; i < currentNodes.length; i++ ) { + Map_ID2Node[currentNodes[i].id()] = currentNodes[i]; + } + currentProperties = graph.getPropertyDataForTtlExport(); + + for ( i = 0; i < currentProperties.length; i++ ) { + Map_ID2Prop[currentProperties[i].id()] = currentProperties[i]; + } + + + prepareHeader(); + preparePrefixList(); + prepareOntologyDef(); + resultingTTLContent += "#################################################################\r\n\r\n"; + preparePrefixRepresentation(); + var property_success = exportProperties(); + var class_success = exportClasses(); + currentNodes = null; + currentProperties = null; + Map_ID2Node = {}; + Map_ID2Prop = {}; + if ( property_success === false || class_success === false ) + return false; + return true; + + }; + + function preparePrefixRepresentation(){ + var i; + var allNodes = graph.getUnfilteredData().nodes; + var allProps = graph.getUnfilteredData().properties; + for ( i = 0; i < allNodes.length; i++ ) { + var nodeIRI = prefixModule.getPrefixRepresentationForFullURI(allNodes[i].iri()); + if ( prefixModule.validURL(nodeIRI) === true ) + allNodes[i].prefixRepresentation = "<" + nodeIRI + ">"; + else + allNodes[i].prefixRepresentation = nodeIRI; + } + for ( i = 0; i < allProps.length; i++ ) { + var propIRI = prefixModule.getPrefixRepresentationForFullURI(allProps[i].iri()); + if ( prefixModule.validURL(propIRI) === true ) + allProps[i].prefixRepresentation = "<" + propIRI + ">"; + else + allProps[i].prefixRepresentation = propIRI; + } + } + + function exportProperties(){ + if ( currentProperties.length === 0 ) return; // we dont need to write that + resultingTTLContent += "### Property Definitions (Number of Property) " + currentProperties.length + " ###\r\n"; + for ( var i = 0; i < currentProperties.length; i++ ) { + + resultingTTLContent += "# --------------------------- Property " + i + "------------------------- \r\n"; + var addedElement = extractPropertyDescription(currentProperties[i]); + resultingTTLContent += addedElement; + //@ workaround for not supported elements + if ( addedElement.indexOf("WHYEMPTYNAME") !== -1 ) { + return false; + } + } + return true; + } + + + function exportClasses(){ + if ( currentNodes.length === 0 ) return; // we dont need to write that + resultingTTLContent += "### Class Definitions (Number of Classes) " + currentNodes.length + " ###\r\n"; + for ( var i = 0; i < currentNodes.length; i++ ) { + // check for node type here and return false + resultingTTLContent += "# --------------------------- Class " + i + "------------------------- \r\n"; + var addedElement = extractClassDescription(currentNodes[i]); + resultingTTLContent += addedElement; + + if ( addedElement.indexOf("WHYEMPTYNAME") !== -1 ) { + return false; + } + } + return true; + } + + function getPresentAttribute( selectedElement, element ){ + var attr = selectedElement.attributes(); + return (attr.indexOf(element) >= 0); + } + + function extractClassDescription( node ){ + var subject = node.prefixRepresentation; + var predicate = "rdf:type"; + var object = node.type(); + if ( node.type() === "owl:equivalentClass" ) + object = "owl:Class"; + if ( node.type() === "owl:disjointUnionOf" ) + object = "owl:Class"; + if ( node.type() === "owl:unionOf" ) + object = "owl:Class"; + var arrayOfNodes = []; + var arrayOfUnionNodes = []; + + if ( node.union() ) { + var union = node.union(); + for ( var u = 0; u < union.length; u++ ) { + var u_node = Map_ID2Node[union[u]]; + arrayOfUnionNodes.push(u_node); + } + } + + if ( node.disjointUnion() ) { + var distUnion = node.disjointUnion(); + for ( var du = 0; du < distUnion.length; du++ ) { + var du_node = Map_ID2Node[distUnion[du]]; + arrayOfNodes.push(du_node); + } + } + + var objectDef = subject + " " + predicate + " " + object; + if ( getPresentAttribute(node, "deprecated") === true ) { + objectDef += ", owl:DeprecatedProperty"; + } + // equivalent class handeled using type itself! + + // check for equivalent classes; + var indent = getIndent(subject); + objectDef += "; \r\n"; + for ( var e = 0; e < node.equivalents().length; e++ ) { + var eqIRI = prefixModule.getPrefixRepresentationForFullURI(node.equivalents()[e].iri()); + var eqNode_prefRepresentation = ""; + if ( prefixModule.validURL(eqIRI) === true ) + eqNode_prefRepresentation = "<" + eqIRI + ">"; + else + eqNode_prefRepresentation = eqIRI; + objectDef += indent + " owl:equivalentClass " + eqNode_prefRepresentation + " ;\r\n"; + } + + // if (getPresentAttribute(node,"equivalent")===true){ + // objectDef+=", owl:EquivalentClass"; + // } + + // add Comments + + if ( node.commentForCurrentLanguage() ) { + + objectDef += indent + " rdfs:comment \"" + node.commentForCurrentLanguage() + "\" ;\r\n"; + } + + if ( node.annotations() ) { + var annotations = node.annotations(); + for ( var an in annotations ) { + if ( annotations.hasOwnProperty(an) ) { + var anArrayObj = annotations[an]; + var anObj = anArrayObj[0]; + var an_ident = anObj.identifier; + var an_val = anObj.value; + + if ( an_ident === "isDefinedBy" ) { + objectDef += indent + " rdfs:isDefinedBy <" + an_val + "> ;\r\n"; + } + if ( an_ident === "term_status" ) { + objectDef += indent + " vs:term_status \"" + an_val + "\" ;\r\n"; + } + } + } + } + + + if ( arrayOfNodes.length > 0 ) { + // add disjoint unionOf + objectDef += indent + " owl:disjointUnionOf ("; + for ( var duE = 0; duE < arrayOfNodes.length; duE++ ) { + var duIri = prefixModule.getPrefixRepresentationForFullURI(arrayOfNodes[duE].iri()); + var duNode_prefRepresentation = ""; + if ( prefixModule.validURL(duIri) === true ) + duNode_prefRepresentation = "<" + duIri + ">"; + else + duNode_prefRepresentation = duIri; + objectDef += indent + indent + duNode_prefRepresentation + " \n"; + } + objectDef += ") ;\r\n"; + } + + if ( arrayOfUnionNodes.length > 0 ) { + // add disjoint unionOf + objectDef += indent + " rdfs:subClassOf [ rdf:type owl:Class ; \r\n"; + objectDef += indent + indent + " owl:unionOf ( "; + + for ( var uE = 0; uE < arrayOfUnionNodes.length; uE++ ) { + + if ( arrayOfUnionNodes[uE] && arrayOfUnionNodes[uE].iri() ) { + var uIri = prefixModule.getPrefixRepresentationForFullURI(arrayOfUnionNodes[uE].iri()); + var uNode_prefRepresentation = ""; + if ( prefixModule.validURL(uIri) === true ) + uNode_prefRepresentation = "<" + uIri + ">"; + else + uNode_prefRepresentation = uIri; + objectDef += indent + indent + indent + uNode_prefRepresentation + " \n"; + } + } + objectDef += ") ;\r\n"; + + + } + + + var allProps = graph.getUnfilteredData().properties; + var myProperties = []; + var i; + for ( i = 0; i < allProps.length; i++ ) { + if ( allProps[i].domain() === node && + ( allProps[i].type() === "rdfs:subClassOf" || + allProps[i].type() === "owl:allValuesFrom" || + allProps[i].type() === "owl:someValuesFrom") + ) { + myProperties.push(allProps[i]); + } + // special case disjoint with>> both domain and range get that property + if ( (allProps[i].domain() === node) && + allProps[i].type() === "owl:disjointWith" ) { + myProperties.push(allProps[i]); + } + + } + for ( i = 0; i < myProperties.length; i++ ) { + // depending on the property we have to do some things; + + // special case + if ( myProperties[i].type() === "owl:someValuesFrom" ) { + objectDef += indent + " rdfs:subClassOf [ rdf:type owl:Restriction ; \r\n"; + objectDef += indent + " owl:onProperty " + myProperties[i].prefixRepresentation + ";\r\n"; + if ( myProperties[i].range().type() !== "owl:Thing" ) { + objectDef += indent + " owl:someValuesFrom " + myProperties[i].range().prefixRepresentation + "\r\n"; + } + objectDef += indent + " ];\r\n"; + continue; + } + + if ( myProperties[i].type() === "owl:allValuesFrom" ) { + objectDef += indent + " rdfs:subClassOf [ rdf:type owl:Restriction ; \r\n"; + objectDef += indent + " owl:onProperty " + myProperties[i].prefixRepresentation + ";\r\n"; + if ( myProperties[i].range().type() !== "owl:Thing" ) { + objectDef += indent + " owl:allValuesFrom " + myProperties[i].range().prefixRepresentation + "\r\n"; + } + objectDef += indent + " ];\r\n"; + continue; + } + + if ( myProperties[i].range().type() !== "owl:Thing" ) { + objectDef += indent + " " + myProperties[i].prefixRepresentation + + " " + myProperties[i].range().prefixRepresentation + " ;\r\n"; + + + } + } + + + objectDef += general_Label_languageExtractor(indent, node.label(), "rdfs:label", true); + return objectDef; + + } + + function extractPropertyDescription( property ){ + var subject = property.prefixRepresentation; + if ( subject.length === 0 ) { + console.log("THIS SHOULD NOT HAPPEN"); + var propIRI = prefixModule.getPrefixRepresentationForFullURI(property.iri()); + console.log("FOUND " + propIRI); + + + } + var predicate = "rdf:type"; + var object = property.type(); + + var objectDef = subject + " " + predicate + " " + object; + if ( getPresentAttribute(property, "deprecated") === true ) { + objectDef += ", owl:DeprecatedProperty"; + } + if ( getPresentAttribute(property, "functional") === true ) { + objectDef += ", owl:FunctionalProperty"; + } + if ( getPresentAttribute(property, "inverse functional") === true ) { + objectDef += ", owl:InverseFunctionalProperty"; + } + if ( getPresentAttribute(property, "symmetric") === true ) { + objectDef += ", owl:SymmetricProperty"; + } + if ( getPresentAttribute(property, "transitive") === true ) { + objectDef += ", owl:TransitiveProperty"; + } + var indent = getIndent(subject); + + if ( property.inverse() ) { + objectDef += "; \r\n"; + objectDef += indent + " owl:inverseOf " + property.inverse().prefixRepresentation; + } + + // check for domain and range; + + + var closeStatement = false; + var domain = property.domain(); + var range = property.range(); + + + objectDef += " ;\r\n"; + + + if ( property.commentForCurrentLanguage() ) { + + objectDef += indent + " rdfs:comment \"" + property.commentForCurrentLanguage() + "\" ;\r\n"; + } + + if ( property.superproperties() ) { + var superProps = property.superproperties(); + for ( var sP = 0; sP < superProps.length; sP++ ) { + var sPelement = superProps[sP]; + objectDef += indent + "rdfs:subPropertyOf " + sPelement.prefixRepresentation + ";\r\n"; + } + // for (var an in annotations){ + // if (annotations.hasOwnProperty(an)){ + // var anArrayObj=annotations[an]; + // var anObj=anArrayObj[0]; + // var an_ident=anObj.identifier; + // var an_val=anObj.value; + // console.log(an_ident + " "+ an_val); + // + // if (an_ident==="isDefinedBy"){ + // objectDef+=indent+" rdfs:isDefinedBy <"+an_val+"> ;\r\n"; + // } + // if (an_ident==="term_status"){ + // objectDef+=indent+" vs:term_status \""+an_val+"\" ;\r\n"; + // } + // } + // } + + } + + if ( property.annotations() ) { + var annotations = property.annotations(); + for ( var an in annotations ) { + if ( annotations.hasOwnProperty(an) ) { + var anArrayObj = annotations[an]; + var anObj = anArrayObj[0]; + var an_ident = anObj.identifier; + var an_val = anObj.value; + + if ( an_ident === "isDefinedBy" ) { + objectDef += indent + " rdfs:isDefinedBy <" + an_val + "> ;\r\n"; + } + if ( an_ident === "term_status" ) { + objectDef += indent + " vs:term_status \"" + an_val + "\" ;\r\n"; + } + } + } + } + + + if ( domain.type() === "owl:Thing" && range.type() === "owl:Thing" ) { + // we do not write domain and range + if ( typeof property.label() !== "object" && property.label().length === 0 ) { + closeStatement = true; + } + } + + + if ( closeStatement === true ) { + var uobjectDef = objectDef.substring(0, objectDef.length - 2); + objectDef = uobjectDef + " . \r\n"; + return objectDef; + } + // objectDef+="; \r\n"; + var labelDescription; + + + if ( domain.type() === "owl:Thing" && range.type() === "owl:Thing" ) { + labelDescription = general_Label_languageExtractor(indent, property.label(), "rdfs:label", true); + objectDef += labelDescription; + } + else { + // do not close the statement; + labelDescription = general_Label_languageExtractor(indent, property.label(), "rdfs:label"); + objectDef += labelDescription; + if ( domain.type() !== "owl:Thing" ) { + objectDef += indent + " rdfs:domain " + domain.prefixRepresentation + ";\r\n"; + } + if ( range.type() !== "owl:Thing" ) { + objectDef += indent + " rdfs:range " + range.prefixRepresentation + ";\r\n"; + } + + // close statement now; + + var s_needUpdate = objectDef; + var s_lastPtr = s_needUpdate.lastIndexOf(";"); + objectDef = s_needUpdate.substring(0, s_lastPtr) + " . \r\n"; + } + + return objectDef; + + } + + + exportTTLModule.resultingTTL_Content = function (){ + return resultingTTLContent; + }; + + function getIndent( name ){ + if ( name === undefined ) { + return "WHYEMPTYNAME?"; + } + return new Array(name.length + 1).join(" "); + } + + function prepareHeader(){ + resultingTTLContent += "#################################################################\r\n"; + resultingTTLContent += "### Generated with the experimental alpha version of the TTL exporter of WebVOWL (version 1.1.7) " + + " http://visualdataweb.de/webvowl/ ###\r\n"; + resultingTTLContent += "#################################################################\r\n\r\n"; + + } + + function preparePrefixList(){ + var ontoIri = graph.options().getGeneralMetaObjectProperty('iri'); + var prefixList = graph.options().prefixList(); + var prefixDef = []; + prefixDef.push('@prefix : \t\t<' + ontoIri + '> .'); + for ( var name in prefixList ) { + if ( prefixList.hasOwnProperty(name) ) { + prefixDef.push('@prefix ' + name + ': \t\t<' + prefixList[name] + '> .'); + } + } + prefixDef.push('@base \t\t\t<' + ontoIri + '> .\r\n'); + + for ( var i = 0; i < prefixDef.length; i++ ) { + resultingTTLContent += prefixDef[i] + '\r\n'; + } + } + + function prepareOntologyDef(){ + var ontoIri = graph.options().getGeneralMetaObjectProperty('iri'); + var indent = getIndent('<' + ontoIri + '>'); + resultingTTLContent += '<' + ontoIri + '> rdf:type owl:Ontology ;\r\n' + + getOntologyTitle(indent) + + getOntologyDescription(indent) + + getOntologyVersion(indent) + + getOntologyAuthor(indent); + + // close the statement; + var s_needUpdate = resultingTTLContent; + var s_lastPtr = s_needUpdate.lastIndexOf(";"); + resultingTTLContent = s_needUpdate.substring(0, s_lastPtr) + " . \r\n"; + } + + function getOntologyTitle( indent ){ + return general_languageExtractor(indent, "title", "dc:title"); + } + + function getOntologyDescription( indent ){ + return general_languageExtractor(indent, "description", "dc:description"); + } + + function getOntologyAuthor( indent ){ + var languageElement = graph.options().getGeneralMetaObjectProperty('author'); + if ( languageElement ) { + if ( typeof languageElement !== "object" ) { + if ( languageElement.length === 0 ) + return ""; // an empty string + var aString = indent + " dc:creator " + '"' + languageElement + '";\r\n'; + return aString; + } + // we assume this thing is an array; + var authorString = indent + " dc:creator " + '"'; + for ( var i = 0; i < languageElement.length - 1; i++ ) { + authorString += languageElement[i] + ", "; + } + authorString += languageElement[languageElement.length - 1] + '";\r\n'; + return authorString; + } else { + return ""; // an empty string + } + } + + function getOntologyVersion( indent ){ + var languageElement = graph.options().getGeneralMetaObjectProperty('version'); + if ( languageElement ) { + if ( typeof languageElement !== "object" ) { + if ( languageElement.length === 0 ) + return ""; // an empty string + } + return general_languageExtractor(indent, "version", "owl:versionInfo"); + } else return ""; // an empty string + } + + function general_languageExtractor( indent, metaObjectDescription, annotationDescription, endStatement ){ + var languageElement = graph.options().getGeneralMetaObjectProperty(metaObjectDescription); + + if ( typeof languageElement === 'object' ) { + + var resultingLanguages = []; + for ( var name in languageElement ) { + if ( languageElement.hasOwnProperty(name) ) { + var content = languageElement[name]; + if ( name === "undefined" ) { + resultingLanguages.push(indent + " " + annotationDescription + ' "' + content + '"@en; \r\n'); + } + else { + resultingLanguages.push(indent + " " + annotationDescription + ' "' + content + '"@' + name + '; \r\n'); + } + } + } + // create resulting titles; + + var resultingString = ""; + for ( var i = 0; i < resultingLanguages.length; i++ ) { + resultingString += resultingLanguages[i]; + } + if ( endStatement && endStatement === true ) { + var needUpdate = resultingString; + var lastPtr = needUpdate.lastIndexOf(";"); + return needUpdate.substring(0, lastPtr) + ". \r\n"; + } else { + return resultingString; + } + + } else { + if ( endStatement && endStatement === true ) { + var s_needUpdate = indent + " " + annotationDescription + ' "' + languageElement + '"@en; \r\n'; + var s_lastPtr = s_needUpdate.lastIndexOf(";"); + return s_needUpdate.substring(0, s_lastPtr) + " . \r\n"; + } + return indent + " " + annotationDescription + ' "' + languageElement + '"@en;\r\n'; + } + } + + function general_Label_languageExtractor( indent, label, annotationDescription, endStatement ){ + var languageElement = label; + + if ( typeof languageElement === 'object' ) { + var resultingLanguages = []; + for ( var name in languageElement ) { + if ( languageElement.hasOwnProperty(name) ) { + var content = languageElement[name]; + if ( name === "undefined" ) { + resultingLanguages.push(indent + " " + annotationDescription + ' "' + content + '"@en; \r\n'); + } + else { + resultingLanguages.push(indent + " " + annotationDescription + ' "' + content + '"@' + name + '; \r\n'); + } + } + } + // create resulting titles; + var resultingString = ""; + for ( var i = 0; i < resultingLanguages.length; i++ ) { + resultingString += resultingLanguages[i]; + } + if ( endStatement && endStatement === true ) { + var needUpdate = resultingString; + var lastPtr = needUpdate.lastIndexOf(";"); + return needUpdate.substring(0, lastPtr) + " . \r\n"; + } else { + return resultingString; + } + + } else { + if ( endStatement && endStatement === true ) { + var s_needUpdate = indent + " " + annotationDescription + ' "' + languageElement + '"@en; \r\n'; + var s_lastPtr = s_needUpdate.lastIndexOf(";"); + return s_needUpdate.substring(0, s_lastPtr) + " . \r\n"; + } + return indent + " " + annotationDescription + ' "' + languageElement + '"@en; \r\n'; + } + } + + return exportTTLModule; + }; + + +/***/ }), + +/***/ 325: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for connecting the filters with the website. + * + * @param graph required for calling a refresh after a filter change + * @returns {{}} + */ + module.exports = function ( graph ){ + + var filterMenu = {}, + checkboxData = [], + menuElement = d3.select("#m_filter"), + menuControl = d3.select("#c_filter a"), + nodeDegreeContainer = d3.select("#nodeDegreeFilteringOption"), + graphDegreeLevel, + defaultDegreeValue = 0, + degreeSlider; + + filterMenu.setDefaultDegreeValue = function ( val ){ + defaultDegreeValue = val; + }; + filterMenu.getDefaultDegreeValue = function (){ + return defaultDegreeValue; + }; + + filterMenu.getGraphObject = function (){ + return graph; + }; + /** some getter function **/ + filterMenu.getCheckBoxContainer = function (){ + return checkboxData; + }; + + filterMenu.getDegreeSliderValue = function (){ + return degreeSlider.property("value"); + }; + /** + * Connects the website with graph filters. + * @param datatypeFilter filter for all datatypes + * @param objectPropertyFilter filter for all object properties + * @param subclassFilter filter for all subclasses + * @param disjointFilter filter for all disjoint with properties + * @param setOperatorFilter filter for all set operators with properties + * @param nodeDegreeFilter filters nodes by their degree + */ + filterMenu.setup = function ( datatypeFilter, objectPropertyFilter, subclassFilter, disjointFilter, setOperatorFilter, nodeDegreeFilter ){ + // TODO: is this here really necessarry? << new menu visualization style? + menuControl.on("mouseover", function (){ + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + }); + menuControl.on("mouseleave", function (){ + filterMenu.highlightForDegreeSlider(false); + }); + + addFilterItem(datatypeFilter, "datatype", "Datatype properties", "#datatypeFilteringOption"); + addFilterItem(objectPropertyFilter, "objectProperty", "Object properties", "#objectPropertyFilteringOption"); + addFilterItem(subclassFilter, "subclass", "Solitary subclasses", "#subclassFilteringOption"); + addFilterItem(disjointFilter, "disjoint", "Class disjointness", "#disjointFilteringOption"); + addFilterItem(setOperatorFilter, "setoperator", "Set operators", "#setOperatorFilteringOption"); + + addNodeDegreeFilter(nodeDegreeFilter, nodeDegreeContainer); + addAnimationFinishedListener(); + }; + + + function addFilterItem( filter, identifier, pluralNameOfFilteredItems, selector ){ + var filterContainer, + filterCheckbox; + + filterContainer = d3.select(selector) + .append("div") + .classed("checkboxContainer", true); + + filterCheckbox = filterContainer.append("input") + .classed("filterCheckbox", true) + .attr("id", identifier + "FilterCheckbox") + .attr("type", "checkbox") + .property("checked", filter.enabled()); + + // Store for easier resetting + checkboxData.push({ checkbox: filterCheckbox, defaultState: filter.enabled() }); + + filterCheckbox.on("click", function ( silent ){ + // There might be no parameters passed because of a manual + // invocation when resetting the filters + var isEnabled = filterCheckbox.property("checked"); + filter.enabled(isEnabled); + if ( silent !== true ) { + // updating graph when silent is false or the parameter is not given. + graph.update(); + } + }); + + filterContainer.append("label") + .attr("for", identifier + "FilterCheckbox") + .text(pluralNameOfFilteredItems); + } + + function addNodeDegreeFilter( nodeDegreeFilter, container ){ + nodeDegreeFilter.setMaxDegreeSetter(function ( maxDegree ){ + degreeSlider.attr("max", maxDegree); + setSliderValue(degreeSlider, Math.min(maxDegree, degreeSlider.property("value"))); + }); + + nodeDegreeFilter.setDegreeGetter(function (){ + return degreeSlider.property("value"); + }); + + nodeDegreeFilter.setDegreeSetter(function ( value ){ + setSliderValue(degreeSlider, value); + }); + + var sliderContainer, + sliderValueLabel; + + sliderContainer = container.append("div") + .classed("distanceSliderContainer", true); + + degreeSlider = sliderContainer.append("input") + .attr("id", "nodeDegreeDistanceSlider") + .attr("type", "range") + .attr("min", 0) + .attr("step", 1); + + sliderContainer.append("label") + .classed("description", true) + .attr("for", "nodeDegreeDistanceSlider") + .text("Degree of collapsing"); + + sliderValueLabel = sliderContainer.append("label") + .classed("value", true) + .attr("for", "nodeDegreeDistanceSlider") + .text(0); + + + degreeSlider.on("change", function ( silent ){ + if ( silent !== true ) { + graph.update(); + graphDegreeLevel = degreeSlider.property("value"); + } + }); + + + degreeSlider.on("input", function (){ + var degree = degreeSlider.property("value"); + sliderValueLabel.text(degree); + }); + + + // adding wheel events + degreeSlider.on("wheel", handleWheelEvent); + degreeSlider.on("focusout", function (){ + if ( degreeSlider.property("value") !== graphDegreeLevel ) { + graph.update(); + } + }); + } + + function handleWheelEvent(){ + var wheelEvent = d3.event; + + var offset; + if ( wheelEvent.deltaY < 0 ) offset = 1; + if ( wheelEvent.deltaY > 0 ) offset = -1; + var maxDeg = parseInt(degreeSlider.attr("max")); + var oldVal = parseInt(degreeSlider.property("value")); + var newSliderValue = oldVal + offset; + if ( oldVal !== newSliderValue && (newSliderValue >= 0 && newSliderValue <= maxDeg) ) { + // only update when they are different [reducing redundant updates] + // set the new value and emit an update signal + degreeSlider.property("value", newSliderValue); + degreeSlider.on("input")();// <<-- sets the text value + graph.update(); + } + d3.event.preventDefault(); + } + + function setSliderValue( slider, value ){ + slider.property("value", value).on("input")(); + } + + /** + * Resets the filters (and also filtered elements) to their default. + */ + filterMenu.reset = function (){ + checkboxData.forEach(function ( checkboxData ){ + var checkbox = checkboxData.checkbox, + enabledByDefault = checkboxData.defaultState, + isChecked = checkbox.property("checked"); + + if ( isChecked !== enabledByDefault ) { + checkbox.property("checked", enabledByDefault); + // Call onclick event handlers programmatically + checkbox.on("click")(); + } + }); + + setSliderValue(degreeSlider, 0); + degreeSlider.on("change")(); + }; + + function addAnimationFinishedListener(){ + menuControl.node().addEventListener("animationend", function (){ + menuControl.classed("buttonPulse", false); + menuControl.classed("filterMenuButtonHighlight", true); + + }); + } + + filterMenu.killButtonAnimation = function (){ + menuControl.classed("buttonPulse", false); + menuControl.classed("filterMenuButtonHighlight", false); + }; + + + filterMenu.highlightForDegreeSlider = function ( enable ){ + if ( !arguments.length ) { + enable = true; + } + menuControl.classed("highlighted", enable); + nodeDegreeContainer.classed("highlighted", enable); + // pulse button handling + if ( menuControl.classed("buttonPulse") === true && enable === true ) { + menuControl.classed("buttonPulse", false); + var timer = setTimeout(function (){ + menuControl.classed("buttonPulse", enable); + clearTimeout(timer); + // after the time is done, remove the pulse but stay highlighted + }, 100); + } else { + menuControl.classed("buttonPulse", enable); + menuControl.classed("filterMenuButtonHighlight", enable); + } + }; + + + /** importer functions **/ + // setting manually the values of the filter + // no update of the gui settings, these are updated in updateSettings + filterMenu.setCheckBoxValue = function ( id, checked ){ + for ( var i = 0; i < checkboxData.length; i++ ) { + var cbdId = checkboxData[i].checkbox.attr("id"); + if ( cbdId === id ) { + checkboxData[i].checkbox.property("checked", checked); + break; + } + } + }; + + filterMenu.getCheckBoxValue = function ( id ){ + for ( var i = 0; i < checkboxData.length; i++ ) { + var cbdId = checkboxData[i].checkbox.attr("id"); + if ( cbdId === id ) { + return checkboxData[i].checkbox.property("checked"); + + } + } + }; + // set the value of the slider + filterMenu.setDegreeSliderValue = function ( val ){ + degreeSlider.property("value", val); + }; + + filterMenu.getDegreeSliderValue = function (){ + return degreeSlider.property("value"); + }; + + // update the gui without invoking graph update (calling silent onclick function) + filterMenu.updateSettings = function (){ + var silent = true; + var sliderValue = degreeSlider.property("value"); + if ( sliderValue > 0 ) { + filterMenu.highlightForDegreeSlider(true); + } else { + filterMenu.highlightForDegreeSlider(false); + } + checkboxData.forEach(function ( checkboxData ){ + var checkbox = checkboxData.checkbox; + checkbox.on("click")(silent); + }); + + degreeSlider.on("input")(); + degreeSlider.on("change")(); + + }; + + return filterMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 326: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for setting up the gravity sliders. + * + * @param graph the associated webvowl graph + * @returns {{}} + */ + module.exports = function ( graph ){ + + var gravityMenu = {}, + sliders = [], + options = graph.graphOptions(), + defaultCharge = options.charge(); + + + /** + * Adds the gravity sliders to the website. + */ + gravityMenu.setup = function (){ + var menuEntry = d3.select("#m_gravity"); + menuEntry.on("mouseover", function (){ + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + }); + addDistanceSlider("#classSliderOption", "class", "Class distance", options.classDistance); + addDistanceSlider("#datatypeSliderOption", "datatype", "Datatype distance", options.datatypeDistance); + }; + + function addDistanceSlider( selector, identifier, label, distanceFunction ){ + var defaultLinkDistance = distanceFunction(); + + var sliderContainer, + sliderValueLabel; + + sliderContainer = d3.select(selector) + .append("div") + .datum({ distanceFunction: distanceFunction }) // connect the options-function with the slider + .classed("distanceSliderContainer", true); + + var slider = sliderContainer.append("input") + .attr("id", identifier + "DistanceSlider") + .attr("type", "range") + .attr("min", 10) + .attr("max", 600) + .attr("value", distanceFunction()) + .attr("step", 10); + + sliderContainer.append("label") + .classed("description", true) + .attr("for", identifier + "DistanceSlider") + .text(label); + + sliderValueLabel = sliderContainer.append("label") + .classed("value", true) + .attr("for", identifier + "DistanceSlider") + .text(distanceFunction()); + + // Store slider for easier resetting + sliders.push(slider); + + slider.on("focusout", function (){ + graph.updateStyle(); + }); + + slider.on("input", function (){ + var distance = slider.property("value"); + distanceFunction(distance); + adjustCharge(defaultLinkDistance); + sliderValueLabel.text(distance); + graph.updateStyle(); + }); + + // add wheel event to the slider + slider.on("wheel", function (){ + var wheelEvent = d3.event; + var offset; + if ( wheelEvent.deltaY < 0 ) offset = 10; + if ( wheelEvent.deltaY > 0 ) offset = -10; + var oldVal = parseInt(slider.property("value")); + var newSliderValue = oldVal + offset; + if ( newSliderValue !== oldVal ) { + slider.property("value", newSliderValue); + distanceFunction(newSliderValue); + slider.on("input")(); // << set text and update the graphStyles + } + d3.event.preventDefault(); + }); + } + + function adjustCharge( defaultLinkDistance ){ + var greaterDistance = Math.max(options.classDistance(), options.datatypeDistance()), + ratio = greaterDistance / defaultLinkDistance, + newCharge = defaultCharge * ratio; + + options.charge(newCharge); + } + + /** + * Resets the gravity sliders to their default. + */ + gravityMenu.reset = function (){ + sliders.forEach(function ( slider ){ + slider.property("value", function ( d ){ + // Simply reload the distance from the options + return d.distanceFunction(); + }); + slider.on("input")(); + }); + }; + + + return gravityMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 327: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for connecting the modes with the website. + * + * @param graph the graph that belongs to these controls + * @returns {{}} + */ + module.exports = function ( graph ){ + + var SAME_COLOR_MODE = { text: "Multicolor", type: "same" }; + var GRADIENT_COLOR_MODE = { text: "Multicolor", type: "gradient" }; + + var modeMenu = {}, + checkboxes = [], + colorModeSwitch; + + var dynamicLabelWidthCheckBox; + // getter and setter for the state of color modes + modeMenu.colorModeState = function ( s ){ + if ( !arguments.length ) return colorModeSwitch.datum().active; + colorModeSwitch.datum().active = s; + return modeMenu; + }; + + + modeMenu.setDynamicLabelWidth = function ( val ){ + dynamicLabelWidthCheckBox.property("checked", val); + }; + // getter for checkboxes + modeMenu.getCheckBoxContainer = function (){ + return checkboxes; + }; + // getter for the color switch [needed? ] + modeMenu.colorModeSwitch = function (){ + return colorModeSwitch; + }; + + /** + * Connects the website with the available graph modes. + */ + modeMenu.setup = function ( pickAndPin, nodeScaling, compactNotation, colorExternals ){ + var menuEntry = d3.select("#m_modes"); + menuEntry.on("mouseover", function (){ + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + }); + addCheckBoxD("labelWidth", "Dynamic label width", "#dynamicLabelWidth", graph.options().dynamicLabelWidth, 1); + addCheckBox("editorMode", "Editing ", "#editMode", graph.editorMode); + addModeItem(pickAndPin, "pickandpin", "Pick & pin", "#pickAndPinOption", false); + addModeItem(nodeScaling, "nodescaling", "Node scaling", "#nodeScalingOption", true); + addModeItem(compactNotation, "compactnotation", "Compact notation", "#compactNotationOption", true); + var container = addModeItem(colorExternals, "colorexternals", "Color externals", "#colorExternalsOption", true); + colorModeSwitch = addExternalModeSelection(container, colorExternals); + }; + function addCheckBoxD( identifier, modeName, selector, onChangeFunc, updateLvl ){ + var moduleOptionContainer = d3.select(selector) + .append("div") + .classed("checkboxContainer", true); + + var moduleCheckbox = moduleOptionContainer.append("input") + .classed("moduleCheckbox", true) + .attr("id", identifier + "ModuleCheckbox") + .attr("type", "checkbox") + .property("checked", onChangeFunc()); + + moduleCheckbox.on("click", function ( d ){ + var isEnabled = moduleCheckbox.property("checked"); + onChangeFunc(isEnabled); + d3.select("#maxLabelWidthSlider").node().disabled = !isEnabled; + d3.select("#maxLabelWidthvalueLabel").classed("disabledLabelForSlider", !isEnabled); + d3.select("#maxLabelWidthDescriptionLabel").classed("disabledLabelForSlider", !isEnabled); + + if ( updateLvl > 0 ) { + graph.animateDynamicLabelWidth(); + // graph.lazyRefresh(); + } + }); + moduleOptionContainer.append("label") + .attr("for", identifier + "ModuleCheckbox") + .text(modeName); + if ( identifier === "editorMode" ) { + moduleOptionContainer.append("label") + .attr("style", "font-size:10px;padding-top:3px") + .text("(experimental)"); + } + + dynamicLabelWidthCheckBox = moduleCheckbox; + } + + function addCheckBox( identifier, modeName, selector, onChangeFunc ){ + var moduleOptionContainer = d3.select(selector) + .append("div") + .classed("checkboxContainer", true); + + var moduleCheckbox = moduleOptionContainer.append("input") + .classed("moduleCheckbox", true) + .attr("id", identifier + "ModuleCheckbox") + .attr("type", "checkbox") + .property("checked", onChangeFunc()); + + moduleCheckbox.on("click", function ( d ){ + var isEnabled = moduleCheckbox.property("checked"); + onChangeFunc(isEnabled); + if ( isEnabled === true ) + graph.showEditorHintIfNeeded(); + }); + moduleOptionContainer.append("label") + .attr("for", identifier + "ModuleCheckbox") + .text(modeName); + if ( identifier === "editorMode" ) { + moduleOptionContainer.append("label") + .attr("style", "font-size:10px;padding-top:3px") + .text(" (experimental)"); + } + } + + function addModeItem( module, identifier, modeName, selector, updateGraphOnClick ){ + var moduleOptionContainer, + moduleCheckbox; + + moduleOptionContainer = d3.select(selector) + .append("div") + .classed("checkboxContainer", true) + .datum({ module: module, defaultState: module.enabled() }); + + moduleCheckbox = moduleOptionContainer.append("input") + .classed("moduleCheckbox", true) + .attr("id", identifier + "ModuleCheckbox") + .attr("type", "checkbox") + .property("checked", module.enabled()); + + // Store for easier resetting all modes + checkboxes.push(moduleCheckbox); + + moduleCheckbox.on("click", function ( d, silent ){ + var isEnabled = moduleCheckbox.property("checked"); + d.module.enabled(isEnabled); + if ( updateGraphOnClick && silent !== true ) { + graph.executeColorExternalsModule(); + graph.executeCompactNotationModule(); + graph.lazyRefresh(); + } + }); + + moduleOptionContainer.append("label") + .attr("for", identifier + "ModuleCheckbox") + .text(modeName); + + return moduleOptionContainer; + } + + function addExternalModeSelection( container, colorExternalsMode ){ + var button = container.append("button").datum({ active: false }).classed("color-mode-switch", true); + applyColorModeSwitchState(button, colorExternalsMode); + + button.on("click", function ( silent ){ + var data = button.datum(); + data.active = !data.active; + applyColorModeSwitchState(button, colorExternalsMode); + if ( colorExternalsMode.enabled() && silent !== true ) { + graph.executeColorExternalsModule(); + graph.lazyRefresh(); + } + }); + + return button; + } + + function applyColorModeSwitchState( element, colorExternalsMode ){ + var isActive = element.datum().active; + var activeColorMode = getColorModeByState(isActive); + + element.classed("active", isActive) + .text(activeColorMode.text); + + if ( colorExternalsMode ) { + colorExternalsMode.colorModeType(activeColorMode.type); + } + } + + function getColorModeByState( isActive ){ + return isActive ? GRADIENT_COLOR_MODE : SAME_COLOR_MODE; + } + + /** + * Resets the modes to their default. + */ + modeMenu.reset = function (){ + checkboxes.forEach(function ( checkbox ){ + var defaultState = checkbox.datum().defaultState, + isChecked = checkbox.property("checked"); + + if ( isChecked !== defaultState ) { + checkbox.property("checked", defaultState); + // Call onclick event handlers programmatically + checkbox.on("click")(checkbox.datum()); + } + + // Reset the module that is connected with the checkbox + checkbox.datum().module.reset(); + }); + + // set the switch to active and simulate disabling + colorModeSwitch.datum().active = true; + colorModeSwitch.on("click")(); + }; + + /** importer functions **/ + // setting manually the values of the filter + // no update of the gui settings, these are updated in updateSettings + modeMenu.setCheckBoxValue = function ( id, checked ){ + for ( var i = 0; i < checkboxes.length; i++ ) { + var cbdId = checkboxes[i].attr("id"); + + if ( cbdId === id ) { + checkboxes[i].property("checked", checked); + break; + } + } + }; + modeMenu.getCheckBoxValue = function ( id ){ + for ( var i = 0; i < checkboxes.length; i++ ) { + var cbdId = checkboxes[i].attr("id"); + if ( cbdId === id ) { + return checkboxes[i].property("checked"); + } + } + }; + + modeMenu.setColorSwitchState = function ( state ){ + // need the !state because we simulate later a click + modeMenu.colorModeState(!state); + }; + modeMenu.setColorSwitchStateUsingURL = function ( state ){ + // need the !state because we simulate later a click + modeMenu.colorModeState(!state); + colorModeSwitch.on("click")(true); + }; + + + modeMenu.updateSettingsUsingURL = function (){ + var silent = true; + checkboxes.forEach(function ( checkbox ){ + checkbox.on("click")(checkbox.datum(), silent); + }); + }; + + modeMenu.updateSettings = function (){ + var silent = true; + checkboxes.forEach(function ( checkbox ){ + checkbox.on("click")(checkbox.datum(), silent); + }); + // this simulates onclick and inverts its state + colorModeSwitch.on("click")(silent); + }; + return modeMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 328: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( graph ){ + var debugMenu = {}, + checkboxes = []; + + + var hoverFlag = false; + var specialCbx; + debugMenu.setup = function (){ + var menuEntry = d3.select("#debugMenuHref"); + + menuEntry.on("mouseover", function (){ + if ( hoverFlag === false ) { + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + specialCbx.on("click")(true); + if ( graph.editorMode() === false ) { + d3.select("#useAccuracyHelper").style("color", "#979797"); + d3.select("#useAccuracyHelper").style("pointer-events", "none"); + + // regardless the state on which useAccuracyHelper is , we are not in editing mode -> disable it + d3.select("#showDraggerObject").style("color", "#979797"); + d3.select("#showDraggerObject").style("pointer-events", "none"); + } else { + d3.select("#useAccuracyHelper").style("color", "#2980b9"); + d3.select("#useAccuracyHelper").style("pointer-events", "auto"); + } + hoverFlag = true; + } + }); + menuEntry.on("mouseout", function (){ + hoverFlag = false; + }); + + + specialCbx = addCheckBox("useAccuracyHelper", "Use accuracy helper", "#useAccuracyHelper", graph.options().useAccuracyHelper, + function ( enabled, silent ){ + if ( !enabled ) { + d3.select("#showDraggerObject").style("color", "#979797"); + d3.select("#showDraggerObject").style("pointer-events", "none"); + d3.select("#showDraggerObjectConfigCheckbox").node().checked = false; + } else { + d3.select("#showDraggerObject").style("color", "#2980b9"); + d3.select("#showDraggerObject").style("pointer-events", "auto"); + } + + if ( silent === true ) return; + graph.lazyRefresh(); + graph.updateDraggerElements(); + } + ); + addCheckBox("showDraggerObject", "Show accuracy helper", "#showDraggerObject", graph.options().showDraggerObject, + function ( enabled, silent ){ + if ( silent === true ) return; + graph.lazyRefresh(); + graph.updateDraggerElements(); + }); + addCheckBox("showFPS_Statistics", "Show rendering statistics", "#showFPS_Statistics", graph.options().showRenderingStatistic, + function ( enabled, silent ){ + + if ( graph.options().getHideDebugFeatures() === false ) { + d3.select("#FPS_Statistics").classed("hidden", !enabled); + } else { + d3.select("#FPS_Statistics").classed("hidden", true); + } + + + }); + addCheckBox("showModeOfOperation", "Show input modality", "#showModeOfOperation", graph.options().showInputModality, + function ( enabled ){ + if ( graph.options().getHideDebugFeatures() === false ) { + d3.select("#modeOfOperationString").classed("hidden", !enabled); + } else { + d3.select("#modeOfOperationString").classed("hidden", true); + } + }); + + + }; + + + function addCheckBox( identifier, modeName, selector, onChangeFunc, _callbackFunction ){ + var configOptionContainer = d3.select(selector) + .append("div") + .classed("checkboxContainer", true); + var configCheckbox = configOptionContainer.append("input") + .classed("moduleCheckbox", true) + .attr("id", identifier + "ConfigCheckbox") + .attr("type", "checkbox") + .property("checked", onChangeFunc()); + + + configCheckbox.on("click", function ( silent ){ + var isEnabled = configCheckbox.property("checked"); + onChangeFunc(isEnabled); + _callbackFunction(isEnabled, silent); + + }); + checkboxes.push(configCheckbox); + configOptionContainer.append("label") + .attr("for", identifier + "ConfigCheckbox") + .text(modeName); + + return configCheckbox; + } + + debugMenu.setCheckBoxValue = function ( identifier, value ){ + for ( var i = 0; i < checkboxes.length; i++ ) { + var cbdId = checkboxes[i].attr("id"); + if ( cbdId === identifier ) { + checkboxes[i].property("checked", value); + break; + } + } + }; + + debugMenu.getCheckBoxValue = function ( id ){ + for ( var i = 0; i < checkboxes.length; i++ ) { + var cbdId = checkboxes[i].attr("id"); + if ( cbdId === id ) { + return checkboxes[i].property("checked"); + } + } + }; + + debugMenu.updateSettings = function (){ + d3.selectAll(".debugOption").classed("hidden", graph.options().getHideDebugFeatures()); + + var silent = true; + checkboxes.forEach(function ( checkbox ){ + checkbox.on("click")(silent); + }); + if ( graph.editorMode() === false ) { + + d3.select("#useAccuracyHelper").style("color", "#979797"); + d3.select("#useAccuracyHelper").style("pointer-events", "none"); + + // regardless the state on which useAccuracyHelper is , we are not in editing mode -> disable it + d3.select("#showDraggerObject").style("color", "#979797"); + d3.select("#showDraggerObject").style("pointer-events", "none"); + } else { + + d3.select("#useAccuracyHelper").style("color", "#2980b9"); + d3.select("#useAccuracyHelper").style("pointer-events", "auto"); + } + + }; + + return debugMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 329: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var unescape = __webpack_require__(330); + + module.exports = function ( graph ){ + + var ontologyMenu = {}, + loadingInfo = d3.select("#loading-info"), + loadingProgress = d3.select("#loading-progress"), + + ontologyMenuTimeout, + fileToLoad, + stopTimer = false, + loadingError = false, + loadingStatusTimer, + conversion_sessionId, + cachedConversions = {}, + loadingModule, + loadOntologyFromText; + var currentLoadedOntologyName = ""; + + String.prototype.beginsWith = function ( string ){ + return (this.indexOf(string) === 0); + }; + + ontologyMenu.getLoadingFunction = function (){ + return loadOntologyFromText; + }; + + ontologyMenu.clearCachedVersion = function (){ + if ( cachedConversions[currentLoadedOntologyName] ) { + cachedConversions[currentLoadedOntologyName] = undefined; + } + }; + + + ontologyMenu.reloadCachedOntology = function (){ + ontologyMenu.clearCachedVersion(); + graph.clearGraphData(); + loadingModule.parseUrlAndLoadOntology(false); + }; + + ontologyMenu.cachedOntology = function ( ontoName ){ + currentLoadedOntologyName = ontoName; + if ( cachedConversions[ontoName] ) { + var locStr = String(location.hash); + d3.select("#reloadSvgIcon").node().disabled = false; + graph.showReloadButtonAfterLayoutOptimization(true); + if ( locStr.indexOf("#file") > -1 ) { + d3.select("#reloadSvgIcon").node().disabled = true; + d3.select("#reloadCachedOntology").node().title = "reloading original version not possible, please reload the file"; + d3.select("#reloadSvgIcon").classed("disabledReloadElement", true); + d3.select("#svgStringText").style("fill", "gray"); + d3.select("#svgStringText").classed("noselect", true); + } + else { + d3.select("#reloadCachedOntology").node().title = "generate new visualization and overwrite cached ontology"; + d3.select("#reloadSvgIcon").classed("disabledReloadElement", false); + d3.select("#svgStringText").style("fill", "black"); + d3.select("#svgStringText").classed("noselect", true); + } + } else { + graph.showReloadButtonAfterLayoutOptimization(false); + + } + return cachedConversions[ontoName]; + }; + ontologyMenu.setCachedOntology = function ( ontoName, ontoContent ){ + cachedConversions[ontoName] = ontoContent; + currentLoadedOntologyName = ontoName; + }; + + ontologyMenu.getErrorStatus = function (){ + return loadingError; + }; + + ontologyMenu.setup = function ( _loadOntologyFromText ){ + loadOntologyFromText = _loadOntologyFromText; + loadingModule = graph.options().loadingModule(); + var menuEntry = d3.select("#m_select"); + menuEntry.on("mouseover", function (){ + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + }); + + setupConverterButtons(); + setupUploadButton(); + + var descriptionButton = d3.select("#error-description-button").datum({ open: false }); + descriptionButton.on("click", function ( data ){ + var errorContainer = d3.select("#error-description-container"); + var errorDetailsButton = d3.select(this); + + // toggle the state + data.open = !data.open; + var descriptionVisible = data.open; + if ( descriptionVisible ) { + errorDetailsButton.text("Hide error details"); + } else { + errorDetailsButton.text("Show error details"); + } + errorContainer.classed("hidden", !descriptionVisible); + }); + + setupUriListener(); + loadingModule.setOntologyMenu(ontologyMenu); + }; + + + function setupUriListener(){ + // reload ontology when hash parameter gets changed manually + d3.select(window).on("hashchange", function (){ + var oldURL = d3.event.oldURL, newURL = d3.event.newURL; + if ( oldURL !== newURL ) { + // don't reload when just the hash parameter gets appended + if ( newURL === oldURL + "#" ) { + return; + } + updateNavigationHrefs(); + loadingModule.parseUrlAndLoadOntology(); + } + }); + updateNavigationHrefs(); + } + + ontologyMenu.stopLoadingTimer = function (){ + stopTimer = true; + clearTimeout(loadingStatusTimer); + }; + + /** + * Quick fix: update all anchor tags that are used as buttons because a click on them + * changes the url and this will load an other ontology. + */ + function updateNavigationHrefs(){ + d3.selectAll("#menuElementContainer > li > a").attr("href", location.hash || "#"); + } + + ontologyMenu.setIriText = function ( text ){ + d3.select("#iri-converter-input").node().value = text; + d3.select("#iri-converter-button").attr("disabled", false); + d3.select("#iri-converter-form").on("submit")(); + }; + + ontologyMenu.clearDetailInformation = function (){ + var bpContainer = d3.select("#bulletPoint_container"); + var htmlCollection = bpContainer.node().children; + var numEntries = htmlCollection.length; + + for ( var i = 0; i < numEntries; i++ ) { + htmlCollection[0].remove(); + } + }; + ontologyMenu.append_message = function ( msg ){ + // forward call + append_message(msg); + }; + function append_message( msg ){ + var bpContainer = d3.select("#bulletPoint_container"); + var div = bpContainer.append("div"); + div.node().innerHTML = msg; + loadingModule.scrollDownDetails(); + } + + ontologyMenu.append_message_toLastBulletPoint = function ( msg ){ + // forward call + append_message_toLastBulletPoint(msg); + }; + + ontologyMenu.append_bulletPoint = function ( msg ){ + // forward call + append_bulletPoint(msg); + }; + function append_message_toLastBulletPoint( msg ){ + var bpContainer = d3.select("#bulletPoint_container"); + var htmlCollection = bpContainer.node().getElementsByTagName("LI"); + var lastItem = htmlCollection.length - 1; + if ( lastItem >= 0 ) { + var oldText = htmlCollection[lastItem].innerHTML; + htmlCollection[lastItem].innerHTML = oldText + msg; + } + loadingModule.scrollDownDetails(); + } + + function append_bulletPoint( msg ){ + var bp_container = d3.select("#bulletPoint_container"); + var bp = bp_container.append("li"); + bp.node().innerHTML = msg; + d3.select("#currentLoadingStep").node().innerHTML = msg; + loadingModule.scrollDownDetails(); + } + + + function setupConverterButtons(){ + var iriConverterButton = d3.select("#iri-converter-button"); + var iriConverterInput = d3.select("#iri-converter-input"); + + iriConverterInput.on("input", function (){ + keepOntologySelectionOpenShortly(); + + var inputIsEmpty = iriConverterInput.property("value") === ""; + iriConverterButton.attr("disabled", inputIsEmpty || undefined); + }).on("click", function (){ + keepOntologySelectionOpenShortly(); + }); + + d3.select("#iri-converter-form").on("submit", function (){ + var inputName = iriConverterInput.property("value"); + + // remove first spaces + var clearedName = inputName.replace(/%20/g, " "); + while ( clearedName.beginsWith(" ") ) { + clearedName = clearedName.substr(1, clearedName.length); + } + // remove ending spaces + while ( clearedName.endsWith(" ") ) { + clearedName = clearedName.substr(0, clearedName.length - 1); + } + // check if iri is actually an url for a json file (ends with .json) + // create lowercase filenames; + inputName = clearedName; + var lc_iri = inputName.toLowerCase(); + if ( lc_iri.endsWith(".json") ) { + location.hash = "url=" + inputName; + iriConverterInput.property("value", ""); + iriConverterInput.on("input")(); + } else { + location.hash = "iri=" + inputName; + iriConverterInput.property("value", ""); + iriConverterInput.on("input")(); + } + d3.event.preventDefault(); + return false; + }); + } + + function setupUploadButton(){ + var input = d3.select("#file-converter-input"), + inputLabel = d3.select("#file-converter-label"), + uploadButton = d3.select("#file-converter-button"); + + input.on("change", function (){ + var selectedFiles = input.property("files"); + if ( selectedFiles.length <= 0 ) { + inputLabel.text("Select ontology file"); + uploadButton.property("disabled", true); + } else { + inputLabel.text(selectedFiles[0].name); + fileToLoad = selectedFiles[0].name; + uploadButton.property("disabled", false); + uploadButton.node().click(); + // close menu; + graph.options().navigationMenu().hideAllMenus(); + } + }); + + uploadButton.on("click", function (){ + var selectedFile = input.property("files")[0]; + if ( !selectedFile ) { + return false; + } + var newHashParameter = "file=" + selectedFile.name; + // Trigger the reupload manually, because the iri is not changing + if ( location.hash === "#" + newHashParameter ) { + loadingModule.parseUrlAndLoadOntology(); + } else { + location.hash = newHashParameter; + } + }); + } + + function setLoadingStatusInfo( message ){ + // check if there is a owl2vowl li item; + var o2vConverterContainer = d3.select("#o2vConverterContainer"); + if ( !o2vConverterContainer.node() ) { + var bp_container = d3.select("#bulletPoint_container"); + var div = bp_container.append("div"); + o2vConverterContainer = div.append("ul"); + o2vConverterContainer.attr("id", "o2vConverterContainer"); + o2vConverterContainer.style("margin-left", "-25px"); + } + // clear o2vConverterContainer; + var htmlCollection = o2vConverterContainer.node().children; + var numEntries = htmlCollection.length; + for ( var i = 0; i < numEntries; i++ ) { + htmlCollection[0].remove(); + } + // split tokens provided by o2v messages + var tokens = message.split("* "); + var liForToken; + for ( var t = 0; t < tokens.length; t++ ) { + var tokenMessage = tokens[t]; + // create li for tokens; + if ( tokenMessage.length > 0 ) { + liForToken = o2vConverterContainer.append("li"); + liForToken.attr("type", "disc"); + liForToken.node().innerHTML = tokenMessage.replace(/\n/g, "
    "); + } + } + if ( liForToken ) + liForToken.node().innerHTML += "
    "; + + loadingModule.scrollDownDetails(); + } + + ontologyMenu.setLoadingStatusInfo = function ( message ){ + // forward call + setLoadingStatusInfo(message); + }; + + function getLoadingStatusOnceCallBacked( callback, parameter ){ + d3.xhr("loadingStatus?sessionId=" + conversion_sessionId, "application/text", function ( error, request ){ + if ( error ) { + console.log("ontologyMenu getLoadingStatusOnceCallBacked throws error"); + console.log("---------Error -----------"); + console.log(error); + console.log("---------Request -----------"); + console.log(request); + } + setLoadingStatusInfo(request.responseText); + callback(parameter); + }); + } + + function getLoadingStatusTimeLooped(){ + d3.xhr("loadingStatus?sessionId=" + conversion_sessionId, "application/text", function ( error, request ){ + if ( error ) { + console.log("ontologyMenu getLoadingStatusTimeLooped throws error"); + console.log("---------Error -----------"); + console.log(error); + console.log("---------Request -----------"); + console.log(request); + } + if ( stopTimer === false ) { + setLoadingStatusInfo(request.responseText); + timedLoadingStatusLogger(); + } + }); + } + + function timedLoadingStatusLogger(){ + clearTimeout(loadingStatusTimer); + if ( stopTimer === false ) { + loadingStatusTimer = setTimeout(function (){ + getLoadingStatusTimeLooped(); + }, 1000); + } + } + + function callbackUpdateLoadingMessage( msg ){ + d3.xhr("loadingStatus", "application/text", function ( error, request ){ + if ( request !== undefined ) { + setLoadingStatusInfo(request.responseText + "
    " + msg); + } else { + append_message(msg); + } + }); + } + + ontologyMenu.setConversionID = function ( id ){ + conversion_sessionId = id; + }; + + ontologyMenu.callbackLoad_Ontology_FromIRI = function ( parameter ){ + var relativePath = parameter[0]; + var ontoName = parameter[1]; + var localThreadId = parameter[2]; + stopTimer = false; + timedLoadingStatusLogger(); + d3.xhr(relativePath, "application/json", function ( error, request ){ + var loadingSuccessful = !error; + // check if error occurred or responseText is empty + if ( (error !== null && error.status === 500) || (request && request.responseText.length === 0) ) { + clearTimeout(loadingStatusTimer); + stopTimer = true; + getLoadingStatusOnceCallBacked(callbackFromIRI_URL_ERROR, [error, request, localThreadId]); + } + var jsonText; + if ( loadingSuccessful ) { + clearTimeout(loadingStatusTimer); + stopTimer = true; + jsonText = request.responseText; + getLoadingStatusOnceCallBacked(callbackFromIRI_Success, [jsonText, ontoName, localThreadId]); + } + }); + }; + + + ontologyMenu.callbackLoad_Ontology_From_DirectInput = function ( text, parameter ){ + var input = text; + var sessionId = parameter[1]; + stopTimer = false; + timedLoadingStatusLogger(); + + var formData = new FormData(); + formData.append("input", input); + formData.append("sessionId", sessionId); + var xhr = new XMLHttpRequest(); + + xhr.open("POST", "directInput", true); + xhr.onload = function (){ + clearTimeout(loadingStatusTimer); + stopTimer = true; + getLoadingStatusOnceCallBacked(callbackForConvert, [xhr, input, sessionId]); + }; + timedLoadingStatusLogger(); + xhr.send(formData); + + }; + function callbackFromIRI_Success( parameter ){ + var local_conversionId = parameter[2]; + if ( local_conversionId !== conversion_sessionId ) { + console.log("The conversion process for file:" + parameter[1] + " has been canceled!"); + ontologyMenu.conversionFinished(local_conversionId); + return; + } + loadingModule.loadFromOWL2VOWL(parameter[0], parameter[1]); + ontologyMenu.conversionFinished(); + + } + + function callbackFromDirectInput_Success( parameter ){ + var local_conversionId = parameter[1]; + if ( local_conversionId !== conversion_sessionId ) { + console.log("The conversion process for file:" + parameter[1] + " has been canceled!"); + ontologyMenu.conversionFinished(local_conversionId); + return; + } + loadingModule.loadFromOWL2VOWL(parameter[0], "DirectInputConversionID" + local_conversionId); + ontologyMenu.conversionFinished(); + + } + + ontologyMenu.getConversionId = function (){ + return conversion_sessionId; + }; + + ontologyMenu.callbackLoad_JSON_FromURL = function ( parameter ){ + var relativePath = parameter[0]; + var ontoName = parameter[1]; + var local_conversionId = parameter[2]; + stopTimer = false; + timedLoadingStatusLogger(); + d3.xhr(relativePath, "application/json", function ( error, request ){ + var loadingSuccessful = !error; + // check if error occurred or responseText is empty + if ( (error !== null && error.status === 500) || (request && request.responseText.length === 0) ) { + clearTimeout(loadingStatusTimer); + stopTimer = true; + loadingSuccessful = false; + console.log(request); + console.log(request.responseText.length); + getLoadingStatusOnceCallBacked(callbackFromJSON_URL_ERROR, [error, request, local_conversionId]); + } + if ( loadingSuccessful ) { + clearTimeout(loadingStatusTimer); + stopTimer = true; + var jsonText = request.responseText; + getLoadingStatusOnceCallBacked(callbackFromJSON_Success, [jsonText, ontoName, local_conversionId]); + } + }); + }; + + function callbackFromJSON_Success( parameter ){ + var local_conversionId = parameter[2]; + if ( local_conversionId !== conversion_sessionId ) { + console.log("The conversion process for file:" + parameter[1] + " has been canceled!"); + return; + } + loadingModule.loadFromOWL2VOWL(parameter[0], parameter[1]); + } + + function callbackFromJSON_URL_ERROR( parameter ){ + var error = parameter[0]; + var request = parameter[1]; + var local_conversionId = parameter[2]; + if ( local_conversionId !== conversion_sessionId ) { + console.log("This thread has been canceled!!"); + ontologyMenu.conversionFinished(local_conversionId); + return; + } + callbackUpdateLoadingMessage("
    Failed to convert the file. " + + " Ontology could not be loaded.
    Is it a valid OWL ontology? Please check with OWL Validator"); + + if ( error !== null && error.status === 500 ) { + append_message("Could not find ontology at the URL"); + } + if ( request && request.responseText.length === 0 ) { + append_message("Received empty graph"); + } + graph.handleOnLoadingError(); + ontologyMenu.conversionFinished(); + } + + + function callbackFromIRI_URL_ERROR( parameter ){ + var error = parameter[0]; + var request = parameter[1]; + var local_conversionId = parameter[2]; + if ( local_conversionId !== conversion_sessionId ) { + console.log("This thread has been canceled!!"); + ontologyMenu.conversionFinished(local_conversionId); + return; + } + callbackUpdateLoadingMessage("
    Failed to convert the file. " + + " Ontology could not be loaded.
    Is it a valid OWL ontology? Please check with OWL Validator"); + + if ( error !== null && error.status === 500 ) { + append_message("Could not find ontology at the URL"); + } + if ( request && request.responseText.length === 0 ) { + append_message("Received empty graph"); + } + graph.handleOnLoadingError(); + ontologyMenu.conversionFinished(); + } + + function callbackFromDirectInput_ERROR( parameter ){ + + var error = parameter[0]; + var request = parameter[1]; + var local_conversionId = parameter[2]; + if ( local_conversionId !== conversion_sessionId ) { + console.log("The loading process for direct input has been canceled!"); + return; + } + // callbackUpdateLoadingMessage("
    Failed to convert the file. "+ + // "Ontology could not be loaded.
    Is it a valid OWL ontology? Please check with OWL Validator"); + if ( error !== null && error.status === 500 ) { + append_message("Could not convert direct input"); + } + if ( request && request.responseText.length === 0 ) { + append_message("Received empty graph"); + } + + graph.handleOnLoadingError(); + ontologyMenu.conversionFinished(); + } + + ontologyMenu.callbackLoadFromOntology = function ( selectedFile, filename, local_threadId ){ + callbackLoadFromOntology(selectedFile, filename, local_threadId); + }; + + function callbackLoadFromOntology( selectedFile, filename, local_threadId ){ + stopTimer = false; + timedLoadingStatusLogger(); + + var formData = new FormData(); + formData.append("ontology", selectedFile); + formData.append("sessionId", local_threadId); + var xhr = new XMLHttpRequest(); + + xhr.open("POST", "convert", true); + xhr.onload = function (){ + clearTimeout(loadingStatusTimer); + stopTimer = true; + console.log(xhr); + getLoadingStatusOnceCallBacked(callbackForConvert, [xhr, filename, local_threadId]); + }; + timedLoadingStatusLogger(); + xhr.send(formData); + } + + function callbackForConvert( parameter ){ + var xhr = parameter[0]; + var filename = parameter[1]; + var local_threadId = parameter[2]; + if ( local_threadId !== conversion_sessionId ) { + console.log("The conversion process for file:" + filename + " has been canceled!"); + ontologyMenu.conversionFinished(local_threadId); + return; + } + if ( xhr.status === 200 ) { + loadingModule.loadFromOWL2VOWL(xhr.responseText, filename); + ontologyMenu.conversionFinished(); + } else { + var uglyJson=xhr.responseText; + var jsonResut=JSON.parse(uglyJson); + var niceJSON=JSON.stringify(jsonResut, 'null', ' '); + niceJSON= niceJSON.replace(new RegExp('\r?\n','g'), '
    '); + callbackUpdateLoadingMessage("Failed to convert the file. " + + "
    Server answer:
    "+ + "
    "+niceJSON+ "
    "+ + "Ontology could not be loaded.
    Is it a valid OWL ontology? Please check with OWL Validator"); + + graph.handleOnLoadingError(); + ontologyMenu.conversionFinished(); + } + } + + ontologyMenu.conversionFinished = function ( id ){ + var local_id = conversion_sessionId; + if ( id ) { + local_id = id; + } + d3.xhr("conversionDone?sessionId=" + local_id, "application/text", function ( error, request ){ + if ( error ) { + console.log("ontologyMenu conversionFinished throws error"); + console.log("---------Error -----------"); + console.log(error); + console.log("---------Request -----------"); + console.log(request); + } + }); + }; + + function keepOntologySelectionOpenShortly(){ + // Events in the menu should not be considered + var ontologySelection = d3.select("#select .toolTipMenu"); + ontologySelection.on("click", function (){ + d3.event.stopPropagation(); + }).on("keydown", function (){ + d3.event.stopPropagation(); + }); + + ontologySelection.style("display", "block"); + + function disableKeepingOpen(){ + ontologySelection.style("display", undefined); + + clearTimeout(ontologyMenuTimeout); + d3.select(window).on("click", undefined).on("keydown", undefined); + ontologySelection.on("mouseover", undefined); + } + + // Clear the timeout to handle fast calls of this function + clearTimeout(ontologyMenuTimeout); + ontologyMenuTimeout = setTimeout(function (){ + disableKeepingOpen(); + }, 3000); + + // Disable forced open selection on interaction + d3.select(window).on("click", function (){ + disableKeepingOpen(); + }).on("keydown", function (){ + disableKeepingOpen(); + }); + + ontologySelection.on("mouseover", function (){ + disableKeepingOpen(); + }); + } + + ontologyMenu.showLoadingStatus = function ( visible ){ + if ( visible === true ) { + displayLoadingIndicators(); + } + else { + hideLoadingInformations(); + } + }; + + function displayLoadingIndicators(){ + d3.select("#layoutLoadingProgressBarContainer").classed("hidden", false); + loadingInfo.classed("hidden", false); + loadingProgress.classed("hidden", false); + } + + function hideLoadingInformations(){ + loadingInfo.classed("hidden", true); + } + + return ontologyMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 330: +/***/ (function(module, exports, __webpack_require__) { + + var toString = __webpack_require__(219), + unescapeHtmlChar = __webpack_require__(331); + + /** Used to match HTML entities and HTML characters. */ + var reEscapedHtml = /&(?:amp|lt|gt|quot|#39);/g, + reHasEscapedHtml = RegExp(reEscapedHtml.source); + + /** + * The inverse of `_.escape`; this method converts the HTML entities + * `&`, `<`, `>`, `"`, and `'` in `string` to + * their corresponding characters. + * + * **Note:** No other HTML entities are unescaped. To unescape additional + * HTML entities use a third-party library like [_he_](https://mths.be/he). + * + * @static + * @memberOf _ + * @since 0.6.0 + * @category String + * @param {string} [string=''] The string to unescape. + * @returns {string} Returns the unescaped string. + * @example + * + * _.unescape('fred, barney, & pebbles'); + * // => 'fred, barney, & pebbles' + */ + function unescape(string) { + string = toString(string); + return (string && reHasEscapedHtml.test(string)) + ? string.replace(reEscapedHtml, unescapeHtmlChar) + : string; + } + + module.exports = unescape; + + +/***/ }), + +/***/ 331: +/***/ (function(module, exports, __webpack_require__) { + + var basePropertyOf = __webpack_require__(332); + + /** Used to map HTML entities to characters. */ + var htmlUnescapes = { + '&': '&', + '<': '<', + '>': '>', + '"': '"', + ''': "'" + }; + + /** + * Used by `_.unescape` to convert HTML entities to characters. + * + * @private + * @param {string} chr The matched character to unescape. + * @returns {string} Returns the unescaped character. + */ + var unescapeHtmlChar = basePropertyOf(htmlUnescapes); + + module.exports = unescapeHtmlChar; + + +/***/ }), + +/***/ 332: +/***/ (function(module, exports) { + + /** + * The base implementation of `_.propertyOf` without support for deep paths. + * + * @private + * @param {Object} object The object to query. + * @returns {Function} Returns the new accessor function. + */ + function basePropertyOf(object) { + return function(key) { + return object == null ? undefined : object[key]; + }; + } + + module.exports = basePropertyOf; + + +/***/ }), + +/***/ 333: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for the pause and resume button. + * + * @param graph the associated webvowl graph + * @returns {{}} + */ + module.exports = function ( graph ){ + + var pauseMenu = {}, + pauseButton; + + + /** + * Adds the pause button to the website. + */ + pauseMenu.setup = function (){ + var menuEntry = d3.select("#pauseOption"); + menuEntry.on("mouseover", function (){ + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + }); + pauseButton = d3.select("#pause-button") + .datum({ paused: false }) + .on("click", function ( d ){ + graph.paused(!d.paused); + d.paused = !d.paused; + updatePauseButton(); + pauseButton.classed("highlighted", d.paused); + }); + // Set these properties the first time manually + updatePauseButton(); + }; + + pauseMenu.setPauseValue = function ( value ){ + pauseButton.datum().paused = value; + graph.paused(value); + pauseButton.classed("highlighted", value); + updatePauseButton(); + }; + + function updatePauseButton(){ + updatePauseButtonClass(); + updatePauseButtonText(); + } + + function updatePauseButtonClass(){ + pauseButton.classed("paused", function ( d ){ + return d.paused; + }); + } + + function updatePauseButtonText(){ + if ( pauseButton.datum().paused ) { + pauseButton.text("Resume"); + } else { + pauseButton.text("Pause"); + } + } + + pauseMenu.reset = function (){ + // resuming + pauseMenu.setPauseValue(false); + }; + + + return pauseMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 334: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for the reset button. + * + * @param graph the associated webvowl graph + * @returns {{}} + */ + module.exports = function ( graph ){ + + var resetMenu = {}, + options = graph.graphOptions(), + resettableModules, + untouchedOptions = webvowl.options(); + + + /** + * Adds the reset button to the website. + * @param _resettableModules modules that can be resetted + */ + resetMenu.setup = function ( _resettableModules ){ + resettableModules = _resettableModules; + d3.select("#reset-button").on("click", resetGraph); + var menuEntry = d3.select("#resetOption"); + menuEntry.on("mouseover", function (){ + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + }); + }; + + function resetGraph(){ + graph.resetSearchHighlight(); + graph.options().searchMenu().clearText(); + options.classDistance(untouchedOptions.classDistance()); + options.datatypeDistance(untouchedOptions.datatypeDistance()); + options.charge(untouchedOptions.charge()); + options.gravity(untouchedOptions.gravity()); + options.linkStrength(untouchedOptions.linkStrength()); + graph.reset(); + + resettableModules.forEach(function ( module ){ + module.reset(); + }); + + graph.updateStyle(); + } + + + return resetMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 335: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the search "engine" + * + * @param graph the associated webvowl graph + * @returns {{}} + */ + module.exports = function ( graph ){ + var searchMenu = {}, + dictionary = [], + entryNames = [], + searchLineEdit, + mergedStringsList, + mergedIdList, + maxEntries = 6, + dictionaryUpdateRequired = true, + labelDictionary, + inputText, + viewStatusOfSearchEntries = false; + + var results = []; + var resultID = []; + var c_locate = d3.select("#locateSearchResult"); + var c_search = d3.select("#c_search"); + var m_search = d3.select("#m_search"); // << dropdown container; + + + String.prototype.beginsWith = function ( string ){ + return (this.indexOf(string) === 0); + }; + + searchMenu.requestDictionaryUpdate = function (){ + dictionaryUpdateRequired = true; + // clear possible pre searched entries + var htmlCollection = m_search.node().children; + var numEntries = htmlCollection.length; + + for ( var i = 0; i < numEntries; i++ ) + htmlCollection[0].remove(); + searchLineEdit.node().value = ""; + }; + + + function updateSearchDictionary(){ + labelDictionary = graph.getUpdateDictionary(); + dictionaryUpdateRequired = false; + dictionary = []; + entryNames = []; + var idList = []; + var stringList = []; + + var i; + for ( i = 0; i < labelDictionary.length; i++ ) { + var lEntry = labelDictionary[i].labelForCurrentLanguage(); + idList.push(labelDictionary[i].id()); + stringList.push(lEntry); + // add all equivalents to the search space; + if ( labelDictionary[i].equivalents && labelDictionary[i].equivalents().length > 0 ) { + var eqs = labelDictionary[i].equivalentsString(); + var eqsLabels = eqs.split(", "); + for ( var e = 0; e < eqsLabels.length; e++ ) { + idList.push(labelDictionary[i].id()); + stringList.push(eqsLabels[e]); + } + } + } + + mergedStringsList = []; + mergedIdList = []; + var indexInStringList = -1; + var currentString; + var currentObjectId; + + for ( i = 0; i < stringList.length; i++ ) { + if ( i === 0 ) { + // just add the elements + mergedStringsList.push(stringList[i]); + mergedIdList.push([]); + mergedIdList[0].push(idList[i]); + continue; + } + else { + currentString = stringList[i]; + currentObjectId = idList[i]; + indexInStringList = mergedStringsList.indexOf(currentString); + } + if ( indexInStringList === -1 ) { + mergedStringsList.push(stringList[i]); + mergedIdList.push([]); + var lastEntry = mergedIdList.length; + mergedIdList[lastEntry - 1].push(currentObjectId); + } else { + mergedIdList[indexInStringList].push(currentObjectId); + } + } + + for ( i = 0; i < mergedStringsList.length; i++ ) { + var aString = mergedStringsList[i]; + var correspondingIdList = mergedIdList[i]; + var idListResult = "[ "; + for ( var j = 0; j < correspondingIdList.length; j++ ) { + idListResult = idListResult + correspondingIdList[j].toString(); + idListResult = idListResult + ", "; + } + idListResult = idListResult.substring(0, idListResult.length - 2); + idListResult = idListResult + " ]"; + + dictionary.push(aString); + entryNames.push(aString); + } + } + + searchMenu.setup = function (){ + // clear dictionary; + dictionary = []; + searchLineEdit = d3.select("#search-input-text"); + searchLineEdit.on("input", userInput); + searchLineEdit.on("keydown", userNavigation); + searchLineEdit.on("click", toggleSearchEntryView); + searchLineEdit.on("mouseover", hoverSearchEntryView); + + c_locate.on("click", function (){ + graph.locateSearchResult(); + }); + + c_locate.on("mouseover", function (){ + searchMenu.hideSearchEntries(); + }); + + }; + + function hoverSearchEntryView(){ + updateSelectionStatusFlags(); + searchMenu.showSearchEntries(); + } + + function toggleSearchEntryView(){ + if ( viewStatusOfSearchEntries ) { + searchMenu.hideSearchEntries(); + } else { + searchMenu.showSearchEntries(); + } + } + + searchMenu.hideSearchEntries = function (){ + m_search.style("display", "none"); + viewStatusOfSearchEntries = false; + }; + + searchMenu.showSearchEntries = function (){ + m_search.style("display", "block"); + viewStatusOfSearchEntries = true; + }; + + function ValidURL( str ){ + var urlregex = /^(https?|ftp):\/\/([a-zA-Z0-9.-]+(:[a-zA-Z0-9.&%$-]+)*@)*((25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9][0-9]?)(\.(25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9]?[0-9])){3}|([a-zA-Z0-9-]+\.)*[a-zA-Z0-9-]+\.(com|edu|gov|int|mil|net|org|biz|arpa|info|name|pro|aero|coop|museum|[a-zA-Z]{2}))(:[0-9]+)*(\/($|[a-zA-Z0-9.,?'\\+&%$#=~_-]+))*$/; + return urlregex.test(str); + + } + + + function updateSelectionStatusFlags(){ + if ( searchLineEdit.node().value.length === 0 ) { + createSearchEntries(); + return; + } + handleAutoCompletion(); + } + + function userNavigation(){ + if ( dictionaryUpdateRequired ) { + updateSearchDictionary(); + } + + var htmlCollection = m_search.node().children; + var numEntries = htmlCollection.length; + + + var move = 0; + var i; + var selectedEntry = -1; + for ( i = 0; i < numEntries; i++ ) { + var atr = htmlCollection[i].getAttribute('class'); + if ( atr === "dbEntrySelected" ) { + selectedEntry = i; + } + } + if ( d3.event.keyCode === 13 ) { + if ( selectedEntry >= 0 && selectedEntry < numEntries ) { + // simulate onClick event + htmlCollection[selectedEntry].onclick(); + searchMenu.hideSearchEntries(); + } + else if ( numEntries === 0 ) { + inputText = searchLineEdit.node().value; + // check if input text ends or begins with with space + // remove first spaces + var clearedText = inputText.replace(/%20/g, " "); + while ( clearedText.beginsWith(" ") ) { + clearedText = clearedText.substr(1, clearedText.length); + } + // remove ending spaces + while ( clearedText.endsWith(" ") ) { + clearedText = clearedText.substr(0, clearedText.length - 1); + } + var iri = clearedText.replace(/ /g, "%20"); + + var valid = ValidURL(iri); + // validate url: + if ( valid ) { + var ontM = graph.options().ontologyMenu(); + ontM.setIriText(iri); + searchLineEdit.node().value = ""; + } + else { + console.log(iri + " is not a valid URL!"); + } + } + } + if ( d3.event.keyCode === 38 ) { + move = -1; + searchMenu.showSearchEntries(); + } + if ( d3.event.keyCode === 40 ) { + move = +1; + searchMenu.showSearchEntries(); + } + + var newSelection = selectedEntry + move; + if ( newSelection !== selectedEntry ) { + + if ( newSelection < 0 && selectedEntry <= 0 ) { + htmlCollection[0].setAttribute('class', "dbEntrySelected"); + } + + if ( newSelection >= numEntries ) { + htmlCollection[selectedEntry].setAttribute('class', "dbEntrySelected"); + } + if ( newSelection >= 0 && newSelection < numEntries ) { + htmlCollection[newSelection].setAttribute('class', "dbEntrySelected"); + if ( selectedEntry >= 0 ) + htmlCollection[selectedEntry].setAttribute('class', "dbEntry"); + } + } + } + + searchMenu.getSearchString = function (){ + return searchLineEdit.node().value; + }; + + + function clearSearchEntries(){ + var htmlCollection = m_search.node().children; + var numEntries = htmlCollection.length; + for ( var i = 0; i < numEntries; i++ ) { + htmlCollection[0].remove(); + } + results = []; + resultID = []; + + } + + function createSearchEntries(){ + inputText = searchLineEdit.node().value; + var i; + var lc_text = inputText.toLowerCase(); + var token; + + for ( i = 0; i < dictionary.length; i++ ) { + var tokenElement = dictionary[i]; + if ( tokenElement === undefined ) { + //@WORKAROUND : nodes with undefined labels are skipped + //@FIX: these nodes are now not added to the dictionary + continue; + } + token = dictionary[i].toLowerCase(); + if ( token.indexOf(lc_text) > -1 ) { + results.push(dictionary[i]); + resultID.push(i); + } + } + } + + function measureTextWidth( text, textStyle ){ + // Set a default value + if ( !textStyle ) { + textStyle = "text"; + } + var d = d3.select("body") + .append("div") + .attr("class", textStyle) + .attr("id", "width-test") // tag this element to identify it + .attr("style", "position:absolute; float:left; white-space:nowrap; visibility:hidden;") + .text(text), + w = document.getElementById("width-test").offsetWidth; + d.remove(); + return w; + } + + function cropText( input ){ + var maxWidth = 250; + var textStyle = "dbEntry"; + var truncatedText = input; + var textWidth; + var ratio; + var newTruncatedTextLength; + while ( true ) { + textWidth = measureTextWidth(truncatedText, textStyle); + if ( textWidth <= maxWidth ) { + break; + } + + ratio = textWidth / maxWidth; + newTruncatedTextLength = Math.floor(truncatedText.length / ratio); + + // detect if nothing changes + if ( truncatedText.length === newTruncatedTextLength ) { + break; + } + + truncatedText = truncatedText.substring(0, newTruncatedTextLength); + } + + if ( input.length > truncatedText.length ) { + return input.substring(0, truncatedText.length - 6); + } + return input; + } + + function createDropDownElements(){ + var numEntries; + var copyRes = results; + var i; + var token; + var newResults = []; + var newResultsIds = []; + + var lc_text = searchLineEdit.node().value.toLowerCase(); + // set the number of shown results to be maxEntries or less; + numEntries = results.length; + if ( numEntries > maxEntries ) + numEntries = maxEntries; + + + for ( i = 0; i < numEntries; i++ ) { + // search for the best entry + var indexElement = 1000000; + var lengthElement = 1000000; + var bestElement = -1; + for ( var j = 0; j < copyRes.length; j++ ) { + token = copyRes[j].toLowerCase(); + var tIe = token.indexOf(lc_text); + var tLe = token.length; + if ( tIe > -1 && tIe <= indexElement && tLe <= lengthElement ) { + bestElement = j; + indexElement = tIe; + lengthElement = tLe; + } + } + newResults.push(copyRes[bestElement]); + newResultsIds.push(resultID[bestElement]); + copyRes[bestElement] = ""; + } + + // add the results to the entry menu + //****************************************** + numEntries = results.length; + if ( numEntries > maxEntries ) + numEntries = maxEntries; + + var filteredOutElements = 0; + for ( i = 0; i < numEntries; i++ ) { + //add results to the dropdown menu + var testEntry = document.createElement('li'); + testEntry.setAttribute('elementID', newResultsIds[i]); + testEntry.onclick = handleClick(newResultsIds[i]); + testEntry.setAttribute('class', "dbEntry"); + + var entries = mergedIdList[newResultsIds[i]]; + var eLen = entries.length; + + var croppedText = cropText(newResults[i]); + + var el0 = entries[0]; + var allSame = true; + var nodeMap = graph.getNodeMapForSearch(); + var visible = eLen; + if ( eLen > 1 ) { + for ( var q = 0; q < eLen; q++ ) { + if ( nodeMap[entries[q]] === undefined ) { + visible--; + } + } + } + + for ( var a = 0; a < eLen; a++ ) { + if ( el0 !== entries[a] ) { + allSame = false; + } + } + if ( croppedText !== newResults[i] ) { + // append ...(#numElements) if needed + if ( eLen > 1 && allSame === false ) { + if ( eLen !== visible ) + croppedText += "... (" + visible + "/" + eLen + ")"; + } + else { + croppedText += "..."; + } + testEntry.title = newResults[i]; + } + else { + if ( eLen > 1 && allSame === false ) { + if ( eLen !== visible ) + croppedText += " (" + visible + "/" + eLen + ")"; + else + croppedText += " (" + eLen + ")"; + } + } + + var searchEntryNode = d3.select(testEntry); + if ( eLen === 1 || allSame === true ) { + if ( nodeMap[entries[0]] === undefined ) { + searchEntryNode.style("color", "#979797"); + testEntry.title = newResults[i] + "\nElement is filtered out."; + testEntry.onclick = function (){ + }; + d3.select(testEntry).style("cursor", "default"); + filteredOutElements++; + } + } else { + if ( visible < 1 ) { + searchEntryNode.style("color", "#979797"); + testEntry.onclick = function (){ + }; + testEntry.title = newResults[i] + "\nAll elements are filtered out."; + d3.select(testEntry).style("cursor", "default"); + filteredOutElements++; + } else { + searchEntryNode.style("color", ""); + } + if ( visible < eLen && visible > 1 ) { + testEntry.title = newResults[i] + "\n" + visible + "/" + eLen + " elements are visible."; + } + } + searchEntryNode.node().innerHTML = croppedText; + m_search.node().appendChild(testEntry); + } + } + + + function handleAutoCompletion(){ + /** pre condition: autoCompletion has already a valid text**/ + clearSearchEntries(); + createSearchEntries(); + createDropDownElements(); + } + + function userInput(){ + c_locate.classed("highlighted", false); + c_locate.node().title = "Nothing to locate"; + + if ( dictionaryUpdateRequired ) { + updateSearchDictionary(); + } + graph.resetSearchHighlight(); + + if ( dictionary.length === 0 ) { + console.log("dictionary is empty"); + return; + } + inputText = searchLineEdit.node().value; + + clearSearchEntries(); + if ( inputText.length !== 0 ) { + createSearchEntries(); + createDropDownElements(); + } + + searchMenu.showSearchEntries(); + } + + function handleClick( elementId ){ + + return function (){ + var id = elementId; + var correspondingIds = mergedIdList[id]; + + // autoComplete the text for the user + var autoComStr = entryNames[id]; + searchLineEdit.node().value = autoComStr; + + graph.resetSearchHighlight(); + graph.highLightNodes(correspondingIds); + c_locate.node().title = "Locate search term"; + if ( autoComStr !== inputText ) { + handleAutoCompletion(); + } + searchMenu.hideSearchEntries(); + }; + } + + searchMenu.clearText = function (){ + searchLineEdit.node().value = ""; + c_locate.classed("highlighted", false); + c_locate.node().title = "Nothing to locate"; + var htmlCollection = m_search.node().children; + var numEntries = htmlCollection.length; + for ( var i = 0; i < numEntries; i++ ) { + htmlCollection[0].remove(); + } + }; + + return searchMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 336: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the navigation "engine" + * + * @param graph the associated webvowl graph + * @returns {{}} + */ + module.exports = function ( graph ){ + var navigationMenu = {}, + scrollContainer = d3.select("#menuElementContainer").node(), + menuContainer = d3.select("#menuContainer").node(), + leftButton = d3.select("#scrollLeftButton"), + rightButton = d3.select("#scrollRightButton"), + scrolLeftValue, + scrollMax, + currentlyVisibleMenu, + currentlyHoveredEntry, + touchedElement = false, + t_scrollLeft, + t_scrollRight, + c_select = [], + m_select = []; + + + function clearAllTimers(){ + cancelAnimationFrame(t_scrollLeft); + cancelAnimationFrame(t_scrollRight); + } + + function timed_scrollRight(){ + scrolLeftValue += 5; + scrollContainer.scrollLeft = scrolLeftValue; + navigationMenu.updateScrollButtonVisibility(); + if ( scrolLeftValue >= scrollMax ) { + clearAllTimers(); + return; + } + t_scrollRight = requestAnimationFrame(timed_scrollRight); + + } + + function timed_scrollLeft(){ + scrolLeftValue -= 5; + scrollContainer.scrollLeft = scrolLeftValue; + navigationMenu.updateScrollButtonVisibility(); + if ( scrolLeftValue <= 0 ) { + clearAllTimers(); + return; + } + t_scrollRight = requestAnimationFrame(timed_scrollLeft); + } + + // collect all menu entries and stuff; + function setupControlsAndMenus(){ + // HEURISTIC : to match the menus and their controllers we remove the first 2 letters and match + c_select = []; + m_select = []; + + var c_temp = []; + var m_temp = []; + var i; + var controlElements = scrollContainer.children; + var numEntries = controlElements.length; + + for ( i = 0; i < numEntries; i++ ) { + c_temp.push(controlElements[i].id.slice(2)); + } + + var menuElements = menuContainer.children; + numEntries = menuElements.length; + for ( i = 0; i < numEntries; i++ ) { + m_temp.push(menuElements[i].id.slice(2)); + } + + numEntries = controlElements.length; + for ( i = 0; i < numEntries; i++ ) { + c_select[i] = "c_" + c_temp[i]; + if ( m_temp.indexOf(c_temp[i]) > -1 ) { + m_select[i] = "m_" + c_temp[i]; + } else { + m_select[i] = undefined; + } + // create custom behavior for click, touch, and hover + d3.select("#" + c_select[i]).on("mouseover", menuElementOnHovered); + d3.select("#" + c_select[i]).on("mouseout", menuElementOutHovered); + + d3.select("#" + c_select[i]).on("click", menuElementClicked); + d3.select("#" + c_select[i]).on("touchstart", menuElementTouched); + + } + + // connect to mouseWheel + d3.select("#menuElementContainer").on("wheel", function (){ + var wheelEvent = d3.event; + var offset; + if ( wheelEvent.deltaY < 0 ) offset = 20; + if ( wheelEvent.deltaY > 0 ) offset = -20; + scrollContainer.scrollLeft += offset; + navigationMenu.hideAllMenus(); + navigationMenu.updateScrollButtonVisibility(); + }); + + // connect scrollIndicator Buttons; + d3.select("#scrollRightButton").on("mousedown", function (){ + scrolLeftValue = scrollContainer.scrollLeft; + navigationMenu.hideAllMenus(); + t_scrollRight = requestAnimationFrame(timed_scrollRight); + + }).on("touchstart", function (){ + scrolLeftValue = scrollContainer.scrollLeft; + navigationMenu.hideAllMenus(); + t_scrollRight = requestAnimationFrame(timed_scrollRight); + }).on("mouseup", clearAllTimers) + .on("touchend", clearAllTimers) + .on("touchcancel", clearAllTimers); + + d3.select("#scrollLeftButton").on("mousedown", function (){ + scrolLeftValue = scrollContainer.scrollLeft; + navigationMenu.hideAllMenus(); + t_scrollLeft = requestAnimationFrame(timed_scrollLeft); + }).on("touchstart", function (){ + scrolLeftValue = scrollContainer.scrollLeft; + navigationMenu.hideAllMenus(); + t_scrollLeft = requestAnimationFrame(timed_scrollLeft); + }).on("mouseup", clearAllTimers) + .on("touchend", clearAllTimers) + .on("touchcancel", clearAllTimers); + + // connect the scroll functionality; + d3.select("#menuElementContainer").on("scroll", function (){ + navigationMenu.updateScrollButtonVisibility(); + navigationMenu.hideAllMenus(); + }); + } + + function menuElementOnHovered(){ + navigationMenu.hideAllMenus(); + if ( touchedElement ) { + return; + } + showSingleMenu(this.id); + } + + function menuElementOutHovered(){ + hoveroutedControMenu(this.id); + } + + function menuElementClicked(){ + var m_element = m_select[c_select.indexOf(this.id)]; + if ( m_element ) { + var menuElement = d3.select("#" + m_element); + if ( menuElement ) { + if ( menuElement.style("display") === "block" ) { + menuElement.style("display", "none");// hide it + } else { + showSingleMenu(this.id); + } + } + } + } + + function menuElementTouched(){ + // it sets a flag that we have touched it, + // since d3. propagates the event for touch as hover and then click, we block the hover event + touchedElement = true; + } + + + function hoveroutedControMenu( controllerID ){ + currentlyHoveredEntry = d3.select("#" + controllerID); + if ( controllerID !== "c_search" ) { + d3.select("#" + controllerID).select("path").style("stroke-width", "0"); + d3.select("#" + controllerID).select("path").style("fill", "#fff"); + } + + } + + function showSingleMenu( controllerID ){ + currentlyHoveredEntry = d3.select("#" + controllerID).node(); + // get the corresponding menu element for this controller + var m_element = m_select[c_select.indexOf(controllerID)]; + if ( m_element ) { + if ( controllerID !== "c_search" ) { + + d3.select("#" + controllerID).select("path").style("stroke-width", "0"); + d3.select("#" + controllerID).select("path").style("fill", "#bdc3c7"); + } + // show it if we have a menu + currentlyVisibleMenu = d3.select("#" + m_element); + currentlyVisibleMenu.style("display", "block"); + if ( m_element === "m_export" ) + graph.options().exportMenu().exportAsUrl(); + updateMenuPosition(); + } + } + + function updateMenuPosition(){ + if ( currentlyHoveredEntry ) { + var leftOffset = currentlyHoveredEntry.offsetLeft; + var scrollOffset = scrollContainer.scrollLeft; + var totalOffset = leftOffset - scrollOffset; + var finalOffset = Math.max(0, totalOffset); + var fullContainer_width = scrollContainer.getBoundingClientRect().width; + var elementWidth = currentlyVisibleMenu.node().getBoundingClientRect().width; + // make priority > first check if we are right + if ( finalOffset + elementWidth > fullContainer_width ) { + finalOffset = fullContainer_width - elementWidth; + } + // fix priority; + finalOffset = Math.max(0, finalOffset); + currentlyVisibleMenu.style("left", finalOffset + "px"); + + // // check if outside the viewport + // var menuWidth=currentlyHoveredEntry.getBoundingClientRect().width; + // var bt_width=36; + // if (totalOffset+menuWidthfullContainer_width){ + // navigationMenu.hideAllMenus(); + // currentlyHoveredEntry=undefined; + // } + } + } + + navigationMenu.hideAllMenus = function (){ + d3.selectAll(".toolTipMenu").style("display", "none"); // hiding all menus + }; + + navigationMenu.updateScrollButtonVisibility = function (){ + scrollMax = scrollContainer.scrollWidth - scrollContainer.clientWidth - 2; + if ( scrollContainer.scrollLeft === 0 ) { + leftButton.classed("hidden", true); + } else { + leftButton.classed("hidden", false); + } + + if ( scrollContainer.scrollLeft > scrollMax ) { + rightButton.classed("hidden", true); + } else { + rightButton.classed("hidden", false); + } + + }; + + navigationMenu.setup = function (){ + setupControlsAndMenus(); + // make sure that the menu elements follow their controller and also their restrictions + // some hovering behavior -- lets the menu disappear when hovered in graph or sidebar; + d3.select("#graph").on("mouseover", function (){ + navigationMenu.hideAllMenus(); + }); + d3.select("#generalDetails").on("mouseover", function (){ + navigationMenu.hideAllMenus(); + }); + }; + + return navigationMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 337: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** The zoom Slider **/ + module.exports = function ( graph ){ + var zoomSlider = {}; + var minMag = graph.options().minMagnification(), + maxMag = graph.options().maxMagnification(), + defZoom, + t_zoomOut, + t_zoomIn, + zoomValue, + showSlider = true, + w = graph.options().width(), + h = graph.options().height(), + slider; + + defZoom = Math.min(w, h) / 1000; + + function clearAllTimers(){ + cancelAnimationFrame(t_zoomOut); + cancelAnimationFrame(t_zoomIn); + } + + function timed_zoomOut(){ + zoomValue = 0.98 * zoomValue; + // fail saves + if ( zoomValue < minMag ) { + zoomValue = minMag; + } + graph.setSliderZoom(zoomValue); + t_zoomOut = requestAnimationFrame(timed_zoomOut); + } + + function timed_zoomIn(){ + zoomValue = 1.02 * zoomValue; + // fail saves + if ( zoomValue > maxMag ) { + zoomValue = maxMag; + } + graph.setSliderZoom(zoomValue); + t_zoomIn = requestAnimationFrame(timed_zoomIn); + } + + zoomSlider.setup = function (){ + slider = d3.select("#zoomSliderParagraph").append("input") + .datum({}) + .attr("id", "zoomSliderElement") + .attr("type", "range") + .attr("value", defZoom) + .attr("min", minMag) + .attr("max", maxMag) + .attr("step", (maxMag - minMag) / 40) + .attr("title", "zoom factor") + .on("input", function (){ + zoomSlider.zooming(); + }); + + d3.select("#zoomOutButton").on("mousedown", function (){ + graph.options().navigationMenu().hideAllMenus(); + zoomValue = graph.scaleFactor(); + t_zoomOut = requestAnimationFrame(timed_zoomOut); + }) + .on("touchstart", function (){ + graph.options().navigationMenu().hideAllMenus(); + zoomValue = graph.scaleFactor(); + t_zoomOut = requestAnimationFrame(timed_zoomOut); + }) + .on("mouseup", clearAllTimers) + .on("touchend", clearAllTimers) + .on("touchcancel", clearAllTimers) + .attr("title", "zoom out"); + + d3.select("#zoomInButton").on("mousedown", function (){ + graph.options().navigationMenu().hideAllMenus(); + zoomValue = graph.scaleFactor(); + t_zoomIn = requestAnimationFrame(timed_zoomIn); + }) + .on("touchstart", function (){ + graph.options().navigationMenu().hideAllMenus(); + zoomValue = graph.scaleFactor(); + t_zoomIn = requestAnimationFrame(timed_zoomIn); + }) + .on("mouseup", clearAllTimers) + .on("touchend", clearAllTimers) + .on("touchcancel", clearAllTimers) + .attr("title", "zoom in"); + + d3.select("#centerGraphButton").on("click", function (){ + graph.options().navigationMenu().hideAllMenus(); + graph.forceRelocationEvent(); + }).attr("title", "center graph"); + + }; + + zoomSlider.showSlider = function ( val ){ + if ( !arguments.length ) return showSlider; + d3.select("#zoomSlider").classed("hidden", !val); + showSlider = val; + }; + + zoomSlider.zooming = function (){ + graph.options().navigationMenu().hideAllMenus(); + var zoomValue = slider.property("value"); + slider.attr("value", zoomValue); + graph.setSliderZoom(zoomValue); + }; + + zoomSlider.updateZoomSliderValue = function ( val ){ + if ( slider ) { + slider.attr("value", val); + slider.property("value", val); + } + }; + + return zoomSlider; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 338: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for the sidebar. + * @param graph the graph that belongs to these controls + * @returns {{}} + */ + module.exports = function ( graph ){ + + var sidebar = {}, + languageTools = webvowl.util.languageTools(), + elementTools = webvowl.util.elementTools(), + // Required for reloading when the language changes + ontologyInfo, + visibleSidebar = 1, + lastSelectedElement, + + detailArea = d3.select("#detailsArea"), + graphArea = d3.select("#canvasArea"), + menuArea = d3.select("#swipeBarContainer"), + collapseButton = d3.select("#sidebarExpandButton"); + + /** + * Setup the menu bar. + */ + + + function setupCollapsing(){ + // adapted version of this example: http://www.normansblog.de/simple-jquery-accordion/ + function collapseContainers( containers ){ + containers.classed("hidden", true); + } + + function expandContainers( containers ){ + containers.classed("hidden", false); + } + + var triggers = d3.selectAll(".accordion-trigger"); + + // Collapse all inactive triggers on startup + collapseContainers(d3.selectAll(".accordion-trigger:not(.accordion-trigger-active) + div")); + + triggers.on("click", function (){ + var selectedTrigger = d3.select(this), + activeTriggers = d3.selectAll(".accordion-trigger-active"); + + if ( selectedTrigger.classed("accordion-trigger-active") ) { + // Collapse the active (which is also the selected) trigger + collapseContainers(d3.select(selectedTrigger.node().nextElementSibling)); + selectedTrigger.classed("accordion-trigger-active", false); + } else { + // Collapse the other trigger ... + collapseContainers(d3.selectAll(".accordion-trigger-active + div")); + activeTriggers.classed("accordion-trigger-active", false); + // ... and expand the selected one + expandContainers(d3.select(selectedTrigger.node().nextElementSibling)); + selectedTrigger.classed("accordion-trigger-active", true); + } + }); + } + + sidebar.clearOntologyInformation = function (){ + + d3.select("#title").text("No title available"); + d3.select("#about").attr("href", "#").attr("target", "_blank").text("not given"); + d3.select("#version").text("--"); + d3.select("#authors").text("--"); + d3.select("#description").text("No description available."); + var container = d3.select("#ontology-metadata"); + container.selectAll("*").remove(); + d3.select("#classCount") + .text("0"); + d3.select("#objectPropertyCount") + .text("0"); + d3.select("#datatypePropertyCount") + .text("0"); + d3.select("#individualCount") + .text("0"); + d3.select("#nodeCount") + .text("0"); + d3.select("#edgeCount") + .text("0"); + + // clear selectedNode info + var isTriggerActive = d3.select("#selection-details-trigger").classed("accordion-trigger-active"); + if ( isTriggerActive ) { + // close accordion + d3.select("#selection-details-trigger").node().click(); + } + showSelectionAdvice(); + + }; + + /** + * Updates the information of the passed ontology. + * @param data the graph data + * @param statistics the statistics module + */ + sidebar.updateOntologyInformation = function ( data, statistics ){ + data = data || {}; + ontologyInfo = data.header || {}; + + updateGraphInformation(); + displayGraphStatistics(undefined, statistics); + displayMetadata(ontologyInfo.other); + + // Reset the sidebar selection + sidebar.updateSelectionInformation(undefined); + + setLanguages(ontologyInfo.languages); + }; + + function setLanguages( languages ){ + languages = languages || []; + + // Put the default and unset label on top of the selection labels + languages.sort(function ( a, b ){ + if ( a === webvowl.util.constants().LANG_IRIBASED ) { + return -1; + } else if ( b === webvowl.util.constants().LANG_IRIBASED ) { + return 1; + } + if ( a === webvowl.util.constants().LANG_UNDEFINED ) { + return -1; + } else if ( b === webvowl.util.constants().LANG_UNDEFINED ) { + return 1; + } + return a.localeCompare(b); + }); + + var languageSelection = d3.select("#language") + .on("change", function (){ + graph.language(d3.event.target.value); + updateGraphInformation(); + sidebar.updateSelectionInformation(lastSelectedElement); + }); + + languageSelection.selectAll("option").remove(); + languageSelection.selectAll("option") + .data(languages) + .enter().append("option") + .attr("value", function ( d ){ + return d; + }) + .text(function ( d ){ + return d; + }); + + if ( !trySelectDefaultLanguage(languageSelection, languages, "en") ) { + if ( !trySelectDefaultLanguage(languageSelection, languages, webvowl.util.constants().LANG_UNDEFINED) ) { + trySelectDefaultLanguage(languageSelection, languages, webvowl.util.constants().LANG_IRIBASED); + } + } + } + + function trySelectDefaultLanguage( selection, languages, language ){ + var langIndex = languages.indexOf(language); + if ( langIndex >= 0 ) { + selection.property("selectedIndex", langIndex); + graph.language(language); + return true; + } + + return false; + } + + function updateGraphInformation(){ + var title = languageTools.textInLanguage(ontologyInfo.title, graph.language()); + d3.select("#title").text(title || "No title available"); + d3.select("#about").attr("href", ontologyInfo.iri).attr("target", "_blank").text(ontologyInfo.iri); + d3.select("#version").text(ontologyInfo.version || "--"); + var authors = ontologyInfo.author; + if ( typeof authors === "string" ) { + // Stay compatible with author info as strings after change in january 2015 + d3.select("#authors").text(authors); + } else if ( authors instanceof Array ) { + d3.select("#authors").text(authors.join(", ")); + } else { + d3.select("#authors").text("--"); + } + + var description = languageTools.textInLanguage(ontologyInfo.description, graph.language()); + d3.select("#description").text(description || "No description available."); + } + + function displayGraphStatistics( deliveredMetrics, statistics ){ + // Metrics are optional and may be undefined + deliveredMetrics = deliveredMetrics || {}; + + d3.select("#classCount") + .text(deliveredMetrics.classCount || statistics.classCount()); + d3.select("#objectPropertyCount") + .text(deliveredMetrics.objectPropertyCount || statistics.objectPropertyCount()); + d3.select("#datatypePropertyCount") + .text(deliveredMetrics.datatypePropertyCount || statistics.datatypePropertyCount()); + d3.select("#individualCount") + .text(deliveredMetrics.totalIndividualCount || statistics.totalIndividualCount()); + d3.select("#nodeCount") + .text(statistics.nodeCount()); + d3.select("#edgeCount") + .text(statistics.edgeCount()); + } + + function displayMetadata( metadata ){ + var container = d3.select("#ontology-metadata"); + container.selectAll("*").remove(); + + listAnnotations(container, metadata); + + if ( container.selectAll(".annotation").size() <= 0 ) { + container.append("p").text("No annotations available."); + } + } + + function listAnnotations( container, annotationObject ){ + annotationObject = annotationObject || {}; //todo + + // Collect the annotations in an array for simpler processing + var annotations = []; + for ( var annotation in annotationObject ) { + if ( annotationObject.hasOwnProperty(annotation) ) { + annotations.push(annotationObject[annotation][0]); + } + } + + container.selectAll(".annotation").remove(); + container.selectAll(".annotation").data(annotations).enter().append("p") + .classed("annotation", true) + .classed("statisticDetails", true) + .text(function ( d ){ + return d.identifier + ":"; + }) + .append("span") + .each(function ( d ){ + appendIriLabel(d3.select(this), d.value, d.type === "iri" ? d.value : undefined); + }); + } + + /** + * Update the information of the selected node. + * @param selectedElement the selection or null if nothing is selected + */ + sidebar.updateSelectionInformation = function ( selectedElement ){ + lastSelectedElement = selectedElement; + + // Click event was prevented when dragging + if ( d3.event && d3.event.defaultPrevented ) { + return; + } + + var isTriggerActive = d3.select("#selection-details-trigger").classed("accordion-trigger-active"); + if ( selectedElement && !isTriggerActive ) { + d3.select("#selection-details-trigger").node().click(); + } else if ( !selectedElement && isTriggerActive ) { + showSelectionAdvice(); + return; + } + + if ( elementTools.isProperty(selectedElement) ) { + displayPropertyInformation(selectedElement); + } else if ( elementTools.isNode(selectedElement) ) { + displayNodeInformation(selectedElement); + } + }; + + function showSelectionAdvice(){ + setSelectionInformationVisibility(false, false, true); + } + + function setSelectionInformationVisibility( showClasses, showProperties, showAdvice ){ + d3.select("#classSelectionInformation").classed("hidden", !showClasses); + d3.select("#propertySelectionInformation").classed("hidden", !showProperties); + d3.select("#noSelectionInformation").classed("hidden", !showAdvice); + } + + function displayPropertyInformation( property ){ + showPropertyInformations(); + + setIriLabel(d3.select("#propname"), property.labelForCurrentLanguage(), property.iri()); + d3.select("#typeProp").text(property.type()); + + if ( property.inverse() !== undefined ) { + d3.select("#inverse").classed("hidden", false); + setIriLabel(d3.select("#inverse span"), property.inverse().labelForCurrentLanguage(), property.inverse().iri()); + } else { + d3.select("#inverse").classed("hidden", true); + } + + var equivalentIriSpan = d3.select("#propEquivUri"); + listNodeArray(equivalentIriSpan, property.equivalents()); + + listNodeArray(d3.select("#subproperties"), property.subproperties()); + listNodeArray(d3.select("#superproperties"), property.superproperties()); + + if ( property.minCardinality() !== undefined ) { + d3.select("#infoCardinality").classed("hidden", true); + d3.select("#minCardinality").classed("hidden", false); + d3.select("#minCardinality span").text(property.minCardinality()); + d3.select("#maxCardinality").classed("hidden", false); + + if ( property.maxCardinality() !== undefined ) { + d3.select("#maxCardinality span").text(property.maxCardinality()); + } else { + d3.select("#maxCardinality span").text("*"); + } + + } else if ( property.cardinality() !== undefined ) { + d3.select("#minCardinality").classed("hidden", true); + d3.select("#maxCardinality").classed("hidden", true); + d3.select("#infoCardinality").classed("hidden", false); + d3.select("#infoCardinality span").text(property.cardinality()); + } else { + d3.select("#infoCardinality").classed("hidden", true); + d3.select("#minCardinality").classed("hidden", true); + d3.select("#maxCardinality").classed("hidden", true); + } + + setIriLabel(d3.select("#domain"), property.domain().labelForCurrentLanguage(), property.domain().iri()); + setIriLabel(d3.select("#range"), property.range().labelForCurrentLanguage(), property.range().iri()); + + displayAttributes(property.attributes(), d3.select("#propAttributes")); + + setTextAndVisibility(d3.select("#propDescription"), property.descriptionForCurrentLanguage()); + setTextAndVisibility(d3.select("#propComment"), property.commentForCurrentLanguage()); + + listAnnotations(d3.select("#propertySelectionInformation"), property.annotations()); + } + + function showPropertyInformations(){ + setSelectionInformationVisibility(false, true, false); + } + + function setIriLabel( element, name, iri ){ + var parent = d3.select(element.node().parentNode); + + if ( name ) { + element.selectAll("*").remove(); + appendIriLabel(element, name, iri); + parent.classed("hidden", false); + } else { + parent.classed("hidden", true); + } + } + + function appendIriLabel( element, name, iri ){ + var tag; + + if ( iri ) { + tag = element.append("a") + .attr("href", iri) + .attr("title", iri) + .attr("target", "_blank"); + } else { + tag = element.append("span"); + } + tag.text(name); + } + + function displayAttributes( attributes, textSpan ){ + var spanParent = d3.select(textSpan.node().parentNode); + + if ( attributes && attributes.length > 0 ) { + // Remove redundant redundant attributes for sidebar + removeElementFromArray("object", attributes); + removeElementFromArray("datatype", attributes); + removeElementFromArray("rdf", attributes); + } + + if ( attributes && attributes.length > 0 ) { + textSpan.text(attributes.join(", ")); + + spanParent.classed("hidden", false); + } else { + spanParent.classed("hidden", true); + } + } + + function removeElementFromArray( element, array ){ + var index = array.indexOf(element); + if ( index > -1 ) { + array.splice(index, 1); + } + } + + function displayNodeInformation( node ){ + showClassInformations(); + + setIriLabel(d3.select("#name"), node.labelForCurrentLanguage(), node.iri()); + + /* Equivalent stuff. */ + var equivalentIriSpan = d3.select("#classEquivUri"); + listNodeArray(equivalentIriSpan, node.equivalents()); + + d3.select("#typeNode").text(node.type()); + listNodeArray(d3.select("#individuals"), node.individuals()); + + /* Disjoint stuff. */ + var disjointNodes = d3.select("#disjointNodes"); + var disjointNodesParent = d3.select(disjointNodes.node().parentNode); + + if ( node.disjointWith() !== undefined ) { + disjointNodes.selectAll("*").remove(); + + node.disjointWith().forEach(function ( element, index ){ + if ( index > 0 ) { + disjointNodes.append("span").text(", "); + } + appendIriLabel(disjointNodes, element.labelForCurrentLanguage(), element.iri()); + }); + + disjointNodesParent.classed("hidden", false); + } else { + disjointNodesParent.classed("hidden", true); + } + + displayAttributes(node.attributes(), d3.select("#classAttributes")); + + setTextAndVisibility(d3.select("#nodeDescription"), node.descriptionForCurrentLanguage()); + setTextAndVisibility(d3.select("#nodeComment"), node.commentForCurrentLanguage()); + + listAnnotations(d3.select("#classSelectionInformation"), node.annotations()); + } + + function showClassInformations(){ + setSelectionInformationVisibility(true, false, false); + } + + function listNodeArray( textSpan, nodes ){ + var spanParent = d3.select(textSpan.node().parentNode); + + if ( nodes && nodes.length ) { + textSpan.selectAll("*").remove(); + nodes.forEach(function ( element, index ){ + if ( index > 0 ) { + textSpan.append("span").text(", "); + } + appendIriLabel(textSpan, element.labelForCurrentLanguage(), element.iri()); + }); + + spanParent.classed("hidden", false); + } else { + spanParent.classed("hidden", true); + } + } + + function setTextAndVisibility( label, value ){ + var parentNode = d3.select(label.node().parentNode); + var hasValue = !!value; + if ( value ) { + label.text(value); + } + parentNode.classed("hidden", !hasValue); + } + + /** Collapsible Sidebar functions; **/ + + sidebar.showSidebar = function ( val, init ){ + // make val to bool + if ( val === 1 ) { + visibleSidebar = true; + collapseButton.node().innerHTML = ">"; + detailArea.classed("hidden", true); + if ( init === true ) { + detailArea.classed("hidden", !visibleSidebar); + graphArea.style("width", "78%"); + graphArea.style("-webkit-animation-name", "none"); + + menuArea.style("width", "78%"); + menuArea.style("-webkit-animation-name", "none"); + + d3.select("#WarningErrorMessagesContainer").style("width", "78%"); + d3.select("#WarningErrorMessagesContainer").style("-webkit-animation-name", "none"); + } else { + graphArea.style("width", "78%"); + graphArea.style("-webkit-animation-name", "sbCollapseAnimation"); + graphArea.style("-webkit-animation-duration", "0.5s"); + + menuArea.style("width", "78%"); + menuArea.style("-webkit-animation-name", "sbCollapseAnimation"); + menuArea.style("-webkit-animation-duration", "0.5s"); + + d3.select("#WarningErrorMessagesContainer").style("width", "78%"); + d3.select("#WarningErrorMessagesContainer").style("-webkit-animation-name", "warn_ExpandRightBarAnimation"); + d3.select("#WarningErrorMessagesContainer").style("-webkit-animation-duration", "0.5s"); + } + graph.options().width(window.innerWidth - (window.innerWidth * 0.22)); + graph.options().navigationMenu().updateScrollButtonVisibility(); + } + if ( val === 0 ) { + visibleSidebar = false; + detailArea.classed("hidden", true); + + collapseButton.node().innerHTML = "<"; + // adjust the layout + if ( init === true ) { + graphArea.style("width", "100%"); + graphArea.style("-webkit-animation-name", "none"); + + menuArea.style("width", "100%"); + menuArea.style("-webkit-animation-name", "none"); + + d3.select("#WarningErrorMessagesContainer").style("width", "100%"); + d3.select("#WarningErrorMessagesContainer").style("-webkit-animation-name", "none"); + } else { + graphArea.style("width", "100%"); + graphArea.style("-webkit-animation-name", "sbExpandAnimation"); + graphArea.style("-webkit-animation-duration", "0.5s"); + + menuArea.style("width", "100%"); + menuArea.style("-webkit-animation-name", "sbExpandAnimation"); + menuArea.style("-webkit-animation-duration", "0.5s"); + + d3.select("#WarningErrorMessagesContainer").style("width", "100%"); + d3.select("#WarningErrorMessagesContainer").style("-webkit-animation-name", "warn_CollapseRightBarAnimation"); + d3.select("#WarningErrorMessagesContainer").style("-webkit-animation-duration", "0.5s"); + + } + graph.options().width(window.innerWidth); + graph.updateCanvasContainerSize(); + graph.options().navigationMenu().updateScrollButtonVisibility(); + } + }; + + sidebar.isSidebarVisible = function (){ + return visibleSidebar; + }; + + sidebar.updateSideBarVis = function ( init ){ + var vis = sidebar.getSidebarVisibility(); + sidebar.showSidebar(parseInt(vis), init); + }; + + sidebar.getSidebarVisibility = function (){ + var isHidden = detailArea.classed("hidden"); + if ( isHidden === false ) return String(1); + if ( isHidden === true ) return String(0); + }; + + sidebar.initSideBarAnimation = function (){ + graphArea.node().addEventListener("animationend", function (){ + detailArea.classed("hidden", !visibleSidebar); + graph.updateCanvasContainerSize(); + graph.options().navigationMenu().updateScrollButtonVisibility(); + }); + }; + + sidebar.setup = function (){ + setupCollapsing(); + sidebar.initSideBarAnimation(); + + collapseButton.on("click", function (){ + graph.options().navigationMenu().hideAllMenus(); + var settingValue = parseInt(sidebar.getSidebarVisibility()); + if ( settingValue === 1 ) sidebar.showSidebar(0); + else sidebar.showSidebar(1); + }); + }; + + + sidebar.updateShowedInformation = function (){ + var editMode = graph.editorMode(); + d3.select("#generalDetails").classed("hidden", editMode); + d3.select("#generalDetailsEdit").classed("hidden", !editMode); + + // store the meta information in graph.options() + + // todo: update edit meta info + graph.options().editSidebar().updateGeneralOntologyInfo(); + + // todo: update showed meta info; + graph.options().sidebar().updateGeneralOntologyInfo(); + + }; + + sidebar.updateGeneralOntologyInfo = function (){ + // get it from graph.options + var generalMetaObj = graph.options().getGeneralMetaObject(); + var preferredLanguage = graph && graph.language ? graph.language() : null; + if ( generalMetaObj.hasOwnProperty("title") ) { + // title has language to it -.- + if ( typeof generalMetaObj.title === "object" ) { + d3.select("#title").node().value = languageTools.textInLanguage(generalMetaObj.title, preferredLanguage); + } else { + d3.select("#title").node().innerHTML = generalMetaObj.title; + } + + } + if ( generalMetaObj.hasOwnProperty("iri") ) d3.select("#about").node().innerHTML = generalMetaObj.iri; + if ( generalMetaObj.hasOwnProperty("iri") ) d3.select("#about").node().href = generalMetaObj.iri; + if ( generalMetaObj.hasOwnProperty("version") ) d3.select("#version").node().innerHTML = generalMetaObj.version; + if ( generalMetaObj.hasOwnProperty("author") ) d3.select("#authors").node().innerHTML = generalMetaObj.author; + // this could also be an object >> + if ( generalMetaObj.hasOwnProperty("description") ) { + if ( typeof generalMetaObj.description === "object" ) { + d3.select("#description").node().innerHTML = languageTools.textInLanguage(generalMetaObj.description, preferredLanguage); + } + else { + d3.select("#description").node().innerHTML = generalMetaObj.description; + } + } + }; + + + return sidebar; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 339: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for the sidebar. + * @param graph the graph that belongs to these controls + * @returns {{}} + */ + module.exports = function ( graph ){ + + var leftSidebar = {}, + languageTools = webvowl.util.languageTools(), + elementTools = webvowl.util.elementTools(); + var collapseButton = d3.select("#leftSideBarCollapseButton"); + var visibleSidebar = 0; + var backupVisibility = 0; + var sideBarContent = d3.select("#leftSideBarContent"); + var sideBarContainer = d3.select("#containerForLeftSideBar"); + var defaultClassSelectionContainers = []; + var defaultDatatypeSelectionContainers = []; + var defaultPropertySelectionContainers = []; + + leftSidebar.setup = function (){ + setupCollapsing(); + leftSidebar.initSideBarAnimation(); + + collapseButton.on("click", function (){ + graph.options().navigationMenu().hideAllMenus(); + var settingValue = parseInt(leftSidebar.getSidebarVisibility()); + if ( settingValue === 0 ) leftSidebar.showSidebar(1); + else leftSidebar.showSidebar(0); + backupVisibility = settingValue; + }); + + setupSelectionContainers(); + d3.select("#WarningErrorMessages").node().addEventListener("animationend", function (){ + d3.select("#WarningErrorMessages").style("-webkit-animation-name", "none"); + }); + + }; + + leftSidebar.hideCollapseButton = function ( val ){ + sideBarContainer.classed("hidden", val); + }; + + + function unselectAllElements( container ){ + for ( var i = 0; i < container.length; i++ ) + container[i].classed("defaultSelected", false); + } + + function selectThisDefaultElement( element ){ + d3.select(element).classed("defaultSelected", true); + } + + function updateDefaultNameInAccordion( element, identifier ){ + var elementDescription = ""; + if ( identifier === "defaultClass" ) elementDescription = "Class: "; + if ( identifier === "defaultDatatype" ) elementDescription = "Datatype: "; + if ( identifier === "defaultProperty" ) elementDescription = "Property: "; + + d3.select("#" + identifier).node().innerHTML = elementDescription + element.innerHTML; + d3.select("#" + identifier).node().title = element.innerHTML; + } + + function classSelectorFunction(){ + unselectAllElements(defaultClassSelectionContainers); + selectThisDefaultElement(this); + updateDefaultNameInAccordion(this, "defaultClass"); + } + + function datatypeSelectorFunction(){ + unselectAllElements(defaultDatatypeSelectionContainers); + selectThisDefaultElement(this); + updateDefaultNameInAccordion(this, "defaultDatatype"); + } + + function propertySelectorFunction(){ + unselectAllElements(defaultPropertySelectionContainers); + selectThisDefaultElement(this); + updateDefaultNameInAccordion(this, "defaultProperty"); + } + + + function setupSelectionContainers(){ + var classContainer = d3.select("#classContainer"); + var datatypeContainer = d3.select("#datatypeContainer"); + var propertyContainer = d3.select("#propertyContainer"); + // create the supported elements + + var defaultClass = "owl:Class"; + var defaultDatatype = "rdfs:Literal"; + var defaultProperty = "owl:objectProperty"; + + var supportedClasses = graph.options().supportedClasses(); + var supportedDatatypes = graph.options().supportedDatatypes(); + var supportedProperties = graph.options().supportedProperties(); + var i; + + for ( i = 0; i < supportedClasses.length; i++ ) { + var aClassSelectionContainer; + aClassSelectionContainer = classContainer.append("div"); + aClassSelectionContainer.classed("containerForDefaultSelection", true); + aClassSelectionContainer.classed("noselect", true); + aClassSelectionContainer.node().id = "selectedClass" + supportedClasses[i]; + aClassSelectionContainer.node().innerHTML = supportedClasses[i]; + + if ( supportedClasses[i] === defaultClass ) { + selectThisDefaultElement(aClassSelectionContainer.node()); + } + aClassSelectionContainer.on("click", classSelectorFunction); + defaultClassSelectionContainers.push(aClassSelectionContainer); + } + + for ( i = 0; i < supportedDatatypes.length; i++ ) { + var aDTSelectionContainer = datatypeContainer.append("div"); + aDTSelectionContainer.classed("containerForDefaultSelection", true); + aDTSelectionContainer.classed("noselect", true); + aDTSelectionContainer.node().id = "selectedDatatype" + supportedDatatypes[i]; + aDTSelectionContainer.node().innerHTML = supportedDatatypes[i]; + + if ( supportedDatatypes[i] === defaultDatatype ) { + selectThisDefaultElement(aDTSelectionContainer.node()); + } + aDTSelectionContainer.on("click", datatypeSelectorFunction); + defaultDatatypeSelectionContainers.push(aDTSelectionContainer); + } + for ( i = 0; i < supportedProperties.length; i++ ) { + var aPropSelectionContainer = propertyContainer.append("div"); + aPropSelectionContainer.classed("containerForDefaultSelection", true); + aPropSelectionContainer.classed("noselect", true); + aPropSelectionContainer.node().id = "selectedClass" + supportedProperties[i]; + aPropSelectionContainer.node().innerHTML = supportedProperties[i]; + aPropSelectionContainer.on("click", propertySelectorFunction); + if ( supportedProperties[i] === defaultProperty ) { + selectThisDefaultElement(aPropSelectionContainer.node()); + } + defaultPropertySelectionContainers.push(aPropSelectionContainer); + } + } + + function setupCollapsing(){ + // adapted version of this example: http://www.normansblog.de/simple-jquery-accordion/ + function collapseContainers( containers ){ + containers.classed("hidden", true); + } + + function expandContainers( containers ){ + containers.classed("hidden", false); + } + + var triggers = d3.selectAll(".accordion-trigger"); + + // Collapse all inactive triggers on startup + // collapseContainers(d3.selectAll(".accordion-trigger:not(.accordion-trigger-active) + div")); + + triggers.on("click", function (){ + var selectedTrigger = d3.select(this); + if ( selectedTrigger.classed("accordion-trigger-active") ) { + // Collapse the active (which is also the selected) trigger + collapseContainers(d3.select(selectedTrigger.node().nextElementSibling)); + selectedTrigger.classed("accordion-trigger-active", false); + } else { + // Collapse the other trigger ... + // collapseContainers(d3.selectAll(".accordion-trigger-active + div")); + // activeTriggers.classed("accordion-trigger-active", false); + // ... and expand the selected one + expandContainers(d3.select(selectedTrigger.node().nextElementSibling)); + selectedTrigger.classed("accordion-trigger-active", true); + } + }); + } + + + leftSidebar.isSidebarVisible = function (){ + return visibleSidebar; + }; + + leftSidebar.updateSideBarVis = function ( init ){ + var vis = leftSidebar.getSidebarVisibility(); + leftSidebar.showSidebar(parseInt(vis), init); + }; + + leftSidebar.initSideBarAnimation = function (){ + sideBarContainer.node().addEventListener("animationend", function (){ + sideBarContent.classed("hidden", !visibleSidebar); + if ( visibleSidebar === true ) { + sideBarContainer.style("width", "200px"); + sideBarContent.classed("hidden", false); + d3.select("#leftSideBarCollapseButton").style("left", "200px"); + d3.select("#leftSideBarCollapseButton").classed("hidden", false); + d3.select("#WarningErrorMessages").style("left", "100px"); + } + else { + sideBarContainer.style("width", "0px"); + d3.select("#leftSideBarCollapseButton").style("left", "0px"); + d3.select("#WarningErrorMessages").style("left", "0px"); + d3.select("#leftSideBarCollapseButton").classed("hidden", false); + + } + graph.updateCanvasContainerSize(); + graph.options().navigationMenu().updateScrollButtonVisibility(); + }); + }; + + leftSidebar.showSidebar = function ( val, init ){ + // make val to bool + var collapseButton = d3.select("#leftSideBarCollapseButton"); + if ( init === true ) { + visibleSidebar = (backupVisibility === 0); + sideBarContent.classed("hidden", !visibleSidebar); + sideBarContainer.style("-webkit-animation-name", "none"); + d3.select("#WarningErrorMessages").style("-webkit-animation-name", "none"); + if ( visibleSidebar === true ) { + sideBarContainer.style("width", "200px"); + sideBarContent.classed("hidden", false); + d3.select("#leftSideBarCollapseButton").style("left", "200px"); + d3.select("#leftSideBarCollapseButton").classed("hidden", false); + d3.select("#WarningErrorMessages").style("left", "100px"); + collapseButton.node().innerHTML = "<"; + } + + else { + sideBarContainer.style("width", "0px"); + d3.select("#WarningErrorMessages").style("left", "0px"); + d3.select("#leftSideBarCollapseButton").style("left", "0px"); + d3.select("#leftSideBarCollapseButton").classed("hidden", false); + collapseButton.node().innerHTML = ">"; + } + + graph.updateCanvasContainerSize(); + graph.options().navigationMenu().updateScrollButtonVisibility(); + return; + } + + d3.select("#leftSideBarCollapseButton").classed("hidden", true); + + if ( val === 1 ) { + visibleSidebar = true; + collapseButton.node().innerHTML = "<"; + // call expand animation; + sideBarContainer.style("-webkit-animation-name", "l_sbExpandAnimation"); + sideBarContainer.style("-webkit-animation-duration", "0.5s"); + // prepare the animation; + + d3.select("#WarningErrorMessages").style("-webkit-animation-name", "warn_ExpandLeftBarAnimation"); + d3.select("#WarningErrorMessages").style("-webkit-animation-duration", "0.5s"); + + } + if ( val === 0 ) { + visibleSidebar = false; + sideBarContent.classed("hidden", true); + collapseButton.node().innerHTML = ">"; + // call collapse animation + sideBarContainer.style("-webkit-animation-name", "l_sbCollapseAnimation"); + sideBarContainer.style("-webkit-animation-duration", "0.5s"); + d3.select("#WarningErrorMessages").style("-webkit-animation-name", "warn_CollapseLeftBarAnimation"); + d3.select("#WarningErrorMessages").style("-webkit-animation-duration", "0.5s"); + d3.select("#WarningErrorMessages").style("left", "0"); + } + + }; + + leftSidebar.getSidebarVisibility = function (){ + var isHidden = sideBarContent.classed("hidden"); + if ( isHidden === false ) return String(1); + if ( isHidden === true ) return String(0); + }; + + return leftSidebar; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 340: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for the sidebar. + * @param graph the graph that belongs to these controls + * @returns {{}} + */ + module.exports = function ( graph ){ + + var editSidebar = {}, + languageTools = webvowl.util.languageTools(), + elementTools = webvowl.util.elementTools(); + + var prefixModule = webvowl.util.prefixTools(graph); + var selectedElementForCharacteristics; + var oldPrefix, oldPrefixURL; + var prefix_editMode = false; + + + editSidebar.clearMetaObjectValue = function (){ + d3.select("#titleEditor").node().value = ""; + d3.select("#iriEditor").node().value = ""; + d3.select("#versionEditor").node().value = ""; + d3.select("#authorsEditor").node().value = ""; + d3.select("#descriptionEditor").node().value = ""; + // todo add clear description; + }; + + + editSidebar.updatePrefixUi = function (){ + editSidebar.updateElementWidth(); + var prefixListContainer = d3.select("#prefixURL_Container"); + while ( prefixListContainer.node().firstChild ) { + prefixListContainer.node().removeChild(prefixListContainer.node().firstChild); + } + setupPrefixList(); + }; + + editSidebar.setup = function (){ + setupCollapsing(); + setupPrefixList(); + setupAddPrefixButton(); + setupSupportedDatatypes(); + + + d3.select("#titleEditor") + .on("change", function (){ + graph.options().addOrUpdateGeneralObjectEntry("title", d3.select("#titleEditor").node().value); + }) + .on("keydown", function (){ + d3.event.stopPropagation(); + if ( d3.event.keyCode === 13 ) { + d3.event.preventDefault(); + graph.options().addOrUpdateGeneralObjectEntry("title", d3.select("#titleEditor").node().value); + } + }); + d3.select("#iriEditor") + .on("change", function (){ + if ( graph.options().addOrUpdateGeneralObjectEntry("iri", d3.select("#iriEditor").node().value) === false ) { + // restore value + d3.select("#iriEditor").node().value = graph.options().getGeneralMetaObjectProperty('iri'); + } + }) + .on("keydown", function (){ + d3.event.stopPropagation(); + if ( d3.event.keyCode === 13 ) { + d3.event.preventDefault(); + if ( graph.options().addOrUpdateGeneralObjectEntry("iri", d3.select("#iriEditor").node().value) === false ) { + // restore value + d3.select("#iriEditor").node().value = graph.options().getGeneralMetaObjectProperty('iri'); + } + } + }); + d3.select("#versionEditor") + .on("change", function (){ + graph.options().addOrUpdateGeneralObjectEntry("version", d3.select("#versionEditor").node().value); + }) + .on("keydown", function (){ + d3.event.stopPropagation(); + if ( d3.event.keyCode === 13 ) { + d3.event.preventDefault(); + graph.options().addOrUpdateGeneralObjectEntry("version", d3.select("#versionEditor").node().value); + } + }); + d3.select("#authorsEditor") + .on("change", function (){ + graph.options().addOrUpdateGeneralObjectEntry("author", d3.select("#authorsEditor").node().value); + }) + .on("keydown", function (){ + d3.event.stopPropagation(); + if ( d3.event.keyCode === 13 ) { + d3.event.preventDefault(); + graph.options().addOrUpdateGeneralObjectEntry("author", d3.select("#authorsEditor").node().value); + } + }); + d3.select("#descriptionEditor") + .on("change", function (){ + graph.options().addOrUpdateGeneralObjectEntry("description", d3.select("#descriptionEditor").node().value); + }); + + editSidebar.updateElementWidth(); + + }; + + function setupSupportedDatatypes(){ + var datatypeEditorSelection = d3.select("#typeEditor_datatype").node(); + var supportedDatatypes = ["undefined", "xsd:boolean", "xsd:double", "xsd:integer", "xsd:string"]; + for ( var i = 0; i < supportedDatatypes.length; i++ ) { + var optB = document.createElement('option'); + optB.innerHTML = supportedDatatypes[i]; + datatypeEditorSelection.appendChild(optB); + } + } + + function highlightDeleteButton( enable, name ){ + var deletePath = d3.select("#del_pathFor_" + name); + var deleteRect = d3.select("#del_rectFor_" + name); + + if ( enable === false ) { + deletePath.node().style = "stroke: #f00;"; + deleteRect.style("cursor", "auto"); + } else { + deletePath.node().style = "stroke: #ff972d;"; + deleteRect.style("cursor", "pointer"); + } + } + + + function highlightEditButton( enable, name, fill ){ + var editPath = d3.select("#pathFor_" + name); + var editRect = d3.select("#rectFor_" + name); + + if ( enable === false ) { + if ( fill ) + editPath.node().style = "fill: #fff; stroke : #fff; stroke-width : 1px"; + else + editPath.node().style = " stroke : #fff; stroke-width : 1px"; + + editRect.style("cursor", "auto"); + } else { + if ( fill ) + editPath.node().style = "fill: #ff972d; stroke : #ff972d; stroke-width : 1px"; + else + editPath.node().style = "stroke : #ff972d; stroke-width : 1px"; + editRect.style("cursor", "pointer"); + } + + } + + function setupAddPrefixButton(){ + var btn = d3.select("#addPrefixButton"); + btn.on("click", function (){ + + // check if we are still in editMode? + if ( prefix_editMode === false ) { + // create new line entry; + var name = "emptyPrefixEntry"; + var prefixListContainer = d3.select("#prefixURL_Container"); + var prefixEditContainer = prefixListContainer.append("div"); + prefixEditContainer.classed("prefixIRIElements", true); + prefixEditContainer.node().id = "prefixContainerFor_" + name; + + var IconContainer = prefixEditContainer.append("div"); + IconContainer.style("position", "absolute"); + IconContainer.node().id = "containerFor_" + name; + var editButton = IconContainer.append("svg"); + editButton.style("width", "14px"); + editButton.style("height", "20px"); + // editButton.classed("editPrefixButton", true); + editButton.classed("noselect", true); + //editButton.node().innerHTML = "\u2714"; + editButton.node().id = "editButtonFor_" + name; + + editButton.node().elementStyle = "save"; + editButton.node().selectorName = name; + var editIcon = editButton.append("g"); + var editRect = editIcon.append("rect"); + var editPath = editIcon.append("path"); + editIcon.node().id = "iconFor_" + name; + editPath.node().id = "pathFor_" + name; + editRect.node().id = "rectFor_" + name; + + editIcon.node().selectorName = name; + editPath.node().selectorName = name; + editRect.node().selectorName = name; + IconContainer.node().title = "Save new prefix and IRI"; + + editPath.classed("editPrefixIcon"); + editPath.style("stroke", "#fff"); + editPath.style("stroke-width", "1px"); + editPath.style("fill", "#fff"); + editRect.attr("width", "14px"); + editRect.attr("height", "14px"); + editRect.style("fill", "#18202A"); + editRect.attr("transform", "matrix(1,0,0,1,-3,4)"); + + editButton.selectAll("g").on("mouseover", function (){ + highlightEditButton(true, this.selectorName, true); + }); + editButton.selectAll("g").on("mouseout", function (){ + highlightEditButton(false, this.selectorName, true); + }); + // Check mark + // M9 16.2L4.8 12l-1.4 1.4L9 19 21 7l-1.4-1.4L9 16.2z + // pencil + // M3 17.25V21h3.75L17.81 9.94l-3.75-3.75L3 17.25zM20.71 7.04c.39-.39.39-1.02 0-1.41l-2.34-2.34c-.39-.39-1.02-.39-1.41 0l-1.83 1.83 3.75 3.75 1.83-1.83z + editPath.attr("d", "M9 16.2L4.8 12l-1.4 1.4L9 19 21 7l-1.4-1.4L9 16.2z"); + editPath.attr("transform", "matrix(0.45,0,0,0.45,0,5)"); + + var prefInput = prefixEditContainer.append("input"); + prefInput.classed("prefixInput", true); + prefInput.node().type = "text"; + prefInput.node().id = "prefixInputFor_" + name; + prefInput.node().autocomplete = "off"; + prefInput.node().value = ""; + prefInput.style("margin-left", "14px"); + + var prefURL = prefixEditContainer.append("input"); + prefURL.classed("prefixURL", true); + prefURL.node().type = "text"; + prefURL.node().id = "prefixURLFor_" + name; + prefURL.node().autocomplete = "off"; + prefURL.node().value = ""; + + prefInput.node().disabled = false; + prefURL.node().disabled = false; + prefix_editMode = true; + var deleteContainer = prefixEditContainer.append("div"); + deleteContainer.style("float", "right"); + var deleteButton = deleteContainer.append("svg"); + deleteButton.node().id = "deleteButtonFor_" + name; + deleteContainer.node().title = "Delete prefix and IRI"; + deleteButton.style("width", "10px"); + deleteButton.style("height", "20px"); + var deleteIcon = deleteButton.append("g"); + var deleteRect = deleteIcon.append("rect"); + var deletePath = deleteIcon.append("path"); + deleteIcon.node().id = "del_iconFor_" + name; + deletePath.node().id = "del_pathFor_" + name; + deleteRect.node().id = "del_rectFor_" + name; + + deleteIcon.node().selectorName = name; + deletePath.node().selectorName = name; + deleteRect.node().selectorName = name; + + + deletePath.style("stroke", "#f00"); + deleteRect.attr("width", "10px"); + deleteRect.attr("height", "14px"); + deleteRect.style("fill", "#18202A"); + deleteRect.attr("transform", "matrix(1,0,0,1,-3,4)"); + + + deletePath.attr("d", "M19 6.41L17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12z"); + deletePath.attr("transform", "matrix(0.45,0,0,0.45,0,5)"); + + deleteButton.selectAll("g").on("mouseover", function (){ + highlightDeleteButton(true, this.selectorName); + }); + deleteButton.selectAll("g").on("mouseout", function (){ + highlightDeleteButton(false, this.selectorName); + }); + + + // connect the buttons; + editButton.on("click", enablePrefixEdit); + deleteButton.on("click", deletePrefixLine); + + editSidebar.updateElementWidth(); + // swap focus to prefixInput + prefInput.node().focus(); + oldPrefix = name; + oldPrefixURL = ""; + d3.select("#addPrefixButton").node().innerHTML = "Save Prefix"; + } else { + d3.select("#editButtonFor_emptyPrefixEntry").on("click")(d3.select("#editButtonFor_emptyPrefixEntry").node()); + } + + }); + + } + + function setupPrefixList(){ + if ( graph.isEditorMode() === false ) return; + var prefixListContainer = d3.select("#prefixURL_Container"); + var prefixElements = graph.options().prefixList(); + for ( var name in prefixElements ) { + if ( prefixElements.hasOwnProperty(name) ) { + var prefixEditContainer = prefixListContainer.append("div"); + prefixEditContainer.classed("prefixIRIElements", true); + prefixEditContainer.node().id = "prefixContainerFor_" + name; + + // create edit button which enables the input fields + var IconContainer = prefixEditContainer.append("div"); + IconContainer.style("position", "absolute"); + IconContainer.node().id = "containerFor_" + name; + var editButton = IconContainer.append("svg"); + editButton.style("width", "14px"); + editButton.style("height", "20px"); + editButton.classed("noselect", true); + editButton.node().id = "editButtonFor_" + name; + IconContainer.node().title = "Edit prefix and IRI"; + editButton.node().elementStyle = "save"; + editButton.node().selectorName = name; + + editButton.node().id = "editButtonFor_" + name; + editButton.node().elementStyle = "edit"; + var editIcon = editButton.append("g"); + var editRect = editIcon.append("rect"); + var editPath = editIcon.append("path"); + editIcon.node().id = "iconFor_" + name; + editPath.node().id = "pathFor_" + name; + editRect.node().id = "rectFor_" + name; + + editIcon.node().selectorName = name; + editPath.node().selectorName = name; + editRect.node().selectorName = name; + + + editPath.classed("editPrefixIcon"); + editPath.style("stroke", "#fff"); + editPath.style("stroke-width", "1px"); + editRect.attr("width", "14px"); + editRect.attr("height", "14px"); + editRect.style("fill", "#18202A"); + editRect.attr("transform", "matrix(1,0,0,1,-3,4)"); + + editButton.selectAll("g").on("mouseover", function (){ + var sender = this; + var fill = false; + var enable = true; + var f_editPath = d3.select("#pathFor_" + sender.selectorName); + var f_editRect = d3.select("#rectFor_" + sender.selectorName); + + if ( enable === false ) { + if ( fill ) + f_editPath.node().style = "fill: #fff; stroke : #fff; stroke-width : 1px"; + else + f_editPath.node().style = " stroke : #fff; stroke-width : 1px"; + + f_editRect.style("cursor", "auto"); + } else { + if ( fill ) + f_editPath.node().style = "fill: #ff972d; stroke : #ff972d; stroke-width : 1px"; + else + f_editPath.node().style = "stroke : #ff972d; stroke-width : 1px"; + f_editRect.style("cursor", "pointer"); + } + }); + editButton.selectAll("g").on("mouseout", function (){ + var sender = this; + var fill = false; + var enable = false; + var f_editPath = d3.select("#pathFor_" + sender.selectorName); + var f_editRect = d3.select("#rectFor_" + sender.selectorName); + + if ( enable === false ) { + if ( fill ) + f_editPath.node().style = "fill: #fff; stroke : #fff; stroke-width : 1px"; + else + f_editPath.node().style = " stroke : #fff; stroke-width : 1px"; + + f_editRect.style("cursor", "auto"); + } else { + if ( fill ) + f_editPath.node().style = "fill: #ff972d; stroke : #ff972d; stroke-width : 1px"; + else + f_editPath.node().style = "stroke : #ff972d; stroke-width : 1px"; + f_editRect.style("cursor", "pointer"); + } + }); + + editPath.attr("d", "M3 17.25V21h3.75L17.81 9.94l-3.75-3.75L3 17.25zM20.71 7.04c.39-.39.39-1.02 0-1.41l-2.34-2.34c-.39-.39-1.02-.39-1.41 0l-1.83 1.83 3.75 3.75 1.83-1.83z"); + editPath.attr("transform", "matrix(-0.45,0,0,0.45,10,5)"); + + // create input field for prefix + var prefInput = prefixEditContainer.append("input"); + prefInput.classed("prefixInput", true); + prefInput.node().type = "text"; + prefInput.node().id = "prefixInputFor_" + name; + prefInput.node().autocomplete = "off"; + prefInput.node().value = name; + prefInput.style("margin-left", "14px"); + + // create input field for prefix url + var prefURL = prefixEditContainer.append("input"); + prefURL.classed("prefixURL", true); + prefURL.node().type = "text"; + prefURL.node().id = "prefixURLFor_" + name; + prefURL.node().autocomplete = "off"; + prefURL.node().value = prefixElements[name]; + prefURL.node().title = prefixElements[name]; + // disable the input fields (already defined elements can be edited later) + prefInput.node().disabled = true; + prefURL.node().disabled = true; + + // create the delete button + var deleteContainer = prefixEditContainer.append("div"); + deleteContainer.style("float", "right"); + var deleteButton = deleteContainer.append("svg"); + deleteButton.node().id = "deleteButtonFor_" + name; + deleteContainer.node().title = "Delete prefix and IRI"; + deleteButton.style("width", "10px"); + deleteButton.style("height", "20px"); + var deleteIcon = deleteButton.append("g"); + var deleteRect = deleteIcon.append("rect"); + var deletePath = deleteIcon.append("path"); + deleteIcon.node().id = "del_iconFor_" + name; + deletePath.node().id = "del_pathFor_" + name; + deleteRect.node().id = "del_rectFor_" + name; + + deleteIcon.node().selectorName = name; + deletePath.node().selectorName = name; + deleteRect.node().selectorName = name; + + + deletePath.style("stroke", "#f00"); + deleteRect.attr("width", "10px"); + deleteRect.attr("height", "14px"); + deleteRect.style("fill", "#18202A"); + deleteRect.attr("transform", "matrix(1,0,0,1,-3,4)"); + + + deletePath.attr("d", "M19 6.41L17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12z"); + deletePath.attr("transform", "matrix(0.45,0,0,0.45,0,5)"); + + deleteButton.selectAll("g").on("mouseover", function (){ + var selector = this; + var enable = true; + var f_deletePath = d3.select("#del_pathFor_" + selector.selectorName); + var f_deleteRect = d3.select("#del_rectFor_" + selector.selectorName); + + if ( enable === false ) { + f_deletePath.node().style = "stroke: #f00;"; + f_deleteRect.style("cursor", "auto"); + } else { + f_deletePath.node().style = "stroke: #ff972d;"; + f_deleteRect.style("cursor", "pointer"); + } + }); + deleteButton.selectAll("g").on("mouseout", function (){ + var selector = this; + var enable = false; + var f_deletePath = d3.select("#del_pathFor_" + selector.selectorName); + var f_deleteRect = d3.select("#del_rectFor_" + selector.selectorName); + + if ( enable === false ) { + f_deletePath.node().style = "stroke: #f00;"; + f_deleteRect.style("cursor", "auto"); + } else { + f_deletePath.node().style = "stroke: #ff972d;"; + f_deleteRect.style("cursor", "pointer"); + } + }); + + + editButton.on("click", enablePrefixEdit); + deleteButton.on("click", deletePrefixLine); + + // EXPERIMENTAL + + if ( name === "rdf" || + name === "rdfs" || + name === "xsd" || name === "dc" || + name === "owl" + ) { + // make them invis so the spacing does not change + IconContainer.classed("hidden", true); + deleteContainer.classed("hidden", true); + } + } + } + prefixModule.updatePrefixModel(); + } + + function deletePrefixLine(){ + if ( this.disabled === true ) return; + d3.select("#addPrefixButton").node().innerHTML = "Add Prefix"; + var selector = this.id.split("_")[1]; + d3.select("#prefixContainerFor_" + selector).remove(); + graph.options().removePrefix(selector); + prefix_editMode = false; // < 0 ) { + var basePref = graph.options().prefixList()[pr]; + if ( basePref === undefined ) { + console.log("ERROR __________________"); + graph.options().warningModule().showWarning("Invalid Element IRI", + "Could not resolve prefix '" + basePref + "'", + "Restoring previous IRI for Element" + element.iri(), 1, false); + d3.select("#element_iriEditor").node().value = element.iri(); + return; + + } + // check if url is not empty + + if ( name.length === 0 ) { + graph.options().warningModule().showWarning("Invalid Element IRI", + "Input IRI is EMPTY", + "Restoring previous IRI for Element" + element.iri(), 1, false); + console.log("NO INPUT PROVIDED"); + d3.select("#element_iriEditor").node().value = element.iri(); + return; + + } + url = basePref + name; + } + else { + url = base + name; + } + } else { + if ( url.length === 0 ) { + // + console.log("NO INPUT PROVIDED"); + d3.select("#element_iriEditor").node().value = element.iri(); + return; + } + // failed to identify anything useful + console.log("Tryig to use the input!"); + url = base + url; + } + } + return url; + } + + function changeIriForElement( element ){ + var url = getURLFROMPrefixedVersion(element); + var base = graph.options().getGeneralMetaObjectProperty("iri"); + var sanityCheckResult; + if ( elementTools.isNode(element) ) { + + sanityCheckResult = graph.checkIfIriClassAlreadyExist(url); + if ( sanityCheckResult === false ) { + element.iri(url); + } else { + // throw warnign + graph.options().warningModule().showWarning("Already seen this class", + "Input IRI: " + url + " for element: " + element.labelForCurrentLanguage() + " already been set", + "Restoring previous IRI for Element : " + element.iri(), 2, false, sanityCheckResult); + + editSidebar.updateSelectionInformation(element); + return; + + } + } + if ( elementTools.isProperty(element) === true ) { + sanityCheckResult = editSidebar.checkProperIriChange(element, url); + if ( sanityCheckResult !== false ) { + graph.options().warningModule().showWarning("Already seen this property", + "Input IRI: " + url + " for element: " + element.labelForCurrentLanguage() + " already been set", + "Restoring previous IRI for Element : " + element.iri(), 1, false, sanityCheckResult); + + editSidebar.updateSelectionInformation(element); + return; + } + } + + // if (element.existingPropertyIRI(url)===true){ + // console.log("I Have seen this Particular URL already "+url); + // graph.options().warningModule().showWarning("Already Seen This one ", + // "Input IRI For Element"+ element.labelForCurrentLanguage()+" already been set ", + // "Restoring previous IRI for Element"+element.iri(),1,false); + // d3.select("#element_iriEditor").node().value=graph.options().prefixModule().getPrefixRepresentationForFullURI(element.iri()); + // editSidebar.updateSelectionInformation(element); + // return; + // } + + element.iri(url); + if ( identifyExternalCharacteristicForElement(base, url) === true ) { + addAttribute(element, "external"); + // background color for external element; + element.backgroundColor("#36C"); + element.redrawElement(); + element.redrawLabelText(); + // handle visual selection + + } else { + removeAttribute(element, "external"); + // background color for external element; + element.backgroundColor(undefined); + element.redrawElement(); + element.redrawLabelText(); + + } + + if ( element.focused() ) { + graph.options().focuserModule().handle(element, true); // unfocus + graph.options().focuserModule().handle(element, true); // focus + } + // graph.options().focuserModule().handle(undefined); + + + d3.select("#element_iriEditor").node().value = prefixModule.getPrefixRepresentationForFullURI(url); + editSidebar.updateSelectionInformation(element); + } + + function validURL( str ){ + var urlregex = /^(https?|ftp):\/\/([a-zA-Z0-9.-]+(:[a-zA-Z0-9.&%$-]+)*@)*((25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9][0-9]?)(\.(25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9]?[0-9])){3}|([a-zA-Z0-9-]+\.)*[a-zA-Z0-9-]+\.(com|edu|gov|int|mil|net|org|biz|arpa|info|name|pro|aero|coop|museum|[a-zA-Z]{2}))(:[0-9]+)*(\/($|[a-zA-Z0-9.,?'\\+&%$#=~_-]+))*$/; + return urlregex.test(str); + } + + + function changeLabelForElement( element ){ + element.label(d3.select("#element_labelEditor").node().value); + element.redrawLabelText(); + } + + editSidebar.updateEditDeleteButtonIds = function ( oldPrefix, newPrefix ){ + d3.select("#prefixInputFor_" + oldPrefix).node().id = "prefixInputFor_" + newPrefix; + d3.select("#prefixURLFor_" + oldPrefix).node().id = "prefixURLFor_" + newPrefix; + d3.select("#deleteButtonFor_" + oldPrefix).node().id = "deleteButtonFor_" + newPrefix; + d3.select("#editButtonFor_" + oldPrefix).node().id = "editButtonFor_" + newPrefix; + + d3.select("#prefixContainerFor_" + oldPrefix).node().id = "prefixContainerFor_" + newPrefix; + }; + + editSidebar.checkForExistingURL = function ( url ){ + var i; + var allProps = graph.getUnfilteredData().properties; + for ( i = 0; i < allProps.length; i++ ) { + if ( allProps[i].iri() === url ) return true; + } + return false; + + }; + editSidebar.checkProperIriChange = function ( element, url ){ + console.log("Element changed Label"); + console.log("Testing URL " + url); + if ( element.type() === "rdfs:subClassOf" || element.type() === "owl:disjointWith" ) { + console.log("ignore this for now, already handled in the type and domain range changer"); + } else { + var i; + var allProps = graph.getUnfilteredData().properties; + for ( i = 0; i < allProps.length; i++ ) { + if ( allProps[i] === element ) continue; + if ( allProps[i].iri() === url ) return allProps[i]; + } + } + return false; + }; + + editSidebar.updateSelectionInformation = function ( element ){ + + if ( element === undefined ) { + // show hint; + d3.select("#selectedElementProperties").classed("hidden", true); + d3.select("#selectedElementPropertiesEmptyHint").classed("hidden", false); + selectedElementForCharacteristics = null; + editSidebar.updateElementWidth(); + } + else { + d3.select("#selectedElementProperties").classed("hidden", false); + d3.select("#selectedElementPropertiesEmptyHint").classed("hidden", true); + d3.select("#typeEditForm_datatype").classed("hidden", true); + + // set the element IRI, and labels + d3.select("#element_iriEditor").node().value = element.iri(); + d3.select("#element_labelEditor").node().value = element.labelForCurrentLanguage(); + d3.select("#element_iriEditor").node().title = element.iri(); + + d3.select("#element_iriEditor") + .on("change", function (){ + var elementIRI = element.iri(); + var prefixed = graph.options().prefixModule().getPrefixRepresentationForFullURI(elementIRI); + if ( prefixed === d3.select("#element_iriEditor").node().value ) { + console.log("Iri is identical, nothing has changed!"); + return; + } + + changeIriForElement(element); + }) + .on("keydown", function (){ + d3.event.stopPropagation(); + if ( d3.event.keyCode === 13 ) { + d3.event.preventDefault(); + console.log("IRI CHANGED Via ENTER pressed"); + changeIriForElement(element); + d3.select("#element_iriEditor").node().title = element.iri(); + } + }); + + var forceIRISync = defaultIriValue(element); + d3.select("#element_labelEditor") + .on("change", function (){ + var sanityCheckResult; + console.log("Element changed Label"); + var url = getURLFROMPrefixedVersion(element); + if ( element.iri() !== url ) { + if ( elementTools.isProperty(element) === true ) { + sanityCheckResult = editSidebar.checkProperIriChange(element, url); + if ( sanityCheckResult !== false ) { + graph.options().warningModule().showWarning("Already seen this property", + "Input IRI: " + url + " for element: " + element.labelForCurrentLanguage() + " already been set", + "Continuing with duplicate property!", 1, false, sanityCheckResult); + editSidebar.updateSelectionInformation(element); + return; + } + } + + if ( elementTools.isNode(element) === true ) { + sanityCheckResult = graph.checkIfIriClassAlreadyExist(url); + if ( sanityCheckResult !== false ) { + graph.options().warningModule().showWarning("Already seen this Class", + "Input IRI: " + url + " for element: " + element.labelForCurrentLanguage() + " already been set", + "Restoring previous IRI for Element : " + element.iri(), 2, false, sanityCheckResult); + + editSidebar.updateSelectionInformation(element); + return; + } + } + element.iri(url); + } + changeLabelForElement(element); + editSidebar.updateSelectionInformation(element); // prevents that it will be changed if node is still active + }) + .on("keydown", function (){ + d3.event.stopPropagation(); + if ( d3.event.keyCode === 13 ) { + d3.event.preventDefault(); + var sanityCheckResult; + console.log("Element changed Label"); + var url = getURLFROMPrefixedVersion(element); + if ( element.iri() !== url ) { + if ( elementTools.isProperty(element) === true ) { + sanityCheckResult = editSidebar.checkProperIriChange(element, url); + if ( sanityCheckResult !== false ) { + graph.options().warningModule().showWarning("Already seen this property", + "Input IRI: " + url + " for element: " + element.labelForCurrentLanguage() + " already been set", + "Continuing with duplicate property!", 1, false, sanityCheckResult); + + editSidebar.updateSelectionInformation(element); + return; + } + } + + if ( elementTools.isNode(element) === true ) { + sanityCheckResult = graph.checkIfIriClassAlreadyExist(url); + if ( sanityCheckResult !== false ) { + graph.options().warningModule().showWarning("Already seen this Class", + "Input IRI: " + url + " for element: " + element.labelForCurrentLanguage() + " already been set", + "Restoring previous IRI for Element : " + element.iri(), 2, false, sanityCheckResult); + + editSidebar.updateSelectionInformation(element); + return; + } + } + element.iri(url); + } + changeLabelForElement(element); + } + }) + .on("keyup", function (){ + if ( forceIRISync ) { + var labelName = d3.select("#element_labelEditor").node().value; + var resourceName = labelName.replaceAll(" ", "_"); + var syncedIRI = element.baseIri() + resourceName; + + //element.iri(syncedIRI); + d3.select("#element_iriEditor").node().title = element.iri(); + d3.select("#element_iriEditor").node().value = prefixModule.getPrefixRepresentationForFullURI(syncedIRI); + } + }); + // check if we are allowed to change IRI OR LABEL + d3.select("#element_iriEditor").node().disabled = false; + d3.select("#element_labelEditor").node().disabled = false; + + if ( element.type() === "rdfs:subClassOf" ) { + d3.select("#element_iriEditor").node().value = "http://www.w3.org/2000/01/rdf-schema#subClassOf"; + d3.select("#element_iriEditor").node().title = "http://www.w3.org/2000/01/rdf-schema#subClassOf"; + d3.select("#element_labelEditor").node().value = "Subclass of"; + d3.select("#element_iriEditor").node().disabled = true; + d3.select("#element_labelEditor").node().disabled = true; + } + if ( element.type() === "owl:Thing" ) { + d3.select("#element_iriEditor").node().value = "http://www.w3.org/2002/07/owl#Thing"; + d3.select("#element_iriEditor").node().title = "http://www.w3.org/2002/07/owl#Thing"; + d3.select("#element_labelEditor").node().value = "Thing"; + d3.select("#element_iriEditor").node().disabled = true; + d3.select("#element_labelEditor").node().disabled = true; + } + + if ( element.type() === "owl:disjointWith" ) { + d3.select("#element_iriEditor").node().value = "http://www.w3.org/2002/07/owl#disjointWith"; + d3.select("#element_iriEditor").node().title = "http://www.w3.org/2002/07/owl#disjointWith"; + d3.select("#element_iriEditor").node().disabled = true; + d3.select("#element_labelEditor").node().disabled = true; + } + + if ( element.type() === "rdfs:Literal" ) { + d3.select("#element_iriEditor").node().value = "http://www.w3.org/2000/01/rdf-schema#Literal"; + d3.select("#element_iriEditor").node().title = "http://www.w3.org/2000/01/rdf-schema#Literal"; + d3.select("#element_iriEditor").node().disabled = true; + d3.select("#element_labelEditor").node().disabled = true; + element.iri("http://www.w3.org/2000/01/rdf-schema#Literal"); + } + if ( element.type() === "rdfs:Datatype" ) { + var datatypeEditorSelection = d3.select("#typeEditor_datatype"); + d3.select("#typeEditForm_datatype").classed("hidden", false); + element.iri("http://www.w3.org/2000/01/rdf-schema#Datatype"); + d3.select("#element_iriEditor").node().value = "http://www.w3.org/2000/01/rdf-schema#Datatype"; + d3.select("#element_iriEditor").node().title = "http://www.w3.org/2000/01/rdf-schema#Datatype"; + d3.select("#element_iriEditor").node().disabled = true; + d3.select("#element_labelEditor").node().disabled = true; + + datatypeEditorSelection.node().value = element.dType(); + if ( datatypeEditorSelection.node().value === "undefined" ) { + d3.select("#element_iriEditor").node().disabled = true; // always prevent IRI modifications + d3.select("#element_labelEditor").node().disabled = false; + } + // reconnect the element + datatypeEditorSelection.on("change", function (){ + changeDatatypeType(element); + }); + } + + // add type selector + var typeEditorSelection = d3.select("#typeEditor").node(); + var htmlCollection = typeEditorSelection.children; + var numEntries = htmlCollection.length; + var i; + var elementPrototypes = getElementPrototypes(element); + for ( i = 0; i < numEntries; i++ ) + typeEditorSelection.removeChild(htmlCollection[0]); + + for ( i = 0; i < elementPrototypes.length; i++ ) { + var optA = document.createElement('option'); + optA.innerHTML = elementPrototypes[i]; + typeEditorSelection.appendChild(optA); + } + // set the proper value in the selection + typeEditorSelection.value = element.type(); + d3.select("#typeEditor").on("change", function (){ + elementTypeSelectionChanged(element); + }); + + + // add characteristics selection + var needChar = elementNeedsCharacteristics(element); + d3.select("#property_characteristics_Container").classed("hidden", !needChar); + if ( needChar === true ) { + addElementsCharacteristics(element); + } + var fullURI = d3.select("#element_iriEditor").node().value; + d3.select("#element_iriEditor").node().value = prefixModule.getPrefixRepresentationForFullURI(fullURI); + d3.select("#element_iriEditor").node().title = fullURI; + editSidebar.updateElementWidth(); + } + + }; + + editSidebar.updateGeneralOntologyInfo = function (){ + var preferredLanguage = graph && graph.language ? graph.language() : null; + + // get it from graph.options + var generalMetaObj = graph.options().getGeneralMetaObject(); + if ( generalMetaObj.hasOwnProperty("title") ) { + // title has language to it -.- + if ( typeof generalMetaObj.title === "object" ) { + d3.select("#titleEditor").node().value = languageTools.textInLanguage(generalMetaObj.title, preferredLanguage); + } else + d3.select("#titleEditor").node().value = generalMetaObj.title; + } + if ( generalMetaObj.hasOwnProperty("iri") ) d3.select("#iriEditor").node().value = generalMetaObj.iri; + if ( generalMetaObj.hasOwnProperty("version") ) d3.select("#versionEditor").node().value = generalMetaObj.version; + if ( generalMetaObj.hasOwnProperty("author") ) d3.select("#authorsEditor").node().value = generalMetaObj.author; + + + if ( generalMetaObj.hasOwnProperty("description") ) { + + if ( typeof generalMetaObj.description === "object" ) + d3.select("#descriptionEditor").node().value = + languageTools.textInLanguage(generalMetaObj.description, preferredLanguage); + else + d3.select("#descriptionEditor").node().value = generalMetaObj.description; + } + else + d3.select("#descriptionEditor").node().value = "No Description"; + }; + + editSidebar.updateElementWidth = function (){ + var height = window.innerHeight - 40; + var lsb_offset = d3.select("#logo").node().getBoundingClientRect().height + 5; + var lsb_height = height - lsb_offset; + d3.select("#containerForLeftSideBar").style("top", lsb_offset + "px"); + d3.select("#leftSideBarCollapseButton").style("top", lsb_offset + "px"); + d3.select("#containerForLeftSideBar").style("height", lsb_height + "px"); + + var div_width = d3.select("#generalDetailsEdit").node().getBoundingClientRect().width; + div_width += 10; + + var title_labelWidth = d3.select("#titleEditor-label").node().getBoundingClientRect().width + 20; + var iri_labelWidth = d3.select("#iriEditor-label").node().getBoundingClientRect().width + 20; + var version_labelWidth = d3.select("#versionEditor-label").node().getBoundingClientRect().width + 20; + var author_labelWidth = d3.select("#authorsEditor-label").node().getBoundingClientRect().width + 20; + //find max width; + var maxW = 0; + maxW = Math.max(maxW, title_labelWidth); + maxW = Math.max(maxW, iri_labelWidth); + maxW = Math.max(maxW, version_labelWidth); + maxW = Math.max(maxW, author_labelWidth); + + var meta_inputWidth = div_width - maxW - 10; + + d3.select("#titleEditor").style("width", meta_inputWidth + "px"); + d3.select("#iriEditor").style("width", meta_inputWidth + "px"); + d3.select("#versionEditor").style("width", meta_inputWidth + "px"); + d3.select("#authorsEditor").style("width", meta_inputWidth + "px"); + + + var elementIri_width = d3.select("#element_iriEditor-label").node().getBoundingClientRect().width + 20; + var elementLabel_width = d3.select("#element_labelEditor-label").node().getBoundingClientRect().width + 20; + var elementType_width = d3.select("#typeEditor-label").node().getBoundingClientRect().width + 20; + var elementDType_width = d3.select("#typeEditor_datatype-label").node().getBoundingClientRect().width + 20; + + maxW = 0; + maxW = Math.max(maxW, elementIri_width); + maxW = Math.max(maxW, elementLabel_width); + maxW = Math.max(maxW, elementType_width); + maxW = Math.max(maxW, elementDType_width); + var selectedElement_inputWidth = div_width - maxW - 10; + + d3.select("#element_iriEditor").style("width", selectedElement_inputWidth + "px"); + d3.select("#element_labelEditor").style("width", selectedElement_inputWidth + "px"); + d3.select("#typeEditor").style("width", selectedElement_inputWidth + 4 + "px"); + d3.select("#typeEditor_datatype").style("width", selectedElement_inputWidth + 4 + "px"); + + // update prefix Element width; + var containerWidth = d3.select("#containerForPrefixURL").node().getBoundingClientRect().width; + if ( containerWidth !== 0 ) { + var inputs = d3.selectAll(".prefixInput"); + if ( inputs.node() ) { + var prefixWidth = d3.selectAll(".prefixInput").node().getBoundingClientRect().width; + d3.selectAll(".prefixURL").style("width", containerWidth - prefixWidth - 45 + "px"); + } + } + }; + + function addElementsCharacteristics( element ){ + // save selected element for checkbox handler + selectedElementForCharacteristics = element; + var i; + // KILL old elements + var charSelectionNode = d3.select("#property_characteristics_Selection"); + var htmlCollection = charSelectionNode.node().children; + if ( htmlCollection ) { + var numEntries = htmlCollection.length; + for ( var q = 0; q < numEntries; q++ ) { + charSelectionNode.node().removeChild(htmlCollection[0]); + } + } + // datatypes kind of ignored by the elementsNeedCharacteristics function + // so we need to check if we are a node or not + if ( element.attributes().indexOf("external") > -1 ) { + // add external span to the div; + var externalCharSpan = charSelectionNode.append("span"); + externalCharSpan.classed("spanForCharSelection", true); + externalCharSpan.node().innerHTML = "external"; + } + var filterContainer, + filterCheckbox; + if ( elementTools.isNode(element) === true ) { + // add the deprecated characteristic; + var arrayOfNodeChars = ["deprecated"]; + for ( i = 0; i < arrayOfNodeChars.length; i++ ) { + filterContainer = charSelectionNode + .append("div") + .classed("checkboxContainer", true) + .style("padding-top", "2px"); + + filterCheckbox = filterContainer.append("input") + .classed("filterCheckbox", true) + .attr("id", "CharacteristicsCheckbox" + i) + .attr("type", "checkbox") + .attr("characteristics", arrayOfNodeChars[i]) + .property("checked", getPresentAttribute(element, arrayOfNodeChars[i])); + // + filterContainer.append("label") + .attr("for", "CharacteristicsCheckbox" + i) + .text(arrayOfNodeChars[i]); + + filterCheckbox.on("click", handleCheckBoxClick); + + } + } + + else { + // add the deprecated characteristic; + var arrayOfPropertyChars = ["deprecated", "inverse functional", "functional", "transitive"]; + if ( elementTools.isDatatypeProperty(element) === true ) { + arrayOfPropertyChars = ["deprecated", "functional"]; + } + for ( i = 0; i < arrayOfPropertyChars.length; i++ ) { + filterContainer = charSelectionNode + .append("div") + .classed("checkboxContainer", true) + .style("padding-top", "2px"); + + filterCheckbox = filterContainer.append("input") + .classed("filterCheckbox", true) + .attr("id", "CharacteristicsCheckbox" + i) + .attr("type", "checkbox") + .attr("characteristics", arrayOfPropertyChars[i]) + .property("checked", getPresentAttribute(element, arrayOfPropertyChars[i])); + // + filterContainer.append("label") + .attr("for", "CharacteristicsCheckbox" + i) + .text(arrayOfPropertyChars[i]); + + filterCheckbox.on("click", handleCheckBoxClick); + + } + } + + + } + + function getPresentAttribute( selectedElement, element ){ + return (selectedElement.attributes().indexOf(element) >= 0); + } + + function handleCheckBoxClick(){ + var checked = this.checked; + var char = this.getAttribute("characteristics"); + if ( checked === true ) { + addAttribute(selectedElementForCharacteristics, char); + } else { + removeAttribute(selectedElementForCharacteristics, char); + } + // graph.executeColorExternalsModule(); + selectedElementForCharacteristics.redrawElement(); + // workaround to have the node still be focused as rendering element + selectedElementForCharacteristics.focused(false); + selectedElementForCharacteristics.toggleFocus(); + + } + + + function addAttribute( selectedElement, char ){ + if ( selectedElement.attributes().indexOf(char) === -1 ) { + // not found add it + var attr = selectedElement.attributes(); + attr.push(char); + selectedElement.attributes(attr); + }// indications string update; + if ( selectedElement.indications().indexOf(char) === -1 ) { + var indications = selectedElement.indications(); + indications.push(char); + selectedElement.indications(indications); + } + // add visual attributes + var visAttr; + if ( selectedElement.visualAttributes().indexOf(char) === -1 ) { + visAttr = selectedElement.visualAttributes(); + visAttr.push(char); + selectedElement.visualAttributes(visAttr); + } + if ( getPresentAttribute(selectedElement, "external") && getPresentAttribute(selectedElement, "deprecated") ) { + visAttr = selectedElement.visualAttributes(); + var visInd = visAttr.indexOf("external"); + if ( visInd > -1 ) { + visAttr.splice(visInd, 1); + } + selectedElement.visualAttributes(visAttr); + } + + } + + function removeAttribute( selectedElement, element ){ + var attr = selectedElement.attributes(); + var indications = selectedElement.indications(); + var visAttr = selectedElement.visualAttributes(); + var attrInd = attr.indexOf(element); + if ( attrInd >= 0 ) { + attr.splice(attrInd, 1); + } + var indInd = indications.indexOf(element); + if ( indInd > -1 ) { + indications.splice(indInd, 1); + } + var visInd = visAttr.indexOf(element); + if ( visInd > -1 ) { + visAttr.splice(visInd, 1); + } + selectedElement.attributes(attr); + selectedElement.indications(indications); + selectedElement.visualAttributes(visAttr); + if ( element === "deprecated" ) { + // set its to its original Style + //typeBaseThign + // todo : fix all different types + if ( selectedElement.type() === "owl:Class" ) selectedElement.styleClass("class"); + if ( selectedElement.type() === "owl:DatatypeProperty" ) selectedElement.styleClass("datatypeproperty"); + if ( selectedElement.type() === "owl:ObjectProperty" ) selectedElement.styleClass("objectproperty"); + if ( selectedElement.type() === "owl:disjointWith" ) selectedElement.styleClass("disjointwith"); + } + } + + + function elementNeedsCharacteristics( element ){ + //TODO: Add more types + if ( element.type() === "owl:Thing" || + element.type() === "rdfs:subClassOf" || + element.type() === "rdfs:Literal" || + element.type() === "rdfs:Datatype" || + element.type() === "rdfs:disjointWith" ) + return false; + + // if (element.attributes().indexOf("external")|| + // element.attributes().indexOf("deprecated")) + // return true; + return true; + + } + + function elementTypeSelectionChanged( element ){ + if ( elementTools.isNode(element) ) { + if ( graph.changeNodeType(element) === false ) { + //restore old value + + if ( elementTools.isDatatype(element) === true ) { + + } + editSidebar.updateSelectionInformation(element); + } + } + + if ( elementTools.isProperty(element) ) { + if ( graph.changePropertyType(element) === false ) { + //restore old value + editSidebar.updateSelectionInformation(element); + + } + } + + } + + function getElementPrototypes( selectedElement ){ + var availiblePrototypes = []; + // TODO the text should be also complied with the prefixes loaded into the ontology + if ( elementTools.isProperty(selectedElement) ) { + if ( selectedElement.type() === "owl:DatatypeProperty" ) + availiblePrototypes.push("owl:DatatypeProperty"); + else { + availiblePrototypes.push("owl:ObjectProperty"); + // handling loops ! + if ( selectedElement.domain() !== selectedElement.range() ) { + availiblePrototypes.push("rdfs:subClassOf"); + } + availiblePrototypes.push("owl:disjointWith"); + availiblePrototypes.push("owl:allValuesFrom"); + availiblePrototypes.push("owl:someValuesFrom"); + } + return availiblePrototypes; + } + if ( selectedElement.renderType() === "rect" ) { + availiblePrototypes.push("rdfs:Literal"); + availiblePrototypes.push("rdfs:Datatype"); + } else { + availiblePrototypes.push("owl:Class"); + availiblePrototypes.push("owl:Thing"); + // TODO: ADD MORE TYPES + // availiblePrototypes.push("owl:complementOf"); + // availiblePrototypes.push("owl:disjointUnionOf"); + } + return availiblePrototypes; + } + + + function setupCollapsing(){ + // TODO : Decision , for now I want to have the control over the collapse expand operation of the + // TODO : elements, otherwise the old approach will also randomly collapse other containers + + // adapted version of this example: http://www.normansblog.de/simple-jquery-accordion/ + function collapseContainers( containers ){ + containers.classed("hidden", true); + } + + function expandContainers( containers ){ + containers.classed("hidden", false); + } + + var triggers = d3.selectAll(".accordion-trigger"); + + // Collapse all inactive triggers on startup + // collapseContainers(d3.selectAll(".accordion-trigger:not(.accordion-trigger-active) + div")); + + triggers.on("click", function (){ + var selectedTrigger = d3.select(this); + if ( selectedTrigger.classed("accordion-trigger-active") ) { + // Collapse the active (which is also the selected) trigger + collapseContainers(d3.select(selectedTrigger.node().nextElementSibling)); + selectedTrigger.classed("accordion-trigger-active", false); + } else { + // Collapse the other trigger ... + // collapseContainers(d3.selectAll(".accordion-trigger-active + div")); + + // ... and expand the selected one + expandContainers(d3.select(selectedTrigger.node().nextElementSibling)); + selectedTrigger.classed("accordion-trigger-active", true); + } + editSidebar.updateElementWidth(); + }); + } + + return editSidebar; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 341: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( graph ){ + var configMenu = {}, + checkboxes = []; + + + configMenu.setup = function (){ + var menuEntry = d3.select("#m_modes"); + menuEntry.on("mouseover", function (){ + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + }); + + addCheckBox("showZoomSlider", "Zoom controls", "#zoomSliderOption", graph.options().zoomSlider().showSlider, 0); + addLabelWidthSlider("#maxLabelWidthSliderOption", "maxLabelWidth", "Max label width", graph.options().maxLabelWidth); + }; + + + function addLabelWidthSlider( selector, identifier, label, onChangeFunction ){ + var sliderContainer, + sliderValueLabel; + + sliderContainer = d3.select(selector) + .append("div") + .classed("distanceSliderContainer", true); + + var slider = sliderContainer.append("input") + .attr("id", identifier + "Slider") + .attr("type", "range") + .attr("min", 20) + .attr("max", 600) + .attr("value", onChangeFunction()) + .attr("step", 10); + sliderContainer.append("label") + .classed("description", true) + .attr("for", identifier + "Slider") + .attr("id", identifier + "DescriptionLabel") + .text(label); + sliderValueLabel = sliderContainer.append("label") + .classed("value", true) + .attr("for", identifier + "Slider") + .attr("id", identifier + "valueLabel") + .text(onChangeFunction()); + + slider.on("input", function (){ + var value = slider.property("value"); + onChangeFunction(value); + sliderValueLabel.text(value); + if ( graph.options().dynamicLabelWidth() === true ) + graph.animateDynamicLabelWidth(); + }); + + // add wheel event to the slider + slider.on("wheel", function (){ + if ( slider.node().disabled === true ) return; + var wheelEvent = d3.event; + var offset; + if ( wheelEvent.deltaY < 0 ) offset = 10; + if ( wheelEvent.deltaY > 0 ) offset = -10; + var oldVal = parseInt(slider.property("value")); + var newSliderValue = oldVal + offset; + if ( newSliderValue !== oldVal ) { + slider.property("value", newSliderValue); + onChangeFunction(newSliderValue); + slider.on("input")(); // << set text and update the graphStyles + } + d3.event.preventDefault(); + }); + } + + function addCheckBox( identifier, modeName, selector, onChangeFunc, updateLvl ){ + var configOptionContainer = d3.select(selector) + .append("div") + .classed("checkboxContainer", true); + var configCheckbox = configOptionContainer.append("input") + .classed("moduleCheckbox", true) + .attr("id", identifier + "ConfigCheckbox") + .attr("type", "checkbox") + .property("checked", onChangeFunc()); + + + configCheckbox.on("click", function ( silent ){ + var isEnabled = configCheckbox.property("checked"); + onChangeFunc(isEnabled); + if ( silent !== true ) { + // updating graph when silent is false or the parameter is not given. + if ( updateLvl === 1 ) { + graph.lazyRefresh(); + //graph.redrawWithoutForce + } + if ( updateLvl === 2 ) { + graph.update(); + } + + if ( updateLvl === 3 ) { + graph.updateDraggerElements(); + } + } + + }); + checkboxes.push(configCheckbox); + configOptionContainer.append("label") + .attr("for", identifier + "ConfigCheckbox") + .text(modeName); + } + + configMenu.setCheckBoxValue = function ( identifier, value ){ + for ( var i = 0; i < checkboxes.length; i++ ) { + var cbdId = checkboxes[i].attr("id"); + if ( cbdId === identifier ) { + checkboxes[i].property("checked", value); + break; + } + } + }; + + configMenu.getCheckBoxValue = function ( id ){ + for ( var i = 0; i < checkboxes.length; i++ ) { + var cbdId = checkboxes[i].attr("id"); + if ( cbdId === id ) { + return checkboxes[i].property("checked"); + } + } + }; + + configMenu.updateSettings = function (){ + var silent = true; + checkboxes.forEach(function ( checkbox ){ + checkbox.on("click")(silent); + }); + }; + + return configMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 342: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( graph ){ + /** some constants **/ + var PREDEFINED = 0, + FILE_UPLOAD = 1, + JSON_URL = 2, + IRI_URL = 3; + + var PROGRESS_BAR_ERROR = 0, + PROGRESS_BAR_BUSY = 1, + PROGRESS_BAR_PERCENT = 2, + progressBarMode = 1; + + var loadingWasSuccessFul = false; + var missingImportsWarning = false; + var showLoadingDetails = false; + var visibilityStatus = true; + + var DEFAULT_JSON_NAME = "ontology"; // This file is loaded by default + var conversion_sessionId; + + /** variable defs **/ + var loadingModule = {}, + menuContainer = d3.select("#loading-info"), + loadingInfoContainer = d3.select("#loadingInfo-container"), + detailsButton = d3.select("#show-loadingInfo-button"), + closeButton = d3.select("#loadingIndicator_closeButton"), + ontologyMenu, + ontologyIdentifierFromURL; + + /** functon defs **/ + loadingModule.checkForScreenSize = function (){ + // checks for window size and adjusts the loading indicator + var w = graph.options().width(), + h = graph.options().height(); + + if ( w < 270 ) { + d3.select("#loading-info").classed("hidden", true); + } else { + // check if it should be visible + if ( visibilityStatus === true ) { + d3.select("#loading-info").classed("hidden", false); + } else { + d3.select("#loading-info").classed("hidden", true); + } + } + if ( h < 150 ) { + d3.select("#loadingInfo_msgBox").classed("hidden", true); + } else { + d3.select("#loadingInfo_msgBox").classed("hidden", false); + } + if ( h < 80 ) { + d3.select("#progressBarContext").classed("hidden", true); + d3.select("#layoutLoadingProgressBarContainer").style("height", "20px"); + } else { + d3.select("#progressBarContext").classed("hidden", false); + d3.select("#layoutLoadingProgressBarContainer").style("height", "50px"); + } + }; + + loadingModule.getMessageVisibilityStatus = function (){ + return visibilityStatus; + }; + + loadingModule.getProgressBarMode = function (){ + return progressBarMode; + }; + + loadingModule.successfullyLoadedOntology = function (){ + return loadingWasSuccessFul; + }; + + loadingModule.missingImportsWarning = function (){ + return missingImportsWarning; + }; + + loadingModule.setOntologyMenu = function ( m ){ + ontologyMenu = m; + }; + + loadingModule.showErrorDetailsMessage = function (){ + loadingModule.showLoadingIndicator(); + loadingModule.expandDetails(); + d3.select("#loadingIndicator_closeButton").classed("hidden", true); + loadingModule.scrollDownDetails(); + }; + + loadingModule.showWarningDetailsMessage = function (){ + d3.select("#currentLoadingStep").style("color", "#ff0"); + loadingModule.showLoadingIndicator(); + loadingModule.expandDetails(); + d3.select("#loadingIndicator_closeButton").classed("hidden", false); + loadingModule.scrollDownDetails(); + }; + + loadingModule.scrollDownDetails = function (){ + var scrollingElement = d3.select("#loadingInfo-container").node(); + scrollingElement.scrollTop = scrollingElement.scrollHeight; + }; + + loadingModule.hideLoadingIndicator = function (){ + d3.select("#loading-info").classed("hidden", true); + visibilityStatus = false; + }; + + loadingModule.showLoadingIndicator = function (){ + d3.select("#loading-info").classed("hidden", false); + visibilityStatus = true; + + }; + + /** -- SETUP -- **/ + loadingModule.setup = function (){ + // create connections for close and details button; + loadingInfoContainer.classed("hidden", !showLoadingDetails); + detailsButton.on("click", function (){ + showLoadingDetails = !showLoadingDetails; + loadingInfoContainer.classed("hidden", !showLoadingDetails); + detailsButton.classed("accordion-trigger-active", showLoadingDetails); + }); + + closeButton.on("click", function (){ + menuContainer.classed("hidden", true); + }); + loadingModule.setBusyMode(); + }; + + loadingModule.updateSize = function (){ + showLoadingDetails = !(loadingInfoContainer.classed("hidden")); + loadingInfoContainer.classed("hidden", !showLoadingDetails); + detailsButton.classed("accordion-trigger-active", showLoadingDetails); + }; + + loadingModule.getDetailsState = function (){ + return showLoadingDetails; + }; + + loadingModule.expandDetails = function (){ + showLoadingDetails = true; + loadingInfoContainer.classed("hidden", !showLoadingDetails); + detailsButton.classed("accordion-trigger-active", showLoadingDetails); + }; + + loadingModule.collapseDetails = function (){ + showLoadingDetails = false; + loadingInfoContainer.classed("hidden", !showLoadingDetails); + detailsButton.classed("accordion-trigger-active", showLoadingDetails); + }; + + loadingModule.setBusyMode = function (){ + d3.select("#currentLoadingStep").style("color", "#fff"); + d3.select("#progressBarValue").node().innherHTML = ""; + d3.select("#progressBarValue").style("width", "20%"); + d3.select("#progressBarValue").classed("busyProgressBar", true); + progressBarMode = PROGRESS_BAR_BUSY; + }; + + loadingModule.setSuccessful = function (){ + d3.select("#currentLoadingStep").style("color", "#0f0"); + }; + + loadingModule.setErrorMode = function (){ + d3.select("#currentLoadingStep").style("color", "#f00"); + d3.select("#progressBarValue").style("width", "0%"); + d3.select("#progressBarValue").classed("busyProgressBar", false); + d3.select("#progressBarValue").node().innherHTML = ""; + progressBarMode = PROGRESS_BAR_ERROR; + }; + + loadingModule.setPercentMode = function (){ + d3.select("#currentLoadingStep").style("color", "#fff"); + d3.select("#progressBarValue").classed("busyProgressBar", false); + d3.select("#progressBarValue").node().innherHTML = "0%"; + d3.select("#progressBarValue").style("width", "0%"); + progressBarMode = PROGRESS_BAR_PERCENT; + }; + + loadingModule.setPercentValue = function ( val ){ + d3.select("#progressBarValue").node().innherHTML = val; + }; + + loadingModule.emptyGraphContentError = function (){ + graph.clearGraphData(); + ontologyMenu.append_message_toLastBulletPoint("failed"); + ontologyMenu.append_message_toLastBulletPoint("
    Error: Received empty graph"); + loadingWasSuccessFul = false; + graph.handleOnLoadingError(); + loadingModule.setErrorMode(); + }; + + loadingModule.isThreadCanceled = function (){ + + }; + + loadingModule.initializeLoader = function ( storeCache ){ + if ( storeCache === true && graph.getCachedJsonObj() !== null ) { + // save cached ontology; + var cachedContent = JSON.stringify(graph.getCachedJsonObj()); + var cachedName = ontologyIdentifierFromURL; + ontologyMenu.setCachedOntology(cachedName, cachedContent); + } + conversion_sessionId = -10000; + ontologyMenu.setConversionID(conversion_sessionId); + ontologyMenu.stopLoadingTimer(); + graph.clearGraphData(); + loadingModule.setBusyMode(); + loadingModule.showLoadingIndicator(); + loadingModule.collapseDetails(); + missingImportsWarning = false; + d3.select("#loadingIndicator_closeButton").classed("hidden", true); + ontologyMenu.clearDetailInformation(); + }; + + /** ------------------ URL Interpreter -------------- **/ + loadingModule.parseUrlAndLoadOntology = function ( storeCache ){ + var autoStore = true; + if ( storeCache === false ) { + autoStore = false; + } + + graph.clearAllGraphData(); + loadingModule.initializeLoader(autoStore); + var urlString = String(location); + var parameterArray = identifyParameter(urlString); + ontologyIdentifierFromURL = DEFAULT_JSON_NAME; + loadGraphOptions(parameterArray); // identifies and loads configuration values + var loadingMethod = identifyOntologyLoadingMethod(ontologyIdentifierFromURL); + d3.select("#progressBarValue").node().innerHTML = " "; + switch ( loadingMethod ) { + case 0: + loadingModule.from_presetOntology(ontologyIdentifierFromURL); + break; + case 1: + loadingModule.from_FileUpload(ontologyIdentifierFromURL); + break; + case 2: + loadingModule.from_JSON_URL(ontologyIdentifierFromURL); + break; + case 3: + loadingModule.from_IRI_URL(ontologyIdentifierFromURL); + break; + default: + console.log("Could not identify loading method , or not IMPLEMENTED YET"); + } + }; + + /** ------------------- LOADING --------------------- **/ + // the loading module splits into 3 branches + // 1] PresetOntology Loading + // 2] File Upload + // 3] Load From URL / IRI + + loadingModule.from_JSON_URL = function ( fileName ){ + var filename = decodeURIComponent(fileName.slice("url=".length)); + ontologyIdentifierFromURL = filename; + + var ontologyContent = ""; + if ( ontologyMenu.cachedOntology(filename) ) { + ontologyMenu.append_bulletPoint("Loading already cached ontology: " + filename); + ontologyContent = ontologyMenu.cachedOntology(filename); + loadingWasSuccessFul = true; // cached Ontology should be true; + parseOntologyContent(ontologyContent); + + } else { + // involve the o2v conveter; + ontologyMenu.append_message("Retrieving ontology from JSON URL " + filename); + requestServerTimeStampForJSON_URL(ontologyMenu.callbackLoad_JSON_FromURL, ["read?json=" + filename, filename]); + } + }; + + function requestServerTimeStampForJSON_URL( callback, parameter ){ + d3.xhr("serverTimeStamp", "application/text", function ( error, request ){ + if ( error ) { + // could not get server timestamp -> no connection to owl2vowl + ontologyMenu.append_bulletPoint("Could not establish connection to OWL2VOWL service"); + fallbackForJSON_URL(callback, parameter); + } else { + conversion_sessionId = request.responseText; + ontologyMenu.setConversionID(conversion_sessionId); + parameter.push(conversion_sessionId); + callback(parameter); + } + }); + + } + + loadingModule.requestServerTimeStampForDirectInput = function ( callback, text ){ + d3.xhr("serverTimeStamp", "application/text", function ( error, request ){ + if ( error ) { + // could not get server timestamp -> no connection to owl2vowl + ontologyMenu.append_bulletPoint("Could not establish connection to OWL2VOWL service"); + loadingModule.setErrorMode(); + ontologyMenu.append_message_toLastBulletPoint("
    Could not connect to OWL2VOWL service "); + loadingModule.showErrorDetailsMessage(); + d3.select("#progressBarValue").style("width", "0%"); + d3.select("#progressBarValue").classed("busyProgressBar", false); + d3.select("#progressBarValue").text("0%"); + + } else { + conversion_sessionId = request.responseText; + ontologyMenu.setConversionID(conversion_sessionId); + callback(text, ["conversionID" + conversion_sessionId, conversion_sessionId]); + } + }); + }; + + loadingModule.from_IRI_URL = function ( fileName ){ + // owl2vowl converters the given ontology url and returns json file; + var filename = decodeURIComponent(fileName.slice("iri=".length)); + ontologyIdentifierFromURL = filename; + + var ontologyContent = ""; + if ( ontologyMenu.cachedOntology(filename) ) { + ontologyMenu.append_bulletPoint("Loading already cached ontology: " + filename); + ontologyContent = ontologyMenu.cachedOntology(filename); + loadingWasSuccessFul = true; // cached Ontology should be true; + parseOntologyContent(ontologyContent); + } else { + // involve the o2v conveter; + var encoded = encodeURIComponent(filename); + ontologyMenu.append_bulletPoint("Retrieving ontology from IRI: " + filename); + requestServerTimeStampForIRI_Converte(ontologyMenu.callbackLoad_Ontology_FromIRI, ["convert?iri=" + encoded, filename]); + } + }; + + loadingModule.fromFileDrop = function ( fileName, file ){ + d3.select("#progressBarValue").node().innerHTML = " "; + loadingModule.initializeLoader(false); + + ontologyMenu.append_bulletPoint("Retrieving ontology from dropped file: " + fileName); + var ontologyContent = ""; + + // two options here + //1] Direct Json Upload + if ( fileName.match(/\.json$/) ) { + ontologyMenu.setConversionID(-10000); + var reader = new FileReader(); + reader.readAsText(file); + reader.onload = function (){ + ontologyContent = reader.result; + ontologyIdentifierFromURL = fileName; + parseOntologyContent(ontologyContent); + }; + } else { + //2] File Upload to OWL2VOWL Converter + // 1) check if we can get a timeStamp; + var parameterArray = [file, fileName]; + requestServerTimeStamp(ontologyMenu.callbackLoadFromOntology, parameterArray); + } + }; + + + loadingModule.from_FileUpload = function ( fileName ){ + loadingModule.setBusyMode(); + var filename = decodeURIComponent(fileName.slice("file=".length)); + ontologyIdentifierFromURL = filename; + var ontologyContent = ""; + if ( ontologyMenu.cachedOntology(filename) ) { + ontologyMenu.append_bulletPoint("Loading already cached ontology: " + filename); + ontologyContent = ontologyMenu.cachedOntology(filename); + loadingWasSuccessFul = true; // cached Ontology should be true; + parseOntologyContent(ontologyContent); + + } else { + // d3.select("#currentLoadingStep").node().innerHTML="Loading ontology from file "+ filename; + ontologyMenu.append_bulletPoint("Retrieving ontology from file: " + filename); + // get the file + var selectedFile = d3.select("#file-converter-input").property("files")[0]; + // No selection -> this was triggered by the iri. Unequal names -> reuploading another file + if ( !selectedFile || (filename && (filename !== selectedFile.name)) ) { + ontologyMenu.append_message_toLastBulletPoint("
    No cached version of \"" + filename + "\" was found.
    Please reupload the file."); + loadingModule.setErrorMode(); + d3.select("#progressBarValue").classed("busyProgressBar", false); + graph.handleOnLoadingError(); + return; + } else { + filename = selectedFile.name; + } + + + // two options here + //1] Direct Json Upload + if ( filename.match(/\.json$/) ) { + ontologyMenu.setConversionID(-10000); + var reader = new FileReader(); + reader.readAsText(selectedFile); + reader.onload = function (){ + ontologyContent = reader.result; + ontologyIdentifierFromURL = filename; + parseOntologyContent(ontologyContent); + }; + } else { + //2] File Upload to OWL2VOWL Converter + // 1) check if we can get a timeStamp; + var parameterArray = [selectedFile, filename]; + requestServerTimeStamp(ontologyMenu.callbackLoadFromOntology, parameterArray); + } + } + }; + + function fallbackForJSON_URL( callback, parameter ){ + ontologyMenu.append_message_toLastBulletPoint("
    Trying to convert with other communication protocol."); + callback(parameter); + + } + + function fallbackConversion( parameter ){ + ontologyMenu.append_message_toLastBulletPoint("
    Trying to convert with other communication protocol."); + var file = parameter[0]; + var name = parameter[1]; + var formData = new FormData(); + formData.append("ontology", file); + + var xhr = new XMLHttpRequest(); + xhr.open("POST", "convert", true); + var ontologyContent = ""; + xhr.onload = function (){ + if ( xhr.status === 200 ) { + ontologyContent = xhr.responseText; + ontologyMenu.setCachedOntology(name, ontologyContent); + ontologyIdentifierFromURL = name; + missingImportsWarning = true; // using this variable for warnings + ontologyMenu.append_message_toLastBulletPoint("
    Success, but you are using a deprecated OWL2VOWL service!"); + parseOntologyContent(ontologyContent); + } + }; + + // check what this thing is doing; + xhr.onreadystatechange = function (){ + if ( xhr.readyState === 4 && xhr.status === 0 ) { + ontologyMenu.append_message_toLastBulletPoint("
    Old protocol also failed to establish connection to OWL2VOWL service!"); + loadingModule.setErrorMode(); + ontologyMenu.append_bulletPoint("Failed to load ontology"); + ontologyMenu.append_message_toLastBulletPoint("
    Could not connect to OWL2VOWL service "); + loadingModule.showErrorDetailsMessage(); + } + }; + xhr.send(formData); + } + + function requestServerTimeStampForIRI_Converte( callback, parameterArray ){ + d3.xhr("serverTimeStamp", "application/text", function ( error, request ){ + loadingModule.setBusyMode(); + if ( error ) { + // could not get server timestamp -> no connection to owl2vowl + ontologyMenu.append_bulletPoint("Could not establish connection to OWL2VOWL service"); + loadingModule.setErrorMode(); + ontologyMenu.append_bulletPoint("Failed to load ontology"); + ontologyMenu.append_message_toLastBulletPoint("
    Could not connect to OWL2VOWL service "); + loadingModule.showErrorDetailsMessage(); + } else { + conversion_sessionId = request.responseText; + ontologyMenu.setConversionID(conversion_sessionId); + // update paramater for new communication paradigm + parameterArray[0] = parameterArray[0] + "&sessionId=" + conversion_sessionId; + parameterArray.push(conversion_sessionId); + callback(parameterArray); + } + }); + } + + function requestServerTimeStamp( callback, parameterArray ){ + d3.xhr("serverTimeStamp", "application/text", function ( error, request ){ + if ( error ) { + // could not get server timestamp -> no connection to owl2vowl + ontologyMenu.append_bulletPoint("Could not establish connection to OWL2VOWL service"); + fallbackConversion(parameterArray); // tries o2v version0.3.4 communication + } else { + conversion_sessionId = request.responseText; + ontologyMenu.setConversionID(conversion_sessionId); + console.log("Request Session ID:" + conversion_sessionId); + callback(parameterArray[0], parameterArray[1], conversion_sessionId); + } + }); + } + + loadingModule.directInput = function ( text ){ + ontologyMenu.clearDetailInformation(); + parseOntologyContent(text); + }; + + loadingModule.loadFromOWL2VOWL = function ( ontoContent, filename ){ + loadingWasSuccessFul = false; + + var old = d3.select("#bulletPoint_container").node().innerHTML; + if ( old.indexOf("(with warnings)") !== -1 ) { + missingImportsWarning = true; + } + + if ( ontologyMenu.cachedOntology(ontoContent) ) { + ontologyMenu.append_bulletPoint("Loading already cached ontology: " + filename); + parseOntologyContent(ontoContent); + } else { // set parse the ontology content; + parseOntologyContent(ontoContent); + } + }; + + loadingModule.from_presetOntology = function ( selectedOntology ){ + ontologyMenu.append_bulletPoint("Retrieving ontology: " + selectedOntology); + loadPresetOntology(selectedOntology); + }; + + function loadPresetOntology( ontology ){ + // check if already cached in ontology menu? + var f2r; + var loadingNewOntologyForEditor=false; + if ( ontology.indexOf("new_ontology") !== -1 ) { + loadingModule.hideLoadingIndicator(); + graph.showEditorHintIfNeeded(); + f2r = "./data/new_ontology.json"; + loadingNewOntologyForEditor=true; + } + + loadingWasSuccessFul = false; + var ontologyContent = ""; + if ( ontologyMenu.cachedOntology(ontology) ) { + ontologyMenu.append_bulletPoint("Loading already cached ontology: " + ontology); + ontologyContent = ontologyMenu.cachedOntology(ontology); + loadingWasSuccessFul = true; // cached Ontology should be true; + loadingModule.showLoadingIndicator(); + parseOntologyContent(ontologyContent); + + } else { + // read the file name + + var fileToRead = "./data/" + ontology + ".json"; + if ( f2r ) { + fileToRead = f2r; + } // overwrite the newOntology Index + // read file + d3.xhr(fileToRead, "application/json", function ( error, request ){ + var loadingSuccessful = !error; + if ( loadingSuccessful ) { + ontologyContent = request.responseText; + parseOntologyContent(ontologyContent); + } else { + + if (loadingNewOntologyForEditor){ + ontologyContent = '{\n' + + ' "_comment": "Empty ontology for WebVOWL Editor",\n' + + ' "header": {\n' + + ' "languages": [\n' + + ' "en"\n' + + ' ],\n' + + ' "baseIris": [\n' + + ' "http://www.w3.org/2000/01/rdf-schema"\n' + + ' ],\n' + + ' "iri": "http://visualdataweb.org/newOntology/",\n' + + ' "title": {\n' + + ' "en": "New ontology"\n' + + ' },\n' + + ' "description": {\n' + + ' "en": "New ontology description"\n' + + ' }\n' + + ' },\n' + + ' "namespace": [],\n' + + ' "metrics": {\n' + + ' "classCount": 0,\n' + + ' "datatypeCount": 0,\n' + + ' "objectPropertyCount": 0,\n' + + ' "datatypePropertyCount": 0,\n' + + ' "propertyCount": 0,\n' + + ' "nodeCount": 0,\n' + + ' "individualCount": 0\n' + + ' }\n' + + '}\n'; + parseOntologyContent(ontologyContent); + }else{ + // some error occurred + ontologyMenu.append_bulletPoint("Failed to load: " + ontology); + if (error.status===0){ // assumption this is CORS error when running locally (error status == 0) + ontologyMenu.append_message_toLastBulletPoint(" ERROR STATUS: " + error.status); + if (window.location.toString().startsWith("file:/")){ + ontologyMenu.append_message_toLastBulletPoint("

    WebVOWL runs in a local instance.

    "); + ontologyMenu.append_message_toLastBulletPoint("

    CORS prevents to automatically load files on host system.

    "); + ontologyMenu.append_message_toLastBulletPoint("

    You can load preprocessed ontologies (i.e. VOWL-JSON files) using the upload feature in the ontology menu or by dragging the files and dropping them on the canvas.

    "); + ontologyMenu.append_message_toLastBulletPoint("

    Hint: Note that the conversion of ontologies into the VOWL-JSON format is not part of WebVOWL but requires an additional converter such as OWL2VOWL.

    "); + ontologyMenu.append_message_toLastBulletPoint("

    Ontologies can be created using the editor mode (i.e. activate editing mode in Modes menu and create a new ontology using the Ontology menu.

    "); + } + }else { + ontologyMenu.append_message_toLastBulletPoint(" ERROR STATUS: " + error.status); + } + + + + graph.handleOnLoadingError(); + loadingModule.setErrorMode(); + } + } + }); + } + } + + + /** -- PARSE JSON CONTENT -- **/ + function parseOntologyContent( content ){ + + ontologyMenu.append_bulletPoint("Reading ontology graph ... "); + var _loader = ontologyMenu.getLoadingFunction(); + _loader(content, ontologyIdentifierFromURL, "noAlternativeNameYet"); + } + + loadingModule.notValidJsonFile = function (){ + graph.clearGraphData(); + ontologyMenu.append_message_toLastBulletPoint(" failed"); + ontologyMenu.append_message_toLastBulletPoint("
    Error: Received empty graph"); + loadingWasSuccessFul = false; + graph.handleOnLoadingError(); + + }; + + loadingModule.validJsonFile = function (){ + ontologyMenu.append_message_toLastBulletPoint("done"); + loadingWasSuccessFul = true; + }; + + + /** --- HELPER FUNCTIONS **/ + + function identifyParameter( url ){ + var numParameters = (url.match(/#/g) || []).length; + // create parameters array + var paramArray = []; + if ( numParameters > 0 ) { + var tokens = url.split("#"); + // skip the first token since it is the address of the server + for ( var i = 1; i < tokens.length; i++ ) { + if ( tokens[i].length === 0 ) { + // this token belongs actually to the last paramArray + paramArray[paramArray.length - 1] = paramArray[paramArray.length - 1] + "#"; + } else { + paramArray.push(tokens[i]); + } + } + } + return paramArray; + } + + + function loadGraphOptions( parameterArray ){ + var optString = "opts="; + + function loadDefaultConfig(){ + graph.options().setOptionsFromURL(graph.options().defaultConfig(), false); + } + + function loadCustomConfig( opts ){ + var changeEditingFlag = false; + var defObj = graph.options().defaultConfig(); + for ( var i = 0; i < opts.length; i++ ) { + var keyVal = opts[i].split('='); + if ( keyVal[0] === "editorMode" ) { + changeEditingFlag = true; + } + defObj[keyVal[0]] = keyVal[1]; + } + graph.options().setOptionsFromURL(defObj, changeEditingFlag); + } + + function identifyOptions( paramArray ){ + if ( paramArray[0].indexOf(optString) >= 0 ) { + // parse the parameters; + var parameterLength = paramArray[0].length; + var givenOptionsStr = paramArray[0].substr(5, parameterLength - 6); + var optionsArray = givenOptionsStr.split(';'); + loadCustomConfig(optionsArray); + } else { + ontologyIdentifierFromURL = paramArray[0]; + loadDefaultConfig(); + } + } + + function identifyOptionsAndOntology( paramArray ){ + + if ( paramArray[0].indexOf(optString) >= 0 ) { + // parse the parameters; + var parameterLength = paramArray[0].length; + var givenOptionsStr = paramArray[0].substr(5, parameterLength - 6); + var optionsArray = givenOptionsStr.split(';'); + loadCustomConfig(optionsArray); + } else { + loadDefaultConfig(); + } + ontologyIdentifierFromURL = paramArray[1]; + } + + switch ( parameterArray.length ) { + case 0: + loadDefaultConfig(); + break; + case 1: + identifyOptions(parameterArray); + break; + case 2: + identifyOptionsAndOntology(parameterArray); + break; + default : + console.log("To many input parameters , loading default config"); + loadDefaultConfig(); + ontologyIdentifierFromURL = "ERROR_TO_MANY_INPUT_PARAMETERS"; + } + } + + + function identifyOntologyLoadingMethod( url ){ + var iriKey = "iri="; + var urlKey = "url="; + var fileKey = "file="; + + var method = -1; + if ( url.substr(0, fileKey.length) === fileKey ) { + method = FILE_UPLOAD; + } else if ( url.substr(0, urlKey.length) === urlKey ) { + method = JSON_URL; + } else if ( url.substr(0, iriKey.length) === iriKey ) { + method = IRI_URL; + } else { + method = PREDEFINED; + } + return method; + } + + return loadingModule; + } + ; + + + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 343: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( graph ){ + /** variable defs **/ + var warningModule = {}; + var superContainer = d3.select("#WarningErrorMessages"); + var _messageContainers = []; + var _messageContext = []; + var _visibleStatus = []; + + var _filterHintId; + var _editorHintId; + var _messageId = -1; + superContainer.style("display", "inline-block"); + var cssStyleIndex = 0; + var styleSelectorIndex = 2; + + + // helper for standalone webvowl in chrome + function createCSSSelector( name, rules ){ + var style = document.createElement('style'); + style.type = 'text/css'; + document.getElementsByTagName('head')[0].appendChild(style); + if ( !(style.sheet || {}).insertRule ) + (style.styleSheet || style.sheet).addRule(name, rules); + else + style.sheet.insertRule(name + "{" + rules + "}", 0); + } + + + function findCSS_Index(){ + createCSSSelector("@keyframes msg_CollapseAnimation", " 0% { top: 0; } 100% { top: -400px;}"); + console.log(document.styleSheets ); + } + + findCSS_Index(); + + warningModule.addMessageBox = function (){ + + // add a container; + _messageId++; + var messageContainer = d3.select("#WarningErrorMessages").append("div"); + messageContainer.node().id = "messageContainerId_" + _messageId; + + var messageContext = messageContainer.append("div"); + messageContext.node().id = "messageContextId_" + _messageId; + messageContext.style("top", "0"); + messageContainer.style("position", "relative"); + messageContainer.style("width", "100%"); + //save in array + _messageContainers.push(messageContainer); + _messageContext.push(messageContext); + + // add animation to the container + messageContainer.node().addEventListener("animationend", _msgContainer_animationEnd); + + // set visible flag that is used in end of animation + _visibleStatus[_messageId] = true; + return _messageId; + }; + + function _msgContainer_animationEnd(){ + var containerId = this.id; + var tokens = containerId.split("_")[1]; + var mContainer = d3.select("#" + containerId); + // get number of children + mContainer.classed("hidden", !_visibleStatus[tokens]); + // clean up DOM + if ( !_visibleStatus[tokens] ) { + mContainer.remove(); + _messageContext[tokens] = null; + _messageContainers[tokens] = null; + } + // remove event listener + var c = d3.select(this); + // c.node().removeEventListener("animationend",_msgContainer_animationEnd); + } + + warningModule.createMessageContext = function ( id ){ + var warningContainer = _messageContext[id]; + var moduleContainer = _messageContainers[id]; + var generalHint = warningContainer.append('div'); + generalHint.node().innerHTML = ""; + _editorHintId = id; + /** Editing mode activated. You can now modify an existing ontology or create a new one via the ontology menu. You can save any ontology using the export menu (and exporting it as TTL file).**/ + generalHint.node().innerHTML += "Editing mode activated.
    " + + "You can now modify an existing ontology or create a new one via the ontology menu.
    " + + "You can save any ontology using the export menu (and exporting it as TTL file)."; + + generalHint.style("padding", "5px"); + generalHint.style("line-height", "1.2em"); + generalHint.style("font-size", "1.2em"); + + + var ul = warningContainer.append('ul'); + ul.append('li').node().innerHTML = "Create a class with double click / tap on empty canvas area."; + ul.append('li').node().innerHTML = "Edit names with double click / tap on element."; + ul.append('li').node().innerHTML = "Selection of default constructors is provided in the left sidebar."; + ul.append('li').node().innerHTML = "Additional editing functionality is provided in the right sidebar."; + + + var gotItButton = warningContainer.append("label"); + gotItButton.node().id = "killWarningErrorMessages_" + id; + gotItButton.node().innerHTML = "Got It"; + gotItButton.on("click", warningModule.closeMessage); + + moduleContainer.classed("hidden", false); + moduleContainer.style("-webkit-animation-name", "warn_ExpandAnimation"); + moduleContainer.style("-webkit-animation-duration", "0.5s"); + }; + + warningModule.showMessage = function ( id ){ + var moduleContainer = _messageContainers[id]; + moduleContainer.classed("hidden", false); + moduleContainer.style("-webkit-animation-name", "warn_ExpandAnimation"); + moduleContainer.style("-webkit-animation-duration", "0.5s"); + }; + + warningModule.closeMessage = function ( id ){ + var nId; + if ( id === undefined ) { + var givenId = this.id; + nId = givenId.split("_")[1]; + } else { + nId = id; + } + if ( id && id.indexOf("_") !== -1 ) { + nId = id.split("_")[1]; + } + _visibleStatus[nId] = false; + // get module; + var moduleContainer = _messageContainers[nId]; + moduleContainer.style("-webkit-animation-name", "warn_CollapseAnimation"); + moduleContainer.style("-webkit-animation-duration", "0.5s"); + + var m_height = moduleContainer.node().getBoundingClientRect().height; + + // find my id in the children + var pNode = moduleContainer.node().parentNode; + + var followingChildren = []; + var pChild = pNode.children; + var pChild_len = pChild.length; + var containerId = moduleContainer.node().id; + var found_me = false; + for ( var i = 0; i < pChild_len; i++ ) { + if ( found_me === true ) { + followingChildren.push(pChild[i].id); + } + + if ( containerId === pChild[i].id ) { + found_me = true; + } + } + + for ( var fc = 0; fc < followingChildren.length; fc++ ) { + var child = d3.select("#" + followingChildren[fc]); + // get the document style and overwrite it; + var superCss = document.styleSheets[styleSelectorIndex].cssRules[cssStyleIndex]; + // remove the existing 0% and 100% rules + superCss.deleteRule("0%"); + superCss.deleteRule("100%"); + + superCss.appendRule("0% {top: 0;}"); + superCss.appendRule("100% {top: -" + m_height + "px;"); + + child.style("-webkit-animation-name", "msg_CollapseAnimation"); + child.style("-webkit-animation-duration", "0.5s"); + child.node().addEventListener("animationend", _child_animationEnd); + } + }; + + function _child_animationEnd(){ + var c = d3.select(this); + c.style("-webkit-animation-name", ""); + c.style("-webkit-animation-duration", ""); + c.node().removeEventListener("animationend", _child_animationEnd); + } + + warningModule.closeFilterHint = function (){ + if ( _messageContainers[_filterHintId] ) { + _messageContainers[_filterHintId].classed("hidden", true); + _messageContainers[_filterHintId].remove(); + _messageContainers[_filterHintId] = null; + _messageContext[_filterHintId] = null; + _visibleStatus[_filterHintId] = false; + } + }; + + warningModule.showEditorHint = function (){ + var id = warningModule.addMessageBox(); + warningModule.createMessageContext(id); + }; + + warningModule.showExporterWarning=function (){ + warningModule.showWarning("Can not export ontology", "Detected unsupported ontology axioms, (e.g. owl:Union)", "Ontology is not exported", 1, false); + }; + + + + warningModule.responseWarning = function ( header, reason, action, callback, parameterArray, forcedWarning ){ + var id = warningModule.addMessageBox(); + var warningContainer = _messageContext[id]; + var moduleContainer = _messageContainers[id]; + _visibleStatus[id] = true; + d3.select("#blockGraphInteractions").classed("hidden", false); + var graphWidth = 0.5 * graph.options().width(); + + if ( header.length > 0 ) { + var head = warningContainer.append("div"); + head.style("padding", "5px"); + var titleHeader = head.append("div"); + // some classes + titleHeader.style("display", "inline-flex"); + titleHeader.node().innerHTML = "Warning:"; + titleHeader.style("padding-right", "3px"); + var msgHeader = head.append("div"); + // some classes + msgHeader.style("display", "inline-flex"); + msgHeader.style("max-width", graphWidth + "px"); + + msgHeader.node().innerHTML = header; + } + if ( reason.length > 0 ) { + var reasonContainer = warningContainer.append("div"); + reasonContainer.style("padding", "5px"); + var reasonHeader = reasonContainer.append("div"); + // some classes + reasonHeader.style("display", "inline-flex"); + reasonHeader.style("padding-right", "3px"); + + reasonHeader.node().innerHTML = "Reason:"; + var msgReason = reasonContainer.append("div"); + // some classes + msgReason.style("display", "inline-flex"); + msgReason.style("max-width", graphWidth + "px"); + msgReason.node().innerHTML = reason; + } + if ( action.length > 0 ) { + var actionContainer = warningContainer.append("div"); + actionContainer.style("padding", "5px"); + var actionHeader = actionContainer.append("div"); + // some classes + actionHeader.style("display", "inline-flex"); + actionHeader.style("padding-right", "8px"); + actionHeader.node().innerHTML = "Action:"; + var msgAction = actionContainer.append("div"); + // some classes + msgAction.style("display", "inline-flex"); + msgAction.style("max-width", graphWidth + "px"); + msgAction.node().innerHTML = action; + } + + var gotItButton = warningContainer.append("label"); + gotItButton.node().id = "killWarningErrorMessages_" + id; + gotItButton.node().innerHTML = "Continue"; + gotItButton.on("click", function (){ + warningModule.closeMessage(this.id); + d3.select("#blockGraphInteractions").classed("hidden", true); + callback(parameterArray[0], parameterArray[1], parameterArray[2], parameterArray[3]); + }); + warningContainer.append("span").node().innerHTML = "|"; + var cancelButton = warningContainer.append("label"); + cancelButton.node().id = "cancelButton_" + id; + cancelButton.node().innerHTML = "Cancel"; + cancelButton.on("click", function (){ + warningModule.closeMessage(this.id); + d3.select("#blockGraphInteractions").classed("hidden", true); + }); + moduleContainer.classed("hidden", false); + moduleContainer.style("-webkit-animation-name", "warn_ExpandAnimation"); + moduleContainer.style("-webkit-animation-duration", "0.5s"); + }; + + warningModule.showFilterHint = function (){ + var id = warningModule.addMessageBox(); + var warningContainer = _messageContext[id]; + var moduleContainer = _messageContainers[id]; + _visibleStatus[id] = true; + + _filterHintId = id; + var generalHint = warningContainer.append('div'); + /** Editing mode activated. You can now modify an existing ontology or create a new one via the ontology menu. You can save any ontology using the export menu (and exporting it as TTL file).**/ + generalHint.node().innerHTML = "Collapsing filter activated.
    " + + "The number of visualized elements has been automatically reduced.
    " + + "Use the degree of collapsing slider in the filter menu to adjust the visualization.

    " + + "Note: A performance decrease could be experienced with a growing amount of visual elements in the graph."; + + + generalHint.style("padding", "5px"); + generalHint.style("line-height", "1.2em"); + generalHint.style("font-size", "1.2em"); + + var gotItButton = warningContainer.append("label"); + gotItButton.node().id = "killFilterMessages_" + id; + gotItButton.node().innerHTML = "Got It"; + gotItButton.on("click", warningModule.closeMessage); + + moduleContainer.classed("hidden", false); + moduleContainer.style("-webkit-animation-name", "warn_ExpandAnimation"); + moduleContainer.style("-webkit-animation-duration", "0.5s"); + }; + + warningModule.showMultiFileUploadWarning = function (){ + var id = warningModule.addMessageBox(); + var warningContainer = _messageContext[id]; + var moduleContainer = _messageContainers[id]; + _visibleStatus[id] = true; + + _filterHintId = id; + var generalHint = warningContainer.append('div'); + + generalHint.node().innerHTML = "Uploading multiple files is not supported.
    "; + + generalHint.style("padding", "5px"); + generalHint.style("line-height", "1.2em"); + generalHint.style("font-size", "1.2em"); + + var gotItButton = warningContainer.append("label"); + gotItButton.node().id = "killFilterMessages_" + id; + gotItButton.node().innerHTML = "Got It"; + gotItButton.on("click", warningModule.closeMessage); + + moduleContainer.classed("hidden", false); + moduleContainer.style("-webkit-animation-name", "warn_ExpandAnimation"); + moduleContainer.style("-webkit-animation-duration", "0.5s"); + }; + + warningModule.showWarning = function ( header, reason, action, type, forcedWarning, additionalOpts ){ + var id = warningModule.addMessageBox(); + var warningContainer = _messageContext[id]; + var moduleContainer = _messageContainers[id]; + _visibleStatus[id] = true; + + // add new one; + var graphWidth = 0.5 * graph.options().width(); + + if ( header.length > 0 ) { + var head = warningContainer.append("div"); + head.style("padding", "5px"); + var titleHeader = head.append("div"); + // some classes + titleHeader.style("display", "inline-flex"); + titleHeader.node().innerHTML = "Warning:"; + titleHeader.style("padding-right", "3px"); + var msgHeader = head.append("div"); + // some classes + msgHeader.style("display", "inline-flex"); + msgHeader.style("max-width", graphWidth + "px"); + + msgHeader.node().innerHTML = header; + } + if ( reason.length > 0 ) { + var reasonContainer = warningContainer.append("div"); + reasonContainer.style("padding", "5px"); + var reasonHeader = reasonContainer.append("div"); + // some classes + reasonHeader.style("display", "inline-flex"); + reasonHeader.style("padding-right", "3px"); + + reasonHeader.node().innerHTML = "Reason:"; + var msgReason = reasonContainer.append("div"); + // some classes + msgReason.style("display", "inline-flex"); + msgReason.style("max-width", graphWidth + "px"); + msgReason.node().innerHTML = reason; + } + if ( action.length > 0 ) { + var actionContainer = warningContainer.append("div"); + actionContainer.style("padding", "5px"); + var actionHeader = actionContainer.append("div"); + // some classes + actionHeader.style("display", "inline-flex"); + actionHeader.style("padding-right", "8px"); + actionHeader.node().innerHTML = "Action:"; + var msgAction = actionContainer.append("div"); + // some classes + msgAction.style("display", "inline-flex"); + msgAction.style("max-width", graphWidth + "px"); + msgAction.node().innerHTML = action; + } + + var gotItButton; + if ( type === 1 ) { + gotItButton = warningContainer.append("label"); + gotItButton.node().id = "killWarningErrorMessages_" + id; + gotItButton.node().innerHTML = "Got It"; + gotItButton.on("click", warningModule.closeMessage); + } + + if ( type === 2 ) { + gotItButton = warningContainer.append("label"); + gotItButton.node().id = "killWarningErrorMessages_" + id; + gotItButton.node().innerHTML = "Got It"; + gotItButton.on("click", warningModule.closeMessage); + warningContainer.append("span").node().innerHTML = "|"; + var zoomToElementButton = warningContainer.append("label"); + zoomToElementButton.node().id = "zoomElementThing_" + id; + zoomToElementButton.node().innerHTML = "Zoom to element "; + zoomToElementButton.on("click", function (){ + // assume the additional Element is for halo; + graph.zoomToElementInGraph(additionalOpts); + }); + warningContainer.append("span").node().innerHTML = "|"; + var ShowElementButton = warningContainer.append("label"); + ShowElementButton.node().id = "showElementThing_" + id; + ShowElementButton.node().innerHTML = "Indicate element"; + ShowElementButton.on("click", function (){ + // assume the additional Element is for halo; + if ( additionalOpts.halo() === false ) { + additionalOpts.drawHalo(); + graph.updatePulseIds([additionalOpts.id()]); + } else { + additionalOpts.removeHalo(); + additionalOpts.drawHalo(); + graph.updatePulseIds([additionalOpts.id()]); + } + }); + } + moduleContainer.classed("hidden", false); + moduleContainer.style("-webkit-animation-name", "warn_ExpandAnimation"); + moduleContainer.style("-webkit-animation-duration", "0.5s"); + moduleContainer.classed("hidden", false); + }; + + return warningModule; + }; + + + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 344: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( graph ){ + /** variable defs **/ + var directInputModule = {}; + var inputContainer = d3.select("#DirectInputContent"); + inputContainer.style("top", "0"); + inputContainer.style("position", "absolute"); + var textArea = d3.select("#directInputTextArea"); + var visibleContainer = false; + + inputContainer.style("border", "1px solid black"); + inputContainer.style("padding", "5px"); + inputContainer.style("background", "#fff"); + + + // connect upload and close button; + directInputModule.handleDirectUpload = function (){ + + var text = textArea.node().value; + var jsonOBJ; + try { + jsonOBJ = JSON.parse(text); + graph.options().loadingModule().directInput(text); + // close if successful + if ( jsonOBJ.class.length > 0 ) { + directInputModule.setDirectInputMode(false); + } + } + catch ( e ) { + try { + // Initialize; + graph.options().loadingModule().initializeLoader(); + graph.options().loadingModule().requestServerTimeStampForDirectInput( + graph.options().ontologyMenu().callbackLoad_Ontology_From_DirectInput, text + ); + } catch ( error2 ) { + console.log("Error " + error2); + d3.select("#Error_onLoad").classed("hidden", false); + d3.select("#Error_onLoad").node().innerHTML = "Failed to convert the input!"; + } + } + }; + + directInputModule.handleCloseButton = function (){ + directInputModule.setDirectInputMode(false); + }; + + directInputModule.updateLayout = function (){ + var w = graph.options().width(); + var h = graph.options().height(); + textArea.style("width", 0.4 * w + "px"); + textArea.style("height", 0.7 * h + "px"); + }; + + directInputModule.setDirectInputMode = function ( val ){ + if ( !val ) { + visibleContainer = !visibleContainer; + } + else { + visibleContainer = val; + } + // update visibility; + directInputModule.updateLayout(); + d3.select("#Error_onLoad").classed("hidden", true); + inputContainer.classed("hidden", !visibleContainer); + }; + + + d3.select("#directUploadBtn").on("click", directInputModule.handleDirectUpload); + d3.select("#close_directUploadBtn").on("click", directInputModule.handleCloseButton); + + return directInputModule; + }; + + + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }) + +/******/ }); diff --git a/doc/releases/0.1.0/data/webvowl/js/webvowl.js b/doc/releases/0.1.0/data/webvowl/js/webvowl.js new file mode 100644 index 0000000..1aba35e --- /dev/null +++ b/doc/releases/0.1.0/data/webvowl/js/webvowl.js @@ -0,0 +1,25345 @@ +webvowl = +/******/ (function(modules) { // webpackBootstrap +/******/ // The module cache +/******/ var installedModules = {}; + +/******/ // The require function +/******/ function __webpack_require__(moduleId) { + +/******/ // Check if module is in cache +/******/ if(installedModules[moduleId]) +/******/ return installedModules[moduleId].exports; + +/******/ // Create a new module (and put it into the cache) +/******/ var module = installedModules[moduleId] = { +/******/ exports: {}, +/******/ id: moduleId, +/******/ loaded: false +/******/ }; + +/******/ // Execute the module function +/******/ modules[moduleId].call(module.exports, module, module.exports, __webpack_require__); + +/******/ // Flag the module as loaded +/******/ module.loaded = true; + +/******/ // Return the exports of the module +/******/ return module.exports; +/******/ } + + +/******/ // expose the modules object (__webpack_modules__) +/******/ __webpack_require__.m = modules; + +/******/ // expose the module cache +/******/ __webpack_require__.c = installedModules; + +/******/ // __webpack_public_path__ +/******/ __webpack_require__.p = ""; + +/******/ // Load entry module and return exports +/******/ return __webpack_require__(0); +/******/ }) +/************************************************************************/ +/******/ ([ +/* 0 */ +/***/ (function(module, exports, __webpack_require__) { + + __webpack_require__(1); + + var nodeMap = __webpack_require__(5)(); + var propertyMap = __webpack_require__(40)(); + + + var webvowl = {}; + webvowl.graph = __webpack_require__(57); + webvowl.options = __webpack_require__(64); + webvowl.version = "1.1.7"; + + webvowl.util = {}; + webvowl.util.constants = __webpack_require__(12); + webvowl.util.languageTools = __webpack_require__(11); + webvowl.util.elementTools = __webpack_require__(63); + webvowl.util.prefixTools = __webpack_require__(72); + webvowl.modules = {}; + webvowl.modules.colorExternalsSwitch = __webpack_require__(73); + webvowl.modules.compactNotationSwitch = __webpack_require__(74); + webvowl.modules.datatypeFilter = __webpack_require__(75); + webvowl.modules.disjointFilter = __webpack_require__(77); + webvowl.modules.focuser = __webpack_require__(78); + webvowl.modules.emptyLiteralFilter = __webpack_require__(79); + webvowl.modules.nodeDegreeFilter = __webpack_require__(80); + webvowl.modules.nodeScalingSwitch = __webpack_require__(81); + webvowl.modules.objectPropertyFilter = __webpack_require__(82); + webvowl.modules.pickAndPin = __webpack_require__(83); + webvowl.modules.selectionDetailsDisplayer = __webpack_require__(315); + webvowl.modules.setOperatorFilter = __webpack_require__(316); + webvowl.modules.statistics = __webpack_require__(317); + webvowl.modules.subclassFilter = __webpack_require__(318); + + + webvowl.nodes = {}; + nodeMap.entries().forEach(function ( entry ){ + mapEntryToIdentifier(webvowl.nodes, entry); + }); + + webvowl.properties = {}; + propertyMap.entries().forEach(function ( entry ){ + mapEntryToIdentifier(webvowl.properties, entry); + }); + + function mapEntryToIdentifier( map, entry ){ + var identifier = entry.key.replace(":", "").toLowerCase(); + map[identifier] = entry.value; + } + + + module.exports = webvowl; + + +/***/ }), +/* 1 */ +/***/ (function(module, exports) { + + // removed by extract-text-webpack-plugin + +/***/ }), +/* 2 */, +/* 3 */, +/* 4 */, +/* 5 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var nodes = []; + nodes.push(__webpack_require__(7)); + nodes.push(__webpack_require__(18)); + nodes.push(__webpack_require__(19)); + nodes.push(__webpack_require__(26)); + nodes.push(__webpack_require__(27)); + nodes.push(__webpack_require__(28)); + nodes.push(__webpack_require__(29)); + nodes.push(__webpack_require__(30)); + nodes.push(__webpack_require__(31)); + nodes.push(__webpack_require__(32)); + nodes.push(__webpack_require__(33)); + nodes.push(__webpack_require__(34)); + nodes.push(__webpack_require__(38)); + nodes.push(__webpack_require__(39)); + + var map = d3.map(nodes, function ( Prototype ){ + return new Prototype().type(); + }); + + module.exports = function (){ + return map; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 6 */ +/***/ (function(module, exports) { + + module.exports = d3; + +/***/ }), +/* 7 */ +/***/ (function(module, exports, __webpack_require__) { + + var RoundNode = __webpack_require__(8); + + module.exports = (function (){ + + var o = function ( graph ){ + RoundNode.apply(this, arguments); + + this.attributes(["external"]) + .type("ExternalClass"); + }; + o.prototype = Object.create(RoundNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 8 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseNode = __webpack_require__(9); + var CenteringTextElement = __webpack_require__(14); + var drawTools = __webpack_require__(17)(); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseNode.apply(this, arguments); + + var that = this, + collapsible = false, + radius = 50, + collapsingGroupElement, + pinGroupElement, + haloGroupElement = null, + rectangularRepresentation = false, + renderingElement, + textBlock; + + this.setRectangularRepresentation = function ( val ){ + rectangularRepresentation = val; + }; + this.getRectangularRepresentation = function (){ + return rectangularRepresentation; + }; + + this.getHalos = function (){ + return haloGroupElement; + }; + + // Properties + this.collapsible = function ( p ){ + if ( !arguments.length ) return collapsible; + collapsible = p; + return this; + }; + + this.textBlock = function ( p ){ + if ( !arguments.length ) return textBlock; + textBlock = p; + return this; + }; + + /** + * This might not be equal to the actual radius, because the instance count is used for its calculation. + * @param p + * @returns {*} + */ + this.radius = function ( p ){ + if ( !arguments.length ) return radius; + radius = p; + return this; + }; + + + // Functions + this.setHoverHighlighting = function ( enable ){ + that.nodeElement().selectAll("circle").classed("hovered", enable); + }; + + this.textWidth = function ( yOffset ){ + var availableWidth = this.actualRadius() * 2; + + // if the text is not placed in the center of the circle, it can't have the full width + if ( yOffset ) { + var relativeOffset = Math.abs(yOffset) / this.actualRadius(); + var isOffsetInsideOfNode = relativeOffset <= 1; + + if ( isOffsetInsideOfNode ) { + availableWidth = Math.cos(relativeOffset) * availableWidth; + } else { + availableWidth = 0; + } + } + + return availableWidth; + }; + + this.toggleFocus = function (){ + that.focused(!that.focused()); + if ( that.nodeElement() ) + that.nodeElement().select("circle").classed("focused", that.focused()); + graph.resetSearchHighlight(); + graph.options().searchMenu().clearText(); + + }; + + this.actualRadius = function (){ + if ( !graph.options().scaleNodesByIndividuals() || that.individuals().length <= 0 ) { + return that.radius(); + } else { + // we could "listen" for radius and maxIndividualCount changes, but this is easier + var MULTIPLIER = 8, + additionalRadius = Math.log(that.individuals().length + 1) * MULTIPLIER + 5; + + return that.radius() + additionalRadius; + } + }; + + this.distanceToBorder = function (){ + return that.actualRadius(); + }; + + this.removeHalo = function (){ + if ( that.halo() ) { + that.halo(false); + if ( haloGroupElement ) { + haloGroupElement.remove(); + } + } + }; + + this.drawHalo = function ( pulseAnimation ){ + that.halo(true); + if ( rectangularRepresentation === true ) { + haloGroupElement = drawTools.drawRectHalo(that.nodeElement(), 80, 80, 5); + } else { + haloGroupElement = drawTools.drawHalo(that.nodeElement(), that.actualRadius(), this.removeHalo); + } + if ( pulseAnimation === false ) { + var pulseItem = haloGroupElement.selectAll(".searchResultA"); + pulseItem.classed("searchResultA", false); + pulseItem.classed("searchResultB", true); + pulseItem.attr("animationRunning", false); + } + }; + + /** + * Draws the pin on a round node on a position depending on its radius. + */ + this.drawPin = function (){ + that.pinned(true); + var dx = (-3.5 / 5) * that.actualRadius(), + dy = (-7 / 10) * that.actualRadius(); + pinGroupElement = drawTools.drawPin(that.nodeElement(), dx, dy, this.removePin, graph.options().showDraggerObject, graph.options().useAccuracyHelper()); + + + }; + + /** + * Removes the pin and refreshs the graph to update the force layout. + */ + this.removePin = function (){ + that.pinned(false); + if ( pinGroupElement ) { + pinGroupElement.remove(); + } + graph.updateStyle(); + }; + + this.drawCollapsingButton = function (){ + + collapsingGroupElement = that.nodeElement() + .append("g") + .classed("hidden-in-export", true) + .attr("transform", function (){ + var dx = (-2 / 5) * that.actualRadius(), + dy = (1 / 2) * that.actualRadius(); + return "translate(" + dx + "," + dy + ")"; + }); + + collapsingGroupElement.append("rect") + .classed("class pin feature", true) + .attr("x", 0) + .attr("y", 0) + .attr("width", 40) + .attr("height", 24); + + collapsingGroupElement.append("line") + .attr("x1", 13) + .attr("y1", 12) + .attr("x2", 27) + .attr("y2", 12); + + collapsingGroupElement.append("line") + .attr("x1", 20) + .attr("y1", 6) + .attr("x2", 20) + .attr("y2", 18); + }; + + /** + * Draws a circular node. + * @param parentElement the element to which this node will be appended + * @param [additionalCssClasses] additional css classes + */ + this.draw = function ( parentElement, additionalCssClasses ){ + var cssClasses = that.collectCssClasses(); + that.nodeElement(parentElement); + + var bgColor = that.backgroundColor(); + if ( bgColor === null ) bgColor = undefined; + if ( that.attributes().indexOf("deprecated") > -1 ) { + bgColor = undefined; + } + if ( additionalCssClasses instanceof Array ) { + cssClasses = cssClasses.concat(additionalCssClasses); + } + if ( rectangularRepresentation === true ) { + renderingElement = drawTools.appendRectangularClass(parentElement, 80, 80, cssClasses, that.labelForCurrentLanguage(), bgColor); + } else { + renderingElement = drawTools.appendCircularClass(parentElement, that.actualRadius(), cssClasses, that.labelForCurrentLanguage(), bgColor); + } + that.postDrawActions(parentElement); + }; + + this.redrawElement = function (){ + renderingElement.remove(); + textBlock.remove(); + var bgColor = that.backgroundColor(); + if ( that.attributes().indexOf("deprecated") > -1 ) { + bgColor = undefined; + } + + var cssClasses = that.collectCssClasses(); + + if ( rectangularRepresentation === true ) { + renderingElement = drawTools.appendRectangularClass(that.nodeElement(), 80, 80, cssClasses, that.labelForCurrentLanguage(), bgColor); + } else { + renderingElement = drawTools.appendCircularClass(that.nodeElement(), that.actualRadius(), cssClasses, that.labelForCurrentLanguage(), bgColor); + } + that.postDrawActions(that.nodeElement()); + }; + /** + * Common actions that should be invoked after drawing a node. + */ + this.postDrawActions = function (){ + that.textBlock(createTextBlock()); + + that.addMouseListeners(); + if ( that.pinned() ) { + that.drawPin(); + } + if ( that.halo() ) { + that.drawHalo(false); + } + if ( that.collapsible() ) { + that.drawCollapsingButton(); + } + }; + + this.redrawLabelText = function (){ + that.textBlock().remove(); + that.textBlock(createTextBlock()); + renderingElement.select("title").text(that.labelForCurrentLanguage()); + }; + function createTextBlock(){ + var bgColor = that.backgroundColor(); + if ( that.attributes().indexOf("deprecated") > -1 ) + bgColor = undefined; + + var textBlock = new CenteringTextElement(that.nodeElement(), bgColor); + + var equivalentsString = that.equivalentsString(); + var suffixForFollowingEquivalents = equivalentsString ? "," : ""; + + textBlock.addText(that.labelForCurrentLanguage(), "", suffixForFollowingEquivalents); + textBlock.addEquivalents(equivalentsString); + if ( !graph.options().compactNotation() ) { + textBlock.addSubText(that.indicationString()); + } + textBlock.addInstanceCount(that.individuals().length); + + return textBlock; + } + + this.equivalentsString = function (){ + var equivalentClasses = that.equivalents(); + if ( !equivalentClasses ) { + return; + } + + return equivalentClasses + .map(function ( node ){ + return node.labelForCurrentLanguage(); + }) + .join(", "); + }; + }; + o.prototype = Object.create(BaseNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 9 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var BaseElement = __webpack_require__(10); + var forceLayoutNodeFunctions = __webpack_require__(13)(); + + module.exports = (function (){ + + var Base = function ( graph ){ + BaseElement.apply(this, arguments); + + var that = this, + // Basic attributes + complement, + disjointUnion, + disjointWith, + individuals = [], + intersection, + union, + links, + rendertype = "round", + // Additional attributes + maxIndividualCount, + fobj, // foreigner object for editing + ignoreLocalHoverEvents = false, + backupFullIri, + // Element containers + nodeElement; + + // array to store my properties; // we will need this also later for semantic zooming stuff + var assignedProperties = []; + that.editingTextElement = false; + + this.isPropertyAssignedToThisElement = function ( property ){ + // this goes via IRIS + console.log("Element IRI :" + property.iri()); + if ( property.type() === "rdfs:subClassOf" ) + for ( var i = 0; i < assignedProperties.length; i++ ) { + var iriEl = assignedProperties[i].iri(); + if ( property.iri() === iriEl ) { + return true; + } + if ( property.type() === "rdfs:subClassOf" && assignedProperties[i].type() === "rdfs:subClassOf" ) + return true; + if ( property.type() === "owl:disjointWith" && assignedProperties[i].type() === "owl:disjointWith" ) + return true; + + } + return false; + }; + + + this.existingPropertyIRI = function ( url ){ + // this goes via IRIS + for ( var i = 0; i < assignedProperties.length; i++ ) { + var iriEl = assignedProperties[i].iri(); + if ( iriEl === url ) { + return true; + } + } + return false; + }; + + this.addProperty = function ( property ){ + if ( assignedProperties.indexOf(property) === -1 ) { + assignedProperties.push(property); + } + }; + + this.removePropertyElement = function ( property ){ + // console.log("Calling removing old property!"+ property.iri()); + if ( assignedProperties.indexOf(property) !== -1 ) { + // console.log("Found it!"); + assignedProperties.splice(assignedProperties.indexOf(property), 1); + } + }; + this.getMyProperties = function (){ + return assignedProperties; + }; + this.copyOtherProperties = function ( otherProperties ){ + assignedProperties = otherProperties; + }; + + this.copyInformation = function ( other ){ + console.log(other.labelForCurrentLanguage()); + if ( other.type() !== "owl:Thing" ) + that.label(other.label()); + that.complement(other.complement()); + that.iri(other.iri()); + that.copyOtherProperties(other.getMyProperties()); + that.baseIri(other.baseIri()); + if ( other.type() === "owl:Class" ) { + that.backupLabel(other.label()); + // console.log("copied backup label"+that.backupLabel()); + } + if ( other.backupLabel() !== undefined ) { + that.backupLabel(other.backupLabel()); + } + }; + + this.enableEditing = function ( autoEditing ){ + if ( autoEditing === false ) + return; + that.raiseDoubleClickEdit(true); + }; + + this.raiseDoubleClickEdit = function ( forceIRISync ){ + d3.selectAll(".foreignelements").remove(); + if ( nodeElement === undefined || this.type() === "owl:Thing" || this.type() === "rdfs:Literal" ) { + console.log("No Container found"); + return; + } + if ( fobj !== undefined ) { + nodeElement.selectAll(".foreignelements").remove(); + } + + backupFullIri = undefined; + graph.options().focuserModule().handle(undefined); + graph.options().focuserModule().handle(that); + // add again the editing elements to that one + if ( graph.isTouchDevice() === true ) { + graph.activateHoverElements(true, that, true); + } + that.editingTextElement = true; + ignoreLocalHoverEvents = true; + that.nodeElement().selectAll("circle").classed("hoveredForEditing", true); + graph.killDelayedTimer(); + graph.ignoreOtherHoverEvents(false); + fobj = nodeElement.append("foreignObject") + .attr("x", -0.5 * (that.textWidth() - 2)) + .attr("y", -12) + .attr("height", 30) + .attr("class", "foreignelements") + .on("dragstart", function (){ + return false; + }) // remove drag operations of text element) + .attr("width", that.textWidth() - 2); + + var editText = fobj.append("xhtml:input") + .attr("class", "nodeEditSpan") + .attr("id", that.id()) + .attr("align", "center") + .attr("contentEditable", "true") + .on("dragstart", function (){ + return false; + }); // remove drag operations of text element) + + var bgColor = '#f00'; + var txtWidth = that.textWidth() - 2; + editText.style({ + + 'align': 'center', + 'color': 'black', + 'width': txtWidth + "px", + 'height': '15px', + 'background-color': bgColor, + 'border-bottom': '2px solid black' + }); + var txtNode = editText.node(); + txtNode.value = that.labelForCurrentLanguage(); + txtNode.focus(); + txtNode.select(); + that.frozen(true); // << releases the not after selection + that.locked(true); + + + d3.event.stopPropagation(); + // ignoreNodeHoverEvent=true; + // // add some events that relate to this object + editText.on("click", function (){ + d3.event.stopPropagation(); + }); + // // remove hover Events for now; + editText.on("mouseout", function (){ + d3.event.stopPropagation(); + + + }); + editText.on("mousedown", function (){ + d3.event.stopPropagation(); + }) + .on("keydown", function (){ + d3.event.stopPropagation(); + if ( d3.event.keyCode === 13 ) { + this.blur(); + that.frozen(false); // << releases the not after selection + that.locked(false); + } + }) + .on("keyup", function (){ + if ( forceIRISync ) { + var labelName = editText.node().value; + var resourceName = labelName.replaceAll(" ", "_"); + var syncedIRI = that.baseIri() + resourceName; + backupFullIri = syncedIRI; + + d3.select("#element_iriEditor").node().title = syncedIRI; + d3.select("#element_iriEditor").node().value = graph.options().prefixModule().getPrefixRepresentationForFullURI(syncedIRI); + } + d3.select("#element_labelEditor").node().value = editText.node().value; + + }) + .on("blur", function (){ + that.editingTextElement = false; + ignoreLocalHoverEvents = false; + that.nodeElement().selectAll("circle").classed("hoveredForEditing", false); + var newLabel = editText.node().value; + nodeElement.selectAll(".foreignelements").remove(); + // that.setLabelForCurrentLanguage(classNameConvention(editText.node().value)); + that.label(newLabel); + that.backupLabel(newLabel); + that.redrawLabelText(); + that.frozen(graph.paused()); + that.locked(graph.paused()); + graph.ignoreOtherHoverEvents(false); + // console.log("Calling blur on Node!"); + if ( backupFullIri ) { + var sanityCheckResult = graph.checkIfIriClassAlreadyExist(backupFullIri); + if ( sanityCheckResult === false ) { + that.iri(backupFullIri); + } else { + // throw warnign + graph.options().warningModule().showWarning("Already seen this class", + "Input IRI: " + backupFullIri + " for element: " + that.labelForCurrentLanguage() + " already been set", + "Restoring previous IRI for Element : " + that.iri(), 2, false, sanityCheckResult); + + } + } + if ( graph.isADraggerActive() === false ) { + graph.options().focuserModule().handle(undefined); + graph.options().focuserModule().handle(that); + } + }); // add a foreiner element to this thing; + }; + + + this.renderType = function ( t ){ + if ( !arguments.length ) return rendertype; + rendertype = t; + return this; + }; + // Properties + this.complement = function ( p ){ + if ( !arguments.length ) return complement; + complement = p; + return this; + }; + + this.disjointUnion = function ( p ){ + if ( !arguments.length ) return disjointUnion; + disjointUnion = p; + return this; + }; + + this.disjointWith = function ( p ){ + if ( !arguments.length ) return disjointWith; + disjointWith = p; + return this; + }; + + this.individuals = function ( p ){ + if ( !arguments.length ) return individuals; + individuals = p || []; + return this; + }; + + this.intersection = function ( p ){ + if ( !arguments.length ) return intersection; + intersection = p; + return this; + }; + + this.links = function ( p ){ + if ( !arguments.length ) return links; + links = p; + return this; + }; + + this.maxIndividualCount = function ( p ){ + if ( !arguments.length ) return maxIndividualCount; + maxIndividualCount = p; + return this; + }; + + this.nodeElement = function ( p ){ + if ( !arguments.length ) return nodeElement; + nodeElement = p; + return this; + }; + + this.union = function ( p ){ + if ( !arguments.length ) return union; + union = p; + return this; + }; + + + /** + * Returns css classes generated from the data of this object. + * @returns {Array} + */ + that.collectCssClasses = function (){ + var cssClasses = []; + + if ( typeof that.styleClass() === "string" ) { + cssClasses.push(that.styleClass()); + } + + cssClasses = cssClasses.concat(that.visualAttributes()); + + return cssClasses; + }; + + + // Reused functions TODO refactor + this.addMouseListeners = function (){ + // Empty node + if ( !that.nodeElement() ) { + console.warn(this); + return; + } + + that.nodeElement().selectAll("*") + .on("mouseover", onMouseOver) + .on("mouseout", onMouseOut); + }; + + this.animationProcess = function (){ + var animRuns = false; + if ( that.getHalos() ) { + var haloGr = that.getHalos(); + var haloEls = haloGr.selectAll(".searchResultA"); + animRuns = haloGr.attr("animationRunning"); + if ( typeof animRuns !== "boolean" ) { + // parse this to a boolean value + animRuns = (animRuns === 'true'); + } + if ( animRuns === false ) { + haloEls.classed("searchResultA", false); + haloEls.classed("searchResultB", true); + } + } + return animRuns; + }; + + this.foreground = function (){ + var selectedNode = that.nodeElement().node(), + nodeContainer = selectedNode.parentNode; + // check if the halo is present and an animation is running + if ( that.animationProcess() === false ) { + // Append hovered element as last child to the container list. + nodeContainer.appendChild(selectedNode); + } + + }; + + function onMouseOver(){ + if ( that.mouseEntered() || ignoreLocalHoverEvents === true ) { + return; + } + + var selectedNode = that.nodeElement().node(), + nodeContainer = selectedNode.parentNode; + + // Append hovered element as last child to the container list. + if ( that.animationProcess() === false ) { + nodeContainer.appendChild(selectedNode); + } + if ( graph.isTouchDevice() === false ) { + that.setHoverHighlighting(true); + that.mouseEntered(true); + if ( graph.editorMode() === true && graph.ignoreOtherHoverEvents() === false ) { + graph.activateHoverElements(true, that); + } + } else { + if ( graph.editorMode() === true && graph.ignoreOtherHoverEvents() === false ) { + graph.activateHoverElements(true, that, true); + } + + } + + + } + + function onMouseOut(){ + that.setHoverHighlighting(false); + that.mouseEntered(false); + if ( graph.editorMode() === true && graph.ignoreOtherHoverEvents() === false ) { + graph.activateHoverElements(false); + } + } + + + forceLayoutNodeFunctions.addTo(this); + }; + + Base.prototype = Object.create(BaseElement.prototype); + Base.prototype.constructor = Base; + + + return Base; + }()); + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 10 */ +/***/ (function(module, exports, __webpack_require__) { + + /** + * The base element for all visual elements of webvowl. + */ + module.exports = (function (){ + + var Base = function ( graph ){ + // Basic attributes + var equivalents = [], + id, + label, + type, + iri, + baseIri, + // Additional attributes + annotations, + attributes = [], + backgroundColor, + comment, + description, + equivalentBase, + visualAttributes = [], + // Style attributes + focused = false, + indications = [], + mouseEntered = false, + styleClass, + visible = true, + + backupLabel, + // Other + languageTools = __webpack_require__(11)(); + + + this.backupLabel = function ( label ){ + if ( !arguments.length ) return backupLabel; + backupLabel = label; + }; + // Properties + this.attributes = function ( p ){ + if ( !arguments.length ) return attributes; + attributes = p; + return this; + }; + + this.annotations = function ( p ){ + if ( !arguments.length ) return annotations; + annotations = p; + return this; + }; + + this.redrawElement = function (){ + // TODO: OVERLOADED BY INDIVIDUAL ELEMENTS + }; + + this.backgroundColor = function ( p ){ + if ( !arguments.length ) return backgroundColor; + backgroundColor = p; + return this; + }; + + this.baseIri = function ( p ){ + if ( !arguments.length ) return baseIri; + baseIri = p; + return this; + }; + + this.comment = function ( p ){ + if ( !arguments.length ) return comment; + comment = p; + return this; + }; + + this.description = function ( p ){ + if ( !arguments.length ) return description; + description = p; + return this; + }; + + this.equivalents = function ( p ){ + if ( !arguments.length ) return equivalents; + equivalents = p || []; + return this; + }; + + this.equivalentBase = function ( p ){ + if ( !arguments.length ) return equivalentBase; + equivalentBase = p; + return this; + }; + + this.focused = function ( p ){ + if ( !arguments.length ) return focused; + focused = p; + return this; + }; + + this.id = function ( p ){ + if ( !arguments.length ) return id; + id = p; + return this; + }; + + this.indications = function ( p ){ + if ( !arguments.length ) return indications; + indications = p; + return this; + }; + + this.iri = function ( p ){ + if ( !arguments.length ) return iri; + iri = p; + return this; + }; + + this.label = function ( p ){ + if ( !arguments.length ) return label; + label = p; + return this; + }; + + this.mouseEntered = function ( p ){ + if ( !arguments.length ) return mouseEntered; + mouseEntered = p; + return this; + }; + + this.styleClass = function ( p ){ + if ( !arguments.length ) return styleClass; + styleClass = p; + return this; + }; + + this.type = function ( p ){ + if ( !arguments.length ) return type; + type = p; + return this; + }; + + this.visible = function ( p ){ + if ( !arguments.length ) return visible; + visible = p; + return this; + }; + + this.visualAttributes = function ( p ){ + if ( !arguments.length ) return visualAttributes; + visualAttributes = p; + return this; + }; + + + this.commentForCurrentLanguage = function (){ + return languageTools.textInLanguage(this.comment(), graph.language()); + }; + + /** + * @returns {string} the css class of this node.. + */ + this.cssClassOfNode = function (){ + return "node" + this.id(); + }; + + this.descriptionForCurrentLanguage = function (){ + return languageTools.textInLanguage(this.description(), graph.language()); + }; + + this.defaultLabel = function (){ + return languageTools.textInLanguage(this.label(), "default"); + }; + + this.indicationString = function (){ + return this.indications().join(", "); + }; + + this.labelForCurrentLanguage = function (){ + var preferredLanguage = graph && graph.language ? graph.language() : null; + return languageTools.textInLanguage(this.label(), preferredLanguage); + }; + }; + + Base.prototype.constructor = Base; + + Base.prototype.equals = function ( other ){ + return other instanceof Base && this.id() === other.id(); + }; + + Base.prototype.toString = function (){ + return this.labelForCurrentLanguage() + " (" + this.type() + ")"; + }; + + + return Base; + }()); + + +/***/ }), +/* 11 */ +/***/ (function(module, exports, __webpack_require__) { + + var constants = __webpack_require__(12)(); + + /** + * Encapsulates methods which return a label in a specific language for a preferred language. + */ + module.exports = (function (){ + + var languageTools = {}; + + + languageTools.textInLanguage = function ( textObject, preferredLanguage ){ + if ( typeof textObject === "undefined" ) { + return undefined; + } + + if ( typeof textObject === "string" ) { + return textObject; + } + + if ( preferredLanguage && textObject.hasOwnProperty(preferredLanguage) ) { + return textObject[preferredLanguage]; + } + + var textForLanguage = searchLanguage(textObject, "en"); + if ( textForLanguage ) { + return textForLanguage; + } + textForLanguage = searchLanguage(textObject, constants.LANG_UNDEFINED); + if ( textForLanguage ) { + return textForLanguage; + } + + return textObject[constants.LANG_IRIBASED]; + }; + + + function searchLanguage( textObject, preferredLanguage ){ + for ( var language in textObject ) { + if ( language === preferredLanguage && textObject.hasOwnProperty(language) ) { + return textObject[language]; + } + } + } + + return function (){ + /* Use a function here to keep a consistent style like webvowl.path.to.module() + * despite having just a single languageTools object. */ + return languageTools; + }; + })(); + + +/***/ }), +/* 12 */ +/***/ (function(module, exports) { + + module.exports = (function (){ + + var constants = {}; + + constants.LANG_IRIBASED = "IRI-based"; + constants.LANG_UNDEFINED = "undefined"; + + return function (){ + /* Use a function here to keep a consistent style like webvowl.path.to.module() + * despite having just a single object. */ + return constants; + }; + })(); + + +/***/ }), +/* 13 */ +/***/ (function(module, exports) { + + /** + * The functions for controlling attributes of nodes of the force layout can't be modelled to the element hierarchy, + * which is used for inheriting visual and OWL-like attributes. + * + * To reduce code redundancy the common functions for controlling the force layout node attributes are excluded into this + * module, which can add them to the node objects. + * + * @type {{}} + */ + var nodeFunctions = {}; + module.exports = function (){ + return nodeFunctions; + }; + + + nodeFunctions.addTo = function ( node ){ + addFixedLocationFunctions(node); + }; + + function addFixedLocationFunctions( node ){ + var locked = false, + frozen = false, + halo = false, + pinned = false; + + node.locked = function ( p ){ + if ( !arguments.length ) { + return locked; + } + locked = p; + applyFixedLocationAttributes(); + return node; + }; + + node.frozen = function ( p ){ + if ( !arguments.length ) { + return frozen; + } + frozen = p; + applyFixedLocationAttributes(); + return node; + }; + + node.halo = function ( p ){ + if ( !arguments.length ) { + return halo; + } + halo = p; + applyFixedLocationAttributes(); + return node; + }; + + node.pinned = function ( p ){ + if ( !arguments.length ) { + return pinned; + } + pinned = p; + applyFixedLocationAttributes(); + return node; + }; + + function applyFixedLocationAttributes(){ + if ( node.locked() || node.frozen() || node.pinned() ) { + node.fixed = true; + } else { + node.fixed = false; + } + } + } + + +/***/ }), +/* 14 */ +/***/ (function(module, exports, __webpack_require__) { + + var textTools = __webpack_require__(15)(); + var AbstractTextElement = __webpack_require__(16); + + module.exports = CenteringTextElement; + function CenteringTextElement( container, backgroundColor ){ + AbstractTextElement.apply(this, arguments); + this.storedFullTextLines = []; + this.storedSpanArrays = []; + this.storedStyle = []; + + } + + CenteringTextElement.prototype = Object.create(AbstractTextElement.prototype); + CenteringTextElement.prototype.constructor = CenteringTextElement; + + CenteringTextElement.prototype.addText = function ( text, prefix, suffix ){ + if ( text ) { + this.addTextline(text, this.CSS_CLASSES.default, prefix, suffix); + } + }; + + CenteringTextElement.prototype.addSubText = function ( text ){ + if ( text ) { + this.addTextline(text, this.CSS_CLASSES.subtext, "(", ")"); + } + }; + + CenteringTextElement.prototype.addEquivalents = function ( text ){ + if ( text ) { + this.addTextline(text, this.CSS_CLASSES.default); + } + }; + + CenteringTextElement.prototype.addInstanceCount = function ( instanceCount ){ + if ( instanceCount ) { + this.addTextline(instanceCount.toString(), this.CSS_CLASSES.instanceCount); + } + }; + CenteringTextElement.prototype.saveCorrespondingSpan = function ( correspondingSpan ){ + this.storedSpanArrays.push(correspondingSpan); + }; + CenteringTextElement.prototype.saveFullTextLine = function ( fullText ){ + this.storedFullTextLines.push(fullText); + }; + CenteringTextElement.prototype.saveStyle = function ( style ){ + this.storedStyle.push(style); + }; + + CenteringTextElement.prototype.updateAllTextElements = function (){ + // TODO : TEST THIS postPrefix >>> _applyPreAndPostFix + for ( var i = 0; i < this.storedSpanArrays.length; i++ ) { + var truncatedText = textTools.truncate(this.storedFullTextLines[i], this._textBlock().datum().textWidth(), this.storedStyle[i]); + this.storedSpanArrays[i].text(truncatedText); + } + }; + + + CenteringTextElement.prototype.addTextline = function ( text, style, prefix, postfix ){ + var truncatedText = textTools.truncate(text, this._textBlock().datum().textWidth(), style); + this.saveFullTextLine(text); + this.saveStyle(style); + var tspan = this._textBlock().append("tspan") + .classed(this.CSS_CLASSES.default, true) + .classed(style, true) + .text(this._applyPreAndPostFix(truncatedText, prefix, postfix)) + .attr("x", 0); + this._repositionTextLine(tspan); + this.saveCorrespondingSpan(tspan); + + this._repositionTextBlock(); + }; + + CenteringTextElement.prototype._repositionTextLine = function ( tspan ){ + var fontSizeProperty = window.getComputedStyle(tspan.node()).getPropertyValue("font-size"); + var fontSize = parseFloat(fontSizeProperty); + + var siblingCount = this._lineCount() - 1; + var lineDistance = siblingCount > 0 ? this.LINE_DISTANCE : 0; + + tspan.attr("dy", fontSize + lineDistance + "px"); + }; + + CenteringTextElement.prototype.getTextBox = function (){ + return this._textBlock(); + }; + + + CenteringTextElement.prototype._repositionTextBlock = function (){ + // Nothing to do if no child elements exist + var lineCount = this._lineCount(); + if ( lineCount < 1 ) { + this._textBlock().attr("y", 0); + return; + } + + var textBlockHeight = this._textBlock().node().getBBox().height; + this._textBlock().attr("y", -textBlockHeight * 0.5 + "px"); + }; + + CenteringTextElement.prototype._lineCount = function (){ + return this._textBlock().property("childElementCount"); + }; + + +/***/ }), +/* 15 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var ADDITIONAL_TEXT_SPACE = 4; + + var tools = {}; + + function measureTextWidth( text, textStyle ){ + // Set a default value + if ( !textStyle ) { + textStyle = "text"; + } + var d = d3.select("body") + .append("div") + .attr("class", textStyle) + .attr("id", "width-test") // tag this element to identify it + .attr("style", "position:absolute; float:left; white-space:nowrap; visibility:hidden;") + .text(text), + w = document.getElementById("width-test").offsetWidth; + d.remove(); + return w; + } + + tools.truncate = function ( text, maxWidth, textStyle, additionalTextSpace ){ + maxWidth -= isNaN(additionalTextSpace) ? ADDITIONAL_TEXT_SPACE : additionalTextSpace; + if ( isNaN(maxWidth) || maxWidth <= 0 ) { + return text; + } + + var truncatedText = text, + newTruncatedTextLength, + textWidth, + ratio; + + while ( true ) { + textWidth = measureTextWidth(truncatedText, textStyle); + if ( textWidth <= maxWidth ) { + break; + } + + ratio = textWidth / maxWidth; + newTruncatedTextLength = Math.floor(truncatedText.length / ratio); + + // detect if nothing changes + if ( truncatedText.length === newTruncatedTextLength ) { + break; + } + + truncatedText = truncatedText.substring(0, newTruncatedTextLength); + } + + if ( text.length > truncatedText.length ) { + return text.substring(0, truncatedText.length - 3) + "..."; + } + return text; + }; + + + module.exports = function (){ + return tools; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 16 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = AbstractTextElement; + + function AbstractTextElement( container, backgroundColor ){ + var textBlock = container.append("text") + .classed("text", true) + .style("fill", this._getTextColor(backgroundColor)) + .attr("text-anchor", "middle"); + + this._textBlock = function (){ + return textBlock; + }; + } + + AbstractTextElement.prototype.LINE_DISTANCE = 1; + AbstractTextElement.prototype.CSS_CLASSES = { + default: "text", + subtext: "subtext", + instanceCount: "instance-count" + }; + AbstractTextElement.prototype.DARK_TEXT_COLOR = "#000"; + AbstractTextElement.prototype.LIGHT_TEXT_COLOR = "#fff"; + + AbstractTextElement.prototype.translation = function ( x, y ){ + this._textBlock().attr("transform", "translate(" + x + ", " + y + ")"); + return this; + }; + + AbstractTextElement.prototype.remove = function (){ + this._textBlock().remove(); + return this; + }; + + AbstractTextElement.prototype._applyPreAndPostFix = function ( text, prefix, postfix ){ + if ( prefix ) { + text = prefix + text; + } + if ( postfix ) { + text += postfix; + } + return text; + }; + + AbstractTextElement.prototype._getTextColor = function ( rawBackgroundColor ){ + if ( !rawBackgroundColor ) { + return AbstractTextElement.prototype.DARK_TEXT_COLOR; + } + + var backgroundColor = d3.rgb(rawBackgroundColor); + if ( calculateLuminance(backgroundColor) > 0.5 ) { + return AbstractTextElement.prototype.DARK_TEXT_COLOR; + } else { + return AbstractTextElement.prototype.LIGHT_TEXT_COLOR; + } + }; + + function calculateLuminance( color ){ + return 0.3 * (color.r / 255) + 0.59 * (color.g / 255) + 0.11 * (color.b / 255); + } + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 17 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains reusable function for drawing nodes. + */ + module.exports = (function (){ + + var tools = {}; + + /** + * Append a circular class node with the passed attributes. + * @param parent the parent element to which the circle will be appended + * @param radius + * @param [cssClasses] an array of additional css classes + * @param [tooltip] + * @param [backgroundColor] + * @returns {*} + */ + tools.appendCircularClass = function ( parent, radius, cssClasses, tooltip, backgroundColor ){ + var circle = parent.append("circle") + .classed("class", true) + .attr("r", radius); + + addCssClasses(circle, cssClasses); + addToolTip(circle, tooltip); + addBackgroundColor(circle, backgroundColor); + + return circle; + }; + + function addCssClasses( element, cssClasses ){ + if ( cssClasses instanceof Array ) { + cssClasses.forEach(function ( cssClass ){ + element.classed(cssClass, true); + }); + } + } + + function addToolTip( element, tooltip ){ + if ( tooltip ) { + element.append("title").text(tooltip); + } + } + + function addBackgroundColor( element, backgroundColor ){ + if ( backgroundColor ) { + element.style("fill", backgroundColor); + } + } + + /** + * Appends a rectangular class node with the passed attributes. + * @param parent the parent element to which the rectangle will be appended + * @param width + * @param height + * @param [cssClasses] an array of additional css classes + * @param [tooltip] + * @param [backgroundColor] + * @returns {*} + */ + tools.appendRectangularClass = function ( parent, width, height, cssClasses, tooltip, backgroundColor ){ + var rectangle = parent.append("rect") + .classed("class", true) + .attr("x", -width / 2) + .attr("y", -height / 2) + .attr("width", width) + .attr("height", height); + + addCssClasses(rectangle, cssClasses); + addToolTip(rectangle, tooltip); + addBackgroundColor(rectangle, backgroundColor); + + return rectangle; + }; + + tools.drawPin = function ( container, dx, dy, onClick, accuraciesHelperFunction, useAccuracyHelper ){ + var pinGroupElement = container + .append("g") + .classed("hidden-in-export", true) + .attr("transform", "translate(" + dx + "," + dy + ")"); + + var base = pinGroupElement.append("circle") + .classed("class pin feature", true) + .attr("r", 12) + .on("click", function (){ + if ( onClick ) { + onClick(); + } + d3.event.stopPropagation(); + }); + + pinGroupElement.append("line") + .attr("x1", 0) + .attr("x2", 0) + .attr("y1", 12) + .attr("y2", 16); + + if ( useAccuracyHelper === true ) { + pinGroupElement.append("circle") + .attr("r", 15) + .attr("cx", -7) + .attr("cy", -7) + .classed("superHiddenElement ", true) + .classed("superOpacityElement", !accuraciesHelperFunction()) + .on("click", function (){ + if ( onClick ) { + onClick(); + } + d3.event.stopPropagation(); + }) + .on("mouseover", function (){ + base.classed("feature_hover", true); + }) + .on("mouseout", function (){ + base.classed("feature_hover", false); + }) + ; + + } + + + return pinGroupElement; + }; + + tools.drawRectHalo = function ( node, width, height, offset ){ + var container; + if ( node.nodeElement ) + container = node.nodeElement(); + else + container = node.labelElement(); + + if ( !container ) { + // console.log("no container found"); + return; + } + + var haloGroupElement = container + .append("g") + .classed("hidden-in-export", true); + + haloGroupElement.append("rect") + .classed("searchResultA", true) + .attr("x", (-width - offset) / 2) + .attr("y", (-offset - height) / 2) + .attr("width", width + offset) + .attr("height", height + offset); + haloGroupElement.attr("animationRunning", true); + + haloGroupElement.node().addEventListener("webkitAnimationEnd", function (){ + var test = haloGroupElement.selectAll(".searchResultA"); + test.classed("searchResultA", false) + .classed("searchResultB", true); + haloGroupElement.attr("animationRunning", false); + }); + haloGroupElement.node().addEventListener("animationend", function (){ + var test = haloGroupElement.selectAll(".searchResultA"); + test.classed("searchResultA", false) + .classed("searchResultB", true); + haloGroupElement.attr("animationRunning", false); + }); + + + return haloGroupElement; + + }; + tools.drawHalo = function ( container, radius ){ + if ( container === undefined ) { + return null; + // there is no element to add the halo to; + // this means the node was not rendered previously + } + + var haloGroupElement = container + .append("g") + .classed("hidden-in-export", true); + + + haloGroupElement.append("circle", ":first-child") + .classed("searchResultA", true) + .attr("r", radius + 15); + haloGroupElement.attr("animationRunning", true); + + + haloGroupElement.node().addEventListener("webkitAnimationEnd", function (){ + var test = haloGroupElement.selectAll(".searchResultA"); + test.classed("searchResultA", false) + .classed("searchResultB", true) + .attr("animationRunning", false); + haloGroupElement.attr("animationRunning", false); + }); + haloGroupElement.node().addEventListener("animationend", function (){ + var test = haloGroupElement.selectAll(".searchResultA"); + test.classed("searchResultA", false) + .classed("searchResultB", true) + .attr("animationRunning", false); + haloGroupElement.attr("animationRunning", false); + }); + + return haloGroupElement; + }; + + return function (){ + // Encapsulate into function to maintain default.module.path() + return tools; + }; + })(); + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 18 */ +/***/ (function(module, exports, __webpack_require__) { + + var RoundNode = __webpack_require__(8); + + module.exports = (function (){ + + var o = function ( graph ){ + RoundNode.apply(this, arguments); + + this.type("owl:Class"); + }; + o.prototype = Object.create(RoundNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 19 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetOperatorNode = __webpack_require__(20); + + module.exports = (function (){ + + var o = function ( graph ){ + SetOperatorNode.apply(this, arguments); + + var that = this, + superDrawFunction = that.draw; + + this.styleClass("complementof") + .type("owl:complementOf"); + + this.draw = function ( element ){ + superDrawFunction(element); + + var symbol = element.append("g").classed("embedded", true); + + symbol.append("circle") + .attr("class", "symbol") + .classed("fineline", true) + .attr("r", 10); + symbol.append("path") + .attr("class", "nofill") + .attr("d", "m -7,-1.5 12,0 0,6") + .attr("transform", "scale(.5)"); + + symbol.attr("transform", + "translate(-" + (that.radius() - 15) / 100 + ",-" + (that.radius() - 15) / 100 + ")"); + + that.postDrawActions(); + }; + }; + o.prototype = Object.create(SetOperatorNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 20 */ +/***/ (function(module, exports, __webpack_require__) { + + var AbsoluteTextElement = __webpack_require__(21); + var BoxArrowLink = __webpack_require__(22); + var RoundNode = __webpack_require__(8); + var drawTools = __webpack_require__(17)(); + + module.exports = (function (){ + + var o = function ( graph ){ + RoundNode.apply(this, arguments); + + var that = this, + superHoverHighlightingFunction = that.setHoverHighlighting, + superPostDrawActions = that.postDrawActions; + + this.setHoverHighlighting = function ( enable ){ + superHoverHighlightingFunction(enable); + + // Highlight links pointing to included nodes when hovering the set operator + that.links() + .filter(function ( link ){ + return link instanceof BoxArrowLink; + }) + .filter(function ( link ){ + return link.domain().equals(that); + }) + .forEach(function ( link ){ + link.property().setHighlighting(enable); + }); + }; + + this.draw = function ( element ){ + that.nodeElement(element); + + drawTools.appendCircularClass(element, that.actualRadius(), + that.collectCssClasses().join(" "), + that.labelForCurrentLanguage(), that.backgroundColor()); + }; + + this.postDrawActions = function (){ + superPostDrawActions(); + that.textBlock().remove(); + + var textElement = new AbsoluteTextElement(that.nodeElement(), that.backgroundColor()); + + var equivalentsString = that.equivalentsString(); + var offsetForFollowingEquivalents = equivalentsString ? -30 : -17; + var suffixForFollowingEquivalents = equivalentsString ? "," : ""; + textElement.addText(that.labelForCurrentLanguage(), offsetForFollowingEquivalents, "", + suffixForFollowingEquivalents); + + textElement.addEquivalents(equivalentsString, -17); + + + if ( !graph.options().compactNotation() ) { + + if ( that.indicationString().length > 0 ) { + textElement.addSubText(that.indicationString(), 17); + textElement.addInstanceCount(that.individuals().length, 30); + } else { + textElement.addInstanceCount(that.individuals().length, 17); + } + } else { + textElement.addInstanceCount(that.individuals().length, 17); + } + + that.textBlock(textElement); + }; + }; + o.prototype = Object.create(RoundNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 21 */ +/***/ (function(module, exports, __webpack_require__) { + + var textTools = __webpack_require__(15)(); + var AbstractTextElement = __webpack_require__(16); + + module.exports = AbsoluteTextElement; + function AbsoluteTextElement( container, backgroundColor ){ + AbstractTextElement.apply(this, arguments); + } + + AbsoluteTextElement.prototype = Object.create(AbstractTextElement.prototype); + AbsoluteTextElement.prototype.constructor = AbsoluteTextElement; + + AbsoluteTextElement.prototype.addText = function ( text, yShift, prefix, suffix ){ + if ( text ) { + this.addTextline(text, this.CSS_CLASSES.default, yShift, prefix, suffix); + } + }; + + AbsoluteTextElement.prototype.addSubText = function ( text, yShift ){ + if ( text ) { + this.addTextline(text, this.CSS_CLASSES.subtext, yShift, "(", ")"); + } + }; + + AbsoluteTextElement.prototype.addEquivalents = function ( text, yShift ){ + if ( text ) { + this.addTextline(text, this.CSS_CLASSES.default, yShift); + } + }; + + AbsoluteTextElement.prototype.addInstanceCount = function ( instanceCount, yShift ){ + if ( instanceCount ) { + this.addTextline(instanceCount.toString(), this.CSS_CLASSES.instanceCount, yShift); + } + }; + + + AbsoluteTextElement.prototype.addTextline = function ( text, style, yShift, prefix, postfix ){ + var truncatedText = textTools.truncate(text, this._textBlock().datum().textWidth(yShift), style); + + var tspan = this._textBlock().append("tspan") + .classed(this.CSS_CLASSES.default, true) + .classed(style, true) + .text(this._applyPreAndPostFix(truncatedText, prefix, postfix)) + .attr("x", 0); + this._repositionTextLine(tspan, yShift); + }; + + AbsoluteTextElement.prototype._repositionTextLine = function ( tspan, yShift ){ + var fontSizeProperty = window.getComputedStyle(tspan.node()).getPropertyValue("font-size"); + var fontSize = parseFloat(fontSizeProperty); + + /* BBox height is not supported in Firefox for tspans and dominant-baseline doesn't work in some SVG editors */ + var approximatedShiftForVerticalCentering = (1 / 3) * fontSize; + + tspan.attr("y", approximatedShiftForVerticalCentering + (yShift || 0) + "px"); + }; + + +/***/ }), +/* 22 */ +/***/ (function(module, exports, __webpack_require__) { + + var PlainLink = __webpack_require__(23); + + + module.exports = BoxArrowLink; + + function BoxArrowLink( domain, range, property ){ + PlainLink.apply(this, arguments); + } + + BoxArrowLink.prototype = Object.create(PlainLink.prototype); + BoxArrowLink.prototype.constructor = BoxArrowLink; + + + BoxArrowLink.prototype.draw = function ( linkGroup, markerContainer ){ + var property = this.label().property(); + var inverse = this.label().inverse(); + + createPropertyMarker(markerContainer, property); + if ( inverse ) { + createInverseMarker(markerContainer, inverse); + } + + PlainLink.prototype.draw.apply(this, arguments); + + // attach the markers to the link + linkGroup.attr("marker-start", "url(#" + property.markerId() + ")"); + if ( inverse ) { + linkGroup.attr("marker-end", "url(#" + inverse.markerId() + ")"); + } + }; + + + function createPropertyMarker( markerContainer, inverse ){ + var inverseMarker = appendBasicMarker(markerContainer, inverse); + inverseMarker.attr("refX", -8); + inverseMarker.append("path") + .attr("d", "M0,-8L8,0L0,8L-8,0L0,-8L8,0") + .classed(inverse.markerType(), true); + + inverse.markerElement(inverseMarker); + } + + function createInverseMarker( markerContainer, property ){ + var marker = appendBasicMarker(markerContainer, property); + marker.attr("refX", 8); + marker.append("path") + .attr("d", "M0,-8L8,0L0,8L-8,0L0,-8L8,0") + .classed(property.markerType(), true); + + property.markerElement(marker); + } + + function appendBasicMarker( markerContainer, property ){ + return markerContainer.append("marker") + .datum(property) + .attr("id", property.markerId()) + .attr("viewBox", "-10 -10 20 20") + .attr("markerWidth", 20) + .attr("markerHeight", 20) + .attr("markerUnits", "userSpaceOnUse") + .attr("orient", "auto"); + } + + +/***/ }), +/* 23 */ +/***/ (function(module, exports, __webpack_require__) { + + var Label = __webpack_require__(24); + + + module.exports = PlainLink; + + /** + * A link connects at least two VOWL nodes. + * The properties connecting the VOWL nodes are stored separately into the label. + * @param domain + * @param range + * @param property + */ + function PlainLink( domain, range, property ){ + var layers, + layerIndex, + loops, + loopIndex, + pathEl, + label = new Label(property, this); + + var backPart = __webpack_require__(25)(domain, label, this), + frontPart = __webpack_require__(25)(label, range, this); + + + this.layers = function ( p ){ + if ( !arguments.length ) return layers; + layers = p; + return this; + }; + + this.layerIndex = function ( p ){ + if ( !arguments.length ) return layerIndex; + layerIndex = p; + return this; + }; + + this.loops = function ( p ){ + if ( !arguments.length ) return loops; + loops = p; + return this; + }; + + this.loopIndex = function ( p ){ + if ( !arguments.length ) return loopIndex; + loopIndex = p; + return this; + }; + + + this.domain = function (){ + return domain; + }; + + this.label = function (){ + return label; + }; + + this.linkParts = function (){ + return [frontPart, backPart]; + }; + + this.range = function (){ + return range; + }; + this.pathObj = function ( pE ){ + if ( !arguments.length ) { + return pathEl; + } + pathEl = pE; + }; + } + + + PlainLink.prototype.draw = function ( linkGroup ){ + var property = this.label().property(); + var inverse = this.label().inverse(); + + property.linkGroup(linkGroup); + if ( inverse ) { + inverse.linkGroup(linkGroup); + } + + var pathElement = linkGroup.append("path"); + pathElement.classed("link-path", true) + .classed(this.domain().cssClassOfNode(), true) + .classed(this.range().cssClassOfNode(), true) + .classed(property.linkType(), true); + this.pathObj(pathElement); + + }; + + + PlainLink.prototype.inverse = function (){ + return this.label().inverse(); + }; + + PlainLink.prototype.isLoop = function (){ + return this.domain().equals(this.range()); + }; + + PlainLink.prototype.property = function (){ + return this.label().property(); + }; + + + +/***/ }), +/* 24 */ +/***/ (function(module, exports) { + + module.exports = Label; + + /** + * A label represents the element(s) which further describe a link. + * It encapsulates the property and its inverse property. + * @param property the property; the inverse is inferred + * @param link the link this label belongs to + */ + function Label( property, link ){ + this.link = function (){ + return link; + }; + + this.property = function (){ + return property; + }; + + // "Forward" the fixed value set on the property to avoid having to access this container + Object.defineProperty(this, "fixed", { + get: function (){ + var inverseFixed = property.inverse() ? property.inverse().fixed : false; + return property.fixed || inverseFixed; + }, + set: function ( v ){ + property.fixed = v; + if ( property.inverse() ) property.inverse().fixed = v; + } + }); + this.frozen = property.frozen; + this.locked = property.locked; + this.pinned = property.pinned; + } + + Label.prototype.actualRadius = function (){ + return this.property().actualRadius(); + }; + + Label.prototype.draw = function ( container ){ + return this.property().draw(container); + }; + + Label.prototype.inverse = function (){ + return this.property().inverse(); + }; + + Label.prototype.equals = function ( other ){ + if ( !other ) { + return false; + } + + var instance = other instanceof Label; + var equalProperty = this.property().equals(other.property()); + + var equalInverse = false; + if ( this.inverse() ) { + equalInverse = this.inverse().equals(other.inverse()); + } else if ( !other.inverse() ) { + equalInverse = true; + } + + return instance && equalProperty && equalInverse; + }; + + +/***/ }), +/* 25 */ +/***/ (function(module, exports) { + + /** + * A linkPart connects two force layout nodes. + * It reprents a link which can be used in d3's force layout. + * @param _domain + * @param _range + * @param _link + */ + module.exports = function ( _domain, _range, _link ){ + var linkPart = {}, + domain = _domain, + link = _link, + range = _range; + + // Define d3 properties + Object.defineProperties(linkPart, { + "source": { value: domain, writable: true }, + "target": { value: range, writable: true } + }); + + + linkPart.domain = function (){ + return domain; + }; + + linkPart.link = function (){ + return link; + }; + + linkPart.range = function (){ + return range; + }; + + + return linkPart; + }; + + +/***/ }), +/* 26 */ +/***/ (function(module, exports, __webpack_require__) { + + var RoundNode = __webpack_require__(8); + + module.exports = (function (){ + + var o = function ( graph ){ + RoundNode.apply(this, arguments); + + this.attributes(["deprecated"]) + .type("owl:DeprecatedClass") + .styleClass("deprecated") + .indications(["deprecated"]); + }; + o.prototype = Object.create(RoundNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 27 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetOperatorNode = __webpack_require__(20); + + module.exports = (function (){ + + var o = function ( graph ){ + SetOperatorNode.apply(this, arguments); + + var that = this, + superDrawFunction = that.draw; + + this.styleClass("disjointunionof") + .type("owl:disjointUnionOf"); + + this.draw = function ( element ){ + superDrawFunction(element); + + var symbol = element.append("g").classed("embedded", true); + + var symbolRadius = 10; + symbol.append("circle") + .attr("class", "symbol") + .attr("r", symbolRadius); + symbol.append("circle") + .attr("cx", 10) + .attr("class", "symbol") + .classed("fineline", true) + .attr("r", symbolRadius); + symbol.append("circle") + .attr("class", "nofill") + .classed("fineline", true) + .attr("r", symbolRadius); + symbol.append("text") + .attr("class", "link") + .text("1") + .attr("transform", "scale(.7)translate(3,5)"); + + symbol.attr("transform", "translate(-" + (that.radius() - 15) / 7 + ",-" + (that.radius() - 15) / 100 + ")"); + + that.postDrawActions(); + }; + }; + o.prototype = Object.create(SetOperatorNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 28 */ +/***/ (function(module, exports, __webpack_require__) { + + var RoundNode = __webpack_require__(8); + var drawTools = __webpack_require__(17)(); + + module.exports = (function (){ + + var o = function ( graph ){ + RoundNode.apply(this, arguments); + + var CIRCLE_SIZE_DIFFERENCE = 4; + var renderingElement; + var that = this, + superActualRadiusFunction = that.actualRadius; + + this.styleClass("equivalentclass") + .type("owl:equivalentClass"); + + this.actualRadius = function (){ + return superActualRadiusFunction() + CIRCLE_SIZE_DIFFERENCE; + }; + + this.redrawElement = function (){ + renderingElement.remove(); + that.textBlock().remove(); + var bgColor = that.backgroundColor(); + + if ( that.attributes().indexOf("deprecated") > -1 ) { + bgColor = undefined; + } + var cssClasses = that.collectCssClasses(); + renderingElement = that.nodeElement().append("g"); + + if ( that.getRectangularRepresentation() === true ) { + drawTools.appendRectangularClass(renderingElement, 84, 84, ["white", "embedded"]); + drawTools.appendRectangularClass(renderingElement, 80 - CIRCLE_SIZE_DIFFERENCE, 80 - CIRCLE_SIZE_DIFFERENCE, cssClasses, that.labelForCurrentLanguage(), bgColor); + } else { + drawTools.appendCircularClass(renderingElement, that.actualRadius(), ["white", "embedded"]); + console.log(cssClasses); + console.log(that.attributes()); + console.log("what is bgColor" + bgColor); + drawTools.appendCircularClass(renderingElement, that.actualRadius() - CIRCLE_SIZE_DIFFERENCE, cssClasses, that.labelForCurrentLanguage(), bgColor); + + } + that.postDrawActions(that.nodeElement()); + + }; + this.draw = function ( parentElement ){ + var cssClasses = that.collectCssClasses(); + + that.nodeElement(parentElement); + renderingElement = parentElement.append("g"); + var bgColor = that.backgroundColor(); + if ( that.attributes().indexOf("deprecated") > -1 ) { + bgColor = undefined; + } + // draw the outer circle at first and afterwards the inner circle + if ( that.getRectangularRepresentation() === true ) { + drawTools.appendRectangularClass(renderingElement, 84, 84, ["white", "embedded"]); + drawTools.appendRectangularClass(renderingElement, 80 - CIRCLE_SIZE_DIFFERENCE, 80 - CIRCLE_SIZE_DIFFERENCE, cssClasses, that.labelForCurrentLanguage(), bgColor); + } else { + drawTools.appendCircularClass(renderingElement, that.actualRadius(), ["white", "embedded"]); + drawTools.appendCircularClass(renderingElement, that.actualRadius() - CIRCLE_SIZE_DIFFERENCE, cssClasses, that.labelForCurrentLanguage(), bgColor); + + } + + that.postDrawActions(); + }; + + /** + * Sets the hover highlighting of this node. + * @param enable + */ + that.setHoverHighlighting = function ( enable ){ + that.nodeElement().selectAll("circle:last-of-type").classed("hovered", enable); + }; + }; + o.prototype = Object.create(RoundNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 29 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetOperatorNode = __webpack_require__(20); + + module.exports = (function (){ + + var o = function ( graph ){ + SetOperatorNode.apply(this, arguments); + + var that = this, + superDrawFunction = that.draw, + INTERSECTION_BACKGROUND_PATH = createIntersectionPath(); + + this.styleClass("intersectionof") + .type("owl:intersectionOf"); + + this.draw = function ( element ){ + superDrawFunction(element); + + var symbol = element.append("g").classed("embedded", true); + + var symbolRadius = 10; + symbol.append("path") + .attr("class", "nostroke") + .classed("symbol", true) + .attr("d", INTERSECTION_BACKGROUND_PATH); + symbol.append("circle") + .attr("class", "nofill") + .classed("fineline", true) + .attr("r", symbolRadius); + symbol.append("circle") + .attr("cx", 10) + .attr("class", "nofill") + .classed("fineline", true) + .attr("r", symbolRadius); + symbol.append("path") + .attr("class", "nofill") + .attr("d", "m 9,5 c 0,-2 0,-4 0,-6 0,0 0,0 0,0 0,0 0,-1.8 -1,-2.3 -0.7,-0.6 -1.7,-0.8 -2.9," + + "-0.8 -1.2,0 -2,0 -3,0.8 -0.7,0.5 -1,1.4 -1,2.3 0,2 0,4 0,6") + .attr("transform", "scale(.5)translate(5,0)"); + + symbol.attr("transform", + "translate(-" + (that.radius() - 15) / 7 + ",-" + (that.radius() - 15) / 100 + ")"); + + that.postDrawActions(); + }; + + function createIntersectionPath(){ + var height = 18; + + var offsetX = 5; + var offsetY = -(height / 2); + + var bezierX = 7; + var bezierY = 5; + var bottomBezierY = height - bezierY; + + var startPosition = "M" + offsetX + "," + offsetY; + var rightSide = "c" + bezierX + "," + bezierY + " " + bezierX + "," + bottomBezierY + " 0," + height; + var leftSide = "c" + -bezierX + "," + -bezierY + " " + -bezierX + "," + -bottomBezierY + " 0," + -height; + + return startPosition + rightSide + leftSide; + } + }; + o.prototype = Object.create(SetOperatorNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 30 */ +/***/ (function(module, exports, __webpack_require__) { + + var OwlThing = __webpack_require__(31); + + module.exports = (function (){ + + var o = function ( graph ){ + OwlThing.apply(this, arguments); + + this.label("Nothing") + .type("owl:Nothing") + .iri("http://www.w3.org/2002/07/owl#Nothing"); + }; + o.prototype = Object.create(OwlThing.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 31 */ +/***/ (function(module, exports, __webpack_require__) { + + var RoundNode = __webpack_require__(8); + + module.exports = (function (){ + + var o = function ( graph ){ + RoundNode.apply(this, arguments); + + var superDrawFunction = this.draw; + + this.label("Thing") + .type("owl:Thing") + .iri("http://www.w3.org/2002/07/owl#Thing") + .radius(30); + + this.draw = function ( element ){ + superDrawFunction(element, ["white", "dashed"]); + }; + }; + o.prototype = Object.create(RoundNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 32 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetOperatorNode = __webpack_require__(20); + + module.exports = (function (){ + + var o = function ( graph ){ + SetOperatorNode.apply(this, arguments); + + var that = this, + superDrawFunction = that.draw; + + this.styleClass("unionof") + .type("owl:unionOf"); + + this.draw = function ( element ){ + superDrawFunction(element); + + var symbol = element.append("g").classed("embedded", true); + + var symbolRadius = 10; + symbol.append("circle") + .attr("class", "symbol") + .attr("r", symbolRadius); + symbol.append("circle") + .attr("cx", 10) + .attr("class", "symbol") + .classed("fineline", true) + .attr("r", symbolRadius); + symbol.append("circle") + .attr("class", "nofill") + .classed("fineline", true) + .attr("r", symbolRadius); + symbol.append("path") + .attr("class", "link") + .attr("d", "m 1,-3 c 0,2 0,4 0,6 0,0 0,0 0,0 0,2 2,3 4,3 2,0 4,-1 4,-3 0,-2 0,-4 0,-6") + .attr("transform", "scale(.5)translate(5,0)"); + + symbol.attr("transform", "translate(-" + (that.radius() - 15) / 7 + ",-" + (that.radius() - 15) / 100 + ")"); + + that.postDrawActions(); + }; + }; + o.prototype = Object.create(SetOperatorNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 33 */ +/***/ (function(module, exports, __webpack_require__) { + + var RoundNode = __webpack_require__(8); + + module.exports = (function (){ + + var o = function ( graph ){ + RoundNode.apply(this, arguments); + + this.attributes(["rdf"]) + .type("rdfs:Class"); + }; + o.prototype = Object.create(RoundNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 34 */ +/***/ (function(module, exports, __webpack_require__) { + + var DatatypeNode = __webpack_require__(35); + + module.exports = (function (){ + + var o = function ( graph ){ + DatatypeNode.apply(this, arguments); + var dTypeString = "undefined"; + this.attributes(["datatype"]) + .type("rdfs:Datatype") + .styleClass("datatype"); + this.dType = function ( val ){ + if ( !arguments.length ) return dTypeString; + dTypeString = val; + + }; + }; + o.prototype = Object.create(DatatypeNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 35 */ +/***/ (function(module, exports, __webpack_require__) { + + var RectangularNode = __webpack_require__(36); + + module.exports = (function (){ + + var o = function ( graph ){ + RectangularNode.apply(this, arguments); + }; + o.prototype = Object.create(RectangularNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 36 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var BaseNode = __webpack_require__(9); + var CenteringTextElement = __webpack_require__(14); + var drawTools = __webpack_require__(17)(); + var rectangularElementTools = __webpack_require__(37)(); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseNode.apply(this, arguments); + + var that = this, + height = 20, + width = 60, + pinGroupElement, + haloGroupElement, + labelWidth = 80, + myWidth = 80, + defaultWidth = 80, + shapeElement, + textBlock, + smallestRadius = height / 2; + + that.renderType("rect"); + // Properties + this.height = function ( p ){ + if ( !arguments.length ) return height; + height = p; + return this; + }; + + this.width = function ( p ){ + if ( !arguments.length ) return width; + width = p; + return this; + }; + + this.getHalos = function (){ + return haloGroupElement; + }; + + // Functions + // for compatibility reasons // TODO resolve + this.actualRadius = function (){ + return smallestRadius; + }; + + this.distanceToBorder = function ( dx, dy ){ + return rectangularElementTools.distanceToBorder(that, dx, dy); + }; + + this.setHoverHighlighting = function ( enable ){ + that.nodeElement().selectAll("rect").classed("hovered", enable); + + var haloGroup = that.getHalos(); + if ( haloGroup ) { + var test = haloGroup.selectAll(".searchResultA"); + test.classed("searchResultA", false); + test.classed("searchResultB", true); + } + + }; + + + // overwrite the labelWith; + + + this.textWidth = function (){ + return labelWidth; + }; + this.width = function (){ + return labelWidth; + }; + + this.getMyWidth = function (){ + // use a simple heuristic + var text = that.labelForCurrentLanguage(); + myWidth = measureTextWidth(text, "text") + 20; + + // check for sub names; + var indicatorText = that.indicationString(); + var indicatorWidth = measureTextWidth(indicatorText, "subtext") + 20; + if ( indicatorWidth > myWidth ) + myWidth = indicatorWidth; + + return myWidth; + }; + + this.textWidth = function (){ + return that.width(); + }; + function measureTextWidth( text, textStyle ){ + // Set a default value + if ( !textStyle ) { + textStyle = "text"; + } + var d = d3.select("body") + .append("div") + .attr("class", textStyle) + .attr("id", "width-test") // tag this element to identify it + .attr("style", "position:absolute; float:left; white-space:nowrap; visibility:hidden;") + .text(text), + w = document.getElementById("width-test").offsetWidth; + d.remove(); + return w; + } + + this.toggleFocus = function (){ + that.focused(!that.focused()); + that.nodeElement().select("rect").classed("focused", that.focused()); + graph.resetSearchHighlight(); + graph.options().searchMenu().clearText(); + }; + + /** + * Draws the rectangular node. + * @param parentElement the element to which this node will be appended + * @param [additionalCssClasses] additional css classes + */ + this.draw = function ( parentElement, additionalCssClasses ){ + var cssClasses = that.collectCssClasses(); + + that.nodeElement(parentElement); + + if ( additionalCssClasses instanceof Array ) { + cssClasses = cssClasses.concat(additionalCssClasses); + } + + // set the value for that.width() + // update labelWidth Value; + if ( graph.options().dynamicLabelWidth() === true ) labelWidth = Math.min(that.getMyWidth(), graph.options().maxLabelWidth()); + else labelWidth = defaultWidth; + + width = labelWidth; + shapeElement = drawTools.appendRectangularClass(parentElement, that.width(), that.height(), cssClasses, that.labelForCurrentLanguage(), that.backgroundColor()); + + textBlock = new CenteringTextElement(parentElement, that.backgroundColor()); + textBlock.addText(that.labelForCurrentLanguage()); + + that.addMouseListeners(); + + if ( that.pinned() ) { + that.drawPin(); + } + if ( that.halo() ) { + that.drawHalo(false); + } + }; + + this.drawPin = function (){ + that.pinned(true); + // if (graph.options().dynamicLabelWidth()===true) labelWidth=that.getMyWidth(); + // else labelWidth=defaultWidth; + // width=labelWidth; + // console.log("this element label Width is "+labelWidth); + var dx = -0.5 * labelWidth + 5, + dy = -1.1 * height; + + pinGroupElement = drawTools.drawPin(that.nodeElement(), dx, dy, this.removePin, graph.options().showDraggerObject, graph.options().useAccuracyHelper()); + + }; + + this.removePin = function (){ + that.pinned(false); + if ( pinGroupElement ) { + pinGroupElement.remove(); + } + graph.updateStyle(); + }; + + this.removeHalo = function (){ + that.halo(false); + if ( haloGroupElement ) { + haloGroupElement.remove(); + haloGroupElement = null; + } + }; + + this.drawHalo = function ( pulseAnimation ){ + that.halo(true); + + var offset = 0; + haloGroupElement = drawTools.drawRectHalo(that, this.width(), this.height(), offset); + + if ( pulseAnimation === false ) { + var pulseItem = haloGroupElement.selectAll(".searchResultA"); + pulseItem.classed("searchResultA", false); + pulseItem.classed("searchResultB", true); + pulseItem.attr("animationRunning", false); + } + + if ( that.pinned() ) { + var selectedNode = pinGroupElement.node(); + var nodeContainer = selectedNode.parentNode; + nodeContainer.appendChild(selectedNode); + } + + }; + + this.updateTextElement = function (){ + textBlock.updateAllTextElements(); + + }; + + this.textBlock = function (){ + return textBlock; + }; + + this.redrawLabelText = function (){ + textBlock.remove(); + textBlock = new CenteringTextElement(that.nodeElement(), that.backgroundColor()); + textBlock.addText(that.labelForCurrentLanguage()); + that.animateDynamicLabelWidth(graph.options().dynamicLabelWidth()); + shapeElement.select("title").text(that.labelForCurrentLanguage()); + }; + + this.animateDynamicLabelWidth = function ( dynamic ){ + that.removeHalo(); + var height = that.height(); + if ( dynamic === true ) { + labelWidth = Math.min(that.getMyWidth(), graph.options().maxLabelWidth()); + shapeElement.transition().tween("attr", function (){ + }) + .ease('linear') + .duration(100) + .attr({ x: -labelWidth / 2, y: -height / 2, width: labelWidth, height: height }) + .each("end", function (){ + that.updateTextElement(); + }); + + } else { + labelWidth = defaultWidth; + that.updateTextElement(); + shapeElement.transition().tween("attr", function (){ + }) + .ease('linear') + .duration(100) + .attr({ x: -labelWidth / 2, y: -height / 2, width: labelWidth, height: height }); + + } + + // for the pin we dont need to differ between different widths -- they are already set + if ( that.pinned() === true && pinGroupElement ) { + + var dx = 0.5 * labelWidth - 10, + dy = -1.1 * height; + + pinGroupElement.transition() + .tween("attr.translate", function (){ + }) + .attr("transform", "translate(" + dx + "," + dy + ")") + .ease('linear') + .duration(100); + } + }; + + this.addTextLabelElement = function (){ + var parentElement = that.nodeElement(); + textBlock = new CenteringTextElement(parentElement, this.backgroundColor()); + textBlock.addText(that.labelForCurrentLanguage()); + }; + + + }; + o.prototype = Object.create(BaseNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 37 */ +/***/ (function(module, exports) { + + var tools = {}; + module.exports = function (){ + return tools; + }; + + tools.distanceToBorder = function ( rect, dx, dy ){ + var width = rect.width(), + height = rect.height(); + + var innerDistance, + m_link = Math.abs(dy / dx), + m_rect = height / width; + + if ( m_link <= m_rect ) { + var timesX = dx / (width / 2), + rectY = dy / timesX; + innerDistance = Math.sqrt(Math.pow(width / 2, 2) + Math.pow(rectY, 2)); + } else { + var timesY = dy / (height / 2), + rectX = dx / timesY; + innerDistance = Math.sqrt(Math.pow(height / 2, 2) + Math.pow(rectX, 2)); + } + + return innerDistance; + }; + + +/***/ }), +/* 38 */ +/***/ (function(module, exports, __webpack_require__) { + + var DatatypeNode = __webpack_require__(35); + + module.exports = (function (){ + + var o = function ( graph ){ + DatatypeNode.apply(this, arguments); + + var superDrawFunction = this.draw, + superLabelFunction = this.label; + + this.attributes(["datatype"]) + .label("Literal") + .styleClass("literal") + .type("rdfs:Literal") + .iri("http://www.w3.org/2000/01/rdf-schema#Literal"); + + this.draw = function ( element ){ + superDrawFunction(element, ["dashed"]); + }; + + this.label = function ( p ){ + if ( !arguments.length ) return superLabelFunction(); + return this; + }; + }; + o.prototype = Object.create(DatatypeNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 39 */ +/***/ (function(module, exports, __webpack_require__) { + + var RoundNode = __webpack_require__(8); + + module.exports = (function (){ + + var o = function ( graph ){ + RoundNode.apply(this, arguments); + + var superDrawFunction = this.draw; + + this.attributes(["rdf"]) + .label("Resource") + .radius(30) + .styleClass("rdfsresource") + .type("rdfs:Resource"); + + this.draw = function ( element ){ + superDrawFunction(element, ["rdf", "dashed"]); + }; + }; + o.prototype = Object.create(RoundNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 40 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var properties = []; + properties.push(__webpack_require__(41)); + properties.push(__webpack_require__(44)); + properties.push(__webpack_require__(45)); + properties.push(__webpack_require__(46)); + properties.push(__webpack_require__(47)); + properties.push(__webpack_require__(48)); + properties.push(__webpack_require__(49)); + properties.push(__webpack_require__(50)); + properties.push(__webpack_require__(51)); + properties.push(__webpack_require__(52)); + properties.push(__webpack_require__(53)); + properties.push(__webpack_require__(54)); + properties.push(__webpack_require__(55)); + properties.push(__webpack_require__(56)); + + var map = d3.map(properties, function ( Prototype ){ + return new Prototype().type(); + }); + + module.exports = function (){ + return map; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 41 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + var superGenerateCardinalityText = this.generateCardinalityText; + + this.linkType("values-from") + .markerType("filled values-from") + .styleClass("allvaluesfromproperty") + .type("owl:allValuesFrom"); + + this.generateCardinalityText = function (){ + var cardinalityText = "A"; + + var superCardinalityText = superGenerateCardinalityText(); + if ( superCardinalityText ) { + cardinalityText += ", " + superCardinalityText; + } + + return cardinalityText; + }; + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + + + +/***/ }), +/* 42 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var BaseElement = __webpack_require__(10); + var CenteringTextElement = __webpack_require__(14); + var drawTools = __webpack_require__(17)(); + var forceLayoutNodeFunctions = __webpack_require__(13)(); + var rectangularElementTools = __webpack_require__(37)(); + var math = __webpack_require__(43)(); + + module.exports = (function (){ + + // Static variables + var labelHeight = 28, + labelWidth = 80, + smallestRadius = labelHeight / 2; + + + // Constructor, private variables and privileged methods + var Base = function ( graph ){ + BaseElement.apply(this, arguments); + + var that = this, + // Basic attributes + cardinality, + domain, + inverse, + link, + minCardinality, + maxCardinality, + range, + subproperties, + superproperties, + // Style attributes + linkType = "normal", + markerType = "filled", + labelVisible = true, + // Element containers + cardinalityElement, + labelElement, + linkGroup, + markerElement, + // Other + ignoreLocalHoverEvents, + fobj, + pinGroupElement, + haloGroupElement, + myWidth = 80, + defaultWidth = 80, + shapeElement, + textElement, + parent_labelObject, + backupFullIri, + + redundantProperties = []; + + + this.existingPropertyIRI = function ( url ){ + return graph.options().editSidebar().checkForExistingURL(url); + }; + + this.getHalos = function (){ + return haloGroupElement; + }; + + this.getPin = function (){ + return pinGroupElement; + }; + this.labelObject = function ( lo, once ){ + if ( !arguments.length ) { + return parent_labelObject; + } + else { + parent_labelObject = lo; + if ( that.inverse() && once !== true ) { + that.inverse().labelObject(lo, true); + } + + } + }; + this.hide = function ( val ){ + that.labelElement().classed("hidden", val); + that.linkGroup().classed("hidden", val); + if ( that.cardinalityElement() ) + that.cardinalityElement().classed("hidden", val); + }; + + // Properties + this.cardinality = function ( p ){ + if ( !arguments.length ) return cardinality; + cardinality = p; + return this; + }; + + this.cardinalityElement = function ( p ){ + if ( !arguments.length ) return cardinalityElement; + cardinalityElement = p; + return this; + }; + + this.domain = function ( p ){ + if ( !arguments.length ) return domain; + domain = p; + return this; + }; + + this.inverse = function ( p ){ + if ( !arguments.length ) return inverse; + inverse = p; + return this; + }; + + this.labelElement = function ( p ){ + if ( !arguments.length ) return labelElement; + labelElement = p; + return this; + }; + + this.labelVisible = function ( p ){ + if ( !arguments.length ) return labelVisible; + labelVisible = p; + return this; + }; + + this.link = function ( p ){ + if ( !arguments.length ) return link; + link = p; + return this; + }; + + this.linkGroup = function ( p ){ + if ( !arguments.length ) return linkGroup; + linkGroup = p; + return this; + }; + + this.linkType = function ( p ){ + if ( !arguments.length ) return linkType; + linkType = p; + return this; + }; + + this.markerElement = function ( p ){ + if ( !arguments.length ) return markerElement; + markerElement = p; + return this; + }; + + this.markerType = function ( p ){ + if ( !arguments.length ) return markerType; + markerType = p; + return this; + }; + + this.maxCardinality = function ( p ){ + if ( !arguments.length ) return maxCardinality; + maxCardinality = p; + return this; + }; + + this.minCardinality = function ( p ){ + if ( !arguments.length ) return minCardinality; + minCardinality = p; + return this; + }; + + this.range = function ( p ){ + if ( !arguments.length ) return range; + range = p; + return this; + }; + + this.redundantProperties = function ( p ){ + if ( !arguments.length ) return redundantProperties; + redundantProperties = p; + return this; + }; + + this.subproperties = function ( p ){ + if ( !arguments.length ) return subproperties; + subproperties = p; + return this; + }; + + this.superproperties = function ( p ){ + if ( !arguments.length ) return superproperties; + superproperties = p; + return this; + }; + + + // Functions + this.distanceToBorder = function ( dx, dy ){ + return rectangularElementTools.distanceToBorder(that, dx, dy); + }; + + this.linkHasMarker = function (){ + return linkType !== "dashed"; + }; + + this.markerId = function (){ + return "marker" + that.id(); + }; + + this.toggleFocus = function (){ + that.focused(!that.focused()); + labelElement.select("rect").classed("focused", that.focused()); + graph.resetSearchHighlight(); + graph.options().searchMenu().clearText(); + }; + this.getShapeElement = function (){ + return shapeElement; + }; + + this.textBlock = function (){ + return textElement; + }; + + this.redrawElement = function (){ + shapeElement.remove(); + textElement.remove(); + + that.drawLabel(that.labelElement()); + that.animateDynamicLabelWidth(graph.options().dynamicLabelWidth()); + + + // shapeElement=this.addRect(that.labelElement()); + // + // var equivalentsString = that.equivalentsString(); + // var suffixForFollowingEquivalents = equivalentsString ? "," : ""; + // + // textElement = new CenteringTextElement(labelContainer, this.backgroundColor()); + // textElement.addText(this.labelForCurrentLanguage(), "", suffixForFollowingEquivalents); + // textElement.addEquivalents(equivalentsString); + // textElement.addSubText(this.indicationString()); + + }; + + // Reused functions TODO refactor + this.draw = function ( labelGroup ){ + function attachLabel( property ){ + var labelContainer = labelGroup.append("g") + .datum(property) + .classed("label", true) + .attr("id", property.id()); + + property.drawLabel(labelContainer); + return labelContainer; + } + + if ( !that.labelVisible() ) { + return undefined; + } + if ( graph.options().dynamicLabelWidth() === true ) myWidth = Math.min(that.getMyWidth(), graph.options().maxLabelWidth()); + else myWidth = defaultWidth; + + that.labelElement(attachLabel(that)); + // Draw an inverse label and reposition both labels if necessary + if ( that.inverse() ) { + var yTransformation = (that.height() / 2) + 1 /* additional space */; + that.inverse() + .labelElement(attachLabel(that.inverse())); + + that.labelElement() + .attr("transform", "translate(" + 0 + ",-" + yTransformation + ")"); + that.inverse() + .labelElement() + .attr("transform", "translate(" + 0 + "," + yTransformation + ")"); + } + + if ( that.pinned() ) { + that.drawPin(); + } else if ( that.inverse() && that.inverse().pinned() ) { + that.inverse().drawPin(); + } + + if ( that.halo() ) + that.drawHalo(false); + + return that.labelElement(); + }; + + this.addRect = function ( labelContainer ){ + var rect = labelContainer.append("rect") + .classed(that.styleClass(), true) + .classed("property", true) + .attr("x", -that.width() / 2) + .attr("y", -that.height() / 2) + .attr("width", that.width()) + .attr("height", that.height()) + .on("mouseover", function (){ + onMouseOver(); + }) + .on("mouseout", function (){ + onMouseOut(); + }); + + rect.append("title") + .text(that.labelForCurrentLanguage()); + + if ( that.visualAttributes() ) { + rect.classed(that.visualAttributes(), true); + } + + var bgColor = that.backgroundColor(); + + if ( that.attributes().indexOf("deprecated") > -1 ) { + bgColor = undefined; + rect.classed("deprecatedproperty", true); + } else { + rect.classed("deprecatedproperty", false); + } + rect.style("fill", bgColor); + + return rect; + }; + this.drawLabel = function ( labelContainer ){ + shapeElement = this.addRect(labelContainer); + + var equivalentsString = that.equivalentsString(); + var suffixForFollowingEquivalents = equivalentsString ? "," : ""; + + var bgColor = that.backgroundColor(); + if ( that.attributes().indexOf("deprecated") > -1 ) { + bgColor = undefined; + } + textElement = new CenteringTextElement(labelContainer, bgColor); + textElement.addText(this.labelForCurrentLanguage(), "", suffixForFollowingEquivalents); + textElement.addEquivalents(equivalentsString); + textElement.addSubText(this.indicationString()); + }; + + this.equivalentsString = function (){ + var equivalentProperties = that.equivalents(); + if ( !equivalentProperties ) { + return; + } + + return equivalentProperties + .map(function ( property ){ + if ( property === undefined || typeof(property) === "string" ) { // @WORKAROUND + return "ERROR"; + } + return property.labelForCurrentLanguage(); + }) + .join(", "); + }; + + this.drawCardinality = function ( container ){ + var cardinalityText = this.generateCardinalityText(); + + if ( cardinalityText ) { + that.cardinalityElement(container); + if ( cardinalityText.indexOf("A") === 0 && cardinalityText.length === 1 ) { + + // replacing text elements to svg elements; + container.classed("cardinality", true) + .attr("text-anchor", "middle") + .append("path") + .classed("cardinality", true) + .attr("d", "m -8.8832678,-11.303355 -7.97e-4,0 0.717374,1.833297 8.22987151,21.371761 8.66826659,-21.2123526 0.797082,-1.9927054 0.02471,0 -0.8218553,1.9927054 -2.2517565,5.4201577 -12.4444429,8e-6 -2.2019394,-5.5795821 z") + .style("fill", "none") + .attr("transform", "matrix(0.5,0,0,0.5,0.5,0.5)"); + return true; + } else if ( cardinalityText.indexOf("E") === 0 && cardinalityText.length === 1 ) { + container.classed("cardinality", true) + .attr("text-anchor", "middle") + .append("path") + .classed("cardinality", true) + .attr("d", "m -5.5788451,-8.0958763 10.8749368,0 0,8.34681523 -9.5707468,0.040132 9.5707468,-0.040132 0,8.42707237 -10.9150654,0") + .style("fill", "none") + .attr("transform", "matrix(0.5,0,0,0.5,0.5,0.5)"); + return true; + } + else { + container.append("text") + .classed("cardinality", true) + .attr("text-anchor", "middle") + .attr("dy", "0.5ex") + .text(cardinalityText); + return true; // drawing successful + } + } else { + return false; + } + }; + + this.generateCardinalityText = function (){ + if ( that.cardinality() ) { + return that.cardinality(); + } else if ( that.minCardinality() || that.maxCardinality() ) { + var minBoundary = that.minCardinality() || "*"; + var maxBoundary = that.maxCardinality() || "*"; + return minBoundary + ".." + maxBoundary; + } + }; + + that.setHighlighting = function ( enable ){ + if ( that.labelElement && that.labelElement() ) { + that.labelElement().select("rect").classed("hovered", enable); + } + that.linkGroup().selectAll("path, text").classed("hovered", enable); + if ( that.markerElement() ) { + that.markerElement().select("path").classed("hovered", enable); + if ( that.cardinalityElement() ) { + that.cardinalityElement().selectAll("path").classed("hovered-MathSymbol", enable); + that.cardinalityElement().classed("hovered", enable); + } + } + var subAndSuperProperties = getSubAndSuperProperties(); + subAndSuperProperties.forEach(function ( property ){ + + if ( property.labelElement && property.labelElement() ) { + property.labelElement().select("rect") + .classed("indirect-highlighting", enable); + } + + }); + var inversed = false; + + if ( graph.ignoreOtherHoverEvents() === false ) { + if ( that.inverse() ) { + inversed = true; + } + + if ( graph.isTouchDevice() === false ) { + graph.activateHoverElementsForProperties(enable, that, inversed); + } + else { + that.labelElement().select("rect").classed("hovered", false); + that.linkGroup().selectAll("path, text").classed("hovered", false); + if ( that.markerElement() ) { + that.markerElement().select("path").classed("hovered", false); + if ( that.cardinalityElement() ) { + that.cardinalityElement().classed("hovered", false); + } + } + graph.activateHoverElementsForProperties(enable, that, inversed, true); + } + } + }; + + /** + * Combines the sub- and superproperties into a single array, because + * they're often used equivalently. + * @returns {Array} + */ + function getSubAndSuperProperties(){ + var properties = []; + + if ( that.subproperties() ) { + properties = properties.concat(that.subproperties()); + } + if ( that.superproperties() ) { + properties = properties.concat(that.superproperties()); + } + + return properties; + } + + /** + * Foregrounds the property, its inverse and the link. + */ + this.foreground = function (){ + // check for additional objects that we can highlight + if ( !that.labelElement() ) + return; + if ( that.labelElement().node().parentNode === null ) { + return; + } + var selectedLabelGroup = that.labelElement().node().parentNode, + labelContainer = selectedLabelGroup.parentNode, + selectedLinkGroup = that.linkGroup().node(), + linkContainer = that.linkGroup().node().parentNode; + if ( that.animationProcess() === false ) { + labelContainer.appendChild(selectedLabelGroup); + } + linkContainer.appendChild(selectedLinkGroup); + }; + + /** + * Foregrounds the sub- and superproperties of this property. + * This is separated from the foreground-function to prevent endless loops. + */ + function foregroundSubAndSuperProperties(){ + var subAndSuperProperties = getSubAndSuperProperties(); + + subAndSuperProperties.forEach(function ( property ){ + if ( property.foreground ) property.foreground(); + }); + } + + function onMouseOver(){ + if ( that.mouseEntered() || ignoreLocalHoverEvents === true ) { + return; + } + that.mouseEntered(true); + that.setHighlighting(true); + that.foreground(); + foregroundSubAndSuperProperties(); + } + + function onMouseOut(){ + that.mouseEntered(false); + that.setHighlighting(false); + } + + this.drawPin = function (){ + that.pinned(true); + if ( graph.options().dynamicLabelWidth() === true ) myWidth = that.getMyWidth(); + else myWidth = defaultWidth; + + if ( that.inverse() ) { + // check which element is rendered on top and add a pin to it + var tr_that = that.labelElement().attr("transform"); + var tr_inv = that.inverse().labelElement().attr("transform"); + + var thatY = /translate\(\s*([^\s,)]+)[ ,]([^\s,)]+)/.exec(tr_that)[2]; + var invY = /translate\(\s*([^\s,)]+)[ ,]([^\s,)]+)/.exec(tr_inv)[2]; + + if ( thatY < invY ) + pinGroupElement = drawTools.drawPin(that.labelElement(), -0.5 * that.width() + 10, -25, this.removePin, graph.options().showDraggerObject, graph.options().useAccuracyHelper()); + else + pinGroupElement = drawTools.drawPin(that.inverse().labelElement(), -0.5 * that.inverse().width() + 10, -25, this.removePin, graph.options().showDraggerObject, graph.options().useAccuracyHelper()); + + } + else { + pinGroupElement = drawTools.drawPin(that.labelElement(), -0.5 * that.width() + 10, -25, this.removePin, graph.options().showDraggerObject, graph.options().useAccuracyHelper()); + } + + + }; + + /** + * Removes the pin and refreshs the graph to update the force layout. + */ + this.removePin = function (){ + that.pinned(false); + if ( pinGroupElement ) { + pinGroupElement.remove(); + } + graph.updateStyle(); + }; + + this.removeHalo = function (){ + that.halo(false); + if ( haloGroupElement ) { + haloGroupElement.remove(); + haloGroupElement = null; + } + }; + + this.animationProcess = function (){ + var animRuns = false; + if ( that.getHalos() ) { + var haloGr = that.getHalos(); + var haloEls = haloGr.selectAll(".searchResultA"); + animRuns = haloGr.attr("animationRunning"); + + if ( typeof animRuns !== "boolean" ) { + // parse this to a boolean value + animRuns = (animRuns === 'true'); + } + if ( animRuns === false ) { + haloEls.classed("searchResultA", false); + haloEls.classed("searchResultB", true); + } + } + return animRuns; + }; + + this.drawHalo = function ( pulseAnimation ){ + that.halo(true); + var offset = 0; + if ( that.labelElement() && that.labelElement().node() ) { + var labelNode = that.labelElement().node(); + var labelContainer = labelNode.parentNode; + // do this only if animation is not running + if ( that.animationProcess() === false ) + labelContainer.appendChild(labelNode); + } + haloGroupElement = drawTools.drawRectHalo(that, that.width(), that.height(), offset); + if ( haloGroupElement ) { + var haloNode = haloGroupElement.node(); + var haloContainer = haloNode.parentNode; + haloContainer.appendChild(haloNode); + } + var selectedNode; + var nodeContainer; + if ( that.pinned() ) { + selectedNode = pinGroupElement.node(); + nodeContainer = selectedNode.parentNode; + nodeContainer.appendChild(selectedNode); + } + if ( that.inverse() && that.inverse().pinned() ) { + if ( that.inverse().getPin() ) { + selectedNode = that.inverse().getPin().node(); + nodeContainer = selectedNode.parentNode; + nodeContainer.appendChild(selectedNode); + } + } + if ( pulseAnimation === false ) { + var pulseItem = haloGroupElement.selectAll(".searchResultA"); + pulseItem.classed("searchResultA", false); + pulseItem.classed("searchResultB", true); + pulseItem.attr("animationRunning", false); + } + }; + + this.getMyWidth = function (){ + var text = that.labelForCurrentLanguage(); + myWidth = measureTextWidth(text, "text") + 20; + // check for sub names; + var indicatorText = that.indicationString(); + var indicatorWidth = measureTextWidth(indicatorText, "subtext") + 20; + if ( indicatorWidth > myWidth ) + myWidth = indicatorWidth; + + return myWidth; + }; + + function measureTextWidth( text, textStyle ){ + // Set a default value + if ( !textStyle ) { + textStyle = "text"; + } + var d = d3.select("body") + .append("div") + .attr("class", textStyle) + .attr("id", "width-test") // tag this element to identify it + .attr("style", "position:absolute; float:left; white-space:nowrap; visibility:hidden;") + .text(text), + w = document.getElementById("width-test").offsetWidth; + d.remove(); + return w; + } + + this.textWidth = function (){ + return myWidth; + }; + this.width = function (){ + return myWidth; + }; + + this.animateDynamicLabelWidth = function ( dynamic ){ + that.removeHalo(); + if ( shapeElement === undefined ) {// this handles setOperatorProperties which dont have a shapeElement! + return; + } + + var h = that.height(); + if ( dynamic === true ) { + myWidth = Math.min(that.getMyWidth(), graph.options().maxLabelWidth()); + shapeElement.transition().tween("attr", function (){ + }) + .ease('linear') + .duration(100) + .attr({ x: -myWidth / 2, y: -h / 2, width: myWidth, height: h }) + .each("end", function (){ + that.updateTextElement(); + }); + } else { + // Static width for property labels = 80 + myWidth = defaultWidth; + that.updateTextElement(); + shapeElement.transition().tween("attr", function (){ + }) + .ease('linear') + .duration(100) + .attr({ x: -myWidth / 2, y: -h / 2, width: myWidth, height: h }); + } + if ( that.pinned() === true && pinGroupElement ) { + var dx = -0.5 * myWidth + 10, + dy = -25; + pinGroupElement.transition() + .tween("attr.translate", function (){ + }) + .attr("transform", "translate(" + dx + "," + dy + ")") + .ease('linear') + .duration(100); + } + }; + + this.redrawLabelText = function (){ + textElement.remove(); + that.addTextLabelElement(); + that.animateDynamicLabelWidth(graph.options().dynamicLabelWidth()); + shapeElement.select("title").text(that.labelForCurrentLanguage()); + }; + + this.addTextLabelElement = function (){ + var labelContainer = that.labelElement(); + + var equivalentsString = that.equivalentsString(); + var suffixForFollowingEquivalents = equivalentsString ? "," : ""; + + textElement = new CenteringTextElement(labelContainer, this.backgroundColor()); + textElement.addText(this.labelForCurrentLanguage(), "", suffixForFollowingEquivalents); + textElement.addEquivalents(equivalentsString); + textElement.addSubText(this.indicationString()); + }; + + this.updateTextElement = function (){ + textElement.updateAllTextElements(); + }; + this.enableEditing = function ( autoEditing ){ + if ( autoEditing === false ) + return; + that.raiseDoubleClickEdit(true); + }; + + this.raiseDoubleClickEdit = function ( forceIRISync ){ + d3.selectAll(".foreignelements").remove(); + if ( that.labelElement() === undefined || this.type() === "owl:disjointWith" || this.type() === "rdfs:subClassOf" ) { + console.log("No Container found"); + return; + } + if ( fobj !== undefined ) { + that.labelElement().selectAll(".foreignelements").remove(); + } + backupFullIri = undefined; + graph.options().focuserModule().handle(undefined); + graph.options().focuserModule().handle(that); + that.editingTextElement = true; + ignoreLocalHoverEvents = true; + that.labelElement().selectAll("rect").classed("hoveredForEditing", true); + that.frozen(true); + graph.killDelayedTimer(); + graph.ignoreOtherHoverEvents(false); + fobj = that.labelElement().append("foreignObject") + .attr("x", -0.5 * that.textWidth()) + .attr("y", -13) + .attr("height", 25) + .attr("class", "foreignelements") + .on("dragstart", function (){ + return false; + }) // remove drag operations of text element) + .attr("width", that.textWidth() - 2); + // adding a Style to the fObject + // + // + // + var editText = fobj.append("xhtml:input") + .attr("class", "nodeEditSpan") + .attr("id", that.id()) + .attr("align", "center") + .attr("contentEditable", "true") + .on("dragstart", function (){ + return false; + }); // remove drag operations of text element) + + var bgColor = '#f00'; + var txtWidth = that.textWidth() - 2; + editText.style({ + // 'line-height': '30px', + 'align': 'center', + 'color': 'black', + 'width': txtWidth + "px", + 'background-color': bgColor, + 'border-bottom': '2px solid black' + }); + var txtNode = editText.node(); + txtNode.value = that.labelForCurrentLanguage(); + txtNode.focus(); + txtNode.select(); + if ( d3.event.stopPropagation ) d3.event.stopPropagation(); + if ( d3.event.sourceEvent && d3.event.sourceEvent.stopPropagation ) d3.event.sourceEvent.stopPropagation(); + + // add some events that relate to this object + editText.on("click", function (){ + if ( d3.event.stopPropagation ) d3.event.stopPropagation(); + if ( d3.event.sourceEvent && d3.event.sourceEvent.stopPropagation ) d3.event.sourceEvent.stopPropagation(); + + }); + // // remove hover Events for now; + editText.on("mouseout", function (){ + if ( d3.event.stopPropagation ) d3.event.stopPropagation(); + if ( d3.event.sourceEvent && d3.event.sourceEvent.stopPropagation ) d3.event.sourceEvent.stopPropagation(); + }); + editText.on("mousedown", function (){ + if ( d3.event.stopPropagation ) d3.event.stopPropagation(); + if ( d3.event.sourceEvent && d3.event.sourceEvent.stopPropagation ) d3.event.sourceEvent.stopPropagation(); + }) + .on("keydown", function (){ + + if ( d3.event.keyCode === 13 ) { + this.blur(); + that.frozen(false); // << releases the not after selection + that.locked(false); + } + }) + .on("keyup", function (){ + if ( forceIRISync ) { + var labelName = editText.node().value; + var resourceName = labelName.replaceAll(" ", "_"); + var syncedIRI = that.baseIri() + resourceName; + backupFullIri = syncedIRI; + + d3.select("#element_iriEditor").node().title = syncedIRI; + d3.select("#element_iriEditor").node().value = graph.options().prefixModule().getPrefixRepresentationForFullURI(syncedIRI); + } + d3.select("#element_labelEditor").node().value = editText.node().value; + + }) + .on("blur", function (){ + + + that.editingTextElement = false; + ignoreLocalHoverEvents = false; + that.labelElement().selectAll("rect").classed("hoveredForEditing", false); + var newLabel = editText.node().value; + that.labelElement().selectAll(".foreignelements").remove(); + // that.setLabelForCurrentLanguage(classNameConvention(editText.node().value)); + that.label(newLabel); + that.backupLabel(newLabel); + that.redrawLabelText(); + updateHoverElements(true); + graph.showHoverElementsAfterAnimation(that, false); + graph.ignoreOtherHoverEvents(false); + + + that.frozen(graph.paused()); + that.locked(graph.paused()); + that.domain().frozen(graph.paused()); + that.domain().locked(graph.paused()); + that.range().frozen(graph.paused()); + that.range().locked(graph.paused()); + graph.removeEditElements(); + if ( backupFullIri ) { + // console.log("Checking if element is Identical ?"); + var sanityCheckResult = graph.options().editSidebar().checkProperIriChange(that, backupFullIri); + if ( sanityCheckResult !== false ) { + graph.options().warningModule().showWarning("Already seen this property", + "Input IRI: " + backupFullIri + " for element: " + that.labelForCurrentLanguage() + " already been set", + "Continuing with duplicate property!", 1, false, sanityCheckResult); + } + that.iri(backupFullIri); + } + graph.options().focuserModule().handle(undefined); + graph.options().focuserModule().handle(that); + graph.updatePropertyDraggerElements(that); + + + }); // add a foreiner element to this thing; + + }; + + // update hover elements + function updateHoverElements( enable ){ + if ( graph.ignoreOtherHoverEvents() === false ) { + var inversed = false; + if ( that.inverse() ) { + inversed = true; + } + if ( enable === true ) { + graph.activateHoverElementsForProperties(enable, that, inversed); + } + } + } + + that.copyInformation = function ( other ){ + that.label(other.label()); + that.iri(other.iri()); + that.baseIri(other.baseIri()); + if ( other.type() === "owl:ObjectProperty" || + other.type() === "owl:DatatypeProperty" ) { + that.backupLabel(other.label()); + // console.log("copied backup label"+that.backupLabel()); + } + if ( other.backupLabel() !== undefined ) { + that.backupLabel(other.backupLabel()); + } + }; + + forceLayoutNodeFunctions.addTo(this); + }; + + Base.prototype = Object.create(BaseElement.prototype); + Base.prototype.constructor = Base; + + Base.prototype.height = function (){ + return labelHeight; + }; + + Base.prototype.width = function (){ + return labelWidth; + }; + + Base.prototype.actualRadius = function (){ + return smallestRadius; + }; + + Base.prototype.textWidth = Base.prototype.width; + + + return Base; + }()); + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 43 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains a collection of mathematical functions with some additional data + * used for WebVOWL. + */ + module.exports = (function (){ + + var math = {}, + loopFunction = d3.svg.line() + .x(function ( d ){ + return d.x; + }) + .y(function ( d ){ + return d.y; + }) + .interpolate("cardinal") + .tension(-1); + + + /** + * Calculates the normal vector of the path between the two nodes. + * @param source the first node + * @param target the second node + * @param length the length of the calculated normal vector + * @returns {{x: number, y: number}} + */ + math.calculateNormalVector = function ( source, target, length ){ + var dx = target.x - source.x, + dy = target.y - source.y; + + var nx = -dy, + ny = dx; + + var vlength = Math.sqrt(nx * nx + ny * ny); + + var ratio = vlength !== 0 ? length / vlength : 0; + + return { "x": nx * ratio, "y": ny * ratio }; + }; + + /** + * Calculates the path for a link, if it is a loop. Currently only working for circlular nodes. + * @param link the link + * @returns {*} + */ + + + + math.getLoopPoints = function ( link ){ + var node = link.domain(), + label = link.label(); + + var fairShareLoopAngle = 360 / link.loops().length, + fairShareLoopAngleWithMargin = fairShareLoopAngle * 0.8, + loopAngle = Math.min(60, fairShareLoopAngleWithMargin); + + if ( label.increasedLoopAngle === true ) + loopAngle = 120; + + + var dx = label.x - node.x, + dy = label.y - node.y, + labelRadian = Math.atan2(dy, dx), + labelAngle = calculateAngle(labelRadian); + + var startAngle = labelAngle - loopAngle / 2, + endAngle = labelAngle + loopAngle / 2; + + + var arcFrom = calculateRadian(startAngle), + arcTo = calculateRadian(endAngle), + + x1 = Math.cos(arcFrom) * node.actualRadius(), + y1 = Math.sin(arcFrom) * node.actualRadius(), + + x2 = Math.cos(arcTo) * node.actualRadius(), + y2 = Math.sin(arcTo) * node.actualRadius(), + + fixPoint1 = { "x": node.x + x1, "y": node.y + y1 }, + fixPoint2 = { "x": node.x + x2, "y": node.y + y2 }; + + return [fixPoint1, fixPoint2]; + }; + math.calculateLoopPath = function ( link ){ + var node = link.domain(), + label = link.label(); + + + var fairShareLoopAngle = 360 / link.loops().length, + fairShareLoopAngleWithMargin = fairShareLoopAngle * 0.8, + loopAngle = Math.min(60, fairShareLoopAngleWithMargin); + + if ( label.increasedLoopAngle === true ) + loopAngle = 120; + + var dx = label.x - node.x, + dy = label.y - node.y, + labelRadian = Math.atan2(dy, dx), + labelAngle = calculateAngle(labelRadian); + + var startAngle = labelAngle - loopAngle / 2, + endAngle = labelAngle + loopAngle / 2; + + var arcFrom = calculateRadian(startAngle), + arcTo = calculateRadian(endAngle), + + x1 = Math.cos(arcFrom) * node.actualRadius(), + y1 = Math.sin(arcFrom) * node.actualRadius(), + + x2 = Math.cos(arcTo) * node.actualRadius(), + y2 = Math.sin(arcTo) * node.actualRadius(), + + fixPoint1 = { "x": node.x + x1, "y": node.y + y1 }, + fixPoint2 = { "x": node.x + x2, "y": node.y + y2 }; + + return loopFunction([fixPoint1, link.label(), fixPoint2]); + }; + + math.calculateLoopPoints = function ( link ){ + var node = link.domain(), + label = link.label(); + + var fairShareLoopAngle = 360 / link.loops().length, + fairShareLoopAngleWithMargin = fairShareLoopAngle * 0.8, + loopAngle = Math.min(60, fairShareLoopAngleWithMargin); + + var dx = label.x - node.x, + dy = label.y - node.y, + labelRadian = Math.atan2(dy, dx), + labelAngle = calculateAngle(labelRadian); + + var startAngle = labelAngle - loopAngle / 2, + endAngle = labelAngle + loopAngle / 2; + + var arcFrom = calculateRadian(startAngle), + arcTo = calculateRadian(endAngle), + + x1 = Math.cos(arcFrom) * node.actualRadius(), + y1 = Math.sin(arcFrom) * node.actualRadius(), + + x2 = Math.cos(arcTo) * (node.actualRadius()), + y2 = Math.sin(arcTo) * (node.actualRadius()), + + fixPoint1 = { "x": node.x + x1, "y": node.y + y1 }, + fixPoint2 = { "x": node.x + x2, "y": node.y + y2 }; + + return [fixPoint1, link.label(), fixPoint2]; + }; + + /** + * @param angle + * @returns {number} the radian of the angle + */ + function calculateRadian( angle ){ + angle = angle % 360; + if ( angle < 0 ) { + angle = angle + 360; + } + return (Math.PI * angle) / 180; + } + + /** + * @param radian + * @returns {number} the angle of the radian + */ + function calculateAngle( radian ){ + return radian * (180 / Math.PI); + } + + /** + * Calculates the point where the link between the source and target node + * intersects the border of the target node. + * @param source the source node + * @param target the target node + * @param additionalDistance additional distance the + * @returns {{x: number, y: number}} + */ + math.calculateIntersection = function ( source, target, additionalDistance ){ + var dx = target.x - source.x, + dy = target.y - source.y, + length = Math.sqrt(dx * dx + dy * dy); + + if ( length === 0 ) { + return { x: source.x, y: source.y }; + } + + var innerDistance = target.distanceToBorder(dx, dy); + + var ratio = (length - (innerDistance + additionalDistance)) / length, + x = dx * ratio + source.x, + y = dy * ratio + source.y; + + return { x: x, y: y }; + }; + + /** + * Calculates the position between the two points. + * @param firstPoint + * @param secondPoint + * @returns {{x: number, y: number}} + */ + math.calculateCenter = function ( firstPoint, secondPoint ){ + return { + x: (firstPoint.x + secondPoint.x) / 2, + y: (firstPoint.y + secondPoint.y) / 2 + }; + }; + + + return function (){ + /* Use a function here to keep a consistent style like webvowl.path.to.module() + * despite having just a single math object. */ + return math; + }; + })(); + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 44 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.attributes(["datatype"]) + .styleClass("datatypeproperty") + .type("owl:DatatypeProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 45 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.attributes(["deprecated"]) + .styleClass("deprecatedproperty") + .type("owl:DeprecatedProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 46 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + var CenteringTextElement = __webpack_require__(14); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + var label = "Disjoint With"; + var shapeElement; + // Disallow overwriting the label + this.label = function ( p ){ + if ( !arguments.length ) return label; + return this; + }; + + this.linkType("dashed") + .styleClass("disjointwith") + .type("owl:disjointWith"); + + this.drawLabel = function ( labelContainer ){ + shapeElement = this.addRect(labelContainer); + + labelContainer.append("circle") + .classed("symbol", true) + .classed("fineline", true) + .classed("embedded", true) + .attr("cx", -12.5) + .attr("r", 10); + + labelContainer.append("circle") + .classed("symbol", true) + .classed("fineline", true) + .classed("embedded", true) + .attr("cx", 12.5) + .attr("r", 10); + + var textElement = new CenteringTextElement(labelContainer, this.backgroundColor()); + if ( !graph.options().compactNotation() ) { + textElement.addSubText("disjoint"); + } + textElement.translation(0, 20); + }; + this.getShapeElement = function (){ + return shapeElement; + }; + this.markerElement = function (){ + return undefined; + }; + + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 47 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.styleClass("equivalentproperty") + .type("owl:equivalentProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 48 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.attributes(["functional"]) + .styleClass("functionalproperty") + .type("owl:FunctionalProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 49 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.attributes(["inverse functional"]) + .styleClass("inversefunctionalproperty") + .type("owl:InverseFunctionalProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 50 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.attributes(["object"]) + .styleClass("objectproperty") + .type("owl:ObjectProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + + + +/***/ }), +/* 51 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + var superGenerateCardinalityText = this.generateCardinalityText; + + this.linkType("values-from") + .markerType("filled values-from") + .styleClass("somevaluesfromproperty") + .type("owl:someValuesFrom"); + + this.generateCardinalityText = function (){ + var cardinalityText = "E"; + + var superCardinalityText = superGenerateCardinalityText(); + if ( superCardinalityText ) { + cardinalityText += ", " + superCardinalityText; + } + + return cardinalityText; + }; + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + + + +/***/ }), +/* 52 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.attributes(["symmetric"]) + .styleClass("symmetricproperty") + .type("owl:SymmetricProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 53 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.attributes(["transitive"]) + .styleClass("transitiveproperty") + .type("owl:TransitiveProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 54 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.attributes(["rdf"]) + .styleClass("rdfproperty") + .type("rdf:Property"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 55 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + var that = this, + superDrawFunction = that.draw, + label = "Subclass of"; + + this.draw = function ( labelGroup ){ + that.labelVisible(!graph.options().compactNotation()); + return superDrawFunction(labelGroup); + }; + + // Disallow overwriting the label + this.label = function ( p ){ + if ( !arguments.length ) return label; + return this; + }; + + this.linkType("dotted") + .markerType("white") + .styleClass("subclass") + .type("rdfs:subClassOf"); + + that.baseIri("http://www.w3.org/2000/01/rdf-schema#"); + that.iri("http://www.w3.org/2000/01/rdf-schema#subClassOf"); + + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 56 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.labelVisible(false) + .linkType("dashed") + .markerType("white") + .styleClass("setoperatorproperty") + .type("setOperatorProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 57 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var _ = __webpack_require__(58); + var math = __webpack_require__(43)(); + var linkCreator = __webpack_require__(60)(); + var elementTools = __webpack_require__(63)(); + // add some maps for nodes and properties -- used for object generation + var nodePrototypeMap = __webpack_require__(5)(); + var propertyPrototypeMap = __webpack_require__(40)(); + + + module.exports = function ( graphContainerSelector ){ + var graph = {}, + CARDINALITY_HDISTANCE = 20, + CARDINALITY_VDISTANCE = 10, + curveFunction = d3.svg.line() + .x(function ( d ){ + return d.x; + }) + .y(function ( d ){ + return d.y; + }) + .interpolate("cardinal"), + options = __webpack_require__(64)(), + parser = __webpack_require__(65)(graph), + language = "default", + paused = false, + // Container for visual elements + graphContainer, + nodeContainer, + labelContainer, + cardinalityContainer, + linkContainer, + // Visual elements + nodeElements, + initialLoad = true, + updateRenderingDuringSimulation = false, + labelGroupElements, + linkGroups, + linkPathElements, + cardinalityElements, + // Internal data + classNodes, + labelNodes, + links, + properties, + unfilteredData, + // Graph behaviour + force, + dragBehaviour, + zoomFactor = 1.0, + centerGraphViewOnLoad = false, + transformAnimation = false, + graphTranslation = [0, 0], + graphUpdateRequired = false, + pulseNodeIds = [], + nodeArrayForPulse = [], + nodeMap = [], + locationId = 0, + defaultZoom = 1.0, + defaultTargetZoom = 0.8, + global_dof = -1, + touchDevice = false, + last_touch_time, + originalD3_dblClickFunction = null, + originalD3_touchZoomFunction = null, + + // editing elements + deleteGroupElement, + addDataPropertyGroupElement, + editContainer, + draggerLayer = null, + draggerObjectsArray = [], + delayedHider, + nodeFreezer, + hoveredNodeElement = null, + currentlySelectedNode = null, + hoveredPropertyElement = null, + draggingStarted = false, + frozenDomainForPropertyDragger, + frozenRangeForPropertyDragger, + + eP = 0, // id for new properties + eN = 0, // id for new Nodes + editMode = true, + debugContainer = d3.select("#FPS_Statistics"), + finishedLoadingSequence = false, + + ignoreOtherHoverEvents = false, + forceNotZooming = false, + now, then, // used for fps computation + showFPS = false, + seenEditorHint = false, + seenFilterWarning = false, + showFilterWarning = false, + + keepDetailsCollapsedOnLoading = true, + adjustingGraphSize = false, + showReloadButtonAfterLayoutOptimization = false, + zoom; + //var prefixModule=require("./prefixRepresentationModule")(graph); + var NodePrototypeMap = createLowerCasePrototypeMap(nodePrototypeMap); + var PropertyPrototypeMap = createLowerCasePrototypeMap(propertyPrototypeMap); + var classDragger = __webpack_require__(68)(graph); + var rangeDragger = __webpack_require__(69)(graph); + var domainDragger = __webpack_require__(70)(graph); + var shadowClone = __webpack_require__(71)(graph); + + graph.math = function (){ + return math; + }; + /** --------------------------------------------------------- **/ + /** -- getter and setter definitions -- **/ + /** --------------------------------------------------------- **/ + graph.isEditorMode = function (){ + return editMode; + }; + graph.getGlobalDOF = function (){ + return global_dof; + }; + graph.setGlobalDOF = function ( val ){ + global_dof = val; + }; + + graph.updateZoomSliderValueFromOutside = function (){ + graph.options().zoomSlider().updateZoomSliderValue(zoomFactor); + }; + + graph.setDefaultZoom = function ( val ){ + defaultZoom = val; + graph.reset(); + graph.options().zoomSlider().updateZoomSliderValue(defaultZoom); + }; + graph.setTargetZoom = function ( val ){ + defaultTargetZoom = val; + }; + graph.graphOptions = function (){ + return options; + }; + + graph.scaleFactor = function (){ + return zoomFactor; + }; + graph.translation = function (){ + return graphTranslation; + }; + + // Returns the visible nodes + graph.graphNodeElements = function (){ + return nodeElements; + }; + // Returns the visible Label Nodes + graph.graphLabelElements = function (){ + return labelNodes; + }; + + graph.graphLinkElements = function (){ + return links; + }; + + graph.setSliderZoom = function ( val ){ + + var cx = 0.5 * graph.options().width(); + var cy = 0.5 * graph.options().height(); + var cp = getWorldPosFromScreen(cx, cy, graphTranslation, zoomFactor); + var sP = [cp.x, cp.y, graph.options().height() / zoomFactor]; + var eP = [cp.x, cp.y, graph.options().height() / val]; + var pos_intp = d3.interpolateZoom(sP, eP); + + graphContainer.attr("transform", transform(sP, cx, cy)) + .transition() + .duration(1) + .attrTween("transform", function (){ + return function ( t ){ + return transform(pos_intp(t), cx, cy); + }; + }) + .each("end", function (){ + graphContainer.attr("transform", "translate(" + graphTranslation + ")scale(" + zoomFactor + ")"); + zoom.translate(graphTranslation); + zoom.scale(zoomFactor); + graph.options().zoomSlider().updateZoomSliderValue(zoomFactor); + }); + }; + + + graph.setZoom = function ( value ){ + zoom.scale(value); + }; + + graph.setTranslation = function ( translation ){ + zoom.translate([translation[0], translation[1]]); + }; + + graph.options = function (){ + return options; + }; + // search functionality + graph.getUpdateDictionary = function (){ + return parser.getDictionary(); + }; + + graph.language = function ( newLanguage ){ + if ( !arguments.length ) return language; + + // Just update if the language changes + if ( language !== newLanguage ) { + language = newLanguage || "default"; + redrawContent(); + recalculatePositions(); + graph.options().searchMenu().requestDictionaryUpdate(); + graph.resetSearchHighlight(); + } + return graph; + }; + + + /** --------------------------------------------------------- **/ + /** graph / rendering related functions **/ + /** --------------------------------------------------------- **/ + + // Initializes the graph. + function initializeGraph(){ + + options.graphContainerSelector(graphContainerSelector); + var moved = false; + force = d3.layout.force() + .on("tick", hiddenRecalculatePositions); + + dragBehaviour = d3.behavior.drag() + .origin(function ( d ){ + return d; + }) + .on("dragstart", function ( d ){ + d3.event.sourceEvent.stopPropagation(); // Prevent panning + graph.ignoreOtherHoverEvents(true); + if ( d.type && d.type() === "Class_dragger" ) { + classDragger.mouseButtonPressed = true; + clearTimeout(delayedHider); + classDragger.selectedViaTouch(true); + d.parentNode().locked(true); + draggingStarted = true; + } else if ( d.type && d.type() === "Range_dragger" ) { + graph.ignoreOtherHoverEvents(true); + clearTimeout(delayedHider); + frozenDomainForPropertyDragger = shadowClone.parentNode().domain(); + frozenRangeForPropertyDragger = shadowClone.parentNode().range(); + shadowClone.setInitialPosition(); + shadowClone.hideClone(false); + shadowClone.hideParentProperty(true); + shadowClone.updateElement(); + deleteGroupElement.classed("hidden", true); + addDataPropertyGroupElement.classed("hidden", true); + frozenDomainForPropertyDragger.frozen(true); + frozenDomainForPropertyDragger.locked(true); + frozenRangeForPropertyDragger.frozen(true); + frozenRangeForPropertyDragger.locked(true); + domainDragger.updateElement(); + domainDragger.mouseButtonPressed = true; + rangeDragger.updateElement(); + rangeDragger.mouseButtonPressed = true; + // shadowClone.setPosition(d.x, d.y); + + + } else if ( d.type && d.type() === "Domain_dragger" ) { + graph.ignoreOtherHoverEvents(true); + clearTimeout(delayedHider); + frozenDomainForPropertyDragger = shadowClone.parentNode().domain(); + frozenRangeForPropertyDragger = shadowClone.parentNode().range(); + shadowClone.setInitialPosition(); + shadowClone.hideClone(false); + shadowClone.hideParentProperty(true); + shadowClone.updateElement(); + deleteGroupElement.classed("hidden", true); + addDataPropertyGroupElement.classed("hidden", true); + + frozenDomainForPropertyDragger.frozen(true); + frozenDomainForPropertyDragger.locked(true); + frozenRangeForPropertyDragger.frozen(true); + frozenRangeForPropertyDragger.locked(true); + domainDragger.updateElement(); + domainDragger.mouseButtonPressed = true; + rangeDragger.updateElement(); + rangeDragger.mouseButtonPressed = true; + } + else { + d.locked(true); + moved = false; + } + }) + .on("drag", function ( d ){ + + if ( d.type && d.type() === "Class_dragger" ) { + clearTimeout(delayedHider); + classDragger.setPosition(d3.event.x, d3.event.y); + } else if ( d.type && d.type() === "Range_dragger" ) { + clearTimeout(delayedHider); + rangeDragger.setPosition(d3.event.x, d3.event.y); + shadowClone.setPosition(d3.event.x, d3.event.y); + domainDragger.updateElementViaRangeDragger(d3.event.x, d3.event.y); + } + else if ( d.type && d.type() === "Domain_dragger" ) { + clearTimeout(delayedHider); + domainDragger.setPosition(d3.event.x, d3.event.y); + shadowClone.setPositionDomain(d3.event.x, d3.event.y); + rangeDragger.updateElementViaDomainDragger(d3.event.x, d3.event.y); + } + + else { + d.px = d3.event.x; + d.py = d3.event.y; + force.resume(); + updateHaloRadius(); + moved = true; + if ( d.renderType && d.renderType() === "round" ) { + classDragger.setParentNode(d); + } + + } + }) + .on("dragend", function ( d ){ + graph.ignoreOtherHoverEvents(false); + if ( d.type && d.type() === "Class_dragger" ) { + var nX = classDragger.x; + var nY = classDragger.y; + clearTimeout(delayedHider); + classDragger.mouseButtonPressed = false; + classDragger.selectedViaTouch(false); + d.setParentNode(d.parentNode()); + + var draggerEndPos = [nX, nY]; + var targetNode = graph.getTargetNode(draggerEndPos); + if ( targetNode ) { + createNewObjectProperty(d.parentNode(), targetNode, draggerEndPos); + } + if ( touchDevice === false ) { + editElementHoverOut(); + } + draggingStarted = false; + } else if ( d.type && d.type() === "Range_dragger" ) { + graph.ignoreOtherHoverEvents(false); + frozenDomainForPropertyDragger.frozen(false); + frozenDomainForPropertyDragger.locked(false); + frozenRangeForPropertyDragger.frozen(false); + frozenRangeForPropertyDragger.locked(false); + rangeDragger.mouseButtonPressed = false; + domainDragger.mouseButtonPressed = false; + domainDragger.updateElement(); + rangeDragger.updateElement(); + shadowClone.hideClone(true); + var rX = rangeDragger.x; + var rY = rangeDragger.y; + var rangeDraggerEndPos = [rX, rY]; + var targetRangeNode = graph.getTargetNode(rangeDraggerEndPos); + if ( elementTools.isDatatype(targetRangeNode) === true ) { + targetRangeNode = null; + console.log("---------------TARGET NODE IS A DATATYPE/ LITERAL ------------"); + } + + if ( targetRangeNode === null ) { + d.reDrawEverthing(); + shadowClone.hideParentProperty(false); + } + else { + d.updateRange(targetRangeNode); + graph.update(); + shadowClone.hideParentProperty(false); + } + } else if ( d.type && d.type() === "Domain_dragger" ) { + graph.ignoreOtherHoverEvents(false); + frozenDomainForPropertyDragger.frozen(false); + frozenDomainForPropertyDragger.locked(false); + frozenRangeForPropertyDragger.frozen(false); + frozenRangeForPropertyDragger.locked(false); + rangeDragger.mouseButtonPressed = false; + domainDragger.mouseButtonPressed = false; + domainDragger.updateElement(); + rangeDragger.updateElement(); + shadowClone.hideClone(true); + + var dX = domainDragger.x; + var dY = domainDragger.y; + var domainDraggerEndPos = [dX, dY]; + var targetDomainNode = graph.getTargetNode(domainDraggerEndPos); + if ( elementTools.isDatatype(targetDomainNode) === true ) { + targetDomainNode = null; + console.log("---------------TARGET NODE IS A DATATYPE/ LITERAL ------------"); + } + shadowClone.hideClone(true); + if ( targetDomainNode === null ) { + d.reDrawEverthing(); + shadowClone.hideParentProperty(false); + } + else { + d.updateDomain(targetDomainNode); + graph.update(); + shadowClone.hideParentProperty(false); + } + } + + else { + d.locked(false); + var pnp = graph.options().pickAndPinModule(); + if ( pnp.enabled() === true && moved === true ) { + if ( d.id ) { // node + pnp.handle(d, true); + } + if ( d.property ) { + pnp.handle(d.property(), true); + } + } + } + }); + + // Apply the zooming factor. + zoom = d3.behavior.zoom() + .duration(150) + .scaleExtent([options.minMagnification(), options.maxMagnification()]) + .on("zoom", zoomed); + + draggerObjectsArray.push(classDragger); + draggerObjectsArray.push(rangeDragger); + draggerObjectsArray.push(domainDragger); + draggerObjectsArray.push(shadowClone); + force.stop(); + } + + graph.lazyRefresh = function (){ + redrawContent(); + recalculatePositions(); + }; + + graph.adjustingGraphSize = function ( val ){ + adjustingGraphSize = val; + }; + + graph.showReloadButtonAfterLayoutOptimization = function ( show ){ + showReloadButtonAfterLayoutOptimization = show; + }; + + + function hiddenRecalculatePositions(){ + finishedLoadingSequence = false; + if ( graph.options().loadingModule().successfullyLoadedOntology() === false ) { + force.stop(); + d3.select("#progressBarValue").node().innerHTML = ""; + graph.updateProgressBarMode(); + graph.options().loadingModule().showErrorDetailsMessage(hiddenRecalculatePositions); + if ( keepDetailsCollapsedOnLoading && adjustingGraphSize === false ) { + graph.options().loadingModule().collapseDetails("hiddenRecalculatePositions"); + } + return; + } + if ( updateRenderingDuringSimulation === false ) { + var value = 1.0 - 10 * force.alpha(); + var percent = parseInt(200 * value) + "%"; + graph.options().loadingModule().setPercentValue(percent); + d3.select("#progressBarValue").style("width", percent); + d3.select("#progressBarValue").node().innerHTML = percent; + + if ( value > 0.49 ) { + updateRenderingDuringSimulation = true; + // show graph container; + if ( graphContainer ) { + graphContainer.style("opacity", "1"); + percent = "100%"; + d3.select("#progressBarValue").style("width", percent); + d3.select("#progressBarValue").node().innerHTML = percent; + graph.options().ontologyMenu().append_message_toLastBulletPoint("done"); + d3.select("#reloadCachedOntology").classed("hidden", !showReloadButtonAfterLayoutOptimization); + if ( showFilterWarning === true && seenFilterWarning === false ) { + graph.options().warningModule().showFilterHint(); + seenFilterWarning = true; + } + } + + if ( initialLoad ) { + if ( graph.paused() === false ) + force.resume(); // resume force + initialLoad = false; + + } + + + finishedLoadingSequence = true; + if ( showFPS === true ) { + force.on("tick", recalculatePositionsWithFPS); + recalculatePositionsWithFPS(); + } + else { + force.on("tick", recalculatePositions); + recalculatePositions(); + } + + if ( centerGraphViewOnLoad === true && force.nodes().length > 0 ) { + if ( force.nodes().length < 10 ) graph.forceRelocationEvent(true); // uses dynamic zoomer; + else graph.forceRelocationEvent(); + centerGraphViewOnLoad = false; + // console.log("--------------------------------------") + } + + + graph.showEditorHintIfNeeded(); + + if ( graph.options().loadingModule().missingImportsWarning() === false ) { + graph.options().loadingModule().hideLoadingIndicator(); + graph.options().ontologyMenu().append_bulletPoint("Successfully loaded ontology"); + graph.options().loadingModule().setSuccessful(); + } else { + graph.options().loadingModule().showWarningDetailsMessage(); + graph.options().ontologyMenu().append_bulletPoint("Loaded ontology with warnings"); + } + } + } + } + + graph.showEditorHintIfNeeded = function (){ + if ( seenEditorHint === false && editMode === true ) { + seenEditorHint = true; + graph.options().warningModule().showEditorHint(); + } + }; + + graph.setForceTickFunctionWithFPS = function (){ + showFPS = true; + if ( force && finishedLoadingSequence === true ) { + force.on("tick", recalculatePositionsWithFPS); + } + + }; + graph.setDefaultForceTickFunction = function (){ + showFPS = false; + if ( force && finishedLoadingSequence === true ) { + force.on("tick", recalculatePositions); + } + }; + function recalculatePositionsWithFPS(){ + // compute the fps + + recalculatePositions(); + now = Date.now(); + var diff = now - then; + var fps = (1000 / (diff)).toFixed(2); + + debugContainer.node().innerHTML = "FPS: " + fps + "
    " + "Nodes: " + force.nodes().length + "
    " + "Links: " + force.links().length; + then = Date.now(); + + } + + function recalculatePositions(){ + // Set node positions + + + // add switch for edit mode to make this faster; + if ( !editMode ) { + nodeElements.attr("transform", function ( node ){ + return "translate(" + node.x + "," + node.y + ")"; + }); + + // Set label group positions + labelGroupElements.attr("transform", function ( label ){ + var position; + + // force centered positions on single-layered links + var link = label.link(); + if ( link.layers().length === 1 && !link.loops() ) { + var linkDomainIntersection = math.calculateIntersection(link.range(), link.domain(), 0); + var linkRangeIntersection = math.calculateIntersection(link.domain(), link.range(), 0); + position = math.calculateCenter(linkDomainIntersection, linkRangeIntersection); + label.x = position.x; + label.y = position.y; + } + return "translate(" + label.x + "," + label.y + ")"; + }); + // Set link paths and calculate additional information + linkPathElements.attr("d", function ( l ){ + if ( l.isLoop() ) { + return math.calculateLoopPath(l); + } + var curvePoint = l.label(); + var pathStart = math.calculateIntersection(curvePoint, l.domain(), 1); + var pathEnd = math.calculateIntersection(curvePoint, l.range(), 1); + + return curveFunction([pathStart, curvePoint, pathEnd]); + }); + + // Set cardinality positions + cardinalityElements.attr("transform", function ( property ){ + + var label = property.link().label(), + pos = math.calculateIntersection(label, property.range(), CARDINALITY_HDISTANCE), + normalV = math.calculateNormalVector(label, property.range(), CARDINALITY_VDISTANCE); + + return "translate(" + (pos.x + normalV.x) + "," + (pos.y + normalV.y) + ")"; + }); + + + updateHaloRadius(); + return; + } + + // TODO: this is Editor redraw function // we need to make this faster!! + + + nodeElements.attr("transform", function ( node ){ + return "translate(" + node.x + "," + node.y + ")"; + }); + + // Set label group positions + labelGroupElements.attr("transform", function ( label ){ + var position; + + // force centered positions on single-layered links + var link = label.link(); + if ( link.layers().length === 1 && !link.loops() ) { + var linkDomainIntersection = math.calculateIntersection(link.range(), link.domain(), 0); + var linkRangeIntersection = math.calculateIntersection(link.domain(), link.range(), 0); + position = math.calculateCenter(linkDomainIntersection, linkRangeIntersection); + label.x = position.x; + label.y = position.y; + label.linkRangeIntersection = linkRangeIntersection; + label.linkDomainIntersection = linkDomainIntersection; + if ( link.property().focused() === true || hoveredPropertyElement !== undefined ) { + rangeDragger.updateElement(); + domainDragger.updateElement(); + // shadowClone.setPosition(link.property().range().x,link.property().range().y); + // shadowClone.setPositionDomain(link.property().domain().x,link.property().domain().y); + } + } else { + label.linkDomainIntersection = math.calculateIntersection(link.label(), link.domain(), 0); + label.linkRangeIntersection = math.calculateIntersection(link.label(), link.range(), 0); + if ( link.property().focused() === true || hoveredPropertyElement !== undefined ) { + rangeDragger.updateElement(); + domainDragger.updateElement(); + // shadowClone.setPosition(link.property().range().x,link.property().range().y); + // shadowClone.setPositionDomain(link.property().domain().x,link.property().domain().y); + } + + } + return "translate(" + label.x + "," + label.y + ")"; + }); + // Set link paths and calculate additional information + linkPathElements.attr("d", function ( l ){ + if ( l.isLoop() ) { + + var ptrAr = math.getLoopPoints(l); + l.label().linkRangeIntersection = ptrAr[1]; + l.label().linkDomainIntersection = ptrAr[0]; + + if ( l.property().focused() === true || hoveredPropertyElement !== undefined ) { + rangeDragger.updateElement(); + domainDragger.updateElement(); + } + return math.calculateLoopPath(l); + } + var curvePoint = l.label(); + var pathStart = math.calculateIntersection(curvePoint, l.domain(), 1); + var pathEnd = math.calculateIntersection(curvePoint, l.range(), 1); + l.linkRangeIntersection = pathStart; + l.linkDomainIntersection = pathEnd; + if ( l.property().focused() === true || hoveredPropertyElement !== undefined ) { + domainDragger.updateElement(); + rangeDragger.updateElement(); + // shadowClone.setPosition(l.property().range().x,l.property().range().y); + // shadowClone.setPositionDomain(l.property().domain().x,l.property().domain().y); + } + return curveFunction([pathStart, curvePoint, pathEnd]); + }); + + // Set cardinality positions + cardinalityElements.attr("transform", function ( property ){ + + var label = property.link().label(), + pos = math.calculateIntersection(label, property.range(), CARDINALITY_HDISTANCE), + normalV = math.calculateNormalVector(label, property.range(), CARDINALITY_VDISTANCE); + + return "translate(" + (pos.x + normalV.x) + "," + (pos.y + normalV.y) + ")"; + }); + + if ( hoveredNodeElement ) { + setDeleteHoverElementPosition(hoveredNodeElement); + setAddDataPropertyHoverElementPosition(hoveredNodeElement); + if ( draggingStarted === false ) { + classDragger.setParentNode(hoveredNodeElement); + } + } + if ( hoveredPropertyElement ) { + setDeleteHoverElementPositionProperty(hoveredPropertyElement); + } + + updateHaloRadius(); + } + + graph.updatePropertyDraggerElements = function ( property ){ + if ( property.type() !== "owl:DatatypeProperty" ) { + + shadowClone.setParentProperty(property); + rangeDragger.setParentProperty(property); + rangeDragger.hideDragger(false); + rangeDragger.addMouseEvents(); + domainDragger.setParentProperty(property); + domainDragger.hideDragger(false); + domainDragger.addMouseEvents(); + + } + else { + rangeDragger.hideDragger(true); + domainDragger.hideDragger(true); + shadowClone.hideClone(true); + } + }; + + function addClickEvents(){ + function executeModules( selectedElement ){ + options.selectionModules().forEach(function ( module ){ + module.handle(selectedElement); + }); + } + + nodeElements.on("click", function ( clickedNode ){ + + // manaual double clicker // helper for iphone 6 etc... + if ( touchDevice === true && doubletap() === true ) { + d3.event.stopPropagation(); + if ( editMode === true ) { + clickedNode.raiseDoubleClickEdit(defaultIriValue(clickedNode)); + } + } + else { + executeModules(clickedNode); + } + }); + + nodeElements.on("dblclick", function ( clickedNode ){ + + d3.event.stopPropagation(); + if ( editMode === true ) { + clickedNode.raiseDoubleClickEdit(defaultIriValue(clickedNode)); + } + }); + + labelGroupElements.selectAll(".label").on("click", function ( clickedProperty ){ + executeModules(clickedProperty); + + // this is for enviroments that do not define dblClick function; + if ( touchDevice === true && doubletap() === true ) { + d3.event.stopPropagation(); + if ( editMode === true ) { + clickedProperty.raiseDoubleClickEdit(defaultIriValue(clickedProperty)); + } + } + + // currently removed the selection of an element to invoke the dragger + // if (editMode===true && clickedProperty.editingTextElement!==true) { + // return; + // // We say that Datatype properties are not allowed to have domain range draggers + // if (clickedProperty.focused() && clickedProperty.type() !== "owl:DatatypeProperty") { + // shadowClone.setParentProperty(clickedProperty); + // rangeDragger.setParentProperty(clickedProperty); + // rangeDragger.hideDragger(false); + // rangeDragger.addMouseEvents(); + // domainDragger.setParentProperty(clickedProperty); + // domainDragger.hideDragger(false); + // domainDragger.addMouseEvents(); + // + // if (clickedProperty.domain()===clickedProperty.range()){ + // clickedProperty.labelObject().increasedLoopAngle=true; + // recalculatePositions(); + // + // } + // + // } else if (clickedProperty.focused() && clickedProperty.type() === "owl:DatatypeProperty") { + // shadowClone.setParentProperty(clickedProperty); + // rangeDragger.setParentProperty(clickedProperty); + // rangeDragger.hideDragger(true); + // rangeDragger.addMouseEvents(); + // domainDragger.setParentProperty(clickedProperty); + // domainDragger.hideDragger(false); + // domainDragger.addMouseEvents(); + // + // } + // else { + // rangeDragger.hideDragger(true); + // domainDragger.hideDragger(true); + // if (clickedProperty.domain()===clickedProperty.range()){ + // clickedProperty.labelObject().increasedLoopAngle=false; + // recalculatePositions(); + // + // } + // } + // } + }); + labelGroupElements.selectAll(".label").on("dblclick", function ( clickedProperty ){ + d3.event.stopPropagation(); + if ( editMode === true ) { + clickedProperty.raiseDoubleClickEdit(defaultIriValue(clickedProperty)); + } + + }); + } + + function defaultIriValue( element ){ + // get the iri of that element; + if ( graph.options().getGeneralMetaObject().iri ) { + var str2Compare = graph.options().getGeneralMetaObject().iri + element.id(); + return element.iri() === str2Compare; + } + return false; + } + + /** Adjusts the containers current scale and position. */ + function zoomed(){ + if ( forceNotZooming === true ) { + zoom.translate(graphTranslation); + zoom.scale(zoomFactor); + return; + } + + + var zoomEventByMWheel = false; + if ( d3.event.sourceEvent ) { + if ( d3.event.sourceEvent.deltaY ) zoomEventByMWheel = true; + } + if ( zoomEventByMWheel === false ) { + if ( transformAnimation === true ) { + return; + } + zoomFactor = d3.event.scale; + graphTranslation = d3.event.translate; + graphContainer.attr("transform", "translate(" + graphTranslation + ")scale(" + zoomFactor + ")"); + updateHaloRadius(); + graph.options().zoomSlider().updateZoomSliderValue(zoomFactor); + return; + } + /** animate the transition **/ + zoomFactor = d3.event.scale; + graphTranslation = d3.event.translate; + graphContainer.transition() + .tween("attr.translate", function (){ + return function ( t ){ + transformAnimation = true; + var tr = d3.transform(graphContainer.attr("transform")); + graphTranslation[0] = tr.translate[0]; + graphTranslation[1] = tr.translate[1]; + zoomFactor = tr.scale[0]; + updateHaloRadius(); + graph.options().zoomSlider().updateZoomSliderValue(zoomFactor); + }; + }) + .each("end", function (){ + transformAnimation = false; + }) + .attr("transform", "translate(" + graphTranslation + ")scale(" + zoomFactor + ")") + .ease('linear') + .duration(250); + }// end of zoomed function + + function redrawGraph(){ + remove(); + + graphContainer = d3.selectAll(options.graphContainerSelector()) + .append("svg") + .classed("vowlGraph", true) + .attr("width", options.width()) + .attr("height", options.height()) + .call(zoom) + .append("g"); + // add touch and double click functions + + var svgGraph = d3.selectAll(".vowlGraph"); + originalD3_dblClickFunction = svgGraph.on("dblclick.zoom"); + originalD3_touchZoomFunction = svgGraph.on("touchstart"); + svgGraph.on("touchstart", touchzoomed); + if ( editMode === true ) { + svgGraph.on("dblclick.zoom", graph.modified_dblClickFunction); + } + else { + svgGraph.on("dblclick.zoom", originalD3_dblClickFunction); + } + + } + + function generateEditElements(){ + addDataPropertyGroupElement = editContainer.append('g') + .classed("hidden-in-export", true) + .classed("hidden", true) + .classed("addDataPropertyElement", true) + .attr("transform", "translate(" + 0 + "," + 0 + ")"); + + + addDataPropertyGroupElement.append("circle") + // .classed("deleteElement", true) + .attr("r", 12) + .attr("cx", 0) + .attr("cy", 0) + .append("title").text("Add Datatype Property"); + + addDataPropertyGroupElement.append("line") + // .classed("deleteElementIcon ",true) + .attr("x1", -8) + .attr("y1", 0) + .attr("x2", 8) + .attr("y2", 0) + .append("title").text("Add Datatype Property"); + + addDataPropertyGroupElement.append("line") + // .classed("deleteElementIcon",true) + .attr("x1", 0) + .attr("y1", -8) + .attr("x2", 0) + .attr("y2", 8) + .append("title").text("Add Datatype Property"); + + if ( graph.options().useAccuracyHelper() ) { + addDataPropertyGroupElement.append("circle") + .attr("r", 15) + .attr("cx", -7) + .attr("cy", 7) + .classed("superHiddenElement", true) + .classed("superOpacityElement", !graph.options().showDraggerObject()); + } + + + deleteGroupElement = editContainer.append('g') + .classed("hidden-in-export", true) + .classed("hidden", true) + .classed("deleteParentElement", true) + .attr("transform", "translate(" + 0 + "," + 0 + ")"); + + deleteGroupElement.append("circle") + .attr("r", 12) + .attr("cx", 0) + .attr("cy", 0) + .append("title").text("Delete This Node"); + + var crossLen = 5; + deleteGroupElement.append("line") + .attr("x1", -crossLen) + .attr("y1", -crossLen) + .attr("x2", crossLen) + .attr("y2", crossLen) + .append("title").text("Delete This Node"); + + deleteGroupElement.append("line") + .attr("x1", crossLen) + .attr("y1", -crossLen) + .attr("x2", -crossLen) + .attr("y2", crossLen) + .append("title").text("Delete This Node"); + + if ( graph.options().useAccuracyHelper() ) { + deleteGroupElement.append("circle") + .attr("r", 15) + .attr("cx", 7) + .attr("cy", -7) + .classed("superHiddenElement", true) + .classed("superOpacityElement", !graph.options().showDraggerObject()); + } + + + } + + graph.getUnfilteredData = function (){ + return unfilteredData; + }; + + graph.getClassDataForTtlExport = function (){ + var allNodes = unfilteredData.nodes; + var nodeData = []; + for ( var i = 0; i < allNodes.length; i++ ) { + if ( allNodes[i].type() !== "rdfs:Literal" && + allNodes[i].type() !== "rdfs:Datatype" && + allNodes[i].type() !== "owl:Thing" ) { + nodeData.push(allNodes[i]); + } + } + return nodeData; + }; + + graph.getPropertyDataForTtlExport = function (){ + var propertyData = []; + var allProperties = unfilteredData.properties; + for ( var i = 0; i < allProperties.length; i++ ) { + // currently using only the object properties + if ( allProperties[i].type() === "owl:ObjectProperty" || + allProperties[i].type() === "owl:DatatypeProperty" || + allProperties[i].type() === "owl:ObjectProperty" + + ) { + propertyData.push(allProperties[i]); + } else { + if ( allProperties[i].type() === "rdfs:subClassOf" ) { + allProperties[i].baseIri("http://www.w3.org/2000/01/rdf-schema#"); + allProperties[i].iri("http://www.w3.org/2000/01/rdf-schema#subClassOf"); + } + if ( allProperties[i].type() === "owl:disjointWith" ) { + allProperties[i].baseIri("http://www.w3.org/2002/07/owl#"); + allProperties[i].iri("http://www.w3.org/2002/07/owl#disjointWith"); + } + } + } + return propertyData; + }; + + graph.getAxiomsForTtlExport = function (){ + var axioms = []; + var allProperties = unfilteredData.properties; + for ( var i = 0; i < allProperties.length; i++ ) { + // currently using only the object properties + if ( allProperties[i].type() === "owl:ObjectProperty" || + allProperties[i].type() === "owl:DatatypeProperty" || + allProperties[i].type() === "owl:ObjectProperty" || + allProperties[i].type() === "rdfs:subClassOf" + ) { + } else { + } + } + return axioms; + }; + + + graph.getUnfilteredData = function (){ + return unfilteredData; + }; + + graph.getClassDataForTtlExport = function (){ + var allNodes = unfilteredData.nodes; + var nodeData = []; + for ( var i = 0; i < allNodes.length; i++ ) { + if ( allNodes[i].type() !== "rdfs:Literal" && + allNodes[i].type() !== "rdfs:Datatype" && + allNodes[i].type() !== "owl:Thing" ) { + nodeData.push(allNodes[i]); + } + } + return nodeData; + }; + + + function redrawContent(){ + var markerContainer; + + if ( !graphContainer ) { + return; + } + + // Empty the graph container + graphContainer.selectAll("*").remove(); + + // Last container -> elements of this container overlap others + linkContainer = graphContainer.append("g").classed("linkContainer", true); + cardinalityContainer = graphContainer.append("g").classed("cardinalityContainer", true); + labelContainer = graphContainer.append("g").classed("labelContainer", true); + nodeContainer = graphContainer.append("g").classed("nodeContainer", true); + + // adding editing Elements + var draggerPathLayer = graphContainer.append("g").classed("linkContainer", true); + draggerLayer = graphContainer.append("g").classed("editContainer", true); + editContainer = graphContainer.append("g").classed("editContainer", true); + + draggerPathLayer.classed("hidden-in-export", true); + editContainer.classed("hidden-in-export", true); + draggerLayer.classed("hidden-in-export", true); + + // Add an extra container for all markers + markerContainer = linkContainer.append("defs"); + var drElement = draggerLayer.selectAll(".node") + .data(draggerObjectsArray).enter() + .append("g") + .classed("node", true) + .classed("hidden-in-export", true) + .attr("id", function ( d ){ + return d.id(); + }) + .call(dragBehaviour); + drElement.each(function ( node ){ + node.svgRoot(d3.select(this)); + node.svgPathLayer(draggerPathLayer); + if ( node.type() === "shadowClone" ) { + node.drawClone(); + node.hideClone(true); + } else { + node.drawNode(); + node.hideDragger(true); + } + }); + generateEditElements(); + + + // Add an extra container for all markers + markerContainer = linkContainer.append("defs"); + + // Draw nodes + + if ( classNodes === undefined ) classNodes = []; + + nodeElements = nodeContainer.selectAll(".node") + .data(classNodes).enter() + .append("g") + .classed("node", true) + .attr("id", function ( d ){ + return d.id(); + }) + .call(dragBehaviour); + nodeElements.each(function ( node ){ + node.draw(d3.select(this)); + }); + + + if ( labelNodes === undefined ) labelNodes = []; + + // Draw label groups (property + inverse) + labelGroupElements = labelContainer.selectAll(".labelGroup") + .data(labelNodes).enter() + .append("g") + .classed("labelGroup", true) + .call(dragBehaviour); + + labelGroupElements.each(function ( label ){ + var success = label.draw(d3.select(this)); + label.property().labelObject(label); + // Remove empty groups without a label. + if ( !success ) { + d3.select(this).remove(); + } + }); + // Place subclass label groups on the bottom of all labels + labelGroupElements.each(function ( label ){ + // the label might be hidden e.g. in compact notation + if ( !this.parentNode ) { + return; + } + + if ( elementTools.isRdfsSubClassOf(label.property()) ) { + var parentNode = this.parentNode; + parentNode.insertBefore(this, parentNode.firstChild); + } + }); + if ( properties === undefined ) properties = []; + // Draw cardinality elements + cardinalityElements = cardinalityContainer.selectAll(".cardinality") + .data(properties).enter() + .append("g") + .classed("cardinality", true); + + cardinalityElements.each(function ( property ){ + var success = property.drawCardinality(d3.select(this)); + + // Remove empty groups without a label. + if ( !success ) { + d3.select(this).remove(); + } + }); + // Draw links + if ( links === undefined ) links = []; + linkGroups = linkContainer.selectAll(".link") + .data(links).enter() + .append("g") + .classed("link", true); + + linkGroups.each(function ( link ){ + link.draw(d3.select(this), markerContainer); + }); + linkPathElements = linkGroups.selectAll("path"); + // Select the path for direct access to receive a better performance + addClickEvents(); + } + + function remove(){ + if ( graphContainer ) { + // Select the parent element because the graph container is a group (e.g. for zooming) + d3.select(graphContainer.node().parentNode).remove(); + } + } + + initializeGraph(); // << call the initialization function + + graph.updateCanvasContainerSize = function (){ + if ( graphContainer ) { + var svgElement = d3.selectAll(".vowlGraph"); + svgElement.attr("width", options.width()); + svgElement.attr("height", options.height()); + graphContainer.attr("transform", "translate(" + graphTranslation + ")scale(" + zoomFactor + ")"); + } + }; + + // Loads all settings, removes the old graph (if it exists) and draws a new one. + graph.start = function (){ + force.stop(); + loadGraphData(true); + redrawGraph(); + graph.update(true); + + if ( graph.options().loadingModule().successfullyLoadedOntology() === false ) { + graph.options().loadingModule().setErrorMode(); + } + + }; + + // Updates only the style of the graph. + graph.updateStyle = function (){ + refreshGraphStyle(); + if ( graph.options().loadingModule().successfullyLoadedOntology() === false ) { + force.stop(); + } else { + force.start(); + } + }; + + graph.reload = function (){ + loadGraphData(); + graph.update(); + + }; + + graph.load = function (){ + force.stop(); + loadGraphData(); + refreshGraphData(); + for ( var i = 0; i < labelNodes.length; i++ ) { + var label = labelNodes[i]; + if ( label.property().x && label.property().y ) { + label.x = label.property().x; + label.y = label.property().y; + // also set the prev position of the label + label.px = label.x; + label.py = label.y; + } + } + graph.update(); + }; + + graph.fastUpdate = function (){ + // fast update function for editor calls; + // -- experimental ; + quick_refreshGraphData(); + updateNodeMap(); + force.start(); + redrawContent(); + graph.updatePulseIds(nodeArrayForPulse); + refreshGraphStyle(); + updateHaloStyles(); + + }; + + graph.getNodeMapForSearch = function (){ + return nodeMap; + }; + function updateNodeMap(){ + nodeMap = []; + var node; + for ( var j = 0; j < force.nodes().length; j++ ) { + node = force.nodes()[j]; + if ( node.id ) { + nodeMap[node.id()] = j; + // check for equivalents + var eqs = node.equivalents(); + if ( eqs.length > 0 ) { + for ( var e = 0; e < eqs.length; e++ ) { + var eqObject = eqs[e]; + nodeMap[eqObject.id()] = j; + } + } + } + if ( node.property ) { + nodeMap[node.property().id()] = j; + var inverse = node.inverse(); + if ( inverse ) { + nodeMap[inverse.id()] = j; + } + } + } + } + + function updateHaloStyles(){ + var haloElement; + var halo; + var node; + for ( var j = 0; j < force.nodes().length; j++ ) { + node = force.nodes()[j]; + if ( node.id ) { + haloElement = node.getHalos(); + if ( haloElement ) { + halo = haloElement.selectAll(".searchResultA"); + halo.classed("searchResultA", false); + halo.classed("searchResultB", true); + } + } + + if ( node.property ) { + haloElement = node.property().getHalos(); + if ( haloElement ) { + halo = haloElement.selectAll(".searchResultA"); + halo.classed("searchResultA", false); + halo.classed("searchResultB", true); + } + } + } + } + + // Updates the graphs displayed data and style. + graph.update = function ( init ){ + var validOntology = graph.options().loadingModule().successfullyLoadedOntology(); + if ( validOntology === false && (init && init === true) ) { + graph.options().loadingModule().collapseDetails(); + return; + } + if ( validOntology === false ) { + return; + } + + keepDetailsCollapsedOnLoading = false; + refreshGraphData(); + // update node map + updateNodeMap(); + + force.start(); + redrawContent(); + graph.updatePulseIds(nodeArrayForPulse); + refreshGraphStyle(); + updateHaloStyles(); + }; + + graph.paused = function ( p ){ + if ( !arguments.length ) return paused; + paused = p; + graph.updateStyle(); + return graph; + }; + // resetting the graph + graph.reset = function (){ + // window size + var w = 0.5 * graph.options().width(); + var h = 0.5 * graph.options().height(); + // computing initial translation for the graph due tue the dynamic default zoom level + var tx = w - defaultZoom * w; + var ty = h - defaultZoom * h; + zoom.translate([tx, ty]) + .scale(defaultZoom); + }; + + + graph.zoomOut = function (){ + + var minMag = options.minMagnification(), + maxMag = options.maxMagnification(); + var stepSize = (maxMag - minMag) / 10; + var val = zoomFactor - stepSize; + if ( val < minMag ) val = minMag; + + var cx = 0.5 * graph.options().width(); + var cy = 0.5 * graph.options().height(); + var cp = getWorldPosFromScreen(cx, cy, graphTranslation, zoomFactor); + var sP = [cp.x, cp.y, graph.options().height() / zoomFactor]; + var eP = [cp.x, cp.y, graph.options().height() / val]; + var pos_intp = d3.interpolateZoom(sP, eP); + + graphContainer.attr("transform", transform(sP, cx, cy)) + .transition() + .duration(250) + .attrTween("transform", function (){ + return function ( t ){ + return transform(pos_intp(t), cx, cy); + }; + }) + .each("end", function (){ + graphContainer.attr("transform", "translate(" + graphTranslation + ")scale(" + zoomFactor + ")"); + zoom.translate(graphTranslation); + zoom.scale(zoomFactor); + updateHaloRadius(); + options.zoomSlider().updateZoomSliderValue(zoomFactor); + }); + + }; + + graph.zoomIn = function (){ + var minMag = options.minMagnification(), + maxMag = options.maxMagnification(); + var stepSize = (maxMag - minMag) / 10; + var val = zoomFactor + stepSize; + if ( val > maxMag ) val = maxMag; + var cx = 0.5 * graph.options().width(); + var cy = 0.5 * graph.options().height(); + var cp = getWorldPosFromScreen(cx, cy, graphTranslation, zoomFactor); + var sP = [cp.x, cp.y, graph.options().height() / zoomFactor]; + var eP = [cp.x, cp.y, graph.options().height() / val]; + var pos_intp = d3.interpolateZoom(sP, eP); + + graphContainer.attr("transform", transform(sP, cx, cy)) + .transition() + .duration(250) + .attrTween("transform", function (){ + return function ( t ){ + return transform(pos_intp(t), cx, cy); + }; + }) + .each("end", function (){ + graphContainer.attr("transform", "translate(" + graphTranslation + ")scale(" + zoomFactor + ")"); + zoom.translate(graphTranslation); + zoom.scale(zoomFactor); + updateHaloRadius(); + options.zoomSlider().updateZoomSliderValue(zoomFactor); + }); + + + }; + + /** --------------------------------------------------------- **/ + /** -- data related handling -- **/ + /** --------------------------------------------------------- **/ + + var cachedJsonOBJ = null; + graph.clearAllGraphData = function (){ + if ( graph.graphNodeElements() && graph.graphNodeElements().length > 0 ) { + cachedJsonOBJ = graph.options().exportMenu().createJSON_exportObject(); + } else { + cachedJsonOBJ = null; + } + force.stop(); + if ( unfilteredData ) { + unfilteredData.nodes = []; + unfilteredData.properties = []; + } + }; + graph.getCachedJsonObj = function (){ + return cachedJsonOBJ; + }; + + // removes data when data could not be loaded + graph.clearGraphData = function (){ + force.stop(); + var sidebar = graph.options().sidebar(); + if ( sidebar ) + sidebar.clearOntologyInformation(); + if ( graphContainer ) + redrawGraph(); + }; + + function generateDictionary( data ){ + var i; + var originalDictionary = []; + var nodes = data.nodes; + for ( i = 0; i < nodes.length; i++ ) { + // check if node has a label + if ( nodes[i].labelForCurrentLanguage() !== undefined ) + originalDictionary.push(nodes[i]); + } + var props = data.properties; + for ( i = 0; i < props.length; i++ ) { + if ( props[i].labelForCurrentLanguage() !== undefined ) + originalDictionary.push(props[i]); + } + parser.setDictionary(originalDictionary); + + var literFilter = graph.options().literalFilter(); + var idsToRemove = literFilter.removedNodes(); + var originalDict = parser.getDictionary(); + var newDict = []; + + // go through the dictionary and remove the ids; + for ( i = 0; i < originalDict.length; i++ ) { + var dictElement = originalDict[i]; + var dictElementId; + if ( dictElement.property ) + dictElementId = dictElement.property().id(); + else + dictElementId = dictElement.id(); + // compare against the removed ids; + var addToDictionary = true; + for ( var j = 0; j < idsToRemove.length; j++ ) { + var currentId = idsToRemove[j]; + if ( currentId === dictElementId ) { + addToDictionary = false; + } + } + if ( addToDictionary === true ) { + newDict.push(dictElement); + } + } + // tell the parser that the dictionary is updated + parser.setDictionary(newDict); + + } + + graph.updateProgressBarMode = function (){ + var loadingModule = graph.options().loadingModule(); + + var state = loadingModule.getProgressBarMode(); + switch ( state ) { + case 0: + loadingModule.setErrorMode(); + break; + case 1: + loadingModule.setBusyMode(); + break; + case 2: + loadingModule.setPercentMode(); + break; + default: + loadingModule.setPercentMode(); + } + }; + + graph.setFilterWarning = function ( val ){ + showFilterWarning = val; + }; + function loadGraphData( init ){ + // reset the locate button and previously selected locations and other variables + + var loadingModule = graph.options().loadingModule(); + force.stop(); + + force.nodes([]); + force.links([]); + nodeArrayForPulse = []; + pulseNodeIds = []; + locationId = 0; + d3.select("#locateSearchResult").classed("highlighted", false); + d3.select("#locateSearchResult").node().title = "Nothing to locate"; + graph.clearGraphData(); + + if ( init ) { + force.stop(); + return; + } + + showFilterWarning = false; + parser.parse(options.data()); + unfilteredData = { + nodes: parser.nodes(), + properties: parser.properties() + }; + // fixing class and property id counter for the editor + eN = unfilteredData.nodes.length + 1; + eP = unfilteredData.properties.length + 1; + + initialLoad = true; + graph.options().warningModule().closeFilterHint(); + + // loading handler + updateRenderingDuringSimulation = true; + var validOntology = graph.options().loadingModule().successfullyLoadedOntology(); + if ( graphContainer && validOntology === true ) { + + updateRenderingDuringSimulation = false; + graph.options().ontologyMenu().append_bulletPoint("Generating visualization ... "); + loadingModule.setPercentMode(); + + if ( unfilteredData.nodes.length > 0 ) { + graphContainer.style("opacity", "0"); + force.on("tick", hiddenRecalculatePositions); + } else { + graphContainer.style("opacity", "1"); + if ( showFPS === true ) { + force.on("tick", recalculatePositionsWithFPS); + } + else { + force.on("tick", recalculatePositions); + } + } + + force.start(); + } else { + force.stop(); + graph.options().ontologyMenu().append_bulletPoint("Failed to load ontology"); + loadingModule.setErrorMode(); + } + // update prefixList( + // update general MetaOBJECT + graph.options().clearMetaObject(); + graph.options().clearGeneralMetaObject(); + graph.options().editSidebar().clearMetaObjectValue(); + if ( options.data() !== undefined ) { + var header = options.data().header; + if ( header ) { + if ( header.iri ) { + graph.options().addOrUpdateGeneralObjectEntry("iri", header.iri); + } + if ( header.title ) { + graph.options().addOrUpdateGeneralObjectEntry("title", header.title); + } + if ( header.author ) { + graph.options().addOrUpdateGeneralObjectEntry("author", header.author); + } + if ( header.version ) { + graph.options().addOrUpdateGeneralObjectEntry("version", header.version); + } + if ( header.description ) { + graph.options().addOrUpdateGeneralObjectEntry("description", header.description); + } + if ( header.prefixList ) { + var pL = header.prefixList; + for ( var pr in pL ) { + if ( pL.hasOwnProperty(pr) ) { + var val = pL[pr]; + graph.options().addPrefix(pr, val); + } + } + } + // get other metadata; + if ( header.other ) { + var otherObjects = header.other; + for ( var name in otherObjects ) { + if ( otherObjects.hasOwnProperty(name) ) { + var otherObj = otherObjects[name]; + if ( otherObj.hasOwnProperty("identifier") && otherObj.hasOwnProperty("value") ) { + graph.options().addOrUpdateMetaObjectEntry(otherObj.identfier, otherObj.value); + } + } + } + } + } + } + // update more meta OBJECT + // Initialize filters with data to replicate consecutive filtering + var initializationData = _.clone(unfilteredData); + options.filterModules().forEach(function ( module ){ + initializationData = filterFunction(module, initializationData, true); + }); + // generate dictionary here ; + generateDictionary(unfilteredData); + + parser.parseSettings(); + graphUpdateRequired = parser.settingsImported(); + centerGraphViewOnLoad = true; + if ( parser.settingsImportGraphZoomAndTranslation() === true ) { + centerGraphViewOnLoad = false; + } + graph.options().searchMenu().requestDictionaryUpdate(); + graph.options().editSidebar().updateGeneralOntologyInfo(); + graph.options().editSidebar().updatePrefixUi(); + graph.options().editSidebar().updateElementWidth(); + } + + graph.handleOnLoadingError = function (){ + force.stop(); + graph.clearGraphData(); + graph.options().ontologyMenu().append_bulletPoint("Failed to load ontology"); + d3.select("#progressBarValue").node().innherHTML = ""; + d3.select("#progressBarValue").classed("busyProgressBar", false); + graph.options().loadingModule().setErrorMode(); + graph.options().loadingModule().showErrorDetailsMessage(); + }; + + function quick_refreshGraphData(){ + links = linkCreator.createLinks(properties); + labelNodes = links.map(function ( link ){ + return link.label(); + }); + + storeLinksOnNodes(classNodes, links); + setForceLayoutData(classNodes, labelNodes, links); + } + + //Applies the data of the graph options object and parses it. The graph is not redrawn. + function refreshGraphData(){ + var shouldExecuteEmptyFilter = options.literalFilter().enabled(); + graph.executeEmptyLiteralFilter(); + options.literalFilter().enabled(shouldExecuteEmptyFilter); + + var preprocessedData = _.clone(unfilteredData); + + // Filter the data + options.filterModules().forEach(function ( module ){ + preprocessedData = filterFunction(module, preprocessedData); + }); + options.focuserModule().handle(undefined, true); + classNodes = preprocessedData.nodes; + properties = preprocessedData.properties; + links = linkCreator.createLinks(properties); + labelNodes = links.map(function ( link ){ + return link.label(); + }); + storeLinksOnNodes(classNodes, links); + setForceLayoutData(classNodes, labelNodes, links); + // for (var i = 0; i < classNodes.length; i++) { + // if (classNodes[i].setRectangularRepresentation) + // classNodes[i].setRectangularRepresentation(graph.options().rectangularRepresentation()); + // } + } + + function filterFunction( module, data, initializing ){ + links = linkCreator.createLinks(data.properties); + storeLinksOnNodes(data.nodes, links); + + if ( initializing ) { + if ( module.initialize ) { + module.initialize(data.nodes, data.properties); + } + } + module.filter(data.nodes, data.properties); + return { + nodes: module.filteredNodes(), + properties: module.filteredProperties() + }; + } + + + /** --------------------------------------------------------- **/ + /** -- force-layout related functions -- **/ + /** --------------------------------------------------------- **/ + function storeLinksOnNodes( nodes, links ){ + for ( var i = 0, nodesLength = nodes.length; i < nodesLength; i++ ) { + var node = nodes[i], + connectedLinks = []; + + // look for properties where this node is the domain or range + for ( var j = 0, linksLength = links.length; j < linksLength; j++ ) { + var link = links[j]; + + if ( link.domain() === node || link.range() === node ) { + connectedLinks.push(link); + } + } + node.links(connectedLinks); + } + } + + function setForceLayoutData( classNodes, labelNodes, links ){ + var d3Links = []; + links.forEach(function ( link ){ + d3Links = d3Links.concat(link.linkParts()); + }); + + var d3Nodes = [].concat(classNodes).concat(labelNodes); + setPositionOfOldLabelsOnNewLabels(force.nodes(), labelNodes); + + force.nodes(d3Nodes) + .links(d3Links); + } + + // The label nodes are positioned randomly, because they are created from scratch if the data changes and lose + // their position information. With this hack the position of old labels is copied to the new labels. + function setPositionOfOldLabelsOnNewLabels( oldLabelNodes, labelNodes ){ + labelNodes.forEach(function ( labelNode ){ + for ( var i = 0; i < oldLabelNodes.length; i++ ) { + var oldNode = oldLabelNodes[i]; + if ( oldNode.equals(labelNode) ) { + labelNode.x = oldNode.x; + labelNode.y = oldNode.y; + labelNode.px = oldNode.px; + labelNode.py = oldNode.py; + break; + } + } + }); + } + + // Applies all options that don't change the graph data. + function refreshGraphStyle(){ + zoom = zoom.scaleExtent([options.minMagnification(), options.maxMagnification()]); + if ( graphContainer ) { + zoom.event(graphContainer); + } + + force.charge(function ( element ){ + var charge = options.charge(); + if ( elementTools.isLabel(element) ) { + charge *= 0.8; + } + return charge; + }) + .size([options.width(), options.height()]) + .linkDistance(calculateLinkPartDistance) + .gravity(options.gravity()) + .linkStrength(options.linkStrength()); // Flexibility of links + + force.nodes().forEach(function ( n ){ + n.frozen(paused); + }); + } + + function calculateLinkPartDistance( linkPart ){ + var link = linkPart.link(); + + if ( link.isLoop() ) { + return options.loopDistance(); + } + + // divide by 2 to receive the length for a single link part + var linkPartDistance = getVisibleLinkDistance(link) / 2; + linkPartDistance += linkPart.domain().actualRadius(); + linkPartDistance += linkPart.range().actualRadius(); + return linkPartDistance; + } + + function getVisibleLinkDistance( link ){ + if ( elementTools.isDatatype(link.domain()) || elementTools.isDatatype(link.range()) ) { + return options.datatypeDistance(); + } else { + return options.classDistance(); + } + } + + /** --------------------------------------------------------- **/ + /** -- animation functions for the nodes -- **/ + /** --------------------------------------------------------- **/ + + graph.animateDynamicLabelWidth = function (){ + var wantedWidth = options.dynamicLabelWidth(); + var i; + for ( i = 0; i < classNodes.length; i++ ) { + var nodeElement = classNodes[i]; + if ( elementTools.isDatatype(nodeElement) ) { + nodeElement.animateDynamicLabelWidth(wantedWidth); + } + } + for ( i = 0; i < properties.length; i++ ) { + properties[i].animateDynamicLabelWidth(wantedWidth); + } + }; + + + /** --------------------------------------------------------- **/ + /** -- halo and localization functions -- **/ + /** --------------------------------------------------------- **/ + function updateHaloRadius(){ + if ( pulseNodeIds && pulseNodeIds.length > 0 ) { + var forceNodes = force.nodes(); + for ( var i = 0; i < pulseNodeIds.length; i++ ) { + var node = forceNodes[pulseNodeIds[i]]; + if ( node ) { + if ( node.property ) { + // match search strings with property label + if ( node.property().inverse ) { + var searchString = graph.options().searchMenu().getSearchString().toLowerCase(); + var name = node.property().labelForCurrentLanguage().toLowerCase(); + if ( name === searchString ) computeDistanceToCenter(node); + else { + node.property().removeHalo(); + if ( node.property().inverse() ) { + if ( !node.property().inverse().getHalos() ) + node.property().inverse().drawHalo(); + computeDistanceToCenter(node, true); + } + if ( node.property().equivalents() ) { + var eq = node.property().equivalents(); + for ( var e = 0; e < eq.length; e++ ) { + if ( !eq[e].getHalos() ) + eq[e].drawHalo(); + } + if ( !node.property().getHalos() ) + node.property().drawHalo(); + computeDistanceToCenter(node, false); + + } + } + } + } + computeDistanceToCenter(node); + } + } + } + } + + function getScreenCoords( x, y, translate, scale ){ + var xn = translate[0] + x * scale; + var yn = translate[1] + y * scale; + return { x: xn, y: yn }; + } + + function getClickedScreenCoords( x, y, translate, scale ){ + var xn = (x - translate[0]) / scale; + var yn = (y - translate[1]) / scale; + return { x: xn, y: yn }; + } + + + function computeDistanceToCenter( node, inverse ){ + var container = node; + var w = graph.options().width(); + var h = graph.options().height(); + var posXY = getScreenCoords(node.x, node.y, graphTranslation, zoomFactor); + + var highlightOfInv = false; + + if ( inverse && inverse === true ) { + highlightOfInv = true; + posXY = getScreenCoords(node.x, node.y + 20, graphTranslation, zoomFactor); + } + var x = posXY.x; + var y = posXY.y; + var nodeIsRect = false; + var halo; + var roundHalo; + var rectHalo; + var borderPoint_x = 0; + var borderPoint_y = 0; + var defaultRadius; + var offset = 15; + var radius; + + if ( node.property && highlightOfInv === true ) { + if ( node.property().inverse() ) { + rectHalo = node.property().inverse().getHalos().select("rect"); + + } else { + if ( node.property().getHalos() ) + rectHalo = node.property().getHalos().select("rect"); + else { + node.property().drawHalo(); + rectHalo = node.property().getHalos().select("rect"); + } + } + rectHalo.classed("hidden", true); + if ( node.property().inverse() ) { + if ( node.property().inverse().getHalos() ) { + roundHalo = node.property().inverse().getHalos().select("circle"); + } + } else { + roundHalo = node.property().getHalos().select("circle"); + } + if ( roundHalo.node() === null ) { + radius = node.property().inverse().width() + 15; + + roundHalo = node.property().inverse().getHalos().append("circle") + .classed("searchResultB", true) + .classed("searchResultA", false) + .attr("r", radius + 15); + + } + halo = roundHalo; // swap the halo to be round + nodeIsRect = true; + container = node.property().inverse(); + } + + if ( node.id ) { + if ( !node.getHalos() ) return; // something went wrong before + halo = node.getHalos().select("rect"); + if ( halo.node() === null ) { + // this is a round node + nodeIsRect = false; + roundHalo = node.getHalos().select("circle"); + defaultRadius = node.actualRadius(); + roundHalo.attr("r", defaultRadius + offset); + halo = roundHalo; + } else { // this is a rect node + nodeIsRect = true; + rectHalo = node.getHalos().select("rect"); + rectHalo.classed("hidden", true); + roundHalo = node.getHalos().select("circle"); + if ( roundHalo.node() === null ) { + radius = node.width(); + roundHalo = node.getHalos().append("circle") + .classed("searchResultB", true) + .classed("searchResultA", false) + .attr("r", radius + offset); + } + halo = roundHalo; + } + } + if ( node.property && !inverse ) { + if ( !node.property().getHalos() ) return; // something went wrong before + rectHalo = node.property().getHalos().select("rect"); + rectHalo.classed("hidden", true); + + roundHalo = node.property().getHalos().select("circle"); + if ( roundHalo.node() === null ) { + radius = node.property().width(); + + roundHalo = node.property().getHalos().append("circle") + .classed("searchResultB", true) + .classed("searchResultA", false) + .attr("r", radius + 15); + + } + halo = roundHalo; // swap the halo to be round + nodeIsRect = true; + container = node.property(); + } + + if ( x < 0 || x > w || y < 0 || y > h ) { + // node outside viewport; + // check for quadrant and get the correct boarder point (intersection with viewport) + if ( x < 0 && y < 0 ) { + borderPoint_x = 0; + borderPoint_y = 0; + } else if ( x > 0 && x < w && y < 0 ) { + borderPoint_x = x; + borderPoint_y = 0; + } else if ( x > w && y < 0 ) { + borderPoint_x = w; + borderPoint_y = 0; + } else if ( x > w && y > 0 && y < h ) { + borderPoint_x = w; + borderPoint_y = y; + } else if ( x > w && y > h ) { + borderPoint_x = w; + borderPoint_y = h; + } else if ( x > 0 && x < w && y > h ) { + borderPoint_x = x; + borderPoint_y = h; + } else if ( x < 0 && y > h ) { + borderPoint_x = 0; + borderPoint_y = h; + } else if ( x < 0 && y > 0 && y < h ) { + borderPoint_x = 0; + borderPoint_y = y; + } + // kill all pulses of nodes that are outside the viewport + container.getHalos().select("rect").classed("searchResultA", false); + container.getHalos().select("circle").classed("searchResultA", false); + container.getHalos().select("rect").classed("searchResultB", true); + container.getHalos().select("circle").classed("searchResultB", true); + halo.classed("hidden", false); + // compute in pixel coordinates length of difference vector + var borderRadius_x = borderPoint_x - x; + var borderRadius_y = borderPoint_y - y; + + var len = borderRadius_x * borderRadius_x + borderRadius_y * borderRadius_y; + len = Math.sqrt(len); + + var normedX = borderRadius_x / len; + var normedY = borderRadius_y / len; + + len = len + 20; // add 20 px; + + // re-normalized vector + var newVectorX = normedX * len + x; + var newVectorY = normedY * len + y; + // compute world coordinates of this point + var wX = (newVectorX - graphTranslation[0]) / zoomFactor; + var wY = (newVectorY - graphTranslation[1]) / zoomFactor; + + // compute distance in world coordinates + var dx = wX - node.x; + var dy = wY - node.y; + if ( highlightOfInv === true ) + dy = wY - node.y - 20; + + if ( highlightOfInv === false && node.property && node.property().inverse() ) + dy = wY - node.y + 20; + + var newRadius = Math.sqrt(dx * dx + dy * dy); + halo = container.getHalos().select("circle"); + // sanity checks and setting new halo radius + if ( !nodeIsRect ) { + defaultRadius = node.actualRadius() + offset; + if ( newRadius < defaultRadius ) { + newRadius = defaultRadius; + } + halo.attr("r", newRadius); + } else { + defaultRadius = 0.5 * container.width(); + if ( newRadius < defaultRadius ) + newRadius = defaultRadius; + halo.attr("r", newRadius); + } + } else { // node is in viewport , render original; + // reset the halo to original radius + defaultRadius = node.actualRadius() + 15; + if ( !nodeIsRect ) { + halo.attr("r", defaultRadius); + } else { // this is rectangular node render as such + halo = container.getHalos().select("rect"); + halo.classed("hidden", false); + //halo.classed("searchResultB", true); + //halo.classed("searchResultA", false); + var aCircHalo = container.getHalos().select("circle"); + aCircHalo.classed("hidden", true); + + container.getHalos().select("rect").classed("hidden", false); + container.getHalos().select("circle").classed("hidden", true); + } + } + } + + function transform( p, cx, cy ){ + // one iteration step for the locate target animation + zoomFactor = graph.options().height() / p[2]; + graphTranslation = [(cx - p[0] * zoomFactor), (cy - p[1] * zoomFactor)]; + updateHaloRadius(); + // update the values in case the user wants to break the animation + zoom.translate(graphTranslation); + zoom.scale(zoomFactor); + graph.options().zoomSlider().updateZoomSliderValue(zoomFactor); + return "translate(" + graphTranslation[0] + "," + graphTranslation[1] + ")scale(" + zoomFactor + ")"; + } + + graph.zoomToElementInGraph = function ( element ){ + targetLocationZoom(element); + }; + graph.updateHaloRadius = function ( element ){ + computeDistanceToCenter(element); + }; + + function targetLocationZoom( target ){ + // store the original information + var cx = 0.5 * graph.options().width(); + var cy = 0.5 * graph.options().height(); + var cp = getWorldPosFromScreen(cx, cy, graphTranslation, zoomFactor); + var sP = [cp.x, cp.y, graph.options().height() / zoomFactor]; + + var zoomLevel = Math.max(defaultZoom + 0.5 * defaultZoom, defaultTargetZoom); + var eP = [target.x, target.y, graph.options().height() / zoomLevel]; + var pos_intp = d3.interpolateZoom(sP, eP); + + var lenAnimation = pos_intp.duration; + if ( lenAnimation > 2500 ) { + lenAnimation = 2500; + } + + graphContainer.attr("transform", transform(sP, cx, cy)) + .transition() + .duration(lenAnimation) + .attrTween("transform", function (){ + return function ( t ){ + return transform(pos_intp(t), cx, cy); + }; + }) + .each("end", function (){ + graphContainer.attr("transform", "translate(" + graphTranslation + ")scale(" + zoomFactor + ")"); + zoom.translate(graphTranslation); + zoom.scale(zoomFactor); + updateHaloRadius(); + }); + } + + function getWorldPosFromScreen( x, y, translate, scale ){ + var temp = scale[0], xn, yn; + if ( temp ) { + xn = (x - translate[0]) / temp; + yn = (y - translate[1]) / temp; + } else { + xn = (x - translate[0]) / scale; + yn = (y - translate[1]) / scale; + } + return { x: xn, y: yn }; + } + + graph.locateSearchResult = function (){ + if ( pulseNodeIds && pulseNodeIds.length > 0 ) { + // move the center of the viewport to this location + if ( transformAnimation === true ) return; // << prevents incrementing the location id if we are in an animation + var node = force.nodes()[pulseNodeIds[locationId]]; + locationId++; + locationId = locationId % pulseNodeIds.length; + if ( node.id ) node.foreground(); + if ( node.property ) node.property().foreground(); + + targetLocationZoom(node); + } + }; + + graph.resetSearchHighlight = function (){ + // get all nodes (handle also already filtered nodes ) + pulseNodeIds = []; + nodeArrayForPulse = []; + // clear from stored nodes + var nodes = unfilteredData.nodes; + var props = unfilteredData.properties; + var j; + for ( j = 0; j < nodes.length; j++ ) { + var node = nodes[j]; + if ( node.removeHalo ) + node.removeHalo(); + } + for ( j = 0; j < props.length; j++ ) { + var prop = props[j]; + if ( prop.removeHalo ) + prop.removeHalo(); + } + }; + + graph.updatePulseIds = function ( nodeIdArray ){ + pulseNodeIds = []; + for ( var i = 0; i < nodeIdArray.length; i++ ) { + var selectedId = nodeIdArray[i]; + var forceId = nodeMap[selectedId]; + if ( forceId !== undefined ) { + var le_node = force.nodes()[forceId]; + if ( le_node.id ) { + if ( pulseNodeIds.indexOf(forceId) === -1 ) { + pulseNodeIds.push(forceId); + } + } + if ( le_node.property ) { + if ( pulseNodeIds.indexOf(forceId) === -1 ) { + pulseNodeIds.push(forceId); + } + } + } + } + locationId = 0; + if ( pulseNodeIds.length > 0 ) { + d3.select("#locateSearchResult").classed("highlighted", true); + d3.select("#locateSearchResult").node().title = "Locate search term"; + } + else { + d3.select("#locateSearchResult").classed("highlighted", false); + d3.select("#locateSearchResult").node().title = "Nothing to locate"; + } + + }; + + graph.highLightNodes = function ( nodeIdArray ){ + if ( nodeIdArray.length === 0 ) { + return; // nothing to highlight + } + pulseNodeIds = []; + nodeArrayForPulse = nodeIdArray; + var missedIds = []; + + // identify the force id to highlight + for ( var i = 0; i < nodeIdArray.length; i++ ) { + var selectedId = nodeIdArray[i]; + var forceId = nodeMap[selectedId]; + if ( forceId !== undefined ) { + var le_node = force.nodes()[forceId]; + if ( le_node.id ) { + if ( pulseNodeIds.indexOf(forceId) === -1 ) { + pulseNodeIds.push(forceId); + le_node.foreground(); + le_node.drawHalo(); + } + } + if ( le_node.property ) { + if ( pulseNodeIds.indexOf(forceId) === -1 ) { + pulseNodeIds.push(forceId); + le_node.property().foreground(); + le_node.property().drawHalo(); + } + } + } + else { + missedIds.push(selectedId); + } + } + + if ( missedIds.length === nodeIdArray.length ) { + + } + // store the highlight on the missed nodes; + var s_nodes = unfilteredData.nodes; + var s_props = unfilteredData.properties; + for ( i = 0; i < missedIds.length; i++ ) { + var missedId = missedIds[i]; + // search for this in the nodes; + for ( var n = 0; n < s_nodes.length; n++ ) { + var nodeId = s_nodes[n].id(); + if ( nodeId === missedId ) { + s_nodes[n].drawHalo(); + } + } + for ( var p = 0; p < s_props.length; p++ ) { + var propId = s_props[p].id(); + if ( propId === missedId ) { + s_props[p].drawHalo(); + } + } + } + if ( missedIds.length === nodeIdArray.length ) { + d3.select("#locateSearchResult").classed("highlighted", false); + } + else { + d3.select("#locateSearchResult").classed("highlighted", true); + } + locationId = 0; + updateHaloRadius(); + }; + + graph.hideHalos = function (){ + var haloElements = d3.selectAll(".searchResultA,.searchResultB"); + haloElements.classed("hidden", true); + return haloElements; + }; + + function nodeInViewport( node, property ){ + + var w = graph.options().width(); + var h = graph.options().height(); + var posXY = getScreenCoords(node.x, node.y, graphTranslation, zoomFactor); + var x = posXY.x; + var y = posXY.y; + + var retVal = !(x < 0 || x > w || y < 0 || y > h); + return retVal; + } + + graph.getBoundingBoxForTex = function (){ + var halos = graph.hideHalos(); + var bbox = graphContainer.node().getBoundingClientRect(); + halos.classed("hidden", false); + var w = graph.options().width(); + var h = graph.options().height(); + + // get the graph coordinates + var topLeft = getWorldPosFromScreen(0, 0, graphTranslation, zoomFactor); + var botRight = getWorldPosFromScreen(w, h, graphTranslation, zoomFactor); + + + var t_topLeft = getWorldPosFromScreen(bbox.left, bbox.top, graphTranslation, zoomFactor); + var t_botRight = getWorldPosFromScreen(bbox.right, bbox.bottom, graphTranslation, zoomFactor); + + // tighten up the bounding box; + + var tX = Math.max(t_topLeft.x, topLeft.x); + var tY = Math.max(t_topLeft.y, topLeft.y); + + var bX = Math.min(t_botRight.x, botRight.x); + var bY = Math.min(t_botRight.y, botRight.y); + + + // tighten further; + var allForceNodes = force.nodes(); + var numNodes = allForceNodes.length; + var visibleNodes = []; + var bbx; + + + var contentBBox = { tx: 1000000000000, ty: 1000000000000, bx: -1000000000000, by: -1000000000000 }; + + for ( var i = 0; i < numNodes; i++ ) { + var node = allForceNodes[i]; + if ( node ) { + if ( node.property ) { + if ( nodeInViewport(node, true) ) { + if ( node.property().labelElement() === undefined ) continue; + bbx = node.property().labelElement().node().getBoundingClientRect(); + if ( bbx ) { + contentBBox.tx = Math.min(contentBBox.tx, bbx.left); + contentBBox.bx = Math.max(contentBBox.bx, bbx.right); + contentBBox.ty = Math.min(contentBBox.ty, bbx.top); + contentBBox.by = Math.max(contentBBox.by, bbx.bottom); + } + } + } else { + if ( nodeInViewport(node, false) ) { + bbx = node.nodeElement().node().getBoundingClientRect(); + if ( bbx ) { + contentBBox.tx = Math.min(contentBBox.tx, bbx.left); + contentBBox.bx = Math.max(contentBBox.bx, bbx.right); + contentBBox.ty = Math.min(contentBBox.ty, bbx.top); + contentBBox.by = Math.max(contentBBox.by, bbx.bottom); + } + } + } + } + } + + var tt_topLeft = getWorldPosFromScreen(contentBBox.tx, contentBBox.ty, graphTranslation, zoomFactor); + var tt_botRight = getWorldPosFromScreen(contentBBox.bx, contentBBox.by, graphTranslation, zoomFactor); + + tX = Math.max(tX, tt_topLeft.x); + tY = Math.max(tY, tt_topLeft.y); + + bX = Math.min(bX, tt_botRight.x); + bY = Math.min(bY, tt_botRight.y); + // y axis flip for tex + return [tX, -tY, bX, -bY]; + + }; + + var updateTargetElement = function (){ + var bbox = graphContainer.node().getBoundingClientRect(); + + + // get the graph coordinates + var bboxOffset = 50; // default radius of a node; + var topLeft = getWorldPosFromScreen(bbox.left, bbox.top, graphTranslation, zoomFactor); + var botRight = getWorldPosFromScreen(bbox.right, bbox.bottom, graphTranslation, zoomFactor); + + var w = graph.options().width(); + if ( graph.options().leftSidebar().isSidebarVisible() === true ) + w -= 200; + var h = graph.options().height(); + topLeft.x += bboxOffset; + topLeft.y -= bboxOffset; + botRight.x -= bboxOffset; + botRight.y += bboxOffset; + + var g_w = botRight.x - topLeft.x; + var g_h = botRight.y - topLeft.y; + + // endpoint position calculations + var posX = 0.5 * (topLeft.x + botRight.x); + var posY = 0.5 * (topLeft.y + botRight.y); + var cx = 0.5 * w, + cy = 0.5 * h; + + if ( graph.options().leftSidebar().isSidebarVisible() === true ) + cx += 200; + var cp = getWorldPosFromScreen(cx, cy, graphTranslation, zoomFactor); + + // zoom factor calculations and fail safes; + var newZoomFactor = 1.0; // fail save if graph and window are squares + //get the smaller one + var a = w / g_w; + var b = h / g_h; + if ( a < b ) newZoomFactor = a; + else newZoomFactor = b; + + + // fail saves + if ( newZoomFactor > zoom.scaleExtent()[1] ) { + newZoomFactor = zoom.scaleExtent()[1]; + } + if ( newZoomFactor < zoom.scaleExtent()[0] ) { + newZoomFactor = zoom.scaleExtent()[0]; + } + + // apply Zooming + var sP = [cp.x, cp.y, h / zoomFactor]; + var eP = [posX, posY, h / newZoomFactor]; + + + var pos_intp = d3.interpolateZoom(sP, eP); + return [pos_intp, cx, cy]; + + }; + + graph.forceRelocationEvent = function ( dynamic ){ + // we need to kill the halo to determine the bounding box; + var halos = graph.hideHalos(); + var bbox = graphContainer.node().getBoundingClientRect(); + halos.classed("hidden", false); + + // get the graph coordinates + var bboxOffset = 50; // default radius of a node; + var topLeft = getWorldPosFromScreen(bbox.left, bbox.top, graphTranslation, zoomFactor); + var botRight = getWorldPosFromScreen(bbox.right, bbox.bottom, graphTranslation, zoomFactor); + + var w = graph.options().width(); + if ( graph.options().leftSidebar().isSidebarVisible() === true ) + w -= 200; + var h = graph.options().height(); + topLeft.x += bboxOffset; + topLeft.y -= bboxOffset; + botRight.x -= bboxOffset; + botRight.y += bboxOffset; + + var g_w = botRight.x - topLeft.x; + var g_h = botRight.y - topLeft.y; + + // endpoint position calculations + var posX = 0.5 * (topLeft.x + botRight.x); + var posY = 0.5 * (topLeft.y + botRight.y); + var cx = 0.5 * w, + cy = 0.5 * h; + + if ( graph.options().leftSidebar().isSidebarVisible() === true ) + cx += 200; + var cp = getWorldPosFromScreen(cx, cy, graphTranslation, zoomFactor); + + // zoom factor calculations and fail safes; + var newZoomFactor = 1.0; // fail save if graph and window are squares + //get the smaller one + var a = w / g_w; + var b = h / g_h; + if ( a < b ) newZoomFactor = a; + else newZoomFactor = b; + + + // fail saves + if ( newZoomFactor > zoom.scaleExtent()[1] ) { + newZoomFactor = zoom.scaleExtent()[1]; + } + if ( newZoomFactor < zoom.scaleExtent()[0] ) { + newZoomFactor = zoom.scaleExtent()[0]; + } + + // apply Zooming + var sP = [cp.x, cp.y, h / zoomFactor]; + var eP = [posX, posY, h / newZoomFactor]; + + + var pos_intp = d3.interpolateZoom(sP, eP); + var lenAnimation = pos_intp.duration; + if ( lenAnimation > 2500 ) { + lenAnimation = 2500; + } + graphContainer.attr("transform", transform(sP, cx, cy)) + .transition() + .duration(lenAnimation) + .attrTween("transform", function (){ + return function ( t ){ + if ( dynamic ) { + var param = updateTargetElement(); + var nV = param[0](t); + return transform(nV, cx, cy); + } + return transform(pos_intp(t), cx, cy); + }; + }) + .each("end", function (){ + if ( dynamic ) { + return; + } + + graphContainer.attr("transform", "translate(" + graphTranslation + ")scale(" + zoomFactor + ")"); + zoom.translate(graphTranslation); + zoom.scale(zoomFactor); + graph.options().zoomSlider().updateZoomSliderValue(zoomFactor); + + + }); + }; + + + graph.isADraggerActive = function (){ + if ( classDragger.mouseButtonPressed === true || + domainDragger.mouseButtonPressed === true || + rangeDragger.mouseButtonPressed === true ) { + return true; + } + return false; + }; + + /** --------------------------------------------------------- **/ + /** -- VOWL EDITOR create/ edit /delete functions -- **/ + /** --------------------------------------------------------- **/ + + graph.changeNodeType = function ( element ){ + + var typeString = d3.select("#typeEditor").node().value; + + if ( graph.classesSanityCheck(element, typeString) === false ) { + // call reselection to restore previous type selection + graph.options().editSidebar().updateSelectionInformation(element); + return; + } + + var prototype = NodePrototypeMap.get(typeString.toLowerCase()); + var aNode = new prototype(graph); + + aNode.x = element.x; + aNode.y = element.y; + aNode.px = element.x; + aNode.py = element.y; + aNode.id(element.id()); + aNode.copyInformation(element); + + if ( typeString === "owl:Thing" ) { + aNode.label("Thing"); + } + else if ( elementTools.isDatatype(element) === false ) { + if ( element.backupLabel() !== undefined ) { + aNode.label(element.backupLabel()); + } else if ( aNode.backupLabel() !== undefined ) { + aNode.label(aNode.backupLabel()); + } else { + aNode.label("NewClass"); + } + } + + if ( typeString === "rdfs:Datatype" ) { + if ( aNode.dType() === "undefined" ) + aNode.label("undefined"); + else { + var identifier = aNode.dType().split(":")[1]; + aNode.label(identifier); + } + } + var i; + // updates the property domain and range + for ( i = 0; i < unfilteredData.properties.length; i++ ) { + if ( unfilteredData.properties[i].domain() === element ) { + // unfilteredData.properties[i].toString(); + unfilteredData.properties[i].domain(aNode); + } + if ( unfilteredData.properties[i].range() === element ) { + unfilteredData.properties[i].range(aNode); + // unfilteredData.properties[i].toString(); + } + } + + // update for fastUpdate: + for ( i = 0; i < properties.length; i++ ) { + if ( properties[i].domain() === element ) { + // unfilteredData.properties[i].toString(); + properties[i].domain(aNode); + } + if ( properties[i].range() === element ) { + properties[i].range(aNode); + // unfilteredData.properties[i].toString(); + } + } + + var remId = unfilteredData.nodes.indexOf(element); + if ( remId !== -1 ) + unfilteredData.nodes.splice(remId, 1); + remId = classNodes.indexOf(element); + if ( remId !== -1 ) + classNodes.splice(remId, 1); + // very important thing for selection!; + addNewNodeElement(aNode); + // handle focuser! + options.focuserModule().handle(aNode); + generateDictionary(unfilteredData); + graph.getUpdateDictionary(); + element = null; + }; + + + graph.changePropertyType = function ( element ){ + var typeString = d3.select("#typeEditor").node().value; + + // create warning + if ( graph.sanityCheckProperty(element.domain(), element.range(), typeString) === false ) return false; + + var propPrototype = PropertyPrototypeMap.get(typeString.toLowerCase()); + var aProp = new propPrototype(graph); + aProp.copyInformation(element); + aProp.id(element.id()); + + element.domain().removePropertyElement(element); + element.range().removePropertyElement(element); + aProp.domain(element.domain()); + aProp.range(element.range()); + + if ( element.backupLabel() !== undefined ) { + aProp.label(element.backupLabel()); + } else { + aProp.label("newObjectProperty"); + } + + if ( aProp.type() === "rdfs:subClassOf" ) { + aProp.iri("http://www.w3.org/2000/01/rdf-schema#subClassOf"); + } else { + if ( element.iri() === "http://www.w3.org/2000/01/rdf-schema#subClassOf" ) + aProp.iri(graph.options().getGeneralMetaObjectProperty('iri') + aProp.id()); + + } + + + if ( graph.propertyCheckExistenceChecker(aProp, element.domain(), element.range()) === false ) { + graph.options().editSidebar().updateSelectionInformation(element); + return; + } + // // TODO: change its base IRI to proper value + // var ontoIRI="http://someTest.de"; + // aProp.baseIri(ontoIRI); + // aProp.iri(aProp.baseIri()+aProp.id()); + + + // add this to the data; + unfilteredData.properties.push(aProp); + if ( properties.indexOf(aProp) === -1 ) + properties.push(aProp); + var remId = unfilteredData.properties.indexOf(element); + if ( remId !== -1 ) + unfilteredData.properties.splice(remId, 1); + if ( properties.indexOf(aProp) === -1 ) + properties.push(aProp); + remId = properties.indexOf(element); + if ( remId !== -1 ) + properties.splice(remId, 1); + graph.fastUpdate(); + aProp.domain().addProperty(aProp); + aProp.range().addProperty(aProp); + if ( element.labelObject() && aProp.labelObject() ) { + aProp.labelObject().x = element.labelObject().x; + aProp.labelObject().px = element.labelObject().px; + aProp.labelObject().y = element.labelObject().y; + aProp.labelObject().py = element.labelObject().py; + } + + options.focuserModule().handle(aProp); + element = null; + }; + + graph.removeEditElements = function (){ + // just added to be called form outside + removeEditElements(); + }; + + function removeEditElements(){ + rangeDragger.hideDragger(true); + domainDragger.hideDragger(true); + shadowClone.hideClone(true); + + classDragger.hideDragger(true); + if ( addDataPropertyGroupElement ) + addDataPropertyGroupElement.classed("hidden", true); + if ( deleteGroupElement ) + deleteGroupElement.classed("hidden", true); + + + if ( hoveredNodeElement ) { + if ( hoveredNodeElement.pinned() === false ) { + hoveredNodeElement.locked(graph.paused()); + hoveredNodeElement.frozen(graph.paused()); + } + } + if ( hoveredPropertyElement ) { + if ( hoveredPropertyElement.pinned() === false ) { + hoveredPropertyElement.locked(graph.paused()); + hoveredPropertyElement.frozen(graph.paused()); + } + } + + + } + + graph.editorMode = function ( val ){ + var create_entry = d3.select("#empty"); + var create_container = d3.select("#emptyContainer"); + + var modeOfOpString = d3.select("#modeOfOperationString").node(); + if ( !arguments.length ) { + create_entry.node().checked = editMode; + if ( editMode === false ) { + create_container.node().title = "Enable editing in modes menu to create a new ontology"; + create_entry.node().title = "Enable editing in modes menu to create a new ontology"; + create_entry.style("pointer-events", "none"); + } else { + create_container.node().title = "Creates a new empty ontology"; + create_entry.node().title = "Creates a new empty ontology"; + d3.select("#useAccuracyHelper").style("color", "#2980b9"); + d3.select("#useAccuracyHelper").style("pointer-events", "auto"); + create_entry.node().disabled = false; + create_entry.style("pointer-events", "auto"); + } + + return editMode; + } + graph.options().setEditorModeForDefaultObject(val); + + // if (seenEditorHint===false && val===true){ + // seenEditorHint=true; + // graph.options().warningModule().showEditorHint(); + // } + editMode = val; + + if ( create_entry ) { + create_entry.classed("disabled", !editMode); + if ( !editMode ) { + create_container.node().title = "Enable editing in modes menu to create a new ontology"; + create_entry.node().title = "Enable editing in modes menu to create a new ontology"; + create_entry.node().disabled = true; + d3.select("#useAccuracyHelper").style("color", "#979797"); + d3.select("#useAccuracyHelper").style("pointer-events", "none"); + create_entry.style("pointer-events", "none"); + } else { + create_container.node().title = "Creates a new empty ontology"; + create_entry.node().title = "Creates a new empty ontology"; + d3.select("#useAccuracyHelper").style("color", "#2980b9"); + d3.select("#useAccuracyHelper").style("pointer-events", "auto"); + create_entry.style("pointer-events", "auto"); + } + } + + // adjust compact notation + // selector = compactNotationOption; + // box =ModuleCheckbox + var compactNotationContainer = d3.select("#compactnotationModuleCheckbox"); + if ( compactNotationContainer ) { + compactNotationContainer.classed("disabled", !editMode); + if ( !editMode ) { + compactNotationContainer.node().title = ""; + compactNotationContainer.node().disabled = false; + compactNotationContainer.style("pointer-events", "auto"); + d3.select("#compactNotationOption").style("color", ""); + d3.select("#compactNotationOption").node().title = ""; + options.literalFilter().enabled(true); + graph.update(); + } else { + // if editor Mode + //1) uncheck the element + d3.select("#compactNotationOption").node().title = "Compact notation can only be used in view mode"; + compactNotationContainer.node().disabled = true; + compactNotationContainer.node().checked = false; + options.compactNotationModule().enabled(false); + options.literalFilter().enabled(false); + graph.executeCompactNotationModule(); + graph.executeEmptyLiteralFilter(); + graph.lazyRefresh(); + compactNotationContainer.style("pointer-events", "none"); + d3.select("#compactNotationOption").style("color", "#979797"); + } + } + + if ( modeOfOpString ) { + if ( touchDevice === true ) { + modeOfOpString.innerHTML = "touch able device detected"; + } else { + modeOfOpString.innerHTML = "point & click device detected"; + } + } + var svgGraph = d3.selectAll(".vowlGraph"); + + if ( editMode === true ) { + options.leftSidebar().showSidebar(options.leftSidebar().getSidebarVisibility(), true); + options.leftSidebar().hideCollapseButton(false); + graph.options().editSidebar().updatePrefixUi(); + graph.options().editSidebar().updateElementWidth(); + svgGraph.on("dblclick.zoom", graph.modified_dblClickFunction); + + } else { + svgGraph.on("dblclick.zoom", originalD3_dblClickFunction); + options.leftSidebar().showSidebar(0); + options.leftSidebar().hideCollapseButton(true); + // hide hovered edit elements + removeEditElements(); + } + options.sidebar().updateShowedInformation(); + options.editSidebar().updateElementWidth(); + + }; + + function createLowerCasePrototypeMap( prototypeMap ){ + return d3.map(prototypeMap.values(), function ( Prototype ){ + return new Prototype().type().toLowerCase(); + }); + } + + function createNewNodeAtPosition( pos ){ + var aNode, prototype; + var forceUpdate = true; + // create a node of that id; + + var typeToCreate = d3.select("#defaultClass").node().title; + prototype = NodePrototypeMap.get(typeToCreate.toLowerCase()); + aNode = new prototype(graph); + var autoEditElement = false; + if ( typeToCreate === "owl:Thing" ) { + aNode.label("Thing"); + } + else { + aNode.label("NewClass"); + autoEditElement = true; + } + aNode.x = pos.x; + aNode.y = pos.y; + aNode.px = aNode.x; + aNode.py = aNode.y; + aNode.id("Class" + eN++); + // aNode.paused(true); + + aNode.baseIri(d3.select("#iriEditor").node().value); + aNode.iri(aNode.baseIri() + aNode.id()); + addNewNodeElement(aNode, forceUpdate); + options.focuserModule().handle(aNode, true); + aNode.frozen(graph.paused()); + aNode.locked(graph.paused()); + aNode.enableEditing(autoEditElement); + } + + + function addNewNodeElement( element ){ + unfilteredData.nodes.push(element); + if ( classNodes.indexOf(element) === -1 ) + classNodes.push(element); + + generateDictionary(unfilteredData); + graph.getUpdateDictionary(); + graph.fastUpdate(); + } + + graph.getTargetNode = function ( position ){ + var dx = position[0]; + var dy = position[1]; + var tN = null; + var minDist = 1000000000000; + // This is a bit OVERKILL for the computation of one node >> TODO: KD-TREE SEARCH + unfilteredData.nodes.forEach(function ( el ){ + var cDist = Math.sqrt((el.x - dx) * (el.x - dx) + (el.y - dy) * (el.y - dy)); + if ( cDist < minDist ) { + minDist = cDist; + tN = el; + } + }); + if ( hoveredNodeElement ) { + var offsetDist = hoveredNodeElement.actualRadius() + 30; + if ( minDist > offsetDist ) return null; + if ( tN.renderType() === "rect" ) return null; + if ( tN === hoveredNodeElement && minDist <= hoveredNodeElement.actualRadius() ) { + return tN; + } else if ( tN === hoveredNodeElement && minDist > hoveredNodeElement.actualRadius() ) { + return null; + } + return tN; + } + else { + + if ( minDist > (tN.actualRadius() + 30) ) + return null; + else return tN; + + } + }; + + graph.genericPropertySanityCheck = function ( domain, range, typeString, header, action ){ + if ( domain === range && typeString === "rdfs:subClassOf" ) { + graph.options().warningModule().showWarning(header, + "rdfs:subClassOf can not be created as loops (domain == range)", + action, 1, false); + return false; + } + if ( domain === range && typeString === "owl:disjointWith" ) { + graph.options().warningModule().showWarning(header, + "owl:disjointWith can not be created as loops (domain == range)", + action, 1, false); + return false; + } + // allProps[i].type()==="owl:allValuesFrom" || + // allProps[i].type()==="owl:someValuesFrom" + if ( domain.type() === "owl:Thing" && typeString === "owl:allValuesFrom" ) { + graph.options().warningModule().showWarning(header, + "owl:allValuesFrom can not originate from owl:Thing", + action, 1, false); + return false; + } + if ( domain.type() === "owl:Thing" && typeString === "owl:someValuesFrom" ) { + graph.options().warningModule().showWarning(header, + "owl:someValuesFrom can not originate from owl:Thing", + action, 1, false); + return false; + } + + if ( range.type() === "owl:Thing" && typeString === "owl:allValuesFrom" ) { + graph.options().warningModule().showWarning(header, + "owl:allValuesFrom can not be connected to owl:Thing", + action, 1, false); + return false; + } + if ( range.type() === "owl:Thing" && typeString === "owl:someValuesFrom" ) { + graph.options().warningModule().showWarning(header, + "owl:someValuesFrom can not be connected to owl:Thing", + action, 1, false); + return false; + } + + return true; // we can Change the domain or range + }; + + graph.checkIfIriClassAlreadyExist = function ( url ){ + // search for a class node with this url + var allNodes = unfilteredData.nodes; + for ( var i = 0; i < allNodes.length; i++ ) { + if ( elementTools.isDatatype(allNodes[i]) === true || allNodes[i].type() === "owl:Thing" ) + continue; + + // now we are a real class; + //get class IRI + var classIRI = allNodes[i].iri(); + + // this gives me the node for halo + if ( url === classIRI ) { + return allNodes[i]; + } + } + return false; + }; + + graph.classesSanityCheck = function ( classElement, targetType ){ + // this is added due to someValuesFrom properties + // we should not be able to change a classElement to a owl:Thing + // when it has a property attached to it that uses these restrictions + // + + if ( targetType === "owl:Class" ) return true; + + else { + // collect all properties which have that one as a domain or range + var allProps = unfilteredData.properties; + for ( var i = 0; i < allProps.length; i++ ) { + if ( allProps[i].range() === classElement || allProps[i].domain() === classElement ) { + // check for the type of that property + if ( allProps[i].type() === "owl:someValuesFrom" ) { + graph.options().warningModule().showWarning("Can not change class type", + "The element has a property that is of type owl:someValuesFrom", + "Element type not changed!", 1, true); + return false; + } + if ( allProps[i].type() === "owl:allValuesFrom" ) { + graph.options().warningModule().showWarning("Can not change class type", + "The element has a property that is of type owl:allValuesFrom", + "Element type not changed!", 1, true); + return false; + } + } + } + + + } + return true; + }; + + graph.propertyCheckExistenceChecker = function ( property, domain, range ){ + var allProps = unfilteredData.properties; + var i; + if ( property.type() === "rdfs:subClassOf" || property.type() === "owl:disjointWith" ) { + + for ( i = 0; i < allProps.length; i++ ) { + if ( allProps[i] === property ) continue; + if ( allProps[i].domain() === domain && allProps[i].range() === range && allProps[i].type() === property.type() ) { + graph.options().warningModule().showWarning("Warning", + "This triple already exist!", + "Element not created!", 1, false); + return false; + } + if ( allProps[i].domain() === range && allProps[i].range() === domain && allProps[i].type() === property.type() ) { + graph.options().warningModule().showWarning("Warning", + "Inverse assignment already exist! ", + "Element not created!", 1, false); + return false; + } + } + return true; + } + return true; + }; + + // graph.checkForTripleDuplicate=function(property){ + // var domain=property.domain(); + // var range=property.range(); + // console.log("checking for duplicates"); + // var b1= domain.isPropertyAssignedToThisElement(property); + // var b2= range.isPropertyAssignedToThisElement(property); + // + // console.log("test domain results in "+ b1); + // console.log("test range results in "+ b1); + // + // if (b1 && b2 ){ + // graph.options().warningModule().showWarning("Warning", + // "This triple already exist!", + // "Element not created!",1,false); + // return false; + // } + // return true; + // }; + + graph.sanityCheckProperty = function ( domain, range, typeString ){ + + // check for duplicate triple in the element; + + + if ( typeString === "owl:objectProperty" && graph.options().objectPropertyFilter().enabled() === true ) { + graph.options().warningModule().showWarning("Warning", + "Object properties are filtered out in the visualization!", + "Element not created!", 1, false); + return false; + } + + if ( typeString === "owl:disjointWith" && graph.options().disjointPropertyFilter().enabled() === true ) { + graph.options().warningModule().showWarning("Warning", + "owl:disjointWith properties are filtered out in the visualization!", + "Element not created!", 1, false); + return false; + } + + + if ( domain === range && typeString === "rdfs:subClassOf" ) { + graph.options().warningModule().showWarning("Warning", + "rdfs:subClassOf can not be created as loops (domain == range)", + "Element not created!", 1, false); + return false; + } + if ( domain === range && typeString === "owl:disjointWith" ) { + graph.options().warningModule().showWarning("Warning", + "owl:disjointWith can not be created as loops (domain == range)", + "Element not created!", 1, false); + return false; + } + + if ( domain.type() === "owl:Thing" && typeString === "owl:someValuesFrom" ) { + graph.options().warningModule().showWarning("Warning", + "owl:someValuesFrom can not originate from owl:Thing", + "Element not created!", 1, false); + return false; + } + if ( domain.type() === "owl:Thing" && typeString === "owl:allValuesFrom" ) { + graph.options().warningModule().showWarning("Warning", + "owl:allValuesFrom can not originate from owl:Thing", + "Element not created!", 1, false); + return false; + } + + if ( range.type() === "owl:Thing" && typeString === "owl:allValuesFrom" ) { + graph.options().warningModule().showWarning("Warning", + "owl:allValuesFrom can not be connected to owl:Thing", + "Element not created!", 1, false); + return false; + } + if ( range.type() === "owl:Thing" && typeString === "owl:someValuesFrom" ) { + graph.options().warningModule().showWarning("Warning", + "owl:someValuesFrom can not be connected to owl:Thing", + "Element not created!", 1, false); + return false; + } + return true; // we can create a property + }; + + function createNewObjectProperty( domain, range, draggerEndposition ){ + // check type of the property that we want to create; + + var defaultPropertyName = d3.select("#defaultProperty").node().title; + + // check if we are allow to create that property + if ( graph.sanityCheckProperty(domain, range, defaultPropertyName) === false ) return false; + + + var propPrototype = PropertyPrototypeMap.get(defaultPropertyName.toLowerCase()); + var aProp = new propPrototype(graph); + aProp.id("objectProperty" + eP++); + aProp.domain(domain); + aProp.range(range); + aProp.label("newObjectProperty"); + aProp.baseIri(d3.select("#iriEditor").node().value); + aProp.iri(aProp.baseIri() + aProp.id()); + + // check for duplicate; + if ( graph.propertyCheckExistenceChecker(aProp, domain, range) === false ) { + // delete aProp; + // hope for garbage collection here -.- + return false; + } + + var autoEditElement = false; + + if ( defaultPropertyName === "owl:objectProperty" ) { + autoEditElement = true; + } + var pX = 0.49 * (domain.x + range.x); + var pY = 0.49 * (domain.y + range.y); + + if ( domain === range ) { + // we use the dragger endposition to determine an angle to put the loop there; + var dirD_x = draggerEndposition[0] - domain.x; + var dirD_y = draggerEndposition[1] - domain.y; + + // normalize; + var len = Math.sqrt(dirD_x * dirD_x + dirD_y * dirD_y); + // it should be very hard to set the position on the same sport but why not handling this + var nx = dirD_x / len; + var ny = dirD_y / len; + // is Nan in javascript like in c len==len returns false when it is not a number? + if ( isNaN(len) ) { + nx = 0; + ny = -1; + } + + // get domain actual raidus + var offset = 2 * domain.actualRadius() + 50; + pX = domain.x + offset * nx; + pY = domain.y + offset * ny; + } + + // add this property to domain and range; + domain.addProperty(aProp); + range.addProperty(aProp); + + + // add this to the data; + unfilteredData.properties.push(aProp); + if ( properties.indexOf(aProp) === -1 ) + properties.push(aProp); + graph.fastUpdate(); + aProp.labelObject().x = pX; + aProp.labelObject().px = pX; + aProp.labelObject().y = pY; + aProp.labelObject().py = pY; + + aProp.frozen(graph.paused()); + aProp.locked(graph.paused()); + domain.frozen(graph.paused()); + domain.locked(graph.paused()); + range.frozen(graph.paused()); + range.locked(graph.paused()); + + + generateDictionary(unfilteredData); + graph.getUpdateDictionary(); + + options.focuserModule().handle(aProp); + graph.activateHoverElementsForProperties(true, aProp, false, touchDevice); + aProp.labelObject().increasedLoopAngle = true; + aProp.enableEditing(autoEditElement); + } + + graph.createDataTypeProperty = function ( node ){ + // random postion issues; + clearTimeout(nodeFreezer); + // tells user when element is filtered out + if ( graph.options().datatypeFilter().enabled() === true ) { + graph.options().warningModule().showWarning("Warning", + "Datatype properties are filtered out in the visualization!", + "Element not created!", 1, false); + return; + } + + + var aNode, prototype; + + // create a default datatype Node >> HERE LITERAL; + var defaultDatatypeName = d3.select("#defaultDatatype").node().title; + if ( defaultDatatypeName === "rdfs:Literal" ) { + prototype = NodePrototypeMap.get("rdfs:literal"); + aNode = new prototype(graph); + aNode.label("Literal"); + aNode.iri("http://www.w3.org/2000/01/rdf-schema#Literal"); + aNode.baseIri("http://www.w3.org/2000/01/rdf-schema#"); + } else { + prototype = NodePrototypeMap.get("rdfs:datatype"); + aNode = new prototype(graph); + var identifier = ""; + if ( defaultDatatypeName === "undefined" ) { + identifier = "undefined"; + + aNode.label(identifier); + // TODO : HANDLER FOR UNDEFINED DATATYPES!!<<<>>>>>>>>>>>.. + aNode.iri("http://www.undefinedDatatype.org/#" + identifier); + aNode.baseIri("http://www.undefinedDatatype.org/#"); + aNode.dType(defaultDatatypeName); + } else { + identifier = defaultDatatypeName.split(":")[1]; + aNode.label(identifier); + aNode.dType(defaultDatatypeName); + aNode.iri("http://www.w3.org/2001/XMLSchema#" + identifier); + aNode.baseIri("http://www.w3.org/2001/XMLSchema#"); + } + } + + + var nX = node.x - node.actualRadius() - 100; + var nY = node.y + node.actualRadius() + 100; + + aNode.x = nX; + aNode.y = nY; + aNode.px = aNode.x; + aNode.py = aNode.y; + aNode.id("NodeId" + eN++); + // add this property to the nodes; + unfilteredData.nodes.push(aNode); + if ( classNodes.indexOf(aNode) === -1 ) + classNodes.push(aNode); + + + // add also the datatype Property to it + var propPrototype = PropertyPrototypeMap.get("owl:datatypeproperty"); + var aProp = new propPrototype(graph); + aProp.id("datatypeProperty" + eP++); + + // create the connection + aProp.domain(node); + aProp.range(aNode); + aProp.label("newDatatypeProperty"); + + + // TODO: change its base IRI to proper value + var ontoIri = d3.select("#iriEditor").node().value; + aProp.baseIri(ontoIri); + aProp.iri(ontoIri + aProp.id()); + // add this to the data; + unfilteredData.properties.push(aProp); + if ( properties.indexOf(aProp) === -1 ) + properties.push(aProp); + graph.fastUpdate(); + generateDictionary(unfilteredData); + graph.getUpdateDictionary(); + + nodeFreezer = setTimeout(function (){ + if ( node && node.frozen() === true && node.pinned() === false && graph.paused() === false ) { + node.frozen(graph.paused()); + node.locked(graph.paused()); + } + }, 1000); + options.focuserModule().handle(undefined); + if ( node ) { + node.frozen(true); + node.locked(true); + } + }; + + graph.removeNodesViaResponse = function ( nodesToRemove, propsToRemove ){ + var i, remId; + // splice them; + for ( i = 0; i < propsToRemove.length; i++ ) { + remId = unfilteredData.properties.indexOf(propsToRemove[i]); + if ( remId !== -1 ) + unfilteredData.properties.splice(remId, 1); + remId = properties.indexOf(propsToRemove[i]); + if ( remId !== -1 ) + properties.splice(remId, 1); + propsToRemove[i] = null; + } + for ( i = 0; i < nodesToRemove.length; i++ ) { + remId = unfilteredData.nodes.indexOf(nodesToRemove[i]); + if ( remId !== -1 ) { + unfilteredData.nodes.splice(remId, 1); + } + remId = classNodes.indexOf(nodesToRemove[i]); + if ( remId !== -1 ) + classNodes.splice(remId, 1); + nodesToRemove[i] = null; + } + graph.fastUpdate(); + generateDictionary(unfilteredData); + graph.getUpdateDictionary(); + options.focuserModule().handle(undefined); + nodesToRemove = null; + propsToRemove = null; + + }; + + graph.removeNodeViaEditor = function ( node ){ + var propsToRemove = []; + var nodesToRemove = []; + var datatypes = 0; + + var remId; + + nodesToRemove.push(node); + for ( var i = 0; i < unfilteredData.properties.length; i++ ) { + if ( unfilteredData.properties[i].domain() === node || unfilteredData.properties[i].range() === node ) { + propsToRemove.push(unfilteredData.properties[i]); + if ( unfilteredData.properties[i].type().toLocaleLowerCase() === "owl:datatypeproperty" && + unfilteredData.properties[i].range() !== node ) { + nodesToRemove.push(unfilteredData.properties[i].range()); + datatypes++; + } + } + } + var removedItems = propsToRemove.length + nodesToRemove.length; + if ( removedItems > 2 ) { + var text = "You are about to delete 1 class and " + propsToRemove.length + " properties"; + if ( datatypes !== 0 ) { + text = "You are about to delete 1 class, " + datatypes + " datatypes and " + propsToRemove.length + " properties"; + } + + + graph.options().warningModule().responseWarning( + "Removing elements", + text, + "Awaiting response!", graph.removeNodesViaResponse, [nodesToRemove, propsToRemove], false); + + + // + // if (confirm("Remove :\n"+propsToRemove.length + " properties\n"+nodesToRemove.length+" classes? ")===false){ + // return; + // }else{ + // // todo : store for undo delete button ; + // } + } else { + // splice them; + for ( i = 0; i < propsToRemove.length; i++ ) { + remId = unfilteredData.properties.indexOf(propsToRemove[i]); + if ( remId !== -1 ) + unfilteredData.properties.splice(remId, 1); + remId = properties.indexOf(propsToRemove[i]); + if ( remId !== -1 ) + properties.splice(remId, 1); + propsToRemove[i] = null; + } + for ( i = 0; i < nodesToRemove.length; i++ ) { + remId = unfilteredData.nodes.indexOf(nodesToRemove[i]); + if ( remId !== -1 ) + unfilteredData.nodes.splice(remId, 1); + remId = classNodes.indexOf(nodesToRemove[i]); + if ( remId !== -1 ) + classNodes.splice(remId, 1); + nodesToRemove[i] = null; + } + graph.fastUpdate(); + generateDictionary(unfilteredData); + graph.getUpdateDictionary(); + options.focuserModule().handle(undefined); + nodesToRemove = null; + propsToRemove = null; + } + }; + + graph.removePropertyViaEditor = function ( property ){ + property.domain().removePropertyElement(property); + property.range().removePropertyElement(property); + var remId; + + if ( property.type().toLocaleLowerCase() === "owl:datatypeproperty" ) { + var datatype = property.range(); + remId = unfilteredData.nodes.indexOf(property.range()); + if ( remId !== -1 ) + unfilteredData.nodes.splice(remId, 1); + remId = classNodes.indexOf(property.range()); + if ( remId !== -1 ) + classNodes.splice(remId, 1); + datatype = null; + } + remId = unfilteredData.properties.indexOf(property); + if ( remId !== -1 ) + unfilteredData.properties.splice(remId, 1); + remId = properties.indexOf(property); + if ( remId !== -1 ) + properties.splice(remId, 1); + if ( property.inverse() ) { + // so we have inverse + property.inverse().inverse(0); + + } + + + hoveredPropertyElement = undefined; + graph.fastUpdate(); + generateDictionary(unfilteredData); + graph.getUpdateDictionary(); + options.focuserModule().handle(undefined); + property = null; + }; + + graph.executeColorExternalsModule = function (){ + options.colorExternalsModule().filter(unfilteredData.nodes, unfilteredData.properties); + }; + + graph.executeCompactNotationModule = function (){ + if ( unfilteredData ) { + options.compactNotationModule().filter(unfilteredData.nodes, unfilteredData.properties); + } + + }; + graph.executeEmptyLiteralFilter = function (){ + + if ( unfilteredData && unfilteredData.nodes.length > 1 ) { + options.literalFilter().filter(unfilteredData.nodes, unfilteredData.properties); + unfilteredData.nodes = options.literalFilter().filteredNodes(); + unfilteredData.properties = options.literalFilter().filteredProperties(); + } + + }; + + + /** --------------------------------------------------------- **/ + /** -- animation functions for the nodes -- **/ + /** --------------------------------------------------------- **/ + + graph.animateDynamicLabelWidth = function (){ + var wantedWidth = options.dynamicLabelWidth(); + var i; + for ( i = 0; i < classNodes.length; i++ ) { + var nodeElement = classNodes[i]; + if ( elementTools.isDatatype(nodeElement) ) { + nodeElement.animateDynamicLabelWidth(wantedWidth); + } + } + for ( i = 0; i < properties.length; i++ ) { + properties[i].animateDynamicLabelWidth(wantedWidth); + } + }; + + + /** --------------------------------------------------------- **/ + /** -- Touch behaviour functions -- **/ + /** --------------------------------------------------------- **/ + + graph.setTouchDevice = function ( val ){ + touchDevice = val; + }; + + graph.isTouchDevice = function (){ + return touchDevice; + }; + + graph.modified_dblClickFunction = function (){ + + d3.event.stopPropagation(); + d3.event.preventDefault(); + // get position where we want to add the node; + var grPos = getClickedScreenCoords(d3.event.clientX, d3.event.clientY, graph.translation(), graph.scaleFactor()); + createNewNodeAtPosition(grPos); + }; + + function doubletap(){ + var touch_time = d3.event.timeStamp; + var numTouchers = 1; + if ( d3.event && d3.event.touches && d3.event.touches.length ) + numTouchers = d3.event.touches.length; + + if ( touch_time - last_touch_time < 300 && numTouchers === 1 ) { + d3.event.stopPropagation(); + if ( editMode === true ) { + //graph.modified_dblClickFunction(); + d3.event.preventDefault(); + d3.event.stopPropagation(); + last_touch_time = touch_time; + return true; + } + } + last_touch_time = touch_time; + return false; + } + + + function touchzoomed(){ + forceNotZooming = true; + + + var touch_time = d3.event.timeStamp; + if ( touch_time - last_touch_time < 300 && d3.event.touches.length === 1 ) { + d3.event.stopPropagation(); + + if ( editMode === true ) { + //graph.modified_dblClickFunction(); + d3.event.preventDefault(); + d3.event.stopPropagation(); + zoom.translate(graphTranslation); + zoom.scale(zoomFactor); + graph.modified_dblTouchFunction(); + } + else { + forceNotZooming = false; + if ( originalD3_touchZoomFunction ) + originalD3_touchZoomFunction(); + } + return; + } + forceNotZooming = false; + last_touch_time = touch_time; + // TODO: WORK AROUND TO CHECK FOR ORIGINAL FUNCTION + if ( originalD3_touchZoomFunction ) + originalD3_touchZoomFunction(); + } + + graph.modified_dblTouchFunction = function ( d ){ + d3.event.stopPropagation(); + d3.event.preventDefault(); + var xy; + if ( editMode === true ) { + xy = d3.touches(d3.selectAll(".vowlGraph").node()); + } + var grPos = getClickedScreenCoords(xy[0][0], xy[0][1], graph.translation(), graph.scaleFactor()); + createNewNodeAtPosition(grPos); + }; + + /** --------------------------------------------------------- **/ + /** -- Hover and Selection functions, adding edit elements -- **/ + /** --------------------------------------------------------- **/ + + graph.ignoreOtherHoverEvents = function ( val ){ + if ( !arguments.length ) { + return ignoreOtherHoverEvents; + } + else ignoreOtherHoverEvents = val; + }; + + function delayedHiddingHoverElements( tbh ){ + if ( tbh === true ) return; + if ( hoveredNodeElement ) { + if ( hoveredNodeElement.editingTextElement === true ) return; + delayedHider = setTimeout(function (){ + deleteGroupElement.classed("hidden", true); + addDataPropertyGroupElement.classed("hidden", true); + classDragger.hideDragger(true); + if ( hoveredNodeElement && hoveredNodeElement.pinned() === false && graph.paused() === false && hoveredNodeElement.editingTextElement === false ) { + hoveredNodeElement.frozen(false); + hoveredNodeElement.locked(false); + } + }, 1000); + } + if ( hoveredPropertyElement ) { + if ( hoveredPropertyElement.editingTextElement === true ) return; + delayedHider = setTimeout(function (){ + deleteGroupElement.classed("hidden", true); + addDataPropertyGroupElement.classed("hidden", true); + classDragger.hideDragger(true); + rangeDragger.hideDragger(true); + domainDragger.hideDragger(true); + shadowClone.hideClone(true); + if ( hoveredPropertyElement && hoveredPropertyElement.focused() === true && graph.options().drawPropertyDraggerOnHover() === true ) { + hoveredPropertyElement.labelObject().increasedLoopAngle = false; + // lazy update + recalculatePositions(); + } + + if ( hoveredPropertyElement && hoveredPropertyElement.pinned() === false && graph.paused() === false && hoveredPropertyElement.editingTextElement === false ) { + hoveredPropertyElement.frozen(false); + hoveredPropertyElement.locked(false); + } + }, 1000); + } + + } + + + // TODO : experimental code for updating dynamic label with and its hover element + graph.hideHoverPropertyElementsForAnimation = function (){ + deleteGroupElement.classed("hidden", true); + }; + graph.showHoverElementsAfterAnimation = function ( property, inversed ){ + setDeleteHoverElementPositionProperty(property, inversed); + deleteGroupElement.classed("hidden", false); + + }; + + function editElementHoverOnHidden(){ + classDragger.nodeElement.classed("classDraggerNodeHovered", true); + classDragger.nodeElement.classed("classDraggerNode", false); + editElementHoverOn(); + } + + function editElementHoverOutHidden(){ + classDragger.nodeElement.classed("classDraggerNodeHovered", false); + classDragger.nodeElement.classed("classDraggerNode", true); + editElementHoverOut(); + } + + function editElementHoverOn( touch ){ + if ( touch === true ) return; + clearTimeout(delayedHider); // ignore touch behaviour + + } + + graph.killDelayedTimer = function (){ + clearTimeout(delayedHider); + clearTimeout(nodeFreezer); + }; + + + function editElementHoverOut( tbh ){ + if ( hoveredNodeElement ) { + if ( graph.ignoreOtherHoverEvents() === true || tbh === true || hoveredNodeElement.editingTextElement === true ) return; + delayedHider = setTimeout(function (){ + if ( graph.isADraggerActive() === true ) return; + deleteGroupElement.classed("hidden", true); + addDataPropertyGroupElement.classed("hidden", true); + classDragger.hideDragger(true); + if ( hoveredNodeElement && hoveredNodeElement.pinned() === false && graph.paused() === false ) { + hoveredNodeElement.frozen(false); + hoveredNodeElement.locked(false); + } + + }, 1000); + } + if ( hoveredPropertyElement ) { + if ( graph.ignoreOtherHoverEvents() === true || tbh === true || hoveredPropertyElement.editingTextElement === true ) return; + delayedHider = setTimeout(function (){ + if ( graph.isADraggerActive() === true ) return; + deleteGroupElement.classed("hidden", true); + addDataPropertyGroupElement.classed("hidden", true); + classDragger.hideDragger(true); + if ( hoveredPropertyElement && hoveredPropertyElement.pinned() === false && graph.paused() === false ) { + hoveredPropertyElement.frozen(false); + hoveredPropertyElement.locked(false); + } + + }, 1000); + } + } + + graph.activateHoverElementsForProperties = function ( val, property, inversed, touchBehaviour ){ + if ( editMode === false ) return; // nothing to do; + + if ( touchBehaviour === undefined ) + touchBehaviour = false; + + if ( val === true ) { + clearTimeout(delayedHider); + if ( hoveredPropertyElement ) { + if ( hoveredPropertyElement.domain() === hoveredPropertyElement.range() ) { + hoveredPropertyElement.labelObject().increasedLoopAngle = false; + recalculatePositions(); + } + } + + hoveredPropertyElement = property; + if ( graph.options().drawPropertyDraggerOnHover() === true ) { + + + if ( property.type() !== "owl:DatatypeProperty" ) { + if ( property.domain() === property.range() ) { + property.labelObject().increasedLoopAngle = true; + recalculatePositions(); + } + shadowClone.setParentProperty(property, inversed); + rangeDragger.setParentProperty(property, inversed); + rangeDragger.hideDragger(false); + rangeDragger.addMouseEvents(); + domainDragger.setParentProperty(property, inversed); + domainDragger.hideDragger(false); + domainDragger.addMouseEvents(); + + + } else if ( property.type() === "owl:DatatypeProperty" ) { + shadowClone.setParentProperty(property, inversed); + rangeDragger.setParentProperty(property, inversed); + rangeDragger.hideDragger(true); + rangeDragger.addMouseEvents(); + domainDragger.setParentProperty(property, inversed); + domainDragger.hideDragger(false); + domainDragger.addMouseEvents(); + } + } + else { // hide when we dont want that option + if ( graph.options().drawPropertyDraggerOnHover() === true ) { + rangeDragger.hideDragger(true); + domainDragger.hideDragger(true); + shadowClone.hideClone(true); + if ( property.domain() === property.range() ) { + property.labelObject().increasedLoopAngle = false; + recalculatePositions(); + } + } + } + + if ( hoveredNodeElement ) { + if ( hoveredNodeElement && hoveredNodeElement.pinned() === false && graph.paused() === false ) { + hoveredNodeElement.frozen(false); + hoveredNodeElement.locked(false); + } + } + hoveredNodeElement = undefined; + deleteGroupElement.classed("hidden", false); + setDeleteHoverElementPositionProperty(property, inversed); + deleteGroupElement.selectAll("*").on("click", function (){ + if ( touchBehaviour && property.focused() === false ) { + graph.options().focuserModule().handle(property); + return; + } + graph.removePropertyViaEditor(property); + d3.event.stopPropagation(); + }); + classDragger.hideDragger(true); + addDataPropertyGroupElement.classed("hidden", true); + } else { + delayedHiddingHoverElements(); + } + }; + + graph.updateDraggerElements = function (){ + + // set opacity style for all elements + + rangeDragger.draggerObject.classed("superOpacityElement", !graph.options().showDraggerObject()); + domainDragger.draggerObject.classed("superOpacityElement", !graph.options().showDraggerObject()); + classDragger.draggerObject.classed("superOpacityElement", !graph.options().showDraggerObject()); + + nodeContainer.selectAll(".superHiddenElement").classed("superOpacityElement", !graph.options().showDraggerObject()); + labelContainer.selectAll(".superHiddenElement").classed("superOpacityElement", !graph.options().showDraggerObject()); + + deleteGroupElement.selectAll(".superHiddenElement").classed("superOpacityElement", !graph.options().showDraggerObject()); + addDataPropertyGroupElement.selectAll(".superHiddenElement").classed("superOpacityElement", !graph.options().showDraggerObject()); + + + }; + + function setAddDataPropertyHoverElementPosition( node ){ + var delX, delY = 0; + if ( node.renderType() === "round" ) { + var scale = 0.5 * Math.sqrt(2.0); + var oX = scale * node.actualRadius(); + var oY = scale * node.actualRadius(); + delX = node.x - oX; + delY = node.y + oY; + addDataPropertyGroupElement.attr("transform", "translate(" + delX + "," + delY + ")"); + } + } + + function setDeleteHoverElementPosition( node ){ + var delX, delY = 0; + if ( node.renderType() === "round" ) { + var scale = 0.5 * Math.sqrt(2.0); + var oX = scale * node.actualRadius(); + var oY = scale * node.actualRadius(); + delX = node.x + oX; + delY = node.y - oY; + } else { + delX = node.x + 0.5 * node.width() + 6; + delY = node.y - 0.5 * node.height() - 6; + } + deleteGroupElement.attr("transform", "translate(" + delX + "," + delY + ")"); + } + + function setDeleteHoverElementPositionProperty( property, inversed ){ + if ( property && property.labelElement() ) { + var pos = [property.labelObject().x, property.labelObject().y]; + var widthElement = parseFloat(property.getShapeElement().attr("width")); + var heightElement = parseFloat(property.getShapeElement().attr("height")); + var delX = pos[0] + 0.5 * widthElement + 6; + var delY = pos[1] - 0.5 * heightElement - 6; + // this is the lower element + if ( property.labelElement().attr("transform") === "translate(0,15)" ) + delY += 15; + // this is upper element + if ( property.labelElement().attr("transform") === "translate(0,-15)" ) + delY -= 15; + deleteGroupElement.attr("transform", "translate(" + delX + "," + delY + ")"); + } else { + deleteGroupElement.classed("hidden", true);// hide when there is no property + } + + + } + + graph.activateHoverElements = function ( val, node, touchBehaviour ){ + if ( editMode === false ) { + return; // nothing to do; + } + if ( touchBehaviour === undefined ) touchBehaviour = false; + if ( val === true ) { + if ( graph.options().drawPropertyDraggerOnHover() === true ) { + rangeDragger.hideDragger(true); + domainDragger.hideDragger(true); + shadowClone.hideClone(true); + } + // make them visible + clearTimeout(delayedHider); + clearTimeout(nodeFreezer); + if ( hoveredNodeElement && node.pinned() === false && graph.paused() === false ) { + hoveredNodeElement.frozen(false); + hoveredNodeElement.locked(false); + } + hoveredNodeElement = node; + if ( node && node.frozen() === false && node.pinned() === false ) { + node.frozen(true); + node.locked(false); + } + if ( hoveredPropertyElement && hoveredPropertyElement.focused() === false ) { + hoveredPropertyElement.labelObject().increasedLoopAngle = false; + recalculatePositions(); + // update the loopAngles; + + } + hoveredPropertyElement = undefined; + deleteGroupElement.classed("hidden", false); + setDeleteHoverElementPosition(node); + + + deleteGroupElement.selectAll("*").on("click", function (){ + if ( touchBehaviour && node.focused() === false ) { + graph.options().focuserModule().handle(node); + return; + } + graph.removeNodeViaEditor(node); + d3.event.stopPropagation(); + }) + .on("mouseover", function (){ + editElementHoverOn(node, touchBehaviour); + }) + .on("mouseout", function (){ + editElementHoverOut(node, touchBehaviour); + }); + + addDataPropertyGroupElement.classed("hidden", true); + classDragger.nodeElement.on("mouseover", editElementHoverOn) + .on("mouseout", editElementHoverOut); + classDragger.draggerObject.on("mouseover", editElementHoverOnHidden) + .on("mouseout", editElementHoverOutHidden); + + // add the dragger element; + if ( node.renderType() === "round" ) { + classDragger.svgRoot(draggerLayer); + classDragger.setParentNode(node); + classDragger.hideDragger(false); + addDataPropertyGroupElement.classed("hidden", false); + setAddDataPropertyHoverElementPosition(node); + addDataPropertyGroupElement.selectAll("*").on("click", function (){ + if ( touchBehaviour && node.focused() === false ) { + graph.options().focuserModule().handle(node); + return; + } + graph.createDataTypeProperty(node); + d3.event.stopPropagation(); + }) + .on("mouseover", function (){ + editElementHoverOn(node, touchBehaviour); + }) + .on("mouseout", function (){ + editElementHoverOut(node, touchBehaviour); + }); + } else { + classDragger.hideDragger(true); + + } + + } else { + delayedHiddingHoverElements(node, touchBehaviour); + + } + }; + + + return graph; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 58 */ +/***/ (function(module, exports, __webpack_require__) { + + var __WEBPACK_AMD_DEFINE_RESULT__;/* WEBPACK VAR INJECTION */(function(global, module) {/** + * @license + * Lodash (Custom Build) + * Build: `lodash core -o ./dist/lodash.core.js` + * Copyright OpenJS Foundation and other contributors + * Released under MIT license + * Based on Underscore.js 1.8.3 + * Copyright Jeremy Ashkenas, DocumentCloud and Investigative Reporters & Editors + */ + ;(function() { + + /** Used as a safe reference for `undefined` in pre-ES5 environments. */ + var undefined; + + /** Used as the semantic version number. */ + var VERSION = '4.17.15'; + + /** Error message constants. */ + var FUNC_ERROR_TEXT = 'Expected a function'; + + /** Used to compose bitmasks for value comparisons. */ + var COMPARE_PARTIAL_FLAG = 1, + COMPARE_UNORDERED_FLAG = 2; + + /** Used to compose bitmasks for function metadata. */ + var WRAP_BIND_FLAG = 1, + WRAP_PARTIAL_FLAG = 32; + + /** Used as references for various `Number` constants. */ + var INFINITY = 1 / 0, + MAX_SAFE_INTEGER = 9007199254740991; + + /** `Object#toString` result references. */ + var argsTag = '[object Arguments]', + arrayTag = '[object Array]', + asyncTag = '[object AsyncFunction]', + boolTag = '[object Boolean]', + dateTag = '[object Date]', + errorTag = '[object Error]', + funcTag = '[object Function]', + genTag = '[object GeneratorFunction]', + numberTag = '[object Number]', + objectTag = '[object Object]', + proxyTag = '[object Proxy]', + regexpTag = '[object RegExp]', + stringTag = '[object String]'; + + /** Used to match HTML entities and HTML characters. */ + var reUnescapedHtml = /[&<>"']/g, + reHasUnescapedHtml = RegExp(reUnescapedHtml.source); + + /** Used to detect unsigned integer values. */ + var reIsUint = /^(?:0|[1-9]\d*)$/; + + /** Used to map characters to HTML entities. */ + var htmlEscapes = { + '&': '&', + '<': '<', + '>': '>', + '"': '"', + "'": ''' + }; + + /** Detect free variable `global` from Node.js. */ + var freeGlobal = typeof global == 'object' && global && global.Object === Object && global; + + /** Detect free variable `self`. */ + var freeSelf = typeof self == 'object' && self && self.Object === Object && self; + + /** Used as a reference to the global object. */ + var root = freeGlobal || freeSelf || Function('return this')(); + + /** Detect free variable `exports`. */ + var freeExports = typeof exports == 'object' && exports && !exports.nodeType && exports; + + /** Detect free variable `module`. */ + var freeModule = freeExports && typeof module == 'object' && module && !module.nodeType && module; + + /*--------------------------------------------------------------------------*/ + + /** + * Appends the elements of `values` to `array`. + * + * @private + * @param {Array} array The array to modify. + * @param {Array} values The values to append. + * @returns {Array} Returns `array`. + */ + function arrayPush(array, values) { + array.push.apply(array, values); + return array; + } + + /** + * The base implementation of `_.findIndex` and `_.findLastIndex` without + * support for iteratee shorthands. + * + * @private + * @param {Array} array The array to inspect. + * @param {Function} predicate The function invoked per iteration. + * @param {number} fromIndex The index to search from. + * @param {boolean} [fromRight] Specify iterating from right to left. + * @returns {number} Returns the index of the matched value, else `-1`. + */ + function baseFindIndex(array, predicate, fromIndex, fromRight) { + var length = array.length, + index = fromIndex + (fromRight ? 1 : -1); + + while ((fromRight ? index-- : ++index < length)) { + if (predicate(array[index], index, array)) { + return index; + } + } + return -1; + } + + /** + * The base implementation of `_.property` without support for deep paths. + * + * @private + * @param {string} key The key of the property to get. + * @returns {Function} Returns the new accessor function. + */ + function baseProperty(key) { + return function(object) { + return object == null ? undefined : object[key]; + }; + } + + /** + * The base implementation of `_.propertyOf` without support for deep paths. + * + * @private + * @param {Object} object The object to query. + * @returns {Function} Returns the new accessor function. + */ + function basePropertyOf(object) { + return function(key) { + return object == null ? undefined : object[key]; + }; + } + + /** + * The base implementation of `_.reduce` and `_.reduceRight`, without support + * for iteratee shorthands, which iterates over `collection` using `eachFunc`. + * + * @private + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} iteratee The function invoked per iteration. + * @param {*} accumulator The initial value. + * @param {boolean} initAccum Specify using the first or last element of + * `collection` as the initial value. + * @param {Function} eachFunc The function to iterate over `collection`. + * @returns {*} Returns the accumulated value. + */ + function baseReduce(collection, iteratee, accumulator, initAccum, eachFunc) { + eachFunc(collection, function(value, index, collection) { + accumulator = initAccum + ? (initAccum = false, value) + : iteratee(accumulator, value, index, collection); + }); + return accumulator; + } + + /** + * The base implementation of `_.values` and `_.valuesIn` which creates an + * array of `object` property values corresponding to the property names + * of `props`. + * + * @private + * @param {Object} object The object to query. + * @param {Array} props The property names to get values for. + * @returns {Object} Returns the array of property values. + */ + function baseValues(object, props) { + return baseMap(props, function(key) { + return object[key]; + }); + } + + /** + * Used by `_.escape` to convert characters to HTML entities. + * + * @private + * @param {string} chr The matched character to escape. + * @returns {string} Returns the escaped character. + */ + var escapeHtmlChar = basePropertyOf(htmlEscapes); + + /** + * Creates a unary function that invokes `func` with its argument transformed. + * + * @private + * @param {Function} func The function to wrap. + * @param {Function} transform The argument transform. + * @returns {Function} Returns the new function. + */ + function overArg(func, transform) { + return function(arg) { + return func(transform(arg)); + }; + } + + /*--------------------------------------------------------------------------*/ + + /** Used for built-in method references. */ + var arrayProto = Array.prototype, + objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** Used to generate unique IDs. */ + var idCounter = 0; + + /** + * Used to resolve the + * [`toStringTag`](http://ecma-international.org/ecma-262/7.0/#sec-object.prototype.tostring) + * of values. + */ + var nativeObjectToString = objectProto.toString; + + /** Used to restore the original `_` reference in `_.noConflict`. */ + var oldDash = root._; + + /** Built-in value references. */ + var objectCreate = Object.create, + propertyIsEnumerable = objectProto.propertyIsEnumerable; + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeIsFinite = root.isFinite, + nativeKeys = overArg(Object.keys, Object), + nativeMax = Math.max; + + /*------------------------------------------------------------------------*/ + + /** + * Creates a `lodash` object which wraps `value` to enable implicit method + * chain sequences. Methods that operate on and return arrays, collections, + * and functions can be chained together. Methods that retrieve a single value + * or may return a primitive value will automatically end the chain sequence + * and return the unwrapped value. Otherwise, the value must be unwrapped + * with `_#value`. + * + * Explicit chain sequences, which must be unwrapped with `_#value`, may be + * enabled using `_.chain`. + * + * The execution of chained methods is lazy, that is, it's deferred until + * `_#value` is implicitly or explicitly called. + * + * Lazy evaluation allows several methods to support shortcut fusion. + * Shortcut fusion is an optimization to merge iteratee calls; this avoids + * the creation of intermediate arrays and can greatly reduce the number of + * iteratee executions. Sections of a chain sequence qualify for shortcut + * fusion if the section is applied to an array and iteratees accept only + * one argument. The heuristic for whether a section qualifies for shortcut + * fusion is subject to change. + * + * Chaining is supported in custom builds as long as the `_#value` method is + * directly or indirectly included in the build. + * + * In addition to lodash methods, wrappers have `Array` and `String` methods. + * + * The wrapper `Array` methods are: + * `concat`, `join`, `pop`, `push`, `shift`, `sort`, `splice`, and `unshift` + * + * The wrapper `String` methods are: + * `replace` and `split` + * + * The wrapper methods that support shortcut fusion are: + * `at`, `compact`, `drop`, `dropRight`, `dropWhile`, `filter`, `find`, + * `findLast`, `head`, `initial`, `last`, `map`, `reject`, `reverse`, `slice`, + * `tail`, `take`, `takeRight`, `takeRightWhile`, `takeWhile`, and `toArray` + * + * The chainable wrapper methods are: + * `after`, `ary`, `assign`, `assignIn`, `assignInWith`, `assignWith`, `at`, + * `before`, `bind`, `bindAll`, `bindKey`, `castArray`, `chain`, `chunk`, + * `commit`, `compact`, `concat`, `conforms`, `constant`, `countBy`, `create`, + * `curry`, `debounce`, `defaults`, `defaultsDeep`, `defer`, `delay`, + * `difference`, `differenceBy`, `differenceWith`, `drop`, `dropRight`, + * `dropRightWhile`, `dropWhile`, `extend`, `extendWith`, `fill`, `filter`, + * `flatMap`, `flatMapDeep`, `flatMapDepth`, `flatten`, `flattenDeep`, + * `flattenDepth`, `flip`, `flow`, `flowRight`, `fromPairs`, `functions`, + * `functionsIn`, `groupBy`, `initial`, `intersection`, `intersectionBy`, + * `intersectionWith`, `invert`, `invertBy`, `invokeMap`, `iteratee`, `keyBy`, + * `keys`, `keysIn`, `map`, `mapKeys`, `mapValues`, `matches`, `matchesProperty`, + * `memoize`, `merge`, `mergeWith`, `method`, `methodOf`, `mixin`, `negate`, + * `nthArg`, `omit`, `omitBy`, `once`, `orderBy`, `over`, `overArgs`, + * `overEvery`, `overSome`, `partial`, `partialRight`, `partition`, `pick`, + * `pickBy`, `plant`, `property`, `propertyOf`, `pull`, `pullAll`, `pullAllBy`, + * `pullAllWith`, `pullAt`, `push`, `range`, `rangeRight`, `rearg`, `reject`, + * `remove`, `rest`, `reverse`, `sampleSize`, `set`, `setWith`, `shuffle`, + * `slice`, `sort`, `sortBy`, `splice`, `spread`, `tail`, `take`, `takeRight`, + * `takeRightWhile`, `takeWhile`, `tap`, `throttle`, `thru`, `toArray`, + * `toPairs`, `toPairsIn`, `toPath`, `toPlainObject`, `transform`, `unary`, + * `union`, `unionBy`, `unionWith`, `uniq`, `uniqBy`, `uniqWith`, `unset`, + * `unshift`, `unzip`, `unzipWith`, `update`, `updateWith`, `values`, + * `valuesIn`, `without`, `wrap`, `xor`, `xorBy`, `xorWith`, `zip`, + * `zipObject`, `zipObjectDeep`, and `zipWith` + * + * The wrapper methods that are **not** chainable by default are: + * `add`, `attempt`, `camelCase`, `capitalize`, `ceil`, `clamp`, `clone`, + * `cloneDeep`, `cloneDeepWith`, `cloneWith`, `conformsTo`, `deburr`, + * `defaultTo`, `divide`, `each`, `eachRight`, `endsWith`, `eq`, `escape`, + * `escapeRegExp`, `every`, `find`, `findIndex`, `findKey`, `findLast`, + * `findLastIndex`, `findLastKey`, `first`, `floor`, `forEach`, `forEachRight`, + * `forIn`, `forInRight`, `forOwn`, `forOwnRight`, `get`, `gt`, `gte`, `has`, + * `hasIn`, `head`, `identity`, `includes`, `indexOf`, `inRange`, `invoke`, + * `isArguments`, `isArray`, `isArrayBuffer`, `isArrayLike`, `isArrayLikeObject`, + * `isBoolean`, `isBuffer`, `isDate`, `isElement`, `isEmpty`, `isEqual`, + * `isEqualWith`, `isError`, `isFinite`, `isFunction`, `isInteger`, `isLength`, + * `isMap`, `isMatch`, `isMatchWith`, `isNaN`, `isNative`, `isNil`, `isNull`, + * `isNumber`, `isObject`, `isObjectLike`, `isPlainObject`, `isRegExp`, + * `isSafeInteger`, `isSet`, `isString`, `isUndefined`, `isTypedArray`, + * `isWeakMap`, `isWeakSet`, `join`, `kebabCase`, `last`, `lastIndexOf`, + * `lowerCase`, `lowerFirst`, `lt`, `lte`, `max`, `maxBy`, `mean`, `meanBy`, + * `min`, `minBy`, `multiply`, `noConflict`, `noop`, `now`, `nth`, `pad`, + * `padEnd`, `padStart`, `parseInt`, `pop`, `random`, `reduce`, `reduceRight`, + * `repeat`, `result`, `round`, `runInContext`, `sample`, `shift`, `size`, + * `snakeCase`, `some`, `sortedIndex`, `sortedIndexBy`, `sortedLastIndex`, + * `sortedLastIndexBy`, `startCase`, `startsWith`, `stubArray`, `stubFalse`, + * `stubObject`, `stubString`, `stubTrue`, `subtract`, `sum`, `sumBy`, + * `template`, `times`, `toFinite`, `toInteger`, `toJSON`, `toLength`, + * `toLower`, `toNumber`, `toSafeInteger`, `toString`, `toUpper`, `trim`, + * `trimEnd`, `trimStart`, `truncate`, `unescape`, `uniqueId`, `upperCase`, + * `upperFirst`, `value`, and `words` + * + * @name _ + * @constructor + * @category Seq + * @param {*} value The value to wrap in a `lodash` instance. + * @returns {Object} Returns the new `lodash` wrapper instance. + * @example + * + * function square(n) { + * return n * n; + * } + * + * var wrapped = _([1, 2, 3]); + * + * // Returns an unwrapped value. + * wrapped.reduce(_.add); + * // => 6 + * + * // Returns a wrapped value. + * var squares = wrapped.map(square); + * + * _.isArray(squares); + * // => false + * + * _.isArray(squares.value()); + * // => true + */ + function lodash(value) { + return value instanceof LodashWrapper + ? value + : new LodashWrapper(value); + } + + /** + * The base implementation of `_.create` without support for assigning + * properties to the created object. + * + * @private + * @param {Object} proto The object to inherit from. + * @returns {Object} Returns the new object. + */ + var baseCreate = (function() { + function object() {} + return function(proto) { + if (!isObject(proto)) { + return {}; + } + if (objectCreate) { + return objectCreate(proto); + } + object.prototype = proto; + var result = new object; + object.prototype = undefined; + return result; + }; + }()); + + /** + * The base constructor for creating `lodash` wrapper objects. + * + * @private + * @param {*} value The value to wrap. + * @param {boolean} [chainAll] Enable explicit method chain sequences. + */ + function LodashWrapper(value, chainAll) { + this.__wrapped__ = value; + this.__actions__ = []; + this.__chain__ = !!chainAll; + } + + LodashWrapper.prototype = baseCreate(lodash.prototype); + LodashWrapper.prototype.constructor = LodashWrapper; + + /*------------------------------------------------------------------------*/ + + /** + * Assigns `value` to `key` of `object` if the existing value is not equivalent + * using [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. + * + * @private + * @param {Object} object The object to modify. + * @param {string} key The key of the property to assign. + * @param {*} value The value to assign. + */ + function assignValue(object, key, value) { + var objValue = object[key]; + if (!(hasOwnProperty.call(object, key) && eq(objValue, value)) || + (value === undefined && !(key in object))) { + baseAssignValue(object, key, value); + } + } + + /** + * The base implementation of `assignValue` and `assignMergeValue` without + * value checks. + * + * @private + * @param {Object} object The object to modify. + * @param {string} key The key of the property to assign. + * @param {*} value The value to assign. + */ + function baseAssignValue(object, key, value) { + object[key] = value; + } + + /** + * The base implementation of `_.delay` and `_.defer` which accepts `args` + * to provide to `func`. + * + * @private + * @param {Function} func The function to delay. + * @param {number} wait The number of milliseconds to delay invocation. + * @param {Array} args The arguments to provide to `func`. + * @returns {number|Object} Returns the timer id or timeout object. + */ + function baseDelay(func, wait, args) { + if (typeof func != 'function') { + throw new TypeError(FUNC_ERROR_TEXT); + } + return setTimeout(function() { func.apply(undefined, args); }, wait); + } + + /** + * The base implementation of `_.forEach` without support for iteratee shorthands. + * + * @private + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} iteratee The function invoked per iteration. + * @returns {Array|Object} Returns `collection`. + */ + var baseEach = createBaseEach(baseForOwn); + + /** + * The base implementation of `_.every` without support for iteratee shorthands. + * + * @private + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} predicate The function invoked per iteration. + * @returns {boolean} Returns `true` if all elements pass the predicate check, + * else `false` + */ + function baseEvery(collection, predicate) { + var result = true; + baseEach(collection, function(value, index, collection) { + result = !!predicate(value, index, collection); + return result; + }); + return result; + } + + /** + * The base implementation of methods like `_.max` and `_.min` which accepts a + * `comparator` to determine the extremum value. + * + * @private + * @param {Array} array The array to iterate over. + * @param {Function} iteratee The iteratee invoked per iteration. + * @param {Function} comparator The comparator used to compare values. + * @returns {*} Returns the extremum value. + */ + function baseExtremum(array, iteratee, comparator) { + var index = -1, + length = array.length; + + while (++index < length) { + var value = array[index], + current = iteratee(value); + + if (current != null && (computed === undefined + ? (current === current && !false) + : comparator(current, computed) + )) { + var computed = current, + result = value; + } + } + return result; + } + + /** + * The base implementation of `_.filter` without support for iteratee shorthands. + * + * @private + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} predicate The function invoked per iteration. + * @returns {Array} Returns the new filtered array. + */ + function baseFilter(collection, predicate) { + var result = []; + baseEach(collection, function(value, index, collection) { + if (predicate(value, index, collection)) { + result.push(value); + } + }); + return result; + } + + /** + * The base implementation of `_.flatten` with support for restricting flattening. + * + * @private + * @param {Array} array The array to flatten. + * @param {number} depth The maximum recursion depth. + * @param {boolean} [predicate=isFlattenable] The function invoked per iteration. + * @param {boolean} [isStrict] Restrict to values that pass `predicate` checks. + * @param {Array} [result=[]] The initial result value. + * @returns {Array} Returns the new flattened array. + */ + function baseFlatten(array, depth, predicate, isStrict, result) { + var index = -1, + length = array.length; + + predicate || (predicate = isFlattenable); + result || (result = []); + + while (++index < length) { + var value = array[index]; + if (depth > 0 && predicate(value)) { + if (depth > 1) { + // Recursively flatten arrays (susceptible to call stack limits). + baseFlatten(value, depth - 1, predicate, isStrict, result); + } else { + arrayPush(result, value); + } + } else if (!isStrict) { + result[result.length] = value; + } + } + return result; + } + + /** + * The base implementation of `baseForOwn` which iterates over `object` + * properties returned by `keysFunc` and invokes `iteratee` for each property. + * Iteratee functions may exit iteration early by explicitly returning `false`. + * + * @private + * @param {Object} object The object to iterate over. + * @param {Function} iteratee The function invoked per iteration. + * @param {Function} keysFunc The function to get the keys of `object`. + * @returns {Object} Returns `object`. + */ + var baseFor = createBaseFor(); + + /** + * The base implementation of `_.forOwn` without support for iteratee shorthands. + * + * @private + * @param {Object} object The object to iterate over. + * @param {Function} iteratee The function invoked per iteration. + * @returns {Object} Returns `object`. + */ + function baseForOwn(object, iteratee) { + return object && baseFor(object, iteratee, keys); + } + + /** + * The base implementation of `_.functions` which creates an array of + * `object` function property names filtered from `props`. + * + * @private + * @param {Object} object The object to inspect. + * @param {Array} props The property names to filter. + * @returns {Array} Returns the function names. + */ + function baseFunctions(object, props) { + return baseFilter(props, function(key) { + return isFunction(object[key]); + }); + } + + /** + * The base implementation of `getTag` without fallbacks for buggy environments. + * + * @private + * @param {*} value The value to query. + * @returns {string} Returns the `toStringTag`. + */ + function baseGetTag(value) { + return objectToString(value); + } + + /** + * The base implementation of `_.gt` which doesn't coerce arguments. + * + * @private + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @returns {boolean} Returns `true` if `value` is greater than `other`, + * else `false`. + */ + function baseGt(value, other) { + return value > other; + } + + /** + * The base implementation of `_.isArguments`. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an `arguments` object, + */ + var baseIsArguments = noop; + + /** + * The base implementation of `_.isDate` without Node.js optimizations. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a date object, else `false`. + */ + function baseIsDate(value) { + return isObjectLike(value) && baseGetTag(value) == dateTag; + } + + /** + * The base implementation of `_.isEqual` which supports partial comparisons + * and tracks traversed objects. + * + * @private + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @param {boolean} bitmask The bitmask flags. + * 1 - Unordered comparison + * 2 - Partial comparison + * @param {Function} [customizer] The function to customize comparisons. + * @param {Object} [stack] Tracks traversed `value` and `other` objects. + * @returns {boolean} Returns `true` if the values are equivalent, else `false`. + */ + function baseIsEqual(value, other, bitmask, customizer, stack) { + if (value === other) { + return true; + } + if (value == null || other == null || (!isObjectLike(value) && !isObjectLike(other))) { + return value !== value && other !== other; + } + return baseIsEqualDeep(value, other, bitmask, customizer, baseIsEqual, stack); + } + + /** + * A specialized version of `baseIsEqual` for arrays and objects which performs + * deep comparisons and tracks traversed objects enabling objects with circular + * references to be compared. + * + * @private + * @param {Object} object The object to compare. + * @param {Object} other The other object to compare. + * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. + * @param {Function} customizer The function to customize comparisons. + * @param {Function} equalFunc The function to determine equivalents of values. + * @param {Object} [stack] Tracks traversed `object` and `other` objects. + * @returns {boolean} Returns `true` if the objects are equivalent, else `false`. + */ + function baseIsEqualDeep(object, other, bitmask, customizer, equalFunc, stack) { + var objIsArr = isArray(object), + othIsArr = isArray(other), + objTag = objIsArr ? arrayTag : baseGetTag(object), + othTag = othIsArr ? arrayTag : baseGetTag(other); + + objTag = objTag == argsTag ? objectTag : objTag; + othTag = othTag == argsTag ? objectTag : othTag; + + var objIsObj = objTag == objectTag, + othIsObj = othTag == objectTag, + isSameTag = objTag == othTag; + + stack || (stack = []); + var objStack = find(stack, function(entry) { + return entry[0] == object; + }); + var othStack = find(stack, function(entry) { + return entry[0] == other; + }); + if (objStack && othStack) { + return objStack[1] == other; + } + stack.push([object, other]); + stack.push([other, object]); + if (isSameTag && !objIsObj) { + var result = (objIsArr) + ? equalArrays(object, other, bitmask, customizer, equalFunc, stack) + : equalByTag(object, other, objTag, bitmask, customizer, equalFunc, stack); + stack.pop(); + return result; + } + if (!(bitmask & COMPARE_PARTIAL_FLAG)) { + var objIsWrapped = objIsObj && hasOwnProperty.call(object, '__wrapped__'), + othIsWrapped = othIsObj && hasOwnProperty.call(other, '__wrapped__'); + + if (objIsWrapped || othIsWrapped) { + var objUnwrapped = objIsWrapped ? object.value() : object, + othUnwrapped = othIsWrapped ? other.value() : other; + + var result = equalFunc(objUnwrapped, othUnwrapped, bitmask, customizer, stack); + stack.pop(); + return result; + } + } + if (!isSameTag) { + return false; + } + var result = equalObjects(object, other, bitmask, customizer, equalFunc, stack); + stack.pop(); + return result; + } + + /** + * The base implementation of `_.isRegExp` without Node.js optimizations. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a regexp, else `false`. + */ + function baseIsRegExp(value) { + return isObjectLike(value) && baseGetTag(value) == regexpTag; + } + + /** + * The base implementation of `_.iteratee`. + * + * @private + * @param {*} [value=_.identity] The value to convert to an iteratee. + * @returns {Function} Returns the iteratee. + */ + function baseIteratee(func) { + if (typeof func == 'function') { + return func; + } + if (func == null) { + return identity; + } + return (typeof func == 'object' ? baseMatches : baseProperty)(func); + } + + /** + * The base implementation of `_.lt` which doesn't coerce arguments. + * + * @private + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @returns {boolean} Returns `true` if `value` is less than `other`, + * else `false`. + */ + function baseLt(value, other) { + return value < other; + } + + /** + * The base implementation of `_.map` without support for iteratee shorthands. + * + * @private + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} iteratee The function invoked per iteration. + * @returns {Array} Returns the new mapped array. + */ + function baseMap(collection, iteratee) { + var index = -1, + result = isArrayLike(collection) ? Array(collection.length) : []; + + baseEach(collection, function(value, key, collection) { + result[++index] = iteratee(value, key, collection); + }); + return result; + } + + /** + * The base implementation of `_.matches` which doesn't clone `source`. + * + * @private + * @param {Object} source The object of property values to match. + * @returns {Function} Returns the new spec function. + */ + function baseMatches(source) { + var props = nativeKeys(source); + return function(object) { + var length = props.length; + if (object == null) { + return !length; + } + object = Object(object); + while (length--) { + var key = props[length]; + if (!(key in object && + baseIsEqual(source[key], object[key], COMPARE_PARTIAL_FLAG | COMPARE_UNORDERED_FLAG) + )) { + return false; + } + } + return true; + }; + } + + /** + * The base implementation of `_.pick` without support for individual + * property identifiers. + * + * @private + * @param {Object} object The source object. + * @param {string[]} paths The property paths to pick. + * @returns {Object} Returns the new object. + */ + function basePick(object, props) { + object = Object(object); + return reduce(props, function(result, key) { + if (key in object) { + result[key] = object[key]; + } + return result; + }, {}); + } + + /** + * The base implementation of `_.rest` which doesn't validate or coerce arguments. + * + * @private + * @param {Function} func The function to apply a rest parameter to. + * @param {number} [start=func.length-1] The start position of the rest parameter. + * @returns {Function} Returns the new function. + */ + function baseRest(func, start) { + return setToString(overRest(func, start, identity), func + ''); + } + + /** + * The base implementation of `_.slice` without an iteratee call guard. + * + * @private + * @param {Array} array The array to slice. + * @param {number} [start=0] The start position. + * @param {number} [end=array.length] The end position. + * @returns {Array} Returns the slice of `array`. + */ + function baseSlice(array, start, end) { + var index = -1, + length = array.length; + + if (start < 0) { + start = -start > length ? 0 : (length + start); + } + end = end > length ? length : end; + if (end < 0) { + end += length; + } + length = start > end ? 0 : ((end - start) >>> 0); + start >>>= 0; + + var result = Array(length); + while (++index < length) { + result[index] = array[index + start]; + } + return result; + } + + /** + * Copies the values of `source` to `array`. + * + * @private + * @param {Array} source The array to copy values from. + * @param {Array} [array=[]] The array to copy values to. + * @returns {Array} Returns `array`. + */ + function copyArray(source) { + return baseSlice(source, 0, source.length); + } + + /** + * The base implementation of `_.some` without support for iteratee shorthands. + * + * @private + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} predicate The function invoked per iteration. + * @returns {boolean} Returns `true` if any element passes the predicate check, + * else `false`. + */ + function baseSome(collection, predicate) { + var result; + + baseEach(collection, function(value, index, collection) { + result = predicate(value, index, collection); + return !result; + }); + return !!result; + } + + /** + * The base implementation of `wrapperValue` which returns the result of + * performing a sequence of actions on the unwrapped `value`, where each + * successive action is supplied the return value of the previous. + * + * @private + * @param {*} value The unwrapped value. + * @param {Array} actions Actions to perform to resolve the unwrapped value. + * @returns {*} Returns the resolved value. + */ + function baseWrapperValue(value, actions) { + var result = value; + return reduce(actions, function(result, action) { + return action.func.apply(action.thisArg, arrayPush([result], action.args)); + }, result); + } + + /** + * Compares values to sort them in ascending order. + * + * @private + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @returns {number} Returns the sort order indicator for `value`. + */ + function compareAscending(value, other) { + if (value !== other) { + var valIsDefined = value !== undefined, + valIsNull = value === null, + valIsReflexive = value === value, + valIsSymbol = false; + + var othIsDefined = other !== undefined, + othIsNull = other === null, + othIsReflexive = other === other, + othIsSymbol = false; + + if ((!othIsNull && !othIsSymbol && !valIsSymbol && value > other) || + (valIsSymbol && othIsDefined && othIsReflexive && !othIsNull && !othIsSymbol) || + (valIsNull && othIsDefined && othIsReflexive) || + (!valIsDefined && othIsReflexive) || + !valIsReflexive) { + return 1; + } + if ((!valIsNull && !valIsSymbol && !othIsSymbol && value < other) || + (othIsSymbol && valIsDefined && valIsReflexive && !valIsNull && !valIsSymbol) || + (othIsNull && valIsDefined && valIsReflexive) || + (!othIsDefined && valIsReflexive) || + !othIsReflexive) { + return -1; + } + } + return 0; + } + + /** + * Copies properties of `source` to `object`. + * + * @private + * @param {Object} source The object to copy properties from. + * @param {Array} props The property identifiers to copy. + * @param {Object} [object={}] The object to copy properties to. + * @param {Function} [customizer] The function to customize copied values. + * @returns {Object} Returns `object`. + */ + function copyObject(source, props, object, customizer) { + var isNew = !object; + object || (object = {}); + + var index = -1, + length = props.length; + + while (++index < length) { + var key = props[index]; + + var newValue = customizer + ? customizer(object[key], source[key], key, object, source) + : undefined; + + if (newValue === undefined) { + newValue = source[key]; + } + if (isNew) { + baseAssignValue(object, key, newValue); + } else { + assignValue(object, key, newValue); + } + } + return object; + } + + /** + * Creates a function like `_.assign`. + * + * @private + * @param {Function} assigner The function to assign values. + * @returns {Function} Returns the new assigner function. + */ + function createAssigner(assigner) { + return baseRest(function(object, sources) { + var index = -1, + length = sources.length, + customizer = length > 1 ? sources[length - 1] : undefined; + + customizer = (assigner.length > 3 && typeof customizer == 'function') + ? (length--, customizer) + : undefined; + + object = Object(object); + while (++index < length) { + var source = sources[index]; + if (source) { + assigner(object, source, index, customizer); + } + } + return object; + }); + } + + /** + * Creates a `baseEach` or `baseEachRight` function. + * + * @private + * @param {Function} eachFunc The function to iterate over a collection. + * @param {boolean} [fromRight] Specify iterating from right to left. + * @returns {Function} Returns the new base function. + */ + function createBaseEach(eachFunc, fromRight) { + return function(collection, iteratee) { + if (collection == null) { + return collection; + } + if (!isArrayLike(collection)) { + return eachFunc(collection, iteratee); + } + var length = collection.length, + index = fromRight ? length : -1, + iterable = Object(collection); + + while ((fromRight ? index-- : ++index < length)) { + if (iteratee(iterable[index], index, iterable) === false) { + break; + } + } + return collection; + }; + } + + /** + * Creates a base function for methods like `_.forIn` and `_.forOwn`. + * + * @private + * @param {boolean} [fromRight] Specify iterating from right to left. + * @returns {Function} Returns the new base function. + */ + function createBaseFor(fromRight) { + return function(object, iteratee, keysFunc) { + var index = -1, + iterable = Object(object), + props = keysFunc(object), + length = props.length; + + while (length--) { + var key = props[fromRight ? length : ++index]; + if (iteratee(iterable[key], key, iterable) === false) { + break; + } + } + return object; + }; + } + + /** + * Creates a function that produces an instance of `Ctor` regardless of + * whether it was invoked as part of a `new` expression or by `call` or `apply`. + * + * @private + * @param {Function} Ctor The constructor to wrap. + * @returns {Function} Returns the new wrapped function. + */ + function createCtor(Ctor) { + return function() { + // Use a `switch` statement to work with class constructors. See + // http://ecma-international.org/ecma-262/7.0/#sec-ecmascript-function-objects-call-thisargument-argumentslist + // for more details. + var args = arguments; + var thisBinding = baseCreate(Ctor.prototype), + result = Ctor.apply(thisBinding, args); + + // Mimic the constructor's `return` behavior. + // See https://es5.github.io/#x13.2.2 for more details. + return isObject(result) ? result : thisBinding; + }; + } + + /** + * Creates a `_.find` or `_.findLast` function. + * + * @private + * @param {Function} findIndexFunc The function to find the collection index. + * @returns {Function} Returns the new find function. + */ + function createFind(findIndexFunc) { + return function(collection, predicate, fromIndex) { + var iterable = Object(collection); + if (!isArrayLike(collection)) { + var iteratee = baseIteratee(predicate, 3); + collection = keys(collection); + predicate = function(key) { return iteratee(iterable[key], key, iterable); }; + } + var index = findIndexFunc(collection, predicate, fromIndex); + return index > -1 ? iterable[iteratee ? collection[index] : index] : undefined; + }; + } + + /** + * Creates a function that wraps `func` to invoke it with the `this` binding + * of `thisArg` and `partials` prepended to the arguments it receives. + * + * @private + * @param {Function} func The function to wrap. + * @param {number} bitmask The bitmask flags. See `createWrap` for more details. + * @param {*} thisArg The `this` binding of `func`. + * @param {Array} partials The arguments to prepend to those provided to + * the new function. + * @returns {Function} Returns the new wrapped function. + */ + function createPartial(func, bitmask, thisArg, partials) { + if (typeof func != 'function') { + throw new TypeError(FUNC_ERROR_TEXT); + } + var isBind = bitmask & WRAP_BIND_FLAG, + Ctor = createCtor(func); + + function wrapper() { + var argsIndex = -1, + argsLength = arguments.length, + leftIndex = -1, + leftLength = partials.length, + args = Array(leftLength + argsLength), + fn = (this && this !== root && this instanceof wrapper) ? Ctor : func; + + while (++leftIndex < leftLength) { + args[leftIndex] = partials[leftIndex]; + } + while (argsLength--) { + args[leftIndex++] = arguments[++argsIndex]; + } + return fn.apply(isBind ? thisArg : this, args); + } + return wrapper; + } + + /** + * A specialized version of `baseIsEqualDeep` for arrays with support for + * partial deep comparisons. + * + * @private + * @param {Array} array The array to compare. + * @param {Array} other The other array to compare. + * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. + * @param {Function} customizer The function to customize comparisons. + * @param {Function} equalFunc The function to determine equivalents of values. + * @param {Object} stack Tracks traversed `array` and `other` objects. + * @returns {boolean} Returns `true` if the arrays are equivalent, else `false`. + */ + function equalArrays(array, other, bitmask, customizer, equalFunc, stack) { + var isPartial = bitmask & COMPARE_PARTIAL_FLAG, + arrLength = array.length, + othLength = other.length; + + if (arrLength != othLength && !(isPartial && othLength > arrLength)) { + return false; + } + var index = -1, + result = true, + seen = (bitmask & COMPARE_UNORDERED_FLAG) ? [] : undefined; + + // Ignore non-index properties. + while (++index < arrLength) { + var arrValue = array[index], + othValue = other[index]; + + var compared; + if (compared !== undefined) { + if (compared) { + continue; + } + result = false; + break; + } + // Recursively compare arrays (susceptible to call stack limits). + if (seen) { + if (!baseSome(other, function(othValue, othIndex) { + if (!indexOf(seen, othIndex) && + (arrValue === othValue || equalFunc(arrValue, othValue, bitmask, customizer, stack))) { + return seen.push(othIndex); + } + })) { + result = false; + break; + } + } else if (!( + arrValue === othValue || + equalFunc(arrValue, othValue, bitmask, customizer, stack) + )) { + result = false; + break; + } + } + return result; + } + + /** + * A specialized version of `baseIsEqualDeep` for comparing objects of + * the same `toStringTag`. + * + * **Note:** This function only supports comparing values with tags of + * `Boolean`, `Date`, `Error`, `Number`, `RegExp`, or `String`. + * + * @private + * @param {Object} object The object to compare. + * @param {Object} other The other object to compare. + * @param {string} tag The `toStringTag` of the objects to compare. + * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. + * @param {Function} customizer The function to customize comparisons. + * @param {Function} equalFunc The function to determine equivalents of values. + * @param {Object} stack Tracks traversed `object` and `other` objects. + * @returns {boolean} Returns `true` if the objects are equivalent, else `false`. + */ + function equalByTag(object, other, tag, bitmask, customizer, equalFunc, stack) { + switch (tag) { + + case boolTag: + case dateTag: + case numberTag: + // Coerce booleans to `1` or `0` and dates to milliseconds. + // Invalid dates are coerced to `NaN`. + return eq(+object, +other); + + case errorTag: + return object.name == other.name && object.message == other.message; + + case regexpTag: + case stringTag: + // Coerce regexes to strings and treat strings, primitives and objects, + // as equal. See http://www.ecma-international.org/ecma-262/7.0/#sec-regexp.prototype.tostring + // for more details. + return object == (other + ''); + + } + return false; + } + + /** + * A specialized version of `baseIsEqualDeep` for objects with support for + * partial deep comparisons. + * + * @private + * @param {Object} object The object to compare. + * @param {Object} other The other object to compare. + * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. + * @param {Function} customizer The function to customize comparisons. + * @param {Function} equalFunc The function to determine equivalents of values. + * @param {Object} stack Tracks traversed `object` and `other` objects. + * @returns {boolean} Returns `true` if the objects are equivalent, else `false`. + */ + function equalObjects(object, other, bitmask, customizer, equalFunc, stack) { + var isPartial = bitmask & COMPARE_PARTIAL_FLAG, + objProps = keys(object), + objLength = objProps.length, + othProps = keys(other), + othLength = othProps.length; + + if (objLength != othLength && !isPartial) { + return false; + } + var index = objLength; + while (index--) { + var key = objProps[index]; + if (!(isPartial ? key in other : hasOwnProperty.call(other, key))) { + return false; + } + } + var result = true; + + var skipCtor = isPartial; + while (++index < objLength) { + key = objProps[index]; + var objValue = object[key], + othValue = other[key]; + + var compared; + // Recursively compare objects (susceptible to call stack limits). + if (!(compared === undefined + ? (objValue === othValue || equalFunc(objValue, othValue, bitmask, customizer, stack)) + : compared + )) { + result = false; + break; + } + skipCtor || (skipCtor = key == 'constructor'); + } + if (result && !skipCtor) { + var objCtor = object.constructor, + othCtor = other.constructor; + + // Non `Object` object instances with different constructors are not equal. + if (objCtor != othCtor && + ('constructor' in object && 'constructor' in other) && + !(typeof objCtor == 'function' && objCtor instanceof objCtor && + typeof othCtor == 'function' && othCtor instanceof othCtor)) { + result = false; + } + } + return result; + } + + /** + * A specialized version of `baseRest` which flattens the rest array. + * + * @private + * @param {Function} func The function to apply a rest parameter to. + * @returns {Function} Returns the new function. + */ + function flatRest(func) { + return setToString(overRest(func, undefined, flatten), func + ''); + } + + /** + * Checks if `value` is a flattenable `arguments` object or array. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is flattenable, else `false`. + */ + function isFlattenable(value) { + return isArray(value) || isArguments(value); + } + + /** + * Checks if `value` is a valid array-like index. + * + * @private + * @param {*} value The value to check. + * @param {number} [length=MAX_SAFE_INTEGER] The upper bounds of a valid index. + * @returns {boolean} Returns `true` if `value` is a valid index, else `false`. + */ + function isIndex(value, length) { + var type = typeof value; + length = length == null ? MAX_SAFE_INTEGER : length; + + return !!length && + (type == 'number' || + (type != 'symbol' && reIsUint.test(value))) && + (value > -1 && value % 1 == 0 && value < length); + } + + /** + * Checks if the given arguments are from an iteratee call. + * + * @private + * @param {*} value The potential iteratee value argument. + * @param {*} index The potential iteratee index or key argument. + * @param {*} object The potential iteratee object argument. + * @returns {boolean} Returns `true` if the arguments are from an iteratee call, + * else `false`. + */ + function isIterateeCall(value, index, object) { + if (!isObject(object)) { + return false; + } + var type = typeof index; + if (type == 'number' + ? (isArrayLike(object) && isIndex(index, object.length)) + : (type == 'string' && index in object) + ) { + return eq(object[index], value); + } + return false; + } + + /** + * This function is like + * [`Object.keys`](http://ecma-international.org/ecma-262/7.0/#sec-object.keys) + * except that it includes inherited enumerable properties. + * + * @private + * @param {Object} object The object to query. + * @returns {Array} Returns the array of property names. + */ + function nativeKeysIn(object) { + var result = []; + if (object != null) { + for (var key in Object(object)) { + result.push(key); + } + } + return result; + } + + /** + * Converts `value` to a string using `Object.prototype.toString`. + * + * @private + * @param {*} value The value to convert. + * @returns {string} Returns the converted string. + */ + function objectToString(value) { + return nativeObjectToString.call(value); + } + + /** + * A specialized version of `baseRest` which transforms the rest array. + * + * @private + * @param {Function} func The function to apply a rest parameter to. + * @param {number} [start=func.length-1] The start position of the rest parameter. + * @param {Function} transform The rest array transform. + * @returns {Function} Returns the new function. + */ + function overRest(func, start, transform) { + start = nativeMax(start === undefined ? (func.length - 1) : start, 0); + return function() { + var args = arguments, + index = -1, + length = nativeMax(args.length - start, 0), + array = Array(length); + + while (++index < length) { + array[index] = args[start + index]; + } + index = -1; + var otherArgs = Array(start + 1); + while (++index < start) { + otherArgs[index] = args[index]; + } + otherArgs[start] = transform(array); + return func.apply(this, otherArgs); + }; + } + + /** + * Sets the `toString` method of `func` to return `string`. + * + * @private + * @param {Function} func The function to modify. + * @param {Function} string The `toString` result. + * @returns {Function} Returns `func`. + */ + var setToString = identity; + + /*------------------------------------------------------------------------*/ + + /** + * Creates an array with all falsey values removed. The values `false`, `null`, + * `0`, `""`, `undefined`, and `NaN` are falsey. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to compact. + * @returns {Array} Returns the new array of filtered values. + * @example + * + * _.compact([0, 1, false, 2, '', 3]); + * // => [1, 2, 3] + */ + function compact(array) { + return baseFilter(array, Boolean); + } + + /** + * Creates a new array concatenating `array` with any additional arrays + * and/or values. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to concatenate. + * @param {...*} [values] The values to concatenate. + * @returns {Array} Returns the new concatenated array. + * @example + * + * var array = [1]; + * var other = _.concat(array, 2, [3], [[4]]); + * + * console.log(other); + * // => [1, 2, 3, [4]] + * + * console.log(array); + * // => [1] + */ + function concat() { + var length = arguments.length; + if (!length) { + return []; + } + var args = Array(length - 1), + array = arguments[0], + index = length; + + while (index--) { + args[index - 1] = arguments[index]; + } + return arrayPush(isArray(array) ? copyArray(array) : [array], baseFlatten(args, 1)); + } + + /** + * This method is like `_.find` except that it returns the index of the first + * element `predicate` returns truthy for instead of the element itself. + * + * @static + * @memberOf _ + * @since 1.1.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @param {number} [fromIndex=0] The index to search from. + * @returns {number} Returns the index of the found element, else `-1`. + * @example + * + * var users = [ + * { 'user': 'barney', 'active': false }, + * { 'user': 'fred', 'active': false }, + * { 'user': 'pebbles', 'active': true } + * ]; + * + * _.findIndex(users, function(o) { return o.user == 'barney'; }); + * // => 0 + * + * // The `_.matches` iteratee shorthand. + * _.findIndex(users, { 'user': 'fred', 'active': false }); + * // => 1 + * + * // The `_.matchesProperty` iteratee shorthand. + * _.findIndex(users, ['active', false]); + * // => 0 + * + * // The `_.property` iteratee shorthand. + * _.findIndex(users, 'active'); + * // => 2 + */ + function findIndex(array, predicate, fromIndex) { + var length = array == null ? 0 : array.length; + if (!length) { + return -1; + } + var index = fromIndex == null ? 0 : toInteger(fromIndex); + if (index < 0) { + index = nativeMax(length + index, 0); + } + return baseFindIndex(array, baseIteratee(predicate, 3), index); + } + + /** + * Flattens `array` a single level deep. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to flatten. + * @returns {Array} Returns the new flattened array. + * @example + * + * _.flatten([1, [2, [3, [4]], 5]]); + * // => [1, 2, [3, [4]], 5] + */ + function flatten(array) { + var length = array == null ? 0 : array.length; + return length ? baseFlatten(array, 1) : []; + } + + /** + * Recursively flattens `array`. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to flatten. + * @returns {Array} Returns the new flattened array. + * @example + * + * _.flattenDeep([1, [2, [3, [4]], 5]]); + * // => [1, 2, 3, 4, 5] + */ + function flattenDeep(array) { + var length = array == null ? 0 : array.length; + return length ? baseFlatten(array, INFINITY) : []; + } + + /** + * Gets the first element of `array`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @alias first + * @category Array + * @param {Array} array The array to query. + * @returns {*} Returns the first element of `array`. + * @example + * + * _.head([1, 2, 3]); + * // => 1 + * + * _.head([]); + * // => undefined + */ + function head(array) { + return (array && array.length) ? array[0] : undefined; + } + + /** + * Gets the index at which the first occurrence of `value` is found in `array` + * using [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. If `fromIndex` is negative, it's used as the + * offset from the end of `array`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @param {number} [fromIndex=0] The index to search from. + * @returns {number} Returns the index of the matched value, else `-1`. + * @example + * + * _.indexOf([1, 2, 1, 2], 2); + * // => 1 + * + * // Search from the `fromIndex`. + * _.indexOf([1, 2, 1, 2], 2, 2); + * // => 3 + */ + function indexOf(array, value, fromIndex) { + var length = array == null ? 0 : array.length; + if (typeof fromIndex == 'number') { + fromIndex = fromIndex < 0 ? nativeMax(length + fromIndex, 0) : fromIndex; + } else { + fromIndex = 0; + } + var index = (fromIndex || 0) - 1, + isReflexive = value === value; + + while (++index < length) { + var other = array[index]; + if ((isReflexive ? other === value : other !== other)) { + return index; + } + } + return -1; + } + + /** + * Gets the last element of `array`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to query. + * @returns {*} Returns the last element of `array`. + * @example + * + * _.last([1, 2, 3]); + * // => 3 + */ + function last(array) { + var length = array == null ? 0 : array.length; + return length ? array[length - 1] : undefined; + } + + /** + * Creates a slice of `array` from `start` up to, but not including, `end`. + * + * **Note:** This method is used instead of + * [`Array#slice`](https://mdn.io/Array/slice) to ensure dense arrays are + * returned. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to slice. + * @param {number} [start=0] The start position. + * @param {number} [end=array.length] The end position. + * @returns {Array} Returns the slice of `array`. + */ + function slice(array, start, end) { + var length = array == null ? 0 : array.length; + start = start == null ? 0 : +start; + end = end === undefined ? length : +end; + return length ? baseSlice(array, start, end) : []; + } + + /*------------------------------------------------------------------------*/ + + /** + * Creates a `lodash` wrapper instance that wraps `value` with explicit method + * chain sequences enabled. The result of such sequences must be unwrapped + * with `_#value`. + * + * @static + * @memberOf _ + * @since 1.3.0 + * @category Seq + * @param {*} value The value to wrap. + * @returns {Object} Returns the new `lodash` wrapper instance. + * @example + * + * var users = [ + * { 'user': 'barney', 'age': 36 }, + * { 'user': 'fred', 'age': 40 }, + * { 'user': 'pebbles', 'age': 1 } + * ]; + * + * var youngest = _ + * .chain(users) + * .sortBy('age') + * .map(function(o) { + * return o.user + ' is ' + o.age; + * }) + * .head() + * .value(); + * // => 'pebbles is 1' + */ + function chain(value) { + var result = lodash(value); + result.__chain__ = true; + return result; + } + + /** + * This method invokes `interceptor` and returns `value`. The interceptor + * is invoked with one argument; (value). The purpose of this method is to + * "tap into" a method chain sequence in order to modify intermediate results. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Seq + * @param {*} value The value to provide to `interceptor`. + * @param {Function} interceptor The function to invoke. + * @returns {*} Returns `value`. + * @example + * + * _([1, 2, 3]) + * .tap(function(array) { + * // Mutate input array. + * array.pop(); + * }) + * .reverse() + * .value(); + * // => [2, 1] + */ + function tap(value, interceptor) { + interceptor(value); + return value; + } + + /** + * This method is like `_.tap` except that it returns the result of `interceptor`. + * The purpose of this method is to "pass thru" values replacing intermediate + * results in a method chain sequence. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Seq + * @param {*} value The value to provide to `interceptor`. + * @param {Function} interceptor The function to invoke. + * @returns {*} Returns the result of `interceptor`. + * @example + * + * _(' abc ') + * .chain() + * .trim() + * .thru(function(value) { + * return [value]; + * }) + * .value(); + * // => ['abc'] + */ + function thru(value, interceptor) { + return interceptor(value); + } + + /** + * Creates a `lodash` wrapper instance with explicit method chain sequences enabled. + * + * @name chain + * @memberOf _ + * @since 0.1.0 + * @category Seq + * @returns {Object} Returns the new `lodash` wrapper instance. + * @example + * + * var users = [ + * { 'user': 'barney', 'age': 36 }, + * { 'user': 'fred', 'age': 40 } + * ]; + * + * // A sequence without explicit chaining. + * _(users).head(); + * // => { 'user': 'barney', 'age': 36 } + * + * // A sequence with explicit chaining. + * _(users) + * .chain() + * .head() + * .pick('user') + * .value(); + * // => { 'user': 'barney' } + */ + function wrapperChain() { + return chain(this); + } + + /** + * Executes the chain sequence to resolve the unwrapped value. + * + * @name value + * @memberOf _ + * @since 0.1.0 + * @alias toJSON, valueOf + * @category Seq + * @returns {*} Returns the resolved unwrapped value. + * @example + * + * _([1, 2, 3]).value(); + * // => [1, 2, 3] + */ + function wrapperValue() { + return baseWrapperValue(this.__wrapped__, this.__actions__); + } + + /*------------------------------------------------------------------------*/ + + /** + * Checks if `predicate` returns truthy for **all** elements of `collection`. + * Iteration is stopped once `predicate` returns falsey. The predicate is + * invoked with three arguments: (value, index|key, collection). + * + * **Note:** This method returns `true` for + * [empty collections](https://en.wikipedia.org/wiki/Empty_set) because + * [everything is true](https://en.wikipedia.org/wiki/Vacuous_truth) of + * elements of empty collections. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Collection + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. + * @returns {boolean} Returns `true` if all elements pass the predicate check, + * else `false`. + * @example + * + * _.every([true, 1, null, 'yes'], Boolean); + * // => false + * + * var users = [ + * { 'user': 'barney', 'age': 36, 'active': false }, + * { 'user': 'fred', 'age': 40, 'active': false } + * ]; + * + * // The `_.matches` iteratee shorthand. + * _.every(users, { 'user': 'barney', 'active': false }); + * // => false + * + * // The `_.matchesProperty` iteratee shorthand. + * _.every(users, ['active', false]); + * // => true + * + * // The `_.property` iteratee shorthand. + * _.every(users, 'active'); + * // => false + */ + function every(collection, predicate, guard) { + predicate = guard ? undefined : predicate; + return baseEvery(collection, baseIteratee(predicate)); + } + + /** + * Iterates over elements of `collection`, returning an array of all elements + * `predicate` returns truthy for. The predicate is invoked with three + * arguments: (value, index|key, collection). + * + * **Note:** Unlike `_.remove`, this method returns a new array. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Collection + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @returns {Array} Returns the new filtered array. + * @see _.reject + * @example + * + * var users = [ + * { 'user': 'barney', 'age': 36, 'active': true }, + * { 'user': 'fred', 'age': 40, 'active': false } + * ]; + * + * _.filter(users, function(o) { return !o.active; }); + * // => objects for ['fred'] + * + * // The `_.matches` iteratee shorthand. + * _.filter(users, { 'age': 36, 'active': true }); + * // => objects for ['barney'] + * + * // The `_.matchesProperty` iteratee shorthand. + * _.filter(users, ['active', false]); + * // => objects for ['fred'] + * + * // The `_.property` iteratee shorthand. + * _.filter(users, 'active'); + * // => objects for ['barney'] + */ + function filter(collection, predicate) { + return baseFilter(collection, baseIteratee(predicate)); + } + + /** + * Iterates over elements of `collection`, returning the first element + * `predicate` returns truthy for. The predicate is invoked with three + * arguments: (value, index|key, collection). + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Collection + * @param {Array|Object} collection The collection to inspect. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @param {number} [fromIndex=0] The index to search from. + * @returns {*} Returns the matched element, else `undefined`. + * @example + * + * var users = [ + * { 'user': 'barney', 'age': 36, 'active': true }, + * { 'user': 'fred', 'age': 40, 'active': false }, + * { 'user': 'pebbles', 'age': 1, 'active': true } + * ]; + * + * _.find(users, function(o) { return o.age < 40; }); + * // => object for 'barney' + * + * // The `_.matches` iteratee shorthand. + * _.find(users, { 'age': 1, 'active': true }); + * // => object for 'pebbles' + * + * // The `_.matchesProperty` iteratee shorthand. + * _.find(users, ['active', false]); + * // => object for 'fred' + * + * // The `_.property` iteratee shorthand. + * _.find(users, 'active'); + * // => object for 'barney' + */ + var find = createFind(findIndex); + + /** + * Iterates over elements of `collection` and invokes `iteratee` for each element. + * The iteratee is invoked with three arguments: (value, index|key, collection). + * Iteratee functions may exit iteration early by explicitly returning `false`. + * + * **Note:** As with other "Collections" methods, objects with a "length" + * property are iterated like arrays. To avoid this behavior use `_.forIn` + * or `_.forOwn` for object iteration. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @alias each + * @category Collection + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} [iteratee=_.identity] The function invoked per iteration. + * @returns {Array|Object} Returns `collection`. + * @see _.forEachRight + * @example + * + * _.forEach([1, 2], function(value) { + * console.log(value); + * }); + * // => Logs `1` then `2`. + * + * _.forEach({ 'a': 1, 'b': 2 }, function(value, key) { + * console.log(key); + * }); + * // => Logs 'a' then 'b' (iteration order is not guaranteed). + */ + function forEach(collection, iteratee) { + return baseEach(collection, baseIteratee(iteratee)); + } + + /** + * Creates an array of values by running each element in `collection` thru + * `iteratee`. The iteratee is invoked with three arguments: + * (value, index|key, collection). + * + * Many lodash methods are guarded to work as iteratees for methods like + * `_.every`, `_.filter`, `_.map`, `_.mapValues`, `_.reject`, and `_.some`. + * + * The guarded methods are: + * `ary`, `chunk`, `curry`, `curryRight`, `drop`, `dropRight`, `every`, + * `fill`, `invert`, `parseInt`, `random`, `range`, `rangeRight`, `repeat`, + * `sampleSize`, `slice`, `some`, `sortBy`, `split`, `take`, `takeRight`, + * `template`, `trim`, `trimEnd`, `trimStart`, and `words` + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Collection + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} [iteratee=_.identity] The function invoked per iteration. + * @returns {Array} Returns the new mapped array. + * @example + * + * function square(n) { + * return n * n; + * } + * + * _.map([4, 8], square); + * // => [16, 64] + * + * _.map({ 'a': 4, 'b': 8 }, square); + * // => [16, 64] (iteration order is not guaranteed) + * + * var users = [ + * { 'user': 'barney' }, + * { 'user': 'fred' } + * ]; + * + * // The `_.property` iteratee shorthand. + * _.map(users, 'user'); + * // => ['barney', 'fred'] + */ + function map(collection, iteratee) { + return baseMap(collection, baseIteratee(iteratee)); + } + + /** + * Reduces `collection` to a value which is the accumulated result of running + * each element in `collection` thru `iteratee`, where each successive + * invocation is supplied the return value of the previous. If `accumulator` + * is not given, the first element of `collection` is used as the initial + * value. The iteratee is invoked with four arguments: + * (accumulator, value, index|key, collection). + * + * Many lodash methods are guarded to work as iteratees for methods like + * `_.reduce`, `_.reduceRight`, and `_.transform`. + * + * The guarded methods are: + * `assign`, `defaults`, `defaultsDeep`, `includes`, `merge`, `orderBy`, + * and `sortBy` + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Collection + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} [iteratee=_.identity] The function invoked per iteration. + * @param {*} [accumulator] The initial value. + * @returns {*} Returns the accumulated value. + * @see _.reduceRight + * @example + * + * _.reduce([1, 2], function(sum, n) { + * return sum + n; + * }, 0); + * // => 3 + * + * _.reduce({ 'a': 1, 'b': 2, 'c': 1 }, function(result, value, key) { + * (result[value] || (result[value] = [])).push(key); + * return result; + * }, {}); + * // => { '1': ['a', 'c'], '2': ['b'] } (iteration order is not guaranteed) + */ + function reduce(collection, iteratee, accumulator) { + return baseReduce(collection, baseIteratee(iteratee), accumulator, arguments.length < 3, baseEach); + } + + /** + * Gets the size of `collection` by returning its length for array-like + * values or the number of own enumerable string keyed properties for objects. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Collection + * @param {Array|Object|string} collection The collection to inspect. + * @returns {number} Returns the collection size. + * @example + * + * _.size([1, 2, 3]); + * // => 3 + * + * _.size({ 'a': 1, 'b': 2 }); + * // => 2 + * + * _.size('pebbles'); + * // => 7 + */ + function size(collection) { + if (collection == null) { + return 0; + } + collection = isArrayLike(collection) ? collection : nativeKeys(collection); + return collection.length; + } + + /** + * Checks if `predicate` returns truthy for **any** element of `collection`. + * Iteration is stopped once `predicate` returns truthy. The predicate is + * invoked with three arguments: (value, index|key, collection). + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Collection + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. + * @returns {boolean} Returns `true` if any element passes the predicate check, + * else `false`. + * @example + * + * _.some([null, 0, 'yes', false], Boolean); + * // => true + * + * var users = [ + * { 'user': 'barney', 'active': true }, + * { 'user': 'fred', 'active': false } + * ]; + * + * // The `_.matches` iteratee shorthand. + * _.some(users, { 'user': 'barney', 'active': false }); + * // => false + * + * // The `_.matchesProperty` iteratee shorthand. + * _.some(users, ['active', false]); + * // => true + * + * // The `_.property` iteratee shorthand. + * _.some(users, 'active'); + * // => true + */ + function some(collection, predicate, guard) { + predicate = guard ? undefined : predicate; + return baseSome(collection, baseIteratee(predicate)); + } + + /** + * Creates an array of elements, sorted in ascending order by the results of + * running each element in a collection thru each iteratee. This method + * performs a stable sort, that is, it preserves the original sort order of + * equal elements. The iteratees are invoked with one argument: (value). + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Collection + * @param {Array|Object} collection The collection to iterate over. + * @param {...(Function|Function[])} [iteratees=[_.identity]] + * The iteratees to sort by. + * @returns {Array} Returns the new sorted array. + * @example + * + * var users = [ + * { 'user': 'fred', 'age': 48 }, + * { 'user': 'barney', 'age': 36 }, + * { 'user': 'fred', 'age': 40 }, + * { 'user': 'barney', 'age': 34 } + * ]; + * + * _.sortBy(users, [function(o) { return o.user; }]); + * // => objects for [['barney', 36], ['barney', 34], ['fred', 48], ['fred', 40]] + * + * _.sortBy(users, ['user', 'age']); + * // => objects for [['barney', 34], ['barney', 36], ['fred', 40], ['fred', 48]] + */ + function sortBy(collection, iteratee) { + var index = 0; + iteratee = baseIteratee(iteratee); + + return baseMap(baseMap(collection, function(value, key, collection) { + return { 'value': value, 'index': index++, 'criteria': iteratee(value, key, collection) }; + }).sort(function(object, other) { + return compareAscending(object.criteria, other.criteria) || (object.index - other.index); + }), baseProperty('value')); + } + + /*------------------------------------------------------------------------*/ + + /** + * Creates a function that invokes `func`, with the `this` binding and arguments + * of the created function, while it's called less than `n` times. Subsequent + * calls to the created function return the result of the last `func` invocation. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Function + * @param {number} n The number of calls at which `func` is no longer invoked. + * @param {Function} func The function to restrict. + * @returns {Function} Returns the new restricted function. + * @example + * + * jQuery(element).on('click', _.before(5, addContactToList)); + * // => Allows adding up to 4 contacts to the list. + */ + function before(n, func) { + var result; + if (typeof func != 'function') { + throw new TypeError(FUNC_ERROR_TEXT); + } + n = toInteger(n); + return function() { + if (--n > 0) { + result = func.apply(this, arguments); + } + if (n <= 1) { + func = undefined; + } + return result; + }; + } + + /** + * Creates a function that invokes `func` with the `this` binding of `thisArg` + * and `partials` prepended to the arguments it receives. + * + * The `_.bind.placeholder` value, which defaults to `_` in monolithic builds, + * may be used as a placeholder for partially applied arguments. + * + * **Note:** Unlike native `Function#bind`, this method doesn't set the "length" + * property of bound functions. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Function + * @param {Function} func The function to bind. + * @param {*} thisArg The `this` binding of `func`. + * @param {...*} [partials] The arguments to be partially applied. + * @returns {Function} Returns the new bound function. + * @example + * + * function greet(greeting, punctuation) { + * return greeting + ' ' + this.user + punctuation; + * } + * + * var object = { 'user': 'fred' }; + * + * var bound = _.bind(greet, object, 'hi'); + * bound('!'); + * // => 'hi fred!' + * + * // Bound with placeholders. + * var bound = _.bind(greet, object, _, '!'); + * bound('hi'); + * // => 'hi fred!' + */ + var bind = baseRest(function(func, thisArg, partials) { + return createPartial(func, WRAP_BIND_FLAG | WRAP_PARTIAL_FLAG, thisArg, partials); + }); + + /** + * Defers invoking the `func` until the current call stack has cleared. Any + * additional arguments are provided to `func` when it's invoked. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Function + * @param {Function} func The function to defer. + * @param {...*} [args] The arguments to invoke `func` with. + * @returns {number} Returns the timer id. + * @example + * + * _.defer(function(text) { + * console.log(text); + * }, 'deferred'); + * // => Logs 'deferred' after one millisecond. + */ + var defer = baseRest(function(func, args) { + return baseDelay(func, 1, args); + }); + + /** + * Invokes `func` after `wait` milliseconds. Any additional arguments are + * provided to `func` when it's invoked. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Function + * @param {Function} func The function to delay. + * @param {number} wait The number of milliseconds to delay invocation. + * @param {...*} [args] The arguments to invoke `func` with. + * @returns {number} Returns the timer id. + * @example + * + * _.delay(function(text) { + * console.log(text); + * }, 1000, 'later'); + * // => Logs 'later' after one second. + */ + var delay = baseRest(function(func, wait, args) { + return baseDelay(func, toNumber(wait) || 0, args); + }); + + /** + * Creates a function that negates the result of the predicate `func`. The + * `func` predicate is invoked with the `this` binding and arguments of the + * created function. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Function + * @param {Function} predicate The predicate to negate. + * @returns {Function} Returns the new negated function. + * @example + * + * function isEven(n) { + * return n % 2 == 0; + * } + * + * _.filter([1, 2, 3, 4, 5, 6], _.negate(isEven)); + * // => [1, 3, 5] + */ + function negate(predicate) { + if (typeof predicate != 'function') { + throw new TypeError(FUNC_ERROR_TEXT); + } + return function() { + var args = arguments; + return !predicate.apply(this, args); + }; + } + + /** + * Creates a function that is restricted to invoking `func` once. Repeat calls + * to the function return the value of the first invocation. The `func` is + * invoked with the `this` binding and arguments of the created function. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Function + * @param {Function} func The function to restrict. + * @returns {Function} Returns the new restricted function. + * @example + * + * var initialize = _.once(createApplication); + * initialize(); + * initialize(); + * // => `createApplication` is invoked once + */ + function once(func) { + return before(2, func); + } + + /*------------------------------------------------------------------------*/ + + /** + * Creates a shallow clone of `value`. + * + * **Note:** This method is loosely based on the + * [structured clone algorithm](https://mdn.io/Structured_clone_algorithm) + * and supports cloning arrays, array buffers, booleans, date objects, maps, + * numbers, `Object` objects, regexes, sets, strings, symbols, and typed + * arrays. The own enumerable properties of `arguments` objects are cloned + * as plain objects. An empty object is returned for uncloneable values such + * as error objects, functions, DOM nodes, and WeakMaps. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to clone. + * @returns {*} Returns the cloned value. + * @see _.cloneDeep + * @example + * + * var objects = [{ 'a': 1 }, { 'b': 2 }]; + * + * var shallow = _.clone(objects); + * console.log(shallow[0] === objects[0]); + * // => true + */ + function clone(value) { + if (!isObject(value)) { + return value; + } + return isArray(value) ? copyArray(value) : copyObject(value, nativeKeys(value)); + } + + /** + * Performs a + * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * comparison between two values to determine if they are equivalent. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @returns {boolean} Returns `true` if the values are equivalent, else `false`. + * @example + * + * var object = { 'a': 1 }; + * var other = { 'a': 1 }; + * + * _.eq(object, object); + * // => true + * + * _.eq(object, other); + * // => false + * + * _.eq('a', 'a'); + * // => true + * + * _.eq('a', Object('a')); + * // => false + * + * _.eq(NaN, NaN); + * // => true + */ + function eq(value, other) { + return value === other || (value !== value && other !== other); + } + + /** + * Checks if `value` is likely an `arguments` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an `arguments` object, + * else `false`. + * @example + * + * _.isArguments(function() { return arguments; }()); + * // => true + * + * _.isArguments([1, 2, 3]); + * // => false + */ + var isArguments = baseIsArguments(function() { return arguments; }()) ? baseIsArguments : function(value) { + return isObjectLike(value) && hasOwnProperty.call(value, 'callee') && + !propertyIsEnumerable.call(value, 'callee'); + }; + + /** + * Checks if `value` is classified as an `Array` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an array, else `false`. + * @example + * + * _.isArray([1, 2, 3]); + * // => true + * + * _.isArray(document.body.children); + * // => false + * + * _.isArray('abc'); + * // => false + * + * _.isArray(_.noop); + * // => false + */ + var isArray = Array.isArray; + + /** + * Checks if `value` is array-like. A value is considered array-like if it's + * not a function and has a `value.length` that's an integer greater than or + * equal to `0` and less than or equal to `Number.MAX_SAFE_INTEGER`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is array-like, else `false`. + * @example + * + * _.isArrayLike([1, 2, 3]); + * // => true + * + * _.isArrayLike(document.body.children); + * // => true + * + * _.isArrayLike('abc'); + * // => true + * + * _.isArrayLike(_.noop); + * // => false + */ + function isArrayLike(value) { + return value != null && isLength(value.length) && !isFunction(value); + } + + /** + * Checks if `value` is classified as a boolean primitive or object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a boolean, else `false`. + * @example + * + * _.isBoolean(false); + * // => true + * + * _.isBoolean(null); + * // => false + */ + function isBoolean(value) { + return value === true || value === false || + (isObjectLike(value) && baseGetTag(value) == boolTag); + } + + /** + * Checks if `value` is classified as a `Date` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a date object, else `false`. + * @example + * + * _.isDate(new Date); + * // => true + * + * _.isDate('Mon April 23 2012'); + * // => false + */ + var isDate = baseIsDate; + + /** + * Checks if `value` is an empty object, collection, map, or set. + * + * Objects are considered empty if they have no own enumerable string keyed + * properties. + * + * Array-like values such as `arguments` objects, arrays, buffers, strings, or + * jQuery-like collections are considered empty if they have a `length` of `0`. + * Similarly, maps and sets are considered empty if they have a `size` of `0`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is empty, else `false`. + * @example + * + * _.isEmpty(null); + * // => true + * + * _.isEmpty(true); + * // => true + * + * _.isEmpty(1); + * // => true + * + * _.isEmpty([1, 2, 3]); + * // => false + * + * _.isEmpty({ 'a': 1 }); + * // => false + */ + function isEmpty(value) { + if (isArrayLike(value) && + (isArray(value) || isString(value) || + isFunction(value.splice) || isArguments(value))) { + return !value.length; + } + return !nativeKeys(value).length; + } + + /** + * Performs a deep comparison between two values to determine if they are + * equivalent. + * + * **Note:** This method supports comparing arrays, array buffers, booleans, + * date objects, error objects, maps, numbers, `Object` objects, regexes, + * sets, strings, symbols, and typed arrays. `Object` objects are compared + * by their own, not inherited, enumerable properties. Functions and DOM + * nodes are compared by strict equality, i.e. `===`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @returns {boolean} Returns `true` if the values are equivalent, else `false`. + * @example + * + * var object = { 'a': 1 }; + * var other = { 'a': 1 }; + * + * _.isEqual(object, other); + * // => true + * + * object === other; + * // => false + */ + function isEqual(value, other) { + return baseIsEqual(value, other); + } + + /** + * Checks if `value` is a finite primitive number. + * + * **Note:** This method is based on + * [`Number.isFinite`](https://mdn.io/Number/isFinite). + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a finite number, else `false`. + * @example + * + * _.isFinite(3); + * // => true + * + * _.isFinite(Number.MIN_VALUE); + * // => true + * + * _.isFinite(Infinity); + * // => false + * + * _.isFinite('3'); + * // => false + */ + function isFinite(value) { + return typeof value == 'number' && nativeIsFinite(value); + } + + /** + * Checks if `value` is classified as a `Function` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a function, else `false`. + * @example + * + * _.isFunction(_); + * // => true + * + * _.isFunction(/abc/); + * // => false + */ + function isFunction(value) { + if (!isObject(value)) { + return false; + } + // The use of `Object#toString` avoids issues with the `typeof` operator + // in Safari 9 which returns 'object' for typed arrays and other constructors. + var tag = baseGetTag(value); + return tag == funcTag || tag == genTag || tag == asyncTag || tag == proxyTag; + } + + /** + * Checks if `value` is a valid array-like length. + * + * **Note:** This method is loosely based on + * [`ToLength`](http://ecma-international.org/ecma-262/7.0/#sec-tolength). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a valid length, else `false`. + * @example + * + * _.isLength(3); + * // => true + * + * _.isLength(Number.MIN_VALUE); + * // => false + * + * _.isLength(Infinity); + * // => false + * + * _.isLength('3'); + * // => false + */ + function isLength(value) { + return typeof value == 'number' && + value > -1 && value % 1 == 0 && value <= MAX_SAFE_INTEGER; + } + + /** + * Checks if `value` is the + * [language type](http://www.ecma-international.org/ecma-262/7.0/#sec-ecmascript-language-types) + * of `Object`. (e.g. arrays, functions, objects, regexes, `new Number(0)`, and `new String('')`) + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an object, else `false`. + * @example + * + * _.isObject({}); + * // => true + * + * _.isObject([1, 2, 3]); + * // => true + * + * _.isObject(_.noop); + * // => true + * + * _.isObject(null); + * // => false + */ + function isObject(value) { + var type = typeof value; + return value != null && (type == 'object' || type == 'function'); + } + + /** + * Checks if `value` is object-like. A value is object-like if it's not `null` + * and has a `typeof` result of "object". + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is object-like, else `false`. + * @example + * + * _.isObjectLike({}); + * // => true + * + * _.isObjectLike([1, 2, 3]); + * // => true + * + * _.isObjectLike(_.noop); + * // => false + * + * _.isObjectLike(null); + * // => false + */ + function isObjectLike(value) { + return value != null && typeof value == 'object'; + } + + /** + * Checks if `value` is `NaN`. + * + * **Note:** This method is based on + * [`Number.isNaN`](https://mdn.io/Number/isNaN) and is not the same as + * global [`isNaN`](https://mdn.io/isNaN) which returns `true` for + * `undefined` and other non-number values. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is `NaN`, else `false`. + * @example + * + * _.isNaN(NaN); + * // => true + * + * _.isNaN(new Number(NaN)); + * // => true + * + * isNaN(undefined); + * // => true + * + * _.isNaN(undefined); + * // => false + */ + function isNaN(value) { + // An `NaN` primitive is the only value that is not equal to itself. + // Perform the `toStringTag` check first to avoid errors with some + // ActiveX objects in IE. + return isNumber(value) && value != +value; + } + + /** + * Checks if `value` is `null`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is `null`, else `false`. + * @example + * + * _.isNull(null); + * // => true + * + * _.isNull(void 0); + * // => false + */ + function isNull(value) { + return value === null; + } + + /** + * Checks if `value` is classified as a `Number` primitive or object. + * + * **Note:** To exclude `Infinity`, `-Infinity`, and `NaN`, which are + * classified as numbers, use the `_.isFinite` method. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a number, else `false`. + * @example + * + * _.isNumber(3); + * // => true + * + * _.isNumber(Number.MIN_VALUE); + * // => true + * + * _.isNumber(Infinity); + * // => true + * + * _.isNumber('3'); + * // => false + */ + function isNumber(value) { + return typeof value == 'number' || + (isObjectLike(value) && baseGetTag(value) == numberTag); + } + + /** + * Checks if `value` is classified as a `RegExp` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a regexp, else `false`. + * @example + * + * _.isRegExp(/abc/); + * // => true + * + * _.isRegExp('/abc/'); + * // => false + */ + var isRegExp = baseIsRegExp; + + /** + * Checks if `value` is classified as a `String` primitive or object. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a string, else `false`. + * @example + * + * _.isString('abc'); + * // => true + * + * _.isString(1); + * // => false + */ + function isString(value) { + return typeof value == 'string' || + (!isArray(value) && isObjectLike(value) && baseGetTag(value) == stringTag); + } + + /** + * Checks if `value` is `undefined`. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is `undefined`, else `false`. + * @example + * + * _.isUndefined(void 0); + * // => true + * + * _.isUndefined(null); + * // => false + */ + function isUndefined(value) { + return value === undefined; + } + + /** + * Converts `value` to an array. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Lang + * @param {*} value The value to convert. + * @returns {Array} Returns the converted array. + * @example + * + * _.toArray({ 'a': 1, 'b': 2 }); + * // => [1, 2] + * + * _.toArray('abc'); + * // => ['a', 'b', 'c'] + * + * _.toArray(1); + * // => [] + * + * _.toArray(null); + * // => [] + */ + function toArray(value) { + if (!isArrayLike(value)) { + return values(value); + } + return value.length ? copyArray(value) : []; + } + + /** + * Converts `value` to an integer. + * + * **Note:** This method is loosely based on + * [`ToInteger`](http://www.ecma-international.org/ecma-262/7.0/#sec-tointeger). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to convert. + * @returns {number} Returns the converted integer. + * @example + * + * _.toInteger(3.2); + * // => 3 + * + * _.toInteger(Number.MIN_VALUE); + * // => 0 + * + * _.toInteger(Infinity); + * // => 1.7976931348623157e+308 + * + * _.toInteger('3.2'); + * // => 3 + */ + var toInteger = Number; + + /** + * Converts `value` to a number. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to process. + * @returns {number} Returns the number. + * @example + * + * _.toNumber(3.2); + * // => 3.2 + * + * _.toNumber(Number.MIN_VALUE); + * // => 5e-324 + * + * _.toNumber(Infinity); + * // => Infinity + * + * _.toNumber('3.2'); + * // => 3.2 + */ + var toNumber = Number; + + /** + * Converts `value` to a string. An empty string is returned for `null` + * and `undefined` values. The sign of `-0` is preserved. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to convert. + * @returns {string} Returns the converted string. + * @example + * + * _.toString(null); + * // => '' + * + * _.toString(-0); + * // => '-0' + * + * _.toString([1, 2, 3]); + * // => '1,2,3' + */ + function toString(value) { + if (typeof value == 'string') { + return value; + } + return value == null ? '' : (value + ''); + } + + /*------------------------------------------------------------------------*/ + + /** + * Assigns own enumerable string keyed properties of source objects to the + * destination object. Source objects are applied from left to right. + * Subsequent sources overwrite property assignments of previous sources. + * + * **Note:** This method mutates `object` and is loosely based on + * [`Object.assign`](https://mdn.io/Object/assign). + * + * @static + * @memberOf _ + * @since 0.10.0 + * @category Object + * @param {Object} object The destination object. + * @param {...Object} [sources] The source objects. + * @returns {Object} Returns `object`. + * @see _.assignIn + * @example + * + * function Foo() { + * this.a = 1; + * } + * + * function Bar() { + * this.c = 3; + * } + * + * Foo.prototype.b = 2; + * Bar.prototype.d = 4; + * + * _.assign({ 'a': 0 }, new Foo, new Bar); + * // => { 'a': 1, 'c': 3 } + */ + var assign = createAssigner(function(object, source) { + copyObject(source, nativeKeys(source), object); + }); + + /** + * This method is like `_.assign` except that it iterates over own and + * inherited source properties. + * + * **Note:** This method mutates `object`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @alias extend + * @category Object + * @param {Object} object The destination object. + * @param {...Object} [sources] The source objects. + * @returns {Object} Returns `object`. + * @see _.assign + * @example + * + * function Foo() { + * this.a = 1; + * } + * + * function Bar() { + * this.c = 3; + * } + * + * Foo.prototype.b = 2; + * Bar.prototype.d = 4; + * + * _.assignIn({ 'a': 0 }, new Foo, new Bar); + * // => { 'a': 1, 'b': 2, 'c': 3, 'd': 4 } + */ + var assignIn = createAssigner(function(object, source) { + copyObject(source, nativeKeysIn(source), object); + }); + + /** + * Creates an object that inherits from the `prototype` object. If a + * `properties` object is given, its own enumerable string keyed properties + * are assigned to the created object. + * + * @static + * @memberOf _ + * @since 2.3.0 + * @category Object + * @param {Object} prototype The object to inherit from. + * @param {Object} [properties] The properties to assign to the object. + * @returns {Object} Returns the new object. + * @example + * + * function Shape() { + * this.x = 0; + * this.y = 0; + * } + * + * function Circle() { + * Shape.call(this); + * } + * + * Circle.prototype = _.create(Shape.prototype, { + * 'constructor': Circle + * }); + * + * var circle = new Circle; + * circle instanceof Circle; + * // => true + * + * circle instanceof Shape; + * // => true + */ + function create(prototype, properties) { + var result = baseCreate(prototype); + return properties == null ? result : assign(result, properties); + } + + /** + * Assigns own and inherited enumerable string keyed properties of source + * objects to the destination object for all destination properties that + * resolve to `undefined`. Source objects are applied from left to right. + * Once a property is set, additional values of the same property are ignored. + * + * **Note:** This method mutates `object`. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Object + * @param {Object} object The destination object. + * @param {...Object} [sources] The source objects. + * @returns {Object} Returns `object`. + * @see _.defaultsDeep + * @example + * + * _.defaults({ 'a': 1 }, { 'b': 2 }, { 'a': 3 }); + * // => { 'a': 1, 'b': 2 } + */ + var defaults = baseRest(function(object, sources) { + object = Object(object); + + var index = -1; + var length = sources.length; + var guard = length > 2 ? sources[2] : undefined; + + if (guard && isIterateeCall(sources[0], sources[1], guard)) { + length = 1; + } + + while (++index < length) { + var source = sources[index]; + var props = keysIn(source); + var propsIndex = -1; + var propsLength = props.length; + + while (++propsIndex < propsLength) { + var key = props[propsIndex]; + var value = object[key]; + + if (value === undefined || + (eq(value, objectProto[key]) && !hasOwnProperty.call(object, key))) { + object[key] = source[key]; + } + } + } + + return object; + }); + + /** + * Checks if `path` is a direct property of `object`. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Object + * @param {Object} object The object to query. + * @param {Array|string} path The path to check. + * @returns {boolean} Returns `true` if `path` exists, else `false`. + * @example + * + * var object = { 'a': { 'b': 2 } }; + * var other = _.create({ 'a': _.create({ 'b': 2 }) }); + * + * _.has(object, 'a'); + * // => true + * + * _.has(object, 'a.b'); + * // => true + * + * _.has(object, ['a', 'b']); + * // => true + * + * _.has(other, 'a'); + * // => false + */ + function has(object, path) { + return object != null && hasOwnProperty.call(object, path); + } + + /** + * Creates an array of the own enumerable property names of `object`. + * + * **Note:** Non-object values are coerced to objects. See the + * [ES spec](http://ecma-international.org/ecma-262/7.0/#sec-object.keys) + * for more details. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Object + * @param {Object} object The object to query. + * @returns {Array} Returns the array of property names. + * @example + * + * function Foo() { + * this.a = 1; + * this.b = 2; + * } + * + * Foo.prototype.c = 3; + * + * _.keys(new Foo); + * // => ['a', 'b'] (iteration order is not guaranteed) + * + * _.keys('hi'); + * // => ['0', '1'] + */ + var keys = nativeKeys; + + /** + * Creates an array of the own and inherited enumerable property names of `object`. + * + * **Note:** Non-object values are coerced to objects. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Object + * @param {Object} object The object to query. + * @returns {Array} Returns the array of property names. + * @example + * + * function Foo() { + * this.a = 1; + * this.b = 2; + * } + * + * Foo.prototype.c = 3; + * + * _.keysIn(new Foo); + * // => ['a', 'b', 'c'] (iteration order is not guaranteed) + */ + var keysIn = nativeKeysIn; + + /** + * Creates an object composed of the picked `object` properties. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Object + * @param {Object} object The source object. + * @param {...(string|string[])} [paths] The property paths to pick. + * @returns {Object} Returns the new object. + * @example + * + * var object = { 'a': 1, 'b': '2', 'c': 3 }; + * + * _.pick(object, ['a', 'c']); + * // => { 'a': 1, 'c': 3 } + */ + var pick = flatRest(function(object, paths) { + return object == null ? {} : basePick(object, paths); + }); + + /** + * This method is like `_.get` except that if the resolved value is a + * function it's invoked with the `this` binding of its parent object and + * its result is returned. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Object + * @param {Object} object The object to query. + * @param {Array|string} path The path of the property to resolve. + * @param {*} [defaultValue] The value returned for `undefined` resolved values. + * @returns {*} Returns the resolved value. + * @example + * + * var object = { 'a': [{ 'b': { 'c1': 3, 'c2': _.constant(4) } }] }; + * + * _.result(object, 'a[0].b.c1'); + * // => 3 + * + * _.result(object, 'a[0].b.c2'); + * // => 4 + * + * _.result(object, 'a[0].b.c3', 'default'); + * // => 'default' + * + * _.result(object, 'a[0].b.c3', _.constant('default')); + * // => 'default' + */ + function result(object, path, defaultValue) { + var value = object == null ? undefined : object[path]; + if (value === undefined) { + value = defaultValue; + } + return isFunction(value) ? value.call(object) : value; + } + + /** + * Creates an array of the own enumerable string keyed property values of `object`. + * + * **Note:** Non-object values are coerced to objects. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Object + * @param {Object} object The object to query. + * @returns {Array} Returns the array of property values. + * @example + * + * function Foo() { + * this.a = 1; + * this.b = 2; + * } + * + * Foo.prototype.c = 3; + * + * _.values(new Foo); + * // => [1, 2] (iteration order is not guaranteed) + * + * _.values('hi'); + * // => ['h', 'i'] + */ + function values(object) { + return object == null ? [] : baseValues(object, keys(object)); + } + + /*------------------------------------------------------------------------*/ + + /** + * Converts the characters "&", "<", ">", '"', and "'" in `string` to their + * corresponding HTML entities. + * + * **Note:** No other characters are escaped. To escape additional + * characters use a third-party library like [_he_](https://mths.be/he). + * + * Though the ">" character is escaped for symmetry, characters like + * ">" and "/" don't need escaping in HTML and have no special meaning + * unless they're part of a tag or unquoted attribute value. See + * [Mathias Bynens's article](https://mathiasbynens.be/notes/ambiguous-ampersands) + * (under "semi-related fun fact") for more details. + * + * When working with HTML you should always + * [quote attribute values](http://wonko.com/post/html-escaping) to reduce + * XSS vectors. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category String + * @param {string} [string=''] The string to escape. + * @returns {string} Returns the escaped string. + * @example + * + * _.escape('fred, barney, & pebbles'); + * // => 'fred, barney, & pebbles' + */ + function escape(string) { + string = toString(string); + return (string && reHasUnescapedHtml.test(string)) + ? string.replace(reUnescapedHtml, escapeHtmlChar) + : string; + } + + /*------------------------------------------------------------------------*/ + + /** + * This method returns the first argument it receives. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Util + * @param {*} value Any value. + * @returns {*} Returns `value`. + * @example + * + * var object = { 'a': 1 }; + * + * console.log(_.identity(object) === object); + * // => true + */ + function identity(value) { + return value; + } + + /** + * Creates a function that invokes `func` with the arguments of the created + * function. If `func` is a property name, the created function returns the + * property value for a given element. If `func` is an array or object, the + * created function returns `true` for elements that contain the equivalent + * source properties, otherwise it returns `false`. + * + * @static + * @since 4.0.0 + * @memberOf _ + * @category Util + * @param {*} [func=_.identity] The value to convert to a callback. + * @returns {Function} Returns the callback. + * @example + * + * var users = [ + * { 'user': 'barney', 'age': 36, 'active': true }, + * { 'user': 'fred', 'age': 40, 'active': false } + * ]; + * + * // The `_.matches` iteratee shorthand. + * _.filter(users, _.iteratee({ 'user': 'barney', 'active': true })); + * // => [{ 'user': 'barney', 'age': 36, 'active': true }] + * + * // The `_.matchesProperty` iteratee shorthand. + * _.filter(users, _.iteratee(['user', 'fred'])); + * // => [{ 'user': 'fred', 'age': 40 }] + * + * // The `_.property` iteratee shorthand. + * _.map(users, _.iteratee('user')); + * // => ['barney', 'fred'] + * + * // Create custom iteratee shorthands. + * _.iteratee = _.wrap(_.iteratee, function(iteratee, func) { + * return !_.isRegExp(func) ? iteratee(func) : function(string) { + * return func.test(string); + * }; + * }); + * + * _.filter(['abc', 'def'], /ef/); + * // => ['def'] + */ + var iteratee = baseIteratee; + + /** + * Creates a function that performs a partial deep comparison between a given + * object and `source`, returning `true` if the given object has equivalent + * property values, else `false`. + * + * **Note:** The created function is equivalent to `_.isMatch` with `source` + * partially applied. + * + * Partial comparisons will match empty array and empty object `source` + * values against any array or object value, respectively. See `_.isEqual` + * for a list of supported value comparisons. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Util + * @param {Object} source The object of property values to match. + * @returns {Function} Returns the new spec function. + * @example + * + * var objects = [ + * { 'a': 1, 'b': 2, 'c': 3 }, + * { 'a': 4, 'b': 5, 'c': 6 } + * ]; + * + * _.filter(objects, _.matches({ 'a': 4, 'c': 6 })); + * // => [{ 'a': 4, 'b': 5, 'c': 6 }] + */ + function matches(source) { + return baseMatches(assign({}, source)); + } + + /** + * Adds all own enumerable string keyed function properties of a source + * object to the destination object. If `object` is a function, then methods + * are added to its prototype as well. + * + * **Note:** Use `_.runInContext` to create a pristine `lodash` function to + * avoid conflicts caused by modifying the original. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Util + * @param {Function|Object} [object=lodash] The destination object. + * @param {Object} source The object of functions to add. + * @param {Object} [options={}] The options object. + * @param {boolean} [options.chain=true] Specify whether mixins are chainable. + * @returns {Function|Object} Returns `object`. + * @example + * + * function vowels(string) { + * return _.filter(string, function(v) { + * return /[aeiou]/i.test(v); + * }); + * } + * + * _.mixin({ 'vowels': vowels }); + * _.vowels('fred'); + * // => ['e'] + * + * _('fred').vowels().value(); + * // => ['e'] + * + * _.mixin({ 'vowels': vowels }, { 'chain': false }); + * _('fred').vowels(); + * // => ['e'] + */ + function mixin(object, source, options) { + var props = keys(source), + methodNames = baseFunctions(source, props); + + if (options == null && + !(isObject(source) && (methodNames.length || !props.length))) { + options = source; + source = object; + object = this; + methodNames = baseFunctions(source, keys(source)); + } + var chain = !(isObject(options) && 'chain' in options) || !!options.chain, + isFunc = isFunction(object); + + baseEach(methodNames, function(methodName) { + var func = source[methodName]; + object[methodName] = func; + if (isFunc) { + object.prototype[methodName] = function() { + var chainAll = this.__chain__; + if (chain || chainAll) { + var result = object(this.__wrapped__), + actions = result.__actions__ = copyArray(this.__actions__); + + actions.push({ 'func': func, 'args': arguments, 'thisArg': object }); + result.__chain__ = chainAll; + return result; + } + return func.apply(object, arrayPush([this.value()], arguments)); + }; + } + }); + + return object; + } + + /** + * Reverts the `_` variable to its previous value and returns a reference to + * the `lodash` function. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Util + * @returns {Function} Returns the `lodash` function. + * @example + * + * var lodash = _.noConflict(); + */ + function noConflict() { + if (root._ === this) { + root._ = oldDash; + } + return this; + } + + /** + * This method returns `undefined`. + * + * @static + * @memberOf _ + * @since 2.3.0 + * @category Util + * @example + * + * _.times(2, _.noop); + * // => [undefined, undefined] + */ + function noop() { + // No operation performed. + } + + /** + * Generates a unique ID. If `prefix` is given, the ID is appended to it. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Util + * @param {string} [prefix=''] The value to prefix the ID with. + * @returns {string} Returns the unique ID. + * @example + * + * _.uniqueId('contact_'); + * // => 'contact_104' + * + * _.uniqueId(); + * // => '105' + */ + function uniqueId(prefix) { + var id = ++idCounter; + return toString(prefix) + id; + } + + /*------------------------------------------------------------------------*/ + + /** + * Computes the maximum value of `array`. If `array` is empty or falsey, + * `undefined` is returned. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Math + * @param {Array} array The array to iterate over. + * @returns {*} Returns the maximum value. + * @example + * + * _.max([4, 2, 8, 6]); + * // => 8 + * + * _.max([]); + * // => undefined + */ + function max(array) { + return (array && array.length) + ? baseExtremum(array, identity, baseGt) + : undefined; + } + + /** + * Computes the minimum value of `array`. If `array` is empty or falsey, + * `undefined` is returned. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Math + * @param {Array} array The array to iterate over. + * @returns {*} Returns the minimum value. + * @example + * + * _.min([4, 2, 8, 6]); + * // => 2 + * + * _.min([]); + * // => undefined + */ + function min(array) { + return (array && array.length) + ? baseExtremum(array, identity, baseLt) + : undefined; + } + + /*------------------------------------------------------------------------*/ + + // Add methods that return wrapped values in chain sequences. + lodash.assignIn = assignIn; + lodash.before = before; + lodash.bind = bind; + lodash.chain = chain; + lodash.compact = compact; + lodash.concat = concat; + lodash.create = create; + lodash.defaults = defaults; + lodash.defer = defer; + lodash.delay = delay; + lodash.filter = filter; + lodash.flatten = flatten; + lodash.flattenDeep = flattenDeep; + lodash.iteratee = iteratee; + lodash.keys = keys; + lodash.map = map; + lodash.matches = matches; + lodash.mixin = mixin; + lodash.negate = negate; + lodash.once = once; + lodash.pick = pick; + lodash.slice = slice; + lodash.sortBy = sortBy; + lodash.tap = tap; + lodash.thru = thru; + lodash.toArray = toArray; + lodash.values = values; + + // Add aliases. + lodash.extend = assignIn; + + // Add methods to `lodash.prototype`. + mixin(lodash, lodash); + + /*------------------------------------------------------------------------*/ + + // Add methods that return unwrapped values in chain sequences. + lodash.clone = clone; + lodash.escape = escape; + lodash.every = every; + lodash.find = find; + lodash.forEach = forEach; + lodash.has = has; + lodash.head = head; + lodash.identity = identity; + lodash.indexOf = indexOf; + lodash.isArguments = isArguments; + lodash.isArray = isArray; + lodash.isBoolean = isBoolean; + lodash.isDate = isDate; + lodash.isEmpty = isEmpty; + lodash.isEqual = isEqual; + lodash.isFinite = isFinite; + lodash.isFunction = isFunction; + lodash.isNaN = isNaN; + lodash.isNull = isNull; + lodash.isNumber = isNumber; + lodash.isObject = isObject; + lodash.isRegExp = isRegExp; + lodash.isString = isString; + lodash.isUndefined = isUndefined; + lodash.last = last; + lodash.max = max; + lodash.min = min; + lodash.noConflict = noConflict; + lodash.noop = noop; + lodash.reduce = reduce; + lodash.result = result; + lodash.size = size; + lodash.some = some; + lodash.uniqueId = uniqueId; + + // Add aliases. + lodash.each = forEach; + lodash.first = head; + + mixin(lodash, (function() { + var source = {}; + baseForOwn(lodash, function(func, methodName) { + if (!hasOwnProperty.call(lodash.prototype, methodName)) { + source[methodName] = func; + } + }); + return source; + }()), { 'chain': false }); + + /*------------------------------------------------------------------------*/ + + /** + * The semantic version number. + * + * @static + * @memberOf _ + * @type {string} + */ + lodash.VERSION = VERSION; + + // Add `Array` methods to `lodash.prototype`. + baseEach(['pop', 'join', 'replace', 'reverse', 'split', 'push', 'shift', 'sort', 'splice', 'unshift'], function(methodName) { + var func = (/^(?:replace|split)$/.test(methodName) ? String.prototype : arrayProto)[methodName], + chainName = /^(?:push|sort|unshift)$/.test(methodName) ? 'tap' : 'thru', + retUnwrapped = /^(?:pop|join|replace|shift)$/.test(methodName); + + lodash.prototype[methodName] = function() { + var args = arguments; + if (retUnwrapped && !this.__chain__) { + var value = this.value(); + return func.apply(isArray(value) ? value : [], args); + } + return this[chainName](function(value) { + return func.apply(isArray(value) ? value : [], args); + }); + }; + }); + + // Add chain sequence methods to the `lodash` wrapper. + lodash.prototype.toJSON = lodash.prototype.valueOf = lodash.prototype.value = wrapperValue; + + /*--------------------------------------------------------------------------*/ + + // Some AMD build optimizers, like r.js, check for condition patterns like: + if (true) { + // Expose Lodash on the global object to prevent errors when Lodash is + // loaded by a script tag in the presence of an AMD loader. + // See http://requirejs.org/docs/errors.html#mismatch for more details. + // Use `_.noConflict` to remove Lodash from the global object. + root._ = lodash; + + // Define as an anonymous module so, through path mapping, it can be + // referenced as the "underscore" module. + !(__WEBPACK_AMD_DEFINE_RESULT__ = function() { + return lodash; + }.call(exports, __webpack_require__, exports, module), __WEBPACK_AMD_DEFINE_RESULT__ !== undefined && (module.exports = __WEBPACK_AMD_DEFINE_RESULT__)); + } + // Check for `exports` after `define` in case a build optimizer adds it. + else if (freeModule) { + // Export for Node.js. + (freeModule.exports = lodash)._ = lodash; + // Export for CommonJS support. + freeExports._ = lodash; + } + else { + // Export to the global object. + root._ = lodash; + } + }.call(this)); + + /* WEBPACK VAR INJECTION */}.call(exports, (function() { return this; }()), __webpack_require__(59)(module))) + +/***/ }), +/* 59 */ +/***/ (function(module, exports) { + + module.exports = function(module) { + if(!module.webpackPolyfill) { + module.deprecate = function() {}; + module.paths = []; + // module.parent = undefined by default + module.children = []; + module.webpackPolyfill = 1; + } + return module; + } + + +/***/ }), +/* 60 */ +/***/ (function(module, exports, __webpack_require__) { + + var ArrowLink = __webpack_require__(61); + var BoxArrowLink = __webpack_require__(22); + var PlainLink = __webpack_require__(23); + var OwlDisjointWith = __webpack_require__(46); + var SetOperatorProperty = __webpack_require__(56); + + /** + * Stores the passed properties in links. + * @returns {Function} + */ + module.exports = (function (){ + var linkCreator = {}; + + /** + * Creates links from the passed properties. + * @param properties + */ + linkCreator.createLinks = function ( properties ){ + var links = groupPropertiesToLinks(properties); + + for ( var i = 0, l = links.length; i < l; i++ ) { + var link = links[i]; + + countAndSetLayers(link, links); + countAndSetLoops(link, links); + } + + return links; + }; + + /** + * Creates links of properties and - if existing - their inverses. + * @param properties the properties + * @returns {Array} + */ + function groupPropertiesToLinks( properties ){ + var links = [], + property, + addedProperties = __webpack_require__(62)(); + + for ( var i = 0, l = properties.length; i < l; i++ ) { + property = properties[i]; + + if ( !addedProperties.has(property) ) { + var link = createLink(property); + + property.link(link); + if ( property.inverse() ) { + property.inverse().link(link); + } + + links.push(link); + + addedProperties.add(property); + if ( property.inverse() ) { + addedProperties.add(property.inverse()); + } + } + } + + return links; + } + + function countAndSetLayers( link, allLinks ){ + var layer, + layers, + i, l; + + if ( typeof link.layers() === "undefined" ) { + layers = []; + + // Search for other links that are another layer + for ( i = 0, l = allLinks.length; i < l; i++ ) { + var otherLink = allLinks[i]; + if ( link.domain() === otherLink.domain() && link.range() === otherLink.range() || + link.domain() === otherLink.range() && link.range() === otherLink.domain() ) { + layers.push(otherLink); + } + } + + // Set the results on each of the layers + for ( i = 0, l = layers.length; i < l; ++i ) { + layer = layers[i]; + + layer.layerIndex(i); + layer.layers(layers); + } + } + } + + function countAndSetLoops( link, allLinks ){ + var loop, + loops, + i, l; + + if ( typeof link.loops() === "undefined" ) { + loops = []; + + // Search for other links that are also loops of the same node + for ( i = 0, l = allLinks.length; i < l; i++ ) { + var otherLink = allLinks[i]; + if ( link.domain() === otherLink.domain() && link.domain() === otherLink.range() ) { + loops.push(otherLink); + } + } + + // Set the results on each of the loops + for ( i = 0, l = loops.length; i < l; ++i ) { + loop = loops[i]; + + loop.loopIndex(i); + loop.loops(loops); + } + } + } + + function createLink( property ){ + var domain = property.domain(); + var range = property.range(); + + if ( property instanceof OwlDisjointWith ) { + return new PlainLink(domain, range, property); + } else if ( property instanceof SetOperatorProperty ) { + return new BoxArrowLink(domain, range, property); + } + return new ArrowLink(domain, range, property); + } + + return function (){ + // Return a function to keep module interfaces consistent + return linkCreator; + }; + })(); + + +/***/ }), +/* 61 */ +/***/ (function(module, exports, __webpack_require__) { + + var PlainLink = __webpack_require__(23); + + + module.exports = ArrowLink; + + function ArrowLink( domain, range, property ){ + PlainLink.apply(this, arguments); + } + + ArrowLink.prototype = Object.create(PlainLink.prototype); + ArrowLink.prototype.constructor = ArrowLink; + + + ArrowLink.prototype.draw = function ( linkGroup, markerContainer ){ + var property = this.label().property(); + var inverse = this.label().inverse(); + + createPropertyMarker(markerContainer, property); + if ( inverse ) { + createInverseMarker(markerContainer, inverse); + } + + PlainLink.prototype.draw.apply(this, arguments); + + // attach the markers to the link + linkGroup.attr("marker-end", "url(#" + property.markerId() + ")"); + if ( inverse ) { + linkGroup.attr("marker-start", "url(#" + inverse.markerId() + ")"); + } + }; + + function createPropertyMarker( markerContainer, property ){ + var marker = appendBasicMarker(markerContainer, property); + //marker.attr("refX", 12); + var m1X = -12; + var m1Y = 8; + var m2X = -12; + var m2Y = -8; + marker.append("path") + //.attr("d", "M0,-8L12,0L0,8Z") + .attr("d", "M0,0L " + m1X + "," + m1Y + "L" + m2X + "," + m2Y + "L" + 0 + "," + 0) + .classed(property.markerType(), true); + + property.markerElement(marker); + } + + function createInverseMarker( markerContainer, inverse ){ + var m1X = -12; + var m1Y = 8; + var m2X = -12; + var m2Y = -8; + var inverseMarker = appendBasicMarker(markerContainer, inverse); + inverseMarker.append("path") + //.attr("d", "M12,-8L0,0L12,8Z") + .attr("d", "M0,0L " + -m1X + "," + -m1Y + "L" + -m2X + "," + -m2Y + "L" + 0 + "," + 0) + .classed(inverse.markerType(), true); + + inverse.markerElement(inverseMarker); + } + + function appendBasicMarker( markerContainer, property ){ + return markerContainer.append("marker") + .datum(property) + .attr("id", property.markerId()) + + .attr("viewBox", "-14 -10 28 20") + .attr("markerWidth", 10) + .attr("markerHeight", 10) + //.attr("markerUnits", "userSpaceOnUse") + .attr("orient", "auto"); + } + + +/***/ }), +/* 62 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * A simple incomplete encapsulation of the d3 set, which is able to store webvowl + * elements by using their id. + */ + module.exports = function ( array ){ + + var set = {}, + d3Set = d3.set(array); + + set.has = function ( webvowlElement ){ + return d3Set.has(webvowlElement.id()); + }; + + set.add = function ( webvowlElement ){ + return d3Set.add(webvowlElement.id()); + }; + + set.remove = function ( webvowlElement ){ + return d3Set.remove(webvowlElement.id()); + }; + + set.empty = function (){ + return d3Set.empty(); + }; + + set.size = function (){ + return d3Set.size(); + }; + + return set; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 63 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + var BaseNode = __webpack_require__(9); + var DatatypeNode = __webpack_require__(35); + var Thing = __webpack_require__(31); + var ObjectProperty = __webpack_require__(50); + var DatatypeProperty = __webpack_require__(44); + var RdfsSubClassOf = __webpack_require__(55); + var Label = __webpack_require__(24); + + + var tools = {}; + module.exports = function (){ + return tools; + }; + + tools.isLabel = function ( element ){ + return element instanceof Label; + }; + + tools.isNode = function ( element ){ + return element instanceof BaseNode; + }; + + tools.isDatatype = function ( node ){ + return node instanceof DatatypeNode; + }; + + tools.isThing = function ( node ){ + return node instanceof Thing; + }; + + tools.isProperty = function ( element ){ + return element instanceof BaseProperty; + }; + + tools.isObjectProperty = function ( element ){ + return element instanceof ObjectProperty; + }; + + tools.isDatatypeProperty = function ( element ){ + return element instanceof DatatypeProperty; + }; + + tools.isRdfsSubClassOf = function ( property ){ + return property instanceof RdfsSubClassOf; + }; + + +/***/ }), +/* 64 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function (){ + var options = {}, + data, + graphContainerSelector, + classDistance = 200, + datatypeDistance = 120, + loopDistance = 150, + charge = -500, + gravity = 0.025, + linkStrength = 1, + height = 600, + width = 800, + selectionModules = [], + filterModules = [], + minMagnification = 0.01, + maxMagnification = 4, + compactNotation = false, + dynamicLabelWidth = true, + // some filters + literalFilter, + // menus + gravityMenu, + filterMenu, + loadingModule, + modeMenu, + pausedMenu, + pickAndPinModule, + resetMenu, + searchMenu, + ontologyMenu, + sidebar, + leftSidebar, + editSidebar, + navigationMenu, + exportMenu, + graphObject, + zoomSlider, + datatypeFilter, + focuserModule, + colorExternalsModule, + compactNotationModule, + objectPropertyFilter, + subclassFilter, + setOperatorFilter, + maxLabelWidth = 120, + metadataObject = {}, + generalOntologyMetaData = {}, + disjointPropertyFilter, + rectangularRep = false, + warningModule, + prefixModule, + drawPropertyDraggerOnHover = true, + showDraggerObject = false, + directInputModule, + scaleNodesByIndividuals = true, + useAccuracyHelper = true, + showRenderingStatistic = true, + showInputModality = false, + hideDebugOptions = true, + nodeDegreeFilter, + debugMenu, + + supportedDatatypes = ["rdfs:Literal", "xsd:boolean", "xsd:double", "xsd:integer", "xsd:string", "undefined"], + supportedClasses = ["owl:Thing", "owl:Class", "owl:DeprecatedClass"], + supportedProperties = ["owl:objectProperty", + "rdfs:subClassOf", + "owl:disjointWith", + "owl:allValuesFrom", + "owl:someValuesFrom" + ], + prefixList = { + rdf: 'http://www.w3.org/1999/02/22-rdf-syntax-ns#', + rdfs: 'http://www.w3.org/2000/01/rdf-schema#', + owl: 'http://www.w3.org/2002/07/owl#', + xsd: 'http://www.w3.org/2001/XMLSchema#', + dc: 'http://purl.org/dc/elements/1.1/#', + xml: 'http://www.w3.org/XML/1998/namespace' + }; + + options.clearMetaObject = function (){ + generalOntologyMetaData = {}; + }; + options.clearGeneralMetaObject = function (){ + generalOntologyMetaData = {}; + }; + + options.debugMenu = function ( val ){ + if ( !arguments.length ) return debugMenu; + debugMenu = val; + }; + + options.getHideDebugFeatures = function (){ + return hideDebugOptions; + }; + options.executeHiddenDebugFeatuers = function (){ + hideDebugOptions = !hideDebugOptions; + d3.selectAll(".debugOption").classed("hidden", hideDebugOptions); + if ( hideDebugOptions === false ) { + graphObject.setForceTickFunctionWithFPS(); + } + else { + graphObject.setDefaultForceTickFunction(); + } + if ( debugMenu ) { + debugMenu.updateSettings(); + } + options.setHideDebugFeaturesForDefaultObject(hideDebugOptions); + }; + + + options.addOrUpdateGeneralObjectEntry = function ( property, value ){ + if ( generalOntologyMetaData.hasOwnProperty(property) ) { + //console.log("Updating Property:"+ property); + if ( property === "iri" ) { + if ( validURL(value) === false ) { + warningModule.showWarning("Invalid Ontology IRI", "Input IRI does not represent an URL", "Restoring previous IRI for ontology", 1, false); + return false; + } + } + generalOntologyMetaData[property] = value; + } else { + generalOntologyMetaData[property] = value; + } + return true; + }; + + options.getGeneralMetaObjectProperty = function ( property ){ + if ( generalOntologyMetaData.hasOwnProperty(property) ) { + return generalOntologyMetaData[property]; + } + }; + + options.getGeneralMetaObject = function (){ + return generalOntologyMetaData; + }; + + options.addOrUpdateMetaObjectEntry = function ( property, value ){ + + if ( metadataObject.hasOwnProperty(property) ) { + metadataObject[property] = value; + } else { + metadataObject[property] = value; + } + }; + + options.getMetaObjectProperty = function ( property ){ + if ( metadataObject.hasOwnProperty(property) ) { + return metadataObject[property]; + } + }; + options.getMetaObject = function (){ + return metadataObject; + }; + + + options.prefixList = function (){ + return prefixList; + }; + options.addPrefix = function ( prefix, url ){ + prefixList[prefix] = url; + }; + + function validURL( str ){ + var urlregex = /^(https?|ftp):\/\/([a-zA-Z0-9.-]+(:[a-zA-Z0-9.&%$-]+)*@)*((25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9][0-9]?)(\.(25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9]?[0-9])){3}|([a-zA-Z0-9-]+\.)*[a-zA-Z0-9-]+\.(com|edu|gov|int|mil|net|org|biz|arpa|info|name|pro|aero|coop|museum|[a-zA-Z]{2}))(:[0-9]+)*(\/($|[a-zA-Z0-9.,?'\\+&%$#=~_-]+))*$/; + return urlregex.test(str); + } + + options.updatePrefix = function ( oldPrefix, newPrefix, oldURL, newURL ){ + if ( oldPrefix === newPrefix && oldURL === newURL ) { + // console.log("Nothing to update"); + return true; + } + if ( oldPrefix === newPrefix && oldURL !== newURL && validURL(newURL) === true ) { + // console.log("Update URL"); + prefixList[oldPrefix] = newURL; + } else if ( oldPrefix === newPrefix && oldURL !== newURL && validURL(newURL) === false ) { + if ( validURL(newURL) === false ) { + warningModule.showWarning("Invalid Prefix IRI", "Input IRI does not represent an IRI", "You should enter a valid IRI in form of a URL", 1, false); + return false; + } + + return false; + } + if ( oldPrefix !== newPrefix && validURL(newURL) === true ) { + + // sanity check + if ( prefixList.hasOwnProperty(newPrefix) ) { + // console.log("Already have this prefix!"); + warningModule.showWarning("Prefix Already Exist", "Prefix: " + newPrefix + " is already defined", "You should use an other one", 1, false); + return false; + } + options.removePrefix(oldPrefix); + options.addPrefix(newPrefix, newURL); + editSidebar.updateEditDeleteButtonIds(oldPrefix, newPrefix); + return true; + } + + // console.log("Is new URL ("+newURL+") valid? >> "+validURL(newURL)); + if ( validURL(newURL) === false ) { + warningModule.showWarning("Invalid Prefix IRI", "Input IRI does not represent an URL", "You should enter a valid URL", 1, false); + + } + return false; + }; + + options.removePrefix = function ( prefix ){ + delete prefixList[prefix]; + }; + + + options.supportedDatatypes = function (){ + return supportedDatatypes; + }; + options.supportedClasses = function (){ + return supportedClasses; + }; + options.supportedProperties = function (){ + return supportedProperties; + }; + + options.datatypeFilter = function ( val ){ + if ( !arguments.length ) return datatypeFilter; + datatypeFilter = val; + }; + + options.showDraggerObject = function ( val ){ + if ( !arguments.length ) { + return showDraggerObject; + } + showDraggerObject = val; + }; + options.useAccuracyHelper = function ( val ){ + if ( !arguments.length ) { + return useAccuracyHelper; + } + useAccuracyHelper = val; + }; + options.showAccuracyHelper = function ( val ){ + if ( !arguments.length ) { + return options.showDraggerObject(); + } + options.showDraggerObject(val); + }; + options.showRenderingStatistic = function ( val ){ + if ( !arguments.length ) { + return showRenderingStatistic; + } + showRenderingStatistic = val; + }; + options.showInputModality = function ( val ){ + if ( !arguments.length ) { + return showInputModality; + } + showInputModality = val; + }; + + options.drawPropertyDraggerOnHover = function ( val ){ + if ( !arguments.length ) return drawPropertyDraggerOnHover; + drawPropertyDraggerOnHover = val; + }; + + options.warningModule = function ( val ){ + if ( !arguments.length ) return warningModule; + warningModule = val; + }; + options.directInputModule = function ( val ){ + if ( !arguments.length ) return directInputModule; + directInputModule = val; + }; + options.prefixModule = function ( val ){ + if ( !arguments.length ) return prefixModule; + prefixModule = val; + }; + + options.focuserModule = function ( val ){ + if ( !arguments.length ) return focuserModule; + focuserModule = val; + }; + options.colorExternalsModule = function ( val ){ + if ( !arguments.length ) return colorExternalsModule; + colorExternalsModule = val; + }; + options.compactNotationModule = function ( val ){ + if ( !arguments.length ) return compactNotationModule; + compactNotationModule = val; + }; + + options.maxLabelWidth = function ( val ){ + if ( !arguments.length ) return maxLabelWidth; + maxLabelWidth = val; + }; + options.objectPropertyFilter = function ( val ){ + if ( !arguments.length ) return objectPropertyFilter; + objectPropertyFilter = val; + }; + options.disjointPropertyFilter = function ( val ){ + if ( !arguments.length ) return disjointPropertyFilter; + disjointPropertyFilter = val; + }; + options.subclassFilter = function ( val ){ + if ( !arguments.length ) return subclassFilter; + subclassFilter = val; + }; + options.setOperatorFilter = function ( val ){ + if ( !arguments.length ) return setOperatorFilter; + setOperatorFilter = val; + }; + options.leftSidebar = function ( val ){ + if ( !arguments.length ) return leftSidebar; + leftSidebar = val; + }; + options.editSidebar = function ( val ){ + if ( !arguments.length ) return editSidebar; + editSidebar = val; + }; + + options.zoomSlider = function ( val ){ + if ( !arguments.length ) return zoomSlider; + zoomSlider = val; + }; + + options.graphObject = function ( val ){ + if ( !arguments.length ) return graphObject; + graphObject = val; + }; + + + var defaultOptionsConfig = {}; + defaultOptionsConfig.sidebar = "1"; + defaultOptionsConfig.doc = -1; + defaultOptionsConfig.cd = 200; + defaultOptionsConfig.dd = 120; + defaultOptionsConfig.editorMode = "false"; + defaultOptionsConfig.filter_datatypes = "false"; + defaultOptionsConfig.filter_objectProperties = "false"; + defaultOptionsConfig.filter_sco = "false"; + defaultOptionsConfig.filter_disjoint = "true"; + defaultOptionsConfig.filter_setOperator = "false"; + defaultOptionsConfig.mode_dynamic = "true"; + defaultOptionsConfig.mode_scaling = "true"; + defaultOptionsConfig.mode_compact = "false"; + defaultOptionsConfig.mode_colorExt = "true"; + defaultOptionsConfig.mode_multiColor = "false"; + defaultOptionsConfig.debugFeatures = "false"; + defaultOptionsConfig.rect = 0; + + + options.initialConfig = function (){ + var initCfg = {}; + initCfg.sidebar = "1"; + initCfg.doc = -1; + initCfg.cd = 200; + initCfg.dd = 120; + initCfg.editorMode = "false"; + initCfg.filter_datatypes = "false"; + initCfg.filter_objectProperties = "false"; + initCfg.filter_sco = "false"; + initCfg.filter_disjoint = "true"; + initCfg.filter_setOperator = "false"; + initCfg.mode_dynamic = "true"; + initCfg.mode_scaling = "true"; + initCfg.mode_compact = "false"; + initCfg.mode_colorExt = "true"; + initCfg.mode_multiColor = "false"; + initCfg.mode_pnp = "false"; + initCfg.debugFeatures = "false"; + initCfg.rect = 0; + return initCfg; + }; + + options.setEditorModeForDefaultObject = function ( val ){ + defaultOptionsConfig.editorMode = String(val); + }; + options.setHideDebugFeaturesForDefaultObject = function ( val ){ + defaultOptionsConfig.debugFeatures = String(!val); + }; + + function updateConfigObject(){ + defaultOptionsConfig.sidebar = options.sidebar().getSidebarVisibility(); + defaultOptionsConfig.cd = options.classDistance(); + defaultOptionsConfig.dd = options.datatypeDistance(); + defaultOptionsConfig.filter_datatypes = String(options.filterMenu().getCheckBoxValue("datatypeFilterCheckbox")); + defaultOptionsConfig.filter_sco = String(options.filterMenu().getCheckBoxValue("subclassFilterCheckbox")); + defaultOptionsConfig.filter_disjoint = String(options.filterMenu().getCheckBoxValue("disjointFilterCheckbox")); + defaultOptionsConfig.filter_setOperator = String(options.filterMenu().getCheckBoxValue("setoperatorFilterCheckbox")); + defaultOptionsConfig.filter_objectProperties = String(options.filterMenu().getCheckBoxValue("objectPropertyFilterCheckbox")); + defaultOptionsConfig.mode_dynamic = String(options.dynamicLabelWidth()); + defaultOptionsConfig.mode_scaling = String(options.modeMenu().getCheckBoxValue("nodescalingModuleCheckbox")); + defaultOptionsConfig.mode_compact = String(options.modeMenu().getCheckBoxValue("compactnotationModuleCheckbox")); + defaultOptionsConfig.mode_colorExt = String(options.modeMenu().getCheckBoxValue("colorexternalsModuleCheckbox")); + defaultOptionsConfig.mode_multiColor = String(options.modeMenu().colorModeState()); + defaultOptionsConfig.mode_pnp = String(options.modeMenu().getCheckBoxValue("pickandpinModuleCheckbox")); + defaultOptionsConfig.rect = 0; + } + + options.defaultConfig = function (){ + updateConfigObject(); + return defaultOptionsConfig; + }; + + options.exportMenu = function ( val ){ + if ( !arguments.length ) return exportMenu; + exportMenu = val; + }; + + options.rectangularRepresentation = function ( val ){ + if ( !arguments.length ) { + return rectangularRep; + } else { + var intVal = parseInt(val); + if ( intVal === 0 ) { + rectangularRep = false; + } else { + rectangularRep = true; + } + } + }; + + options.dynamicLabelWidth = function ( val ){ + if ( !arguments.length ) + return dynamicLabelWidth; + else { + dynamicLabelWidth = val; + } + }; + options.sidebar = function ( s ){ + if ( !arguments.length ) return sidebar; + sidebar = s; + return options; + + }; + + options.navigationMenu = function ( m ){ + if ( !arguments.length ) return navigationMenu; + navigationMenu = m; + return options; + + }; + + options.ontologyMenu = function ( m ){ + if ( !arguments.length ) return ontologyMenu; + ontologyMenu = m; + return options; + }; + + options.searchMenu = function ( m ){ + if ( !arguments.length ) return searchMenu; + searchMenu = m; + return options; + }; + + options.resetMenu = function ( m ){ + if ( !arguments.length ) return resetMenu; + resetMenu = m; + return options; + }; + + options.pausedMenu = function ( m ){ + if ( !arguments.length ) return pausedMenu; + pausedMenu = m; + return options; + }; + + options.pickAndPinModule = function ( m ){ + if ( !arguments.length ) return pickAndPinModule; + pickAndPinModule = m; + return options; + }; + + options.gravityMenu = function ( m ){ + if ( !arguments.length ) return gravityMenu; + gravityMenu = m; + return options; + }; + + options.filterMenu = function ( m ){ + if ( !arguments.length ) return filterMenu; + filterMenu = m; + return options; + }; + + options.modeMenu = function ( m ){ + if ( !arguments.length ) return modeMenu; + modeMenu = m; + return options; + }; + + options.charge = function ( p ){ + if ( !arguments.length ) return charge; + charge = +p; + return options; + }; + + options.classDistance = function ( p ){ + if ( !arguments.length ) return classDistance; + classDistance = +p; + return options; + }; + + options.compactNotation = function ( p ){ + + if ( !arguments.length ) return compactNotation; + compactNotation = p; + return options; + }; + + options.data = function ( p ){ + if ( !arguments.length ) return data; + data = p; + return options; + }; + + options.datatypeDistance = function ( p ){ + if ( !arguments.length ) return datatypeDistance; + datatypeDistance = +p; + return options; + }; + + options.filterModules = function ( p ){ + if ( !arguments.length ) return filterModules; + filterModules = p; + return options; + }; + + options.graphContainerSelector = function ( p ){ + if ( !arguments.length ) return graphContainerSelector; + graphContainerSelector = p; + return options; + }; + + options.gravity = function ( p ){ + if ( !arguments.length ) return gravity; + gravity = +p; + return options; + }; + + options.height = function ( p ){ + if ( !arguments.length ) return height; + height = +p; + return options; + }; + + options.linkStrength = function ( p ){ + if ( !arguments.length ) return linkStrength; + linkStrength = +p; + return options; + }; + + options.loopDistance = function ( p ){ + if ( !arguments.length ) return loopDistance; + loopDistance = p; + return options; + }; + + options.minMagnification = function ( p ){ + if ( !arguments.length ) return minMagnification; + minMagnification = +p; + return options; + }; + + options.maxMagnification = function ( p ){ + if ( !arguments.length ) return maxMagnification; + maxMagnification = +p; + return options; + }; + + options.scaleNodesByIndividuals = function ( p ){ + if ( !arguments.length ) return scaleNodesByIndividuals; + scaleNodesByIndividuals = p; + return options; + }; + + options.selectionModules = function ( p ){ + if ( !arguments.length ) return selectionModules; + selectionModules = p; + return options; + }; + + options.width = function ( p ){ + if ( !arguments.length ) return width; + width = +p; + return options; + }; + + options.literalFilter = function ( p ){ + if ( !arguments.length ) return literalFilter; + literalFilter = p; + return options; + }; + options.nodeDegreeFilter = function ( p ){ + if ( !arguments.length ) return nodeDegreeFilter; + nodeDegreeFilter = p; + return options; + }; + + options.loadingModule = function ( p ){ + if ( !arguments.length ) return loadingModule; + loadingModule = p; + return options; + }; + + // define url loadable options; + // update all set values in the default object + options.setOptionsFromURL = function ( opts, changeEditFlag ){ + if ( opts.sidebar !== undefined ) sidebar.showSidebar(parseInt(opts.sidebar), true); + if ( opts.doc ) { + var asInt = parseInt(opts.doc); + filterMenu.setDegreeSliderValue(asInt); + graphObject.setGlobalDOF(asInt); + // reset the value to be -1; + defaultOptionsConfig.doc = -1; + } + var settingFlag = false; + if ( opts.editorMode ) { + if ( opts.editorMode === "true" ) settingFlag = true; + d3.select("#editorModeModuleCheckbox").node().checked = settingFlag; + + if ( changeEditFlag && changeEditFlag === true ) { + graphObject.editorMode(settingFlag); + } + + // update config object + defaultOptionsConfig.editorMode = opts.editorMode; + + } + if ( opts.cd ) { // class distance + options.classDistance(opts.cd); // class distance + defaultOptionsConfig.cd = opts.cd; + } + if ( opts.dd ) { // data distance + options.datatypeDistance(opts.dd); + defaultOptionsConfig.cd = opts.cd; + } + if ( opts.cd || opts.dd ) options.gravityMenu().reset(); // reset the values so the slider is updated; + + + settingFlag = false; + if ( opts.filter_datatypes ) { + if ( opts.filter_datatypes === "true" ) settingFlag = true; + filterMenu.setCheckBoxValue("datatypeFilterCheckbox", settingFlag); + defaultOptionsConfig.filter_datatypes = opts.filter_datatypes; + } + if ( opts.debugFeatures ) { + if ( opts.debugFeatures === "true" ) settingFlag = true; + hideDebugOptions = settingFlag; + if ( options.getHideDebugFeatures() === false ) { + options.executeHiddenDebugFeatuers(); + } + defaultOptionsConfig.debugFeatures = opts.debugFeatures; + } + + settingFlag = false; + if ( opts.filter_objectProperties ) { + if ( opts.filter_objectProperties === "true" ) settingFlag = true; + filterMenu.setCheckBoxValue("objectPropertyFilterCheckbox", settingFlag); + defaultOptionsConfig.filter_objectProperties = opts.filter_objectProperties; + } + settingFlag = false; + if ( opts.filter_sco ) { + if ( opts.filter_sco === "true" ) settingFlag = true; + filterMenu.setCheckBoxValue("subclassFilterCheckbox", settingFlag); + defaultOptionsConfig.filter_sco = opts.filter_sco; + } + settingFlag = false; + if ( opts.filter_disjoint ) { + if ( opts.filter_disjoint === "true" ) settingFlag = true; + filterMenu.setCheckBoxValue("disjointFilterCheckbox", settingFlag); + defaultOptionsConfig.filter_disjoint = opts.filter_disjoint; + } + settingFlag = false; + if ( opts.filter_setOperator ) { + if ( opts.filter_setOperator === "true" ) settingFlag = true; + filterMenu.setCheckBoxValue("setoperatorFilterCheckbox", settingFlag); + defaultOptionsConfig.filter_setOperator = opts.filter_setOperator; + } + filterMenu.updateSettings(); + + // modesMenu + settingFlag = false; + if ( opts.mode_dynamic ) { + if ( opts.mode_dynamic === "true" ) settingFlag = true; + modeMenu.setDynamicLabelWidth(settingFlag); + dynamicLabelWidth = settingFlag; + defaultOptionsConfig.mode_dynamic = opts.mode_dynamic; + } + // settingFlag=false; + // THIS SHOULD NOT BE SET USING THE OPTIONS ON THE URL + // if (opts.mode_picnpin) { + // graph.options().filterMenu().setCheckBoxValue("pickandpin ModuleCheckbox", settingFlag); + // } + + settingFlag = false; + if ( opts.mode_pnp ) { + if ( opts.mode_pnp === "true" ) settingFlag = true; + modeMenu.setCheckBoxValue("pickandpinModuleCheckbox", settingFlag); + defaultOptionsConfig.mode_pnp = opts.mode_pnp; + } + + settingFlag = false; + if ( opts.mode_scaling ) { + if ( opts.mode_scaling === "true" ) settingFlag = true; + modeMenu.setCheckBoxValue("nodescalingModuleCheckbox", settingFlag); + defaultOptionsConfig.mode_scaling = opts.mode_scaling; + } + + settingFlag = false; + if ( opts.mode_compact ) { + if ( opts.mode_compact === "true" ) settingFlag = true; + modeMenu.setCheckBoxValue("compactnotationModuleCheckbox", settingFlag); + defaultOptionsConfig.mode_compact = opts.mode_compact; + } + + settingFlag = false; + if ( opts.mode_colorExt ) { + if ( opts.mode_colorExt === "true" ) settingFlag = true; + modeMenu.setCheckBoxValue("colorexternalsModuleCheckbox", settingFlag); + defaultOptionsConfig.mode_colorExt = opts.mode_colorExt; + } + + settingFlag = false; + if ( opts.mode_multiColor ) { + if ( opts.mode_multiColor === "true" ) settingFlag = true; + modeMenu.setColorSwitchStateUsingURL(settingFlag); + defaultOptionsConfig.mode_multiColor = opts.mode_multiColor; + } + modeMenu.updateSettingsUsingURL(); + options.rectangularRepresentation(opts.rect); + }; + + return options; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 65 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var OwlDisjointWith = __webpack_require__(46); + var attributeParser = __webpack_require__(66)(); + var equivalentPropertyMerger = __webpack_require__(67)(); + var nodePrototypeMap = __webpack_require__(5)(); + var propertyPrototypeMap = __webpack_require__(40)(); + + /** + * Encapsulates the parsing and preparation logic of the input data. + * @param graph the graph object that will be passed to the elements + * @returns {{}} + */ + module.exports = function ( graph ){ + var parser = {}, + nodes, + properties, + classMap, + settingsData, + settingsImported = false, + settingsImportGraphZoomAndTranslation = false, + dictionary = [], + propertyMap; + + parser.getDictionary = function (){ + return dictionary; + }; + + parser.setDictionary = function ( d ){ + dictionary = d; + }; + + parser.settingsImported = function (){ + return settingsImported; + }; + parser.settingsImportGraphZoomAndTranslation = function (){ + return settingsImportGraphZoomAndTranslation; + }; + + parser.parseSettings = function (){ + settingsImported = true; + settingsImportGraphZoomAndTranslation = false; + + if ( !settingsData ) { + settingsImported = false; + return; + } + /** global settings **********************************************************/ + if ( settingsData.global ) { + if ( settingsData.global.zoom ) { + var zoomFactor = settingsData.global.zoom; + graph.setZoom(zoomFactor); + settingsImportGraphZoomAndTranslation = true; + } + + if ( settingsData.global.translation ) { + var translation = settingsData.global.translation; + graph.setTranslation(translation); + settingsImportGraphZoomAndTranslation = true; + } + + if ( settingsData.global.paused ) { + var paused = settingsData.global.paused; + graph.options().pausedMenu().setPauseValue(paused); + } + } + /** Gravity Settings **********************************************************/ + if ( settingsData.gravity ) { + if ( settingsData.gravity.classDistance ) { + var classDistance = settingsData.gravity.classDistance; + graph.options().classDistance(classDistance); + } + if ( settingsData.gravity.datatypeDistance ) { + var datatypeDistance = settingsData.gravity.datatypeDistance; + graph.options().datatypeDistance(datatypeDistance); + } + graph.options().gravityMenu().reset(); // reads the options values and sets the gui values + } + + + // shared variable declaration + + var i; + var id; + var checked; + /** Filter Settings **********************************************************/ + if ( settingsData.filter ) { + // checkbox settings + if ( settingsData.filter.checkBox ) { + var filter_cb = settingsData.filter.checkBox; + for ( i = 0; i < filter_cb.length; i++ ) { + id = filter_cb[i].id; + checked = filter_cb[i].checked; + graph.options().filterMenu().setCheckBoxValue(id, checked); + } + } + // node degree filter settings + if ( settingsData.filter.degreeSliderValue ) { + var degreeSliderValue = settingsData.filter.degreeSliderValue; + graph.options().filterMenu().setDegreeSliderValue(degreeSliderValue); + } + graph.options().filterMenu().updateSettings(); + } + + /** Modes Setting **********************************************************/ + if ( settingsData.modes ) { + // checkbox settings + if ( settingsData.modes.checkBox ) { + var modes_cb = settingsData.modes.checkBox; + for ( i = 0; i < modes_cb.length; i++ ) { + id = modes_cb[i].id; + checked = modes_cb[i].checked; + graph.options().modeMenu().setCheckBoxValue(id, checked); + } + } + // color switch settings + var state = settingsData.modes.colorSwitchState; + // state could be undefined + if ( state === true || state === false ) { + graph.options().modeMenu().setColorSwitchState(state); + } + graph.options().modeMenu().updateSettings(); + } + graph.updateStyle(); // updates graph representation(setting charges and distances) + }; + + + /** + * Parses the ontology data and preprocesses it (e.g. connecting inverse properties and so on). + * @param ontologyData the loaded ontology json file + */ + parser.parse = function ( ontologyData ){ + if ( !ontologyData ) { + nodes = []; + properties = []; + dictionary = []; + return; + } + dictionary = []; + if ( ontologyData.settings ) settingsData = ontologyData.settings; + else settingsData = undefined; + + var classes = combineClasses(ontologyData.class, ontologyData.classAttribute), + datatypes = combineClasses(ontologyData.datatype, ontologyData.datatypeAttribute), + combinedClassesAndDatatypes = classes.concat(datatypes), + unparsedProperties = ontologyData.property || [], + combinedProperties; + + // Inject properties for unions, intersections, ... + addSetOperatorProperties(combinedClassesAndDatatypes, unparsedProperties); + combinedProperties = combineProperties(unparsedProperties, ontologyData.propertyAttribute); + classMap = mapElements(combinedClassesAndDatatypes); + propertyMap = mapElements(combinedProperties); + mergeRangesOfEquivalentProperties(combinedProperties, combinedClassesAndDatatypes); + + // Process the graph data + convertTypesToIris(combinedClassesAndDatatypes, ontologyData.namespace); + convertTypesToIris(combinedProperties, ontologyData.namespace); + nodes = createNodeStructure(combinedClassesAndDatatypes, classMap); + properties = createPropertyStructure(combinedProperties, classMap, propertyMap); + }; + + /** + * @return {Array} the preprocessed nodes + */ + parser.nodes = function (){ + return nodes; + }; + + /** + * @returns {Array} the preprocessed properties + */ + parser.properties = function (){ + return properties; + }; + + /** + * Combines the passed objects with its attributes and prototypes. This also applies + * attributes defined in the base of the prototype. + */ + function combineClasses( baseObjects, attributes ){ + var combinations = []; + var prototypeMap = createLowerCasePrototypeMap(nodePrototypeMap); + + if ( baseObjects ) { + baseObjects.forEach(function ( element ){ + var matchingAttribute; + + if ( attributes ) { + // Look for an attribute with the same id and merge them + for ( var i = 0; i < attributes.length; i++ ) { + var attribute = attributes[i]; + if ( element.id === attribute.id ) { + matchingAttribute = attribute; + break; + } + } + addAdditionalAttributes(element, matchingAttribute); + } + + // Then look for a prototype to add its properties + var Prototype = prototypeMap.get(element.type.toLowerCase()); + + if ( Prototype ) { + addAdditionalAttributes(element, Prototype); // TODO might be unnecessary + + var node = new Prototype(graph); + node.annotations(element.annotations) + .baseIri(element.baseIri) + .comment(element.comment) + .complement(element.complement) + .disjointUnion(element.disjointUnion) + .description(element.description) + .equivalents(element.equivalent) + .id(element.id) + .intersection(element.intersection) + .label(element.label) + // .type(element.type) Ignore, because we predefined it + .union(element.union) + .iri(element.iri); + if ( element.pos ) { + node.x = element.pos[0]; + node.y = element.pos[1]; + node.px = node.x; + node.py = node.y; + } + //class element pin + var elementPinned = element.pinned; + if ( elementPinned === true ) { + node.pinned(true); + graph.options().pickAndPinModule().addPinnedElement(node); + } + // Create node objects for all individuals + if ( element.individuals ) { + element.individuals.forEach(function ( individual ){ + var individualNode = new Prototype(graph); + individualNode.label(individual.labels) + .iri(individual.iri); + + node.individuals().push(individualNode); + }); + } + + if ( element.attributes ) { + var deduplicatedAttributes = d3.set(element.attributes.concat(node.attributes())); + node.attributes(deduplicatedAttributes.values()); + } + combinations.push(node); + } else { + console.error("Unknown element type: " + element.type); + } + }); + } + + return combinations; + } + + function combineProperties( baseObjects, attributes ){ + var combinations = []; + var prototypeMap = createLowerCasePrototypeMap(propertyPrototypeMap); + + if ( baseObjects ) { + baseObjects.forEach(function ( element ){ + var matchingAttribute; + + if ( attributes ) { + // Look for an attribute with the same id and merge them + for ( var i = 0; i < attributes.length; i++ ) { + var attribute = attributes[i]; + if ( element.id === attribute.id ) { + matchingAttribute = attribute; + break; + } + } + addAdditionalAttributes(element, matchingAttribute); + } + + // Then look for a prototype to add its properties + var Prototype = prototypeMap.get(element.type.toLowerCase()); + + if ( Prototype ) { + // Create the matching object and set the properties + var property = new Prototype(graph); + property.annotations(element.annotations) + .baseIri(element.baseIri) + .cardinality(element.cardinality) + .comment(element.comment) + .domain(element.domain) + .description(element.description) + .equivalents(element.equivalent) + .id(element.id) + .inverse(element.inverse) + .label(element.label) + .minCardinality(element.minCardinality) + .maxCardinality(element.maxCardinality) + .range(element.range) + .subproperties(element.subproperty) + .superproperties(element.superproperty) + // .type(element.type) Ignore, because we predefined it + .iri(element.iri); + + // adding property position + if ( element.pos ) { + property.x = element.pos[0]; + property.y = element.pos[1]; + property.px = element.pos[0]; + property.py = element.pos[1]; + } + var elementPinned = element.pinned; + if ( elementPinned === true ) { + property.pinned(true); + graph.options().pickAndPinModule().addPinnedElement(property); + } + + + if ( element.attributes ) { + var deduplicatedAttributes = d3.set(element.attributes.concat(property.attributes())); + property.attributes(deduplicatedAttributes.values()); + } + combinations.push(property); + } else { + console.error("Unknown element type: " + element.type); + } + + }); + } + + return combinations; + } + + function createLowerCasePrototypeMap( prototypeMap ){ + return d3.map(prototypeMap.values(), function ( Prototype ){ + return new Prototype().type().toLowerCase(); + }); + } + + function mergeRangesOfEquivalentProperties( properties, nodes ){ + // pass clones of arrays into the merger to keep the current functionality of this module + var newNodes = equivalentPropertyMerger.merge(properties.slice(), nodes.slice(), propertyMap, classMap, graph); + + // replace all the existing nodes and map the nodes again + nodes.length = 0; + Array.prototype.push.apply(nodes, newNodes); + classMap = mapElements(nodes); + } + + /** + * Checks all attributes which have to be rewritten. + * For example: + * equivalent is filled with only ID's of the corresponding nodes. It would be better to used the + * object instead of the ID so we swap the ID's with the correct object reference and can delete it from drawing + * because it is not necessary. + */ + function createNodeStructure( rawNodes, classMap ){ + var nodes = []; + + // Set the default values + var maxIndividualCount = 0; + rawNodes.forEach(function ( node ){ + maxIndividualCount = Math.max(maxIndividualCount, node.individuals().length); + node.visible(true); + }); + + rawNodes.forEach(function ( node ){ + // Merge and connect the equivalent nodes + processEquivalentIds(node, classMap); + + attributeParser.parseClassAttributes(node); + + node.maxIndividualCount(maxIndividualCount); + }); + + // Collect all nodes that should be displayed + rawNodes.forEach(function ( node ){ + if ( node.visible() ) { + nodes.push(node); + } + }); + + return nodes; + } + + /** + * Sets the disjoint attribute of the nodes if a disjoint label is found. + * @param property + */ + function processDisjoints( property ){ + if ( property instanceof OwlDisjointWith === false ) { + return; + } + + var domain = property.domain(), + range = property.range(); + + // Check the domain. + if ( !domain.disjointWith() ) { + domain.disjointWith([]); + } + + // Check the range. + if ( !range.disjointWith() ) { + range.disjointWith([]); + } + + domain.disjointWith().push(property.range()); + range.disjointWith().push(property.domain()); + } + + /** + * Connect all properties and also their sub- and superproperties. + * We iterate over the rawProperties array because it is way faster than iterating + * over an object and its attributes. + * + * @param rawProperties the properties + * @param classMap a map of all classes + * @param propertyMap the properties in a map + */ + function createPropertyStructure( rawProperties, classMap, propertyMap ){ + var properties = []; + // Set default values + rawProperties.forEach(function ( property ){ + property.visible(true); + }); + + // Connect properties + rawProperties.forEach(function ( property ){ + var domain, + range, + domainObject, + rangeObject, + inverse; + + /* Skip properties that have no information about their domain and range, like + inverse properties with optional inverse and optional domain and range attributes */ + if ( (property.domain() && property.range()) || property.inverse() ) { + + var inversePropertyId = findId(property.inverse()); + // Look if an inverse property exists + if ( inversePropertyId ) { + inverse = propertyMap[inversePropertyId]; + if ( !inverse ) { + console.warn("No inverse property was found for id: " + inversePropertyId); + property.inverse(undefined); + } + } + + // Either domain and range are set on this property or at the inverse + if ( typeof property.domain() !== "undefined" && typeof property.range() !== "undefined" ) { + domain = findId(property.domain()); + range = findId(property.range()); + + domainObject = classMap[domain]; + rangeObject = classMap[range]; + } else if ( inverse ) { + // Domain and range need to be switched + domain = findId(inverse.range()); + range = findId(inverse.domain()); + + domainObject = classMap[domain]; + rangeObject = classMap[range]; + } else { + console.warn("Domain and range not found for property: " + property.id()); + } + + // Set the references on this property + property.domain(domainObject); + property.range(rangeObject); + + // Also set the attributes of the inverse property + if ( inverse ) { + property.inverse(inverse); + inverse.inverse(property); + + // Switch domain and range + inverse.domain(rangeObject); + inverse.range(domainObject); + } + } + // Reference sub- and superproperties + referenceSubOrSuperProperties(property.subproperties()); + referenceSubOrSuperProperties(property.superproperties()); + }); + + // Merge equivalent properties and process disjoints. + rawProperties.forEach(function ( property ){ + processEquivalentIds(property, propertyMap); + processDisjoints(property); + + attributeParser.parsePropertyAttributes(property); + }); + // Add additional information to the properties + rawProperties.forEach(function ( property ){ + // Properties of merged classes should point to/from the visible equivalent class + var propertyWasRerouted = false; + + if ( property.domain() === undefined ) { + console.warn("No Domain was found for id:" + property.id()); + return; + } + + if ( wasNodeMerged(property.domain()) ) { + property.domain(property.domain().equivalentBase()); + propertyWasRerouted = true; + } + if ( property.range() === undefined ) { + console.warn("No range was found for id:" + property.id()); + return; + } + if ( wasNodeMerged(property.range()) ) { + property.range(property.range().equivalentBase()); + propertyWasRerouted = true; + } + // But there should not be two equal properties between the same domain and range + var equalProperty = getOtherEqualProperty(rawProperties, property); + + if ( propertyWasRerouted && equalProperty ) { + property.visible(false); + + equalProperty.redundantProperties().push(property); + } + + // Hide property if source or target node is hidden + if ( !property.domain().visible() || !property.range().visible() ) { + property.visible(false); + } + + // Collect all properties that should be displayed + if ( property.visible() ) { + properties.push(property); + } + }); + return properties; + } + + function referenceSubOrSuperProperties( subOrSuperPropertiesArray ){ + var i, l; + + if ( !subOrSuperPropertiesArray ) { + return; + } + + for ( i = 0, l = subOrSuperPropertiesArray.length; i < l; ++i ) { + var subOrSuperPropertyId = findId(subOrSuperPropertiesArray[i]); + var subOrSuperProperty = propertyMap[subOrSuperPropertyId]; + + if ( subOrSuperProperty ) { + // Replace id with object + subOrSuperPropertiesArray[i] = subOrSuperProperty; + } else { + console.warn("No sub-/superproperty was found for id: " + subOrSuperPropertyId); + } + } + } + + function wasNodeMerged( node ){ + return !node.visible() && node.equivalentBase(); + } + + function getOtherEqualProperty( properties, referenceProperty ){ + var i, l, property; + + for ( i = 0, l = properties.length; i < l; i++ ) { + property = properties[i]; + + if ( referenceProperty === property ) { + continue; + } + if ( referenceProperty.domain() !== property.domain() || + referenceProperty.range() !== property.range() ) { + continue; + } + + // Check for an equal IRI, if non existent compare label and type + if ( referenceProperty.iri() && property.iri() ) { + if ( referenceProperty.iri() === property.iri() ) { + return property; + } + } else if ( referenceProperty.type() === property.type() && + referenceProperty.defaultLabel() === property.defaultLabel() ) { + return property; + } + } + + return undefined; + } + + /** + * Generates and adds properties for links to set operators. + * @param classes unprocessed classes + * @param properties unprocessed properties + */ + function addSetOperatorProperties( classes, properties ){ + function addProperties( domainId, rangeIds, operatorType ){ + if ( !rangeIds ) { + return; + } + + rangeIds.forEach(function ( rangeId, index ){ + var property = { + id: "GENERATED-" + operatorType + "-" + domainId + "-" + rangeId + "-" + index, + type: "setOperatorProperty", + domain: domainId, + range: rangeId + }; + + properties.push(property); + }); + } + + classes.forEach(function ( clss ){ + addProperties(clss.id(), clss.complement(), "COMPLEMENT"); + addProperties(clss.id(), clss.intersection(), "INTERSECTION"); + addProperties(clss.id(), clss.union(), "UNION"); + addProperties(clss.id(), clss.disjointUnion(), "DISJOINTUNION"); + }); + } + + /** + * Replaces the ids of equivalent nodes/properties with the matching objects, cross references them + * and tags them as processed. + * @param element a node or a property + * @param elementMap a map where nodes/properties can be looked up + */ + function processEquivalentIds( element, elementMap ){ + var eqIds = element.equivalents(); + + if ( !eqIds || element.equivalentBase() ) { + return; + } + + // Replace ids with the corresponding objects + for ( var i = 0, l = eqIds.length; i < l; ++i ) { + var eqId = findId(eqIds[i]); + var eqObject = elementMap[eqId]; + + if ( eqObject ) { + // Cross reference both objects + eqObject.equivalents(eqObject.equivalents()); + eqObject.equivalents().push(element); + eqObject.equivalentBase(element); + eqIds[i] = eqObject; + + // Hide other equivalent nodes + eqObject.visible(false); + } else { + console.warn("No class/property was found for equivalent id: " + eqId); + } + } + } + + /** + * Tries to convert the type to an iri and sets it. + * @param elements classes or properties + * @param namespaces an array of namespaces + */ + function convertTypesToIris( elements, namespaces ){ + elements.forEach(function ( element ){ + if ( typeof element.iri() === "string" ) { + element.iri(replaceNamespace(element.iri(), namespaces)); + } + }); + } + + /** + * Creates a map by mapping the array with the passed function. + * @param array the array + * @returns {{}} + */ + function mapElements( array ){ + var map = {}; + for ( var i = 0, length = array.length; i < length; i++ ) { + var element = array[i]; + map[element.id()] = element; + } + return map; + } + + /** + * Adds the attributes of the additional object to the base object, but doesn't + * overwrite existing ones. + * + * @param base the base object + * @param addition the object with additional data + * @returns the combination is also returned + */ + function addAdditionalAttributes( base, addition ){ + // Check for an undefined value + addition = addition || {}; + + for ( var addAttribute in addition ) { + // Add the attribute if it doesn't exist + if ( !(addAttribute in base) && addition.hasOwnProperty(addAttribute) ) { + base[addAttribute] = addition[addAttribute]; + } + } + return base; + } + + /** + * Replaces the namespace (and the separator) if one exists and returns the new value. + * @param address the address with a namespace in it + * @param namespaces an array of namespaces + * @returns {string} the processed address with the (possibly) replaced namespace + */ + function replaceNamespace( address, namespaces ){ + var separatorIndex = address.indexOf(":"); + if ( separatorIndex === -1 ) { + return address; + } + var namespaceName = address.substring(0, separatorIndex); + + for ( var i = 0, length = namespaces.length; i < length; ++i ) { + var namespace = namespaces[i]; + if ( namespaceName === namespace.name ) { + return namespace.iri + address.substring(separatorIndex + 1); + } + } + + return address; + } + + /** + * Looks whether the passed object is already the id or if it was replaced + * with the object that belongs to the id. + * @param object an id, a class or a property + * @returns {string} the id of the passed object or undefined + */ + function findId( object ){ + if ( !object ) { + return undefined; + } else if ( typeof object === "string" ) { + return object; + } else if ( "id" in object ) { + return object.id(); + } else { + console.warn("No Id was found for this object: " + object); + return undefined; + } + } + + return parser; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 66 */ +/***/ (function(module, exports) { + + /** + * Parses the attributes an element has and sets the corresponding attributes. + * @returns {Function} + */ + module.exports = (function (){ + var attributeParser = {}, + // Style + ANONYMOUS = "anonymous", + DATATYPE = "datatype", + DEPRECATED = "deprecated", + EXTERNAL = "external", + OBJECT = "object", + RDF = "rdf", + // Representations + ASYMMETRIC = "asymmetric", + FUNCTIONAL = "functional", + INVERSE_FUNCTIONAL = "inverse functional", + IRREFLEXIVE = "irreflexive", + KEY = "key", + REFLEXIVE = "reflexive", + SYMMETRIC = "symmetric", + TRANSITIVE = "transitive", + // Attribute groups + VISUAL_ATTRIBUTE_GROUPS = [ + [DEPRECATED, DATATYPE, OBJECT, RDF], + [ANONYMOUS] + ], + CLASS_INDICATIONS = [DEPRECATED, EXTERNAL], + PROPERTY_INDICATIONS = [ASYMMETRIC, FUNCTIONAL, INVERSE_FUNCTIONAL, IRREFLEXIVE, KEY, REFLEXIVE, SYMMETRIC, + TRANSITIVE]; + + /** + * Parses and sets the attributes of a class. + * @param clazz + */ + attributeParser.parseClassAttributes = function ( clazz ){ + if ( !(clazz.attributes() instanceof Array) ) { + return; + } + + parseVisualAttributes(clazz); + parseClassIndications(clazz); + }; + + function parseVisualAttributes( element ){ + VISUAL_ATTRIBUTE_GROUPS.forEach(function ( attributeGroup ){ + setVisualAttributeOfGroup(element, attributeGroup); + }); + } + + function setVisualAttributeOfGroup( element, group ){ + var i, l, attribute; + + for ( i = 0, l = group.length; i < l; i++ ) { + attribute = group[i]; + if ( element.attributes().indexOf(attribute) >= 0 ) { + element.visualAttributes().push(attribute); + + // Just a single attribute is possible + break; + } + } + } + + function parseClassIndications( clazz ){ + var i, l, indication; + + for ( i = 0, l = CLASS_INDICATIONS.length; i < l; i++ ) { + indication = CLASS_INDICATIONS[i]; + + if ( clazz.attributes().indexOf(indication) >= 0 ) { + clazz.indications().push(indication); + } + } + } + + /** + * Parses and sets the attributes of a property. + * @param property + */ + attributeParser.parsePropertyAttributes = function ( property ){ + if ( !(property.attributes() instanceof Array) ) { + return; + } + + parseVisualAttributes(property); + parsePropertyIndications(property); + }; + + function parsePropertyIndications( property ){ + var i, l, indication; + + for ( i = 0, l = PROPERTY_INDICATIONS.length; i < l; i++ ) { + indication = PROPERTY_INDICATIONS[i]; + + if ( property.attributes().indexOf(indication) >= 0 ) { + property.indications().push(indication); + } + } + } + + + return function (){ + // Return a function to keep module interfaces consistent + return attributeParser; + }; + })(); + + +/***/ }), +/* 67 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var OwlThing = __webpack_require__(31); + var RdfsLiteral = __webpack_require__(38); + var elementTools = __webpack_require__(63)(); + + var equivalentPropertyMerger = {}; + module.exports = function (){ + return equivalentPropertyMerger; + }; + + var PREFIX = "GENERATED-MERGED_RANGE-"; + var OBJECT_PROPERTY_DEFAULT_RANGE_TYPE = "owl:Thing"; + var DATA_PROPERTY_DEFAULT_RANGE_TYPE = "rdfs:Literal"; + + + equivalentPropertyMerger.merge = function ( properties, nodes, propertyMap, nodeMap, graph ){ + var totalNodeIdsToHide = d3.set(); + var processedPropertyIds = d3.set(); + var mergeNodes = []; + + for ( var i = 0; i < properties.length; i++ ) { + var property = properties[i]; + var equivalents = property.equivalents().map(createIdToPropertyMapper(propertyMap)); + + if ( equivalents.length === 0 || processedPropertyIds.has(property.id()) ) { + continue; + } + + var propertyWithEquivalents = equivalents.concat(property); + + var mergeNode = findMergeNode(propertyWithEquivalents, nodeMap); + if ( !mergeNode ) { + if ( mergeNode !== undefined ) { + mergeNode = createDefaultMergeNode(property, graph); + mergeNodes.push(mergeNode); + } + } + + var nodeIdsToHide = replaceRangesAndCollectNodesToHide(propertyWithEquivalents, mergeNode, properties, + processedPropertyIds); + for ( var j = 0; j < nodeIdsToHide.length; j++ ) { + totalNodeIdsToHide.add(nodeIdsToHide[j]); + } + } + + return filterVisibleNodes(nodes.concat(mergeNodes), totalNodeIdsToHide); + }; + + + function createIdToPropertyMapper( propertyMap ){ + return function ( id ){ + return propertyMap[id]; + }; + } + + function findMergeNode( propertyWithEquivalents, nodeMap ){ + var typeMap = mapPropertiesRangesToType(propertyWithEquivalents, nodeMap); + var typeSet = d3.set(typeMap.keys()); + + // default types are the fallback values and should be ignored for the type determination + typeSet.remove(OBJECT_PROPERTY_DEFAULT_RANGE_TYPE); + typeSet.remove(DATA_PROPERTY_DEFAULT_RANGE_TYPE); + + // exactly one type to chose from -> take the node of this type as range + if ( typeSet.size() === 1 ) { + var type = typeSet.values()[0]; + var ranges = typeMap.get(type); + + if ( ranges.length === 1 ) { + return ranges[0]; + } + } + } + + function mapPropertiesRangesToType( properties, nodeMap ){ + var typeMap = d3.map(); + + properties.forEach(function ( property ){ + if ( property === undefined ) //@ WORKAROUND + return; + + var range = nodeMap[property.range()]; + var type = range.type(); + + if ( !typeMap.has(type) ) { + typeMap.set(type, []); + } + + typeMap.get(type).push(range); + }); + + return typeMap; + } + + function createDefaultMergeNode( property, graph ){ + var range; + + if ( elementTools.isDatatypeProperty(property) ) { + range = new RdfsLiteral(graph); + } else { + range = new OwlThing(graph); + } + range.id(PREFIX + property.id()); + + return range; + } + + function replaceRangesAndCollectNodesToHide( propertyWithEquivalents, mergeNode, properties, processedPropertyIds ){ + var nodesToHide = []; + + propertyWithEquivalents.forEach(function ( property ){ + + if ( property === undefined || mergeNode === undefined ) // @ WORKAROUND + return; + var oldRangeId = property.range(); + property.range(mergeNode.id()); + if ( !isDomainOrRangeOfOtherProperty(oldRangeId, properties) ) { + nodesToHide.push(oldRangeId); + } + + processedPropertyIds.add(property.id()); + }); + + return nodesToHide; + } + + function isDomainOrRangeOfOtherProperty( nodeId, properties ){ + for ( var i = 0; i < properties.length; i++ ) { + var property = properties[i]; + if ( property.domain() === nodeId || property.range() === nodeId ) { + return true; + } + } + + return false; + } + + function filterVisibleNodes( nodes, nodeIdsToHide ){ + var filteredNodes = []; + + nodes.forEach(function ( node ){ + if ( !nodeIdsToHide.has(node.id()) ) { + filteredNodes.push(node); + } + }); + + return filteredNodes; + } + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 68 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( graph ){ + /** variable defs **/ + var Class_dragger = {}; + Class_dragger.nodeId = 10001; + Class_dragger.parent = undefined; + Class_dragger.x = 0; + Class_dragger.y = 0; + Class_dragger.rootElement = undefined; + Class_dragger.rootNodeLayer = undefined; + Class_dragger.pathLayer = undefined; + Class_dragger.mouseEnteredVar = false; + Class_dragger.mouseButtonPressed = false; + Class_dragger.nodeElement = undefined; + Class_dragger.draggerObject = undefined; + Class_dragger.pathElement = undefined; + Class_dragger.typus = "Class_dragger"; + + Class_dragger.type = function (){ + return Class_dragger.typus; + }; + + Class_dragger.parentNode = function (){ + return Class_dragger.parent; + }; + + Class_dragger.hideClass_dragger = function ( val ){ + Class_dragger.pathElement.classed("hidden", val); + Class_dragger.nodeElement.classed("hidden", val); + Class_dragger.draggerObject.classed("hidden", val); + }; + + Class_dragger.setParentNode = function ( parentNode ){ + Class_dragger.parent = parentNode; + + if ( Class_dragger.mouseButtonPressed === false ) { + if ( Class_dragger.parent.actualRadius && Class_dragger.parent.actualRadius() ) { + Class_dragger.x = Class_dragger.parent.x + 10 + Class_dragger.parent.actualRadius(); + Class_dragger.y = Class_dragger.parent.y + 10 + Class_dragger.parent.actualRadius(); + } else { + Class_dragger.x = Class_dragger.parent.x + 60; + Class_dragger.y = Class_dragger.parent.y + 60; + } + } + Class_dragger.updateElement(); + }; + + Class_dragger.hideDragger = function ( val ){ + if ( Class_dragger.pathElement ) Class_dragger.pathElement.classed("hidden", val); + if ( Class_dragger.nodeElement ) Class_dragger.nodeElement.classed("hidden", val); + if ( Class_dragger.draggerObject ) Class_dragger.draggerObject.classed("hidden", val); + + }; + /** BASE HANDLING FUNCTIONS ------------------------------------------------- **/ + Class_dragger.id = function ( index ){ + if ( !arguments.length ) { + return Class_dragger.nodeId; + } + Class_dragger.nodeId = index; + }; + + Class_dragger.svgPathLayer = function ( layer ){ + Class_dragger.pathLayer = layer.append('g'); + }; + + Class_dragger.svgRoot = function ( root ){ + if ( !arguments.length ) + return Class_dragger.rootElement; + Class_dragger.rootElement = root; + Class_dragger.rootNodeLayer = Class_dragger.rootElement.append('g'); + Class_dragger.addMouseEvents(); + }; + + /** DRAWING FUNCTIONS ------------------------------------------------- **/ + Class_dragger.drawNode = function (){ + Class_dragger.pathElement = Class_dragger.pathLayer.append('line') + .classed("classNodeDragPath", true); + Class_dragger.pathElement.attr("x1", 0) + .attr("y1", 0) + .attr("x2", 0) + .attr("y2", 0); + + // var lineData = [ + // {"x": 0, "y": 0}, + // {"x": 0, "y": 40}, + // {"x": -40, "y": 0}, + // {"x": 0, "y": -40}, + // {"x": 0, "y": 0} + // ]; + + var lineData = [ + { "x": -40, "y": 0 }, // start + { "x": -20, "y": -10 }, + { "x": 20, "y": -50 }, + { "x": -10, "y": 0 }, // center + { "x": 20, "y": 50 }, + { "x": -20, "y": 10 }, + { "x": -40, "y": 0 } + ]; + + + var lineFunction = d3.svg.line() + .x(function ( d ){ + return d.x; + }) + .y(function ( d ){ + return d.y; + }) + .interpolate("basis-closed"); + var pathData = "M 20,40 C 0,15 0,-15 20,-40 L -40,0 Z"; + // var pathData="M 20,40 C 0,15 0,-15 20,-40 20,-40 -35.22907,-23.905556 -45.113897,0.06313453 -35.22907,20.095453 20,40 20,40 Z"; + // var pathData="M 39.107144,51.25 C 0,17.362169 0,-13.75 39.285715,-49.821429 c 0,0 -69.58321,34.511175 -100.714286,50.35714329 C -22.96643,20.324376 39.107144,51.25 39.107144,51.25 Z"; + + Class_dragger.nodeElement = Class_dragger.rootNodeLayer.append('path').attr("d", pathData); + Class_dragger.nodeElement.classed("classDraggerNode", true); + Class_dragger.draggerObject = Class_dragger.rootNodeLayer.append("circle"); + if ( graph.options().useAccuracyHelper() ) { + Class_dragger.draggerObject.attr("r", 40) + .attr("cx", 0) + .attr("cy", 0) + .classed("superHiddenElement", true); + Class_dragger.draggerObject.classed("superOpacityElement", !graph.options().showDraggerObject()); + } + + + }; + + Class_dragger.updateElement = function (){ + + // Class_dragger.pathLayer.attr("transform", "translate(" + Class_dragger.x + "," + Class_dragger.y + ")"); + // Class_dragger.rootElement.attr("transform", "translate(" + Class_dragger.x + "," + Class_dragger.y + ")"); + if ( Class_dragger.pathElement ) { + + // compute start point ; + + + var sX = Class_dragger.parent.x, + sY = Class_dragger.parent.y, + eX = Class_dragger.x, + eY = Class_dragger.y; + + + // this is used only when you dont have a proper layout ordering; + var dirX = eX - sX; + var dirY = eY - sY; + var len = Math.sqrt((dirX * dirX) + (dirY * dirY)); + + var nX = dirX / len; + var nY = dirY / len; + + var ppX = sX + nX * Class_dragger.parent.actualRadius(); + var ppY = sY + nY * Class_dragger.parent.actualRadius(); + + var ncx = nX * 15; + var ncy = nY * 15; + Class_dragger.draggerObject.attr("cx", ncx) + .attr("cy", ncy); + + Class_dragger.pathElement.attr("x1", ppX) + .attr("y1", ppY) + .attr("x2", eX) + .attr("y2", eY); + } + var angle = Math.atan2(Class_dragger.parent.y - Class_dragger.y, Class_dragger.parent.x - Class_dragger.x) * 180 / Math.PI; + + Class_dragger.nodeElement.attr("transform", "translate(" + Class_dragger.x + "," + Class_dragger.y + ")" + "rotate(" + angle + ")"); + Class_dragger.draggerObject.attr("transform", "translate(" + Class_dragger.x + "," + Class_dragger.y + ")"); + // console.log("update Elmenent root element"+Class_dragger.x + "," + Class_dragger.y ); + // + // Class_dragger.nodeElement.attr("transform", function (d) { + // return "rotate(" + angle + ")"; + // }); + }; + + /** MOUSE HANDLING FUNCTIONS ------------------------------------------------- **/ + + Class_dragger.addMouseEvents = function (){ + // console.log("adding mouse events"); + Class_dragger.rootNodeLayer.selectAll("*").on("mouseover", Class_dragger.onMouseOver) + .on("mouseout", Class_dragger.onMouseOut) + .on("click", function (){ + }) + .on("dblclick", function (){ + }) + .on("mousedown", Class_dragger.mouseDown) + .on("mouseup", Class_dragger.mouseUp); + }; + + Class_dragger.mouseDown = function (){ + Class_dragger.nodeElement.style("cursor", "move"); + Class_dragger.nodeElement.classed("classDraggerNodeHovered", true); + Class_dragger.mouseButtonPressed = true; + console.log("Mouse DOWN from Dragger"); + }; + + Class_dragger.mouseUp = function (){ + Class_dragger.nodeElement.style("cursor", "auto"); + Class_dragger.mouseButtonPressed = false; + console.log("Mouse UP from Dragger"); + }; + + + Class_dragger.mouseEntered = function ( p ){ + if ( !arguments.length ) return Class_dragger.mouseEnteredVar; + Class_dragger.mouseEnteredVar = p; + return Class_dragger; + }; + + Class_dragger.selectedViaTouch = function ( val ){ + Class_dragger.nodeElement.classed("classDraggerNode", !val); + Class_dragger.nodeElement.classed("classDraggerNodeHovered", val); + + }; + + Class_dragger.onMouseOver = function (){ + if ( Class_dragger.mouseEntered() ) { + return; + } + Class_dragger.nodeElement.classed("classDraggerNode", false); + Class_dragger.nodeElement.classed("classDraggerNodeHovered", true); + var selectedNode = Class_dragger.rootElement.node(), + nodeContainer = selectedNode.parentNode; + nodeContainer.appendChild(selectedNode); + + Class_dragger.mouseEntered(true); + + }; + Class_dragger.onMouseOut = function (){ + if ( Class_dragger.mouseButtonPressed === true ) + return; + Class_dragger.nodeElement.classed("classDraggerNodeHovered", false); + Class_dragger.nodeElement.classed("classDraggerNode", true); + Class_dragger.mouseEntered(false); + }; + + Class_dragger.setPosition = function ( x, y ){ + + Class_dragger.x = x; + Class_dragger.y = y; + Class_dragger.updateElement(); + }; + + Class_dragger.setAdditionalClassForClass_dragger = function ( name, val ){ + // console.log("Class_dragger should sett the class here") + // Class_dragger.nodeElement.classed(name,val); + + }; + return Class_dragger; + }; + + + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 69 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( graph ){ + /** variable defs **/ + var Range_dragger = {}; + Range_dragger.nodeId = 10002; + Range_dragger.parent = undefined; + Range_dragger.x = 0; + Range_dragger.y = 0; + Range_dragger.rootElement = undefined; + Range_dragger.rootNodeLayer = undefined; + Range_dragger.pathLayer = undefined; + Range_dragger.mouseEnteredVar = false; + Range_dragger.mouseButtonPressed = false; + Range_dragger.nodeElement = undefined; + Range_dragger.draggerObject = undefined; + + Range_dragger.pathElement = undefined; + Range_dragger.typus = "Range_dragger"; + + Range_dragger.type = function (){ + return Range_dragger.typus; + }; + + // TODO: We need the endPoint of the Link here! + Range_dragger.parentNode = function (){ + return Range_dragger.parent; + }; + + Range_dragger.hide_dragger = function ( val ){ + Range_dragger.pathElement.classed("hidden", val); + Range_dragger.nodeElement.classed("hidden", val); + Range_dragger.draggerObject.classed("hidden", val); + }; + Range_dragger.hideDragger = function ( val ){ + if ( Range_dragger.pathElement ) Range_dragger.pathElement.classed("hidden", val); + if ( Range_dragger.nodeElement ) Range_dragger.nodeElement.classed("hidden", val); + if ( Range_dragger.draggerObject ) Range_dragger.draggerObject.classed("hidden", val); + + + }; + + Range_dragger.reDrawEverthing = function (){ + Range_dragger.setParentProperty(Range_dragger.parent); + }; + Range_dragger.updateRange = function ( newRange ){ + + if ( graph.genericPropertySanityCheck(Range_dragger.parent.domain(), newRange, + Range_dragger.parent.type(), + "Could not update range", "Restoring previous range") === false ) return; + + // check for triple duplicates! + + if ( graph.propertyCheckExistenceChecker(Range_dragger.parent, Range_dragger.parent.domain(), newRange) === false ) + return; + if ( Range_dragger.parent.labelElement() === undefined ) return; + if ( Range_dragger.parent.labelElement().attr("transform") === "translate(0,15)" || + Range_dragger.parent.labelElement().attr("transform") === "translate(0,-15)" ) { + var prop = Range_dragger.parent; + Range_dragger.parent.inverse().inverse(null); + Range_dragger.parent.inverse(null); + prop.range(newRange); + } + + else { + Range_dragger.parent.range(newRange); + } + // update the position of the new range + var rX = newRange.x; + var rY = newRange.y; + + var dX = Range_dragger.parent.domain().x; + var dY = Range_dragger.parent.domain().y; + + + // center + var cX = 0.49 * (dX + rX); + var cY = 0.49 * (dY + rY); + // put position there; + Range_dragger.parent.labelElement().x = cX; + Range_dragger.parent.labelElement().px = cX; + Range_dragger.parent.labelElement().y = cY; + Range_dragger.parent.labelElement().py = cY; + + }; + + Range_dragger.setParentProperty = function ( parentProperty, inversed ){ + Range_dragger.parent = parentProperty; + var iP; + var renElem; + Range_dragger.isLoopProperty = false; + if ( parentProperty.domain() === parentProperty.range() ) Range_dragger.isLoopProperty = true; + Range_dragger.parent = parentProperty; + renElem = parentProperty.labelObject(); + if ( inversed === true ) { + if ( parentProperty.labelElement() && parentProperty.labelElement().attr("transform") === "translate(0,15)" ) { + iP = renElem.linkDomainIntersection; + if ( renElem.linkDomainIntersection ) { + Range_dragger.x = iP.x; + Range_dragger.y = iP.y; + } + } else { + iP = renElem.linkRangeIntersection; + if ( renElem.linkRangeIntersection ) { + Range_dragger.x = iP.x; + Range_dragger.y = iP.y; + } + } + } + else { + iP = renElem.linkRangeIntersection; + if ( renElem.linkRangeIntersection ) { + Range_dragger.x = iP.x; + Range_dragger.y = iP.y; + } + } + + Range_dragger.updateElement(); + }; + + + /** BASE HANDLING FUNCTIONS ------------------------------------------------- **/ + Range_dragger.id = function ( index ){ + if ( !arguments.length ) { + return Range_dragger.nodeId; + } + Range_dragger.nodeId = index; + }; + + Range_dragger.svgPathLayer = function ( layer ){ + Range_dragger.pathLayer = layer.append('g'); + }; + + Range_dragger.svgRoot = function ( root ){ + if ( !arguments.length ) + return Range_dragger.rootElement; + Range_dragger.rootElement = root; + Range_dragger.rootNodeLayer = Range_dragger.rootElement.append('g'); + Range_dragger.addMouseEvents(); + }; + + /** DRAWING FUNCTIONS ------------------------------------------------- **/ + Range_dragger.drawNode = function (){ + Range_dragger.pathElement = Range_dragger.pathLayer.append('line') + .classed("classNodeDragPath", true); + Range_dragger.pathElement.attr("x1", 0) + .attr("y1", 0) + .attr("x2", 0) + .attr("y2", 0); + + // var lineData = [ + // {"x": 0, "y": 0}, + // {"x": 0, "y": 40}, + // {"x": -40, "y": 0}, + // {"x": 0, "y": -40}, + // {"x": 0, "y": 0} + // ]; + + var lineData = [ + { "x": -40, "y": 0 }, // start + { "x": -20, "y": -10 }, + { "x": 20, "y": -50 }, + { "x": -10, "y": 0 }, // center + { "x": 20, "y": 50 }, + { "x": -20, "y": 10 }, + { "x": -40, "y": 0 } + ]; + + + var lineFunction = d3.svg.line() + .x(function ( d ){ + return d.x; + }) + .y(function ( d ){ + return d.y; + }) + .interpolate("basis-closed"); + var pathData = "M 61,40 C 41,15 41,-15 61,-40 L 1,0 Z"; + + Range_dragger.nodeElement = Range_dragger.rootNodeLayer.append('path').attr("d", pathData); + Range_dragger.nodeElement.classed("classDraggerNode", true); + if ( graph.options().useAccuracyHelper() ) { + Range_dragger.draggerObject = Range_dragger.rootNodeLayer.append("circle"); + Range_dragger.draggerObject.attr("r", 40) + .attr("cx", 0) + .attr("cy", 0) + .classed("superHiddenElement", true); + Range_dragger.draggerObject.classed("superOpacityElement", !graph.options().showDraggerObject()); + } + + + }; + + Range_dragger.updateElementViaDomainDragger = function ( x, y ){ + + var range_x = x; + var range_y = y; + + var dex = Range_dragger.parent.range().x; + var dey = Range_dragger.parent.range().y; + + var dir_X = x - dex; + var dir_Y = y - dey; + + var len = Math.sqrt(dir_X * dir_X + dir_Y * dir_Y); + + var nX = dir_X / len; + var nY = dir_Y / len; + + + var ep_range_x = dex + nX * Range_dragger.parent.range().actualRadius(); + var ep_range_y = dey + nY * Range_dragger.parent.range().actualRadius(); + + + var dx = range_x - ep_range_x; + var dy = range_y - ep_range_y; + len = Math.sqrt(dx * dx + dy * dy); + nX = dx / len; + nY = dy / len; + + var angle = Math.atan2(ep_range_y - range_y, ep_range_x - range_x) * 180 / Math.PI + 180; + Range_dragger.nodeElement.attr("transform", "translate(" + ep_range_x + "," + ep_range_y + ")" + "rotate(" + angle + ")"); + var doX = ep_range_x + nX * 40; + var doY = ep_range_y + nY * 40; + Range_dragger.draggerObject.attr("transform", "translate(" + doX + "," + doY + ")"); + + }; + + + Range_dragger.updateElement = function (){ + if ( Range_dragger.mouseButtonPressed === true || Range_dragger.parent === undefined ) return; + + var range = Range_dragger.parent.range(); + var iP = Range_dragger.parent.labelObject().linkRangeIntersection; + if ( Range_dragger.parent.labelElement() === undefined ) return; + var offsetForLoop = 48; + if ( Range_dragger.parent.labelElement().attr("transform") === "translate(0,15)" ) { + range = Range_dragger.parent.inverse().domain(); + iP = Range_dragger.parent.labelObject().linkDomainIntersection; + offsetForLoop = -48; + } + + if ( iP === undefined ) return; + var range_x = range.x; + var range_y = range.y; + + var ep_range_x = iP.x; + var ep_range_y = iP.y; + // offset for dragger object + var dx = range_x - ep_range_x; + var dy = range_y - ep_range_y; + var len = Math.sqrt(dx * dx + dy * dy); + var nX = dx / len; + var nY = dy / len; + var angle = Math.atan2(ep_range_y - range_y, ep_range_x - range_x) * 180 / Math.PI; + + var doX = ep_range_x - nX * 40; + var doY = ep_range_y - nY * 40; + + if ( Range_dragger.isLoopProperty === true ) + angle -= offsetForLoop; + + + Range_dragger.nodeElement.attr("transform", "translate(" + ep_range_x + "," + ep_range_y + ")" + "rotate(" + angle + ")"); + Range_dragger.draggerObject.attr("transform", "translate(" + doX + "," + doY + ")"); + + + }; + + /** MOUSE HANDLING FUNCTIONS ------------------------------------------------- **/ + + Range_dragger.addMouseEvents = function (){ + var rootLayer = Range_dragger.rootNodeLayer.selectAll("*"); + rootLayer.on("mouseover", Range_dragger.onMouseOver) + .on("mouseout", Range_dragger.onMouseOut) + .on("click", function (){ + }) + .on("dblclick", function (){ + }) + .on("mousedown", Range_dragger.mouseDown) + .on("mouseup", Range_dragger.mouseUp); + }; + + Range_dragger.mouseDown = function (){ + Range_dragger.nodeElement.style("cursor", "move"); + Range_dragger.nodeElement.classed("classDraggerNodeHovered", true); + Range_dragger.mouseButtonPressed = true; + }; + + Range_dragger.mouseUp = function (){ + Range_dragger.nodeElement.style("cursor", "auto"); + Range_dragger.nodeElement.classed("classDraggerNodeHovered", false); + Range_dragger.mouseButtonPressed = false; + }; + + + Range_dragger.mouseEntered = function ( p ){ + if ( !arguments.length ) return Range_dragger.mouseEnteredVar; + Range_dragger.mouseEnteredVar = p; + return Range_dragger; + }; + + Range_dragger.selectedViaTouch = function ( val ){ + Range_dragger.nodeElement.classed("classDraggerNode", !val); + Range_dragger.nodeElement.classed("classDraggerNodeHovered", val); + + }; + + Range_dragger.onMouseOver = function (){ + if ( Range_dragger.mouseEntered() ) { + return; + } + Range_dragger.nodeElement.classed("classDraggerNode", false); + Range_dragger.nodeElement.classed("classDraggerNodeHovered", true); + var selectedNode = Range_dragger.rootElement.node(), + nodeContainer = selectedNode.parentNode; + nodeContainer.appendChild(selectedNode); + + Range_dragger.mouseEntered(true); + + }; + Range_dragger.onMouseOut = function (){ + if ( Range_dragger.mouseButtonPressed === true ) + return; + Range_dragger.nodeElement.classed("classDraggerNodeHovered", false); + Range_dragger.nodeElement.classed("classDraggerNode", true); + Range_dragger.mouseEntered(false); + }; + + Range_dragger.setPosition = function ( x, y ){ + var range_x = Range_dragger.parent.domain().x; + var range_y = Range_dragger.parent.domain().y; + + // var position of the rangeEndPoint + var ep_range_x = x; + var ep_range_y = y; + + // offset for dragger object + var dx = range_x - ep_range_x; + var dy = range_y - ep_range_y; + + var len = Math.sqrt(dx * dx + dy * dy); + + var nX = dx / len; + var nY = dy / len; + + + var angle = Math.atan2(dy, dx) * 180 / Math.PI; + var doX = ep_range_x + nX * 40; + var doY = ep_range_y + nY * 40; + Range_dragger.nodeElement.attr("transform", "translate(" + ep_range_x + "," + ep_range_y + ")" + "rotate(" + angle + ")"); + Range_dragger.draggerObject.attr("transform", "translate(" + doX + "," + doY + ")"); + Range_dragger.x = x; + Range_dragger.y = y; + + }; + + Range_dragger.setAdditionalClassForClass_dragger = function ( name, val ){ + + }; + return Range_dragger; + }; + + + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 70 */ +/***/ (function(module, exports) { + + module.exports = function ( graph ){ + /** variable defs **/ + var Domain_dragger = {}; + Domain_dragger.nodeId = 10002; + Domain_dragger.parent = undefined; + Domain_dragger.x = 0; + Domain_dragger.y = 0; + Domain_dragger.rootElement = undefined; + Domain_dragger.rootNodeLayer = undefined; + Domain_dragger.pathLayer = undefined; + Domain_dragger.mouseEnteredVar = false; + Domain_dragger.mouseButtonPressed = false; + Domain_dragger.nodeElement = undefined; + Domain_dragger.draggerObject = undefined; + + Domain_dragger.pathElement = undefined; + Domain_dragger.typus = "Domain_dragger"; + + Domain_dragger.type = function (){ + return Domain_dragger.typus; + }; + + + // TODO: We need the endPoint of the Link here! + Domain_dragger.parentNode = function (){ + return Domain_dragger.parent; + }; + + Domain_dragger.hide_dragger = function ( val ){ + Domain_dragger.pathElement.classed("hidden", val); + Domain_dragger.nodeElement.classed("hidden", val); + Domain_dragger.draggerObject.classed("hidden", val); + }; + + Domain_dragger.reDrawEverthing = function (){ + Domain_dragger.setParentProperty(Domain_dragger.parent); + }; + Domain_dragger.updateDomain = function ( newDomain ){ + + if ( graph.genericPropertySanityCheck(Domain_dragger.parent.range(), newDomain, Domain_dragger.parent.type(), + "Could not update domain", "Restoring previous domain") === false ) { + Domain_dragger.updateElement(); + return; + } + + if ( graph.propertyCheckExistenceChecker(Domain_dragger.parent, newDomain, Domain_dragger.parent.range()) === false ) + return; + + + if ( Domain_dragger.parent.labelElement() === undefined ) { + Domain_dragger.updateElement(); + return; + } + if ( Domain_dragger.parent.labelElement().attr("transform") === "translate(0,15)" || + Domain_dragger.parent.labelElement().attr("transform") === "translate(0,-15)" ) { + var prop = Domain_dragger.parent; + Domain_dragger.parent.inverse().inverse(null); + Domain_dragger.parent.inverse(null); + console.log("SPLITTING ITEMS!"); + prop.domain(newDomain); + } + else { + Domain_dragger.parent.domain(newDomain); + } + + // update the position of the new range + var rX = Domain_dragger.parent.range().x; + var rY = Domain_dragger.parent.range().y; + var dX = newDomain.x; + var dY = newDomain.y; + + // center + var cX = 0.49 * (dX + rX); + var cY = 0.49 * (dY + rY); + // put position there; + Domain_dragger.parent.labelObject().x = cX; + Domain_dragger.parent.labelObject().px = cX; + Domain_dragger.parent.labelObject().y = cY; + Domain_dragger.parent.labelObject().py = cY; + Domain_dragger.updateElement(); + + }; + + Domain_dragger.setParentProperty = function ( parentProperty, inverted ){ + Domain_dragger.invertedProperty = inverted; + var renElem; + var iP; + Domain_dragger.isLoopProperty = false; + if ( parentProperty.domain() === parentProperty.range() ) + Domain_dragger.isLoopProperty = true; + + Domain_dragger.parent = parentProperty; + renElem = parentProperty.labelObject(); + if ( inverted === true ) { + + // this is the lower element + if ( parentProperty.labelElement() && parentProperty.labelElement().attr("transform") === "translate(0,15)" ) { + // console.log("This is the lower element!"); + iP = renElem.linkRangeIntersection; + if ( renElem.linkRangeIntersection ) { + Domain_dragger.x = iP.x; + Domain_dragger.y = iP.y; + } + } + else { + // console.log("This is the upper element"); + iP = renElem.linkDomainIntersection; + if ( renElem.linkDomainIntersection ) { + Domain_dragger.x = iP.x; + Domain_dragger.y = iP.y; + } + } + } + else { + // console.log("This is single element"); + iP = renElem.linkDomainIntersection; + if ( renElem.linkDomainIntersection ) { + Domain_dragger.x = iP.x; + Domain_dragger.y = iP.y; + } + } + Domain_dragger.updateElement(); + + }; + + Domain_dragger.hideDragger = function ( val ){ + if ( Domain_dragger.pathElement ) Domain_dragger.pathElement.classed("hidden", val); + if ( Domain_dragger.nodeElement ) Domain_dragger.nodeElement.classed("hidden", val); + if ( Domain_dragger.draggerObject ) Domain_dragger.draggerObject.classed("hidden", val); + + + }; + /** BASE HANDLING FUNCTIONS ------------------------------------------------- **/ + Domain_dragger.id = function ( index ){ + if ( !arguments.length ) { + return Domain_dragger.nodeId; + } + Domain_dragger.nodeId = index; + }; + + Domain_dragger.svgPathLayer = function ( layer ){ + Domain_dragger.pathLayer = layer.append('g'); + }; + + Domain_dragger.svgRoot = function ( root ){ + if ( !arguments.length ) + return Domain_dragger.rootElement; + Domain_dragger.rootElement = root; + Domain_dragger.rootNodeLayer = Domain_dragger.rootElement.append('g'); + Domain_dragger.addMouseEvents(); + }; + + /** DRAWING FUNCTIONS ------------------------------------------------- **/ + Domain_dragger.drawNode = function (){ + Domain_dragger.pathElement = Domain_dragger.pathLayer.append('line') + .classed("classNodeDragPath", true); + Domain_dragger.pathElement.attr("x1", 0) + .attr("y1", 0) + .attr("x2", 0) + .attr("y2", 0); + + var pathData = "M 10,40 C -10,15 -10,-15 10,-40 -8.8233455,-13.641384 -36.711107,-5.1228436 -50,0 -36.696429,4.9079017 -8.6403157,13.745728 10,40 Z"; + Domain_dragger.nodeElement = Domain_dragger.rootNodeLayer.append('path').attr("d", pathData); + Domain_dragger.nodeElement.classed("classDraggerNode", true); + if ( graph.options().useAccuracyHelper() ) { + Domain_dragger.draggerObject = Domain_dragger.rootNodeLayer.append("circle"); + Domain_dragger.draggerObject.attr("r", 40) + .attr("cx", 0) + .attr("cy", 0) + .classed("superHiddenElement", true); + Domain_dragger.draggerObject.classed("superOpacityElement", !graph.options().showDraggerObject()); + } + + + }; + Domain_dragger.updateElementViaRangeDragger = function ( x, y ){ + var range_x = x; + var range_y = y; + + var dex = Domain_dragger.parent.domain().x; + var dey = Domain_dragger.parent.domain().y; + + var dir_X = x - dex; + var dir_Y = y - dey; + + var len = Math.sqrt(dir_X * dir_X + dir_Y * dir_Y); + + var nX = dir_X / len; + var nY = dir_Y / len; + + + var ep_range_x = dex + nX * Domain_dragger.parent.domain().actualRadius(); + var ep_range_y = dey + nY * Domain_dragger.parent.domain().actualRadius(); + + var angle = Math.atan2(ep_range_y - range_y, ep_range_x - range_x) * 180 / Math.PI; + + Domain_dragger.nodeElement.attr("transform", "translate(" + ep_range_x + "," + ep_range_y + ")" + "rotate(" + angle + ")"); + var dox = ep_range_x + nX * 20; + var doy = ep_range_y + nY * 20; + Domain_dragger.draggerObject.attr("transform", "translate(" + dox + "," + doy + ")"); + }; + + + Domain_dragger.updateElement = function (){ + if ( Domain_dragger.mouseButtonPressed === true || Domain_dragger.parent === undefined ) return; + + var domain = Domain_dragger.parent.domain(); + var iP = Domain_dragger.parent.labelObject().linkDomainIntersection; + if ( Domain_dragger.parent.labelElement() === undefined ) return; + if ( Domain_dragger.parent.labelElement().attr("transform") === "translate(0,15)" ) { + Domain_dragger.parent.inverse().domain(); + iP = Domain_dragger.parent.labelObject().linkRangeIntersection; + + } + var range_x = domain.x; + var range_y = domain.y; + + + if ( iP === undefined ) return; + var ep_range_x = iP.x; + var ep_range_y = iP.y; + + var dx = range_x - ep_range_x; + var dy = range_y - ep_range_y; + var len = Math.sqrt(dx * dx + dy * dy); + + var nX = dx / len; + var nY = dy / len; + + var dox = ep_range_x - nX * 20; + var doy = ep_range_y - nY * 20; + var angle = Math.atan2(ep_range_y - range_y, ep_range_x - range_x) * 180 / Math.PI + 180; + + Domain_dragger.nodeElement.attr("transform", "translate(" + ep_range_x + "," + ep_range_y + ")" + "rotate(" + angle + ")"); + Domain_dragger.draggerObject.attr("transform", "translate(" + dox + "," + doy + ")"); + }; + + /** MOUSE HANDLING FUNCTIONS ------------------------------------------------- **/ + + Domain_dragger.addMouseEvents = function (){ + var rootLayer = Domain_dragger.rootNodeLayer.selectAll("*"); + rootLayer.on("mouseover", Domain_dragger.onMouseOver) + .on("mouseout", Domain_dragger.onMouseOut) + .on("click", function (){ + }) + .on("dblclick", function (){ + }) + .on("mousedown", Domain_dragger.mouseDown) + .on("mouseup", Domain_dragger.mouseUp); + }; + + Domain_dragger.mouseDown = function (){ + Domain_dragger.nodeElement.style("cursor", "move"); + Domain_dragger.nodeElement.classed("classDraggerNodeHovered", true); + Domain_dragger.mouseButtonPressed = true; + }; + + Domain_dragger.mouseUp = function (){ + Domain_dragger.nodeElement.style("cursor", "auto"); + Domain_dragger.nodeElement.classed("classDraggerNodeHovered", false); + Domain_dragger.mouseButtonPressed = false; + }; + + + Domain_dragger.mouseEntered = function ( p ){ + if ( !arguments.length ) return Domain_dragger.mouseEnteredVar; + Domain_dragger.mouseEnteredVar = p; + return Domain_dragger; + }; + + Domain_dragger.selectedViaTouch = function ( val ){ + Domain_dragger.nodeElement.classed("classDraggerNode", !val); + Domain_dragger.nodeElement.classed("classDraggerNodeHovered", val); + + }; + + Domain_dragger.onMouseOver = function (){ + if ( Domain_dragger.mouseEntered() ) { + return; + } + Domain_dragger.nodeElement.classed("classDraggerNode", false); + Domain_dragger.nodeElement.classed("classDraggerNodeHovered", true); + var selectedNode = Domain_dragger.rootElement.node(), + nodeContainer = selectedNode.parentNode; + nodeContainer.appendChild(selectedNode); + + Domain_dragger.mouseEntered(true); + + }; + Domain_dragger.onMouseOut = function (){ + if ( Domain_dragger.mouseButtonPressed === true ) + return; + Domain_dragger.nodeElement.classed("classDraggerNodeHovered", false); + Domain_dragger.nodeElement.classed("classDraggerNode", true); + Domain_dragger.mouseEntered(false); + }; + + Domain_dragger.setPosition = function ( x, y ){ + var range_x = Domain_dragger.parent.range().x; + var range_y = Domain_dragger.parent.range().y; + + // var position of the rangeEndPoint + var ep_range_x = x; + var ep_range_y = y; + + // offset for dragger object + var dx = range_x - ep_range_x; + var dy = range_y - ep_range_y; + + var len = Math.sqrt(dx * dx + dy * dy); + + var nX = dx / len; + var nY = dy / len; + var dox = ep_range_x + nX * 20; + var doy = ep_range_y + nY * 20; + + var angle = Math.atan2(range_y - ep_range_y, range_x - ep_range_x) * 180 / Math.PI + 180; + + Domain_dragger.nodeElement.attr("transform", "translate(" + ep_range_x + "," + ep_range_y + ")" + "rotate(" + angle + ")"); + Domain_dragger.draggerObject.attr("transform", "translate(" + dox + "," + doy + ")"); + + Domain_dragger.x = x; + Domain_dragger.y = y; + + }; + + Domain_dragger.setAdditionalClassForClass_dragger = function ( name, val ){ + // console.log("Class_dragger should sett the class here") + // Class_dragger.nodeElement.classed(name,val); + + }; + return Domain_dragger; + }; + + + + +/***/ }), +/* 71 */ +/***/ (function(module, exports, __webpack_require__) { + + var CenteringTextElement = __webpack_require__(14); + var elementTools = __webpack_require__(63)(); + var math = __webpack_require__(43)(); + module.exports = function ( graph ){ + /** variable defs **/ + var ShadowClone = {}; + ShadowClone.nodeId = 10003; + ShadowClone.parent = undefined; + ShadowClone.s_x = 0; + ShadowClone.s_y = 0; + ShadowClone.e_x = 0; + ShadowClone.e_y = 0; + ShadowClone.rootElement = undefined; + ShadowClone.rootNodeLayer = undefined; + ShadowClone.pathLayer = undefined; + ShadowClone.nodeElement = undefined; + ShadowClone.pathElement = undefined; + ShadowClone.typus = "shadowClone"; + + + ShadowClone.type = function (){ + return ShadowClone.typus; + }; + + // TODO: We need the endPoint of the Link here! + ShadowClone.parentNode = function (){ + return ShadowClone.parent; + }; + + ShadowClone.setParentProperty = function ( parentProperty, inverted ){ + ShadowClone.invertedProperty = inverted; + ShadowClone.parent = parentProperty; + var renElment; + if ( inverted === true ) { + renElment = parentProperty.inverse().labelObject(); + if ( renElment.linkRangeIntersection && renElment.linkDomainIntersection ) { + var iiP_range = renElment.linkDomainIntersection; + var iiP_domain = renElment.linkRangeIntersection; + ShadowClone.s_x = iiP_domain.x; + ShadowClone.s_y = iiP_domain.y; + ShadowClone.e_x = iiP_range.x; + ShadowClone.e_y = iiP_range.y; + } + } + else { + renElment = parentProperty.labelObject(); + + if ( renElment.linkRangeIntersection && renElment.linkDomainIntersection ) { + var iP_range = renElment.linkRangeIntersection; + var iP_domain = renElment.linkDomainIntersection; + ShadowClone.s_x = iP_domain.x; + ShadowClone.s_y = iP_domain.y; + ShadowClone.e_x = iP_range.x; + ShadowClone.e_y = iP_range.y; + } + + } + + ShadowClone.rootNodeLayer.remove(); + ShadowClone.rootNodeLayer = ShadowClone.rootElement.append('g'); + ShadowClone.rootNodeLayer.datum(parentProperty); + + // ShadowClone.pathElement.remove(); + // ShadowClone.pathElement = ShadowClone.pathLayer.append('line'); + // + // ShadowClone.pathElement.attr("x1", ShadowClone.s_x) + // .attr("y1", ShadowClone.s_y) + // .attr("x2", ShadowClone.e_x) + // .attr("y2", ShadowClone.e_y); + ShadowClone.pathElement.remove(); + ShadowClone.pathElement = ShadowClone.pathLayer.append('line'); + ShadowClone.markerElement = ShadowClone.pathLayer.append("marker"); + ShadowClone.markerElement.attr("id", "shadowCloneMarker"); + ShadowClone.pathElement.attr("x1", ShadowClone.e_x) + .attr("y1", ShadowClone.e_y) + .attr("x2", ShadowClone.s_x) + .attr("y2", ShadowClone.s_y); + ShadowClone.pathElement.classed(parentProperty.linkType(), true); + + if ( parentProperty.markerElement() ) { + ShadowClone.markerElement.attr("viewBox", parentProperty.markerElement().attr("viewBox")) + .attr("markerWidth", parentProperty.markerElement().attr("markerWidth")) + .attr("markerHeight", parentProperty.markerElement().attr("markerHeight")) + .attr("orient", parentProperty.markerElement().attr("orient")); + + var markerPath = parentProperty.markerElement().select("path"); + ShadowClone.markerElement.append("path") + .attr("d", markerPath.attr("d")) + .classed(parentProperty.markerType(), true); + + ShadowClone.pathElement.attr("marker-end", "url(#" + "shadowCloneMarker" + ")"); + ShadowClone.markerElement.classed("hidden", !elementTools.isDatatypeProperty(parentProperty)); + } + var rect = ShadowClone.rootNodeLayer.append("rect") + .classed(parentProperty.styleClass(), true) + .classed("property", true) + .attr("x", -parentProperty.width() / 2) + .attr("y", -parentProperty.height() / 2) + .attr("width", parentProperty.width()) + .attr("height", parentProperty.height()); + + if ( parentProperty.visualAttributes() ) { + rect.classed(parentProperty.visualAttributes(), true); + } + rect.classed("datatype", false); + var bgColor = parentProperty.backgroundColor(); + + if ( parentProperty.attributes().indexOf("deprecated") > -1 ) { + bgColor = undefined; + rect.classed("deprecatedproperty", true); + } else { + rect.classed("deprecatedproperty", false); + } + rect.style("fill", bgColor); + + // add Text; + var equivalentsString = parentProperty.equivalentsString(); + var suffixForFollowingEquivalents = equivalentsString ? "," : ""; + + + var textElement = new CenteringTextElement(ShadowClone.rootNodeLayer, bgColor); + textElement.addText(parentProperty.labelForCurrentLanguage(), "", suffixForFollowingEquivalents); + textElement.addEquivalents(equivalentsString); + textElement.addSubText(parentProperty.indicationString()); + + + var cx = 0.5 * (ShadowClone.s_x + ShadowClone.e_x); + var cy = 0.5 * (ShadowClone.s_y + ShadowClone.e_y); + ShadowClone.rootNodeLayer.attr("transform", "translate(" + cx + "," + cy + ")"); + ShadowClone.rootNodeLayer.classed("hidden", true); + ShadowClone.pathElement.classed("hidden", true); + + + }; + + ShadowClone.hideClone = function ( val ){ + if ( ShadowClone.rootNodeLayer ) ShadowClone.rootNodeLayer.classed("hidden", val); + if ( ShadowClone.pathElement ) ShadowClone.pathElement.classed("hidden", val); + }; + + ShadowClone.hideParentProperty = function ( val ){ + + var labelObj = ShadowClone.parent.labelObject(); + if ( labelObj ) { + if ( ShadowClone.parent.labelElement().attr("transform") === "translate(0,15)" || + ShadowClone.parent.labelElement().attr("transform") === "translate(0,-15)" ) + ShadowClone.parent.inverse().hide(val); + + + } + ShadowClone.parent.hide(val); + + + }; + + /** BASE HANDLING FUNCTIONS ------------------------------------------------- **/ + ShadowClone.id = function ( index ){ + if ( !arguments.length ) { + return ShadowClone.nodeId; + } + ShadowClone.nodeId = index; + }; + + ShadowClone.svgPathLayer = function ( layer ){ + ShadowClone.pathLayer = layer.append('g'); + }; + + ShadowClone.svgRoot = function ( root ){ + if ( !arguments.length ) + return ShadowClone.rootElement; + ShadowClone.rootElement = root; + ShadowClone.rootNodeLayer = ShadowClone.rootElement.append('g'); + + }; + + /** DRAWING FUNCTIONS ------------------------------------------------- **/ + ShadowClone.drawClone = function (){ + ShadowClone.pathElement = ShadowClone.pathLayer.append('line'); + + ShadowClone.pathElement.attr("x1", 0) + .attr("y1", 0) + .attr("x2", 0) + .attr("y2", 0); + + }; + + + ShadowClone.updateElement = function (){ + ShadowClone.pathElement.attr("x1", ShadowClone.e_x) + .attr("y1", ShadowClone.e_y) + .attr("x2", ShadowClone.s_x) + .attr("y2", ShadowClone.s_y); + + var cx = 0.5 * (ShadowClone.s_x + ShadowClone.e_x); + var cy = 0.5 * (ShadowClone.s_y + ShadowClone.e_y); + ShadowClone.rootNodeLayer.attr("transform", "translate(" + cx + "," + cy + ")"); + }; + + ShadowClone.setInitialPosition = function (){ + + var renElment = ShadowClone.parent.labelObject(); + if ( renElment.linkRangeIntersection && renElment.linkDomainIntersection ) { + var iP_range = renElment.linkRangeIntersection; + var iP_domain = renElment.linkDomainIntersection; + ShadowClone.e_x = iP_domain.x; + ShadowClone.e_y = iP_domain.y; + ShadowClone.s_x = iP_range.x; + ShadowClone.s_y = iP_range.y; + } + ShadowClone.updateElement(); + return; + // + // var rex=ShadowClone.parent.range().x; + // var rey=ShadowClone.parent.range().y; + // + // + // var dex=ShadowClone.parent.domain().x; + // var dey=ShadowClone.parent.domain().y; + // + // + // var dir_X= rex-dex; + // var dir_Y= rey-dey; + // + // var len=Math.sqrt(dir_X*dir_X+dir_Y*dir_Y); + // var nX=dir_X/len; + // var nY=dir_Y/len; + // ShadowClone.s_x=rex-nX*ShadowClone.parent.range().actualRadius(); + // ShadowClone.s_y=rey-nY*ShadowClone.parent.range().actualRadius(); + // + // ShadowClone.e_x=dex+nX*ShadowClone.parent.domain().actualRadius(); + // ShadowClone.e_y=dey+nY*ShadowClone.parent.domain().actualRadius(); + // ShadowClone.updateElement(); + + }; + ShadowClone.setPositionDomain = function ( e_x, e_y ){ + + var rex = ShadowClone.parent.range().x; + var rey = ShadowClone.parent.range().y; + + + if ( elementTools.isDatatype(ShadowClone.parent.range()) === true ) { + var intersection = math.calculateIntersection({ x: e_x, y: e_y }, ShadowClone.parent.range(), 0); + ShadowClone.s_x = intersection.x; + ShadowClone.s_y = intersection.y; + } else { + var dir_X = rex - e_x; + var dir_Y = rey - e_y; + + var len = Math.sqrt(dir_X * dir_X + dir_Y * dir_Y); + + var nX = dir_X / len; + var nY = dir_Y / len; + ShadowClone.s_x = rex - nX * ShadowClone.parent.range().actualRadius(); + ShadowClone.s_y = rey - nY * ShadowClone.parent.range().actualRadius(); + + } + + + ShadowClone.e_x = e_x; + ShadowClone.e_y = e_y; + ShadowClone.updateElement(); + }; + + ShadowClone.setPosition = function ( s_x, s_y ){ + ShadowClone.s_x = s_x; + ShadowClone.s_y = s_y; + + // add normalized dir; + + var dex = ShadowClone.parent.domain().x; + var dey = ShadowClone.parent.domain().y; + + var dir_X = s_x - dex; + var dir_Y = s_y - dey; + + var len = Math.sqrt(dir_X * dir_X + dir_Y * dir_Y); + + var nX = dir_X / len; + var nY = dir_Y / len; + + + ShadowClone.e_x = dex + nX * ShadowClone.parent.domain().actualRadius(); + ShadowClone.e_y = dey + nY * ShadowClone.parent.domain().actualRadius(); + + + ShadowClone.updateElement(); + + + }; + + + /** MOUSE HANDLING FUNCTIONS ------------------------------------------------- **/ + + return ShadowClone; + }; + + + + +/***/ }), +/* 72 */ +/***/ (function(module, exports) { + + module.exports = function ( graph ){ + /** variable defs **/ + var prefixRepresentationModule = {}; + + var currentPrefixModel; + + prefixRepresentationModule.updatePrefixModel = function (){ + currentPrefixModel = graph.options().prefixList(); + }; + + + prefixRepresentationModule.validURL = function ( url ){ + return validURL(url); + }; + function validURL( str ){ + var urlregex = /^(https?|ftp):\/\/([a-zA-Z0-9.-]+(:[a-zA-Z0-9.&%$-]+)*@)*((25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9][0-9]?)(\.(25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9]?[0-9])){3}|([a-zA-Z0-9-]+\.)*[a-zA-Z0-9-]+\.(com|edu|gov|int|mil|net|org|biz|arpa|info|name|pro|aero|coop|museum|[a-zA-Z]{2}))(:[0-9]+)*(\/($|[a-zA-Z0-9.,?'\\+&%$#=~_-]+))*$/; + return urlregex.test(str); + } + + function splitURLIntoBaseAndResource( fullURL ){ + var splitedURL = { base: "", resource: "" }; + if ( fullURL === undefined ) { + splitedURL = { base: "ERROR", resource: "NOT FOUND" }; + return splitedURL; + } + + var resource, base; + // check if there is a last hashTag + if ( fullURL.indexOf("#") > -1 ) { + resource = fullURL.substring(fullURL.lastIndexOf('#') + 1); + base = fullURL.substring(0, fullURL.length - resource.length); + // overwrite base if it is ontologyIri; + if ( base === graph.options().getGeneralMetaObjectProperty('iri') ) { + base = ":"; + } + splitedURL.base = base; + splitedURL.resource = resource; + } else { + resource = fullURL.substring(fullURL.lastIndexOf('/') + 1); + base = fullURL.substring(0, fullURL.length - resource.length); + // overwrite base if it is ontologyIri; + if ( base === graph.options().getGeneralMetaObjectProperty('iri') ) { + base = ":"; + } + splitedURL.base = base; + splitedURL.resource = resource; + } + return splitedURL; + } + + prefixRepresentationModule.getPrefixRepresentationForFullURI = function ( fullURL ){ + prefixRepresentationModule.updatePrefixModel(); + var splittedURL = splitURLIntoBaseAndResource(fullURL); + + // lazy approach , for + // loop over prefix model + for ( var name in currentPrefixModel ) { + if ( currentPrefixModel.hasOwnProperty(name) ) { + // THIS IS CASE SENSITIVE! + if ( currentPrefixModel[name] === splittedURL.base ) { + return name + ":" + splittedURL.resource; + } + } + } + + if ( splittedURL.base === ":" ) { + return ":" + splittedURL.resource; + } + + return fullURL; + }; + + + return prefixRepresentationModule; + }; + + + + +/***/ }), +/* 73 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var _ = __webpack_require__(58); + + module.exports = function (){ + + var DEFAULT_STATE = true; + var COLOR_MODES = [ + { type: "same", range: [d3.rgb("#36C"), d3.rgb("#36C")] }, + { type: "gradient", range: [d3.rgb("#36C"), d3.rgb("#EE2867")] } // taken from LD-VOWL + ]; + + var filter = {}, + nodes, + properties, + enabled = DEFAULT_STATE, + filteredNodes, + filteredProperties, + colorModeType = "same"; + + + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + + var externalElements = filterExternalElements(nodes.concat(properties)); + + if ( enabled ) { + setColorsForExternals(externalElements); + } else { + resetBackgroundColors(externalElements); + } + + filteredNodes = nodes; + filteredProperties = properties; + }; + + function filterExternalElements( elements ){ + return elements.filter(function ( element ){ + if ( element.visualAttributes().indexOf("deprecated") >= 0 ) { + // deprecated is the only attribute which has preference over external + return false; + } + + return element.attributes().indexOf("external") >= 0; + }); + } + + function setColorsForExternals( elements ){ + var iriMap = mapExternalsToBaseUri(elements); + var entries = iriMap.entries(); + + var colorScale = d3.scale.linear() + .domain([0, entries.length - 1]) + .range(_.find(COLOR_MODES, { type: colorModeType }).range) + .interpolate(d3.interpolateHsl); + + for ( var i = 0; i < entries.length; i++ ) { + var groupedElements = entries[i].value; + setBackgroundColorForElements(groupedElements, colorScale(i)); + } + } + + function mapExternalsToBaseUri( elements ){ + var map = d3.map(); + + elements.forEach(function ( element ){ + var baseIri = element.baseIri(); + + if ( !map.has(baseIri) ) { + map.set(baseIri, []); + } + map.get(baseIri).push(element); + }); + + return map; + } + + function setBackgroundColorForElements( elements, backgroundColor ){ + elements.forEach(function ( element ){ + element.backgroundColor(backgroundColor); + }); + } + + function resetBackgroundColors( elements ){ + console.log("Resetting color"); + elements.forEach(function ( element ){ + element.backgroundColor(null); + }); + } + + filter.colorModeType = function ( p ){ + if ( !arguments.length ) return colorModeType; + colorModeType = p; + return filter; + }; + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + filter.reset = function (){ + enabled = DEFAULT_STATE; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 74 */ +/***/ (function(module, exports) { + + /** + * This module abuses the filter function a bit like the statistics module. Nothing is filtered. + * + * @returns {{}} + */ + + + module.exports = function ( graph ){ + + var DEFAULT_STATE = false; + + var filter = {}, + nodes, + properties, + enabled = DEFAULT_STATE, + filteredNodes, + filteredProperties; + + + /** + * If enabled, redundant details won't be drawn anymore. + * @param untouchedNodes + * @param untouchedProperties + */ + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + graph.options().compactNotation(enabled); + filteredNodes = nodes; + filteredProperties = properties; + }; + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + filter.reset = function (){ + enabled = DEFAULT_STATE; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }), +/* 75 */ +/***/ (function(module, exports, __webpack_require__) { + + var elementTools = __webpack_require__(63)(); + var filterTools = __webpack_require__(76)(); + + module.exports = function (){ + + var filter = {}, + nodes, + properties, + enabled = false, + filteredNodes, + filteredProperties; + + + /** + * If enabled, all datatypes and literals including connected properties are filtered. + * @param untouchedNodes + * @param untouchedProperties + */ + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + + if ( this.enabled() ) { + removeDatatypesAndLiterals(); + } + + filteredNodes = nodes; + filteredProperties = properties; + }; + + function removeDatatypesAndLiterals(){ + var filteredData = filterTools.filterNodesAndTidy(nodes, properties, isNoDatatypeOrLiteral); + + nodes = filteredData.nodes; + properties = filteredData.properties; + } + + function isNoDatatypeOrLiteral( node ){ + return !elementTools.isDatatype(node); + } + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }), +/* 76 */ +/***/ (function(module, exports, __webpack_require__) { + + var elementTools = __webpack_require__(63)(); + + module.exports = (function (){ + + var tools = {}; + + /** + * Filters the passed nodes and removes dangling properties. + * @param nodes + * @param properties + * @param shouldKeepNode function that returns true if the node should be kept + * @returns {{nodes: Array, properties: Array}} the filtered nodes and properties + */ + tools.filterNodesAndTidy = function ( nodes, properties, shouldKeepNode ){ + var removedNodes = __webpack_require__(62)(), + cleanedNodes = [], + cleanedProperties = []; + + nodes.forEach(function ( node ){ + if ( shouldKeepNode(node) ) { + cleanedNodes.push(node); + } else { + removedNodes.add(node); + } + }); + + properties.forEach(function ( property ){ + if ( propertyHasVisibleNodes(removedNodes, property) ) { + cleanedProperties.push(property); + } else if ( elementTools.isDatatypeProperty(property) ) { + // Remove floating datatypes/literals, because they belong to their datatype property + var index = cleanedNodes.indexOf(property.range()); + if ( index >= 0 ) { + cleanedNodes.splice(index, 1); + } + } + }); + + return { + nodes: cleanedNodes, + properties: cleanedProperties + }; + }; + + /** + * Returns true, if the domain and the range of this property have not been removed. + * @param removedNodes + * @param property + * @returns {boolean} true if property isn't dangling + */ + function propertyHasVisibleNodes( removedNodes, property ){ + return !removedNodes.has(property.domain()) && !removedNodes.has(property.range()); + } + + + return function (){ + return tools; + }; + })(); + + +/***/ }), +/* 77 */ +/***/ (function(module, exports, __webpack_require__) { + + var OwlDisjointWith = __webpack_require__(46); + + module.exports = function (){ + + var filter = {}, + nodes, + properties, + // According to the specification enabled by default + enabled = true, + filteredNodes, + filteredProperties; + + + /** + * If enabled, all disjoint with properties are filtered. + * @param untouchedNodes + * @param untouchedProperties + */ + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + + if ( this.enabled() ) { + removeDisjointWithProperties(); + } + + filteredNodes = nodes; + filteredProperties = properties; + }; + + function removeDisjointWithProperties(){ + var cleanedProperties = [], + i, l, property; + + for ( i = 0, l = properties.length; i < l; i++ ) { + property = properties[i]; + + if ( !(property instanceof OwlDisjointWith) ) { + cleanedProperties.push(property); + } + } + + properties = cleanedProperties; + } + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }), +/* 78 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( graph ){ + var focuser = {}, + focusedElement; + var elementTools = webvowl.util.elementTools(); + focuser.handle = function ( selectedElement, forced ){ + // Don't display details on a drag event, which will be prevented + if ( d3.event && d3.event.defaultPrevented && forced === undefined ) { + return; + } + + if ( focusedElement !== undefined ) { + focusedElement.toggleFocus(); + } + + if ( focusedElement !== selectedElement && selectedElement ) { + selectedElement.toggleFocus(); + focusedElement = selectedElement; + } else { + focusedElement = undefined; + } + if ( focusedElement && focusedElement.focused() ) { + graph.options().editSidebar().updateSelectionInformation(focusedElement); + if ( elementTools.isProperty(selectedElement) === true ) { + var inversed = false; + if ( selectedElement.inverse() ) { + inversed = true; + } + graph.activateHoverElementsForProperties(true, selectedElement, inversed, graph.isTouchDevice()); + } + else { + graph.activateHoverElements(true, selectedElement, graph.isTouchDevice()); + } + } + else { + graph.options().editSidebar().updateSelectionInformation(undefined); + graph.removeEditElements(); + } + }; + + /** + * Removes the focus if an element is focussed. + */ + focuser.reset = function (){ + if ( focusedElement ) { + focusedElement.toggleFocus(); + focusedElement = undefined; + } + }; + + return focuser; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 79 */ +/***/ (function(module, exports) { + + /** @WORKAROUND CODE: + * clears empty literals that are provided by owl2vowl: 0.2.2x*/ + + + module.exports = function (){ + + var filter = {}, + enabled = true, + filteredNodes, + removedNodes, + filteredProperties; + + filter.enabled = function ( val ){ + if ( !arguments.length ) { + return enabled; + } + enabled = val; + }; + + filter.filter = function ( nodes, properties ){ + if ( enabled === false ) { + filteredNodes = nodes; + filteredProperties = properties; + removedNodes = []; + return; + } + var literalUsageMap = []; + var thingUsageMap = []; + var node; + for ( var i = 0; i < properties.length; i++ ) { + // get property range; + var prop = properties[i]; + + // checking for literals + if ( prop.range() ) { + node = prop.range(); + if ( node.type() === "rdfs:Literal" ) { + literalUsageMap[node.id()] = 1; + } + } + // checking for thing + if ( prop.range() ) { + node = prop.range(); + if ( node.type() === "owl:Thing" ) { + thingUsageMap[node.id()] = 1; + } + } + if ( prop.domain() ) { + node = prop.domain(); + if ( node.type() === "owl:Thing" ) { + thingUsageMap[node.id()] = 1; + } + } + + } + var nodesToRemove = []; + var newNodes = []; + // todo: test and make it faster + for ( i = 0; i < nodes.length; i++ ) { + var nodeId = nodes[i].id(); + if ( nodes[i].type() === "rdfs:Literal" ) { + if ( literalUsageMap[nodeId] === undefined ) { + nodesToRemove.push(nodeId); + } + else { + newNodes.push(nodes[i]); + } + // check for node type == OWL:THING + } else if ( nodes[i].type() === "owl:Thing" ) { + if ( thingUsageMap[nodeId] === undefined ) { + nodesToRemove.push(nodeId); + } + else { + newNodes.push(nodes[i]); + } + } else { + newNodes.push(nodes[i]); + } + } + + filteredNodes = newNodes; + filteredProperties = properties; + removedNodes = nodesToRemove; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.removedNodes = function (){ + return removedNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }), +/* 80 */ +/***/ (function(module, exports, __webpack_require__) { + + var elementTools = __webpack_require__(63)(); + var filterTools = __webpack_require__(76)(); + + module.exports = function ( menu ){ + + var filter = {}, + nodes, + properties, + enabled = true, + filteredNodes, + filteredProperties, + maxDegreeSetter, + degreeGetter, + lastFiltedDegree, + degreeSetter; + + + var NODE_COUNT_LIMIT_FOR_AUTO_ENABLING = 50; + + + filter.initialize = function ( nodes, properties ){ + lastFiltedDegree = -1; + var maxLinkCount = findMaxLinkCount(nodes); + if ( maxDegreeSetter instanceof Function ) { + maxDegreeSetter(maxLinkCount); + } + + menu.setDefaultDegreeValue(findAutoDefaultDegree(nodes, properties, maxLinkCount)); + var defaultDegree = findDefaultDegree(maxLinkCount); + if ( degreeSetter instanceof Function ) { + degreeSetter(defaultDegree); + if ( defaultDegree > 0 ) { + menu.highlightForDegreeSlider(true); + menu.getGraphObject().setFilterWarning(true); + + } + } else { + console.error("No degree setter function set."); + } + }; + + function findAutoDefaultDegree( nodes, properties, maxDegree ){ + for ( var degree = 0; degree < maxDegree; degree++ ) { + var filteredData = filterByNodeDegree(nodes, properties, degree); + + if ( filteredData.nodes.length <= NODE_COUNT_LIMIT_FOR_AUTO_ENABLING ) { + return degree; + } + } + return 0; + } + + function findDefaultDegree( maxDegree ){ + var globalDegOfFilter = menu.getGraphObject().getGlobalDOF(); + if ( globalDegOfFilter >= 0 ) { + if ( globalDegOfFilter <= maxDegree ) { + return globalDegOfFilter; + } else { + menu.getGraphObject().setGlobalDOF(maxDegree); + return maxDegree; + } + } + return menu.getDefaultDegreeValue(); + } + + /** + * If enabled, all nodes are filter by their node degree. + * @param untouchedNodes + * @param untouchedProperties + */ + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + + if ( this.enabled() ) { + if ( degreeGetter instanceof Function ) { + filterByNodeDegreeAndApply(degreeGetter()); + } else { + console.error("No degree query function set."); + } + } + + filteredNodes = nodes; + filteredProperties = properties; + + if ( filteredNodes.length === 0 ) { + degreeSetter(0); + filteredNodes = untouchedNodes; + filteredProperties = untouchedProperties; + } + lastFiltedDegree = degreeGetter(); + }; + + function findMaxLinkCount( nodes ){ + var maxLinkCount = 0; + for ( var i = 0, l = nodes.length; i < l; i++ ) { + var linksWithoutDatatypes = filterOutDatatypes(nodes[i].links()); + + maxLinkCount = Math.max(maxLinkCount, linksWithoutDatatypes.length); + } + return maxLinkCount; + } + + function filterOutDatatypes( links ){ + return links.filter(function ( link ){ + return !elementTools.isDatatypeProperty(link.property()); + }); + } + + function filterByNodeDegreeAndApply( minDegree ){ + var filteredData = filterByNodeDegree(nodes, properties, minDegree); + nodes = filteredData.nodes; + properties = filteredData.properties; + } + + function filterByNodeDegree( nodes, properties, minDegree ){ + return filterTools.filterNodesAndTidy(nodes, properties, hasRequiredDegree(minDegree)); + } + + function hasRequiredDegree( minDegree ){ + return function ( node ){ + return filterOutDatatypes(node.links()).length >= minDegree; + }; + } + + filter.setMaxDegreeSetter = function ( _maxDegreeSetter ){ + maxDegreeSetter = _maxDegreeSetter; + }; + + filter.setDegreeGetter = function ( _degreeGetter ){ + degreeGetter = _degreeGetter; + }; + + filter.setDegreeSetter = function ( _degreeSetter ){ + degreeSetter = _degreeSetter; + }; + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }), +/* 81 */ +/***/ (function(module, exports) { + + /** + * This module abuses the filter function a bit like the statistics module. Nothing is filtered. + * + * @returns {{}} + */ + module.exports = function ( graph ){ + + var DEFAULT_STATE = true; + + var filter = {}, + nodes, + properties, + enabled = DEFAULT_STATE, + filteredNodes, + filteredProperties; + + + /** + * If enabled, the scaling of nodes according to individuals will be enabled. + * @param untouchedNodes + * @param untouchedProperties + */ + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + + graph.options().scaleNodesByIndividuals(enabled); + + filteredNodes = nodes; + filteredProperties = properties; + }; + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + filter.reset = function (){ + enabled = DEFAULT_STATE; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }), +/* 82 */ +/***/ (function(module, exports, __webpack_require__) { + + var elementTools = __webpack_require__(63)(); + + + module.exports = function (){ + + var filter = {}, + nodes, + properties, + enabled = false, + filteredNodes, + filteredProperties; + + + /** + * If enabled, all object properties and things without any other property are filtered. + * @param untouchedNodes + * @param untouchedProperties + */ + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + + if ( this.enabled() ) { + removeObjectProperties(); + } + + filteredNodes = nodes; + filteredProperties = properties; + }; + + function removeObjectProperties(){ + properties = properties.filter(isNoObjectProperty); + nodes = nodes.filter(isNoFloatingThing); + } + + function isNoObjectProperty( property ){ + return !elementTools.isObjectProperty(property); + } + + function isNoFloatingThing( node ){ + var isNoThing = !elementTools.isThing(node); + var hasNonFilteredProperties = hasPropertiesOtherThanObjectProperties(node, properties); + return isNoThing || hasNonFilteredProperties; + } + + function hasPropertiesOtherThanObjectProperties( node, properties ){ + for ( var i = 0; i < properties.length; i++ ) { + var property = properties[i]; + if ( property.domain() !== node && property.range() !== node ) { + continue; + } + + if ( isNoObjectProperty(property) ) { + return true; + } + } + + return false; + } + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }), +/* 83 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var _ = __webpack_require__(84); + var elementTools = __webpack_require__(63)(); + + module.exports = function (){ + var pap = {}, + enabled = false, + pinnedElements = []; + + pap.addPinnedElement = function ( element ){ + // check if element is already in list + var indexInArray = pinnedElements.indexOf(element); + if ( indexInArray === -1 ) { + pinnedElements.push(element); + } + }; + + pap.handle = function ( selection, forced ){ + if ( !enabled ) { + return; + } + + if ( !forced ) { + if ( wasNotDragged() ) { + return; + } + } + if ( elementTools.isProperty(selection) ) { + if ( selection.inverse() && selection.inverse().pinned() ) { + return; + } else if ( hasNoParallelProperties(selection) ) { + return; + } + } + + if ( !selection.pinned() ) { + selection.drawPin(); + pap.addPinnedElement(selection); + } + }; + + function wasNotDragged(){ + return !d3.event.defaultPrevented; + } + + function hasNoParallelProperties( property ){ + return _.intersection(property.domain().links(), property.range().links()).length === 1; + } + + pap.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return pap; + }; + + pap.reset = function (){ + pinnedElements.forEach(function ( element ){ + element.removePin(); + }); + // Clear the array of stored nodes + pinnedElements.length = 0; + }; + + return pap; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 84 */ +/***/ (function(module, exports, __webpack_require__) { + + module.exports = { + 'chunk': __webpack_require__(85), + 'compact': __webpack_require__(105), + 'concat': __webpack_require__(106), + 'difference': __webpack_require__(114), + 'differenceBy': __webpack_require__(167), + 'differenceWith': __webpack_require__(229), + 'drop': __webpack_require__(230), + 'dropRight': __webpack_require__(231), + 'dropRightWhile': __webpack_require__(232), + 'dropWhile': __webpack_require__(234), + 'fill': __webpack_require__(235), + 'findIndex': __webpack_require__(239), + 'findLastIndex': __webpack_require__(240), + 'first': __webpack_require__(241), + 'flatten': __webpack_require__(243), + 'flattenDeep': __webpack_require__(244), + 'flattenDepth': __webpack_require__(245), + 'fromPairs': __webpack_require__(246), + 'head': __webpack_require__(242), + 'indexOf': __webpack_require__(247), + 'initial': __webpack_require__(248), + 'intersection': __webpack_require__(249), + 'intersectionBy': __webpack_require__(252), + 'intersectionWith': __webpack_require__(253), + 'join': __webpack_require__(254), + 'last': __webpack_require__(228), + 'lastIndexOf': __webpack_require__(255), + 'nth': __webpack_require__(257), + 'pull': __webpack_require__(259), + 'pullAll': __webpack_require__(260), + 'pullAllBy': __webpack_require__(263), + 'pullAllWith': __webpack_require__(264), + 'pullAt': __webpack_require__(265), + 'remove': __webpack_require__(272), + 'reverse': __webpack_require__(273), + 'slice': __webpack_require__(274), + 'sortedIndex': __webpack_require__(275), + 'sortedIndexBy': __webpack_require__(278), + 'sortedIndexOf': __webpack_require__(279), + 'sortedLastIndex': __webpack_require__(280), + 'sortedLastIndexBy': __webpack_require__(281), + 'sortedLastIndexOf': __webpack_require__(282), + 'sortedUniq': __webpack_require__(283), + 'sortedUniqBy': __webpack_require__(285), + 'tail': __webpack_require__(286), + 'take': __webpack_require__(287), + 'takeRight': __webpack_require__(288), + 'takeRightWhile': __webpack_require__(289), + 'takeWhile': __webpack_require__(290), + 'union': __webpack_require__(291), + 'unionBy': __webpack_require__(295), + 'unionWith': __webpack_require__(296), + 'uniq': __webpack_require__(297), + 'uniqBy': __webpack_require__(298), + 'uniqWith': __webpack_require__(299), + 'unzip': __webpack_require__(300), + 'unzipWith': __webpack_require__(301), + 'without': __webpack_require__(302), + 'xor': __webpack_require__(303), + 'xorBy': __webpack_require__(305), + 'xorWith': __webpack_require__(306), + 'zip': __webpack_require__(307), + 'zipObject': __webpack_require__(308), + 'zipObjectDeep': __webpack_require__(312), + 'zipWith': __webpack_require__(314) + }; + + +/***/ }), +/* 85 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86), + isIterateeCall = __webpack_require__(87), + toInteger = __webpack_require__(100); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeCeil = Math.ceil, + nativeMax = Math.max; + + /** + * Creates an array of elements split into groups the length of `size`. + * If `array` can't be split evenly, the final chunk will be the remaining + * elements. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to process. + * @param {number} [size=1] The length of each chunk + * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. + * @returns {Array} Returns the new array of chunks. + * @example + * + * _.chunk(['a', 'b', 'c', 'd'], 2); + * // => [['a', 'b'], ['c', 'd']] + * + * _.chunk(['a', 'b', 'c', 'd'], 3); + * // => [['a', 'b', 'c'], ['d']] + */ + function chunk(array, size, guard) { + if ((guard ? isIterateeCall(array, size, guard) : size === undefined)) { + size = 1; + } else { + size = nativeMax(toInteger(size), 0); + } + var length = array == null ? 0 : array.length; + if (!length || size < 1) { + return []; + } + var index = 0, + resIndex = 0, + result = Array(nativeCeil(length / size)); + + while (index < length) { + result[resIndex++] = baseSlice(array, index, (index += size)); + } + return result; + } + + module.exports = chunk; + + +/***/ }), +/* 86 */ +/***/ (function(module, exports) { + + /** + * The base implementation of `_.slice` without an iteratee call guard. + * + * @private + * @param {Array} array The array to slice. + * @param {number} [start=0] The start position. + * @param {number} [end=array.length] The end position. + * @returns {Array} Returns the slice of `array`. + */ + function baseSlice(array, start, end) { + var index = -1, + length = array.length; + + if (start < 0) { + start = -start > length ? 0 : (length + start); + } + end = end > length ? length : end; + if (end < 0) { + end += length; + } + length = start > end ? 0 : ((end - start) >>> 0); + start >>>= 0; + + var result = Array(length); + while (++index < length) { + result[index] = array[index + start]; + } + return result; + } + + module.exports = baseSlice; + + +/***/ }), +/* 87 */ +/***/ (function(module, exports, __webpack_require__) { + + var eq = __webpack_require__(88), + isArrayLike = __webpack_require__(89), + isIndex = __webpack_require__(99), + isObject = __webpack_require__(97); + + /** + * Checks if the given arguments are from an iteratee call. + * + * @private + * @param {*} value The potential iteratee value argument. + * @param {*} index The potential iteratee index or key argument. + * @param {*} object The potential iteratee object argument. + * @returns {boolean} Returns `true` if the arguments are from an iteratee call, + * else `false`. + */ + function isIterateeCall(value, index, object) { + if (!isObject(object)) { + return false; + } + var type = typeof index; + if (type == 'number' + ? (isArrayLike(object) && isIndex(index, object.length)) + : (type == 'string' && index in object) + ) { + return eq(object[index], value); + } + return false; + } + + module.exports = isIterateeCall; + + +/***/ }), +/* 88 */ +/***/ (function(module, exports) { + + /** + * Performs a + * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * comparison between two values to determine if they are equivalent. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @returns {boolean} Returns `true` if the values are equivalent, else `false`. + * @example + * + * var object = { 'a': 1 }; + * var other = { 'a': 1 }; + * + * _.eq(object, object); + * // => true + * + * _.eq(object, other); + * // => false + * + * _.eq('a', 'a'); + * // => true + * + * _.eq('a', Object('a')); + * // => false + * + * _.eq(NaN, NaN); + * // => true + */ + function eq(value, other) { + return value === other || (value !== value && other !== other); + } + + module.exports = eq; + + +/***/ }), +/* 89 */ +/***/ (function(module, exports, __webpack_require__) { + + var isFunction = __webpack_require__(90), + isLength = __webpack_require__(98); + + /** + * Checks if `value` is array-like. A value is considered array-like if it's + * not a function and has a `value.length` that's an integer greater than or + * equal to `0` and less than or equal to `Number.MAX_SAFE_INTEGER`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is array-like, else `false`. + * @example + * + * _.isArrayLike([1, 2, 3]); + * // => true + * + * _.isArrayLike(document.body.children); + * // => true + * + * _.isArrayLike('abc'); + * // => true + * + * _.isArrayLike(_.noop); + * // => false + */ + function isArrayLike(value) { + return value != null && isLength(value.length) && !isFunction(value); + } + + module.exports = isArrayLike; + + +/***/ }), +/* 90 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseGetTag = __webpack_require__(91), + isObject = __webpack_require__(97); + + /** `Object#toString` result references. */ + var asyncTag = '[object AsyncFunction]', + funcTag = '[object Function]', + genTag = '[object GeneratorFunction]', + proxyTag = '[object Proxy]'; + + /** + * Checks if `value` is classified as a `Function` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a function, else `false`. + * @example + * + * _.isFunction(_); + * // => true + * + * _.isFunction(/abc/); + * // => false + */ + function isFunction(value) { + if (!isObject(value)) { + return false; + } + // The use of `Object#toString` avoids issues with the `typeof` operator + // in Safari 9 which returns 'object' for typed arrays and other constructors. + var tag = baseGetTag(value); + return tag == funcTag || tag == genTag || tag == asyncTag || tag == proxyTag; + } + + module.exports = isFunction; + + +/***/ }), +/* 91 */ +/***/ (function(module, exports, __webpack_require__) { + + var Symbol = __webpack_require__(92), + getRawTag = __webpack_require__(95), + objectToString = __webpack_require__(96); + + /** `Object#toString` result references. */ + var nullTag = '[object Null]', + undefinedTag = '[object Undefined]'; + + /** Built-in value references. */ + var symToStringTag = Symbol ? Symbol.toStringTag : undefined; + + /** + * The base implementation of `getTag` without fallbacks for buggy environments. + * + * @private + * @param {*} value The value to query. + * @returns {string} Returns the `toStringTag`. + */ + function baseGetTag(value) { + if (value == null) { + return value === undefined ? undefinedTag : nullTag; + } + return (symToStringTag && symToStringTag in Object(value)) + ? getRawTag(value) + : objectToString(value); + } + + module.exports = baseGetTag; + + +/***/ }), +/* 92 */ +/***/ (function(module, exports, __webpack_require__) { + + var root = __webpack_require__(93); + + /** Built-in value references. */ + var Symbol = root.Symbol; + + module.exports = Symbol; + + +/***/ }), +/* 93 */ +/***/ (function(module, exports, __webpack_require__) { + + var freeGlobal = __webpack_require__(94); + + /** Detect free variable `self`. */ + var freeSelf = typeof self == 'object' && self && self.Object === Object && self; + + /** Used as a reference to the global object. */ + var root = freeGlobal || freeSelf || Function('return this')(); + + module.exports = root; + + +/***/ }), +/* 94 */ +/***/ (function(module, exports) { + + /* WEBPACK VAR INJECTION */(function(global) {/** Detect free variable `global` from Node.js. */ + var freeGlobal = typeof global == 'object' && global && global.Object === Object && global; + + module.exports = freeGlobal; + + /* WEBPACK VAR INJECTION */}.call(exports, (function() { return this; }()))) + +/***/ }), +/* 95 */ +/***/ (function(module, exports, __webpack_require__) { + + var Symbol = __webpack_require__(92); + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * Used to resolve the + * [`toStringTag`](http://ecma-international.org/ecma-262/7.0/#sec-object.prototype.tostring) + * of values. + */ + var nativeObjectToString = objectProto.toString; + + /** Built-in value references. */ + var symToStringTag = Symbol ? Symbol.toStringTag : undefined; + + /** + * A specialized version of `baseGetTag` which ignores `Symbol.toStringTag` values. + * + * @private + * @param {*} value The value to query. + * @returns {string} Returns the raw `toStringTag`. + */ + function getRawTag(value) { + var isOwn = hasOwnProperty.call(value, symToStringTag), + tag = value[symToStringTag]; + + try { + value[symToStringTag] = undefined; + var unmasked = true; + } catch (e) {} + + var result = nativeObjectToString.call(value); + if (unmasked) { + if (isOwn) { + value[symToStringTag] = tag; + } else { + delete value[symToStringTag]; + } + } + return result; + } + + module.exports = getRawTag; + + +/***/ }), +/* 96 */ +/***/ (function(module, exports) { + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** + * Used to resolve the + * [`toStringTag`](http://ecma-international.org/ecma-262/7.0/#sec-object.prototype.tostring) + * of values. + */ + var nativeObjectToString = objectProto.toString; + + /** + * Converts `value` to a string using `Object.prototype.toString`. + * + * @private + * @param {*} value The value to convert. + * @returns {string} Returns the converted string. + */ + function objectToString(value) { + return nativeObjectToString.call(value); + } + + module.exports = objectToString; + + +/***/ }), +/* 97 */ +/***/ (function(module, exports) { + + /** + * Checks if `value` is the + * [language type](http://www.ecma-international.org/ecma-262/7.0/#sec-ecmascript-language-types) + * of `Object`. (e.g. arrays, functions, objects, regexes, `new Number(0)`, and `new String('')`) + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an object, else `false`. + * @example + * + * _.isObject({}); + * // => true + * + * _.isObject([1, 2, 3]); + * // => true + * + * _.isObject(_.noop); + * // => true + * + * _.isObject(null); + * // => false + */ + function isObject(value) { + var type = typeof value; + return value != null && (type == 'object' || type == 'function'); + } + + module.exports = isObject; + + +/***/ }), +/* 98 */ +/***/ (function(module, exports) { + + /** Used as references for various `Number` constants. */ + var MAX_SAFE_INTEGER = 9007199254740991; + + /** + * Checks if `value` is a valid array-like length. + * + * **Note:** This method is loosely based on + * [`ToLength`](http://ecma-international.org/ecma-262/7.0/#sec-tolength). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a valid length, else `false`. + * @example + * + * _.isLength(3); + * // => true + * + * _.isLength(Number.MIN_VALUE); + * // => false + * + * _.isLength(Infinity); + * // => false + * + * _.isLength('3'); + * // => false + */ + function isLength(value) { + return typeof value == 'number' && + value > -1 && value % 1 == 0 && value <= MAX_SAFE_INTEGER; + } + + module.exports = isLength; + + +/***/ }), +/* 99 */ +/***/ (function(module, exports) { + + /** Used as references for various `Number` constants. */ + var MAX_SAFE_INTEGER = 9007199254740991; + + /** Used to detect unsigned integer values. */ + var reIsUint = /^(?:0|[1-9]\d*)$/; + + /** + * Checks if `value` is a valid array-like index. + * + * @private + * @param {*} value The value to check. + * @param {number} [length=MAX_SAFE_INTEGER] The upper bounds of a valid index. + * @returns {boolean} Returns `true` if `value` is a valid index, else `false`. + */ + function isIndex(value, length) { + var type = typeof value; + length = length == null ? MAX_SAFE_INTEGER : length; + + return !!length && + (type == 'number' || + (type != 'symbol' && reIsUint.test(value))) && + (value > -1 && value % 1 == 0 && value < length); + } + + module.exports = isIndex; + + +/***/ }), +/* 100 */ +/***/ (function(module, exports, __webpack_require__) { + + var toFinite = __webpack_require__(101); + + /** + * Converts `value` to an integer. + * + * **Note:** This method is loosely based on + * [`ToInteger`](http://www.ecma-international.org/ecma-262/7.0/#sec-tointeger). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to convert. + * @returns {number} Returns the converted integer. + * @example + * + * _.toInteger(3.2); + * // => 3 + * + * _.toInteger(Number.MIN_VALUE); + * // => 0 + * + * _.toInteger(Infinity); + * // => 1.7976931348623157e+308 + * + * _.toInteger('3.2'); + * // => 3 + */ + function toInteger(value) { + var result = toFinite(value), + remainder = result % 1; + + return result === result ? (remainder ? result - remainder : result) : 0; + } + + module.exports = toInteger; + + +/***/ }), +/* 101 */ +/***/ (function(module, exports, __webpack_require__) { + + var toNumber = __webpack_require__(102); + + /** Used as references for various `Number` constants. */ + var INFINITY = 1 / 0, + MAX_INTEGER = 1.7976931348623157e+308; + + /** + * Converts `value` to a finite number. + * + * @static + * @memberOf _ + * @since 4.12.0 + * @category Lang + * @param {*} value The value to convert. + * @returns {number} Returns the converted number. + * @example + * + * _.toFinite(3.2); + * // => 3.2 + * + * _.toFinite(Number.MIN_VALUE); + * // => 5e-324 + * + * _.toFinite(Infinity); + * // => 1.7976931348623157e+308 + * + * _.toFinite('3.2'); + * // => 3.2 + */ + function toFinite(value) { + if (!value) { + return value === 0 ? value : 0; + } + value = toNumber(value); + if (value === INFINITY || value === -INFINITY) { + var sign = (value < 0 ? -1 : 1); + return sign * MAX_INTEGER; + } + return value === value ? value : 0; + } + + module.exports = toFinite; + + +/***/ }), +/* 102 */ +/***/ (function(module, exports, __webpack_require__) { + + var isObject = __webpack_require__(97), + isSymbol = __webpack_require__(103); + + /** Used as references for various `Number` constants. */ + var NAN = 0 / 0; + + /** Used to match leading and trailing whitespace. */ + var reTrim = /^\s+|\s+$/g; + + /** Used to detect bad signed hexadecimal string values. */ + var reIsBadHex = /^[-+]0x[0-9a-f]+$/i; + + /** Used to detect binary string values. */ + var reIsBinary = /^0b[01]+$/i; + + /** Used to detect octal string values. */ + var reIsOctal = /^0o[0-7]+$/i; + + /** Built-in method references without a dependency on `root`. */ + var freeParseInt = parseInt; + + /** + * Converts `value` to a number. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to process. + * @returns {number} Returns the number. + * @example + * + * _.toNumber(3.2); + * // => 3.2 + * + * _.toNumber(Number.MIN_VALUE); + * // => 5e-324 + * + * _.toNumber(Infinity); + * // => Infinity + * + * _.toNumber('3.2'); + * // => 3.2 + */ + function toNumber(value) { + if (typeof value == 'number') { + return value; + } + if (isSymbol(value)) { + return NAN; + } + if (isObject(value)) { + var other = typeof value.valueOf == 'function' ? value.valueOf() : value; + value = isObject(other) ? (other + '') : other; + } + if (typeof value != 'string') { + return value === 0 ? value : +value; + } + value = value.replace(reTrim, ''); + var isBinary = reIsBinary.test(value); + return (isBinary || reIsOctal.test(value)) + ? freeParseInt(value.slice(2), isBinary ? 2 : 8) + : (reIsBadHex.test(value) ? NAN : +value); + } + + module.exports = toNumber; + + +/***/ }), +/* 103 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseGetTag = __webpack_require__(91), + isObjectLike = __webpack_require__(104); + + /** `Object#toString` result references. */ + var symbolTag = '[object Symbol]'; + + /** + * Checks if `value` is classified as a `Symbol` primitive or object. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a symbol, else `false`. + * @example + * + * _.isSymbol(Symbol.iterator); + * // => true + * + * _.isSymbol('abc'); + * // => false + */ + function isSymbol(value) { + return typeof value == 'symbol' || + (isObjectLike(value) && baseGetTag(value) == symbolTag); + } + + module.exports = isSymbol; + + +/***/ }), +/* 104 */ +/***/ (function(module, exports) { + + /** + * Checks if `value` is object-like. A value is object-like if it's not `null` + * and has a `typeof` result of "object". + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is object-like, else `false`. + * @example + * + * _.isObjectLike({}); + * // => true + * + * _.isObjectLike([1, 2, 3]); + * // => true + * + * _.isObjectLike(_.noop); + * // => false + * + * _.isObjectLike(null); + * // => false + */ + function isObjectLike(value) { + return value != null && typeof value == 'object'; + } + + module.exports = isObjectLike; + + +/***/ }), +/* 105 */ +/***/ (function(module, exports) { + + /** + * Creates an array with all falsey values removed. The values `false`, `null`, + * `0`, `""`, `undefined`, and `NaN` are falsey. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to compact. + * @returns {Array} Returns the new array of filtered values. + * @example + * + * _.compact([0, 1, false, 2, '', 3]); + * // => [1, 2, 3] + */ + function compact(array) { + var index = -1, + length = array == null ? 0 : array.length, + resIndex = 0, + result = []; + + while (++index < length) { + var value = array[index]; + if (value) { + result[resIndex++] = value; + } + } + return result; + } + + module.exports = compact; + + +/***/ }), +/* 106 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayPush = __webpack_require__(107), + baseFlatten = __webpack_require__(108), + copyArray = __webpack_require__(113), + isArray = __webpack_require__(112); + + /** + * Creates a new array concatenating `array` with any additional arrays + * and/or values. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to concatenate. + * @param {...*} [values] The values to concatenate. + * @returns {Array} Returns the new concatenated array. + * @example + * + * var array = [1]; + * var other = _.concat(array, 2, [3], [[4]]); + * + * console.log(other); + * // => [1, 2, 3, [4]] + * + * console.log(array); + * // => [1] + */ + function concat() { + var length = arguments.length; + if (!length) { + return []; + } + var args = Array(length - 1), + array = arguments[0], + index = length; + + while (index--) { + args[index - 1] = arguments[index]; + } + return arrayPush(isArray(array) ? copyArray(array) : [array], baseFlatten(args, 1)); + } + + module.exports = concat; + + +/***/ }), +/* 107 */ +/***/ (function(module, exports) { + + /** + * Appends the elements of `values` to `array`. + * + * @private + * @param {Array} array The array to modify. + * @param {Array} values The values to append. + * @returns {Array} Returns `array`. + */ + function arrayPush(array, values) { + var index = -1, + length = values.length, + offset = array.length; + + while (++index < length) { + array[offset + index] = values[index]; + } + return array; + } + + module.exports = arrayPush; + + +/***/ }), +/* 108 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayPush = __webpack_require__(107), + isFlattenable = __webpack_require__(109); + + /** + * The base implementation of `_.flatten` with support for restricting flattening. + * + * @private + * @param {Array} array The array to flatten. + * @param {number} depth The maximum recursion depth. + * @param {boolean} [predicate=isFlattenable] The function invoked per iteration. + * @param {boolean} [isStrict] Restrict to values that pass `predicate` checks. + * @param {Array} [result=[]] The initial result value. + * @returns {Array} Returns the new flattened array. + */ + function baseFlatten(array, depth, predicate, isStrict, result) { + var index = -1, + length = array.length; + + predicate || (predicate = isFlattenable); + result || (result = []); + + while (++index < length) { + var value = array[index]; + if (depth > 0 && predicate(value)) { + if (depth > 1) { + // Recursively flatten arrays (susceptible to call stack limits). + baseFlatten(value, depth - 1, predicate, isStrict, result); + } else { + arrayPush(result, value); + } + } else if (!isStrict) { + result[result.length] = value; + } + } + return result; + } + + module.exports = baseFlatten; + + +/***/ }), +/* 109 */ +/***/ (function(module, exports, __webpack_require__) { + + var Symbol = __webpack_require__(92), + isArguments = __webpack_require__(110), + isArray = __webpack_require__(112); + + /** Built-in value references. */ + var spreadableSymbol = Symbol ? Symbol.isConcatSpreadable : undefined; + + /** + * Checks if `value` is a flattenable `arguments` object or array. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is flattenable, else `false`. + */ + function isFlattenable(value) { + return isArray(value) || isArguments(value) || + !!(spreadableSymbol && value && value[spreadableSymbol]); + } + + module.exports = isFlattenable; + + +/***/ }), +/* 110 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIsArguments = __webpack_require__(111), + isObjectLike = __webpack_require__(104); + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** Built-in value references. */ + var propertyIsEnumerable = objectProto.propertyIsEnumerable; + + /** + * Checks if `value` is likely an `arguments` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an `arguments` object, + * else `false`. + * @example + * + * _.isArguments(function() { return arguments; }()); + * // => true + * + * _.isArguments([1, 2, 3]); + * // => false + */ + var isArguments = baseIsArguments(function() { return arguments; }()) ? baseIsArguments : function(value) { + return isObjectLike(value) && hasOwnProperty.call(value, 'callee') && + !propertyIsEnumerable.call(value, 'callee'); + }; + + module.exports = isArguments; + + +/***/ }), +/* 111 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseGetTag = __webpack_require__(91), + isObjectLike = __webpack_require__(104); + + /** `Object#toString` result references. */ + var argsTag = '[object Arguments]'; + + /** + * The base implementation of `_.isArguments`. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an `arguments` object, + */ + function baseIsArguments(value) { + return isObjectLike(value) && baseGetTag(value) == argsTag; + } + + module.exports = baseIsArguments; + + +/***/ }), +/* 112 */ +/***/ (function(module, exports) { + + /** + * Checks if `value` is classified as an `Array` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an array, else `false`. + * @example + * + * _.isArray([1, 2, 3]); + * // => true + * + * _.isArray(document.body.children); + * // => false + * + * _.isArray('abc'); + * // => false + * + * _.isArray(_.noop); + * // => false + */ + var isArray = Array.isArray; + + module.exports = isArray; + + +/***/ }), +/* 113 */ +/***/ (function(module, exports) { + + /** + * Copies the values of `source` to `array`. + * + * @private + * @param {Array} source The array to copy values from. + * @param {Array} [array=[]] The array to copy values to. + * @returns {Array} Returns `array`. + */ + function copyArray(source, array) { + var index = -1, + length = source.length; + + array || (array = Array(length)); + while (++index < length) { + array[index] = source[index]; + } + return array; + } + + module.exports = copyArray; + + +/***/ }), +/* 114 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseDifference = __webpack_require__(115), + baseFlatten = __webpack_require__(108), + baseRest = __webpack_require__(157), + isArrayLikeObject = __webpack_require__(166); + + /** + * Creates an array of `array` values not included in the other given arrays + * using [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. The order and references of result values are + * determined by the first array. + * + * **Note:** Unlike `_.pullAll`, this method returns a new array. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {...Array} [values] The values to exclude. + * @returns {Array} Returns the new array of filtered values. + * @see _.without, _.xor + * @example + * + * _.difference([2, 1], [2, 3]); + * // => [1] + */ + var difference = baseRest(function(array, values) { + return isArrayLikeObject(array) + ? baseDifference(array, baseFlatten(values, 1, isArrayLikeObject, true)) + : []; + }); + + module.exports = difference; + + +/***/ }), +/* 115 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetCache = __webpack_require__(116), + arrayIncludes = __webpack_require__(148), + arrayIncludesWith = __webpack_require__(153), + arrayMap = __webpack_require__(154), + baseUnary = __webpack_require__(155), + cacheHas = __webpack_require__(156); + + /** Used as the size to enable large array optimizations. */ + var LARGE_ARRAY_SIZE = 200; + + /** + * The base implementation of methods like `_.difference` without support + * for excluding multiple arrays or iteratee shorthands. + * + * @private + * @param {Array} array The array to inspect. + * @param {Array} values The values to exclude. + * @param {Function} [iteratee] The iteratee invoked per element. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new array of filtered values. + */ + function baseDifference(array, values, iteratee, comparator) { + var index = -1, + includes = arrayIncludes, + isCommon = true, + length = array.length, + result = [], + valuesLength = values.length; + + if (!length) { + return result; + } + if (iteratee) { + values = arrayMap(values, baseUnary(iteratee)); + } + if (comparator) { + includes = arrayIncludesWith; + isCommon = false; + } + else if (values.length >= LARGE_ARRAY_SIZE) { + includes = cacheHas; + isCommon = false; + values = new SetCache(values); + } + outer: + while (++index < length) { + var value = array[index], + computed = iteratee == null ? value : iteratee(value); + + value = (comparator || value !== 0) ? value : 0; + if (isCommon && computed === computed) { + var valuesIndex = valuesLength; + while (valuesIndex--) { + if (values[valuesIndex] === computed) { + continue outer; + } + } + result.push(value); + } + else if (!includes(values, computed, comparator)) { + result.push(value); + } + } + return result; + } + + module.exports = baseDifference; + + +/***/ }), +/* 116 */ +/***/ (function(module, exports, __webpack_require__) { + + var MapCache = __webpack_require__(117), + setCacheAdd = __webpack_require__(146), + setCacheHas = __webpack_require__(147); + + /** + * + * Creates an array cache object to store unique values. + * + * @private + * @constructor + * @param {Array} [values] The values to cache. + */ + function SetCache(values) { + var index = -1, + length = values == null ? 0 : values.length; + + this.__data__ = new MapCache; + while (++index < length) { + this.add(values[index]); + } + } + + // Add methods to `SetCache`. + SetCache.prototype.add = SetCache.prototype.push = setCacheAdd; + SetCache.prototype.has = setCacheHas; + + module.exports = SetCache; + + +/***/ }), +/* 117 */ +/***/ (function(module, exports, __webpack_require__) { + + var mapCacheClear = __webpack_require__(118), + mapCacheDelete = __webpack_require__(140), + mapCacheGet = __webpack_require__(143), + mapCacheHas = __webpack_require__(144), + mapCacheSet = __webpack_require__(145); + + /** + * Creates a map cache object to store key-value pairs. + * + * @private + * @constructor + * @param {Array} [entries] The key-value pairs to cache. + */ + function MapCache(entries) { + var index = -1, + length = entries == null ? 0 : entries.length; + + this.clear(); + while (++index < length) { + var entry = entries[index]; + this.set(entry[0], entry[1]); + } + } + + // Add methods to `MapCache`. + MapCache.prototype.clear = mapCacheClear; + MapCache.prototype['delete'] = mapCacheDelete; + MapCache.prototype.get = mapCacheGet; + MapCache.prototype.has = mapCacheHas; + MapCache.prototype.set = mapCacheSet; + + module.exports = MapCache; + + +/***/ }), +/* 118 */ +/***/ (function(module, exports, __webpack_require__) { + + var Hash = __webpack_require__(119), + ListCache = __webpack_require__(132), + Map = __webpack_require__(139); + + /** + * Removes all key-value entries from the map. + * + * @private + * @name clear + * @memberOf MapCache + */ + function mapCacheClear() { + this.size = 0; + this.__data__ = { + 'hash': new Hash, + 'map': new (Map || ListCache), + 'string': new Hash + }; + } + + module.exports = mapCacheClear; + + +/***/ }), +/* 119 */ +/***/ (function(module, exports, __webpack_require__) { + + var hashClear = __webpack_require__(120), + hashDelete = __webpack_require__(128), + hashGet = __webpack_require__(129), + hashHas = __webpack_require__(130), + hashSet = __webpack_require__(131); + + /** + * Creates a hash object. + * + * @private + * @constructor + * @param {Array} [entries] The key-value pairs to cache. + */ + function Hash(entries) { + var index = -1, + length = entries == null ? 0 : entries.length; + + this.clear(); + while (++index < length) { + var entry = entries[index]; + this.set(entry[0], entry[1]); + } + } + + // Add methods to `Hash`. + Hash.prototype.clear = hashClear; + Hash.prototype['delete'] = hashDelete; + Hash.prototype.get = hashGet; + Hash.prototype.has = hashHas; + Hash.prototype.set = hashSet; + + module.exports = Hash; + + +/***/ }), +/* 120 */ +/***/ (function(module, exports, __webpack_require__) { + + var nativeCreate = __webpack_require__(121); + + /** + * Removes all key-value entries from the hash. + * + * @private + * @name clear + * @memberOf Hash + */ + function hashClear() { + this.__data__ = nativeCreate ? nativeCreate(null) : {}; + this.size = 0; + } + + module.exports = hashClear; + + +/***/ }), +/* 121 */ +/***/ (function(module, exports, __webpack_require__) { + + var getNative = __webpack_require__(122); + + /* Built-in method references that are verified to be native. */ + var nativeCreate = getNative(Object, 'create'); + + module.exports = nativeCreate; + + +/***/ }), +/* 122 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIsNative = __webpack_require__(123), + getValue = __webpack_require__(127); + + /** + * Gets the native function at `key` of `object`. + * + * @private + * @param {Object} object The object to query. + * @param {string} key The key of the method to get. + * @returns {*} Returns the function if it's native, else `undefined`. + */ + function getNative(object, key) { + var value = getValue(object, key); + return baseIsNative(value) ? value : undefined; + } + + module.exports = getNative; + + +/***/ }), +/* 123 */ +/***/ (function(module, exports, __webpack_require__) { + + var isFunction = __webpack_require__(90), + isMasked = __webpack_require__(124), + isObject = __webpack_require__(97), + toSource = __webpack_require__(126); + + /** + * Used to match `RegExp` + * [syntax characters](http://ecma-international.org/ecma-262/7.0/#sec-patterns). + */ + var reRegExpChar = /[\\^$.*+?()[\]{}|]/g; + + /** Used to detect host constructors (Safari). */ + var reIsHostCtor = /^\[object .+?Constructor\]$/; + + /** Used for built-in method references. */ + var funcProto = Function.prototype, + objectProto = Object.prototype; + + /** Used to resolve the decompiled source of functions. */ + var funcToString = funcProto.toString; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** Used to detect if a method is native. */ + var reIsNative = RegExp('^' + + funcToString.call(hasOwnProperty).replace(reRegExpChar, '\\$&') + .replace(/hasOwnProperty|(function).*?(?=\\\()| for .+?(?=\\\])/g, '$1.*?') + '$' + ); + + /** + * The base implementation of `_.isNative` without bad shim checks. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a native function, + * else `false`. + */ + function baseIsNative(value) { + if (!isObject(value) || isMasked(value)) { + return false; + } + var pattern = isFunction(value) ? reIsNative : reIsHostCtor; + return pattern.test(toSource(value)); + } + + module.exports = baseIsNative; + + +/***/ }), +/* 124 */ +/***/ (function(module, exports, __webpack_require__) { + + var coreJsData = __webpack_require__(125); + + /** Used to detect methods masquerading as native. */ + var maskSrcKey = (function() { + var uid = /[^.]+$/.exec(coreJsData && coreJsData.keys && coreJsData.keys.IE_PROTO || ''); + return uid ? ('Symbol(src)_1.' + uid) : ''; + }()); + + /** + * Checks if `func` has its source masked. + * + * @private + * @param {Function} func The function to check. + * @returns {boolean} Returns `true` if `func` is masked, else `false`. + */ + function isMasked(func) { + return !!maskSrcKey && (maskSrcKey in func); + } + + module.exports = isMasked; + + +/***/ }), +/* 125 */ +/***/ (function(module, exports, __webpack_require__) { + + var root = __webpack_require__(93); + + /** Used to detect overreaching core-js shims. */ + var coreJsData = root['__core-js_shared__']; + + module.exports = coreJsData; + + +/***/ }), +/* 126 */ +/***/ (function(module, exports) { + + /** Used for built-in method references. */ + var funcProto = Function.prototype; + + /** Used to resolve the decompiled source of functions. */ + var funcToString = funcProto.toString; + + /** + * Converts `func` to its source code. + * + * @private + * @param {Function} func The function to convert. + * @returns {string} Returns the source code. + */ + function toSource(func) { + if (func != null) { + try { + return funcToString.call(func); + } catch (e) {} + try { + return (func + ''); + } catch (e) {} + } + return ''; + } + + module.exports = toSource; + + +/***/ }), +/* 127 */ +/***/ (function(module, exports) { + + /** + * Gets the value at `key` of `object`. + * + * @private + * @param {Object} [object] The object to query. + * @param {string} key The key of the property to get. + * @returns {*} Returns the property value. + */ + function getValue(object, key) { + return object == null ? undefined : object[key]; + } + + module.exports = getValue; + + +/***/ }), +/* 128 */ +/***/ (function(module, exports) { + + /** + * Removes `key` and its value from the hash. + * + * @private + * @name delete + * @memberOf Hash + * @param {Object} hash The hash to modify. + * @param {string} key The key of the value to remove. + * @returns {boolean} Returns `true` if the entry was removed, else `false`. + */ + function hashDelete(key) { + var result = this.has(key) && delete this.__data__[key]; + this.size -= result ? 1 : 0; + return result; + } + + module.exports = hashDelete; + + +/***/ }), +/* 129 */ +/***/ (function(module, exports, __webpack_require__) { + + var nativeCreate = __webpack_require__(121); + + /** Used to stand-in for `undefined` hash values. */ + var HASH_UNDEFINED = '__lodash_hash_undefined__'; + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * Gets the hash value for `key`. + * + * @private + * @name get + * @memberOf Hash + * @param {string} key The key of the value to get. + * @returns {*} Returns the entry value. + */ + function hashGet(key) { + var data = this.__data__; + if (nativeCreate) { + var result = data[key]; + return result === HASH_UNDEFINED ? undefined : result; + } + return hasOwnProperty.call(data, key) ? data[key] : undefined; + } + + module.exports = hashGet; + + +/***/ }), +/* 130 */ +/***/ (function(module, exports, __webpack_require__) { + + var nativeCreate = __webpack_require__(121); + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * Checks if a hash value for `key` exists. + * + * @private + * @name has + * @memberOf Hash + * @param {string} key The key of the entry to check. + * @returns {boolean} Returns `true` if an entry for `key` exists, else `false`. + */ + function hashHas(key) { + var data = this.__data__; + return nativeCreate ? (data[key] !== undefined) : hasOwnProperty.call(data, key); + } + + module.exports = hashHas; + + +/***/ }), +/* 131 */ +/***/ (function(module, exports, __webpack_require__) { + + var nativeCreate = __webpack_require__(121); + + /** Used to stand-in for `undefined` hash values. */ + var HASH_UNDEFINED = '__lodash_hash_undefined__'; + + /** + * Sets the hash `key` to `value`. + * + * @private + * @name set + * @memberOf Hash + * @param {string} key The key of the value to set. + * @param {*} value The value to set. + * @returns {Object} Returns the hash instance. + */ + function hashSet(key, value) { + var data = this.__data__; + this.size += this.has(key) ? 0 : 1; + data[key] = (nativeCreate && value === undefined) ? HASH_UNDEFINED : value; + return this; + } + + module.exports = hashSet; + + +/***/ }), +/* 132 */ +/***/ (function(module, exports, __webpack_require__) { + + var listCacheClear = __webpack_require__(133), + listCacheDelete = __webpack_require__(134), + listCacheGet = __webpack_require__(136), + listCacheHas = __webpack_require__(137), + listCacheSet = __webpack_require__(138); + + /** + * Creates an list cache object. + * + * @private + * @constructor + * @param {Array} [entries] The key-value pairs to cache. + */ + function ListCache(entries) { + var index = -1, + length = entries == null ? 0 : entries.length; + + this.clear(); + while (++index < length) { + var entry = entries[index]; + this.set(entry[0], entry[1]); + } + } + + // Add methods to `ListCache`. + ListCache.prototype.clear = listCacheClear; + ListCache.prototype['delete'] = listCacheDelete; + ListCache.prototype.get = listCacheGet; + ListCache.prototype.has = listCacheHas; + ListCache.prototype.set = listCacheSet; + + module.exports = ListCache; + + +/***/ }), +/* 133 */ +/***/ (function(module, exports) { + + /** + * Removes all key-value entries from the list cache. + * + * @private + * @name clear + * @memberOf ListCache + */ + function listCacheClear() { + this.__data__ = []; + this.size = 0; + } + + module.exports = listCacheClear; + + +/***/ }), +/* 134 */ +/***/ (function(module, exports, __webpack_require__) { + + var assocIndexOf = __webpack_require__(135); + + /** Used for built-in method references. */ + var arrayProto = Array.prototype; + + /** Built-in value references. */ + var splice = arrayProto.splice; + + /** + * Removes `key` and its value from the list cache. + * + * @private + * @name delete + * @memberOf ListCache + * @param {string} key The key of the value to remove. + * @returns {boolean} Returns `true` if the entry was removed, else `false`. + */ + function listCacheDelete(key) { + var data = this.__data__, + index = assocIndexOf(data, key); + + if (index < 0) { + return false; + } + var lastIndex = data.length - 1; + if (index == lastIndex) { + data.pop(); + } else { + splice.call(data, index, 1); + } + --this.size; + return true; + } + + module.exports = listCacheDelete; + + +/***/ }), +/* 135 */ +/***/ (function(module, exports, __webpack_require__) { + + var eq = __webpack_require__(88); + + /** + * Gets the index at which the `key` is found in `array` of key-value pairs. + * + * @private + * @param {Array} array The array to inspect. + * @param {*} key The key to search for. + * @returns {number} Returns the index of the matched value, else `-1`. + */ + function assocIndexOf(array, key) { + var length = array.length; + while (length--) { + if (eq(array[length][0], key)) { + return length; + } + } + return -1; + } + + module.exports = assocIndexOf; + + +/***/ }), +/* 136 */ +/***/ (function(module, exports, __webpack_require__) { + + var assocIndexOf = __webpack_require__(135); + + /** + * Gets the list cache value for `key`. + * + * @private + * @name get + * @memberOf ListCache + * @param {string} key The key of the value to get. + * @returns {*} Returns the entry value. + */ + function listCacheGet(key) { + var data = this.__data__, + index = assocIndexOf(data, key); + + return index < 0 ? undefined : data[index][1]; + } + + module.exports = listCacheGet; + + +/***/ }), +/* 137 */ +/***/ (function(module, exports, __webpack_require__) { + + var assocIndexOf = __webpack_require__(135); + + /** + * Checks if a list cache value for `key` exists. + * + * @private + * @name has + * @memberOf ListCache + * @param {string} key The key of the entry to check. + * @returns {boolean} Returns `true` if an entry for `key` exists, else `false`. + */ + function listCacheHas(key) { + return assocIndexOf(this.__data__, key) > -1; + } + + module.exports = listCacheHas; + + +/***/ }), +/* 138 */ +/***/ (function(module, exports, __webpack_require__) { + + var assocIndexOf = __webpack_require__(135); + + /** + * Sets the list cache `key` to `value`. + * + * @private + * @name set + * @memberOf ListCache + * @param {string} key The key of the value to set. + * @param {*} value The value to set. + * @returns {Object} Returns the list cache instance. + */ + function listCacheSet(key, value) { + var data = this.__data__, + index = assocIndexOf(data, key); + + if (index < 0) { + ++this.size; + data.push([key, value]); + } else { + data[index][1] = value; + } + return this; + } + + module.exports = listCacheSet; + + +/***/ }), +/* 139 */ +/***/ (function(module, exports, __webpack_require__) { + + var getNative = __webpack_require__(122), + root = __webpack_require__(93); + + /* Built-in method references that are verified to be native. */ + var Map = getNative(root, 'Map'); + + module.exports = Map; + + +/***/ }), +/* 140 */ +/***/ (function(module, exports, __webpack_require__) { + + var getMapData = __webpack_require__(141); + + /** + * Removes `key` and its value from the map. + * + * @private + * @name delete + * @memberOf MapCache + * @param {string} key The key of the value to remove. + * @returns {boolean} Returns `true` if the entry was removed, else `false`. + */ + function mapCacheDelete(key) { + var result = getMapData(this, key)['delete'](key); + this.size -= result ? 1 : 0; + return result; + } + + module.exports = mapCacheDelete; + + +/***/ }), +/* 141 */ +/***/ (function(module, exports, __webpack_require__) { + + var isKeyable = __webpack_require__(142); + + /** + * Gets the data for `map`. + * + * @private + * @param {Object} map The map to query. + * @param {string} key The reference key. + * @returns {*} Returns the map data. + */ + function getMapData(map, key) { + var data = map.__data__; + return isKeyable(key) + ? data[typeof key == 'string' ? 'string' : 'hash'] + : data.map; + } + + module.exports = getMapData; + + +/***/ }), +/* 142 */ +/***/ (function(module, exports) { + + /** + * Checks if `value` is suitable for use as unique object key. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is suitable, else `false`. + */ + function isKeyable(value) { + var type = typeof value; + return (type == 'string' || type == 'number' || type == 'symbol' || type == 'boolean') + ? (value !== '__proto__') + : (value === null); + } + + module.exports = isKeyable; + + +/***/ }), +/* 143 */ +/***/ (function(module, exports, __webpack_require__) { + + var getMapData = __webpack_require__(141); + + /** + * Gets the map value for `key`. + * + * @private + * @name get + * @memberOf MapCache + * @param {string} key The key of the value to get. + * @returns {*} Returns the entry value. + */ + function mapCacheGet(key) { + return getMapData(this, key).get(key); + } + + module.exports = mapCacheGet; + + +/***/ }), +/* 144 */ +/***/ (function(module, exports, __webpack_require__) { + + var getMapData = __webpack_require__(141); + + /** + * Checks if a map value for `key` exists. + * + * @private + * @name has + * @memberOf MapCache + * @param {string} key The key of the entry to check. + * @returns {boolean} Returns `true` if an entry for `key` exists, else `false`. + */ + function mapCacheHas(key) { + return getMapData(this, key).has(key); + } + + module.exports = mapCacheHas; + + +/***/ }), +/* 145 */ +/***/ (function(module, exports, __webpack_require__) { + + var getMapData = __webpack_require__(141); + + /** + * Sets the map `key` to `value`. + * + * @private + * @name set + * @memberOf MapCache + * @param {string} key The key of the value to set. + * @param {*} value The value to set. + * @returns {Object} Returns the map cache instance. + */ + function mapCacheSet(key, value) { + var data = getMapData(this, key), + size = data.size; + + data.set(key, value); + this.size += data.size == size ? 0 : 1; + return this; + } + + module.exports = mapCacheSet; + + +/***/ }), +/* 146 */ +/***/ (function(module, exports) { + + /** Used to stand-in for `undefined` hash values. */ + var HASH_UNDEFINED = '__lodash_hash_undefined__'; + + /** + * Adds `value` to the array cache. + * + * @private + * @name add + * @memberOf SetCache + * @alias push + * @param {*} value The value to cache. + * @returns {Object} Returns the cache instance. + */ + function setCacheAdd(value) { + this.__data__.set(value, HASH_UNDEFINED); + return this; + } + + module.exports = setCacheAdd; + + +/***/ }), +/* 147 */ +/***/ (function(module, exports) { + + /** + * Checks if `value` is in the array cache. + * + * @private + * @name has + * @memberOf SetCache + * @param {*} value The value to search for. + * @returns {number} Returns `true` if `value` is found, else `false`. + */ + function setCacheHas(value) { + return this.__data__.has(value); + } + + module.exports = setCacheHas; + + +/***/ }), +/* 148 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIndexOf = __webpack_require__(149); + + /** + * A specialized version of `_.includes` for arrays without support for + * specifying an index to search from. + * + * @private + * @param {Array} [array] The array to inspect. + * @param {*} target The value to search for. + * @returns {boolean} Returns `true` if `target` is found, else `false`. + */ + function arrayIncludes(array, value) { + var length = array == null ? 0 : array.length; + return !!length && baseIndexOf(array, value, 0) > -1; + } + + module.exports = arrayIncludes; + + +/***/ }), +/* 149 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFindIndex = __webpack_require__(150), + baseIsNaN = __webpack_require__(151), + strictIndexOf = __webpack_require__(152); + + /** + * The base implementation of `_.indexOf` without `fromIndex` bounds checks. + * + * @private + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @param {number} fromIndex The index to search from. + * @returns {number} Returns the index of the matched value, else `-1`. + */ + function baseIndexOf(array, value, fromIndex) { + return value === value + ? strictIndexOf(array, value, fromIndex) + : baseFindIndex(array, baseIsNaN, fromIndex); + } + + module.exports = baseIndexOf; + + +/***/ }), +/* 150 */ +/***/ (function(module, exports) { + + /** + * The base implementation of `_.findIndex` and `_.findLastIndex` without + * support for iteratee shorthands. + * + * @private + * @param {Array} array The array to inspect. + * @param {Function} predicate The function invoked per iteration. + * @param {number} fromIndex The index to search from. + * @param {boolean} [fromRight] Specify iterating from right to left. + * @returns {number} Returns the index of the matched value, else `-1`. + */ + function baseFindIndex(array, predicate, fromIndex, fromRight) { + var length = array.length, + index = fromIndex + (fromRight ? 1 : -1); + + while ((fromRight ? index-- : ++index < length)) { + if (predicate(array[index], index, array)) { + return index; + } + } + return -1; + } + + module.exports = baseFindIndex; + + +/***/ }), +/* 151 */ +/***/ (function(module, exports) { + + /** + * The base implementation of `_.isNaN` without support for number objects. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is `NaN`, else `false`. + */ + function baseIsNaN(value) { + return value !== value; + } + + module.exports = baseIsNaN; + + +/***/ }), +/* 152 */ +/***/ (function(module, exports) { + + /** + * A specialized version of `_.indexOf` which performs strict equality + * comparisons of values, i.e. `===`. + * + * @private + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @param {number} fromIndex The index to search from. + * @returns {number} Returns the index of the matched value, else `-1`. + */ + function strictIndexOf(array, value, fromIndex) { + var index = fromIndex - 1, + length = array.length; + + while (++index < length) { + if (array[index] === value) { + return index; + } + } + return -1; + } + + module.exports = strictIndexOf; + + +/***/ }), +/* 153 */ +/***/ (function(module, exports) { + + /** + * This function is like `arrayIncludes` except that it accepts a comparator. + * + * @private + * @param {Array} [array] The array to inspect. + * @param {*} target The value to search for. + * @param {Function} comparator The comparator invoked per element. + * @returns {boolean} Returns `true` if `target` is found, else `false`. + */ + function arrayIncludesWith(array, value, comparator) { + var index = -1, + length = array == null ? 0 : array.length; + + while (++index < length) { + if (comparator(value, array[index])) { + return true; + } + } + return false; + } + + module.exports = arrayIncludesWith; + + +/***/ }), +/* 154 */ +/***/ (function(module, exports) { + + /** + * A specialized version of `_.map` for arrays without support for iteratee + * shorthands. + * + * @private + * @param {Array} [array] The array to iterate over. + * @param {Function} iteratee The function invoked per iteration. + * @returns {Array} Returns the new mapped array. + */ + function arrayMap(array, iteratee) { + var index = -1, + length = array == null ? 0 : array.length, + result = Array(length); + + while (++index < length) { + result[index] = iteratee(array[index], index, array); + } + return result; + } + + module.exports = arrayMap; + + +/***/ }), +/* 155 */ +/***/ (function(module, exports) { + + /** + * The base implementation of `_.unary` without support for storing metadata. + * + * @private + * @param {Function} func The function to cap arguments for. + * @returns {Function} Returns the new capped function. + */ + function baseUnary(func) { + return function(value) { + return func(value); + }; + } + + module.exports = baseUnary; + + +/***/ }), +/* 156 */ +/***/ (function(module, exports) { + + /** + * Checks if a `cache` value for `key` exists. + * + * @private + * @param {Object} cache The cache to query. + * @param {string} key The key of the entry to check. + * @returns {boolean} Returns `true` if an entry for `key` exists, else `false`. + */ + function cacheHas(cache, key) { + return cache.has(key); + } + + module.exports = cacheHas; + + +/***/ }), +/* 157 */ +/***/ (function(module, exports, __webpack_require__) { + + var identity = __webpack_require__(158), + overRest = __webpack_require__(159), + setToString = __webpack_require__(161); + + /** + * The base implementation of `_.rest` which doesn't validate or coerce arguments. + * + * @private + * @param {Function} func The function to apply a rest parameter to. + * @param {number} [start=func.length-1] The start position of the rest parameter. + * @returns {Function} Returns the new function. + */ + function baseRest(func, start) { + return setToString(overRest(func, start, identity), func + ''); + } + + module.exports = baseRest; + + +/***/ }), +/* 158 */ +/***/ (function(module, exports) { + + /** + * This method returns the first argument it receives. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Util + * @param {*} value Any value. + * @returns {*} Returns `value`. + * @example + * + * var object = { 'a': 1 }; + * + * console.log(_.identity(object) === object); + * // => true + */ + function identity(value) { + return value; + } + + module.exports = identity; + + +/***/ }), +/* 159 */ +/***/ (function(module, exports, __webpack_require__) { + + var apply = __webpack_require__(160); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeMax = Math.max; + + /** + * A specialized version of `baseRest` which transforms the rest array. + * + * @private + * @param {Function} func The function to apply a rest parameter to. + * @param {number} [start=func.length-1] The start position of the rest parameter. + * @param {Function} transform The rest array transform. + * @returns {Function} Returns the new function. + */ + function overRest(func, start, transform) { + start = nativeMax(start === undefined ? (func.length - 1) : start, 0); + return function() { + var args = arguments, + index = -1, + length = nativeMax(args.length - start, 0), + array = Array(length); + + while (++index < length) { + array[index] = args[start + index]; + } + index = -1; + var otherArgs = Array(start + 1); + while (++index < start) { + otherArgs[index] = args[index]; + } + otherArgs[start] = transform(array); + return apply(func, this, otherArgs); + }; + } + + module.exports = overRest; + + +/***/ }), +/* 160 */ +/***/ (function(module, exports) { + + /** + * A faster alternative to `Function#apply`, this function invokes `func` + * with the `this` binding of `thisArg` and the arguments of `args`. + * + * @private + * @param {Function} func The function to invoke. + * @param {*} thisArg The `this` binding of `func`. + * @param {Array} args The arguments to invoke `func` with. + * @returns {*} Returns the result of `func`. + */ + function apply(func, thisArg, args) { + switch (args.length) { + case 0: return func.call(thisArg); + case 1: return func.call(thisArg, args[0]); + case 2: return func.call(thisArg, args[0], args[1]); + case 3: return func.call(thisArg, args[0], args[1], args[2]); + } + return func.apply(thisArg, args); + } + + module.exports = apply; + + +/***/ }), +/* 161 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSetToString = __webpack_require__(162), + shortOut = __webpack_require__(165); + + /** + * Sets the `toString` method of `func` to return `string`. + * + * @private + * @param {Function} func The function to modify. + * @param {Function} string The `toString` result. + * @returns {Function} Returns `func`. + */ + var setToString = shortOut(baseSetToString); + + module.exports = setToString; + + +/***/ }), +/* 162 */ +/***/ (function(module, exports, __webpack_require__) { + + var constant = __webpack_require__(163), + defineProperty = __webpack_require__(164), + identity = __webpack_require__(158); + + /** + * The base implementation of `setToString` without support for hot loop shorting. + * + * @private + * @param {Function} func The function to modify. + * @param {Function} string The `toString` result. + * @returns {Function} Returns `func`. + */ + var baseSetToString = !defineProperty ? identity : function(func, string) { + return defineProperty(func, 'toString', { + 'configurable': true, + 'enumerable': false, + 'value': constant(string), + 'writable': true + }); + }; + + module.exports = baseSetToString; + + +/***/ }), +/* 163 */ +/***/ (function(module, exports) { + + /** + * Creates a function that returns `value`. + * + * @static + * @memberOf _ + * @since 2.4.0 + * @category Util + * @param {*} value The value to return from the new function. + * @returns {Function} Returns the new constant function. + * @example + * + * var objects = _.times(2, _.constant({ 'a': 1 })); + * + * console.log(objects); + * // => [{ 'a': 1 }, { 'a': 1 }] + * + * console.log(objects[0] === objects[1]); + * // => true + */ + function constant(value) { + return function() { + return value; + }; + } + + module.exports = constant; + + +/***/ }), +/* 164 */ +/***/ (function(module, exports, __webpack_require__) { + + var getNative = __webpack_require__(122); + + var defineProperty = (function() { + try { + var func = getNative(Object, 'defineProperty'); + func({}, '', {}); + return func; + } catch (e) {} + }()); + + module.exports = defineProperty; + + +/***/ }), +/* 165 */ +/***/ (function(module, exports) { + + /** Used to detect hot functions by number of calls within a span of milliseconds. */ + var HOT_COUNT = 800, + HOT_SPAN = 16; + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeNow = Date.now; + + /** + * Creates a function that'll short out and invoke `identity` instead + * of `func` when it's called `HOT_COUNT` or more times in `HOT_SPAN` + * milliseconds. + * + * @private + * @param {Function} func The function to restrict. + * @returns {Function} Returns the new shortable function. + */ + function shortOut(func) { + var count = 0, + lastCalled = 0; + + return function() { + var stamp = nativeNow(), + remaining = HOT_SPAN - (stamp - lastCalled); + + lastCalled = stamp; + if (remaining > 0) { + if (++count >= HOT_COUNT) { + return arguments[0]; + } + } else { + count = 0; + } + return func.apply(undefined, arguments); + }; + } + + module.exports = shortOut; + + +/***/ }), +/* 166 */ +/***/ (function(module, exports, __webpack_require__) { + + var isArrayLike = __webpack_require__(89), + isObjectLike = __webpack_require__(104); + + /** + * This method is like `_.isArrayLike` except that it also checks if `value` + * is an object. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an array-like object, + * else `false`. + * @example + * + * _.isArrayLikeObject([1, 2, 3]); + * // => true + * + * _.isArrayLikeObject(document.body.children); + * // => true + * + * _.isArrayLikeObject('abc'); + * // => false + * + * _.isArrayLikeObject(_.noop); + * // => false + */ + function isArrayLikeObject(value) { + return isObjectLike(value) && isArrayLike(value); + } + + module.exports = isArrayLikeObject; + + +/***/ }), +/* 167 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseDifference = __webpack_require__(115), + baseFlatten = __webpack_require__(108), + baseIteratee = __webpack_require__(168), + baseRest = __webpack_require__(157), + isArrayLikeObject = __webpack_require__(166), + last = __webpack_require__(228); + + /** + * This method is like `_.difference` except that it accepts `iteratee` which + * is invoked for each element of `array` and `values` to generate the criterion + * by which they're compared. The order and references of result values are + * determined by the first array. The iteratee is invoked with one argument: + * (value). + * + * **Note:** Unlike `_.pullAllBy`, this method returns a new array. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {...Array} [values] The values to exclude. + * @param {Function} [iteratee=_.identity] The iteratee invoked per element. + * @returns {Array} Returns the new array of filtered values. + * @example + * + * _.differenceBy([2.1, 1.2], [2.3, 3.4], Math.floor); + * // => [1.2] + * + * // The `_.property` iteratee shorthand. + * _.differenceBy([{ 'x': 2 }, { 'x': 1 }], [{ 'x': 1 }], 'x'); + * // => [{ 'x': 2 }] + */ + var differenceBy = baseRest(function(array, values) { + var iteratee = last(values); + if (isArrayLikeObject(iteratee)) { + iteratee = undefined; + } + return isArrayLikeObject(array) + ? baseDifference(array, baseFlatten(values, 1, isArrayLikeObject, true), baseIteratee(iteratee, 2)) + : []; + }); + + module.exports = differenceBy; + + +/***/ }), +/* 168 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseMatches = __webpack_require__(169), + baseMatchesProperty = __webpack_require__(211), + identity = __webpack_require__(158), + isArray = __webpack_require__(112), + property = __webpack_require__(225); + + /** + * The base implementation of `_.iteratee`. + * + * @private + * @param {*} [value=_.identity] The value to convert to an iteratee. + * @returns {Function} Returns the iteratee. + */ + function baseIteratee(value) { + // Don't store the `typeof` result in a variable to avoid a JIT bug in Safari 9. + // See https://bugs.webkit.org/show_bug.cgi?id=156034 for more details. + if (typeof value == 'function') { + return value; + } + if (value == null) { + return identity; + } + if (typeof value == 'object') { + return isArray(value) + ? baseMatchesProperty(value[0], value[1]) + : baseMatches(value); + } + return property(value); + } + + module.exports = baseIteratee; + + +/***/ }), +/* 169 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIsMatch = __webpack_require__(170), + getMatchData = __webpack_require__(208), + matchesStrictComparable = __webpack_require__(210); + + /** + * The base implementation of `_.matches` which doesn't clone `source`. + * + * @private + * @param {Object} source The object of property values to match. + * @returns {Function} Returns the new spec function. + */ + function baseMatches(source) { + var matchData = getMatchData(source); + if (matchData.length == 1 && matchData[0][2]) { + return matchesStrictComparable(matchData[0][0], matchData[0][1]); + } + return function(object) { + return object === source || baseIsMatch(object, source, matchData); + }; + } + + module.exports = baseMatches; + + +/***/ }), +/* 170 */ +/***/ (function(module, exports, __webpack_require__) { + + var Stack = __webpack_require__(171), + baseIsEqual = __webpack_require__(177); + + /** Used to compose bitmasks for value comparisons. */ + var COMPARE_PARTIAL_FLAG = 1, + COMPARE_UNORDERED_FLAG = 2; + + /** + * The base implementation of `_.isMatch` without support for iteratee shorthands. + * + * @private + * @param {Object} object The object to inspect. + * @param {Object} source The object of property values to match. + * @param {Array} matchData The property names, values, and compare flags to match. + * @param {Function} [customizer] The function to customize comparisons. + * @returns {boolean} Returns `true` if `object` is a match, else `false`. + */ + function baseIsMatch(object, source, matchData, customizer) { + var index = matchData.length, + length = index, + noCustomizer = !customizer; + + if (object == null) { + return !length; + } + object = Object(object); + while (index--) { + var data = matchData[index]; + if ((noCustomizer && data[2]) + ? data[1] !== object[data[0]] + : !(data[0] in object) + ) { + return false; + } + } + while (++index < length) { + data = matchData[index]; + var key = data[0], + objValue = object[key], + srcValue = data[1]; + + if (noCustomizer && data[2]) { + if (objValue === undefined && !(key in object)) { + return false; + } + } else { + var stack = new Stack; + if (customizer) { + var result = customizer(objValue, srcValue, key, object, source, stack); + } + if (!(result === undefined + ? baseIsEqual(srcValue, objValue, COMPARE_PARTIAL_FLAG | COMPARE_UNORDERED_FLAG, customizer, stack) + : result + )) { + return false; + } + } + } + return true; + } + + module.exports = baseIsMatch; + + +/***/ }), +/* 171 */ +/***/ (function(module, exports, __webpack_require__) { + + var ListCache = __webpack_require__(132), + stackClear = __webpack_require__(172), + stackDelete = __webpack_require__(173), + stackGet = __webpack_require__(174), + stackHas = __webpack_require__(175), + stackSet = __webpack_require__(176); + + /** + * Creates a stack cache object to store key-value pairs. + * + * @private + * @constructor + * @param {Array} [entries] The key-value pairs to cache. + */ + function Stack(entries) { + var data = this.__data__ = new ListCache(entries); + this.size = data.size; + } + + // Add methods to `Stack`. + Stack.prototype.clear = stackClear; + Stack.prototype['delete'] = stackDelete; + Stack.prototype.get = stackGet; + Stack.prototype.has = stackHas; + Stack.prototype.set = stackSet; + + module.exports = Stack; + + +/***/ }), +/* 172 */ +/***/ (function(module, exports, __webpack_require__) { + + var ListCache = __webpack_require__(132); + + /** + * Removes all key-value entries from the stack. + * + * @private + * @name clear + * @memberOf Stack + */ + function stackClear() { + this.__data__ = new ListCache; + this.size = 0; + } + + module.exports = stackClear; + + +/***/ }), +/* 173 */ +/***/ (function(module, exports) { + + /** + * Removes `key` and its value from the stack. + * + * @private + * @name delete + * @memberOf Stack + * @param {string} key The key of the value to remove. + * @returns {boolean} Returns `true` if the entry was removed, else `false`. + */ + function stackDelete(key) { + var data = this.__data__, + result = data['delete'](key); + + this.size = data.size; + return result; + } + + module.exports = stackDelete; + + +/***/ }), +/* 174 */ +/***/ (function(module, exports) { + + /** + * Gets the stack value for `key`. + * + * @private + * @name get + * @memberOf Stack + * @param {string} key The key of the value to get. + * @returns {*} Returns the entry value. + */ + function stackGet(key) { + return this.__data__.get(key); + } + + module.exports = stackGet; + + +/***/ }), +/* 175 */ +/***/ (function(module, exports) { + + /** + * Checks if a stack value for `key` exists. + * + * @private + * @name has + * @memberOf Stack + * @param {string} key The key of the entry to check. + * @returns {boolean} Returns `true` if an entry for `key` exists, else `false`. + */ + function stackHas(key) { + return this.__data__.has(key); + } + + module.exports = stackHas; + + +/***/ }), +/* 176 */ +/***/ (function(module, exports, __webpack_require__) { + + var ListCache = __webpack_require__(132), + Map = __webpack_require__(139), + MapCache = __webpack_require__(117); + + /** Used as the size to enable large array optimizations. */ + var LARGE_ARRAY_SIZE = 200; + + /** + * Sets the stack `key` to `value`. + * + * @private + * @name set + * @memberOf Stack + * @param {string} key The key of the value to set. + * @param {*} value The value to set. + * @returns {Object} Returns the stack cache instance. + */ + function stackSet(key, value) { + var data = this.__data__; + if (data instanceof ListCache) { + var pairs = data.__data__; + if (!Map || (pairs.length < LARGE_ARRAY_SIZE - 1)) { + pairs.push([key, value]); + this.size = ++data.size; + return this; + } + data = this.__data__ = new MapCache(pairs); + } + data.set(key, value); + this.size = data.size; + return this; + } + + module.exports = stackSet; + + +/***/ }), +/* 177 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIsEqualDeep = __webpack_require__(178), + isObjectLike = __webpack_require__(104); + + /** + * The base implementation of `_.isEqual` which supports partial comparisons + * and tracks traversed objects. + * + * @private + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @param {boolean} bitmask The bitmask flags. + * 1 - Unordered comparison + * 2 - Partial comparison + * @param {Function} [customizer] The function to customize comparisons. + * @param {Object} [stack] Tracks traversed `value` and `other` objects. + * @returns {boolean} Returns `true` if the values are equivalent, else `false`. + */ + function baseIsEqual(value, other, bitmask, customizer, stack) { + if (value === other) { + return true; + } + if (value == null || other == null || (!isObjectLike(value) && !isObjectLike(other))) { + return value !== value && other !== other; + } + return baseIsEqualDeep(value, other, bitmask, customizer, baseIsEqual, stack); + } + + module.exports = baseIsEqual; + + +/***/ }), +/* 178 */ +/***/ (function(module, exports, __webpack_require__) { + + var Stack = __webpack_require__(171), + equalArrays = __webpack_require__(179), + equalByTag = __webpack_require__(181), + equalObjects = __webpack_require__(185), + getTag = __webpack_require__(203), + isArray = __webpack_require__(112), + isBuffer = __webpack_require__(194), + isTypedArray = __webpack_require__(196); + + /** Used to compose bitmasks for value comparisons. */ + var COMPARE_PARTIAL_FLAG = 1; + + /** `Object#toString` result references. */ + var argsTag = '[object Arguments]', + arrayTag = '[object Array]', + objectTag = '[object Object]'; + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * A specialized version of `baseIsEqual` for arrays and objects which performs + * deep comparisons and tracks traversed objects enabling objects with circular + * references to be compared. + * + * @private + * @param {Object} object The object to compare. + * @param {Object} other The other object to compare. + * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. + * @param {Function} customizer The function to customize comparisons. + * @param {Function} equalFunc The function to determine equivalents of values. + * @param {Object} [stack] Tracks traversed `object` and `other` objects. + * @returns {boolean} Returns `true` if the objects are equivalent, else `false`. + */ + function baseIsEqualDeep(object, other, bitmask, customizer, equalFunc, stack) { + var objIsArr = isArray(object), + othIsArr = isArray(other), + objTag = objIsArr ? arrayTag : getTag(object), + othTag = othIsArr ? arrayTag : getTag(other); + + objTag = objTag == argsTag ? objectTag : objTag; + othTag = othTag == argsTag ? objectTag : othTag; + + var objIsObj = objTag == objectTag, + othIsObj = othTag == objectTag, + isSameTag = objTag == othTag; + + if (isSameTag && isBuffer(object)) { + if (!isBuffer(other)) { + return false; + } + objIsArr = true; + objIsObj = false; + } + if (isSameTag && !objIsObj) { + stack || (stack = new Stack); + return (objIsArr || isTypedArray(object)) + ? equalArrays(object, other, bitmask, customizer, equalFunc, stack) + : equalByTag(object, other, objTag, bitmask, customizer, equalFunc, stack); + } + if (!(bitmask & COMPARE_PARTIAL_FLAG)) { + var objIsWrapped = objIsObj && hasOwnProperty.call(object, '__wrapped__'), + othIsWrapped = othIsObj && hasOwnProperty.call(other, '__wrapped__'); + + if (objIsWrapped || othIsWrapped) { + var objUnwrapped = objIsWrapped ? object.value() : object, + othUnwrapped = othIsWrapped ? other.value() : other; + + stack || (stack = new Stack); + return equalFunc(objUnwrapped, othUnwrapped, bitmask, customizer, stack); + } + } + if (!isSameTag) { + return false; + } + stack || (stack = new Stack); + return equalObjects(object, other, bitmask, customizer, equalFunc, stack); + } + + module.exports = baseIsEqualDeep; + + +/***/ }), +/* 179 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetCache = __webpack_require__(116), + arraySome = __webpack_require__(180), + cacheHas = __webpack_require__(156); + + /** Used to compose bitmasks for value comparisons. */ + var COMPARE_PARTIAL_FLAG = 1, + COMPARE_UNORDERED_FLAG = 2; + + /** + * A specialized version of `baseIsEqualDeep` for arrays with support for + * partial deep comparisons. + * + * @private + * @param {Array} array The array to compare. + * @param {Array} other The other array to compare. + * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. + * @param {Function} customizer The function to customize comparisons. + * @param {Function} equalFunc The function to determine equivalents of values. + * @param {Object} stack Tracks traversed `array` and `other` objects. + * @returns {boolean} Returns `true` if the arrays are equivalent, else `false`. + */ + function equalArrays(array, other, bitmask, customizer, equalFunc, stack) { + var isPartial = bitmask & COMPARE_PARTIAL_FLAG, + arrLength = array.length, + othLength = other.length; + + if (arrLength != othLength && !(isPartial && othLength > arrLength)) { + return false; + } + // Assume cyclic values are equal. + var stacked = stack.get(array); + if (stacked && stack.get(other)) { + return stacked == other; + } + var index = -1, + result = true, + seen = (bitmask & COMPARE_UNORDERED_FLAG) ? new SetCache : undefined; + + stack.set(array, other); + stack.set(other, array); + + // Ignore non-index properties. + while (++index < arrLength) { + var arrValue = array[index], + othValue = other[index]; + + if (customizer) { + var compared = isPartial + ? customizer(othValue, arrValue, index, other, array, stack) + : customizer(arrValue, othValue, index, array, other, stack); + } + if (compared !== undefined) { + if (compared) { + continue; + } + result = false; + break; + } + // Recursively compare arrays (susceptible to call stack limits). + if (seen) { + if (!arraySome(other, function(othValue, othIndex) { + if (!cacheHas(seen, othIndex) && + (arrValue === othValue || equalFunc(arrValue, othValue, bitmask, customizer, stack))) { + return seen.push(othIndex); + } + })) { + result = false; + break; + } + } else if (!( + arrValue === othValue || + equalFunc(arrValue, othValue, bitmask, customizer, stack) + )) { + result = false; + break; + } + } + stack['delete'](array); + stack['delete'](other); + return result; + } + + module.exports = equalArrays; + + +/***/ }), +/* 180 */ +/***/ (function(module, exports) { + + /** + * A specialized version of `_.some` for arrays without support for iteratee + * shorthands. + * + * @private + * @param {Array} [array] The array to iterate over. + * @param {Function} predicate The function invoked per iteration. + * @returns {boolean} Returns `true` if any element passes the predicate check, + * else `false`. + */ + function arraySome(array, predicate) { + var index = -1, + length = array == null ? 0 : array.length; + + while (++index < length) { + if (predicate(array[index], index, array)) { + return true; + } + } + return false; + } + + module.exports = arraySome; + + +/***/ }), +/* 181 */ +/***/ (function(module, exports, __webpack_require__) { + + var Symbol = __webpack_require__(92), + Uint8Array = __webpack_require__(182), + eq = __webpack_require__(88), + equalArrays = __webpack_require__(179), + mapToArray = __webpack_require__(183), + setToArray = __webpack_require__(184); + + /** Used to compose bitmasks for value comparisons. */ + var COMPARE_PARTIAL_FLAG = 1, + COMPARE_UNORDERED_FLAG = 2; + + /** `Object#toString` result references. */ + var boolTag = '[object Boolean]', + dateTag = '[object Date]', + errorTag = '[object Error]', + mapTag = '[object Map]', + numberTag = '[object Number]', + regexpTag = '[object RegExp]', + setTag = '[object Set]', + stringTag = '[object String]', + symbolTag = '[object Symbol]'; + + var arrayBufferTag = '[object ArrayBuffer]', + dataViewTag = '[object DataView]'; + + /** Used to convert symbols to primitives and strings. */ + var symbolProto = Symbol ? Symbol.prototype : undefined, + symbolValueOf = symbolProto ? symbolProto.valueOf : undefined; + + /** + * A specialized version of `baseIsEqualDeep` for comparing objects of + * the same `toStringTag`. + * + * **Note:** This function only supports comparing values with tags of + * `Boolean`, `Date`, `Error`, `Number`, `RegExp`, or `String`. + * + * @private + * @param {Object} object The object to compare. + * @param {Object} other The other object to compare. + * @param {string} tag The `toStringTag` of the objects to compare. + * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. + * @param {Function} customizer The function to customize comparisons. + * @param {Function} equalFunc The function to determine equivalents of values. + * @param {Object} stack Tracks traversed `object` and `other` objects. + * @returns {boolean} Returns `true` if the objects are equivalent, else `false`. + */ + function equalByTag(object, other, tag, bitmask, customizer, equalFunc, stack) { + switch (tag) { + case dataViewTag: + if ((object.byteLength != other.byteLength) || + (object.byteOffset != other.byteOffset)) { + return false; + } + object = object.buffer; + other = other.buffer; + + case arrayBufferTag: + if ((object.byteLength != other.byteLength) || + !equalFunc(new Uint8Array(object), new Uint8Array(other))) { + return false; + } + return true; + + case boolTag: + case dateTag: + case numberTag: + // Coerce booleans to `1` or `0` and dates to milliseconds. + // Invalid dates are coerced to `NaN`. + return eq(+object, +other); + + case errorTag: + return object.name == other.name && object.message == other.message; + + case regexpTag: + case stringTag: + // Coerce regexes to strings and treat strings, primitives and objects, + // as equal. See http://www.ecma-international.org/ecma-262/7.0/#sec-regexp.prototype.tostring + // for more details. + return object == (other + ''); + + case mapTag: + var convert = mapToArray; + + case setTag: + var isPartial = bitmask & COMPARE_PARTIAL_FLAG; + convert || (convert = setToArray); + + if (object.size != other.size && !isPartial) { + return false; + } + // Assume cyclic values are equal. + var stacked = stack.get(object); + if (stacked) { + return stacked == other; + } + bitmask |= COMPARE_UNORDERED_FLAG; + + // Recursively compare objects (susceptible to call stack limits). + stack.set(object, other); + var result = equalArrays(convert(object), convert(other), bitmask, customizer, equalFunc, stack); + stack['delete'](object); + return result; + + case symbolTag: + if (symbolValueOf) { + return symbolValueOf.call(object) == symbolValueOf.call(other); + } + } + return false; + } + + module.exports = equalByTag; + + +/***/ }), +/* 182 */ +/***/ (function(module, exports, __webpack_require__) { + + var root = __webpack_require__(93); + + /** Built-in value references. */ + var Uint8Array = root.Uint8Array; + + module.exports = Uint8Array; + + +/***/ }), +/* 183 */ +/***/ (function(module, exports) { + + /** + * Converts `map` to its key-value pairs. + * + * @private + * @param {Object} map The map to convert. + * @returns {Array} Returns the key-value pairs. + */ + function mapToArray(map) { + var index = -1, + result = Array(map.size); + + map.forEach(function(value, key) { + result[++index] = [key, value]; + }); + return result; + } + + module.exports = mapToArray; + + +/***/ }), +/* 184 */ +/***/ (function(module, exports) { + + /** + * Converts `set` to an array of its values. + * + * @private + * @param {Object} set The set to convert. + * @returns {Array} Returns the values. + */ + function setToArray(set) { + var index = -1, + result = Array(set.size); + + set.forEach(function(value) { + result[++index] = value; + }); + return result; + } + + module.exports = setToArray; + + +/***/ }), +/* 185 */ +/***/ (function(module, exports, __webpack_require__) { + + var getAllKeys = __webpack_require__(186); + + /** Used to compose bitmasks for value comparisons. */ + var COMPARE_PARTIAL_FLAG = 1; + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * A specialized version of `baseIsEqualDeep` for objects with support for + * partial deep comparisons. + * + * @private + * @param {Object} object The object to compare. + * @param {Object} other The other object to compare. + * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. + * @param {Function} customizer The function to customize comparisons. + * @param {Function} equalFunc The function to determine equivalents of values. + * @param {Object} stack Tracks traversed `object` and `other` objects. + * @returns {boolean} Returns `true` if the objects are equivalent, else `false`. + */ + function equalObjects(object, other, bitmask, customizer, equalFunc, stack) { + var isPartial = bitmask & COMPARE_PARTIAL_FLAG, + objProps = getAllKeys(object), + objLength = objProps.length, + othProps = getAllKeys(other), + othLength = othProps.length; + + if (objLength != othLength && !isPartial) { + return false; + } + var index = objLength; + while (index--) { + var key = objProps[index]; + if (!(isPartial ? key in other : hasOwnProperty.call(other, key))) { + return false; + } + } + // Assume cyclic values are equal. + var stacked = stack.get(object); + if (stacked && stack.get(other)) { + return stacked == other; + } + var result = true; + stack.set(object, other); + stack.set(other, object); + + var skipCtor = isPartial; + while (++index < objLength) { + key = objProps[index]; + var objValue = object[key], + othValue = other[key]; + + if (customizer) { + var compared = isPartial + ? customizer(othValue, objValue, key, other, object, stack) + : customizer(objValue, othValue, key, object, other, stack); + } + // Recursively compare objects (susceptible to call stack limits). + if (!(compared === undefined + ? (objValue === othValue || equalFunc(objValue, othValue, bitmask, customizer, stack)) + : compared + )) { + result = false; + break; + } + skipCtor || (skipCtor = key == 'constructor'); + } + if (result && !skipCtor) { + var objCtor = object.constructor, + othCtor = other.constructor; + + // Non `Object` object instances with different constructors are not equal. + if (objCtor != othCtor && + ('constructor' in object && 'constructor' in other) && + !(typeof objCtor == 'function' && objCtor instanceof objCtor && + typeof othCtor == 'function' && othCtor instanceof othCtor)) { + result = false; + } + } + stack['delete'](object); + stack['delete'](other); + return result; + } + + module.exports = equalObjects; + + +/***/ }), +/* 186 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseGetAllKeys = __webpack_require__(187), + getSymbols = __webpack_require__(188), + keys = __webpack_require__(191); + + /** + * Creates an array of own enumerable property names and symbols of `object`. + * + * @private + * @param {Object} object The object to query. + * @returns {Array} Returns the array of property names and symbols. + */ + function getAllKeys(object) { + return baseGetAllKeys(object, keys, getSymbols); + } + + module.exports = getAllKeys; + + +/***/ }), +/* 187 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayPush = __webpack_require__(107), + isArray = __webpack_require__(112); + + /** + * The base implementation of `getAllKeys` and `getAllKeysIn` which uses + * `keysFunc` and `symbolsFunc` to get the enumerable property names and + * symbols of `object`. + * + * @private + * @param {Object} object The object to query. + * @param {Function} keysFunc The function to get the keys of `object`. + * @param {Function} symbolsFunc The function to get the symbols of `object`. + * @returns {Array} Returns the array of property names and symbols. + */ + function baseGetAllKeys(object, keysFunc, symbolsFunc) { + var result = keysFunc(object); + return isArray(object) ? result : arrayPush(result, symbolsFunc(object)); + } + + module.exports = baseGetAllKeys; + + +/***/ }), +/* 188 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayFilter = __webpack_require__(189), + stubArray = __webpack_require__(190); + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Built-in value references. */ + var propertyIsEnumerable = objectProto.propertyIsEnumerable; + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeGetSymbols = Object.getOwnPropertySymbols; + + /** + * Creates an array of the own enumerable symbols of `object`. + * + * @private + * @param {Object} object The object to query. + * @returns {Array} Returns the array of symbols. + */ + var getSymbols = !nativeGetSymbols ? stubArray : function(object) { + if (object == null) { + return []; + } + object = Object(object); + return arrayFilter(nativeGetSymbols(object), function(symbol) { + return propertyIsEnumerable.call(object, symbol); + }); + }; + + module.exports = getSymbols; + + +/***/ }), +/* 189 */ +/***/ (function(module, exports) { + + /** + * A specialized version of `_.filter` for arrays without support for + * iteratee shorthands. + * + * @private + * @param {Array} [array] The array to iterate over. + * @param {Function} predicate The function invoked per iteration. + * @returns {Array} Returns the new filtered array. + */ + function arrayFilter(array, predicate) { + var index = -1, + length = array == null ? 0 : array.length, + resIndex = 0, + result = []; + + while (++index < length) { + var value = array[index]; + if (predicate(value, index, array)) { + result[resIndex++] = value; + } + } + return result; + } + + module.exports = arrayFilter; + + +/***/ }), +/* 190 */ +/***/ (function(module, exports) { + + /** + * This method returns a new empty array. + * + * @static + * @memberOf _ + * @since 4.13.0 + * @category Util + * @returns {Array} Returns the new empty array. + * @example + * + * var arrays = _.times(2, _.stubArray); + * + * console.log(arrays); + * // => [[], []] + * + * console.log(arrays[0] === arrays[1]); + * // => false + */ + function stubArray() { + return []; + } + + module.exports = stubArray; + + +/***/ }), +/* 191 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayLikeKeys = __webpack_require__(192), + baseKeys = __webpack_require__(199), + isArrayLike = __webpack_require__(89); + + /** + * Creates an array of the own enumerable property names of `object`. + * + * **Note:** Non-object values are coerced to objects. See the + * [ES spec](http://ecma-international.org/ecma-262/7.0/#sec-object.keys) + * for more details. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Object + * @param {Object} object The object to query. + * @returns {Array} Returns the array of property names. + * @example + * + * function Foo() { + * this.a = 1; + * this.b = 2; + * } + * + * Foo.prototype.c = 3; + * + * _.keys(new Foo); + * // => ['a', 'b'] (iteration order is not guaranteed) + * + * _.keys('hi'); + * // => ['0', '1'] + */ + function keys(object) { + return isArrayLike(object) ? arrayLikeKeys(object) : baseKeys(object); + } + + module.exports = keys; + + +/***/ }), +/* 192 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseTimes = __webpack_require__(193), + isArguments = __webpack_require__(110), + isArray = __webpack_require__(112), + isBuffer = __webpack_require__(194), + isIndex = __webpack_require__(99), + isTypedArray = __webpack_require__(196); + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * Creates an array of the enumerable property names of the array-like `value`. + * + * @private + * @param {*} value The value to query. + * @param {boolean} inherited Specify returning inherited property names. + * @returns {Array} Returns the array of property names. + */ + function arrayLikeKeys(value, inherited) { + var isArr = isArray(value), + isArg = !isArr && isArguments(value), + isBuff = !isArr && !isArg && isBuffer(value), + isType = !isArr && !isArg && !isBuff && isTypedArray(value), + skipIndexes = isArr || isArg || isBuff || isType, + result = skipIndexes ? baseTimes(value.length, String) : [], + length = result.length; + + for (var key in value) { + if ((inherited || hasOwnProperty.call(value, key)) && + !(skipIndexes && ( + // Safari 9 has enumerable `arguments.length` in strict mode. + key == 'length' || + // Node.js 0.10 has enumerable non-index properties on buffers. + (isBuff && (key == 'offset' || key == 'parent')) || + // PhantomJS 2 has enumerable non-index properties on typed arrays. + (isType && (key == 'buffer' || key == 'byteLength' || key == 'byteOffset')) || + // Skip index properties. + isIndex(key, length) + ))) { + result.push(key); + } + } + return result; + } + + module.exports = arrayLikeKeys; + + +/***/ }), +/* 193 */ +/***/ (function(module, exports) { + + /** + * The base implementation of `_.times` without support for iteratee shorthands + * or max array length checks. + * + * @private + * @param {number} n The number of times to invoke `iteratee`. + * @param {Function} iteratee The function invoked per iteration. + * @returns {Array} Returns the array of results. + */ + function baseTimes(n, iteratee) { + var index = -1, + result = Array(n); + + while (++index < n) { + result[index] = iteratee(index); + } + return result; + } + + module.exports = baseTimes; + + +/***/ }), +/* 194 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(module) {var root = __webpack_require__(93), + stubFalse = __webpack_require__(195); + + /** Detect free variable `exports`. */ + var freeExports = typeof exports == 'object' && exports && !exports.nodeType && exports; + + /** Detect free variable `module`. */ + var freeModule = freeExports && typeof module == 'object' && module && !module.nodeType && module; + + /** Detect the popular CommonJS extension `module.exports`. */ + var moduleExports = freeModule && freeModule.exports === freeExports; + + /** Built-in value references. */ + var Buffer = moduleExports ? root.Buffer : undefined; + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeIsBuffer = Buffer ? Buffer.isBuffer : undefined; + + /** + * Checks if `value` is a buffer. + * + * @static + * @memberOf _ + * @since 4.3.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a buffer, else `false`. + * @example + * + * _.isBuffer(new Buffer(2)); + * // => true + * + * _.isBuffer(new Uint8Array(2)); + * // => false + */ + var isBuffer = nativeIsBuffer || stubFalse; + + module.exports = isBuffer; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(59)(module))) + +/***/ }), +/* 195 */ +/***/ (function(module, exports) { + + /** + * This method returns `false`. + * + * @static + * @memberOf _ + * @since 4.13.0 + * @category Util + * @returns {boolean} Returns `false`. + * @example + * + * _.times(2, _.stubFalse); + * // => [false, false] + */ + function stubFalse() { + return false; + } + + module.exports = stubFalse; + + +/***/ }), +/* 196 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIsTypedArray = __webpack_require__(197), + baseUnary = __webpack_require__(155), + nodeUtil = __webpack_require__(198); + + /* Node.js helper references. */ + var nodeIsTypedArray = nodeUtil && nodeUtil.isTypedArray; + + /** + * Checks if `value` is classified as a typed array. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a typed array, else `false`. + * @example + * + * _.isTypedArray(new Uint8Array); + * // => true + * + * _.isTypedArray([]); + * // => false + */ + var isTypedArray = nodeIsTypedArray ? baseUnary(nodeIsTypedArray) : baseIsTypedArray; + + module.exports = isTypedArray; + + +/***/ }), +/* 197 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseGetTag = __webpack_require__(91), + isLength = __webpack_require__(98), + isObjectLike = __webpack_require__(104); + + /** `Object#toString` result references. */ + var argsTag = '[object Arguments]', + arrayTag = '[object Array]', + boolTag = '[object Boolean]', + dateTag = '[object Date]', + errorTag = '[object Error]', + funcTag = '[object Function]', + mapTag = '[object Map]', + numberTag = '[object Number]', + objectTag = '[object Object]', + regexpTag = '[object RegExp]', + setTag = '[object Set]', + stringTag = '[object String]', + weakMapTag = '[object WeakMap]'; + + var arrayBufferTag = '[object ArrayBuffer]', + dataViewTag = '[object DataView]', + float32Tag = '[object Float32Array]', + float64Tag = '[object Float64Array]', + int8Tag = '[object Int8Array]', + int16Tag = '[object Int16Array]', + int32Tag = '[object Int32Array]', + uint8Tag = '[object Uint8Array]', + uint8ClampedTag = '[object Uint8ClampedArray]', + uint16Tag = '[object Uint16Array]', + uint32Tag = '[object Uint32Array]'; + + /** Used to identify `toStringTag` values of typed arrays. */ + var typedArrayTags = {}; + typedArrayTags[float32Tag] = typedArrayTags[float64Tag] = + typedArrayTags[int8Tag] = typedArrayTags[int16Tag] = + typedArrayTags[int32Tag] = typedArrayTags[uint8Tag] = + typedArrayTags[uint8ClampedTag] = typedArrayTags[uint16Tag] = + typedArrayTags[uint32Tag] = true; + typedArrayTags[argsTag] = typedArrayTags[arrayTag] = + typedArrayTags[arrayBufferTag] = typedArrayTags[boolTag] = + typedArrayTags[dataViewTag] = typedArrayTags[dateTag] = + typedArrayTags[errorTag] = typedArrayTags[funcTag] = + typedArrayTags[mapTag] = typedArrayTags[numberTag] = + typedArrayTags[objectTag] = typedArrayTags[regexpTag] = + typedArrayTags[setTag] = typedArrayTags[stringTag] = + typedArrayTags[weakMapTag] = false; + + /** + * The base implementation of `_.isTypedArray` without Node.js optimizations. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a typed array, else `false`. + */ + function baseIsTypedArray(value) { + return isObjectLike(value) && + isLength(value.length) && !!typedArrayTags[baseGetTag(value)]; + } + + module.exports = baseIsTypedArray; + + +/***/ }), +/* 198 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(module) {var freeGlobal = __webpack_require__(94); + + /** Detect free variable `exports`. */ + var freeExports = typeof exports == 'object' && exports && !exports.nodeType && exports; + + /** Detect free variable `module`. */ + var freeModule = freeExports && typeof module == 'object' && module && !module.nodeType && module; + + /** Detect the popular CommonJS extension `module.exports`. */ + var moduleExports = freeModule && freeModule.exports === freeExports; + + /** Detect free variable `process` from Node.js. */ + var freeProcess = moduleExports && freeGlobal.process; + + /** Used to access faster Node.js helpers. */ + var nodeUtil = (function() { + try { + // Use `util.types` for Node.js 10+. + var types = freeModule && freeModule.require && freeModule.require('util').types; + + if (types) { + return types; + } + + // Legacy `process.binding('util')` for Node.js < 10. + return freeProcess && freeProcess.binding && freeProcess.binding('util'); + } catch (e) {} + }()); + + module.exports = nodeUtil; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(59)(module))) + +/***/ }), +/* 199 */ +/***/ (function(module, exports, __webpack_require__) { + + var isPrototype = __webpack_require__(200), + nativeKeys = __webpack_require__(201); + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * The base implementation of `_.keys` which doesn't treat sparse arrays as dense. + * + * @private + * @param {Object} object The object to query. + * @returns {Array} Returns the array of property names. + */ + function baseKeys(object) { + if (!isPrototype(object)) { + return nativeKeys(object); + } + var result = []; + for (var key in Object(object)) { + if (hasOwnProperty.call(object, key) && key != 'constructor') { + result.push(key); + } + } + return result; + } + + module.exports = baseKeys; + + +/***/ }), +/* 200 */ +/***/ (function(module, exports) { + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** + * Checks if `value` is likely a prototype object. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a prototype, else `false`. + */ + function isPrototype(value) { + var Ctor = value && value.constructor, + proto = (typeof Ctor == 'function' && Ctor.prototype) || objectProto; + + return value === proto; + } + + module.exports = isPrototype; + + +/***/ }), +/* 201 */ +/***/ (function(module, exports, __webpack_require__) { + + var overArg = __webpack_require__(202); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeKeys = overArg(Object.keys, Object); + + module.exports = nativeKeys; + + +/***/ }), +/* 202 */ +/***/ (function(module, exports) { + + /** + * Creates a unary function that invokes `func` with its argument transformed. + * + * @private + * @param {Function} func The function to wrap. + * @param {Function} transform The argument transform. + * @returns {Function} Returns the new function. + */ + function overArg(func, transform) { + return function(arg) { + return func(transform(arg)); + }; + } + + module.exports = overArg; + + +/***/ }), +/* 203 */ +/***/ (function(module, exports, __webpack_require__) { + + var DataView = __webpack_require__(204), + Map = __webpack_require__(139), + Promise = __webpack_require__(205), + Set = __webpack_require__(206), + WeakMap = __webpack_require__(207), + baseGetTag = __webpack_require__(91), + toSource = __webpack_require__(126); + + /** `Object#toString` result references. */ + var mapTag = '[object Map]', + objectTag = '[object Object]', + promiseTag = '[object Promise]', + setTag = '[object Set]', + weakMapTag = '[object WeakMap]'; + + var dataViewTag = '[object DataView]'; + + /** Used to detect maps, sets, and weakmaps. */ + var dataViewCtorString = toSource(DataView), + mapCtorString = toSource(Map), + promiseCtorString = toSource(Promise), + setCtorString = toSource(Set), + weakMapCtorString = toSource(WeakMap); + + /** + * Gets the `toStringTag` of `value`. + * + * @private + * @param {*} value The value to query. + * @returns {string} Returns the `toStringTag`. + */ + var getTag = baseGetTag; + + // Fallback for data views, maps, sets, and weak maps in IE 11 and promises in Node.js < 6. + if ((DataView && getTag(new DataView(new ArrayBuffer(1))) != dataViewTag) || + (Map && getTag(new Map) != mapTag) || + (Promise && getTag(Promise.resolve()) != promiseTag) || + (Set && getTag(new Set) != setTag) || + (WeakMap && getTag(new WeakMap) != weakMapTag)) { + getTag = function(value) { + var result = baseGetTag(value), + Ctor = result == objectTag ? value.constructor : undefined, + ctorString = Ctor ? toSource(Ctor) : ''; + + if (ctorString) { + switch (ctorString) { + case dataViewCtorString: return dataViewTag; + case mapCtorString: return mapTag; + case promiseCtorString: return promiseTag; + case setCtorString: return setTag; + case weakMapCtorString: return weakMapTag; + } + } + return result; + }; + } + + module.exports = getTag; + + +/***/ }), +/* 204 */ +/***/ (function(module, exports, __webpack_require__) { + + var getNative = __webpack_require__(122), + root = __webpack_require__(93); + + /* Built-in method references that are verified to be native. */ + var DataView = getNative(root, 'DataView'); + + module.exports = DataView; + + +/***/ }), +/* 205 */ +/***/ (function(module, exports, __webpack_require__) { + + var getNative = __webpack_require__(122), + root = __webpack_require__(93); + + /* Built-in method references that are verified to be native. */ + var Promise = getNative(root, 'Promise'); + + module.exports = Promise; + + +/***/ }), +/* 206 */ +/***/ (function(module, exports, __webpack_require__) { + + var getNative = __webpack_require__(122), + root = __webpack_require__(93); + + /* Built-in method references that are verified to be native. */ + var Set = getNative(root, 'Set'); + + module.exports = Set; + + +/***/ }), +/* 207 */ +/***/ (function(module, exports, __webpack_require__) { + + var getNative = __webpack_require__(122), + root = __webpack_require__(93); + + /* Built-in method references that are verified to be native. */ + var WeakMap = getNative(root, 'WeakMap'); + + module.exports = WeakMap; + + +/***/ }), +/* 208 */ +/***/ (function(module, exports, __webpack_require__) { + + var isStrictComparable = __webpack_require__(209), + keys = __webpack_require__(191); + + /** + * Gets the property names, values, and compare flags of `object`. + * + * @private + * @param {Object} object The object to query. + * @returns {Array} Returns the match data of `object`. + */ + function getMatchData(object) { + var result = keys(object), + length = result.length; + + while (length--) { + var key = result[length], + value = object[key]; + + result[length] = [key, value, isStrictComparable(value)]; + } + return result; + } + + module.exports = getMatchData; + + +/***/ }), +/* 209 */ +/***/ (function(module, exports, __webpack_require__) { + + var isObject = __webpack_require__(97); + + /** + * Checks if `value` is suitable for strict equality comparisons, i.e. `===`. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` if suitable for strict + * equality comparisons, else `false`. + */ + function isStrictComparable(value) { + return value === value && !isObject(value); + } + + module.exports = isStrictComparable; + + +/***/ }), +/* 210 */ +/***/ (function(module, exports) { + + /** + * A specialized version of `matchesProperty` for source values suitable + * for strict equality comparisons, i.e. `===`. + * + * @private + * @param {string} key The key of the property to get. + * @param {*} srcValue The value to match. + * @returns {Function} Returns the new spec function. + */ + function matchesStrictComparable(key, srcValue) { + return function(object) { + if (object == null) { + return false; + } + return object[key] === srcValue && + (srcValue !== undefined || (key in Object(object))); + }; + } + + module.exports = matchesStrictComparable; + + +/***/ }), +/* 211 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIsEqual = __webpack_require__(177), + get = __webpack_require__(212), + hasIn = __webpack_require__(222), + isKey = __webpack_require__(215), + isStrictComparable = __webpack_require__(209), + matchesStrictComparable = __webpack_require__(210), + toKey = __webpack_require__(221); + + /** Used to compose bitmasks for value comparisons. */ + var COMPARE_PARTIAL_FLAG = 1, + COMPARE_UNORDERED_FLAG = 2; + + /** + * The base implementation of `_.matchesProperty` which doesn't clone `srcValue`. + * + * @private + * @param {string} path The path of the property to get. + * @param {*} srcValue The value to match. + * @returns {Function} Returns the new spec function. + */ + function baseMatchesProperty(path, srcValue) { + if (isKey(path) && isStrictComparable(srcValue)) { + return matchesStrictComparable(toKey(path), srcValue); + } + return function(object) { + var objValue = get(object, path); + return (objValue === undefined && objValue === srcValue) + ? hasIn(object, path) + : baseIsEqual(srcValue, objValue, COMPARE_PARTIAL_FLAG | COMPARE_UNORDERED_FLAG); + }; + } + + module.exports = baseMatchesProperty; + + +/***/ }), +/* 212 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseGet = __webpack_require__(213); + + /** + * Gets the value at `path` of `object`. If the resolved value is + * `undefined`, the `defaultValue` is returned in its place. + * + * @static + * @memberOf _ + * @since 3.7.0 + * @category Object + * @param {Object} object The object to query. + * @param {Array|string} path The path of the property to get. + * @param {*} [defaultValue] The value returned for `undefined` resolved values. + * @returns {*} Returns the resolved value. + * @example + * + * var object = { 'a': [{ 'b': { 'c': 3 } }] }; + * + * _.get(object, 'a[0].b.c'); + * // => 3 + * + * _.get(object, ['a', '0', 'b', 'c']); + * // => 3 + * + * _.get(object, 'a.b.c', 'default'); + * // => 'default' + */ + function get(object, path, defaultValue) { + var result = object == null ? undefined : baseGet(object, path); + return result === undefined ? defaultValue : result; + } + + module.exports = get; + + +/***/ }), +/* 213 */ +/***/ (function(module, exports, __webpack_require__) { + + var castPath = __webpack_require__(214), + toKey = __webpack_require__(221); + + /** + * The base implementation of `_.get` without support for default values. + * + * @private + * @param {Object} object The object to query. + * @param {Array|string} path The path of the property to get. + * @returns {*} Returns the resolved value. + */ + function baseGet(object, path) { + path = castPath(path, object); + + var index = 0, + length = path.length; + + while (object != null && index < length) { + object = object[toKey(path[index++])]; + } + return (index && index == length) ? object : undefined; + } + + module.exports = baseGet; + + +/***/ }), +/* 214 */ +/***/ (function(module, exports, __webpack_require__) { + + var isArray = __webpack_require__(112), + isKey = __webpack_require__(215), + stringToPath = __webpack_require__(216), + toString = __webpack_require__(219); + + /** + * Casts `value` to a path array if it's not one. + * + * @private + * @param {*} value The value to inspect. + * @param {Object} [object] The object to query keys on. + * @returns {Array} Returns the cast property path array. + */ + function castPath(value, object) { + if (isArray(value)) { + return value; + } + return isKey(value, object) ? [value] : stringToPath(toString(value)); + } + + module.exports = castPath; + + +/***/ }), +/* 215 */ +/***/ (function(module, exports, __webpack_require__) { + + var isArray = __webpack_require__(112), + isSymbol = __webpack_require__(103); + + /** Used to match property names within property paths. */ + var reIsDeepProp = /\.|\[(?:[^[\]]*|(["'])(?:(?!\1)[^\\]|\\.)*?\1)\]/, + reIsPlainProp = /^\w*$/; + + /** + * Checks if `value` is a property name and not a property path. + * + * @private + * @param {*} value The value to check. + * @param {Object} [object] The object to query keys on. + * @returns {boolean} Returns `true` if `value` is a property name, else `false`. + */ + function isKey(value, object) { + if (isArray(value)) { + return false; + } + var type = typeof value; + if (type == 'number' || type == 'symbol' || type == 'boolean' || + value == null || isSymbol(value)) { + return true; + } + return reIsPlainProp.test(value) || !reIsDeepProp.test(value) || + (object != null && value in Object(object)); + } + + module.exports = isKey; + + +/***/ }), +/* 216 */ +/***/ (function(module, exports, __webpack_require__) { + + var memoizeCapped = __webpack_require__(217); + + /** Used to match property names within property paths. */ + var rePropName = /[^.[\]]+|\[(?:(-?\d+(?:\.\d+)?)|(["'])((?:(?!\2)[^\\]|\\.)*?)\2)\]|(?=(?:\.|\[\])(?:\.|\[\]|$))/g; + + /** Used to match backslashes in property paths. */ + var reEscapeChar = /\\(\\)?/g; + + /** + * Converts `string` to a property path array. + * + * @private + * @param {string} string The string to convert. + * @returns {Array} Returns the property path array. + */ + var stringToPath = memoizeCapped(function(string) { + var result = []; + if (string.charCodeAt(0) === 46 /* . */) { + result.push(''); + } + string.replace(rePropName, function(match, number, quote, subString) { + result.push(quote ? subString.replace(reEscapeChar, '$1') : (number || match)); + }); + return result; + }); + + module.exports = stringToPath; + + +/***/ }), +/* 217 */ +/***/ (function(module, exports, __webpack_require__) { + + var memoize = __webpack_require__(218); + + /** Used as the maximum memoize cache size. */ + var MAX_MEMOIZE_SIZE = 500; + + /** + * A specialized version of `_.memoize` which clears the memoized function's + * cache when it exceeds `MAX_MEMOIZE_SIZE`. + * + * @private + * @param {Function} func The function to have its output memoized. + * @returns {Function} Returns the new memoized function. + */ + function memoizeCapped(func) { + var result = memoize(func, function(key) { + if (cache.size === MAX_MEMOIZE_SIZE) { + cache.clear(); + } + return key; + }); + + var cache = result.cache; + return result; + } + + module.exports = memoizeCapped; + + +/***/ }), +/* 218 */ +/***/ (function(module, exports, __webpack_require__) { + + var MapCache = __webpack_require__(117); + + /** Error message constants. */ + var FUNC_ERROR_TEXT = 'Expected a function'; + + /** + * Creates a function that memoizes the result of `func`. If `resolver` is + * provided, it determines the cache key for storing the result based on the + * arguments provided to the memoized function. By default, the first argument + * provided to the memoized function is used as the map cache key. The `func` + * is invoked with the `this` binding of the memoized function. + * + * **Note:** The cache is exposed as the `cache` property on the memoized + * function. Its creation may be customized by replacing the `_.memoize.Cache` + * constructor with one whose instances implement the + * [`Map`](http://ecma-international.org/ecma-262/7.0/#sec-properties-of-the-map-prototype-object) + * method interface of `clear`, `delete`, `get`, `has`, and `set`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Function + * @param {Function} func The function to have its output memoized. + * @param {Function} [resolver] The function to resolve the cache key. + * @returns {Function} Returns the new memoized function. + * @example + * + * var object = { 'a': 1, 'b': 2 }; + * var other = { 'c': 3, 'd': 4 }; + * + * var values = _.memoize(_.values); + * values(object); + * // => [1, 2] + * + * values(other); + * // => [3, 4] + * + * object.a = 2; + * values(object); + * // => [1, 2] + * + * // Modify the result cache. + * values.cache.set(object, ['a', 'b']); + * values(object); + * // => ['a', 'b'] + * + * // Replace `_.memoize.Cache`. + * _.memoize.Cache = WeakMap; + */ + function memoize(func, resolver) { + if (typeof func != 'function' || (resolver != null && typeof resolver != 'function')) { + throw new TypeError(FUNC_ERROR_TEXT); + } + var memoized = function() { + var args = arguments, + key = resolver ? resolver.apply(this, args) : args[0], + cache = memoized.cache; + + if (cache.has(key)) { + return cache.get(key); + } + var result = func.apply(this, args); + memoized.cache = cache.set(key, result) || cache; + return result; + }; + memoized.cache = new (memoize.Cache || MapCache); + return memoized; + } + + // Expose `MapCache`. + memoize.Cache = MapCache; + + module.exports = memoize; + + +/***/ }), +/* 219 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseToString = __webpack_require__(220); + + /** + * Converts `value` to a string. An empty string is returned for `null` + * and `undefined` values. The sign of `-0` is preserved. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to convert. + * @returns {string} Returns the converted string. + * @example + * + * _.toString(null); + * // => '' + * + * _.toString(-0); + * // => '-0' + * + * _.toString([1, 2, 3]); + * // => '1,2,3' + */ + function toString(value) { + return value == null ? '' : baseToString(value); + } + + module.exports = toString; + + +/***/ }), +/* 220 */ +/***/ (function(module, exports, __webpack_require__) { + + var Symbol = __webpack_require__(92), + arrayMap = __webpack_require__(154), + isArray = __webpack_require__(112), + isSymbol = __webpack_require__(103); + + /** Used as references for various `Number` constants. */ + var INFINITY = 1 / 0; + + /** Used to convert symbols to primitives and strings. */ + var symbolProto = Symbol ? Symbol.prototype : undefined, + symbolToString = symbolProto ? symbolProto.toString : undefined; + + /** + * The base implementation of `_.toString` which doesn't convert nullish + * values to empty strings. + * + * @private + * @param {*} value The value to process. + * @returns {string} Returns the string. + */ + function baseToString(value) { + // Exit early for strings to avoid a performance hit in some environments. + if (typeof value == 'string') { + return value; + } + if (isArray(value)) { + // Recursively convert values (susceptible to call stack limits). + return arrayMap(value, baseToString) + ''; + } + if (isSymbol(value)) { + return symbolToString ? symbolToString.call(value) : ''; + } + var result = (value + ''); + return (result == '0' && (1 / value) == -INFINITY) ? '-0' : result; + } + + module.exports = baseToString; + + +/***/ }), +/* 221 */ +/***/ (function(module, exports, __webpack_require__) { + + var isSymbol = __webpack_require__(103); + + /** Used as references for various `Number` constants. */ + var INFINITY = 1 / 0; + + /** + * Converts `value` to a string key if it's not a string or symbol. + * + * @private + * @param {*} value The value to inspect. + * @returns {string|symbol} Returns the key. + */ + function toKey(value) { + if (typeof value == 'string' || isSymbol(value)) { + return value; + } + var result = (value + ''); + return (result == '0' && (1 / value) == -INFINITY) ? '-0' : result; + } + + module.exports = toKey; + + +/***/ }), +/* 222 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseHasIn = __webpack_require__(223), + hasPath = __webpack_require__(224); + + /** + * Checks if `path` is a direct or inherited property of `object`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Object + * @param {Object} object The object to query. + * @param {Array|string} path The path to check. + * @returns {boolean} Returns `true` if `path` exists, else `false`. + * @example + * + * var object = _.create({ 'a': _.create({ 'b': 2 }) }); + * + * _.hasIn(object, 'a'); + * // => true + * + * _.hasIn(object, 'a.b'); + * // => true + * + * _.hasIn(object, ['a', 'b']); + * // => true + * + * _.hasIn(object, 'b'); + * // => false + */ + function hasIn(object, path) { + return object != null && hasPath(object, path, baseHasIn); + } + + module.exports = hasIn; + + +/***/ }), +/* 223 */ +/***/ (function(module, exports) { + + /** + * The base implementation of `_.hasIn` without support for deep paths. + * + * @private + * @param {Object} [object] The object to query. + * @param {Array|string} key The key to check. + * @returns {boolean} Returns `true` if `key` exists, else `false`. + */ + function baseHasIn(object, key) { + return object != null && key in Object(object); + } + + module.exports = baseHasIn; + + +/***/ }), +/* 224 */ +/***/ (function(module, exports, __webpack_require__) { + + var castPath = __webpack_require__(214), + isArguments = __webpack_require__(110), + isArray = __webpack_require__(112), + isIndex = __webpack_require__(99), + isLength = __webpack_require__(98), + toKey = __webpack_require__(221); + + /** + * Checks if `path` exists on `object`. + * + * @private + * @param {Object} object The object to query. + * @param {Array|string} path The path to check. + * @param {Function} hasFunc The function to check properties. + * @returns {boolean} Returns `true` if `path` exists, else `false`. + */ + function hasPath(object, path, hasFunc) { + path = castPath(path, object); + + var index = -1, + length = path.length, + result = false; + + while (++index < length) { + var key = toKey(path[index]); + if (!(result = object != null && hasFunc(object, key))) { + break; + } + object = object[key]; + } + if (result || ++index != length) { + return result; + } + length = object == null ? 0 : object.length; + return !!length && isLength(length) && isIndex(key, length) && + (isArray(object) || isArguments(object)); + } + + module.exports = hasPath; + + +/***/ }), +/* 225 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseProperty = __webpack_require__(226), + basePropertyDeep = __webpack_require__(227), + isKey = __webpack_require__(215), + toKey = __webpack_require__(221); + + /** + * Creates a function that returns the value at `path` of a given object. + * + * @static + * @memberOf _ + * @since 2.4.0 + * @category Util + * @param {Array|string} path The path of the property to get. + * @returns {Function} Returns the new accessor function. + * @example + * + * var objects = [ + * { 'a': { 'b': 2 } }, + * { 'a': { 'b': 1 } } + * ]; + * + * _.map(objects, _.property('a.b')); + * // => [2, 1] + * + * _.map(_.sortBy(objects, _.property(['a', 'b'])), 'a.b'); + * // => [1, 2] + */ + function property(path) { + return isKey(path) ? baseProperty(toKey(path)) : basePropertyDeep(path); + } + + module.exports = property; + + +/***/ }), +/* 226 */ +/***/ (function(module, exports) { + + /** + * The base implementation of `_.property` without support for deep paths. + * + * @private + * @param {string} key The key of the property to get. + * @returns {Function} Returns the new accessor function. + */ + function baseProperty(key) { + return function(object) { + return object == null ? undefined : object[key]; + }; + } + + module.exports = baseProperty; + + +/***/ }), +/* 227 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseGet = __webpack_require__(213); + + /** + * A specialized version of `baseProperty` which supports deep paths. + * + * @private + * @param {Array|string} path The path of the property to get. + * @returns {Function} Returns the new accessor function. + */ + function basePropertyDeep(path) { + return function(object) { + return baseGet(object, path); + }; + } + + module.exports = basePropertyDeep; + + +/***/ }), +/* 228 */ +/***/ (function(module, exports) { + + /** + * Gets the last element of `array`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to query. + * @returns {*} Returns the last element of `array`. + * @example + * + * _.last([1, 2, 3]); + * // => 3 + */ + function last(array) { + var length = array == null ? 0 : array.length; + return length ? array[length - 1] : undefined; + } + + module.exports = last; + + +/***/ }), +/* 229 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseDifference = __webpack_require__(115), + baseFlatten = __webpack_require__(108), + baseRest = __webpack_require__(157), + isArrayLikeObject = __webpack_require__(166), + last = __webpack_require__(228); + + /** + * This method is like `_.difference` except that it accepts `comparator` + * which is invoked to compare elements of `array` to `values`. The order and + * references of result values are determined by the first array. The comparator + * is invoked with two arguments: (arrVal, othVal). + * + * **Note:** Unlike `_.pullAllWith`, this method returns a new array. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {...Array} [values] The values to exclude. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new array of filtered values. + * @example + * + * var objects = [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }]; + * + * _.differenceWith(objects, [{ 'x': 1, 'y': 2 }], _.isEqual); + * // => [{ 'x': 2, 'y': 1 }] + */ + var differenceWith = baseRest(function(array, values) { + var comparator = last(values); + if (isArrayLikeObject(comparator)) { + comparator = undefined; + } + return isArrayLikeObject(array) + ? baseDifference(array, baseFlatten(values, 1, isArrayLikeObject, true), undefined, comparator) + : []; + }); + + module.exports = differenceWith; + + +/***/ }), +/* 230 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86), + toInteger = __webpack_require__(100); + + /** + * Creates a slice of `array` with `n` elements dropped from the beginning. + * + * @static + * @memberOf _ + * @since 0.5.0 + * @category Array + * @param {Array} array The array to query. + * @param {number} [n=1] The number of elements to drop. + * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. + * @returns {Array} Returns the slice of `array`. + * @example + * + * _.drop([1, 2, 3]); + * // => [2, 3] + * + * _.drop([1, 2, 3], 2); + * // => [3] + * + * _.drop([1, 2, 3], 5); + * // => [] + * + * _.drop([1, 2, 3], 0); + * // => [1, 2, 3] + */ + function drop(array, n, guard) { + var length = array == null ? 0 : array.length; + if (!length) { + return []; + } + n = (guard || n === undefined) ? 1 : toInteger(n); + return baseSlice(array, n < 0 ? 0 : n, length); + } + + module.exports = drop; + + +/***/ }), +/* 231 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86), + toInteger = __webpack_require__(100); + + /** + * Creates a slice of `array` with `n` elements dropped from the end. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to query. + * @param {number} [n=1] The number of elements to drop. + * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. + * @returns {Array} Returns the slice of `array`. + * @example + * + * _.dropRight([1, 2, 3]); + * // => [1, 2] + * + * _.dropRight([1, 2, 3], 2); + * // => [1] + * + * _.dropRight([1, 2, 3], 5); + * // => [] + * + * _.dropRight([1, 2, 3], 0); + * // => [1, 2, 3] + */ + function dropRight(array, n, guard) { + var length = array == null ? 0 : array.length; + if (!length) { + return []; + } + n = (guard || n === undefined) ? 1 : toInteger(n); + n = length - n; + return baseSlice(array, 0, n < 0 ? 0 : n); + } + + module.exports = dropRight; + + +/***/ }), +/* 232 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + baseWhile = __webpack_require__(233); + + /** + * Creates a slice of `array` excluding elements dropped from the end. + * Elements are dropped until `predicate` returns falsey. The predicate is + * invoked with three arguments: (value, index, array). + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to query. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @returns {Array} Returns the slice of `array`. + * @example + * + * var users = [ + * { 'user': 'barney', 'active': true }, + * { 'user': 'fred', 'active': false }, + * { 'user': 'pebbles', 'active': false } + * ]; + * + * _.dropRightWhile(users, function(o) { return !o.active; }); + * // => objects for ['barney'] + * + * // The `_.matches` iteratee shorthand. + * _.dropRightWhile(users, { 'user': 'pebbles', 'active': false }); + * // => objects for ['barney', 'fred'] + * + * // The `_.matchesProperty` iteratee shorthand. + * _.dropRightWhile(users, ['active', false]); + * // => objects for ['barney'] + * + * // The `_.property` iteratee shorthand. + * _.dropRightWhile(users, 'active'); + * // => objects for ['barney', 'fred', 'pebbles'] + */ + function dropRightWhile(array, predicate) { + return (array && array.length) + ? baseWhile(array, baseIteratee(predicate, 3), true, true) + : []; + } + + module.exports = dropRightWhile; + + +/***/ }), +/* 233 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86); + + /** + * The base implementation of methods like `_.dropWhile` and `_.takeWhile` + * without support for iteratee shorthands. + * + * @private + * @param {Array} array The array to query. + * @param {Function} predicate The function invoked per iteration. + * @param {boolean} [isDrop] Specify dropping elements instead of taking them. + * @param {boolean} [fromRight] Specify iterating from right to left. + * @returns {Array} Returns the slice of `array`. + */ + function baseWhile(array, predicate, isDrop, fromRight) { + var length = array.length, + index = fromRight ? length : -1; + + while ((fromRight ? index-- : ++index < length) && + predicate(array[index], index, array)) {} + + return isDrop + ? baseSlice(array, (fromRight ? 0 : index), (fromRight ? index + 1 : length)) + : baseSlice(array, (fromRight ? index + 1 : 0), (fromRight ? length : index)); + } + + module.exports = baseWhile; + + +/***/ }), +/* 234 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + baseWhile = __webpack_require__(233); + + /** + * Creates a slice of `array` excluding elements dropped from the beginning. + * Elements are dropped until `predicate` returns falsey. The predicate is + * invoked with three arguments: (value, index, array). + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to query. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @returns {Array} Returns the slice of `array`. + * @example + * + * var users = [ + * { 'user': 'barney', 'active': false }, + * { 'user': 'fred', 'active': false }, + * { 'user': 'pebbles', 'active': true } + * ]; + * + * _.dropWhile(users, function(o) { return !o.active; }); + * // => objects for ['pebbles'] + * + * // The `_.matches` iteratee shorthand. + * _.dropWhile(users, { 'user': 'barney', 'active': false }); + * // => objects for ['fred', 'pebbles'] + * + * // The `_.matchesProperty` iteratee shorthand. + * _.dropWhile(users, ['active', false]); + * // => objects for ['pebbles'] + * + * // The `_.property` iteratee shorthand. + * _.dropWhile(users, 'active'); + * // => objects for ['barney', 'fred', 'pebbles'] + */ + function dropWhile(array, predicate) { + return (array && array.length) + ? baseWhile(array, baseIteratee(predicate, 3), true) + : []; + } + + module.exports = dropWhile; + + +/***/ }), +/* 235 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFill = __webpack_require__(236), + isIterateeCall = __webpack_require__(87); + + /** + * Fills elements of `array` with `value` from `start` up to, but not + * including, `end`. + * + * **Note:** This method mutates `array`. + * + * @static + * @memberOf _ + * @since 3.2.0 + * @category Array + * @param {Array} array The array to fill. + * @param {*} value The value to fill `array` with. + * @param {number} [start=0] The start position. + * @param {number} [end=array.length] The end position. + * @returns {Array} Returns `array`. + * @example + * + * var array = [1, 2, 3]; + * + * _.fill(array, 'a'); + * console.log(array); + * // => ['a', 'a', 'a'] + * + * _.fill(Array(3), 2); + * // => [2, 2, 2] + * + * _.fill([4, 6, 8, 10], '*', 1, 3); + * // => [4, '*', '*', 10] + */ + function fill(array, value, start, end) { + var length = array == null ? 0 : array.length; + if (!length) { + return []; + } + if (start && typeof start != 'number' && isIterateeCall(array, value, start)) { + start = 0; + end = length; + } + return baseFill(array, value, start, end); + } + + module.exports = fill; + + +/***/ }), +/* 236 */ +/***/ (function(module, exports, __webpack_require__) { + + var toInteger = __webpack_require__(100), + toLength = __webpack_require__(237); + + /** + * The base implementation of `_.fill` without an iteratee call guard. + * + * @private + * @param {Array} array The array to fill. + * @param {*} value The value to fill `array` with. + * @param {number} [start=0] The start position. + * @param {number} [end=array.length] The end position. + * @returns {Array} Returns `array`. + */ + function baseFill(array, value, start, end) { + var length = array.length; + + start = toInteger(start); + if (start < 0) { + start = -start > length ? 0 : (length + start); + } + end = (end === undefined || end > length) ? length : toInteger(end); + if (end < 0) { + end += length; + } + end = start > end ? 0 : toLength(end); + while (start < end) { + array[start++] = value; + } + return array; + } + + module.exports = baseFill; + + +/***/ }), +/* 237 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseClamp = __webpack_require__(238), + toInteger = __webpack_require__(100); + + /** Used as references for the maximum length and index of an array. */ + var MAX_ARRAY_LENGTH = 4294967295; + + /** + * Converts `value` to an integer suitable for use as the length of an + * array-like object. + * + * **Note:** This method is based on + * [`ToLength`](http://ecma-international.org/ecma-262/7.0/#sec-tolength). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to convert. + * @returns {number} Returns the converted integer. + * @example + * + * _.toLength(3.2); + * // => 3 + * + * _.toLength(Number.MIN_VALUE); + * // => 0 + * + * _.toLength(Infinity); + * // => 4294967295 + * + * _.toLength('3.2'); + * // => 3 + */ + function toLength(value) { + return value ? baseClamp(toInteger(value), 0, MAX_ARRAY_LENGTH) : 0; + } + + module.exports = toLength; + + +/***/ }), +/* 238 */ +/***/ (function(module, exports) { + + /** + * The base implementation of `_.clamp` which doesn't coerce arguments. + * + * @private + * @param {number} number The number to clamp. + * @param {number} [lower] The lower bound. + * @param {number} upper The upper bound. + * @returns {number} Returns the clamped number. + */ + function baseClamp(number, lower, upper) { + if (number === number) { + if (upper !== undefined) { + number = number <= upper ? number : upper; + } + if (lower !== undefined) { + number = number >= lower ? number : lower; + } + } + return number; + } + + module.exports = baseClamp; + + +/***/ }), +/* 239 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFindIndex = __webpack_require__(150), + baseIteratee = __webpack_require__(168), + toInteger = __webpack_require__(100); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeMax = Math.max; + + /** + * This method is like `_.find` except that it returns the index of the first + * element `predicate` returns truthy for instead of the element itself. + * + * @static + * @memberOf _ + * @since 1.1.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @param {number} [fromIndex=0] The index to search from. + * @returns {number} Returns the index of the found element, else `-1`. + * @example + * + * var users = [ + * { 'user': 'barney', 'active': false }, + * { 'user': 'fred', 'active': false }, + * { 'user': 'pebbles', 'active': true } + * ]; + * + * _.findIndex(users, function(o) { return o.user == 'barney'; }); + * // => 0 + * + * // The `_.matches` iteratee shorthand. + * _.findIndex(users, { 'user': 'fred', 'active': false }); + * // => 1 + * + * // The `_.matchesProperty` iteratee shorthand. + * _.findIndex(users, ['active', false]); + * // => 0 + * + * // The `_.property` iteratee shorthand. + * _.findIndex(users, 'active'); + * // => 2 + */ + function findIndex(array, predicate, fromIndex) { + var length = array == null ? 0 : array.length; + if (!length) { + return -1; + } + var index = fromIndex == null ? 0 : toInteger(fromIndex); + if (index < 0) { + index = nativeMax(length + index, 0); + } + return baseFindIndex(array, baseIteratee(predicate, 3), index); + } + + module.exports = findIndex; + + +/***/ }), +/* 240 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFindIndex = __webpack_require__(150), + baseIteratee = __webpack_require__(168), + toInteger = __webpack_require__(100); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeMax = Math.max, + nativeMin = Math.min; + + /** + * This method is like `_.findIndex` except that it iterates over elements + * of `collection` from right to left. + * + * @static + * @memberOf _ + * @since 2.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @param {number} [fromIndex=array.length-1] The index to search from. + * @returns {number} Returns the index of the found element, else `-1`. + * @example + * + * var users = [ + * { 'user': 'barney', 'active': true }, + * { 'user': 'fred', 'active': false }, + * { 'user': 'pebbles', 'active': false } + * ]; + * + * _.findLastIndex(users, function(o) { return o.user == 'pebbles'; }); + * // => 2 + * + * // The `_.matches` iteratee shorthand. + * _.findLastIndex(users, { 'user': 'barney', 'active': true }); + * // => 0 + * + * // The `_.matchesProperty` iteratee shorthand. + * _.findLastIndex(users, ['active', false]); + * // => 2 + * + * // The `_.property` iteratee shorthand. + * _.findLastIndex(users, 'active'); + * // => 0 + */ + function findLastIndex(array, predicate, fromIndex) { + var length = array == null ? 0 : array.length; + if (!length) { + return -1; + } + var index = length - 1; + if (fromIndex !== undefined) { + index = toInteger(fromIndex); + index = fromIndex < 0 + ? nativeMax(length + index, 0) + : nativeMin(index, length - 1); + } + return baseFindIndex(array, baseIteratee(predicate, 3), index, true); + } + + module.exports = findLastIndex; + + +/***/ }), +/* 241 */ +/***/ (function(module, exports, __webpack_require__) { + + module.exports = __webpack_require__(242); + + +/***/ }), +/* 242 */ +/***/ (function(module, exports) { + + /** + * Gets the first element of `array`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @alias first + * @category Array + * @param {Array} array The array to query. + * @returns {*} Returns the first element of `array`. + * @example + * + * _.head([1, 2, 3]); + * // => 1 + * + * _.head([]); + * // => undefined + */ + function head(array) { + return (array && array.length) ? array[0] : undefined; + } + + module.exports = head; + + +/***/ }), +/* 243 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFlatten = __webpack_require__(108); + + /** + * Flattens `array` a single level deep. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to flatten. + * @returns {Array} Returns the new flattened array. + * @example + * + * _.flatten([1, [2, [3, [4]], 5]]); + * // => [1, 2, [3, [4]], 5] + */ + function flatten(array) { + var length = array == null ? 0 : array.length; + return length ? baseFlatten(array, 1) : []; + } + + module.exports = flatten; + + +/***/ }), +/* 244 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFlatten = __webpack_require__(108); + + /** Used as references for various `Number` constants. */ + var INFINITY = 1 / 0; + + /** + * Recursively flattens `array`. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to flatten. + * @returns {Array} Returns the new flattened array. + * @example + * + * _.flattenDeep([1, [2, [3, [4]], 5]]); + * // => [1, 2, 3, 4, 5] + */ + function flattenDeep(array) { + var length = array == null ? 0 : array.length; + return length ? baseFlatten(array, INFINITY) : []; + } + + module.exports = flattenDeep; + + +/***/ }), +/* 245 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFlatten = __webpack_require__(108), + toInteger = __webpack_require__(100); + + /** + * Recursively flatten `array` up to `depth` times. + * + * @static + * @memberOf _ + * @since 4.4.0 + * @category Array + * @param {Array} array The array to flatten. + * @param {number} [depth=1] The maximum recursion depth. + * @returns {Array} Returns the new flattened array. + * @example + * + * var array = [1, [2, [3, [4]], 5]]; + * + * _.flattenDepth(array, 1); + * // => [1, 2, [3, [4]], 5] + * + * _.flattenDepth(array, 2); + * // => [1, 2, 3, [4], 5] + */ + function flattenDepth(array, depth) { + var length = array == null ? 0 : array.length; + if (!length) { + return []; + } + depth = depth === undefined ? 1 : toInteger(depth); + return baseFlatten(array, depth); + } + + module.exports = flattenDepth; + + +/***/ }), +/* 246 */ +/***/ (function(module, exports) { + + /** + * The inverse of `_.toPairs`; this method returns an object composed + * from key-value `pairs`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} pairs The key-value pairs. + * @returns {Object} Returns the new object. + * @example + * + * _.fromPairs([['a', 1], ['b', 2]]); + * // => { 'a': 1, 'b': 2 } + */ + function fromPairs(pairs) { + var index = -1, + length = pairs == null ? 0 : pairs.length, + result = {}; + + while (++index < length) { + var pair = pairs[index]; + result[pair[0]] = pair[1]; + } + return result; + } + + module.exports = fromPairs; + + +/***/ }), +/* 247 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIndexOf = __webpack_require__(149), + toInteger = __webpack_require__(100); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeMax = Math.max; + + /** + * Gets the index at which the first occurrence of `value` is found in `array` + * using [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. If `fromIndex` is negative, it's used as the + * offset from the end of `array`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @param {number} [fromIndex=0] The index to search from. + * @returns {number} Returns the index of the matched value, else `-1`. + * @example + * + * _.indexOf([1, 2, 1, 2], 2); + * // => 1 + * + * // Search from the `fromIndex`. + * _.indexOf([1, 2, 1, 2], 2, 2); + * // => 3 + */ + function indexOf(array, value, fromIndex) { + var length = array == null ? 0 : array.length; + if (!length) { + return -1; + } + var index = fromIndex == null ? 0 : toInteger(fromIndex); + if (index < 0) { + index = nativeMax(length + index, 0); + } + return baseIndexOf(array, value, index); + } + + module.exports = indexOf; + + +/***/ }), +/* 248 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86); + + /** + * Gets all but the last element of `array`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to query. + * @returns {Array} Returns the slice of `array`. + * @example + * + * _.initial([1, 2, 3]); + * // => [1, 2] + */ + function initial(array) { + var length = array == null ? 0 : array.length; + return length ? baseSlice(array, 0, -1) : []; + } + + module.exports = initial; + + +/***/ }), +/* 249 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayMap = __webpack_require__(154), + baseIntersection = __webpack_require__(250), + baseRest = __webpack_require__(157), + castArrayLikeObject = __webpack_require__(251); + + /** + * Creates an array of unique values that are included in all given arrays + * using [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. The order and references of result values are + * determined by the first array. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @returns {Array} Returns the new array of intersecting values. + * @example + * + * _.intersection([2, 1], [2, 3]); + * // => [2] + */ + var intersection = baseRest(function(arrays) { + var mapped = arrayMap(arrays, castArrayLikeObject); + return (mapped.length && mapped[0] === arrays[0]) + ? baseIntersection(mapped) + : []; + }); + + module.exports = intersection; + + +/***/ }), +/* 250 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetCache = __webpack_require__(116), + arrayIncludes = __webpack_require__(148), + arrayIncludesWith = __webpack_require__(153), + arrayMap = __webpack_require__(154), + baseUnary = __webpack_require__(155), + cacheHas = __webpack_require__(156); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeMin = Math.min; + + /** + * The base implementation of methods like `_.intersection`, without support + * for iteratee shorthands, that accepts an array of arrays to inspect. + * + * @private + * @param {Array} arrays The arrays to inspect. + * @param {Function} [iteratee] The iteratee invoked per element. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new array of shared values. + */ + function baseIntersection(arrays, iteratee, comparator) { + var includes = comparator ? arrayIncludesWith : arrayIncludes, + length = arrays[0].length, + othLength = arrays.length, + othIndex = othLength, + caches = Array(othLength), + maxLength = Infinity, + result = []; + + while (othIndex--) { + var array = arrays[othIndex]; + if (othIndex && iteratee) { + array = arrayMap(array, baseUnary(iteratee)); + } + maxLength = nativeMin(array.length, maxLength); + caches[othIndex] = !comparator && (iteratee || (length >= 120 && array.length >= 120)) + ? new SetCache(othIndex && array) + : undefined; + } + array = arrays[0]; + + var index = -1, + seen = caches[0]; + + outer: + while (++index < length && result.length < maxLength) { + var value = array[index], + computed = iteratee ? iteratee(value) : value; + + value = (comparator || value !== 0) ? value : 0; + if (!(seen + ? cacheHas(seen, computed) + : includes(result, computed, comparator) + )) { + othIndex = othLength; + while (--othIndex) { + var cache = caches[othIndex]; + if (!(cache + ? cacheHas(cache, computed) + : includes(arrays[othIndex], computed, comparator)) + ) { + continue outer; + } + } + if (seen) { + seen.push(computed); + } + result.push(value); + } + } + return result; + } + + module.exports = baseIntersection; + + +/***/ }), +/* 251 */ +/***/ (function(module, exports, __webpack_require__) { + + var isArrayLikeObject = __webpack_require__(166); + + /** + * Casts `value` to an empty array if it's not an array like object. + * + * @private + * @param {*} value The value to inspect. + * @returns {Array|Object} Returns the cast array-like object. + */ + function castArrayLikeObject(value) { + return isArrayLikeObject(value) ? value : []; + } + + module.exports = castArrayLikeObject; + + +/***/ }), +/* 252 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayMap = __webpack_require__(154), + baseIntersection = __webpack_require__(250), + baseIteratee = __webpack_require__(168), + baseRest = __webpack_require__(157), + castArrayLikeObject = __webpack_require__(251), + last = __webpack_require__(228); + + /** + * This method is like `_.intersection` except that it accepts `iteratee` + * which is invoked for each element of each `arrays` to generate the criterion + * by which they're compared. The order and references of result values are + * determined by the first array. The iteratee is invoked with one argument: + * (value). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @param {Function} [iteratee=_.identity] The iteratee invoked per element. + * @returns {Array} Returns the new array of intersecting values. + * @example + * + * _.intersectionBy([2.1, 1.2], [2.3, 3.4], Math.floor); + * // => [2.1] + * + * // The `_.property` iteratee shorthand. + * _.intersectionBy([{ 'x': 1 }], [{ 'x': 2 }, { 'x': 1 }], 'x'); + * // => [{ 'x': 1 }] + */ + var intersectionBy = baseRest(function(arrays) { + var iteratee = last(arrays), + mapped = arrayMap(arrays, castArrayLikeObject); + + if (iteratee === last(mapped)) { + iteratee = undefined; + } else { + mapped.pop(); + } + return (mapped.length && mapped[0] === arrays[0]) + ? baseIntersection(mapped, baseIteratee(iteratee, 2)) + : []; + }); + + module.exports = intersectionBy; + + +/***/ }), +/* 253 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayMap = __webpack_require__(154), + baseIntersection = __webpack_require__(250), + baseRest = __webpack_require__(157), + castArrayLikeObject = __webpack_require__(251), + last = __webpack_require__(228); + + /** + * This method is like `_.intersection` except that it accepts `comparator` + * which is invoked to compare elements of `arrays`. The order and references + * of result values are determined by the first array. The comparator is + * invoked with two arguments: (arrVal, othVal). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new array of intersecting values. + * @example + * + * var objects = [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }]; + * var others = [{ 'x': 1, 'y': 1 }, { 'x': 1, 'y': 2 }]; + * + * _.intersectionWith(objects, others, _.isEqual); + * // => [{ 'x': 1, 'y': 2 }] + */ + var intersectionWith = baseRest(function(arrays) { + var comparator = last(arrays), + mapped = arrayMap(arrays, castArrayLikeObject); + + comparator = typeof comparator == 'function' ? comparator : undefined; + if (comparator) { + mapped.pop(); + } + return (mapped.length && mapped[0] === arrays[0]) + ? baseIntersection(mapped, undefined, comparator) + : []; + }); + + module.exports = intersectionWith; + + +/***/ }), +/* 254 */ +/***/ (function(module, exports) { + + /** Used for built-in method references. */ + var arrayProto = Array.prototype; + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeJoin = arrayProto.join; + + /** + * Converts all elements in `array` into a string separated by `separator`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to convert. + * @param {string} [separator=','] The element separator. + * @returns {string} Returns the joined string. + * @example + * + * _.join(['a', 'b', 'c'], '~'); + * // => 'a~b~c' + */ + function join(array, separator) { + return array == null ? '' : nativeJoin.call(array, separator); + } + + module.exports = join; + + +/***/ }), +/* 255 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFindIndex = __webpack_require__(150), + baseIsNaN = __webpack_require__(151), + strictLastIndexOf = __webpack_require__(256), + toInteger = __webpack_require__(100); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeMax = Math.max, + nativeMin = Math.min; + + /** + * This method is like `_.indexOf` except that it iterates over elements of + * `array` from right to left. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @param {number} [fromIndex=array.length-1] The index to search from. + * @returns {number} Returns the index of the matched value, else `-1`. + * @example + * + * _.lastIndexOf([1, 2, 1, 2], 2); + * // => 3 + * + * // Search from the `fromIndex`. + * _.lastIndexOf([1, 2, 1, 2], 2, 2); + * // => 1 + */ + function lastIndexOf(array, value, fromIndex) { + var length = array == null ? 0 : array.length; + if (!length) { + return -1; + } + var index = length; + if (fromIndex !== undefined) { + index = toInteger(fromIndex); + index = index < 0 ? nativeMax(length + index, 0) : nativeMin(index, length - 1); + } + return value === value + ? strictLastIndexOf(array, value, index) + : baseFindIndex(array, baseIsNaN, index, true); + } + + module.exports = lastIndexOf; + + +/***/ }), +/* 256 */ +/***/ (function(module, exports) { + + /** + * A specialized version of `_.lastIndexOf` which performs strict equality + * comparisons of values, i.e. `===`. + * + * @private + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @param {number} fromIndex The index to search from. + * @returns {number} Returns the index of the matched value, else `-1`. + */ + function strictLastIndexOf(array, value, fromIndex) { + var index = fromIndex + 1; + while (index--) { + if (array[index] === value) { + return index; + } + } + return index; + } + + module.exports = strictLastIndexOf; + + +/***/ }), +/* 257 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseNth = __webpack_require__(258), + toInteger = __webpack_require__(100); + + /** + * Gets the element at index `n` of `array`. If `n` is negative, the nth + * element from the end is returned. + * + * @static + * @memberOf _ + * @since 4.11.0 + * @category Array + * @param {Array} array The array to query. + * @param {number} [n=0] The index of the element to return. + * @returns {*} Returns the nth element of `array`. + * @example + * + * var array = ['a', 'b', 'c', 'd']; + * + * _.nth(array, 1); + * // => 'b' + * + * _.nth(array, -2); + * // => 'c'; + */ + function nth(array, n) { + return (array && array.length) ? baseNth(array, toInteger(n)) : undefined; + } + + module.exports = nth; + + +/***/ }), +/* 258 */ +/***/ (function(module, exports, __webpack_require__) { + + var isIndex = __webpack_require__(99); + + /** + * The base implementation of `_.nth` which doesn't coerce arguments. + * + * @private + * @param {Array} array The array to query. + * @param {number} n The index of the element to return. + * @returns {*} Returns the nth element of `array`. + */ + function baseNth(array, n) { + var length = array.length; + if (!length) { + return; + } + n += n < 0 ? length : 0; + return isIndex(n, length) ? array[n] : undefined; + } + + module.exports = baseNth; + + +/***/ }), +/* 259 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseRest = __webpack_require__(157), + pullAll = __webpack_require__(260); + + /** + * Removes all given values from `array` using + * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. + * + * **Note:** Unlike `_.without`, this method mutates `array`. Use `_.remove` + * to remove elements from an array by predicate. + * + * @static + * @memberOf _ + * @since 2.0.0 + * @category Array + * @param {Array} array The array to modify. + * @param {...*} [values] The values to remove. + * @returns {Array} Returns `array`. + * @example + * + * var array = ['a', 'b', 'c', 'a', 'b', 'c']; + * + * _.pull(array, 'a', 'c'); + * console.log(array); + * // => ['b', 'b'] + */ + var pull = baseRest(pullAll); + + module.exports = pull; + + +/***/ }), +/* 260 */ +/***/ (function(module, exports, __webpack_require__) { + + var basePullAll = __webpack_require__(261); + + /** + * This method is like `_.pull` except that it accepts an array of values to remove. + * + * **Note:** Unlike `_.difference`, this method mutates `array`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to modify. + * @param {Array} values The values to remove. + * @returns {Array} Returns `array`. + * @example + * + * var array = ['a', 'b', 'c', 'a', 'b', 'c']; + * + * _.pullAll(array, ['a', 'c']); + * console.log(array); + * // => ['b', 'b'] + */ + function pullAll(array, values) { + return (array && array.length && values && values.length) + ? basePullAll(array, values) + : array; + } + + module.exports = pullAll; + + +/***/ }), +/* 261 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayMap = __webpack_require__(154), + baseIndexOf = __webpack_require__(149), + baseIndexOfWith = __webpack_require__(262), + baseUnary = __webpack_require__(155), + copyArray = __webpack_require__(113); + + /** Used for built-in method references. */ + var arrayProto = Array.prototype; + + /** Built-in value references. */ + var splice = arrayProto.splice; + + /** + * The base implementation of `_.pullAllBy` without support for iteratee + * shorthands. + * + * @private + * @param {Array} array The array to modify. + * @param {Array} values The values to remove. + * @param {Function} [iteratee] The iteratee invoked per element. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns `array`. + */ + function basePullAll(array, values, iteratee, comparator) { + var indexOf = comparator ? baseIndexOfWith : baseIndexOf, + index = -1, + length = values.length, + seen = array; + + if (array === values) { + values = copyArray(values); + } + if (iteratee) { + seen = arrayMap(array, baseUnary(iteratee)); + } + while (++index < length) { + var fromIndex = 0, + value = values[index], + computed = iteratee ? iteratee(value) : value; + + while ((fromIndex = indexOf(seen, computed, fromIndex, comparator)) > -1) { + if (seen !== array) { + splice.call(seen, fromIndex, 1); + } + splice.call(array, fromIndex, 1); + } + } + return array; + } + + module.exports = basePullAll; + + +/***/ }), +/* 262 */ +/***/ (function(module, exports) { + + /** + * This function is like `baseIndexOf` except that it accepts a comparator. + * + * @private + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @param {number} fromIndex The index to search from. + * @param {Function} comparator The comparator invoked per element. + * @returns {number} Returns the index of the matched value, else `-1`. + */ + function baseIndexOfWith(array, value, fromIndex, comparator) { + var index = fromIndex - 1, + length = array.length; + + while (++index < length) { + if (comparator(array[index], value)) { + return index; + } + } + return -1; + } + + module.exports = baseIndexOfWith; + + +/***/ }), +/* 263 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + basePullAll = __webpack_require__(261); + + /** + * This method is like `_.pullAll` except that it accepts `iteratee` which is + * invoked for each element of `array` and `values` to generate the criterion + * by which they're compared. The iteratee is invoked with one argument: (value). + * + * **Note:** Unlike `_.differenceBy`, this method mutates `array`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to modify. + * @param {Array} values The values to remove. + * @param {Function} [iteratee=_.identity] The iteratee invoked per element. + * @returns {Array} Returns `array`. + * @example + * + * var array = [{ 'x': 1 }, { 'x': 2 }, { 'x': 3 }, { 'x': 1 }]; + * + * _.pullAllBy(array, [{ 'x': 1 }, { 'x': 3 }], 'x'); + * console.log(array); + * // => [{ 'x': 2 }] + */ + function pullAllBy(array, values, iteratee) { + return (array && array.length && values && values.length) + ? basePullAll(array, values, baseIteratee(iteratee, 2)) + : array; + } + + module.exports = pullAllBy; + + +/***/ }), +/* 264 */ +/***/ (function(module, exports, __webpack_require__) { + + var basePullAll = __webpack_require__(261); + + /** + * This method is like `_.pullAll` except that it accepts `comparator` which + * is invoked to compare elements of `array` to `values`. The comparator is + * invoked with two arguments: (arrVal, othVal). + * + * **Note:** Unlike `_.differenceWith`, this method mutates `array`. + * + * @static + * @memberOf _ + * @since 4.6.0 + * @category Array + * @param {Array} array The array to modify. + * @param {Array} values The values to remove. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns `array`. + * @example + * + * var array = [{ 'x': 1, 'y': 2 }, { 'x': 3, 'y': 4 }, { 'x': 5, 'y': 6 }]; + * + * _.pullAllWith(array, [{ 'x': 3, 'y': 4 }], _.isEqual); + * console.log(array); + * // => [{ 'x': 1, 'y': 2 }, { 'x': 5, 'y': 6 }] + */ + function pullAllWith(array, values, comparator) { + return (array && array.length && values && values.length) + ? basePullAll(array, values, undefined, comparator) + : array; + } + + module.exports = pullAllWith; + + +/***/ }), +/* 265 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayMap = __webpack_require__(154), + baseAt = __webpack_require__(266), + basePullAt = __webpack_require__(267), + compareAscending = __webpack_require__(270), + flatRest = __webpack_require__(271), + isIndex = __webpack_require__(99); + + /** + * Removes elements from `array` corresponding to `indexes` and returns an + * array of removed elements. + * + * **Note:** Unlike `_.at`, this method mutates `array`. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to modify. + * @param {...(number|number[])} [indexes] The indexes of elements to remove. + * @returns {Array} Returns the new array of removed elements. + * @example + * + * var array = ['a', 'b', 'c', 'd']; + * var pulled = _.pullAt(array, [1, 3]); + * + * console.log(array); + * // => ['a', 'c'] + * + * console.log(pulled); + * // => ['b', 'd'] + */ + var pullAt = flatRest(function(array, indexes) { + var length = array == null ? 0 : array.length, + result = baseAt(array, indexes); + + basePullAt(array, arrayMap(indexes, function(index) { + return isIndex(index, length) ? +index : index; + }).sort(compareAscending)); + + return result; + }); + + module.exports = pullAt; + + +/***/ }), +/* 266 */ +/***/ (function(module, exports, __webpack_require__) { + + var get = __webpack_require__(212); + + /** + * The base implementation of `_.at` without support for individual paths. + * + * @private + * @param {Object} object The object to iterate over. + * @param {string[]} paths The property paths to pick. + * @returns {Array} Returns the picked elements. + */ + function baseAt(object, paths) { + var index = -1, + length = paths.length, + result = Array(length), + skip = object == null; + + while (++index < length) { + result[index] = skip ? undefined : get(object, paths[index]); + } + return result; + } + + module.exports = baseAt; + + +/***/ }), +/* 267 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseUnset = __webpack_require__(268), + isIndex = __webpack_require__(99); + + /** Used for built-in method references. */ + var arrayProto = Array.prototype; + + /** Built-in value references. */ + var splice = arrayProto.splice; + + /** + * The base implementation of `_.pullAt` without support for individual + * indexes or capturing the removed elements. + * + * @private + * @param {Array} array The array to modify. + * @param {number[]} indexes The indexes of elements to remove. + * @returns {Array} Returns `array`. + */ + function basePullAt(array, indexes) { + var length = array ? indexes.length : 0, + lastIndex = length - 1; + + while (length--) { + var index = indexes[length]; + if (length == lastIndex || index !== previous) { + var previous = index; + if (isIndex(index)) { + splice.call(array, index, 1); + } else { + baseUnset(array, index); + } + } + } + return array; + } + + module.exports = basePullAt; + + +/***/ }), +/* 268 */ +/***/ (function(module, exports, __webpack_require__) { + + var castPath = __webpack_require__(214), + last = __webpack_require__(228), + parent = __webpack_require__(269), + toKey = __webpack_require__(221); + + /** + * The base implementation of `_.unset`. + * + * @private + * @param {Object} object The object to modify. + * @param {Array|string} path The property path to unset. + * @returns {boolean} Returns `true` if the property is deleted, else `false`. + */ + function baseUnset(object, path) { + path = castPath(path, object); + object = parent(object, path); + return object == null || delete object[toKey(last(path))]; + } + + module.exports = baseUnset; + + +/***/ }), +/* 269 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseGet = __webpack_require__(213), + baseSlice = __webpack_require__(86); + + /** + * Gets the parent value at `path` of `object`. + * + * @private + * @param {Object} object The object to query. + * @param {Array} path The path to get the parent value of. + * @returns {*} Returns the parent value. + */ + function parent(object, path) { + return path.length < 2 ? object : baseGet(object, baseSlice(path, 0, -1)); + } + + module.exports = parent; + + +/***/ }), +/* 270 */ +/***/ (function(module, exports, __webpack_require__) { + + var isSymbol = __webpack_require__(103); + + /** + * Compares values to sort them in ascending order. + * + * @private + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @returns {number} Returns the sort order indicator for `value`. + */ + function compareAscending(value, other) { + if (value !== other) { + var valIsDefined = value !== undefined, + valIsNull = value === null, + valIsReflexive = value === value, + valIsSymbol = isSymbol(value); + + var othIsDefined = other !== undefined, + othIsNull = other === null, + othIsReflexive = other === other, + othIsSymbol = isSymbol(other); + + if ((!othIsNull && !othIsSymbol && !valIsSymbol && value > other) || + (valIsSymbol && othIsDefined && othIsReflexive && !othIsNull && !othIsSymbol) || + (valIsNull && othIsDefined && othIsReflexive) || + (!valIsDefined && othIsReflexive) || + !valIsReflexive) { + return 1; + } + if ((!valIsNull && !valIsSymbol && !othIsSymbol && value < other) || + (othIsSymbol && valIsDefined && valIsReflexive && !valIsNull && !valIsSymbol) || + (othIsNull && valIsDefined && valIsReflexive) || + (!othIsDefined && valIsReflexive) || + !othIsReflexive) { + return -1; + } + } + return 0; + } + + module.exports = compareAscending; + + +/***/ }), +/* 271 */ +/***/ (function(module, exports, __webpack_require__) { + + var flatten = __webpack_require__(243), + overRest = __webpack_require__(159), + setToString = __webpack_require__(161); + + /** + * A specialized version of `baseRest` which flattens the rest array. + * + * @private + * @param {Function} func The function to apply a rest parameter to. + * @returns {Function} Returns the new function. + */ + function flatRest(func) { + return setToString(overRest(func, undefined, flatten), func + ''); + } + + module.exports = flatRest; + + +/***/ }), +/* 272 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + basePullAt = __webpack_require__(267); + + /** + * Removes all elements from `array` that `predicate` returns truthy for + * and returns an array of the removed elements. The predicate is invoked + * with three arguments: (value, index, array). + * + * **Note:** Unlike `_.filter`, this method mutates `array`. Use `_.pull` + * to pull elements from an array by value. + * + * @static + * @memberOf _ + * @since 2.0.0 + * @category Array + * @param {Array} array The array to modify. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @returns {Array} Returns the new array of removed elements. + * @example + * + * var array = [1, 2, 3, 4]; + * var evens = _.remove(array, function(n) { + * return n % 2 == 0; + * }); + * + * console.log(array); + * // => [1, 3] + * + * console.log(evens); + * // => [2, 4] + */ + function remove(array, predicate) { + var result = []; + if (!(array && array.length)) { + return result; + } + var index = -1, + indexes = [], + length = array.length; + + predicate = baseIteratee(predicate, 3); + while (++index < length) { + var value = array[index]; + if (predicate(value, index, array)) { + result.push(value); + indexes.push(index); + } + } + basePullAt(array, indexes); + return result; + } + + module.exports = remove; + + +/***/ }), +/* 273 */ +/***/ (function(module, exports) { + + /** Used for built-in method references. */ + var arrayProto = Array.prototype; + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeReverse = arrayProto.reverse; + + /** + * Reverses `array` so that the first element becomes the last, the second + * element becomes the second to last, and so on. + * + * **Note:** This method mutates `array` and is based on + * [`Array#reverse`](https://mdn.io/Array/reverse). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to modify. + * @returns {Array} Returns `array`. + * @example + * + * var array = [1, 2, 3]; + * + * _.reverse(array); + * // => [3, 2, 1] + * + * console.log(array); + * // => [3, 2, 1] + */ + function reverse(array) { + return array == null ? array : nativeReverse.call(array); + } + + module.exports = reverse; + + +/***/ }), +/* 274 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86), + isIterateeCall = __webpack_require__(87), + toInteger = __webpack_require__(100); + + /** + * Creates a slice of `array` from `start` up to, but not including, `end`. + * + * **Note:** This method is used instead of + * [`Array#slice`](https://mdn.io/Array/slice) to ensure dense arrays are + * returned. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to slice. + * @param {number} [start=0] The start position. + * @param {number} [end=array.length] The end position. + * @returns {Array} Returns the slice of `array`. + */ + function slice(array, start, end) { + var length = array == null ? 0 : array.length; + if (!length) { + return []; + } + if (end && typeof end != 'number' && isIterateeCall(array, start, end)) { + start = 0; + end = length; + } + else { + start = start == null ? 0 : toInteger(start); + end = end === undefined ? length : toInteger(end); + } + return baseSlice(array, start, end); + } + + module.exports = slice; + + +/***/ }), +/* 275 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSortedIndex = __webpack_require__(276); + + /** + * Uses a binary search to determine the lowest index at which `value` + * should be inserted into `array` in order to maintain its sort order. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The sorted array to inspect. + * @param {*} value The value to evaluate. + * @returns {number} Returns the index at which `value` should be inserted + * into `array`. + * @example + * + * _.sortedIndex([30, 50], 40); + * // => 1 + */ + function sortedIndex(array, value) { + return baseSortedIndex(array, value); + } + + module.exports = sortedIndex; + + +/***/ }), +/* 276 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSortedIndexBy = __webpack_require__(277), + identity = __webpack_require__(158), + isSymbol = __webpack_require__(103); + + /** Used as references for the maximum length and index of an array. */ + var MAX_ARRAY_LENGTH = 4294967295, + HALF_MAX_ARRAY_LENGTH = MAX_ARRAY_LENGTH >>> 1; + + /** + * The base implementation of `_.sortedIndex` and `_.sortedLastIndex` which + * performs a binary search of `array` to determine the index at which `value` + * should be inserted into `array` in order to maintain its sort order. + * + * @private + * @param {Array} array The sorted array to inspect. + * @param {*} value The value to evaluate. + * @param {boolean} [retHighest] Specify returning the highest qualified index. + * @returns {number} Returns the index at which `value` should be inserted + * into `array`. + */ + function baseSortedIndex(array, value, retHighest) { + var low = 0, + high = array == null ? low : array.length; + + if (typeof value == 'number' && value === value && high <= HALF_MAX_ARRAY_LENGTH) { + while (low < high) { + var mid = (low + high) >>> 1, + computed = array[mid]; + + if (computed !== null && !isSymbol(computed) && + (retHighest ? (computed <= value) : (computed < value))) { + low = mid + 1; + } else { + high = mid; + } + } + return high; + } + return baseSortedIndexBy(array, value, identity, retHighest); + } + + module.exports = baseSortedIndex; + + +/***/ }), +/* 277 */ +/***/ (function(module, exports, __webpack_require__) { + + var isSymbol = __webpack_require__(103); + + /** Used as references for the maximum length and index of an array. */ + var MAX_ARRAY_LENGTH = 4294967295, + MAX_ARRAY_INDEX = MAX_ARRAY_LENGTH - 1; + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeFloor = Math.floor, + nativeMin = Math.min; + + /** + * The base implementation of `_.sortedIndexBy` and `_.sortedLastIndexBy` + * which invokes `iteratee` for `value` and each element of `array` to compute + * their sort ranking. The iteratee is invoked with one argument; (value). + * + * @private + * @param {Array} array The sorted array to inspect. + * @param {*} value The value to evaluate. + * @param {Function} iteratee The iteratee invoked per element. + * @param {boolean} [retHighest] Specify returning the highest qualified index. + * @returns {number} Returns the index at which `value` should be inserted + * into `array`. + */ + function baseSortedIndexBy(array, value, iteratee, retHighest) { + value = iteratee(value); + + var low = 0, + high = array == null ? 0 : array.length, + valIsNaN = value !== value, + valIsNull = value === null, + valIsSymbol = isSymbol(value), + valIsUndefined = value === undefined; + + while (low < high) { + var mid = nativeFloor((low + high) / 2), + computed = iteratee(array[mid]), + othIsDefined = computed !== undefined, + othIsNull = computed === null, + othIsReflexive = computed === computed, + othIsSymbol = isSymbol(computed); + + if (valIsNaN) { + var setLow = retHighest || othIsReflexive; + } else if (valIsUndefined) { + setLow = othIsReflexive && (retHighest || othIsDefined); + } else if (valIsNull) { + setLow = othIsReflexive && othIsDefined && (retHighest || !othIsNull); + } else if (valIsSymbol) { + setLow = othIsReflexive && othIsDefined && !othIsNull && (retHighest || !othIsSymbol); + } else if (othIsNull || othIsSymbol) { + setLow = false; + } else { + setLow = retHighest ? (computed <= value) : (computed < value); + } + if (setLow) { + low = mid + 1; + } else { + high = mid; + } + } + return nativeMin(high, MAX_ARRAY_INDEX); + } + + module.exports = baseSortedIndexBy; + + +/***/ }), +/* 278 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + baseSortedIndexBy = __webpack_require__(277); + + /** + * This method is like `_.sortedIndex` except that it accepts `iteratee` + * which is invoked for `value` and each element of `array` to compute their + * sort ranking. The iteratee is invoked with one argument: (value). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The sorted array to inspect. + * @param {*} value The value to evaluate. + * @param {Function} [iteratee=_.identity] The iteratee invoked per element. + * @returns {number} Returns the index at which `value` should be inserted + * into `array`. + * @example + * + * var objects = [{ 'x': 4 }, { 'x': 5 }]; + * + * _.sortedIndexBy(objects, { 'x': 4 }, function(o) { return o.x; }); + * // => 0 + * + * // The `_.property` iteratee shorthand. + * _.sortedIndexBy(objects, { 'x': 4 }, 'x'); + * // => 0 + */ + function sortedIndexBy(array, value, iteratee) { + return baseSortedIndexBy(array, value, baseIteratee(iteratee, 2)); + } + + module.exports = sortedIndexBy; + + +/***/ }), +/* 279 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSortedIndex = __webpack_require__(276), + eq = __webpack_require__(88); + + /** + * This method is like `_.indexOf` except that it performs a binary + * search on a sorted `array`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @returns {number} Returns the index of the matched value, else `-1`. + * @example + * + * _.sortedIndexOf([4, 5, 5, 5, 6], 5); + * // => 1 + */ + function sortedIndexOf(array, value) { + var length = array == null ? 0 : array.length; + if (length) { + var index = baseSortedIndex(array, value); + if (index < length && eq(array[index], value)) { + return index; + } + } + return -1; + } + + module.exports = sortedIndexOf; + + +/***/ }), +/* 280 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSortedIndex = __webpack_require__(276); + + /** + * This method is like `_.sortedIndex` except that it returns the highest + * index at which `value` should be inserted into `array` in order to + * maintain its sort order. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The sorted array to inspect. + * @param {*} value The value to evaluate. + * @returns {number} Returns the index at which `value` should be inserted + * into `array`. + * @example + * + * _.sortedLastIndex([4, 5, 5, 5, 6], 5); + * // => 4 + */ + function sortedLastIndex(array, value) { + return baseSortedIndex(array, value, true); + } + + module.exports = sortedLastIndex; + + +/***/ }), +/* 281 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + baseSortedIndexBy = __webpack_require__(277); + + /** + * This method is like `_.sortedLastIndex` except that it accepts `iteratee` + * which is invoked for `value` and each element of `array` to compute their + * sort ranking. The iteratee is invoked with one argument: (value). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The sorted array to inspect. + * @param {*} value The value to evaluate. + * @param {Function} [iteratee=_.identity] The iteratee invoked per element. + * @returns {number} Returns the index at which `value` should be inserted + * into `array`. + * @example + * + * var objects = [{ 'x': 4 }, { 'x': 5 }]; + * + * _.sortedLastIndexBy(objects, { 'x': 4 }, function(o) { return o.x; }); + * // => 1 + * + * // The `_.property` iteratee shorthand. + * _.sortedLastIndexBy(objects, { 'x': 4 }, 'x'); + * // => 1 + */ + function sortedLastIndexBy(array, value, iteratee) { + return baseSortedIndexBy(array, value, baseIteratee(iteratee, 2), true); + } + + module.exports = sortedLastIndexBy; + + +/***/ }), +/* 282 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSortedIndex = __webpack_require__(276), + eq = __webpack_require__(88); + + /** + * This method is like `_.lastIndexOf` except that it performs a binary + * search on a sorted `array`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @returns {number} Returns the index of the matched value, else `-1`. + * @example + * + * _.sortedLastIndexOf([4, 5, 5, 5, 6], 5); + * // => 3 + */ + function sortedLastIndexOf(array, value) { + var length = array == null ? 0 : array.length; + if (length) { + var index = baseSortedIndex(array, value, true) - 1; + if (eq(array[index], value)) { + return index; + } + } + return -1; + } + + module.exports = sortedLastIndexOf; + + +/***/ }), +/* 283 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSortedUniq = __webpack_require__(284); + + /** + * This method is like `_.uniq` except that it's designed and optimized + * for sorted arrays. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @returns {Array} Returns the new duplicate free array. + * @example + * + * _.sortedUniq([1, 1, 2]); + * // => [1, 2] + */ + function sortedUniq(array) { + return (array && array.length) + ? baseSortedUniq(array) + : []; + } + + module.exports = sortedUniq; + + +/***/ }), +/* 284 */ +/***/ (function(module, exports, __webpack_require__) { + + var eq = __webpack_require__(88); + + /** + * The base implementation of `_.sortedUniq` and `_.sortedUniqBy` without + * support for iteratee shorthands. + * + * @private + * @param {Array} array The array to inspect. + * @param {Function} [iteratee] The iteratee invoked per element. + * @returns {Array} Returns the new duplicate free array. + */ + function baseSortedUniq(array, iteratee) { + var index = -1, + length = array.length, + resIndex = 0, + result = []; + + while (++index < length) { + var value = array[index], + computed = iteratee ? iteratee(value) : value; + + if (!index || !eq(computed, seen)) { + var seen = computed; + result[resIndex++] = value === 0 ? 0 : value; + } + } + return result; + } + + module.exports = baseSortedUniq; + + +/***/ }), +/* 285 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + baseSortedUniq = __webpack_require__(284); + + /** + * This method is like `_.uniqBy` except that it's designed and optimized + * for sorted arrays. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {Function} [iteratee] The iteratee invoked per element. + * @returns {Array} Returns the new duplicate free array. + * @example + * + * _.sortedUniqBy([1.1, 1.2, 2.3, 2.4], Math.floor); + * // => [1.1, 2.3] + */ + function sortedUniqBy(array, iteratee) { + return (array && array.length) + ? baseSortedUniq(array, baseIteratee(iteratee, 2)) + : []; + } + + module.exports = sortedUniqBy; + + +/***/ }), +/* 286 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86); + + /** + * Gets all but the first element of `array`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to query. + * @returns {Array} Returns the slice of `array`. + * @example + * + * _.tail([1, 2, 3]); + * // => [2, 3] + */ + function tail(array) { + var length = array == null ? 0 : array.length; + return length ? baseSlice(array, 1, length) : []; + } + + module.exports = tail; + + +/***/ }), +/* 287 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86), + toInteger = __webpack_require__(100); + + /** + * Creates a slice of `array` with `n` elements taken from the beginning. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to query. + * @param {number} [n=1] The number of elements to take. + * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. + * @returns {Array} Returns the slice of `array`. + * @example + * + * _.take([1, 2, 3]); + * // => [1] + * + * _.take([1, 2, 3], 2); + * // => [1, 2] + * + * _.take([1, 2, 3], 5); + * // => [1, 2, 3] + * + * _.take([1, 2, 3], 0); + * // => [] + */ + function take(array, n, guard) { + if (!(array && array.length)) { + return []; + } + n = (guard || n === undefined) ? 1 : toInteger(n); + return baseSlice(array, 0, n < 0 ? 0 : n); + } + + module.exports = take; + + +/***/ }), +/* 288 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86), + toInteger = __webpack_require__(100); + + /** + * Creates a slice of `array` with `n` elements taken from the end. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to query. + * @param {number} [n=1] The number of elements to take. + * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. + * @returns {Array} Returns the slice of `array`. + * @example + * + * _.takeRight([1, 2, 3]); + * // => [3] + * + * _.takeRight([1, 2, 3], 2); + * // => [2, 3] + * + * _.takeRight([1, 2, 3], 5); + * // => [1, 2, 3] + * + * _.takeRight([1, 2, 3], 0); + * // => [] + */ + function takeRight(array, n, guard) { + var length = array == null ? 0 : array.length; + if (!length) { + return []; + } + n = (guard || n === undefined) ? 1 : toInteger(n); + n = length - n; + return baseSlice(array, n < 0 ? 0 : n, length); + } + + module.exports = takeRight; + + +/***/ }), +/* 289 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + baseWhile = __webpack_require__(233); + + /** + * Creates a slice of `array` with elements taken from the end. Elements are + * taken until `predicate` returns falsey. The predicate is invoked with + * three arguments: (value, index, array). + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to query. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @returns {Array} Returns the slice of `array`. + * @example + * + * var users = [ + * { 'user': 'barney', 'active': true }, + * { 'user': 'fred', 'active': false }, + * { 'user': 'pebbles', 'active': false } + * ]; + * + * _.takeRightWhile(users, function(o) { return !o.active; }); + * // => objects for ['fred', 'pebbles'] + * + * // The `_.matches` iteratee shorthand. + * _.takeRightWhile(users, { 'user': 'pebbles', 'active': false }); + * // => objects for ['pebbles'] + * + * // The `_.matchesProperty` iteratee shorthand. + * _.takeRightWhile(users, ['active', false]); + * // => objects for ['fred', 'pebbles'] + * + * // The `_.property` iteratee shorthand. + * _.takeRightWhile(users, 'active'); + * // => [] + */ + function takeRightWhile(array, predicate) { + return (array && array.length) + ? baseWhile(array, baseIteratee(predicate, 3), false, true) + : []; + } + + module.exports = takeRightWhile; + + +/***/ }), +/* 290 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + baseWhile = __webpack_require__(233); + + /** + * Creates a slice of `array` with elements taken from the beginning. Elements + * are taken until `predicate` returns falsey. The predicate is invoked with + * three arguments: (value, index, array). + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to query. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @returns {Array} Returns the slice of `array`. + * @example + * + * var users = [ + * { 'user': 'barney', 'active': false }, + * { 'user': 'fred', 'active': false }, + * { 'user': 'pebbles', 'active': true } + * ]; + * + * _.takeWhile(users, function(o) { return !o.active; }); + * // => objects for ['barney', 'fred'] + * + * // The `_.matches` iteratee shorthand. + * _.takeWhile(users, { 'user': 'barney', 'active': false }); + * // => objects for ['barney'] + * + * // The `_.matchesProperty` iteratee shorthand. + * _.takeWhile(users, ['active', false]); + * // => objects for ['barney', 'fred'] + * + * // The `_.property` iteratee shorthand. + * _.takeWhile(users, 'active'); + * // => [] + */ + function takeWhile(array, predicate) { + return (array && array.length) + ? baseWhile(array, baseIteratee(predicate, 3)) + : []; + } + + module.exports = takeWhile; + + +/***/ }), +/* 291 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFlatten = __webpack_require__(108), + baseRest = __webpack_require__(157), + baseUniq = __webpack_require__(292), + isArrayLikeObject = __webpack_require__(166); + + /** + * Creates an array of unique values, in order, from all given arrays using + * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @returns {Array} Returns the new array of combined values. + * @example + * + * _.union([2], [1, 2]); + * // => [2, 1] + */ + var union = baseRest(function(arrays) { + return baseUniq(baseFlatten(arrays, 1, isArrayLikeObject, true)); + }); + + module.exports = union; + + +/***/ }), +/* 292 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetCache = __webpack_require__(116), + arrayIncludes = __webpack_require__(148), + arrayIncludesWith = __webpack_require__(153), + cacheHas = __webpack_require__(156), + createSet = __webpack_require__(293), + setToArray = __webpack_require__(184); + + /** Used as the size to enable large array optimizations. */ + var LARGE_ARRAY_SIZE = 200; + + /** + * The base implementation of `_.uniqBy` without support for iteratee shorthands. + * + * @private + * @param {Array} array The array to inspect. + * @param {Function} [iteratee] The iteratee invoked per element. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new duplicate free array. + */ + function baseUniq(array, iteratee, comparator) { + var index = -1, + includes = arrayIncludes, + length = array.length, + isCommon = true, + result = [], + seen = result; + + if (comparator) { + isCommon = false; + includes = arrayIncludesWith; + } + else if (length >= LARGE_ARRAY_SIZE) { + var set = iteratee ? null : createSet(array); + if (set) { + return setToArray(set); + } + isCommon = false; + includes = cacheHas; + seen = new SetCache; + } + else { + seen = iteratee ? [] : result; + } + outer: + while (++index < length) { + var value = array[index], + computed = iteratee ? iteratee(value) : value; + + value = (comparator || value !== 0) ? value : 0; + if (isCommon && computed === computed) { + var seenIndex = seen.length; + while (seenIndex--) { + if (seen[seenIndex] === computed) { + continue outer; + } + } + if (iteratee) { + seen.push(computed); + } + result.push(value); + } + else if (!includes(seen, computed, comparator)) { + if (seen !== result) { + seen.push(computed); + } + result.push(value); + } + } + return result; + } + + module.exports = baseUniq; + + +/***/ }), +/* 293 */ +/***/ (function(module, exports, __webpack_require__) { + + var Set = __webpack_require__(206), + noop = __webpack_require__(294), + setToArray = __webpack_require__(184); + + /** Used as references for various `Number` constants. */ + var INFINITY = 1 / 0; + + /** + * Creates a set object of `values`. + * + * @private + * @param {Array} values The values to add to the set. + * @returns {Object} Returns the new set. + */ + var createSet = !(Set && (1 / setToArray(new Set([,-0]))[1]) == INFINITY) ? noop : function(values) { + return new Set(values); + }; + + module.exports = createSet; + + +/***/ }), +/* 294 */ +/***/ (function(module, exports) { + + /** + * This method returns `undefined`. + * + * @static + * @memberOf _ + * @since 2.3.0 + * @category Util + * @example + * + * _.times(2, _.noop); + * // => [undefined, undefined] + */ + function noop() { + // No operation performed. + } + + module.exports = noop; + + +/***/ }), +/* 295 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFlatten = __webpack_require__(108), + baseIteratee = __webpack_require__(168), + baseRest = __webpack_require__(157), + baseUniq = __webpack_require__(292), + isArrayLikeObject = __webpack_require__(166), + last = __webpack_require__(228); + + /** + * This method is like `_.union` except that it accepts `iteratee` which is + * invoked for each element of each `arrays` to generate the criterion by + * which uniqueness is computed. Result values are chosen from the first + * array in which the value occurs. The iteratee is invoked with one argument: + * (value). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @param {Function} [iteratee=_.identity] The iteratee invoked per element. + * @returns {Array} Returns the new array of combined values. + * @example + * + * _.unionBy([2.1], [1.2, 2.3], Math.floor); + * // => [2.1, 1.2] + * + * // The `_.property` iteratee shorthand. + * _.unionBy([{ 'x': 1 }], [{ 'x': 2 }, { 'x': 1 }], 'x'); + * // => [{ 'x': 1 }, { 'x': 2 }] + */ + var unionBy = baseRest(function(arrays) { + var iteratee = last(arrays); + if (isArrayLikeObject(iteratee)) { + iteratee = undefined; + } + return baseUniq(baseFlatten(arrays, 1, isArrayLikeObject, true), baseIteratee(iteratee, 2)); + }); + + module.exports = unionBy; + + +/***/ }), +/* 296 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFlatten = __webpack_require__(108), + baseRest = __webpack_require__(157), + baseUniq = __webpack_require__(292), + isArrayLikeObject = __webpack_require__(166), + last = __webpack_require__(228); + + /** + * This method is like `_.union` except that it accepts `comparator` which + * is invoked to compare elements of `arrays`. Result values are chosen from + * the first array in which the value occurs. The comparator is invoked + * with two arguments: (arrVal, othVal). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new array of combined values. + * @example + * + * var objects = [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }]; + * var others = [{ 'x': 1, 'y': 1 }, { 'x': 1, 'y': 2 }]; + * + * _.unionWith(objects, others, _.isEqual); + * // => [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }, { 'x': 1, 'y': 1 }] + */ + var unionWith = baseRest(function(arrays) { + var comparator = last(arrays); + comparator = typeof comparator == 'function' ? comparator : undefined; + return baseUniq(baseFlatten(arrays, 1, isArrayLikeObject, true), undefined, comparator); + }); + + module.exports = unionWith; + + +/***/ }), +/* 297 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseUniq = __webpack_require__(292); + + /** + * Creates a duplicate-free version of an array, using + * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons, in which only the first occurrence of each element + * is kept. The order of result values is determined by the order they occur + * in the array. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to inspect. + * @returns {Array} Returns the new duplicate free array. + * @example + * + * _.uniq([2, 1, 2]); + * // => [2, 1] + */ + function uniq(array) { + return (array && array.length) ? baseUniq(array) : []; + } + + module.exports = uniq; + + +/***/ }), +/* 298 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + baseUniq = __webpack_require__(292); + + /** + * This method is like `_.uniq` except that it accepts `iteratee` which is + * invoked for each element in `array` to generate the criterion by which + * uniqueness is computed. The order of result values is determined by the + * order they occur in the array. The iteratee is invoked with one argument: + * (value). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {Function} [iteratee=_.identity] The iteratee invoked per element. + * @returns {Array} Returns the new duplicate free array. + * @example + * + * _.uniqBy([2.1, 1.2, 2.3], Math.floor); + * // => [2.1, 1.2] + * + * // The `_.property` iteratee shorthand. + * _.uniqBy([{ 'x': 1 }, { 'x': 2 }, { 'x': 1 }], 'x'); + * // => [{ 'x': 1 }, { 'x': 2 }] + */ + function uniqBy(array, iteratee) { + return (array && array.length) ? baseUniq(array, baseIteratee(iteratee, 2)) : []; + } + + module.exports = uniqBy; + + +/***/ }), +/* 299 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseUniq = __webpack_require__(292); + + /** + * This method is like `_.uniq` except that it accepts `comparator` which + * is invoked to compare elements of `array`. The order of result values is + * determined by the order they occur in the array.The comparator is invoked + * with two arguments: (arrVal, othVal). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new duplicate free array. + * @example + * + * var objects = [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }, { 'x': 1, 'y': 2 }]; + * + * _.uniqWith(objects, _.isEqual); + * // => [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }] + */ + function uniqWith(array, comparator) { + comparator = typeof comparator == 'function' ? comparator : undefined; + return (array && array.length) ? baseUniq(array, undefined, comparator) : []; + } + + module.exports = uniqWith; + + +/***/ }), +/* 300 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayFilter = __webpack_require__(189), + arrayMap = __webpack_require__(154), + baseProperty = __webpack_require__(226), + baseTimes = __webpack_require__(193), + isArrayLikeObject = __webpack_require__(166); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeMax = Math.max; + + /** + * This method is like `_.zip` except that it accepts an array of grouped + * elements and creates an array regrouping the elements to their pre-zip + * configuration. + * + * @static + * @memberOf _ + * @since 1.2.0 + * @category Array + * @param {Array} array The array of grouped elements to process. + * @returns {Array} Returns the new array of regrouped elements. + * @example + * + * var zipped = _.zip(['a', 'b'], [1, 2], [true, false]); + * // => [['a', 1, true], ['b', 2, false]] + * + * _.unzip(zipped); + * // => [['a', 'b'], [1, 2], [true, false]] + */ + function unzip(array) { + if (!(array && array.length)) { + return []; + } + var length = 0; + array = arrayFilter(array, function(group) { + if (isArrayLikeObject(group)) { + length = nativeMax(group.length, length); + return true; + } + }); + return baseTimes(length, function(index) { + return arrayMap(array, baseProperty(index)); + }); + } + + module.exports = unzip; + + +/***/ }), +/* 301 */ +/***/ (function(module, exports, __webpack_require__) { + + var apply = __webpack_require__(160), + arrayMap = __webpack_require__(154), + unzip = __webpack_require__(300); + + /** + * This method is like `_.unzip` except that it accepts `iteratee` to specify + * how regrouped values should be combined. The iteratee is invoked with the + * elements of each group: (...group). + * + * @static + * @memberOf _ + * @since 3.8.0 + * @category Array + * @param {Array} array The array of grouped elements to process. + * @param {Function} [iteratee=_.identity] The function to combine + * regrouped values. + * @returns {Array} Returns the new array of regrouped elements. + * @example + * + * var zipped = _.zip([1, 2], [10, 20], [100, 200]); + * // => [[1, 10, 100], [2, 20, 200]] + * + * _.unzipWith(zipped, _.add); + * // => [3, 30, 300] + */ + function unzipWith(array, iteratee) { + if (!(array && array.length)) { + return []; + } + var result = unzip(array); + if (iteratee == null) { + return result; + } + return arrayMap(result, function(group) { + return apply(iteratee, undefined, group); + }); + } + + module.exports = unzipWith; + + +/***/ }), +/* 302 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseDifference = __webpack_require__(115), + baseRest = __webpack_require__(157), + isArrayLikeObject = __webpack_require__(166); + + /** + * Creates an array excluding all given values using + * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. + * + * **Note:** Unlike `_.pull`, this method returns a new array. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {...*} [values] The values to exclude. + * @returns {Array} Returns the new array of filtered values. + * @see _.difference, _.xor + * @example + * + * _.without([2, 1, 2, 3], 1, 2); + * // => [3] + */ + var without = baseRest(function(array, values) { + return isArrayLikeObject(array) + ? baseDifference(array, values) + : []; + }); + + module.exports = without; + + +/***/ }), +/* 303 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayFilter = __webpack_require__(189), + baseRest = __webpack_require__(157), + baseXor = __webpack_require__(304), + isArrayLikeObject = __webpack_require__(166); + + /** + * Creates an array of unique values that is the + * [symmetric difference](https://en.wikipedia.org/wiki/Symmetric_difference) + * of the given arrays. The order of result values is determined by the order + * they occur in the arrays. + * + * @static + * @memberOf _ + * @since 2.4.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @returns {Array} Returns the new array of filtered values. + * @see _.difference, _.without + * @example + * + * _.xor([2, 1], [2, 3]); + * // => [1, 3] + */ + var xor = baseRest(function(arrays) { + return baseXor(arrayFilter(arrays, isArrayLikeObject)); + }); + + module.exports = xor; + + +/***/ }), +/* 304 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseDifference = __webpack_require__(115), + baseFlatten = __webpack_require__(108), + baseUniq = __webpack_require__(292); + + /** + * The base implementation of methods like `_.xor`, without support for + * iteratee shorthands, that accepts an array of arrays to inspect. + * + * @private + * @param {Array} arrays The arrays to inspect. + * @param {Function} [iteratee] The iteratee invoked per element. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new array of values. + */ + function baseXor(arrays, iteratee, comparator) { + var length = arrays.length; + if (length < 2) { + return length ? baseUniq(arrays[0]) : []; + } + var index = -1, + result = Array(length); + + while (++index < length) { + var array = arrays[index], + othIndex = -1; + + while (++othIndex < length) { + if (othIndex != index) { + result[index] = baseDifference(result[index] || array, arrays[othIndex], iteratee, comparator); + } + } + } + return baseUniq(baseFlatten(result, 1), iteratee, comparator); + } + + module.exports = baseXor; + + +/***/ }), +/* 305 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayFilter = __webpack_require__(189), + baseIteratee = __webpack_require__(168), + baseRest = __webpack_require__(157), + baseXor = __webpack_require__(304), + isArrayLikeObject = __webpack_require__(166), + last = __webpack_require__(228); + + /** + * This method is like `_.xor` except that it accepts `iteratee` which is + * invoked for each element of each `arrays` to generate the criterion by + * which by which they're compared. The order of result values is determined + * by the order they occur in the arrays. The iteratee is invoked with one + * argument: (value). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @param {Function} [iteratee=_.identity] The iteratee invoked per element. + * @returns {Array} Returns the new array of filtered values. + * @example + * + * _.xorBy([2.1, 1.2], [2.3, 3.4], Math.floor); + * // => [1.2, 3.4] + * + * // The `_.property` iteratee shorthand. + * _.xorBy([{ 'x': 1 }], [{ 'x': 2 }, { 'x': 1 }], 'x'); + * // => [{ 'x': 2 }] + */ + var xorBy = baseRest(function(arrays) { + var iteratee = last(arrays); + if (isArrayLikeObject(iteratee)) { + iteratee = undefined; + } + return baseXor(arrayFilter(arrays, isArrayLikeObject), baseIteratee(iteratee, 2)); + }); + + module.exports = xorBy; + + +/***/ }), +/* 306 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayFilter = __webpack_require__(189), + baseRest = __webpack_require__(157), + baseXor = __webpack_require__(304), + isArrayLikeObject = __webpack_require__(166), + last = __webpack_require__(228); + + /** + * This method is like `_.xor` except that it accepts `comparator` which is + * invoked to compare elements of `arrays`. The order of result values is + * determined by the order they occur in the arrays. The comparator is invoked + * with two arguments: (arrVal, othVal). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new array of filtered values. + * @example + * + * var objects = [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }]; + * var others = [{ 'x': 1, 'y': 1 }, { 'x': 1, 'y': 2 }]; + * + * _.xorWith(objects, others, _.isEqual); + * // => [{ 'x': 2, 'y': 1 }, { 'x': 1, 'y': 1 }] + */ + var xorWith = baseRest(function(arrays) { + var comparator = last(arrays); + comparator = typeof comparator == 'function' ? comparator : undefined; + return baseXor(arrayFilter(arrays, isArrayLikeObject), undefined, comparator); + }); + + module.exports = xorWith; + + +/***/ }), +/* 307 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseRest = __webpack_require__(157), + unzip = __webpack_require__(300); + + /** + * Creates an array of grouped elements, the first of which contains the + * first elements of the given arrays, the second of which contains the + * second elements of the given arrays, and so on. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {...Array} [arrays] The arrays to process. + * @returns {Array} Returns the new array of grouped elements. + * @example + * + * _.zip(['a', 'b'], [1, 2], [true, false]); + * // => [['a', 1, true], ['b', 2, false]] + */ + var zip = baseRest(unzip); + + module.exports = zip; + + +/***/ }), +/* 308 */ +/***/ (function(module, exports, __webpack_require__) { + + var assignValue = __webpack_require__(309), + baseZipObject = __webpack_require__(311); + + /** + * This method is like `_.fromPairs` except that it accepts two arrays, + * one of property identifiers and one of corresponding values. + * + * @static + * @memberOf _ + * @since 0.4.0 + * @category Array + * @param {Array} [props=[]] The property identifiers. + * @param {Array} [values=[]] The property values. + * @returns {Object} Returns the new object. + * @example + * + * _.zipObject(['a', 'b'], [1, 2]); + * // => { 'a': 1, 'b': 2 } + */ + function zipObject(props, values) { + return baseZipObject(props || [], values || [], assignValue); + } + + module.exports = zipObject; + + +/***/ }), +/* 309 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseAssignValue = __webpack_require__(310), + eq = __webpack_require__(88); + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * Assigns `value` to `key` of `object` if the existing value is not equivalent + * using [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. + * + * @private + * @param {Object} object The object to modify. + * @param {string} key The key of the property to assign. + * @param {*} value The value to assign. + */ + function assignValue(object, key, value) { + var objValue = object[key]; + if (!(hasOwnProperty.call(object, key) && eq(objValue, value)) || + (value === undefined && !(key in object))) { + baseAssignValue(object, key, value); + } + } + + module.exports = assignValue; + + +/***/ }), +/* 310 */ +/***/ (function(module, exports, __webpack_require__) { + + var defineProperty = __webpack_require__(164); + + /** + * The base implementation of `assignValue` and `assignMergeValue` without + * value checks. + * + * @private + * @param {Object} object The object to modify. + * @param {string} key The key of the property to assign. + * @param {*} value The value to assign. + */ + function baseAssignValue(object, key, value) { + if (key == '__proto__' && defineProperty) { + defineProperty(object, key, { + 'configurable': true, + 'enumerable': true, + 'value': value, + 'writable': true + }); + } else { + object[key] = value; + } + } + + module.exports = baseAssignValue; + + +/***/ }), +/* 311 */ +/***/ (function(module, exports) { + + /** + * This base implementation of `_.zipObject` which assigns values using `assignFunc`. + * + * @private + * @param {Array} props The property identifiers. + * @param {Array} values The property values. + * @param {Function} assignFunc The function to assign values. + * @returns {Object} Returns the new object. + */ + function baseZipObject(props, values, assignFunc) { + var index = -1, + length = props.length, + valsLength = values.length, + result = {}; + + while (++index < length) { + var value = index < valsLength ? values[index] : undefined; + assignFunc(result, props[index], value); + } + return result; + } + + module.exports = baseZipObject; + + +/***/ }), +/* 312 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSet = __webpack_require__(313), + baseZipObject = __webpack_require__(311); + + /** + * This method is like `_.zipObject` except that it supports property paths. + * + * @static + * @memberOf _ + * @since 4.1.0 + * @category Array + * @param {Array} [props=[]] The property identifiers. + * @param {Array} [values=[]] The property values. + * @returns {Object} Returns the new object. + * @example + * + * _.zipObjectDeep(['a.b[0].c', 'a.b[1].d'], [1, 2]); + * // => { 'a': { 'b': [{ 'c': 1 }, { 'd': 2 }] } } + */ + function zipObjectDeep(props, values) { + return baseZipObject(props || [], values || [], baseSet); + } + + module.exports = zipObjectDeep; + + +/***/ }), +/* 313 */ +/***/ (function(module, exports, __webpack_require__) { + + var assignValue = __webpack_require__(309), + castPath = __webpack_require__(214), + isIndex = __webpack_require__(99), + isObject = __webpack_require__(97), + toKey = __webpack_require__(221); + + /** + * The base implementation of `_.set`. + * + * @private + * @param {Object} object The object to modify. + * @param {Array|string} path The path of the property to set. + * @param {*} value The value to set. + * @param {Function} [customizer] The function to customize path creation. + * @returns {Object} Returns `object`. + */ + function baseSet(object, path, value, customizer) { + if (!isObject(object)) { + return object; + } + path = castPath(path, object); + + var index = -1, + length = path.length, + lastIndex = length - 1, + nested = object; + + while (nested != null && ++index < length) { + var key = toKey(path[index]), + newValue = value; + + if (index != lastIndex) { + var objValue = nested[key]; + newValue = customizer ? customizer(objValue, key, nested) : undefined; + if (newValue === undefined) { + newValue = isObject(objValue) + ? objValue + : (isIndex(path[index + 1]) ? [] : {}); + } + } + assignValue(nested, key, newValue); + nested = nested[key]; + } + return object; + } + + module.exports = baseSet; + + +/***/ }), +/* 314 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseRest = __webpack_require__(157), + unzipWith = __webpack_require__(301); + + /** + * This method is like `_.zip` except that it accepts `iteratee` to specify + * how grouped values should be combined. The iteratee is invoked with the + * elements of each group: (...group). + * + * @static + * @memberOf _ + * @since 3.8.0 + * @category Array + * @param {...Array} [arrays] The arrays to process. + * @param {Function} [iteratee=_.identity] The function to combine + * grouped values. + * @returns {Array} Returns the new array of grouped elements. + * @example + * + * _.zipWith([1, 2], [10, 20], [100, 200], function(a, b, c) { + * return a + b + c; + * }); + * // => [111, 222] + */ + var zipWith = baseRest(function(arrays) { + var length = arrays.length, + iteratee = length > 1 ? arrays[length - 1] : undefined; + + iteratee = typeof iteratee == 'function' ? (arrays.pop(), iteratee) : undefined; + return unzipWith(arrays, iteratee); + }); + + module.exports = zipWith; + + +/***/ }), +/* 315 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( handlerFunction ){ + var viewer = {}, + lastSelectedElement; + + viewer.handle = function ( selectedElement ){ + // Don't display details on a drag event, which will be prevented + if ( d3.event.defaultPrevented ) { + return; + } + + var isSelection = true; + + // Deselection of the focused element + if ( lastSelectedElement === selectedElement ) { + isSelection = false; + } + + if ( handlerFunction instanceof Function ) { + if ( isSelection ) { + handlerFunction(selectedElement); + } else { + handlerFunction(undefined); + } + } + + if ( isSelection ) { + lastSelectedElement = selectedElement; + } else { + lastSelectedElement = undefined; + } + }; + + /** + * Resets the displayed information to its default. + */ + viewer.reset = function (){ + if ( lastSelectedElement ) { + handlerFunction(undefined); + lastSelectedElement = undefined; + } + }; + + return viewer; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 316 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetOperatorNode = __webpack_require__(20); + + module.exports = function (){ + + var filter = {}, + nodes, + properties, + enabled = false, + filteredNodes, + filteredProperties, + filterTools = __webpack_require__(76)(); + + + /** + * If enabled, all set operators including connected properties are filtered. + * @param untouchedNodes + * @param untouchedProperties + */ + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + + if ( this.enabled() ) { + removeSetOperators(); + } + + filteredNodes = nodes; + filteredProperties = properties; + }; + + function removeSetOperators(){ + var filteredData = filterTools.filterNodesAndTidy(nodes, properties, isNoSetOperator); + + nodes = filteredData.nodes; + properties = filteredData.properties; + } + + function isNoSetOperator( node ){ + return !(node instanceof SetOperatorNode); + } + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }), +/* 317 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var SetOperatorNode = __webpack_require__(20); + var OwlThing = __webpack_require__(31); + var OwlNothing = __webpack_require__(30); + var elementTools = __webpack_require__(63)(); + + module.exports = function (){ + + var statistics = {}, + nodeCount, + occurencesOfClassAndDatatypeTypes = {}, + edgeCount, + occurencesOfPropertyTypes = {}, + classCount, + datatypeCount, + datatypePropertyCount, + objectPropertyCount, + propertyCount, + totalIndividualCount, + filteredNodes, + filteredProperties; + + + statistics.filter = function ( classesAndDatatypes, properties ){ + resetStoredData(); + + storeTotalCounts(classesAndDatatypes, properties); + storeClassAndDatatypeCount(classesAndDatatypes); + storePropertyCount(properties); + + storeOccurencesOfTypes(classesAndDatatypes, occurencesOfClassAndDatatypeTypes); + storeOccurencesOfTypes(properties, occurencesOfPropertyTypes); + + storeTotalIndividualCount(classesAndDatatypes); + + filteredNodes = classesAndDatatypes; + filteredProperties = properties; + }; + + function resetStoredData(){ + nodeCount = 0; + edgeCount = 0; + classCount = 0; + datatypeCount = 0; + datatypePropertyCount = 0; + objectPropertyCount = 0; + propertyCount = 0; + totalIndividualCount = 0; + } + + function storeTotalCounts( classesAndDatatypes, properties ){ + nodeCount = classesAndDatatypes.length; + + var seenProperties = __webpack_require__(62)(), i, l, property; + for ( i = 0, l = properties.length; i < l; i++ ) { + property = properties[i]; + if ( !seenProperties.has(property) ) { + edgeCount += 1; + } + + seenProperties.add(property); + if ( property.inverse() ) { + seenProperties.add(property.inverse()); + } + } + } + + function storeClassAndDatatypeCount( classesAndDatatypes ){ + // Each datatype should be counted just a single time + var datatypeSet = d3.set(), + hasThing = false, + hasNothing = false; + classCount = 0; + var old = 0, newcc = 0; + classesAndDatatypes.forEach(function ( node ){ + if ( elementTools.isDatatype(node) ) { + datatypeSet.add(node.defaultLabel()); + } else if ( !(node instanceof SetOperatorNode) ) { + if ( node instanceof OwlThing ) { + hasThing = true; + } else if ( node instanceof OwlNothing ) { + hasNothing = true; + } else { + old = classCount; + var adds = 1 + countElementArray(node.equivalents()); + classCount += adds; + newcc = classCount; + } + } else if ( node instanceof SetOperatorNode ) { + old = classCount; + classCount += 1; + newcc = classCount; + } + }); + + // count things and nothings just a single time + // classCount += hasThing ? 1 : 0; + // classCount += hasNothing ? 1 : 0; + + datatypeCount = datatypeSet.size(); + } + + function storePropertyCount( properties ){ + for ( var i = 0, l = properties.length; i < l; i++ ) { + var property = properties[i]; + var attr; + var result = false; + if ( property.attributes ) { + attr = property.attributes(); + if ( attr && attr.indexOf("datatype") !== -1 ) { + result = true; + } + } + if ( result === true ) { + datatypePropertyCount += getExtendedPropertyCount(property); + } else if ( elementTools.isObjectProperty(property) ) { + objectPropertyCount += getExtendedPropertyCount(property); + } + } + propertyCount = objectPropertyCount + datatypePropertyCount; + } + + function getExtendedPropertyCount( property ){ + // count the property itself + var count = 1; + + // and count properties this property represents + count += countElementArray(property.equivalents()); + count += countElementArray(property.redundantProperties()); + + return count; + } + + function countElementArray( properties ){ + if ( properties ) { + return properties.length; + } + return 0; + } + + function storeOccurencesOfTypes( elements, storage ){ + elements.forEach(function ( element ){ + var type = element.type(), + typeCount = storage[type]; + + if ( typeof typeCount === "undefined" ) { + typeCount = 0; + } else { + typeCount += 1; + } + storage[type] = typeCount; + }); + } + + function storeTotalIndividualCount( nodes ){ + var sawIndividuals = {}; + var totalCount = 0; + for ( var i = 0, l = nodes.length; i < l; i++ ) { + var individuals = nodes[i].individuals(); + + var tempCount = 0; + for ( var iA = 0; iA < individuals.length; iA++ ) { + if ( sawIndividuals[individuals[iA].iri()] === undefined ) { + sawIndividuals[individuals[iA].iri()] = 1; // this iri for that individual is now set to 1 >> seen it + tempCount++; + } + } + totalCount += tempCount; + } + totalIndividualCount = totalCount; + sawIndividuals = {}; // clear the object + + } + + + statistics.nodeCount = function (){ + return nodeCount; + }; + + statistics.occurencesOfClassAndDatatypeTypes = function (){ + return occurencesOfClassAndDatatypeTypes; + }; + + statistics.edgeCount = function (){ + return edgeCount; + }; + + statistics.occurencesOfPropertyTypes = function (){ + return occurencesOfPropertyTypes; + }; + + statistics.classCount = function (){ + return classCount; + }; + + statistics.datatypeCount = function (){ + return datatypeCount; + }; + + statistics.datatypePropertyCount = function (){ + return datatypePropertyCount; + }; + + statistics.objectPropertyCount = function (){ + return objectPropertyCount; + }; + + statistics.propertyCount = function (){ + return propertyCount; + }; + + statistics.totalIndividualCount = function (){ + return totalIndividualCount; + }; + + + // Functions a filter must have + statistics.filteredNodes = function (){ + return filteredNodes; + }; + + statistics.filteredProperties = function (){ + return filteredProperties; + }; + + + return statistics; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 318 */ +/***/ (function(module, exports, __webpack_require__) { + + var elementTools = __webpack_require__(63)(); + + module.exports = function (){ + + var filter = {}, + nodes, + properties, + enabled = false, + filteredNodes, + filteredProperties; + + + /** + * If enabled subclasses that have only subclass properties are filtered. + * @param untouchedNodes + * @param untouchedProperties + */ + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + + if ( this.enabled() ) { + hideSubclassesWithoutOwnProperties(); + } + + filteredNodes = nodes; + filteredProperties = properties; + }; + + function hideSubclassesWithoutOwnProperties(){ + var unneededProperties = [], + unneededClasses = [], + subclasses = [], + connectedProperties, + subclass, + property, + i, // index, + l; // length + + + for ( i = 0, l = properties.length; i < l; i++ ) { + property = properties[i]; + if ( elementTools.isRdfsSubClassOf(property) ) { + subclasses.push(property.domain()); + } + } + + for ( i = 0, l = subclasses.length; i < l; i++ ) { + subclass = subclasses[i]; + connectedProperties = findRelevantConnectedProperties(subclass, properties); + + // Only remove the node and its properties, if they're all subclassOf properties + if ( areOnlySubclassProperties(connectedProperties) && + doesNotInheritFromMultipleClasses(subclass, connectedProperties) ) { + + unneededProperties = unneededProperties.concat(connectedProperties); + unneededClasses.push(subclass); + } + } + + nodes = removeUnneededElements(nodes, unneededClasses); + properties = removeUnneededElements(properties, unneededProperties); + } + + /** + * Looks recursively for connected properties. Because just subclasses are relevant, + * we just look recursively for their properties. + * + * @param node + * @param allProperties + * @param visitedNodes a visited nodes which is used on recursive invocation + * @returns {Array} + */ + function findRelevantConnectedProperties( node, allProperties, visitedNodes ){ + var connectedProperties = [], + property, + i, + l; + + for ( i = 0, l = allProperties.length; i < l; i++ ) { + property = allProperties[i]; + if ( property.domain() === node || + property.range() === node ) { + + connectedProperties.push(property); + + + /* Special case: SuperClass <-(1) Subclass <-(2) Subclass ->(3) e.g. Datatype + * We need to find the last property recursively. Otherwise, we would remove the subClassOf + * property (1) because we didn't see the datatype property (3). + */ + + // Look only for subclass properties, because these are the relevant properties + if ( elementTools.isRdfsSubClassOf(property) ) { + var domain = property.domain(); + visitedNodes = visitedNodes || __webpack_require__(62)(); + + // If we have the range, there might be a nested property on the domain + if ( node === property.range() && !visitedNodes.has(domain) ) { + visitedNodes.add(domain); + var nestedConnectedProperties = findRelevantConnectedProperties(domain, allProperties, visitedNodes); + connectedProperties = connectedProperties.concat(nestedConnectedProperties); + } + } + } + } + + return connectedProperties; + } + + function areOnlySubclassProperties( connectedProperties ){ + var onlySubclassProperties = true, + property, + i, + l; + + for ( i = 0, l = connectedProperties.length; i < l; i++ ) { + property = connectedProperties[i]; + + if ( !elementTools.isRdfsSubClassOf(property) ) { + onlySubclassProperties = false; + break; + } + } + + return onlySubclassProperties; + } + + function doesNotInheritFromMultipleClasses( subclass, connectedProperties ){ + var superClassCount = 0; + + for ( var i = 0, l = connectedProperties.length; i < l; i++ ) { + var property = connectedProperties[i]; + + if ( property.domain() === subclass ) { + superClassCount += 1; + } + + if ( superClassCount > 1 ) { + return false; + } + } + + return true; + } + + function removeUnneededElements( array, removableElements ){ + var disjoint = [], + element, + i, + l; + + for ( i = 0, l = array.length; i < l; i++ ) { + element = array[i]; + if ( removableElements.indexOf(element) === -1 ) { + disjoint.push(element); + } + } + return disjoint; + } + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }) +/******/ ]); \ No newline at end of file diff --git a/doc/releases/0.1.0/data/webvowl/license.txt b/doc/releases/0.1.0/data/webvowl/license.txt new file mode 100644 index 0000000..008e54c --- /dev/null +++ b/doc/releases/0.1.0/data/webvowl/license.txt @@ -0,0 +1,21 @@ +The MIT License (MIT) + +Copyright (c) 2014-2019 Vincent Link, Steffen Lohmann, Eduard Marbach, Stefan Negru, Vitalis Wiens + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in +all copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. 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    language en
    +

    Neuroelectrophysiology Analysis Ontology

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    Release: 2024-12-06

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    This version:
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    http://purl.org/neao/0.1.0/
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    Latest version:
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    http://purl.org/neao/
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    Revision:
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    0.1.0
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    Issued on:
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    2024-12-06
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    Authors:
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    Cristiano Köhler, Forschungszentrum Jülich
    Michael Denker, Forschungszentrum Jülich
    + +
    Download serialization:
    JSON-LD RDF/XML N-Triples TTL
    License:
    https://creativecommons.org/licenses/by/4.0/ +
    + +Provenance of this page
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    +
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    +Ontology Specification Draft +
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    + + +

    Introduction back to ToC

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    The Neuroelectrophysiology Analysis Ontology (NEAO) defines a controlled vocabulary and conceptual representations of the typical processes involved in the analysis of neural activity data acquired using electrophysiology techniques.

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    Electrophysiology is a branch of physiology that studies the electrical properties of biological entities. The studies involve measurements of electric potentials and/or currents, as well as electrical manipulations (e.g. stimuli with electric pulses). Neuroelectrophysiology is the application of electrophysiology techniques to investigate the function of neural tissue.

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    Neuroelectrophysiology recording is the process of data acquisition, and it usually involves placing electrodes (of several configurations and types) into a preparation of neural tissue. The data will contain a representation of the voltages or currents in the preparation during the recording session, usually as a time series. The analysis requires specific methods to progressively process and transform the recorded data, which generate results and insights.

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    The scope of the NEAO aims to provide a comprehensive representation of neuroelectrophysiology data and analysis processes, standardizing the description of their properties and relationships. The NEAO does not provide a detailed representation of electrophysiology recording techniques, data acquisition methods/equipment, and experimental settings/subjects. The goal is to ensure a common representation of data analysis that can be used by tools to provide a detailed and semantically-enriched description of the processes involved.

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    NEAO: Description back to ToC

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    The NEAO design assumes that neuroelectrophysiology data analysis consists of a sequence of small, atomic steps, each performing a specific action to generate, transform, or characterize data.

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    For example, consider the example below illustrating the sequence of steps to plot the power spectral density (PSD) of a local field potential (LFP) time series recorded by an extracellular electrode implanted in a brain area and saved to a data file. + +

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    First, the raw data is loaded from the file into a data structure containing the voltage time series acquired by the recording equipment. The LFP is the low-frequency component of the extracellular signal (e.g., below 250 Hz), so a low-pass filter with a 250 Hz cutoff is applied to obtain the LFP time series. The PSD is then computed from the filtered data, resulting in an array of power density estimates for various frequency values. This power spectrum can be plotted and saved to a file. In this example, each step takes input data, processes it, and produces output data, with parameters (e.g., the low-pass cutoff frequency for filtering) controlling each step.

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    We propose the NEAO to describe such scenarios: + +

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    NEAO is organized around the central AnalysisStep class to model the atomic steps of the analysis. This class represents any process that generates new data entities (e.g., generating artificial LFP data) or performs specific operations to extract additional information from existing data entities. These operations include data transformations (e.g., filtering the raw signal into the LFP) or computations of new, derived data (e.g., obtaining the PSD from the LFP signal). Thus, each analysis step either acts on existing data entities or produces new data.

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    Two additional classes complete the core of the ontology model: Data and AnalysisParameter.

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    The Data class represents any entity containing information used during the analysis and serves as the input and output for analysis steps. It can represent data obtained from biological electrophysiology recordings or data generated or transformed during analysis steps. In the example of computing the PSD from an electrode signal, the raw signal time series, the filtered LFP time series, the resulting PSD estimate array, and the plot are all instances of the Data class.

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    The AnalysisParameter class represents information entities that control the behavior of an analysis step. These parameters do not provide data to the step but influence its output. In the example above, the filter step uses a 250 Hz low-frequency cutoff parameter to set the bandwidth of the output signal. + +

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    Solving ambiguities in the description of neuroelectrophysiology data analysis

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    To accurately describe neuroelectrophysiology data analysis, two key aspects must be considered:

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    1. Multiple complementary and overlapping analysis methods can be used to understand a feature of brain activity from the recorded data, with each method's strengths and limitations influencing the results. For instance, various algorithms can compute the PSD of recorded signals, each producing similar measures but with different interpretations based on characteristics such as their frequency resolution.

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    2. The implementation of a specific analysis method can vary across different software tools, potentially leading to subtle differences in results even when using the same underlying method.

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    Therefore, a clear and unambiguous description of both the methodology and the software implementations is essential for reliable insights into neuroelectrophysiology data analysis. NEAO aims to address the ambiguities that can be present when describing the steps, data, and parameters during the analysis:

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    • Naming: NEAO introduces a controlled vocabulary for naming classes, which is associated with a clear description, to avoid confusion with similar terms. Moreover, each class has a clear label, alternative labels to account for synonyms, and common abbreviations.

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    • Code: NEAO structures details of the code executing an analysis step ensuring precise identification of software tools and their versions.

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    • Bibliographic References: NEAO links analysis steps to specific publications ensuring clear identification of the method’s version and its detailed description.

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    Obtaining broader insights on the analyses by semantic groupings

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    The main NEAO classes provide detailed descriptions of specific analysis steps, data, and parameters. One example of a specific step is the computation of a PSD using either the Welch or the multitaper method.

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    However, to gain broader insights, general information about the analysis must be available. For instance, instead of querying if an analysis step used a specific method for computing a PSD (such as the Welch or multitaper), one may be interested in identifying if the analysis step is part of a category of methods (that includes any method that computes a PSD).

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    NEAO provides classes that introduce those semantic groupings, organizing the information in relevant categories and allowing more generalized insights on the analyses.

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    NEAO organization

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    The NEAO definitions are divided into submodules, each defining a small ontology associated with a single namespace.

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    The core model is defined in a base module, and each of the three main classes (AnalysisStep, Data, and AnalysisParameter) is expanded in additional modules.

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    The documentation for each submodule provides extended details on the implementation, and is accessible in the table below:

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    Individual modules defined in NEAO
    RootThe overall module, that contains the main metadata and publishing information of NEAO.neao<http://purl.org/neao/>
    BaseThe top-level classes of the NEAO model that are imported by other modules. It defines the three main classes, the software implementation description, and all the related properties.neao_base<http://purl.org/neao/base#>
    StepsModule to extend the AnalysisStep base class, in order to define the specific analysis steps and their semantic groupings.neao_steps<http://purl.org/neao/steps#>
    DataModule to extend the Data base class, in order to define the specific data entities and their semantic groupings.neao_data<http://purl.org/neao/data#>
    ParametersModule to extend the AnalysisParameter base class, in order to define the specific parameters and their semantic groupings.neao_params<http://purl.org/neao/parameters#>
    BibliographyDefine individuals with the bibliographic references used to annotate AnalysisStep classes.neao_bib<http://purl.org/neao/bibliography#>
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    Acknowledgments back to ToC

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    This work was performed as part of the Helmholtz School for Data Science in Life, Earth and Energy (HDS-LEE) and received funding from the Helmholtz Association of German Research Centres. This project has received funding from the European Union’s Horizon 2020 Framework Programme for Research and Innovation under Specific Grant Agreement No. 945539 (Human Brain Project SGA3), the European Union’s Horizon Europe Programme under the Specific Grant Agreement No. 101147319 (EBRAINS 2.0 Project), the Ministry of Culture and Science of the State of North Rhine-Westphalia, Germany (NRW-network "iBehave", grant number: NW21-049), and the Joint Lab "Supercomputing and Modeling for the Human Brain."

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    The authors would like to thank Silvio Peroni for developing LODE, a Live OWL Documentation Environment, which is used for representing the Cross Referencing Section of this document and Daniel Garijo for developing Widoco, the program used to create the template used in this documentation.

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    + + +
    + + + + + + + diff --git a/doc/releases/0.1.0/neao.jsonld b/doc/releases/0.1.0/neao.jsonld new file mode 100644 index 0000000..411c686 --- /dev/null +++ b/doc/releases/0.1.0/neao.jsonld @@ -0,0 +1,12813 @@ +[ { + "@id" : "_:genid1", + "@type" : [ "http://www.w3.org/2002/07/owl#Restriction" ], + "http://www.w3.org/2002/07/owl#hasValue" : [ { + "@type" : "http://www.w3.org/2001/XMLSchema#boolean", + "@value" : "true" + } ], + "http://www.w3.org/2002/07/owl#onProperty" : [ { + "@id" : "http://purl.org/neao/data#isArtificial" + } ] +}, { + "@id" : "_:genid10", + "@type" : [ "http://www.w3.org/2002/07/owl#Restriction" ], + "http://www.w3.org/2002/07/owl#hasValue" : [ { + "@type" : "http://www.w3.org/2001/XMLSchema#boolean", + "@value" : "false" + } ], + "http://www.w3.org/2002/07/owl#onProperty" : [ { + "@id" : "http://purl.org/neao/steps#isDirected" + } ] +}, { + "@id" : "_:genid100", + "@type" : [ "http://www.w3.org/2002/07/owl#Restriction" ], + 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It can be recorded from a biological entity or from a simulation yielding comparable data, or it can be generated/transformed by other analysis step processes." + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "data" + } ] +}, { + "@id" : "http://purl.org/neao/base#DataRepresentation", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Defines the formal structure to represent a piece of data." + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "data representation" + } ] +}, { + "@id" : "http://purl.org/neao/base#ElectrophysiologySignalSource", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Defines the source of a recorded piece of electrophysiology data, i.e., the recorded signals. 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A function performs specific tasks, and can be implemented as part of a single computer program or in a software package (library) so that it can be reused across several programs." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#SoftwareImplementation" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "function" + } ] +}, { + "@id" : "http://purl.org/neao/base#Program", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A set of instructions that is executed by a computer. The instructions of the program can be executed by an interpreter or compiled to machine code. 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The software contains a sequence or set of instructions that is used by the computer to perform all the computations required to execute the analysis step." + } ], + "http://www.w3.org/2002/07/owl#disjointWith" : [ { + "@id" : "http://purl.org/neao/base#SoftwarePackage" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "software implementation" + } ] +}, { + "@id" : "http://purl.org/neao/base#SoftwarePackage", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A collection of one or more programs that can be executed by a computer and/or one or more functions that can be imported and used when writing programs." + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "software package" + } ] +}, { + "@id" : "http://purl.org/neao/base#abbreviation", + "@type" : [ "http://www.w3.org/2002/07/owl#AnnotationProperty" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A string defining an abbreviation that is frequently used to refer to individuals represented by the class." + } ], + "http://www.w3.org/2000/01/rdf-schema#range" : [ { + "@id" : "http://www.w3.org/2001/XMLSchema#string" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "abbreviation" + } ] +}, { + "@id" : "http://purl.org/neao/base#hasBibliographicReference", + "@type" : [ "http://www.w3.org/2002/07/owl#AnnotationProperty" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Defines the bibliographic reference associated with the entity. 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"http://purl.org/neao/data#PhaseLockingValueMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "corrected imaginary phase locking value" + } ] +}, { + "@id" : "http://purl.org/neao/data#CorrelationMeasure", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Data that contains a measure of correlation." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "correlation measure" + } ] +}, { + "@id" : "http://purl.org/neao/data#Covariance", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed covariance values between the inputs." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#CovarianceMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "covariance" + } ] +}, { + "@id" : "http://purl.org/neao/data#CovarianceMeasure", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Data that contains a measure of covariance." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "covariance measure" + } ] +}, { + "@id" : "http://purl.org/neao/data#CrossCorrelationFunction", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "CCF" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed estimator of the cross-correlation function." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#CrossCorrelationMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "cross-correlation function" + } ] +}, { + "@id" : "http://purl.org/neao/data#CrossCorrelationMeasure", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Data that contains a measure of cross-correlation." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "cross-correlation measure" + } ] +}, { + "@id" : "http://purl.org/neao/data#CrossPowerSpectralDensity", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "CPSD" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed cross power spectral density (CPSD)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#SpectralDensity" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "cross-spectrum" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "cross power spectral density" + } ] +}, { + "@id" : "http://purl.org/neao/data#CrossSpectrogram", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed cross-spectrogram." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "cross-spectrogram" + } ] +}, { + "@id" : "http://purl.org/neao/data#CubicAnalysisResult", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The result of the CuBIC analysis." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#SpikeTrainSynchronyMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "CuBIC analysis result" + } ] +}, { + "@id" : "http://purl.org/neao/data#CurrentSourceDensity", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "CSD" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The profile of current densities estimated by a current source density analysis." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "current source density" + } ] +}, { + "@id" : "http://purl.org/neao/data#DebiasedSquaredWeightedPhaseLagIndex", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "debiased squared WPLI" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed debiased squared weighted phase lag index (WPLI)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#PhaseLagIndexMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "debiased squared weighted phase lag index" + } ] +}, { + "@id" : "http://purl.org/neao/data#DimensionalityReductionOutput", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Data that contains an output of applying a dimensionality reduction transformation to the input data." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2002/07/owl#equivalentClass" : [ { + "@id" : "_:genid2" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "dimensionality reduction output" + } ] +}, { + "@id" : "http://purl.org/neao/data#DirectedPhaseLagIndex", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "DPLI" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed directed phase lag index (DPLI)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#PhaseLagIndexMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "directed phase lag index" + } ] +}, { + "@id" : "http://purl.org/neao/data#DirectedTransferFunction", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "DTF" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed directed transfer function (DTF)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "directed transfer function" + } ] +}, { + "@id" : "http://purl.org/neao/data#DirectionalGrangerCausality", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed directional Granger causality from one input to the other." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#GrangerCausalityMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "directional Granger causality" + } ] +}, { + "@id" : "http://purl.org/neao/data#DiscreteFourierTransform", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "DFT" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The complex sinusoid coefficients obtained by applying the Discrete Fourier Transform (DFT) to the input data (e.g., using the FFT algorithm)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "discrete Fourier transform" + } ] +}, { + "@id" : "http://purl.org/neao/data#DistanceCovarianceDimension", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A dimension identified by applying distance covariance analysis (DCA) to the input data." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#DimensionalityReductionOutput" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "distance covariance dimension" + } ] +}, { + "@id" : "http://purl.org/neao/data#Epoch", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Data that represents a finite time interval (window). 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"http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "event" + } ] +}, { + "@id" : "http://purl.org/neao/data#EventRelatedPotential", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "ERP" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed event-related potential (ERP)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "event-related potential" + } ] +}, { + "@id" : "http://purl.org/neao/data#EventTriggeredAverage", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed event-triggered average." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#TriggeredAverageMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "event-triggered average" + } ] +}, { + "@id" : "http://purl.org/neao/data#EvokedPotential", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "EP" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed evoked potential (EP)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#EventRelatedPotential" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "evoked potential" + } ] +}, { + "@id" : "http://purl.org/neao/data#FiringRate", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed firing rate." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "firing rate" + } ] +}, { + "@id" : "http://purl.org/neao/data#FisherLinearDiscriminant", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A Fisher linear discriminant obtained by applying linear discrimination analysis (LDA) to the input data." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#DimensionalityReductionOutput" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "Fisher linear discriminant" + } ] +}, { + "@id" : "http://purl.org/neao/data#GrangerCausalityMeasure", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Data that contains a measure of Granger causality." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "Granger causality measure" + } ] +}, { + "@id" : "http://purl.org/neao/data#GrangerTotalInterdependence", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed total interdependence in the Granger causality analysis." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#GrangerCausalityMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "Granger total interdependence" + } ] +}, { + "@id" : "http://purl.org/neao/data#ISIDistance", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed ISI-distance." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#SpikeTrainDistance" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "ISI-distance" + } ] +}, { + "@id" : "http://purl.org/neao/data#ImaginaryCoherency", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed imaginary part of the coherency." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#CoherencyMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "imaginary coherency" + } ] +}, { + "@id" : "http://purl.org/neao/data#IndependentComponent", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Data that contains an independent component produced by applying independent component analysis (ICA) to the input data." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "independent component" + } ] +}, { + "@id" : "http://purl.org/neao/data#InstantaneousFiringRate", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed instantaneous firing rate." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#FiringRate" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "instantaneous firing rate" + } ] +}, { + "@id" : "http://purl.org/neao/data#InstantaneousGrangerCausality", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed instantaneous Granger causality." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#GrangerCausalityMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "instantaneous Granger causality" + } ] +}, { + "@id" : "http://purl.org/neao/data#InterquartileRange", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "IQR" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed interquartile range, with the difference between the 75th and 25th percentile values." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#InterquartileRangeMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "interquartile range" + } ] +}, { + "@id" : "http://purl.org/neao/data#InterquartileRangeLowerLimit", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The lower limit of the computed interquartile range, corresponding to the 25th percentile." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#InterquartileRangeMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "lower limit of interquartile range" + } ] +}, { + "@id" : "http://purl.org/neao/data#InterquartileRangeMeasure", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "IQR measure" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Data that contains the description of an interquartile range (IQR)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "interquartile range measure" + } ] +}, { + "@id" : "http://purl.org/neao/data#InterquartileRangeUpperLimit", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The upper limit of the computed interquartile range, corresponding to the 75th percentile." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#InterquartileRangeMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "upper limit of interquartile range" + } ] +}, { + "@id" : "http://purl.org/neao/data#InterspikeIntervalHistogram", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "ISIH" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed interspike interval histogram (ISIH)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "interspike interval histogram" + } ] +}, { + "@id" : "http://purl.org/neao/data#InterspikeIntervalVariabilityMeasure", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Data that contains a measure describing the variability of the interspike intervals." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "interspike interval variability measure" + } ] +}, { + "@id" : "http://purl.org/neao/data#InterspikeIntervals", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "ISIs" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed interspike intervals (ISIs)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "interspike intervals" + } ] +}, { + "@id" : "http://purl.org/neao/data#JointPeristimulusTimeHistogramMatrix", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "JPSTH matrix" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed joint peristimulus time histogram (JPSTH) matrix." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "joint peristimulus time histogram matrix" + } ] +}, { + "@id" : "http://purl.org/neao/data#LV", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed local variation (LV) measure." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#InterspikeIntervalVariabilityMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "LV" + } ] +}, { + "@id" : "http://purl.org/neao/data#LVR", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed revised local variation (LvR) measure." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#InterspikeIntervalVariabilityMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "LvR" + } ] +}, { + "@id" : "http://purl.org/neao/data#MagnitudeCoherence", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed magnitude coherence." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#CoherenceMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "magnitude coherence" + } ] +}, { + "@id" : "http://purl.org/neao/data#MaximizedImaginaryCoherency", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "MIC" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed maximized imaginary coherency (MIC)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#CoherencyMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "maximized imaginary coherency" + } ] +}, { + "@id" : "http://purl.org/neao/data#Mean", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed mean." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "mean" + } ] +}, { + "@id" : "http://purl.org/neao/data#MeanFiringRate", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "MFR" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed mean firing rate." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#FiringRate" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "mean firing rate" + } ] +}, { + "@id" : "http://purl.org/neao/data#MeanPhaseVector", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed mean phase vector (i.e., the angle and length)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#MeanPhaseVectorMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "mean phase vector" + } ] +}, { + "@id" : "http://purl.org/neao/data#MeanPhaseVectorAngle", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The angle of the computed mean phase vector." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#MeanPhaseVectorMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "mean phase vector angle" + } ] +}, { + "@id" : "http://purl.org/neao/data#MeanPhaseVectorLength", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The length of the computed mean phase vector." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#MeanPhaseVectorMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "mean phase vector length" + } ] +}, { + "@id" : "http://purl.org/neao/data#MeanPhaseVectorMeasure", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Data that contains the description or elements of the mean phase vector." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "mean phase vector measure" + } ] +}, { + "@id" : "http://purl.org/neao/data#MeanVectorLength", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "MVL" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed mean vector length (MVL)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#PhaseAmplitudeCouplingMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "mean vector length" + } ] +}, { + "@id" : "http://purl.org/neao/data#Median", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed median." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "median" + } ] +}, { + "@id" : "http://purl.org/neao/data#ModulationIndex", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "MI" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed modulation index (MI)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#PhaseAmplitudeCouplingMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "modulation index" + } ] +}, { + "@id" : "http://purl.org/neao/data#MorletWavelet", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Data that contains the generated Morlet wavelet values for a sequence of time points." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "Morlet wavelet" + } ] +}, { + "@id" : "http://purl.org/neao/data#MultivariateInteractionMeasure", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "MIM" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed multivariate interaction measure (MIM)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "multivariate interaction measure" + } ] +}, { + "@id" : "http://purl.org/neao/data#MutualInformation", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "MI" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed mutual information (MI)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "mutual information" + } ] +}, { + "@id" : "http://purl.org/neao/data#NeuralTrajectory", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A neural trajectory obtained by applying Gaussian process factor analysis (GPFA) to the input data containing multitrial spiking activity of a neuronal population." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#TimeSeries" + }, { + "@id" : "_:genid3" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "neural trajectory" + } ] +}, { + "@id" : "http://purl.org/neao/data#NeuronalActivityPattern", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Data that contains the description of a neuronal activity pattern, which is obtained from a neuronal activity pattern detection analysis." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "cell assembly" + }, { + "@language" : "en", + "@value" : "neuronal assembly" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "neuronal activity pattern" + } ] +}, { + "@id" : "http://purl.org/neao/data#NeuronalPopulationVector", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed neuronal population vector." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "population vector" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "neuronal population vector" + } ] +}, { + "@id" : "http://purl.org/neao/data#NoiseCorrelations", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "NC" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed noise correlations (NC)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#SpikeTrainCorrelationMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "noise correlations" + } ] +}, { + "@id" : "http://purl.org/neao/data#NoiseCovariance", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed noise covariance." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#CovarianceMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "noise covariance" + } ] +}, { + "@id" : "http://purl.org/neao/data#OrthogonalizedPowerEnvelopeCorrelation", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed orthogonalized power envelope correlation." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#CorrelationMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "orthogonalized power envelope correlation" + } ] +}, { + "@id" : "http://purl.org/neao/data#PairwisePhaseConsistency", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "PPC" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed pairwise phase consistency (PPC) measure." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "pairwise phase consistency" + } ] +}, { + "@id" : "http://purl.org/neao/data#PartialCoherence", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed partial coherence." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#CoherenceMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "partial coherence" + } ] +}, { + "@id" : "http://purl.org/neao/data#PartialDirectedCoherence", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "PDC" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed partial directed coherence (PDC)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "partial directed coherence" + } ] +}, { + "@id" : "http://purl.org/neao/data#PeristimulusCoincidenceHistogram", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed peristimulus coincidence histogram." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "peristimulus coincidence histogram" + } ] +}, { + "@id" : "http://purl.org/neao/data#PeristimulusTimeHistogram", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "PSTH" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed peristimulus time histogram (PSTH). The stimulus or event of interest can occur at any time point within the interval analyzed. However, if the histogram represents the neuronal activity after the stimulus presentation or event occurrence, this can be referred as post-stimulus time histogram. Conversely, if the histogram shows the activity of the neuron before the stimulus presentation or event, this can be referred as prestimulus time histogram. Finally, if the histogram considers a behavioral event (or an event that is not an externally presented stimulus), the histogram can be referred to as perievent time histogram (PETH)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#TimeHistogram" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "perievent time histogram" + }, { + "@language" : "en", + "@value" : "post-stimulus time histogram" + }, { + "@language" : "en", + "@value" : "prestimulus time histogram" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "peristimulus time histogram" + } ] +}, { + "@id" : "http://purl.org/neao/data#PhaseAmplitudeCouplingMeasure", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "PAC measure" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Data that contains a measure of phase-amplitude coupling (PAC)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "phase amplitude coupling measure" + } ] +}, { + "@id" : "http://purl.org/neao/data#PhaseAngles", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A measure of phase defining the angle on the unit circle that corresponds to the current position within the waveform's cycle. The range of angles in a full cycle is from 0 to 2*pi radians or 0 to 360 degrees." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "phase angles" + } ] +}, { + "@id" : "http://purl.org/neao/data#PhaseLagIndex", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "PLI" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed phase lag index (PLI)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#PhaseLagIndexMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "phase lag index" + } ] +}, { + "@id" : "http://purl.org/neao/data#PhaseLagIndexMeasure", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "PLI measure" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Data that contains a measure computed by a phase-lag index analysis." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "phase lag index measure" + } ] +}, { + "@id" : "http://purl.org/neao/data#PhaseLockingValue", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "PLV" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed phase locking value (PLV)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#PhaseLockingValueMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "phase locking value" + } ] +}, { + "@id" : "http://purl.org/neao/data#PhaseLockingValueMeasure", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "PLV measure" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Data that contains a phase locking value (PLV) measure." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "phase locking value measure" + } ] +}, { + "@id" : "http://purl.org/neao/data#PhaseSlopeIndex", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "PSI" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed phase slope index (PSI)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "phase slope index" + } ] +}, { + "@id" : "http://purl.org/neao/data#Plot", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A graphical representation of data values. It is used to visually communicate quantitative information, providing intuitive insights that can complement numerical analysis. It is often produced by later steps in the analysis after the computation of measures, to provide the visual representation of the results." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "plot" + } ] +}, { + "@id" : "http://purl.org/neao/data#PopulationHistogram", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed population histogram." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#TimeHistogram" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "population histogram" + } ] +}, { + "@id" : "http://purl.org/neao/data#PowerSpectralDensity", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "PSD" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed power spectral density (PSD)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#SpectralDensity" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "spectrum" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "power spectral density" + } ] +}, { + "@id" : "http://purl.org/neao/data#PrincipalComponent", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A principal component obtained by applying principal component analysis (PCA) to the input data." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#DimensionalityReductionOutput" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "principal component" + } ] +}, { + "@id" : "http://purl.org/neao/data#RectifiedAreaUnderCurve", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "RAUC" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed rectified area under the curve (RAUC)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "rectified area under the curve" + } ] +}, { + "@id" : "http://purl.org/neao/data#RegularizedCovariance", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The covariance values computed with regularization techniques for numerical stability." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#Covariance" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "regularized covariance" + } ] +}, { + "@id" : "http://purl.org/neao/data#SPADEPattern", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A neuronal activity pattern obtained by the Spatio-temporal PAttern Detection and Evaluation (SPADE) analysis." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#NeuronalActivityPattern" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "SPADE pattern" + } ] +}, { + "@id" : "http://purl.org/neao/data#SPIKEDistance", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed SPIKE distance." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#SpikeTrainDistance" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "SPIKE distance" + } ] +}, { + "@id" : "http://purl.org/neao/data#SPIKESynchronization", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed SPIKE synchronization distance." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#SpikeTrainDistance" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "SPIKE synchronization" + } ] +}, { + "@id" : "http://purl.org/neao/data#ShortTimeFourierTransform", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "STFT" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The complex sinusoid coefficients obtained by applying the short-time Fourier transform (STFT) to the input data." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "short-time Fourier transform" + } ] +}, { + "@id" : "http://purl.org/neao/data#SpectralDensity", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Data that contains the density of a measure of the input(s) over the frequency spectrum." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spectral density" + } ] +}, { + "@id" : "http://purl.org/neao/data#Spectrogram", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed spectrogram." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spectrogram" + } ] +}, { + "@id" : "http://purl.org/neao/data#SpikeContrast", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed Spike-contrast." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#SpikeTrainSynchronyMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "Spike-contrast" + } ] +}, { + "@id" : "http://purl.org/neao/data#SpikeFieldCoherence", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "SFC" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed spike-field coherence (SFC)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spike-field coherence" + } ] +}, { + "@id" : "http://purl.org/neao/data#SpikeTimeTilingCoefficient", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "STTC" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed spike time tiling coefficient (STTC)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#SpikeTrainCorrelationMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spike time tiling coefficient" + } ] +}, { + "@id" : "http://purl.org/neao/data#SpikeTrain", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Data that contains the sequence of time points when an action potential (spike) occurs. A spike train can be obtained by electrophysiological recordings from the neural tissue (i.e., the data contains the times when spikes occur naturally in response to various stimuli or during spontaneous activity) or artificially-generated using specific statistical procedures or simulations of neuronal activity." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2002/07/owl#disjointWith" : [ { + "@id" : "http://purl.org/neao/data#SpikeTrainSurrogate" + }, { + "@id" : "http://purl.org/neao/data#TimeSeries" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spike train" + } ] +}, { + "@id" : "http://purl.org/neao/data#SpikeTrainAutocorrelationHistogram", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed spike train autocorrelation histogram." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#AutocorrelationMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spike train autocorrelation histogram" + } ] +}, { + "@id" : "http://purl.org/neao/data#SpikeTrainAutocorrelationTimeScale", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed spike train autocorrelation time scale." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spike train autocorrelation time scale" + } ] +}, { + "@id" : "http://purl.org/neao/data#SpikeTrainCorrelationMeasure", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Data that contains a measure estimating the correlation between spike trains." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#CorrelationMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "correlation measure" + } ] +}, { + "@id" : "http://purl.org/neao/data#SpikeTrainCrossCorrelationHistogram", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "CCH" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed spike train cross-correlation histogram." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#CrossCorrelationMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "correlogram" + }, { + "@language" : "en", + "@value" : "cross-correlogram" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spike train cross-correlation histogram" + } ] +}, { + "@id" : "http://purl.org/neao/data#SpikeTrainDistance", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Data that contains a spike train distance measure." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spike train distance" + } ] +}, { + "@id" : "http://purl.org/neao/data#SpikeTrainFanoFactor", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "FF" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed Fano factor (FF) for a set of input spike trains." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spike train Fano factor" + } ] +}, { + "@id" : "http://purl.org/neao/data#SpikeTrainPearsonCorrelationCoefficient", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed Pearson correlation coefficient between two spike trains." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#SpikeTrainCorrelationMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spike train Pearson correlation coefficient" + } ] +}, { + "@id" : "http://purl.org/neao/data#SpikeTrainSurrogate", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Data that contains a spike train surrogate. It is generated from spike train inputs using distinct methods to alter the original spike times." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2002/07/owl#disjointWith" : [ { + "@id" : "http://purl.org/neao/data#TimeSeries" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spike train surrogate" + } ] +}, { + "@id" : "http://purl.org/neao/data#SpikeTrainSynchronyMeasure", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Data that contains a measure describing synchronization in two or more spike trains containing the activity of different neurons." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spike train synchrony measure" + } ] +}, { + "@id" : "http://purl.org/neao/data#SpikeTrainTimeHistogram", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed spike train time histogram." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#TimeHistogram" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spike train time histogram" + } ] +}, { + "@id" : "http://purl.org/neao/data#SpikeTriggeredAverage", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "STA" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed spike-triggered average (STA)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#TriggeredAverageMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spike-triggered average" + } ] +}, { + "@id" : "http://purl.org/neao/data#SpikeTriggeredLFPAverage", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed spike-triggered average of the local field potential (LFP) signal." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#SpikeTriggeredAverage" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spike-triggered local field potential average" + } ] +}, { + "@id" : "http://purl.org/neao/data#SpikeTriggeredPhase", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed spike-triggered phase angles." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spike-triggered phase" + } ] +}, { + "@id" : "http://purl.org/neao/data#SpikeWaveform", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Data that contains the characteristic voltage change over time observed in the electrical recording of a neuron's action potential (spike). This waveform represents the rapid depolarization and repolarization of the neuron's membrane potential during the action potential. The data is acquired in a finite number of samples that correspond to a time window around the spike time (i.e., with periods before and after the action potential onset)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spike waveform" + } ] +}, { + "@id" : "http://purl.org/neao/data#SpikeWaveformAverage", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed average across the spike waveforms." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#SpikeWavevormStatistic" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spike waveform average" + } ] +}, { + "@id" : "http://purl.org/neao/data#SpikeWaveformSNR", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "spike waveform SNR" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed signal-to-noise ratio of the spike waveforms." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#SpikeWavevormStatistic" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spike waveform signal-to-noise ratio" + } ] +}, { + "@id" : "http://purl.org/neao/data#SpikeWaveformVariance", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed variance across the spike waveforms." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#SpikeWavevormStatistic" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spike waveform variance" + } ] +}, { + "@id" : "http://purl.org/neao/data#SpikeWaveformWidth", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed spike waveform width." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#SpikeWavevormStatistic" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spike waveform width" + } ] +}, { + "@id" : "http://purl.org/neao/data#SpikeWavevormStatistic", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Data that contains measures used to describe specific characteristics or make inferences from spike waveforms." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spike waveform statistic" + } ] +}, { + "@id" : "http://purl.org/neao/data#StandardDeviation", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "SD" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed standard deviation (SD)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "standard deviation" + } ] +}, { + "@id" : "http://purl.org/neao/data#StandardErrorMean", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "SEM" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed standard error of the mean (SEM)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "standard error of the mean" + } ] +}, { + "@id" : "http://purl.org/neao/data#StockwellTransform", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The result of computing the Stockwell transform (S transform)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "S transform" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "Stockwell transform" + } ] +}, { + "@id" : "http://purl.org/neao/data#TensorComponent", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A tensor component obtained by applying tensor component analysis (TCA) to the input data." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#DimensionalityReductionOutput" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "tensor component" + } ] +}, { + "@id" : "http://purl.org/neao/data#TimeHistogram", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Data that contains a time histogram, i.e., a histogram that shows the distribution of a measure across specified time intervals (bins)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "time histogram" + } ] +}, { + "@id" : "http://purl.org/neao/data#TimeSeries", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Data that contains values of a specific quantity (e.g., voltage) acquired as a series of successive samples over time. Typically, there is a fixed interval between the samples (sampling period), with each sample representing a distinct time point in the series." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "time series" + } ] +}, { + "@id" : "http://purl.org/neao/data#TransferEntropy", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "TE" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed transfer entropy (TE)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "transfer entropy" + } ] +}, { + "@id" : "http://purl.org/neao/data#TriggeredAverageMeasure", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Data that contains the output of a triggered average analysis." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "triggered average measure" + } ] +}, { + "@id" : "http://purl.org/neao/data#TuningCurve", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed tuning curve." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "tuning curve" + } ] +}, { + "@id" : "http://purl.org/neao/data#UnbiasedSquaredPhaseLagIndex", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "unbiased squared PLI" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed unbiased squared phase lag index (PLI)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#PhaseLagIndexMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "unbiased squared phase lag index" + } ] +}, { + "@id" : "http://purl.org/neao/data#UnitaryEventPattern", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "UE pattern" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A neuronal activity pattern obtained by the Unitary Event (UE) analysis." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#NeuronalActivityPattern" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "Unitary Event pattern" + } ] +}, { + "@id" : "http://purl.org/neao/data#VanRossumDistance", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed van Rossum distance." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#SpikeTrainDistance" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "van Rossum distance" + } ] +}, { + "@id" : "http://purl.org/neao/data#Variance", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed variance." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "variance" + } ] +}, { + "@id" : "http://purl.org/neao/data#VictorPurpuraDistance", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed Victor-Purpura distance." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#SpikeTrainDistance" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "Victor-Purpura distance" + } ] +}, { + "@id" : "http://purl.org/neao/data#WaveletTransform", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Data that contains the result of a wavelet transform analysis, i.e., decomposing a time series using a mother wavelet function." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "scaleogram" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "wavelet transform" + } ] +}, { + "@id" : "http://purl.org/neao/data#WeightedPhaseLagIndex", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "WPLI" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The computed weighted phase lag index (WPLI)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/data#PhaseLagIndexMeasure" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "weighted phase lag index" + } ] +}, { + "@id" : "http://purl.org/neao/data#isArtificial", + "@type" : [ "http://www.w3.org/2002/07/owl#DatatypeProperty" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Defines if the data is artificially-generated (true) or obtained from experimental recordings (false)." + } ], + "http://www.w3.org/2000/01/rdf-schema#domain" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2000/01/rdf-schema#range" : [ { + "@id" : "http://www.w3.org/2001/XMLSchema#boolean" + } ], + "http://www.w3.org/2000/01/rdf-schema#subPropertyOf" : [ { + "@id" : "http://www.w3.org/2002/07/owl#topDataProperty" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "is artificial" + } ] +}, { + "@id" : "http://purl.org/neao/data#isAveraged", + "@type" : [ "http://www.w3.org/2002/07/owl#DatatypeProperty" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Defines if the data is the result of an aggregation to obtain an average estimate from other data (true)." + } ], + "http://www.w3.org/2000/01/rdf-schema#domain" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2000/01/rdf-schema#range" : [ { + "@id" : "http://www.w3.org/2001/XMLSchema#boolean" + } ], + "http://www.w3.org/2000/01/rdf-schema#subPropertyOf" : [ { + "@id" : "http://www.w3.org/2002/07/owl#topDataProperty" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "is averaged" + } ] +}, { + "@id" : "http://purl.org/neao/data#isDetrended", + "@type" : [ "http://www.w3.org/2002/07/owl#DatatypeProperty" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Defines if a detrending transformation was applied to the data (true)." + } ], + "http://www.w3.org/2000/01/rdf-schema#domain" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2000/01/rdf-schema#range" : [ { + "@id" : "http://www.w3.org/2001/XMLSchema#boolean" + } ], + "http://www.w3.org/2000/01/rdf-schema#subPropertyOf" : [ { + "@id" : "http://www.w3.org/2002/07/owl#topDataProperty" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "is detrended" + } ] +}, { + "@id" : "http://purl.org/neao/data#isDimensionalityReduction", + "@type" : [ "http://www.w3.org/2002/07/owl#DatatypeProperty" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Defines if the data is a result of a dimensionality reduction transformation (true)." + } ], + "http://www.w3.org/2000/01/rdf-schema#domain" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2000/01/rdf-schema#range" : [ { + "@id" : "http://www.w3.org/2001/XMLSchema#boolean" + } ], + "http://www.w3.org/2000/01/rdf-schema#subPropertyOf" : [ { + "@id" : "http://www.w3.org/2002/07/owl#topDataProperty" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "is dimensionality reduction" + } ] +}, { + "@id" : "http://purl.org/neao/data#isDownsampled", + "@type" : [ "http://www.w3.org/2002/07/owl#DatatypeProperty" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Defines if a downsampling transformation was applied to the data (true)." + } ], + "http://www.w3.org/2000/01/rdf-schema#domain" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2000/01/rdf-schema#range" : [ { + "@id" : "http://www.w3.org/2001/XMLSchema#boolean" + } ], + "http://www.w3.org/2000/01/rdf-schema#subPropertyOf" : [ { + "@id" : "http://purl.org/neao/data#isResampled" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "is downsampled" + } ] +}, { + "@id" : "http://purl.org/neao/data#isFiltered", + "@type" : [ "http://www.w3.org/2002/07/owl#DatatypeProperty" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Defines if a digital filter was applied to the data (true)." + } ], + "http://www.w3.org/2000/01/rdf-schema#domain" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2000/01/rdf-schema#range" : [ { + "@id" : "http://www.w3.org/2001/XMLSchema#boolean" + } ], + "http://www.w3.org/2000/01/rdf-schema#subPropertyOf" : [ { + "@id" : "http://www.w3.org/2002/07/owl#topDataProperty" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "is filtered" + } ] +}, { + "@id" : "http://purl.org/neao/data#isInterpolated", + "@type" : [ "http://www.w3.org/2002/07/owl#DatatypeProperty" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Defines if a interpolation data transformation was applied to the data (true)." + } ], + "http://www.w3.org/2000/01/rdf-schema#domain" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2000/01/rdf-schema#range" : [ { + "@id" : "http://www.w3.org/2001/XMLSchema#boolean" + } ], + "http://www.w3.org/2000/01/rdf-schema#subPropertyOf" : [ { + "@id" : "http://www.w3.org/2002/07/owl#topDataProperty" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "is interpolated" + } ] +}, { + "@id" : "http://purl.org/neao/data#isNormalized", + "@type" : [ "http://www.w3.org/2002/07/owl#DatatypeProperty" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Defines if a data normalization transformation was applied to the data (true)." + } ], + "http://www.w3.org/2000/01/rdf-schema#domain" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2000/01/rdf-schema#range" : [ { + "@id" : "http://www.w3.org/2001/XMLSchema#boolean" + } ], + "http://www.w3.org/2000/01/rdf-schema#subPropertyOf" : [ { + "@id" : "http://www.w3.org/2002/07/owl#topDataProperty" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "is normalized" + } ] +}, { + "@id" : "http://purl.org/neao/data#isRectified", + "@type" : [ "http://www.w3.org/2002/07/owl#DatatypeProperty" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Defines if a rectification transformation was applied to the data (true)." + } ], + "http://www.w3.org/2000/01/rdf-schema#domain" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2000/01/rdf-schema#range" : [ { + "@id" : "http://www.w3.org/2001/XMLSchema#boolean" + } ], + "http://www.w3.org/2000/01/rdf-schema#subPropertyOf" : [ { + "@id" : "http://www.w3.org/2002/07/owl#topDataProperty" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "is rectified" + } ] +}, { + "@id" : "http://purl.org/neao/data#isRereferenced", + "@type" : [ "http://www.w3.org/2002/07/owl#DatatypeProperty" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Defines if a transformation to change the reference in the recorded data was applied (true)." + } ], + "http://www.w3.org/2000/01/rdf-schema#domain" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2000/01/rdf-schema#range" : [ { + "@id" : "http://www.w3.org/2001/XMLSchema#boolean" + } ], + "http://www.w3.org/2000/01/rdf-schema#subPropertyOf" : [ { + "@id" : "http://www.w3.org/2002/07/owl#topDataProperty" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "is rereferenced" + } ] +}, { + "@id" : "http://purl.org/neao/data#isResampled", + "@type" : [ "http://www.w3.org/2002/07/owl#DatatypeProperty" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Defines if a resampling transformation was applied to the data (true)." + } ], + "http://www.w3.org/2000/01/rdf-schema#domain" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2000/01/rdf-schema#range" : [ { + "@id" : "http://www.w3.org/2001/XMLSchema#boolean" + } ], + "http://www.w3.org/2000/01/rdf-schema#subPropertyOf" : [ { + "@id" : "http://www.w3.org/2002/07/owl#topDataProperty" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "is resampled" + } ] +}, { + "@id" : "http://purl.org/neao/data#isSmoothed", + "@type" : [ "http://www.w3.org/2002/07/owl#DatatypeProperty" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Defines if a data smoothing transformation was applied to the data (true)." + } ], + "http://www.w3.org/2000/01/rdf-schema#domain" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2000/01/rdf-schema#range" : [ { + "@id" : "http://www.w3.org/2001/XMLSchema#boolean" + } ], + "http://www.w3.org/2000/01/rdf-schema#subPropertyOf" : [ { + "@id" : "http://www.w3.org/2002/07/owl#topDataProperty" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "is smoothed" + } ] +}, { + "@id" : "http://purl.org/neao/data#isUpsampled", + "@type" : [ "http://www.w3.org/2002/07/owl#DatatypeProperty" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Defines if an upsampling transformation was applied to the data (true)." + } ], + "http://www.w3.org/2000/01/rdf-schema#domain" : [ { + "@id" : "http://purl.org/neao/base#Data" + } ], + "http://www.w3.org/2000/01/rdf-schema#range" : [ { + "@id" : "http://www.w3.org/2001/XMLSchema#boolean" + } ], + "http://www.w3.org/2000/01/rdf-schema#subPropertyOf" : [ { + "@id" : "http://purl.org/neao/data#isResampled" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "is upsampled" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#ASSETAnalysisParameter", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A parameter used by the Analysis of Sequences of Synchronous Events (ASSET) method, used to identify neuronal activity patterns in spike data." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisParameter" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "ASSET analysis parameter" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#ASSETClusteringDistanceStretchFactor", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "When computing the elliptical distance measure used by the DBSCAN algorithm to cluster the mask matrix entries to find the diagonal structures, the parameter value is used to stretch angular coefficients deviating from 45 degrees. This reflects into the shape of the neighborhood around a point in the DBSCAN procedure. A large stretch factor will produce neighborhoods that are narrower and closer to a line in the 45 degree direction. Smaller stretch factors will produce neighborhoods that are more elliptical, with the major axis in the 45 degree direction, and the minor axis in the 135 degree direction. Therefore, the smaller stretch factor increases the minor axis of this ellipsis. Together with the DBSCAN neighborhood radius parameter, this should be used to tweak the neighborhood ellipsis such that it is contained in the rectangular kernel used to filter the probability matrix entries when computing the joint probability matrix." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/parameters#ASSETAnalysisParameter" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "distance stretch factor in ASSET clustering" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#ASSETJointProbabilityMatrixFilterShape", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A tuple of integers that determines the width and length of a rectangular kernel used to cover a diagonal structure in the intersection matrix. The kernel is centered in a point in the probability matrix, and defines a neighborhood around that point. Inside the kernel, a chosen number of largest neighbors in the probability matrix is used to compute the joint probability value for the center point. The kernel is rotated in 45 degree angle." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/parameters#ASSETAnalysisParameter" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "kernel shape in ASSET joint probability matrix" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "filter shape in ASSET joint probability matrix" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#ASSETJointProbabilityMatrixNumberLargestNeighbors", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Defines the number of elements inside the filter kernel that are used to compute the joint probability value for a matrix entry. The probability matrix values inside the kernel for that entry are ordered from the largest to the lowest value, and the first N elements corresponding to the parameter value are taken." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/parameters#ASSETAnalysisParameter" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "number of largest neighbors in ASSET joint probability matrix" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#ASSETMaskMatrixSignificanceThresholds", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Real values (range 0-1) used as thresholds to determine if the entries in the probability matrix and joint probability matrices are significant. Entry significance is defined as a probability value greater than the threshold values specified by the parameter. Significant entries in both probability and joint probability matrices are defined as 1 in the mask matrix." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/parameters#ASSETAnalysisParameter" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "significance thresholds in ASSET mask matrix" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#BartlettSmoothingKernel", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The kernel function has a triangular shape with end points at zero." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/parameters#SmoothingKernel" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "Bartlett smoothing kernel" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#BinSize", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "When discretizing continuous data into smaller intervals (bins), the parameter value determines the width of the intervals (in the unit of the data being discretized). Bins are adjacent and can be of different sizes." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisParameter" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "bin width" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "bin size" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#BlackmanWindowFunction", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Window function that uses the first three terms of a summation of cosines, minimizing spectral leakage. It was proposed by Ralph Beebe Blackman. The coefficients are an approximation of the ones used in the exact Blackman window function. Therefore, this window does not remove the third and fourth side lobes but produces smoother edges." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/parameters#WindowFunction" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "Blackman window function" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#BoxcarSmoothingKernel", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The kernel function is zero over the entire interval except for a single (smaller) interval where it has a constant value. This non-zero interval is the total width of the kernel." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/parameters#SmoothingKernel" + } ], + "http://www.w3.org/2002/07/owl#disjointWith" : [ { + "@id" : "http://purl.org/neao/parameters#ExponentialSmoothingKernel" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "Boxcar smoothing kernel" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#DBSCANMinimumNeighbors", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Integer value that determines the minimum number of points that must be present in the neighborhood of a sample point such that it is considered a core point. The parameter value includes the sample point being evaluated." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/parameters#DBSCANParameter" + } ], + "http://www.w3.org/2002/07/owl#disjointWith" : [ { + "@id" : "http://purl.org/neao/parameters#DBSCANNeighborhoodRadius" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "DBSCAN minimum samples" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "DBSCAN minimum number of neighbors" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#DBSCANNeighborhoodRadius", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Determines the radius around a sample point used to define its neighborhood. The parameter defines the maximum distance between two sample points such that they are considered to be in the same neighborhood." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/parameters#DBSCANParameter" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "DBSCAN epsilon" + }, { + "@language" : "en", + "@value" : "DBSCAN maximum distance" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "DBSCAN neighborhood radius" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#DBSCANParameter", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A parameter used by the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) data clustering method." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisParameter" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "DBSCAN parameter" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#DPSSWindowFunction", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "DPSS window function" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A set of orthogonal sequences optimized to simultaneously achieve maximum concentration of energy within a defined frequency band and minimum leakage into neighboring frequency bands. They are frequently used as tapers in multiple applications (e.g., multitaper power spectral density estimation). The first sequence (order 0 or Slepian sequence) has maximal energy concentration in the main lobe." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/parameters#WindowFunction" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "Slepian sequences window function" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "discrete prolate spheroidal sequences window function" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#DitheringTime", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A time interval that defines a dithering distribution used to draw random numbers to displace individual spike times in a spike train." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisParameter" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "dithering time" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#DownsampleFactor", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A real value that indicates the factor by which the sampling period of a sampled time series is reduced in a downsampling operation." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisParameter" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "decimation factor" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "downsample factor" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#ExactBlackmanWindowFunction", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Window function that uses the first three terms of a summation of cosines. It was proposed by Ralph Beebe Blackman. The coefficients are selected to remove the third and fourth side lobes, but the edges are discontinuous." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/parameters#WindowFunction" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "exact Blackman window" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#ExponentialSmoothingKernel", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The kernel function is zero for points before the kernel center point, maximum at the center point, and decay exponentially for points greater than the center point. This kernel is asymmetric." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/parameters#SmoothingKernel" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "exponential smoothing kernel" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#FilterOrder", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Integer value specifying the rate at which the filter response in the transition band falls. A higher filter order corresponds to a faster filter response decay." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisParameter" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "filter order" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#FiringRate", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The parameter value determines the average number of spikes fired by a neuron per time unit. It is used to control the behavior of steps that require a firing rate to control the output (e.g., a target mean firing rate when generating an artificial spike train)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisParameter" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "firing rate" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#FrequencyResolution", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "In analyses producing estimates in the frequency domain, the parameter determines the width of the frequency bins in the output, i.e., the resolution of the output on the frequency axis." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisParameter" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "frequency resolution" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#HammingSmoothingKernel", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The kernel function corresponds to a raised cosine (i.e., a single period of a cosine function \"raised\") with positive endpoints." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/parameters#SmoothingKernel" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "Hamming smoothing kernel" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#HammingWindowFunction", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A window function that corresponds to a raised cosine (i.e., a single period of a cosine function \"raised\") but with positive endpoints. Therefore, the function does not eliminate the discontinuities in the signal. It has better cancellation of the nearest side lobe, and a poorer cancellation of the others, with a wide main lobe. It is named after Richard Wesley Hamming." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/parameters#WindowFunction" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "Hamming window function" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#HannSmoothingKernel", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The kernel function corresponds to a raised cosine (i.e., a single period of a cosine function \"raised\" such that the negative troughs are zero). The endpoints reach zero smoothly at the boundaries." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/parameters#SmoothingKernel" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "Hann smoothing kernel" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#HannWindowFunction", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A window function that corresponds to a raised cosine (i.e., a single period of a cosine function \"raised\" such that the negative troughs are zero). Therefore, the function reaches zero smoothly at the boundaries and eliminates all discontinuities in the signal. It has a wide main lobe and low side lobes. It is named after Julius von Hann." + }, { + "@language" : "en", + "@value" : "raised-cosine window function" + }, { + "@language" : "en", + "@value" : "von Hann window function" + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/parameters#WindowFunction" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "hanning window function" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "Hann window function" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#HighPassFrequencyCutoff", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "When applying a filter to a time series, the frequency components below this parameter value will be attenuated. Usually, the parameter value corresponds to the frequency component attenuated by 3 dB in the filter transition band." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisParameter" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "high-pass frequency cutoff" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#KaiserWindowFunction", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "This window function approximates the DPSS window function using Bessel functions. It is easier to compute than the DPSS window function. It was developed by James Kaiser." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/parameters#WindowFunction" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "Kaiser-Bessel window function" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "Kaiser window function" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#KernelWidth", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The total width of a smoothing kernel." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisParameter" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "kernel width" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#LowPassFrequencyCutoff", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "When applying a filter to a time series, the frequency components above this parameter value will be attenuated. Usually, the parameter value corresponds to the frequency component attenuated by 3 dB in the filter transition band." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisParameter" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "low-pass frequency cutoff" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#NumberFFTSamples", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Length of the time series considered by application of a fast Fourier transform (FFT). The value determines the frequency bin size based on the sampling frequency of the input data, and the length of the vector representing the result of the discrete Fourier transform." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisParameter" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "FFT points" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "number of FFT samples" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#PeakResolution", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The parameter defines the separation of individual peaks in the output." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisParameter" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "peak resolution" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#SamplingFrequency", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The parameter determines the number of samples per time unit in sampled data. It is the inverse of the sampling period, i.e., the interval between two consecutive samples." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisParameter" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "sampling rate" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "sampling frequency" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#ShapeFactor", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "When determining a probability distribution, the parameter affects the shape of the distribution. This is in contrast to other parameters that affect the location (e.g., mean) or scale (e.g., variance) of the distribution." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisParameter" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "shape factor" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#SmoothingKernel", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A smoothing kernel can be used in non-parametric smoothing techniques such as kernel smoothing or kernel density estimation. It represents a weighting function that assigns weights to neighboring data points based on their distance from a given point (the kernel center). Closer points are given higher weights. The weighted average of the data points within the kernel is computed to produce a smoothed estimate of the underlying data (e.g., a signal or probability density function). Smoothing kernels are characterized by their shape (e.g., Boxcar, exponential) and bandwidth. The bandwidth determines the extent of influence of neighboring data points on the smoothed estimate." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisParameter" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "smoothing kernel" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#TemporalResolution", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The parameter determines the smallest time interval that can be detected or produced by the method. In sampled time series data, this equals to the sampling period, i.e, the time interval between two consecutive samples." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisParameter" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "temporal resolution" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#WaveletCenterFrequency", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The value of the center frequency of a wavelet. This is the frequency at which the wavelet oscillates most strongly, and it influences how effectively the wavelet can capture features of a signal at different frequencies. Wavelets with higher center frequencies are better suited for analyzing high-frequency components of a signal, while those with lower center frequencies are more effective for capturing low-frequency components." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisParameter" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "wavelet center frequency" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#WindowFunction", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A mathematical function that is zero-valued outside a defined interval. When multiplied by another function or sampled data, the values outside the window interval will be transformed to zero, and the values inside the window will be weighted by the window function values. \n\nWindow functions are used to select and modify a finite segment of a signal. This is useful for applying the fast Fourier transform (FFT) to a finite set of data where the length is not an integer number of periods of the signal. In this situation, there will be discontinuities at the boundaries of the signal, and the data in the frequency domain produced by the FFT will have frequency components not present in the original signal (spectral leakage). The window function can be used to reduce this discontinuities and mitigate spectral leakage when performing spectral analysis.\n\nSeveral types of window function exist. They will vary in shape in the time domain and will have distinct frequency characteristics in the frequency domain, with a main lobe and several side lobes. The main lobe is centered at each frequency component in the time domain, and the side lobes approach zero. These characteristics can be used to control the effect of spectral leakage when performing the analysis." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisParameter" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "apodization function" + }, { + "@language" : "en", + "@value" : "tapering function" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "window function" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#WindowLengthSamples", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Integer value that defines the number of samples encompassed by a window in sampled data, i.e., the window length. The window corresponds to a finite interval in the sampled data (e.g., a time interval in sampled time series data)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisParameter" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "window length in samples" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#WindowOverlapFactor", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Real value (range 0-1) that determines the proportion of overlap between two adjacent windows. The window is a finite interval in the data (e.g., a time interval in time series data)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisParameter" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "window overlap factor" + } ] +}, { + "@id" : "http://purl.org/neao/parameters#WindowOverlapSamples", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Integer value (range 0 to the window length in samples) that determines the number of samples where two adjacent windows overlap. The window corresponds to a finite interval in sampled data (e.g., a time interval in sampled time series data)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisParameter" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "window overlap in samples" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ASSETAnalysisProbabilityMatrixSubstep", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Torre2016_e1004939" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "ASSET analysis substep that computes the probability matrix (PMAT). The probability matrix contains, for each entry in the intersection matrix, the cumulative probability representing the probability of having the overlap in the IMAT under the assumption that the spike trains are independent. If an entry in the PMAT is large, the null hypothesis of independence is rejected, and the alternative hypothesis that the observed overlap reflects active synchronization between the involved neurons at the time bins of the intersection is accepted. The PMAT computation can be done with either an analytical or Monte Carlo approach." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#ASSETAnalysisSubstep" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "ASSET analysis probability matrix substep" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ASSETAnalysisSubstep", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Torre2016_e1004939" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that is an individual part of the ASSET analysis method to identify neuronal activity patterns in spike train data." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "ASSET analysis substep" + } ] +}, { + "@id" : "http://purl.org/neao/steps#AnalysisPurpose", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Analysis purpose refers to the specific objective or goal that an analysis is intended to achieve. It outlines what the analysis step aims to discover, understand, or demonstrate. This class is intended for grouping steps that perform analyses with similar goals/outputs but with distinct methodological or algorithmic approaches. It is used as a normalization class via the hasPurpose object property." + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "analysis purpose" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyAdaptiveKernelSmoothing", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A kernel smoothing that uses a variable-width kernel. The kernel width varies adaptively depending on the local density of the data. This method takes into consideration local variations in data density, resulting in a more accurate representation of the underlying patterns and structures." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#KernelSmoothing" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply adaptive kernel smoothing" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyAnalyticSignalConversion", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A data transformation that uses the Hilbert transform of a real-valued input time series to construct the analytic signal, a complex-valued time series where the real part is the original real-valued signal and the imaginary part is the Hilbert transform. The analytic signal does not have negative frequency components." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DataTransformation" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply analytic signal conversion" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyButterworthFilter", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An infinite impulse response filtering that uses a Butterworth type filter, i.e., a filter designed to have a maximally flat frequency response in the passband (no ripples). The frequency response gradually decreases to zero in the stopband, and the steepness of the decrease (roll-off) is controlled by the order of the filter." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#InfiniteImpulseResponseFiltering" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "apply maximally flat magnitude filter" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply Butterworth filter" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyCanonicalPolyadicTensorDecomposition", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "apply CPD" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Williams2018_1099" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A tensor component analysis (TCA) that expresses the input high-dimensional tensor as a sum of rank-one tensors (tensor components). Each dimension in the tensor component corresponds to a dimension in the input high-dimensional tensor. For neural data, a tensor could be used to represent trial-by-trial spiking activity, with neurons, time, and trials as dimensions. Therefore, each tensor component produced from that input will have a rank-one tensor for the neurons, time, and trial, which describes both within- and between-trial changes." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#TensorComponentAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "apply tensor rank decomposition" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply canonical polyadic tensor decomposition" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyCoupledCanonicalPolyadicTensorDecomposition", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "apply CCPD" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Sorensen2013_228" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A tensor component analysis (TCA) that expresses multiple high-dimensional input tensors as a sum of rank one tensors (tensor components). The output tensor components have shared vectors that summarize an input dimension across all input tensors. For example, if analyzing two tensors, each representing trial-by-trial spiking activity obtained from a distinct experimental subject (neurons X time X trials), the coupled canonical polyadic tensor decomposition (CCPD) could produce tensor components for each dataset where the vector for the trial and time dimensions are the same, but the neuron dimension is unique for each dataset (hence, each subject). Therefore, CCPD is useful for scenarios with multiple and related datasets, allowing for the exploitation of shared information to enhance the decomposition results." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#TensorComponentAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply coupled canonical polyadic tensor decomposition" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyDFTNoiseRemoval", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "apply DFT noise removal" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A line noise removal that uses a discrete Fourier transform (DFT) filter and estimates the power line component amplitude in the input data by fitting a sine and cosine at a user-specified line noise frequency (e.g., 50 Hz), followed by the subtraction of those components from the input." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#LineNoiseRemoval" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply discrete Fourier transform noise removal" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyDataConcatenation", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A data transformation that joins two or more data inputs into a single data element. For example, in a multitrial experimental session, where data was acquired separately as one epoch per trial, a continuous data segment for the session can be constructed by concatenating all trial epochs together." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DataTransformation" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply data concatenation" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyDemixedPrincipalComponentAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "apply dPCA" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Kobak2016_e10989" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A principal component analysis (PCA) that uses a modified version of the standard PCA for neural activity data analysis. Demixed PCA (dPCA) not only obtains a low-dimensional representation of the input data, but it also demixes the dependencies of the population activity on the task parameters. Therefore, dPCA can show the dependence of the neural representation on parameters such as stimuli, subject decisions, or rewards." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#PrincipalComponentAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply demixed principal component analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyDiscreteFourierTransform", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A frequency-domain transformation that applies the discrete Fourier transform (DFT) to an input time series acquired in equally-spaced samples. The DFT is used to obtain the frequency representation of the time-domain input. The DFT output is a sequence of coefficients of complex sinusoids, each representing a frequency component in the input signal. Each frequency component consists of an interval (or bin), and the width of the bin determines the frequency resolution of the DFT. The number of frequency components and the frequency resolution is determined by the length of the input signal (number of samples) and the sampling frequency. For large datasets, the computation is computationally expensive (O(N^2) complexity)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#FrequencyDomainTransformation" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "apply DFT" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply discrete Fourier transform" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyDistanceCovarianceAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "apply DCA" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Cowley2017_242" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A dimensionality reduction that identifies linear and nonlinear relationships between multiple input datasets. The method identifies linear projections (DCA dimensions) that maximize the distance covariance statistic (an Euclidean-based correlational statistic). For example, for recordings from different brain regions (two neuronal populations), the distance covariance analysis (DCA) can identify the dimensions in the population activity in the different brain areas that are related to each other. The dimensionality reduction can also take other dependent variables into account (e.g., stimulus or behavioral variables)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DimensionalityReduction" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply distance covariance analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyDownsampling", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A resampling that reduces the number of samples in the input data (i.e., reduces the sampling frequency). This is often accomplished after applying an anti-aliasing filter (i.e., to remove frequencies above half the value of the new sampling frequency)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#Resampling" + } ], + "http://www.w3.org/2002/07/owl#disjointWith" : [ { + "@id" : "http://purl.org/neao/steps#ApplyUpsampling" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "apply decimation" + }, { + "@language" : "en", + "@value" : "apply downscaling" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply downsampling" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyFastFourierTransform", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A frequency-domain transformation that uses the fast Fourier transform (FFT) algorithm to compute the discrete Fourier transform (DFT). The computation of the DFT is computationally expensive for large datasets. The FFT reduces the number of computations significantly by using a divide-and-conquer approach, leveraging the symmetry and periodicity properties of the DFT. The complexity is O(N log N). The output of the method is similar to the DFT, i.e., a sequence of coefficients of complex sinusoids, each representing a frequency component in the input signal. The FFT takes a size parameter, that refers to the number of points in the input data sequence that is used for the computation. The FFT size determines the frequency resolution, and, for maximal efficiency, should be a multiple of 2." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#ApplyDiscreteFourierTransform" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "apply FFT" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply fast Fourier transform" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyFiniteImpulseResponseFilter", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "apply FIR filter" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A finite impulse response (FIR) filtering where a custom-designed FIR filter is applied to the input data." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#FiniteImpulseResponseFiltering" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply finite impulse response filter" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyFiniteImpulseResponseFilterKaiserWindow", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "apply FIR filter with Kaiser window" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A finite impulse response (FIR) filtering that uses a FIR filter whose impulse response is controlled by applying a Kaiser window function." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#FiniteImpulseResponseFiltering" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply finite impulse response filter with Kaiser window" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyFixedKernelSmoothing", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A kernel smoothing that uses a fixed-width kernel. The kernel type and kernel width can be specified as parameters." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#KernelSmoothing" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply fixed kernel smoothing" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyGeneralLinearModelPolynomialDetrending", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A detrending that uses a general linear model to fit a polynomial from the input data and remove the mean and linear trend." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#Detrending" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply general linear model polynomial detrending" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyHilbertTransform", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A data transformation that applies the Hilbert transform to a real-valued time series. The Hilbert transform shifts the phase of each frequency component of the signal by 90 degrees: positive frequencies are shifted by -90 degrees, and negative frequencies are shifted by +90 degrees. This can be used to construct the analytic signal." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DataTransformation" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply Hilbert transform" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyIndependentComponentAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "apply ICA" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Jutten1991_1" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A data transformation that separates a multivariate input signal into additive subcomponents (independent components). The independent components are statistically independent from each other." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DataTransformation" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply independent component analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyInfiniteImpulseResponseFilter", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "apply IIR filter" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An infinite impulse response (IIR) filtering where a custom-designed IIR filter is applied to the input data." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#InfiniteImpulseResponseFiltering" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply infinite impulse response filter" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyInterpolation", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A data transformation that estimates new (intermediate) values between the known values in the input data. This can be accomplished using several methods, such as linear interpolation (i.e., estimating the values along a straight line connecting adjacent points), polynomial interpolation (i.e., using polynomials to estimate the values between points), or spline Interpolation (i.e., using piecewise polynomials that pass through the known data points and provide a smooth curve)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DataTransformation" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply interpolation" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyLinearDiscriminantAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "apply LDA" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A dimensionality reduction that finds a linear combination of features that separates two or more classes defined in the input data. The input data must have a variable that defines the class for each observation, and continuous variables that are used for the linear discriminant analysis (LDA). LDA finds an optimal projection vector that maximizes the distance between the means of the different classes, and minimizes the variance within each class. LDA projects the input data into the lower-dimensional space, therefore reducing the number of features while retaining the information needed for classification. The optimal projection vectors found by LDA are the Fisher linear discriminants." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DimensionalityReduction" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply linear discriminant analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyLocalLinearRegressionDetrending", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Bokil2010_146" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A detrending that removes a running line fit using local linear regression. Local linear regression estimates a function by fitting a low-order polynomial to data within a sliding window (local neighborhood) across the input data." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#Detrending" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply local linear regression detrending" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyLocalRegressionAndLikelihoodSmoothing", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Bokil2010_146" + }, { + "@id" : "http://purl.org/neao/bibliography#Loader2006" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A data smoothing that estimates a low-order polynomial in a local neighborhood (window) of any value in the input data. Polynomial coefficients are estimated using the least mean squares method. Contrary to kernel smoothing methods, this is a non-parametric approach and has reduced bias at the boundaries of the input data." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DataSmoothing" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply local regression and likelihood smoothing" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyMedianRescaling", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A data normalization that uses the median and interquartile range (IQR) to rescale the values of the input data. This method is less sensitive to outliers (compared to the z-score transform), and therefore is known as robust scaling." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DataNormalization" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "apply robust scaling" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply median rescaling" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyMinMaxNormalization", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A data normalization that adjusts the range and distribution of values in the data input such that they fall within a fixed range, based on the minimum and maximum values in the input data. In the typical case, the values are normalized to the [0, 1] interval." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DataNormalization" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "apply rescaling" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply min-max normalization" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyMovementArtifactRemoval", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An artifact removal that identifies and removes artifacts originating from movements of the experimental subject (e.g., eye movement, head movement)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#ArtifactRemoval" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply movement artifact removal" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyNeuralTrajectoryGaussianProcessFactorAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "apply GPFA" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Yu2009_614" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A dimensionality reduction that uses the Gaussian process factor analysis (GPFA) method described by Yu et al. (2009). GPFA extracts smooth, low-dimensional neural trajectories that summarize the activity recorded simultaneously from many neurons on individual experimental trials over time. The input is a set of spike trains representing multitrial activity of multiple neurons recorded in parallel. The input spike trains are binned, and factor analysis is applied to reduce the dimensionality while smoothing the resulting low-dimensional trajectories by fitting a Gaussian process (GP) model to them. The identified trajectories are called neural trajectories, and show the evolution of the activity of the population of neurons over time." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DimensionalityReduction" + }, { + "@id" : "_:genid4" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply neural trajectory Gaussian process factor analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyNonNegativeTensorComponentAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A tensor component analysis (TCA) where a non-negative constraint is applied to the decomposition. This is desirable when the underlying components have physical interpretation and negative values are not possible." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#TensorComponentAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply non-negative tensor component analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyNotchFilter", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An infinite impulse response filtering that uses a filter designed to attenuate or eliminate a narrow band of frequencies in the input data (stopband) while allowing other frequencies to pass through relatively unaffected." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#InfiniteImpulseResponseFiltering" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply notch filter" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyNotchFilterNoiseRemoval", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A line noise removal that employs a notch filter to remove line noise. A notch filter is designed to attenuate or eliminate a narrow band of frequencies in the input data (stopband) while allowing other frequencies to pass through relatively unaffected. The notch filter stop band is usually centered at the power line frequency (i.e., 50 Hz or 60 Hz depending on the location)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#LineNoiseRemoval" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply notch filter noise removal" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyOutlierRemoval", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An artifact removal that identifies and removes values in the input data that differs significantly from other values (outliers). Outliers may arise from the variability in the measurement or be the result of experimental error." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#ArtifactRemoval" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply outlier removal" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyPadding", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A data transformation that adds extra data (often zeros or other predefined values) to the beginning, end, or both sides of the input data." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DataTransformation" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply padding" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyProbabilisticPrincipalComponentAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "apply pPCA" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Tipping1999_611" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A principal component analysis (PCA) that assumes a probabilistic model for the generation of the observed data, according to Tipping & Bishop (1999). The model assumes that the values in the data input are generated from the lower-dimensional subspace of latent variables (principal components) plus an additive Gaussian noise. This generalizes the standard PCA for the case where the noise covariance approaches zero. The probabilistic PCA (pPCA) allows for uncertainty estimation and modeling of the data generation process, and can be employed when there are missing values in the input data." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#PrincipalComponentAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply probabilistic principal component analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyRectification", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A data transformation that computes the absolute value of the input data (rectification)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DataTransformation" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply rectification" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyRereference", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A data transformation that changes the reference point of the data recorded from an electrode. This can be performed by calculating the average across the data obtained from all electrodes and subtracting it from each individual electrode’s data (reducing common noise) or referencing each electrode to its nearest neighbor or a defined pair, subtracting one signal from another (bipolar referencing)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DataTransformation" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply rereference" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplySpectrumInterpolationNoiseRemoval", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Mewett2004_524" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A line noise removal that uses spectral interpolation to remove power line noise. After obtaining the discrete Fourier transform (DFT) of the input signal with noise, the original frequency component at the power line oscillation frequency can be estimated by interpolating the amplitude spectrum (obtained from the DFT) at the power line frequency (e.g., 50 Hz), followed by the inverse DFT to reconstruct the signal." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#LineNoiseRemoval" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply spectrum interpolation noise removal" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplySpikeExtractionFromTimeSeries", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A data transformation that obtains a series of spike times (i.e., a spike train) from an input time series (e.g., voltages recorded from an electrode). The spike times can be estimated, for example, by taking all the time points where the values in the input data are greater or lower than a threshold value." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DataTransformation" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply spike extraction from time series" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplySpikeTrainBinarization", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A data transformation that takes an input spike train and returns an array of boolean values indicating if at least one spike occurred at individual time points." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DataTransformation" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply spike train binarization" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplySpikeTrainBinning", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A data transformation that performs a binning operation on the input spike train data. The transformation discretizes the duration of the input spike train(s) into smaller time intervals (bins), and obtains the number of spikes occurring into each bin (binned spike train). Additionally, the occurrence of spikes into each bin can be converted into a binary form (i.e., bins with or without spikes). This is known as clipping. The width of the bin interval is specified by a parameter (bin size)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DataTransformation" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply spike train binning" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplySpikeWaveformInterpolation", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A data transformation that estimates additional (unknown) values between sample points of a spike waveform input." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#ApplyInterpolation" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply spike waveform interpolation" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplySpikeWaveformOutlierRejection", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An artifact removal that identifies and removes spike waveforms that differ significantly from the other spike waveforms in the input. This usually involves identifying waveforms with too late peaks, or in which the rising phase of the potential does not align with the peaks of all other waveforms in the input." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#ArtifactRemoval" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply spike waveform outlier rejection" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplySpikeWaveformPeakAlignment", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A data transformation that modifies input spike waveforms in order to align their peak values in time." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DataTransformation" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply spike waveform peak alignment" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyStandardPrincipalComponentAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "apply standard PCA" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A principal component analysis (PCA) that operates by computing the covariance matrix of the input data, which is then decomposed into its eigenvectors and eigenvalues. The eigenvectors, corresponding to the principal components (PCs), are sorted by the magnitude of their associated eigenvalues. The eigenvectors with the largest eigenvalues explain the most variance in the data and thus form the primary PCs." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#PrincipalComponentAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "apply classical principal component analysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply standard principal component analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyStimulationArtifactRemoval", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An artifact removal that identifies and removes artifacts originating from presenting a stimulus during the recording (e.g., electrical stimulation)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#ArtifactRemoval" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply stimulation artifact removal" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplySum", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A data transformation that performs the addition of two or more data inputs to obtain a sum." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DataTransformation" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply sum" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplySynchronousSpikeRemoval", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An artifact removal that identifies and removes spikes across two or more spike train inputs that occurred simultaneously within a temporal precision specified by a parameter. The temporal precision is usually the sampling rate used by the recording equipment: if different neurons fired within an interval equal to or smaller than the sampling period, this suggests that this synchronous activity does not come from temporal synchronization of the neurons but rather due to an interference in the recording (e.g., electrical noise picked simultaneously by multiple channels)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#ArtifactRemoval" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply synchronous spike removal" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyThomsonRegressionNoiseRemoval", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Thomson1982_1055" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A line noise removal that uses Thomson's regression method (1982) for detecting sinusoids, that identifies and removes significant sine waves from the input data. The desired frequencies can be specified by parameter, or determined using an F-statistic." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#LineNoiseRemoval" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply Thomson regression noise removal" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyTrialExtraction", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A data transformation that extracts trial segments from an input data entity storing a longer and continuous data stream. A trial is a single instance of a repeated experimental procedure. For example, during an electrophysiology experiment, a visual stimulus might be presented several times, with neural activity recorded each time. Each presentation of the stimulus defines a trial. Since the data is recorded continuously, this data transformation identifies and isolates the segments of data corresponding to each individual stimulus presentation, returning them as separate data entities." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DataTransformation" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply trial extraction" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyUpsampling", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A resampling that increases the number of samples in the data (i.e., increases the sampling frequency). This is often accomplished by adding new (zero-valued) samples between existing ones followed by applying a lowpass filter to replace the zeros and smooth out the discontinuities." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#Resampling" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "apply upscaling" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply upsampling" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyWaveformOutlierRejection", + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An artifact removal step that aims to identify and remove input spike waveforms that differs significantly from other waveforms in the input. This include spike waveforms with too late peak or where the action potential does not rise towards the peak of other waveforms." + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyWindowedSincFilter", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A finite impulse response filtering that employs the convolution with a sinc function kernel multiplied by a window function (e.g., Blackman or Hamming). The kernel is obtained by evaluating the sinc function for the cutoff frequencies specified as parameters, followed by truncation of the filter skirt, and applying the window to reduce the artifacts introduced from the truncation. The windowed-sinc filter is stable and very efficient to separate one band of frequencies from another." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#FiniteImpulseResponseFiltering" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply windowed-sinc filter" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ApplyZscoreTransform", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A data normalization that transforms the values of the input data to have zero mean and unit variance." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DataNormalization" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "apply standardization" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "apply z-score transform" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ArtifactRemoval", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A data transformation that aims to identify and remove artifacts from the input data. Artifacts are unwanted disturbances that distorts the data. In an electrophysiology experiment, they can arise from various sources: environmental interference (e.g., electromagnetic interference from nearby equipment), physiological processes (e.g., eye movement, heart beat), and technical instrumentation issues (e.g., baseline drift of the recorded potentials)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DataTransformation" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "artifact removal" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ArtificialDataGeneration", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A data generation that produces artificial data. Artificial data refers to data that is generated programmatically rather than obtained from experimental recordings (e.g., neural simulations or by using specific statistical procedures). The artificial data generation procedure does not take experimentally-recorded data as input, and the generation of the output data depends only on parameters to the method employed. The isArtificial data property is defined as True for outputs of artificial data generation steps." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DataGeneration" + } ], + "http://www.w3.org/2002/07/owl#equivalentClass" : [ { + "@id" : "_:genid5" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "artificial data generation" + } ] +}, { + "@id" : "http://purl.org/neao/steps#AutocorrelationAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step used to compute a measure of autocorrelation, i.e., the correlation of the input with displaced (lagged or advanced) versions of itself. The computation produces the autocorrelation value for every lag considered." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + }, { + "@id" : "_:genid6" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "autocorrelation analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#BivariateAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that has only two distinct inputs considered for the computation of the output (e.g., the two time series with the local field potential recorded from two electrodes used to compute a cross-correlation)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2002/07/owl#disjointWith" : [ { + "@id" : "http://purl.org/neao/steps#MultivariateAnalysis" + } ], + "http://www.w3.org/2002/07/owl#equivalentClass" : [ { + "@id" : "_:genid7" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "pairwise analysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "bivariate analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#CentralTendencyStatisticalAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A statistical analysis to compute a measure of central tendency, i.e., that represents the center or typical value of the input data." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#StatisticalAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "central tendency statistical analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#CoherenceAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spectral analysis that computes a measure of coherence between two or more inputs. Coherence is a real measure that describes the linear association of the distinct inputs (e.g., two time series) in different frequency bands. It corresponds to the absolute value of the coherency." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpectralAnalysis" + }, { + "@id" : "_:genid8" + }, { + "@id" : "_:genid9" + }, { + "@id" : "_:genid10" + }, { + "@id" : "_:genid11" + }, { + "@id" : "_:genid12" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "coherence analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#CoherencyAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spectral analysis that computes a measure of coherency between two inputs. Coherency is a complex-valued measure that describes the linear association of the distinct inputs (e.g., two time series) in different frequency bands." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpectralAnalysis" + }, { + "@id" : "_:genid13" + }, { + "@id" : "_:genid14" + }, { + "@id" : "_:genid15" + }, { + "@id" : "_:genid16" + }, { + "@id" : "_:genid17" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "coherency analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#CompoundAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that is composed by two or more substeps, each performing a part of the analysis with its own data inputs/outputs and analysis parameters." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2002/07/owl#equivalentClass" : [ { + "@id" : "_:genid18" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compound analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeASSETClusterMatrix", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Torre2016_e1004939" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "ASSET analysis substep that computes the cluster matrix (CMAT) in the ASSET analysis, using DBSCAN with a modified distance metric. It takes the mask matrix (MMAT) as input. The cluster matrix groups the significant entries in the MMAT according to each diagonal structure that they belong to. For each significant entry in the MMAT, the CMAT will have an integer value: -1 for significant entries that do not belong to any diagonal structure, or any value greater than zero with the identification of the cluster that the entry belongs to." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#ASSETAnalysisSubstep" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute ASSET cluster matrix" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeASSETIntersectionMatrix", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Torre2016_e1004939" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "ASSET analysis substep that computes the intersection matrix (IMAT). For a set of input spike trains, binned with a bin width, each entry in the IMAT corresponds to a pair of distinct bins (i.e., distinct time points in the data). The value in the entry corresponds to the number of neurons that fired in both bins corresponding to that entry. When groups of neurons fire in a sequence that repeats in time, the IMAT will show patterns that follow a diagonal direction (diagonal structure). The ASSET method aims to identify the diagonal structures by automated statistical testing and clustering procedures." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#ASSETAnalysisSubstep" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute ASSET intersection matrix" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeASSETJointProbabilityMatrix", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Torre2016_e1004939" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "ASSET analysis substep that computes the joint probability matrix (JMAT). For every entry in the probability matrix (PMAT), the computation produces the combined probability of a fixed number of neighbors in a rectangular kernel (with fixed length and width as parameters) covering a diagonal structure. A value in the JMAT reflects how likely entries with high probability in the PMAT are to be located in the same diagonal structure." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#ASSETAnalysisSubstep" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute ASSET joint probability matrix" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeASSETMaskMatrix", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Torre2016_e1004939" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "ASSET analysis substep that computes the mask matrix (MMAT). The parameters are the threshold values that are used to determine if the entries in the probability matrix (PMAT) and joint probability matrix (JMAT) are significant. Entry significance in either matrix is defined as a probability value greater than the provided threshold value. Significant entries in both probability and joint probability matrices are defined as 1 in the mask matrix." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#ASSETAnalysisSubstep" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute ASSET mask matrix" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeASSETProbabilityMatrixAnalytical", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Torre2016_e1004939" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "ASSET analysis probability matrix substep that computes the probability matrix (PMAT) using the assumption that the input spike trains are independent and Poisson. The computation can take as input the firing rate profiles of the spike trains used for the intersection matrix (IMAT), or those will be automatically computed using convolution with a boxcar kernel of specified width. The probability distribution of the value in the intersection matrix (IMAT) is approximated by a Poisson distribution computed using LeCam's approximation. The output is a matrix with the cumulative probabilities representing the probability of having each overlap in the IMAT strictly lower than the observed overlap, under the null hypothesis of independence of the input spike trains." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#ASSETAnalysisProbabilityMatrixSubstep" + } ], + "http://www.w3.org/2002/07/owl#disjointWith" : [ { + "@id" : "http://purl.org/neao/steps#ComputeASSETProbabilityMatrixMonteCarlo" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute ASSET probability matrix (analytical method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeASSETProbabilityMatrixMonteCarlo", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Torre2016_e1004939" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "ASSET analysis probability matrix substep that computes the probability matrix (PMAT) employing a Monte Carlo approach using surrogate data obtained from the input spike trains. Different than the analytical method of computation, the null hypothesis in this method does not incorporate the assumptions that the spike trains are Poisson. Spike train surrogates can be generated using distinct methods." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#ASSETAnalysisProbabilityMatrixSubstep" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute ASSET probability matrix (Monte Carlo method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeASSETSequenceSynchronousEventsExtraction", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Torre2016_e1004939" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "Last substep of the ASSET analysis method. Given the cluster matrix (CMAT), the identity of the neurons present in each bin of the repeated sequence in the identified diagonal structures is extracted (considering the input spike trains for the computation of the intersection matrix). The output of this substep is the final description of the ASSET pattern for each diagonal structure in the CMAT." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#ASSETAnalysisSubstep" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute ASSET sequence of synchronous events extraction" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeAngularMeanSpikePhases", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Vinck2012_53" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A phase analysis that computes the angle obtained from averaging the phases of an input signal at the time points where spikes occurred. For the computation, the phases are represented as vectors in the unit circle, the mean phase vector is computed, and the angle is extracted." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#PhaseAnalysis" + }, { + "@id" : "_:genid19" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute angular mean of spike phases" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeAutocorrelationFunction", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute ACF" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An autocorrelation analysis that computes the estimator for the autocorrelation function, i.e. the autocorrelation values of a time series input for a number of lags. The autocorrelation function shows temporal dependencies and repetitive patterns within the input data. The value of the autocorrelation at a specific lag shows how similar the values in the time series input are when separated by a number of time units equal to that lag. The autocorrelation value of 0 indicates no correlation. The autocorrelation varies between 1 and -1 (positive and negative correlation, respectively)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#AutocorrelationAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute autocorrelation function" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeCV", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute CV" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A dispersion statistical analysis that computes the coefficient of variation (CV). The CV is the ratio of the standard deviation to the mean. It is useful to compare different inputs, as the measure is unitless and indicates the relative variability in the input data." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DispersionStatisticalAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute coefficient of variation" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeCV2", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Holt1996_1806" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An interspike interval variability analysis that computes the CV2, a measure of the intrinsic variability of a spike train that considers adjacent interspike intervals. The CV2 is more robust against fluctuations in the firing rate than the usual approach of taking the coefficient of variation of the interspike intervals of the spike train." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#InterspikeIntervalVariabilityAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute CV2" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeCVInterspikeIntervals", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute CV ISIs" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An interspike interval variability analysis that computes the coefficient of variation (CV) of the interspike intervals (ISIs). The CV is computed as the ratio of the standard deviation of the ISIs to their mean." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#InterspikeIntervalVariabilityAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute coefficient of variation of the interspike intervals" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeCanonicalCoherence", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute caCOH" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Vidaurre2019_116009" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A coherence analysis that computes the canonical coherence (caCOH) according to Vidaurre et al. (2019). The computation maximizes the coherence between two inputs (e.g., distinct datasets with electroencephalogram, electromyogram or local field potential recordings). The absolute value of the coherence between the two multivariate spaces of the inputs in the frequency domain is maximized. The caCOH aims to maximize the strength of the synchronization of oscillatory signals when two multichannel datasets are present (e.g., multiple subjects). The method then finds two spatial projections maximizing the strength of synchronization." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#CoherenceAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute canonical coherence" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeCoherence", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A coherence analysis that computes the coherence value between two inputs. It is obtained from the magnitude of the complex-valued cross power spectral density obtained for the two inputs normalized by their power spectral density (i.e., auto spectral density). Several frequency decomposition approaches can be used to obtain the cross and auto power spectral densities from the inputs. The computation can return the magnitude coherence (i.e., by taking the absolute value of the cross power spectral density and normalizing by the square root of the product of the two auto spectral densities) or the magnitude squared coherence (i.e., by computing the squared magnitude of the cross power spectral density and normalizing by the product of the two auto spectral densities)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#CoherenceAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute coherence" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeCoherenceCarter", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Carter1987_236" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A coherence analysis that computes the coherence from two inputs according to Carter (1987). The computation produces the magnitude squared coherence." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#ComputeCoherence" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute coherence (Carter method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeCoherenceMultitaper", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Thomson1982_1055" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A coherence analysis where the coherence value between the two inputs is computed using cross and auto power spectral densities obtained using a multitaper approach according to Thomson (1982)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#ComputeCoherence" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute coherence (multitaper method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeCoherenceRosenberg", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Rosenberg1989_1" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A coherence analysis that computes the coherence from two inputs according to Rosenberg et al. (1989). The method is described for point processes (i.e., spike trains). The computation produces the magnitude squared coherence." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#ComputeCoherence" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute coherence (Rosenberg method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeCoherenceWelch", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Welch1967_70" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A coherence analysis where the coherence value between the two inputs is obtained from cross and auto power spectral densities obtained using the method described by Welch (1967). For the computation, the inputs are divided into multiple overlapping segments, and the overall cross and power spectral densities for computing the coherence are obtained from averaging the single-segment estimates." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#ComputeCoherence" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute coherence (Welch method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeCoherency", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A coherency analysis that computes the coherency for two inputs. It is computed from the complex-valued cross power spectral density obtained for the two inputs normalized by the square root of the product of their power spectral densities (i.e., auto spectral densities). For each frequency, the magnitude of the complex-valued coherency describes the strength of the association and the angle describes the phase lag between the two inputs. If the inputs contain multi-epoch data (e.g., multiple trial repetitions), the cross and auto spectral densities are averaged across epochs." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#CoherencyAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "compute complex coherency" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute coherency" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeComplexityDistribution", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Gruen2007_96" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spike train synchrony analysis that computes the complexity distribution across a set of input spike trains that typically contain the activity of different neurons. In a neuronal population, the complexity represents the total number of neurons that were spiking within a discrete time interval. For the computation, the binarized population histogram (i.e., a spike time histogram computed across spike trains, where each bin will have the count of spike trains that had at least one spike within the bin interval) is obtained using a bin size specified as a parameter. The value at each bin is the complexity. The complexity distribution is obtained by finding the frequency of each complexity value (complexity histogram) and corresponding probability density function (PDF). The complexity PDF describes the likelihood of different complexity values occurring within the neuronal population." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpikeTrainSynchronyAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute complexity distribution" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeConfidenceIntervalBootstrap", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A confidence interval resampling analysis that computes the confidence interval using bootstrapping techniques to create many simulated samples (bootstrap samples). It involves repeatedly sampling, with replacement, from the input (observed) data. The total number of bootstrap samples is defined as a parameter. Bootstrapping makes minimal assumptions about the underlying distribution of the data, making it especially useful for small samples or when the data do not meet the assumptions of traditional parametric (non-resampling) methods." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#ConfidenceIntervalResamplingAnalysis" + } ], + "http://www.w3.org/2002/07/owl#disjointWith" : [ { + "@id" : "http://purl.org/neao/steps#ComputeConfidenceIntervalJackknife" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute confidence interval (bootstrap resampling)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeConfidenceIntervalJackknife", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A confidence interval resampling analysis that computes the confidence interval using jackknife techniques. It involves systematically leaving out one observation at a time from the input (sample) set and calculating the statistic of interest on each of these \"leave-one-out\" samples. The confidence interval is computed based on statistics obtained from those jackknife samples. Jackknife is useful for small samples or when the data do not meet the assumptions of traditional parametric (non-resampling) methods." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#ConfidenceIntervalResamplingAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute confidence interval (jackknife resampling)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeConfidenceIntervalNonResampling", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A confidence interval statistical analysis that computes the confidence interval assuming a statistical distribution of the input data, and uses measures of central tendency and dispersion obtained from the data points in the input(s) (e.g., mean and standard error of the mean when assuming a normal distribution). The computation relies on theoretical distributions and established statistical formulas." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#ConfidenceIntervalStatisticalAnalysis" + } ], + "http://www.w3.org/2002/07/owl#disjointWith" : [ { + "@id" : "http://purl.org/neao/steps#ConfidenceIntervalResamplingAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute confidence interval (non-resampling)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeContinuousWaveletTransform", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute CWT" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A wavelet transform analysis that convolves the input time series with scaled and translated versions of the mother wavelet. The scale parameter can be non-dyadic (i.e., can take values that are not powers of 2). The mother wavelet used is passed as a parameter, and several types can be used (e.g., Morlet, Mexican hat, Hermitian, Meyer, Poisson). The continuous wavelet transform (CWT) is ideal for analyzing non-stationary signals, with transient behavior, rapidly changing frequencies or slowly varying changes. It is comparable to the short-time Fourier transform (STFT)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#WaveletTransformAnalysis" + } ], + "http://www.w3.org/2002/07/owl#disjointWith" : [ { + "@id" : "http://purl.org/neao/steps#ComputeMorletWaveletTransform" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute continuous wavelet transform" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeCorrectedImaginaryPhaseLockingValue", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute ciPLV" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Bruna2018_056011" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A phase locking value analysis that computes the corrected imaginary phase locking value (ciPLV), following the implementation from Bruña & Maestú (2018). It re-formulates the original phase locking value (PLV) for computational efficiency. The computation uses the imaginary part of the PLV, to make the metric insensitive to zero lag synchronizations (that can be the result of volume conduction)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#PhaseLockingValueAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute corrected imaginary phase locking value" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeCovariance", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A covariance analysis that computes the values of covariance in pairwise input data." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#CovarianceAnalysis" + }, { + "@id" : "_:genid20" + }, { + "@id" : "_:genid21" + }, { + "@id" : "_:genid22" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute covariance" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeCrossCorrelationFunction", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute CCF" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A cross-correlation analysis that computes an estimate of the cross-correlation function, i.e. the cross-correlation values of two time series inputs for a number of lags. The cross-correlation function shows temporal dependencies of the first input series with respect to the second. The value of the cross-correlation at a specific lag shows how similar the values in the first input series are to values in the second input at time points separated by a number of time units equal to that lag. The cross-correlation value of 0 indicates no correlation. The cross-correlation varies between 1 and -1 (positive and negative correlation, respectively)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#CrossCorrelationAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute cross-correlation function" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeCrossCorrelationFunctionBiased", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute CCF (biased)" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that computes the biased estimator for the cross-correlation function. The biased estimator produces cross-correlation values that deviate from the true cross-correlation." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#ComputeCrossCorrelationFunction" + } ], + "http://www.w3.org/2002/07/owl#disjointWith" : [ { + "@id" : "http://purl.org/neao/steps#ComputeCrossCorrelationFunctionUnbiased" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute cross-correlation function (biased)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeCrossCorrelationFunctionUnbiased", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute CCF (unbiased)" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Stoica2005" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that computes the unbiased estimator for the cross-correlation function, using the formula in Stoica & Moses (2005). The unbiased estimation uses a correction for the bias due to zero-padding in the computation, applied to the normalization coefficient. Therefore, the resultant cross-correlation values are closer to the true cross-correlation." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#ComputeCrossCorrelationFunction" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute cross-correlation function (unbiased)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeCrossPowerSpectralDensityMorletWavelet", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A cross power spectral density analysis that uses the Morlet wavelet transform to obtain the frequency information of the two inputs used to compute the cross power spectral density." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#CrossPowerSpectralDensityAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute cross power spectral density (Morlet wavelet method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeCrossPowerSpectralDensityMultitaper", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute CPSD (multitaper method)" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Thomson1982_1055" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A cross power spectral density (CPSD) analysis that uses a multitaper approach to compute the CPSD, according to Thomson (1982). The multitaper method uses discrete prolate spheroidal functions (DPSS, also known as Slepian sequences) as tapers applied to the inputs. For the computation, a CPSD using the periodogram method is obtained for each pair of tapered signals. The DPSS functions are orthogonal, and therefore applying multiple DPSS tapers result in independent estimates of the CPSD. The final CPSD is obtained by averaging the CPSDs across all tapers. The multitaper method reduces variance and bias in the CPSD, and has a high frequency resolution. However, it is computationally expensive. The number of tapers used is passed as parameter, or estimated from the desired resolution." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#CrossPowerSpectralDensityAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute cross power spectral density (multitaper method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeCrossPowerSpectralDensityPeriodogram", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute CPSD (periodogram method)" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A cross power spectral density (CPSD) analysis that uses the periodogram method. For the computation, the discrete Fourier transform of each input is obtained and their cross-power spectrum is obtained. A window function can be applied to the inputs before the Fourier transform, to reduce spectral leakage. The final CPSD is obtained by normalizing the cross-power spectrum to the unit frequency using the equivalent noise bandwidth (a factor that depends on the coefficients of the window function and the sampling rate). If no window function is used or a window that does not attenuate the signal is used (e.g., Boxcar or rectangular window) the equivalent noise bandwidth is equal to the frequency resolution." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#CrossPowerSpectralDensityAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "compute cross-periodogram" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute cross power spectral density (periodogram method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeCrossPowerSpectralDensityWelch", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute CPSD (Welch method)" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Welch1967_70" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A cross power spectral density (CPSD) analysis that uses the method defined by Welch (1967). For the computation, the two inputs are divided into several overlapping segments (length and overlap passed as parameters, or computed for the desired frequency resolution based on the input length and sampling frequency). A window function (e.g., Hann) is applied to each segment, and the cross power spectral density using the periodogram method is computed. The final CPSD is obtained by averaging all the periodograms with the individual CPSDs." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#CrossPowerSpectralDensityAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute cross power spectral density (Welch method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeCrossSpectrogramShortTimeFourierTransform", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute cross-spectrogram (STFT method)" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spectrogram analysis that computes a cross-spectrogram using the short-time Fourier transform (STFT). The cross-spectrogram is the time-resolved description of the power of a pair of distinct inputs across the different frequency components. This can be used to investigate how common activity between the two inputs is distributed across the frequency components, and how it varies over time." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpectrogramAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute cross-spectrogram (short-time Fourier transform method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeCubicAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Staude2010_327" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spike train synchrony analysis that uses the Cumulant Based Inference of higher-order Correlation (CuBIC) test described in Staude et al. (2010). CuBIC is a statistical method to detect the presence of higher order correlations in parallel spike trains from a neuronal population (i.e., correlations among three or more neurons). It is based on the analysis of the cumulants of the population spike count. The test takes a population histogram as input data (i.e., a spike train time histogram computed across spike trains with the activity of distinct neurons). A null hypothesis that the third cumulant of the data is less than or equal to the maximized third cumulant for a correlation order is iteratively tested (with increasing orders of correlation). The output is the minimum correlation order necessary to explain the value of the third cumulant calculated from the population spike count, together with the p-values of the hypothesis tests performed." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpikeTrainSynchronyAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute CuBIC analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeCurrentSourceDensityICSD", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute iCSD" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Leski2007_207" + }, { + "@id" : "http://purl.org/neao/bibliography#Leski2011_401" + }, { + "@id" : "http://purl.org/neao/bibliography#Pettersen2006_116" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A current source density (CSD) analysis that uses the inverse current source density (iCSD) estimation method described by Pettersen et al. (2006). The iCSD is based on the inversion of the electrostatic forward solution and can be applied to data obtained from electrodes with multiple configurations. The method can handle cases with spatially confined cortical activity and spatially varying extracellular conductivity.\n \nThree options for CSD estimation using the iCSD exist. The CSD is assumed to have cylindrical symmetry and follows one of three possible assumptions:\n1. is localized in infinitely thin discs;\n2. is step-wise constant;\n3. is continuous and smoothly varying (using cubic splines) in the vertical direction." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#CurrentSourceDensityAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute current source density (inverse method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeCurrentSourceDensityKCSD", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute kCSD" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Potworowski2012_541" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A current source density (CSD) analysis that uses kernel methods to compute the CSD (kCSD), described by Potworowski et al. (2012). kCSD is non parametric and can estimate the CSD using signals recorded from arbitrarily distributed electrodes, as the assumption of regular electrode placement is not necessary. The method can handle 1D, 2D or 3D electrode configurations. The kCSD can also estimate CSD at any location, as it is not limited to the electrode positions, and uses cross-validation to ensure no overfitting." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#CurrentSourceDensityAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute current source density (kernel method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeCurrentSourceDensityStandard", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute CSD" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Freeman1975_369" + }, { + "@id" : "http://purl.org/neao/bibliography#Vaknin1988_131" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A current source density (CSD) analysis that uses a double spatial derivative of the recorded extracellular potentials to compute the CSD. The original method by Freeman & Nicholson (1975) assumes homogeneous cortical in-plane activity, constant extracellular electrical conductivity and equidistant electrode contacts, and can only predict the CSD at interior electrode positions. Vaknin et al. (1988) suggested a procedure to obtain the CSD for the first and last electrodes by copying the outmost recordings, therefore extending the grid beyond the electrode contacts. This is based on the assumption that the potential varies negligibly above the first and below the last electrode." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#CurrentSourceDensityAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute current source density (standard method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeDebiasedSquaredWeightedPhaseLagIndex", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute debiased squared WPLI" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Vinck2011_1548" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A phase lag index (PLI) analysis that computes the debiased squared weighted PLI (WPLI) following Vinck et al. (2011). The direct PLI estimator is positively biased, especially when the sample sizes (i.e., number of trials) are small. The debiased squared WPLI is computed by computing the imaginary components of the cross spectral densities, computing the average imaginary component of the cross spectral densities, and normalizing by the computed average over the magnitudes of the imaginary component of the cross spectral densities." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#PhaseLagIndexAnalysis" + }, { + "@id" : "_:genid23" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute debiased squared weighted phase lag index" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeDirectedPhaseLagIndex", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute DPLI" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Stam2012_1415" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A phase lag index (PLI) analysis that computes the directed PLI (DPLI) according to Stam & van Straaten (2012). The DPLI uses the Heaviside step function on the imaginary part of the cross power spectral density, and provides the ability to discriminate whether the first time series is leading or lagging the second. The DPLI ranges between 0 and 1. A DPLI value of 0.5 means that the first time series leads and lags the second time series equally often. A DPLI value greater than 0.5 means that the first time series leads the second more often than it lags. A value of 1 means that the first time series always leads. On the contrary, a DPLI value smaller than 0.5 means that the first time series lags the second more often than it leads. A DPLI value of zero means that the first time series always lags. The PLI can be computed from the DPLI." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#PhaseLagIndexAnalysis" + }, { + "@id" : "_:genid24" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute directed phase lag index" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeDirectedTransferFunction", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute DTF" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Kaminski1991_203" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A functional connectivity analysis that computes the directed transfer function (DTF) according to Kaminski & Blinowska (1991). DTF can estimate the direction and frequency content of the brain activity flow. The DTF measure is obtained from the spectral transfer matrix computed from multivariate time series input data. For the DTF computation, the spectral transfer matrix is obtained from a multivariate autoregressive model. The DTF estimate is obtained by using a normalization factor computed by the sum along the rows of the spectral transfer matrix. The DTF can have values in the range from 0 to 1." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#FunctionalConnectivityAnalysis" + }, { + "@id" : "_:genid25" + }, { + "@id" : "_:genid26" + }, { + "@id" : "_:genid27" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute directed transfer function" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeEventRelatedPotential", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute ERP" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that computes the event-related potential (ERP). The ERP is the neural activity (e.g., local field potential or electroencephalogram voltages) around a presented stimulus or spontaneous behavioral event. Usually, the event is presented/occurs repeatedly across multiple trials, obtaining multiple event-related potential waveforms that can be averaged to cancel the noise." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute event-related potential" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeEventTriggeredAverage", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A triggered average analysis that uses an event of interest such as an external stimulus (e.g., electrical, visual, auditory) or a spontaneous behavior (e.g., eye blink) as a trigger to average a signal. The output of the method will provide the average value of the signal around the time where each event occurred (event-triggered average)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#TriggeredAverageAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute event-triggered average" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeFrequencyDomainConditionalGrangerCausality", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Dhamala2008_354" + }, { + "@id" : "http://purl.org/neao/bibliography#Ding2006_0608035" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A conditional Granger causality (GC) analysis that computes the GC measures in the frequency domain." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#ConditionalGrangerCausalityAnalysis" + }, { + "@id" : "_:genid28" + } ], + "http://www.w3.org/2002/07/owl#disjointWith" : [ { + "@id" : "http://purl.org/neao/steps#ComputeTimeDomainConditionalGrangerCausality" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute frequency domain conditional Granger causality" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeFrequencyDomainPairwiseGrangerCausalityBrovelli", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Brovelli2004_9849" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A frequency domain pairwise Granger causality (GC) analysis that uses the parametric approach according to Brovelli et al. (2004). It uses an MVAR (multivariate autoregressive model) to obtain the coefficients used for the computation of the spectral transfer matrix needed for GC estimation according to the frequency domain GC formulation by Geweke (1982)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#FrequencyDomainPairwiseGrangerCausalityAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute frequency domain pairwise Granger causality (Brovelli method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeFrequencyDomainPairwiseGrangerCausalityDhamala", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Dhamala2008_354" + }, { + "@id" : "http://purl.org/neao/bibliography#Wilson1972_420" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A frequency domain pairwise Granger causality (GC) analysis that uses the non-parametric approach according to Dhamala et al. (2008). It is based on Fourier and wavelet transforms to obtain the spectral density matrix and the algorithm from Wilson (1972) for its factorization." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#FrequencyDomainPairwiseGrangerCausalityAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute frequency domain pairwise Granger causality (Dhamala method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeFrequencyDomainPairwiseGrangerCausalityHafner", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Hafner2008_215" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A frequency domain pairwise Granger causality (GC) analysis that uses the parametric approach according to Hafner & Herwartz (2008). It uses a multivariate GARCH (generalized autoregressive conditional heteroskedasticity) model and constructs a Wald test on noncausality in variance. This is an alternative to methods based on the residuals of estimated univariate models. The Wald test has superior power properties." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#FrequencyDomainPairwiseGrangerCausalityAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute frequency domain pairwise Granger causality (Hafner method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeFrequencyDomainPairwiseGrangerCausalityWen", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Wen2013_20110610" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A frequency domain pairwise Granger causality (GC) analysis that uses the non-parametric approach according to Wen et al. (2013). It is a multivariate framework for estimating GC based on spectral density matrix factorization. The approach requires only a single estimation of the spectral density matrix for the entire dataset (e.g., multiple time series inputs). GC for the subsets (i.e., pairs of inputs) can then be calculated by factorizing the relevant submatrix of this overall spectral density matrix." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#FrequencyDomainPairwiseGrangerCausalityAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute frequency domain pairwise Granger causality (Wen method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeISIDistance", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Kreuz2007_151" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A time-scale independent spike train distance analysis that computes the ISI-distance, described in Kreuz et al. (2007). For the computation, the discrete sequence of spike times is transformed into a continuous temporal profile with one value per sample point. The values at each time point are derived from the interspike intervals. The distance is then obtained as the temporal average of the time profile. ISI-distance is well-designed to describe similarities in the firing rate profile of the input spike trains, but it is not optimal to capture neuronal synchrony." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#TimeScaleIndependentSpikeTrainDistanceAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute ISI-distance" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeImaginaryCoherency", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Nolte2004_2292" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A coherency analysis that computes the imaginary part of the coherency for two inputs according to Nolte et al. (2004). For the computation, the imaginary part of the complex-valued cross power spectral density obtained for the two inputs is normalized by the square root of the product of their power spectral densities (i.e., auto spectral densities). If the inputs contain multi-epoch data (e.g., multiple trial repetitions), the cross and auto spectral densities are averaged across epochs. The imaginary part of the coherency is less affected by volume conduction than the (complex) coherency." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#CoherencyAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute imaginary coherency" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeInstantaneousFiringRateInterspikeInterval", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An instantaneous firing rate analysis that computes the instantaneous firing rate by using the reciprocal of the interspike intervals." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#InstantaneousFiringRateAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute instantaneous firing rate (interspike interval method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeInstantaneousFiringRateKernelDensityEstimation", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An instantaneous firing rate analysis that computes the instantaneous firing rate by convolution of spike times with a kernel function. The output of the computation is a weighted average of the spikes around the kernel." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#InstantaneousFiringRateAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "compute instantaneous firing rate (kernel smoothing method)" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute instantaneous firing rate (kernel density estimation method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeInstantaneousFiringRateLocalRegression", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Bokil2010_146" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An instantaneous firing rate analysis that computes the instantaneous firing rate using local regression methods. The estimation procedure approximates the log of the firing rate using a low-order polynomial within a moving window (local neighborhood)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#InstantaneousFiringRateAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute instantaneous firing rate (local regression method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeInterquartileRange", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute IQR" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A dispersion statistical analysis that computes the interquartile range (IQR). The IQR is the difference between the 75th and 25th percentiles (i.e., the range within which the central 50% of the data points lie)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DispersionStatisticalAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute interquartile range" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeInterspikeIntervalHistogram", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute ISIH" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An interspike interval analysis that computes the histogram of interspike intervals. For the computation, a time interval with fixed duration starting from zero is discretized into smaller intervals (bins). The count of input interspike intervals whose values fall into each bin is obtained. Therefore, the output contains a representation of the distribution of the interspike intervals in the input." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#InterspikeIntervalAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute interspike interval histogram" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeInterspikeIntervals", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute ISIs" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An interspike interval analysis that computes the intervals between successive spikes in a spike train (interspike intervals; ISIs)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#InterspikeIntervalAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute interspike intervals" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeJointPeristimulusTimeHistogram", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute JPSTH" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Aertsen1987_1" + }, { + "@id" : "http://purl.org/neao/bibliography#Brown2004_456" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spike train synchrony analysis that computes the joint peristimulus time histogram (JPSTH) from trial-by-trial spike train inputs obtained from two different neurons, after the repeated presentation of a stimulus. The JPSTH provides a representation of the timing relationship between the firing of the two neurons in response to the stimulus. It combines the peristimulus time histograms (PSTHs) of each neuron to illustrate how their firing rates co-vary over time relative to the stimulus event. This helps in understanding the temporal correlation between the neurons.\n\nThe computation can produce three outputs: \n\n* the JPSTH matrix (i.e., a matrix whose bins contain the counts of coincidences in the firing of the two neurons);\n* the peristimulus coincidence histogram (i.e., a histogram obtained from a cross-section along the main diagonal of the JPSTH matrix);\n* the cross-correlation histogram computed by summing the bins along the main and each paradiagonal of the JPSTH matrix (after normalizing by the bin length, as the paradiagonals in the JPSTH matrix are of different lengths)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpikeTrainSynchronyAnalysis" + }, { + "@id" : "_:genid29" + }, { + "@id" : "_:genid30" + }, { + "@id" : "_:genid31" + }, { + "@id" : "_:genid32" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute joint peristimulus time histogram" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeLV", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute LV" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Shinomoto2003_2823" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An interspike interval variability analysis that computes the local variation (LV) of the interspike intervals. LV reflects the stepwise variability of a sequence of spikes, and is able to extract the spiking characteristics of individual neurons even in the presence of external modulations of the firing rate." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#InterspikeIntervalVariabilityAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute local variation" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeLVR", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute LvR" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Shinomoto2009_e1000433" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An interspike interval variability analysis that computes the revised local variation (LvR) of interspike intervals. Compared to the original local variation (LV) measure, LvR has better invariance to fluctuations in the firing rate fluctuations. This is achieved by using a refractoriness constant in the computation of the measure." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#InterspikeIntervalVariabilityAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute revised local variation" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeMaximizedImaginaryCoherency", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute MIC" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Ewald2012_476" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A coherency analysis that computes the maximized imaginary coherency (MIC) according to Ewald et al. (2012). The computation uses an eigenvalue-based optimization to find weight vectors that maximize the imaginary part of coherency computed between virtual channels derived from the input data. The weights are optimized for each frequency component. After the weights are obtained, the final MIC measure is obtained for each frequency." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#CoherencyAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute maximized imaginary coherency" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeMean", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A central tendency statistical analysis that computes the mean of the input data. The mean is the arithmetic average of all data points." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#CentralTendencyStatisticalAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute mean" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeMeanFiringRate", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute MFR" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A firing rate analysis that computes the mean firing rate, defined as the number of spikes in a time interval divided by the duration of the interval. The mean firing rate is the temporal average of the neuronal activity over that interval." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#FiringRateAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute mean firing rate" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeMeanPhaseVector", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A phase analysis that computes the mean among two or more input phases. For the computation, the input phases are represented as vectors in the unit circle, and the mean phase vector is computed. The analysis can return the mean phase vector (i.e., angle and length), the vector angle, or the vector length." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#PhaseAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute mean phase vector" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeMeanVectorLengthCanolty", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute MVL (Canolty method)" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Canolty2006_1626" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A mean vector length (MVL) analysis that computes the mean vector length as described in Canolty et al. (2006). For the computation, phase is extracted from the low-frequency analytic signal, and amplitude is extracted from the high-frequency analytic signal. The phase angle and magnitude is used to define a complex-valued time series, and each complex value is a vector in the polar plane. Averaging all vectors yields a mean vector whose length indicates the coupling strength and whose direction indicates the phase where amplitude is strongest. Without coupling, the vectors cancel out, resulting in a short mean vector without meaningful phase direction. If phase-amplitude coupling exists, the magnitude of a subset of vectors is especially high at a specific phase or narrow phase range." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#MeanVectorLengthAnalysis" + } ], + "http://www.w3.org/2002/07/owl#disjointWith" : [ { + "@id" : "http://purl.org/neao/steps#ComputeMeanVectorLengthOzkurt" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute mean vector length (Canolty method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeMeanVectorLengthOzkurt", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute MVL (Özkurt method)" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Ozkurt2011_438" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A mean vector length (MVL) analysis that computes the MVL as described in Özkurt & Schnitzler (2011). The original MVL (Canolty et al., 2006) may be affected by factors in the input data (e.g., amplitude outliers or non-uniform distribution of phase angles). This computation estimates a direct MVL that is amplitude-normalized to obtain values in the 0 to 1 range, and that takes care of possible amplitude differences in the raw data." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#MeanVectorLengthAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute mean vector length (Özkurt method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeMedian", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A central tendency statistical analysis that computes the median of the input data. The median is the middle value when data points are arranged in ascending order (i.e., it divides the data points in two equal halves, with 50% of the data points below it and 50% above it). If there is an even number of data points, the median is the average of the two middle values." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#CentralTendencyStatisticalAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute median" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeModulationIndex", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute MI" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Tort2010_1195" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A phase-amplitude coupling (PAC) analysis that computes the modulation index (MI) as described in Tort et al. (2010). For the computation, the Hilbert transform is used to obtain the instantaneous phase from the input time series with the low-frequency oscillation, and the instantaneous amplitude from the input time series with the high-frequency oscillation. The phase of the low-frequency oscillation is discretized into bins and the amplitude of the high-frequency oscillation is averaged within each bin to create a distribution. This distribution is then compared to a uniform distribution using the Kullback-Leibler divergence, normalized by the maximum possible divergence, resulting in the MI." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#PhaseAmplitudeCouplingAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute modulation index" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeMorletWaveletTransform", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A wavelet transform analysis based on the complex-valued Morlet wavelet. The transform can be performed either in the time domain (by convolution) or in the frequency domain (by multiplication)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#WaveletTransformAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute Morlet wavelet transform" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeMorletWaveletTransformLeVanQuyen", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#LeVanQuyen2001_83" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A wavelet transform analysis using the Morlet wavelet where the parametrization of the mother wavelet is done according to Le Van Quyen et al. (2001). The size of the mother wavelet is determined in number of cycles to control the frequency and temporal resolutions (approximate number of oscillation cycles within a wavelet)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#ComputeMorletWaveletTransform" + } ], + "http://www.w3.org/2002/07/owl#disjointWith" : [ { + "@id" : "http://purl.org/neao/steps#ComputeMorletWaveletTransformTallonBaudry" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute Morlet wavelet transform (Le Van Quyen method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeMorletWaveletTransformTallonBaudry", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#TallonBaudry1997_722" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A wavelet transform analysis using the Morlet wavelet based on the methods described in Tallon-Baudry et al. (1997). The ratio of the central frequency to the spectral bandwidth is 7, with central frequencies ranging from 20 to 100 Hz in 1 Hz steps. This resulted in varying time/frequency resolution across the spectrum: time resolution increases with frequency, while frequency resolution decreases." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#ComputeMorletWaveletTransform" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute Morlet wavelet transform (Tallon-Baudry method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeMultivariateInteractionMeasure", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute MIM" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Ewald2012_476" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A functional connectivity analysis that computes the multivariate interaction measure (MIM) as defined by Ewald et al. (2012). MIM is constructed from the maximization of imaginary coherency." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#FunctionalConnectivityAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute multivariate interaction measure" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeMutualInformation", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute MI" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Cover2012" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A functional connectivity analysis that computes a mutual information (MI) measure. MI is based on Shannon information theory, and quantifies the amount of information from one input that is obtained from another input. Therefore, it can be used to determine how the neuronal activity provides information about a variable (e.g., behavioral stimulus) or how the information flows between different brain regions or neurons. The MI is measured in bits." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#FunctionalConnectivityAnalysis" + }, { + "@id" : "_:genid33" + }, { + "@id" : "_:genid34" + }, { + "@id" : "_:genid35" + }, { + "@id" : "_:genid36" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute mutual information" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeNeuronalPopulationVector", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Georgopoulos1983_327" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that computes the neuronal population vector, used to describe the collective activity of a group of neurons. The neuronal population vector is obtained taking as inputs the multiple responses of a neuronal population in the context of distinct values of a behavioral measure (e.g., tuning curves showing the response of each individual neuron to different arm movement directions in the 2-D space). The analysis step obtains a weighted vectorial sum of the neural activities, which will result in an estimate of the behavioral measure considering the collective activity of the population (e.g., the movement direction given the neuronal activity)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "compute population vector" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute neuronal population vector" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeNoiseCorrelations", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute NC" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Cohen2011_811" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spike train correlation analysis that computes the noise correlations (NC) between two input spike trains. The NC is the Pearson's correlation coefficient of spike count responses to repeated presentations of identical stimuli, under the same behavioral conditions. The spike counts are typically measured over the time scale of a stimulus presentation or a behavioral trial, which range from a few hundred milliseconds to several seconds. NC assesses whether neurons exhibit trial-by-trial fluctuations in firing rates that are not influenced by varying sensory or behavioral conditions." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpikeTrainCorrelationAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute noise correlations" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeNoiseCovariance", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A covariance analysis that computes the noise covariance, i.e., how much two noise signals vary together. The noise data inputs can be non-subject recordings (e.g., recordings from the empty experimental room) or are obtained from periods without stimulation or meaningful experimental manipulations (e.g., prestimulus intervals). These reflect random variations or disturbances that are not part of the actual signal or data of interest." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#CovarianceAnalysis" + }, { + "@id" : "_:genid37" + }, { + "@id" : "_:genid38" + }, { + "@id" : "_:genid39" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute noise covariance" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeOptimalBinSize", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Scott1979_605" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that finds the optimal bin size considering the input data when discretizing data into smaller intervals (bins). The computation uses the formula from Scott (1979)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute optimal bin size" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeOptimalKernelBandwidth", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Shimazaki2010_171" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that computes the optimal fixed bandwidth (width) for a Gaussian kernel used for the estimation of the firing rate using kernel density estimation. The analysis step uses the input spike train for which the firing rate will be computed, and follows the implementation by Shimazaki & Shinomoto (2010)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute optimal kernel bandwidth" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeOrthogonalizedPowerEnvelopeCorrelation", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Hipp2012_884" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A functional connectivity analysis that computes the orthogonalized power envelope correlation, according to Hipp et al. (2012). This method relies on correlations between the instantaneous amplitudes of cross-region input signals (power envelopes). The instantaneous amplitudes of the two input time series are orthogonalized aiming to remove spurious correlations of signal power (e.g., due to limited spatial resolution of electrophysiological measures)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#CorrelationAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute orthogonalized power envelope correlation" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputePairwisePhaseConsistency", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute PPC" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Vinck2010_112" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A phase analysis that computes the pairwise phase consistency (PPC) measure according to Vinck et al. (2010). The PPC quantifies the distribution of phase differences across the inputs, but is less biased by the number of observations in comparison to the phase locking value (PLV). For the computation, the phase difference (angular distance) is obtained for all pairs of observations in the input (that can be represented as vectors in the unit circle, where the angle is the relative phase). The cosine of the angular distance (an estimate of the dot product of the vectors corresponding to each element in a pair) is computed for every pair, and the PPC estimate is obtained from the average of all pairwise dot products. With phase synchronization, the distribution of the pairwise dot products is centered around an average value, while without synchronization it will be distributed across the unit circle. The PPC provides an unbiased estimate of the squared PLV." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#PhaseAnalysis" + }, { + "@id" : "_:genid40" + }, { + "@id" : "_:genid41" + }, { + "@id" : "_:genid42" + }, { + "@id" : "_:genid43" + }, { + "@id" : "_:genid44" + }, { + "@id" : "_:genid45" + }, { + "@id" : "_:genid46" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute pairwise phase consistency" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputePartialCoherence", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Rosenberg1998_57" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A coherence analysis that computes the partial coherence, i.e., the coherence value between a pair of inputs (e.g., time series with recordings from two distinct electrode channels) after removing the influence of one or more additional inputs (e.g., the time series with the recordings from all remaining channels). The partial coherence is computed according to Rosenberg et al. (1998). The partial coherence reflects the linear association in the frequency domain (for each frequency component) between the pair of inputs of interest, removing spurious coherence caused by confounding factors such as shared inputs to the pair of interest or volume conduction." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#CoherenceAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute partial coherence" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputePartialDirectedCoherence", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute PDC" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Baccala2001_463" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A coherence analysis that computes the partial directed coherence (PDC) according to Baccalá & Sameshima (2001). The PDC describes the relationships between multivariate time series inputs (direction of information flow). To compute the PDC, the multivariate partial coherences obtained from multivariate autoregressive models are decomposed. The PDC reflects a frequency-domain representation of the concept associated with Granger causality." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpectralAnalysis" + }, { + "@id" : "_:genid47" + }, { + "@id" : "_:genid48" + }, { + "@id" : "_:genid49" + }, { + "@id" : "_:genid50" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute partial directed coherence" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputePeristimulusTimeHistogramAdaptiveKernelSmoothing", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute PSTH (adaptive kernel smoothing)" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A peristimulus time histogram (PSTH) analysis that computes the PSTH using kernel density smoothing with an adaptive kernel width. The adaptive kernel is obtained by first computing the PSTH with a fixed-width kernel, and then modifying the kernel width in order to have a constant but time-dependent average number of spikes under the kernel (i.e., segments of the data with a high density of spikes will have a reduced kernel width)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#PeristimulusTimeHistogramAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute peristimulus time histogram (adaptive kernel smoothing)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputePeristimulusTimeHistogramFixedKernelSmoothing", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute PSTH (fixed kernel smoothing)" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A peristimulus time histogram (PSTH) analysis that computes the PSTH using kernel density smoothing with a fixed kernel width specified as parameter." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#PeristimulusTimeHistogramAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute peristimulus time histogram (fixed kernel smoothing)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputePeristimulusTimeHistogramOptimalBinSize", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@id" : "http://purl.org/neao/bibliography#Scott1979_605" + }, { + "@language" : "en", + "@value" : "compute PSTH (optimal bin size)" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A peristimulus time histogram (PSTH) analysis that computes the PSTH finding the optimal bin size from the input spike train data, using the formula from Scott (1979)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#PeristimulusTimeHistogramAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute peristimulus time histogram (optimal bin size)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputePeristimulusTimeHistogramUserSelectedBinSize", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute PSTH (user-selected bin size)" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A peristimulus time histogram (PSTH) analysis that computes the PSTH using a fixed bin size specified as a parameter." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#PeristimulusTimeHistogramAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute peristimulus time histogram (user-selected bin size)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputePhaseDifference", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A phase analysis that computes the difference between two input phases." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#PhaseAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute phase difference" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputePhaseLagIndex", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute PLI" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Stam2007_1178" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A phase lag index (PLI) analysis that computes the PLI following Stam et al. (2007). The input data contains multiple repetitions of a pair of signals (e.g., time series with recordings from a pair of electrodes across multiple trials). For each repetition, the sign of the phase differences between the two time series is obtained from the imaginary part of the cross power spectral density (CPSD). The PLI value is the absolute value of the average of the signs of all repetitions. The PLI ranges between 0 and 1. A PLI of zero means that the first time series leads the second equally often (i.e., indicates either no coupling or coupling with a phase difference centered around 0 mod π, which could be from common sources such as volume conduction). A value greater than zero means an imbalance in the likelihood of the first time series to be either leading or lagging the second time series. A PLI of 1 indicates perfect phase locking, and that the first time series only leads or only lags (at a value of phase differences different from 0 mod π)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#PhaseLagIndexAnalysis" + }, { + "@id" : "_:genid51" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute phase lag index" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputePhaseLockingValue", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute PLV" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Lachaux1999_194" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A phase locking value (PLV) analysis that computes the PLV value as originally described by Lachaux et al. (1999). The input data is a set of pairs of time series (e.g., the trial-by-trial local field potential recorded from two different electrodes). For each time series pair, the instantaneous phase is obtained (e.g., using the Hilbert transform or wavelet decomposition), and the phase difference for each time point is obtained. The PLV value is computed by averaging the complex phase differences across all pairs, obtaining one PLV value per time point. The PLV ranges from 0 to 1. A PLV of 1 indicates perfect phase locking, meaning the phase difference between the two time series is constant over time. A PLV of 0 indicates no phase locking, meaning the phase difference is randomly distributed over time." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#PhaseLockingValueAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute phase locking value" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputePhaseSlopeIndex", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute PSI" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Nolte2008_234101" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A functional connectivity analysis that computes the phase slope index (PSI) according to Nolte et al. (2008). The PSI is based on the slope of the phase of the cross-spectral density between two time series inputs, considering how the phase difference between two signals changes as you move from one frequency bin to the next. It is computed from the complex-valued coherency using a bandwidth specified as parameter. For the computation, the change in phase difference between neighboring frequency bins is obtained (considering the specified bandwidth) and weighted. The PSI value deviates from zero when the phase difference changes consistently across frequencies and there is substantial coherence. The sign of the PSI indicates the temporal order of the two signals (i.e., which signal is leading the other one)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#PhaseAnalysis" + }, { + "@id" : "_:genid52" + }, { + "@id" : "_:genid53" + }, { + "@id" : "_:genid54" + }, { + "@id" : "_:genid55" + }, { + "@id" : "_:genid56" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute phase slope index" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputePopulationHistogram", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spike train time histogram analysis that computes a histogram across two or more spike trains that contain the activity of different neurons (i.e., a neuronal population), recorded at fully-overlapping time intervals. The activity in each histogram bin reflects the combined activity of the population at that time, and the distribution of the histogram corresponds to the population activity over time." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpikeTrainTimeHistogramAnalysis" + } ], + "http://www.w3.org/2002/07/owl#disjointWith" : [ { + "@id" : "http://purl.org/neao/steps#PeristimulusTimeHistogramAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute population histogram" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputePowerSpectralDensityBartlett", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute PSD (Bartlett method)" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Bartlett1950_1" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A power spectral density (PSD) analysis that uses the method defined by Bartlett (1950). For the computation, the input time is divided into non-overlapping segments, with length specified as a parameter. A periodogram is computed for each segment to obtain the single-segment PSD. The final PSD is obtained by averaging all the single-segment PSDs. A window function can be applied to each segment before computing the periodograms. The PSD obtained with the Bartlett method is less noisy than a single periodogram obtained from the entire signal, although the frequency resolution of the estimates is reduced due to segmenting. It is equivalent to the Welch method without any segment overlap." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#PowerSpectralDensityAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute power spectral density (Bartlett method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputePowerSpectralDensityMultitaper", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute PSD (multitaper method)" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Thomson1982_1055" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A power spectral density (PSD) analysis that uses a multitaper approach to compute the PSD, according to Thomson (1982). The multitaper method uses discrete prolate spheroidal functions (DPSS, also known as Slepian sequences) as tapers applied to the input signal. For the computation, a PSD using the periodogram method is obtained for each tapered signal. The DPSS functions are orthogonal, and therefore applying multiple DPSS tapers result in independent estimates of the PSD. The final PSD is obtained by averaging the periodograms across all tapers. The multitaper method reduces variance and bias in the PSD, and has a high frequency resolution. However, it is computationally expensive. The number of tapers used is passed as parameter, or estimated from the desired resolution." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#PowerSpectralDensityAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute power spectral density (multitaper method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputePowerSpectralDensityPeriodogram", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute PSD (periodogram method)" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A power spectral density (PSD) analysis that uses the periodogram method. For the computation, the discrete Fourier transform is applied to the full length of the input, and the power spectrum is obtained. To reduce spectral leakage, a window function can be applied to the input before the computation of the Fourier transform (this is referred as the modified periodogram). The power spectrum is then normalized to the unit frequency, using the equivalent noise bandwidth (a factor that depends on the coefficients of the window function and the sampling rate). If no window function is used or a window that does not attenuate the signal is used (e.g., Boxcar or rectangular window) the equivalent noise bandwidth is equal to the frequency resolution. The PSD using the periodogram is computationally simple to obtain." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#PowerSpectralDensityAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "compute FFT power spectral density" + }, { + "@language" : "en", + "@value" : "compute periodogram" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute power spectral density (periodogram method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputePowerSpectralDensityWelch", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute PSD (Welch method)" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Welch1967_70" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A power spectral density (PSD) analysis that uses the method defined by Welch (1967). For the computation, the input is divided into several overlapping segments (length and overlap passed as parameters, or computed for the desired frequency resolution based on the input length and sampling frequency). A window function (e.g., Hann) is applied to each segment, and a periodogram is computed to obtain the PSD for the segment. The final PSD is obtained by averaging all the periodograms with the single-segment PSDs. If there is no overlap between segments, this is equivalent to the Bartlett method." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#PowerSpectralDensityAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute power spectral density (Welch method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeRateChangeDetectionMultipleFilterTest", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Messer2014_2027" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that uses the change point detection algorithm from Messer et al. (2014) to determine if a input spike train has constant firing rate (stationary) or has one or more points in which the firing rate decreases or increases (change point). In the latter case, the spike train is considered non-stationary. The analysis step outputs one or more change points in the case of non-stationarity." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute rate change detection multiple filter test" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeRectifiedAreaUnderCurve", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute RAUC" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that computes the rectified area under the curve (RAUC). For the computation, the input signal is rectified (i.e., the absolute value is obtained) and the area under the curve is computed by integration using the composite trapezoidal rule." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute rectified area under the curve" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeRegularizedCovariance", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A covariance analysis where the computation of the covariance values incorporates regularization techniques to improve the numerical stability, especially if the number of samples is small." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#ComputeCovariance" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute regularized covariance" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeSPIKEDistance", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Kreuz2012_1457" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A time-scale independent spike train distance analysis that computes the SPIKE-distance, described in Kreuz et al. (2012). For the computation, the discrete sequence of spike times is transformed in a continuous temporal profile with one value per sample point. The values at each time point are derived from the differences in the spike times of the two input spike trains. Compared to the ISI-distance, the SPIKE-distance is more sensitive to spike timing." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#TimeScaleIndependentSpikeTrainDistanceAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute SPIKE distance" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeSPIKESynchronization", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Kreuz2015_3432" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A time-scale independent spike train distance analysis that computes the SPIKE synchronization distance, described in Kreuz et al. (2015). The distance detects coincidences in the spiking activity and can quantify the degree of synchrony in the input spike trains. The metric quantifies the overall fraction of coincidences. It is zero-valued if and only if the input spike trains do not contain any coincidences. It has a value of 1 if and only if each spike in every input spike train has one matching spike in all the other spike trains." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#TimeScaleIndependentSpikeTrainDistanceAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute SPIKE synchronization" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeShortTimeFourierTransform", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute STFT" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A time-frequency analysis that computes the short-time Fourier transform (STFT) of the input time series. The analysis divides the input time-domain signal into short segments with equal time and computes the Fourier transform for each segment. The output is a sequence of coefficients of complex sinusoids, each representing a frequency component in the input signal at a distinct time segment. Therefore, this provides the the time-localized frequency and phase information of the input. The segments can be windowed using a window function." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#TimeFrequencyAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute short-time Fourier transform" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeSpectrogramMorletWavelet", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spectrogram analysis that uses the Morlet wavelet transform on the input to obtain the time-frequency information used to build the spectrogram." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpectrogramAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute spectrogram (Morlet wavelet method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeSpectrogramMultitaper", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spectrogram analysis that uses a multitaper approach to obtain the time-frequency information from the input and that is used to build the spectrogram." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpectrogramAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute spectrogram (multitaper method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeSpectrogramShortTimeFourierTransform", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute spectrogram (STFT method)" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spectrogram analysis that uses the short-time Fourier transform (STFT) on the input to obtain the time-frequency information used to build the spectrogram." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpectrogramAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute spectrogram (short-time Fourier transform method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeSpikeContrast", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Ciba2018_136" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spike train synchrony analysis that computes the Spike-contrast measure using the method described by Ciba et al. (2018). Spike-contrast is a time-scale independent measure of spike synchrony. The input is a set of parallel spike train data recorded from a population of neurons. The algorithm is based on the temporal \"contrast\" (activity vs. non-activity in certain time bins). The computation outputs a single synchrony value (comparable to a spike train distance) and a synchrony curve showing the value of Spike-contrast as a function of the bin size." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpikeTrainSynchronyAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute Spike-contrast" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeSpikeFieldCoherenceFries", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Fries2001_1560" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spike-field coherence analysis that uses the method described in Fries et al. (2001) to compute the coherence between the spike train and the LFP. For the computation, first a spike-triggered average (STA) is obtained between the spike train and the LFP time series. Then, the power spectrum is obtained for each of the LFP segments used for the computation of the STA. These spectra are averaged to obtain the spike-triggered power spectrum. The SFC is then computed as the ratio of the power spectrum of the STA over the spike-triggered power spectrum." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpikeFieldCoherenceAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute spike-field coherence (Fries method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeSpikeFieldCoherenceMultitaper", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute SFC (multitaper method)" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spike-field coherence analysis that uses a multitaper approach to compute the coherence between the spike train and the LFP." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpikeFieldCoherenceAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute spike-field coherence (multitaper method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeSpikeFieldCoherenceWelch", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute SFC (Welch method)" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Welch1967_70" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spike-field coherence analysis step that uses the method by Welch (1967) to compute the coherence between the spike train and the LFP." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpikeFieldCoherenceAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute spike-field coherence (Welch method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeSpikeTimeTilingCoefficient", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute STTC" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Cutts2014_14288" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spike train correlation analysis that computes the spike time tiling coefficient (STTC) as described by Cutts and Eglen (2014). The STTC measures the pairwise correlation between two input spike trains, and has advantages over the related correlation index: it is not confounded by the firing rate, it distinguishes lack of correlation from anti-correlation, periods without neural activity don't add to the correlation, and it is sensitive to firing patterns. The computation is based on a synchronicity window parameter, that is used to define short time windows around each spike that are used in the computation (spike time tiling)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpikeTrainCorrelationAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute spike time tiling coefficient" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeSpikeTrainAutocorrelationHistogram", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An autocorrelation analysis that computes the autocorrelation histogram for a input spike train. The histogram is obtained by sliding a time window that is discretized into smaller time intervals (bins) centered on a spike (corresponding to the lag zero). The spike count in each bin is obtained. Therefore, this binning process measures the number of spikes occurring at various time lags relative to the center spike. The histogram window is slidden over each spike in the input spike train, and the spike count in each bin is accumulated to produce the autocorrelation histogram output. The width of the bin interval is controlled by a parameter." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#AutocorrelationAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute spike train autocorrelation histogram" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeSpikeTrainAutocorrelationTimeScale", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Wieland2015_040901" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that computes the autocorrelation time of a binned spike train input (spike train autocorrelation time scale). The computation follows the method described by Wieland et al. (2015)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute spike train autocorrelation time scale" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeSpikeTrainCrossCorrelationHistogram", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute CCH" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A cross-correlation analysis that computes the cross-correlation histogram (CCH) for a pair of input spike trains. The CCH shows how often spikes in the reference spike train occur before or after spikes in the reference spike train, at distinct lag intervals. For the computation, the spike trains are aligned in time. The histogram is obtained by sliding a time window that is discretized into smaller time intervals (bins) centered on a spike of the first (reference) input spike train (corresponding to the lag zero). The spike count of the second (target) spike train input is then obtained in each bin. Therefore, this binning process measures the number of spikes in the target spike train occurring at various time lags relative to the spikes in the reference spike train. The histogram window is slidden over each spike in the reference spike train, and the spike count in each bin is accumulated to produce the CCH output. The width of the bin interval is controlled by a parameter." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#CrossCorrelationAnalysis" + }, { + "@id" : "_:genid57" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "compute correlogram" + }, { + "@language" : "en", + "@value" : "compute cross-correlogram" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute spike train cross-correlation histogram" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeSpikeTrainCrossCorrelationHistogramEggermont", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute CCH (Eggermont method)" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Eggermont2010_77" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A computation of the cross-correlation histogram (CCH) for a pair of binned input spike trains using the method described in Eggermont (2010). The formula is valid for binned spike train inputs with at most one spike per bin, and returns the cross-correlation coefficient for the lags considered (range -1 to 1)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#ComputeSpikeTrainCrossCorrelationHistogram" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "compute correlogram (Eggermont method)" + }, { + "@language" : "en", + "@value" : "compute cross-correlogram (Eggermont method)" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute spike train cross-correlation histogram (Eggermont method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeSpikeTrainFanoFactor", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Nawrot2008_374" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that computes the Fano factor (FF) for a set of input spike trains. For each input spike train, the spike count is obtained. The Fano factor is defined as the ratio of the variance of the spike count to the mean spike count, across all spike trains. The Fano factor is usually computed for spike trains representing the activity of the same neuron over different trials. The value is interpreted as the higher the Fano factor value, the larger the cross-trial non-stationarity. For a stationary Poisson process, the Fano factor has value equal to 1." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#NeuronalFiringRegularityAnalysis" + }, { + "@id" : "_:genid58" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute spike train Fano factor" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeSpikeTrainPearsonCorrelationCoefficient", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spike train correlation analysis that computes the Pearson correlation coefficient between two spike train inputs. The Pearson correlation coefficient is a real value that quantifies the linear relationship between the two spike trains. It has range [-1, 1], where 1 indicates a perfect positive linear relationship, -1 indicates a perfect negative linear relationship, and 0 indicates no linear relationship. For the computation, the input spike trains are discretized into time intervals (bins), and the spike count is obtained in each bin. The Pearson correlation coefficient is obtained by normalizing the covariance between the binned spike trains: the covariance is divided by the product of the standard deviation of each." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpikeTrainCorrelationAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute spike train Pearson correlation coefficient" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeSpikeTrainTimeHistogram", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that computes the time histogram of a spike train. If the spike count in a bin is divided by the duration of the bin, this can be used to estimate the instantaneous firing rate at the bin interval." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpikeTrainTimeHistogramAnalysis" + }, { + "@id" : "_:genid59" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute spike train time histogram" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeSpikeTriggeredAverage", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute STA" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A triggered average analysis that uses spike times as triggers to obtain the average of a signal around each spike (spike-triggered average)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#TriggeredAverageAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute spike-triggered average" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeSpikeTriggeredLFPAverage", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute STA" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A triggered average analysis that uses spike times as triggers to average the local field potential (LFP) signal. The LFP is the low-frequency component of the potential recorded within a specific region of the brain using extracellular electrodes. The output of the method will provide an estimation of the average LFP voltage around each spike, i.e., the spike-triggered average of the LFP signal." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#ComputeSpikeTriggeredAverage" + }, { + "@id" : "_:genid60" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute spike-triggered local field potential average" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeSpikeTriggeredPhase", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A phase analysis that computes the phase angle values of an analytic signal input (or from the analytic signal obtained from an input time series) at the time points where spikes occurred. The spike times are defined in a spike train input. The output is an array with the phase angle at each spike time in the input spike train (spike-triggered phases)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#PhaseAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute spike-triggered phase" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeSpikeWaveformAverage", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spike waveform analysis that computes the average across two or more spike waveform inputs. For the computation, the mean value across all inputs is obtained for each time point in the sampled spike waveform. This is frequently used to reduce noise across multiple spike waveform samples of a single neuron." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpikeWaveformAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute spike waveform average" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeSpikeWaveformSNR", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute spike waveform SNR" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Hatsopoulos2007_5105" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spike waveform analysis that computes the signal-to-noise ratio (SNR) for a set of input spike waveforms according to Hatsopoulos (2007). The SNR is defined as the difference in mean peak-to-trough voltage divided by twice the mean standard deviation (SD).The mean SD is obtained by averaging the SDs computed for each time point in the spike waveform." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpikeWaveformAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute spike waveform signal-to-noise ratio" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeSpikeWaveformVariance", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spike waveform analysis that computes the variance across two or more spike waveform inputs. For the computation, the value of the variance across all inputs is obtained for each time point in the spike waveform." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpikeWaveformAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute spike waveform variance" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeSpikeWaveformWidth", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spike waveform analysis that computes the width of a spike waveform input. The computation takes two time points of interest (e.g, the times of the peak and the trough), and the width is the difference with respect to the time points (e.g., number of time points in between or time interval)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpikeWaveformAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute spike waveform width" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeStandardDeviation", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute SD" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A dispersion statistical analysis that computes the standard deviation (SD), i.e., the square root of the variance. The SD indicates the average distance of each data point from the mean." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DispersionStatisticalAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute standard deviation" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeStandardErrorMean", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute SEM" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A dispersion statistical analysis that computes the standard error of the mean (SEM). The SEM is the standard deviation of the sampling distribution of the sample mean. It provides an estimate of how much the sample mean is expected to fluctuate around the true population mean. Smaller SEM values indicates that the sample mean is a more accurate estimate of the population mean. The SEM decreases as the sample size increases, as larger samples provide a more reliable estimate of the population mean." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DispersionStatisticalAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute standard error of the mean" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeStockwellTransform", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Stockwell1996_998" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A time-frequency analysis that computes the Stockwell transform (S transform) of the input time series. The S transform generalizes the short-time Fourier transform (STFT) and extends the continuous wavelet transform (CWT). The main difference is that STFT uses a constant window width for all frequencies. The S transform is based on a moving and scalable localizing Gaussian window. Therefore, the window is frequency-dependent (adaptive windowing), which results in better time resolution in higher frequencies and better frequency resolution at lower frequencies. This makes the S transform more suitable to detect transient signals in high frequencies. The computation is computationally expensive, although fast algorithms are available." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#TimeFrequencyAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "compute S transform" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute Stockwell transform" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeTimeDomainConditionalGrangerCausality", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Ding2006_0608035" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A conditional Granger causality (GC) analysis that computes the GC measures in the time domain." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#ConditionalGrangerCausalityAnalysis" + }, { + "@id" : "_:genid61" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute time domain conditional Granger causality" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeTimeDomainPairwiseGrangerCausality", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Ding2006_0608035" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A pairwise Granger causality (GC) analysis that computes measures of GC between two inputs in the time domain. The computation involves fitting two separate autoregressive (AR) models to the input data and comparing their fit to determine if one time series can predict the other. The quality of the fit is assessed by the variance of the residuals, with GC defined as the natural logarithm of the ratio of the residual variances from the two AR models. The first AR model is univariate, predicting the future values of one time series (e.g., the first) only from its past values. The second AR model is bivariate, predicting the future values of the first time series from its past values as well as the past values of the second time series. If the bivariate model reduces the variance of the residuals (ratio greater than 1), the GC value will be positive, indicating that the second time series Granger causes the first (directional GC estimate from the second to the first). The same method is used to predict the second time series from the first, yielding the directional GC estimate from the first to the second time series. The order of the AR model is defined as parameter, and optimal values can be estimated using optimization techniques." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#PairwiseGrangerCausalityAnalysis" + }, { + "@id" : "_:genid62" + } ], + "http://www.w3.org/2002/07/owl#disjointWith" : [ { + "@id" : "http://purl.org/neao/steps#FrequencyDomainPairwiseGrangerCausalityAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute time domain pairwise Granger causality" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeTransferEntropy", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute TE" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Schreiber2000_461" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A functional connectivity analysis that computes a measure of transfer entropy (TE) between two input time series. TE measures the directional transfer of information between the time series. It extends Granger causality, and is able to detect non-linear forms of interaction." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#FunctionalConnectivityAnalysis" + }, { + "@id" : "_:genid63" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute transfer entropy" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeTuningCurve", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A firing rate analysis that computes a tuning curve. The tuning curve describes the firing rate of a neuron as a function of a continuous attribute (e.g., orientation of a visual grating stimulus)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#FiringRateAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute tuning curve" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeUnbiasedSquaredPhaseLagIndex", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute unbiased squared PLI" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Vinck2011_1548" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A phase lag index (PLI) analysis that computes an unbiased estimate for the squared PLI following Vinck et al. (2011). The direct PLI estimator is positively biased, especially when the sample sizes (i.e., number of trials) are small. The unbiased squared PLI is computed by averaging all pairwise products of the signs computed across the repetitions. Pairs with identical observations are excluded. The unbiased squared PLI is less affected by small-sample size biases." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#PhaseLagIndexAnalysis" + }, { + "@id" : "_:genid64" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute unbiased squared phase lag index" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeVanRossumDistance", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Rossum2001_751" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A time-scale dependent spike train distance analysis that computes the van Rossum distance introduced in van Rossum (2001). For the computation, each spike in the input spike trains is convolved with an exponential kernel, producing continuous function representations of the input spike trains. The time scale parameter of the distance is set by the time constant of the exponential kernel. The distance is then obtained as the Euclidean distance of the convolved spike trains." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#TimeScaleDependentSpikeTrainDistanceAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute van Rossum distance" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeVariance", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A dispersion statistical analysis that computes the variance, i.e., the average of the squared differences from the mean." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DispersionStatisticalAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute variance" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeVictorPurpuraDistance", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Victor1996_1310" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A time-scale dependent spike train distance analysis that computes the Victor-Purpura distance, introduced in Victor & Purpura (1996). The metric defines the distance between two spike train inputs with respect to the minimum cost of transforming one spike train into the order considering three operations: spike insertion, spike deletion and shifting a spike by some interval. The first two operations have a fixed cost equal to 1. The latter depends on a cost per time unit parameter, which sets the time scale of the analysis." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#TimeScaleDependentSpikeTrainDistanceAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute Victor-Purpura distance" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputeWeightedPhaseLagIndex", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute WPLI" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Vinck2011_1548" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A phase lag index (PLI) analysis that computes the weighted PLI (WPLI) following Vinck et al. (2011). The original PLI (Stam, 2007) is discontinuous, and small perturbations can turn phase lags into leads (and vice versa). Therefore, this hinders its capacity to detect changes in phase synchronization of small magnitude. The WPLI extends the PLI to weight the contributions of the phase leads and lags by the magnitude of the imaginary component of the cross spectral density. Therefore, these increases the power to detect changes in phase synchronization. The WPLI ranges between 0 and 1. A WPLI of zero means that there is no imbalance in the first time series leading or lagging the second (i.e., the total weight of all leading relationships is equal to the total weight of lagging relationships). A value greater than zero means an imbalance in the likelihood of leading or lagging. A WPLI of 1 indicates perfect phase locking, and that the first time series only leads or only lags." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#PhaseLagIndexAnalysis" + }, { + "@id" : "_:genid65" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute weighted phase lag index" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ComputedEvokedPotential", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "compute EP" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that computes the evoked potential (EP). The EP is the neural activity (e.g., local field potential or electroencephalogram voltages) around a presented stimulus (e.g., auditory, visual, electrical). Usually, the stimulus is presented repeatedly across multiple trials, obtaining multiple evoked potential waveforms that can be averaged to cancel the noise. It is an event-related potential (ERP) obtained from presenting a stimulus rather than spontaneous behavioral events." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#ComputeEventRelatedPotential" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "compute evoked potential" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ConditionalGrangerCausalityAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A Granger causality (GC) analysis that computes a measure of conditional GC between the inputs. The conditional GC is the causality between two inputs (e.g., two time series) while controlling for the influence of an additional input (e.g., a third time series). This allows a more complete understanding of the causal relationships in multivariate time series data." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#GrangerCausalityAnalysis" + }, { + "@id" : "_:genid66" + } ], + "http://www.w3.org/2002/07/owl#disjointWith" : [ { + "@id" : "http://purl.org/neao/steps#PairwiseGrangerCausalityAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "conditional Granger causality analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ConfidenceIntervalResamplingAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A confidence interval statistical analysis that computes the confidence interval using techniques to generate multiple samples from the (observed) data input(s)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#ConfidenceIntervalStatisticalAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "confidence interval with resampling analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ConfidenceIntervalStatisticalAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A statistical analysis that computes a confidence interval (CI). The CI is a measure providing a range of values of a parameter, derived from the input (sample) data, that is likely to contain the true value of the parameter in the population with a specified level of confidence. The level of confidence is specified as a parameter to the method. For example, a 95% confidence interval means that if the same population is sampled multiple times, approximately 95% of the intervals calculated from those samples will contain the true population parameter. Confidence intervals are used to estimate parameters such as the mean and are essential for making inferences about the population based on sample data. The output contains the upper and lower limits of the CI." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#StatisticalAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "confidence interval statistical analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#CorrelatedSpikeTimesGeneration", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spike train generation where the output spike trains will have spikes that are correlated in time. These methods can be used to generate spike trains with patterns in their activity." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpikeTrainGeneration" + } ], + "http://www.w3.org/2002/07/owl#disjointWith" : [ { + "@id" : "http://purl.org/neao/steps#RandomSpikeTimesGeneration" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "correlated spike times generation" + } ] +}, { + "@id" : "http://purl.org/neao/steps#CorrelationAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that computes a measure of correlation between two inputs. Correlation is a measure that quantifies the strength to which two variables change together. It is a scaled version of the covariance, and the values are restricted to the -1 to +1 interval. Between time series, it is computed in the time domain." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + }, { + "@id" : "_:genid68" + }, { + "@id" : "_:genid69" + }, { + "@id" : "_:genid70" + }, { + "@id" : "_:genid71" + }, { + "@id" : "_:genid72" + } ], + "http://www.w3.org/2002/07/owl#equivalentClass" : [ { + "@id" : "_:genid67" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "correlation analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#CorrelationPurpose", + "@type" : [ "http://www.w3.org/2002/07/owl#NamedIndividual" ], + "http://www.w3.org/1999/02/22-rdf-syntax-ns#type" : [ { + "@id" : "http://purl.org/neao/steps#AnalysisPurpose" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The analysis purpose of computing a correlation measure." + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "correlation purpose" + } ] +}, { + "@id" : "http://purl.org/neao/steps#CovarianceAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step used to compute a measure of covariance from two inputs. The covariance indicates the extent to which the two inputs change together. If the greater values of one variable mainly correspond with the greater values of the other variable, and the same applies to the lesser values, then the covariance is positive. Conversely, if greater values of one variable mainly correspond to the lesser values of the other variable, then the covariance is negative." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "covariance analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#CrossCorrelationAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step used to compute a measure of cross-correlation, i.e., the correlation of two inputs computed for distinct time lags of the first to the second. The computation produces the cross-correlation value for every lag considered." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + }, { + "@id" : "_:genid73" + }, { + "@id" : "_:genid74" + }, { + "@id" : "_:genid75" + }, { + "@id" : "_:genid76" + }, { + "@id" : "_:genid77" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "cross-correlation analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#CrossPowerSpectralDensityAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "CPSD analysis" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spectral density analysis that computes the cross power spectral density (CPSD) of two inputs, i.e., the distribution of their power across the different frequency components per unit frequency. The CPSD shows in the frequency domain how the two inputs are correlated in the time domain, and is equivalent to the Fourier transform of the cross-correlation function between the two signals. If the inputs are not correlated, the CPSD will be flat across the frequencies. A peak suggests that the signals are correlated at that frequency. The CPSD is often referred to as cross-spectrum." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpectralDensityAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "cross power spectral density analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#CurrentSourceDensityAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "CSD analysis" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step used to analyze extracellular electrical potentials (e.g., local field potentials or evoked potentials) recorded from multiple locations, enabling the estimation of the current sources responsible for generating these potentials. The methods can be applied to data recorded from different electrode configurations: laminar probe-like electrodes (1D methods), microelectrode array-like electrodes (2D methods) or electrodes configurations recording from a volume (e.g., multiple laminar probes or array electrodes with shanks with multiple depths; 3D methods). The output of the current source analysis provides the spatial map showing where currents are entering (sources) and leaving (sinks) the neural tissue. For each point in the map, a quantitative value indicates the magnitude of the current density at that point." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "source imaging analysis" + }, { + "@language" : "en", + "@value" : "source localization analysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "current source density analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#DataGeneration", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that generates new data entities. This can be done using other input data as a start (e.g., generating a spike train surrogate from spike trains obtained from experimental recordings) or generate new data using algorithms that take specific parameters (e.g., generating a spike train using a probability distribution defined by specific parameters)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "data generation" + } ] +}, { + "@id" : "http://purl.org/neao/steps#DataNormalization", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A data transformation that adjusts the ranges and distributions of the values in the input data. This can be used to transform data measured in distinct (i.e. not directly comparable) scales to a common (i.e. comparable) scale." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DataTransformation" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "data normalization" + } ] +}, { + "@id" : "http://purl.org/neao/steps#DataSmoothing", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A data transformation that uses statistical techniques to remove noise and fluctuations from the input data to reveal underlying trends and patterns." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DataTransformation" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "data smoothing" + } ] +}, { + "@id" : "http://purl.org/neao/steps#DataSmoothingPurpose", + "@type" : [ "http://www.w3.org/2002/07/owl#NamedIndividual" ], + "http://www.w3.org/1999/02/22-rdf-syntax-ns#type" : [ { + "@id" : "http://purl.org/neao/steps#AnalysisPurpose" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The analysis purpose of smoothing the data." + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "data smoothing purpose" + } ] +}, { + "@id" : "http://purl.org/neao/steps#DataTransformation", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that takes one or more inputs and modifies the contents, such that it fits a particular purpose. The data transformation steps are frequently used during pre-processing the input data for the analyses. Usually, a data transformation will not change the main representation or quality of the inputs. For example, a digital filtering step will remove certain frequency components from a time series. However, the output will resemble the original input with respect to shape or physical units. In addition, the inputs can also be converted to other formats or representations that are needed for a particular analysis step. For example, spike trains can be discretized into small intervals (binning) or the dimensionality of the input can be reduced using principal component analysis. The data transformation is in contrast to steps that perform computations that take the input and generate a derived measure with new information. For example, when computing the mean firing rate from a spike train, a single scalar value is obtained from the spike count in the input data." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "data transformation" + } ] +}, { + "@id" : "http://purl.org/neao/steps#Detrending", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A data transformation that removes a trend (i.e., a change in the mean over time) from an input time series." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DataTransformation" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "detrending" + } ] +}, { + "@id" : "http://purl.org/neao/steps#DigitalFiltering", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A data transformation that processes digital signal inputs (i.e., sampled time series) to attenuate or amplify specific frequency components. Digital filters can be designed using various methods, achieving distinct frequency responses and stability." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DataTransformation" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "digital filtering" + } ] +}, { + "@id" : "http://purl.org/neao/steps#DimensionalityReduction", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A data transformation that obtains a low-dimensional (simplified) representation of the high-dimensional input data. This step retains important information in the input data while minimizing redundancy and noise." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DataTransformation" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "dimensionality reduction" + } ] +}, { + "@id" : "http://purl.org/neao/steps#DirectedAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step where the output provides information on the direction of influence in the relationships among the inputs (e.g., in the cross-correlation histogram, it is possible to analyze the timing of the spikes of the first input spike train with respect to the timing of the spikes of the second input spike train, i.e., whether they likely occur before or after)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2002/07/owl#disjointWith" : [ { + "@id" : "http://purl.org/neao/steps#NonDirectedAnalysis" + } ], + "http://www.w3.org/2002/07/owl#equivalentClass" : [ { + "@id" : "_:genid78" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "directed analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#DispersionStatisticalAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A statistical analysis that computes a measure that represents the variability in the input data. It indicated the degree to which the data points differ from the central tendency." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#StatisticalAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "dispersion statistical analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#DistanceAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2002/07/owl#equivalentClass" : [ { + "@id" : "_:genid79" + } ] +}, { + "@id" : "http://purl.org/neao/steps#DistancePurpose", + "@type" : [ "http://www.w3.org/2002/07/owl#NamedIndividual" ], + "http://www.w3.org/1999/02/22-rdf-syntax-ns#type" : [ { + "@id" : "http://purl.org/neao/steps#AnalysisPurpose" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The analysis purpose of computing a distance metric." + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "distance purpose" + } ] +}, { + "@id" : "http://purl.org/neao/steps#Execute3dSPADEAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Stella2019_104022" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A SPADE analysis that uses the 3d-SPADE implementation as defined in Stella et al. (2019). The 3d-SPADE analysis considers spatio-temporal patterns (i.e., not restricted to synchronous patterns), and the pattern signature used for statistical testing considers the size, number of occurrences and duration of a pattern." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SPADEAnalysis" + } ], + "http://www.w3.org/2002/07/owl#disjointWith" : [ { + "@id" : "http://purl.org/neao/steps#ExecuteNon3dSPADEAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "execute 3d-SPADE analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ExecuteASSETAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Torre2016_e1004939" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A neuronal activity pattern detection analysis that uses the Analysis of Sequences of Synchronous EvenTs (ASSET) method defined in Torre et al. (2016). ASSET is an automatized test to identify the sequential activations of groups of neurons that repeat in time. The identification of the repeated sequences is possible by computing the intersection matrix. The input spike data is discretized into smaller intervals (bins), and the overlap of neuronal activity at each bin pair is obtained as a matrix. When a sequence of activations exists and repeats in time, a characteristic diagonal structure appears in the matrix.\n\nThe ASSET analysis provides a robust statistical test to automatically identify the diagonal structures and to provide the neurons and their activation pattern in each repeated sequence. Overall, the analysis is composed by 6 substeps:\n\n1. Compute the intersection matrix (IMAT) from a set of input spike trains, using a specified bin size to discretize the data.\n2. Obtain the probability matrix (PMAT).\n3. Obtain the joint probability matrix (JMAT).\n4. Extract significant entries in both PMAT and JMAT using specified thresholds, obtaining the mask matrix (MMAT).\n5. Obtain the cluster matrix (CMAT) by using DBSCAN to cluster the significant entries in the MMAT to find each diagonal structure. Parameters for DBSCAN control the clustering result. A modified distance metric is used.\n6. From the identified clusters (each a single diagonal structure in the IMAT), obtain the neuronal composition and the order of activation, producing the final neuronal activity patterns as output." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#NeuronalActivityPatternDetectionAnalysis" + }, { + "@id" : "_:genid80" + }, { + "@id" : "_:genid81" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "execute ASSET analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ExecuteCellAssemblyDetectionAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "execute CAD analysis" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Russo2017_e19428" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A neuronal activity pattern detection analysis that uses the Cell Assembly Detection (CAD) method as defined in Russo & Durstewitz (2017). CAD allows detecting spatio-temporal spike patterns at different time scales, levels of precision, and with arbitrary internal organization. The analysis identifies patterns with different delays between the spikes (within a window determining the minimum and maximum lags), and is performed in two steps using an agglomerative clustering algorithm. First, significant pairwise correlations are identified, which is followed by the clustering procedure that progressively finds interactions of higher order. At each agglomeration step, the method can filter out patterns involving the same neurons, keeping the most significant pattern (significance pruning). In an additional pruning step, assemblies part of a larger assembly can also be eliminated (controlled by the subgroup pruning parameter). The algorithm stops when the detected assemblies reach their maximum size (determined by a parameter). The statistical test assumes independence under non-stationarity and Poisson distribution of the input spike trains." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#NeuronalActivityPatternDetectionAnalysis" + }, { + "@id" : "_:genid82" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "execute Cell Assembly Detection analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ExecuteNon3dSPADEAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Quaglio2017_41" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A SPADE analysis that uses the SPADE implementation as defined in Quaglio et al. (2017). This is the extension of SPADE to consider spatio-temporal patterns (i.e., patterns not restricted to synchronous spiking). In the non-3d SPADE analysis, the pattern signature used for statistical testing considers only the size and number of occurrences of a pattern." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SPADEAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "execute non-3d-SPADE analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ExecuteUnitaryEventAnalysisAnalytical", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "execute UE analysis (analytical method)" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Gruen1999_67" + }, { + "@id" : "http://purl.org/neao/bibliography#Gruen2002_43" + }, { + "@id" : "http://purl.org/neao/bibliography#Gruen2002_81" + }, { + "@id" : "http://purl.org/neao/bibliography#Gruen2003_335" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A unitary event (UE) analysis that uses the analytical approach to determine the significance of the empirical coincidences in binned spike train data, as defined in Grün et al. (1999, 2002a, 2002b, and 2003). The analytical method tests if the number of empirical coincidences is consistent with the coincidence distribution resulting from independent processes. This distribution can be expressed analytically assuming that the input spike trains follow Poisson statistics. The UEs can be determined trial by trial, where the analytical expectancy is computed for each trial and then summed over all trials, or by averaging over all trials (according to Grün, 2003)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#UnitaryEventAnalysis" + } ], + "http://www.w3.org/2002/07/owl#disjointWith" : [ { + "@id" : "http://purl.org/neao/steps#ExecuteUnitaryEventAnalysisMonteCarlo" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "execute Unitary Event analysis (analytical method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ExecuteUnitaryEventAnalysisMonteCarlo", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "execute UE analysis (Monte Carlo method)" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Gruen2009_1126" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A unitary event (UE) analysis that uses a Monte Carlo approach based on spike train surrogates to determine the significance of the empirical coincidences in binned spike train data, according to Grün (2009). The Monte Carlo method does not rely on the assumption that the input spike data follows Poisson statistics. For the assessment of significance, the distribution of expected coincidences is determined by surrogates (spike train randomization) in each trial, and then summed over trials. The number of surrogates is determined by a parameter." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#UnitaryEventAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "execute Unitary Event analysis (Monte Carlo method)" + } ] +}, { + "@id" : "http://purl.org/neao/steps#FieldFieldCouplingAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that computes interactions between the neural activity represented by distinct local field potential (LFP) signals (e.g., LFP obtained from different electrodes, or distinct LFP frequency bands)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2002/07/owl#disjointWith" : [ { + "@id" : "http://purl.org/neao/steps#SpikeSpikeCouplingAnalysis" + } ], + "http://www.w3.org/2002/07/owl#equivalentClass" : [ { + "@id" : "_:genid83" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "field-field coupling analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#FieldFieldCouplingPurpose", + "@type" : [ "http://www.w3.org/2002/07/owl#NamedIndividual" ], + "http://www.w3.org/1999/02/22-rdf-syntax-ns#type" : [ { + "@id" : "http://purl.org/neao/steps#AnalysisPurpose" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The analysis purpose of assessing the interactions between inputs with local field potential data." + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "field-field coupling purpose" + } ] +}, { + "@id" : "http://purl.org/neao/steps#FiniteImpulseResponseFiltering", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "FIR filtering" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A digital filtering that uses a filter whose impulse response (i.e., the response of the filter to a brief input impulse) decays to zero after a finite amount of time. Therefore, the output of the filter depends on a finite number of past samples. The finite impulse response (FIR) filters are stable and can be designed such that they do not distort the phase of the signal. However, they have a higher computational cost." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DigitalFiltering" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "finite impulse response filtering" + } ] +}, { + "@id" : "http://purl.org/neao/steps#FiringRateAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step used to compute a measure quantifying the firing rate of one or more neurons. The firing rate is the number of action potential (spikes) that a neuron fires per time unit and is defined with a unit of frequency (e.g., Hz or spikes/s)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "firing rate analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#FrequencyDomainAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that analyzes the input(s) with respect to its(their) frequency content." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2002/07/owl#disjointWith" : [ { + "@id" : "http://purl.org/neao/steps#TimeDomainAnalysis" + } ], + "http://www.w3.org/2002/07/owl#equivalentClass" : [ { + "@id" : "_:genid84" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "frequency domain analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#FrequencyDomainPairwiseGrangerCausalityAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Geweke1982_304" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A pairwise Granger causality (GC) analysis that computes measures of GC between two inputs in the frequency domain. This is an extension of the GC concept in the time domain, and the measures of GC are obtained for the different frequency components of the inputs, according to Geweke (1982). The computation of the frequency-domain GC measures is based on two elements: the noise covariance matrix and the spectral transfer matrix. These can be estimated either with parametric or non-parametric methods. For the parametric estimation, an autoregressive model is fit and the Fourier transform of the autoregressive coefficients is used to obtain the spectral transfer matrix. For the non-parametric estimation, the cross-spectral density (CSD) matrix is obtained (using methods for CSD estimation such as multitapering or wavelet), and the CSD matrix is factorized to obtain the noise covariance and spectral transfer matrices." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#PairwiseGrangerCausalityAnalysis" + }, { + "@id" : "_:genid85" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "frequency domain pairwise granger causality analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#FrequencyDomainTransformation", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A data transformation that converts a time series input from the time to the frequency domain, i.e., reveal the different frequency components that make up the original signal." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DataTransformation" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "frequency domain transformation" + } ] +}, { + "@id" : "http://purl.org/neao/steps#FunctionalConnectivityAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "FCA" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that computes measures of functional connectivity. Functional connectivity refers to statistical dependencies and patterns of synchronization between the neural activity that indicate the functional interactions and co-activations that are relevant for the function of the nervous system (e.g., the interactions between different brain regions). It does not imply direct physical connections." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2002/07/owl#equivalentClass" : [ { + "@id" : "_:genid86" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "functional connectivity analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#FunctionalConnectivityPurpose", + "@type" : [ "http://www.w3.org/2002/07/owl#NamedIndividual" ], + "http://www.w3.org/1999/02/22-rdf-syntax-ns#type" : [ { + "@id" : "http://purl.org/neao/steps#AnalysisPurpose" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The analysis purpose of estimating functional connectivity." + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "functional connectivity purpose" + } ] +}, { + "@id" : "http://purl.org/neao/steps#GenerateCompoundPoissonProcess", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/dc/terms/bibliographicCitation" : [ { + "@id" : "http://purl.org/neao/bibliography#Staude2010_327" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A correlated spike times generation that produces spike trains using a compound Poisson process (CPP) according to Staude et al. (2010). The CPP is a model for parallel and correlated processes with Poisson spiking statistics at predefined firing rates." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#CorrelatedSpikeTimesGeneration" + } ], + "http://www.w3.org/2002/07/owl#disjointWith" : [ { + "@id" : "http://purl.org/neao/steps#GenerateSingleInteractionProcess" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "generate CPP" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "generate compound Poisson process" + } ] +}, { + "@id" : "http://purl.org/neao/steps#GenerateISIDitheringSurrogate", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "generate ISI-D surrogate" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Stella2022_ENEURO" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spike train surrogate generation step where each spike is displaced according to the interspike interval (ISI) distribution sampled from the input spike train." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpikeTrainSurrogateGeneration" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "generate joint interspike interval dithering surrogate" + } ] +}, { + "@id" : "http://purl.org/neao/steps#GenerateISIShufflingSurrogate", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Louis2010_359" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spike train surrogate generation step where the interspike intervals (ISIs) of the input spike train is randomly sorted. This preserves the ISI distribution and spike count as in the original spike train input, but destroys temporal dependencies and firing rate profile." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpikeTrainSurrogateGeneration" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "generate interspike interval shuffling surrogate" + } ] +}, { + "@id" : "http://purl.org/neao/steps#GenerateJointISIDitheringSurrogate", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "generate JISI-D surrogate" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Louis2010_127" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spike train surrogate generation step where spikes from adjacent interspike intervals (ISIs) are dithered according to the joint-ISI (JISI) probability distribution. The distribution is obtained from the input spike train by computing the JISI histogram (i.e., a two-dimensional histogram that shows the frequency of ISIs with a given duration that are immediately followed by intervals with another duration). Due to non-stationarities in the input spike train and/or its limited duration, it is difficult to accurately estimate the underlying JISI probability distribution. Therefore, a 2D-Gaussian smoothing is applied to the JISI histogram (with a variance determined by parameter). Dithering a spike according to this (smoothed) two-dimensional histogram involves moving the spike along the anti-diagonal of the JISI distribution. The dithering time is defined by a parameter." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpikeTrainSurrogateGeneration" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "generate joint interspike interval dithering surrogate" + } ] +}, { + "@id" : "http://purl.org/neao/steps#GenerateMorletWavelet", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A data generation that constructs a Morlet wavelet considering the selected parameters (i.e., sampling frequency, fundamental frequency, and number of cycles per frequency). The Morlet wavelet is composed by a complex exponential multiplied by a Gaussian window. The output data contains the discrete time points and the corresponding wavelet values." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DataGeneration" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "generate Morlet wavelet" + } ] +}, { + "@id" : "http://purl.org/neao/steps#GenerateNonStationaryGammaProcess", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A random spike times generation that uses a gamma probability distribution to produce spike trains where the firing rate varies over time." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#RandomSpikeTimesGeneration" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "generate non-stationary gamma process" + } ] +}, { + "@id" : "http://purl.org/neao/steps#GenerateNonStationaryPoissonProcess", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A random spike times generation that uses a Poisson probability distribution to produce spike trains where the firing rate varies over time. A dead time can be specified as parameter (i.e., an interval where no spikes can occur, which is analogous to the neuronal refractory period)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#RandomSpikeTimesGeneration" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "generate non-stationary Poisson process" + } ] +}, { + "@id" : "http://purl.org/neao/steps#GenerateSingleInteractionProcess", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Kuhn2003_67" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A correlated spike times generation that produces a multidimensional Poisson single interaction process (SIP) plus independent Poisson processes, according to Kuhn et al. (2003). The Poisson SIP consists of Poisson time series that are independent except for events that are simultaneous in all of them." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#CorrelatedSpikeTimesGeneration" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "generate SIP" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "generate single interaction process" + } ] +}, { + "@id" : "http://purl.org/neao/steps#GenerateSpikeTimeRandomizationSurrogate", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Louis2010_359" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spike train surrogate generation step that keeps the spike count of the input spike train, but the spike times in the surrogate spike train output are randomly chosen within the duration interval of the input spike train." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpikeTrainSurrogateGeneration" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "generate spike time randomization surrogate" + } ] +}, { + "@id" : "http://purl.org/neao/steps#GenerateSpikeTrainDitheringSurrogate", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Louis2010_359" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spike train surrogate generation step that displaces the whole input spike train by a random amount of time (independent for each surrogate generated). The amount of displacement is specified as a parameter (dither time), and occurs in a window (-dither time, dither time). This surrogate maintains the ISIs and the temporal correlations within the spike train." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpikeTrainSurrogateGeneration" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "generate spike train dithering surrogate" + } ] +}, { + "@id" : "http://purl.org/neao/steps#GenerateStationaryGammaProcess", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A random spike times generation that uses a gamma probability distribution to produce spike trains with a constant firing rate." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#RandomSpikeTimesGeneration" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "generate stationary gamma process" + } ] +}, { + "@id" : "http://purl.org/neao/steps#GenerateStationaryInverseGaussianProcess", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A random spike times generation that uses a inverse Gaussian probability distribution to produce spike trains with a constant firing rate." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#RandomSpikeTimesGeneration" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "generate stationary inverse Gaussian process" + } ] +}, { + "@id" : "http://purl.org/neao/steps#GenerateStationaryLogNormalProcess", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A random spike times generation that uses a log-normal probability distribution to produce spike trains with a constant firing rate." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#RandomSpikeTimesGeneration" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "generate stationary log-normal process" + } ] +}, { + "@id" : "http://purl.org/neao/steps#GenerateStationaryPoissonProcess", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Deger2012_443" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A random spike times generation that uses a Poisson probability distribution to produce spike trains with a constant firing rate. A dead time can be specified as parameter (i.e., an interval where no spikes can occur, which is analogous to the neuronal refractory period)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#RandomSpikeTimesGeneration" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "generate stationary Poisson process" + } ] +}, { + "@id" : "http://purl.org/neao/steps#GenerateTrialShiftingSurrogate", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Stella2022_ENEURO" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spike train surrogate generation step that shifts the entire spike train (containing the data of a single experimental trial) by an amount randomly chosen from a uniform distribution. The amount of displacement is specified as a parameter (dither time), and occurs in a window (-dither time, dither time). The input is a collection of spike trains of the same neuron, containing the spiking activity during different experimental trials. The amount of shift is independently chosen across trials and neurons. This surrogate preserves the ISI distribution and temporal correlations within the single-trial spike train." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpikeTrainSurrogateGeneration" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "generate trial shifting surrogate" + } ] +}, { + "@id" : "http://purl.org/neao/steps#GenerateTrialShufflingSurrogate", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Louis2010_359" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spike train surrogate generation step where the the spike trains of single-trial activity of one of the neurons are randomly permuted, so that each trial is no longer paired with the corresponding trial of the other neuron, but with a randomly selected one. The input is a collection of spike trains with multitrial activity data of multiple neurons recorded in parallel." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpikeTrainSurrogateGeneration" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "generate trial shuffling surrogate" + } ] +}, { + "@id" : "http://purl.org/neao/steps#GenerateUniformSpikeDitheringSurrogate", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "generate UD surrogate" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Louis2010_359" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spike train surrogate generation step that displaces each spike time in the input spike train according to a uniform distribution centered on the spike. The displacement occurs in a time window around the spike defined by a parameter (dither time)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpikeTrainSurrogateGeneration" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "generate uniform spike dithering surrogate" + } ] +}, { + "@id" : "http://purl.org/neao/steps#GenerateUniformSpikeDitheringSurrogateWithDeadTime", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "generate UDD surrogate" + } ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Stella2022_ENEURO" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spike train surrogate generation step that displaces each spike time in the input spike train according to a uniform distribution centered on the spike. The displacement occurs in a time window around the spike defined by a parameter (dither time) that is constrained to the intervals between adjacent spikes to avoid two spikes closer than a dead time (specified by parameter). This mimics the refractory period behavior of neurons, where the neuron cannot fire additional spikes for a short interval after one spike." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpikeTrainSurrogateGeneration" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "generate uniform spike dithering surrogate with dead time" + } ] +}, { + "@id" : "http://purl.org/neao/steps#GenerateWindowShufflingSurrogate", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#hasBibliographicReference" : [ { + "@id" : "http://purl.org/neao/bibliography#Stella2022_ENEURO" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spike train surrogate generation step that shuffles the entries of a binned spike train within exclusive maximal displacement windows. The maximal displacement is specified by parameter, and represents the maximum number of bins that a spike can be displaced within the window." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpikeTrainSurrogateGeneration" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "generate bin shuffling within exclusive windows surrogate" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "generate window shuffling surrogate" + } ] +}, { + "@id" : "http://purl.org/neao/steps#GrangerCausalityAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "GC analysis" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A functional connectivity analysis that computes measures of Granger causality (GC). GC is a statistical concept where the future values of a time series are predicted based on its past values and the past values of other time series. GC quantifies bi-directional interactions between the inputs, determining the directional influence from one input to another. For example, with two inputs, GC measures how much the first input influences the second and vice versa (directional GC measure). This provides estimates of the directed connectivity between the inputs. It is also possible to compute associated measures, such as the instantaneous GC (a measure of interdependence between the inputs not accounted by their bi-directional interactions, such as shared neural input) and the total interdependence (the sum of all directional and instantaneous interactions between the inputs). The analysis can be performed in the time or frequency domains, and can take two (bivariate) or more inputs (multivariate)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#FunctionalConnectivityAnalysis" + }, { + "@id" : "_:genid87" + }, { + "@id" : "_:genid88" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "Granger causality analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#InfiniteImpulseResponseFiltering", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "IIR filtering" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A digital filtering that uses a filter whose impulse response (i.e., the response of the filter to a brief input impulse) persists infinitely. Therefore, the output of the filter can depend on an infinite number of past samples. The infinite impulse response (IIR) filters can become unstable and distort the phase of the signal, but have a lower computational cost." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DigitalFiltering" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "infinite impulse response filtering" + } ] +}, { + "@id" : "http://purl.org/neao/steps#InstantaneousFiringRateAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A firing rate analysis that computes the instantaneous firing rate, which is the estimate of the firing rate at a specific point in time. The instantaneous firing rate value can be obtained by several methods." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#FiringRateAnalysis" + } ], + "http://www.w3.org/2002/07/owl#equivalentClass" : [ { + "@id" : "_:genid89" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "instantaneous firing rate analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#InstantaneousFiringRatePurpose", + "@type" : [ "http://www.w3.org/2002/07/owl#NamedIndividual" ], + "http://www.w3.org/1999/02/22-rdf-syntax-ns#type" : [ { + "@id" : "http://purl.org/neao/steps#AnalysisPurpose" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The analysis purpose of estimating the instantaneous firing rate." + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "instantaneous firing rate purpose" + } ] +}, { + "@id" : "http://purl.org/neao/steps#InterspikeIntervalAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "ISI analysis" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that computes or analyzes the interval between successive spikes in a spike train (interspike interval; ISI)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "interspike interval analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#InterspikeIntervalVariabilityAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An interspike interval analysis that computes a measure describing the variability of the interspike intervals. The measure can assess how regular a neuron is firing." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#InterspikeIntervalAnalysis" + }, { + "@id" : "_:genid90" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "interspike interval variability analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#KernelSmoothing", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A data smoothing that performs a convolution of the input data with a kernel function. This computes a weighted average of the data around the kernel. Several kernel types can be used for the smoothing (e.g., Gaussian, exponential) and the kernel shape is controlled by a width parameter." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DataSmoothing" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "kernel smoothing" + } ] +}, { + "@id" : "http://purl.org/neao/steps#LatentDynamicsAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that aims to identify underlying patterns and structures within time series or sequential data that are not directly observable. It involves modeling hidden (latent) variables that influence the observed data and their evolution over time. The analysis captures temporal dependencies and dynamics within the data, providing insights into the processes that generate the observed sequences." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2002/07/owl#equivalentClass" : [ { + "@id" : "_:genid91" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "latent dynamics analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#LatentDynamicsPurpose", + "@type" : [ "http://www.w3.org/2002/07/owl#NamedIndividual" ], + "http://www.w3.org/1999/02/22-rdf-syntax-ns#type" : [ { + "@id" : "http://purl.org/neao/steps#AnalysisPurpose" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The analysis purpose of estimating latent dynamics." + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "latent dynamics purpose" + } ] +}, { + "@id" : "http://purl.org/neao/steps#LineNoiseRemoval", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A data transformation that removes noise induced by the power line." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DataTransformation" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "line noise cancellation" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "line noise removal" + } ] +}, { + "@id" : "http://purl.org/neao/steps#MeanVectorLengthAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "MVL analysis" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A phase-amplitude coupling (PAC) analysis that computes the mean vector length (MVL) measure. The MVL is based on a mean vector obtained from a time series defined in the complex plane, where the amplitude is taken from the high-frequency oscillation input and the phase from the low-frequency oscillation input." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#PhaseAmplitudeCouplingAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "mean vector length analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ModelBasedAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that depends on assumptions on the interactions between the inputs to perform the computations. For example, the Granger causality analysis assumes linear relationships between the input signals." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2002/07/owl#equivalentClass" : [ { + "@id" : "_:genid92" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "model-based analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#ModelFreeAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that does not depend on assumptions on the interactions between the inputs to perform the computations. For example, it can consider probability distributions obtained from the input data." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2002/07/owl#equivalentClass" : [ { + "@id" : "_:genid93" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "model-free analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#MultivariateAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that has three or more distinct inputs considered for the computation of the output (e.g., the time series with the local field potential signals recorded from three or more electrodes, used to compute the partial directed coherence)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2002/07/owl#equivalentClass" : [ { + "@id" : "_:genid94" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "multivariate analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#NeuronalActivityPatternDetectionAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that aims to identify a neuronal activity pattern, i.e., spikes of a group of neurons that occur in a specific spatio-temporal configuration." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + }, { + "@id" : "_:genid95" + }, { + "@id" : "_:genid96" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "neuronal activity pattern detection analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#NeuronalFiringRegularityAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that computes measures to assess the regularity in the firing of a neuron. Neuronal firing regularity refers to the consistency or variability in the timing of action potentials (spikes) generated by a neuron." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2002/07/owl#equivalentClass" : [ { + "@id" : "_:genid97" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "spike time variability analysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "neuronal firing regularity analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#NeuronalFiringRegularityPurpose", + "@type" : [ "http://www.w3.org/2002/07/owl#NamedIndividual" ], + "http://www.w3.org/1999/02/22-rdf-syntax-ns#type" : [ { + "@id" : "http://purl.org/neao/steps#AnalysisPurpose" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The analysis purpose of assessing the regularity in neuronal firing." + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "neuronal firing regularity purpose" + } ] +}, { + "@id" : "http://purl.org/neao/steps#NeuronalSynchronizationPurpose", + "@type" : [ "http://www.w3.org/2002/07/owl#NamedIndividual" ], + "http://www.w3.org/1999/02/22-rdf-syntax-ns#type" : [ { + "@id" : "http://purl.org/neao/steps#AnalysisPurpose" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The analysis purpose of assessing neuronal synchronization." + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "neural synchronization purpose" + } ] +}, { + "@id" : "http://purl.org/neao/steps#NonDirectedAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step where the output does not provide information on the direction of influence in the relationships among the inputs (e.g., in the Pearson correlation coefficient computed between two spike trains, it is possible to know how strongly they tend to fire together. However, it is not possible to analyze the timing of the spikes of the first input spike with respect to the timing of the spikes of the second input spike train)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2002/07/owl#equivalentClass" : [ { + "@id" : "_:genid98" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "non-directed analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#PairwiseGrangerCausalityAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A Granger causality (GC) analysis that computes a measure of GC between two inputs." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#GrangerCausalityAnalysis" + }, { + "@id" : "_:genid99" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "pairwise Granger causality analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#PeristimulusTimeHistogramAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "PSTH analysis" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spike train time histogram analysis that computes the peristimulus time histogram (PSTH). PSTH is the time histogram of two or more spike trains containing repeated recordings of a single neuron around the time when an event of interest occurred. The event of interest can occur at any time point during the duration of the source spike trains. The distribution of the histogram corresponds to the distribution of the activity of the neuron with respect to the event across the repeated recordings. The event of interest can be an externally presented stimulus or a spontaneous behavioral event. If the histogram represents the neuronal activity after the stimulus presentation or event occurrence, this can be referred as post-stimulus time histogram. Conversely, if the histogram shows the activity of the neuron before the stimulus presentation or event, this can be referred as prestimulus time histogram. Finally, if the histogram considers a behavioral event (or an event that is not an externally presented stimulus), the histogram can be referred to as perievent time histogram (PETH)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpikeTrainTimeHistogramAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "peristimulus time histogram analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#PhaseAmplitudeCouplingAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "PAC analysis" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A phase analysis that computes measures describing how the phase of a low-frequency oscillation modulates the amplitude of a high-frequency oscillation. Phase-amplitude coupling (PAC) can be used to investigate interactions between different frequency bands in the neural activity." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#PhaseAnalysis" + }, { + "@id" : "_:genid100" + }, { + "@id" : "_:genid101" + }, { + "@id" : "_:genid102" + }, { + "@id" : "_:genid103" + }, { + "@id" : "_:genid104" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "phase-amplitude coupling analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#PhaseAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that computes measures related to the phase in the input data. Phase expresses the position of a time-varying signal relative to a fixed reference point in time. For periodic and oscillatory signals (e.g., a sine waveform), phase analysis involves determining the angle on the unit circle that corresponds to the current position within the waveform's cycle. This helps understanding the timing and synchronization of the oscillations in the input data." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "phase analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#PhaseLagIndexAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "PLI analysis" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A phase analysis that computes the phase lag index (PLI). The PLI measures the asymmetry of the distribution of the phase differences between two input time series, i.e., if there is an imbalance in the likelihood of the first time series leading or lagging the second time series. It is designed to be invariant to common sources, such as volume conduction and/or active reference electrodes." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#PhaseAnalysis" + }, { + "@id" : "_:genid105" + }, { + "@id" : "_:genid106" + }, { + "@id" : "_:genid107" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "phase lag index analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#PhaseLockingValueAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "PLV analysis" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A phase analysis that computes the phase locking value (PLV). The PLV quantifies the consistency of the phase difference between two input time series across time (e.g., multiple experimental trials)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#PhaseAnalysis" + }, { + "@id" : "_:genid108" + }, { + "@id" : "_:genid109" + }, { + "@id" : "_:genid110" + }, { + "@id" : "_:genid111" + }, { + "@id" : "_:genid112" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "phase locking value analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#PowerSpectralDensityAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "PSD analysis" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spectral density analysis that computes the power spectral density of an input, i.e., the distribution of power across the different frequency components of the input signal per unit frequency. It is equivalent to the Fourier transform of the autocorrelation function of the input signal. The computed power spectral density values can be corrected depending on the analysis returning the two-sided (i.e., with negative frequencies) or one-sided (i.e., positive frequencies only) PSD. The PSD is often referred to as spectrum." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpectralDensityAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "auto spectral density analysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "power spectral density analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#PrincipalComponentAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "PCA" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A dimensionality reduction that reduces the dimensionality of the input data represented as a matrix with numerous rows and columns. It transforms the data into a set of principal components (PCs) that capture the maximum variance in the input. Each PC is a linear combination of the original variables and serves as a new axis in a lower-dimensional space. The PCs are orthogonal to each other, meaning they capture independent aspects of the input data's variability." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DimensionalityReduction" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "principal component analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#RandomSpikeTimesGeneration", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spike train generation where the output spike trains will have random spike times, taken from a specific probability distribution. The generation process can produce spike trains where the firing rate is constant (stationary) or varies (non-stationary) over time." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpikeTrainGeneration" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "random spike times generation" + } ] +}, { + "@id" : "http://purl.org/neao/steps#Resampling", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A data transformation that changes the number of samples in the input data." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DataTransformation" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "resampling" + } ] +}, { + "@id" : "http://purl.org/neao/steps#SPADEAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A neuronal activity pattern detection analysis that uses the Spatio-temporal PAttern Detection and Evaluation (SPADE) method. The SPADE analysis takes a set of parallel spike trains as input, and returns significant spatio-temporal neuronal activity (spike) patterns. \n\nThe SPADE method consists of three substeps:\n\n1. Detect all putative patterns in the input data using the frequent item set mining (FIM) algorithm. This step requires the discretization of the input spike train data (binning). The bin size determines the temporal resolution of the analysis.\n\n2. The detected FIM patterns are evaluated for statistical significance, considering the null hypothesis of independence of the spike trains given the modulations by the firing rate. This substep is called Pattern Spectrum Filtering (PSF). For the testing, the patterns are pooled based on their signature: size and occurrence count (non-3d-SPADE) or size, occurrence count and pattern duration (3d-SPADE). The pattern spectrum collects the counts of patterns from each signature. The statistical test is done by a Monte Carlo approach, using spike train surrogates generated from the original data. The final output of this substep is the p-value spectrum, which has the same dimensions as the pattern spectrum. The p-value is computed as the ratio of surrogates containing patterns with that signature to the total number of realizations.\n\n3. Conditional test on the significant patterns to remove patterns arising from the overlap of true pattern spikes and chance spikes (pattern set reduction; PSR)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#NeuronalActivityPatternDetectionAnalysis" + }, { + "@id" : "_:genid113" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "SPADE analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#SpectralAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that computes measures describing the input data with respect to its frequency contents." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spectral analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#SpectralDensityAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A spectral analysis that computes the density of a measure of the input(s) over the frequency spectrum. Density means that the measure value (e.g., power) for each frequency component is expressed per unit frequency. For example, for an input time series with voltages recorded from an electrode (measured in V), the power for each frequency component of the signal will be in V**2, while the power density will be in V**2/Hz. Therefore, the power values are normalized per unit frequency. This normalization allows for consistent comparisons of results from analyses with different frequency resolutions, as the spectral density remains unaffected by these variations." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#SpectralAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spectral density analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#SpectrogramAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A time-frequency analysis that shows the power (or power density) of different frequency components of the input(s) as they change over time. This can be obtained for a single input (spectrogram) or for two distinct inputs (cross-spectrogram)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#TimeFrequencyAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spectrogram analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#SpikeFieldCoherenceAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "SFC analysis" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that computes the spike-field coherence (SFC), which is the coherence computed between an input spike train and an input time series with the local field potential (LFP). Coherence is a measure of the association between the two inputs in the frequency domain. SFC can be used to quantify the relationship between the spiking activity of neurons and the oscillatory activity in the LFP. It represents the similarity of dynamics between the spike train and the voltage fluctuations produced by the neural activity in the local environment where the spiking activity was recorded." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + }, { + "@id" : "_:genid114" + }, { + "@id" : "_:genid115" + }, { + "@id" : "_:genid116" + }, { + "@id" : "_:genid117" + }, { + "@id" : "_:genid118" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spike-field coherence analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#SpikeFieldCouplingAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that computes interactions between the spiking activity of neurons (individual or population) and the local field potential (LFP)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2002/07/owl#disjointWith" : [ { + "@id" : "http://purl.org/neao/steps#SpikeSpikeCouplingAnalysis" + } ], + "http://www.w3.org/2002/07/owl#equivalentClass" : [ { + "@id" : "_:genid119" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spike-field coupling analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#SpikeFieldCouplingPurpose", + "@type" : [ "http://www.w3.org/2002/07/owl#NamedIndividual" ], + "http://www.w3.org/1999/02/22-rdf-syntax-ns#type" : [ { + "@id" : "http://purl.org/neao/steps#AnalysisPurpose" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The analysis purpose of assessing interactions between spiking activity and the local field potential." + } ], + "http://www.w3.org/2004/02/skos/core#altLabel" : [ { + "@language" : "en", + "@value" : "spike-LFP coupling purpose" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spike-field coupling purpose" + } ] +}, { + "@id" : "http://purl.org/neao/steps#SpikeSpikeCouplingAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that computes interactions between the spiking activity of one or more neurons." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2002/07/owl#equivalentClass" : [ { + "@id" : "_:genid120" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spike-spike coupling analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#SpikeSpikeCouplingPurpose", + "@type" : [ "http://www.w3.org/2002/07/owl#NamedIndividual" ], + "http://www.w3.org/1999/02/22-rdf-syntax-ns#type" : [ { + "@id" : "http://purl.org/neao/steps#AnalysisPurpose" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "The analysis purpose of assessing interactions between the spiking activity of neurons." + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spike-spike coupling purpose" + } ] +}, { + "@id" : "http://purl.org/neao/steps#SpikeTrainCorrelationAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that computes measures estimating the correlation between spike train inputs. The correlation value is a normalized measure of covariation in the input spike train data, and reflects the strength and direction of the association: positive values mean that the inputs vary in the same direction, and negative values mean that the inputs vary in opposite directions (e.g., if the activity in one spike train increases, it decreases in the other)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + }, { + "@id" : "_:genid121" + }, { + "@id" : "_:genid122" + }, { + "@id" : "_:genid123" + }, { + "@id" : "_:genid124" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spike train correlation analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#SpikeTrainDissimilarityAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that computes a measure comparing spike train inputs and providing an estimation of their similarity/dissimilarity. This is frequently done by computing spike train distances, which are measures that assign the notion of distance, i.e., the input spike trains are considered as elements in a space and, if similar, will be close together." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spike train dissimilarity analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#SpikeTrainGeneration", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A data generation that produces one or more artificial spike trains using distinct statistical procedures to determine the spike times." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DataGeneration" + }, { + "@id" : "_:genid125" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spike train generation" + } ] +}, { + "@id" : "http://purl.org/neao/steps#SpikeTrainSurrogateGeneration", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A data generation that produces one or more spike train surrogates. A spike train surrogate is a new spike train derived from an input spike train (usually experimentally recorded). This is done using methods that alter the original spike times while trying to maintain specific statistical features of the original spike train (e.g., firing rate, interspike interval distribution). This is used to destroy fine temporal correlations in the spiking activity." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#DataGeneration" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spike train surrogate generation" + } ] +}, { + "@id" : "http://purl.org/neao/steps#SpikeTrainSynchronyAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step to assess synchronization in two or more spike train inputs that typically represent the activity of different neurons. Spike train synchronization refers to the temporal coordination of action potentials (spikes) between neurons, and describes the degree to which their spikes tend to occur at the same time." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spike train synchrony analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#SpikeTrainTimeHistogramAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A firing rate analysis that computes histograms of spike train data over time. The time histogram is obtained by discretizing the duration of the spike train into distinct time intervals (bins), and obtaining the spike count inside each bin. \n\nThe histogram can show one of three different measures:\n\n* the spike count at each bin (across all spike trains);\n* the mean spike count per bin (spike count in the bin divided by the number of spike trains);\n* the firing rate (mean spike count in the bin divided by bin width)." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/steps#FiringRateAnalysis" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spike train time histogram analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#SpikeWaveformAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "An analysis step that is used to compute measures to describe or make inferences from spike waveform input data. A spike waveform refers to the shape of an electrical signal produced by a neuron when it fires an action potential." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "spike waveform analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#StatisticalAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A generic analysis step that computes measures to summarize and make inferences about the data input. These include measures of central tendency, dispersion and confidence intervals. The subclasses represent analysis steps that are usually used for aggregation of data and description of samples (e.g., compute the mean and standard deviation of the output of trial-by-trial analyses or across subjects). All analysis steps for specific applications related to the analysis of neuroelectrophysiology data itself (e.g., analyzing interspike interval variability) are covered by separate, independent classes." + } ], + "http://www.w3.org/2000/01/rdf-schema#subClassOf" : [ { + "@id" : "http://purl.org/neao/base#AnalysisStep" + } ], + "http://www.w3.org/2004/02/skos/core#prefLabel" : [ { + "@language" : "en", + "@value" : "statistical analysis" + } ] +}, { + "@id" : "http://purl.org/neao/steps#TensorComponentAnalysis", + "@type" : [ "http://www.w3.org/2002/07/owl#Class" ], + "http://purl.org/neao/base#abbreviation" : [ { + "@language" : "en", + "@value" : "TCA" + } ], + "http://www.w3.org/2000/01/rdf-schema#comment" : [ { + "@language" : "en", + "@value" : "A dimensionality reduction that reduces the dimensionality of the input data represented as a tensor (i.e., an array with multiple dimensions). 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"https://isbndb.com/book/9780131139565", + "@type" : [ "http://www.w3.org/2002/07/owl#NamedIndividual" ] +}, { + "@id" : "https://isbndb.com/book/9781118585771", + "@type" : [ "http://www.w3.org/2002/07/owl#NamedIndividual" ] +}, { + "@id" : "https://isbndb.com/book/9789971502553#Aertsen_1", + "@type" : [ "http://www.w3.org/2002/07/owl#NamedIndividual" ] +}, { + "@id" : "https://proceedings.mlr.press/v54/cowley17a.html", + "@type" : [ "http://www.w3.org/2002/07/owl#NamedIndividual" ] +} ] \ No newline at end of file diff --git a/doc/releases/0.1.0/neao.nt b/doc/releases/0.1.0/neao.nt new file mode 100644 index 0000000..0a0eb9e --- /dev/null +++ b/doc/releases/0.1.0/neao.nt @@ -0,0 +1,5654 @@ + . + . + "2022-01-19" . + "Cristiano Köhler (ORCID: 0000-0003-0503-5264)" . + "Michael Denker (ORCID: 0000-0003-1255-7300)" . + . + "neao" . + "http://purl.org/neao/" . + "The Neuroelectrophysiology Analysis Ontology (NEAO) defines a controlled vocabulary and conceptual representations of the typical processes involved in the analysis of neural activity data acquired using electrophysiology techniques.\n\nElectrophysiology is a branch of physiology that studies the electrical properties of biological entities. The studies involve measurements of electric potentials and/or currents, as well as electrical manipulations (e.g. stimuli with electric pulses). Neuroelectrophysiology is the application of electrophysiology techniques to investigate the function of neural tissue.\n\nNeuroelectrophysiology recording is the process of data acquisition, and it usually involves placing electrodes (of several configurations and types) into a preparation of neural tissue. The data will contain a representation of the voltages or currents in the preparation during the recording session, usually as a time series. The analysis requires specific methods to progressively process and transform the recorded data, which generate results and insights.\n\nThe scope of the NEAO aims to provide a comprehensive representation of neuroelectrophysiology data and analysis processes, standardizing the description of their properties and relationships. The NEAO does not provide a detailed representation of electrophysiology recording techniques, data acquisition methods/equipment, and experimental settings/subjects. The goal is to ensure a common representation of data analysis that can be used by tools to provide a detailed and semantically-enriched description of the processes involved."@en . + "Neuroelectrophysiology Analysis Ontology"@en . + "0.1.0" . +# +# +# ################################################################# +# # +# # Annotation properties +# # +# ################################################################# +# +# +# http://purl.org/dc/terms/bibliographicCitation + . +# +# http://purl.org/dc/terms/created + . +# +# http://purl.org/dc/terms/creator + . +# +# http://purl.org/dc/terms/license + . +# +# http://purl.org/neao/base#abbreviation + . + "A string defining an abbreviation that is frequently used to refer to individuals represented by the class."@en . + "abbreviation"@en . + . +# +# http://purl.org/neao/base#hasBibliographicReference + . + "Defines the bibliographic reference associated with the entity. The bibliographic reference should contain the details represented by the entity (e.g., method description, software publication)."@en . + "has bibliographic reference"@en . + . +# +# http://purl.org/vocab/vann/preferredNamespacePrefix + . +# +# http://purl.org/vocab/vann/preferredNamespaceUri + . +# +# http://www.w3.org/2004/02/skos/core#altLabel + . +# +# http://www.w3.org/2004/02/skos/core#editorialNote + . +# +# http://www.w3.org/2004/02/skos/core#prefLabel + . +# +# +# +# ################################################################# +# # +# # Object Properties +# # +# ################################################################# +# +# +# http://purl.org/neao/base#hasInput + . + . + . + "Defines a data entity that is used to provide information for one analysis step. The analysis step will make use of this information and produce zero or more data entities as outputs."@en . + "has input"@en . +# +# http://purl.org/neao/base#hasOutput + . + . + . + "Defines a data entity that was produced by an analysis step. This can be newly data generated by the analysis step, or derived data, based on one or more data inputs."@en . + "has output"@en . +# +# http://purl.org/neao/base#hasSource + . + . + . + "Defines the electrophysiology signal source associated with the data entity. One example of use is to define if the data holds a signal obtained by extracellular recordings, or a more specific description involving anatomical structures together with the recording technique."@en . + "has source"@en . +# +# http://purl.org/neao/base#hasSubstep + . + . + . + "Points to an analysis step that is part of a (larger) compound analysis, represented by the subject with the property."@en . + "has substep"@en . +# +# http://purl.org/neao/base#isImplementedIn + . + . + . + "Defines the code source that implemented the analysis step."@en . + "is implemented in"@en . +# +# http://purl.org/neao/base#isImplementedInPackage + . + . + . + "Defines the software package that contains a particular code."@en . + "is implemented in package"@en . +# +# http://purl.org/neao/base#isRepresentedAs + . + . + . + "Defines how the data entity is represented to be used by software (e.g., data array, list, file)"@en . + "is represented as"@en . +# +# http://purl.org/neao/base#usesParameter + . + . + . + "Defines a parameter used by the analysis step."@en . + "uses parameter"@en . +# +# http://purl.org/neao/steps#hasPurpose + . + . + . + "Defines an analysis purpose for the analysis step. This property is used to group analysis steps according to their similarity."@en . + "has purpose"@en . +# +# http://purl.org/spar/biro/references + . + . +# +# +# +# ################################################################# +# # +# # Data properties +# # +# ################################################################# +# +# +# http://purl.org/neao/base#nameInDefinition + . + . + . + "Specifies the name of the function as it is defined in the code that implemented it. For example, for Python functions, this is what is specified in the 'def' statement (i.e., def function_name(arg), the value of this property is function_name)."@en . + "name in definition"@en . +# +# http://purl.org/neao/base#packageName + . + . + . + "Version of the software package."@en . + "package version"@en . +# +# http://purl.org/neao/base#packageVersion + . + . + . + "Specifies the version of the package, as defined by the string used when it was released."@en . + "package version"@en . +# +# http://purl.org/neao/base#programName + . + . + . + "Defines the name of the program."@en . + "program name"@en . +# +# http://purl.org/neao/base#version + . + . + . + "Version of the code for a specific program or function. This can be used to define a specific version for the code of a single function or program within a software package."@en . + "version"@en . +# +# http://purl.org/neao/data#isArtificial + . + . + . + . + "Defines if the data is artificially-generated (true) or obtained from experimental recordings (false)."@en . + "is artificial"@en . +# +# http://purl.org/neao/data#isAveraged + . + . + . + . + "Defines if the data is the result of an aggregation to obtain an average estimate from other data (true)."@en . + "is averaged"@en . +# +# http://purl.org/neao/data#isDetrended + . + . + . + . + "Defines if a detrending transformation was applied to the data (true)."@en . + "is detrended"@en . +# +# http://purl.org/neao/data#isDimensionalityReduction + . + . + . + . + "Defines if the data is a result of a dimensionality reduction transformation (true)."@en . + "is dimensionality reduction"@en . +# +# http://purl.org/neao/data#isDownsampled + . + . + . + . + "Defines if a downsampling transformation was applied to the data (true)."@en . + "is downsampled"@en . +# +# http://purl.org/neao/data#isFiltered + . + . + . + . + "Defines if a digital filter was applied to the data (true)."@en . + "is filtered"@en . +# +# http://purl.org/neao/data#isInterpolated + . + . + . + . + "Defines if a interpolation data transformation was applied to the data (true)."@en . + "is interpolated"@en . +# +# http://purl.org/neao/data#isNormalized + . + . + . + . + "Defines if a data normalization transformation was applied to the data (true)."@en . + "is normalized"@en . +# +# http://purl.org/neao/data#isRectified + . + . + . + . + "Defines if a rectification transformation was applied to the data (true)."@en . + "is rectified"@en . +# +# http://purl.org/neao/data#isRereferenced + . + . + . + . + "Defines if a transformation to change the reference in the recorded data was applied (true)."@en . + "is rereferenced"@en . +# +# http://purl.org/neao/data#isResampled + . + . + . + . + "Defines if a resampling transformation was applied to the data (true)."@en . + "is resampled"@en . +# +# http://purl.org/neao/data#isSmoothed + . + . + . + . + "Defines if a data smoothing transformation was applied to the data (true)."@en . + "is smoothed"@en . +# +# http://purl.org/neao/data#isUpsampled + . + . + . + . + "Defines if an upsampling transformation was applied to the data (true)."@en . + "is upsampled"@en . +# +# http://purl.org/neao/steps#isBivariate + . + . + . + . + "Defines if the analysis step uses two data inputs (true)."@en . + "is bivariate"@en . +# +# http://purl.org/neao/steps#isDirected + . + . + . + . + "Defines if the analysis step is used to perform an analysis providing information on the direction of the association between the inputs (true) opposed to no direction information (false)."@en . + "is directed"@en . +# +# http://purl.org/neao/steps#isFrequencyDomain + . + . + . + . + "Defines if the analysis in the step is performed in the frequency domain (true)."@en . + "is frequency domain"@en . +# +# http://purl.org/neao/steps#isModelBased + . + . + . + . + "Defines if the step performs a model-based (true) or model-free analysis (false)."@en . + "is model-based"@en . +# +# http://purl.org/neao/steps#isMultivariate + . + . + . + . + "Defines if the analysis step uses three or more data inputs (true)."@en . + "is multivariate"@en . +# +# http://purl.org/neao/steps#isTimeDomain + . + . + . + . + "Defines if the analysis in the step is performed in the time domain (true)."@en . + "is time domain"@en . +# +# +# +# ################################################################# +# # +# # Classes +# # +# ################################################################# +# +# +# http://purl.org/neao/base#AnalysisParameter + . + "An information entity that controls the behavior of an analysis step. It does not provide data, but rather changes how the computations operate when transforming or generating new data."@en . + "parameter"@en . +# +# http://purl.org/neao/base#AnalysisStep + . + "A process that generates new data entities or performs specific operations (clean, select, transform, or inspect/visualize) using existing data entities. Ultimately, the goal is to obtain useful information from the data. An analysis step can take zero or more data inputs and can generate one or more data outputs. The behavior of the operation can optionally be controlled by one or more parameters. A complete analysis is composed by one or more analysis steps."@en . + "analysis step"@en . +# +# http://purl.org/neao/base#Data + . + "An entity that represents a piece of data, i.e., relevant information, during the analysis. It can be recorded from a biological entity or from a simulation yielding comparable data, or it can be generated/transformed by other analysis step processes."@en . + "data"@en . +# +# http://purl.org/neao/base#DataRepresentation + . + "Defines the formal structure to represent a piece of data."@en . + "data representation"@en . +# +# http://purl.org/neao/base#ElectrophysiologySignalSource + . + "Defines the source of a recorded piece of electrophysiology data, i.e., the recorded signals. This is a general concept, that can be expanded to incorporate the anatomical/tissue description from where the signal was recorded, as well as the recording technique.\n\nFor example, voltage potentials can be acquired from extracellular electrodes situtated on the scalp (electroencephalogram), directly on the cortical surface (electrocorticogram) or implanted deep into a specific brain region (multielectrode array)."@en . + "electrophysiology signal source"@en . +# +# http://purl.org/neao/base#Function + . + . + "A reusable set of instructions that can be used when writing computer programs. A function performs specific tasks, and can be implemented as part of a single computer program or in a software package (library) so that it can be reused across several programs."@en . + "function"@en . +# +# http://purl.org/neao/base#Program + . + . + "A set of instructions that is executed by a computer. The instructions of the program can be executed by an interpreter or compiled to machine code. The program instructs the computer to perform tasks and it is called by the operating system."@en . + "program"@en . +# +# http://purl.org/neao/base#SoftwareImplementation + . + . + "Describes the details for the execution of the analysis step using a computer. The software contains a sequence or set of instructions that is used by the computer to perform all the computations required to execute the analysis step."@en . + "software implementation"@en . +# +# http://purl.org/neao/base#SoftwarePackage + . + "A collection of one or more programs that can be executed by a computer and/or one or more functions that can be imported and used when writing programs."@en . + "software package"@en . +# +# http://purl.org/neao/data#ASSETAnalysisMatrix + . + . + "Data that contains a matrix computed by one of the ASSET analysis substeps, as part of the execution of the ASSET analysis for the detection of neuronal activity patterns."@en . + "ASSET analysis matrix"@en . +# +# http://purl.org/neao/data#ASSETClusterMatrix + . + . + "CMAT"@en . + "The cluster matrix (CMAT) computed in the ASSET analysis."@en . + "ASSET cluster matrix"@en . +# +# http://purl.org/neao/data#ASSETIntersectionMatrix + . + . + "IMAT"@en . + "The intersection matrix (IMAT) computed in the ASSET analysis."@en . + "ASSET intersection matrix"@en . +# +# http://purl.org/neao/data#ASSETJointProbabilityMatrix + . + . + "JMAT"@en . + "The joint probability matrix (JMAT) computed in the ASSET analysis."@en . + "ASSET joint probability matrix"@en . +# +# http://purl.org/neao/data#ASSETMaskMatrix + . + . + "MMAT"@en . + "The mask matrix (MMAT) computed in the ASSET analysis."@en . + "ASSET mask matrix"@en . +# +# http://purl.org/neao/data#ASSETPattern + . + . + "A neuronal activity pattern obtained by the ASSET analysis. The ASSET patterns are the output of the last substep of the ASSET analysis that identifies the neurons present in each repeated sequence, based on the diagonal structures in the cluster matrix."@en . + "ASSET pattern"@en . +# +# http://purl.org/neao/data#ASSETProbabilityMatrix + . + . + "PMAT"@en . + "The probability matrix (PMAT) computed in the ASSET analysis."@en . + "ASSET probability matrix"@en . +# +# http://purl.org/neao/data#AnalyticSignal + . + . + "The analytic signal obtained from a time series using the Hilbert transform."@en . + "analytic signal"@en . +# +# http://purl.org/neao/data#AngularMeanSpikePhases + . + . + "The computed angular mean of the spike phases."@en . + "angular mean of spike phases"@en . +# +# http://purl.org/neao/data#ArtificialData + . + _:genid1 . +_:genid1 "true"^^ . +_:genid1 . +_:genid1 . + . + "Data that is generated programmatically rather than obtained from experimental recordings."@en . + "artificial data"@en . +# +# http://purl.org/neao/data#AutocorrelationFunction + . + . + "ACF"@en . + "The computed estimator of the autocorrelation function."@en . + "autocorrelation function"@en . +# +# http://purl.org/neao/data#AutocorrelationMeasure + . + . + "Data that contains a measure of autocorrelation."@en . + "autocorrelation measure"@en . +# +# http://purl.org/neao/data#BinnedSpikeTrain + . + . + "The output of applying binning to the input spike train data."@en . + "binned spike train"@en . +# +# http://purl.org/neao/data#CV + . + . + "CV"@en . + "The computed coefficient of variation (CV)."@en . + "coefficient of variation"@en . +# +# http://purl.org/neao/data#CV2 + . + . + "The computed CV2 measure."@en . + "CV2"@en . +# +# http://purl.org/neao/data#CVInterspikeIntervals + . + . + "CV ISIs"@en . + "The computed coefficient of variation (CV) of the interspike intervals (ISIs)."@en . + "coefficient of variation of the interspike intervals"@en . +# +# http://purl.org/neao/data#CanonicalCoherence + . + . + "caCOH"@en . + "The computed canonical coherence (caCOH)."@en . + "canonical coherence"@en . +# +# http://purl.org/neao/data#CellAssemblyDetectionPattern + . + . + "CAD pattern"@en . + "A neuronal activity pattern obtained by the Cell Assembly Detection (CAD) analysis."@en . + "Cell Assembly Detection pattern"@en . +# +# http://purl.org/neao/data#ChangePoint + . + . + "A change point identified by the rate change detection multiple filter test."@en . + "change point"@en . +# +# http://purl.org/neao/data#Coherence + . + . + "The computed magnitude squared coherence. This is the typical output of a computation estimating coherence, and it is frequently referred as just coherence."@en . + "magnitude squared coherence"@en . + "coherence"@en . +# +# http://purl.org/neao/data#CoherenceMeasure + . + . + "Data that contains a measure of coherence."@en . + "coherence measure"@en . +# +# http://purl.org/neao/data#Coherency + . + . + "The computed coherency."@en . + "complex coherency"@en . + "coherency"@en . +# +# http://purl.org/neao/data#CoherencyMeasure + . + . + "Data that contains a measure of coherency."@en . + "coherency measure"@en . +# +# http://purl.org/neao/data#ComplexityDistribution + . + . + "The computed complexity distribution across the spike trains."@en . + "complexity distribution"@en . +# +# http://purl.org/neao/data#ConditionalGrangerCausality + . + . + "The computed conditional Granger causality."@en . + "conditional Granger causality"@en . +# +# http://purl.org/neao/data#ConfidenceInterval + . + . + "CI"@en . + "The computed confidence interval (CI), with the lower and upper limits."@en . + "confidence interval"@en . +# +# http://purl.org/neao/data#ConfidenceIntervalLowerLimit + . + . + "The lower limit value of the computed confidence interval."@en . + "lower limit of confidence interval"@en . +# +# http://purl.org/neao/data#ConfidenceIntervalMeasure + . + . + "Data that contains the description of a confidence interval (CI)."@en . + "CI measure"@en . + "confidence interval measure"@en . +# +# http://purl.org/neao/data#ConfidenceIntervalUpperLimit + . + . + "The upper limit value of the computed confidence interval."@en . + "upper limit of confidence interval"@en . +# +# http://purl.org/neao/data#CorrectedImaginaryPhaseLockingValue + . + . + "ciPLV"@en . + "The computed corrected imaginary phase locking value (ciPLV)."@en . + "corrected imaginary phase locking value"@en . +# +# http://purl.org/neao/data#CorrelationMeasure + . + . + "Data that contains a measure of correlation."@en . + "correlation measure"@en . +# +# http://purl.org/neao/data#Covariance + . + . + "The computed covariance values between the inputs."@en . + "covariance"@en . +# +# http://purl.org/neao/data#CovarianceMeasure + . + . + "Data that contains a measure of covariance."@en . + "covariance measure"@en . +# +# http://purl.org/neao/data#CrossCorrelationFunction + . + . + "CCF"@en . + "The computed estimator of the cross-correlation function."@en . + "cross-correlation function"@en . +# +# http://purl.org/neao/data#CrossCorrelationMeasure + . + . + "Data that contains a measure of cross-correlation."@en . + "cross-correlation measure"@en . +# +# http://purl.org/neao/data#CrossPowerSpectralDensity + . + . + "CPSD"@en . + "The computed cross power spectral density (CPSD)."@en . + "cross-spectrum"@en . + "cross power spectral density"@en . +# +# http://purl.org/neao/data#CrossSpectrogram + . + . + "The computed cross-spectrogram."@en . + "cross-spectrogram"@en . +# +# http://purl.org/neao/data#CubicAnalysisResult + . + . + "The result of the CuBIC analysis."@en . + "CuBIC analysis result"@en . +# +# http://purl.org/neao/data#CurrentSourceDensity + . + . + "CSD"@en . + "The profile of current densities estimated by a current source density analysis."@en . + "current source density"@en . +# +# http://purl.org/neao/data#DebiasedSquaredWeightedPhaseLagIndex + . + . + "debiased squared WPLI"@en . + "The computed debiased squared weighted phase lag index (WPLI)."@en . + "debiased squared weighted phase lag index"@en . +# +# http://purl.org/neao/data#DimensionalityReductionOutput + . + _:genid2 . +_:genid2 "true"^^ . +_:genid2 . +_:genid2 . + . + "Data that contains an output of applying a dimensionality reduction transformation to the input data."@en . + "dimensionality reduction output"@en . +# +# http://purl.org/neao/data#DirectedPhaseLagIndex + . + . + "DPLI"@en . + "The computed directed phase lag index (DPLI)."@en . + "directed phase lag index"@en . +# +# http://purl.org/neao/data#DirectedTransferFunction + . + . + "DTF"@en . + "The computed directed transfer function (DTF)."@en . + "directed transfer function"@en . +# +# http://purl.org/neao/data#DirectionalGrangerCausality + . + . + "The computed directional Granger causality from one input to the other."@en . + "directional Granger causality"@en . +# +# http://purl.org/neao/data#DiscreteFourierTransform + . + . + "DFT"@en . + "The complex sinusoid coefficients obtained by applying the Discrete Fourier Transform (DFT) to the input data (e.g., using the FFT algorithm)."@en . + "discrete Fourier transform"@en . +# +# http://purl.org/neao/data#DistanceCovarianceDimension + . + . + "A dimension identified by applying distance covariance analysis (DCA) to the input data."@en . + "distance covariance dimension"@en . +# +# http://purl.org/neao/data#Epoch + . + . + "Data that represents a finite time interval (window). For example, the interval between the start and end of a behavioral trial in the recording session."@en . + "epoch"@en . +# +# http://purl.org/neao/data#Event + . + . + . + . + . + "Data that contains the time(s) when an event of interest occurred (e.g., a certain behavior or stimulus in an experimental trial)."@en . + "event"@en . +# +# http://purl.org/neao/data#EventRelatedPotential + . + . + "ERP"@en . + "The computed event-related potential (ERP)."@en . + "event-related potential"@en . +# +# http://purl.org/neao/data#EventTriggeredAverage + . + . + "The computed event-triggered average."@en . + "event-triggered average"@en . +# +# http://purl.org/neao/data#EvokedPotential + . + . + "EP"@en . + "The computed evoked potential (EP)."@en . + "evoked potential"@en . +# +# http://purl.org/neao/data#FiringRate + . + . + "The computed firing rate."@en . + "firing rate"@en . +# +# http://purl.org/neao/data#FisherLinearDiscriminant + . + . + "A Fisher linear discriminant obtained by applying linear discrimination analysis (LDA) to the input data."@en . + "Fisher linear discriminant"@en . +# +# http://purl.org/neao/data#GrangerCausalityMeasure + . + . + "Data that contains a measure of Granger causality."@en . + "Granger causality measure"@en . +# +# http://purl.org/neao/data#GrangerTotalInterdependence + . + . + "The computed total interdependence in the Granger causality analysis."@en . + "Granger total interdependence"@en . +# +# http://purl.org/neao/data#ISIDistance + . + . + "The computed ISI-distance."@en . + "ISI-distance"@en . +# +# http://purl.org/neao/data#ImaginaryCoherency + . + . + "The computed imaginary part of the coherency."@en . + "imaginary coherency"@en . +# +# http://purl.org/neao/data#IndependentComponent + . + . + "Data that contains an independent component produced by applying independent component analysis (ICA) to the input data."@en . + "independent component"@en . +# +# http://purl.org/neao/data#InstantaneousFiringRate + . + . + "The computed instantaneous firing rate."@en . + "instantaneous firing rate"@en . +# +# http://purl.org/neao/data#InstantaneousGrangerCausality + . + . + "The computed instantaneous Granger causality."@en . + "instantaneous Granger causality"@en . +# +# http://purl.org/neao/data#InterquartileRange + . + . + "IQR"@en . + "The computed interquartile range, with the difference between the 75th and 25th percentile values."@en . + "interquartile range"@en . +# +# http://purl.org/neao/data#InterquartileRangeLowerLimit + . + . + "The lower limit of the computed interquartile range, corresponding to the 25th percentile."@en . + "lower limit of interquartile range"@en . +# +# http://purl.org/neao/data#InterquartileRangeMeasure + . + . + "IQR measure"@en . + "Data that contains the description of an interquartile range (IQR)."@en . + "interquartile range measure"@en . +# +# http://purl.org/neao/data#InterquartileRangeUpperLimit + . + . + "The upper limit of the computed interquartile range, corresponding to the 75th percentile."@en . + "upper limit of interquartile range"@en . +# +# http://purl.org/neao/data#InterspikeIntervalHistogram + . + . + "ISIH"@en . + "The computed interspike interval histogram (ISIH)."@en . + "interspike interval histogram"@en . +# +# http://purl.org/neao/data#InterspikeIntervalVariabilityMeasure + . + . + "Data that contains a measure describing the variability of the interspike intervals."@en . + "interspike interval variability measure"@en . +# +# http://purl.org/neao/data#InterspikeIntervals + . + . + "ISIs"@en . + "The computed interspike intervals (ISIs)."@en . + "interspike intervals"@en . +# +# http://purl.org/neao/data#JointPeristimulusTimeHistogramMatrix + . + . + "JPSTH matrix"@en . + "The computed joint peristimulus time histogram (JPSTH) matrix."@en . + "joint peristimulus time histogram matrix"@en . +# +# http://purl.org/neao/data#LV + . + . + "The computed local variation (LV) measure."@en . + "LV"@en . +# +# http://purl.org/neao/data#LVR + . + . + "The computed revised local variation (LvR) measure."@en . + "LvR"@en . +# +# http://purl.org/neao/data#MagnitudeCoherence + . + . + "The computed magnitude coherence."@en . + "magnitude coherence"@en . +# +# http://purl.org/neao/data#MaximizedImaginaryCoherency + . + . + "MIC"@en . + "The computed maximized imaginary coherency (MIC)."@en . + "maximized imaginary coherency"@en . +# +# http://purl.org/neao/data#Mean + . + . + "The computed mean."@en . + "mean"@en . +# +# http://purl.org/neao/data#MeanFiringRate + . + . + "MFR"@en . + "The computed mean firing rate."@en . + "mean firing rate"@en . +# +# http://purl.org/neao/data#MeanPhaseVector + . + . + "The computed mean phase vector (i.e., the angle and length)."@en . + "mean phase vector"@en . +# +# http://purl.org/neao/data#MeanPhaseVectorAngle + . + . + "The angle of the computed mean phase vector."@en . + "mean phase vector angle"@en . +# +# http://purl.org/neao/data#MeanPhaseVectorLength + . + . + "The length of the computed mean phase vector."@en . + "mean phase vector length"@en . +# +# http://purl.org/neao/data#MeanPhaseVectorMeasure + . + . + "Data that contains the description or elements of the mean phase vector."@en . + "mean phase vector measure"@en . +# +# http://purl.org/neao/data#MeanVectorLength + . + . + "MVL"@en . + "The computed mean vector length (MVL)."@en . + "mean vector length"@en . +# +# http://purl.org/neao/data#Median + . + . + "The computed median."@en . + "median"@en . +# +# http://purl.org/neao/data#ModulationIndex + . + . + "MI"@en . + "The computed modulation index (MI)."@en . + "modulation index"@en . +# +# http://purl.org/neao/data#MorletWavelet + . + . + "Data that contains the generated Morlet wavelet values for a sequence of time points."@en . + "Morlet wavelet"@en . +# +# http://purl.org/neao/data#MultivariateInteractionMeasure + . + . + "MIM"@en . + "The computed multivariate interaction measure (MIM)."@en . + "multivariate interaction measure"@en . +# +# http://purl.org/neao/data#MutualInformation + . + . + "MI"@en . + "The computed mutual information (MI)."@en . + "mutual information"@en . +# +# http://purl.org/neao/data#NeuralTrajectory + . + . + _:genid3 . +_:genid3 "true"^^ . +_:genid3 . +_:genid3 . + "A neural trajectory obtained by applying Gaussian process factor analysis (GPFA) to the input data containing multitrial spiking activity of a neuronal population."@en . + "neural trajectory"@en . +# +# http://purl.org/neao/data#NeuronalActivityPattern + . + . + "Data that contains the description of a neuronal activity pattern, which is obtained from a neuronal activity pattern detection analysis."@en . + "cell assembly"@en . + "neuronal assembly"@en . + "neuronal activity pattern"@en . +# +# http://purl.org/neao/data#NeuronalPopulationVector + . + . + "The computed neuronal population vector."@en . + "population vector"@en . + "neuronal population vector"@en . +# +# http://purl.org/neao/data#NoiseCorrelations + . + . + "NC"@en . + "The computed noise correlations (NC)."@en . + "noise correlations"@en . +# +# http://purl.org/neao/data#NoiseCovariance + . + . + "The computed noise covariance."@en . + "noise covariance"@en . +# +# http://purl.org/neao/data#OrthogonalizedPowerEnvelopeCorrelation + . + . + "The computed orthogonalized power envelope correlation."@en . + "orthogonalized power envelope correlation"@en . +# +# http://purl.org/neao/data#PairwisePhaseConsistency + . + . + "PPC"@en . + "The computed pairwise phase consistency (PPC) measure."@en . + "pairwise phase consistency"@en . +# +# http://purl.org/neao/data#PartialCoherence + . + . + "The computed partial coherence."@en . + "partial coherence"@en . +# +# http://purl.org/neao/data#PartialDirectedCoherence + . + . + "PDC"@en . + "The computed partial directed coherence (PDC)."@en . + "partial directed coherence"@en . +# +# http://purl.org/neao/data#PeristimulusCoincidenceHistogram + . + . + "The computed peristimulus coincidence histogram."@en . + "peristimulus coincidence histogram"@en . +# +# http://purl.org/neao/data#PeristimulusTimeHistogram + . + . + "PSTH"@en . + "The computed peristimulus time histogram (PSTH). The stimulus or event of interest can occur at any time point within the interval analyzed. However, if the histogram represents the neuronal activity after the stimulus presentation or event occurrence, this can be referred as post-stimulus time histogram. Conversely, if the histogram shows the activity of the neuron before the stimulus presentation or event, this can be referred as prestimulus time histogram. Finally, if the histogram considers a behavioral event (or an event that is not an externally presented stimulus), the histogram can be referred to as perievent time histogram (PETH)."@en . + "perievent time histogram"@en . + "post-stimulus time histogram"@en . + "prestimulus time histogram"@en . + "peristimulus time histogram"@en . +# +# http://purl.org/neao/data#PhaseAmplitudeCouplingMeasure + . + . + "PAC measure"@en . + "Data that contains a measure of phase-amplitude coupling (PAC)."@en . + "phase amplitude coupling measure"@en . +# +# http://purl.org/neao/data#PhaseAngles + . + . + "A measure of phase defining the angle on the unit circle that corresponds to the current position within the waveform's cycle. The range of angles in a full cycle is from 0 to 2*pi radians or 0 to 360 degrees."@en . + "phase angles"@en . +# +# http://purl.org/neao/data#PhaseLagIndex + . + . + "PLI"@en . + "The computed phase lag index (PLI)."@en . + "phase lag index"@en . +# +# http://purl.org/neao/data#PhaseLagIndexMeasure + . + . + "PLI measure"@en . + "Data that contains a measure computed by a phase-lag index analysis."@en . + "phase lag index measure"@en . +# +# http://purl.org/neao/data#PhaseLockingValue + . + . + "PLV"@en . + "The computed phase locking value (PLV)."@en . + "phase locking value"@en . +# +# http://purl.org/neao/data#PhaseLockingValueMeasure + . + . + "PLV measure"@en . + "Data that contains a phase locking value (PLV) measure."@en . + "phase locking value measure"@en . +# +# http://purl.org/neao/data#PhaseSlopeIndex + . + . + "PSI"@en . + "The computed phase slope index (PSI)."@en . + "phase slope index"@en . +# +# http://purl.org/neao/data#Plot + . + . + "A graphical representation of data values. It is used to visually communicate quantitative information, providing intuitive insights that can complement numerical analysis. It is often produced by later steps in the analysis after the computation of measures, to provide the visual representation of the results."@en . + "plot"@en . +# +# http://purl.org/neao/data#PopulationHistogram + . + . + "The computed population histogram."@en . + "population histogram"@en . +# +# http://purl.org/neao/data#PowerSpectralDensity + . + . + "PSD"@en . + "The computed power spectral density (PSD)."@en . + "spectrum"@en . + "power spectral density"@en . +# +# http://purl.org/neao/data#PrincipalComponent + . + . + "A principal component obtained by applying principal component analysis (PCA) to the input data."@en . + "principal component"@en . +# +# http://purl.org/neao/data#RectifiedAreaUnderCurve + . + . + "RAUC"@en . + "The computed rectified area under the curve (RAUC)."@en . + "rectified area under the curve"@en . +# +# http://purl.org/neao/data#RegularizedCovariance + . + . + "The covariance values computed with regularization techniques for numerical stability."@en . + "regularized covariance"@en . +# +# http://purl.org/neao/data#SPADEPattern + . + . + "A neuronal activity pattern obtained by the Spatio-temporal PAttern Detection and Evaluation (SPADE) analysis."@en . + "SPADE pattern"@en . +# +# http://purl.org/neao/data#SPIKEDistance + . + . + "The computed SPIKE distance."@en . + "SPIKE distance"@en . +# +# http://purl.org/neao/data#SPIKESynchronization + . + . + "The computed SPIKE synchronization distance."@en . + "SPIKE synchronization"@en . +# +# http://purl.org/neao/data#ShortTimeFourierTransform + . + . + "STFT"@en . + "The complex sinusoid coefficients obtained by applying the short-time Fourier transform (STFT) to the input data."@en . + "short-time Fourier transform"@en . +# +# http://purl.org/neao/data#SpectralDensity + . + . + "Data that contains the density of a measure of the input(s) over the frequency spectrum."@en . + "spectral density"@en . +# +# http://purl.org/neao/data#Spectrogram + . + . + "The computed spectrogram."@en . + "spectrogram"@en . +# +# http://purl.org/neao/data#SpikeContrast + . + . + "The computed Spike-contrast."@en . + "Spike-contrast"@en . +# +# http://purl.org/neao/data#SpikeFieldCoherence + . + . + "SFC"@en . + "The computed spike-field coherence (SFC)."@en . + "spike-field coherence"@en . +# +# http://purl.org/neao/data#SpikeTimeTilingCoefficient + . + . + "STTC"@en . + "The computed spike time tiling coefficient (STTC)."@en . + "spike time tiling coefficient"@en . +# +# http://purl.org/neao/data#SpikeTrain + . + . + . + . + "Data that contains the sequence of time points when an action potential (spike) occurs. A spike train can be obtained by electrophysiological recordings from the neural tissue (i.e., the data contains the times when spikes occur naturally in response to various stimuli or during spontaneous activity) or artificially-generated using specific statistical procedures or simulations of neuronal activity."@en . + "spike train"@en . +# +# http://purl.org/neao/data#SpikeTrainAutocorrelationHistogram + . + . + "The computed spike train autocorrelation histogram."@en . + "spike train autocorrelation histogram"@en . +# +# http://purl.org/neao/data#SpikeTrainAutocorrelationTimeScale + . + . + "The computed spike train autocorrelation time scale."@en . + "spike train autocorrelation time scale"@en . +# +# http://purl.org/neao/data#SpikeTrainCorrelationMeasure + . + . + "Data that contains a measure estimating the correlation between spike trains."@en . + "correlation measure"@en . +# +# http://purl.org/neao/data#SpikeTrainCrossCorrelationHistogram + . + . + "CCH"@en . + "The computed spike train cross-correlation histogram."@en . + "correlogram"@en . + "cross-correlogram"@en . + "spike train cross-correlation histogram"@en . +# +# http://purl.org/neao/data#SpikeTrainDistance + . + . + "Data that contains a spike train distance measure."@en . + "spike train distance"@en . +# +# http://purl.org/neao/data#SpikeTrainFanoFactor + . + . + "FF"@en . + "The computed Fano factor (FF) for a set of input spike trains."@en . + "spike train Fano factor"@en . +# +# http://purl.org/neao/data#SpikeTrainPearsonCorrelationCoefficient + . + . + "The computed Pearson correlation coefficient between two spike trains."@en . + "spike train Pearson correlation coefficient"@en . +# +# http://purl.org/neao/data#SpikeTrainSurrogate + . + . + . + "Data that contains a spike train surrogate. It is generated from spike train inputs using distinct methods to alter the original spike times."@en . + "spike train surrogate"@en . +# +# http://purl.org/neao/data#SpikeTrainSynchronyMeasure + . + . + "Data that contains a measure describing synchronization in two or more spike trains containing the activity of different neurons."@en . + "spike train synchrony measure"@en . +# +# http://purl.org/neao/data#SpikeTrainTimeHistogram + . + . + "The computed spike train time histogram."@en . + "spike train time histogram"@en . +# +# http://purl.org/neao/data#SpikeTriggeredAverage + . + . + "STA"@en . + "The computed spike-triggered average (STA)."@en . + "spike-triggered average"@en . +# +# http://purl.org/neao/data#SpikeTriggeredLFPAverage + . + . + "The computed spike-triggered average of the local field potential (LFP) signal."@en . + "spike-triggered local field potential average"@en . +# +# http://purl.org/neao/data#SpikeTriggeredPhase + . + . + "The computed spike-triggered phase angles."@en . + "spike-triggered phase"@en . +# +# http://purl.org/neao/data#SpikeWaveform + . + . + "Data that contains the characteristic voltage change over time observed in the electrical recording of a neuron's action potential (spike). This waveform represents the rapid depolarization and repolarization of the neuron's membrane potential during the action potential. The data is acquired in a finite number of samples that correspond to a time window around the spike time (i.e., with periods before and after the action potential onset)."@en . + "spike waveform"@en . +# +# http://purl.org/neao/data#SpikeWaveformAverage + . + . + "The computed average across the spike waveforms."@en . + "spike waveform average"@en . +# +# http://purl.org/neao/data#SpikeWaveformSNR + . + . + "spike waveform SNR"@en . + "The computed signal-to-noise ratio of the spike waveforms."@en . + "spike waveform signal-to-noise ratio"@en . +# +# http://purl.org/neao/data#SpikeWaveformVariance + . + . + "The computed variance across the spike waveforms."@en . + "spike waveform variance"@en . +# +# http://purl.org/neao/data#SpikeWaveformWidth + . + . + "The computed spike waveform width."@en . + "spike waveform width"@en . +# +# http://purl.org/neao/data#SpikeWavevormStatistic + . + . + "Data that contains measures used to describe specific characteristics or make inferences from spike waveforms."@en . + "spike waveform statistic"@en . +# +# http://purl.org/neao/data#StandardDeviation + . + . + "SD"@en . + "The computed standard deviation (SD)."@en . + "standard deviation"@en . +# +# http://purl.org/neao/data#StandardErrorMean + . + . + "SEM"@en . + "The computed standard error of the mean (SEM)."@en . + "standard error of the mean"@en . +# +# http://purl.org/neao/data#StockwellTransform + . + . + "The result of computing the Stockwell transform (S transform)."@en . + "S transform"@en . + "Stockwell transform"@en . +# +# http://purl.org/neao/data#TensorComponent + . + . + "A tensor component obtained by applying tensor component analysis (TCA) to the input data."@en . + "tensor component"@en . +# +# http://purl.org/neao/data#TimeHistogram + . + . + "Data that contains a time histogram, i.e., a histogram that shows the distribution of a measure across specified time intervals (bins)."@en . + "time histogram"@en . +# +# http://purl.org/neao/data#TimeSeries + . + . + "Data that contains values of a specific quantity (e.g., voltage) acquired as a series of successive samples over time. Typically, there is a fixed interval between the samples (sampling period), with each sample representing a distinct time point in the series."@en . + "time series"@en . +# +# http://purl.org/neao/data#TransferEntropy + . + . + "TE"@en . + "The computed transfer entropy (TE)."@en . + "transfer entropy"@en . +# +# http://purl.org/neao/data#TriggeredAverageMeasure + . + . + "Data that contains the output of a triggered average analysis."@en . + "triggered average measure"@en . +# +# http://purl.org/neao/data#TuningCurve + . + . + "The computed tuning curve."@en . + "tuning curve"@en . +# +# http://purl.org/neao/data#UnbiasedSquaredPhaseLagIndex + . + . + "unbiased squared PLI"@en . + "The computed unbiased squared phase lag index (PLI)."@en . + "unbiased squared phase lag index"@en . +# +# http://purl.org/neao/data#UnitaryEventPattern + . + . + "UE pattern"@en . + "A neuronal activity pattern obtained by the Unitary Event (UE) analysis."@en . + "Unitary Event pattern"@en . +# +# http://purl.org/neao/data#VanRossumDistance + . + . + "The computed van Rossum distance."@en . + "van Rossum distance"@en . +# +# http://purl.org/neao/data#Variance + . + . + "The computed variance."@en . + "variance"@en . +# +# http://purl.org/neao/data#VictorPurpuraDistance + . + . + "The computed Victor-Purpura distance."@en . + "Victor-Purpura distance"@en . +# +# http://purl.org/neao/data#WaveletTransform + . + . + "Data that contains the result of a wavelet transform analysis, i.e., decomposing a time series using a mother wavelet function."@en . + "scaleogram"@en . + "wavelet transform"@en . +# +# http://purl.org/neao/data#WeightedPhaseLagIndex + . + . + "WPLI"@en . + "The computed weighted phase lag index (WPLI)."@en . + "weighted phase lag index"@en . +# +# http://purl.org/neao/parameters#ASSETAnalysisParameter + . + . + "A parameter used by the Analysis of Sequences of Synchronous Events (ASSET) method, used to identify neuronal activity patterns in spike data."@en . + "ASSET analysis parameter"@en . +# +# http://purl.org/neao/parameters#ASSETClusteringDistanceStretchFactor + . + . + "When computing the elliptical distance measure used by the DBSCAN algorithm to cluster the mask matrix entries to find the diagonal structures, the parameter value is used to stretch angular coefficients deviating from 45 degrees. This reflects into the shape of the neighborhood around a point in the DBSCAN procedure. A large stretch factor will produce neighborhoods that are narrower and closer to a line in the 45 degree direction. Smaller stretch factors will produce neighborhoods that are more elliptical, with the major axis in the 45 degree direction, and the minor axis in the 135 degree direction. Therefore, the smaller stretch factor increases the minor axis of this ellipsis. Together with the DBSCAN neighborhood radius parameter, this should be used to tweak the neighborhood ellipsis such that it is contained in the rectangular kernel used to filter the probability matrix entries when computing the joint probability matrix."@en . + "distance stretch factor in ASSET clustering"@en . +# +# http://purl.org/neao/parameters#ASSETJointProbabilityMatrixFilterShape + . + . + "A tuple of integers that determines the width and length of a rectangular kernel used to cover a diagonal structure in the intersection matrix. The kernel is centered in a point in the probability matrix, and defines a neighborhood around that point. Inside the kernel, a chosen number of largest neighbors in the probability matrix is used to compute the joint probability value for the center point. The kernel is rotated in 45 degree angle."@en . + "kernel shape in ASSET joint probability matrix"@en . + "filter shape in ASSET joint probability matrix"@en . +# +# http://purl.org/neao/parameters#ASSETJointProbabilityMatrixNumberLargestNeighbors + . + . + "Defines the number of elements inside the filter kernel that are used to compute the joint probability value for a matrix entry. The probability matrix values inside the kernel for that entry are ordered from the largest to the lowest value, and the first N elements corresponding to the parameter value are taken."@en . + "number of largest neighbors in ASSET joint probability matrix"@en . +# +# http://purl.org/neao/parameters#ASSETMaskMatrixSignificanceThresholds + . + . + "Real values (range 0-1) used as thresholds to determine if the entries in the probability matrix and joint probability matrices are significant. Entry significance is defined as a probability value greater than the threshold values specified by the parameter. Significant entries in both probability and joint probability matrices are defined as 1 in the mask matrix."@en . + "significance thresholds in ASSET mask matrix"@en . +# +# http://purl.org/neao/parameters#BartlettSmoothingKernel + . + . + "The kernel function has a triangular shape with end points at zero."@en . + "Bartlett smoothing kernel"@en . +# +# http://purl.org/neao/parameters#BinSize + . + . + "When discretizing continuous data into smaller intervals (bins), the parameter value determines the width of the intervals (in the unit of the data being discretized). Bins are adjacent and can be of different sizes."@en . + "bin width"@en . + "bin size"@en . +# +# http://purl.org/neao/parameters#BlackmanWindowFunction + . + . + "Window function that uses the first three terms of a summation of cosines, minimizing spectral leakage. It was proposed by Ralph Beebe Blackman. The coefficients are an approximation of the ones used in the exact Blackman window function. Therefore, this window does not remove the third and fourth side lobes but produces smoother edges."@en . + "Blackman window function"@en . +# +# http://purl.org/neao/parameters#BoxcarSmoothingKernel + . + . + . + "The kernel function is zero over the entire interval except for a single (smaller) interval where it has a constant value. This non-zero interval is the total width of the kernel."@en . + "Boxcar smoothing kernel"@en . +# +# http://purl.org/neao/parameters#DBSCANMinimumNeighbors + . + . + . + "Integer value that determines the minimum number of points that must be present in the neighborhood of a sample point such that it is considered a core point. The parameter value includes the sample point being evaluated."@en . + "DBSCAN minimum samples"@en . + "DBSCAN minimum number of neighbors"@en . +# +# http://purl.org/neao/parameters#DBSCANNeighborhoodRadius + . + . + "Determines the radius around a sample point used to define its neighborhood. The parameter defines the maximum distance between two sample points such that they are considered to be in the same neighborhood."@en . + "DBSCAN epsilon"@en . + "DBSCAN maximum distance"@en . + "DBSCAN neighborhood radius"@en . +# +# http://purl.org/neao/parameters#DBSCANParameter + . + . + "A parameter used by the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) data clustering method."@en . + "DBSCAN parameter"@en . +# +# http://purl.org/neao/parameters#DPSSWindowFunction + . + . + "DPSS window function"@en . + "A set of orthogonal sequences optimized to simultaneously achieve maximum concentration of energy within a defined frequency band and minimum leakage into neighboring frequency bands. They are frequently used as tapers in multiple applications (e.g., multitaper power spectral density estimation). The first sequence (order 0 or Slepian sequence) has maximal energy concentration in the main lobe."@en . + "Slepian sequences window function"@en . + "discrete prolate spheroidal sequences window function"@en . +# +# http://purl.org/neao/parameters#DitheringTime + . + . + "A time interval that defines a dithering distribution used to draw random numbers to displace individual spike times in a spike train."@en . + "dithering time"@en . +# +# http://purl.org/neao/parameters#DownsampleFactor + . + . + "A real value that indicates the factor by which the sampling period of a sampled time series is reduced in a downsampling operation."@en . + "decimation factor"@en . + "downsample factor"@en . +# +# http://purl.org/neao/parameters#ExactBlackmanWindowFunction + . + . + "Window function that uses the first three terms of a summation of cosines. It was proposed by Ralph Beebe Blackman. The coefficients are selected to remove the third and fourth side lobes, but the edges are discontinuous."@en . + "exact Blackman window"@en . +# +# http://purl.org/neao/parameters#ExponentialSmoothingKernel + . + . + "The kernel function is zero for points before the kernel center point, maximum at the center point, and decay exponentially for points greater than the center point. This kernel is asymmetric."@en . + "exponential smoothing kernel"@en . +# +# http://purl.org/neao/parameters#FilterOrder + . + . + "Integer value specifying the rate at which the filter response in the transition band falls. A higher filter order corresponds to a faster filter response decay."@en . + "filter order"@en . +# +# http://purl.org/neao/parameters#FiringRate + . + . + "The parameter value determines the average number of spikes fired by a neuron per time unit. It is used to control the behavior of steps that require a firing rate to control the output (e.g., a target mean firing rate when generating an artificial spike train)."@en . + "firing rate"@en . +# +# http://purl.org/neao/parameters#FrequencyResolution + . + . + "In analyses producing estimates in the frequency domain, the parameter determines the width of the frequency bins in the output, i.e., the resolution of the output on the frequency axis."@en . + "frequency resolution"@en . +# +# http://purl.org/neao/parameters#HammingSmoothingKernel + . + . + "The kernel function corresponds to a raised cosine (i.e., a single period of a cosine function \"raised\") with positive endpoints."@en . + "Hamming smoothing kernel"@en . +# +# http://purl.org/neao/parameters#HammingWindowFunction + . + . + "A window function that corresponds to a raised cosine (i.e., a single period of a cosine function \"raised\") but with positive endpoints. Therefore, the function does not eliminate the discontinuities in the signal. It has better cancellation of the nearest side lobe, and a poorer cancellation of the others, with a wide main lobe. It is named after Richard Wesley Hamming."@en . + "Hamming window function"@en . +# +# http://purl.org/neao/parameters#HannSmoothingKernel + . + . + "The kernel function corresponds to a raised cosine (i.e., a single period of a cosine function \"raised\" such that the negative troughs are zero). The endpoints reach zero smoothly at the boundaries."@en . + "Hann smoothing kernel"@en . +# +# http://purl.org/neao/parameters#HannWindowFunction + . + . + "A window function that corresponds to a raised cosine (i.e., a single period of a cosine function \"raised\" such that the negative troughs are zero). Therefore, the function reaches zero smoothly at the boundaries and eliminates all discontinuities in the signal. It has a wide main lobe and low side lobes. It is named after Julius von Hann."@en . + "raised-cosine window function"@en . + "von Hann window function"@en . + "hanning window function"@en . + "Hann window function"@en . +# +# http://purl.org/neao/parameters#HighPassFrequencyCutoff + . + . + "When applying a filter to a time series, the frequency components below this parameter value will be attenuated. Usually, the parameter value corresponds to the frequency component attenuated by 3 dB in the filter transition band."@en . + "high-pass frequency cutoff"@en . +# +# http://purl.org/neao/parameters#KaiserWindowFunction + . + . + "This window function approximates the DPSS window function using Bessel functions. It is easier to compute than the DPSS window function. It was developed by James Kaiser."@en . + "Kaiser-Bessel window function"@en . + "Kaiser window function"@en . +# +# http://purl.org/neao/parameters#KernelWidth + . + . + "The total width of a smoothing kernel."@en . + "kernel width"@en . +# +# http://purl.org/neao/parameters#LowPassFrequencyCutoff + . + . + "When applying a filter to a time series, the frequency components above this parameter value will be attenuated. Usually, the parameter value corresponds to the frequency component attenuated by 3 dB in the filter transition band."@en . + "low-pass frequency cutoff"@en . +# +# http://purl.org/neao/parameters#NumberFFTSamples + . + . + "Length of the time series considered by application of a fast Fourier transform (FFT). The value determines the frequency bin size based on the sampling frequency of the input data, and the length of the vector representing the result of the discrete Fourier transform."@en . + "FFT points"@en . + "number of FFT samples"@en . +# +# http://purl.org/neao/parameters#PeakResolution + . + . + "The parameter defines the separation of individual peaks in the output."@en . + "peak resolution"@en . +# +# http://purl.org/neao/parameters#SamplingFrequency + . + . + "The parameter determines the number of samples per time unit in sampled data. It is the inverse of the sampling period, i.e., the interval between two consecutive samples."@en . + "sampling rate"@en . + "sampling frequency"@en . +# +# http://purl.org/neao/parameters#ShapeFactor + . + . + "When determining a probability distribution, the parameter affects the shape of the distribution. This is in contrast to other parameters that affect the location (e.g., mean) or scale (e.g., variance) of the distribution."@en . + "shape factor"@en . +# +# http://purl.org/neao/parameters#SmoothingKernel + . + . + "A smoothing kernel can be used in non-parametric smoothing techniques such as kernel smoothing or kernel density estimation. It represents a weighting function that assigns weights to neighboring data points based on their distance from a given point (the kernel center). Closer points are given higher weights. The weighted average of the data points within the kernel is computed to produce a smoothed estimate of the underlying data (e.g., a signal or probability density function). Smoothing kernels are characterized by their shape (e.g., Boxcar, exponential) and bandwidth. The bandwidth determines the extent of influence of neighboring data points on the smoothed estimate."@en . + "smoothing kernel"@en . +# +# http://purl.org/neao/parameters#TemporalResolution + . + . + "The parameter determines the smallest time interval that can be detected or produced by the method. In sampled time series data, this equals to the sampling period, i.e, the time interval between two consecutive samples."@en . + "temporal resolution"@en . +# +# http://purl.org/neao/parameters#WaveletCenterFrequency + . + . + "The value of the center frequency of a wavelet. This is the frequency at which the wavelet oscillates most strongly, and it influences how effectively the wavelet can capture features of a signal at different frequencies. Wavelets with higher center frequencies are better suited for analyzing high-frequency components of a signal, while those with lower center frequencies are more effective for capturing low-frequency components."@en . + "wavelet center frequency"@en . +# +# http://purl.org/neao/parameters#WindowFunction + . + . + "A mathematical function that is zero-valued outside a defined interval. When multiplied by another function or sampled data, the values outside the window interval will be transformed to zero, and the values inside the window will be weighted by the window function values. \n\nWindow functions are used to select and modify a finite segment of a signal. This is useful for applying the fast Fourier transform (FFT) to a finite set of data where the length is not an integer number of periods of the signal. In this situation, there will be discontinuities at the boundaries of the signal, and the data in the frequency domain produced by the FFT will have frequency components not present in the original signal (spectral leakage). The window function can be used to reduce this discontinuities and mitigate spectral leakage when performing spectral analysis.\n\nSeveral types of window function exist. They will vary in shape in the time domain and will have distinct frequency characteristics in the frequency domain, with a main lobe and several side lobes. The main lobe is centered at each frequency component in the time domain, and the side lobes approach zero. These characteristics can be used to control the effect of spectral leakage when performing the analysis."@en . + "apodization function"@en . + "tapering function"@en . + "window function"@en . +# +# http://purl.org/neao/parameters#WindowLengthSamples + . + . + "Integer value that defines the number of samples encompassed by a window in sampled data, i.e., the window length. The window corresponds to a finite interval in the sampled data (e.g., a time interval in sampled time series data)."@en . + "window length in samples"@en . +# +# http://purl.org/neao/parameters#WindowOverlapFactor + . + . + "Real value (range 0-1) that determines the proportion of overlap between two adjacent windows. The window is a finite interval in the data (e.g., a time interval in time series data)."@en . + "window overlap factor"@en . +# +# http://purl.org/neao/parameters#WindowOverlapSamples + . + . + "Integer value (range 0 to the window length in samples) that determines the number of samples where two adjacent windows overlap. The window corresponds to a finite interval in sampled data (e.g., a time interval in sampled time series data)."@en . + "window overlap in samples"@en . +# +# http://purl.org/neao/steps#ASSETAnalysisProbabilityMatrixSubstep + . + . + . + "ASSET analysis substep that computes the probability matrix (PMAT). The probability matrix contains, for each entry in the intersection matrix, the cumulative probability representing the probability of having the overlap in the IMAT under the assumption that the spike trains are independent. If an entry in the PMAT is large, the null hypothesis of independence is rejected, and the alternative hypothesis that the observed overlap reflects active synchronization between the involved neurons at the time bins of the intersection is accepted. The PMAT computation can be done with either an analytical or Monte Carlo approach."@en . + "ASSET analysis probability matrix substep"@en . +# +# http://purl.org/neao/steps#ASSETAnalysisSubstep + . + . + . + "An analysis step that is an individual part of the ASSET analysis method to identify neuronal activity patterns in spike train data."@en . + "ASSET analysis substep"@en . +# +# http://purl.org/neao/steps#AnalysisPurpose + . + "Analysis purpose refers to the specific objective or goal that an analysis is intended to achieve. It outlines what the analysis step aims to discover, understand, or demonstrate. This class is intended for grouping steps that perform analyses with similar goals/outputs but with distinct methodological or algorithmic approaches. It is used as a normalization class via the hasPurpose object property."@en . + "analysis purpose"@en . +# +# http://purl.org/neao/steps#ApplyAdaptiveKernelSmoothing + . + . + "A kernel smoothing that uses a variable-width kernel. The kernel width varies adaptively depending on the local density of the data. This method takes into consideration local variations in data density, resulting in a more accurate representation of the underlying patterns and structures."@en . + "apply adaptive kernel smoothing"@en . +# +# http://purl.org/neao/steps#ApplyAnalyticSignalConversion + . + . + "A data transformation that uses the Hilbert transform of a real-valued input time series to construct the analytic signal, a complex-valued time series where the real part is the original real-valued signal and the imaginary part is the Hilbert transform. The analytic signal does not have negative frequency components."@en . + "apply analytic signal conversion"@en . +# +# http://purl.org/neao/steps#ApplyButterworthFilter + . + . + "An infinite impulse response filtering that uses a Butterworth type filter, i.e., a filter designed to have a maximally flat frequency response in the passband (no ripples). The frequency response gradually decreases to zero in the stopband, and the steepness of the decrease (roll-off) is controlled by the order of the filter."@en . + "apply maximally flat magnitude filter"@en . + "apply Butterworth filter"@en . +# +# http://purl.org/neao/steps#ApplyCanonicalPolyadicTensorDecomposition + . + . + "apply CPD"@en . + . + "A tensor component analysis (TCA) that expresses the input high-dimensional tensor as a sum of rank-one tensors (tensor components). Each dimension in the tensor component corresponds to a dimension in the input high-dimensional tensor. For neural data, a tensor could be used to represent trial-by-trial spiking activity, with neurons, time, and trials as dimensions. Therefore, each tensor component produced from that input will have a rank-one tensor for the neurons, time, and trial, which describes both within- and between-trial changes."@en . + "apply tensor rank decomposition"@en . + "apply canonical polyadic tensor decomposition"@en . +# +# http://purl.org/neao/steps#ApplyCoupledCanonicalPolyadicTensorDecomposition + . + . + "apply CCPD"@en . + . + "A tensor component analysis (TCA) that expresses multiple high-dimensional input tensors as a sum of rank one tensors (tensor components). The output tensor components have shared vectors that summarize an input dimension across all input tensors. For example, if analyzing two tensors, each representing trial-by-trial spiking activity obtained from a distinct experimental subject (neurons X time X trials), the coupled canonical polyadic tensor decomposition (CCPD) could produce tensor components for each dataset where the vector for the trial and time dimensions are the same, but the neuron dimension is unique for each dataset (hence, each subject). Therefore, CCPD is useful for scenarios with multiple and related datasets, allowing for the exploitation of shared information to enhance the decomposition results."@en . + "apply coupled canonical polyadic tensor decomposition"@en . +# +# http://purl.org/neao/steps#ApplyDFTNoiseRemoval + . + . + "apply DFT noise removal"@en . + "A line noise removal that uses a discrete Fourier transform (DFT) filter and estimates the power line component amplitude in the input data by fitting a sine and cosine at a user-specified line noise frequency (e.g., 50 Hz), followed by the subtraction of those components from the input."@en . + "apply discrete Fourier transform noise removal"@en . +# +# http://purl.org/neao/steps#ApplyDataConcatenation + . + . + "A data transformation that joins two or more data inputs into a single data element. For example, in a multitrial experimental session, where data was acquired separately as one epoch per trial, a continuous data segment for the session can be constructed by concatenating all trial epochs together."@en . + "apply data concatenation"@en . +# +# http://purl.org/neao/steps#ApplyDemixedPrincipalComponentAnalysis + . + . + "apply dPCA"@en . + . + "A principal component analysis (PCA) that uses a modified version of the standard PCA for neural activity data analysis. Demixed PCA (dPCA) not only obtains a low-dimensional representation of the input data, but it also demixes the dependencies of the population activity on the task parameters. Therefore, dPCA can show the dependence of the neural representation on parameters such as stimuli, subject decisions, or rewards."@en . + "apply demixed principal component analysis"@en . +# +# http://purl.org/neao/steps#ApplyDiscreteFourierTransform + . + . + "A frequency-domain transformation that applies the discrete Fourier transform (DFT) to an input time series acquired in equally-spaced samples. The DFT is used to obtain the frequency representation of the time-domain input. The DFT output is a sequence of coefficients of complex sinusoids, each representing a frequency component in the input signal. Each frequency component consists of an interval (or bin), and the width of the bin determines the frequency resolution of the DFT. The number of frequency components and the frequency resolution is determined by the length of the input signal (number of samples) and the sampling frequency. For large datasets, the computation is computationally expensive (O(N^2) complexity)."@en . + "apply DFT"@en . + "apply discrete Fourier transform"@en . +# +# http://purl.org/neao/steps#ApplyDistanceCovarianceAnalysis + . + . + "apply DCA"@en . + . + "A dimensionality reduction that identifies linear and nonlinear relationships between multiple input datasets. The method identifies linear projections (DCA dimensions) that maximize the distance covariance statistic (an Euclidean-based correlational statistic). For example, for recordings from different brain regions (two neuronal populations), the distance covariance analysis (DCA) can identify the dimensions in the population activity in the different brain areas that are related to each other. The dimensionality reduction can also take other dependent variables into account (e.g., stimulus or behavioral variables)."@en . + "apply distance covariance analysis"@en . +# +# http://purl.org/neao/steps#ApplyDownsampling + . + . + . + "A resampling that reduces the number of samples in the input data (i.e., reduces the sampling frequency). This is often accomplished after applying an anti-aliasing filter (i.e., to remove frequencies above half the value of the new sampling frequency)."@en . + "apply decimation"@en . + "apply downscaling"@en . + "apply downsampling"@en . +# +# http://purl.org/neao/steps#ApplyFastFourierTransform + . + . + "A frequency-domain transformation that uses the fast Fourier transform (FFT) algorithm to compute the discrete Fourier transform (DFT). The computation of the DFT is computationally expensive for large datasets. The FFT reduces the number of computations significantly by using a divide-and-conquer approach, leveraging the symmetry and periodicity properties of the DFT. The complexity is O(N log N). The output of the method is similar to the DFT, i.e., a sequence of coefficients of complex sinusoids, each representing a frequency component in the input signal. The FFT takes a size parameter, that refers to the number of points in the input data sequence that is used for the computation. The FFT size determines the frequency resolution, and, for maximal efficiency, should be a multiple of 2."@en . + "apply FFT"@en . + "apply fast Fourier transform"@en . +# +# http://purl.org/neao/steps#ApplyFiniteImpulseResponseFilter + . + . + "apply FIR filter"@en . + "A finite impulse response (FIR) filtering where a custom-designed FIR filter is applied to the input data."@en . + "apply finite impulse response filter"@en . +# +# http://purl.org/neao/steps#ApplyFiniteImpulseResponseFilterKaiserWindow + . + . + "apply FIR filter with Kaiser window"@en . + "A finite impulse response (FIR) filtering that uses a FIR filter whose impulse response is controlled by applying a Kaiser window function."@en . + "apply finite impulse response filter with Kaiser window"@en . +# +# http://purl.org/neao/steps#ApplyFixedKernelSmoothing + . + . + "A kernel smoothing that uses a fixed-width kernel. The kernel type and kernel width can be specified as parameters."@en . + "apply fixed kernel smoothing"@en . +# +# http://purl.org/neao/steps#ApplyGeneralLinearModelPolynomialDetrending + . + . + "A detrending that uses a general linear model to fit a polynomial from the input data and remove the mean and linear trend."@en . + "apply general linear model polynomial detrending"@en . +# +# http://purl.org/neao/steps#ApplyHilbertTransform + . + . + "A data transformation that applies the Hilbert transform to a real-valued time series. The Hilbert transform shifts the phase of each frequency component of the signal by 90 degrees: positive frequencies are shifted by -90 degrees, and negative frequencies are shifted by +90 degrees. This can be used to construct the analytic signal."@en . + "apply Hilbert transform"@en . +# +# http://purl.org/neao/steps#ApplyIndependentComponentAnalysis + . + . + "apply ICA"@en . + . + "A data transformation that separates a multivariate input signal into additive subcomponents (independent components). The independent components are statistically independent from each other."@en . + "apply independent component analysis"@en . +# +# http://purl.org/neao/steps#ApplyInfiniteImpulseResponseFilter + . + . + "apply IIR filter"@en . + "An infinite impulse response (IIR) filtering where a custom-designed IIR filter is applied to the input data."@en . + "apply infinite impulse response filter"@en . +# +# http://purl.org/neao/steps#ApplyInterpolation + . + . + "A data transformation that estimates new (intermediate) values between the known values in the input data. This can be accomplished using several methods, such as linear interpolation (i.e., estimating the values along a straight line connecting adjacent points), polynomial interpolation (i.e., using polynomials to estimate the values between points), or spline Interpolation (i.e., using piecewise polynomials that pass through the known data points and provide a smooth curve)."@en . + "apply interpolation"@en . +# +# http://purl.org/neao/steps#ApplyLinearDiscriminantAnalysis + . + . + "apply LDA"@en . + "A dimensionality reduction that finds a linear combination of features that separates two or more classes defined in the input data. The input data must have a variable that defines the class for each observation, and continuous variables that are used for the linear discriminant analysis (LDA). LDA finds an optimal projection vector that maximizes the distance between the means of the different classes, and minimizes the variance within each class. LDA projects the input data into the lower-dimensional space, therefore reducing the number of features while retaining the information needed for classification. The optimal projection vectors found by LDA are the Fisher linear discriminants."@en . + "apply linear discriminant analysis"@en . +# +# http://purl.org/neao/steps#ApplyLocalLinearRegressionDetrending + . + . + . + "A detrending that removes a running line fit using local linear regression. Local linear regression estimates a function by fitting a low-order polynomial to data within a sliding window (local neighborhood) across the input data."@en . + "apply local linear regression detrending"@en . +# +# http://purl.org/neao/steps#ApplyLocalRegressionAndLikelihoodSmoothing + . + . + . + . + "A data smoothing that estimates a low-order polynomial in a local neighborhood (window) of any value in the input data. Polynomial coefficients are estimated using the least mean squares method. Contrary to kernel smoothing methods, this is a non-parametric approach and has reduced bias at the boundaries of the input data."@en . + "apply local regression and likelihood smoothing"@en . +# +# http://purl.org/neao/steps#ApplyMedianRescaling + . + . + "A data normalization that uses the median and interquartile range (IQR) to rescale the values of the input data. This method is less sensitive to outliers (compared to the z-score transform), and therefore is known as robust scaling."@en . + "apply robust scaling"@en . + "apply median rescaling"@en . +# +# http://purl.org/neao/steps#ApplyMinMaxNormalization + . + . + "A data normalization that adjusts the range and distribution of values in the data input such that they fall within a fixed range, based on the minimum and maximum values in the input data. In the typical case, the values are normalized to the [0, 1] interval."@en . + "apply rescaling"@en . + "apply min-max normalization"@en . +# +# http://purl.org/neao/steps#ApplyMovementArtifactRemoval + . + . + "An artifact removal that identifies and removes artifacts originating from movements of the experimental subject (e.g., eye movement, head movement)."@en . + "apply movement artifact removal"@en . +# +# http://purl.org/neao/steps#ApplyNeuralTrajectoryGaussianProcessFactorAnalysis + . + . + _:genid4 . +_:genid4 . +_:genid4 . +_:genid4 . + "apply GPFA"@en . + . + "A dimensionality reduction that uses the Gaussian process factor analysis (GPFA) method described by Yu et al. (2009). GPFA extracts smooth, low-dimensional neural trajectories that summarize the activity recorded simultaneously from many neurons on individual experimental trials over time. The input is a set of spike trains representing multitrial activity of multiple neurons recorded in parallel. The input spike trains are binned, and factor analysis is applied to reduce the dimensionality while smoothing the resulting low-dimensional trajectories by fitting a Gaussian process (GP) model to them. The identified trajectories are called neural trajectories, and show the evolution of the activity of the population of neurons over time."@en . + "apply neural trajectory Gaussian process factor analysis"@en . +# +# http://purl.org/neao/steps#ApplyNonNegativeTensorComponentAnalysis + . + . + "A tensor component analysis (TCA) where a non-negative constraint is applied to the decomposition. This is desirable when the underlying components have physical interpretation and negative values are not possible."@en . + "apply non-negative tensor component analysis"@en . +# +# http://purl.org/neao/steps#ApplyNotchFilter + . + . + "An infinite impulse response filtering that uses a filter designed to attenuate or eliminate a narrow band of frequencies in the input data (stopband) while allowing other frequencies to pass through relatively unaffected."@en . + "apply notch filter"@en . +# +# http://purl.org/neao/steps#ApplyNotchFilterNoiseRemoval + . + . + "A line noise removal that employs a notch filter to remove line noise. A notch filter is designed to attenuate or eliminate a narrow band of frequencies in the input data (stopband) while allowing other frequencies to pass through relatively unaffected. The notch filter stop band is usually centered at the power line frequency (i.e., 50 Hz or 60 Hz depending on the location)."@en . + "apply notch filter noise removal"@en . +# +# http://purl.org/neao/steps#ApplyOutlierRemoval + . + . + "An artifact removal that identifies and removes values in the input data that differs significantly from other values (outliers). Outliers may arise from the variability in the measurement or be the result of experimental error."@en . + "apply outlier removal"@en . +# +# http://purl.org/neao/steps#ApplyPadding + . + . + "A data transformation that adds extra data (often zeros or other predefined values) to the beginning, end, or both sides of the input data."@en . + "apply padding"@en . +# +# http://purl.org/neao/steps#ApplyProbabilisticPrincipalComponentAnalysis + . + . + "apply pPCA"@en . + . + "A principal component analysis (PCA) that assumes a probabilistic model for the generation of the observed data, according to Tipping & Bishop (1999). The model assumes that the values in the data input are generated from the lower-dimensional subspace of latent variables (principal components) plus an additive Gaussian noise. This generalizes the standard PCA for the case where the noise covariance approaches zero. The probabilistic PCA (pPCA) allows for uncertainty estimation and modeling of the data generation process, and can be employed when there are missing values in the input data."@en . + "apply probabilistic principal component analysis"@en . +# +# http://purl.org/neao/steps#ApplyRectification + . + . + "A data transformation that computes the absolute value of the input data (rectification)."@en . + "apply rectification"@en . +# +# http://purl.org/neao/steps#ApplyRereference + . + . + "A data transformation that changes the reference point of the data recorded from an electrode. This can be performed by calculating the average across the data obtained from all electrodes and subtracting it from each individual electrode’s data (reducing common noise) or referencing each electrode to its nearest neighbor or a defined pair, subtracting one signal from another (bipolar referencing)."@en . + "apply rereference"@en . +# +# http://purl.org/neao/steps#ApplySpectrumInterpolationNoiseRemoval + . + . + . + "A line noise removal that uses spectral interpolation to remove power line noise. After obtaining the discrete Fourier transform (DFT) of the input signal with noise, the original frequency component at the power line oscillation frequency can be estimated by interpolating the amplitude spectrum (obtained from the DFT) at the power line frequency (e.g., 50 Hz), followed by the inverse DFT to reconstruct the signal."@en . + "apply spectrum interpolation noise removal"@en . +# +# http://purl.org/neao/steps#ApplySpikeExtractionFromTimeSeries + . + . + "A data transformation that obtains a series of spike times (i.e., a spike train) from an input time series (e.g., voltages recorded from an electrode). The spike times can be estimated, for example, by taking all the time points where the values in the input data are greater or lower than a threshold value."@en . + "apply spike extraction from time series"@en . +# +# http://purl.org/neao/steps#ApplySpikeTrainBinarization + . + . + "A data transformation that takes an input spike train and returns an array of boolean values indicating if at least one spike occurred at individual time points."@en . + "apply spike train binarization"@en . +# +# http://purl.org/neao/steps#ApplySpikeTrainBinning + . + . + "A data transformation that performs a binning operation on the input spike train data. The transformation discretizes the duration of the input spike train(s) into smaller time intervals (bins), and obtains the number of spikes occurring into each bin (binned spike train). Additionally, the occurrence of spikes into each bin can be converted into a binary form (i.e., bins with or without spikes). This is known as clipping. The width of the bin interval is specified by a parameter (bin size)."@en . + "apply spike train binning"@en . +# +# http://purl.org/neao/steps#ApplySpikeWaveformInterpolation + . + . + "A data transformation that estimates additional (unknown) values between sample points of a spike waveform input."@en . + "apply spike waveform interpolation"@en . +# +# http://purl.org/neao/steps#ApplySpikeWaveformOutlierRejection + . + . + "An artifact removal that identifies and removes spike waveforms that differ significantly from the other spike waveforms in the input. This usually involves identifying waveforms with too late peaks, or in which the rising phase of the potential does not align with the peaks of all other waveforms in the input."@en . + "apply spike waveform outlier rejection"@en . +# +# http://purl.org/neao/steps#ApplySpikeWaveformPeakAlignment + . + . + "A data transformation that modifies input spike waveforms in order to align their peak values in time."@en . + "apply spike waveform peak alignment"@en . +# +# http://purl.org/neao/steps#ApplyStandardPrincipalComponentAnalysis + . + . + "apply standard PCA"@en . + "A principal component analysis (PCA) that operates by computing the covariance matrix of the input data, which is then decomposed into its eigenvectors and eigenvalues. The eigenvectors, corresponding to the principal components (PCs), are sorted by the magnitude of their associated eigenvalues. The eigenvectors with the largest eigenvalues explain the most variance in the data and thus form the primary PCs."@en . + "apply classical principal component analysis"@en . + "apply standard principal component analysis"@en . +# +# http://purl.org/neao/steps#ApplyStimulationArtifactRemoval + . + . + "An artifact removal that identifies and removes artifacts originating from presenting a stimulus during the recording (e.g., electrical stimulation)."@en . + "apply stimulation artifact removal"@en . +# +# http://purl.org/neao/steps#ApplySum + . + . + "A data transformation that performs the addition of two or more data inputs to obtain a sum."@en . + "apply sum"@en . +# +# http://purl.org/neao/steps#ApplySynchronousSpikeRemoval + . + . + "An artifact removal that identifies and removes spikes across two or more spike train inputs that occurred simultaneously within a temporal precision specified by a parameter. The temporal precision is usually the sampling rate used by the recording equipment: if different neurons fired within an interval equal to or smaller than the sampling period, this suggests that this synchronous activity does not come from temporal synchronization of the neurons but rather due to an interference in the recording (e.g., electrical noise picked simultaneously by multiple channels)."@en . + "apply synchronous spike removal"@en . +# +# http://purl.org/neao/steps#ApplyThomsonRegressionNoiseRemoval + . + . + . + "A line noise removal that uses Thomson's regression method (1982) for detecting sinusoids, that identifies and removes significant sine waves from the input data. The desired frequencies can be specified by parameter, or determined using an F-statistic."@en . + "apply Thomson regression noise removal"@en . +# +# http://purl.org/neao/steps#ApplyTrialExtraction + . + . + "A data transformation that extracts trial segments from an input data entity storing a longer and continuous data stream. A trial is a single instance of a repeated experimental procedure. For example, during an electrophysiology experiment, a visual stimulus might be presented several times, with neural activity recorded each time. Each presentation of the stimulus defines a trial. Since the data is recorded continuously, this data transformation identifies and isolates the segments of data corresponding to each individual stimulus presentation, returning them as separate data entities."@en . + "apply trial extraction"@en . +# +# http://purl.org/neao/steps#ApplyUpsampling + . + . + "A resampling that increases the number of samples in the data (i.e., increases the sampling frequency). This is often accomplished by adding new (zero-valued) samples between existing ones followed by applying a lowpass filter to replace the zeros and smooth out the discontinuities."@en . + "apply upscaling"@en . + "apply upsampling"@en . +# +# http://purl.org/neao/steps#ApplyWindowedSincFilter + . + . + "A finite impulse response filtering that employs the convolution with a sinc function kernel multiplied by a window function (e.g., Blackman or Hamming). The kernel is obtained by evaluating the sinc function for the cutoff frequencies specified as parameters, followed by truncation of the filter skirt, and applying the window to reduce the artifacts introduced from the truncation. The windowed-sinc filter is stable and very efficient to separate one band of frequencies from another."@en . + "apply windowed-sinc filter"@en . +# +# http://purl.org/neao/steps#ApplyZscoreTransform + . + . + "A data normalization that transforms the values of the input data to have zero mean and unit variance."@en . + "apply standardization"@en . + "apply z-score transform"@en . +# +# http://purl.org/neao/steps#ArtifactRemoval + . + . + "A data transformation that aims to identify and remove artifacts from the input data. Artifacts are unwanted disturbances that distorts the data. In an electrophysiology experiment, they can arise from various sources: environmental interference (e.g., electromagnetic interference from nearby equipment), physiological processes (e.g., eye movement, heart beat), and technical instrumentation issues (e.g., baseline drift of the recorded potentials)."@en . + "artifact removal"@en . +# +# http://purl.org/neao/steps#ArtificialDataGeneration + . + _:genid5 . +_:genid5 . +_:genid5 . +_:genid5 . + . + "A data generation that produces artificial data. Artificial data refers to data that is generated programmatically rather than obtained from experimental recordings (e.g., neural simulations or by using specific statistical procedures). The artificial data generation procedure does not take experimentally-recorded data as input, and the generation of the output data depends only on parameters to the method employed. The isArtificial data property is defined as True for outputs of artificial data generation steps."@en . + "artificial data generation"@en . +# +# http://purl.org/neao/steps#AutocorrelationAnalysis + . + . + _:genid6 . +_:genid6 "true"^^ . +_:genid6 . +_:genid6 . + "An analysis step used to compute a measure of autocorrelation, i.e., the correlation of the input with displaced (lagged or advanced) versions of itself. The computation produces the autocorrelation value for every lag considered."@en . + "autocorrelation analysis"@en . +# +# http://purl.org/neao/steps#BivariateAnalysis + . + _:genid7 . +_:genid7 "true"^^ . +_:genid7 . +_:genid7 . + . + . + "An analysis step that has only two distinct inputs considered for the computation of the output (e.g., the two time series with the local field potential recorded from two electrodes used to compute a cross-correlation)."@en . + "pairwise analysis"@en . + "bivariate analysis"@en . +# +# http://purl.org/neao/steps#CentralTendencyStatisticalAnalysis + . + . + "A statistical analysis to compute a measure of central tendency, i.e., that represents the center or typical value of the input data."@en . + "central tendency statistical analysis"@en . +# +# http://purl.org/neao/steps#CoherenceAnalysis + . + . + _:genid8 . +_:genid8 . +_:genid8 . +_:genid8 . + _:genid9 . +_:genid9 "true"^^ . +_:genid9 . +_:genid9 . + _:genid10 . +_:genid10 "false"^^ . +_:genid10 . +_:genid10 . + _:genid11 . +_:genid11 "true"^^ . +_:genid11 . +_:genid11 . + _:genid12 . +_:genid12 "true"^^ . +_:genid12 . +_:genid12 . + "A spectral analysis that computes a measure of coherence between two or more inputs. Coherence is a real measure that describes the linear association of the distinct inputs (e.g., two time series) in different frequency bands. It corresponds to the absolute value of the coherency."@en . + "coherence analysis"@en . +# +# http://purl.org/neao/steps#CoherencyAnalysis + . + . + _:genid13 . +_:genid13 . +_:genid13 . +_:genid13 . + _:genid14 . +_:genid14 "true"^^ . +_:genid14 . +_:genid14 . + _:genid15 . +_:genid15 "false"^^ . +_:genid15 . +_:genid15 . + _:genid16 . +_:genid16 "true"^^ . +_:genid16 . +_:genid16 . + _:genid17 . +_:genid17 "true"^^ . +_:genid17 . +_:genid17 . + "A spectral analysis that computes a measure of coherency between two inputs. Coherency is a complex-valued measure that describes the linear association of the distinct inputs (e.g., two time series) in different frequency bands."@en . + "coherency analysis"@en . +# +# http://purl.org/neao/steps#CompoundAnalysis + . + _:genid18 . +_:genid18 . +_:genid18 . +_:genid18 . + . + "An analysis step that is composed by two or more substeps, each performing a part of the analysis with its own data inputs/outputs and analysis parameters."@en . + "compound analysis"@en . +# +# http://purl.org/neao/steps#ComputeASSETClusterMatrix + . + . + . + "ASSET analysis substep that computes the cluster matrix (CMAT) in the ASSET analysis, using DBSCAN with a modified distance metric. It takes the mask matrix (MMAT) as input. The cluster matrix groups the significant entries in the MMAT according to each diagonal structure that they belong to. For each significant entry in the MMAT, the CMAT will have an integer value: -1 for significant entries that do not belong to any diagonal structure, or any value greater than zero with the identification of the cluster that the entry belongs to."@en . + "compute ASSET cluster matrix"@en . +# +# http://purl.org/neao/steps#ComputeASSETIntersectionMatrix + . + . + . + "ASSET analysis substep that computes the intersection matrix (IMAT). For a set of input spike trains, binned with a bin width, each entry in the IMAT corresponds to a pair of distinct bins (i.e., distinct time points in the data). The value in the entry corresponds to the number of neurons that fired in both bins corresponding to that entry. When groups of neurons fire in a sequence that repeats in time, the IMAT will show patterns that follow a diagonal direction (diagonal structure). The ASSET method aims to identify the diagonal structures by automated statistical testing and clustering procedures."@en . + "compute ASSET intersection matrix"@en . +# +# http://purl.org/neao/steps#ComputeASSETJointProbabilityMatrix + . + . + . + "ASSET analysis substep that computes the joint probability matrix (JMAT). For every entry in the probability matrix (PMAT), the computation produces the combined probability of a fixed number of neighbors in a rectangular kernel (with fixed length and width as parameters) covering a diagonal structure. A value in the JMAT reflects how likely entries with high probability in the PMAT are to be located in the same diagonal structure."@en . + "compute ASSET joint probability matrix"@en . +# +# http://purl.org/neao/steps#ComputeASSETMaskMatrix + . + . + . + "ASSET analysis substep that computes the mask matrix (MMAT). The parameters are the threshold values that are used to determine if the entries in the probability matrix (PMAT) and joint probability matrix (JMAT) are significant. Entry significance in either matrix is defined as a probability value greater than the provided threshold value. Significant entries in both probability and joint probability matrices are defined as 1 in the mask matrix."@en . + "compute ASSET mask matrix"@en . +# +# http://purl.org/neao/steps#ComputeASSETProbabilityMatrixAnalytical + . + . + . + . + "ASSET analysis probability matrix substep that computes the probability matrix (PMAT) using the assumption that the input spike trains are independent and Poisson. The computation can take as input the firing rate profiles of the spike trains used for the intersection matrix (IMAT), or those will be automatically computed using convolution with a boxcar kernel of specified width. The probability distribution of the value in the intersection matrix (IMAT) is approximated by a Poisson distribution computed using LeCam's approximation. The output is a matrix with the cumulative probabilities representing the probability of having each overlap in the IMAT strictly lower than the observed overlap, under the null hypothesis of independence of the input spike trains."@en . + "compute ASSET probability matrix (analytical method)"@en . +# +# http://purl.org/neao/steps#ComputeASSETProbabilityMatrixMonteCarlo + . + . + . + "ASSET analysis probability matrix substep that computes the probability matrix (PMAT) employing a Monte Carlo approach using surrogate data obtained from the input spike trains. Different than the analytical method of computation, the null hypothesis in this method does not incorporate the assumptions that the spike trains are Poisson. Spike train surrogates can be generated using distinct methods."@en . + "compute ASSET probability matrix (Monte Carlo method)"@en . +# +# http://purl.org/neao/steps#ComputeASSETSequenceSynchronousEventsExtraction + . + . + . + "Last substep of the ASSET analysis method. Given the cluster matrix (CMAT), the identity of the neurons present in each bin of the repeated sequence in the identified diagonal structures is extracted (considering the input spike trains for the computation of the intersection matrix). The output of this substep is the final description of the ASSET pattern for each diagonal structure in the CMAT."@en . + "compute ASSET sequence of synchronous events extraction"@en . +# +# http://purl.org/neao/steps#ComputeAngularMeanSpikePhases + . + . + _:genid19 . +_:genid19 . +_:genid19 . +_:genid19 . + . + "A phase analysis that computes the angle obtained from averaging the phases of an input signal at the time points where spikes occurred. For the computation, the phases are represented as vectors in the unit circle, the mean phase vector is computed, and the angle is extracted."@en . + "compute angular mean of spike phases"@en . +# +# http://purl.org/neao/steps#ComputeAutocorrelationFunction + . + . + "compute ACF"@en . + "An autocorrelation analysis that computes the estimator for the autocorrelation function, i.e. the autocorrelation values of a time series input for a number of lags. The autocorrelation function shows temporal dependencies and repetitive patterns within the input data. The value of the autocorrelation at a specific lag shows how similar the values in the time series input are when separated by a number of time units equal to that lag. The autocorrelation value of 0 indicates no correlation. The autocorrelation varies between 1 and -1 (positive and negative correlation, respectively)."@en . + "compute autocorrelation function"@en . +# +# http://purl.org/neao/steps#ComputeCV + . + . + "compute CV"@en . + "A dispersion statistical analysis that computes the coefficient of variation (CV). The CV is the ratio of the standard deviation to the mean. It is useful to compare different inputs, as the measure is unitless and indicates the relative variability in the input data."@en . + "compute coefficient of variation"@en . +# +# http://purl.org/neao/steps#ComputeCV2 + . + . + . + "An interspike interval variability analysis that computes the CV2, a measure of the intrinsic variability of a spike train that considers adjacent interspike intervals. The CV2 is more robust against fluctuations in the firing rate than the usual approach of taking the coefficient of variation of the interspike intervals of the spike train."@en . + "compute CV2"@en . +# +# http://purl.org/neao/steps#ComputeCVInterspikeIntervals + . + . + "compute CV ISIs"@en . + "An interspike interval variability analysis that computes the coefficient of variation (CV) of the interspike intervals (ISIs). The CV is computed as the ratio of the standard deviation of the ISIs to their mean."@en . + "compute coefficient of variation of the interspike intervals"@en . +# +# http://purl.org/neao/steps#ComputeCanonicalCoherence + . + . + "compute caCOH"@en . + . + "A coherence analysis that computes the canonical coherence (caCOH) according to Vidaurre et al. (2019). The computation maximizes the coherence between two inputs (e.g., distinct datasets with electroencephalogram, electromyogram or local field potential recordings). The absolute value of the coherence between the two multivariate spaces of the inputs in the frequency domain is maximized. The caCOH aims to maximize the strength of the synchronization of oscillatory signals when two multichannel datasets are present (e.g., multiple subjects). The method then finds two spatial projections maximizing the strength of synchronization."@en . + "compute canonical coherence"@en . +# +# http://purl.org/neao/steps#ComputeCoherence + . + . + "A coherence analysis that computes the coherence value between two inputs. It is obtained from the magnitude of the complex-valued cross power spectral density obtained for the two inputs normalized by their power spectral density (i.e., auto spectral density). Several frequency decomposition approaches can be used to obtain the cross and auto power spectral densities from the inputs. The computation can return the magnitude coherence (i.e., by taking the absolute value of the cross power spectral density and normalizing by the square root of the product of the two auto spectral densities) or the magnitude squared coherence (i.e., by computing the squared magnitude of the cross power spectral density and normalizing by the product of the two auto spectral densities)."@en . + "compute coherence"@en . +# +# http://purl.org/neao/steps#ComputeCoherenceCarter + . + . + . + "A coherence analysis that computes the coherence from two inputs according to Carter (1987). The computation produces the magnitude squared coherence."@en . + "compute coherence (Carter method)"@en . +# +# http://purl.org/neao/steps#ComputeCoherenceMultitaper + . + . + . + "A coherence analysis where the coherence value between the two inputs is computed using cross and auto power spectral densities obtained using a multitaper approach according to Thomson (1982)."@en . + "compute coherence (multitaper method)"@en . +# +# http://purl.org/neao/steps#ComputeCoherenceRosenberg + . + . + . + "A coherence analysis that computes the coherence from two inputs according to Rosenberg et al. (1989). The method is described for point processes (i.e., spike trains). The computation produces the magnitude squared coherence."@en . + "compute coherence (Rosenberg method)"@en . +# +# http://purl.org/neao/steps#ComputeCoherenceWelch + . + . + . + "A coherence analysis where the coherence value between the two inputs is obtained from cross and auto power spectral densities obtained using the method described by Welch (1967). For the computation, the inputs are divided into multiple overlapping segments, and the overall cross and power spectral densities for computing the coherence are obtained from averaging the single-segment estimates."@en . + "compute coherence (Welch method)"@en . +# +# http://purl.org/neao/steps#ComputeCoherency + . + . + "A coherency analysis that computes the coherency for two inputs. It is computed from the complex-valued cross power spectral density obtained for the two inputs normalized by the square root of the product of their power spectral densities (i.e., auto spectral densities). For each frequency, the magnitude of the complex-valued coherency describes the strength of the association and the angle describes the phase lag between the two inputs. If the inputs contain multi-epoch data (e.g., multiple trial repetitions), the cross and auto spectral densities are averaged across epochs."@en . + "compute complex coherency"@en . + "compute coherency"@en . +# +# http://purl.org/neao/steps#ComputeComplexityDistribution + . + . + . + "A spike train synchrony analysis that computes the complexity distribution across a set of input spike trains that typically contain the activity of different neurons. In a neuronal population, the complexity represents the total number of neurons that were spiking within a discrete time interval. For the computation, the binarized population histogram (i.e., a spike time histogram computed across spike trains, where each bin will have the count of spike trains that had at least one spike within the bin interval) is obtained using a bin size specified as a parameter. The value at each bin is the complexity. The complexity distribution is obtained by finding the frequency of each complexity value (complexity histogram) and corresponding probability density function (PDF). The complexity PDF describes the likelihood of different complexity values occurring within the neuronal population."@en . + "compute complexity distribution"@en . +# +# http://purl.org/neao/steps#ComputeConfidenceIntervalBootstrap + . + . + . + "A confidence interval resampling analysis that computes the confidence interval using bootstrapping techniques to create many simulated samples (bootstrap samples). It involves repeatedly sampling, with replacement, from the input (observed) data. The total number of bootstrap samples is defined as a parameter. Bootstrapping makes minimal assumptions about the underlying distribution of the data, making it especially useful for small samples or when the data do not meet the assumptions of traditional parametric (non-resampling) methods."@en . + "compute confidence interval (bootstrap resampling)"@en . +# +# http://purl.org/neao/steps#ComputeConfidenceIntervalJackknife + . + . + "A confidence interval resampling analysis that computes the confidence interval using jackknife techniques. It involves systematically leaving out one observation at a time from the input (sample) set and calculating the statistic of interest on each of these \"leave-one-out\" samples. The confidence interval is computed based on statistics obtained from those jackknife samples. Jackknife is useful for small samples or when the data do not meet the assumptions of traditional parametric (non-resampling) methods."@en . + "compute confidence interval (jackknife resampling)"@en . +# +# http://purl.org/neao/steps#ComputeConfidenceIntervalNonResampling + . + . + . + "A confidence interval statistical analysis that computes the confidence interval assuming a statistical distribution of the input data, and uses measures of central tendency and dispersion obtained from the data points in the input(s) (e.g., mean and standard error of the mean when assuming a normal distribution). The computation relies on theoretical distributions and established statistical formulas."@en . + "compute confidence interval (non-resampling)"@en . +# +# http://purl.org/neao/steps#ComputeContinuousWaveletTransform + . + . + . + "compute CWT"@en . + "A wavelet transform analysis that convolves the input time series with scaled and translated versions of the mother wavelet. The scale parameter can be non-dyadic (i.e., can take values that are not powers of 2). The mother wavelet used is passed as a parameter, and several types can be used (e.g., Morlet, Mexican hat, Hermitian, Meyer, Poisson). The continuous wavelet transform (CWT) is ideal for analyzing non-stationary signals, with transient behavior, rapidly changing frequencies or slowly varying changes. It is comparable to the short-time Fourier transform (STFT)."@en . + "compute continuous wavelet transform"@en . +# +# http://purl.org/neao/steps#ComputeCorrectedImaginaryPhaseLockingValue + . + . + "compute ciPLV"@en . + . + "A phase locking value analysis that computes the corrected imaginary phase locking value (ciPLV), following the implementation from Bruña & Maestú (2018). It re-formulates the original phase locking value (PLV) for computational efficiency. The computation uses the imaginary part of the PLV, to make the metric insensitive to zero lag synchronizations (that can be the result of volume conduction)."@en . + "compute corrected imaginary phase locking value"@en . +# +# http://purl.org/neao/steps#ComputeCovariance + . + . + _:genid20 . +_:genid20 "true"^^ . +_:genid20 . +_:genid20 . + _:genid21 . +_:genid21 "false"^^ . +_:genid21 . +_:genid21 . + _:genid22 . +_:genid22 "true"^^ . +_:genid22 . +_:genid22 . + "A covariance analysis that computes the values of covariance in pairwise input data."@en . + "compute covariance"@en . +# +# http://purl.org/neao/steps#ComputeCrossCorrelationFunction + . + . + "compute CCF"@en . + "A cross-correlation analysis that computes an estimate of the cross-correlation function, i.e. the cross-correlation values of two time series inputs for a number of lags. The cross-correlation function shows temporal dependencies of the first input series with respect to the second. The value of the cross-correlation at a specific lag shows how similar the values in the first input series are to values in the second input at time points separated by a number of time units equal to that lag. The cross-correlation value of 0 indicates no correlation. The cross-correlation varies between 1 and -1 (positive and negative correlation, respectively)."@en . + "compute cross-correlation function"@en . +# +# http://purl.org/neao/steps#ComputeCrossCorrelationFunctionBiased + . + . + . + "compute CCF (biased)"@en . + "An analysis step that computes the biased estimator for the cross-correlation function. The biased estimator produces cross-correlation values that deviate from the true cross-correlation."@en . + "compute cross-correlation function (biased)"@en . +# +# http://purl.org/neao/steps#ComputeCrossCorrelationFunctionUnbiased + . + . + "compute CCF (unbiased)"@en . + . + "An analysis step that computes the unbiased estimator for the cross-correlation function, using the formula in Stoica & Moses (2005). The unbiased estimation uses a correction for the bias due to zero-padding in the computation, applied to the normalization coefficient. Therefore, the resultant cross-correlation values are closer to the true cross-correlation."@en . + "compute cross-correlation function (unbiased)"@en . +# +# http://purl.org/neao/steps#ComputeCrossPowerSpectralDensityMorletWavelet + . + . + "A cross power spectral density analysis that uses the Morlet wavelet transform to obtain the frequency information of the two inputs used to compute the cross power spectral density."@en . + "compute cross power spectral density (Morlet wavelet method)"@en . +# +# http://purl.org/neao/steps#ComputeCrossPowerSpectralDensityMultitaper + . + . + "compute CPSD (multitaper method)"@en . + . + "A cross power spectral density (CPSD) analysis that uses a multitaper approach to compute the CPSD, according to Thomson (1982). The multitaper method uses discrete prolate spheroidal functions (DPSS, also known as Slepian sequences) as tapers applied to the inputs. For the computation, a CPSD using the periodogram method is obtained for each pair of tapered signals. The DPSS functions are orthogonal, and therefore applying multiple DPSS tapers result in independent estimates of the CPSD. The final CPSD is obtained by averaging the CPSDs across all tapers. The multitaper method reduces variance and bias in the CPSD, and has a high frequency resolution. However, it is computationally expensive. The number of tapers used is passed as parameter, or estimated from the desired resolution."@en . + "compute cross power spectral density (multitaper method)"@en . +# +# http://purl.org/neao/steps#ComputeCrossPowerSpectralDensityPeriodogram + . + . + "compute CPSD (periodogram method)"@en . + "A cross power spectral density (CPSD) analysis that uses the periodogram method. For the computation, the discrete Fourier transform of each input is obtained and their cross-power spectrum is obtained. A window function can be applied to the inputs before the Fourier transform, to reduce spectral leakage. The final CPSD is obtained by normalizing the cross-power spectrum to the unit frequency using the equivalent noise bandwidth (a factor that depends on the coefficients of the window function and the sampling rate). If no window function is used or a window that does not attenuate the signal is used (e.g., Boxcar or rectangular window) the equivalent noise bandwidth is equal to the frequency resolution."@en . + "compute cross-periodogram"@en . + "compute cross power spectral density (periodogram method)"@en . +# +# http://purl.org/neao/steps#ComputeCrossPowerSpectralDensityWelch + . + . + "compute CPSD (Welch method)"@en . + . + "A cross power spectral density (CPSD) analysis that uses the method defined by Welch (1967). For the computation, the two inputs are divided into several overlapping segments (length and overlap passed as parameters, or computed for the desired frequency resolution based on the input length and sampling frequency). A window function (e.g., Hann) is applied to each segment, and the cross power spectral density using the periodogram method is computed. The final CPSD is obtained by averaging all the periodograms with the individual CPSDs."@en . + "compute cross power spectral density (Welch method)"@en . +# +# http://purl.org/neao/steps#ComputeCrossSpectrogramShortTimeFourierTransform + . + . + "compute cross-spectrogram (STFT method)"@en . + "A spectrogram analysis that computes a cross-spectrogram using the short-time Fourier transform (STFT). The cross-spectrogram is the time-resolved description of the power of a pair of distinct inputs across the different frequency components. This can be used to investigate how common activity between the two inputs is distributed across the frequency components, and how it varies over time."@en . + "compute cross-spectrogram (short-time Fourier transform method)"@en . +# +# http://purl.org/neao/steps#ComputeCubicAnalysis + . + . + . + "A spike train synchrony analysis that uses the Cumulant Based Inference of higher-order Correlation (CuBIC) test described in Staude et al. (2010). CuBIC is a statistical method to detect the presence of higher order correlations in parallel spike trains from a neuronal population (i.e., correlations among three or more neurons). It is based on the analysis of the cumulants of the population spike count. The test takes a population histogram as input data (i.e., a spike train time histogram computed across spike trains with the activity of distinct neurons). A null hypothesis that the third cumulant of the data is less than or equal to the maximized third cumulant for a correlation order is iteratively tested (with increasing orders of correlation). The output is the minimum correlation order necessary to explain the value of the third cumulant calculated from the population spike count, together with the p-values of the hypothesis tests performed."@en . + "compute CuBIC analysis"@en . +# +# http://purl.org/neao/steps#ComputeCurrentSourceDensityICSD + . + . + "compute iCSD"@en . + . + . + . + "A current source density (CSD) analysis that uses the inverse current source density (iCSD) estimation method described by Pettersen et al. (2006). The iCSD is based on the inversion of the electrostatic forward solution and can be applied to data obtained from electrodes with multiple configurations. The method can handle cases with spatially confined cortical activity and spatially varying extracellular conductivity.\n \nThree options for CSD estimation using the iCSD exist. The CSD is assumed to have cylindrical symmetry and follows one of three possible assumptions:\n1. is localized in infinitely thin discs;\n2. is step-wise constant;\n3. is continuous and smoothly varying (using cubic splines) in the vertical direction."@en . + "compute current source density (inverse method)"@en . +# +# http://purl.org/neao/steps#ComputeCurrentSourceDensityKCSD + . + . + "compute kCSD"@en . + . + "A current source density (CSD) analysis that uses kernel methods to compute the CSD (kCSD), described by Potworowski et al. (2012). kCSD is non parametric and can estimate the CSD using signals recorded from arbitrarily distributed electrodes, as the assumption of regular electrode placement is not necessary. The method can handle 1D, 2D or 3D electrode configurations. The kCSD can also estimate CSD at any location, as it is not limited to the electrode positions, and uses cross-validation to ensure no overfitting."@en . + "compute current source density (kernel method)"@en . +# +# http://purl.org/neao/steps#ComputeCurrentSourceDensityStandard + . + . + "compute CSD"@en . + . + . + "A current source density (CSD) analysis that uses a double spatial derivative of the recorded extracellular potentials to compute the CSD. The original method by Freeman & Nicholson (1975) assumes homogeneous cortical in-plane activity, constant extracellular electrical conductivity and equidistant electrode contacts, and can only predict the CSD at interior electrode positions. Vaknin et al. (1988) suggested a procedure to obtain the CSD for the first and last electrodes by copying the outmost recordings, therefore extending the grid beyond the electrode contacts. This is based on the assumption that the potential varies negligibly above the first and below the last electrode."@en . + "compute current source density (standard method)"@en . +# +# http://purl.org/neao/steps#ComputeDebiasedSquaredWeightedPhaseLagIndex + . + . + _:genid23 . +_:genid23 "false"^^ . +_:genid23 . +_:genid23 . + "compute debiased squared WPLI"@en . + . + "A phase lag index (PLI) analysis that computes the debiased squared weighted PLI (WPLI) following Vinck et al. (2011). The direct PLI estimator is positively biased, especially when the sample sizes (i.e., number of trials) are small. The debiased squared WPLI is computed by computing the imaginary components of the cross spectral densities, computing the average imaginary component of the cross spectral densities, and normalizing by the computed average over the magnitudes of the imaginary component of the cross spectral densities."@en . + "compute debiased squared weighted phase lag index"@en . +# +# http://purl.org/neao/steps#ComputeDirectedPhaseLagIndex + . + . + _:genid24 . +_:genid24 "true"^^ . +_:genid24 . +_:genid24 . + "compute DPLI"@en . + . + "A phase lag index (PLI) analysis that computes the directed PLI (DPLI) according to Stam & van Straaten (2012). The DPLI uses the Heaviside step function on the imaginary part of the cross power spectral density, and provides the ability to discriminate whether the first time series is leading or lagging the second. The DPLI ranges between 0 and 1. A DPLI value of 0.5 means that the first time series leads and lags the second time series equally often. A DPLI value greater than 0.5 means that the first time series leads the second more often than it lags. A value of 1 means that the first time series always leads. On the contrary, a DPLI value smaller than 0.5 means that the first time series lags the second more often than it leads. A DPLI value of zero means that the first time series always lags. The PLI can be computed from the DPLI."@en . + "compute directed phase lag index"@en . +# +# http://purl.org/neao/steps#ComputeDirectedTransferFunction + . + . + _:genid25 . +_:genid25 "true"^^ . +_:genid25 . +_:genid25 . + _:genid26 . +_:genid26 "true"^^ . +_:genid26 . +_:genid26 . + _:genid27 . +_:genid27 "true"^^ . +_:genid27 . +_:genid27 . + "compute DTF"@en . + . + "A functional connectivity analysis that computes the directed transfer function (DTF) according to Kaminski & Blinowska (1991). DTF can estimate the direction and frequency content of the brain activity flow. The DTF measure is obtained from the spectral transfer matrix computed from multivariate time series input data. For the DTF computation, the spectral transfer matrix is obtained from a multivariate autoregressive model. The DTF estimate is obtained by using a normalization factor computed by the sum along the rows of the spectral transfer matrix. The DTF can have values in the range from 0 to 1."@en . + "compute directed transfer function"@en . +# +# http://purl.org/neao/steps#ComputeEventRelatedPotential + . + . + "compute ERP"@en . + "An analysis step that computes the event-related potential (ERP). The ERP is the neural activity (e.g., local field potential or electroencephalogram voltages) around a presented stimulus or spontaneous behavioral event. Usually, the event is presented/occurs repeatedly across multiple trials, obtaining multiple event-related potential waveforms that can be averaged to cancel the noise."@en . + "compute event-related potential"@en . +# +# http://purl.org/neao/steps#ComputeEventTriggeredAverage + . + . + "A triggered average analysis that uses an event of interest such as an external stimulus (e.g., electrical, visual, auditory) or a spontaneous behavior (e.g., eye blink) as a trigger to average a signal. The output of the method will provide the average value of the signal around the time where each event occurred (event-triggered average)."@en . + "compute event-triggered average"@en . +# +# http://purl.org/neao/steps#ComputeFrequencyDomainConditionalGrangerCausality + . + . + _:genid28 . +_:genid28 "true"^^ . +_:genid28 . +_:genid28 . + . + . + . + "A conditional Granger causality (GC) analysis that computes the GC measures in the frequency domain."@en . + "compute frequency domain conditional Granger causality"@en . +# +# http://purl.org/neao/steps#ComputeFrequencyDomainPairwiseGrangerCausalityBrovelli + . + . + . + "A frequency domain pairwise Granger causality (GC) analysis that uses the parametric approach according to Brovelli et al. (2004). It uses an MVAR (multivariate autoregressive model) to obtain the coefficients used for the computation of the spectral transfer matrix needed for GC estimation according to the frequency domain GC formulation by Geweke (1982)."@en . + "compute frequency domain pairwise Granger causality (Brovelli method)"@en . +# +# http://purl.org/neao/steps#ComputeFrequencyDomainPairwiseGrangerCausalityDhamala + . + . + . + . + "A frequency domain pairwise Granger causality (GC) analysis that uses the non-parametric approach according to Dhamala et al. (2008). It is based on Fourier and wavelet transforms to obtain the spectral density matrix and the algorithm from Wilson (1972) for its factorization."@en . + "compute frequency domain pairwise Granger causality (Dhamala method)"@en . +# +# http://purl.org/neao/steps#ComputeFrequencyDomainPairwiseGrangerCausalityHafner + . + . + . + "A frequency domain pairwise Granger causality (GC) analysis that uses the parametric approach according to Hafner & Herwartz (2008). It uses a multivariate GARCH (generalized autoregressive conditional heteroskedasticity) model and constructs a Wald test on noncausality in variance. This is an alternative to methods based on the residuals of estimated univariate models. The Wald test has superior power properties."@en . + "compute frequency domain pairwise Granger causality (Hafner method)"@en . +# +# http://purl.org/neao/steps#ComputeFrequencyDomainPairwiseGrangerCausalityWen + . + . + . + "A frequency domain pairwise Granger causality (GC) analysis that uses the non-parametric approach according to Wen et al. (2013). It is a multivariate framework for estimating GC based on spectral density matrix factorization. The approach requires only a single estimation of the spectral density matrix for the entire dataset (e.g., multiple time series inputs). GC for the subsets (i.e., pairs of inputs) can then be calculated by factorizing the relevant submatrix of this overall spectral density matrix."@en . + "compute frequency domain pairwise Granger causality (Wen method)"@en . +# +# http://purl.org/neao/steps#ComputeISIDistance + . + . + . + "A time-scale independent spike train distance analysis that computes the ISI-distance, described in Kreuz et al. (2007). For the computation, the discrete sequence of spike times is transformed into a continuous temporal profile with one value per sample point. The values at each time point are derived from the interspike intervals. The distance is then obtained as the temporal average of the time profile. ISI-distance is well-designed to describe similarities in the firing rate profile of the input spike trains, but it is not optimal to capture neuronal synchrony."@en . + "compute ISI-distance"@en . +# +# http://purl.org/neao/steps#ComputeImaginaryCoherency + . + . + . + "A coherency analysis that computes the imaginary part of the coherency for two inputs according to Nolte et al. (2004). For the computation, the imaginary part of the complex-valued cross power spectral density obtained for the two inputs is normalized by the square root of the product of their power spectral densities (i.e., auto spectral densities). If the inputs contain multi-epoch data (e.g., multiple trial repetitions), the cross and auto spectral densities are averaged across epochs. The imaginary part of the coherency is less affected by volume conduction than the (complex) coherency."@en . + "compute imaginary coherency"@en . +# +# http://purl.org/neao/steps#ComputeInstantaneousFiringRateInterspikeInterval + . + . + "An instantaneous firing rate analysis that computes the instantaneous firing rate by using the reciprocal of the interspike intervals."@en . + "compute instantaneous firing rate (interspike interval method)"@en . +# +# http://purl.org/neao/steps#ComputeInstantaneousFiringRateKernelDensityEstimation + . + . + "An instantaneous firing rate analysis that computes the instantaneous firing rate by convolution of spike times with a kernel function. The output of the computation is a weighted average of the spikes around the kernel."@en . + "compute instantaneous firing rate (kernel smoothing method)"@en . + "compute instantaneous firing rate (kernel density estimation method)"@en . +# +# http://purl.org/neao/steps#ComputeInstantaneousFiringRateLocalRegression + . + . + . + "An instantaneous firing rate analysis that computes the instantaneous firing rate using local regression methods. The estimation procedure approximates the log of the firing rate using a low-order polynomial within a moving window (local neighborhood)."@en . + "compute instantaneous firing rate (local regression method)"@en . +# +# http://purl.org/neao/steps#ComputeInterquartileRange + . + . + "compute IQR"@en . + "A dispersion statistical analysis that computes the interquartile range (IQR). The IQR is the difference between the 75th and 25th percentiles (i.e., the range within which the central 50% of the data points lie)."@en . + "compute interquartile range"@en . +# +# http://purl.org/neao/steps#ComputeInterspikeIntervalHistogram + . + . + "compute ISIH"@en . + "An interspike interval analysis that computes the histogram of interspike intervals. For the computation, a time interval with fixed duration starting from zero is discretized into smaller intervals (bins). The count of input interspike intervals whose values fall into each bin is obtained. Therefore, the output contains a representation of the distribution of the interspike intervals in the input."@en . + "compute interspike interval histogram"@en . +# +# http://purl.org/neao/steps#ComputeInterspikeIntervals + . + . + "compute ISIs"@en . + "An interspike interval analysis that computes the intervals between successive spikes in a spike train (interspike intervals; ISIs)."@en . + "compute interspike intervals"@en . +# +# http://purl.org/neao/steps#ComputeJointPeristimulusTimeHistogram + . + . + _:genid29 . +_:genid29 . +_:genid29 . +_:genid29 . + _:genid30 . +_:genid30 "true"^^ . +_:genid30 . +_:genid30 . + _:genid31 . +_:genid31 "false"^^ . +_:genid31 . +_:genid31 . + _:genid32 . +_:genid32 "true"^^ . +_:genid32 . +_:genid32 . + "compute JPSTH"@en . + . + . + "A spike train synchrony analysis that computes the joint peristimulus time histogram (JPSTH) from trial-by-trial spike train inputs obtained from two different neurons, after the repeated presentation of a stimulus. The JPSTH provides a representation of the timing relationship between the firing of the two neurons in response to the stimulus. It combines the peristimulus time histograms (PSTHs) of each neuron to illustrate how their firing rates co-vary over time relative to the stimulus event. This helps in understanding the temporal correlation between the neurons.\n\nThe computation can produce three outputs: \n\n* the JPSTH matrix (i.e., a matrix whose bins contain the counts of coincidences in the firing of the two neurons);\n* the peristimulus coincidence histogram (i.e., a histogram obtained from a cross-section along the main diagonal of the JPSTH matrix);\n* the cross-correlation histogram computed by summing the bins along the main and each paradiagonal of the JPSTH matrix (after normalizing by the bin length, as the paradiagonals in the JPSTH matrix are of different lengths)."@en . + "compute joint peristimulus time histogram"@en . +# +# http://purl.org/neao/steps#ComputeLV + . + . + "compute LV"@en . + . + "An interspike interval variability analysis that computes the local variation (LV) of the interspike intervals. LV reflects the stepwise variability of a sequence of spikes, and is able to extract the spiking characteristics of individual neurons even in the presence of external modulations of the firing rate."@en . + "compute local variation"@en . +# +# http://purl.org/neao/steps#ComputeLVR + . + . + "compute LvR"@en . + . + "An interspike interval variability analysis that computes the revised local variation (LvR) of interspike intervals. Compared to the original local variation (LV) measure, LvR has better invariance to fluctuations in the firing rate fluctuations. This is achieved by using a refractoriness constant in the computation of the measure."@en . + "compute revised local variation"@en . +# +# http://purl.org/neao/steps#ComputeMaximizedImaginaryCoherency + . + . + "compute MIC"@en . + . + "A coherency analysis that computes the maximized imaginary coherency (MIC) according to Ewald et al. (2012). The computation uses an eigenvalue-based optimization to find weight vectors that maximize the imaginary part of coherency computed between virtual channels derived from the input data. The weights are optimized for each frequency component. After the weights are obtained, the final MIC measure is obtained for each frequency."@en . + "compute maximized imaginary coherency"@en . +# +# http://purl.org/neao/steps#ComputeMean + . + . + "A central tendency statistical analysis that computes the mean of the input data. The mean is the arithmetic average of all data points."@en . + "compute mean"@en . +# +# http://purl.org/neao/steps#ComputeMeanFiringRate + . + . + "compute MFR"@en . + "A firing rate analysis that computes the mean firing rate, defined as the number of spikes in a time interval divided by the duration of the interval. The mean firing rate is the temporal average of the neuronal activity over that interval."@en . + "compute mean firing rate"@en . +# +# http://purl.org/neao/steps#ComputeMeanPhaseVector + . + . + "A phase analysis that computes the mean among two or more input phases. For the computation, the input phases are represented as vectors in the unit circle, and the mean phase vector is computed. The analysis can return the mean phase vector (i.e., angle and length), the vector angle, or the vector length."@en . + "compute mean phase vector"@en . +# +# http://purl.org/neao/steps#ComputeMeanVectorLengthCanolty + . + . + . + "compute MVL (Canolty method)"@en . + . + "A mean vector length (MVL) analysis that computes the mean vector length as described in Canolty et al. (2006). For the computation, phase is extracted from the low-frequency analytic signal, and amplitude is extracted from the high-frequency analytic signal. The phase angle and magnitude is used to define a complex-valued time series, and each complex value is a vector in the polar plane. Averaging all vectors yields a mean vector whose length indicates the coupling strength and whose direction indicates the phase where amplitude is strongest. Without coupling, the vectors cancel out, resulting in a short mean vector without meaningful phase direction. If phase-amplitude coupling exists, the magnitude of a subset of vectors is especially high at a specific phase or narrow phase range."@en . + "compute mean vector length (Canolty method)"@en . +# +# http://purl.org/neao/steps#ComputeMeanVectorLengthOzkurt + . + . + "compute MVL (Özkurt method)"@en . + . + "A mean vector length (MVL) analysis that computes the MVL as described in Özkurt & Schnitzler (2011). The original MVL (Canolty et al., 2006) may be affected by factors in the input data (e.g., amplitude outliers or non-uniform distribution of phase angles). This computation estimates a direct MVL that is amplitude-normalized to obtain values in the 0 to 1 range, and that takes care of possible amplitude differences in the raw data."@en . + "compute mean vector length (Özkurt method)"@en . +# +# http://purl.org/neao/steps#ComputeMedian + . + . + "A central tendency statistical analysis that computes the median of the input data. The median is the middle value when data points are arranged in ascending order (i.e., it divides the data points in two equal halves, with 50% of the data points below it and 50% above it). If there is an even number of data points, the median is the average of the two middle values."@en . + "compute median"@en . +# +# http://purl.org/neao/steps#ComputeModulationIndex + . + . + "compute MI"@en . + . + "A phase-amplitude coupling (PAC) analysis that computes the modulation index (MI) as described in Tort et al. (2010). For the computation, the Hilbert transform is used to obtain the instantaneous phase from the input time series with the low-frequency oscillation, and the instantaneous amplitude from the input time series with the high-frequency oscillation. The phase of the low-frequency oscillation is discretized into bins and the amplitude of the high-frequency oscillation is averaged within each bin to create a distribution. This distribution is then compared to a uniform distribution using the Kullback-Leibler divergence, normalized by the maximum possible divergence, resulting in the MI."@en . + "compute modulation index"@en . +# +# http://purl.org/neao/steps#ComputeMorletWaveletTransform + . + . + "A wavelet transform analysis based on the complex-valued Morlet wavelet. The transform can be performed either in the time domain (by convolution) or in the frequency domain (by multiplication)."@en . + "compute Morlet wavelet transform"@en . +# +# http://purl.org/neao/steps#ComputeMorletWaveletTransformLeVanQuyen + . + . + . + . + "A wavelet transform analysis using the Morlet wavelet where the parametrization of the mother wavelet is done according to Le Van Quyen et al. (2001). The size of the mother wavelet is determined in number of cycles to control the frequency and temporal resolutions (approximate number of oscillation cycles within a wavelet)."@en . + "compute Morlet wavelet transform (Le Van Quyen method)"@en . +# +# http://purl.org/neao/steps#ComputeMorletWaveletTransformTallonBaudry + . + . + . + "A wavelet transform analysis using the Morlet wavelet based on the methods described in Tallon-Baudry et al. (1997). The ratio of the central frequency to the spectral bandwidth is 7, with central frequencies ranging from 20 to 100 Hz in 1 Hz steps. This resulted in varying time/frequency resolution across the spectrum: time resolution increases with frequency, while frequency resolution decreases."@en . + "compute Morlet wavelet transform (Tallon-Baudry method)"@en . +# +# http://purl.org/neao/steps#ComputeMultivariateInteractionMeasure + . + . + "compute MIM"@en . + . + "A functional connectivity analysis that computes the multivariate interaction measure (MIM) as defined by Ewald et al. (2012). MIM is constructed from the maximization of imaginary coherency."@en . + "compute multivariate interaction measure"@en . +# +# http://purl.org/neao/steps#ComputeMutualInformation + . + . + _:genid33 . +_:genid33 "true"^^ . +_:genid33 . +_:genid33 . + _:genid34 . +_:genid34 "false"^^ . +_:genid34 . +_:genid34 . + _:genid35 . +_:genid35 "false"^^ . +_:genid35 . +_:genid35 . + _:genid36 . +_:genid36 "true"^^ . +_:genid36 . +_:genid36 . + "compute MI"@en . + . + "A functional connectivity analysis that computes a mutual information (MI) measure. MI is based on Shannon information theory, and quantifies the amount of information from one input that is obtained from another input. Therefore, it can be used to determine how the neuronal activity provides information about a variable (e.g., behavioral stimulus) or how the information flows between different brain regions or neurons. The MI is measured in bits."@en . + "compute mutual information"@en . +# +# http://purl.org/neao/steps#ComputeNeuronalPopulationVector + . + . + . + "An analysis step that computes the neuronal population vector, used to describe the collective activity of a group of neurons. The neuronal population vector is obtained taking as inputs the multiple responses of a neuronal population in the context of distinct values of a behavioral measure (e.g., tuning curves showing the response of each individual neuron to different arm movement directions in the 2-D space). The analysis step obtains a weighted vectorial sum of the neural activities, which will result in an estimate of the behavioral measure considering the collective activity of the population (e.g., the movement direction given the neuronal activity)."@en . + "compute population vector"@en . + "compute neuronal population vector"@en . +# +# http://purl.org/neao/steps#ComputeNoiseCorrelations + . + . + "compute NC"@en . + . + "A spike train correlation analysis that computes the noise correlations (NC) between two input spike trains. The NC is the Pearson's correlation coefficient of spike count responses to repeated presentations of identical stimuli, under the same behavioral conditions. The spike counts are typically measured over the time scale of a stimulus presentation or a behavioral trial, which range from a few hundred milliseconds to several seconds. NC assesses whether neurons exhibit trial-by-trial fluctuations in firing rates that are not influenced by varying sensory or behavioral conditions."@en . + "compute noise correlations"@en . +# +# http://purl.org/neao/steps#ComputeNoiseCovariance + . + . + _:genid37 . +_:genid37 "true"^^ . +_:genid37 . +_:genid37 . + _:genid38 . +_:genid38 "false"^^ . +_:genid38 . +_:genid38 . + _:genid39 . +_:genid39 "true"^^ . +_:genid39 . +_:genid39 . + "A covariance analysis that computes the noise covariance, i.e., how much two noise signals vary together. The noise data inputs can be non-subject recordings (e.g., recordings from the empty experimental room) or are obtained from periods without stimulation or meaningful experimental manipulations (e.g., prestimulus intervals). These reflect random variations or disturbances that are not part of the actual signal or data of interest."@en . + "compute noise covariance"@en . +# +# http://purl.org/neao/steps#ComputeOptimalBinSize + . + . + . + "An analysis step that finds the optimal bin size considering the input data when discretizing data into smaller intervals (bins). The computation uses the formula from Scott (1979)."@en . + "compute optimal bin size"@en . +# +# http://purl.org/neao/steps#ComputeOptimalKernelBandwidth + . + . + . + "An analysis step that computes the optimal fixed bandwidth (width) for a Gaussian kernel used for the estimation of the firing rate using kernel density estimation. The analysis step uses the input spike train for which the firing rate will be computed, and follows the implementation by Shimazaki & Shinomoto (2010)."@en . + "compute optimal kernel bandwidth"@en . +# +# http://purl.org/neao/steps#ComputeOrthogonalizedPowerEnvelopeCorrelation + . + . + . + "A functional connectivity analysis that computes the orthogonalized power envelope correlation, according to Hipp et al. (2012). This method relies on correlations between the instantaneous amplitudes of cross-region input signals (power envelopes). The instantaneous amplitudes of the two input time series are orthogonalized aiming to remove spurious correlations of signal power (e.g., due to limited spatial resolution of electrophysiological measures)."@en . + "compute orthogonalized power envelope correlation"@en . +# +# http://purl.org/neao/steps#ComputePairwisePhaseConsistency + . + . + _:genid40 . +_:genid40 . +_:genid40 . +_:genid40 . + _:genid41 . +_:genid41 . +_:genid41 . +_:genid41 . + _:genid42 . +_:genid42 . +_:genid42 . +_:genid42 . + _:genid43 . +_:genid43 "true"^^ . +_:genid43 . +_:genid43 . + _:genid44 . +_:genid44 "true"^^ . +_:genid44 . +_:genid44 . + _:genid45 . +_:genid45 "true"^^ . +_:genid45 . +_:genid45 . + _:genid46 . +_:genid46 "true"^^ . +_:genid46 . +_:genid46 . + "compute PPC"@en . + . + "A phase analysis that computes the pairwise phase consistency (PPC) measure according to Vinck et al. (2010). The PPC quantifies the distribution of phase differences across the inputs, but is less biased by the number of observations in comparison to the phase locking value (PLV). For the computation, the phase difference (angular distance) is obtained for all pairs of observations in the input (that can be represented as vectors in the unit circle, where the angle is the relative phase). The cosine of the angular distance (an estimate of the dot product of the vectors corresponding to each element in a pair) is computed for every pair, and the PPC estimate is obtained from the average of all pairwise dot products. With phase synchronization, the distribution of the pairwise dot products is centered around an average value, while without synchronization it will be distributed across the unit circle. The PPC provides an unbiased estimate of the squared PLV."@en . + "compute pairwise phase consistency"@en . +# +# http://purl.org/neao/steps#ComputePartialCoherence + . + . + . + "A coherence analysis that computes the partial coherence, i.e., the coherence value between a pair of inputs (e.g., time series with recordings from two distinct electrode channels) after removing the influence of one or more additional inputs (e.g., the time series with the recordings from all remaining channels). The partial coherence is computed according to Rosenberg et al. (1998). The partial coherence reflects the linear association in the frequency domain (for each frequency component) between the pair of inputs of interest, removing spurious coherence caused by confounding factors such as shared inputs to the pair of interest or volume conduction."@en . + "compute partial coherence"@en . +# +# http://purl.org/neao/steps#ComputePartialDirectedCoherence + . + . + _:genid47 . +_:genid47 . +_:genid47 . +_:genid47 . + _:genid48 . +_:genid48 "true"^^ . +_:genid48 . +_:genid48 . + _:genid49 . +_:genid49 "true"^^ . +_:genid49 . +_:genid49 . + _:genid50 . +_:genid50 "true"^^ . +_:genid50 . +_:genid50 . + "compute PDC"@en . + . + "A coherence analysis that computes the partial directed coherence (PDC) according to Baccalá & Sameshima (2001). The PDC describes the relationships between multivariate time series inputs (direction of information flow). To compute the PDC, the multivariate partial coherences obtained from multivariate autoregressive models are decomposed. The PDC reflects a frequency-domain representation of the concept associated with Granger causality."@en . + "compute partial directed coherence"@en . +# +# http://purl.org/neao/steps#ComputePeristimulusTimeHistogramAdaptiveKernelSmoothing + . + . + "compute PSTH (adaptive kernel smoothing)"@en . + "A peristimulus time histogram (PSTH) analysis that computes the PSTH using kernel density smoothing with an adaptive kernel width. The adaptive kernel is obtained by first computing the PSTH with a fixed-width kernel, and then modifying the kernel width in order to have a constant but time-dependent average number of spikes under the kernel (i.e., segments of the data with a high density of spikes will have a reduced kernel width)."@en . + "compute peristimulus time histogram (adaptive kernel smoothing)"@en . +# +# http://purl.org/neao/steps#ComputePeristimulusTimeHistogramFixedKernelSmoothing + . + . + "compute PSTH (fixed kernel smoothing)"@en . + "A peristimulus time histogram (PSTH) analysis that computes the PSTH using kernel density smoothing with a fixed kernel width specified as parameter."@en . + "compute peristimulus time histogram (fixed kernel smoothing)"@en . +# +# http://purl.org/neao/steps#ComputePeristimulusTimeHistogramOptimalBinSize + . + . + . + "compute PSTH (optimal bin size)"@en . + "A peristimulus time histogram (PSTH) analysis that computes the PSTH finding the optimal bin size from the input spike train data, using the formula from Scott (1979)."@en . + "compute peristimulus time histogram (optimal bin size)"@en . +# +# http://purl.org/neao/steps#ComputePeristimulusTimeHistogramUserSelectedBinSize + . + . + "compute PSTH (user-selected bin size)"@en . + "A peristimulus time histogram (PSTH) analysis that computes the PSTH using a fixed bin size specified as a parameter."@en . + "compute peristimulus time histogram (user-selected bin size)"@en . +# +# http://purl.org/neao/steps#ComputePhaseDifference + . + . + "A phase analysis that computes the difference between two input phases."@en . + "compute phase difference"@en . +# +# http://purl.org/neao/steps#ComputePhaseLagIndex + . + . + _:genid51 . +_:genid51 "false"^^ . +_:genid51 . +_:genid51 . + "compute PLI"@en . + . + "A phase lag index (PLI) analysis that computes the PLI following Stam et al. (2007). The input data contains multiple repetitions of a pair of signals (e.g., time series with recordings from a pair of electrodes across multiple trials). For each repetition, the sign of the phase differences between the two time series is obtained from the imaginary part of the cross power spectral density (CPSD). The PLI value is the absolute value of the average of the signs of all repetitions. The PLI ranges between 0 and 1. A PLI of zero means that the first time series leads the second equally often (i.e., indicates either no coupling or coupling with a phase difference centered around 0 mod π, which could be from common sources such as volume conduction). A value greater than zero means an imbalance in the likelihood of the first time series to be either leading or lagging the second time series. A PLI of 1 indicates perfect phase locking, and that the first time series only leads or only lags (at a value of phase differences different from 0 mod π)."@en . + "compute phase lag index"@en . +# +# http://purl.org/neao/steps#ComputePhaseLockingValue + . + . + "compute PLV"@en . + . + "A phase locking value (PLV) analysis that computes the PLV value as originally described by Lachaux et al. (1999). The input data is a set of pairs of time series (e.g., the trial-by-trial local field potential recorded from two different electrodes). For each time series pair, the instantaneous phase is obtained (e.g., using the Hilbert transform or wavelet decomposition), and the phase difference for each time point is obtained. The PLV value is computed by averaging the complex phase differences across all pairs, obtaining one PLV value per time point. The PLV ranges from 0 to 1. A PLV of 1 indicates perfect phase locking, meaning the phase difference between the two time series is constant over time. A PLV of 0 indicates no phase locking, meaning the phase difference is randomly distributed over time."@en . + "compute phase locking value"@en . +# +# http://purl.org/neao/steps#ComputePhaseSlopeIndex + . + . + _:genid52 . +_:genid52 . +_:genid52 . +_:genid52 . + _:genid53 . +_:genid53 "true"^^ . +_:genid53 . +_:genid53 . + _:genid54 . +_:genid54 "true"^^ . +_:genid54 . +_:genid54 . + _:genid55 . +_:genid55 "true"^^ . +_:genid55 . +_:genid55 . + _:genid56 . +_:genid56 "true"^^ . +_:genid56 . +_:genid56 . + "compute PSI"@en . + . + "A functional connectivity analysis that computes the phase slope index (PSI) according to Nolte et al. (2008). The PSI is based on the slope of the phase of the cross-spectral density between two time series inputs, considering how the phase difference between two signals changes as you move from one frequency bin to the next. It is computed from the complex-valued coherency using a bandwidth specified as parameter. For the computation, the change in phase difference between neighboring frequency bins is obtained (considering the specified bandwidth) and weighted. The PSI value deviates from zero when the phase difference changes consistently across frequencies and there is substantial coherence. The sign of the PSI indicates the temporal order of the two signals (i.e., which signal is leading the other one)."@en . + "compute phase slope index"@en . +# +# http://purl.org/neao/steps#ComputePopulationHistogram + . + . + . + "A spike train time histogram analysis that computes a histogram across two or more spike trains that contain the activity of different neurons (i.e., a neuronal population), recorded at fully-overlapping time intervals. The activity in each histogram bin reflects the combined activity of the population at that time, and the distribution of the histogram corresponds to the population activity over time."@en . + "compute population histogram"@en . +# +# http://purl.org/neao/steps#ComputePowerSpectralDensityBartlett + . + . + "compute PSD (Bartlett method)"@en . + . + "A power spectral density (PSD) analysis that uses the method defined by Bartlett (1950). For the computation, the input time is divided into non-overlapping segments, with length specified as a parameter. A periodogram is computed for each segment to obtain the single-segment PSD. The final PSD is obtained by averaging all the single-segment PSDs. A window function can be applied to each segment before computing the periodograms. The PSD obtained with the Bartlett method is less noisy than a single periodogram obtained from the entire signal, although the frequency resolution of the estimates is reduced due to segmenting. It is equivalent to the Welch method without any segment overlap."@en . + "compute power spectral density (Bartlett method)"@en . +# +# http://purl.org/neao/steps#ComputePowerSpectralDensityMultitaper + . + . + "compute PSD (multitaper method)"@en . + . + "A power spectral density (PSD) analysis that uses a multitaper approach to compute the PSD, according to Thomson (1982). The multitaper method uses discrete prolate spheroidal functions (DPSS, also known as Slepian sequences) as tapers applied to the input signal. For the computation, a PSD using the periodogram method is obtained for each tapered signal. The DPSS functions are orthogonal, and therefore applying multiple DPSS tapers result in independent estimates of the PSD. The final PSD is obtained by averaging the periodograms across all tapers. The multitaper method reduces variance and bias in the PSD, and has a high frequency resolution. However, it is computationally expensive. The number of tapers used is passed as parameter, or estimated from the desired resolution."@en . + "compute power spectral density (multitaper method)"@en . +# +# http://purl.org/neao/steps#ComputePowerSpectralDensityPeriodogram + . + . + "compute PSD (periodogram method)"@en . + "A power spectral density (PSD) analysis that uses the periodogram method. For the computation, the discrete Fourier transform is applied to the full length of the input, and the power spectrum is obtained. To reduce spectral leakage, a window function can be applied to the input before the computation of the Fourier transform (this is referred as the modified periodogram). The power spectrum is then normalized to the unit frequency, using the equivalent noise bandwidth (a factor that depends on the coefficients of the window function and the sampling rate). If no window function is used or a window that does not attenuate the signal is used (e.g., Boxcar or rectangular window) the equivalent noise bandwidth is equal to the frequency resolution. The PSD using the periodogram is computationally simple to obtain."@en . + "compute FFT power spectral density"@en . + "compute periodogram"@en . + "compute power spectral density (periodogram method)"@en . +# +# http://purl.org/neao/steps#ComputePowerSpectralDensityWelch + . + . + "compute PSD (Welch method)"@en . + . + "A power spectral density (PSD) analysis that uses the method defined by Welch (1967). For the computation, the input is divided into several overlapping segments (length and overlap passed as parameters, or computed for the desired frequency resolution based on the input length and sampling frequency). A window function (e.g., Hann) is applied to each segment, and a periodogram is computed to obtain the PSD for the segment. The final PSD is obtained by averaging all the periodograms with the single-segment PSDs. If there is no overlap between segments, this is equivalent to the Bartlett method."@en . + "compute power spectral density (Welch method)"@en . +# +# http://purl.org/neao/steps#ComputeRateChangeDetectionMultipleFilterTest + . + . + . + "An analysis step that uses the change point detection algorithm from Messer et al. (2014) to determine if a input spike train has constant firing rate (stationary) or has one or more points in which the firing rate decreases or increases (change point). In the latter case, the spike train is considered non-stationary. The analysis step outputs one or more change points in the case of non-stationarity."@en . + "compute rate change detection multiple filter test"@en . +# +# http://purl.org/neao/steps#ComputeRectifiedAreaUnderCurve + . + . + "compute RAUC"@en . + "An analysis step that computes the rectified area under the curve (RAUC). For the computation, the input signal is rectified (i.e., the absolute value is obtained) and the area under the curve is computed by integration using the composite trapezoidal rule."@en . + "compute rectified area under the curve"@en . +# +# http://purl.org/neao/steps#ComputeRegularizedCovariance + . + . + "A covariance analysis where the computation of the covariance values incorporates regularization techniques to improve the numerical stability, especially if the number of samples is small."@en . + "compute regularized covariance"@en . +# +# http://purl.org/neao/steps#ComputeSPIKEDistance + . + . + . + "A time-scale independent spike train distance analysis that computes the SPIKE-distance, described in Kreuz et al. (2012). For the computation, the discrete sequence of spike times is transformed in a continuous temporal profile with one value per sample point. The values at each time point are derived from the differences in the spike times of the two input spike trains. Compared to the ISI-distance, the SPIKE-distance is more sensitive to spike timing."@en . + "compute SPIKE distance"@en . +# +# http://purl.org/neao/steps#ComputeSPIKESynchronization + . + . + . + "A time-scale independent spike train distance analysis that computes the SPIKE synchronization distance, described in Kreuz et al. (2015). The distance detects coincidences in the spiking activity and can quantify the degree of synchrony in the input spike trains. The metric quantifies the overall fraction of coincidences. It is zero-valued if and only if the input spike trains do not contain any coincidences. It has a value of 1 if and only if each spike in every input spike train has one matching spike in all the other spike trains."@en . + "compute SPIKE synchronization"@en . +# +# http://purl.org/neao/steps#ComputeShortTimeFourierTransform + . + . + "compute STFT"@en . + "A time-frequency analysis that computes the short-time Fourier transform (STFT) of the input time series. The analysis divides the input time-domain signal into short segments with equal time and computes the Fourier transform for each segment. The output is a sequence of coefficients of complex sinusoids, each representing a frequency component in the input signal at a distinct time segment. Therefore, this provides the the time-localized frequency and phase information of the input. The segments can be windowed using a window function."@en . + "compute short-time Fourier transform"@en . +# +# http://purl.org/neao/steps#ComputeSpectrogramMorletWavelet + . + . + "A spectrogram analysis that uses the Morlet wavelet transform on the input to obtain the time-frequency information used to build the spectrogram."@en . + "compute spectrogram (Morlet wavelet method)"@en . +# +# http://purl.org/neao/steps#ComputeSpectrogramMultitaper + . + . + "A spectrogram analysis that uses a multitaper approach to obtain the time-frequency information from the input and that is used to build the spectrogram."@en . + "compute spectrogram (multitaper method)"@en . +# +# http://purl.org/neao/steps#ComputeSpectrogramShortTimeFourierTransform + . + . + "compute spectrogram (STFT method)"@en . + "A spectrogram analysis that uses the short-time Fourier transform (STFT) on the input to obtain the time-frequency information used to build the spectrogram."@en . + "compute spectrogram (short-time Fourier transform method)"@en . +# +# http://purl.org/neao/steps#ComputeSpikeContrast + . + . + . + "A spike train synchrony analysis that computes the Spike-contrast measure using the method described by Ciba et al. (2018). Spike-contrast is a time-scale independent measure of spike synchrony. The input is a set of parallel spike train data recorded from a population of neurons. The algorithm is based on the temporal \"contrast\" (activity vs. non-activity in certain time bins). The computation outputs a single synchrony value (comparable to a spike train distance) and a synchrony curve showing the value of Spike-contrast as a function of the bin size."@en . + "compute Spike-contrast"@en . +# +# http://purl.org/neao/steps#ComputeSpikeFieldCoherenceFries + . + . + . + "A spike-field coherence analysis that uses the method described in Fries et al. (2001) to compute the coherence between the spike train and the LFP. For the computation, first a spike-triggered average (STA) is obtained between the spike train and the LFP time series. Then, the power spectrum is obtained for each of the LFP segments used for the computation of the STA. These spectra are averaged to obtain the spike-triggered power spectrum. The SFC is then computed as the ratio of the power spectrum of the STA over the spike-triggered power spectrum."@en . + "compute spike-field coherence (Fries method)"@en . +# +# http://purl.org/neao/steps#ComputeSpikeFieldCoherenceMultitaper + . + . + "compute SFC (multitaper method)"@en . + "A spike-field coherence analysis that uses a multitaper approach to compute the coherence between the spike train and the LFP."@en . + "compute spike-field coherence (multitaper method)"@en . +# +# http://purl.org/neao/steps#ComputeSpikeFieldCoherenceWelch + . + . + "compute SFC (Welch method)"@en . + . + "A spike-field coherence analysis step that uses the method by Welch (1967) to compute the coherence between the spike train and the LFP."@en . + "compute spike-field coherence (Welch method)"@en . +# +# http://purl.org/neao/steps#ComputeSpikeTimeTilingCoefficient + . + . + "compute STTC"@en . + . + "A spike train correlation analysis that computes the spike time tiling coefficient (STTC) as described by Cutts and Eglen (2014). The STTC measures the pairwise correlation between two input spike trains, and has advantages over the related correlation index: it is not confounded by the firing rate, it distinguishes lack of correlation from anti-correlation, periods without neural activity don't add to the correlation, and it is sensitive to firing patterns. The computation is based on a synchronicity window parameter, that is used to define short time windows around each spike that are used in the computation (spike time tiling)."@en . + "compute spike time tiling coefficient"@en . +# +# http://purl.org/neao/steps#ComputeSpikeTrainAutocorrelationHistogram + . + . + "An autocorrelation analysis that computes the autocorrelation histogram for a input spike train. The histogram is obtained by sliding a time window that is discretized into smaller time intervals (bins) centered on a spike (corresponding to the lag zero). The spike count in each bin is obtained. Therefore, this binning process measures the number of spikes occurring at various time lags relative to the center spike. The histogram window is slidden over each spike in the input spike train, and the spike count in each bin is accumulated to produce the autocorrelation histogram output. The width of the bin interval is controlled by a parameter."@en . + "compute spike train autocorrelation histogram"@en . +# +# http://purl.org/neao/steps#ComputeSpikeTrainAutocorrelationTimeScale + . + . + . + "An analysis step that computes the autocorrelation time of a binned spike train input (spike train autocorrelation time scale). The computation follows the method described by Wieland et al. (2015)."@en . + "compute spike train autocorrelation time scale"@en . +# +# http://purl.org/neao/steps#ComputeSpikeTrainCrossCorrelationHistogram + . + . + _:genid57 . +_:genid57 . +_:genid57 . +_:genid57 . + "compute CCH"@en . + "A cross-correlation analysis that computes the cross-correlation histogram (CCH) for a pair of input spike trains. The CCH shows how often spikes in the reference spike train occur before or after spikes in the reference spike train, at distinct lag intervals. For the computation, the spike trains are aligned in time. The histogram is obtained by sliding a time window that is discretized into smaller time intervals (bins) centered on a spike of the first (reference) input spike train (corresponding to the lag zero). The spike count of the second (target) spike train input is then obtained in each bin. Therefore, this binning process measures the number of spikes in the target spike train occurring at various time lags relative to the spikes in the reference spike train. The histogram window is slidden over each spike in the reference spike train, and the spike count in each bin is accumulated to produce the CCH output. The width of the bin interval is controlled by a parameter."@en . + "compute correlogram"@en . + "compute cross-correlogram"@en . + "compute spike train cross-correlation histogram"@en . +# +# http://purl.org/neao/steps#ComputeSpikeTrainCrossCorrelationHistogramEggermont + . + . + "compute CCH (Eggermont method)"@en . + . + "A computation of the cross-correlation histogram (CCH) for a pair of binned input spike trains using the method described in Eggermont (2010). The formula is valid for binned spike train inputs with at most one spike per bin, and returns the cross-correlation coefficient for the lags considered (range -1 to 1)."@en . + "compute correlogram (Eggermont method)"@en . + "compute cross-correlogram (Eggermont method)"@en . + "compute spike train cross-correlation histogram (Eggermont method)"@en . +# +# http://purl.org/neao/steps#ComputeSpikeTrainFanoFactor + . + . + _:genid58 . +_:genid58 . +_:genid58 . +_:genid58 . + . + "An analysis step that computes the Fano factor (FF) for a set of input spike trains. For each input spike train, the spike count is obtained. The Fano factor is defined as the ratio of the variance of the spike count to the mean spike count, across all spike trains. The Fano factor is usually computed for spike trains representing the activity of the same neuron over different trials. The value is interpreted as the higher the Fano factor value, the larger the cross-trial non-stationarity. For a stationary Poisson process, the Fano factor has value equal to 1."@en . + "compute spike train Fano factor"@en . +# +# http://purl.org/neao/steps#ComputeSpikeTrainPearsonCorrelationCoefficient + . + . + "A spike train correlation analysis that computes the Pearson correlation coefficient between two spike train inputs. The Pearson correlation coefficient is a real value that quantifies the linear relationship between the two spike trains. It has range [-1, 1], where 1 indicates a perfect positive linear relationship, -1 indicates a perfect negative linear relationship, and 0 indicates no linear relationship. For the computation, the input spike trains are discretized into time intervals (bins), and the spike count is obtained in each bin. The Pearson correlation coefficient is obtained by normalizing the covariance between the binned spike trains: the covariance is divided by the product of the standard deviation of each."@en . + "compute spike train Pearson correlation coefficient"@en . +# +# http://purl.org/neao/steps#ComputeSpikeTrainTimeHistogram + . + . + _:genid59 . +_:genid59 . +_:genid59 . +_:genid59 . + "An analysis step that computes the time histogram of a spike train. If the spike count in a bin is divided by the duration of the bin, this can be used to estimate the instantaneous firing rate at the bin interval."@en . + "compute spike train time histogram"@en . +# +# http://purl.org/neao/steps#ComputeSpikeTriggeredAverage + . + . + "compute STA"@en . + "A triggered average analysis that uses spike times as triggers to obtain the average of a signal around each spike (spike-triggered average)."@en . + "compute spike-triggered average"@en . +# +# http://purl.org/neao/steps#ComputeSpikeTriggeredLFPAverage + . + . + _:genid60 . +_:genid60 . +_:genid60 . +_:genid60 . + "compute STA"@en . + "A triggered average analysis that uses spike times as triggers to average the local field potential (LFP) signal. The LFP is the low-frequency component of the potential recorded within a specific region of the brain using extracellular electrodes. The output of the method will provide an estimation of the average LFP voltage around each spike, i.e., the spike-triggered average of the LFP signal."@en . + "compute spike-triggered local field potential average"@en . +# +# http://purl.org/neao/steps#ComputeSpikeTriggeredPhase + . + . + "A phase analysis that computes the phase angle values of an analytic signal input (or from the analytic signal obtained from an input time series) at the time points where spikes occurred. The spike times are defined in a spike train input. The output is an array with the phase angle at each spike time in the input spike train (spike-triggered phases)."@en . + "compute spike-triggered phase"@en . +# +# http://purl.org/neao/steps#ComputeSpikeWaveformAverage + . + . + "A spike waveform analysis that computes the average across two or more spike waveform inputs. For the computation, the mean value across all inputs is obtained for each time point in the sampled spike waveform. This is frequently used to reduce noise across multiple spike waveform samples of a single neuron."@en . + "compute spike waveform average"@en . +# +# http://purl.org/neao/steps#ComputeSpikeWaveformSNR + . + . + "compute spike waveform SNR"@en . + . + "A spike waveform analysis that computes the signal-to-noise ratio (SNR) for a set of input spike waveforms according to Hatsopoulos (2007). The SNR is defined as the difference in mean peak-to-trough voltage divided by twice the mean standard deviation (SD).The mean SD is obtained by averaging the SDs computed for each time point in the spike waveform."@en . + "compute spike waveform signal-to-noise ratio"@en . +# +# http://purl.org/neao/steps#ComputeSpikeWaveformVariance + . + . + "A spike waveform analysis that computes the variance across two or more spike waveform inputs. For the computation, the value of the variance across all inputs is obtained for each time point in the spike waveform."@en . + "compute spike waveform variance"@en . +# +# http://purl.org/neao/steps#ComputeSpikeWaveformWidth + . + . + "A spike waveform analysis that computes the width of a spike waveform input. The computation takes two time points of interest (e.g, the times of the peak and the trough), and the width is the difference with respect to the time points (e.g., number of time points in between or time interval)."@en . + "compute spike waveform width"@en . +# +# http://purl.org/neao/steps#ComputeStandardDeviation + . + . + "compute SD"@en . + "A dispersion statistical analysis that computes the standard deviation (SD), i.e., the square root of the variance. The SD indicates the average distance of each data point from the mean."@en . + "compute standard deviation"@en . +# +# http://purl.org/neao/steps#ComputeStandardErrorMean + . + . + "compute SEM"@en . + "A dispersion statistical analysis that computes the standard error of the mean (SEM). The SEM is the standard deviation of the sampling distribution of the sample mean. It provides an estimate of how much the sample mean is expected to fluctuate around the true population mean. Smaller SEM values indicates that the sample mean is a more accurate estimate of the population mean. The SEM decreases as the sample size increases, as larger samples provide a more reliable estimate of the population mean."@en . + "compute standard error of the mean"@en . +# +# http://purl.org/neao/steps#ComputeStockwellTransform + . + . + . + "A time-frequency analysis that computes the Stockwell transform (S transform) of the input time series. The S transform generalizes the short-time Fourier transform (STFT) and extends the continuous wavelet transform (CWT). The main difference is that STFT uses a constant window width for all frequencies. The S transform is based on a moving and scalable localizing Gaussian window. Therefore, the window is frequency-dependent (adaptive windowing), which results in better time resolution in higher frequencies and better frequency resolution at lower frequencies. This makes the S transform more suitable to detect transient signals in high frequencies. The computation is computationally expensive, although fast algorithms are available."@en . + "compute S transform"@en . + "compute Stockwell transform"@en . +# +# http://purl.org/neao/steps#ComputeTimeDomainConditionalGrangerCausality + . + . + _:genid61 . +_:genid61 "true"^^ . +_:genid61 . +_:genid61 . + . + "A conditional Granger causality (GC) analysis that computes the GC measures in the time domain."@en . + "compute time domain conditional Granger causality"@en . +# +# http://purl.org/neao/steps#ComputeTimeDomainPairwiseGrangerCausality + . + . + _:genid62 . +_:genid62 "true"^^ . +_:genid62 . +_:genid62 . + . + . + "A pairwise Granger causality (GC) analysis that computes measures of GC between two inputs in the time domain. The computation involves fitting two separate autoregressive (AR) models to the input data and comparing their fit to determine if one time series can predict the other. The quality of the fit is assessed by the variance of the residuals, with GC defined as the natural logarithm of the ratio of the residual variances from the two AR models. The first AR model is univariate, predicting the future values of one time series (e.g., the first) only from its past values. The second AR model is bivariate, predicting the future values of the first time series from its past values as well as the past values of the second time series. If the bivariate model reduces the variance of the residuals (ratio greater than 1), the GC value will be positive, indicating that the second time series Granger causes the first (directional GC estimate from the second to the first). The same method is used to predict the second time series from the first, yielding the directional GC estimate from the first to the second time series. The order of the AR model is defined as parameter, and optimal values can be estimated using optimization techniques."@en . + "compute time domain pairwise Granger causality"@en . +# +# http://purl.org/neao/steps#ComputeTransferEntropy + . + . + _:genid63 . +_:genid63 "false"^^ . +_:genid63 . +_:genid63 . + "compute TE"@en . + . + "A functional connectivity analysis that computes a measure of transfer entropy (TE) between two input time series. TE measures the directional transfer of information between the time series. It extends Granger causality, and is able to detect non-linear forms of interaction."@en . + "compute transfer entropy"@en . +# +# http://purl.org/neao/steps#ComputeTuningCurve + . + . + "A firing rate analysis that computes a tuning curve. The tuning curve describes the firing rate of a neuron as a function of a continuous attribute (e.g., orientation of a visual grating stimulus)."@en . + "compute tuning curve"@en . +# +# http://purl.org/neao/steps#ComputeUnbiasedSquaredPhaseLagIndex + . + . + _:genid64 . +_:genid64 "false"^^ . +_:genid64 . +_:genid64 . + "compute unbiased squared PLI"@en . + . + "A phase lag index (PLI) analysis that computes an unbiased estimate for the squared PLI following Vinck et al. (2011). The direct PLI estimator is positively biased, especially when the sample sizes (i.e., number of trials) are small. The unbiased squared PLI is computed by averaging all pairwise products of the signs computed across the repetitions. Pairs with identical observations are excluded. The unbiased squared PLI is less affected by small-sample size biases."@en . + "compute unbiased squared phase lag index"@en . +# +# http://purl.org/neao/steps#ComputeVanRossumDistance + . + . + . + "A time-scale dependent spike train distance analysis that computes the van Rossum distance introduced in van Rossum (2001). For the computation, each spike in the input spike trains is convolved with an exponential kernel, producing continuous function representations of the input spike trains. The time scale parameter of the distance is set by the time constant of the exponential kernel. The distance is then obtained as the Euclidean distance of the convolved spike trains."@en . + "compute van Rossum distance"@en . +# +# http://purl.org/neao/steps#ComputeVariance + . + . + "A dispersion statistical analysis that computes the variance, i.e., the average of the squared differences from the mean."@en . + "compute variance"@en . +# +# http://purl.org/neao/steps#ComputeVictorPurpuraDistance + . + . + . + "A time-scale dependent spike train distance analysis that computes the Victor-Purpura distance, introduced in Victor & Purpura (1996). The metric defines the distance between two spike train inputs with respect to the minimum cost of transforming one spike train into the order considering three operations: spike insertion, spike deletion and shifting a spike by some interval. The first two operations have a fixed cost equal to 1. The latter depends on a cost per time unit parameter, which sets the time scale of the analysis."@en . + "compute Victor-Purpura distance"@en . +# +# http://purl.org/neao/steps#ComputeWeightedPhaseLagIndex + . + . + _:genid65 . +_:genid65 "false"^^ . +_:genid65 . +_:genid65 . + "compute WPLI"@en . + . + "A phase lag index (PLI) analysis that computes the weighted PLI (WPLI) following Vinck et al. (2011). The original PLI (Stam, 2007) is discontinuous, and small perturbations can turn phase lags into leads (and vice versa). Therefore, this hinders its capacity to detect changes in phase synchronization of small magnitude. The WPLI extends the PLI to weight the contributions of the phase leads and lags by the magnitude of the imaginary component of the cross spectral density. Therefore, these increases the power to detect changes in phase synchronization. The WPLI ranges between 0 and 1. A WPLI of zero means that there is no imbalance in the first time series leading or lagging the second (i.e., the total weight of all leading relationships is equal to the total weight of lagging relationships). A value greater than zero means an imbalance in the likelihood of leading or lagging. A WPLI of 1 indicates perfect phase locking, and that the first time series only leads or only lags."@en . + "compute weighted phase lag index"@en . +# +# http://purl.org/neao/steps#ComputedEvokedPotential + . + . + "compute EP"@en . + "An analysis step that computes the evoked potential (EP). The EP is the neural activity (e.g., local field potential or electroencephalogram voltages) around a presented stimulus (e.g., auditory, visual, electrical). Usually, the stimulus is presented repeatedly across multiple trials, obtaining multiple evoked potential waveforms that can be averaged to cancel the noise. It is an event-related potential (ERP) obtained from presenting a stimulus rather than spontaneous behavioral events."@en . + "compute evoked potential"@en . +# +# http://purl.org/neao/steps#ConditionalGrangerCausalityAnalysis + . + . + _:genid66 . +_:genid66 "true"^^ . +_:genid66 . +_:genid66 . + . + "A Granger causality (GC) analysis that computes a measure of conditional GC between the inputs. The conditional GC is the causality between two inputs (e.g., two time series) while controlling for the influence of an additional input (e.g., a third time series). This allows a more complete understanding of the causal relationships in multivariate time series data."@en . + "conditional Granger causality analysis"@en . +# +# http://purl.org/neao/steps#ConfidenceIntervalResamplingAnalysis + . + . + "A confidence interval statistical analysis that computes the confidence interval using techniques to generate multiple samples from the (observed) data input(s)."@en . + "confidence interval with resampling analysis"@en . +# +# http://purl.org/neao/steps#ConfidenceIntervalStatisticalAnalysis + . + . + "A statistical analysis that computes a confidence interval (CI). The CI is a measure providing a range of values of a parameter, derived from the input (sample) data, that is likely to contain the true value of the parameter in the population with a specified level of confidence. The level of confidence is specified as a parameter to the method. For example, a 95% confidence interval means that if the same population is sampled multiple times, approximately 95% of the intervals calculated from those samples will contain the true population parameter. Confidence intervals are used to estimate parameters such as the mean and are essential for making inferences about the population based on sample data. The output contains the upper and lower limits of the CI."@en . + "confidence interval statistical analysis"@en . +# +# http://purl.org/neao/steps#CorrelatedSpikeTimesGeneration + . + . + . + "A spike train generation where the output spike trains will have spikes that are correlated in time. These methods can be used to generate spike trains with patterns in their activity."@en . + "correlated spike times generation"@en . +# +# http://purl.org/neao/steps#CorrelationAnalysis + . + _:genid67 . +_:genid67 . +_:genid67 . +_:genid67 . + . + _:genid68 . +_:genid68 . +_:genid68 . +_:genid68 . + _:genid69 . +_:genid69 "true"^^ . +_:genid69 . +_:genid69 . + _:genid70 . +_:genid70 "false"^^ . +_:genid70 . +_:genid70 . + _:genid71 . +_:genid71 "true"^^ . +_:genid71 . +_:genid71 . + _:genid72 . +_:genid72 "true"^^ . +_:genid72 . +_:genid72 . + "An analysis step that computes a measure of correlation between two inputs. Correlation is a measure that quantifies the strength to which two variables change together. It is a scaled version of the covariance, and the values are restricted to the -1 to +1 interval. Between time series, it is computed in the time domain."@en . + "correlation analysis"@en . +# +# http://purl.org/neao/steps#CovarianceAnalysis + . + . + "An analysis step used to compute a measure of covariance from two inputs. The covariance indicates the extent to which the two inputs change together. If the greater values of one variable mainly correspond with the greater values of the other variable, and the same applies to the lesser values, then the covariance is positive. Conversely, if greater values of one variable mainly correspond to the lesser values of the other variable, then the covariance is negative."@en . + "covariance analysis"@en . +# +# http://purl.org/neao/steps#CrossCorrelationAnalysis + . + . + _:genid73 . +_:genid73 . +_:genid73 . +_:genid73 . + _:genid74 . +_:genid74 "true"^^ . +_:genid74 . +_:genid74 . + _:genid75 . +_:genid75 "true"^^ . +_:genid75 . +_:genid75 . + _:genid76 . +_:genid76 "true"^^ . +_:genid76 . +_:genid76 . + _:genid77 . +_:genid77 "true"^^ . +_:genid77 . +_:genid77 . + "An analysis step used to compute a measure of cross-correlation, i.e., the correlation of two inputs computed for distinct time lags of the first to the second. The computation produces the cross-correlation value for every lag considered."@en . + "cross-correlation analysis"@en . +# +# http://purl.org/neao/steps#CrossPowerSpectralDensityAnalysis + . + . + "CPSD analysis"@en . + "A spectral density analysis that computes the cross power spectral density (CPSD) of two inputs, i.e., the distribution of their power across the different frequency components per unit frequency. The CPSD shows in the frequency domain how the two inputs are correlated in the time domain, and is equivalent to the Fourier transform of the cross-correlation function between the two signals. If the inputs are not correlated, the CPSD will be flat across the frequencies. A peak suggests that the signals are correlated at that frequency. The CPSD is often referred to as cross-spectrum."@en . + "cross power spectral density analysis"@en . +# +# http://purl.org/neao/steps#CurrentSourceDensityAnalysis + . + . + "CSD analysis"@en . + "An analysis step used to analyze extracellular electrical potentials (e.g., local field potentials or evoked potentials) recorded from multiple locations, enabling the estimation of the current sources responsible for generating these potentials. The methods can be applied to data recorded from different electrode configurations: laminar probe-like electrodes (1D methods), microelectrode array-like electrodes (2D methods) or electrodes configurations recording from a volume (e.g., multiple laminar probes or array electrodes with shanks with multiple depths; 3D methods). The output of the current source analysis provides the spatial map showing where currents are entering (sources) and leaving (sinks) the neural tissue. For each point in the map, a quantitative value indicates the magnitude of the current density at that point."@en . + "source imaging analysis"@en . + "source localization analysis"@en . + "current source density analysis"@en . +# +# http://purl.org/neao/steps#DataGeneration + . + . + "An analysis step that generates new data entities. This can be done using other input data as a start (e.g., generating a spike train surrogate from spike trains obtained from experimental recordings) or generate new data using algorithms that take specific parameters (e.g., generating a spike train using a probability distribution defined by specific parameters)."@en . + "data generation"@en . +# +# http://purl.org/neao/steps#DataNormalization + . + . + "A data transformation that adjusts the ranges and distributions of the values in the input data. This can be used to transform data measured in distinct (i.e. not directly comparable) scales to a common (i.e. comparable) scale."@en . + "data normalization"@en . +# +# http://purl.org/neao/steps#DataSmoothing + . + . + "A data transformation that uses statistical techniques to remove noise and fluctuations from the input data to reveal underlying trends and patterns."@en . + "data smoothing"@en . +# +# http://purl.org/neao/steps#DataTransformation + . + . + "An analysis step that takes one or more inputs and modifies the contents, such that it fits a particular purpose. The data transformation steps are frequently used during pre-processing the input data for the analyses. Usually, a data transformation will not change the main representation or quality of the inputs. For example, a digital filtering step will remove certain frequency components from a time series. However, the output will resemble the original input with respect to shape or physical units. In addition, the inputs can also be converted to other formats or representations that are needed for a particular analysis step. For example, spike trains can be discretized into small intervals (binning) or the dimensionality of the input can be reduced using principal component analysis. The data transformation is in contrast to steps that perform computations that take the input and generate a derived measure with new information. For example, when computing the mean firing rate from a spike train, a single scalar value is obtained from the spike count in the input data."@en . + "data transformation"@en . +# +# http://purl.org/neao/steps#Detrending + . + . + "A data transformation that removes a trend (i.e., a change in the mean over time) from an input time series."@en . + "detrending"@en . +# +# http://purl.org/neao/steps#DigitalFiltering + . + . + "A data transformation that processes digital signal inputs (i.e., sampled time series) to attenuate or amplify specific frequency components. Digital filters can be designed using various methods, achieving distinct frequency responses and stability."@en . + "digital filtering"@en . +# +# http://purl.org/neao/steps#DimensionalityReduction + . + . + "A data transformation that obtains a low-dimensional (simplified) representation of the high-dimensional input data. This step retains important information in the input data while minimizing redundancy and noise."@en . + "dimensionality reduction"@en . +# +# http://purl.org/neao/steps#DirectedAnalysis + . + _:genid78 . +_:genid78 "true"^^ . +_:genid78 . +_:genid78 . + . + . + "An analysis step where the output provides information on the direction of influence in the relationships among the inputs (e.g., in the cross-correlation histogram, it is possible to analyze the timing of the spikes of the first input spike train with respect to the timing of the spikes of the second input spike train, i.e., whether they likely occur before or after)."@en . + "directed analysis"@en . +# +# http://purl.org/neao/steps#DispersionStatisticalAnalysis + . + . + "A statistical analysis that computes a measure that represents the variability in the input data. It indicated the degree to which the data points differ from the central tendency."@en . + "dispersion statistical analysis"@en . +# +# http://purl.org/neao/steps#DistanceAnalysis + . + _:genid79 . +_:genid79 . +_:genid79 . +_:genid79 . + . +# +# http://purl.org/neao/steps#Execute3dSPADEAnalysis + . + . + . + . + "A SPADE analysis that uses the 3d-SPADE implementation as defined in Stella et al. (2019). The 3d-SPADE analysis considers spatio-temporal patterns (i.e., not restricted to synchronous patterns), and the pattern signature used for statistical testing considers the size, number of occurrences and duration of a pattern."@en . + "execute 3d-SPADE analysis"@en . +# +# http://purl.org/neao/steps#ExecuteASSETAnalysis + . + . + _:genid80 . +_:genid80 . +_:genid80 . +_:genid80 . + _:genid81 . +_:genid81 "false"^^ . +_:genid81 . +_:genid81 . + . + "A neuronal activity pattern detection analysis that uses the Analysis of Sequences of Synchronous EvenTs (ASSET) method defined in Torre et al. (2016). ASSET is an automatized test to identify the sequential activations of groups of neurons that repeat in time. The identification of the repeated sequences is possible by computing the intersection matrix. The input spike data is discretized into smaller intervals (bins), and the overlap of neuronal activity at each bin pair is obtained as a matrix. When a sequence of activations exists and repeats in time, a characteristic diagonal structure appears in the matrix.\n\nThe ASSET analysis provides a robust statistical test to automatically identify the diagonal structures and to provide the neurons and their activation pattern in each repeated sequence. Overall, the analysis is composed by 6 substeps:\n\n1. Compute the intersection matrix (IMAT) from a set of input spike trains, using a specified bin size to discretize the data.\n2. Obtain the probability matrix (PMAT).\n3. Obtain the joint probability matrix (JMAT).\n4. Extract significant entries in both PMAT and JMAT using specified thresholds, obtaining the mask matrix (MMAT).\n5. Obtain the cluster matrix (CMAT) by using DBSCAN to cluster the significant entries in the MMAT to find each diagonal structure. Parameters for DBSCAN control the clustering result. A modified distance metric is used.\n6. From the identified clusters (each a single diagonal structure in the IMAT), obtain the neuronal composition and the order of activation, producing the final neuronal activity patterns as output."@en . + "execute ASSET analysis"@en . +# +# http://purl.org/neao/steps#ExecuteCellAssemblyDetectionAnalysis + . + . + _:genid82 . +_:genid82 "false"^^ . +_:genid82 . +_:genid82 . + "execute CAD analysis"@en . + . + "A neuronal activity pattern detection analysis that uses the Cell Assembly Detection (CAD) method as defined in Russo & Durstewitz (2017). CAD allows detecting spatio-temporal spike patterns at different time scales, levels of precision, and with arbitrary internal organization. The analysis identifies patterns with different delays between the spikes (within a window determining the minimum and maximum lags), and is performed in two steps using an agglomerative clustering algorithm. First, significant pairwise correlations are identified, which is followed by the clustering procedure that progressively finds interactions of higher order. At each agglomeration step, the method can filter out patterns involving the same neurons, keeping the most significant pattern (significance pruning). In an additional pruning step, assemblies part of a larger assembly can also be eliminated (controlled by the subgroup pruning parameter). The algorithm stops when the detected assemblies reach their maximum size (determined by a parameter). The statistical test assumes independence under non-stationarity and Poisson distribution of the input spike trains."@en . + "execute Cell Assembly Detection analysis"@en . +# +# http://purl.org/neao/steps#ExecuteNon3dSPADEAnalysis + . + . + . + "A SPADE analysis that uses the SPADE implementation as defined in Quaglio et al. (2017). This is the extension of SPADE to consider spatio-temporal patterns (i.e., patterns not restricted to synchronous spiking). In the non-3d SPADE analysis, the pattern signature used for statistical testing considers only the size and number of occurrences of a pattern."@en . + "execute non-3d-SPADE analysis"@en . +# +# http://purl.org/neao/steps#ExecuteUnitaryEventAnalysisAnalytical + . + . + . + "execute UE analysis (analytical method)"@en . + . + . + . + . + "A unitary event (UE) analysis that uses the analytical approach to determine the significance of the empirical coincidences in binned spike train data, as defined in Grün et al. (1999, 2002a, 2002b, and 2003). The analytical method tests if the number of empirical coincidences is consistent with the coincidence distribution resulting from independent processes. This distribution can be expressed analytically assuming that the input spike trains follow Poisson statistics. The UEs can be determined trial by trial, where the analytical expectancy is computed for each trial and then summed over all trials, or by averaging over all trials (according to Grün, 2003)."@en . + "execute Unitary Event analysis (analytical method)"@en . +# +# http://purl.org/neao/steps#ExecuteUnitaryEventAnalysisMonteCarlo + . + . + "execute UE analysis (Monte Carlo method)"@en . + . + "A unitary event (UE) analysis that uses a Monte Carlo approach based on spike train surrogates to determine the significance of the empirical coincidences in binned spike train data, according to Grün (2009). The Monte Carlo method does not rely on the assumption that the input spike data follows Poisson statistics. For the assessment of significance, the distribution of expected coincidences is determined by surrogates (spike train randomization) in each trial, and then summed over trials. The number of surrogates is determined by a parameter."@en . + "execute Unitary Event analysis (Monte Carlo method)"@en . +# +# http://purl.org/neao/steps#FieldFieldCouplingAnalysis + . + _:genid83 . +_:genid83 . +_:genid83 . +_:genid83 . + . + . + "An analysis step that computes interactions between the neural activity represented by distinct local field potential (LFP) signals (e.g., LFP obtained from different electrodes, or distinct LFP frequency bands)."@en . + "field-field coupling analysis"@en . +# +# http://purl.org/neao/steps#FiniteImpulseResponseFiltering + . + . + "FIR filtering"@en . + "A digital filtering that uses a filter whose impulse response (i.e., the response of the filter to a brief input impulse) decays to zero after a finite amount of time. Therefore, the output of the filter depends on a finite number of past samples. The finite impulse response (FIR) filters are stable and can be designed such that they do not distort the phase of the signal. However, they have a higher computational cost."@en . + "finite impulse response filtering"@en . +# +# http://purl.org/neao/steps#FiringRateAnalysis + . + . + "An analysis step used to compute a measure quantifying the firing rate of one or more neurons. The firing rate is the number of action potential (spikes) that a neuron fires per time unit and is defined with a unit of frequency (e.g., Hz or spikes/s)."@en . + "firing rate analysis"@en . +# +# http://purl.org/neao/steps#FrequencyDomainAnalysis + . + _:genid84 . +_:genid84 "true"^^ . +_:genid84 . +_:genid84 . + . + . + "An analysis step that analyzes the input(s) with respect to its(their) frequency content."@en . + "frequency domain analysis"@en . +# +# http://purl.org/neao/steps#FrequencyDomainPairwiseGrangerCausalityAnalysis + . + . + _:genid85 . +_:genid85 "true"^^ . +_:genid85 . +_:genid85 . + . + "A pairwise Granger causality (GC) analysis that computes measures of GC between two inputs in the frequency domain. This is an extension of the GC concept in the time domain, and the measures of GC are obtained for the different frequency components of the inputs, according to Geweke (1982). The computation of the frequency-domain GC measures is based on two elements: the noise covariance matrix and the spectral transfer matrix. These can be estimated either with parametric or non-parametric methods. For the parametric estimation, an autoregressive model is fit and the Fourier transform of the autoregressive coefficients is used to obtain the spectral transfer matrix. For the non-parametric estimation, the cross-spectral density (CSD) matrix is obtained (using methods for CSD estimation such as multitapering or wavelet), and the CSD matrix is factorized to obtain the noise covariance and spectral transfer matrices."@en . + "frequency domain pairwise granger causality analysis"@en . +# +# http://purl.org/neao/steps#FrequencyDomainTransformation + . + . + "A data transformation that converts a time series input from the time to the frequency domain, i.e., reveal the different frequency components that make up the original signal."@en . + "frequency domain transformation"@en . +# +# http://purl.org/neao/steps#FunctionalConnectivityAnalysis + . + _:genid86 . +_:genid86 . +_:genid86 . +_:genid86 . + . + "FCA"@en . + "An analysis step that computes measures of functional connectivity. Functional connectivity refers to statistical dependencies and patterns of synchronization between the neural activity that indicate the functional interactions and co-activations that are relevant for the function of the nervous system (e.g., the interactions between different brain regions). It does not imply direct physical connections."@en . + "functional connectivity analysis"@en . +# +# http://purl.org/neao/steps#GenerateCompoundPoissonProcess + . + . + . + . + "A correlated spike times generation that produces spike trains using a compound Poisson process (CPP) according to Staude et al. (2010). The CPP is a model for parallel and correlated processes with Poisson spiking statistics at predefined firing rates."@en . + "generate CPP"@en . + "generate compound Poisson process"@en . +# +# http://purl.org/neao/steps#GenerateISIDitheringSurrogate + . + . + "generate ISI-D surrogate"@en . + . + "A spike train surrogate generation step where each spike is displaced according to the interspike interval (ISI) distribution sampled from the input spike train."@en . + "generate joint interspike interval dithering surrogate"@en . +# +# http://purl.org/neao/steps#GenerateISIShufflingSurrogate + . + . + . + "A spike train surrogate generation step where the interspike intervals (ISIs) of the input spike train is randomly sorted. This preserves the ISI distribution and spike count as in the original spike train input, but destroys temporal dependencies and firing rate profile."@en . + "generate interspike interval shuffling surrogate"@en . +# +# http://purl.org/neao/steps#GenerateJointISIDitheringSurrogate + . + . + "generate JISI-D surrogate"@en . + . + "A spike train surrogate generation step where spikes from adjacent interspike intervals (ISIs) are dithered according to the joint-ISI (JISI) probability distribution. The distribution is obtained from the input spike train by computing the JISI histogram (i.e., a two-dimensional histogram that shows the frequency of ISIs with a given duration that are immediately followed by intervals with another duration). Due to non-stationarities in the input spike train and/or its limited duration, it is difficult to accurately estimate the underlying JISI probability distribution. Therefore, a 2D-Gaussian smoothing is applied to the JISI histogram (with a variance determined by parameter). Dithering a spike according to this (smoothed) two-dimensional histogram involves moving the spike along the anti-diagonal of the JISI distribution. The dithering time is defined by a parameter."@en . + "generate joint interspike interval dithering surrogate"@en . +# +# http://purl.org/neao/steps#GenerateMorletWavelet + . + . + "A data generation that constructs a Morlet wavelet considering the selected parameters (i.e., sampling frequency, fundamental frequency, and number of cycles per frequency). The Morlet wavelet is composed by a complex exponential multiplied by a Gaussian window. The output data contains the discrete time points and the corresponding wavelet values."@en . + "generate Morlet wavelet"@en . +# +# http://purl.org/neao/steps#GenerateNonStationaryGammaProcess + . + . + "A random spike times generation that uses a gamma probability distribution to produce spike trains where the firing rate varies over time."@en . + "generate non-stationary gamma process"@en . +# +# http://purl.org/neao/steps#GenerateNonStationaryPoissonProcess + . + . + "A random spike times generation that uses a Poisson probability distribution to produce spike trains where the firing rate varies over time. A dead time can be specified as parameter (i.e., an interval where no spikes can occur, which is analogous to the neuronal refractory period)."@en . + "generate non-stationary Poisson process"@en . +# +# http://purl.org/neao/steps#GenerateSingleInteractionProcess + . + . + . + "A correlated spike times generation that produces a multidimensional Poisson single interaction process (SIP) plus independent Poisson processes, according to Kuhn et al. (2003). The Poisson SIP consists of Poisson time series that are independent except for events that are simultaneous in all of them."@en . + "generate SIP"@en . + "generate single interaction process"@en . +# +# http://purl.org/neao/steps#GenerateSpikeTimeRandomizationSurrogate + . + . + . + "A spike train surrogate generation step that keeps the spike count of the input spike train, but the spike times in the surrogate spike train output are randomly chosen within the duration interval of the input spike train."@en . + "generate spike time randomization surrogate"@en . +# +# http://purl.org/neao/steps#GenerateSpikeTrainDitheringSurrogate + . + . + . + "A spike train surrogate generation step that displaces the whole input spike train by a random amount of time (independent for each surrogate generated). The amount of displacement is specified as a parameter (dither time), and occurs in a window (-dither time, dither time). This surrogate maintains the ISIs and the temporal correlations within the spike train."@en . + "generate spike train dithering surrogate"@en . +# +# http://purl.org/neao/steps#GenerateStationaryGammaProcess + . + . + "A random spike times generation that uses a gamma probability distribution to produce spike trains with a constant firing rate."@en . + "generate stationary gamma process"@en . +# +# http://purl.org/neao/steps#GenerateStationaryInverseGaussianProcess + . + . + "A random spike times generation that uses a inverse Gaussian probability distribution to produce spike trains with a constant firing rate."@en . + "generate stationary inverse Gaussian process"@en . +# +# http://purl.org/neao/steps#GenerateStationaryLogNormalProcess + . + . + "A random spike times generation that uses a log-normal probability distribution to produce spike trains with a constant firing rate."@en . + "generate stationary log-normal process"@en . +# +# http://purl.org/neao/steps#GenerateStationaryPoissonProcess + . + . + . + "A random spike times generation that uses a Poisson probability distribution to produce spike trains with a constant firing rate. A dead time can be specified as parameter (i.e., an interval where no spikes can occur, which is analogous to the neuronal refractory period)."@en . + "generate stationary Poisson process"@en . +# +# http://purl.org/neao/steps#GenerateTrialShiftingSurrogate + . + . + . + "A spike train surrogate generation step that shifts the entire spike train (containing the data of a single experimental trial) by an amount randomly chosen from a uniform distribution. The amount of displacement is specified as a parameter (dither time), and occurs in a window (-dither time, dither time). The input is a collection of spike trains of the same neuron, containing the spiking activity during different experimental trials. The amount of shift is independently chosen across trials and neurons. This surrogate preserves the ISI distribution and temporal correlations within the single-trial spike train."@en . + "generate trial shifting surrogate"@en . +# +# http://purl.org/neao/steps#GenerateTrialShufflingSurrogate + . + . + . + "A spike train surrogate generation step where the the spike trains of single-trial activity of one of the neurons are randomly permuted, so that each trial is no longer paired with the corresponding trial of the other neuron, but with a randomly selected one. The input is a collection of spike trains with multitrial activity data of multiple neurons recorded in parallel."@en . + "generate trial shuffling surrogate"@en . +# +# http://purl.org/neao/steps#GenerateUniformSpikeDitheringSurrogate + . + . + "generate UD surrogate"@en . + . + "A spike train surrogate generation step that displaces each spike time in the input spike train according to a uniform distribution centered on the spike. The displacement occurs in a time window around the spike defined by a parameter (dither time)."@en . + "generate uniform spike dithering surrogate"@en . +# +# http://purl.org/neao/steps#GenerateUniformSpikeDitheringSurrogateWithDeadTime + . + . + "generate UDD surrogate"@en . + . + "A spike train surrogate generation step that displaces each spike time in the input spike train according to a uniform distribution centered on the spike. The displacement occurs in a time window around the spike defined by a parameter (dither time) that is constrained to the intervals between adjacent spikes to avoid two spikes closer than a dead time (specified by parameter). This mimics the refractory period behavior of neurons, where the neuron cannot fire additional spikes for a short interval after one spike."@en . + "generate uniform spike dithering surrogate with dead time"@en . +# +# http://purl.org/neao/steps#GenerateWindowShufflingSurrogate + . + . + . + "A spike train surrogate generation step that shuffles the entries of a binned spike train within exclusive maximal displacement windows. The maximal displacement is specified by parameter, and represents the maximum number of bins that a spike can be displaced within the window."@en . + "generate bin shuffling within exclusive windows surrogate"@en . + "generate window shuffling surrogate"@en . +# +# http://purl.org/neao/steps#GrangerCausalityAnalysis + . + . + _:genid87 . +_:genid87 "true"^^ . +_:genid87 . +_:genid87 . + _:genid88 . +_:genid88 "true"^^ . +_:genid88 . +_:genid88 . + "GC analysis"@en . + "A functional connectivity analysis that computes measures of Granger causality (GC). GC is a statistical concept where the future values of a time series are predicted based on its past values and the past values of other time series. GC quantifies bi-directional interactions between the inputs, determining the directional influence from one input to another. For example, with two inputs, GC measures how much the first input influences the second and vice versa (directional GC measure). This provides estimates of the directed connectivity between the inputs. It is also possible to compute associated measures, such as the instantaneous GC (a measure of interdependence between the inputs not accounted by their bi-directional interactions, such as shared neural input) and the total interdependence (the sum of all directional and instantaneous interactions between the inputs). The analysis can be performed in the time or frequency domains, and can take two (bivariate) or more inputs (multivariate)."@en . + "Granger causality analysis"@en . +# +# http://purl.org/neao/steps#InfiniteImpulseResponseFiltering + . + . + "IIR filtering"@en . + "A digital filtering that uses a filter whose impulse response (i.e., the response of the filter to a brief input impulse) persists infinitely. Therefore, the output of the filter can depend on an infinite number of past samples. The infinite impulse response (IIR) filters can become unstable and distort the phase of the signal, but have a lower computational cost."@en . + "infinite impulse response filtering"@en . +# +# http://purl.org/neao/steps#InstantaneousFiringRateAnalysis + . + _:genid89 . +_:genid89 . +_:genid89 . +_:genid89 . + . + "A firing rate analysis that computes the instantaneous firing rate, which is the estimate of the firing rate at a specific point in time. The instantaneous firing rate value can be obtained by several methods."@en . + "instantaneous firing rate analysis"@en . +# +# http://purl.org/neao/steps#InterspikeIntervalAnalysis + . + . + "ISI analysis"@en . + "An analysis step that computes or analyzes the interval between successive spikes in a spike train (interspike interval; ISI)."@en . + "interspike interval analysis"@en . +# +# http://purl.org/neao/steps#InterspikeIntervalVariabilityAnalysis + . + . + _:genid90 . +_:genid90 . +_:genid90 . +_:genid90 . + "An interspike interval analysis that computes a measure describing the variability of the interspike intervals. The measure can assess how regular a neuron is firing."@en . + "interspike interval variability analysis"@en . +# +# http://purl.org/neao/steps#KernelSmoothing + . + . + "A data smoothing that performs a convolution of the input data with a kernel function. This computes a weighted average of the data around the kernel. Several kernel types can be used for the smoothing (e.g., Gaussian, exponential) and the kernel shape is controlled by a width parameter."@en . + "kernel smoothing"@en . +# +# http://purl.org/neao/steps#LatentDynamicsAnalysis + . + _:genid91 . +_:genid91 . +_:genid91 . +_:genid91 . + . + "An analysis step that aims to identify underlying patterns and structures within time series or sequential data that are not directly observable. It involves modeling hidden (latent) variables that influence the observed data and their evolution over time. The analysis captures temporal dependencies and dynamics within the data, providing insights into the processes that generate the observed sequences."@en . + "latent dynamics analysis"@en . +# +# http://purl.org/neao/steps#LineNoiseRemoval + . + . + "A data transformation that removes noise induced by the power line."@en . + "line noise cancellation"@en . + "line noise removal"@en . +# +# http://purl.org/neao/steps#MeanVectorLengthAnalysis + . + . + "MVL analysis"@en . + "A phase-amplitude coupling (PAC) analysis that computes the mean vector length (MVL) measure. The MVL is based on a mean vector obtained from a time series defined in the complex plane, where the amplitude is taken from the high-frequency oscillation input and the phase from the low-frequency oscillation input."@en . + "mean vector length analysis"@en . +# +# http://purl.org/neao/steps#ModelBasedAnalysis + . + _:genid92 . +_:genid92 "true"^^ . +_:genid92 . +_:genid92 . + . + "An analysis step that depends on assumptions on the interactions between the inputs to perform the computations. For example, the Granger causality analysis assumes linear relationships between the input signals."@en . + "model-based analysis"@en . +# +# http://purl.org/neao/steps#ModelFreeAnalysis + . + _:genid93 . +_:genid93 "false"^^ . +_:genid93 . +_:genid93 . + . + "An analysis step that does not depend on assumptions on the interactions between the inputs to perform the computations. For example, it can consider probability distributions obtained from the input data."@en . + "model-free analysis"@en . +# +# http://purl.org/neao/steps#MultivariateAnalysis + . + _:genid94 . +_:genid94 "true"^^ . +_:genid94 . +_:genid94 . + . + "An analysis step that has three or more distinct inputs considered for the computation of the output (e.g., the time series with the local field potential signals recorded from three or more electrodes, used to compute the partial directed coherence)."@en . + "multivariate analysis"@en . +# +# http://purl.org/neao/steps#NeuronalActivityPatternDetectionAnalysis + . + . + _:genid95 . +_:genid95 "true"^^ . +_:genid95 . +_:genid95 . + _:genid96 . +_:genid96 "true"^^ . +_:genid96 . +_:genid96 . + "An analysis step that aims to identify a neuronal activity pattern, i.e., spikes of a group of neurons that occur in a specific spatio-temporal configuration."@en . + "neuronal activity pattern detection analysis"@en . +# +# http://purl.org/neao/steps#NeuronalFiringRegularityAnalysis + . + _:genid97 . +_:genid97 . +_:genid97 . +_:genid97 . + . + "An analysis step that computes measures to assess the regularity in the firing of a neuron. Neuronal firing regularity refers to the consistency or variability in the timing of action potentials (spikes) generated by a neuron."@en . + "spike time variability analysis"@en . + "neuronal firing regularity analysis"@en . +# +# http://purl.org/neao/steps#NonDirectedAnalysis + . + _:genid98 . +_:genid98 "false"^^ . +_:genid98 . +_:genid98 . + . + "An analysis step where the output does not provide information on the direction of influence in the relationships among the inputs (e.g., in the Pearson correlation coefficient computed between two spike trains, it is possible to know how strongly they tend to fire together. However, it is not possible to analyze the timing of the spikes of the first input spike with respect to the timing of the spikes of the second input spike train)."@en . + "non-directed analysis"@en . +# +# http://purl.org/neao/steps#PairwiseGrangerCausalityAnalysis + . + . + _:genid99 . +_:genid99 "true"^^ . +_:genid99 . +_:genid99 . + "A Granger causality (GC) analysis that computes a measure of GC between two inputs."@en . + "pairwise Granger causality analysis"@en . +# +# http://purl.org/neao/steps#PeristimulusTimeHistogramAnalysis + . + . + "PSTH analysis"@en . + "A spike train time histogram analysis that computes the peristimulus time histogram (PSTH). PSTH is the time histogram of two or more spike trains containing repeated recordings of a single neuron around the time when an event of interest occurred. The event of interest can occur at any time point during the duration of the source spike trains. The distribution of the histogram corresponds to the distribution of the activity of the neuron with respect to the event across the repeated recordings. The event of interest can be an externally presented stimulus or a spontaneous behavioral event. If the histogram represents the neuronal activity after the stimulus presentation or event occurrence, this can be referred as post-stimulus time histogram. Conversely, if the histogram shows the activity of the neuron before the stimulus presentation or event, this can be referred as prestimulus time histogram. Finally, if the histogram considers a behavioral event (or an event that is not an externally presented stimulus), the histogram can be referred to as perievent time histogram (PETH)."@en . + "peristimulus time histogram analysis"@en . +# +# http://purl.org/neao/steps#PhaseAmplitudeCouplingAnalysis + . + . + _:genid100 . +_:genid100 . +_:genid100 . +_:genid100 . + _:genid101 . +_:genid101 . +_:genid101 . +_:genid101 . + _:genid102 . +_:genid102 "true"^^ . +_:genid102 . +_:genid102 . + _:genid103 . +_:genid103 "false"^^ . +_:genid103 . +_:genid103 . + _:genid104 . +_:genid104 "true"^^ . +_:genid104 . +_:genid104 . + "PAC analysis"@en . + "A phase analysis that computes measures describing how the phase of a low-frequency oscillation modulates the amplitude of a high-frequency oscillation. Phase-amplitude coupling (PAC) can be used to investigate interactions between different frequency bands in the neural activity."@en . + "phase-amplitude coupling analysis"@en . +# +# http://purl.org/neao/steps#PhaseAnalysis + . + . + "An analysis step that computes measures related to the phase in the input data. Phase expresses the position of a time-varying signal relative to a fixed reference point in time. For periodic and oscillatory signals (e.g., a sine waveform), phase analysis involves determining the angle on the unit circle that corresponds to the current position within the waveform's cycle. This helps understanding the timing and synchronization of the oscillations in the input data."@en . + "phase analysis"@en . +# +# http://purl.org/neao/steps#PhaseLagIndexAnalysis + . + . + _:genid105 . +_:genid105 . +_:genid105 . +_:genid105 . + _:genid106 . +_:genid106 "true"^^ . +_:genid106 . +_:genid106 . + _:genid107 . +_:genid107 "true"^^ . +_:genid107 . +_:genid107 . + "PLI analysis"@en . + "A phase analysis that computes the phase lag index (PLI). The PLI measures the asymmetry of the distribution of the phase differences between two input time series, i.e., if there is an imbalance in the likelihood of the first time series leading or lagging the second time series. It is designed to be invariant to common sources, such as volume conduction and/or active reference electrodes."@en . + "phase lag index analysis"@en . +# +# http://purl.org/neao/steps#PhaseLockingValueAnalysis + . + . + _:genid108 . +_:genid108 . +_:genid108 . +_:genid108 . + _:genid109 . +_:genid109 "true"^^ . +_:genid109 . +_:genid109 . + _:genid110 . +_:genid110 "false"^^ . +_:genid110 . +_:genid110 . + _:genid111 . +_:genid111 "true"^^ . +_:genid111 . +_:genid111 . + _:genid112 . +_:genid112 "true"^^ . +_:genid112 . +_:genid112 . + "PLV analysis"@en . + "A phase analysis that computes the phase locking value (PLV). The PLV quantifies the consistency of the phase difference between two input time series across time (e.g., multiple experimental trials)."@en . + "phase locking value analysis"@en . +# +# http://purl.org/neao/steps#PowerSpectralDensityAnalysis + . + . + "PSD analysis"@en . + "A spectral density analysis that computes the power spectral density of an input, i.e., the distribution of power across the different frequency components of the input signal per unit frequency. It is equivalent to the Fourier transform of the autocorrelation function of the input signal. The computed power spectral density values can be corrected depending on the analysis returning the two-sided (i.e., with negative frequencies) or one-sided (i.e., positive frequencies only) PSD. The PSD is often referred to as spectrum."@en . + "auto spectral density analysis"@en . + "power spectral density analysis"@en . +# +# http://purl.org/neao/steps#PrincipalComponentAnalysis + . + . + "PCA"@en . + "A dimensionality reduction that reduces the dimensionality of the input data represented as a matrix with numerous rows and columns. It transforms the data into a set of principal components (PCs) that capture the maximum variance in the input. Each PC is a linear combination of the original variables and serves as a new axis in a lower-dimensional space. The PCs are orthogonal to each other, meaning they capture independent aspects of the input data's variability."@en . + "principal component analysis"@en . +# +# http://purl.org/neao/steps#RandomSpikeTimesGeneration + . + . + "A spike train generation where the output spike trains will have random spike times, taken from a specific probability distribution. The generation process can produce spike trains where the firing rate is constant (stationary) or varies (non-stationary) over time."@en . + "random spike times generation"@en . +# +# http://purl.org/neao/steps#Resampling + . + . + "A data transformation that changes the number of samples in the input data."@en . + "resampling"@en . +# +# http://purl.org/neao/steps#SPADEAnalysis + . + . + _:genid113 . +_:genid113 "false"^^ . +_:genid113 . +_:genid113 . + "A neuronal activity pattern detection analysis that uses the Spatio-temporal PAttern Detection and Evaluation (SPADE) method. The SPADE analysis takes a set of parallel spike trains as input, and returns significant spatio-temporal neuronal activity (spike) patterns. \n\nThe SPADE method consists of three substeps:\n\n1. Detect all putative patterns in the input data using the frequent item set mining (FIM) algorithm. This step requires the discretization of the input spike train data (binning). The bin size determines the temporal resolution of the analysis.\n\n2. The detected FIM patterns are evaluated for statistical significance, considering the null hypothesis of independence of the spike trains given the modulations by the firing rate. This substep is called Pattern Spectrum Filtering (PSF). For the testing, the patterns are pooled based on their signature: size and occurrence count (non-3d-SPADE) or size, occurrence count and pattern duration (3d-SPADE). The pattern spectrum collects the counts of patterns from each signature. The statistical test is done by a Monte Carlo approach, using spike train surrogates generated from the original data. The final output of this substep is the p-value spectrum, which has the same dimensions as the pattern spectrum. The p-value is computed as the ratio of surrogates containing patterns with that signature to the total number of realizations.\n\n3. Conditional test on the significant patterns to remove patterns arising from the overlap of true pattern spikes and chance spikes (pattern set reduction; PSR)."@en . + "SPADE analysis"@en . +# +# http://purl.org/neao/steps#SpectralAnalysis + . + . + "An analysis step that computes measures describing the input data with respect to its frequency contents."@en . + "spectral analysis"@en . +# +# http://purl.org/neao/steps#SpectralDensityAnalysis + . + . + "A spectral analysis that computes the density of a measure of the input(s) over the frequency spectrum. Density means that the measure value (e.g., power) for each frequency component is expressed per unit frequency. For example, for an input time series with voltages recorded from an electrode (measured in V), the power for each frequency component of the signal will be in V**2, while the power density will be in V**2/Hz. Therefore, the power values are normalized per unit frequency. This normalization allows for consistent comparisons of results from analyses with different frequency resolutions, as the spectral density remains unaffected by these variations."@en . + "spectral density analysis"@en . +# +# http://purl.org/neao/steps#SpectrogramAnalysis + . + . + "A time-frequency analysis that shows the power (or power density) of different frequency components of the input(s) as they change over time. This can be obtained for a single input (spectrogram) or for two distinct inputs (cross-spectrogram)."@en . + "spectrogram analysis"@en . +# +# http://purl.org/neao/steps#SpikeFieldCoherenceAnalysis + . + . + _:genid114 . +_:genid114 . +_:genid114 . +_:genid114 . + _:genid115 . +_:genid115 . +_:genid115 . +_:genid115 . + _:genid116 . +_:genid116 "true"^^ . +_:genid116 . +_:genid116 . + _:genid117 . +_:genid117 "false"^^ . +_:genid117 . +_:genid117 . + _:genid118 . +_:genid118 "true"^^ . +_:genid118 . +_:genid118 . + "SFC analysis"@en . + "An analysis step that computes the spike-field coherence (SFC), which is the coherence computed between an input spike train and an input time series with the local field potential (LFP). Coherence is a measure of the association between the two inputs in the frequency domain. SFC can be used to quantify the relationship between the spiking activity of neurons and the oscillatory activity in the LFP. It represents the similarity of dynamics between the spike train and the voltage fluctuations produced by the neural activity in the local environment where the spiking activity was recorded."@en . + "spike-field coherence analysis"@en . +# +# http://purl.org/neao/steps#SpikeFieldCouplingAnalysis + . + _:genid119 . +_:genid119 . +_:genid119 . +_:genid119 . + . + . + "An analysis step that computes interactions between the spiking activity of neurons (individual or population) and the local field potential (LFP)."@en . + "spike-field coupling analysis"@en . +# +# http://purl.org/neao/steps#SpikeSpikeCouplingAnalysis + . + _:genid120 . +_:genid120 . +_:genid120 . +_:genid120 . + . + "An analysis step that computes interactions between the spiking activity of one or more neurons."@en . + "spike-spike coupling analysis"@en . +# +# http://purl.org/neao/steps#SpikeTrainCorrelationAnalysis + . + . + _:genid121 . +_:genid121 . +_:genid121 . +_:genid121 . + _:genid122 . +_:genid122 "true"^^ . +_:genid122 . +_:genid122 . + _:genid123 . +_:genid123 "false"^^ . +_:genid123 . +_:genid123 . + _:genid124 . +_:genid124 "true"^^ . +_:genid124 . +_:genid124 . + "An analysis step that computes measures estimating the correlation between spike train inputs. The correlation value is a normalized measure of covariation in the input spike train data, and reflects the strength and direction of the association: positive values mean that the inputs vary in the same direction, and negative values mean that the inputs vary in opposite directions (e.g., if the activity in one spike train increases, it decreases in the other)."@en . + "spike train correlation analysis"@en . +# +# http://purl.org/neao/steps#SpikeTrainDissimilarityAnalysis + . + . + "An analysis step that computes a measure comparing spike train inputs and providing an estimation of their similarity/dissimilarity. This is frequently done by computing spike train distances, which are measures that assign the notion of distance, i.e., the input spike trains are considered as elements in a space and, if similar, will be close together."@en . + "spike train dissimilarity analysis"@en . +# +# http://purl.org/neao/steps#SpikeTrainGeneration + . + . + _:genid125 . +_:genid125 . +_:genid125 . +_:genid125 . + "A data generation that produces one or more artificial spike trains using distinct statistical procedures to determine the spike times."@en . + "spike train generation"@en . +# +# http://purl.org/neao/steps#SpikeTrainSurrogateGeneration + . + . + "A data generation that produces one or more spike train surrogates. A spike train surrogate is a new spike train derived from an input spike train (usually experimentally recorded). This is done using methods that alter the original spike times while trying to maintain specific statistical features of the original spike train (e.g., firing rate, interspike interval distribution). This is used to destroy fine temporal correlations in the spiking activity."@en . + "spike train surrogate generation"@en . +# +# http://purl.org/neao/steps#SpikeTrainSynchronyAnalysis + . + . + "An analysis step to assess synchronization in two or more spike train inputs that typically represent the activity of different neurons. Spike train synchronization refers to the temporal coordination of action potentials (spikes) between neurons, and describes the degree to which their spikes tend to occur at the same time."@en . + "spike train synchrony analysis"@en . +# +# http://purl.org/neao/steps#SpikeTrainTimeHistogramAnalysis + . + . + "A firing rate analysis that computes histograms of spike train data over time. The time histogram is obtained by discretizing the duration of the spike train into distinct time intervals (bins), and obtaining the spike count inside each bin. \n\nThe histogram can show one of three different measures:\n\n* the spike count at each bin (across all spike trains);\n* the mean spike count per bin (spike count in the bin divided by the number of spike trains);\n* the firing rate (mean spike count in the bin divided by bin width)."@en . + "spike train time histogram analysis"@en . +# +# http://purl.org/neao/steps#SpikeWaveformAnalysis + . + . + "An analysis step that is used to compute measures to describe or make inferences from spike waveform input data. A spike waveform refers to the shape of an electrical signal produced by a neuron when it fires an action potential."@en . + "spike waveform analysis"@en . +# +# http://purl.org/neao/steps#StatisticalAnalysis + . + . + "A generic analysis step that computes measures to summarize and make inferences about the data input. These include measures of central tendency, dispersion and confidence intervals. The subclasses represent analysis steps that are usually used for aggregation of data and description of samples (e.g., compute the mean and standard deviation of the output of trial-by-trial analyses or across subjects). All analysis steps for specific applications related to the analysis of neuroelectrophysiology data itself (e.g., analyzing interspike interval variability) are covered by separate, independent classes."@en . + "statistical analysis"@en . +# +# http://purl.org/neao/steps#TensorComponentAnalysis + . + . + "TCA"@en . + "A dimensionality reduction that reduces the dimensionality of the input data represented as a tensor (i.e., an array with multiple dimensions). The tensor component analysis (TCA) transforms the data into a set of low-dimensional tensors that capture the maximum variance in the input (tensor components)."@en . + "tensor principal component analysis"@en . + "tensor component analysis"@en . +# +# http://purl.org/neao/steps#TimeDomainAnalysis + . + _:genid126 . +_:genid126 "true"^^ . +_:genid126 . +_:genid126 . + . + "An analysis step that analyzes the input(s) with respect to time."@en . + "time domain analysis"@en . +# +# http://purl.org/neao/steps#TimeFrequencyAnalysis + . + . + "A spectral analysis that computes measures describing the frequency content of the input(s) in a time-resolved manner. It allows the analysis of how different frequency components evolve over time, which is essential for non-stationary signals whose spectral characteristics change. The joint time-frequency representation helps in identifying transient features, frequency shifts, and other dynamic behaviors in the input(s)."@en . + "time-frequency analysis"@en . +# +# http://purl.org/neao/steps#TimeScaleDependentSpikeTrainDistanceAnalysis + . + . + _:genid127 . +_:genid127 . +_:genid127 . +_:genid127 . + _:genid128 . +_:genid128 "true"^^ . +_:genid128 . +_:genid128 . + _:genid129 . +_:genid129 "false"^^ . +_:genid129 . +_:genid129 . + _:genid130 . +_:genid130 "true"^^ . +_:genid130 . +_:genid130 . + "A spike train dissimilarity analysis that computes a spike train distance that depends on a parameter that determines a temporal scale in the spike trains to which the distance is sensitive. By computing the spike train distance for different time scale parameter values, it is possible to make inferences on the time scale that is discriminative in the neural activity."@en . + "time-scale dependent spike train distance analysis"@en . +# +# http://purl.org/neao/steps#TimeScaleIndependentSpikeTrainDistanceAnalysis + . + . + _:genid131 . +_:genid131 . +_:genid131 . +_:genid131 . + _:genid132 . +_:genid132 "true"^^ . +_:genid132 . +_:genid132 . + _:genid133 . +_:genid133 "false"^^ . +_:genid133 . +_:genid133 . + _:genid134 . +_:genid134 "true"^^ . +_:genid134 . +_:genid134 . + "A spike train dissimilarity analysis that computes a spike train distance that does not depend on a time scale parameter and that are time-scale adaptive. They can be used in scenarios where there are no previous knowledge of the relevant time scales in the input spike trains."@en . + "time-scale independent spike train distance analysis"@en . +# +# http://purl.org/neao/steps#TriggeredAverageAnalysis + . + . + "An analysis step where a signal is averaged to obtain a value around a point in time representing an event of interest (i.e., a trigger). For each event time, a finite duration window of the input time series is selected around the event time. An average for each time point is then obtained across all windows."@en . + "triggered average analysis"@en . +# +# http://purl.org/neao/steps#UnitaryEventAnalysis + . + . + _:genid135 . +_:genid135 "false"^^ . +_:genid135 . +_:genid135 . + "UE analysis"@en . + . + "A neuronal activity pattern detection analysis that uses the Unitary Event (UE) method. UE is a statistical technique focused on identifying synchronous activity among neurons, known as unitary events (UEs), which occur more frequently than an expectation based solely on firing rates. The input can contain spike trains from one or more neurons and one or more trials. For the computation, the input spike train data is discretized into small time intervals (bins), and coincidences across the different spike trains are computed. The significance of the number of observed (empirical) coincidences is determined by comparing to an expected number given the firing rates of the neurons. To account for possible non-stationarities in the firing rates, the method uses a sliding temporal window over the data, whose width is specified as parameter. Therefore, a measure of significant spike synchrony (joint surprise) is obtained for each window. The statistical evaluation can be done using either analytical methods or Monte-Carlo testing with surrogate spike data. The output presents the significant coincidences (UE patterns) and the participant neurons."@en . + "Unitary Event analysis"@en . +# +# http://purl.org/neao/steps#WaveletTransformAnalysis + . + . + . + "A time-frequency analysis that uses wavelets to obtain the time-frequency representation of the time series input. The wavelet is a rapidly decaying oscillation. The wavelet transform breaks the signal into shifted and scaled versions of the wavelet (mother wavelet), and the output contains the information on both the frequencies present in the signal and the time. The wavelets provide good localization in time and frequency, making them suitable to analyze signals with transient features. Different types of wavelets exist, with distinct properties. They can be chosen to tailor the analysis to particular purposes. The output of the wavelet transform is often referred to as scaleogram."@en . + "wavelet transform analysis"@en . +# +# http://purl.org/spar/biro/BibliographicReference + . +# +# +# +# ################################################################# +# # +# # Individuals +# # +# ################################################################# +# +# +# http://purl.org/neao/bibliography#Aertsen1987_1 + . + . + . + "A. Aertsen, T. Bonhoeffer, & J. Krüger, \"Coherent activity in neuronal populations: analysis and interpretation,\" in E. R. Caianiello (ed) Physics of Cognitive Processes, pp. 1-34, World Scientific, 1987" . + "Aertsen et al. (1987)"@en . +# +# http://purl.org/neao/bibliography#Baccala2001_463 + . + . + . + "L. Baccalá & K. Sameshima, \"Partial directed coherence: a new concept in neural structure determination,\" Biol. Cyb., vol. 84, pp. 463-474, 2001" . + "Baccalá & Sameshima (2001)"@en . +# +# http://purl.org/neao/bibliography#Bartlett1950_1 + . + . + . + "M.S. 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(2009)"@en . +# +# http://purl.org/neao/steps#CorrelationPurpose + . + . + "The analysis purpose of computing a correlation measure."@en . + "correlation purpose"@en . +# +# http://purl.org/neao/steps#DataSmoothingPurpose + . + . + "The analysis purpose of smoothing the data."@en . + "data smoothing purpose"@en . +# +# http://purl.org/neao/steps#DistancePurpose + . + . + "The analysis purpose of computing a distance metric."@en . + "distance purpose"@en . +# +# http://purl.org/neao/steps#FieldFieldCouplingPurpose + . + . + "The analysis purpose of assessing the interactions between inputs with local field potential data."@en . + "field-field coupling purpose"@en . +# +# http://purl.org/neao/steps#FunctionalConnectivityPurpose + . + . + "The analysis purpose of estimating functional connectivity."@en . + "functional connectivity purpose"@en . +# +# http://purl.org/neao/steps#InstantaneousFiringRatePurpose + . + . + "The analysis purpose of estimating the instantaneous firing rate."@en . + "instantaneous firing rate purpose"@en . +# +# http://purl.org/neao/steps#LatentDynamicsPurpose + . + . + "The analysis purpose of estimating latent dynamics."@en . + "latent dynamics purpose"@en . +# +# http://purl.org/neao/steps#NeuronalFiringRegularityPurpose + . + . + "The analysis purpose of assessing the regularity in neuronal firing."@en . + "neuronal firing regularity purpose"@en . +# +# http://purl.org/neao/steps#NeuronalSynchronizationPurpose + . + . + "The analysis purpose of assessing neuronal synchronization."@en . + "neural synchronization purpose"@en . +# +# http://purl.org/neao/steps#SpikeFieldCouplingPurpose + . + . + "The analysis purpose of assessing interactions between spiking activity and the local field potential."@en . + "spike-LFP coupling purpose"@en . + "spike-field coupling purpose"@en . +# +# http://purl.org/neao/steps#SpikeSpikeCouplingPurpose + . + . + "The analysis purpose of assessing interactions between the spiking activity of neurons."@en . + "spike-spike coupling purpose"@en . +# +# https://doi.org/10.1002/hbm.20346 + . +# +# https://doi.org/10.1007/BF00198091 + . +# +# https://doi.org/10.1007/BF02350994 + . +# +# https://doi.org/10.1007/PL00007990 + . +# +# https://doi.org/10.1007/b98858 + . +# +# https://doi.org/10.1007/s00422-002-0386-2 + . +# +# https://doi.org/10.1007/s10827-009-0180-4 + . +# +# https://doi.org/10.1007/s10827-009-0195-x + . +# +# https://doi.org/10.1007/s10827-011-0362-8 + . +# +# https://doi.org/10.1007/s10827-011-0374-4 + . +# +# https://doi.org/10.1007/s12021-007-9000-z + . +# +# https://doi.org/10.1007/s12021-011-9111-4 + . +# +# https://doi.org/10.1007/978-1-4419-5675-0_17 + . +# +# https://doi.org/10.1007/978-1-4419-5675-0_5 + . +# +# https://doi.org/10.1007/978-3-540-88853-6_8 + . +# +# https://doi.org/10.1007/978-3-642-68915-4_34 + . +# +# https://doi.org/10.1016/j.biosystems.2019.104022 + . +# +# https://doi.org/10.1016/j.clinph.2004.04.029 + . +# +# https://doi.org/10.1016/j.jneumeth.2005.12.005 + . +# +# https://doi.org/10.1016/j.jneumeth.2007.05.031 + . +# +# https://doi.org/10.1016/j.jneumeth.2007.10.013 + . +# +# https://doi.org/10.1016/j.jneumeth.2010.06.020 + . +# +# https://doi.org/10.1016/j.jneumeth.2011.08.014 + . +# +# https://doi.org/10.1016/j.jneumeth.2017.09.008 + . +# +# https://doi.org/10.1016/j.neuroimage.2008.02.020 + . +# +# https://doi.org/10.1016/j.neuroimage.2010.01.073 + . +# +# https://doi.org/10.1016/j.neuroimage.2011.01.055 + . +# +# https://doi.org/10.1016/j.neuroimage.2011.11.084 + . +# +# https://doi.org/10.1016/j.neuroimage.2012.05.050 + . +# +# https://doi.org/10.1016/j.neuroimage.2019.116009 + . +# +# https://doi.org/10.1016/j.neuron.2018.05.015 + . +# +# https://doi.org/10.1016/0079-6107(89)90004-7 + . +# +# https://doi.org/10.1016/0165-0270(88)90056-8 + . +# +# https://doi.org/10.1016/0165-1684(91)90079-X + . +# +# https://doi.org/10.1016/S0165-0270(01)00372-7 + . +# +# https://doi.org/10.1016/S0165-0270(98)00061-2 + . +# +# https://doi.org/10.1016/S0165-0270(99)00126-0 + . +# +# https://doi.org/10.1038/nn.2842 + . +# +# https://doi.org/10.1038/nn.3101 + . +# +# https://doi.org/10.1038/nn1228 + . +# +# https://doi.org/10.1073/pnas.0308538101 + . +# +# https://doi.org/10.1080/01621459.1982.10477803 + . +# +# https://doi.org/10.1088/1741-2552/aacfe4 + . +# +# https://doi.org/10.1093/biomet/37.1-2.1 + . +# +# https://doi.org/10.1093/biomet/66.3.605 + . +# +# https://doi.org/10.1098/rsta.2011.0610 + . +# +# https://doi.org/10.1103/PhysRevE.92.040901 + . +# +# https://doi.org/10.1103/PhysRevLett.100.234101 + . +# +# https://doi.org/10.1103/PhysRevLett.85.461 + . +# +# https://doi.org/10.1109/CAMSAP.2013.6714049 + . +# +# https://doi.org/10.1109/PROC.1982.12433 + . +# +# https://doi.org/10.1109/PROC.1987.13723 + . +# +# https://doi.org/10.1109/TAU.1967.1161901 + . +# +# https://doi.org/10.1109/78.492555 + . +# +# https://doi.org/10.1111/1467-9868.00196 + . +# +# https://doi.org/10.1126/science.1055465 + . +# +# https://doi.org/10.1126/science.1128115 + . +# +# https://doi.org/10.1126/science.278.5345.1950 + . +# +# https://doi.org/10.1137/0123044 + . +# +# https://doi.org/10.1146/annurev.fl.24.010192.002143 + . +# +# https://doi.org/10.1152/jn.00093.2008 + . +# +# https://doi.org/10.1152/jn.00106.2010 + . +# +# https://doi.org/10.1152/jn.00848.2014 + . +# +# https://doi.org/10.1152/jn.00873.2012 + . +# +# https://doi.org/10.1152/jn.1975.38.2.369 + . +# +# https://doi.org/10.1152/jn.1996.76.2.1310 + . +# +# https://doi.org/10.1152/jn.90941.2008 + . +# +# https://doi.org/10.1162/NECO_a_00236 + . +# +# https://doi.org/10.1162/089976601300014321 + . +# +# https://doi.org/10.1162/089976602753284455 + . +# +# https://doi.org/10.1162/089976602753284464 + . +# +# https://doi.org/10.1162/089976603321043702 + . +# +# https://doi.org/10.1162/089976603322518759 + . +# +# https://doi.org/10.1214/14-AOAS782 + . +# +# https://doi.org/10.1371/journal.pcbi.1000433 + . +# +# https://doi.org/10.1371/journal.pcbi.1004939 + . +# +# https://doi.org/10.1523/ENEURO.0505-21.2022 + . +# +# https://doi.org/10.1523/JNEUROSCI.17-02-00722.1997 + . +# +# https://doi.org/10.1523/JNEUROSCI.2767-14.2014 + . +# +# https://doi.org/10.2307/27715168 + . +# +# https://doi.org/10.3389/fncom.2010.00127 + . +# +# https://doi.org/10.3389/fncom.2017.00041 + . +# +# https://doi.org/10.48550/arXiv.q-bio/0608035 + . +# +# https://doi.org/10.7554/eLife.10989 + . +# +# https://doi.org/10.7554/eLife.19428 + . +# +# https://isbndb.com/book/9780131139565 + . +# +# https://isbndb.com/book/9781118585771 + . +# +# https://isbndb.com/book/9789971502553#Aertsen_1 + . +# +# https://proceedings.mlr.press/v54/cowley17a.html + . +# +# +# +# ################################################################# +# # +# # Annotations +# # +# ################################################################# +# +# + "An artifact removal step that aims to identify and remove input spike waveforms that differs significantly from other waveforms in the input. This include spike waveforms with too late peak or where the action potential does not rise towards the peak of other waveforms."@en . +# +# +# +# ################################################################# +# # +# # General axioms +# # +# ################################################################# +# +# +_:genid136 . +_:genid136 _:genid139 . +_:genid139 _:genid138 . +_:genid138 _:genid137 . +_:genid137 . +_:genid137 . +_:genid137 . +_:genid138 . +_:genid138 . +_:genid139 . +_:genid139 . +# +_:genid140 . +_:genid140 _:genid145 . +_:genid145 _:genid144 . +_:genid144 _:genid143 . +_:genid143 _:genid142 . +_:genid142 _:genid141 . +_:genid141 . +_:genid141 . +_:genid141 . +_:genid142 . +_:genid142 . +_:genid143 . +_:genid143 . +_:genid144 . +_:genid144 . +_:genid145 . +_:genid145 . +# +_:genid146 . +_:genid146 _:genid149 . +_:genid149 _:genid148 . +_:genid148 _:genid147 . +_:genid147 . +_:genid147 . +_:genid147 . +_:genid148 . +_:genid148 . +_:genid149 . +_:genid149 . +# 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+_:genid248 . +_:genid249 . +_:genid249 . +_:genid250 . +_:genid250 . +_:genid251 . +_:genid251 . +# +_:genid252 . +_:genid252 _:genid256 . +_:genid256 _:genid255 . +_:genid255 _:genid254 . +_:genid254 _:genid253 . +_:genid253 . +_:genid253 . +_:genid253 . +_:genid254 . +_:genid254 . +_:genid255 . +_:genid255 . +_:genid256 . +_:genid256 . +# +_:genid257 . +_:genid257 _:genid260 . +_:genid260 _:genid259 . +_:genid259 _:genid258 . +_:genid258 . +_:genid258 . +_:genid258 . +_:genid259 . +_:genid259 . +_:genid260 . +_:genid260 . +# +_:genid261 . +_:genid261 _:genid271 . +_:genid271 _:genid270 . +_:genid270 _:genid269 . +_:genid269 _:genid268 . +_:genid268 _:genid267 . +_:genid267 _:genid266 . +_:genid266 _:genid265 . +_:genid265 _:genid264 . +_:genid264 _:genid263 . +_:genid263 _:genid262 . +_:genid262 . +_:genid262 . +_:genid262 . +_:genid263 . +_:genid263 . +_:genid264 . +_:genid264 . +_:genid265 . +_:genid265 . +_:genid266 . +_:genid266 . +_:genid267 . +_:genid267 . +_:genid268 . +_:genid268 . +_:genid269 . +_:genid269 . +_:genid270 . +_:genid270 . +_:genid271 . +_:genid271 . +# +_:genid272 . +_:genid272 _:genid278 . +_:genid278 _:genid277 . +_:genid277 _:genid276 . +_:genid276 _:genid275 . +_:genid275 _:genid274 . +_:genid274 _:genid273 . +_:genid273 . +_:genid273 . +_:genid273 . +_:genid274 . +_:genid274 . +_:genid275 . +_:genid275 . +_:genid276 . +_:genid276 . +_:genid277 . +_:genid277 . +_:genid278 . +_:genid278 . +# +# Generated by the OWL API (version 5.1.18) https://github.com/owlcs/owlapi/ diff --git a/doc/releases/0.1.0/neao.ttl b/doc/releases/0.1.0/neao.ttl new file mode 100644 index 0000000..07a87c0 --- /dev/null +++ b/doc/releases/0.1.0/neao.ttl @@ -0,0 +1,6210 @@ +@prefix : . +@prefix owl: . +@prefix rdf: . +@prefix xml: . +@prefix xsd: . +@prefix rdfs: . +@base . + + rdf:type owl:Ontology ; + owl:versionIRI ; + "2022-01-19" ; + "Cristiano Köhler (ORCID: 0000-0003-0503-5264)" , + "Michael Denker (ORCID: 0000-0003-1255-7300)" ; + ; + "neao" ; + "http://purl.org/neao/" ; + rdfs:comment """The Neuroelectrophysiology Analysis Ontology (NEAO) defines a controlled vocabulary and conceptual representations of the typical processes involved in the analysis of neural activity data acquired using electrophysiology techniques. + +Electrophysiology is a branch of physiology that studies the electrical properties of biological entities. The studies involve measurements of electric potentials and/or currents, as well as electrical manipulations (e.g. stimuli with electric pulses). Neuroelectrophysiology is the application of electrophysiology techniques to investigate the function of neural tissue. + +Neuroelectrophysiology recording is the process of data acquisition, and it usually involves placing electrodes (of several configurations and types) into a preparation of neural tissue. The data will contain a representation of the voltages or currents in the preparation during the recording session, usually as a time series. The analysis requires specific methods to progressively process and transform the recorded data, which generate results and insights. + +The scope of the NEAO aims to provide a comprehensive representation of neuroelectrophysiology data and analysis processes, standardizing the description of their properties and relationships. The NEAO does not provide a detailed representation of electrophysiology recording techniques, data acquisition methods/equipment, and experimental settings/subjects. The goal is to ensure a common representation of data analysis that can be used by tools to provide a detailed and semantically-enriched description of the processes involved."""@en ; + rdfs:label "Neuroelectrophysiology Analysis Ontology"@en ; + owl:versionInfo "0.1.0" . + +################################################################# +# Annotation properties +################################################################# + +### http://purl.org/dc/terms/bibliographicCitation + rdf:type owl:AnnotationProperty . + + +### http://purl.org/dc/terms/created + rdf:type owl:AnnotationProperty . + + +### http://purl.org/dc/terms/creator + rdf:type owl:AnnotationProperty . + + +### http://purl.org/dc/terms/license + rdf:type owl:AnnotationProperty . + + +### http://purl.org/neao/base#abbreviation + rdf:type owl:AnnotationProperty ; + rdfs:comment "A string defining an abbreviation that is frequently used to refer to individuals represented by the class."@en ; + "abbreviation"@en ; + rdfs:range xsd:string . + + +### http://purl.org/neao/base#hasBibliographicReference + rdf:type owl:AnnotationProperty ; + rdfs:comment "Defines the bibliographic reference associated with the entity. The bibliographic reference should contain the details represented by the entity (e.g., method description, software publication)."@en ; + "has bibliographic reference"@en ; + rdfs:range . + + +### http://purl.org/vocab/vann/preferredNamespacePrefix + rdf:type owl:AnnotationProperty . + + +### http://purl.org/vocab/vann/preferredNamespaceUri + rdf:type owl:AnnotationProperty . + + +### http://www.w3.org/2004/02/skos/core#altLabel + rdf:type owl:AnnotationProperty . + + +### http://www.w3.org/2004/02/skos/core#editorialNote + rdf:type owl:AnnotationProperty . + + +### http://www.w3.org/2004/02/skos/core#prefLabel + rdf:type owl:AnnotationProperty . + + +################################################################# +# Object Properties +################################################################# + +### http://purl.org/neao/base#hasInput + rdf:type owl:ObjectProperty ; + rdfs:domain ; + rdfs:range ; + rdfs:comment "Defines a data entity that is used to provide information for one analysis step. The analysis step will make use of this information and produce zero or more data entities as outputs."@en ; + "has input"@en . + + +### http://purl.org/neao/base#hasOutput + rdf:type owl:ObjectProperty ; + rdfs:domain ; + rdfs:range ; + rdfs:comment "Defines a data entity that was produced by an analysis step. This can be newly data generated by the analysis step, or derived data, based on one or more data inputs."@en ; + "has output"@en . + + +### http://purl.org/neao/base#hasSource + rdf:type owl:ObjectProperty ; + rdfs:domain ; + rdfs:range ; + rdfs:comment "Defines the electrophysiology signal source associated with the data entity. One example of use is to define if the data holds a signal obtained by extracellular recordings, or a more specific description involving anatomical structures together with the recording technique."@en ; + "has source"@en . + + +### http://purl.org/neao/base#hasSubstep + rdf:type owl:ObjectProperty ; + rdfs:domain ; + rdfs:range ; + rdfs:comment "Points to an analysis step that is part of a (larger) compound analysis, represented by the subject with the property."@en ; + "has substep"@en . + + +### http://purl.org/neao/base#isImplementedIn + rdf:type owl:ObjectProperty ; + rdfs:domain ; + rdfs:range ; + rdfs:comment "Defines the code source that implemented the analysis step."@en ; + "is implemented in"@en . + + +### http://purl.org/neao/base#isImplementedInPackage + rdf:type owl:ObjectProperty ; + rdfs:domain ; + rdfs:range ; + rdfs:comment "Defines the software package that contains a particular code."@en ; + "is implemented in package"@en . + + +### http://purl.org/neao/base#isRepresentedAs + rdf:type owl:ObjectProperty ; + rdfs:domain ; + rdfs:range ; + rdfs:comment "Defines how the data entity is represented to be used by software (e.g., data array, list, file)"@en ; + "is represented as"@en . + + +### http://purl.org/neao/base#usesParameter + rdf:type owl:ObjectProperty ; + rdfs:domain ; + rdfs:range ; + rdfs:comment "Defines a parameter used by the analysis step."@en ; + "uses parameter"@en . + + +### http://purl.org/neao/steps#hasPurpose + rdf:type owl:ObjectProperty ; + rdfs:domain ; + rdfs:range ; + rdfs:comment "Defines an analysis purpose for the analysis step. This property is used to group analysis steps according to their similarity."@en ; + "has purpose"@en . + + +### http://purl.org/spar/biro/references + rdf:type owl:ObjectProperty ; + rdfs:domain . + + +################################################################# +# Data properties +################################################################# + +### http://purl.org/neao/base#nameInDefinition + rdf:type owl:DatatypeProperty ; + rdfs:domain ; + rdfs:range xsd:string ; + rdfs:comment "Specifies the name of the function as it is defined in the code that implemented it. For example, for Python functions, this is what is specified in the 'def' statement (i.e., def function_name(arg), the value of this property is function_name)."@en ; + "name in definition"@en . + + +### http://purl.org/neao/base#packageName + rdf:type owl:DatatypeProperty ; + rdfs:domain ; + rdfs:range rdfs:Literal ; + rdfs:comment "Version of the software package."@en ; + "package version"@en . + + +### http://purl.org/neao/base#packageVersion + rdf:type owl:DatatypeProperty ; + rdfs:domain ; + rdfs:range rdfs:Literal ; + rdfs:comment "Specifies the version of the package, as defined by the string used when it was released."@en ; + "package version"@en . + + +### http://purl.org/neao/base#programName + rdf:type owl:DatatypeProperty ; + rdfs:domain ; + rdfs:range xsd:string ; + rdfs:comment "Defines the name of the program."@en ; + "program name"@en . + + +### http://purl.org/neao/base#version + rdf:type owl:DatatypeProperty ; + rdfs:domain ; + rdfs:range rdfs:Literal ; + rdfs:comment "Version of the code for a specific program or function. This can be used to define a specific version for the code of a single function or program within a software package."@en ; + "version"@en . + + +### http://purl.org/neao/data#isArtificial + rdf:type owl:DatatypeProperty ; + rdfs:subPropertyOf owl:topDataProperty ; + rdfs:domain ; + rdfs:range xsd:boolean ; + rdfs:comment "Defines if the data is artificially-generated (true) or obtained from experimental recordings (false)."@en ; + "is artificial"@en . + + +### http://purl.org/neao/data#isAveraged + rdf:type owl:DatatypeProperty ; + rdfs:subPropertyOf owl:topDataProperty ; + rdfs:domain ; + rdfs:range xsd:boolean ; + rdfs:comment "Defines if the data is the result of an aggregation to obtain an average estimate from other data (true)."@en ; + "is averaged"@en . + + +### http://purl.org/neao/data#isDetrended + rdf:type owl:DatatypeProperty ; + rdfs:subPropertyOf owl:topDataProperty ; + rdfs:domain ; + rdfs:range xsd:boolean ; + rdfs:comment "Defines if a detrending transformation was applied to the data (true)."@en ; + "is detrended"@en . + + +### http://purl.org/neao/data#isDimensionalityReduction + rdf:type owl:DatatypeProperty ; + rdfs:subPropertyOf owl:topDataProperty ; + rdfs:domain ; + rdfs:range xsd:boolean ; + rdfs:comment "Defines if the data is a result of a dimensionality reduction transformation (true)."@en ; + "is dimensionality reduction"@en . + + +### http://purl.org/neao/data#isDownsampled + rdf:type owl:DatatypeProperty ; + rdfs:subPropertyOf ; + rdfs:domain ; + rdfs:range xsd:boolean ; + rdfs:comment "Defines if a downsampling transformation was applied to the data (true)."@en ; + "is downsampled"@en . + + +### http://purl.org/neao/data#isFiltered + rdf:type owl:DatatypeProperty ; + rdfs:subPropertyOf owl:topDataProperty ; + rdfs:domain ; + rdfs:range xsd:boolean ; + rdfs:comment "Defines if a digital filter was applied to the data (true)."@en ; + "is filtered"@en . + + +### http://purl.org/neao/data#isInterpolated + rdf:type owl:DatatypeProperty ; + rdfs:subPropertyOf owl:topDataProperty ; + rdfs:domain ; + rdfs:range xsd:boolean ; + rdfs:comment "Defines if a interpolation data transformation was applied to the data (true)."@en ; + "is interpolated"@en . + + +### http://purl.org/neao/data#isNormalized + rdf:type owl:DatatypeProperty ; + rdfs:subPropertyOf owl:topDataProperty ; + rdfs:domain ; + rdfs:range xsd:boolean ; + rdfs:comment "Defines if a data normalization transformation was applied to the data (true)."@en ; + "is normalized"@en . + + +### http://purl.org/neao/data#isRectified + rdf:type owl:DatatypeProperty ; + rdfs:subPropertyOf owl:topDataProperty ; + rdfs:domain ; + rdfs:range xsd:boolean ; + rdfs:comment "Defines if a rectification transformation was applied to the data (true)."@en ; + "is rectified"@en . + + +### http://purl.org/neao/data#isRereferenced + rdf:type owl:DatatypeProperty ; + rdfs:subPropertyOf owl:topDataProperty ; + rdfs:domain ; + rdfs:range xsd:boolean ; + rdfs:comment "Defines if a transformation to change the reference in the recorded data was applied (true)."@en ; + "is rereferenced"@en . + + +### http://purl.org/neao/data#isResampled + rdf:type owl:DatatypeProperty ; + rdfs:subPropertyOf owl:topDataProperty ; + rdfs:domain ; + rdfs:range xsd:boolean ; + rdfs:comment "Defines if a resampling transformation was applied to the data (true)."@en ; + "is resampled"@en . + + +### http://purl.org/neao/data#isSmoothed + rdf:type owl:DatatypeProperty ; + rdfs:subPropertyOf owl:topDataProperty ; + rdfs:domain ; + rdfs:range xsd:boolean ; + rdfs:comment "Defines if a data smoothing transformation was applied to the data (true)."@en ; + "is smoothed"@en . + + +### http://purl.org/neao/data#isUpsampled + rdf:type owl:DatatypeProperty ; + rdfs:subPropertyOf ; + rdfs:domain ; + rdfs:range xsd:boolean ; + rdfs:comment "Defines if an upsampling transformation was applied to the data (true)."@en ; + "is upsampled"@en . + + +### http://purl.org/neao/steps#isBivariate + rdf:type owl:DatatypeProperty ; + rdfs:subPropertyOf owl:topDataProperty ; + rdfs:domain ; + rdfs:range xsd:boolean ; + rdfs:comment "Defines if the analysis step uses two data inputs (true)."@en ; + "is bivariate"@en . + + +### http://purl.org/neao/steps#isDirected + rdf:type owl:DatatypeProperty ; + rdfs:subPropertyOf owl:topDataProperty ; + rdfs:domain ; + rdfs:range xsd:boolean ; + rdfs:comment "Defines if the analysis step is used to perform an analysis providing information on the direction of the association between the inputs (true) opposed to no direction information (false)."@en ; + "is directed"@en . + + +### http://purl.org/neao/steps#isFrequencyDomain + rdf:type owl:DatatypeProperty ; + rdfs:subPropertyOf owl:topDataProperty ; + rdfs:domain ; + rdfs:range xsd:boolean ; + rdfs:comment "Defines if the analysis in the step is performed in the frequency domain (true)."@en ; + "is frequency domain"@en . + + +### http://purl.org/neao/steps#isModelBased + rdf:type owl:DatatypeProperty ; + rdfs:subPropertyOf owl:topDataProperty ; + rdfs:domain ; + rdfs:range xsd:boolean ; + rdfs:comment "Defines if the step performs a model-based (true) or model-free analysis (false)."@en ; + "is model-based"@en . + + +### http://purl.org/neao/steps#isMultivariate + rdf:type owl:DatatypeProperty ; + rdfs:subPropertyOf owl:topDataProperty ; + rdfs:domain ; + rdfs:range xsd:boolean ; + rdfs:comment "Defines if the analysis step uses three or more data inputs (true)."@en ; + "is multivariate"@en . + + +### http://purl.org/neao/steps#isTimeDomain + rdf:type owl:DatatypeProperty ; + rdfs:subPropertyOf owl:topDataProperty ; + rdfs:domain ; + rdfs:range xsd:boolean ; + rdfs:comment "Defines if the analysis in the step is performed in the time domain (true)."@en ; + "is time domain"@en . + + +################################################################# +# Classes +################################################################# + +### http://purl.org/neao/base#AnalysisParameter + rdf:type owl:Class ; + rdfs:comment "An information entity that controls the behavior of an analysis step. It does not provide data, but rather changes how the computations operate when transforming or generating new data."@en ; + "parameter"@en . + + +### http://purl.org/neao/base#AnalysisStep + rdf:type owl:Class ; + rdfs:comment "A process that generates new data entities or performs specific operations (clean, select, transform, or inspect/visualize) using existing data entities. Ultimately, the goal is to obtain useful information from the data. An analysis step can take zero or more data inputs and can generate one or more data outputs. The behavior of the operation can optionally be controlled by one or more parameters. A complete analysis is composed by one or more analysis steps."@en ; + "analysis step"@en . + + +### http://purl.org/neao/base#Data + rdf:type owl:Class ; + rdfs:comment "An entity that represents a piece of data, i.e., relevant information, during the analysis. It can be recorded from a biological entity or from a simulation yielding comparable data, or it can be generated/transformed by other analysis step processes."@en ; + "data"@en . + + +### http://purl.org/neao/base#DataRepresentation + rdf:type owl:Class ; + rdfs:comment "Defines the formal structure to represent a piece of data."@en ; + "data representation"@en . + + +### http://purl.org/neao/base#ElectrophysiologySignalSource + rdf:type owl:Class ; + rdfs:comment """Defines the source of a recorded piece of electrophysiology data, i.e., the recorded signals. This is a general concept, that can be expanded to incorporate the anatomical/tissue description from where the signal was recorded, as well as the recording technique. + +For example, voltage potentials can be acquired from extracellular electrodes situtated on the scalp (electroencephalogram), directly on the cortical surface (electrocorticogram) or implanted deep into a specific brain region (multielectrode array)."""@en ; + "electrophysiology signal source"@en . + + +### http://purl.org/neao/base#Function + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A reusable set of instructions that can be used when writing computer programs. A function performs specific tasks, and can be implemented as part of a single computer program or in a software package (library) so that it can be reused across several programs."@en ; + "function"@en . + + +### http://purl.org/neao/base#Program + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A set of instructions that is executed by a computer. The instructions of the program can be executed by an interpreter or compiled to machine code. The program instructs the computer to perform tasks and it is called by the operating system."@en ; + "program"@en . + + +### http://purl.org/neao/base#SoftwareImplementation + rdf:type owl:Class ; + owl:disjointWith ; + rdfs:comment "Describes the details for the execution of the analysis step using a computer. The software contains a sequence or set of instructions that is used by the computer to perform all the computations required to execute the analysis step."@en ; + "software implementation"@en . + + +### http://purl.org/neao/base#SoftwarePackage + rdf:type owl:Class ; + rdfs:comment "A collection of one or more programs that can be executed by a computer and/or one or more functions that can be imported and used when writing programs."@en ; + "software package"@en . + + +### http://purl.org/neao/data#ASSETAnalysisMatrix + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Data that contains a matrix computed by one of the ASSET analysis substeps, as part of the execution of the ASSET analysis for the detection of neuronal activity patterns."@en ; + "ASSET analysis matrix"@en . + + +### http://purl.org/neao/data#ASSETClusterMatrix + rdf:type owl:Class ; + rdfs:subClassOf ; + "CMAT"@en ; + rdfs:comment "The cluster matrix (CMAT) computed in the ASSET analysis."@en ; + "ASSET cluster matrix"@en . + + +### http://purl.org/neao/data#ASSETIntersectionMatrix + rdf:type owl:Class ; + rdfs:subClassOf ; + "IMAT"@en ; + rdfs:comment "The intersection matrix (IMAT) computed in the ASSET analysis."@en ; + "ASSET intersection matrix"@en . + + +### http://purl.org/neao/data#ASSETJointProbabilityMatrix + rdf:type owl:Class ; + rdfs:subClassOf ; + "JMAT"@en ; + rdfs:comment "The joint probability matrix (JMAT) computed in the ASSET analysis."@en ; + "ASSET joint probability matrix"@en . + + +### http://purl.org/neao/data#ASSETMaskMatrix + rdf:type owl:Class ; + rdfs:subClassOf ; + "MMAT"@en ; + rdfs:comment "The mask matrix (MMAT) computed in the ASSET analysis."@en ; + "ASSET mask matrix"@en . + + +### http://purl.org/neao/data#ASSETPattern + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A neuronal activity pattern obtained by the ASSET analysis. The ASSET patterns are the output of the last substep of the ASSET analysis that identifies the neurons present in each repeated sequence, based on the diagonal structures in the cluster matrix."@en ; + "ASSET pattern"@en . + + +### http://purl.org/neao/data#ASSETProbabilityMatrix + rdf:type owl:Class ; + rdfs:subClassOf ; + "PMAT"@en ; + rdfs:comment "The probability matrix (PMAT) computed in the ASSET analysis."@en ; + "ASSET probability matrix"@en . + + +### http://purl.org/neao/data#AnalyticSignal + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The analytic signal obtained from a time series using the Hilbert transform."@en ; + "analytic signal"@en . + + +### http://purl.org/neao/data#AngularMeanSpikePhases + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed angular mean of the spike phases."@en ; + "angular mean of spike phases"@en . + + +### http://purl.org/neao/data#ArtificialData + rdf:type owl:Class ; + owl:equivalentClass [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + rdfs:subClassOf ; + rdfs:comment "Data that is generated programmatically rather than obtained from experimental recordings."@en ; + "artificial data"@en . + + +### http://purl.org/neao/data#AutocorrelationFunction + rdf:type owl:Class ; + rdfs:subClassOf ; + "ACF"@en ; + rdfs:comment "The computed estimator of the autocorrelation function."@en ; + "autocorrelation function"@en . + + +### http://purl.org/neao/data#AutocorrelationMeasure + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Data that contains a measure of autocorrelation."@en ; + "autocorrelation measure"@en . + + +### http://purl.org/neao/data#BinnedSpikeTrain + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The output of applying binning to the input spike train data."@en ; + "binned spike train"@en . + + +### http://purl.org/neao/data#CV + rdf:type owl:Class ; + rdfs:subClassOf ; + "CV"@en ; + rdfs:comment "The computed coefficient of variation (CV)."@en ; + "coefficient of variation"@en . + + +### http://purl.org/neao/data#CV2 + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed CV2 measure."@en ; + "CV2"@en . + + +### http://purl.org/neao/data#CVInterspikeIntervals + rdf:type owl:Class ; + rdfs:subClassOf ; + "CV ISIs"@en ; + rdfs:comment "The computed coefficient of variation (CV) of the interspike intervals (ISIs)."@en ; + "coefficient of variation of the interspike intervals"@en . + + +### http://purl.org/neao/data#CanonicalCoherence + rdf:type owl:Class ; + rdfs:subClassOf ; + "caCOH"@en ; + rdfs:comment "The computed canonical coherence (caCOH)."@en ; + "canonical coherence"@en . + + +### http://purl.org/neao/data#CellAssemblyDetectionPattern + rdf:type owl:Class ; + rdfs:subClassOf ; + "CAD pattern"@en ; + rdfs:comment "A neuronal activity pattern obtained by the Cell Assembly Detection (CAD) analysis."@en ; + "Cell Assembly Detection pattern"@en . + + +### http://purl.org/neao/data#ChangePoint + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A change point identified by the rate change detection multiple filter test."@en ; + "change point"@en . + + +### http://purl.org/neao/data#Coherence + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed magnitude squared coherence. This is the typical output of a computation estimating coherence, and it is frequently referred as just coherence."@en ; + "magnitude squared coherence"@en ; + "coherence"@en . + + +### http://purl.org/neao/data#CoherenceMeasure + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Data that contains a measure of coherence."@en ; + "coherence measure"@en . + + +### http://purl.org/neao/data#Coherency + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed coherency."@en ; + "complex coherency"@en ; + "coherency"@en . + + +### http://purl.org/neao/data#CoherencyMeasure + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Data that contains a measure of coherency."@en ; + "coherency measure"@en . + + +### http://purl.org/neao/data#ComplexityDistribution + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed complexity distribution across the spike trains."@en ; + "complexity distribution"@en . + + +### http://purl.org/neao/data#ConditionalGrangerCausality + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed conditional Granger causality."@en ; + "conditional Granger causality"@en . + + +### http://purl.org/neao/data#ConfidenceInterval + rdf:type owl:Class ; + rdfs:subClassOf ; + "CI"@en ; + rdfs:comment "The computed confidence interval (CI), with the lower and upper limits."@en ; + "confidence interval"@en . + + +### http://purl.org/neao/data#ConfidenceIntervalLowerLimit + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The lower limit value of the computed confidence interval."@en ; + "lower limit of confidence interval"@en . + + +### http://purl.org/neao/data#ConfidenceIntervalMeasure + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Data that contains the description of a confidence interval (CI)."@en ; + "CI measure"@en ; + "confidence interval measure"@en . + + +### http://purl.org/neao/data#ConfidenceIntervalUpperLimit + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The upper limit value of the computed confidence interval."@en ; + "upper limit of confidence interval"@en . + + +### http://purl.org/neao/data#CorrectedImaginaryPhaseLockingValue + rdf:type owl:Class ; + rdfs:subClassOf ; + "ciPLV"@en ; + rdfs:comment "The computed corrected imaginary phase locking value (ciPLV)."@en ; + "corrected imaginary phase locking value"@en . + + +### http://purl.org/neao/data#CorrelationMeasure + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Data that contains a measure of correlation."@en ; + "correlation measure"@en . + + +### http://purl.org/neao/data#Covariance + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed covariance values between the inputs."@en ; + "covariance"@en . + + +### http://purl.org/neao/data#CovarianceMeasure + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Data that contains a measure of covariance."@en ; + "covariance measure"@en . + + +### http://purl.org/neao/data#CrossCorrelationFunction + rdf:type owl:Class ; + rdfs:subClassOf ; + "CCF"@en ; + rdfs:comment "The computed estimator of the cross-correlation function."@en ; + "cross-correlation function"@en . + + +### http://purl.org/neao/data#CrossCorrelationMeasure + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Data that contains a measure of cross-correlation."@en ; + "cross-correlation measure"@en . + + +### http://purl.org/neao/data#CrossPowerSpectralDensity + rdf:type owl:Class ; + rdfs:subClassOf ; + "CPSD"@en ; + rdfs:comment "The computed cross power spectral density (CPSD)."@en ; + "cross-spectrum"@en ; + "cross power spectral density"@en . + + +### http://purl.org/neao/data#CrossSpectrogram + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed cross-spectrogram."@en ; + "cross-spectrogram"@en . + + +### http://purl.org/neao/data#CubicAnalysisResult + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The result of the CuBIC analysis."@en ; + "CuBIC analysis result"@en . + + +### http://purl.org/neao/data#CurrentSourceDensity + rdf:type owl:Class ; + rdfs:subClassOf ; + "CSD"@en ; + rdfs:comment "The profile of current densities estimated by a current source density analysis."@en ; + "current source density"@en . + + +### http://purl.org/neao/data#DebiasedSquaredWeightedPhaseLagIndex + rdf:type owl:Class ; + rdfs:subClassOf ; + "debiased squared WPLI"@en ; + rdfs:comment "The computed debiased squared weighted phase lag index (WPLI)."@en ; + "debiased squared weighted phase lag index"@en . + + +### http://purl.org/neao/data#DimensionalityReductionOutput + rdf:type owl:Class ; + owl:equivalentClass [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + rdfs:subClassOf ; + rdfs:comment "Data that contains an output of applying a dimensionality reduction transformation to the input data."@en ; + "dimensionality reduction output"@en . + + +### http://purl.org/neao/data#DirectedPhaseLagIndex + rdf:type owl:Class ; + rdfs:subClassOf ; + "DPLI"@en ; + rdfs:comment "The computed directed phase lag index (DPLI)."@en ; + "directed phase lag index"@en . + + +### http://purl.org/neao/data#DirectedTransferFunction + rdf:type owl:Class ; + rdfs:subClassOf ; + "DTF"@en ; + rdfs:comment "The computed directed transfer function (DTF)."@en ; + "directed transfer function"@en . + + +### http://purl.org/neao/data#DirectionalGrangerCausality + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed directional Granger causality from one input to the other."@en ; + "directional Granger causality"@en . + + +### http://purl.org/neao/data#DiscreteFourierTransform + rdf:type owl:Class ; + rdfs:subClassOf ; + "DFT"@en ; + rdfs:comment "The complex sinusoid coefficients obtained by applying the Discrete Fourier Transform (DFT) to the input data (e.g., using the FFT algorithm)."@en ; + "discrete Fourier transform"@en . + + +### http://purl.org/neao/data#DistanceCovarianceDimension + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A dimension identified by applying distance covariance analysis (DCA) to the input data."@en ; + "distance covariance dimension"@en . + + +### http://purl.org/neao/data#Epoch + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Data that represents a finite time interval (window). For example, the interval between the start and end of a behavioral trial in the recording session."@en ; + "epoch"@en . + + +### http://purl.org/neao/data#Event + rdf:type owl:Class ; + rdfs:subClassOf ; + owl:disjointWith , + , + ; + rdfs:comment "Data that contains the time(s) when an event of interest occurred (e.g., a certain behavior or stimulus in an experimental trial)."@en ; + "event"@en . + + +### http://purl.org/neao/data#EventRelatedPotential + rdf:type owl:Class ; + rdfs:subClassOf ; + "ERP"@en ; + rdfs:comment "The computed event-related potential (ERP)."@en ; + "event-related potential"@en . + + +### http://purl.org/neao/data#EventTriggeredAverage + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed event-triggered average."@en ; + "event-triggered average"@en . + + +### http://purl.org/neao/data#EvokedPotential + rdf:type owl:Class ; + rdfs:subClassOf ; + "EP"@en ; + rdfs:comment "The computed evoked potential (EP)."@en ; + "evoked potential"@en . + + +### http://purl.org/neao/data#FiringRate + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed firing rate."@en ; + "firing rate"@en . + + +### http://purl.org/neao/data#FisherLinearDiscriminant + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A Fisher linear discriminant obtained by applying linear discrimination analysis (LDA) to the input data."@en ; + "Fisher linear discriminant"@en . + + +### http://purl.org/neao/data#GrangerCausalityMeasure + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Data that contains a measure of Granger causality."@en ; + "Granger causality measure"@en . + + +### http://purl.org/neao/data#GrangerTotalInterdependence + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed total interdependence in the Granger causality analysis."@en ; + "Granger total interdependence"@en . + + +### http://purl.org/neao/data#ISIDistance + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed ISI-distance."@en ; + "ISI-distance"@en . + + +### http://purl.org/neao/data#ImaginaryCoherency + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed imaginary part of the coherency."@en ; + "imaginary coherency"@en . + + +### http://purl.org/neao/data#IndependentComponent + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Data that contains an independent component produced by applying independent component analysis (ICA) to the input data."@en ; + "independent component"@en . + + +### http://purl.org/neao/data#InstantaneousFiringRate + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed instantaneous firing rate."@en ; + "instantaneous firing rate"@en . + + +### http://purl.org/neao/data#InstantaneousGrangerCausality + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed instantaneous Granger causality."@en ; + "instantaneous Granger causality"@en . + + +### http://purl.org/neao/data#InterquartileRange + rdf:type owl:Class ; + rdfs:subClassOf ; + "IQR"@en ; + rdfs:comment "The computed interquartile range, with the difference between the 75th and 25th percentile values."@en ; + "interquartile range"@en . + + +### http://purl.org/neao/data#InterquartileRangeLowerLimit + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The lower limit of the computed interquartile range, corresponding to the 25th percentile."@en ; + "lower limit of interquartile range"@en . + + +### http://purl.org/neao/data#InterquartileRangeMeasure + rdf:type owl:Class ; + rdfs:subClassOf ; + "IQR measure"@en ; + rdfs:comment "Data that contains the description of an interquartile range (IQR)."@en ; + "interquartile range measure"@en . + + +### http://purl.org/neao/data#InterquartileRangeUpperLimit + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The upper limit of the computed interquartile range, corresponding to the 75th percentile."@en ; + "upper limit of interquartile range"@en . + + +### http://purl.org/neao/data#InterspikeIntervalHistogram + rdf:type owl:Class ; + rdfs:subClassOf ; + "ISIH"@en ; + rdfs:comment "The computed interspike interval histogram (ISIH)."@en ; + "interspike interval histogram"@en . + + +### http://purl.org/neao/data#InterspikeIntervalVariabilityMeasure + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Data that contains a measure describing the variability of the interspike intervals."@en ; + "interspike interval variability measure"@en . + + +### http://purl.org/neao/data#InterspikeIntervals + rdf:type owl:Class ; + rdfs:subClassOf ; + "ISIs"@en ; + rdfs:comment "The computed interspike intervals (ISIs)."@en ; + "interspike intervals"@en . + + +### http://purl.org/neao/data#JointPeristimulusTimeHistogramMatrix + rdf:type owl:Class ; + rdfs:subClassOf ; + "JPSTH matrix"@en ; + rdfs:comment "The computed joint peristimulus time histogram (JPSTH) matrix."@en ; + "joint peristimulus time histogram matrix"@en . + + +### http://purl.org/neao/data#LV + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed local variation (LV) measure."@en ; + "LV"@en . + + +### http://purl.org/neao/data#LVR + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed revised local variation (LvR) measure."@en ; + "LvR"@en . + + +### http://purl.org/neao/data#MagnitudeCoherence + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed magnitude coherence."@en ; + "magnitude coherence"@en . + + +### http://purl.org/neao/data#MaximizedImaginaryCoherency + rdf:type owl:Class ; + rdfs:subClassOf ; + "MIC"@en ; + rdfs:comment "The computed maximized imaginary coherency (MIC)."@en ; + "maximized imaginary coherency"@en . + + +### http://purl.org/neao/data#Mean + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed mean."@en ; + "mean"@en . + + +### http://purl.org/neao/data#MeanFiringRate + rdf:type owl:Class ; + rdfs:subClassOf ; + "MFR"@en ; + rdfs:comment "The computed mean firing rate."@en ; + "mean firing rate"@en . + + +### http://purl.org/neao/data#MeanPhaseVector + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed mean phase vector (i.e., the angle and length)."@en ; + "mean phase vector"@en . + + +### http://purl.org/neao/data#MeanPhaseVectorAngle + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The angle of the computed mean phase vector."@en ; + "mean phase vector angle"@en . + + +### http://purl.org/neao/data#MeanPhaseVectorLength + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The length of the computed mean phase vector."@en ; + "mean phase vector length"@en . + + +### http://purl.org/neao/data#MeanPhaseVectorMeasure + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Data that contains the description or elements of the mean phase vector."@en ; + "mean phase vector measure"@en . + + +### http://purl.org/neao/data#MeanVectorLength + rdf:type owl:Class ; + rdfs:subClassOf ; + "MVL"@en ; + rdfs:comment "The computed mean vector length (MVL)."@en ; + "mean vector length"@en . + + +### http://purl.org/neao/data#Median + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed median."@en ; + "median"@en . + + +### http://purl.org/neao/data#ModulationIndex + rdf:type owl:Class ; + rdfs:subClassOf ; + "MI"@en ; + rdfs:comment "The computed modulation index (MI)."@en ; + "modulation index"@en . + + +### http://purl.org/neao/data#MorletWavelet + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Data that contains the generated Morlet wavelet values for a sequence of time points."@en ; + "Morlet wavelet"@en . + + +### http://purl.org/neao/data#MultivariateInteractionMeasure + rdf:type owl:Class ; + rdfs:subClassOf ; + "MIM"@en ; + rdfs:comment "The computed multivariate interaction measure (MIM)."@en ; + "multivariate interaction measure"@en . + + +### http://purl.org/neao/data#MutualInformation + rdf:type owl:Class ; + rdfs:subClassOf ; + "MI"@en ; + rdfs:comment "The computed mutual information (MI)."@en ; + "mutual information"@en . + + +### http://purl.org/neao/data#NeuralTrajectory + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + rdfs:comment "A neural trajectory obtained by applying Gaussian process factor analysis (GPFA) to the input data containing multitrial spiking activity of a neuronal population."@en ; + "neural trajectory"@en . + + +### http://purl.org/neao/data#NeuronalActivityPattern + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Data that contains the description of a neuronal activity pattern, which is obtained from a neuronal activity pattern detection analysis."@en ; + "cell assembly"@en , + "neuronal assembly"@en ; + "neuronal activity pattern"@en . + + +### http://purl.org/neao/data#NeuronalPopulationVector + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed neuronal population vector."@en ; + "population vector"@en ; + "neuronal population vector"@en . + + +### http://purl.org/neao/data#NoiseCorrelations + rdf:type owl:Class ; + rdfs:subClassOf ; + "NC"@en ; + rdfs:comment "The computed noise correlations (NC)."@en ; + "noise correlations"@en . + + +### http://purl.org/neao/data#NoiseCovariance + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed noise covariance."@en ; + "noise covariance"@en . + + +### http://purl.org/neao/data#OrthogonalizedPowerEnvelopeCorrelation + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed orthogonalized power envelope correlation."@en ; + "orthogonalized power envelope correlation"@en . + + +### http://purl.org/neao/data#PairwisePhaseConsistency + rdf:type owl:Class ; + rdfs:subClassOf ; + "PPC"@en ; + rdfs:comment "The computed pairwise phase consistency (PPC) measure."@en ; + "pairwise phase consistency"@en . + + +### http://purl.org/neao/data#PartialCoherence + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed partial coherence."@en ; + "partial coherence"@en . + + +### http://purl.org/neao/data#PartialDirectedCoherence + rdf:type owl:Class ; + rdfs:subClassOf ; + "PDC"@en ; + rdfs:comment "The computed partial directed coherence (PDC)."@en ; + "partial directed coherence"@en . + + +### http://purl.org/neao/data#PeristimulusCoincidenceHistogram + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed peristimulus coincidence histogram."@en ; + "peristimulus coincidence histogram"@en . + + +### http://purl.org/neao/data#PeristimulusTimeHistogram + rdf:type owl:Class ; + rdfs:subClassOf ; + "PSTH"@en ; + rdfs:comment "The computed peristimulus time histogram (PSTH). The stimulus or event of interest can occur at any time point within the interval analyzed. However, if the histogram represents the neuronal activity after the stimulus presentation or event occurrence, this can be referred as post-stimulus time histogram. Conversely, if the histogram shows the activity of the neuron before the stimulus presentation or event, this can be referred as prestimulus time histogram. Finally, if the histogram considers a behavioral event (or an event that is not an externally presented stimulus), the histogram can be referred to as perievent time histogram (PETH)."@en ; + "perievent time histogram"@en , + "post-stimulus time histogram"@en , + "prestimulus time histogram"@en ; + "peristimulus time histogram"@en . + + +### http://purl.org/neao/data#PhaseAmplitudeCouplingMeasure + rdf:type owl:Class ; + rdfs:subClassOf ; + "PAC measure"@en ; + rdfs:comment "Data that contains a measure of phase-amplitude coupling (PAC)."@en ; + "phase amplitude coupling measure"@en . + + +### http://purl.org/neao/data#PhaseAngles + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A measure of phase defining the angle on the unit circle that corresponds to the current position within the waveform's cycle. The range of angles in a full cycle is from 0 to 2*pi radians or 0 to 360 degrees."@en ; + "phase angles"@en . + + +### http://purl.org/neao/data#PhaseLagIndex + rdf:type owl:Class ; + rdfs:subClassOf ; + "PLI"@en ; + rdfs:comment "The computed phase lag index (PLI)."@en ; + "phase lag index"@en . + + +### http://purl.org/neao/data#PhaseLagIndexMeasure + rdf:type owl:Class ; + rdfs:subClassOf ; + "PLI measure"@en ; + rdfs:comment "Data that contains a measure computed by a phase-lag index analysis."@en ; + "phase lag index measure"@en . + + +### http://purl.org/neao/data#PhaseLockingValue + rdf:type owl:Class ; + rdfs:subClassOf ; + "PLV"@en ; + rdfs:comment "The computed phase locking value (PLV)."@en ; + "phase locking value"@en . + + +### http://purl.org/neao/data#PhaseLockingValueMeasure + rdf:type owl:Class ; + rdfs:subClassOf ; + "PLV measure"@en ; + rdfs:comment "Data that contains a phase locking value (PLV) measure."@en ; + "phase locking value measure"@en . + + +### http://purl.org/neao/data#PhaseSlopeIndex + rdf:type owl:Class ; + rdfs:subClassOf ; + "PSI"@en ; + rdfs:comment "The computed phase slope index (PSI)."@en ; + "phase slope index"@en . + + +### http://purl.org/neao/data#Plot + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A graphical representation of data values. It is used to visually communicate quantitative information, providing intuitive insights that can complement numerical analysis. It is often produced by later steps in the analysis after the computation of measures, to provide the visual representation of the results."@en ; + "plot"@en . + + +### http://purl.org/neao/data#PopulationHistogram + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed population histogram."@en ; + "population histogram"@en . + + +### http://purl.org/neao/data#PowerSpectralDensity + rdf:type owl:Class ; + rdfs:subClassOf ; + "PSD"@en ; + rdfs:comment "The computed power spectral density (PSD)."@en ; + "spectrum"@en ; + "power spectral density"@en . + + +### http://purl.org/neao/data#PrincipalComponent + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A principal component obtained by applying principal component analysis (PCA) to the input data."@en ; + "principal component"@en . + + +### http://purl.org/neao/data#RectifiedAreaUnderCurve + rdf:type owl:Class ; + rdfs:subClassOf ; + "RAUC"@en ; + rdfs:comment "The computed rectified area under the curve (RAUC)."@en ; + "rectified area under the curve"@en . + + +### http://purl.org/neao/data#RegularizedCovariance + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The covariance values computed with regularization techniques for numerical stability."@en ; + "regularized covariance"@en . + + +### http://purl.org/neao/data#SPADEPattern + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A neuronal activity pattern obtained by the Spatio-temporal PAttern Detection and Evaluation (SPADE) analysis."@en ; + "SPADE pattern"@en . + + +### http://purl.org/neao/data#SPIKEDistance + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed SPIKE distance."@en ; + "SPIKE distance"@en . + + +### http://purl.org/neao/data#SPIKESynchronization + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed SPIKE synchronization distance."@en ; + "SPIKE synchronization"@en . + + +### http://purl.org/neao/data#ShortTimeFourierTransform + rdf:type owl:Class ; + rdfs:subClassOf ; + "STFT"@en ; + rdfs:comment "The complex sinusoid coefficients obtained by applying the short-time Fourier transform (STFT) to the input data."@en ; + "short-time Fourier transform"@en . + + +### http://purl.org/neao/data#SpectralDensity + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Data that contains the density of a measure of the input(s) over the frequency spectrum."@en ; + "spectral density"@en . + + +### http://purl.org/neao/data#Spectrogram + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed spectrogram."@en ; + "spectrogram"@en . + + +### http://purl.org/neao/data#SpikeContrast + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed Spike-contrast."@en ; + "Spike-contrast"@en . + + +### http://purl.org/neao/data#SpikeFieldCoherence + rdf:type owl:Class ; + rdfs:subClassOf ; + "SFC"@en ; + rdfs:comment "The computed spike-field coherence (SFC)."@en ; + "spike-field coherence"@en . + + +### http://purl.org/neao/data#SpikeTimeTilingCoefficient + rdf:type owl:Class ; + rdfs:subClassOf ; + "STTC"@en ; + rdfs:comment "The computed spike time tiling coefficient (STTC)."@en ; + "spike time tiling coefficient"@en . + + +### http://purl.org/neao/data#SpikeTrain + rdf:type owl:Class ; + rdfs:subClassOf ; + owl:disjointWith , + ; + rdfs:comment "Data that contains the sequence of time points when an action potential (spike) occurs. A spike train can be obtained by electrophysiological recordings from the neural tissue (i.e., the data contains the times when spikes occur naturally in response to various stimuli or during spontaneous activity) or artificially-generated using specific statistical procedures or simulations of neuronal activity."@en ; + "spike train"@en . + + +### http://purl.org/neao/data#SpikeTrainAutocorrelationHistogram + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed spike train autocorrelation histogram."@en ; + "spike train autocorrelation histogram"@en . + + +### http://purl.org/neao/data#SpikeTrainAutocorrelationTimeScale + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed spike train autocorrelation time scale."@en ; + "spike train autocorrelation time scale"@en . + + +### http://purl.org/neao/data#SpikeTrainCorrelationMeasure + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Data that contains a measure estimating the correlation between spike trains."@en ; + "correlation measure"@en . + + +### http://purl.org/neao/data#SpikeTrainCrossCorrelationHistogram + rdf:type owl:Class ; + rdfs:subClassOf ; + "CCH"@en ; + rdfs:comment "The computed spike train cross-correlation histogram."@en ; + "correlogram"@en , + "cross-correlogram"@en ; + "spike train cross-correlation histogram"@en . + + +### http://purl.org/neao/data#SpikeTrainDistance + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Data that contains a spike train distance measure."@en ; + "spike train distance"@en . + + +### http://purl.org/neao/data#SpikeTrainFanoFactor + rdf:type owl:Class ; + rdfs:subClassOf ; + "FF"@en ; + rdfs:comment "The computed Fano factor (FF) for a set of input spike trains."@en ; + "spike train Fano factor"@en . + + +### http://purl.org/neao/data#SpikeTrainPearsonCorrelationCoefficient + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed Pearson correlation coefficient between two spike trains."@en ; + "spike train Pearson correlation coefficient"@en . + + +### http://purl.org/neao/data#SpikeTrainSurrogate + rdf:type owl:Class ; + rdfs:subClassOf ; + owl:disjointWith ; + rdfs:comment "Data that contains a spike train surrogate. It is generated from spike train inputs using distinct methods to alter the original spike times."@en ; + "spike train surrogate"@en . + + +### http://purl.org/neao/data#SpikeTrainSynchronyMeasure + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Data that contains a measure describing synchronization in two or more spike trains containing the activity of different neurons."@en ; + "spike train synchrony measure"@en . + + +### http://purl.org/neao/data#SpikeTrainTimeHistogram + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed spike train time histogram."@en ; + "spike train time histogram"@en . + + +### http://purl.org/neao/data#SpikeTriggeredAverage + rdf:type owl:Class ; + rdfs:subClassOf ; + "STA"@en ; + rdfs:comment "The computed spike-triggered average (STA)."@en ; + "spike-triggered average"@en . + + +### http://purl.org/neao/data#SpikeTriggeredLFPAverage + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed spike-triggered average of the local field potential (LFP) signal."@en ; + "spike-triggered local field potential average"@en . + + +### http://purl.org/neao/data#SpikeTriggeredPhase + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed spike-triggered phase angles."@en ; + "spike-triggered phase"@en . + + +### http://purl.org/neao/data#SpikeWaveform + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Data that contains the characteristic voltage change over time observed in the electrical recording of a neuron's action potential (spike). This waveform represents the rapid depolarization and repolarization of the neuron's membrane potential during the action potential. The data is acquired in a finite number of samples that correspond to a time window around the spike time (i.e., with periods before and after the action potential onset)."@en ; + "spike waveform"@en . + + +### http://purl.org/neao/data#SpikeWaveformAverage + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed average across the spike waveforms."@en ; + "spike waveform average"@en . + + +### http://purl.org/neao/data#SpikeWaveformSNR + rdf:type owl:Class ; + rdfs:subClassOf ; + "spike waveform SNR"@en ; + rdfs:comment "The computed signal-to-noise ratio of the spike waveforms."@en ; + "spike waveform signal-to-noise ratio"@en . + + +### http://purl.org/neao/data#SpikeWaveformVariance + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed variance across the spike waveforms."@en ; + "spike waveform variance"@en . + + +### http://purl.org/neao/data#SpikeWaveformWidth + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed spike waveform width."@en ; + "spike waveform width"@en . + + +### http://purl.org/neao/data#SpikeWavevormStatistic + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Data that contains measures used to describe specific characteristics or make inferences from spike waveforms."@en ; + "spike waveform statistic"@en . + + +### http://purl.org/neao/data#StandardDeviation + rdf:type owl:Class ; + rdfs:subClassOf ; + "SD"@en ; + rdfs:comment "The computed standard deviation (SD)."@en ; + "standard deviation"@en . + + +### http://purl.org/neao/data#StandardErrorMean + rdf:type owl:Class ; + rdfs:subClassOf ; + "SEM"@en ; + rdfs:comment "The computed standard error of the mean (SEM)."@en ; + "standard error of the mean"@en . + + +### http://purl.org/neao/data#StockwellTransform + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The result of computing the Stockwell transform (S transform)."@en ; + "S transform"@en ; + "Stockwell transform"@en . + + +### http://purl.org/neao/data#TensorComponent + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A tensor component obtained by applying tensor component analysis (TCA) to the input data."@en ; + "tensor component"@en . + + +### http://purl.org/neao/data#TimeHistogram + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Data that contains a time histogram, i.e., a histogram that shows the distribution of a measure across specified time intervals (bins)."@en ; + "time histogram"@en . + + +### http://purl.org/neao/data#TimeSeries + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Data that contains values of a specific quantity (e.g., voltage) acquired as a series of successive samples over time. Typically, there is a fixed interval between the samples (sampling period), with each sample representing a distinct time point in the series."@en ; + "time series"@en . + + +### http://purl.org/neao/data#TransferEntropy + rdf:type owl:Class ; + rdfs:subClassOf ; + "TE"@en ; + rdfs:comment "The computed transfer entropy (TE)."@en ; + "transfer entropy"@en . + + +### http://purl.org/neao/data#TriggeredAverageMeasure + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Data that contains the output of a triggered average analysis."@en ; + "triggered average measure"@en . + + +### http://purl.org/neao/data#TuningCurve + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed tuning curve."@en ; + "tuning curve"@en . + + +### http://purl.org/neao/data#UnbiasedSquaredPhaseLagIndex + rdf:type owl:Class ; + rdfs:subClassOf ; + "unbiased squared PLI"@en ; + rdfs:comment "The computed unbiased squared phase lag index (PLI)."@en ; + "unbiased squared phase lag index"@en . + + +### http://purl.org/neao/data#UnitaryEventPattern + rdf:type owl:Class ; + rdfs:subClassOf ; + "UE pattern"@en ; + rdfs:comment "A neuronal activity pattern obtained by the Unitary Event (UE) analysis."@en ; + "Unitary Event pattern"@en . + + +### http://purl.org/neao/data#VanRossumDistance + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed van Rossum distance."@en ; + "van Rossum distance"@en . + + +### http://purl.org/neao/data#Variance + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed variance."@en ; + "variance"@en . + + +### http://purl.org/neao/data#VictorPurpuraDistance + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The computed Victor-Purpura distance."@en ; + "Victor-Purpura distance"@en . + + +### http://purl.org/neao/data#WaveletTransform + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Data that contains the result of a wavelet transform analysis, i.e., decomposing a time series using a mother wavelet function."@en ; + "scaleogram"@en ; + "wavelet transform"@en . + + +### http://purl.org/neao/data#WeightedPhaseLagIndex + rdf:type owl:Class ; + rdfs:subClassOf ; + "WPLI"@en ; + rdfs:comment "The computed weighted phase lag index (WPLI)."@en ; + "weighted phase lag index"@en . + + +### http://purl.org/neao/parameters#ASSETAnalysisParameter + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A parameter used by the Analysis of Sequences of Synchronous Events (ASSET) method, used to identify neuronal activity patterns in spike data."@en ; + "ASSET analysis parameter"@en . + + +### http://purl.org/neao/parameters#ASSETClusteringDistanceStretchFactor + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "When computing the elliptical distance measure used by the DBSCAN algorithm to cluster the mask matrix entries to find the diagonal structures, the parameter value is used to stretch angular coefficients deviating from 45 degrees. This reflects into the shape of the neighborhood around a point in the DBSCAN procedure. A large stretch factor will produce neighborhoods that are narrower and closer to a line in the 45 degree direction. Smaller stretch factors will produce neighborhoods that are more elliptical, with the major axis in the 45 degree direction, and the minor axis in the 135 degree direction. Therefore, the smaller stretch factor increases the minor axis of this ellipsis. Together with the DBSCAN neighborhood radius parameter, this should be used to tweak the neighborhood ellipsis such that it is contained in the rectangular kernel used to filter the probability matrix entries when computing the joint probability matrix."@en ; + "distance stretch factor in ASSET clustering"@en . + + +### http://purl.org/neao/parameters#ASSETJointProbabilityMatrixFilterShape + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A tuple of integers that determines the width and length of a rectangular kernel used to cover a diagonal structure in the intersection matrix. The kernel is centered in a point in the probability matrix, and defines a neighborhood around that point. Inside the kernel, a chosen number of largest neighbors in the probability matrix is used to compute the joint probability value for the center point. The kernel is rotated in 45 degree angle."@en ; + "kernel shape in ASSET joint probability matrix"@en ; + "filter shape in ASSET joint probability matrix"@en . + + +### http://purl.org/neao/parameters#ASSETJointProbabilityMatrixNumberLargestNeighbors + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Defines the number of elements inside the filter kernel that are used to compute the joint probability value for a matrix entry. The probability matrix values inside the kernel for that entry are ordered from the largest to the lowest value, and the first N elements corresponding to the parameter value are taken."@en ; + "number of largest neighbors in ASSET joint probability matrix"@en . + + +### http://purl.org/neao/parameters#ASSETMaskMatrixSignificanceThresholds + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Real values (range 0-1) used as thresholds to determine if the entries in the probability matrix and joint probability matrices are significant. Entry significance is defined as a probability value greater than the threshold values specified by the parameter. Significant entries in both probability and joint probability matrices are defined as 1 in the mask matrix."@en ; + "significance thresholds in ASSET mask matrix"@en . + + +### http://purl.org/neao/parameters#BartlettSmoothingKernel + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The kernel function has a triangular shape with end points at zero."@en ; + "Bartlett smoothing kernel"@en . + + +### http://purl.org/neao/parameters#BinSize + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "When discretizing continuous data into smaller intervals (bins), the parameter value determines the width of the intervals (in the unit of the data being discretized). Bins are adjacent and can be of different sizes."@en ; + "bin width"@en ; + "bin size"@en . + + +### http://purl.org/neao/parameters#BlackmanWindowFunction + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Window function that uses the first three terms of a summation of cosines, minimizing spectral leakage. It was proposed by Ralph Beebe Blackman. The coefficients are an approximation of the ones used in the exact Blackman window function. Therefore, this window does not remove the third and fourth side lobes but produces smoother edges."@en ; + "Blackman window function"@en . + + +### http://purl.org/neao/parameters#BoxcarSmoothingKernel + rdf:type owl:Class ; + rdfs:subClassOf ; + owl:disjointWith ; + rdfs:comment "The kernel function is zero over the entire interval except for a single (smaller) interval where it has a constant value. This non-zero interval is the total width of the kernel."@en ; + "Boxcar smoothing kernel"@en . + + +### http://purl.org/neao/parameters#DBSCANMinimumNeighbors + rdf:type owl:Class ; + rdfs:subClassOf ; + owl:disjointWith ; + rdfs:comment "Integer value that determines the minimum number of points that must be present in the neighborhood of a sample point such that it is considered a core point. The parameter value includes the sample point being evaluated."@en ; + "DBSCAN minimum samples"@en ; + "DBSCAN minimum number of neighbors"@en . + + +### http://purl.org/neao/parameters#DBSCANNeighborhoodRadius + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Determines the radius around a sample point used to define its neighborhood. The parameter defines the maximum distance between two sample points such that they are considered to be in the same neighborhood."@en ; + "DBSCAN epsilon"@en , + "DBSCAN maximum distance"@en ; + "DBSCAN neighborhood radius"@en . + + +### http://purl.org/neao/parameters#DBSCANParameter + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A parameter used by the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) data clustering method."@en ; + "DBSCAN parameter"@en . + + +### http://purl.org/neao/parameters#DPSSWindowFunction + rdf:type owl:Class ; + rdfs:subClassOf ; + "DPSS window function"@en ; + rdfs:comment "A set of orthogonal sequences optimized to simultaneously achieve maximum concentration of energy within a defined frequency band and minimum leakage into neighboring frequency bands. They are frequently used as tapers in multiple applications (e.g., multitaper power spectral density estimation). The first sequence (order 0 or Slepian sequence) has maximal energy concentration in the main lobe."@en ; + "Slepian sequences window function"@en ; + "discrete prolate spheroidal sequences window function"@en . + + +### http://purl.org/neao/parameters#DitheringTime + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A time interval that defines a dithering distribution used to draw random numbers to displace individual spike times in a spike train."@en ; + "dithering time"@en . + + +### http://purl.org/neao/parameters#DownsampleFactor + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A real value that indicates the factor by which the sampling period of a sampled time series is reduced in a downsampling operation."@en ; + "decimation factor"@en ; + "downsample factor"@en . + + +### http://purl.org/neao/parameters#ExactBlackmanWindowFunction + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Window function that uses the first three terms of a summation of cosines. It was proposed by Ralph Beebe Blackman. The coefficients are selected to remove the third and fourth side lobes, but the edges are discontinuous."@en ; + "exact Blackman window"@en . + + +### http://purl.org/neao/parameters#ExponentialSmoothingKernel + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The kernel function is zero for points before the kernel center point, maximum at the center point, and decay exponentially for points greater than the center point. This kernel is asymmetric."@en ; + "exponential smoothing kernel"@en . + + +### http://purl.org/neao/parameters#FilterOrder + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Integer value specifying the rate at which the filter response in the transition band falls. A higher filter order corresponds to a faster filter response decay."@en ; + "filter order"@en . + + +### http://purl.org/neao/parameters#FiringRate + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The parameter value determines the average number of spikes fired by a neuron per time unit. It is used to control the behavior of steps that require a firing rate to control the output (e.g., a target mean firing rate when generating an artificial spike train)."@en ; + "firing rate"@en . + + +### http://purl.org/neao/parameters#FrequencyResolution + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "In analyses producing estimates in the frequency domain, the parameter determines the width of the frequency bins in the output, i.e., the resolution of the output on the frequency axis."@en ; + "frequency resolution"@en . + + +### http://purl.org/neao/parameters#HammingSmoothingKernel + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The kernel function corresponds to a raised cosine (i.e., a single period of a cosine function \"raised\") with positive endpoints."@en ; + "Hamming smoothing kernel"@en . + + +### http://purl.org/neao/parameters#HammingWindowFunction + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A window function that corresponds to a raised cosine (i.e., a single period of a cosine function \"raised\") but with positive endpoints. Therefore, the function does not eliminate the discontinuities in the signal. It has better cancellation of the nearest side lobe, and a poorer cancellation of the others, with a wide main lobe. It is named after Richard Wesley Hamming."@en ; + "Hamming window function"@en . + + +### http://purl.org/neao/parameters#HannSmoothingKernel + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The kernel function corresponds to a raised cosine (i.e., a single period of a cosine function \"raised\" such that the negative troughs are zero). The endpoints reach zero smoothly at the boundaries."@en ; + "Hann smoothing kernel"@en . + + +### http://purl.org/neao/parameters#HannWindowFunction + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A window function that corresponds to a raised cosine (i.e., a single period of a cosine function \"raised\" such that the negative troughs are zero). Therefore, the function reaches zero smoothly at the boundaries and eliminates all discontinuities in the signal. It has a wide main lobe and low side lobes. It is named after Julius von Hann."@en , + "raised-cosine window function"@en , + "von Hann window function"@en ; + "hanning window function"@en ; + "Hann window function"@en . + + +### http://purl.org/neao/parameters#HighPassFrequencyCutoff + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "When applying a filter to a time series, the frequency components below this parameter value will be attenuated. Usually, the parameter value corresponds to the frequency component attenuated by 3 dB in the filter transition band."@en ; + "high-pass frequency cutoff"@en . + + +### http://purl.org/neao/parameters#KaiserWindowFunction + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "This window function approximates the DPSS window function using Bessel functions. It is easier to compute than the DPSS window function. It was developed by James Kaiser."@en ; + "Kaiser-Bessel window function"@en ; + "Kaiser window function"@en . + + +### http://purl.org/neao/parameters#KernelWidth + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The total width of a smoothing kernel."@en ; + "kernel width"@en . + + +### http://purl.org/neao/parameters#LowPassFrequencyCutoff + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "When applying a filter to a time series, the frequency components above this parameter value will be attenuated. Usually, the parameter value corresponds to the frequency component attenuated by 3 dB in the filter transition band."@en ; + "low-pass frequency cutoff"@en . + + +### http://purl.org/neao/parameters#NumberFFTSamples + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Length of the time series considered by application of a fast Fourier transform (FFT). The value determines the frequency bin size based on the sampling frequency of the input data, and the length of the vector representing the result of the discrete Fourier transform."@en ; + "FFT points"@en ; + "number of FFT samples"@en . + + +### http://purl.org/neao/parameters#PeakResolution + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The parameter defines the separation of individual peaks in the output."@en ; + "peak resolution"@en . + + +### http://purl.org/neao/parameters#SamplingFrequency + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The parameter determines the number of samples per time unit in sampled data. It is the inverse of the sampling period, i.e., the interval between two consecutive samples."@en ; + "sampling rate"@en ; + "sampling frequency"@en . + + +### http://purl.org/neao/parameters#ShapeFactor + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "When determining a probability distribution, the parameter affects the shape of the distribution. This is in contrast to other parameters that affect the location (e.g., mean) or scale (e.g., variance) of the distribution."@en ; + "shape factor"@en . + + +### http://purl.org/neao/parameters#SmoothingKernel + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A smoothing kernel can be used in non-parametric smoothing techniques such as kernel smoothing or kernel density estimation. It represents a weighting function that assigns weights to neighboring data points based on their distance from a given point (the kernel center). Closer points are given higher weights. The weighted average of the data points within the kernel is computed to produce a smoothed estimate of the underlying data (e.g., a signal or probability density function). Smoothing kernels are characterized by their shape (e.g., Boxcar, exponential) and bandwidth. The bandwidth determines the extent of influence of neighboring data points on the smoothed estimate."@en ; + "smoothing kernel"@en . + + +### http://purl.org/neao/parameters#TemporalResolution + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The parameter determines the smallest time interval that can be detected or produced by the method. In sampled time series data, this equals to the sampling period, i.e, the time interval between two consecutive samples."@en ; + "temporal resolution"@en . + + +### http://purl.org/neao/parameters#WaveletCenterFrequency + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "The value of the center frequency of a wavelet. This is the frequency at which the wavelet oscillates most strongly, and it influences how effectively the wavelet can capture features of a signal at different frequencies. Wavelets with higher center frequencies are better suited for analyzing high-frequency components of a signal, while those with lower center frequencies are more effective for capturing low-frequency components."@en ; + "wavelet center frequency"@en . + + +### http://purl.org/neao/parameters#WindowFunction + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment """A mathematical function that is zero-valued outside a defined interval. When multiplied by another function or sampled data, the values outside the window interval will be transformed to zero, and the values inside the window will be weighted by the window function values. + +Window functions are used to select and modify a finite segment of a signal. This is useful for applying the fast Fourier transform (FFT) to a finite set of data where the length is not an integer number of periods of the signal. In this situation, there will be discontinuities at the boundaries of the signal, and the data in the frequency domain produced by the FFT will have frequency components not present in the original signal (spectral leakage). The window function can be used to reduce this discontinuities and mitigate spectral leakage when performing spectral analysis. + +Several types of window function exist. They will vary in shape in the time domain and will have distinct frequency characteristics in the frequency domain, with a main lobe and several side lobes. The main lobe is centered at each frequency component in the time domain, and the side lobes approach zero. These characteristics can be used to control the effect of spectral leakage when performing the analysis."""@en ; + "apodization function"@en , + "tapering function"@en ; + "window function"@en . + + +### http://purl.org/neao/parameters#WindowLengthSamples + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Integer value that defines the number of samples encompassed by a window in sampled data, i.e., the window length. The window corresponds to a finite interval in the sampled data (e.g., a time interval in sampled time series data)."@en ; + "window length in samples"@en . + + +### http://purl.org/neao/parameters#WindowOverlapFactor + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Real value (range 0-1) that determines the proportion of overlap between two adjacent windows. The window is a finite interval in the data (e.g., a time interval in time series data)."@en ; + "window overlap factor"@en . + + +### http://purl.org/neao/parameters#WindowOverlapSamples + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "Integer value (range 0 to the window length in samples) that determines the number of samples where two adjacent windows overlap. The window corresponds to a finite interval in sampled data (e.g., a time interval in sampled time series data)."@en ; + "window overlap in samples"@en . + + +### http://purl.org/neao/steps#ASSETAnalysisProbabilityMatrixSubstep + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "ASSET analysis substep that computes the probability matrix (PMAT). The probability matrix contains, for each entry in the intersection matrix, the cumulative probability representing the probability of having the overlap in the IMAT under the assumption that the spike trains are independent. If an entry in the PMAT is large, the null hypothesis of independence is rejected, and the alternative hypothesis that the observed overlap reflects active synchronization between the involved neurons at the time bins of the intersection is accepted. The PMAT computation can be done with either an analytical or Monte Carlo approach."@en ; + "ASSET analysis probability matrix substep"@en . + + +### http://purl.org/neao/steps#ASSETAnalysisSubstep + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "An analysis step that is an individual part of the ASSET analysis method to identify neuronal activity patterns in spike train data."@en ; + "ASSET analysis substep"@en . + + +### http://purl.org/neao/steps#AnalysisPurpose + rdf:type owl:Class ; + rdfs:comment "Analysis purpose refers to the specific objective or goal that an analysis is intended to achieve. It outlines what the analysis step aims to discover, understand, or demonstrate. This class is intended for grouping steps that perform analyses with similar goals/outputs but with distinct methodological or algorithmic approaches. It is used as a normalization class via the hasPurpose object property."@en ; + "analysis purpose"@en . + + +### http://purl.org/neao/steps#ApplyAdaptiveKernelSmoothing + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A kernel smoothing that uses a variable-width kernel. The kernel width varies adaptively depending on the local density of the data. This method takes into consideration local variations in data density, resulting in a more accurate representation of the underlying patterns and structures."@en ; + "apply adaptive kernel smoothing"@en . + + +### http://purl.org/neao/steps#ApplyAnalyticSignalConversion + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A data transformation that uses the Hilbert transform of a real-valued input time series to construct the analytic signal, a complex-valued time series where the real part is the original real-valued signal and the imaginary part is the Hilbert transform. The analytic signal does not have negative frequency components."@en ; + "apply analytic signal conversion"@en . + + +### http://purl.org/neao/steps#ApplyButterworthFilter + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "An infinite impulse response filtering that uses a Butterworth type filter, i.e., a filter designed to have a maximally flat frequency response in the passband (no ripples). The frequency response gradually decreases to zero in the stopband, and the steepness of the decrease (roll-off) is controlled by the order of the filter."@en ; + "apply maximally flat magnitude filter"@en ; + "apply Butterworth filter"@en . + + +### http://purl.org/neao/steps#ApplyCanonicalPolyadicTensorDecomposition + rdf:type owl:Class ; + rdfs:subClassOf ; + "apply CPD"@en ; + ; + rdfs:comment "A tensor component analysis (TCA) that expresses the input high-dimensional tensor as a sum of rank-one tensors (tensor components). Each dimension in the tensor component corresponds to a dimension in the input high-dimensional tensor. For neural data, a tensor could be used to represent trial-by-trial spiking activity, with neurons, time, and trials as dimensions. Therefore, each tensor component produced from that input will have a rank-one tensor for the neurons, time, and trial, which describes both within- and between-trial changes."@en ; + "apply tensor rank decomposition"@en ; + "apply canonical polyadic tensor decomposition"@en . + + +### http://purl.org/neao/steps#ApplyCoupledCanonicalPolyadicTensorDecomposition + rdf:type owl:Class ; + rdfs:subClassOf ; + "apply CCPD"@en ; + ; + rdfs:comment "A tensor component analysis (TCA) that expresses multiple high-dimensional input tensors as a sum of rank one tensors (tensor components). The output tensor components have shared vectors that summarize an input dimension across all input tensors. For example, if analyzing two tensors, each representing trial-by-trial spiking activity obtained from a distinct experimental subject (neurons X time X trials), the coupled canonical polyadic tensor decomposition (CCPD) could produce tensor components for each dataset where the vector for the trial and time dimensions are the same, but the neuron dimension is unique for each dataset (hence, each subject). Therefore, CCPD is useful for scenarios with multiple and related datasets, allowing for the exploitation of shared information to enhance the decomposition results."@en ; + "apply coupled canonical polyadic tensor decomposition"@en . + + +### http://purl.org/neao/steps#ApplyDFTNoiseRemoval + rdf:type owl:Class ; + rdfs:subClassOf ; + "apply DFT noise removal"@en ; + rdfs:comment "A line noise removal that uses a discrete Fourier transform (DFT) filter and estimates the power line component amplitude in the input data by fitting a sine and cosine at a user-specified line noise frequency (e.g., 50 Hz), followed by the subtraction of those components from the input."@en ; + "apply discrete Fourier transform noise removal"@en . + + +### http://purl.org/neao/steps#ApplyDataConcatenation + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A data transformation that joins two or more data inputs into a single data element. For example, in a multitrial experimental session, where data was acquired separately as one epoch per trial, a continuous data segment for the session can be constructed by concatenating all trial epochs together."@en ; + "apply data concatenation"@en . + + +### http://purl.org/neao/steps#ApplyDemixedPrincipalComponentAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + "apply dPCA"@en ; + ; + rdfs:comment "A principal component analysis (PCA) that uses a modified version of the standard PCA for neural activity data analysis. Demixed PCA (dPCA) not only obtains a low-dimensional representation of the input data, but it also demixes the dependencies of the population activity on the task parameters. Therefore, dPCA can show the dependence of the neural representation on parameters such as stimuli, subject decisions, or rewards."@en ; + "apply demixed principal component analysis"@en . + + +### http://purl.org/neao/steps#ApplyDiscreteFourierTransform + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A frequency-domain transformation that applies the discrete Fourier transform (DFT) to an input time series acquired in equally-spaced samples. The DFT is used to obtain the frequency representation of the time-domain input. The DFT output is a sequence of coefficients of complex sinusoids, each representing a frequency component in the input signal. Each frequency component consists of an interval (or bin), and the width of the bin determines the frequency resolution of the DFT. The number of frequency components and the frequency resolution is determined by the length of the input signal (number of samples) and the sampling frequency. For large datasets, the computation is computationally expensive (O(N^2) complexity)."@en ; + "apply DFT"@en ; + "apply discrete Fourier transform"@en . + + +### http://purl.org/neao/steps#ApplyDistanceCovarianceAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + "apply DCA"@en ; + ; + rdfs:comment "A dimensionality reduction that identifies linear and nonlinear relationships between multiple input datasets. The method identifies linear projections (DCA dimensions) that maximize the distance covariance statistic (an Euclidean-based correlational statistic). For example, for recordings from different brain regions (two neuronal populations), the distance covariance analysis (DCA) can identify the dimensions in the population activity in the different brain areas that are related to each other. The dimensionality reduction can also take other dependent variables into account (e.g., stimulus or behavioral variables)."@en ; + "apply distance covariance analysis"@en . + + +### http://purl.org/neao/steps#ApplyDownsampling + rdf:type owl:Class ; + rdfs:subClassOf ; + owl:disjointWith ; + rdfs:comment "A resampling that reduces the number of samples in the input data (i.e., reduces the sampling frequency). This is often accomplished after applying an anti-aliasing filter (i.e., to remove frequencies above half the value of the new sampling frequency)."@en ; + "apply decimation"@en , + "apply downscaling"@en ; + "apply downsampling"@en . + + +### http://purl.org/neao/steps#ApplyFastFourierTransform + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A frequency-domain transformation that uses the fast Fourier transform (FFT) algorithm to compute the discrete Fourier transform (DFT). The computation of the DFT is computationally expensive for large datasets. The FFT reduces the number of computations significantly by using a divide-and-conquer approach, leveraging the symmetry and periodicity properties of the DFT. The complexity is O(N log N). The output of the method is similar to the DFT, i.e., a sequence of coefficients of complex sinusoids, each representing a frequency component in the input signal. The FFT takes a size parameter, that refers to the number of points in the input data sequence that is used for the computation. The FFT size determines the frequency resolution, and, for maximal efficiency, should be a multiple of 2."@en ; + "apply FFT"@en ; + "apply fast Fourier transform"@en . + + +### http://purl.org/neao/steps#ApplyFiniteImpulseResponseFilter + rdf:type owl:Class ; + rdfs:subClassOf ; + "apply FIR filter"@en ; + rdfs:comment "A finite impulse response (FIR) filtering where a custom-designed FIR filter is applied to the input data."@en ; + "apply finite impulse response filter"@en . + + +### http://purl.org/neao/steps#ApplyFiniteImpulseResponseFilterKaiserWindow + rdf:type owl:Class ; + rdfs:subClassOf ; + "apply FIR filter with Kaiser window"@en ; + rdfs:comment "A finite impulse response (FIR) filtering that uses a FIR filter whose impulse response is controlled by applying a Kaiser window function."@en ; + "apply finite impulse response filter with Kaiser window"@en . + + +### http://purl.org/neao/steps#ApplyFixedKernelSmoothing + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A kernel smoothing that uses a fixed-width kernel. The kernel type and kernel width can be specified as parameters."@en ; + "apply fixed kernel smoothing"@en . + + +### http://purl.org/neao/steps#ApplyGeneralLinearModelPolynomialDetrending + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A detrending that uses a general linear model to fit a polynomial from the input data and remove the mean and linear trend."@en ; + "apply general linear model polynomial detrending"@en . + + +### http://purl.org/neao/steps#ApplyHilbertTransform + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A data transformation that applies the Hilbert transform to a real-valued time series. The Hilbert transform shifts the phase of each frequency component of the signal by 90 degrees: positive frequencies are shifted by -90 degrees, and negative frequencies are shifted by +90 degrees. This can be used to construct the analytic signal."@en ; + "apply Hilbert transform"@en . + + +### http://purl.org/neao/steps#ApplyIndependentComponentAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + "apply ICA"@en ; + ; + rdfs:comment "A data transformation that separates a multivariate input signal into additive subcomponents (independent components). The independent components are statistically independent from each other."@en ; + "apply independent component analysis"@en . + + +### http://purl.org/neao/steps#ApplyInfiniteImpulseResponseFilter + rdf:type owl:Class ; + rdfs:subClassOf ; + "apply IIR filter"@en ; + rdfs:comment "An infinite impulse response (IIR) filtering where a custom-designed IIR filter is applied to the input data."@en ; + "apply infinite impulse response filter"@en . + + +### http://purl.org/neao/steps#ApplyInterpolation + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A data transformation that estimates new (intermediate) values between the known values in the input data. This can be accomplished using several methods, such as linear interpolation (i.e., estimating the values along a straight line connecting adjacent points), polynomial interpolation (i.e., using polynomials to estimate the values between points), or spline Interpolation (i.e., using piecewise polynomials that pass through the known data points and provide a smooth curve)."@en ; + "apply interpolation"@en . + + +### http://purl.org/neao/steps#ApplyLinearDiscriminantAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + "apply LDA"@en ; + rdfs:comment "A dimensionality reduction that finds a linear combination of features that separates two or more classes defined in the input data. The input data must have a variable that defines the class for each observation, and continuous variables that are used for the linear discriminant analysis (LDA). LDA finds an optimal projection vector that maximizes the distance between the means of the different classes, and minimizes the variance within each class. LDA projects the input data into the lower-dimensional space, therefore reducing the number of features while retaining the information needed for classification. The optimal projection vectors found by LDA are the Fisher linear discriminants."@en ; + "apply linear discriminant analysis"@en . + + +### http://purl.org/neao/steps#ApplyLocalLinearRegressionDetrending + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A detrending that removes a running line fit using local linear regression. Local linear regression estimates a function by fitting a low-order polynomial to data within a sliding window (local neighborhood) across the input data."@en ; + "apply local linear regression detrending"@en . + + +### http://purl.org/neao/steps#ApplyLocalRegressionAndLikelihoodSmoothing + rdf:type owl:Class ; + rdfs:subClassOf ; + , + ; + rdfs:comment "A data smoothing that estimates a low-order polynomial in a local neighborhood (window) of any value in the input data. Polynomial coefficients are estimated using the least mean squares method. Contrary to kernel smoothing methods, this is a non-parametric approach and has reduced bias at the boundaries of the input data."@en ; + "apply local regression and likelihood smoothing"@en . + + +### http://purl.org/neao/steps#ApplyMedianRescaling + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A data normalization that uses the median and interquartile range (IQR) to rescale the values of the input data. This method is less sensitive to outliers (compared to the z-score transform), and therefore is known as robust scaling."@en ; + "apply robust scaling"@en ; + "apply median rescaling"@en . + + +### http://purl.org/neao/steps#ApplyMinMaxNormalization + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A data normalization that adjusts the range and distribution of values in the data input such that they fall within a fixed range, based on the minimum and maximum values in the input data. In the typical case, the values are normalized to the [0, 1] interval."@en ; + "apply rescaling"@en ; + "apply min-max normalization"@en . + + +### http://purl.org/neao/steps#ApplyMovementArtifactRemoval + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "An artifact removal that identifies and removes artifacts originating from movements of the experimental subject (e.g., eye movement, head movement)."@en ; + "apply movement artifact removal"@en . + + +### http://purl.org/neao/steps#ApplyNeuralTrajectoryGaussianProcessFactorAnalysis + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] ; + "apply GPFA"@en ; + ; + rdfs:comment "A dimensionality reduction that uses the Gaussian process factor analysis (GPFA) method described by Yu et al. (2009). GPFA extracts smooth, low-dimensional neural trajectories that summarize the activity recorded simultaneously from many neurons on individual experimental trials over time. The input is a set of spike trains representing multitrial activity of multiple neurons recorded in parallel. The input spike trains are binned, and factor analysis is applied to reduce the dimensionality while smoothing the resulting low-dimensional trajectories by fitting a Gaussian process (GP) model to them. The identified trajectories are called neural trajectories, and show the evolution of the activity of the population of neurons over time."@en ; + "apply neural trajectory Gaussian process factor analysis"@en . + + +### http://purl.org/neao/steps#ApplyNonNegativeTensorComponentAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A tensor component analysis (TCA) where a non-negative constraint is applied to the decomposition. This is desirable when the underlying components have physical interpretation and negative values are not possible."@en ; + "apply non-negative tensor component analysis"@en . + + +### http://purl.org/neao/steps#ApplyNotchFilter + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "An infinite impulse response filtering that uses a filter designed to attenuate or eliminate a narrow band of frequencies in the input data (stopband) while allowing other frequencies to pass through relatively unaffected."@en ; + "apply notch filter"@en . + + +### http://purl.org/neao/steps#ApplyNotchFilterNoiseRemoval + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A line noise removal that employs a notch filter to remove line noise. A notch filter is designed to attenuate or eliminate a narrow band of frequencies in the input data (stopband) while allowing other frequencies to pass through relatively unaffected. The notch filter stop band is usually centered at the power line frequency (i.e., 50 Hz or 60 Hz depending on the location)."@en ; + "apply notch filter noise removal"@en . + + +### http://purl.org/neao/steps#ApplyOutlierRemoval + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "An artifact removal that identifies and removes values in the input data that differs significantly from other values (outliers). Outliers may arise from the variability in the measurement or be the result of experimental error."@en ; + "apply outlier removal"@en . + + +### http://purl.org/neao/steps#ApplyPadding + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A data transformation that adds extra data (often zeros or other predefined values) to the beginning, end, or both sides of the input data."@en ; + "apply padding"@en . + + +### http://purl.org/neao/steps#ApplyProbabilisticPrincipalComponentAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + "apply pPCA"@en ; + ; + rdfs:comment "A principal component analysis (PCA) that assumes a probabilistic model for the generation of the observed data, according to Tipping & Bishop (1999). The model assumes that the values in the data input are generated from the lower-dimensional subspace of latent variables (principal components) plus an additive Gaussian noise. This generalizes the standard PCA for the case where the noise covariance approaches zero. The probabilistic PCA (pPCA) allows for uncertainty estimation and modeling of the data generation process, and can be employed when there are missing values in the input data."@en ; + "apply probabilistic principal component analysis"@en . + + +### http://purl.org/neao/steps#ApplyRectification + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A data transformation that computes the absolute value of the input data (rectification)."@en ; + "apply rectification"@en . + + +### http://purl.org/neao/steps#ApplyRereference + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A data transformation that changes the reference point of the data recorded from an electrode. This can be performed by calculating the average across the data obtained from all electrodes and subtracting it from each individual electrode’s data (reducing common noise) or referencing each electrode to its nearest neighbor or a defined pair, subtracting one signal from another (bipolar referencing)."@en ; + "apply rereference"@en . + + +### http://purl.org/neao/steps#ApplySpectrumInterpolationNoiseRemoval + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A line noise removal that uses spectral interpolation to remove power line noise. After obtaining the discrete Fourier transform (DFT) of the input signal with noise, the original frequency component at the power line oscillation frequency can be estimated by interpolating the amplitude spectrum (obtained from the DFT) at the power line frequency (e.g., 50 Hz), followed by the inverse DFT to reconstruct the signal."@en ; + "apply spectrum interpolation noise removal"@en . + + +### http://purl.org/neao/steps#ApplySpikeExtractionFromTimeSeries + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A data transformation that obtains a series of spike times (i.e., a spike train) from an input time series (e.g., voltages recorded from an electrode). The spike times can be estimated, for example, by taking all the time points where the values in the input data are greater or lower than a threshold value."@en ; + "apply spike extraction from time series"@en . + + +### http://purl.org/neao/steps#ApplySpikeTrainBinarization + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A data transformation that takes an input spike train and returns an array of boolean values indicating if at least one spike occurred at individual time points."@en ; + "apply spike train binarization"@en . + + +### http://purl.org/neao/steps#ApplySpikeTrainBinning + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A data transformation that performs a binning operation on the input spike train data. The transformation discretizes the duration of the input spike train(s) into smaller time intervals (bins), and obtains the number of spikes occurring into each bin (binned spike train). Additionally, the occurrence of spikes into each bin can be converted into a binary form (i.e., bins with or without spikes). This is known as clipping. The width of the bin interval is specified by a parameter (bin size)."@en ; + "apply spike train binning"@en . + + +### http://purl.org/neao/steps#ApplySpikeWaveformInterpolation + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A data transformation that estimates additional (unknown) values between sample points of a spike waveform input."@en ; + "apply spike waveform interpolation"@en . + + +### http://purl.org/neao/steps#ApplySpikeWaveformOutlierRejection + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "An artifact removal that identifies and removes spike waveforms that differ significantly from the other spike waveforms in the input. This usually involves identifying waveforms with too late peaks, or in which the rising phase of the potential does not align with the peaks of all other waveforms in the input."@en ; + "apply spike waveform outlier rejection"@en . + + +### http://purl.org/neao/steps#ApplySpikeWaveformPeakAlignment + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A data transformation that modifies input spike waveforms in order to align their peak values in time."@en ; + "apply spike waveform peak alignment"@en . + + +### http://purl.org/neao/steps#ApplyStandardPrincipalComponentAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + "apply standard PCA"@en ; + rdfs:comment "A principal component analysis (PCA) that operates by computing the covariance matrix of the input data, which is then decomposed into its eigenvectors and eigenvalues. The eigenvectors, corresponding to the principal components (PCs), are sorted by the magnitude of their associated eigenvalues. The eigenvectors with the largest eigenvalues explain the most variance in the data and thus form the primary PCs."@en ; + "apply classical principal component analysis"@en ; + "apply standard principal component analysis"@en . + + +### http://purl.org/neao/steps#ApplyStimulationArtifactRemoval + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "An artifact removal that identifies and removes artifacts originating from presenting a stimulus during the recording (e.g., electrical stimulation)."@en ; + "apply stimulation artifact removal"@en . + + +### http://purl.org/neao/steps#ApplySum + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A data transformation that performs the addition of two or more data inputs to obtain a sum."@en ; + "apply sum"@en . + + +### http://purl.org/neao/steps#ApplySynchronousSpikeRemoval + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "An artifact removal that identifies and removes spikes across two or more spike train inputs that occurred simultaneously within a temporal precision specified by a parameter. The temporal precision is usually the sampling rate used by the recording equipment: if different neurons fired within an interval equal to or smaller than the sampling period, this suggests that this synchronous activity does not come from temporal synchronization of the neurons but rather due to an interference in the recording (e.g., electrical noise picked simultaneously by multiple channels)."@en ; + "apply synchronous spike removal"@en . + + +### http://purl.org/neao/steps#ApplyThomsonRegressionNoiseRemoval + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A line noise removal that uses Thomson's regression method (1982) for detecting sinusoids, that identifies and removes significant sine waves from the input data. The desired frequencies can be specified by parameter, or determined using an F-statistic."@en ; + "apply Thomson regression noise removal"@en . + + +### http://purl.org/neao/steps#ApplyTrialExtraction + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A data transformation that extracts trial segments from an input data entity storing a longer and continuous data stream. A trial is a single instance of a repeated experimental procedure. For example, during an electrophysiology experiment, a visual stimulus might be presented several times, with neural activity recorded each time. Each presentation of the stimulus defines a trial. Since the data is recorded continuously, this data transformation identifies and isolates the segments of data corresponding to each individual stimulus presentation, returning them as separate data entities."@en ; + "apply trial extraction"@en . + + +### http://purl.org/neao/steps#ApplyUpsampling + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A resampling that increases the number of samples in the data (i.e., increases the sampling frequency). This is often accomplished by adding new (zero-valued) samples between existing ones followed by applying a lowpass filter to replace the zeros and smooth out the discontinuities."@en ; + "apply upscaling"@en ; + "apply upsampling"@en . + + +### http://purl.org/neao/steps#ApplyWindowedSincFilter + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A finite impulse response filtering that employs the convolution with a sinc function kernel multiplied by a window function (e.g., Blackman or Hamming). The kernel is obtained by evaluating the sinc function for the cutoff frequencies specified as parameters, followed by truncation of the filter skirt, and applying the window to reduce the artifacts introduced from the truncation. The windowed-sinc filter is stable and very efficient to separate one band of frequencies from another."@en ; + "apply windowed-sinc filter"@en . + + +### http://purl.org/neao/steps#ApplyZscoreTransform + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A data normalization that transforms the values of the input data to have zero mean and unit variance."@en ; + "apply standardization"@en ; + "apply z-score transform"@en . + + +### http://purl.org/neao/steps#ArtifactRemoval + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A data transformation that aims to identify and remove artifacts from the input data. Artifacts are unwanted disturbances that distorts the data. In an electrophysiology experiment, they can arise from various sources: environmental interference (e.g., electromagnetic interference from nearby equipment), physiological processes (e.g., eye movement, heart beat), and technical instrumentation issues (e.g., baseline drift of the recorded potentials)."@en ; + "artifact removal"@en . + + +### http://purl.org/neao/steps#ArtificialDataGeneration + rdf:type owl:Class ; + owl:equivalentClass [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:someValuesFrom + ] ; + rdfs:subClassOf ; + rdfs:comment "A data generation that produces artificial data. Artificial data refers to data that is generated programmatically rather than obtained from experimental recordings (e.g., neural simulations or by using specific statistical procedures). The artificial data generation procedure does not take experimentally-recorded data as input, and the generation of the output data depends only on parameters to the method employed. The isArtificial data property is defined as True for outputs of artificial data generation steps."@en ; + "artificial data generation"@en . + + +### http://purl.org/neao/steps#AutocorrelationAnalysis + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + rdfs:comment "An analysis step used to compute a measure of autocorrelation, i.e., the correlation of the input with displaced (lagged or advanced) versions of itself. The computation produces the autocorrelation value for every lag considered."@en ; + "autocorrelation analysis"@en . + + +### http://purl.org/neao/steps#BivariateAnalysis + rdf:type owl:Class ; + owl:equivalentClass [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + rdfs:subClassOf ; + owl:disjointWith ; + rdfs:comment "An analysis step that has only two distinct inputs considered for the computation of the output (e.g., the two time series with the local field potential recorded from two electrodes used to compute a cross-correlation)."@en ; + "pairwise analysis"@en ; + "bivariate analysis"@en . + + +### http://purl.org/neao/steps#CentralTendencyStatisticalAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A statistical analysis to compute a measure of central tendency, i.e., that represents the center or typical value of the input data."@en ; + "central tendency statistical analysis"@en . + + +### http://purl.org/neao/steps#CoherenceAnalysis + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "false"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + rdfs:comment "A spectral analysis that computes a measure of coherence between two or more inputs. Coherence is a real measure that describes the linear association of the distinct inputs (e.g., two time series) in different frequency bands. It corresponds to the absolute value of the coherency."@en ; + "coherence analysis"@en . + + +### http://purl.org/neao/steps#CoherencyAnalysis + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "false"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + rdfs:comment "A spectral analysis that computes a measure of coherency between two inputs. Coherency is a complex-valued measure that describes the linear association of the distinct inputs (e.g., two time series) in different frequency bands."@en ; + "coherency analysis"@en . + + +### http://purl.org/neao/steps#CompoundAnalysis + rdf:type owl:Class ; + owl:equivalentClass [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:someValuesFrom + ] ; + rdfs:subClassOf ; + rdfs:comment "An analysis step that is composed by two or more substeps, each performing a part of the analysis with its own data inputs/outputs and analysis parameters."@en ; + "compound analysis"@en . + + +### http://purl.org/neao/steps#ComputeASSETClusterMatrix + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "ASSET analysis substep that computes the cluster matrix (CMAT) in the ASSET analysis, using DBSCAN with a modified distance metric. It takes the mask matrix (MMAT) as input. The cluster matrix groups the significant entries in the MMAT according to each diagonal structure that they belong to. For each significant entry in the MMAT, the CMAT will have an integer value: -1 for significant entries that do not belong to any diagonal structure, or any value greater than zero with the identification of the cluster that the entry belongs to."@en ; + "compute ASSET cluster matrix"@en . + + +### http://purl.org/neao/steps#ComputeASSETIntersectionMatrix + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "ASSET analysis substep that computes the intersection matrix (IMAT). For a set of input spike trains, binned with a bin width, each entry in the IMAT corresponds to a pair of distinct bins (i.e., distinct time points in the data). The value in the entry corresponds to the number of neurons that fired in both bins corresponding to that entry. When groups of neurons fire in a sequence that repeats in time, the IMAT will show patterns that follow a diagonal direction (diagonal structure). The ASSET method aims to identify the diagonal structures by automated statistical testing and clustering procedures."@en ; + "compute ASSET intersection matrix"@en . + + +### http://purl.org/neao/steps#ComputeASSETJointProbabilityMatrix + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "ASSET analysis substep that computes the joint probability matrix (JMAT). For every entry in the probability matrix (PMAT), the computation produces the combined probability of a fixed number of neighbors in a rectangular kernel (with fixed length and width as parameters) covering a diagonal structure. A value in the JMAT reflects how likely entries with high probability in the PMAT are to be located in the same diagonal structure."@en ; + "compute ASSET joint probability matrix"@en . + + +### http://purl.org/neao/steps#ComputeASSETMaskMatrix + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "ASSET analysis substep that computes the mask matrix (MMAT). The parameters are the threshold values that are used to determine if the entries in the probability matrix (PMAT) and joint probability matrix (JMAT) are significant. Entry significance in either matrix is defined as a probability value greater than the provided threshold value. Significant entries in both probability and joint probability matrices are defined as 1 in the mask matrix."@en ; + "compute ASSET mask matrix"@en . + + +### http://purl.org/neao/steps#ComputeASSETProbabilityMatrixAnalytical + rdf:type owl:Class ; + rdfs:subClassOf ; + owl:disjointWith ; + ; + rdfs:comment "ASSET analysis probability matrix substep that computes the probability matrix (PMAT) using the assumption that the input spike trains are independent and Poisson. The computation can take as input the firing rate profiles of the spike trains used for the intersection matrix (IMAT), or those will be automatically computed using convolution with a boxcar kernel of specified width. The probability distribution of the value in the intersection matrix (IMAT) is approximated by a Poisson distribution computed using LeCam's approximation. The output is a matrix with the cumulative probabilities representing the probability of having each overlap in the IMAT strictly lower than the observed overlap, under the null hypothesis of independence of the input spike trains."@en ; + "compute ASSET probability matrix (analytical method)"@en . + + +### http://purl.org/neao/steps#ComputeASSETProbabilityMatrixMonteCarlo + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "ASSET analysis probability matrix substep that computes the probability matrix (PMAT) employing a Monte Carlo approach using surrogate data obtained from the input spike trains. Different than the analytical method of computation, the null hypothesis in this method does not incorporate the assumptions that the spike trains are Poisson. Spike train surrogates can be generated using distinct methods."@en ; + "compute ASSET probability matrix (Monte Carlo method)"@en . + + +### http://purl.org/neao/steps#ComputeASSETSequenceSynchronousEventsExtraction + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "Last substep of the ASSET analysis method. Given the cluster matrix (CMAT), the identity of the neurons present in each bin of the repeated sequence in the identified diagonal structures is extracted (considering the input spike trains for the computation of the intersection matrix). The output of this substep is the final description of the ASSET pattern for each diagonal structure in the CMAT."@en ; + "compute ASSET sequence of synchronous events extraction"@en . + + +### http://purl.org/neao/steps#ComputeAngularMeanSpikePhases + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] ; + ; + rdfs:comment "A phase analysis that computes the angle obtained from averaging the phases of an input signal at the time points where spikes occurred. For the computation, the phases are represented as vectors in the unit circle, the mean phase vector is computed, and the angle is extracted."@en ; + "compute angular mean of spike phases"@en . + + +### http://purl.org/neao/steps#ComputeAutocorrelationFunction + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute ACF"@en ; + rdfs:comment "An autocorrelation analysis that computes the estimator for the autocorrelation function, i.e. the autocorrelation values of a time series input for a number of lags. The autocorrelation function shows temporal dependencies and repetitive patterns within the input data. The value of the autocorrelation at a specific lag shows how similar the values in the time series input are when separated by a number of time units equal to that lag. The autocorrelation value of 0 indicates no correlation. The autocorrelation varies between 1 and -1 (positive and negative correlation, respectively)."@en ; + "compute autocorrelation function"@en . + + +### http://purl.org/neao/steps#ComputeCV + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute CV"@en ; + rdfs:comment "A dispersion statistical analysis that computes the coefficient of variation (CV). The CV is the ratio of the standard deviation to the mean. It is useful to compare different inputs, as the measure is unitless and indicates the relative variability in the input data."@en ; + "compute coefficient of variation"@en . + + +### http://purl.org/neao/steps#ComputeCV2 + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "An interspike interval variability analysis that computes the CV2, a measure of the intrinsic variability of a spike train that considers adjacent interspike intervals. The CV2 is more robust against fluctuations in the firing rate than the usual approach of taking the coefficient of variation of the interspike intervals of the spike train."@en ; + "compute CV2"@en . + + +### http://purl.org/neao/steps#ComputeCVInterspikeIntervals + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute CV ISIs"@en ; + rdfs:comment "An interspike interval variability analysis that computes the coefficient of variation (CV) of the interspike intervals (ISIs). The CV is computed as the ratio of the standard deviation of the ISIs to their mean."@en ; + "compute coefficient of variation of the interspike intervals"@en . + + +### http://purl.org/neao/steps#ComputeCanonicalCoherence + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute caCOH"@en ; + ; + rdfs:comment "A coherence analysis that computes the canonical coherence (caCOH) according to Vidaurre et al. (2019). The computation maximizes the coherence between two inputs (e.g., distinct datasets with electroencephalogram, electromyogram or local field potential recordings). The absolute value of the coherence between the two multivariate spaces of the inputs in the frequency domain is maximized. The caCOH aims to maximize the strength of the synchronization of oscillatory signals when two multichannel datasets are present (e.g., multiple subjects). The method then finds two spatial projections maximizing the strength of synchronization."@en ; + "compute canonical coherence"@en . + + +### http://purl.org/neao/steps#ComputeCoherence + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A coherence analysis that computes the coherence value between two inputs. It is obtained from the magnitude of the complex-valued cross power spectral density obtained for the two inputs normalized by their power spectral density (i.e., auto spectral density). Several frequency decomposition approaches can be used to obtain the cross and auto power spectral densities from the inputs. The computation can return the magnitude coherence (i.e., by taking the absolute value of the cross power spectral density and normalizing by the square root of the product of the two auto spectral densities) or the magnitude squared coherence (i.e., by computing the squared magnitude of the cross power spectral density and normalizing by the product of the two auto spectral densities)."@en ; + "compute coherence"@en . + + +### http://purl.org/neao/steps#ComputeCoherenceCarter + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A coherence analysis that computes the coherence from two inputs according to Carter (1987). The computation produces the magnitude squared coherence."@en ; + "compute coherence (Carter method)"@en . + + +### http://purl.org/neao/steps#ComputeCoherenceMultitaper + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A coherence analysis where the coherence value between the two inputs is computed using cross and auto power spectral densities obtained using a multitaper approach according to Thomson (1982)."@en ; + "compute coherence (multitaper method)"@en . + + +### http://purl.org/neao/steps#ComputeCoherenceRosenberg + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A coherence analysis that computes the coherence from two inputs according to Rosenberg et al. (1989). The method is described for point processes (i.e., spike trains). The computation produces the magnitude squared coherence."@en ; + "compute coherence (Rosenberg method)"@en . + + +### http://purl.org/neao/steps#ComputeCoherenceWelch + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A coherence analysis where the coherence value between the two inputs is obtained from cross and auto power spectral densities obtained using the method described by Welch (1967). For the computation, the inputs are divided into multiple overlapping segments, and the overall cross and power spectral densities for computing the coherence are obtained from averaging the single-segment estimates."@en ; + "compute coherence (Welch method)"@en . + + +### http://purl.org/neao/steps#ComputeCoherency + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A coherency analysis that computes the coherency for two inputs. It is computed from the complex-valued cross power spectral density obtained for the two inputs normalized by the square root of the product of their power spectral densities (i.e., auto spectral densities). For each frequency, the magnitude of the complex-valued coherency describes the strength of the association and the angle describes the phase lag between the two inputs. If the inputs contain multi-epoch data (e.g., multiple trial repetitions), the cross and auto spectral densities are averaged across epochs."@en ; + "compute complex coherency"@en ; + "compute coherency"@en . + + +### http://purl.org/neao/steps#ComputeComplexityDistribution + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A spike train synchrony analysis that computes the complexity distribution across a set of input spike trains that typically contain the activity of different neurons. In a neuronal population, the complexity represents the total number of neurons that were spiking within a discrete time interval. For the computation, the binarized population histogram (i.e., a spike time histogram computed across spike trains, where each bin will have the count of spike trains that had at least one spike within the bin interval) is obtained using a bin size specified as a parameter. The value at each bin is the complexity. The complexity distribution is obtained by finding the frequency of each complexity value (complexity histogram) and corresponding probability density function (PDF). The complexity PDF describes the likelihood of different complexity values occurring within the neuronal population."@en ; + "compute complexity distribution"@en . + + +### http://purl.org/neao/steps#ComputeConfidenceIntervalBootstrap + rdf:type owl:Class ; + rdfs:subClassOf ; + owl:disjointWith ; + rdfs:comment "A confidence interval resampling analysis that computes the confidence interval using bootstrapping techniques to create many simulated samples (bootstrap samples). It involves repeatedly sampling, with replacement, from the input (observed) data. The total number of bootstrap samples is defined as a parameter. Bootstrapping makes minimal assumptions about the underlying distribution of the data, making it especially useful for small samples or when the data do not meet the assumptions of traditional parametric (non-resampling) methods."@en ; + "compute confidence interval (bootstrap resampling)"@en . + + +### http://purl.org/neao/steps#ComputeConfidenceIntervalJackknife + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A confidence interval resampling analysis that computes the confidence interval using jackknife techniques. It involves systematically leaving out one observation at a time from the input (sample) set and calculating the statistic of interest on each of these \"leave-one-out\" samples. The confidence interval is computed based on statistics obtained from those jackknife samples. Jackknife is useful for small samples or when the data do not meet the assumptions of traditional parametric (non-resampling) methods."@en ; + "compute confidence interval (jackknife resampling)"@en . + + +### http://purl.org/neao/steps#ComputeConfidenceIntervalNonResampling + rdf:type owl:Class ; + rdfs:subClassOf ; + owl:disjointWith ; + rdfs:comment "A confidence interval statistical analysis that computes the confidence interval assuming a statistical distribution of the input data, and uses measures of central tendency and dispersion obtained from the data points in the input(s) (e.g., mean and standard error of the mean when assuming a normal distribution). The computation relies on theoretical distributions and established statistical formulas."@en ; + "compute confidence interval (non-resampling)"@en . + + +### http://purl.org/neao/steps#ComputeContinuousWaveletTransform + rdf:type owl:Class ; + rdfs:subClassOf ; + owl:disjointWith ; + "compute CWT"@en ; + rdfs:comment "A wavelet transform analysis that convolves the input time series with scaled and translated versions of the mother wavelet. The scale parameter can be non-dyadic (i.e., can take values that are not powers of 2). The mother wavelet used is passed as a parameter, and several types can be used (e.g., Morlet, Mexican hat, Hermitian, Meyer, Poisson). The continuous wavelet transform (CWT) is ideal for analyzing non-stationary signals, with transient behavior, rapidly changing frequencies or slowly varying changes. It is comparable to the short-time Fourier transform (STFT)."@en ; + "compute continuous wavelet transform"@en . + + +### http://purl.org/neao/steps#ComputeCorrectedImaginaryPhaseLockingValue + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute ciPLV"@en ; + ; + rdfs:comment "A phase locking value analysis that computes the corrected imaginary phase locking value (ciPLV), following the implementation from Bruña & Maestú (2018). It re-formulates the original phase locking value (PLV) for computational efficiency. The computation uses the imaginary part of the PLV, to make the metric insensitive to zero lag synchronizations (that can be the result of volume conduction)."@en ; + "compute corrected imaginary phase locking value"@en . + + +### http://purl.org/neao/steps#ComputeCovariance + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "false"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + rdfs:comment "A covariance analysis that computes the values of covariance in pairwise input data."@en ; + "compute covariance"@en . + + +### http://purl.org/neao/steps#ComputeCrossCorrelationFunction + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute CCF"@en ; + rdfs:comment "A cross-correlation analysis that computes an estimate of the cross-correlation function, i.e. the cross-correlation values of two time series inputs for a number of lags. The cross-correlation function shows temporal dependencies of the first input series with respect to the second. The value of the cross-correlation at a specific lag shows how similar the values in the first input series are to values in the second input at time points separated by a number of time units equal to that lag. The cross-correlation value of 0 indicates no correlation. The cross-correlation varies between 1 and -1 (positive and negative correlation, respectively)."@en ; + "compute cross-correlation function"@en . + + +### http://purl.org/neao/steps#ComputeCrossCorrelationFunctionBiased + rdf:type owl:Class ; + rdfs:subClassOf ; + owl:disjointWith ; + "compute CCF (biased)"@en ; + rdfs:comment "An analysis step that computes the biased estimator for the cross-correlation function. The biased estimator produces cross-correlation values that deviate from the true cross-correlation."@en ; + "compute cross-correlation function (biased)"@en . + + +### http://purl.org/neao/steps#ComputeCrossCorrelationFunctionUnbiased + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute CCF (unbiased)"@en ; + ; + rdfs:comment "An analysis step that computes the unbiased estimator for the cross-correlation function, using the formula in Stoica & Moses (2005). The unbiased estimation uses a correction for the bias due to zero-padding in the computation, applied to the normalization coefficient. Therefore, the resultant cross-correlation values are closer to the true cross-correlation."@en ; + "compute cross-correlation function (unbiased)"@en . + + +### http://purl.org/neao/steps#ComputeCrossPowerSpectralDensityMorletWavelet + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A cross power spectral density analysis that uses the Morlet wavelet transform to obtain the frequency information of the two inputs used to compute the cross power spectral density."@en ; + "compute cross power spectral density (Morlet wavelet method)"@en . + + +### http://purl.org/neao/steps#ComputeCrossPowerSpectralDensityMultitaper + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute CPSD (multitaper method)"@en ; + ; + rdfs:comment "A cross power spectral density (CPSD) analysis that uses a multitaper approach to compute the CPSD, according to Thomson (1982). The multitaper method uses discrete prolate spheroidal functions (DPSS, also known as Slepian sequences) as tapers applied to the inputs. For the computation, a CPSD using the periodogram method is obtained for each pair of tapered signals. The DPSS functions are orthogonal, and therefore applying multiple DPSS tapers result in independent estimates of the CPSD. The final CPSD is obtained by averaging the CPSDs across all tapers. The multitaper method reduces variance and bias in the CPSD, and has a high frequency resolution. However, it is computationally expensive. The number of tapers used is passed as parameter, or estimated from the desired resolution."@en ; + "compute cross power spectral density (multitaper method)"@en . + + +### http://purl.org/neao/steps#ComputeCrossPowerSpectralDensityPeriodogram + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute CPSD (periodogram method)"@en ; + rdfs:comment "A cross power spectral density (CPSD) analysis that uses the periodogram method. For the computation, the discrete Fourier transform of each input is obtained and their cross-power spectrum is obtained. A window function can be applied to the inputs before the Fourier transform, to reduce spectral leakage. The final CPSD is obtained by normalizing the cross-power spectrum to the unit frequency using the equivalent noise bandwidth (a factor that depends on the coefficients of the window function and the sampling rate). If no window function is used or a window that does not attenuate the signal is used (e.g., Boxcar or rectangular window) the equivalent noise bandwidth is equal to the frequency resolution."@en ; + "compute cross-periodogram"@en ; + "compute cross power spectral density (periodogram method)"@en . + + +### http://purl.org/neao/steps#ComputeCrossPowerSpectralDensityWelch + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute CPSD (Welch method)"@en ; + ; + rdfs:comment "A cross power spectral density (CPSD) analysis that uses the method defined by Welch (1967). For the computation, the two inputs are divided into several overlapping segments (length and overlap passed as parameters, or computed for the desired frequency resolution based on the input length and sampling frequency). A window function (e.g., Hann) is applied to each segment, and the cross power spectral density using the periodogram method is computed. The final CPSD is obtained by averaging all the periodograms with the individual CPSDs."@en ; + "compute cross power spectral density (Welch method)"@en . + + +### http://purl.org/neao/steps#ComputeCrossSpectrogramShortTimeFourierTransform + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute cross-spectrogram (STFT method)"@en ; + rdfs:comment "A spectrogram analysis that computes a cross-spectrogram using the short-time Fourier transform (STFT). The cross-spectrogram is the time-resolved description of the power of a pair of distinct inputs across the different frequency components. This can be used to investigate how common activity between the two inputs is distributed across the frequency components, and how it varies over time."@en ; + "compute cross-spectrogram (short-time Fourier transform method)"@en . + + +### http://purl.org/neao/steps#ComputeCubicAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A spike train synchrony analysis that uses the Cumulant Based Inference of higher-order Correlation (CuBIC) test described in Staude et al. (2010). CuBIC is a statistical method to detect the presence of higher order correlations in parallel spike trains from a neuronal population (i.e., correlations among three or more neurons). It is based on the analysis of the cumulants of the population spike count. The test takes a population histogram as input data (i.e., a spike train time histogram computed across spike trains with the activity of distinct neurons). A null hypothesis that the third cumulant of the data is less than or equal to the maximized third cumulant for a correlation order is iteratively tested (with increasing orders of correlation). The output is the minimum correlation order necessary to explain the value of the third cumulant calculated from the population spike count, together with the p-values of the hypothesis tests performed."@en ; + "compute CuBIC analysis"@en . + + +### http://purl.org/neao/steps#ComputeCurrentSourceDensityICSD + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute iCSD"@en ; + , + , + ; + rdfs:comment """A current source density (CSD) analysis that uses the inverse current source density (iCSD) estimation method described by Pettersen et al. (2006). The iCSD is based on the inversion of the electrostatic forward solution and can be applied to data obtained from electrodes with multiple configurations. The method can handle cases with spatially confined cortical activity and spatially varying extracellular conductivity. + +Three options for CSD estimation using the iCSD exist. The CSD is assumed to have cylindrical symmetry and follows one of three possible assumptions: +1. is localized in infinitely thin discs; +2. is step-wise constant; +3. is continuous and smoothly varying (using cubic splines) in the vertical direction."""@en ; + "compute current source density (inverse method)"@en . + + +### http://purl.org/neao/steps#ComputeCurrentSourceDensityKCSD + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute kCSD"@en ; + ; + rdfs:comment "A current source density (CSD) analysis that uses kernel methods to compute the CSD (kCSD), described by Potworowski et al. (2012). kCSD is non parametric and can estimate the CSD using signals recorded from arbitrarily distributed electrodes, as the assumption of regular electrode placement is not necessary. The method can handle 1D, 2D or 3D electrode configurations. The kCSD can also estimate CSD at any location, as it is not limited to the electrode positions, and uses cross-validation to ensure no overfitting."@en ; + "compute current source density (kernel method)"@en . + + +### http://purl.org/neao/steps#ComputeCurrentSourceDensityStandard + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute CSD"@en ; + , + ; + rdfs:comment "A current source density (CSD) analysis that uses a double spatial derivative of the recorded extracellular potentials to compute the CSD. The original method by Freeman & Nicholson (1975) assumes homogeneous cortical in-plane activity, constant extracellular electrical conductivity and equidistant electrode contacts, and can only predict the CSD at interior electrode positions. Vaknin et al. (1988) suggested a procedure to obtain the CSD for the first and last electrodes by copying the outmost recordings, therefore extending the grid beyond the electrode contacts. This is based on the assumption that the potential varies negligibly above the first and below the last electrode."@en ; + "compute current source density (standard method)"@en . + + +### http://purl.org/neao/steps#ComputeDebiasedSquaredWeightedPhaseLagIndex + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "false"^^xsd:boolean + ] ; + "compute debiased squared WPLI"@en ; + ; + rdfs:comment "A phase lag index (PLI) analysis that computes the debiased squared weighted PLI (WPLI) following Vinck et al. (2011). The direct PLI estimator is positively biased, especially when the sample sizes (i.e., number of trials) are small. The debiased squared WPLI is computed by computing the imaginary components of the cross spectral densities, computing the average imaginary component of the cross spectral densities, and normalizing by the computed average over the magnitudes of the imaginary component of the cross spectral densities."@en ; + "compute debiased squared weighted phase lag index"@en . + + +### http://purl.org/neao/steps#ComputeDirectedPhaseLagIndex + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + "compute DPLI"@en ; + ; + rdfs:comment "A phase lag index (PLI) analysis that computes the directed PLI (DPLI) according to Stam & van Straaten (2012). The DPLI uses the Heaviside step function on the imaginary part of the cross power spectral density, and provides the ability to discriminate whether the first time series is leading or lagging the second. The DPLI ranges between 0 and 1. A DPLI value of 0.5 means that the first time series leads and lags the second time series equally often. A DPLI value greater than 0.5 means that the first time series leads the second more often than it lags. A value of 1 means that the first time series always leads. On the contrary, a DPLI value smaller than 0.5 means that the first time series lags the second more often than it leads. A DPLI value of zero means that the first time series always lags. The PLI can be computed from the DPLI."@en ; + "compute directed phase lag index"@en . + + +### http://purl.org/neao/steps#ComputeDirectedTransferFunction + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + "compute DTF"@en ; + ; + rdfs:comment "A functional connectivity analysis that computes the directed transfer function (DTF) according to Kaminski & Blinowska (1991). DTF can estimate the direction and frequency content of the brain activity flow. The DTF measure is obtained from the spectral transfer matrix computed from multivariate time series input data. For the DTF computation, the spectral transfer matrix is obtained from a multivariate autoregressive model. The DTF estimate is obtained by using a normalization factor computed by the sum along the rows of the spectral transfer matrix. The DTF can have values in the range from 0 to 1."@en ; + "compute directed transfer function"@en . + + +### http://purl.org/neao/steps#ComputeEventRelatedPotential + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute ERP"@en ; + rdfs:comment "An analysis step that computes the event-related potential (ERP). The ERP is the neural activity (e.g., local field potential or electroencephalogram voltages) around a presented stimulus or spontaneous behavioral event. Usually, the event is presented/occurs repeatedly across multiple trials, obtaining multiple event-related potential waveforms that can be averaged to cancel the noise."@en ; + "compute event-related potential"@en . + + +### http://purl.org/neao/steps#ComputeEventTriggeredAverage + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A triggered average analysis that uses an event of interest such as an external stimulus (e.g., electrical, visual, auditory) or a spontaneous behavior (e.g., eye blink) as a trigger to average a signal. The output of the method will provide the average value of the signal around the time where each event occurred (event-triggered average)."@en ; + "compute event-triggered average"@en . + + +### http://purl.org/neao/steps#ComputeFrequencyDomainConditionalGrangerCausality + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + owl:disjointWith ; + , + ; + rdfs:comment "A conditional Granger causality (GC) analysis that computes the GC measures in the frequency domain."@en ; + "compute frequency domain conditional Granger causality"@en . + + +### http://purl.org/neao/steps#ComputeFrequencyDomainPairwiseGrangerCausalityBrovelli + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A frequency domain pairwise Granger causality (GC) analysis that uses the parametric approach according to Brovelli et al. (2004). It uses an MVAR (multivariate autoregressive model) to obtain the coefficients used for the computation of the spectral transfer matrix needed for GC estimation according to the frequency domain GC formulation by Geweke (1982)."@en ; + "compute frequency domain pairwise Granger causality (Brovelli method)"@en . + + +### http://purl.org/neao/steps#ComputeFrequencyDomainPairwiseGrangerCausalityDhamala + rdf:type owl:Class ; + rdfs:subClassOf ; + , + ; + rdfs:comment "A frequency domain pairwise Granger causality (GC) analysis that uses the non-parametric approach according to Dhamala et al. (2008). It is based on Fourier and wavelet transforms to obtain the spectral density matrix and the algorithm from Wilson (1972) for its factorization."@en ; + "compute frequency domain pairwise Granger causality (Dhamala method)"@en . + + +### http://purl.org/neao/steps#ComputeFrequencyDomainPairwiseGrangerCausalityHafner + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A frequency domain pairwise Granger causality (GC) analysis that uses the parametric approach according to Hafner & Herwartz (2008). It uses a multivariate GARCH (generalized autoregressive conditional heteroskedasticity) model and constructs a Wald test on noncausality in variance. This is an alternative to methods based on the residuals of estimated univariate models. The Wald test has superior power properties."@en ; + "compute frequency domain pairwise Granger causality (Hafner method)"@en . + + +### http://purl.org/neao/steps#ComputeFrequencyDomainPairwiseGrangerCausalityWen + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A frequency domain pairwise Granger causality (GC) analysis that uses the non-parametric approach according to Wen et al. (2013). It is a multivariate framework for estimating GC based on spectral density matrix factorization. The approach requires only a single estimation of the spectral density matrix for the entire dataset (e.g., multiple time series inputs). GC for the subsets (i.e., pairs of inputs) can then be calculated by factorizing the relevant submatrix of this overall spectral density matrix."@en ; + "compute frequency domain pairwise Granger causality (Wen method)"@en . + + +### http://purl.org/neao/steps#ComputeISIDistance + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A time-scale independent spike train distance analysis that computes the ISI-distance, described in Kreuz et al. (2007). For the computation, the discrete sequence of spike times is transformed into a continuous temporal profile with one value per sample point. The values at each time point are derived from the interspike intervals. The distance is then obtained as the temporal average of the time profile. ISI-distance is well-designed to describe similarities in the firing rate profile of the input spike trains, but it is not optimal to capture neuronal synchrony."@en ; + "compute ISI-distance"@en . + + +### http://purl.org/neao/steps#ComputeImaginaryCoherency + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A coherency analysis that computes the imaginary part of the coherency for two inputs according to Nolte et al. (2004). For the computation, the imaginary part of the complex-valued cross power spectral density obtained for the two inputs is normalized by the square root of the product of their power spectral densities (i.e., auto spectral densities). If the inputs contain multi-epoch data (e.g., multiple trial repetitions), the cross and auto spectral densities are averaged across epochs. The imaginary part of the coherency is less affected by volume conduction than the (complex) coherency."@en ; + "compute imaginary coherency"@en . + + +### http://purl.org/neao/steps#ComputeInstantaneousFiringRateInterspikeInterval + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "An instantaneous firing rate analysis that computes the instantaneous firing rate by using the reciprocal of the interspike intervals."@en ; + "compute instantaneous firing rate (interspike interval method)"@en . + + +### http://purl.org/neao/steps#ComputeInstantaneousFiringRateKernelDensityEstimation + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "An instantaneous firing rate analysis that computes the instantaneous firing rate by convolution of spike times with a kernel function. The output of the computation is a weighted average of the spikes around the kernel."@en ; + "compute instantaneous firing rate (kernel smoothing method)"@en ; + "compute instantaneous firing rate (kernel density estimation method)"@en . + + +### http://purl.org/neao/steps#ComputeInstantaneousFiringRateLocalRegression + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "An instantaneous firing rate analysis that computes the instantaneous firing rate using local regression methods. The estimation procedure approximates the log of the firing rate using a low-order polynomial within a moving window (local neighborhood)."@en ; + "compute instantaneous firing rate (local regression method)"@en . + + +### http://purl.org/neao/steps#ComputeInterquartileRange + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute IQR"@en ; + rdfs:comment "A dispersion statistical analysis that computes the interquartile range (IQR). The IQR is the difference between the 75th and 25th percentiles (i.e., the range within which the central 50% of the data points lie)."@en ; + "compute interquartile range"@en . + + +### http://purl.org/neao/steps#ComputeInterspikeIntervalHistogram + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute ISIH"@en ; + rdfs:comment "An interspike interval analysis that computes the histogram of interspike intervals. For the computation, a time interval with fixed duration starting from zero is discretized into smaller intervals (bins). The count of input interspike intervals whose values fall into each bin is obtained. Therefore, the output contains a representation of the distribution of the interspike intervals in the input."@en ; + "compute interspike interval histogram"@en . + + +### http://purl.org/neao/steps#ComputeInterspikeIntervals + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute ISIs"@en ; + rdfs:comment "An interspike interval analysis that computes the intervals between successive spikes in a spike train (interspike intervals; ISIs)."@en ; + "compute interspike intervals"@en . + + +### http://purl.org/neao/steps#ComputeJointPeristimulusTimeHistogram + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "false"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + "compute JPSTH"@en ; + , + ; + rdfs:comment """A spike train synchrony analysis that computes the joint peristimulus time histogram (JPSTH) from trial-by-trial spike train inputs obtained from two different neurons, after the repeated presentation of a stimulus. The JPSTH provides a representation of the timing relationship between the firing of the two neurons in response to the stimulus. It combines the peristimulus time histograms (PSTHs) of each neuron to illustrate how their firing rates co-vary over time relative to the stimulus event. This helps in understanding the temporal correlation between the neurons. + +The computation can produce three outputs: + +* the JPSTH matrix (i.e., a matrix whose bins contain the counts of coincidences in the firing of the two neurons); +* the peristimulus coincidence histogram (i.e., a histogram obtained from a cross-section along the main diagonal of the JPSTH matrix); +* the cross-correlation histogram computed by summing the bins along the main and each paradiagonal of the JPSTH matrix (after normalizing by the bin length, as the paradiagonals in the JPSTH matrix are of different lengths)."""@en ; + "compute joint peristimulus time histogram"@en . + + +### http://purl.org/neao/steps#ComputeLV + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute LV"@en ; + ; + rdfs:comment "An interspike interval variability analysis that computes the local variation (LV) of the interspike intervals. LV reflects the stepwise variability of a sequence of spikes, and is able to extract the spiking characteristics of individual neurons even in the presence of external modulations of the firing rate."@en ; + "compute local variation"@en . + + +### http://purl.org/neao/steps#ComputeLVR + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute LvR"@en ; + ; + rdfs:comment "An interspike interval variability analysis that computes the revised local variation (LvR) of interspike intervals. Compared to the original local variation (LV) measure, LvR has better invariance to fluctuations in the firing rate fluctuations. This is achieved by using a refractoriness constant in the computation of the measure."@en ; + "compute revised local variation"@en . + + +### http://purl.org/neao/steps#ComputeMaximizedImaginaryCoherency + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute MIC"@en ; + ; + rdfs:comment "A coherency analysis that computes the maximized imaginary coherency (MIC) according to Ewald et al. (2012). The computation uses an eigenvalue-based optimization to find weight vectors that maximize the imaginary part of coherency computed between virtual channels derived from the input data. The weights are optimized for each frequency component. After the weights are obtained, the final MIC measure is obtained for each frequency."@en ; + "compute maximized imaginary coherency"@en . + + +### http://purl.org/neao/steps#ComputeMean + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A central tendency statistical analysis that computes the mean of the input data. The mean is the arithmetic average of all data points."@en ; + "compute mean"@en . + + +### http://purl.org/neao/steps#ComputeMeanFiringRate + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute MFR"@en ; + rdfs:comment "A firing rate analysis that computes the mean firing rate, defined as the number of spikes in a time interval divided by the duration of the interval. The mean firing rate is the temporal average of the neuronal activity over that interval."@en ; + "compute mean firing rate"@en . + + +### http://purl.org/neao/steps#ComputeMeanPhaseVector + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A phase analysis that computes the mean among two or more input phases. For the computation, the input phases are represented as vectors in the unit circle, and the mean phase vector is computed. The analysis can return the mean phase vector (i.e., angle and length), the vector angle, or the vector length."@en ; + "compute mean phase vector"@en . + + +### http://purl.org/neao/steps#ComputeMeanVectorLengthCanolty + rdf:type owl:Class ; + rdfs:subClassOf ; + owl:disjointWith ; + "compute MVL (Canolty method)"@en ; + ; + rdfs:comment "A mean vector length (MVL) analysis that computes the mean vector length as described in Canolty et al. (2006). For the computation, phase is extracted from the low-frequency analytic signal, and amplitude is extracted from the high-frequency analytic signal. The phase angle and magnitude is used to define a complex-valued time series, and each complex value is a vector in the polar plane. Averaging all vectors yields a mean vector whose length indicates the coupling strength and whose direction indicates the phase where amplitude is strongest. Without coupling, the vectors cancel out, resulting in a short mean vector without meaningful phase direction. If phase-amplitude coupling exists, the magnitude of a subset of vectors is especially high at a specific phase or narrow phase range."@en ; + "compute mean vector length (Canolty method)"@en . + + +### http://purl.org/neao/steps#ComputeMeanVectorLengthOzkurt + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute MVL (Özkurt method)"@en ; + ; + rdfs:comment "A mean vector length (MVL) analysis that computes the MVL as described in Özkurt & Schnitzler (2011). The original MVL (Canolty et al., 2006) may be affected by factors in the input data (e.g., amplitude outliers or non-uniform distribution of phase angles). This computation estimates a direct MVL that is amplitude-normalized to obtain values in the 0 to 1 range, and that takes care of possible amplitude differences in the raw data."@en ; + "compute mean vector length (Özkurt method)"@en . + + +### http://purl.org/neao/steps#ComputeMedian + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A central tendency statistical analysis that computes the median of the input data. The median is the middle value when data points are arranged in ascending order (i.e., it divides the data points in two equal halves, with 50% of the data points below it and 50% above it). If there is an even number of data points, the median is the average of the two middle values."@en ; + "compute median"@en . + + +### http://purl.org/neao/steps#ComputeModulationIndex + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute MI"@en ; + ; + rdfs:comment "A phase-amplitude coupling (PAC) analysis that computes the modulation index (MI) as described in Tort et al. (2010). For the computation, the Hilbert transform is used to obtain the instantaneous phase from the input time series with the low-frequency oscillation, and the instantaneous amplitude from the input time series with the high-frequency oscillation. The phase of the low-frequency oscillation is discretized into bins and the amplitude of the high-frequency oscillation is averaged within each bin to create a distribution. This distribution is then compared to a uniform distribution using the Kullback-Leibler divergence, normalized by the maximum possible divergence, resulting in the MI."@en ; + "compute modulation index"@en . + + +### http://purl.org/neao/steps#ComputeMorletWaveletTransform + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A wavelet transform analysis based on the complex-valued Morlet wavelet. The transform can be performed either in the time domain (by convolution) or in the frequency domain (by multiplication)."@en ; + "compute Morlet wavelet transform"@en . + + +### http://purl.org/neao/steps#ComputeMorletWaveletTransformLeVanQuyen + rdf:type owl:Class ; + rdfs:subClassOf ; + owl:disjointWith ; + ; + rdfs:comment "A wavelet transform analysis using the Morlet wavelet where the parametrization of the mother wavelet is done according to Le Van Quyen et al. (2001). The size of the mother wavelet is determined in number of cycles to control the frequency and temporal resolutions (approximate number of oscillation cycles within a wavelet)."@en ; + "compute Morlet wavelet transform (Le Van Quyen method)"@en . + + +### http://purl.org/neao/steps#ComputeMorletWaveletTransformTallonBaudry + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A wavelet transform analysis using the Morlet wavelet based on the methods described in Tallon-Baudry et al. (1997). The ratio of the central frequency to the spectral bandwidth is 7, with central frequencies ranging from 20 to 100 Hz in 1 Hz steps. This resulted in varying time/frequency resolution across the spectrum: time resolution increases with frequency, while frequency resolution decreases."@en ; + "compute Morlet wavelet transform (Tallon-Baudry method)"@en . + + +### http://purl.org/neao/steps#ComputeMultivariateInteractionMeasure + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute MIM"@en ; + ; + rdfs:comment "A functional connectivity analysis that computes the multivariate interaction measure (MIM) as defined by Ewald et al. (2012). MIM is constructed from the maximization of imaginary coherency."@en ; + "compute multivariate interaction measure"@en . + + +### http://purl.org/neao/steps#ComputeMutualInformation + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "false"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "false"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + "compute MI"@en ; + ; + rdfs:comment "A functional connectivity analysis that computes a mutual information (MI) measure. MI is based on Shannon information theory, and quantifies the amount of information from one input that is obtained from another input. Therefore, it can be used to determine how the neuronal activity provides information about a variable (e.g., behavioral stimulus) or how the information flows between different brain regions or neurons. The MI is measured in bits."@en ; + "compute mutual information"@en . + + +### http://purl.org/neao/steps#ComputeNeuronalPopulationVector + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "An analysis step that computes the neuronal population vector, used to describe the collective activity of a group of neurons. The neuronal population vector is obtained taking as inputs the multiple responses of a neuronal population in the context of distinct values of a behavioral measure (e.g., tuning curves showing the response of each individual neuron to different arm movement directions in the 2-D space). The analysis step obtains a weighted vectorial sum of the neural activities, which will result in an estimate of the behavioral measure considering the collective activity of the population (e.g., the movement direction given the neuronal activity)."@en ; + "compute population vector"@en ; + "compute neuronal population vector"@en . + + +### http://purl.org/neao/steps#ComputeNoiseCorrelations + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute NC"@en ; + ; + rdfs:comment "A spike train correlation analysis that computes the noise correlations (NC) between two input spike trains. The NC is the Pearson's correlation coefficient of spike count responses to repeated presentations of identical stimuli, under the same behavioral conditions. The spike counts are typically measured over the time scale of a stimulus presentation or a behavioral trial, which range from a few hundred milliseconds to several seconds. NC assesses whether neurons exhibit trial-by-trial fluctuations in firing rates that are not influenced by varying sensory or behavioral conditions."@en ; + "compute noise correlations"@en . + + +### http://purl.org/neao/steps#ComputeNoiseCovariance + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "false"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + rdfs:comment "A covariance analysis that computes the noise covariance, i.e., how much two noise signals vary together. The noise data inputs can be non-subject recordings (e.g., recordings from the empty experimental room) or are obtained from periods without stimulation or meaningful experimental manipulations (e.g., prestimulus intervals). These reflect random variations or disturbances that are not part of the actual signal or data of interest."@en ; + "compute noise covariance"@en . + + +### http://purl.org/neao/steps#ComputeOptimalBinSize + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "An analysis step that finds the optimal bin size considering the input data when discretizing data into smaller intervals (bins). The computation uses the formula from Scott (1979)."@en ; + "compute optimal bin size"@en . + + +### http://purl.org/neao/steps#ComputeOptimalKernelBandwidth + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "An analysis step that computes the optimal fixed bandwidth (width) for a Gaussian kernel used for the estimation of the firing rate using kernel density estimation. The analysis step uses the input spike train for which the firing rate will be computed, and follows the implementation by Shimazaki & Shinomoto (2010)."@en ; + "compute optimal kernel bandwidth"@en . + + +### http://purl.org/neao/steps#ComputeOrthogonalizedPowerEnvelopeCorrelation + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A functional connectivity analysis that computes the orthogonalized power envelope correlation, according to Hipp et al. (2012). This method relies on correlations between the instantaneous amplitudes of cross-region input signals (power envelopes). The instantaneous amplitudes of the two input time series are orthogonalized aiming to remove spurious correlations of signal power (e.g., due to limited spatial resolution of electrophysiological measures)."@en ; + "compute orthogonalized power envelope correlation"@en . + + +### http://purl.org/neao/steps#ComputePairwisePhaseConsistency + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + "compute PPC"@en ; + ; + rdfs:comment "A phase analysis that computes the pairwise phase consistency (PPC) measure according to Vinck et al. (2010). The PPC quantifies the distribution of phase differences across the inputs, but is less biased by the number of observations in comparison to the phase locking value (PLV). For the computation, the phase difference (angular distance) is obtained for all pairs of observations in the input (that can be represented as vectors in the unit circle, where the angle is the relative phase). The cosine of the angular distance (an estimate of the dot product of the vectors corresponding to each element in a pair) is computed for every pair, and the PPC estimate is obtained from the average of all pairwise dot products. With phase synchronization, the distribution of the pairwise dot products is centered around an average value, while without synchronization it will be distributed across the unit circle. The PPC provides an unbiased estimate of the squared PLV."@en ; + "compute pairwise phase consistency"@en . + + +### http://purl.org/neao/steps#ComputePartialCoherence + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A coherence analysis that computes the partial coherence, i.e., the coherence value between a pair of inputs (e.g., time series with recordings from two distinct electrode channels) after removing the influence of one or more additional inputs (e.g., the time series with the recordings from all remaining channels). The partial coherence is computed according to Rosenberg et al. (1998). The partial coherence reflects the linear association in the frequency domain (for each frequency component) between the pair of inputs of interest, removing spurious coherence caused by confounding factors such as shared inputs to the pair of interest or volume conduction."@en ; + "compute partial coherence"@en . + + +### http://purl.org/neao/steps#ComputePartialDirectedCoherence + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + "compute PDC"@en ; + ; + rdfs:comment "A coherence analysis that computes the partial directed coherence (PDC) according to Baccalá & Sameshima (2001). The PDC describes the relationships between multivariate time series inputs (direction of information flow). To compute the PDC, the multivariate partial coherences obtained from multivariate autoregressive models are decomposed. The PDC reflects a frequency-domain representation of the concept associated with Granger causality."@en ; + "compute partial directed coherence"@en . + + +### http://purl.org/neao/steps#ComputePeristimulusTimeHistogramAdaptiveKernelSmoothing + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute PSTH (adaptive kernel smoothing)"@en ; + rdfs:comment "A peristimulus time histogram (PSTH) analysis that computes the PSTH using kernel density smoothing with an adaptive kernel width. The adaptive kernel is obtained by first computing the PSTH with a fixed-width kernel, and then modifying the kernel width in order to have a constant but time-dependent average number of spikes under the kernel (i.e., segments of the data with a high density of spikes will have a reduced kernel width)."@en ; + "compute peristimulus time histogram (adaptive kernel smoothing)"@en . + + +### http://purl.org/neao/steps#ComputePeristimulusTimeHistogramFixedKernelSmoothing + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute PSTH (fixed kernel smoothing)"@en ; + rdfs:comment "A peristimulus time histogram (PSTH) analysis that computes the PSTH using kernel density smoothing with a fixed kernel width specified as parameter."@en ; + "compute peristimulus time histogram (fixed kernel smoothing)"@en . + + +### http://purl.org/neao/steps#ComputePeristimulusTimeHistogramOptimalBinSize + rdf:type owl:Class ; + rdfs:subClassOf ; + , + "compute PSTH (optimal bin size)"@en ; + rdfs:comment "A peristimulus time histogram (PSTH) analysis that computes the PSTH finding the optimal bin size from the input spike train data, using the formula from Scott (1979)."@en ; + "compute peristimulus time histogram (optimal bin size)"@en . + + +### http://purl.org/neao/steps#ComputePeristimulusTimeHistogramUserSelectedBinSize + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute PSTH (user-selected bin size)"@en ; + rdfs:comment "A peristimulus time histogram (PSTH) analysis that computes the PSTH using a fixed bin size specified as a parameter."@en ; + "compute peristimulus time histogram (user-selected bin size)"@en . + + +### http://purl.org/neao/steps#ComputePhaseDifference + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A phase analysis that computes the difference between two input phases."@en ; + "compute phase difference"@en . + + +### http://purl.org/neao/steps#ComputePhaseLagIndex + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "false"^^xsd:boolean + ] ; + "compute PLI"@en ; + ; + rdfs:comment "A phase lag index (PLI) analysis that computes the PLI following Stam et al. (2007). The input data contains multiple repetitions of a pair of signals (e.g., time series with recordings from a pair of electrodes across multiple trials). For each repetition, the sign of the phase differences between the two time series is obtained from the imaginary part of the cross power spectral density (CPSD). The PLI value is the absolute value of the average of the signs of all repetitions. The PLI ranges between 0 and 1. A PLI of zero means that the first time series leads the second equally often (i.e., indicates either no coupling or coupling with a phase difference centered around 0 mod π, which could be from common sources such as volume conduction). A value greater than zero means an imbalance in the likelihood of the first time series to be either leading or lagging the second time series. A PLI of 1 indicates perfect phase locking, and that the first time series only leads or only lags (at a value of phase differences different from 0 mod π)."@en ; + "compute phase lag index"@en . + + +### http://purl.org/neao/steps#ComputePhaseLockingValue + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute PLV"@en ; + ; + rdfs:comment "A phase locking value (PLV) analysis that computes the PLV value as originally described by Lachaux et al. (1999). The input data is a set of pairs of time series (e.g., the trial-by-trial local field potential recorded from two different electrodes). For each time series pair, the instantaneous phase is obtained (e.g., using the Hilbert transform or wavelet decomposition), and the phase difference for each time point is obtained. The PLV value is computed by averaging the complex phase differences across all pairs, obtaining one PLV value per time point. The PLV ranges from 0 to 1. A PLV of 1 indicates perfect phase locking, meaning the phase difference between the two time series is constant over time. A PLV of 0 indicates no phase locking, meaning the phase difference is randomly distributed over time."@en ; + "compute phase locking value"@en . + + +### http://purl.org/neao/steps#ComputePhaseSlopeIndex + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + "compute PSI"@en ; + ; + rdfs:comment "A functional connectivity analysis that computes the phase slope index (PSI) according to Nolte et al. (2008). The PSI is based on the slope of the phase of the cross-spectral density between two time series inputs, considering how the phase difference between two signals changes as you move from one frequency bin to the next. It is computed from the complex-valued coherency using a bandwidth specified as parameter. For the computation, the change in phase difference between neighboring frequency bins is obtained (considering the specified bandwidth) and weighted. The PSI value deviates from zero when the phase difference changes consistently across frequencies and there is substantial coherence. The sign of the PSI indicates the temporal order of the two signals (i.e., which signal is leading the other one)."@en ; + "compute phase slope index"@en . + + +### http://purl.org/neao/steps#ComputePopulationHistogram + rdf:type owl:Class ; + rdfs:subClassOf ; + owl:disjointWith ; + rdfs:comment "A spike train time histogram analysis that computes a histogram across two or more spike trains that contain the activity of different neurons (i.e., a neuronal population), recorded at fully-overlapping time intervals. The activity in each histogram bin reflects the combined activity of the population at that time, and the distribution of the histogram corresponds to the population activity over time."@en ; + "compute population histogram"@en . + + +### http://purl.org/neao/steps#ComputePowerSpectralDensityBartlett + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute PSD (Bartlett method)"@en ; + ; + rdfs:comment "A power spectral density (PSD) analysis that uses the method defined by Bartlett (1950). For the computation, the input time is divided into non-overlapping segments, with length specified as a parameter. A periodogram is computed for each segment to obtain the single-segment PSD. The final PSD is obtained by averaging all the single-segment PSDs. A window function can be applied to each segment before computing the periodograms. The PSD obtained with the Bartlett method is less noisy than a single periodogram obtained from the entire signal, although the frequency resolution of the estimates is reduced due to segmenting. It is equivalent to the Welch method without any segment overlap."@en ; + "compute power spectral density (Bartlett method)"@en . + + +### http://purl.org/neao/steps#ComputePowerSpectralDensityMultitaper + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute PSD (multitaper method)"@en ; + ; + rdfs:comment "A power spectral density (PSD) analysis that uses a multitaper approach to compute the PSD, according to Thomson (1982). The multitaper method uses discrete prolate spheroidal functions (DPSS, also known as Slepian sequences) as tapers applied to the input signal. For the computation, a PSD using the periodogram method is obtained for each tapered signal. The DPSS functions are orthogonal, and therefore applying multiple DPSS tapers result in independent estimates of the PSD. The final PSD is obtained by averaging the periodograms across all tapers. The multitaper method reduces variance and bias in the PSD, and has a high frequency resolution. However, it is computationally expensive. The number of tapers used is passed as parameter, or estimated from the desired resolution."@en ; + "compute power spectral density (multitaper method)"@en . + + +### http://purl.org/neao/steps#ComputePowerSpectralDensityPeriodogram + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute PSD (periodogram method)"@en ; + rdfs:comment "A power spectral density (PSD) analysis that uses the periodogram method. For the computation, the discrete Fourier transform is applied to the full length of the input, and the power spectrum is obtained. To reduce spectral leakage, a window function can be applied to the input before the computation of the Fourier transform (this is referred as the modified periodogram). The power spectrum is then normalized to the unit frequency, using the equivalent noise bandwidth (a factor that depends on the coefficients of the window function and the sampling rate). If no window function is used or a window that does not attenuate the signal is used (e.g., Boxcar or rectangular window) the equivalent noise bandwidth is equal to the frequency resolution. The PSD using the periodogram is computationally simple to obtain."@en ; + "compute FFT power spectral density"@en , + "compute periodogram"@en ; + "compute power spectral density (periodogram method)"@en . + + +### http://purl.org/neao/steps#ComputePowerSpectralDensityWelch + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute PSD (Welch method)"@en ; + ; + rdfs:comment "A power spectral density (PSD) analysis that uses the method defined by Welch (1967). For the computation, the input is divided into several overlapping segments (length and overlap passed as parameters, or computed for the desired frequency resolution based on the input length and sampling frequency). A window function (e.g., Hann) is applied to each segment, and a periodogram is computed to obtain the PSD for the segment. The final PSD is obtained by averaging all the periodograms with the single-segment PSDs. If there is no overlap between segments, this is equivalent to the Bartlett method."@en ; + "compute power spectral density (Welch method)"@en . + + +### http://purl.org/neao/steps#ComputeRateChangeDetectionMultipleFilterTest + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "An analysis step that uses the change point detection algorithm from Messer et al. (2014) to determine if a input spike train has constant firing rate (stationary) or has one or more points in which the firing rate decreases or increases (change point). In the latter case, the spike train is considered non-stationary. The analysis step outputs one or more change points in the case of non-stationarity."@en ; + "compute rate change detection multiple filter test"@en . + + +### http://purl.org/neao/steps#ComputeRectifiedAreaUnderCurve + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute RAUC"@en ; + rdfs:comment "An analysis step that computes the rectified area under the curve (RAUC). For the computation, the input signal is rectified (i.e., the absolute value is obtained) and the area under the curve is computed by integration using the composite trapezoidal rule."@en ; + "compute rectified area under the curve"@en . + + +### http://purl.org/neao/steps#ComputeRegularizedCovariance + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A covariance analysis where the computation of the covariance values incorporates regularization techniques to improve the numerical stability, especially if the number of samples is small."@en ; + "compute regularized covariance"@en . + + +### http://purl.org/neao/steps#ComputeSPIKEDistance + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A time-scale independent spike train distance analysis that computes the SPIKE-distance, described in Kreuz et al. (2012). For the computation, the discrete sequence of spike times is transformed in a continuous temporal profile with one value per sample point. The values at each time point are derived from the differences in the spike times of the two input spike trains. Compared to the ISI-distance, the SPIKE-distance is more sensitive to spike timing."@en ; + "compute SPIKE distance"@en . + + +### http://purl.org/neao/steps#ComputeSPIKESynchronization + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A time-scale independent spike train distance analysis that computes the SPIKE synchronization distance, described in Kreuz et al. (2015). The distance detects coincidences in the spiking activity and can quantify the degree of synchrony in the input spike trains. The metric quantifies the overall fraction of coincidences. It is zero-valued if and only if the input spike trains do not contain any coincidences. It has a value of 1 if and only if each spike in every input spike train has one matching spike in all the other spike trains."@en ; + "compute SPIKE synchronization"@en . + + +### http://purl.org/neao/steps#ComputeShortTimeFourierTransform + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute STFT"@en ; + rdfs:comment "A time-frequency analysis that computes the short-time Fourier transform (STFT) of the input time series. The analysis divides the input time-domain signal into short segments with equal time and computes the Fourier transform for each segment. The output is a sequence of coefficients of complex sinusoids, each representing a frequency component in the input signal at a distinct time segment. Therefore, this provides the the time-localized frequency and phase information of the input. The segments can be windowed using a window function."@en ; + "compute short-time Fourier transform"@en . + + +### http://purl.org/neao/steps#ComputeSpectrogramMorletWavelet + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A spectrogram analysis that uses the Morlet wavelet transform on the input to obtain the time-frequency information used to build the spectrogram."@en ; + "compute spectrogram (Morlet wavelet method)"@en . + + +### http://purl.org/neao/steps#ComputeSpectrogramMultitaper + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A spectrogram analysis that uses a multitaper approach to obtain the time-frequency information from the input and that is used to build the spectrogram."@en ; + "compute spectrogram (multitaper method)"@en . + + +### http://purl.org/neao/steps#ComputeSpectrogramShortTimeFourierTransform + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute spectrogram (STFT method)"@en ; + rdfs:comment "A spectrogram analysis that uses the short-time Fourier transform (STFT) on the input to obtain the time-frequency information used to build the spectrogram."@en ; + "compute spectrogram (short-time Fourier transform method)"@en . + + +### http://purl.org/neao/steps#ComputeSpikeContrast + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A spike train synchrony analysis that computes the Spike-contrast measure using the method described by Ciba et al. (2018). Spike-contrast is a time-scale independent measure of spike synchrony. The input is a set of parallel spike train data recorded from a population of neurons. The algorithm is based on the temporal \"contrast\" (activity vs. non-activity in certain time bins). The computation outputs a single synchrony value (comparable to a spike train distance) and a synchrony curve showing the value of Spike-contrast as a function of the bin size."@en ; + "compute Spike-contrast"@en . + + +### http://purl.org/neao/steps#ComputeSpikeFieldCoherenceFries + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A spike-field coherence analysis that uses the method described in Fries et al. (2001) to compute the coherence between the spike train and the LFP. For the computation, first a spike-triggered average (STA) is obtained between the spike train and the LFP time series. Then, the power spectrum is obtained for each of the LFP segments used for the computation of the STA. These spectra are averaged to obtain the spike-triggered power spectrum. The SFC is then computed as the ratio of the power spectrum of the STA over the spike-triggered power spectrum."@en ; + "compute spike-field coherence (Fries method)"@en . + + +### http://purl.org/neao/steps#ComputeSpikeFieldCoherenceMultitaper + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute SFC (multitaper method)"@en ; + rdfs:comment "A spike-field coherence analysis that uses a multitaper approach to compute the coherence between the spike train and the LFP."@en ; + "compute spike-field coherence (multitaper method)"@en . + + +### http://purl.org/neao/steps#ComputeSpikeFieldCoherenceWelch + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute SFC (Welch method)"@en ; + ; + rdfs:comment "A spike-field coherence analysis step that uses the method by Welch (1967) to compute the coherence between the spike train and the LFP."@en ; + "compute spike-field coherence (Welch method)"@en . + + +### http://purl.org/neao/steps#ComputeSpikeTimeTilingCoefficient + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute STTC"@en ; + ; + rdfs:comment "A spike train correlation analysis that computes the spike time tiling coefficient (STTC) as described by Cutts and Eglen (2014). The STTC measures the pairwise correlation between two input spike trains, and has advantages over the related correlation index: it is not confounded by the firing rate, it distinguishes lack of correlation from anti-correlation, periods without neural activity don't add to the correlation, and it is sensitive to firing patterns. The computation is based on a synchronicity window parameter, that is used to define short time windows around each spike that are used in the computation (spike time tiling)."@en ; + "compute spike time tiling coefficient"@en . + + +### http://purl.org/neao/steps#ComputeSpikeTrainAutocorrelationHistogram + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "An autocorrelation analysis that computes the autocorrelation histogram for a input spike train. The histogram is obtained by sliding a time window that is discretized into smaller time intervals (bins) centered on a spike (corresponding to the lag zero). The spike count in each bin is obtained. Therefore, this binning process measures the number of spikes occurring at various time lags relative to the center spike. The histogram window is slidden over each spike in the input spike train, and the spike count in each bin is accumulated to produce the autocorrelation histogram output. The width of the bin interval is controlled by a parameter."@en ; + "compute spike train autocorrelation histogram"@en . + + +### http://purl.org/neao/steps#ComputeSpikeTrainAutocorrelationTimeScale + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "An analysis step that computes the autocorrelation time of a binned spike train input (spike train autocorrelation time scale). The computation follows the method described by Wieland et al. (2015)."@en ; + "compute spike train autocorrelation time scale"@en . + + +### http://purl.org/neao/steps#ComputeSpikeTrainCrossCorrelationHistogram + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] ; + "compute CCH"@en ; + rdfs:comment "A cross-correlation analysis that computes the cross-correlation histogram (CCH) for a pair of input spike trains. The CCH shows how often spikes in the reference spike train occur before or after spikes in the reference spike train, at distinct lag intervals. For the computation, the spike trains are aligned in time. The histogram is obtained by sliding a time window that is discretized into smaller time intervals (bins) centered on a spike of the first (reference) input spike train (corresponding to the lag zero). The spike count of the second (target) spike train input is then obtained in each bin. Therefore, this binning process measures the number of spikes in the target spike train occurring at various time lags relative to the spikes in the reference spike train. The histogram window is slidden over each spike in the reference spike train, and the spike count in each bin is accumulated to produce the CCH output. The width of the bin interval is controlled by a parameter."@en ; + "compute correlogram"@en , + "compute cross-correlogram"@en ; + "compute spike train cross-correlation histogram"@en . + + +### http://purl.org/neao/steps#ComputeSpikeTrainCrossCorrelationHistogramEggermont + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute CCH (Eggermont method)"@en ; + ; + rdfs:comment "A computation of the cross-correlation histogram (CCH) for a pair of binned input spike trains using the method described in Eggermont (2010). The formula is valid for binned spike train inputs with at most one spike per bin, and returns the cross-correlation coefficient for the lags considered (range -1 to 1)."@en ; + "compute correlogram (Eggermont method)"@en , + "compute cross-correlogram (Eggermont method)"@en ; + "compute spike train cross-correlation histogram (Eggermont method)"@en . + + +### http://purl.org/neao/steps#ComputeSpikeTrainFanoFactor + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] ; + ; + rdfs:comment "An analysis step that computes the Fano factor (FF) for a set of input spike trains. For each input spike train, the spike count is obtained. The Fano factor is defined as the ratio of the variance of the spike count to the mean spike count, across all spike trains. The Fano factor is usually computed for spike trains representing the activity of the same neuron over different trials. The value is interpreted as the higher the Fano factor value, the larger the cross-trial non-stationarity. For a stationary Poisson process, the Fano factor has value equal to 1."@en ; + "compute spike train Fano factor"@en . + + +### http://purl.org/neao/steps#ComputeSpikeTrainPearsonCorrelationCoefficient + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A spike train correlation analysis that computes the Pearson correlation coefficient between two spike train inputs. The Pearson correlation coefficient is a real value that quantifies the linear relationship between the two spike trains. It has range [-1, 1], where 1 indicates a perfect positive linear relationship, -1 indicates a perfect negative linear relationship, and 0 indicates no linear relationship. For the computation, the input spike trains are discretized into time intervals (bins), and the spike count is obtained in each bin. The Pearson correlation coefficient is obtained by normalizing the covariance between the binned spike trains: the covariance is divided by the product of the standard deviation of each."@en ; + "compute spike train Pearson correlation coefficient"@en . + + +### http://purl.org/neao/steps#ComputeSpikeTrainTimeHistogram + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] ; + rdfs:comment "An analysis step that computes the time histogram of a spike train. If the spike count in a bin is divided by the duration of the bin, this can be used to estimate the instantaneous firing rate at the bin interval."@en ; + "compute spike train time histogram"@en . + + +### http://purl.org/neao/steps#ComputeSpikeTriggeredAverage + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute STA"@en ; + rdfs:comment "A triggered average analysis that uses spike times as triggers to obtain the average of a signal around each spike (spike-triggered average)."@en ; + "compute spike-triggered average"@en . + + +### http://purl.org/neao/steps#ComputeSpikeTriggeredLFPAverage + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] ; + "compute STA"@en ; + rdfs:comment "A triggered average analysis that uses spike times as triggers to average the local field potential (LFP) signal. The LFP is the low-frequency component of the potential recorded within a specific region of the brain using extracellular electrodes. The output of the method will provide an estimation of the average LFP voltage around each spike, i.e., the spike-triggered average of the LFP signal."@en ; + "compute spike-triggered local field potential average"@en . + + +### http://purl.org/neao/steps#ComputeSpikeTriggeredPhase + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A phase analysis that computes the phase angle values of an analytic signal input (or from the analytic signal obtained from an input time series) at the time points where spikes occurred. The spike times are defined in a spike train input. The output is an array with the phase angle at each spike time in the input spike train (spike-triggered phases)."@en ; + "compute spike-triggered phase"@en . + + +### http://purl.org/neao/steps#ComputeSpikeWaveformAverage + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A spike waveform analysis that computes the average across two or more spike waveform inputs. For the computation, the mean value across all inputs is obtained for each time point in the sampled spike waveform. This is frequently used to reduce noise across multiple spike waveform samples of a single neuron."@en ; + "compute spike waveform average"@en . + + +### http://purl.org/neao/steps#ComputeSpikeWaveformSNR + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute spike waveform SNR"@en ; + ; + rdfs:comment "A spike waveform analysis that computes the signal-to-noise ratio (SNR) for a set of input spike waveforms according to Hatsopoulos (2007). The SNR is defined as the difference in mean peak-to-trough voltage divided by twice the mean standard deviation (SD).The mean SD is obtained by averaging the SDs computed for each time point in the spike waveform."@en ; + "compute spike waveform signal-to-noise ratio"@en . + + +### http://purl.org/neao/steps#ComputeSpikeWaveformVariance + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A spike waveform analysis that computes the variance across two or more spike waveform inputs. For the computation, the value of the variance across all inputs is obtained for each time point in the spike waveform."@en ; + "compute spike waveform variance"@en . + + +### http://purl.org/neao/steps#ComputeSpikeWaveformWidth + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A spike waveform analysis that computes the width of a spike waveform input. The computation takes two time points of interest (e.g, the times of the peak and the trough), and the width is the difference with respect to the time points (e.g., number of time points in between or time interval)."@en ; + "compute spike waveform width"@en . + + +### http://purl.org/neao/steps#ComputeStandardDeviation + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute SD"@en ; + rdfs:comment "A dispersion statistical analysis that computes the standard deviation (SD), i.e., the square root of the variance. The SD indicates the average distance of each data point from the mean."@en ; + "compute standard deviation"@en . + + +### http://purl.org/neao/steps#ComputeStandardErrorMean + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute SEM"@en ; + rdfs:comment "A dispersion statistical analysis that computes the standard error of the mean (SEM). The SEM is the standard deviation of the sampling distribution of the sample mean. It provides an estimate of how much the sample mean is expected to fluctuate around the true population mean. Smaller SEM values indicates that the sample mean is a more accurate estimate of the population mean. The SEM decreases as the sample size increases, as larger samples provide a more reliable estimate of the population mean."@en ; + "compute standard error of the mean"@en . + + +### http://purl.org/neao/steps#ComputeStockwellTransform + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A time-frequency analysis that computes the Stockwell transform (S transform) of the input time series. The S transform generalizes the short-time Fourier transform (STFT) and extends the continuous wavelet transform (CWT). The main difference is that STFT uses a constant window width for all frequencies. The S transform is based on a moving and scalable localizing Gaussian window. Therefore, the window is frequency-dependent (adaptive windowing), which results in better time resolution in higher frequencies and better frequency resolution at lower frequencies. This makes the S transform more suitable to detect transient signals in high frequencies. The computation is computationally expensive, although fast algorithms are available."@en ; + "compute S transform"@en ; + "compute Stockwell transform"@en . + + +### http://purl.org/neao/steps#ComputeTimeDomainConditionalGrangerCausality + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + ; + rdfs:comment "A conditional Granger causality (GC) analysis that computes the GC measures in the time domain."@en ; + "compute time domain conditional Granger causality"@en . + + +### http://purl.org/neao/steps#ComputeTimeDomainPairwiseGrangerCausality + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + owl:disjointWith ; + ; + rdfs:comment "A pairwise Granger causality (GC) analysis that computes measures of GC between two inputs in the time domain. The computation involves fitting two separate autoregressive (AR) models to the input data and comparing their fit to determine if one time series can predict the other. The quality of the fit is assessed by the variance of the residuals, with GC defined as the natural logarithm of the ratio of the residual variances from the two AR models. The first AR model is univariate, predicting the future values of one time series (e.g., the first) only from its past values. The second AR model is bivariate, predicting the future values of the first time series from its past values as well as the past values of the second time series. If the bivariate model reduces the variance of the residuals (ratio greater than 1), the GC value will be positive, indicating that the second time series Granger causes the first (directional GC estimate from the second to the first). The same method is used to predict the second time series from the first, yielding the directional GC estimate from the first to the second time series. The order of the AR model is defined as parameter, and optimal values can be estimated using optimization techniques."@en ; + "compute time domain pairwise Granger causality"@en . + + +### http://purl.org/neao/steps#ComputeTransferEntropy + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "false"^^xsd:boolean + ] ; + "compute TE"@en ; + ; + rdfs:comment "A functional connectivity analysis that computes a measure of transfer entropy (TE) between two input time series. TE measures the directional transfer of information between the time series. It extends Granger causality, and is able to detect non-linear forms of interaction."@en ; + "compute transfer entropy"@en . + + +### http://purl.org/neao/steps#ComputeTuningCurve + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A firing rate analysis that computes a tuning curve. The tuning curve describes the firing rate of a neuron as a function of a continuous attribute (e.g., orientation of a visual grating stimulus)."@en ; + "compute tuning curve"@en . + + +### http://purl.org/neao/steps#ComputeUnbiasedSquaredPhaseLagIndex + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "false"^^xsd:boolean + ] ; + "compute unbiased squared PLI"@en ; + ; + rdfs:comment "A phase lag index (PLI) analysis that computes an unbiased estimate for the squared PLI following Vinck et al. (2011). The direct PLI estimator is positively biased, especially when the sample sizes (i.e., number of trials) are small. The unbiased squared PLI is computed by averaging all pairwise products of the signs computed across the repetitions. Pairs with identical observations are excluded. The unbiased squared PLI is less affected by small-sample size biases."@en ; + "compute unbiased squared phase lag index"@en . + + +### http://purl.org/neao/steps#ComputeVanRossumDistance + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A time-scale dependent spike train distance analysis that computes the van Rossum distance introduced in van Rossum (2001). For the computation, each spike in the input spike trains is convolved with an exponential kernel, producing continuous function representations of the input spike trains. The time scale parameter of the distance is set by the time constant of the exponential kernel. The distance is then obtained as the Euclidean distance of the convolved spike trains."@en ; + "compute van Rossum distance"@en . + + +### http://purl.org/neao/steps#ComputeVariance + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A dispersion statistical analysis that computes the variance, i.e., the average of the squared differences from the mean."@en ; + "compute variance"@en . + + +### http://purl.org/neao/steps#ComputeVictorPurpuraDistance + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A time-scale dependent spike train distance analysis that computes the Victor-Purpura distance, introduced in Victor & Purpura (1996). The metric defines the distance between two spike train inputs with respect to the minimum cost of transforming one spike train into the order considering three operations: spike insertion, spike deletion and shifting a spike by some interval. The first two operations have a fixed cost equal to 1. The latter depends on a cost per time unit parameter, which sets the time scale of the analysis."@en ; + "compute Victor-Purpura distance"@en . + + +### http://purl.org/neao/steps#ComputeWeightedPhaseLagIndex + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "false"^^xsd:boolean + ] ; + "compute WPLI"@en ; + ; + rdfs:comment "A phase lag index (PLI) analysis that computes the weighted PLI (WPLI) following Vinck et al. (2011). The original PLI (Stam, 2007) is discontinuous, and small perturbations can turn phase lags into leads (and vice versa). Therefore, this hinders its capacity to detect changes in phase synchronization of small magnitude. The WPLI extends the PLI to weight the contributions of the phase leads and lags by the magnitude of the imaginary component of the cross spectral density. Therefore, these increases the power to detect changes in phase synchronization. The WPLI ranges between 0 and 1. A WPLI of zero means that there is no imbalance in the first time series leading or lagging the second (i.e., the total weight of all leading relationships is equal to the total weight of lagging relationships). A value greater than zero means an imbalance in the likelihood of leading or lagging. A WPLI of 1 indicates perfect phase locking, and that the first time series only leads or only lags."@en ; + "compute weighted phase lag index"@en . + + +### http://purl.org/neao/steps#ComputedEvokedPotential + rdf:type owl:Class ; + rdfs:subClassOf ; + "compute EP"@en ; + rdfs:comment "An analysis step that computes the evoked potential (EP). The EP is the neural activity (e.g., local field potential or electroencephalogram voltages) around a presented stimulus (e.g., auditory, visual, electrical). Usually, the stimulus is presented repeatedly across multiple trials, obtaining multiple evoked potential waveforms that can be averaged to cancel the noise. It is an event-related potential (ERP) obtained from presenting a stimulus rather than spontaneous behavioral events."@en ; + "compute evoked potential"@en . + + +### http://purl.org/neao/steps#ConditionalGrangerCausalityAnalysis + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + owl:disjointWith ; + rdfs:comment "A Granger causality (GC) analysis that computes a measure of conditional GC between the inputs. The conditional GC is the causality between two inputs (e.g., two time series) while controlling for the influence of an additional input (e.g., a third time series). This allows a more complete understanding of the causal relationships in multivariate time series data."@en ; + "conditional Granger causality analysis"@en . + + +### http://purl.org/neao/steps#ConfidenceIntervalResamplingAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A confidence interval statistical analysis that computes the confidence interval using techniques to generate multiple samples from the (observed) data input(s)."@en ; + "confidence interval with resampling analysis"@en . + + +### http://purl.org/neao/steps#ConfidenceIntervalStatisticalAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A statistical analysis that computes a confidence interval (CI). The CI is a measure providing a range of values of a parameter, derived from the input (sample) data, that is likely to contain the true value of the parameter in the population with a specified level of confidence. The level of confidence is specified as a parameter to the method. For example, a 95% confidence interval means that if the same population is sampled multiple times, approximately 95% of the intervals calculated from those samples will contain the true population parameter. Confidence intervals are used to estimate parameters such as the mean and are essential for making inferences about the population based on sample data. The output contains the upper and lower limits of the CI."@en ; + "confidence interval statistical analysis"@en . + + +### http://purl.org/neao/steps#CorrelatedSpikeTimesGeneration + rdf:type owl:Class ; + rdfs:subClassOf ; + owl:disjointWith ; + rdfs:comment "A spike train generation where the output spike trains will have spikes that are correlated in time. These methods can be used to generate spike trains with patterns in their activity."@en ; + "correlated spike times generation"@en . + + +### http://purl.org/neao/steps#CorrelationAnalysis + rdf:type owl:Class ; + owl:equivalentClass [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "false"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + rdfs:comment "An analysis step that computes a measure of correlation between two inputs. Correlation is a measure that quantifies the strength to which two variables change together. It is a scaled version of the covariance, and the values are restricted to the -1 to +1 interval. Between time series, it is computed in the time domain."@en ; + "correlation analysis"@en . + + +### http://purl.org/neao/steps#CovarianceAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "An analysis step used to compute a measure of covariance from two inputs. The covariance indicates the extent to which the two inputs change together. If the greater values of one variable mainly correspond with the greater values of the other variable, and the same applies to the lesser values, then the covariance is positive. Conversely, if greater values of one variable mainly correspond to the lesser values of the other variable, then the covariance is negative."@en ; + "covariance analysis"@en . + + +### http://purl.org/neao/steps#CrossCorrelationAnalysis + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + rdfs:comment "An analysis step used to compute a measure of cross-correlation, i.e., the correlation of two inputs computed for distinct time lags of the first to the second. The computation produces the cross-correlation value for every lag considered."@en ; + "cross-correlation analysis"@en . + + +### http://purl.org/neao/steps#CrossPowerSpectralDensityAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + "CPSD analysis"@en ; + rdfs:comment "A spectral density analysis that computes the cross power spectral density (CPSD) of two inputs, i.e., the distribution of their power across the different frequency components per unit frequency. The CPSD shows in the frequency domain how the two inputs are correlated in the time domain, and is equivalent to the Fourier transform of the cross-correlation function between the two signals. If the inputs are not correlated, the CPSD will be flat across the frequencies. A peak suggests that the signals are correlated at that frequency. The CPSD is often referred to as cross-spectrum."@en ; + "cross power spectral density analysis"@en . + + +### http://purl.org/neao/steps#CurrentSourceDensityAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + "CSD analysis"@en ; + rdfs:comment "An analysis step used to analyze extracellular electrical potentials (e.g., local field potentials or evoked potentials) recorded from multiple locations, enabling the estimation of the current sources responsible for generating these potentials. The methods can be applied to data recorded from different electrode configurations: laminar probe-like electrodes (1D methods), microelectrode array-like electrodes (2D methods) or electrodes configurations recording from a volume (e.g., multiple laminar probes or array electrodes with shanks with multiple depths; 3D methods). The output of the current source analysis provides the spatial map showing where currents are entering (sources) and leaving (sinks) the neural tissue. For each point in the map, a quantitative value indicates the magnitude of the current density at that point."@en ; + "source imaging analysis"@en , + "source localization analysis"@en ; + "current source density analysis"@en . + + +### http://purl.org/neao/steps#DataGeneration + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "An analysis step that generates new data entities. This can be done using other input data as a start (e.g., generating a spike train surrogate from spike trains obtained from experimental recordings) or generate new data using algorithms that take specific parameters (e.g., generating a spike train using a probability distribution defined by specific parameters)."@en ; + "data generation"@en . + + +### http://purl.org/neao/steps#DataNormalization + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A data transformation that adjusts the ranges and distributions of the values in the input data. This can be used to transform data measured in distinct (i.e. not directly comparable) scales to a common (i.e. comparable) scale."@en ; + "data normalization"@en . + + +### http://purl.org/neao/steps#DataSmoothing + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A data transformation that uses statistical techniques to remove noise and fluctuations from the input data to reveal underlying trends and patterns."@en ; + "data smoothing"@en . + + +### http://purl.org/neao/steps#DataTransformation + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "An analysis step that takes one or more inputs and modifies the contents, such that it fits a particular purpose. The data transformation steps are frequently used during pre-processing the input data for the analyses. Usually, a data transformation will not change the main representation or quality of the inputs. For example, a digital filtering step will remove certain frequency components from a time series. However, the output will resemble the original input with respect to shape or physical units. In addition, the inputs can also be converted to other formats or representations that are needed for a particular analysis step. For example, spike trains can be discretized into small intervals (binning) or the dimensionality of the input can be reduced using principal component analysis. The data transformation is in contrast to steps that perform computations that take the input and generate a derived measure with new information. For example, when computing the mean firing rate from a spike train, a single scalar value is obtained from the spike count in the input data."@en ; + "data transformation"@en . + + +### http://purl.org/neao/steps#Detrending + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A data transformation that removes a trend (i.e., a change in the mean over time) from an input time series."@en ; + "detrending"@en . + + +### http://purl.org/neao/steps#DigitalFiltering + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A data transformation that processes digital signal inputs (i.e., sampled time series) to attenuate or amplify specific frequency components. Digital filters can be designed using various methods, achieving distinct frequency responses and stability."@en ; + "digital filtering"@en . + + +### http://purl.org/neao/steps#DimensionalityReduction + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A data transformation that obtains a low-dimensional (simplified) representation of the high-dimensional input data. This step retains important information in the input data while minimizing redundancy and noise."@en ; + "dimensionality reduction"@en . + + +### http://purl.org/neao/steps#DirectedAnalysis + rdf:type owl:Class ; + owl:equivalentClass [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + rdfs:subClassOf ; + owl:disjointWith ; + rdfs:comment "An analysis step where the output provides information on the direction of influence in the relationships among the inputs (e.g., in the cross-correlation histogram, it is possible to analyze the timing of the spikes of the first input spike train with respect to the timing of the spikes of the second input spike train, i.e., whether they likely occur before or after)."@en ; + "directed analysis"@en . + + +### http://purl.org/neao/steps#DispersionStatisticalAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A statistical analysis that computes a measure that represents the variability in the input data. It indicated the degree to which the data points differ from the central tendency."@en ; + "dispersion statistical analysis"@en . + + +### http://purl.org/neao/steps#DistanceAnalysis + rdf:type owl:Class ; + owl:equivalentClass [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] ; + rdfs:subClassOf . + + +### http://purl.org/neao/steps#Execute3dSPADEAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + owl:disjointWith ; + ; + rdfs:comment "A SPADE analysis that uses the 3d-SPADE implementation as defined in Stella et al. (2019). The 3d-SPADE analysis considers spatio-temporal patterns (i.e., not restricted to synchronous patterns), and the pattern signature used for statistical testing considers the size, number of occurrences and duration of a pattern."@en ; + "execute 3d-SPADE analysis"@en . + + +### http://purl.org/neao/steps#ExecuteASSETAnalysis + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:someValuesFrom + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "false"^^xsd:boolean + ] ; + ; + rdfs:comment """A neuronal activity pattern detection analysis that uses the Analysis of Sequences of Synchronous EvenTs (ASSET) method defined in Torre et al. (2016). ASSET is an automatized test to identify the sequential activations of groups of neurons that repeat in time. The identification of the repeated sequences is possible by computing the intersection matrix. The input spike data is discretized into smaller intervals (bins), and the overlap of neuronal activity at each bin pair is obtained as a matrix. When a sequence of activations exists and repeats in time, a characteristic diagonal structure appears in the matrix. + +The ASSET analysis provides a robust statistical test to automatically identify the diagonal structures and to provide the neurons and their activation pattern in each repeated sequence. Overall, the analysis is composed by 6 substeps: + +1. Compute the intersection matrix (IMAT) from a set of input spike trains, using a specified bin size to discretize the data. +2. Obtain the probability matrix (PMAT). +3. Obtain the joint probability matrix (JMAT). +4. Extract significant entries in both PMAT and JMAT using specified thresholds, obtaining the mask matrix (MMAT). +5. Obtain the cluster matrix (CMAT) by using DBSCAN to cluster the significant entries in the MMAT to find each diagonal structure. Parameters for DBSCAN control the clustering result. A modified distance metric is used. +6. From the identified clusters (each a single diagonal structure in the IMAT), obtain the neuronal composition and the order of activation, producing the final neuronal activity patterns as output."""@en ; + "execute ASSET analysis"@en . + + +### http://purl.org/neao/steps#ExecuteCellAssemblyDetectionAnalysis + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "false"^^xsd:boolean + ] ; + "execute CAD analysis"@en ; + ; + rdfs:comment "A neuronal activity pattern detection analysis that uses the Cell Assembly Detection (CAD) method as defined in Russo & Durstewitz (2017). CAD allows detecting spatio-temporal spike patterns at different time scales, levels of precision, and with arbitrary internal organization. The analysis identifies patterns with different delays between the spikes (within a window determining the minimum and maximum lags), and is performed in two steps using an agglomerative clustering algorithm. First, significant pairwise correlations are identified, which is followed by the clustering procedure that progressively finds interactions of higher order. At each agglomeration step, the method can filter out patterns involving the same neurons, keeping the most significant pattern (significance pruning). In an additional pruning step, assemblies part of a larger assembly can also be eliminated (controlled by the subgroup pruning parameter). The algorithm stops when the detected assemblies reach their maximum size (determined by a parameter). The statistical test assumes independence under non-stationarity and Poisson distribution of the input spike trains."@en ; + "execute Cell Assembly Detection analysis"@en . + + +### http://purl.org/neao/steps#ExecuteNon3dSPADEAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A SPADE analysis that uses the SPADE implementation as defined in Quaglio et al. (2017). This is the extension of SPADE to consider spatio-temporal patterns (i.e., patterns not restricted to synchronous spiking). In the non-3d SPADE analysis, the pattern signature used for statistical testing considers only the size and number of occurrences of a pattern."@en ; + "execute non-3d-SPADE analysis"@en . + + +### http://purl.org/neao/steps#ExecuteUnitaryEventAnalysisAnalytical + rdf:type owl:Class ; + rdfs:subClassOf ; + owl:disjointWith ; + "execute UE analysis (analytical method)"@en ; + , + , + , + ; + rdfs:comment "A unitary event (UE) analysis that uses the analytical approach to determine the significance of the empirical coincidences in binned spike train data, as defined in Grün et al. (1999, 2002a, 2002b, and 2003). The analytical method tests if the number of empirical coincidences is consistent with the coincidence distribution resulting from independent processes. This distribution can be expressed analytically assuming that the input spike trains follow Poisson statistics. The UEs can be determined trial by trial, where the analytical expectancy is computed for each trial and then summed over all trials, or by averaging over all trials (according to Grün, 2003)."@en ; + "execute Unitary Event analysis (analytical method)"@en . + + +### http://purl.org/neao/steps#ExecuteUnitaryEventAnalysisMonteCarlo + rdf:type owl:Class ; + rdfs:subClassOf ; + "execute UE analysis (Monte Carlo method)"@en ; + ; + rdfs:comment "A unitary event (UE) analysis that uses a Monte Carlo approach based on spike train surrogates to determine the significance of the empirical coincidences in binned spike train data, according to Grün (2009). The Monte Carlo method does not rely on the assumption that the input spike data follows Poisson statistics. For the assessment of significance, the distribution of expected coincidences is determined by surrogates (spike train randomization) in each trial, and then summed over trials. The number of surrogates is determined by a parameter."@en ; + "execute Unitary Event analysis (Monte Carlo method)"@en . + + +### http://purl.org/neao/steps#FieldFieldCouplingAnalysis + rdf:type owl:Class ; + owl:equivalentClass [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] ; + rdfs:subClassOf ; + owl:disjointWith ; + rdfs:comment "An analysis step that computes interactions between the neural activity represented by distinct local field potential (LFP) signals (e.g., LFP obtained from different electrodes, or distinct LFP frequency bands)."@en ; + "field-field coupling analysis"@en . + + +### http://purl.org/neao/steps#FiniteImpulseResponseFiltering + rdf:type owl:Class ; + rdfs:subClassOf ; + "FIR filtering"@en ; + rdfs:comment "A digital filtering that uses a filter whose impulse response (i.e., the response of the filter to a brief input impulse) decays to zero after a finite amount of time. Therefore, the output of the filter depends on a finite number of past samples. The finite impulse response (FIR) filters are stable and can be designed such that they do not distort the phase of the signal. However, they have a higher computational cost."@en ; + "finite impulse response filtering"@en . + + +### http://purl.org/neao/steps#FiringRateAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "An analysis step used to compute a measure quantifying the firing rate of one or more neurons. The firing rate is the number of action potential (spikes) that a neuron fires per time unit and is defined with a unit of frequency (e.g., Hz or spikes/s)."@en ; + "firing rate analysis"@en . + + +### http://purl.org/neao/steps#FrequencyDomainAnalysis + rdf:type owl:Class ; + owl:equivalentClass [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + rdfs:subClassOf ; + owl:disjointWith ; + rdfs:comment "An analysis step that analyzes the input(s) with respect to its(their) frequency content."@en ; + "frequency domain analysis"@en . + + +### http://purl.org/neao/steps#FrequencyDomainPairwiseGrangerCausalityAnalysis + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + ; + rdfs:comment "A pairwise Granger causality (GC) analysis that computes measures of GC between two inputs in the frequency domain. This is an extension of the GC concept in the time domain, and the measures of GC are obtained for the different frequency components of the inputs, according to Geweke (1982). The computation of the frequency-domain GC measures is based on two elements: the noise covariance matrix and the spectral transfer matrix. These can be estimated either with parametric or non-parametric methods. For the parametric estimation, an autoregressive model is fit and the Fourier transform of the autoregressive coefficients is used to obtain the spectral transfer matrix. For the non-parametric estimation, the cross-spectral density (CSD) matrix is obtained (using methods for CSD estimation such as multitapering or wavelet), and the CSD matrix is factorized to obtain the noise covariance and spectral transfer matrices."@en ; + "frequency domain pairwise granger causality analysis"@en . + + +### http://purl.org/neao/steps#FrequencyDomainTransformation + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A data transformation that converts a time series input from the time to the frequency domain, i.e., reveal the different frequency components that make up the original signal."@en ; + "frequency domain transformation"@en . + + +### http://purl.org/neao/steps#FunctionalConnectivityAnalysis + rdf:type owl:Class ; + owl:equivalentClass [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] ; + rdfs:subClassOf ; + "FCA"@en ; + rdfs:comment "An analysis step that computes measures of functional connectivity. Functional connectivity refers to statistical dependencies and patterns of synchronization between the neural activity that indicate the functional interactions and co-activations that are relevant for the function of the nervous system (e.g., the interactions between different brain regions). It does not imply direct physical connections."@en ; + "functional connectivity analysis"@en . + + +### http://purl.org/neao/steps#GenerateCompoundPoissonProcess + rdf:type owl:Class ; + rdfs:subClassOf ; + owl:disjointWith ; + ; + rdfs:comment "A correlated spike times generation that produces spike trains using a compound Poisson process (CPP) according to Staude et al. (2010). The CPP is a model for parallel and correlated processes with Poisson spiking statistics at predefined firing rates."@en ; + "generate CPP"@en ; + "generate compound Poisson process"@en . + + +### http://purl.org/neao/steps#GenerateISIDitheringSurrogate + rdf:type owl:Class ; + rdfs:subClassOf ; + "generate ISI-D surrogate"@en ; + ; + rdfs:comment "A spike train surrogate generation step where each spike is displaced according to the interspike interval (ISI) distribution sampled from the input spike train."@en ; + "generate joint interspike interval dithering surrogate"@en . + + +### http://purl.org/neao/steps#GenerateISIShufflingSurrogate + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A spike train surrogate generation step where the interspike intervals (ISIs) of the input spike train is randomly sorted. This preserves the ISI distribution and spike count as in the original spike train input, but destroys temporal dependencies and firing rate profile."@en ; + "generate interspike interval shuffling surrogate"@en . + + +### http://purl.org/neao/steps#GenerateJointISIDitheringSurrogate + rdf:type owl:Class ; + rdfs:subClassOf ; + "generate JISI-D surrogate"@en ; + ; + rdfs:comment "A spike train surrogate generation step where spikes from adjacent interspike intervals (ISIs) are dithered according to the joint-ISI (JISI) probability distribution. The distribution is obtained from the input spike train by computing the JISI histogram (i.e., a two-dimensional histogram that shows the frequency of ISIs with a given duration that are immediately followed by intervals with another duration). Due to non-stationarities in the input spike train and/or its limited duration, it is difficult to accurately estimate the underlying JISI probability distribution. Therefore, a 2D-Gaussian smoothing is applied to the JISI histogram (with a variance determined by parameter). Dithering a spike according to this (smoothed) two-dimensional histogram involves moving the spike along the anti-diagonal of the JISI distribution. The dithering time is defined by a parameter."@en ; + "generate joint interspike interval dithering surrogate"@en . + + +### http://purl.org/neao/steps#GenerateMorletWavelet + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A data generation that constructs a Morlet wavelet considering the selected parameters (i.e., sampling frequency, fundamental frequency, and number of cycles per frequency). The Morlet wavelet is composed by a complex exponential multiplied by a Gaussian window. The output data contains the discrete time points and the corresponding wavelet values."@en ; + "generate Morlet wavelet"@en . + + +### http://purl.org/neao/steps#GenerateNonStationaryGammaProcess + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A random spike times generation that uses a gamma probability distribution to produce spike trains where the firing rate varies over time."@en ; + "generate non-stationary gamma process"@en . + + +### http://purl.org/neao/steps#GenerateNonStationaryPoissonProcess + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A random spike times generation that uses a Poisson probability distribution to produce spike trains where the firing rate varies over time. A dead time can be specified as parameter (i.e., an interval where no spikes can occur, which is analogous to the neuronal refractory period)."@en ; + "generate non-stationary Poisson process"@en . + + +### http://purl.org/neao/steps#GenerateSingleInteractionProcess + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A correlated spike times generation that produces a multidimensional Poisson single interaction process (SIP) plus independent Poisson processes, according to Kuhn et al. (2003). The Poisson SIP consists of Poisson time series that are independent except for events that are simultaneous in all of them."@en ; + "generate SIP"@en ; + "generate single interaction process"@en . + + +### http://purl.org/neao/steps#GenerateSpikeTimeRandomizationSurrogate + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A spike train surrogate generation step that keeps the spike count of the input spike train, but the spike times in the surrogate spike train output are randomly chosen within the duration interval of the input spike train."@en ; + "generate spike time randomization surrogate"@en . + + +### http://purl.org/neao/steps#GenerateSpikeTrainDitheringSurrogate + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A spike train surrogate generation step that displaces the whole input spike train by a random amount of time (independent for each surrogate generated). The amount of displacement is specified as a parameter (dither time), and occurs in a window (-dither time, dither time). This surrogate maintains the ISIs and the temporal correlations within the spike train."@en ; + "generate spike train dithering surrogate"@en . + + +### http://purl.org/neao/steps#GenerateStationaryGammaProcess + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A random spike times generation that uses a gamma probability distribution to produce spike trains with a constant firing rate."@en ; + "generate stationary gamma process"@en . + + +### http://purl.org/neao/steps#GenerateStationaryInverseGaussianProcess + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A random spike times generation that uses a inverse Gaussian probability distribution to produce spike trains with a constant firing rate."@en ; + "generate stationary inverse Gaussian process"@en . + + +### http://purl.org/neao/steps#GenerateStationaryLogNormalProcess + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A random spike times generation that uses a log-normal probability distribution to produce spike trains with a constant firing rate."@en ; + "generate stationary log-normal process"@en . + + +### http://purl.org/neao/steps#GenerateStationaryPoissonProcess + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A random spike times generation that uses a Poisson probability distribution to produce spike trains with a constant firing rate. A dead time can be specified as parameter (i.e., an interval where no spikes can occur, which is analogous to the neuronal refractory period)."@en ; + "generate stationary Poisson process"@en . + + +### http://purl.org/neao/steps#GenerateTrialShiftingSurrogate + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A spike train surrogate generation step that shifts the entire spike train (containing the data of a single experimental trial) by an amount randomly chosen from a uniform distribution. The amount of displacement is specified as a parameter (dither time), and occurs in a window (-dither time, dither time). The input is a collection of spike trains of the same neuron, containing the spiking activity during different experimental trials. The amount of shift is independently chosen across trials and neurons. This surrogate preserves the ISI distribution and temporal correlations within the single-trial spike train."@en ; + "generate trial shifting surrogate"@en . + + +### http://purl.org/neao/steps#GenerateTrialShufflingSurrogate + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A spike train surrogate generation step where the the spike trains of single-trial activity of one of the neurons are randomly permuted, so that each trial is no longer paired with the corresponding trial of the other neuron, but with a randomly selected one. The input is a collection of spike trains with multitrial activity data of multiple neurons recorded in parallel."@en ; + "generate trial shuffling surrogate"@en . + + +### http://purl.org/neao/steps#GenerateUniformSpikeDitheringSurrogate + rdf:type owl:Class ; + rdfs:subClassOf ; + "generate UD surrogate"@en ; + ; + rdfs:comment "A spike train surrogate generation step that displaces each spike time in the input spike train according to a uniform distribution centered on the spike. The displacement occurs in a time window around the spike defined by a parameter (dither time)."@en ; + "generate uniform spike dithering surrogate"@en . + + +### http://purl.org/neao/steps#GenerateUniformSpikeDitheringSurrogateWithDeadTime + rdf:type owl:Class ; + rdfs:subClassOf ; + "generate UDD surrogate"@en ; + ; + rdfs:comment "A spike train surrogate generation step that displaces each spike time in the input spike train according to a uniform distribution centered on the spike. The displacement occurs in a time window around the spike defined by a parameter (dither time) that is constrained to the intervals between adjacent spikes to avoid two spikes closer than a dead time (specified by parameter). This mimics the refractory period behavior of neurons, where the neuron cannot fire additional spikes for a short interval after one spike."@en ; + "generate uniform spike dithering surrogate with dead time"@en . + + +### http://purl.org/neao/steps#GenerateWindowShufflingSurrogate + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A spike train surrogate generation step that shuffles the entries of a binned spike train within exclusive maximal displacement windows. The maximal displacement is specified by parameter, and represents the maximum number of bins that a spike can be displaced within the window."@en ; + "generate bin shuffling within exclusive windows surrogate"@en ; + "generate window shuffling surrogate"@en . + + +### http://purl.org/neao/steps#GrangerCausalityAnalysis + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + "GC analysis"@en ; + rdfs:comment "A functional connectivity analysis that computes measures of Granger causality (GC). GC is a statistical concept where the future values of a time series are predicted based on its past values and the past values of other time series. GC quantifies bi-directional interactions between the inputs, determining the directional influence from one input to another. For example, with two inputs, GC measures how much the first input influences the second and vice versa (directional GC measure). This provides estimates of the directed connectivity between the inputs. It is also possible to compute associated measures, such as the instantaneous GC (a measure of interdependence between the inputs not accounted by their bi-directional interactions, such as shared neural input) and the total interdependence (the sum of all directional and instantaneous interactions between the inputs). The analysis can be performed in the time or frequency domains, and can take two (bivariate) or more inputs (multivariate)."@en ; + "Granger causality analysis"@en . + + +### http://purl.org/neao/steps#InfiniteImpulseResponseFiltering + rdf:type owl:Class ; + rdfs:subClassOf ; + "IIR filtering"@en ; + rdfs:comment "A digital filtering that uses a filter whose impulse response (i.e., the response of the filter to a brief input impulse) persists infinitely. Therefore, the output of the filter can depend on an infinite number of past samples. The infinite impulse response (IIR) filters can become unstable and distort the phase of the signal, but have a lower computational cost."@en ; + "infinite impulse response filtering"@en . + + +### http://purl.org/neao/steps#InstantaneousFiringRateAnalysis + rdf:type owl:Class ; + owl:equivalentClass [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] ; + rdfs:subClassOf ; + rdfs:comment "A firing rate analysis that computes the instantaneous firing rate, which is the estimate of the firing rate at a specific point in time. The instantaneous firing rate value can be obtained by several methods."@en ; + "instantaneous firing rate analysis"@en . + + +### http://purl.org/neao/steps#InterspikeIntervalAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + "ISI analysis"@en ; + rdfs:comment "An analysis step that computes or analyzes the interval between successive spikes in a spike train (interspike interval; ISI)."@en ; + "interspike interval analysis"@en . + + +### http://purl.org/neao/steps#InterspikeIntervalVariabilityAnalysis + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] ; + rdfs:comment "An interspike interval analysis that computes a measure describing the variability of the interspike intervals. The measure can assess how regular a neuron is firing."@en ; + "interspike interval variability analysis"@en . + + +### http://purl.org/neao/steps#KernelSmoothing + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A data smoothing that performs a convolution of the input data with a kernel function. This computes a weighted average of the data around the kernel. Several kernel types can be used for the smoothing (e.g., Gaussian, exponential) and the kernel shape is controlled by a width parameter."@en ; + "kernel smoothing"@en . + + +### http://purl.org/neao/steps#LatentDynamicsAnalysis + rdf:type owl:Class ; + owl:equivalentClass [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] ; + rdfs:subClassOf ; + rdfs:comment "An analysis step that aims to identify underlying patterns and structures within time series or sequential data that are not directly observable. It involves modeling hidden (latent) variables that influence the observed data and their evolution over time. The analysis captures temporal dependencies and dynamics within the data, providing insights into the processes that generate the observed sequences."@en ; + "latent dynamics analysis"@en . + + +### http://purl.org/neao/steps#LineNoiseRemoval + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A data transformation that removes noise induced by the power line."@en ; + "line noise cancellation"@en ; + "line noise removal"@en . + + +### http://purl.org/neao/steps#MeanVectorLengthAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + "MVL analysis"@en ; + rdfs:comment "A phase-amplitude coupling (PAC) analysis that computes the mean vector length (MVL) measure. The MVL is based on a mean vector obtained from a time series defined in the complex plane, where the amplitude is taken from the high-frequency oscillation input and the phase from the low-frequency oscillation input."@en ; + "mean vector length analysis"@en . + + +### http://purl.org/neao/steps#ModelBasedAnalysis + rdf:type owl:Class ; + owl:equivalentClass [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + rdfs:subClassOf ; + rdfs:comment "An analysis step that depends on assumptions on the interactions between the inputs to perform the computations. For example, the Granger causality analysis assumes linear relationships between the input signals."@en ; + "model-based analysis"@en . + + +### http://purl.org/neao/steps#ModelFreeAnalysis + rdf:type owl:Class ; + owl:equivalentClass [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "false"^^xsd:boolean + ] ; + rdfs:subClassOf ; + rdfs:comment "An analysis step that does not depend on assumptions on the interactions between the inputs to perform the computations. For example, it can consider probability distributions obtained from the input data."@en ; + "model-free analysis"@en . + + +### http://purl.org/neao/steps#MultivariateAnalysis + rdf:type owl:Class ; + owl:equivalentClass [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + rdfs:subClassOf ; + rdfs:comment "An analysis step that has three or more distinct inputs considered for the computation of the output (e.g., the time series with the local field potential signals recorded from three or more electrodes, used to compute the partial directed coherence)."@en ; + "multivariate analysis"@en . + + +### http://purl.org/neao/steps#NeuronalActivityPatternDetectionAnalysis + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + rdfs:comment "An analysis step that aims to identify a neuronal activity pattern, i.e., spikes of a group of neurons that occur in a specific spatio-temporal configuration."@en ; + "neuronal activity pattern detection analysis"@en . + + +### http://purl.org/neao/steps#NeuronalFiringRegularityAnalysis + rdf:type owl:Class ; + owl:equivalentClass [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] ; + rdfs:subClassOf ; + rdfs:comment "An analysis step that computes measures to assess the regularity in the firing of a neuron. Neuronal firing regularity refers to the consistency or variability in the timing of action potentials (spikes) generated by a neuron."@en ; + "spike time variability analysis"@en ; + "neuronal firing regularity analysis"@en . + + +### http://purl.org/neao/steps#NonDirectedAnalysis + rdf:type owl:Class ; + owl:equivalentClass [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "false"^^xsd:boolean + ] ; + rdfs:subClassOf ; + rdfs:comment "An analysis step where the output does not provide information on the direction of influence in the relationships among the inputs (e.g., in the Pearson correlation coefficient computed between two spike trains, it is possible to know how strongly they tend to fire together. However, it is not possible to analyze the timing of the spikes of the first input spike with respect to the timing of the spikes of the second input spike train)."@en ; + "non-directed analysis"@en . + + +### http://purl.org/neao/steps#PairwiseGrangerCausalityAnalysis + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + rdfs:comment "A Granger causality (GC) analysis that computes a measure of GC between two inputs."@en ; + "pairwise Granger causality analysis"@en . + + +### http://purl.org/neao/steps#PeristimulusTimeHistogramAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + "PSTH analysis"@en ; + rdfs:comment "A spike train time histogram analysis that computes the peristimulus time histogram (PSTH). PSTH is the time histogram of two or more spike trains containing repeated recordings of a single neuron around the time when an event of interest occurred. The event of interest can occur at any time point during the duration of the source spike trains. The distribution of the histogram corresponds to the distribution of the activity of the neuron with respect to the event across the repeated recordings. The event of interest can be an externally presented stimulus or a spontaneous behavioral event. If the histogram represents the neuronal activity after the stimulus presentation or event occurrence, this can be referred as post-stimulus time histogram. Conversely, if the histogram shows the activity of the neuron before the stimulus presentation or event, this can be referred as prestimulus time histogram. Finally, if the histogram considers a behavioral event (or an event that is not an externally presented stimulus), the histogram can be referred to as perievent time histogram (PETH)."@en ; + "peristimulus time histogram analysis"@en . + + +### http://purl.org/neao/steps#PhaseAmplitudeCouplingAnalysis + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "false"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + "PAC analysis"@en ; + rdfs:comment "A phase analysis that computes measures describing how the phase of a low-frequency oscillation modulates the amplitude of a high-frequency oscillation. Phase-amplitude coupling (PAC) can be used to investigate interactions between different frequency bands in the neural activity."@en ; + "phase-amplitude coupling analysis"@en . + + +### http://purl.org/neao/steps#PhaseAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "An analysis step that computes measures related to the phase in the input data. Phase expresses the position of a time-varying signal relative to a fixed reference point in time. For periodic and oscillatory signals (e.g., a sine waveform), phase analysis involves determining the angle on the unit circle that corresponds to the current position within the waveform's cycle. This helps understanding the timing and synchronization of the oscillations in the input data."@en ; + "phase analysis"@en . + + +### http://purl.org/neao/steps#PhaseLagIndexAnalysis + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + "PLI analysis"@en ; + rdfs:comment "A phase analysis that computes the phase lag index (PLI). The PLI measures the asymmetry of the distribution of the phase differences between two input time series, i.e., if there is an imbalance in the likelihood of the first time series leading or lagging the second time series. It is designed to be invariant to common sources, such as volume conduction and/or active reference electrodes."@en ; + "phase lag index analysis"@en . + + +### http://purl.org/neao/steps#PhaseLockingValueAnalysis + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "false"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + "PLV analysis"@en ; + rdfs:comment "A phase analysis that computes the phase locking value (PLV). The PLV quantifies the consistency of the phase difference between two input time series across time (e.g., multiple experimental trials)."@en ; + "phase locking value analysis"@en . + + +### http://purl.org/neao/steps#PowerSpectralDensityAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + "PSD analysis"@en ; + rdfs:comment "A spectral density analysis that computes the power spectral density of an input, i.e., the distribution of power across the different frequency components of the input signal per unit frequency. It is equivalent to the Fourier transform of the autocorrelation function of the input signal. The computed power spectral density values can be corrected depending on the analysis returning the two-sided (i.e., with negative frequencies) or one-sided (i.e., positive frequencies only) PSD. The PSD is often referred to as spectrum."@en ; + "auto spectral density analysis"@en ; + "power spectral density analysis"@en . + + +### http://purl.org/neao/steps#PrincipalComponentAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + "PCA"@en ; + rdfs:comment "A dimensionality reduction that reduces the dimensionality of the input data represented as a matrix with numerous rows and columns. It transforms the data into a set of principal components (PCs) that capture the maximum variance in the input. Each PC is a linear combination of the original variables and serves as a new axis in a lower-dimensional space. The PCs are orthogonal to each other, meaning they capture independent aspects of the input data's variability."@en ; + "principal component analysis"@en . + + +### http://purl.org/neao/steps#RandomSpikeTimesGeneration + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A spike train generation where the output spike trains will have random spike times, taken from a specific probability distribution. The generation process can produce spike trains where the firing rate is constant (stationary) or varies (non-stationary) over time."@en ; + "random spike times generation"@en . + + +### http://purl.org/neao/steps#Resampling + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A data transformation that changes the number of samples in the input data."@en ; + "resampling"@en . + + +### http://purl.org/neao/steps#SPADEAnalysis + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "false"^^xsd:boolean + ] ; + rdfs:comment """A neuronal activity pattern detection analysis that uses the Spatio-temporal PAttern Detection and Evaluation (SPADE) method. The SPADE analysis takes a set of parallel spike trains as input, and returns significant spatio-temporal neuronal activity (spike) patterns. + +The SPADE method consists of three substeps: + +1. Detect all putative patterns in the input data using the frequent item set mining (FIM) algorithm. This step requires the discretization of the input spike train data (binning). The bin size determines the temporal resolution of the analysis. + +2. The detected FIM patterns are evaluated for statistical significance, considering the null hypothesis of independence of the spike trains given the modulations by the firing rate. This substep is called Pattern Spectrum Filtering (PSF). For the testing, the patterns are pooled based on their signature: size and occurrence count (non-3d-SPADE) or size, occurrence count and pattern duration (3d-SPADE). The pattern spectrum collects the counts of patterns from each signature. The statistical test is done by a Monte Carlo approach, using spike train surrogates generated from the original data. The final output of this substep is the p-value spectrum, which has the same dimensions as the pattern spectrum. The p-value is computed as the ratio of surrogates containing patterns with that signature to the total number of realizations. + +3. Conditional test on the significant patterns to remove patterns arising from the overlap of true pattern spikes and chance spikes (pattern set reduction; PSR)."""@en ; + "SPADE analysis"@en . + + +### http://purl.org/neao/steps#SpectralAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "An analysis step that computes measures describing the input data with respect to its frequency contents."@en ; + "spectral analysis"@en . + + +### http://purl.org/neao/steps#SpectralDensityAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A spectral analysis that computes the density of a measure of the input(s) over the frequency spectrum. Density means that the measure value (e.g., power) for each frequency component is expressed per unit frequency. For example, for an input time series with voltages recorded from an electrode (measured in V), the power for each frequency component of the signal will be in V**2, while the power density will be in V**2/Hz. Therefore, the power values are normalized per unit frequency. This normalization allows for consistent comparisons of results from analyses with different frequency resolutions, as the spectral density remains unaffected by these variations."@en ; + "spectral density analysis"@en . + + +### http://purl.org/neao/steps#SpectrogramAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A time-frequency analysis that shows the power (or power density) of different frequency components of the input(s) as they change over time. This can be obtained for a single input (spectrogram) or for two distinct inputs (cross-spectrogram)."@en ; + "spectrogram analysis"@en . + + +### http://purl.org/neao/steps#SpikeFieldCoherenceAnalysis + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "false"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + "SFC analysis"@en ; + rdfs:comment "An analysis step that computes the spike-field coherence (SFC), which is the coherence computed between an input spike train and an input time series with the local field potential (LFP). Coherence is a measure of the association between the two inputs in the frequency domain. SFC can be used to quantify the relationship between the spiking activity of neurons and the oscillatory activity in the LFP. It represents the similarity of dynamics between the spike train and the voltage fluctuations produced by the neural activity in the local environment where the spiking activity was recorded."@en ; + "spike-field coherence analysis"@en . + + +### http://purl.org/neao/steps#SpikeFieldCouplingAnalysis + rdf:type owl:Class ; + owl:equivalentClass [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] ; + rdfs:subClassOf ; + owl:disjointWith ; + rdfs:comment "An analysis step that computes interactions between the spiking activity of neurons (individual or population) and the local field potential (LFP)."@en ; + "spike-field coupling analysis"@en . + + +### http://purl.org/neao/steps#SpikeSpikeCouplingAnalysis + rdf:type owl:Class ; + owl:equivalentClass [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] ; + rdfs:subClassOf ; + rdfs:comment "An analysis step that computes interactions between the spiking activity of one or more neurons."@en ; + "spike-spike coupling analysis"@en . + + +### http://purl.org/neao/steps#SpikeTrainCorrelationAnalysis + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "false"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + rdfs:comment "An analysis step that computes measures estimating the correlation between spike train inputs. The correlation value is a normalized measure of covariation in the input spike train data, and reflects the strength and direction of the association: positive values mean that the inputs vary in the same direction, and negative values mean that the inputs vary in opposite directions (e.g., if the activity in one spike train increases, it decreases in the other)."@en ; + "spike train correlation analysis"@en . + + +### http://purl.org/neao/steps#SpikeTrainDissimilarityAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "An analysis step that computes a measure comparing spike train inputs and providing an estimation of their similarity/dissimilarity. This is frequently done by computing spike train distances, which are measures that assign the notion of distance, i.e., the input spike trains are considered as elements in a space and, if similar, will be close together."@en ; + "spike train dissimilarity analysis"@en . + + +### http://purl.org/neao/steps#SpikeTrainGeneration + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:allValuesFrom + ] ; + rdfs:comment "A data generation that produces one or more artificial spike trains using distinct statistical procedures to determine the spike times."@en ; + "spike train generation"@en . + + +### http://purl.org/neao/steps#SpikeTrainSurrogateGeneration + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A data generation that produces one or more spike train surrogates. A spike train surrogate is a new spike train derived from an input spike train (usually experimentally recorded). This is done using methods that alter the original spike times while trying to maintain specific statistical features of the original spike train (e.g., firing rate, interspike interval distribution). This is used to destroy fine temporal correlations in the spiking activity."@en ; + "spike train surrogate generation"@en . + + +### http://purl.org/neao/steps#SpikeTrainSynchronyAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "An analysis step to assess synchronization in two or more spike train inputs that typically represent the activity of different neurons. Spike train synchronization refers to the temporal coordination of action potentials (spikes) between neurons, and describes the degree to which their spikes tend to occur at the same time."@en ; + "spike train synchrony analysis"@en . + + +### http://purl.org/neao/steps#SpikeTrainTimeHistogramAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment """A firing rate analysis that computes histograms of spike train data over time. The time histogram is obtained by discretizing the duration of the spike train into distinct time intervals (bins), and obtaining the spike count inside each bin. + +The histogram can show one of three different measures: + +* the spike count at each bin (across all spike trains); +* the mean spike count per bin (spike count in the bin divided by the number of spike trains); +* the firing rate (mean spike count in the bin divided by bin width)."""@en ; + "spike train time histogram analysis"@en . + + +### http://purl.org/neao/steps#SpikeWaveformAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "An analysis step that is used to compute measures to describe or make inferences from spike waveform input data. A spike waveform refers to the shape of an electrical signal produced by a neuron when it fires an action potential."@en ; + "spike waveform analysis"@en . + + +### http://purl.org/neao/steps#StatisticalAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A generic analysis step that computes measures to summarize and make inferences about the data input. These include measures of central tendency, dispersion and confidence intervals. The subclasses represent analysis steps that are usually used for aggregation of data and description of samples (e.g., compute the mean and standard deviation of the output of trial-by-trial analyses or across subjects). All analysis steps for specific applications related to the analysis of neuroelectrophysiology data itself (e.g., analyzing interspike interval variability) are covered by separate, independent classes."@en ; + "statistical analysis"@en . + + +### http://purl.org/neao/steps#TensorComponentAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + "TCA"@en ; + rdfs:comment "A dimensionality reduction that reduces the dimensionality of the input data represented as a tensor (i.e., an array with multiple dimensions). The tensor component analysis (TCA) transforms the data into a set of low-dimensional tensors that capture the maximum variance in the input (tensor components)."@en ; + "tensor principal component analysis"@en ; + "tensor component analysis"@en . + + +### http://purl.org/neao/steps#TimeDomainAnalysis + rdf:type owl:Class ; + owl:equivalentClass [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + rdfs:subClassOf ; + rdfs:comment "An analysis step that analyzes the input(s) with respect to time."@en ; + "time domain analysis"@en . + + +### http://purl.org/neao/steps#TimeFrequencyAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "A spectral analysis that computes measures describing the frequency content of the input(s) in a time-resolved manner. It allows the analysis of how different frequency components evolve over time, which is essential for non-stationary signals whose spectral characteristics change. The joint time-frequency representation helps in identifying transient features, frequency shifts, and other dynamic behaviors in the input(s)."@en ; + "time-frequency analysis"@en . + + +### http://purl.org/neao/steps#TimeScaleDependentSpikeTrainDistanceAnalysis + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "false"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + rdfs:comment "A spike train dissimilarity analysis that computes a spike train distance that depends on a parameter that determines a temporal scale in the spike trains to which the distance is sensitive. By computing the spike train distance for different time scale parameter values, it is possible to make inferences on the time scale that is discriminative in the neural activity."@en ; + "time-scale dependent spike train distance analysis"@en . + + +### http://purl.org/neao/steps#TimeScaleIndependentSpikeTrainDistanceAnalysis + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "false"^^xsd:boolean + ] , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "true"^^xsd:boolean + ] ; + rdfs:comment "A spike train dissimilarity analysis that computes a spike train distance that does not depend on a time scale parameter and that are time-scale adaptive. They can be used in scenarios where there are no previous knowledge of the relevant time scales in the input spike trains."@en ; + "time-scale independent spike train distance analysis"@en . + + +### http://purl.org/neao/steps#TriggeredAverageAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + rdfs:comment "An analysis step where a signal is averaged to obtain a value around a point in time representing an event of interest (i.e., a trigger). For each event time, a finite duration window of the input time series is selected around the event time. An average for each time point is then obtained across all windows."@en ; + "triggered average analysis"@en . + + +### http://purl.org/neao/steps#UnitaryEventAnalysis + rdf:type owl:Class ; + rdfs:subClassOf , + [ rdf:type owl:Restriction ; + owl:onProperty ; + owl:hasValue "false"^^xsd:boolean + ] ; + "UE analysis"@en ; + ; + rdfs:comment "A neuronal activity pattern detection analysis that uses the Unitary Event (UE) method. UE is a statistical technique focused on identifying synchronous activity among neurons, known as unitary events (UEs), which occur more frequently than an expectation based solely on firing rates. The input can contain spike trains from one or more neurons and one or more trials. For the computation, the input spike train data is discretized into small time intervals (bins), and coincidences across the different spike trains are computed. The significance of the number of observed (empirical) coincidences is determined by comparing to an expected number given the firing rates of the neurons. To account for possible non-stationarities in the firing rates, the method uses a sliding temporal window over the data, whose width is specified as parameter. Therefore, a measure of significant spike synchrony (joint surprise) is obtained for each window. The statistical evaluation can be done using either analytical methods or Monte-Carlo testing with surrogate spike data. The output presents the significant coincidences (UE patterns) and the participant neurons."@en ; + "Unitary Event analysis"@en . + + +### http://purl.org/neao/steps#WaveletTransformAnalysis + rdf:type owl:Class ; + rdfs:subClassOf ; + ; + rdfs:comment "A time-frequency analysis that uses wavelets to obtain the time-frequency representation of the time series input. The wavelet is a rapidly decaying oscillation. The wavelet transform breaks the signal into shifted and scaled versions of the wavelet (mother wavelet), and the output contains the information on both the frequencies present in the signal and the time. The wavelets provide good localization in time and frequency, making them suitable to analyze signals with transient features. Different types of wavelets exist, with distinct properties. They can be chosen to tailor the analysis to particular purposes. The output of the wavelet transform is often referred to as scaleogram."@en ; + "wavelet transform analysis"@en . + + +### http://purl.org/spar/biro/BibliographicReference + rdf:type owl:Class . + + +################################################################# +# Individuals +################################################################# + +### http://purl.org/neao/bibliography#Aertsen1987_1 + rdf:type owl:NamedIndividual , + ; + ; + "A. Aertsen, T. Bonhoeffer, & J. Krüger, \"Coherent activity in neuronal populations: analysis and interpretation,\" in E. R. Caianiello (ed) Physics of Cognitive Processes, pp. 1-34, World Scientific, 1987" ; + "Aertsen et al. (1987)"@en . + + +### http://purl.org/neao/bibliography#Baccala2001_463 + rdf:type owl:NamedIndividual , + ; + ; + "L. Baccalá & K. Sameshima, \"Partial directed coherence: a new concept in neural structure determination,\" Biol. Cyb., vol. 84, pp. 463-474, 2001" ; + "Baccalá & Sameshima (2001)"@en . + + +### http://purl.org/neao/bibliography#Bartlett1950_1 + rdf:type owl:NamedIndividual , + ; + ; + "M.S. Bartlett, \"Periodogram Analysis and Continuous Spectra,\" Biometrika, vol. 37, pp. 1-16, 1950" ; + "Bartlett (1950)"@en . + + +### http://purl.org/neao/bibliography#Bokil2010_146 + rdf:type owl:NamedIndividual , + ; + ; + "H. Bokil, P. Andrews, J. Kulkarni, S. Mehta, & P. Mitra, \"Chronux: a platform for analyzing neural signals,\" J. Neurosci. Meth., vol. 192, pp. 146-151, 2010" ; + "Bokil et al. (2010)"@en . + + +### http://purl.org/neao/bibliography#Brovelli2004_9849 + rdf:type owl:NamedIndividual , + ; + ; + "A. Brovelli, M. Ding, A. Ledberg, Y. Chen, R. Nakamura, & S. Bressler, \"Beta oscillations in a large-scale sensorimotor cortical network: directional influences revealed by granger causality,\" Proc. Natl. Acad. Sci. U.S.A., vol. 101, pp. 9849-9854, 2004" ; + "Brovelli et al. 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Thomas, \"Elements of Information Theory,\" John Wiley and Sons, 2012" ; + "Cover & Thomas (2012)"@en . + + +### http://purl.org/neao/bibliography#Cowley2017_242 + rdf:type owl:NamedIndividual , + ; + ; + "B. Cowley, J. Semedo, A. Zandvakili, M. Smith, A. Kohn, & B. Yu, \"Distance Covariance Analysis,\" in A. Singh & J. Zhu (eds) Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, Proceedings of Machine Learning Research, vol. 54, pp. 242-251, 2017" ; + "Cowley et al. (2017)"@en . + + +### http://purl.org/neao/bibliography#Cutts2014_14288 + rdf:type owl:NamedIndividual , + ; + ; + "C. S. Cutts & S. J. Eglen, \"Detecting pairwise correlations in spike trains: an objective comparison of methods and application to the study of retinal waves,\" J. Neurosci., vol. 34, no. 43, pp. 14288-14303, 2014" ; + "Cutts & Eglen (2014)"@en . + + +### http://purl.org/neao/bibliography#Deger2012_443 + rdf:type owl:NamedIndividual , + ; + ; + "M. Deger, M. 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Neurophysiol., no. 101, pp. 1126-1140, 2009" ; + "Grün (2009)"@en . + + +### http://purl.org/neao/bibliography#Hafner2008_215 + rdf:type owl:NamedIndividual , + ; + ; + "C. Hafner & H. Herwartz, \"Testing for causality in variance using multivariate GARCH models,\" Ann. Econ. Statist., vol. 89, pp. 215-241, 2008" ; + "Hafner & Herwartz (2008)"@en . + + +### http://purl.org/neao/bibliography#Hipp2012_884 + rdf:type owl:NamedIndividual , + ; + ; + "J. F. Hipp, D. J. Hawellek, M. Corbetta, M. Siegel, & A. K. Engel, \"Large-scale cortical correlation structure of spontaneous oscillatory activity,\" Nat. Neurosci., vol. 15, no. 6, pp. 884-890, 2012" ; + "Hipp et al. (2012)"@en . + + +### http://purl.org/neao/bibliography#Jutten1991_1 + rdf:type owl:NamedIndividual , + ; + ; + "C. Jutten & J. 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http://purl.org/neao/steps#SpikeFieldCouplingPurpose + rdf:type owl:NamedIndividual , + ; + rdfs:comment "The analysis purpose of assessing interactions between spiking activity and the local field potential."@en ; + "spike-LFP coupling purpose"@en ; + "spike-field coupling purpose"@en . + + +### http://purl.org/neao/steps#SpikeSpikeCouplingPurpose + rdf:type owl:NamedIndividual , + ; + rdfs:comment "The analysis purpose of assessing interactions between the spiking activity of neurons."@en ; + "spike-spike coupling purpose"@en . + + +### https://doi.org/10.1002/hbm.20346 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.1007/BF00198091 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.1007/BF02350994 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.1007/PL00007990 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.1007/b98858 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.1007/s00422-002-0386-2 + rdf:type owl:NamedIndividual . 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https://doi.org/10.1109/TAU.1967.1161901 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.1109/78.492555 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.1111/1467-9868.00196 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.1126/science.1055465 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.1126/science.1128115 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.1126/science.278.5345.1950 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.1137/0123044 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.1146/annurev.fl.24.010192.002143 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.1152/jn.00093.2008 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.1152/jn.00106.2010 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.1152/jn.00848.2014 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.1152/jn.00873.2012 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.1152/jn.1975.38.2.369 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.1152/jn.1996.76.2.1310 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.1152/jn.90941.2008 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.1162/NECO_a_00236 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.1162/089976601300014321 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.1162/089976602753284455 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.1162/089976602753284464 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.1162/089976603321043702 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.1162/089976603322518759 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.1214/14-AOAS782 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.1371/journal.pcbi.1000433 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.1371/journal.pcbi.1004939 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.1523/ENEURO.0505-21.2022 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.1523/JNEUROSCI.17-02-00722.1997 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.1523/JNEUROSCI.2767-14.2014 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.2307/27715168 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.3389/fncom.2010.00127 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.3389/fncom.2017.00041 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.48550/arXiv.q-bio/0608035 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.7554/eLife.10989 + rdf:type owl:NamedIndividual . + + +### https://doi.org/10.7554/eLife.19428 + rdf:type owl:NamedIndividual . + + +### https://isbndb.com/book/9780131139565 + rdf:type owl:NamedIndividual . + + +### https://isbndb.com/book/9781118585771 + rdf:type owl:NamedIndividual . + + +### https://isbndb.com/book/9789971502553#Aertsen_1 + rdf:type owl:NamedIndividual . + + +### https://proceedings.mlr.press/v54/cowley17a.html + rdf:type owl:NamedIndividual . + + +################################################################# +# Annotations +################################################################# + + rdfs:comment "An artifact removal step that aims to identify and remove input spike waveforms that differs significantly from other waveforms in the input. This include spike waveforms with too late peak or where the action potential does not rise towards the peak of other waveforms."@en . + + +################################################################# +# General axioms +################################################################# + +[ rdf:type owl:AllDisjointClasses ; + owl:members ( + + + ) +] . + + +[ rdf:type owl:AllDisjointClasses ; + owl:members ( + + + + + ) +] . + + +[ rdf:type owl:AllDisjointClasses ; + owl:members ( + + + ) +] . + + +[ rdf:type owl:AllDisjointClasses ; + owl:members ( + + + ) +] . + + +[ rdf:type owl:AllDisjointClasses ; + owl:members ( + + + + + + + + + + + + + + + + + + + + + + ) +] . + + +[ rdf:type owl:AllDisjointClasses ; + owl:members ( + + + + ) +] . + + +[ rdf:type owl:AllDisjointClasses ; + owl:members ( + + + + + + + + + + + + + + + ) +] . + + +[ rdf:type owl:AllDisjointClasses ; + owl:members ( + + + + + + ) +] . + + +[ rdf:type owl:AllDisjointClasses ; + owl:members ( + + + + + ) +] . + + +[ rdf:type owl:AllDisjointClasses ; + owl:members ( + + + ) +] . + + +[ rdf:type owl:AllDisjointClasses ; + owl:members ( + + + ) +] . + + +[ rdf:type owl:AllDisjointClasses ; + owl:members ( + + + + ) +] . + + +[ rdf:type owl:AllDisjointClasses ; + owl:members ( + + + + ) +] . + + +[ rdf:type owl:AllDisjointClasses ; + owl:members ( + + + + ) +] . + + +[ rdf:type owl:AllDisjointClasses ; + owl:members ( + + + ) +] . + + +[ rdf:type owl:AllDisjointClasses ; + owl:members ( + + + + ) +] . + + +[ rdf:type owl:AllDisjointClasses ; + owl:members ( + + + ) +] . + + +[ rdf:type owl:AllDisjointClasses ; + owl:members ( + + + + ) +] . + + +[ rdf:type owl:AllDisjointClasses ; + owl:members ( + + + + ) +] . + + +[ rdf:type owl:AllDisjointClasses ; + owl:members ( + + + ) +] . + + +[ rdf:type owl:AllDisjointClasses ; + owl:members ( + + + + + + + + + + ) +] . + + +[ rdf:type owl:AllDisjointClasses ; + owl:members ( + + + + + + ) +] . + + +### Generated by the OWL API (version 5.1.18) https://github.com/owlcs/owlapi/ diff --git a/doc/releases/0.1.0/neao.xml b/doc/releases/0.1.0/neao.xml new file mode 100644 index 0000000..8af085d --- /dev/null +++ b/doc/releases/0.1.0/neao.xml @@ -0,0 +1,9380 @@ + + + + + 2022-01-19 + Cristiano Köhler (ORCID: 0000-0003-0503-5264) + Michael Denker (ORCID: 0000-0003-1255-7300) + + neao + http://purl.org/neao/ + The Neuroelectrophysiology Analysis Ontology (NEAO) defines a controlled vocabulary and conceptual representations of the typical processes involved in the analysis of neural activity data acquired using electrophysiology techniques. + +Electrophysiology is a branch of physiology that studies the electrical properties of biological entities. The studies involve measurements of electric potentials and/or currents, as well as electrical manipulations (e.g. stimuli with electric pulses). Neuroelectrophysiology is the application of electrophysiology techniques to investigate the function of neural tissue. + +Neuroelectrophysiology recording is the process of data acquisition, and it usually involves placing electrodes (of several configurations and types) into a preparation of neural tissue. The data will contain a representation of the voltages or currents in the preparation during the recording session, usually as a time series. The analysis requires specific methods to progressively process and transform the recorded data, which generate results and insights. + +The scope of the NEAO aims to provide a comprehensive representation of neuroelectrophysiology data and analysis processes, standardizing the description of their properties and relationships. The NEAO does not provide a detailed representation of electrophysiology recording techniques, data acquisition methods/equipment, and experimental settings/subjects. The goal is to ensure a common representation of data analysis that can be used by tools to provide a detailed and semantically-enriched description of the processes involved. + Neuroelectrophysiology Analysis Ontology + 0.1.0 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + A string defining an abbreviation that is frequently used to refer to individuals represented by the class. + abbreviation + + + + + + + + + + Defines the bibliographic reference associated with the entity. The bibliographic reference should contain the details represented by the entity (e.g., method description, software publication). + has bibliographic reference + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Defines a data entity that is used to provide information for one analysis step. The analysis step will make use of this information and produce zero or more data entities as outputs. + has input + + + + + + + + + + + Defines a data entity that was produced by an analysis step. This can be newly data generated by the analysis step, or derived data, based on one or more data inputs. + has output + + + + + + + + + + + Defines the electrophysiology signal source associated with the data entity. One example of use is to define if the data holds a signal obtained by extracellular recordings, or a more specific description involving anatomical structures together with the recording technique. + has source + + + + + + + + + + + Points to an analysis step that is part of a (larger) compound analysis, represented by the subject with the property. + has substep + + + + + + + + + + + Defines the code source that implemented the analysis step. + is implemented in + + + + + + + + + + + Defines the software package that contains a particular code. + is implemented in package + + + + + + + + + + + Defines how the data entity is represented to be used by software (e.g., data array, list, file) + is represented as + + + + + + + + + + + Defines a parameter used by the analysis step. + uses parameter + + + + + + + + + + + Defines an analysis purpose for the analysis step. This property is used to group analysis steps according to their similarity. + has purpose + + + + + + + + + + + + + + + + + + + + + + + + + + Specifies the name of the function as it is defined in the code that implemented it. For example, for Python functions, this is what is specified in the 'def' statement (i.e., def function_name(arg), the value of this property is function_name). + name in definition + + + + + + + + + + + Version of the software package. + package version + + + + + + + + + + + Specifies the version of the package, as defined by the string used when it was released. + package version + + + + + + + + + + + Defines the name of the program. + program name + + + + + + + + + + + Version of the code for a specific program or function. This can be used to define a specific version for the code of a single function or program within a software package. + version + + + + + + + + + + + + Defines if the data is artificially-generated (true) or obtained from experimental recordings (false). + is artificial + + + + + + + + + + + + Defines if the data is the result of an aggregation to obtain an average estimate from other data (true). + is averaged + + + + + + + + + + + + Defines if a detrending transformation was applied to the data (true). + is detrended + + + + + + + + + + + + Defines if the data is a result of a dimensionality reduction transformation (true). + is dimensionality reduction + + + + + + + + + + + + Defines if a downsampling transformation was applied to the data (true). + is downsampled + + + + + + + + + + + + Defines if a digital filter was applied to the data (true). + is filtered + + + + + + + + + + + + Defines if a interpolation data transformation was applied to the data (true). + is interpolated + + + + + + + + + + + + Defines if a data normalization transformation was applied to the data (true). + is normalized + + + + + + + + + + + + Defines if a rectification transformation was applied to the data (true). + is rectified + + + + + + + + + + + + Defines if a transformation to change the reference in the recorded data was applied (true). + is rereferenced + + + + + + + + + + + + Defines if a resampling transformation was applied to the data (true). + is resampled + + + + + + + + + + + + Defines if a data smoothing transformation was applied to the data (true). + is smoothed + + + + + + + + + + + + Defines if an upsampling transformation was applied to the data (true). + is upsampled + + + + + + + + + + + + Defines if the analysis step uses two data inputs (true). + is bivariate + + + + + + + + + + + + Defines if the analysis step is used to perform an analysis providing information on the direction of the association between the inputs (true) opposed to no direction information (false). + is directed + + + + + + + + + + + + Defines if the analysis in the step is performed in the frequency domain (true). + is frequency domain + + + + + + + + + + + + Defines if the step performs a model-based (true) or model-free analysis (false). + is model-based + + + + + + + + + + + + Defines if the analysis step uses three or more data inputs (true). + is multivariate + + + + + + + + + + + + Defines if the analysis in the step is performed in the time domain (true). + is time domain + + + + + + + + + + + + + + + An information entity that controls the behavior of an analysis step. It does not provide data, but rather changes how the computations operate when transforming or generating new data. + parameter + + + + + + + + + A process that generates new data entities or performs specific operations (clean, select, transform, or inspect/visualize) using existing data entities. Ultimately, the goal is to obtain useful information from the data. An analysis step can take zero or more data inputs and can generate one or more data outputs. The behavior of the operation can optionally be controlled by one or more parameters. A complete analysis is composed by one or more analysis steps. + analysis step + + + + + + + + + An entity that represents a piece of data, i.e., relevant information, during the analysis. It can be recorded from a biological entity or from a simulation yielding comparable data, or it can be generated/transformed by other analysis step processes. + data + + + + + + + + + Defines the formal structure to represent a piece of data. + data representation + + + + + + + + + Defines the source of a recorded piece of electrophysiology data, i.e., the recorded signals. This is a general concept, that can be expanded to incorporate the anatomical/tissue description from where the signal was recorded, as well as the recording technique. + +For example, voltage potentials can be acquired from extracellular electrodes situtated on the scalp (electroencephalogram), directly on the cortical surface (electrocorticogram) or implanted deep into a specific brain region (multielectrode array). + electrophysiology signal source + + + + + + + + + + A reusable set of instructions that can be used when writing computer programs. A function performs specific tasks, and can be implemented as part of a single computer program or in a software package (library) so that it can be reused across several programs. + function + + + + + + + + + + A set of instructions that is executed by a computer. The instructions of the program can be executed by an interpreter or compiled to machine code. The program instructs the computer to perform tasks and it is called by the operating system. + program + + + + + + + + + + Describes the details for the execution of the analysis step using a computer. The software contains a sequence or set of instructions that is used by the computer to perform all the computations required to execute the analysis step. + software implementation + + + + + + + + + A collection of one or more programs that can be executed by a computer and/or one or more functions that can be imported and used when writing programs. + software package + + + + + + + + + + Data that contains a matrix computed by one of the ASSET analysis substeps, as part of the execution of the ASSET analysis for the detection of neuronal activity patterns. + ASSET analysis matrix + + + + + + + + + + CMAT + The cluster matrix (CMAT) computed in the ASSET analysis. + ASSET cluster matrix + + + + + + + + + + IMAT + The intersection matrix (IMAT) computed in the ASSET analysis. + ASSET intersection matrix + + + + + + + + + + JMAT + The joint probability matrix (JMAT) computed in the ASSET analysis. + ASSET joint probability matrix + + + + + + + + + + MMAT + The mask matrix (MMAT) computed in the ASSET analysis. + ASSET mask matrix + + + + + + + + + + A neuronal activity pattern obtained by the ASSET analysis. The ASSET patterns are the output of the last substep of the ASSET analysis that identifies the neurons present in each repeated sequence, based on the diagonal structures in the cluster matrix. + ASSET pattern + + + + + + + + + + PMAT + The probability matrix (PMAT) computed in the ASSET analysis. + ASSET probability matrix + + + + + + + + + + The analytic signal obtained from a time series using the Hilbert transform. + analytic signal + + + + + + + + + + The computed angular mean of the spike phases. + angular mean of spike phases + + + + + + + + + + + + true + + + + Data that is generated programmatically rather than obtained from experimental recordings. + artificial data + + + + + + + + + + ACF + The computed estimator of the autocorrelation function. + autocorrelation function + + + + + + + + + + Data that contains a measure of autocorrelation. + autocorrelation measure + + + + + + + + + + The output of applying binning to the input spike train data. + binned spike train + + + + + + + + + + CV + The computed coefficient of variation (CV). + coefficient of variation + + + + + + + + + + The computed CV2 measure. + CV2 + + + + + + + + + + CV ISIs + The computed coefficient of variation (CV) of the interspike intervals (ISIs). + coefficient of variation of the interspike intervals + + + + + + + + + + caCOH + The computed canonical coherence (caCOH). + canonical coherence + + + + + + + + + + CAD pattern + A neuronal activity pattern obtained by the Cell Assembly Detection (CAD) analysis. + Cell Assembly Detection pattern + + + + + + + + + + A change point identified by the rate change detection multiple filter test. + change point + + + + + + + + + + The computed magnitude squared coherence. This is the typical output of a computation estimating coherence, and it is frequently referred as just coherence. + magnitude squared coherence + coherence + + + + + + + + + + Data that contains a measure of coherence. + coherence measure + + + + + + + + + + The computed coherency. + complex coherency + coherency + + + + + + + + + + Data that contains a measure of coherency. + coherency measure + + + + + + + + + + The computed complexity distribution across the spike trains. + complexity distribution + + + + + + + + + + The computed conditional Granger causality. + conditional Granger causality + + + + + + + + + + CI + The computed confidence interval (CI), with the lower and upper limits. + confidence interval + + + + + + + + + + The lower limit value of the computed confidence interval. + lower limit of confidence interval + + + + + + + + + + Data that contains the description of a confidence interval (CI). + CI measure + confidence interval measure + + + + + + + + + + The upper limit value of the computed confidence interval. + upper limit of confidence interval + + + + + + + + + + ciPLV + The computed corrected imaginary phase locking value (ciPLV). + corrected imaginary phase locking value + + + + + + + + + + Data that contains a measure of correlation. + correlation measure + + + + + + + + + + The computed covariance values between the inputs. + covariance + + + + + + + + + + Data that contains a measure of covariance. + covariance measure + + + + + + + + + + CCF + The computed estimator of the cross-correlation function. + cross-correlation function + + + + + + + + + + Data that contains a measure of cross-correlation. + cross-correlation measure + + + + + + + + + + CPSD + The computed cross power spectral density (CPSD). + cross-spectrum + cross power spectral density + + + + + + + + + + The computed cross-spectrogram. + cross-spectrogram + + + + + + + + + + The result of the CuBIC analysis. + CuBIC analysis result + + + + + + + + + + CSD + The profile of current densities estimated by a current source density analysis. + current source density + + + + + + + + + + debiased squared WPLI + The computed debiased squared weighted phase lag index (WPLI). + debiased squared weighted phase lag index + + + + + + + + + + + + true + + + + Data that contains an output of applying a dimensionality reduction transformation to the input data. + dimensionality reduction output + + + + + + + + + + DPLI + The computed directed phase lag index (DPLI). + directed phase lag index + + + + + + + + + + DTF + The computed directed transfer function (DTF). + directed transfer function + + + + + + + + + + The computed directional Granger causality from one input to the other. + directional Granger causality + + + + + + + + + + DFT + The complex sinusoid coefficients obtained by applying the Discrete Fourier Transform (DFT) to the input data (e.g., using the FFT algorithm). + discrete Fourier transform + + + + + + + + + + A dimension identified by applying distance covariance analysis (DCA) to the input data. + distance covariance dimension + + + + + + + + + + Data that represents a finite time interval (window). For example, the interval between the start and end of a behavioral trial in the recording session. + epoch + + + + + + + + + + + + + Data that contains the time(s) when an event of interest occurred (e.g., a certain behavior or stimulus in an experimental trial). + event + + + + + + + + + + ERP + The computed event-related potential (ERP). + event-related potential + + + + + + + + + + The computed event-triggered average. + event-triggered average + + + + + + + + + + EP + The computed evoked potential (EP). + evoked potential + + + + + + + + + + The computed firing rate. + firing rate + + + + + + + + + + A Fisher linear discriminant obtained by applying linear discrimination analysis (LDA) to the input data. + Fisher linear discriminant + + + + + + + + + + Data that contains a measure of Granger causality. + Granger causality measure + + + + + + + + + + The computed total interdependence in the Granger causality analysis. + Granger total interdependence + + + + + + + + + + The computed ISI-distance. + ISI-distance + + + + + + + + + + The computed imaginary part of the coherency. + imaginary coherency + + + + + + + + + + Data that contains an independent component produced by applying independent component analysis (ICA) to the input data. + independent component + + + + + + + + + + The computed instantaneous firing rate. + instantaneous firing rate + + + + + + + + + + The computed instantaneous Granger causality. + instantaneous Granger causality + + + + + + + + + + IQR + The computed interquartile range, with the difference between the 75th and 25th percentile values. + interquartile range + + + + + + + + + + The lower limit of the computed interquartile range, corresponding to the 25th percentile. + lower limit of interquartile range + + + + + + + + + + IQR measure + Data that contains the description of an interquartile range (IQR). + interquartile range measure + + + + + + + + + + The upper limit of the computed interquartile range, corresponding to the 75th percentile. + upper limit of interquartile range + + + + + + + + + + ISIH + The computed interspike interval histogram (ISIH). + interspike interval histogram + + + + + + + + + + Data that contains a measure describing the variability of the interspike intervals. + interspike interval variability measure + + + + + + + + + + ISIs + The computed interspike intervals (ISIs). + interspike intervals + + + + + + + + + + JPSTH matrix + The computed joint peristimulus time histogram (JPSTH) matrix. + joint peristimulus time histogram matrix + + + + + + + + + + The computed local variation (LV) measure. + LV + + + + + + + + + + The computed revised local variation (LvR) measure. + LvR + + + + + + + + + + The computed magnitude coherence. + magnitude coherence + + + + + + + + + + MIC + The computed maximized imaginary coherency (MIC). + maximized imaginary coherency + + + + + + + + + + The computed mean. + mean + + + + + + + + + + MFR + The computed mean firing rate. + mean firing rate + + + + + + + + + + The computed mean phase vector (i.e., the angle and length). + mean phase vector + + + + + + + + + + The angle of the computed mean phase vector. + mean phase vector angle + + + + + + + + + + The length of the computed mean phase vector. + mean phase vector length + + + + + + + + + + Data that contains the description or elements of the mean phase vector. + mean phase vector measure + + + + + + + + + + MVL + The computed mean vector length (MVL). + mean vector length + + + + + + + + + + The computed median. + median + + + + + + + + + + MI + The computed modulation index (MI). + modulation index + + + + + + + + + + Data that contains the generated Morlet wavelet values for a sequence of time points. + Morlet wavelet + + + + + + + + + + MIM + The computed multivariate interaction measure (MIM). + multivariate interaction measure + + + + + + + + + + MI + The computed mutual information (MI). + mutual information + + + + + + + + + + + + + true + + + A neural trajectory obtained by applying Gaussian process factor analysis (GPFA) to the input data containing multitrial spiking activity of a neuronal population. + neural trajectory + + + + + + + + + + Data that contains the description of a neuronal activity pattern, which is obtained from a neuronal activity pattern detection analysis. + cell assembly + neuronal assembly + neuronal activity pattern + + + + + + + + + + The computed neuronal population vector. + population vector + neuronal population vector + + + + + + + + + + NC + The computed noise correlations (NC). + noise correlations + + + + + + + + + + The computed noise covariance. + noise covariance + + + + + + + + + + The computed orthogonalized power envelope correlation. + orthogonalized power envelope correlation + + + + + + + + + + PPC + The computed pairwise phase consistency (PPC) measure. + pairwise phase consistency + + + + + + + + + + The computed partial coherence. + partial coherence + + + + + + + + + + PDC + The computed partial directed coherence (PDC). + partial directed coherence + + + + + + + + + + The computed peristimulus coincidence histogram. + peristimulus coincidence histogram + + + + + + + + + + PSTH + The computed peristimulus time histogram (PSTH). The stimulus or event of interest can occur at any time point within the interval analyzed. However, if the histogram represents the neuronal activity after the stimulus presentation or event occurrence, this can be referred as post-stimulus time histogram. Conversely, if the histogram shows the activity of the neuron before the stimulus presentation or event, this can be referred as prestimulus time histogram. Finally, if the histogram considers a behavioral event (or an event that is not an externally presented stimulus), the histogram can be referred to as perievent time histogram (PETH). + perievent time histogram + post-stimulus time histogram + prestimulus time histogram + peristimulus time histogram + + + + + + + + + + PAC measure + Data that contains a measure of phase-amplitude coupling (PAC). + phase amplitude coupling measure + + + + + + + + + + A measure of phase defining the angle on the unit circle that corresponds to the current position within the waveform's cycle. The range of angles in a full cycle is from 0 to 2*pi radians or 0 to 360 degrees. + phase angles + + + + + + + + + + PLI + The computed phase lag index (PLI). + phase lag index + + + + + + + + + + PLI measure + Data that contains a measure computed by a phase-lag index analysis. + phase lag index measure + + + + + + + + + + PLV + The computed phase locking value (PLV). + phase locking value + + + + + + + + + + PLV measure + Data that contains a phase locking value (PLV) measure. + phase locking value measure + + + + + + + + + + PSI + The computed phase slope index (PSI). + phase slope index + + + + + + + + + + A graphical representation of data values. It is used to visually communicate quantitative information, providing intuitive insights that can complement numerical analysis. It is often produced by later steps in the analysis after the computation of measures, to provide the visual representation of the results. + plot + + + + + + + + + + The computed population histogram. + population histogram + + + + + + + + + + PSD + The computed power spectral density (PSD). + spectrum + power spectral density + + + + + + + + + + A principal component obtained by applying principal component analysis (PCA) to the input data. + principal component + + + + + + + + + + RAUC + The computed rectified area under the curve (RAUC). + rectified area under the curve + + + + + + + + + + The covariance values computed with regularization techniques for numerical stability. + regularized covariance + + + + + + + + + + A neuronal activity pattern obtained by the Spatio-temporal PAttern Detection and Evaluation (SPADE) analysis. + SPADE pattern + + + + + + + + + + The computed SPIKE distance. + SPIKE distance + + + + + + + + + + The computed SPIKE synchronization distance. + SPIKE synchronization + + + + + + + + + + STFT + The complex sinusoid coefficients obtained by applying the short-time Fourier transform (STFT) to the input data. + short-time Fourier transform + + + + + + + + + + Data that contains the density of a measure of the input(s) over the frequency spectrum. + spectral density + + + + + + + + + + The computed spectrogram. + spectrogram + + + + + + + + + + The computed Spike-contrast. + Spike-contrast + + + + + + + + + + SFC + The computed spike-field coherence (SFC). + spike-field coherence + + + + + + + + + + STTC + The computed spike time tiling coefficient (STTC). + spike time tiling coefficient + + + + + + + + + + + + Data that contains the sequence of time points when an action potential (spike) occurs. A spike train can be obtained by electrophysiological recordings from the neural tissue (i.e., the data contains the times when spikes occur naturally in response to various stimuli or during spontaneous activity) or artificially-generated using specific statistical procedures or simulations of neuronal activity. + spike train + + + + + + + + + + The computed spike train autocorrelation histogram. + spike train autocorrelation histogram + + + + + + + + + + The computed spike train autocorrelation time scale. + spike train autocorrelation time scale + + + + + + + + + + Data that contains a measure estimating the correlation between spike trains. + correlation measure + + + + + + + + + + CCH + The computed spike train cross-correlation histogram. + correlogram + cross-correlogram + spike train cross-correlation histogram + + + + + + + + + + Data that contains a spike train distance measure. + spike train distance + + + + + + + + + + FF + The computed Fano factor (FF) for a set of input spike trains. + spike train Fano factor + + + + + + + + + + The computed Pearson correlation coefficient between two spike trains. + spike train Pearson correlation coefficient + + + + + + + + + + + Data that contains a spike train surrogate. It is generated from spike train inputs using distinct methods to alter the original spike times. + spike train surrogate + + + + + + + + + + Data that contains a measure describing synchronization in two or more spike trains containing the activity of different neurons. + spike train synchrony measure + + + + + + + + + + The computed spike train time histogram. + spike train time histogram + + + + + + + + + + STA + The computed spike-triggered average (STA). + spike-triggered average + + + + + + + + + + The computed spike-triggered average of the local field potential (LFP) signal. + spike-triggered local field potential average + + + + + + + + + + The computed spike-triggered phase angles. + spike-triggered phase + + + + + + + + + + Data that contains the characteristic voltage change over time observed in the electrical recording of a neuron's action potential (spike). This waveform represents the rapid depolarization and repolarization of the neuron's membrane potential during the action potential. The data is acquired in a finite number of samples that correspond to a time window around the spike time (i.e., with periods before and after the action potential onset). + spike waveform + + + + + + + + + + The computed average across the spike waveforms. + spike waveform average + + + + + + + + + + spike waveform SNR + The computed signal-to-noise ratio of the spike waveforms. + spike waveform signal-to-noise ratio + + + + + + + + + + The computed variance across the spike waveforms. + spike waveform variance + + + + + + + + + + The computed spike waveform width. + spike waveform width + + + + + + + + + + Data that contains measures used to describe specific characteristics or make inferences from spike waveforms. + spike waveform statistic + + + + + + + + + + SD + The computed standard deviation (SD). + standard deviation + + + + + + + + + + SEM + The computed standard error of the mean (SEM). + standard error of the mean + + + + + + + + + + The result of computing the Stockwell transform (S transform). + S transform + Stockwell transform + + + + + + + + + + A tensor component obtained by applying tensor component analysis (TCA) to the input data. + tensor component + + + + + + + + + + Data that contains a time histogram, i.e., a histogram that shows the distribution of a measure across specified time intervals (bins). + time histogram + + + + + + + + + + Data that contains values of a specific quantity (e.g., voltage) acquired as a series of successive samples over time. Typically, there is a fixed interval between the samples (sampling period), with each sample representing a distinct time point in the series. + time series + + + + + + + + + + TE + The computed transfer entropy (TE). + transfer entropy + + + + + + + + + + Data that contains the output of a triggered average analysis. + triggered average measure + + + + + + + + + + The computed tuning curve. + tuning curve + + + + + + + + + + unbiased squared PLI + The computed unbiased squared phase lag index (PLI). + unbiased squared phase lag index + + + + + + + + + + UE pattern + A neuronal activity pattern obtained by the Unitary Event (UE) analysis. + Unitary Event pattern + + + + + + + + + + The computed van Rossum distance. + van Rossum distance + + + + + + + + + + The computed variance. + variance + + + + + + + + + + The computed Victor-Purpura distance. + Victor-Purpura distance + + + + + + + + + + Data that contains the result of a wavelet transform analysis, i.e., decomposing a time series using a mother wavelet function. + scaleogram + wavelet transform + + + + + + + + + + WPLI + The computed weighted phase lag index (WPLI). + weighted phase lag index + + + + + + + + + + A parameter used by the Analysis of Sequences of Synchronous Events (ASSET) method, used to identify neuronal activity patterns in spike data. + ASSET analysis parameter + + + + + + + + + + When computing the elliptical distance measure used by the DBSCAN algorithm to cluster the mask matrix entries to find the diagonal structures, the parameter value is used to stretch angular coefficients deviating from 45 degrees. This reflects into the shape of the neighborhood around a point in the DBSCAN procedure. A large stretch factor will produce neighborhoods that are narrower and closer to a line in the 45 degree direction. Smaller stretch factors will produce neighborhoods that are more elliptical, with the major axis in the 45 degree direction, and the minor axis in the 135 degree direction. Therefore, the smaller stretch factor increases the minor axis of this ellipsis. Together with the DBSCAN neighborhood radius parameter, this should be used to tweak the neighborhood ellipsis such that it is contained in the rectangular kernel used to filter the probability matrix entries when computing the joint probability matrix. + distance stretch factor in ASSET clustering + + + + + + + + + + A tuple of integers that determines the width and length of a rectangular kernel used to cover a diagonal structure in the intersection matrix. The kernel is centered in a point in the probability matrix, and defines a neighborhood around that point. Inside the kernel, a chosen number of largest neighbors in the probability matrix is used to compute the joint probability value for the center point. The kernel is rotated in 45 degree angle. + kernel shape in ASSET joint probability matrix + filter shape in ASSET joint probability matrix + + + + + + + + + + Defines the number of elements inside the filter kernel that are used to compute the joint probability value for a matrix entry. The probability matrix values inside the kernel for that entry are ordered from the largest to the lowest value, and the first N elements corresponding to the parameter value are taken. + number of largest neighbors in ASSET joint probability matrix + + + + + + + + + + Real values (range 0-1) used as thresholds to determine if the entries in the probability matrix and joint probability matrices are significant. Entry significance is defined as a probability value greater than the threshold values specified by the parameter. Significant entries in both probability and joint probability matrices are defined as 1 in the mask matrix. + significance thresholds in ASSET mask matrix + + + + + + + + + + The kernel function has a triangular shape with end points at zero. + Bartlett smoothing kernel + + + + + + + + + + When discretizing continuous data into smaller intervals (bins), the parameter value determines the width of the intervals (in the unit of the data being discretized). Bins are adjacent and can be of different sizes. + bin width + bin size + + + + + + + + + + Window function that uses the first three terms of a summation of cosines, minimizing spectral leakage. It was proposed by Ralph Beebe Blackman. The coefficients are an approximation of the ones used in the exact Blackman window function. Therefore, this window does not remove the third and fourth side lobes but produces smoother edges. + Blackman window function + + + + + + + + + + + The kernel function is zero over the entire interval except for a single (smaller) interval where it has a constant value. This non-zero interval is the total width of the kernel. + Boxcar smoothing kernel + + + + + + + + + + + Integer value that determines the minimum number of points that must be present in the neighborhood of a sample point such that it is considered a core point. The parameter value includes the sample point being evaluated. + DBSCAN minimum samples + DBSCAN minimum number of neighbors + + + + + + + + + + Determines the radius around a sample point used to define its neighborhood. The parameter defines the maximum distance between two sample points such that they are considered to be in the same neighborhood. + DBSCAN epsilon + DBSCAN maximum distance + DBSCAN neighborhood radius + + + + + + + + + + A parameter used by the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) data clustering method. + DBSCAN parameter + + + + + + + + + + DPSS window function + A set of orthogonal sequences optimized to simultaneously achieve maximum concentration of energy within a defined frequency band and minimum leakage into neighboring frequency bands. They are frequently used as tapers in multiple applications (e.g., multitaper power spectral density estimation). The first sequence (order 0 or Slepian sequence) has maximal energy concentration in the main lobe. + Slepian sequences window function + discrete prolate spheroidal sequences window function + + + + + + + + + + A time interval that defines a dithering distribution used to draw random numbers to displace individual spike times in a spike train. + dithering time + + + + + + + + + + A real value that indicates the factor by which the sampling period of a sampled time series is reduced in a downsampling operation. + decimation factor + downsample factor + + + + + + + + + + Window function that uses the first three terms of a summation of cosines. It was proposed by Ralph Beebe Blackman. The coefficients are selected to remove the third and fourth side lobes, but the edges are discontinuous. + exact Blackman window + + + + + + + + + + The kernel function is zero for points before the kernel center point, maximum at the center point, and decay exponentially for points greater than the center point. This kernel is asymmetric. + exponential smoothing kernel + + + + + + + + + + Integer value specifying the rate at which the filter response in the transition band falls. A higher filter order corresponds to a faster filter response decay. + filter order + + + + + + + + + + The parameter value determines the average number of spikes fired by a neuron per time unit. It is used to control the behavior of steps that require a firing rate to control the output (e.g., a target mean firing rate when generating an artificial spike train). + firing rate + + + + + + + + + + In analyses producing estimates in the frequency domain, the parameter determines the width of the frequency bins in the output, i.e., the resolution of the output on the frequency axis. + frequency resolution + + + + + + + + + + The kernel function corresponds to a raised cosine (i.e., a single period of a cosine function "raised") with positive endpoints. + Hamming smoothing kernel + + + + + + + + + + A window function that corresponds to a raised cosine (i.e., a single period of a cosine function "raised") but with positive endpoints. Therefore, the function does not eliminate the discontinuities in the signal. It has better cancellation of the nearest side lobe, and a poorer cancellation of the others, with a wide main lobe. It is named after Richard Wesley Hamming. + Hamming window function + + + + + + + + + + The kernel function corresponds to a raised cosine (i.e., a single period of a cosine function "raised" such that the negative troughs are zero). The endpoints reach zero smoothly at the boundaries. + Hann smoothing kernel + + + + + + + + + + A window function that corresponds to a raised cosine (i.e., a single period of a cosine function "raised" such that the negative troughs are zero). Therefore, the function reaches zero smoothly at the boundaries and eliminates all discontinuities in the signal. It has a wide main lobe and low side lobes. It is named after Julius von Hann. + raised-cosine window function + von Hann window function + hanning window function + Hann window function + + + + + + + + + + When applying a filter to a time series, the frequency components below this parameter value will be attenuated. Usually, the parameter value corresponds to the frequency component attenuated by 3 dB in the filter transition band. + high-pass frequency cutoff + + + + + + + + + + This window function approximates the DPSS window function using Bessel functions. It is easier to compute than the DPSS window function. It was developed by James Kaiser. + Kaiser-Bessel window function + Kaiser window function + + + + + + + + + + The total width of a smoothing kernel. + kernel width + + + + + + + + + + When applying a filter to a time series, the frequency components above this parameter value will be attenuated. Usually, the parameter value corresponds to the frequency component attenuated by 3 dB in the filter transition band. + low-pass frequency cutoff + + + + + + + + + + Length of the time series considered by application of a fast Fourier transform (FFT). The value determines the frequency bin size based on the sampling frequency of the input data, and the length of the vector representing the result of the discrete Fourier transform. + FFT points + number of FFT samples + + + + + + + + + + The parameter defines the separation of individual peaks in the output. + peak resolution + + + + + + + + + + The parameter determines the number of samples per time unit in sampled data. It is the inverse of the sampling period, i.e., the interval between two consecutive samples. + sampling rate + sampling frequency + + + + + + + + + + When determining a probability distribution, the parameter affects the shape of the distribution. This is in contrast to other parameters that affect the location (e.g., mean) or scale (e.g., variance) of the distribution. + shape factor + + + + + + + + + + A smoothing kernel can be used in non-parametric smoothing techniques such as kernel smoothing or kernel density estimation. It represents a weighting function that assigns weights to neighboring data points based on their distance from a given point (the kernel center). Closer points are given higher weights. The weighted average of the data points within the kernel is computed to produce a smoothed estimate of the underlying data (e.g., a signal or probability density function). Smoothing kernels are characterized by their shape (e.g., Boxcar, exponential) and bandwidth. The bandwidth determines the extent of influence of neighboring data points on the smoothed estimate. + smoothing kernel + + + + + + + + + + The parameter determines the smallest time interval that can be detected or produced by the method. In sampled time series data, this equals to the sampling period, i.e, the time interval between two consecutive samples. + temporal resolution + + + + + + + + + + The value of the center frequency of a wavelet. This is the frequency at which the wavelet oscillates most strongly, and it influences how effectively the wavelet can capture features of a signal at different frequencies. Wavelets with higher center frequencies are better suited for analyzing high-frequency components of a signal, while those with lower center frequencies are more effective for capturing low-frequency components. + wavelet center frequency + + + + + + + + + + A mathematical function that is zero-valued outside a defined interval. When multiplied by another function or sampled data, the values outside the window interval will be transformed to zero, and the values inside the window will be weighted by the window function values. + +Window functions are used to select and modify a finite segment of a signal. This is useful for applying the fast Fourier transform (FFT) to a finite set of data where the length is not an integer number of periods of the signal. In this situation, there will be discontinuities at the boundaries of the signal, and the data in the frequency domain produced by the FFT will have frequency components not present in the original signal (spectral leakage). The window function can be used to reduce this discontinuities and mitigate spectral leakage when performing spectral analysis. + +Several types of window function exist. They will vary in shape in the time domain and will have distinct frequency characteristics in the frequency domain, with a main lobe and several side lobes. The main lobe is centered at each frequency component in the time domain, and the side lobes approach zero. These characteristics can be used to control the effect of spectral leakage when performing the analysis. + apodization function + tapering function + window function + + + + + + + + + + Integer value that defines the number of samples encompassed by a window in sampled data, i.e., the window length. The window corresponds to a finite interval in the sampled data (e.g., a time interval in sampled time series data). + window length in samples + + + + + + + + + + Real value (range 0-1) that determines the proportion of overlap between two adjacent windows. The window is a finite interval in the data (e.g., a time interval in time series data). + window overlap factor + + + + + + + + + + Integer value (range 0 to the window length in samples) that determines the number of samples where two adjacent windows overlap. The window corresponds to a finite interval in sampled data (e.g., a time interval in sampled time series data). + window overlap in samples + + + + + + + + + + + ASSET analysis substep that computes the probability matrix (PMAT). The probability matrix contains, for each entry in the intersection matrix, the cumulative probability representing the probability of having the overlap in the IMAT under the assumption that the spike trains are independent. If an entry in the PMAT is large, the null hypothesis of independence is rejected, and the alternative hypothesis that the observed overlap reflects active synchronization between the involved neurons at the time bins of the intersection is accepted. The PMAT computation can be done with either an analytical or Monte Carlo approach. + ASSET analysis probability matrix substep + + + + + + + + + + + An analysis step that is an individual part of the ASSET analysis method to identify neuronal activity patterns in spike train data. + ASSET analysis substep + + + + + + + + + Analysis purpose refers to the specific objective or goal that an analysis is intended to achieve. It outlines what the analysis step aims to discover, understand, or demonstrate. This class is intended for grouping steps that perform analyses with similar goals/outputs but with distinct methodological or algorithmic approaches. It is used as a normalization class via the hasPurpose object property. + analysis purpose + + + + + + + + + + A kernel smoothing that uses a variable-width kernel. The kernel width varies adaptively depending on the local density of the data. This method takes into consideration local variations in data density, resulting in a more accurate representation of the underlying patterns and structures. + apply adaptive kernel smoothing + + + + + + + + + + A data transformation that uses the Hilbert transform of a real-valued input time series to construct the analytic signal, a complex-valued time series where the real part is the original real-valued signal and the imaginary part is the Hilbert transform. The analytic signal does not have negative frequency components. + apply analytic signal conversion + + + + + + + + + + An infinite impulse response filtering that uses a Butterworth type filter, i.e., a filter designed to have a maximally flat frequency response in the passband (no ripples). The frequency response gradually decreases to zero in the stopband, and the steepness of the decrease (roll-off) is controlled by the order of the filter. + apply maximally flat magnitude filter + apply Butterworth filter + + + + + + + + + + apply CPD + + A tensor component analysis (TCA) that expresses the input high-dimensional tensor as a sum of rank-one tensors (tensor components). Each dimension in the tensor component corresponds to a dimension in the input high-dimensional tensor. For neural data, a tensor could be used to represent trial-by-trial spiking activity, with neurons, time, and trials as dimensions. Therefore, each tensor component produced from that input will have a rank-one tensor for the neurons, time, and trial, which describes both within- and between-trial changes. + apply tensor rank decomposition + apply canonical polyadic tensor decomposition + + + + + + + + + + apply CCPD + + A tensor component analysis (TCA) that expresses multiple high-dimensional input tensors as a sum of rank one tensors (tensor components). The output tensor components have shared vectors that summarize an input dimension across all input tensors. For example, if analyzing two tensors, each representing trial-by-trial spiking activity obtained from a distinct experimental subject (neurons X time X trials), the coupled canonical polyadic tensor decomposition (CCPD) could produce tensor components for each dataset where the vector for the trial and time dimensions are the same, but the neuron dimension is unique for each dataset (hence, each subject). Therefore, CCPD is useful for scenarios with multiple and related datasets, allowing for the exploitation of shared information to enhance the decomposition results. + apply coupled canonical polyadic tensor decomposition + + + + + + + + + + apply DFT noise removal + A line noise removal that uses a discrete Fourier transform (DFT) filter and estimates the power line component amplitude in the input data by fitting a sine and cosine at a user-specified line noise frequency (e.g., 50 Hz), followed by the subtraction of those components from the input. + apply discrete Fourier transform noise removal + + + + + + + + + + A data transformation that joins two or more data inputs into a single data element. For example, in a multitrial experimental session, where data was acquired separately as one epoch per trial, a continuous data segment for the session can be constructed by concatenating all trial epochs together. + apply data concatenation + + + + + + + + + + apply dPCA + + A principal component analysis (PCA) that uses a modified version of the standard PCA for neural activity data analysis. Demixed PCA (dPCA) not only obtains a low-dimensional representation of the input data, but it also demixes the dependencies of the population activity on the task parameters. Therefore, dPCA can show the dependence of the neural representation on parameters such as stimuli, subject decisions, or rewards. + apply demixed principal component analysis + + + + + + + + + + A frequency-domain transformation that applies the discrete Fourier transform (DFT) to an input time series acquired in equally-spaced samples. The DFT is used to obtain the frequency representation of the time-domain input. The DFT output is a sequence of coefficients of complex sinusoids, each representing a frequency component in the input signal. Each frequency component consists of an interval (or bin), and the width of the bin determines the frequency resolution of the DFT. The number of frequency components and the frequency resolution is determined by the length of the input signal (number of samples) and the sampling frequency. For large datasets, the computation is computationally expensive (O(N^2) complexity). + apply DFT + apply discrete Fourier transform + + + + + + + + + + apply DCA + + A dimensionality reduction that identifies linear and nonlinear relationships between multiple input datasets. The method identifies linear projections (DCA dimensions) that maximize the distance covariance statistic (an Euclidean-based correlational statistic). For example, for recordings from different brain regions (two neuronal populations), the distance covariance analysis (DCA) can identify the dimensions in the population activity in the different brain areas that are related to each other. The dimensionality reduction can also take other dependent variables into account (e.g., stimulus or behavioral variables). + apply distance covariance analysis + + + + + + + + + + + A resampling that reduces the number of samples in the input data (i.e., reduces the sampling frequency). This is often accomplished after applying an anti-aliasing filter (i.e., to remove frequencies above half the value of the new sampling frequency). + apply decimation + apply downscaling + apply downsampling + + + + + + + + + + A frequency-domain transformation that uses the fast Fourier transform (FFT) algorithm to compute the discrete Fourier transform (DFT). The computation of the DFT is computationally expensive for large datasets. The FFT reduces the number of computations significantly by using a divide-and-conquer approach, leveraging the symmetry and periodicity properties of the DFT. The complexity is O(N log N). The output of the method is similar to the DFT, i.e., a sequence of coefficients of complex sinusoids, each representing a frequency component in the input signal. The FFT takes a size parameter, that refers to the number of points in the input data sequence that is used for the computation. The FFT size determines the frequency resolution, and, for maximal efficiency, should be a multiple of 2. + apply FFT + apply fast Fourier transform + + + + + + + + + + apply FIR filter + A finite impulse response (FIR) filtering where a custom-designed FIR filter is applied to the input data. + apply finite impulse response filter + + + + + + + + + + apply FIR filter with Kaiser window + A finite impulse response (FIR) filtering that uses a FIR filter whose impulse response is controlled by applying a Kaiser window function. + apply finite impulse response filter with Kaiser window + + + + + + + + + + A kernel smoothing that uses a fixed-width kernel. The kernel type and kernel width can be specified as parameters. + apply fixed kernel smoothing + + + + + + + + + + A detrending that uses a general linear model to fit a polynomial from the input data and remove the mean and linear trend. + apply general linear model polynomial detrending + + + + + + + + + + A data transformation that applies the Hilbert transform to a real-valued time series. The Hilbert transform shifts the phase of each frequency component of the signal by 90 degrees: positive frequencies are shifted by -90 degrees, and negative frequencies are shifted by +90 degrees. This can be used to construct the analytic signal. + apply Hilbert transform + + + + + + + + + + apply ICA + + A data transformation that separates a multivariate input signal into additive subcomponents (independent components). The independent components are statistically independent from each other. + apply independent component analysis + + + + + + + + + + apply IIR filter + An infinite impulse response (IIR) filtering where a custom-designed IIR filter is applied to the input data. + apply infinite impulse response filter + + + + + + + + + + A data transformation that estimates new (intermediate) values between the known values in the input data. This can be accomplished using several methods, such as linear interpolation (i.e., estimating the values along a straight line connecting adjacent points), polynomial interpolation (i.e., using polynomials to estimate the values between points), or spline Interpolation (i.e., using piecewise polynomials that pass through the known data points and provide a smooth curve). + apply interpolation + + + + + + + + + + apply LDA + A dimensionality reduction that finds a linear combination of features that separates two or more classes defined in the input data. The input data must have a variable that defines the class for each observation, and continuous variables that are used for the linear discriminant analysis (LDA). LDA finds an optimal projection vector that maximizes the distance between the means of the different classes, and minimizes the variance within each class. LDA projects the input data into the lower-dimensional space, therefore reducing the number of features while retaining the information needed for classification. The optimal projection vectors found by LDA are the Fisher linear discriminants. + apply linear discriminant analysis + + + + + + + + + + + A detrending that removes a running line fit using local linear regression. Local linear regression estimates a function by fitting a low-order polynomial to data within a sliding window (local neighborhood) across the input data. + apply local linear regression detrending + + + + + + + + + + + + A data smoothing that estimates a low-order polynomial in a local neighborhood (window) of any value in the input data. Polynomial coefficients are estimated using the least mean squares method. Contrary to kernel smoothing methods, this is a non-parametric approach and has reduced bias at the boundaries of the input data. + apply local regression and likelihood smoothing + + + + + + + + + + A data normalization that uses the median and interquartile range (IQR) to rescale the values of the input data. This method is less sensitive to outliers (compared to the z-score transform), and therefore is known as robust scaling. + apply robust scaling + apply median rescaling + + + + + + + + + + A data normalization that adjusts the range and distribution of values in the data input such that they fall within a fixed range, based on the minimum and maximum values in the input data. In the typical case, the values are normalized to the [0, 1] interval. + apply rescaling + apply min-max normalization + + + + + + + + + + An artifact removal that identifies and removes artifacts originating from movements of the experimental subject (e.g., eye movement, head movement). + apply movement artifact removal + + + + + + + + + + + + + + + + apply GPFA + + A dimensionality reduction that uses the Gaussian process factor analysis (GPFA) method described by Yu et al. (2009). GPFA extracts smooth, low-dimensional neural trajectories that summarize the activity recorded simultaneously from many neurons on individual experimental trials over time. The input is a set of spike trains representing multitrial activity of multiple neurons recorded in parallel. The input spike trains are binned, and factor analysis is applied to reduce the dimensionality while smoothing the resulting low-dimensional trajectories by fitting a Gaussian process (GP) model to them. The identified trajectories are called neural trajectories, and show the evolution of the activity of the population of neurons over time. + apply neural trajectory Gaussian process factor analysis + + + + + + + + + + A tensor component analysis (TCA) where a non-negative constraint is applied to the decomposition. This is desirable when the underlying components have physical interpretation and negative values are not possible. + apply non-negative tensor component analysis + + + + + + + + + + An infinite impulse response filtering that uses a filter designed to attenuate or eliminate a narrow band of frequencies in the input data (stopband) while allowing other frequencies to pass through relatively unaffected. + apply notch filter + + + + + + + + + + A line noise removal that employs a notch filter to remove line noise. A notch filter is designed to attenuate or eliminate a narrow band of frequencies in the input data (stopband) while allowing other frequencies to pass through relatively unaffected. The notch filter stop band is usually centered at the power line frequency (i.e., 50 Hz or 60 Hz depending on the location). + apply notch filter noise removal + + + + + + + + + + An artifact removal that identifies and removes values in the input data that differs significantly from other values (outliers). Outliers may arise from the variability in the measurement or be the result of experimental error. + apply outlier removal + + + + + + + + + + A data transformation that adds extra data (often zeros or other predefined values) to the beginning, end, or both sides of the input data. + apply padding + + + + + + + + + + apply pPCA + + A principal component analysis (PCA) that assumes a probabilistic model for the generation of the observed data, according to Tipping & Bishop (1999). The model assumes that the values in the data input are generated from the lower-dimensional subspace of latent variables (principal components) plus an additive Gaussian noise. This generalizes the standard PCA for the case where the noise covariance approaches zero. The probabilistic PCA (pPCA) allows for uncertainty estimation and modeling of the data generation process, and can be employed when there are missing values in the input data. + apply probabilistic principal component analysis + + + + + + + + + + A data transformation that computes the absolute value of the input data (rectification). + apply rectification + + + + + + + + + + A data transformation that changes the reference point of the data recorded from an electrode. This can be performed by calculating the average across the data obtained from all electrodes and subtracting it from each individual electrode’s data (reducing common noise) or referencing each electrode to its nearest neighbor or a defined pair, subtracting one signal from another (bipolar referencing). + apply rereference + + + + + + + + + + + A line noise removal that uses spectral interpolation to remove power line noise. After obtaining the discrete Fourier transform (DFT) of the input signal with noise, the original frequency component at the power line oscillation frequency can be estimated by interpolating the amplitude spectrum (obtained from the DFT) at the power line frequency (e.g., 50 Hz), followed by the inverse DFT to reconstruct the signal. + apply spectrum interpolation noise removal + + + + + + + + + + A data transformation that obtains a series of spike times (i.e., a spike train) from an input time series (e.g., voltages recorded from an electrode). The spike times can be estimated, for example, by taking all the time points where the values in the input data are greater or lower than a threshold value. + apply spike extraction from time series + + + + + + + + + + A data transformation that takes an input spike train and returns an array of boolean values indicating if at least one spike occurred at individual time points. + apply spike train binarization + + + + + + + + + + A data transformation that performs a binning operation on the input spike train data. The transformation discretizes the duration of the input spike train(s) into smaller time intervals (bins), and obtains the number of spikes occurring into each bin (binned spike train). Additionally, the occurrence of spikes into each bin can be converted into a binary form (i.e., bins with or without spikes). This is known as clipping. The width of the bin interval is specified by a parameter (bin size). + apply spike train binning + + + + + + + + + + A data transformation that estimates additional (unknown) values between sample points of a spike waveform input. + apply spike waveform interpolation + + + + + + + + + + An artifact removal that identifies and removes spike waveforms that differ significantly from the other spike waveforms in the input. This usually involves identifying waveforms with too late peaks, or in which the rising phase of the potential does not align with the peaks of all other waveforms in the input. + apply spike waveform outlier rejection + + + + + + + + + + A data transformation that modifies input spike waveforms in order to align their peak values in time. + apply spike waveform peak alignment + + + + + + + + + + apply standard PCA + A principal component analysis (PCA) that operates by computing the covariance matrix of the input data, which is then decomposed into its eigenvectors and eigenvalues. The eigenvectors, corresponding to the principal components (PCs), are sorted by the magnitude of their associated eigenvalues. The eigenvectors with the largest eigenvalues explain the most variance in the data and thus form the primary PCs. + apply classical principal component analysis + apply standard principal component analysis + + + + + + + + + + An artifact removal that identifies and removes artifacts originating from presenting a stimulus during the recording (e.g., electrical stimulation). + apply stimulation artifact removal + + + + + + + + + + A data transformation that performs the addition of two or more data inputs to obtain a sum. + apply sum + + + + + + + + + + An artifact removal that identifies and removes spikes across two or more spike train inputs that occurred simultaneously within a temporal precision specified by a parameter. The temporal precision is usually the sampling rate used by the recording equipment: if different neurons fired within an interval equal to or smaller than the sampling period, this suggests that this synchronous activity does not come from temporal synchronization of the neurons but rather due to an interference in the recording (e.g., electrical noise picked simultaneously by multiple channels). + apply synchronous spike removal + + + + + + + + + + + A line noise removal that uses Thomson's regression method (1982) for detecting sinusoids, that identifies and removes significant sine waves from the input data. The desired frequencies can be specified by parameter, or determined using an F-statistic. + apply Thomson regression noise removal + + + + + + + + + + A data transformation that extracts trial segments from an input data entity storing a longer and continuous data stream. A trial is a single instance of a repeated experimental procedure. For example, during an electrophysiology experiment, a visual stimulus might be presented several times, with neural activity recorded each time. Each presentation of the stimulus defines a trial. Since the data is recorded continuously, this data transformation identifies and isolates the segments of data corresponding to each individual stimulus presentation, returning them as separate data entities. + apply trial extraction + + + + + + + + + + A resampling that increases the number of samples in the data (i.e., increases the sampling frequency). This is often accomplished by adding new (zero-valued) samples between existing ones followed by applying a lowpass filter to replace the zeros and smooth out the discontinuities. + apply upscaling + apply upsampling + + + + + + + + + + A finite impulse response filtering that employs the convolution with a sinc function kernel multiplied by a window function (e.g., Blackman or Hamming). The kernel is obtained by evaluating the sinc function for the cutoff frequencies specified as parameters, followed by truncation of the filter skirt, and applying the window to reduce the artifacts introduced from the truncation. The windowed-sinc filter is stable and very efficient to separate one band of frequencies from another. + apply windowed-sinc filter + + + + + + + + + + A data normalization that transforms the values of the input data to have zero mean and unit variance. + apply standardization + apply z-score transform + + + + + + + + + + A data transformation that aims to identify and remove artifacts from the input data. Artifacts are unwanted disturbances that distorts the data. In an electrophysiology experiment, they can arise from various sources: environmental interference (e.g., electromagnetic interference from nearby equipment), physiological processes (e.g., eye movement, heart beat), and technical instrumentation issues (e.g., baseline drift of the recorded potentials). + artifact removal + + + + + + + + + + + + + + + + A data generation that produces artificial data. Artificial data refers to data that is generated programmatically rather than obtained from experimental recordings (e.g., neural simulations or by using specific statistical procedures). The artificial data generation procedure does not take experimentally-recorded data as input, and the generation of the output data depends only on parameters to the method employed. The isArtificial data property is defined as True for outputs of artificial data generation steps. + artificial data generation + + + + + + + + + + + + + true + + + An analysis step used to compute a measure of autocorrelation, i.e., the correlation of the input with displaced (lagged or advanced) versions of itself. The computation produces the autocorrelation value for every lag considered. + autocorrelation analysis + + + + + + + + + + + + true + + + + + An analysis step that has only two distinct inputs considered for the computation of the output (e.g., the two time series with the local field potential recorded from two electrodes used to compute a cross-correlation). + pairwise analysis + bivariate analysis + + + + + + + + + + A statistical analysis to compute a measure of central tendency, i.e., that represents the center or typical value of the input data. + central tendency statistical analysis + + + + + + + + + + + + + + + + + + + true + + + + + + false + + + + + + true + + + + + + true + + + A spectral analysis that computes a measure of coherence between two or more inputs. Coherence is a real measure that describes the linear association of the distinct inputs (e.g., two time series) in different frequency bands. It corresponds to the absolute value of the coherency. + coherence analysis + + + + + + + + + + + + + + + + + + + true + + + + + + false + + + + + + true + + + + + + true + + + A spectral analysis that computes a measure of coherency between two inputs. Coherency is a complex-valued measure that describes the linear association of the distinct inputs (e.g., two time series) in different frequency bands. + coherency analysis + + + + + + + + + + + + + + + + An analysis step that is composed by two or more substeps, each performing a part of the analysis with its own data inputs/outputs and analysis parameters. + compound analysis + + + + + + + + + + + ASSET analysis substep that computes the cluster matrix (CMAT) in the ASSET analysis, using DBSCAN with a modified distance metric. It takes the mask matrix (MMAT) as input. The cluster matrix groups the significant entries in the MMAT according to each diagonal structure that they belong to. For each significant entry in the MMAT, the CMAT will have an integer value: -1 for significant entries that do not belong to any diagonal structure, or any value greater than zero with the identification of the cluster that the entry belongs to. + compute ASSET cluster matrix + + + + + + + + + + + ASSET analysis substep that computes the intersection matrix (IMAT). For a set of input spike trains, binned with a bin width, each entry in the IMAT corresponds to a pair of distinct bins (i.e., distinct time points in the data). The value in the entry corresponds to the number of neurons that fired in both bins corresponding to that entry. When groups of neurons fire in a sequence that repeats in time, the IMAT will show patterns that follow a diagonal direction (diagonal structure). The ASSET method aims to identify the diagonal structures by automated statistical testing and clustering procedures. + compute ASSET intersection matrix + + + + + + + + + + + ASSET analysis substep that computes the joint probability matrix (JMAT). For every entry in the probability matrix (PMAT), the computation produces the combined probability of a fixed number of neighbors in a rectangular kernel (with fixed length and width as parameters) covering a diagonal structure. A value in the JMAT reflects how likely entries with high probability in the PMAT are to be located in the same diagonal structure. + compute ASSET joint probability matrix + + + + + + + + + + + ASSET analysis substep that computes the mask matrix (MMAT). The parameters are the threshold values that are used to determine if the entries in the probability matrix (PMAT) and joint probability matrix (JMAT) are significant. Entry significance in either matrix is defined as a probability value greater than the provided threshold value. Significant entries in both probability and joint probability matrices are defined as 1 in the mask matrix. + compute ASSET mask matrix + + + + + + + + + + + + ASSET analysis probability matrix substep that computes the probability matrix (PMAT) using the assumption that the input spike trains are independent and Poisson. The computation can take as input the firing rate profiles of the spike trains used for the intersection matrix (IMAT), or those will be automatically computed using convolution with a boxcar kernel of specified width. The probability distribution of the value in the intersection matrix (IMAT) is approximated by a Poisson distribution computed using LeCam's approximation. The output is a matrix with the cumulative probabilities representing the probability of having each overlap in the IMAT strictly lower than the observed overlap, under the null hypothesis of independence of the input spike trains. + compute ASSET probability matrix (analytical method) + + + + + + + + + + + ASSET analysis probability matrix substep that computes the probability matrix (PMAT) employing a Monte Carlo approach using surrogate data obtained from the input spike trains. Different than the analytical method of computation, the null hypothesis in this method does not incorporate the assumptions that the spike trains are Poisson. Spike train surrogates can be generated using distinct methods. + compute ASSET probability matrix (Monte Carlo method) + + + + + + + + + + + Last substep of the ASSET analysis method. Given the cluster matrix (CMAT), the identity of the neurons present in each bin of the repeated sequence in the identified diagonal structures is extracted (considering the input spike trains for the computation of the intersection matrix). The output of this substep is the final description of the ASSET pattern for each diagonal structure in the CMAT. + compute ASSET sequence of synchronous events extraction + + + + + + + + + + + + + + + + + A phase analysis that computes the angle obtained from averaging the phases of an input signal at the time points where spikes occurred. For the computation, the phases are represented as vectors in the unit circle, the mean phase vector is computed, and the angle is extracted. + compute angular mean of spike phases + + + + + + + + + + compute ACF + An autocorrelation analysis that computes the estimator for the autocorrelation function, i.e. the autocorrelation values of a time series input for a number of lags. The autocorrelation function shows temporal dependencies and repetitive patterns within the input data. The value of the autocorrelation at a specific lag shows how similar the values in the time series input are when separated by a number of time units equal to that lag. The autocorrelation value of 0 indicates no correlation. The autocorrelation varies between 1 and -1 (positive and negative correlation, respectively). + compute autocorrelation function + + + + + + + + + + compute CV + A dispersion statistical analysis that computes the coefficient of variation (CV). The CV is the ratio of the standard deviation to the mean. It is useful to compare different inputs, as the measure is unitless and indicates the relative variability in the input data. + compute coefficient of variation + + + + + + + + + + + An interspike interval variability analysis that computes the CV2, a measure of the intrinsic variability of a spike train that considers adjacent interspike intervals. The CV2 is more robust against fluctuations in the firing rate than the usual approach of taking the coefficient of variation of the interspike intervals of the spike train. + compute CV2 + + + + + + + + + + compute CV ISIs + An interspike interval variability analysis that computes the coefficient of variation (CV) of the interspike intervals (ISIs). The CV is computed as the ratio of the standard deviation of the ISIs to their mean. + compute coefficient of variation of the interspike intervals + + + + + + + + + + compute caCOH + + A coherence analysis that computes the canonical coherence (caCOH) according to Vidaurre et al. (2019). The computation maximizes the coherence between two inputs (e.g., distinct datasets with electroencephalogram, electromyogram or local field potential recordings). The absolute value of the coherence between the two multivariate spaces of the inputs in the frequency domain is maximized. The caCOH aims to maximize the strength of the synchronization of oscillatory signals when two multichannel datasets are present (e.g., multiple subjects). The method then finds two spatial projections maximizing the strength of synchronization. + compute canonical coherence + + + + + + + + + + A coherence analysis that computes the coherence value between two inputs. It is obtained from the magnitude of the complex-valued cross power spectral density obtained for the two inputs normalized by their power spectral density (i.e., auto spectral density). Several frequency decomposition approaches can be used to obtain the cross and auto power spectral densities from the inputs. The computation can return the magnitude coherence (i.e., by taking the absolute value of the cross power spectral density and normalizing by the square root of the product of the two auto spectral densities) or the magnitude squared coherence (i.e., by computing the squared magnitude of the cross power spectral density and normalizing by the product of the two auto spectral densities). + compute coherence + + + + + + + + + + + A coherence analysis that computes the coherence from two inputs according to Carter (1987). The computation produces the magnitude squared coherence. + compute coherence (Carter method) + + + + + + + + + + + A coherence analysis where the coherence value between the two inputs is computed using cross and auto power spectral densities obtained using a multitaper approach according to Thomson (1982). + compute coherence (multitaper method) + + + + + + + + + + + A coherence analysis that computes the coherence from two inputs according to Rosenberg et al. (1989). The method is described for point processes (i.e., spike trains). The computation produces the magnitude squared coherence. + compute coherence (Rosenberg method) + + + + + + + + + + + A coherence analysis where the coherence value between the two inputs is obtained from cross and auto power spectral densities obtained using the method described by Welch (1967). For the computation, the inputs are divided into multiple overlapping segments, and the overall cross and power spectral densities for computing the coherence are obtained from averaging the single-segment estimates. + compute coherence (Welch method) + + + + + + + + + + A coherency analysis that computes the coherency for two inputs. It is computed from the complex-valued cross power spectral density obtained for the two inputs normalized by the square root of the product of their power spectral densities (i.e., auto spectral densities). For each frequency, the magnitude of the complex-valued coherency describes the strength of the association and the angle describes the phase lag between the two inputs. If the inputs contain multi-epoch data (e.g., multiple trial repetitions), the cross and auto spectral densities are averaged across epochs. + compute complex coherency + compute coherency + + + + + + + + + + + A spike train synchrony analysis that computes the complexity distribution across a set of input spike trains that typically contain the activity of different neurons. In a neuronal population, the complexity represents the total number of neurons that were spiking within a discrete time interval. For the computation, the binarized population histogram (i.e., a spike time histogram computed across spike trains, where each bin will have the count of spike trains that had at least one spike within the bin interval) is obtained using a bin size specified as a parameter. The value at each bin is the complexity. The complexity distribution is obtained by finding the frequency of each complexity value (complexity histogram) and corresponding probability density function (PDF). The complexity PDF describes the likelihood of different complexity values occurring within the neuronal population. + compute complexity distribution + + + + + + + + + + + A confidence interval resampling analysis that computes the confidence interval using bootstrapping techniques to create many simulated samples (bootstrap samples). It involves repeatedly sampling, with replacement, from the input (observed) data. The total number of bootstrap samples is defined as a parameter. Bootstrapping makes minimal assumptions about the underlying distribution of the data, making it especially useful for small samples or when the data do not meet the assumptions of traditional parametric (non-resampling) methods. + compute confidence interval (bootstrap resampling) + + + + + + + + + + A confidence interval resampling analysis that computes the confidence interval using jackknife techniques. It involves systematically leaving out one observation at a time from the input (sample) set and calculating the statistic of interest on each of these "leave-one-out" samples. The confidence interval is computed based on statistics obtained from those jackknife samples. Jackknife is useful for small samples or when the data do not meet the assumptions of traditional parametric (non-resampling) methods. + compute confidence interval (jackknife resampling) + + + + + + + + + + + A confidence interval statistical analysis that computes the confidence interval assuming a statistical distribution of the input data, and uses measures of central tendency and dispersion obtained from the data points in the input(s) (e.g., mean and standard error of the mean when assuming a normal distribution). The computation relies on theoretical distributions and established statistical formulas. + compute confidence interval (non-resampling) + + + + + + + + + + + compute CWT + A wavelet transform analysis that convolves the input time series with scaled and translated versions of the mother wavelet. The scale parameter can be non-dyadic (i.e., can take values that are not powers of 2). The mother wavelet used is passed as a parameter, and several types can be used (e.g., Morlet, Mexican hat, Hermitian, Meyer, Poisson). The continuous wavelet transform (CWT) is ideal for analyzing non-stationary signals, with transient behavior, rapidly changing frequencies or slowly varying changes. It is comparable to the short-time Fourier transform (STFT). + compute continuous wavelet transform + + + + + + + + + + compute ciPLV + + A phase locking value analysis that computes the corrected imaginary phase locking value (ciPLV), following the implementation from Bruña & Maestú (2018). It re-formulates the original phase locking value (PLV) for computational efficiency. The computation uses the imaginary part of the PLV, to make the metric insensitive to zero lag synchronizations (that can be the result of volume conduction). + compute corrected imaginary phase locking value + + + + + + + + + + + + + true + + + + + + false + + + + + + true + + + A covariance analysis that computes the values of covariance in pairwise input data. + compute covariance + + + + + + + + + + compute CCF + A cross-correlation analysis that computes an estimate of the cross-correlation function, i.e. the cross-correlation values of two time series inputs for a number of lags. The cross-correlation function shows temporal dependencies of the first input series with respect to the second. The value of the cross-correlation at a specific lag shows how similar the values in the first input series are to values in the second input at time points separated by a number of time units equal to that lag. The cross-correlation value of 0 indicates no correlation. The cross-correlation varies between 1 and -1 (positive and negative correlation, respectively). + compute cross-correlation function + + + + + + + + + + + compute CCF (biased) + An analysis step that computes the biased estimator for the cross-correlation function. The biased estimator produces cross-correlation values that deviate from the true cross-correlation. + compute cross-correlation function (biased) + + + + + + + + + + compute CCF (unbiased) + + An analysis step that computes the unbiased estimator for the cross-correlation function, using the formula in Stoica & Moses (2005). The unbiased estimation uses a correction for the bias due to zero-padding in the computation, applied to the normalization coefficient. Therefore, the resultant cross-correlation values are closer to the true cross-correlation. + compute cross-correlation function (unbiased) + + + + + + + + + + A cross power spectral density analysis that uses the Morlet wavelet transform to obtain the frequency information of the two inputs used to compute the cross power spectral density. + compute cross power spectral density (Morlet wavelet method) + + + + + + + + + + compute CPSD (multitaper method) + + A cross power spectral density (CPSD) analysis that uses a multitaper approach to compute the CPSD, according to Thomson (1982). The multitaper method uses discrete prolate spheroidal functions (DPSS, also known as Slepian sequences) as tapers applied to the inputs. For the computation, a CPSD using the periodogram method is obtained for each pair of tapered signals. The DPSS functions are orthogonal, and therefore applying multiple DPSS tapers result in independent estimates of the CPSD. The final CPSD is obtained by averaging the CPSDs across all tapers. The multitaper method reduces variance and bias in the CPSD, and has a high frequency resolution. However, it is computationally expensive. The number of tapers used is passed as parameter, or estimated from the desired resolution. + compute cross power spectral density (multitaper method) + + + + + + + + + + compute CPSD (periodogram method) + A cross power spectral density (CPSD) analysis that uses the periodogram method. For the computation, the discrete Fourier transform of each input is obtained and their cross-power spectrum is obtained. A window function can be applied to the inputs before the Fourier transform, to reduce spectral leakage. The final CPSD is obtained by normalizing the cross-power spectrum to the unit frequency using the equivalent noise bandwidth (a factor that depends on the coefficients of the window function and the sampling rate). If no window function is used or a window that does not attenuate the signal is used (e.g., Boxcar or rectangular window) the equivalent noise bandwidth is equal to the frequency resolution. + compute cross-periodogram + compute cross power spectral density (periodogram method) + + + + + + + + + + compute CPSD (Welch method) + + A cross power spectral density (CPSD) analysis that uses the method defined by Welch (1967). For the computation, the two inputs are divided into several overlapping segments (length and overlap passed as parameters, or computed for the desired frequency resolution based on the input length and sampling frequency). A window function (e.g., Hann) is applied to each segment, and the cross power spectral density using the periodogram method is computed. The final CPSD is obtained by averaging all the periodograms with the individual CPSDs. + compute cross power spectral density (Welch method) + + + + + + + + + + compute cross-spectrogram (STFT method) + A spectrogram analysis that computes a cross-spectrogram using the short-time Fourier transform (STFT). The cross-spectrogram is the time-resolved description of the power of a pair of distinct inputs across the different frequency components. This can be used to investigate how common activity between the two inputs is distributed across the frequency components, and how it varies over time. + compute cross-spectrogram (short-time Fourier transform method) + + + + + + + + + + + A spike train synchrony analysis that uses the Cumulant Based Inference of higher-order Correlation (CuBIC) test described in Staude et al. (2010). CuBIC is a statistical method to detect the presence of higher order correlations in parallel spike trains from a neuronal population (i.e., correlations among three or more neurons). It is based on the analysis of the cumulants of the population spike count. The test takes a population histogram as input data (i.e., a spike train time histogram computed across spike trains with the activity of distinct neurons). A null hypothesis that the third cumulant of the data is less than or equal to the maximized third cumulant for a correlation order is iteratively tested (with increasing orders of correlation). The output is the minimum correlation order necessary to explain the value of the third cumulant calculated from the population spike count, together with the p-values of the hypothesis tests performed. + compute CuBIC analysis + + + + + + + + + + compute iCSD + + + + A current source density (CSD) analysis that uses the inverse current source density (iCSD) estimation method described by Pettersen et al. (2006). The iCSD is based on the inversion of the electrostatic forward solution and can be applied to data obtained from electrodes with multiple configurations. The method can handle cases with spatially confined cortical activity and spatially varying extracellular conductivity. + +Three options for CSD estimation using the iCSD exist. The CSD is assumed to have cylindrical symmetry and follows one of three possible assumptions: +1. is localized in infinitely thin discs; +2. is step-wise constant; +3. is continuous and smoothly varying (using cubic splines) in the vertical direction. + compute current source density (inverse method) + + + + + + + + + + compute kCSD + + A current source density (CSD) analysis that uses kernel methods to compute the CSD (kCSD), described by Potworowski et al. (2012). kCSD is non parametric and can estimate the CSD using signals recorded from arbitrarily distributed electrodes, as the assumption of regular electrode placement is not necessary. The method can handle 1D, 2D or 3D electrode configurations. The kCSD can also estimate CSD at any location, as it is not limited to the electrode positions, and uses cross-validation to ensure no overfitting. + compute current source density (kernel method) + + + + + + + + + + compute CSD + + + A current source density (CSD) analysis that uses a double spatial derivative of the recorded extracellular potentials to compute the CSD. The original method by Freeman & Nicholson (1975) assumes homogeneous cortical in-plane activity, constant extracellular electrical conductivity and equidistant electrode contacts, and can only predict the CSD at interior electrode positions. Vaknin et al. (1988) suggested a procedure to obtain the CSD for the first and last electrodes by copying the outmost recordings, therefore extending the grid beyond the electrode contacts. This is based on the assumption that the potential varies negligibly above the first and below the last electrode. + compute current source density (standard method) + + + + + + + + + + + + + false + + + compute debiased squared WPLI + + A phase lag index (PLI) analysis that computes the debiased squared weighted PLI (WPLI) following Vinck et al. (2011). The direct PLI estimator is positively biased, especially when the sample sizes (i.e., number of trials) are small. The debiased squared WPLI is computed by computing the imaginary components of the cross spectral densities, computing the average imaginary component of the cross spectral densities, and normalizing by the computed average over the magnitudes of the imaginary component of the cross spectral densities. + compute debiased squared weighted phase lag index + + + + + + + + + + + + + true + + + compute DPLI + + A phase lag index (PLI) analysis that computes the directed PLI (DPLI) according to Stam & van Straaten (2012). The DPLI uses the Heaviside step function on the imaginary part of the cross power spectral density, and provides the ability to discriminate whether the first time series is leading or lagging the second. The DPLI ranges between 0 and 1. A DPLI value of 0.5 means that the first time series leads and lags the second time series equally often. A DPLI value greater than 0.5 means that the first time series leads the second more often than it lags. A value of 1 means that the first time series always leads. On the contrary, a DPLI value smaller than 0.5 means that the first time series lags the second more often than it leads. A DPLI value of zero means that the first time series always lags. The PLI can be computed from the DPLI. + compute directed phase lag index + + + + + + + + + + + + + true + + + + + + true + + + + + + true + + + compute DTF + + A functional connectivity analysis that computes the directed transfer function (DTF) according to Kaminski & Blinowska (1991). DTF can estimate the direction and frequency content of the brain activity flow. The DTF measure is obtained from the spectral transfer matrix computed from multivariate time series input data. For the DTF computation, the spectral transfer matrix is obtained from a multivariate autoregressive model. The DTF estimate is obtained by using a normalization factor computed by the sum along the rows of the spectral transfer matrix. The DTF can have values in the range from 0 to 1. + compute directed transfer function + + + + + + + + + + compute ERP + An analysis step that computes the event-related potential (ERP). The ERP is the neural activity (e.g., local field potential or electroencephalogram voltages) around a presented stimulus or spontaneous behavioral event. Usually, the event is presented/occurs repeatedly across multiple trials, obtaining multiple event-related potential waveforms that can be averaged to cancel the noise. + compute event-related potential + + + + + + + + + + A triggered average analysis that uses an event of interest such as an external stimulus (e.g., electrical, visual, auditory) or a spontaneous behavior (e.g., eye blink) as a trigger to average a signal. The output of the method will provide the average value of the signal around the time where each event occurred (event-triggered average). + compute event-triggered average + + + + + + + + + + + + + true + + + + + + A conditional Granger causality (GC) analysis that computes the GC measures in the frequency domain. + compute frequency domain conditional Granger causality + + + + + + + + + + + A frequency domain pairwise Granger causality (GC) analysis that uses the parametric approach according to Brovelli et al. (2004). It uses an MVAR (multivariate autoregressive model) to obtain the coefficients used for the computation of the spectral transfer matrix needed for GC estimation according to the frequency domain GC formulation by Geweke (1982). + compute frequency domain pairwise Granger causality (Brovelli method) + + + + + + + + + + + + A frequency domain pairwise Granger causality (GC) analysis that uses the non-parametric approach according to Dhamala et al. (2008). It is based on Fourier and wavelet transforms to obtain the spectral density matrix and the algorithm from Wilson (1972) for its factorization. + compute frequency domain pairwise Granger causality (Dhamala method) + + + + + + + + + + + A frequency domain pairwise Granger causality (GC) analysis that uses the parametric approach according to Hafner & Herwartz (2008). It uses a multivariate GARCH (generalized autoregressive conditional heteroskedasticity) model and constructs a Wald test on noncausality in variance. This is an alternative to methods based on the residuals of estimated univariate models. The Wald test has superior power properties. + compute frequency domain pairwise Granger causality (Hafner method) + + + + + + + + + + + A frequency domain pairwise Granger causality (GC) analysis that uses the non-parametric approach according to Wen et al. (2013). It is a multivariate framework for estimating GC based on spectral density matrix factorization. The approach requires only a single estimation of the spectral density matrix for the entire dataset (e.g., multiple time series inputs). GC for the subsets (i.e., pairs of inputs) can then be calculated by factorizing the relevant submatrix of this overall spectral density matrix. + compute frequency domain pairwise Granger causality (Wen method) + + + + + + + + + + + A time-scale independent spike train distance analysis that computes the ISI-distance, described in Kreuz et al. (2007). For the computation, the discrete sequence of spike times is transformed into a continuous temporal profile with one value per sample point. The values at each time point are derived from the interspike intervals. The distance is then obtained as the temporal average of the time profile. ISI-distance is well-designed to describe similarities in the firing rate profile of the input spike trains, but it is not optimal to capture neuronal synchrony. + compute ISI-distance + + + + + + + + + + + A coherency analysis that computes the imaginary part of the coherency for two inputs according to Nolte et al. (2004). For the computation, the imaginary part of the complex-valued cross power spectral density obtained for the two inputs is normalized by the square root of the product of their power spectral densities (i.e., auto spectral densities). If the inputs contain multi-epoch data (e.g., multiple trial repetitions), the cross and auto spectral densities are averaged across epochs. The imaginary part of the coherency is less affected by volume conduction than the (complex) coherency. + compute imaginary coherency + + + + + + + + + + An instantaneous firing rate analysis that computes the instantaneous firing rate by using the reciprocal of the interspike intervals. + compute instantaneous firing rate (interspike interval method) + + + + + + + + + + An instantaneous firing rate analysis that computes the instantaneous firing rate by convolution of spike times with a kernel function. The output of the computation is a weighted average of the spikes around the kernel. + compute instantaneous firing rate (kernel smoothing method) + compute instantaneous firing rate (kernel density estimation method) + + + + + + + + + + + An instantaneous firing rate analysis that computes the instantaneous firing rate using local regression methods. The estimation procedure approximates the log of the firing rate using a low-order polynomial within a moving window (local neighborhood). + compute instantaneous firing rate (local regression method) + + + + + + + + + + compute IQR + A dispersion statistical analysis that computes the interquartile range (IQR). The IQR is the difference between the 75th and 25th percentiles (i.e., the range within which the central 50% of the data points lie). + compute interquartile range + + + + + + + + + + compute ISIH + An interspike interval analysis that computes the histogram of interspike intervals. For the computation, a time interval with fixed duration starting from zero is discretized into smaller intervals (bins). The count of input interspike intervals whose values fall into each bin is obtained. Therefore, the output contains a representation of the distribution of the interspike intervals in the input. + compute interspike interval histogram + + + + + + + + + + compute ISIs + An interspike interval analysis that computes the intervals between successive spikes in a spike train (interspike intervals; ISIs). + compute interspike intervals + + + + + + + + + + + + + + + + + + + true + + + + + + false + + + + + + true + + + compute JPSTH + + + A spike train synchrony analysis that computes the joint peristimulus time histogram (JPSTH) from trial-by-trial spike train inputs obtained from two different neurons, after the repeated presentation of a stimulus. The JPSTH provides a representation of the timing relationship between the firing of the two neurons in response to the stimulus. It combines the peristimulus time histograms (PSTHs) of each neuron to illustrate how their firing rates co-vary over time relative to the stimulus event. This helps in understanding the temporal correlation between the neurons. + +The computation can produce three outputs: + +* the JPSTH matrix (i.e., a matrix whose bins contain the counts of coincidences in the firing of the two neurons); +* the peristimulus coincidence histogram (i.e., a histogram obtained from a cross-section along the main diagonal of the JPSTH matrix); +* the cross-correlation histogram computed by summing the bins along the main and each paradiagonal of the JPSTH matrix (after normalizing by the bin length, as the paradiagonals in the JPSTH matrix are of different lengths). + compute joint peristimulus time histogram + + + + + + + + + + compute LV + + An interspike interval variability analysis that computes the local variation (LV) of the interspike intervals. LV reflects the stepwise variability of a sequence of spikes, and is able to extract the spiking characteristics of individual neurons even in the presence of external modulations of the firing rate. + compute local variation + + + + + + + + + + compute LvR + + An interspike interval variability analysis that computes the revised local variation (LvR) of interspike intervals. Compared to the original local variation (LV) measure, LvR has better invariance to fluctuations in the firing rate fluctuations. This is achieved by using a refractoriness constant in the computation of the measure. + compute revised local variation + + + + + + + + + + compute MIC + + A coherency analysis that computes the maximized imaginary coherency (MIC) according to Ewald et al. (2012). The computation uses an eigenvalue-based optimization to find weight vectors that maximize the imaginary part of coherency computed between virtual channels derived from the input data. The weights are optimized for each frequency component. After the weights are obtained, the final MIC measure is obtained for each frequency. + compute maximized imaginary coherency + + + + + + + + + + A central tendency statistical analysis that computes the mean of the input data. The mean is the arithmetic average of all data points. + compute mean + + + + + + + + + + compute MFR + A firing rate analysis that computes the mean firing rate, defined as the number of spikes in a time interval divided by the duration of the interval. The mean firing rate is the temporal average of the neuronal activity over that interval. + compute mean firing rate + + + + + + + + + + A phase analysis that computes the mean among two or more input phases. For the computation, the input phases are represented as vectors in the unit circle, and the mean phase vector is computed. The analysis can return the mean phase vector (i.e., angle and length), the vector angle, or the vector length. + compute mean phase vector + + + + + + + + + + + compute MVL (Canolty method) + + A mean vector length (MVL) analysis that computes the mean vector length as described in Canolty et al. (2006). For the computation, phase is extracted from the low-frequency analytic signal, and amplitude is extracted from the high-frequency analytic signal. The phase angle and magnitude is used to define a complex-valued time series, and each complex value is a vector in the polar plane. Averaging all vectors yields a mean vector whose length indicates the coupling strength and whose direction indicates the phase where amplitude is strongest. Without coupling, the vectors cancel out, resulting in a short mean vector without meaningful phase direction. If phase-amplitude coupling exists, the magnitude of a subset of vectors is especially high at a specific phase or narrow phase range. + compute mean vector length (Canolty method) + + + + + + + + + + compute MVL (Özkurt method) + + A mean vector length (MVL) analysis that computes the MVL as described in Özkurt & Schnitzler (2011). The original MVL (Canolty et al., 2006) may be affected by factors in the input data (e.g., amplitude outliers or non-uniform distribution of phase angles). This computation estimates a direct MVL that is amplitude-normalized to obtain values in the 0 to 1 range, and that takes care of possible amplitude differences in the raw data. + compute mean vector length (Özkurt method) + + + + + + + + + + A central tendency statistical analysis that computes the median of the input data. The median is the middle value when data points are arranged in ascending order (i.e., it divides the data points in two equal halves, with 50% of the data points below it and 50% above it). If there is an even number of data points, the median is the average of the two middle values. + compute median + + + + + + + + + + compute MI + + A phase-amplitude coupling (PAC) analysis that computes the modulation index (MI) as described in Tort et al. (2010). For the computation, the Hilbert transform is used to obtain the instantaneous phase from the input time series with the low-frequency oscillation, and the instantaneous amplitude from the input time series with the high-frequency oscillation. The phase of the low-frequency oscillation is discretized into bins and the amplitude of the high-frequency oscillation is averaged within each bin to create a distribution. This distribution is then compared to a uniform distribution using the Kullback-Leibler divergence, normalized by the maximum possible divergence, resulting in the MI. + compute modulation index + + + + + + + + + + A wavelet transform analysis based on the complex-valued Morlet wavelet. The transform can be performed either in the time domain (by convolution) or in the frequency domain (by multiplication). + compute Morlet wavelet transform + + + + + + + + + + + + A wavelet transform analysis using the Morlet wavelet where the parametrization of the mother wavelet is done according to Le Van Quyen et al. (2001). The size of the mother wavelet is determined in number of cycles to control the frequency and temporal resolutions (approximate number of oscillation cycles within a wavelet). + compute Morlet wavelet transform (Le Van Quyen method) + + + + + + + + + + + A wavelet transform analysis using the Morlet wavelet based on the methods described in Tallon-Baudry et al. (1997). The ratio of the central frequency to the spectral bandwidth is 7, with central frequencies ranging from 20 to 100 Hz in 1 Hz steps. This resulted in varying time/frequency resolution across the spectrum: time resolution increases with frequency, while frequency resolution decreases. + compute Morlet wavelet transform (Tallon-Baudry method) + + + + + + + + + + compute MIM + + A functional connectivity analysis that computes the multivariate interaction measure (MIM) as defined by Ewald et al. (2012). MIM is constructed from the maximization of imaginary coherency. + compute multivariate interaction measure + + + + + + + + + + + + + true + + + + + + false + + + + + + false + + + + + + true + + + compute MI + + A functional connectivity analysis that computes a mutual information (MI) measure. MI is based on Shannon information theory, and quantifies the amount of information from one input that is obtained from another input. Therefore, it can be used to determine how the neuronal activity provides information about a variable (e.g., behavioral stimulus) or how the information flows between different brain regions or neurons. The MI is measured in bits. + compute mutual information + + + + + + + + + + + An analysis step that computes the neuronal population vector, used to describe the collective activity of a group of neurons. The neuronal population vector is obtained taking as inputs the multiple responses of a neuronal population in the context of distinct values of a behavioral measure (e.g., tuning curves showing the response of each individual neuron to different arm movement directions in the 2-D space). The analysis step obtains a weighted vectorial sum of the neural activities, which will result in an estimate of the behavioral measure considering the collective activity of the population (e.g., the movement direction given the neuronal activity). + compute population vector + compute neuronal population vector + + + + + + + + + + compute NC + + A spike train correlation analysis that computes the noise correlations (NC) between two input spike trains. The NC is the Pearson's correlation coefficient of spike count responses to repeated presentations of identical stimuli, under the same behavioral conditions. The spike counts are typically measured over the time scale of a stimulus presentation or a behavioral trial, which range from a few hundred milliseconds to several seconds. NC assesses whether neurons exhibit trial-by-trial fluctuations in firing rates that are not influenced by varying sensory or behavioral conditions. + compute noise correlations + + + + + + + + + + + + + true + + + + + + false + + + + + + true + + + A covariance analysis that computes the noise covariance, i.e., how much two noise signals vary together. The noise data inputs can be non-subject recordings (e.g., recordings from the empty experimental room) or are obtained from periods without stimulation or meaningful experimental manipulations (e.g., prestimulus intervals). These reflect random variations or disturbances that are not part of the actual signal or data of interest. + compute noise covariance + + + + + + + + + + + An analysis step that finds the optimal bin size considering the input data when discretizing data into smaller intervals (bins). The computation uses the formula from Scott (1979). + compute optimal bin size + + + + + + + + + + + An analysis step that computes the optimal fixed bandwidth (width) for a Gaussian kernel used for the estimation of the firing rate using kernel density estimation. The analysis step uses the input spike train for which the firing rate will be computed, and follows the implementation by Shimazaki & Shinomoto (2010). + compute optimal kernel bandwidth + + + + + + + + + + + A functional connectivity analysis that computes the orthogonalized power envelope correlation, according to Hipp et al. (2012). This method relies on correlations between the instantaneous amplitudes of cross-region input signals (power envelopes). The instantaneous amplitudes of the two input time series are orthogonalized aiming to remove spurious correlations of signal power (e.g., due to limited spatial resolution of electrophysiological measures). + compute orthogonalized power envelope correlation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + true + + + + + + true + + + + + + true + + + + + + true + + + compute PPC + + A phase analysis that computes the pairwise phase consistency (PPC) measure according to Vinck et al. (2010). The PPC quantifies the distribution of phase differences across the inputs, but is less biased by the number of observations in comparison to the phase locking value (PLV). For the computation, the phase difference (angular distance) is obtained for all pairs of observations in the input (that can be represented as vectors in the unit circle, where the angle is the relative phase). The cosine of the angular distance (an estimate of the dot product of the vectors corresponding to each element in a pair) is computed for every pair, and the PPC estimate is obtained from the average of all pairwise dot products. With phase synchronization, the distribution of the pairwise dot products is centered around an average value, while without synchronization it will be distributed across the unit circle. The PPC provides an unbiased estimate of the squared PLV. + compute pairwise phase consistency + + + + + + + + + + + A coherence analysis that computes the partial coherence, i.e., the coherence value between a pair of inputs (e.g., time series with recordings from two distinct electrode channels) after removing the influence of one or more additional inputs (e.g., the time series with the recordings from all remaining channels). The partial coherence is computed according to Rosenberg et al. (1998). The partial coherence reflects the linear association in the frequency domain (for each frequency component) between the pair of inputs of interest, removing spurious coherence caused by confounding factors such as shared inputs to the pair of interest or volume conduction. + compute partial coherence + + + + + + + + + + + + + + + + + + + true + + + + + + true + + + + + + true + + + compute PDC + + A coherence analysis that computes the partial directed coherence (PDC) according to Baccalá & Sameshima (2001). The PDC describes the relationships between multivariate time series inputs (direction of information flow). To compute the PDC, the multivariate partial coherences obtained from multivariate autoregressive models are decomposed. The PDC reflects a frequency-domain representation of the concept associated with Granger causality. + compute partial directed coherence + + + + + + + + + + compute PSTH (adaptive kernel smoothing) + A peristimulus time histogram (PSTH) analysis that computes the PSTH using kernel density smoothing with an adaptive kernel width. The adaptive kernel is obtained by first computing the PSTH with a fixed-width kernel, and then modifying the kernel width in order to have a constant but time-dependent average number of spikes under the kernel (i.e., segments of the data with a high density of spikes will have a reduced kernel width). + compute peristimulus time histogram (adaptive kernel smoothing) + + + + + + + + + + compute PSTH (fixed kernel smoothing) + A peristimulus time histogram (PSTH) analysis that computes the PSTH using kernel density smoothing with a fixed kernel width specified as parameter. + compute peristimulus time histogram (fixed kernel smoothing) + + + + + + + + + + + compute PSTH (optimal bin size) + A peristimulus time histogram (PSTH) analysis that computes the PSTH finding the optimal bin size from the input spike train data, using the formula from Scott (1979). + compute peristimulus time histogram (optimal bin size) + + + + + + + + + + compute PSTH (user-selected bin size) + A peristimulus time histogram (PSTH) analysis that computes the PSTH using a fixed bin size specified as a parameter. + compute peristimulus time histogram (user-selected bin size) + + + + + + + + + + A phase analysis that computes the difference between two input phases. + compute phase difference + + + + + + + + + + + + + false + + + compute PLI + + A phase lag index (PLI) analysis that computes the PLI following Stam et al. (2007). The input data contains multiple repetitions of a pair of signals (e.g., time series with recordings from a pair of electrodes across multiple trials). For each repetition, the sign of the phase differences between the two time series is obtained from the imaginary part of the cross power spectral density (CPSD). The PLI value is the absolute value of the average of the signs of all repetitions. The PLI ranges between 0 and 1. A PLI of zero means that the first time series leads the second equally often (i.e., indicates either no coupling or coupling with a phase difference centered around 0 mod π, which could be from common sources such as volume conduction). A value greater than zero means an imbalance in the likelihood of the first time series to be either leading or lagging the second time series. A PLI of 1 indicates perfect phase locking, and that the first time series only leads or only lags (at a value of phase differences different from 0 mod π). + compute phase lag index + + + + + + + + + + compute PLV + + A phase locking value (PLV) analysis that computes the PLV value as originally described by Lachaux et al. (1999). The input data is a set of pairs of time series (e.g., the trial-by-trial local field potential recorded from two different electrodes). For each time series pair, the instantaneous phase is obtained (e.g., using the Hilbert transform or wavelet decomposition), and the phase difference for each time point is obtained. The PLV value is computed by averaging the complex phase differences across all pairs, obtaining one PLV value per time point. The PLV ranges from 0 to 1. A PLV of 1 indicates perfect phase locking, meaning the phase difference between the two time series is constant over time. A PLV of 0 indicates no phase locking, meaning the phase difference is randomly distributed over time. + compute phase locking value + + + + + + + + + + + + + + + + + + + true + + + + + + true + + + + + + true + + + + + + true + + + compute PSI + + A functional connectivity analysis that computes the phase slope index (PSI) according to Nolte et al. (2008). The PSI is based on the slope of the phase of the cross-spectral density between two time series inputs, considering how the phase difference between two signals changes as you move from one frequency bin to the next. It is computed from the complex-valued coherency using a bandwidth specified as parameter. For the computation, the change in phase difference between neighboring frequency bins is obtained (considering the specified bandwidth) and weighted. The PSI value deviates from zero when the phase difference changes consistently across frequencies and there is substantial coherence. The sign of the PSI indicates the temporal order of the two signals (i.e., which signal is leading the other one). + compute phase slope index + + + + + + + + + + + A spike train time histogram analysis that computes a histogram across two or more spike trains that contain the activity of different neurons (i.e., a neuronal population), recorded at fully-overlapping time intervals. The activity in each histogram bin reflects the combined activity of the population at that time, and the distribution of the histogram corresponds to the population activity over time. + compute population histogram + + + + + + + + + + compute PSD (Bartlett method) + + A power spectral density (PSD) analysis that uses the method defined by Bartlett (1950). For the computation, the input time is divided into non-overlapping segments, with length specified as a parameter. A periodogram is computed for each segment to obtain the single-segment PSD. The final PSD is obtained by averaging all the single-segment PSDs. A window function can be applied to each segment before computing the periodograms. The PSD obtained with the Bartlett method is less noisy than a single periodogram obtained from the entire signal, although the frequency resolution of the estimates is reduced due to segmenting. It is equivalent to the Welch method without any segment overlap. + compute power spectral density (Bartlett method) + + + + + + + + + + compute PSD (multitaper method) + + A power spectral density (PSD) analysis that uses a multitaper approach to compute the PSD, according to Thomson (1982). The multitaper method uses discrete prolate spheroidal functions (DPSS, also known as Slepian sequences) as tapers applied to the input signal. For the computation, a PSD using the periodogram method is obtained for each tapered signal. The DPSS functions are orthogonal, and therefore applying multiple DPSS tapers result in independent estimates of the PSD. The final PSD is obtained by averaging the periodograms across all tapers. The multitaper method reduces variance and bias in the PSD, and has a high frequency resolution. However, it is computationally expensive. The number of tapers used is passed as parameter, or estimated from the desired resolution. + compute power spectral density (multitaper method) + + + + + + + + + + compute PSD (periodogram method) + A power spectral density (PSD) analysis that uses the periodogram method. For the computation, the discrete Fourier transform is applied to the full length of the input, and the power spectrum is obtained. To reduce spectral leakage, a window function can be applied to the input before the computation of the Fourier transform (this is referred as the modified periodogram). The power spectrum is then normalized to the unit frequency, using the equivalent noise bandwidth (a factor that depends on the coefficients of the window function and the sampling rate). If no window function is used or a window that does not attenuate the signal is used (e.g., Boxcar or rectangular window) the equivalent noise bandwidth is equal to the frequency resolution. The PSD using the periodogram is computationally simple to obtain. + compute FFT power spectral density + compute periodogram + compute power spectral density (periodogram method) + + + + + + + + + + compute PSD (Welch method) + + A power spectral density (PSD) analysis that uses the method defined by Welch (1967). For the computation, the input is divided into several overlapping segments (length and overlap passed as parameters, or computed for the desired frequency resolution based on the input length and sampling frequency). A window function (e.g., Hann) is applied to each segment, and a periodogram is computed to obtain the PSD for the segment. The final PSD is obtained by averaging all the periodograms with the single-segment PSDs. If there is no overlap between segments, this is equivalent to the Bartlett method. + compute power spectral density (Welch method) + + + + + + + + + + + An analysis step that uses the change point detection algorithm from Messer et al. (2014) to determine if a input spike train has constant firing rate (stationary) or has one or more points in which the firing rate decreases or increases (change point). In the latter case, the spike train is considered non-stationary. The analysis step outputs one or more change points in the case of non-stationarity. + compute rate change detection multiple filter test + + + + + + + + + + compute RAUC + An analysis step that computes the rectified area under the curve (RAUC). For the computation, the input signal is rectified (i.e., the absolute value is obtained) and the area under the curve is computed by integration using the composite trapezoidal rule. + compute rectified area under the curve + + + + + + + + + + A covariance analysis where the computation of the covariance values incorporates regularization techniques to improve the numerical stability, especially if the number of samples is small. + compute regularized covariance + + + + + + + + + + + A time-scale independent spike train distance analysis that computes the SPIKE-distance, described in Kreuz et al. (2012). For the computation, the discrete sequence of spike times is transformed in a continuous temporal profile with one value per sample point. The values at each time point are derived from the differences in the spike times of the two input spike trains. Compared to the ISI-distance, the SPIKE-distance is more sensitive to spike timing. + compute SPIKE distance + + + + + + + + + + + A time-scale independent spike train distance analysis that computes the SPIKE synchronization distance, described in Kreuz et al. (2015). The distance detects coincidences in the spiking activity and can quantify the degree of synchrony in the input spike trains. The metric quantifies the overall fraction of coincidences. It is zero-valued if and only if the input spike trains do not contain any coincidences. It has a value of 1 if and only if each spike in every input spike train has one matching spike in all the other spike trains. + compute SPIKE synchronization + + + + + + + + + + compute STFT + A time-frequency analysis that computes the short-time Fourier transform (STFT) of the input time series. The analysis divides the input time-domain signal into short segments with equal time and computes the Fourier transform for each segment. The output is a sequence of coefficients of complex sinusoids, each representing a frequency component in the input signal at a distinct time segment. Therefore, this provides the the time-localized frequency and phase information of the input. The segments can be windowed using a window function. + compute short-time Fourier transform + + + + + + + + + + A spectrogram analysis that uses the Morlet wavelet transform on the input to obtain the time-frequency information used to build the spectrogram. + compute spectrogram (Morlet wavelet method) + + + + + + + + + + A spectrogram analysis that uses a multitaper approach to obtain the time-frequency information from the input and that is used to build the spectrogram. + compute spectrogram (multitaper method) + + + + + + + + + + compute spectrogram (STFT method) + A spectrogram analysis that uses the short-time Fourier transform (STFT) on the input to obtain the time-frequency information used to build the spectrogram. + compute spectrogram (short-time Fourier transform method) + + + + + + + + + + + A spike train synchrony analysis that computes the Spike-contrast measure using the method described by Ciba et al. (2018). Spike-contrast is a time-scale independent measure of spike synchrony. The input is a set of parallel spike train data recorded from a population of neurons. The algorithm is based on the temporal "contrast" (activity vs. non-activity in certain time bins). The computation outputs a single synchrony value (comparable to a spike train distance) and a synchrony curve showing the value of Spike-contrast as a function of the bin size. + compute Spike-contrast + + + + + + + + + + + A spike-field coherence analysis that uses the method described in Fries et al. (2001) to compute the coherence between the spike train and the LFP. For the computation, first a spike-triggered average (STA) is obtained between the spike train and the LFP time series. Then, the power spectrum is obtained for each of the LFP segments used for the computation of the STA. These spectra are averaged to obtain the spike-triggered power spectrum. The SFC is then computed as the ratio of the power spectrum of the STA over the spike-triggered power spectrum. + compute spike-field coherence (Fries method) + + + + + + + + + + compute SFC (multitaper method) + A spike-field coherence analysis that uses a multitaper approach to compute the coherence between the spike train and the LFP. + compute spike-field coherence (multitaper method) + + + + + + + + + + compute SFC (Welch method) + + A spike-field coherence analysis step that uses the method by Welch (1967) to compute the coherence between the spike train and the LFP. + compute spike-field coherence (Welch method) + + + + + + + + + + compute STTC + + A spike train correlation analysis that computes the spike time tiling coefficient (STTC) as described by Cutts and Eglen (2014). The STTC measures the pairwise correlation between two input spike trains, and has advantages over the related correlation index: it is not confounded by the firing rate, it distinguishes lack of correlation from anti-correlation, periods without neural activity don't add to the correlation, and it is sensitive to firing patterns. The computation is based on a synchronicity window parameter, that is used to define short time windows around each spike that are used in the computation (spike time tiling). + compute spike time tiling coefficient + + + + + + + + + + An autocorrelation analysis that computes the autocorrelation histogram for a input spike train. The histogram is obtained by sliding a time window that is discretized into smaller time intervals (bins) centered on a spike (corresponding to the lag zero). The spike count in each bin is obtained. Therefore, this binning process measures the number of spikes occurring at various time lags relative to the center spike. The histogram window is slidden over each spike in the input spike train, and the spike count in each bin is accumulated to produce the autocorrelation histogram output. The width of the bin interval is controlled by a parameter. + compute spike train autocorrelation histogram + + + + + + + + + + + An analysis step that computes the autocorrelation time of a binned spike train input (spike train autocorrelation time scale). The computation follows the method described by Wieland et al. (2015). + compute spike train autocorrelation time scale + + + + + + + + + + + + + + + + compute CCH + A cross-correlation analysis that computes the cross-correlation histogram (CCH) for a pair of input spike trains. The CCH shows how often spikes in the reference spike train occur before or after spikes in the reference spike train, at distinct lag intervals. For the computation, the spike trains are aligned in time. The histogram is obtained by sliding a time window that is discretized into smaller time intervals (bins) centered on a spike of the first (reference) input spike train (corresponding to the lag zero). The spike count of the second (target) spike train input is then obtained in each bin. Therefore, this binning process measures the number of spikes in the target spike train occurring at various time lags relative to the spikes in the reference spike train. The histogram window is slidden over each spike in the reference spike train, and the spike count in each bin is accumulated to produce the CCH output. The width of the bin interval is controlled by a parameter. + compute correlogram + compute cross-correlogram + compute spike train cross-correlation histogram + + + + + + + + + + compute CCH (Eggermont method) + + A computation of the cross-correlation histogram (CCH) for a pair of binned input spike trains using the method described in Eggermont (2010). The formula is valid for binned spike train inputs with at most one spike per bin, and returns the cross-correlation coefficient for the lags considered (range -1 to 1). + compute correlogram (Eggermont method) + compute cross-correlogram (Eggermont method) + compute spike train cross-correlation histogram (Eggermont method) + + + + + + + + + + + + + + + + + An analysis step that computes the Fano factor (FF) for a set of input spike trains. For each input spike train, the spike count is obtained. The Fano factor is defined as the ratio of the variance of the spike count to the mean spike count, across all spike trains. The Fano factor is usually computed for spike trains representing the activity of the same neuron over different trials. The value is interpreted as the higher the Fano factor value, the larger the cross-trial non-stationarity. For a stationary Poisson process, the Fano factor has value equal to 1. + compute spike train Fano factor + + + + + + + + + + A spike train correlation analysis that computes the Pearson correlation coefficient between two spike train inputs. The Pearson correlation coefficient is a real value that quantifies the linear relationship between the two spike trains. It has range [-1, 1], where 1 indicates a perfect positive linear relationship, -1 indicates a perfect negative linear relationship, and 0 indicates no linear relationship. For the computation, the input spike trains are discretized into time intervals (bins), and the spike count is obtained in each bin. The Pearson correlation coefficient is obtained by normalizing the covariance between the binned spike trains: the covariance is divided by the product of the standard deviation of each. + compute spike train Pearson correlation coefficient + + + + + + + + + + + + + + + + An analysis step that computes the time histogram of a spike train. If the spike count in a bin is divided by the duration of the bin, this can be used to estimate the instantaneous firing rate at the bin interval. + compute spike train time histogram + + + + + + + + + + compute STA + A triggered average analysis that uses spike times as triggers to obtain the average of a signal around each spike (spike-triggered average). + compute spike-triggered average + + + + + + + + + + + + + + + + compute STA + A triggered average analysis that uses spike times as triggers to average the local field potential (LFP) signal. The LFP is the low-frequency component of the potential recorded within a specific region of the brain using extracellular electrodes. The output of the method will provide an estimation of the average LFP voltage around each spike, i.e., the spike-triggered average of the LFP signal. + compute spike-triggered local field potential average + + + + + + + + + + A phase analysis that computes the phase angle values of an analytic signal input (or from the analytic signal obtained from an input time series) at the time points where spikes occurred. The spike times are defined in a spike train input. The output is an array with the phase angle at each spike time in the input spike train (spike-triggered phases). + compute spike-triggered phase + + + + + + + + + + A spike waveform analysis that computes the average across two or more spike waveform inputs. For the computation, the mean value across all inputs is obtained for each time point in the sampled spike waveform. This is frequently used to reduce noise across multiple spike waveform samples of a single neuron. + compute spike waveform average + + + + + + + + + + compute spike waveform SNR + + A spike waveform analysis that computes the signal-to-noise ratio (SNR) for a set of input spike waveforms according to Hatsopoulos (2007). The SNR is defined as the difference in mean peak-to-trough voltage divided by twice the mean standard deviation (SD).The mean SD is obtained by averaging the SDs computed for each time point in the spike waveform. + compute spike waveform signal-to-noise ratio + + + + + + + + + + A spike waveform analysis that computes the variance across two or more spike waveform inputs. For the computation, the value of the variance across all inputs is obtained for each time point in the spike waveform. + compute spike waveform variance + + + + + + + + + + A spike waveform analysis that computes the width of a spike waveform input. The computation takes two time points of interest (e.g, the times of the peak and the trough), and the width is the difference with respect to the time points (e.g., number of time points in between or time interval). + compute spike waveform width + + + + + + + + + + compute SD + A dispersion statistical analysis that computes the standard deviation (SD), i.e., the square root of the variance. The SD indicates the average distance of each data point from the mean. + compute standard deviation + + + + + + + + + + compute SEM + A dispersion statistical analysis that computes the standard error of the mean (SEM). The SEM is the standard deviation of the sampling distribution of the sample mean. It provides an estimate of how much the sample mean is expected to fluctuate around the true population mean. Smaller SEM values indicates that the sample mean is a more accurate estimate of the population mean. The SEM decreases as the sample size increases, as larger samples provide a more reliable estimate of the population mean. + compute standard error of the mean + + + + + + + + + + + A time-frequency analysis that computes the Stockwell transform (S transform) of the input time series. The S transform generalizes the short-time Fourier transform (STFT) and extends the continuous wavelet transform (CWT). The main difference is that STFT uses a constant window width for all frequencies. The S transform is based on a moving and scalable localizing Gaussian window. Therefore, the window is frequency-dependent (adaptive windowing), which results in better time resolution in higher frequencies and better frequency resolution at lower frequencies. This makes the S transform more suitable to detect transient signals in high frequencies. The computation is computationally expensive, although fast algorithms are available. + compute S transform + compute Stockwell transform + + + + + + + + + + + + + true + + + + A conditional Granger causality (GC) analysis that computes the GC measures in the time domain. + compute time domain conditional Granger causality + + + + + + + + + + + + + true + + + + + A pairwise Granger causality (GC) analysis that computes measures of GC between two inputs in the time domain. The computation involves fitting two separate autoregressive (AR) models to the input data and comparing their fit to determine if one time series can predict the other. The quality of the fit is assessed by the variance of the residuals, with GC defined as the natural logarithm of the ratio of the residual variances from the two AR models. The first AR model is univariate, predicting the future values of one time series (e.g., the first) only from its past values. The second AR model is bivariate, predicting the future values of the first time series from its past values as well as the past values of the second time series. If the bivariate model reduces the variance of the residuals (ratio greater than 1), the GC value will be positive, indicating that the second time series Granger causes the first (directional GC estimate from the second to the first). The same method is used to predict the second time series from the first, yielding the directional GC estimate from the first to the second time series. The order of the AR model is defined as parameter, and optimal values can be estimated using optimization techniques. + compute time domain pairwise Granger causality + + + + + + + + + + + + + false + + + compute TE + + A functional connectivity analysis that computes a measure of transfer entropy (TE) between two input time series. TE measures the directional transfer of information between the time series. It extends Granger causality, and is able to detect non-linear forms of interaction. + compute transfer entropy + + + + + + + + + + A firing rate analysis that computes a tuning curve. The tuning curve describes the firing rate of a neuron as a function of a continuous attribute (e.g., orientation of a visual grating stimulus). + compute tuning curve + + + + + + + + + + + + + false + + + compute unbiased squared PLI + + A phase lag index (PLI) analysis that computes an unbiased estimate for the squared PLI following Vinck et al. (2011). The direct PLI estimator is positively biased, especially when the sample sizes (i.e., number of trials) are small. The unbiased squared PLI is computed by averaging all pairwise products of the signs computed across the repetitions. Pairs with identical observations are excluded. The unbiased squared PLI is less affected by small-sample size biases. + compute unbiased squared phase lag index + + + + + + + + + + + A time-scale dependent spike train distance analysis that computes the van Rossum distance introduced in van Rossum (2001). For the computation, each spike in the input spike trains is convolved with an exponential kernel, producing continuous function representations of the input spike trains. The time scale parameter of the distance is set by the time constant of the exponential kernel. The distance is then obtained as the Euclidean distance of the convolved spike trains. + compute van Rossum distance + + + + + + + + + + A dispersion statistical analysis that computes the variance, i.e., the average of the squared differences from the mean. + compute variance + + + + + + + + + + + A time-scale dependent spike train distance analysis that computes the Victor-Purpura distance, introduced in Victor & Purpura (1996). The metric defines the distance between two spike train inputs with respect to the minimum cost of transforming one spike train into the order considering three operations: spike insertion, spike deletion and shifting a spike by some interval. The first two operations have a fixed cost equal to 1. The latter depends on a cost per time unit parameter, which sets the time scale of the analysis. + compute Victor-Purpura distance + + + + + + + + + + + + + false + + + compute WPLI + + A phase lag index (PLI) analysis that computes the weighted PLI (WPLI) following Vinck et al. (2011). The original PLI (Stam, 2007) is discontinuous, and small perturbations can turn phase lags into leads (and vice versa). Therefore, this hinders its capacity to detect changes in phase synchronization of small magnitude. The WPLI extends the PLI to weight the contributions of the phase leads and lags by the magnitude of the imaginary component of the cross spectral density. Therefore, these increases the power to detect changes in phase synchronization. The WPLI ranges between 0 and 1. A WPLI of zero means that there is no imbalance in the first time series leading or lagging the second (i.e., the total weight of all leading relationships is equal to the total weight of lagging relationships). A value greater than zero means an imbalance in the likelihood of leading or lagging. A WPLI of 1 indicates perfect phase locking, and that the first time series only leads or only lags. + compute weighted phase lag index + + + + + + + + + + compute EP + An analysis step that computes the evoked potential (EP). The EP is the neural activity (e.g., local field potential or electroencephalogram voltages) around a presented stimulus (e.g., auditory, visual, electrical). Usually, the stimulus is presented repeatedly across multiple trials, obtaining multiple evoked potential waveforms that can be averaged to cancel the noise. It is an event-related potential (ERP) obtained from presenting a stimulus rather than spontaneous behavioral events. + compute evoked potential + + + + + + + + + + + + + true + + + + A Granger causality (GC) analysis that computes a measure of conditional GC between the inputs. The conditional GC is the causality between two inputs (e.g., two time series) while controlling for the influence of an additional input (e.g., a third time series). This allows a more complete understanding of the causal relationships in multivariate time series data. + conditional Granger causality analysis + + + + + + + + + + A confidence interval statistical analysis that computes the confidence interval using techniques to generate multiple samples from the (observed) data input(s). + confidence interval with resampling analysis + + + + + + + + + + A statistical analysis that computes a confidence interval (CI). The CI is a measure providing a range of values of a parameter, derived from the input (sample) data, that is likely to contain the true value of the parameter in the population with a specified level of confidence. The level of confidence is specified as a parameter to the method. For example, a 95% confidence interval means that if the same population is sampled multiple times, approximately 95% of the intervals calculated from those samples will contain the true population parameter. Confidence intervals are used to estimate parameters such as the mean and are essential for making inferences about the population based on sample data. The output contains the upper and lower limits of the CI. + confidence interval statistical analysis + + + + + + + + + + + A spike train generation where the output spike trains will have spikes that are correlated in time. These methods can be used to generate spike trains with patterns in their activity. + correlated spike times generation + + + + + + + + + + + + + + + + + + + + + + + + + true + + + + + + false + + + + + + true + + + + + + true + + + An analysis step that computes a measure of correlation between two inputs. Correlation is a measure that quantifies the strength to which two variables change together. It is a scaled version of the covariance, and the values are restricted to the -1 to +1 interval. Between time series, it is computed in the time domain. + correlation analysis + + + + + + + + + + An analysis step used to compute a measure of covariance from two inputs. The covariance indicates the extent to which the two inputs change together. If the greater values of one variable mainly correspond with the greater values of the other variable, and the same applies to the lesser values, then the covariance is positive. Conversely, if greater values of one variable mainly correspond to the lesser values of the other variable, then the covariance is negative. + covariance analysis + + + + + + + + + + + + + + + + + + + true + + + + + + true + + + + + + true + + + + + + true + + + An analysis step used to compute a measure of cross-correlation, i.e., the correlation of two inputs computed for distinct time lags of the first to the second. The computation produces the cross-correlation value for every lag considered. + cross-correlation analysis + + + + + + + + + + CPSD analysis + A spectral density analysis that computes the cross power spectral density (CPSD) of two inputs, i.e., the distribution of their power across the different frequency components per unit frequency. The CPSD shows in the frequency domain how the two inputs are correlated in the time domain, and is equivalent to the Fourier transform of the cross-correlation function between the two signals. If the inputs are not correlated, the CPSD will be flat across the frequencies. A peak suggests that the signals are correlated at that frequency. The CPSD is often referred to as cross-spectrum. + cross power spectral density analysis + + + + + + + + + + CSD analysis + An analysis step used to analyze extracellular electrical potentials (e.g., local field potentials or evoked potentials) recorded from multiple locations, enabling the estimation of the current sources responsible for generating these potentials. The methods can be applied to data recorded from different electrode configurations: laminar probe-like electrodes (1D methods), microelectrode array-like electrodes (2D methods) or electrodes configurations recording from a volume (e.g., multiple laminar probes or array electrodes with shanks with multiple depths; 3D methods). The output of the current source analysis provides the spatial map showing where currents are entering (sources) and leaving (sinks) the neural tissue. For each point in the map, a quantitative value indicates the magnitude of the current density at that point. + source imaging analysis + source localization analysis + current source density analysis + + + + + + + + + + An analysis step that generates new data entities. This can be done using other input data as a start (e.g., generating a spike train surrogate from spike trains obtained from experimental recordings) or generate new data using algorithms that take specific parameters (e.g., generating a spike train using a probability distribution defined by specific parameters). + data generation + + + + + + + + + + A data transformation that adjusts the ranges and distributions of the values in the input data. This can be used to transform data measured in distinct (i.e. not directly comparable) scales to a common (i.e. comparable) scale. + data normalization + + + + + + + + + + A data transformation that uses statistical techniques to remove noise and fluctuations from the input data to reveal underlying trends and patterns. + data smoothing + + + + + + + + + + An analysis step that takes one or more inputs and modifies the contents, such that it fits a particular purpose. The data transformation steps are frequently used during pre-processing the input data for the analyses. Usually, a data transformation will not change the main representation or quality of the inputs. For example, a digital filtering step will remove certain frequency components from a time series. However, the output will resemble the original input with respect to shape or physical units. In addition, the inputs can also be converted to other formats or representations that are needed for a particular analysis step. For example, spike trains can be discretized into small intervals (binning) or the dimensionality of the input can be reduced using principal component analysis. The data transformation is in contrast to steps that perform computations that take the input and generate a derived measure with new information. For example, when computing the mean firing rate from a spike train, a single scalar value is obtained from the spike count in the input data. + data transformation + + + + + + + + + + A data transformation that removes a trend (i.e., a change in the mean over time) from an input time series. + detrending + + + + + + + + + + A data transformation that processes digital signal inputs (i.e., sampled time series) to attenuate or amplify specific frequency components. Digital filters can be designed using various methods, achieving distinct frequency responses and stability. + digital filtering + + + + + + + + + + A data transformation that obtains a low-dimensional (simplified) representation of the high-dimensional input data. This step retains important information in the input data while minimizing redundancy and noise. + dimensionality reduction + + + + + + + + + + + + true + + + + + An analysis step where the output provides information on the direction of influence in the relationships among the inputs (e.g., in the cross-correlation histogram, it is possible to analyze the timing of the spikes of the first input spike train with respect to the timing of the spikes of the second input spike train, i.e., whether they likely occur before or after). + directed analysis + + + + + + + + + + A statistical analysis that computes a measure that represents the variability in the input data. It indicated the degree to which the data points differ from the central tendency. + dispersion statistical analysis + + + + + + + + + + + + + + + + + + + + + + + + + + + A SPADE analysis that uses the 3d-SPADE implementation as defined in Stella et al. (2019). The 3d-SPADE analysis considers spatio-temporal patterns (i.e., not restricted to synchronous patterns), and the pattern signature used for statistical testing considers the size, number of occurrences and duration of a pattern. + execute 3d-SPADE analysis + + + + + + + + + + + + + + + + + + + false + + + + A neuronal activity pattern detection analysis that uses the Analysis of Sequences of Synchronous EvenTs (ASSET) method defined in Torre et al. (2016). ASSET is an automatized test to identify the sequential activations of groups of neurons that repeat in time. The identification of the repeated sequences is possible by computing the intersection matrix. The input spike data is discretized into smaller intervals (bins), and the overlap of neuronal activity at each bin pair is obtained as a matrix. When a sequence of activations exists and repeats in time, a characteristic diagonal structure appears in the matrix. + +The ASSET analysis provides a robust statistical test to automatically identify the diagonal structures and to provide the neurons and their activation pattern in each repeated sequence. Overall, the analysis is composed by 6 substeps: + +1. Compute the intersection matrix (IMAT) from a set of input spike trains, using a specified bin size to discretize the data. +2. Obtain the probability matrix (PMAT). +3. Obtain the joint probability matrix (JMAT). +4. Extract significant entries in both PMAT and JMAT using specified thresholds, obtaining the mask matrix (MMAT). +5. Obtain the cluster matrix (CMAT) by using DBSCAN to cluster the significant entries in the MMAT to find each diagonal structure. Parameters for DBSCAN control the clustering result. A modified distance metric is used. +6. From the identified clusters (each a single diagonal structure in the IMAT), obtain the neuronal composition and the order of activation, producing the final neuronal activity patterns as output. + execute ASSET analysis + + + + + + + + + + + + + false + + + execute CAD analysis + + A neuronal activity pattern detection analysis that uses the Cell Assembly Detection (CAD) method as defined in Russo & Durstewitz (2017). CAD allows detecting spatio-temporal spike patterns at different time scales, levels of precision, and with arbitrary internal organization. The analysis identifies patterns with different delays between the spikes (within a window determining the minimum and maximum lags), and is performed in two steps using an agglomerative clustering algorithm. First, significant pairwise correlations are identified, which is followed by the clustering procedure that progressively finds interactions of higher order. At each agglomeration step, the method can filter out patterns involving the same neurons, keeping the most significant pattern (significance pruning). In an additional pruning step, assemblies part of a larger assembly can also be eliminated (controlled by the subgroup pruning parameter). The algorithm stops when the detected assemblies reach their maximum size (determined by a parameter). The statistical test assumes independence under non-stationarity and Poisson distribution of the input spike trains. + execute Cell Assembly Detection analysis + + + + + + + + + + + A SPADE analysis that uses the SPADE implementation as defined in Quaglio et al. (2017). This is the extension of SPADE to consider spatio-temporal patterns (i.e., patterns not restricted to synchronous spiking). In the non-3d SPADE analysis, the pattern signature used for statistical testing considers only the size and number of occurrences of a pattern. + execute non-3d-SPADE analysis + + + + + + + + + + + execute UE analysis (analytical method) + + + + + A unitary event (UE) analysis that uses the analytical approach to determine the significance of the empirical coincidences in binned spike train data, as defined in Grün et al. (1999, 2002a, 2002b, and 2003). The analytical method tests if the number of empirical coincidences is consistent with the coincidence distribution resulting from independent processes. This distribution can be expressed analytically assuming that the input spike trains follow Poisson statistics. The UEs can be determined trial by trial, where the analytical expectancy is computed for each trial and then summed over all trials, or by averaging over all trials (according to Grün, 2003). + execute Unitary Event analysis (analytical method) + + + + + + + + + + execute UE analysis (Monte Carlo method) + + A unitary event (UE) analysis that uses a Monte Carlo approach based on spike train surrogates to determine the significance of the empirical coincidences in binned spike train data, according to Grün (2009). The Monte Carlo method does not rely on the assumption that the input spike data follows Poisson statistics. For the assessment of significance, the distribution of expected coincidences is determined by surrogates (spike train randomization) in each trial, and then summed over trials. The number of surrogates is determined by a parameter. + execute Unitary Event analysis (Monte Carlo method) + + + + + + + + + + + + + + + + + An analysis step that computes interactions between the neural activity represented by distinct local field potential (LFP) signals (e.g., LFP obtained from different electrodes, or distinct LFP frequency bands). + field-field coupling analysis + + + + + + + + + + FIR filtering + A digital filtering that uses a filter whose impulse response (i.e., the response of the filter to a brief input impulse) decays to zero after a finite amount of time. Therefore, the output of the filter depends on a finite number of past samples. The finite impulse response (FIR) filters are stable and can be designed such that they do not distort the phase of the signal. However, they have a higher computational cost. + finite impulse response filtering + + + + + + + + + + An analysis step used to compute a measure quantifying the firing rate of one or more neurons. The firing rate is the number of action potential (spikes) that a neuron fires per time unit and is defined with a unit of frequency (e.g., Hz or spikes/s). + firing rate analysis + + + + + + + + + + + + true + + + + + An analysis step that analyzes the input(s) with respect to its(their) frequency content. + frequency domain analysis + + + + + + + + + + + + + true + + + + A pairwise Granger causality (GC) analysis that computes measures of GC between two inputs in the frequency domain. This is an extension of the GC concept in the time domain, and the measures of GC are obtained for the different frequency components of the inputs, according to Geweke (1982). The computation of the frequency-domain GC measures is based on two elements: the noise covariance matrix and the spectral transfer matrix. These can be estimated either with parametric or non-parametric methods. For the parametric estimation, an autoregressive model is fit and the Fourier transform of the autoregressive coefficients is used to obtain the spectral transfer matrix. For the non-parametric estimation, the cross-spectral density (CSD) matrix is obtained (using methods for CSD estimation such as multitapering or wavelet), and the CSD matrix is factorized to obtain the noise covariance and spectral transfer matrices. + frequency domain pairwise granger causality analysis + + + + + + + + + + A data transformation that converts a time series input from the time to the frequency domain, i.e., reveal the different frequency components that make up the original signal. + frequency domain transformation + + + + + + + + + + + + + + + + FCA + An analysis step that computes measures of functional connectivity. Functional connectivity refers to statistical dependencies and patterns of synchronization between the neural activity that indicate the functional interactions and co-activations that are relevant for the function of the nervous system (e.g., the interactions between different brain regions). It does not imply direct physical connections. + functional connectivity analysis + + + + + + + + + + + + A correlated spike times generation that produces spike trains using a compound Poisson process (CPP) according to Staude et al. (2010). The CPP is a model for parallel and correlated processes with Poisson spiking statistics at predefined firing rates. + generate CPP + generate compound Poisson process + + + + + + + + + + generate ISI-D surrogate + + A spike train surrogate generation step where each spike is displaced according to the interspike interval (ISI) distribution sampled from the input spike train. + generate joint interspike interval dithering surrogate + + + + + + + + + + + A spike train surrogate generation step where the interspike intervals (ISIs) of the input spike train is randomly sorted. This preserves the ISI distribution and spike count as in the original spike train input, but destroys temporal dependencies and firing rate profile. + generate interspike interval shuffling surrogate + + + + + + + + + + generate JISI-D surrogate + + A spike train surrogate generation step where spikes from adjacent interspike intervals (ISIs) are dithered according to the joint-ISI (JISI) probability distribution. The distribution is obtained from the input spike train by computing the JISI histogram (i.e., a two-dimensional histogram that shows the frequency of ISIs with a given duration that are immediately followed by intervals with another duration). Due to non-stationarities in the input spike train and/or its limited duration, it is difficult to accurately estimate the underlying JISI probability distribution. Therefore, a 2D-Gaussian smoothing is applied to the JISI histogram (with a variance determined by parameter). Dithering a spike according to this (smoothed) two-dimensional histogram involves moving the spike along the anti-diagonal of the JISI distribution. The dithering time is defined by a parameter. + generate joint interspike interval dithering surrogate + + + + + + + + + + A data generation that constructs a Morlet wavelet considering the selected parameters (i.e., sampling frequency, fundamental frequency, and number of cycles per frequency). The Morlet wavelet is composed by a complex exponential multiplied by a Gaussian window. The output data contains the discrete time points and the corresponding wavelet values. + generate Morlet wavelet + + + + + + + + + + A random spike times generation that uses a gamma probability distribution to produce spike trains where the firing rate varies over time. + generate non-stationary gamma process + + + + + + + + + + A random spike times generation that uses a Poisson probability distribution to produce spike trains where the firing rate varies over time. A dead time can be specified as parameter (i.e., an interval where no spikes can occur, which is analogous to the neuronal refractory period). + generate non-stationary Poisson process + + + + + + + + + + + A correlated spike times generation that produces a multidimensional Poisson single interaction process (SIP) plus independent Poisson processes, according to Kuhn et al. (2003). The Poisson SIP consists of Poisson time series that are independent except for events that are simultaneous in all of them. + generate SIP + generate single interaction process + + + + + + + + + + + A spike train surrogate generation step that keeps the spike count of the input spike train, but the spike times in the surrogate spike train output are randomly chosen within the duration interval of the input spike train. + generate spike time randomization surrogate + + + + + + + + + + + A spike train surrogate generation step that displaces the whole input spike train by a random amount of time (independent for each surrogate generated). The amount of displacement is specified as a parameter (dither time), and occurs in a window (-dither time, dither time). This surrogate maintains the ISIs and the temporal correlations within the spike train. + generate spike train dithering surrogate + + + + + + + + + + A random spike times generation that uses a gamma probability distribution to produce spike trains with a constant firing rate. + generate stationary gamma process + + + + + + + + + + A random spike times generation that uses a inverse Gaussian probability distribution to produce spike trains with a constant firing rate. + generate stationary inverse Gaussian process + + + + + + + + + + A random spike times generation that uses a log-normal probability distribution to produce spike trains with a constant firing rate. + generate stationary log-normal process + + + + + + + + + + + A random spike times generation that uses a Poisson probability distribution to produce spike trains with a constant firing rate. A dead time can be specified as parameter (i.e., an interval where no spikes can occur, which is analogous to the neuronal refractory period). + generate stationary Poisson process + + + + + + + + + + + A spike train surrogate generation step that shifts the entire spike train (containing the data of a single experimental trial) by an amount randomly chosen from a uniform distribution. The amount of displacement is specified as a parameter (dither time), and occurs in a window (-dither time, dither time). The input is a collection of spike trains of the same neuron, containing the spiking activity during different experimental trials. The amount of shift is independently chosen across trials and neurons. This surrogate preserves the ISI distribution and temporal correlations within the single-trial spike train. + generate trial shifting surrogate + + + + + + + + + + + A spike train surrogate generation step where the the spike trains of single-trial activity of one of the neurons are randomly permuted, so that each trial is no longer paired with the corresponding trial of the other neuron, but with a randomly selected one. The input is a collection of spike trains with multitrial activity data of multiple neurons recorded in parallel. + generate trial shuffling surrogate + + + + + + + + + + generate UD surrogate + + A spike train surrogate generation step that displaces each spike time in the input spike train according to a uniform distribution centered on the spike. The displacement occurs in a time window around the spike defined by a parameter (dither time). + generate uniform spike dithering surrogate + + + + + + + + + + generate UDD surrogate + + A spike train surrogate generation step that displaces each spike time in the input spike train according to a uniform distribution centered on the spike. The displacement occurs in a time window around the spike defined by a parameter (dither time) that is constrained to the intervals between adjacent spikes to avoid two spikes closer than a dead time (specified by parameter). This mimics the refractory period behavior of neurons, where the neuron cannot fire additional spikes for a short interval after one spike. + generate uniform spike dithering surrogate with dead time + + + + + + + + + + + A spike train surrogate generation step that shuffles the entries of a binned spike train within exclusive maximal displacement windows. The maximal displacement is specified by parameter, and represents the maximum number of bins that a spike can be displaced within the window. + generate bin shuffling within exclusive windows surrogate + generate window shuffling surrogate + + + + + + + + + + + + + true + + + + + + true + + + GC analysis + A functional connectivity analysis that computes measures of Granger causality (GC). GC is a statistical concept where the future values of a time series are predicted based on its past values and the past values of other time series. GC quantifies bi-directional interactions between the inputs, determining the directional influence from one input to another. For example, with two inputs, GC measures how much the first input influences the second and vice versa (directional GC measure). This provides estimates of the directed connectivity between the inputs. It is also possible to compute associated measures, such as the instantaneous GC (a measure of interdependence between the inputs not accounted by their bi-directional interactions, such as shared neural input) and the total interdependence (the sum of all directional and instantaneous interactions between the inputs). The analysis can be performed in the time or frequency domains, and can take two (bivariate) or more inputs (multivariate). + Granger causality analysis + + + + + + + + + + IIR filtering + A digital filtering that uses a filter whose impulse response (i.e., the response of the filter to a brief input impulse) persists infinitely. Therefore, the output of the filter can depend on an infinite number of past samples. The infinite impulse response (IIR) filters can become unstable and distort the phase of the signal, but have a lower computational cost. + infinite impulse response filtering + + + + + + + + + + + + + + + + A firing rate analysis that computes the instantaneous firing rate, which is the estimate of the firing rate at a specific point in time. The instantaneous firing rate value can be obtained by several methods. + instantaneous firing rate analysis + + + + + + + + + + ISI analysis + An analysis step that computes or analyzes the interval between successive spikes in a spike train (interspike interval; ISI). + interspike interval analysis + + + + + + + + + + + + + + + + An interspike interval analysis that computes a measure describing the variability of the interspike intervals. The measure can assess how regular a neuron is firing. + interspike interval variability analysis + + + + + + + + + + A data smoothing that performs a convolution of the input data with a kernel function. This computes a weighted average of the data around the kernel. Several kernel types can be used for the smoothing (e.g., Gaussian, exponential) and the kernel shape is controlled by a width parameter. + kernel smoothing + + + + + + + + + + + + + + + + An analysis step that aims to identify underlying patterns and structures within time series or sequential data that are not directly observable. It involves modeling hidden (latent) variables that influence the observed data and their evolution over time. The analysis captures temporal dependencies and dynamics within the data, providing insights into the processes that generate the observed sequences. + latent dynamics analysis + + + + + + + + + + A data transformation that removes noise induced by the power line. + line noise cancellation + line noise removal + + + + + + + + + + MVL analysis + A phase-amplitude coupling (PAC) analysis that computes the mean vector length (MVL) measure. The MVL is based on a mean vector obtained from a time series defined in the complex plane, where the amplitude is taken from the high-frequency oscillation input and the phase from the low-frequency oscillation input. + mean vector length analysis + + + + + + + + + + + + true + + + + An analysis step that depends on assumptions on the interactions between the inputs to perform the computations. For example, the Granger causality analysis assumes linear relationships between the input signals. + model-based analysis + + + + + + + + + + + + false + + + + An analysis step that does not depend on assumptions on the interactions between the inputs to perform the computations. For example, it can consider probability distributions obtained from the input data. + model-free analysis + + + + + + + + + + + + true + + + + An analysis step that has three or more distinct inputs considered for the computation of the output (e.g., the time series with the local field potential signals recorded from three or more electrodes, used to compute the partial directed coherence). + multivariate analysis + + + + + + + + + + + + + true + + + + + + true + + + An analysis step that aims to identify a neuronal activity pattern, i.e., spikes of a group of neurons that occur in a specific spatio-temporal configuration. + neuronal activity pattern detection analysis + + + + + + + + + + + + + + + + An analysis step that computes measures to assess the regularity in the firing of a neuron. Neuronal firing regularity refers to the consistency or variability in the timing of action potentials (spikes) generated by a neuron. + spike time variability analysis + neuronal firing regularity analysis + + + + + + + + + + + + false + + + + An analysis step where the output does not provide information on the direction of influence in the relationships among the inputs (e.g., in the Pearson correlation coefficient computed between two spike trains, it is possible to know how strongly they tend to fire together. However, it is not possible to analyze the timing of the spikes of the first input spike with respect to the timing of the spikes of the second input spike train). + non-directed analysis + + + + + + + + + + + + + true + + + A Granger causality (GC) analysis that computes a measure of GC between two inputs. + pairwise Granger causality analysis + + + + + + + + + + PSTH analysis + A spike train time histogram analysis that computes the peristimulus time histogram (PSTH). PSTH is the time histogram of two or more spike trains containing repeated recordings of a single neuron around the time when an event of interest occurred. The event of interest can occur at any time point during the duration of the source spike trains. The distribution of the histogram corresponds to the distribution of the activity of the neuron with respect to the event across the repeated recordings. The event of interest can be an externally presented stimulus or a spontaneous behavioral event. If the histogram represents the neuronal activity after the stimulus presentation or event occurrence, this can be referred as post-stimulus time histogram. Conversely, if the histogram shows the activity of the neuron before the stimulus presentation or event, this can be referred as prestimulus time histogram. Finally, if the histogram considers a behavioral event (or an event that is not an externally presented stimulus), the histogram can be referred to as perievent time histogram (PETH). + peristimulus time histogram analysis + + + + + + + + + + + + + + + + + + + + + + + + + true + + + + + + false + + + + + + true + + + PAC analysis + A phase analysis that computes measures describing how the phase of a low-frequency oscillation modulates the amplitude of a high-frequency oscillation. Phase-amplitude coupling (PAC) can be used to investigate interactions between different frequency bands in the neural activity. + phase-amplitude coupling analysis + + + + + + + + + + An analysis step that computes measures related to the phase in the input data. Phase expresses the position of a time-varying signal relative to a fixed reference point in time. For periodic and oscillatory signals (e.g., a sine waveform), phase analysis involves determining the angle on the unit circle that corresponds to the current position within the waveform's cycle. This helps understanding the timing and synchronization of the oscillations in the input data. + phase analysis + + + + + + + + + + + + + + + + + + + true + + + + + + true + + + PLI analysis + A phase analysis that computes the phase lag index (PLI). The PLI measures the asymmetry of the distribution of the phase differences between two input time series, i.e., if there is an imbalance in the likelihood of the first time series leading or lagging the second time series. It is designed to be invariant to common sources, such as volume conduction and/or active reference electrodes. + phase lag index analysis + + + + + + + + + + + + + + + + + + + true + + + + + + false + + + + + + true + + + + + + true + + + PLV analysis + A phase analysis that computes the phase locking value (PLV). The PLV quantifies the consistency of the phase difference between two input time series across time (e.g., multiple experimental trials). + phase locking value analysis + + + + + + + + + + PSD analysis + A spectral density analysis that computes the power spectral density of an input, i.e., the distribution of power across the different frequency components of the input signal per unit frequency. It is equivalent to the Fourier transform of the autocorrelation function of the input signal. The computed power spectral density values can be corrected depending on the analysis returning the two-sided (i.e., with negative frequencies) or one-sided (i.e., positive frequencies only) PSD. The PSD is often referred to as spectrum. + auto spectral density analysis + power spectral density analysis + + + + + + + + + + PCA + A dimensionality reduction that reduces the dimensionality of the input data represented as a matrix with numerous rows and columns. It transforms the data into a set of principal components (PCs) that capture the maximum variance in the input. Each PC is a linear combination of the original variables and serves as a new axis in a lower-dimensional space. The PCs are orthogonal to each other, meaning they capture independent aspects of the input data's variability. + principal component analysis + + + + + + + + + + A spike train generation where the output spike trains will have random spike times, taken from a specific probability distribution. The generation process can produce spike trains where the firing rate is constant (stationary) or varies (non-stationary) over time. + random spike times generation + + + + + + + + + + A data transformation that changes the number of samples in the input data. + resampling + + + + + + + + + + + + + false + + + A neuronal activity pattern detection analysis that uses the Spatio-temporal PAttern Detection and Evaluation (SPADE) method. The SPADE analysis takes a set of parallel spike trains as input, and returns significant spatio-temporal neuronal activity (spike) patterns. + +The SPADE method consists of three substeps: + +1. Detect all putative patterns in the input data using the frequent item set mining (FIM) algorithm. This step requires the discretization of the input spike train data (binning). The bin size determines the temporal resolution of the analysis. + +2. The detected FIM patterns are evaluated for statistical significance, considering the null hypothesis of independence of the spike trains given the modulations by the firing rate. This substep is called Pattern Spectrum Filtering (PSF). For the testing, the patterns are pooled based on their signature: size and occurrence count (non-3d-SPADE) or size, occurrence count and pattern duration (3d-SPADE). The pattern spectrum collects the counts of patterns from each signature. The statistical test is done by a Monte Carlo approach, using spike train surrogates generated from the original data. The final output of this substep is the p-value spectrum, which has the same dimensions as the pattern spectrum. The p-value is computed as the ratio of surrogates containing patterns with that signature to the total number of realizations. + +3. Conditional test on the significant patterns to remove patterns arising from the overlap of true pattern spikes and chance spikes (pattern set reduction; PSR). + SPADE analysis + + + + + + + + + + An analysis step that computes measures describing the input data with respect to its frequency contents. + spectral analysis + + + + + + + + + + A spectral analysis that computes the density of a measure of the input(s) over the frequency spectrum. Density means that the measure value (e.g., power) for each frequency component is expressed per unit frequency. For example, for an input time series with voltages recorded from an electrode (measured in V), the power for each frequency component of the signal will be in V**2, while the power density will be in V**2/Hz. Therefore, the power values are normalized per unit frequency. This normalization allows for consistent comparisons of results from analyses with different frequency resolutions, as the spectral density remains unaffected by these variations. + spectral density analysis + + + + + + + + + + A time-frequency analysis that shows the power (or power density) of different frequency components of the input(s) as they change over time. This can be obtained for a single input (spectrogram) or for two distinct inputs (cross-spectrogram). + spectrogram analysis + + + + + + + + + + + + + + + + + + + + + + + + + true + + + + + + false + + + + + + true + + + SFC analysis + An analysis step that computes the spike-field coherence (SFC), which is the coherence computed between an input spike train and an input time series with the local field potential (LFP). Coherence is a measure of the association between the two inputs in the frequency domain. SFC can be used to quantify the relationship between the spiking activity of neurons and the oscillatory activity in the LFP. It represents the similarity of dynamics between the spike train and the voltage fluctuations produced by the neural activity in the local environment where the spiking activity was recorded. + spike-field coherence analysis + + + + + + + + + + + + + + + + + An analysis step that computes interactions between the spiking activity of neurons (individual or population) and the local field potential (LFP). + spike-field coupling analysis + + + + + + + + + + + + + + + + An analysis step that computes interactions between the spiking activity of one or more neurons. + spike-spike coupling analysis + + + + + + + + + + + + + + + + + + + true + + + + + + false + + + + + + true + + + An analysis step that computes measures estimating the correlation between spike train inputs. The correlation value is a normalized measure of covariation in the input spike train data, and reflects the strength and direction of the association: positive values mean that the inputs vary in the same direction, and negative values mean that the inputs vary in opposite directions (e.g., if the activity in one spike train increases, it decreases in the other). + spike train correlation analysis + + + + + + + + + + An analysis step that computes a measure comparing spike train inputs and providing an estimation of their similarity/dissimilarity. This is frequently done by computing spike train distances, which are measures that assign the notion of distance, i.e., the input spike trains are considered as elements in a space and, if similar, will be close together. + spike train dissimilarity analysis + + + + + + + + + + + + + + + + A data generation that produces one or more artificial spike trains using distinct statistical procedures to determine the spike times. + spike train generation + + + + + + + + + + A data generation that produces one or more spike train surrogates. A spike train surrogate is a new spike train derived from an input spike train (usually experimentally recorded). This is done using methods that alter the original spike times while trying to maintain specific statistical features of the original spike train (e.g., firing rate, interspike interval distribution). This is used to destroy fine temporal correlations in the spiking activity. + spike train surrogate generation + + + + + + + + + + An analysis step to assess synchronization in two or more spike train inputs that typically represent the activity of different neurons. Spike train synchronization refers to the temporal coordination of action potentials (spikes) between neurons, and describes the degree to which their spikes tend to occur at the same time. + spike train synchrony analysis + + + + + + + + + + A firing rate analysis that computes histograms of spike train data over time. The time histogram is obtained by discretizing the duration of the spike train into distinct time intervals (bins), and obtaining the spike count inside each bin. + +The histogram can show one of three different measures: + +* the spike count at each bin (across all spike trains); +* the mean spike count per bin (spike count in the bin divided by the number of spike trains); +* the firing rate (mean spike count in the bin divided by bin width). + spike train time histogram analysis + + + + + + + + + + An analysis step that is used to compute measures to describe or make inferences from spike waveform input data. A spike waveform refers to the shape of an electrical signal produced by a neuron when it fires an action potential. + spike waveform analysis + + + + + + + + + + A generic analysis step that computes measures to summarize and make inferences about the data input. These include measures of central tendency, dispersion and confidence intervals. The subclasses represent analysis steps that are usually used for aggregation of data and description of samples (e.g., compute the mean and standard deviation of the output of trial-by-trial analyses or across subjects). All analysis steps for specific applications related to the analysis of neuroelectrophysiology data itself (e.g., analyzing interspike interval variability) are covered by separate, independent classes. + statistical analysis + + + + + + + + + + TCA + A dimensionality reduction that reduces the dimensionality of the input data represented as a tensor (i.e., an array with multiple dimensions). The tensor component analysis (TCA) transforms the data into a set of low-dimensional tensors that capture the maximum variance in the input (tensor components). + tensor principal component analysis + tensor component analysis + + + + + + + + + + + + true + + + + An analysis step that analyzes the input(s) with respect to time. + time domain analysis + + + + + + + + + + A spectral analysis that computes measures describing the frequency content of the input(s) in a time-resolved manner. It allows the analysis of how different frequency components evolve over time, which is essential for non-stationary signals whose spectral characteristics change. The joint time-frequency representation helps in identifying transient features, frequency shifts, and other dynamic behaviors in the input(s). + time-frequency analysis + + + + + + + + + + + + + + + + + + + true + + + + + + false + + + + + + true + + + A spike train dissimilarity analysis that computes a spike train distance that depends on a parameter that determines a temporal scale in the spike trains to which the distance is sensitive. By computing the spike train distance for different time scale parameter values, it is possible to make inferences on the time scale that is discriminative in the neural activity. + time-scale dependent spike train distance analysis + + + + + + + + + + + + + + + + + + + true + + + + + + false + + + + + + true + + + A spike train dissimilarity analysis that computes a spike train distance that does not depend on a time scale parameter and that are time-scale adaptive. They can be used in scenarios where there are no previous knowledge of the relevant time scales in the input spike trains. + time-scale independent spike train distance analysis + + + + + + + + + + An analysis step where a signal is averaged to obtain a value around a point in time representing an event of interest (i.e., a trigger). For each event time, a finite duration window of the input time series is selected around the event time. An average for each time point is then obtained across all windows. + triggered average analysis + + + + + + + + + + + + + false + + + UE analysis + + A neuronal activity pattern detection analysis that uses the Unitary Event (UE) method. UE is a statistical technique focused on identifying synchronous activity among neurons, known as unitary events (UEs), which occur more frequently than an expectation based solely on firing rates. The input can contain spike trains from one or more neurons and one or more trials. For the computation, the input spike train data is discretized into small time intervals (bins), and coincidences across the different spike trains are computed. The significance of the number of observed (empirical) coincidences is determined by comparing to an expected number given the firing rates of the neurons. To account for possible non-stationarities in the firing rates, the method uses a sliding temporal window over the data, whose width is specified as parameter. Therefore, a measure of significant spike synchrony (joint surprise) is obtained for each window. The statistical evaluation can be done using either analytical methods or Monte-Carlo testing with surrogate spike data. The output presents the significant coincidences (UE patterns) and the participant neurons. + Unitary Event analysis + + + + + + + + + + + A time-frequency analysis that uses wavelets to obtain the time-frequency representation of the time series input. The wavelet is a rapidly decaying oscillation. 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V. Shenoy, & M. Sahani, "Gaussian-Process Factor Analysis for Low-Dimensional Single-Trial Analysis of Neural Population Activity," J. Neurophysiol., vol. 102, no. 1, pp. 614-635, 2009 + Yu et al. (2009) + + + + + + + + + + The analysis purpose of computing a correlation measure. + correlation purpose + + + + + + + + + + The analysis purpose of smoothing the data. + data smoothing purpose + + + + + + + + + + The analysis purpose of computing a distance metric. + distance purpose + + + + + + + + + + The analysis purpose of assessing the interactions between inputs with local field potential data. + field-field coupling purpose + + + + + + + + + + The analysis purpose of estimating functional connectivity. + functional connectivity purpose + + + + + + + + + + The analysis purpose of estimating the instantaneous firing rate. + instantaneous firing rate purpose + + + + + + + + + + The analysis purpose of estimating latent dynamics. + latent dynamics purpose + + + + + + + + + + The analysis purpose of assessing the regularity in neuronal firing. + neuronal firing regularity purpose + + + + + + + + + + The analysis purpose of assessing neuronal synchronization. + neural synchronization purpose + + + + + + + + + + The analysis purpose of assessing interactions between spiking activity and the local field potential. + spike-LFP coupling purpose + spike-field coupling purpose + + + + + + + + + + The analysis purpose of assessing interactions between the spiking activity of neurons. + spike-spike coupling purpose + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + An artifact removal step that aims to identify and remove input spike waveforms that differs significantly from other waveforms in the input. This include spike waveforms with too late peak or where the action potential does not rise towards the peak of other waveforms. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/doc/releases/0.1.0/parameters/index.html b/doc/releases/0.1.0/parameters/index.html new file mode 100644 index 0000000..9547320 --- /dev/null +++ b/doc/releases/0.1.0/parameters/index.html @@ -0,0 +1,2018 @@ + + + Neuroelectrophysiology Analysis Ontology - Analysis Parameters + + + + + + + + + +
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    language en
    +

    Neuroelectrophysiology Analysis Ontology - Analysis Parameters

    +

    Release: 2024-12-06

    + + +
    +
    This version:
    +
    http://purl.org/neao/0.1.0/parameters#
    +
    Latest version:
    +
    http://purl.org/neao/parameters#
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    Revision:
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    0.1.0
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    Issued on:
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    2024-12-06
    +
    Authors:
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    Cristiano Köhler, Forschungszentrum Jülich
    Michael Denker, Forschungszentrum Jülich
    + +
    License:
    https://creativecommons.org/licenses/by/4.0/ +
    Visualization:
    Visualize with WebVowl
    +
    + +Provenance of this page
    +
    +
    +
    +Ontology Specification Draft +
    +
    +
    + + +

    Introduction back to ToC

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    This module in the Neuroelectrophysiology Analysis Ontology (NEAO) contains classes that represent parameters in the analyses.

    + +

    A parameter is an information entity that controls the behavior of an analysis step, but does not provide data that is used by the step to produce the output.

     +
    +

    Namespace declarations

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    + + + + + + + + + + + + + + +
    Table 1: Namespaces used in the document
    dcterms<http://purl.org/dc/terms/>
    neao_base<http://purl.org/neao/base#>
    neao_params<http://purl.org/neao/parameters#>
    owl<http://www.w3.org/2002/07/owl#>
    rdf<http://www.w3.org/1999/02/22-rdf-syntax-ns#>
    rdfs<http://www.w3.org/2000/01/rdf-schema#>
    skos<http://www.w3.org/2004/02/skos/core#>
    vann<http://purl.org/vocab/vann/>
    xml<http://www.w3.org/XML/1998/namespace>
    xsd<http://www.w3.org/2001/XMLSchema#>
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    NEAO Analysis Parameters: Description back to ToC

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    The classes in this module are subclasses of the AnalysisParameter base class and are associated with the analysis steps (defined in the steps module) through the usesParameter object property. These classes can provide semantic information to analysis parameters

    + +

    The parameter entities control the behavior of the analysis step. For example, in a low-pass filtering step in the analysis, where a raw wideband signal is transformed to isolate the frequency components smaller than a cutoff frequency, the time series with the raw signal is the data input, and the low-pass frequency cutoff frequency value is a parameter.

    + +

    A parameter is then represented by an individual associated with the usesParameter object property. This provides flexibility to describe a parameter in detail and make inferences based on semantic information. For example, a low pass filter setting of 250 Hz can be represented by two properties: one for the integer value 250 and another for the unit "Hz". The representation adopted by NEAO enhances machine readability compared to a single string value like "250 Hz". NEAO does not predefine specific properties for the AnalysisParameter class, allowing the use of existing ontologies, such as QUDT, to describe physical quantities. Moreover, the value of usesParameter can be associated with the multiple classes derived from AnalysisParameter that are defined in this module, providing semantic meanings (e.g., using the LowPassFrequencyCutoff class for a low-frequency cutoff parameter).

    + + + +

    Cross-reference for NEAO Analysis Parameters classes, object properties and data properties back to ToC

    +This section provides details for each class and property defined by NEAO Analysis Parameters. +
    +

    Classes

    + +
    +

    ASSET analysis parameterc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#ASSETAnalysisParameter

    +
    + A parameter used by the Analysis of Sequences of Synchronous Events (ASSET) method, used to identify neuronal activity patterns in spike data. +
    +
    +
    has super-classes
    +
    + analysis parameter + c +
    +
    has sub-classes
    +
    + distance stretch factor in ASSET clustering + c, filter shape in ASSET joint probability matrix + c, number of largest neighbors in ASSET joint probability matrix + c, significance thresholds in ASSET mask matrix + c +
    +
    is disjoint with
    +
    + bin size + c, DBSCAN parameter + c, dithering time + c, downsample factor + c, filter order + c, firing rate + c, frequency resolution + c, high-pass frequency cutoff + c, kernel width + c, low-pass frequency cutoff + c, number of FFT samples + c, peak resolution + c, sampling frequency + c, shape factor + c, smoothing kernel + c, temporal resolution + c, wavelet center frequency + c, window function + c, window length in samples + c, window overlap factor + c, window overlap in samples + c +
    +
    +
    +
    +

    Bartlett smoothing kernelc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#BartlettSmoothingKernel

    +
    + The kernel function has a triangular shape with end points at zero. +
    +
    +
    has super-classes
    +
    + smoothing kernel + c +
    +
    +
    +
    +

    bin sizec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#BinSize

    +
    + When discretizing continuous data into smaller intervals (bins), the parameter value determines the width of the intervals (in the unit of the data being discretized). Bins are adjacent and can be of different sizes. +
    +
    +
    has super-classes
    +
    + analysis parameter + c +
    +
    is disjoint with
    +
    + ASSET analysis parameter + c, DBSCAN parameter + c, dithering time + c, downsample factor + c, filter order + c, firing rate + c, frequency resolution + c, high-pass frequency cutoff + c, kernel width + c, low-pass frequency cutoff + c, number of FFT samples + c, peak resolution + c, sampling frequency + c, shape factor + c, smoothing kernel + c, temporal resolution + c, wavelet center frequency + c, window function + c, window length in samples + c, window overlap factor + c, window overlap in samples + c, dithering time + c, downsample factor + c, filter order + c, firing rate + c, frequency resolution + c, high-pass frequency cutoff + c, low-pass frequency cutoff + c, peak resolution + c, sampling frequency + c, shape factor + c, window function + c, window length in samples + c, window overlap factor + c, window overlap in samples + c +
    +
    +
    +
    +

    Blackman window functionc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#BlackmanWindowFunction

    +
    + Window function that uses the first three terms of a summation of cosines, minimizing spectral leakage. It was proposed by Ralph Beebe Blackman. The coefficients are an approximation of the ones used in the exact Blackman window function. Therefore, this window does not remove the third and fourth side lobes but produces smoother edges. +
    +
    +
    has super-classes
    +
    + window function + c +
    +
    is disjoint with
    +
    + discrete prolate spheroidal sequences window function + c, exact Blackman window + c, Hamming window function + c, Hann window function + c, Kaiser window function + c, discrete prolate spheroidal sequences window function + c, Hamming window function + c, Hann window function + c, Kaiser window function + c +
    +
    +
    +
    +

    Boxcar smoothing kernelc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#BoxcarSmoothingKernel

    +
    + The kernel function is zero over the entire interval except for a single (smaller) interval where it has a constant value. This non-zero interval is the total width of the kernel. +
    +
    +
    has super-classes
    +
    + smoothing kernel + c +
    +
    is disjoint with
    +
    + exponential smoothing kernel + c +
    +
    +
    +
    +

    DBSCAN minimum number of neighborsc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#DBSCANMinimumNeighbors

    +
    + Integer value that determines the minimum number of points that must be present in the neighborhood of a sample point such that it is considered a core point. The parameter value includes the sample point being evaluated. +
    +
    +
    has super-classes
    +
    + DBSCAN parameter + c +
    +
    is disjoint with
    +
    + DBSCAN neighborhood radius + c +
    +
    +
    +
    +

    DBSCAN neighborhood radiusc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#DBSCANNeighborhoodRadius

    +
    + Determines the radius around a sample point used to define its neighborhood. The parameter defines the maximum distance between two sample points such that they are considered to be in the same neighborhood. +
    +
    +
    has super-classes
    +
    + DBSCAN parameter + c +
    +
    is disjoint with
    +
    + DBSCAN minimum number of neighbors + c +
    +
    +
    +
    +

    DBSCAN parameterc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#DBSCANParameter

    +
    + A parameter used by the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) data clustering method. +
    +
    +
    has super-classes
    +
    + analysis parameter + c +
    +
    has sub-classes
    +
    + DBSCAN minimum number of neighbors + c, DBSCAN neighborhood radius + c +
    +
    is disjoint with
    +
    + ASSET analysis parameter + c, bin size + c, dithering time + c, downsample factor + c, filter order + c, firing rate + c, frequency resolution + c, high-pass frequency cutoff + c, kernel width + c, low-pass frequency cutoff + c, number of FFT samples + c, peak resolution + c, sampling frequency + c, shape factor + c, smoothing kernel + c, temporal resolution + c, wavelet center frequency + c, window function + c, window length in samples + c, window overlap factor + c, window overlap in samples + c +
    +
    +
    +
    +

    discrete prolate spheroidal sequences window functionc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#DPSSWindowFunction

    +
    + A set of orthogonal sequences optimized to simultaneously achieve maximum concentration of energy within a defined frequency band and minimum leakage into neighboring frequency bands. They are frequently used as tapers in multiple applications (e.g., multitaper power spectral density estimation). The first sequence (order 0 or Slepian sequence) has maximal energy concentration in the main lobe. +
    +
    +
    has super-classes
    +
    + window function + c +
    +
    is disjoint with
    +
    + Blackman window function + c, exact Blackman window + c, Hamming window function + c, Hann window function + c, Kaiser window function + c, Blackman window function + c, Hamming window function + c, Hann window function + c, Kaiser window function + c +
    +
    +
    +
    +

    distance stretch factor in ASSET clusteringc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#ASSETClusteringDistanceStretchFactor

    +
    + When computing the elliptical distance measure used by the DBSCAN algorithm to cluster the mask matrix entries to find the diagonal structures, the parameter value is used to stretch angular coefficients deviating from 45 degrees. This reflects into the shape of the neighborhood around a point in the DBSCAN procedure. A large stretch factor will produce neighborhoods that are narrower and closer to a line in the 45 degree direction. Smaller stretch factors will produce neighborhoods that are more elliptical, with the major axis in the 45 degree direction, and the minor axis in the 135 degree direction. Therefore, the smaller stretch factor increases the minor axis of this ellipsis. Together with the DBSCAN neighborhood radius parameter, this should be used to tweak the neighborhood ellipsis such that it is contained in the rectangular kernel used to filter the probability matrix entries when computing the joint probability matrix. +
    +
    +
    has super-classes
    +
    + ASSET analysis parameter + c +
    +
    is disjoint with
    +
    + filter shape in ASSET joint probability matrix + c, number of largest neighbors in ASSET joint probability matrix + c, significance thresholds in ASSET mask matrix + c +
    +
    +
    +
    +

    dithering timec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#DitheringTime

    +
    + A time interval that defines a dithering distribution used to draw random numbers to displace individual spike times in a spike train. +
    +
    +
    has super-classes
    +
    + analysis parameter + c +
    +
    is disjoint with
    +
    + ASSET analysis parameter + c, bin size + c, DBSCAN parameter + c, downsample factor + c, filter order + c, firing rate + c, frequency resolution + c, high-pass frequency cutoff + c, kernel width + c, low-pass frequency cutoff + c, number of FFT samples + c, peak resolution + c, sampling frequency + c, shape factor + c, smoothing kernel + c, temporal resolution + c, wavelet center frequency + c, window function + c, window length in samples + c, window overlap factor + c, window overlap in samples + c, bin size + c, downsample factor + c, filter order + c, firing rate + c, frequency resolution + c, high-pass frequency cutoff + c, low-pass frequency cutoff + c, peak resolution + c, sampling frequency + c, shape factor + c, window function + c, window length in samples + c, window overlap factor + c, window overlap in samples + c +
    +
    +
    +
    +

    downsample factorc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#DownsampleFactor

    +
    + A real value that indicates the factor by which the sampling period of a sampled time series is reduced in a downsampling operation. +
    +
    +
    has super-classes
    +
    + analysis parameter + c +
    +
    is disjoint with
    +
    + ASSET analysis parameter + c, bin size + c, DBSCAN parameter + c, dithering time + c, filter order + c, firing rate + c, frequency resolution + c, high-pass frequency cutoff + c, kernel width + c, low-pass frequency cutoff + c, number of FFT samples + c, peak resolution + c, sampling frequency + c, shape factor + c, smoothing kernel + c, temporal resolution + c, wavelet center frequency + c, window function + c, window length in samples + c, window overlap factor + c, window overlap in samples + c, bin size + c, dithering time + c, filter order + c, firing rate + c, frequency resolution + c, high-pass frequency cutoff + c, low-pass frequency cutoff + c, peak resolution + c, sampling frequency + c, shape factor + c, window function + c, window length in samples + c, window overlap factor + c, window overlap in samples + c +
    +
    +
    +
    +

    exact Blackman windowc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#ExactBlackmanWindowFunction

    +
    + Window function that uses the first three terms of a summation of cosines. It was proposed by Ralph Beebe Blackman. The coefficients are selected to remove the third and fourth side lobes, but the edges are discontinuous. +
    +
    +
    has super-classes
    +
    + window function + c +
    +
    is disjoint with
    +
    + Blackman window function + c, discrete prolate spheroidal sequences window function + c, Hamming window function + c, Hann window function + c, Kaiser window function + c +
    +
    +
    +
    +

    exponential smoothing kernelc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#ExponentialSmoothingKernel

    +
    + The kernel function is zero for points before the kernel center point, maximum at the center point, and decay exponentially for points greater than the center point. This kernel is asymmetric. +
    +
    +
    has super-classes
    +
    + smoothing kernel + c +
    +
    is disjoint with
    +
    + Boxcar smoothing kernel + c +
    +
    +
    +
    +

    filter orderc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#FilterOrder

    +
    + Integer value specifying the rate at which the filter response in the transition band falls. A higher filter order corresponds to a faster filter response decay. +
    +
    +
    has super-classes
    +
    + analysis parameter + c +
    +
    is disjoint with
    +
    + ASSET analysis parameter + c, bin size + c, DBSCAN parameter + c, dithering time + c, downsample factor + c, firing rate + c, frequency resolution + c, high-pass frequency cutoff + c, kernel width + c, low-pass frequency cutoff + c, number of FFT samples + c, peak resolution + c, sampling frequency + c, shape factor + c, smoothing kernel + c, temporal resolution + c, wavelet center frequency + c, window function + c, window length in samples + c, window overlap factor + c, window overlap in samples + c, bin size + c, dithering time + c, downsample factor + c, firing rate + c, frequency resolution + c, high-pass frequency cutoff + c, low-pass frequency cutoff + c, peak resolution + c, sampling frequency + c, shape factor + c, window function + c, window length in samples + c, window overlap factor + c, window overlap in samples + c +
    +
    +
    +
    +

    filter shape in ASSET joint probability matrixc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#ASSETJointProbabilityMatrixFilterShape

    +
    + A tuple of integers that determines the width and length of a rectangular kernel used to cover a diagonal structure in the intersection matrix. The kernel is centered in a point in the probability matrix, and defines a neighborhood around that point. Inside the kernel, a chosen number of largest neighbors in the probability matrix is used to compute the joint probability value for the center point. The kernel is rotated in 45 degree angle. +
    +
    +
    has super-classes
    +
    + ASSET analysis parameter + c +
    +
    is disjoint with
    +
    + distance stretch factor in ASSET clustering + c, number of largest neighbors in ASSET joint probability matrix + c, significance thresholds in ASSET mask matrix + c +
    +
    +
    +
    +

    firing ratec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#FiringRate

    +
    + The parameter value determines the average number of spikes fired by a neuron per time unit. It is used to control the behavior of steps that require a firing rate to control the output (e.g., a target mean firing rate when generating an artificial spike train). +
    +
    +
    has super-classes
    +
    + analysis parameter + c +
    +
    is disjoint with
    +
    + ASSET analysis parameter + c, bin size + c, DBSCAN parameter + c, dithering time + c, downsample factor + c, filter order + c, frequency resolution + c, high-pass frequency cutoff + c, kernel width + c, low-pass frequency cutoff + c, number of FFT samples + c, peak resolution + c, sampling frequency + c, shape factor + c, smoothing kernel + c, temporal resolution + c, wavelet center frequency + c, window function + c, window length in samples + c, window overlap factor + c, window overlap in samples + c, bin size + c, dithering time + c, downsample factor + c, filter order + c, frequency resolution + c, high-pass frequency cutoff + c, low-pass frequency cutoff + c, peak resolution + c, sampling frequency + c, shape factor + c, window function + c, window length in samples + c, window overlap factor + c, window overlap in samples + c +
    +
    +
    +
    +

    frequency resolutionc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#FrequencyResolution

    +
    + In analyses producing estimates in the frequency domain, the parameter determines the width of the frequency bins in the output, i.e., the resolution of the output on the frequency axis. +
    +
    +
    has super-classes
    +
    + analysis parameter + c +
    +
    is disjoint with
    +
    + ASSET analysis parameter + c, bin size + c, DBSCAN parameter + c, dithering time + c, downsample factor + c, filter order + c, firing rate + c, high-pass frequency cutoff + c, kernel width + c, low-pass frequency cutoff + c, number of FFT samples + c, peak resolution + c, sampling frequency + c, shape factor + c, smoothing kernel + c, temporal resolution + c, wavelet center frequency + c, window function + c, window length in samples + c, window overlap factor + c, window overlap in samples + c, bin size + c, dithering time + c, downsample factor + c, filter order + c, firing rate + c, high-pass frequency cutoff + c, low-pass frequency cutoff + c, peak resolution + c, sampling frequency + c, shape factor + c, window function + c, window length in samples + c, window overlap factor + c, window overlap in samples + c +
    +
    +
    +
    +

    Hamming smoothing kernelc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#HammingSmoothingKernel

    +
    + The kernel function corresponds to a raised cosine (i.e., a single period of a cosine function "raised") with positive endpoints. +
    +
    +
    has super-classes
    +
    + smoothing kernel + c +
    +
    +
    +
    +

    Hamming window functionc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#HammingWindowFunction

    +
    + A window function that corresponds to a raised cosine (i.e., a single period of a cosine function "raised") but with positive endpoints. Therefore, the function does not eliminate the discontinuities in the signal. It has better cancellation of the nearest side lobe, and a poorer cancellation of the others, with a wide main lobe. It is named after Richard Wesley Hamming. +
    +
    +
    has super-classes
    +
    + window function + c +
    +
    is disjoint with
    +
    + Blackman window function + c, discrete prolate spheroidal sequences window function + c, exact Blackman window + c, Hann window function + c, Kaiser window function + c, Blackman window function + c, discrete prolate spheroidal sequences window function + c, Hann window function + c, Kaiser window function + c +
    +
    +
    +
    +

    Hann smoothing kernelc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#HannSmoothingKernel

    +
    + The kernel function corresponds to a raised cosine (i.e., a single period of a cosine function "raised" such that the negative troughs are zero). The endpoints reach zero smoothly at the boundaries. +
    +
    +
    has super-classes
    +
    + smoothing kernel + c +
    +
    +
    +
    +

    Hann window functionc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#HannWindowFunction

    +
    + A window function that corresponds to a raised cosine (i.e., a single period of a cosine function "raised" such that the negative troughs are zero). Therefore, the function reaches zero smoothly at the boundaries and eliminates all discontinuities in the signal. It has a wide main lobe and low side lobes. It is named after Julius von Hann. +
    +
    +
    has super-classes
    +
    + window function + c +
    +
    is disjoint with
    +
    + Blackman window function + c, discrete prolate spheroidal sequences window function + c, exact Blackman window + c, Hamming window function + c, Kaiser window function + c, Blackman window function + c, discrete prolate spheroidal sequences window function + c, Hamming window function + c, Kaiser window function + c +
    +
    +
    +
    +

    high-pass frequency cutoffc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#HighPassFrequencyCutoff

    +
    + When applying a filter to a time series, the frequency components below this parameter value will be attenuated. Usually, the parameter value corresponds to the frequency component attenuated by 3 dB in the filter transition band. +
    +
    +
    has super-classes
    +
    + analysis parameter + c +
    +
    is disjoint with
    +
    + ASSET analysis parameter + c, bin size + c, DBSCAN parameter + c, dithering time + c, downsample factor + c, filter order + c, firing rate + c, frequency resolution + c, kernel width + c, low-pass frequency cutoff + c, number of FFT samples + c, peak resolution + c, sampling frequency + c, shape factor + c, smoothing kernel + c, temporal resolution + c, wavelet center frequency + c, window function + c, window length in samples + c, window overlap factor + c, window overlap in samples + c, bin size + c, dithering time + c, downsample factor + c, filter order + c, firing rate + c, frequency resolution + c, low-pass frequency cutoff + c, peak resolution + c, sampling frequency + c, shape factor + c, window function + c, window length in samples + c, window overlap factor + c, window overlap in samples + c +
    +
    +
    +
    +

    Kaiser window functionc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#KaiserWindowFunction

    +
    + This window function approximates the DPSS window function using Bessel functions. It is easier to compute than the DPSS window function. It was developed by James Kaiser. +
    +
    +
    has super-classes
    +
    + window function + c +
    +
    is disjoint with
    +
    + Blackman window function + c, discrete prolate spheroidal sequences window function + c, exact Blackman window + c, Hamming window function + c, Hann window function + c, Blackman window function + c, discrete prolate spheroidal sequences window function + c, Hamming window function + c, Hann window function + c +
    +
    +
    +
    +

    kernel widthc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#KernelWidth

    +
    + The total width of a smoothing kernel. +
    +
    +
    has super-classes
    +
    + analysis parameter + c +
    +
    is disjoint with
    +
    + ASSET analysis parameter + c, bin size + c, DBSCAN parameter + c, dithering time + c, downsample factor + c, filter order + c, firing rate + c, frequency resolution + c, high-pass frequency cutoff + c, low-pass frequency cutoff + c, number of FFT samples + c, peak resolution + c, sampling frequency + c, shape factor + c, smoothing kernel + c, temporal resolution + c, wavelet center frequency + c, window function + c, window length in samples + c, window overlap factor + c, window overlap in samples + c +
    +
    +
    +
    +

    low-pass frequency cutoffc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#LowPassFrequencyCutoff

    +
    + When applying a filter to a time series, the frequency components above this parameter value will be attenuated. Usually, the parameter value corresponds to the frequency component attenuated by 3 dB in the filter transition band. +
    +
    +
    has super-classes
    +
    + analysis parameter + c +
    +
    is disjoint with
    +
    + ASSET analysis parameter + c, bin size + c, DBSCAN parameter + c, dithering time + c, downsample factor + c, filter order + c, firing rate + c, frequency resolution + c, high-pass frequency cutoff + c, kernel width + c, number of FFT samples + c, peak resolution + c, sampling frequency + c, shape factor + c, smoothing kernel + c, temporal resolution + c, wavelet center frequency + c, window function + c, window length in samples + c, window overlap factor + c, window overlap in samples + c, bin size + c, dithering time + c, downsample factor + c, filter order + c, firing rate + c, frequency resolution + c, high-pass frequency cutoff + c, peak resolution + c, sampling frequency + c, shape factor + c, window function + c, window length in samples + c, window overlap factor + c, window overlap in samples + c +
    +
    +
    +
    +

    number of FFT samplesc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#NumberFFTSamples

    +
    + Length of the time series considered by application of a fast Fourier transform (FFT). The value determines the frequency bin size based on the sampling frequency of the input data, and the length of the vector representing the result of the discrete Fourier transform. +
    +
    +
    has super-classes
    +
    + analysis parameter + c +
    +
    is disjoint with
    +
    + ASSET analysis parameter + c, bin size + c, DBSCAN parameter + c, dithering time + c, downsample factor + c, filter order + c, firing rate + c, frequency resolution + c, high-pass frequency cutoff + c, kernel width + c, low-pass frequency cutoff + c, peak resolution + c, sampling frequency + c, shape factor + c, smoothing kernel + c, temporal resolution + c, wavelet center frequency + c, window function + c, window length in samples + c, window overlap factor + c, window overlap in samples + c +
    +
    +
    +
    +

    number of largest neighbors in ASSET joint probability matrixc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#ASSETJointProbabilityMatrixNumberLargestNeighbors

    +
    + Defines the number of elements inside the filter kernel that are used to compute the joint probability value for a matrix entry. The probability matrix values inside the kernel for that entry are ordered from the largest to the lowest value, and the first N elements corresponding to the parameter value are taken. +
    +
    +
    has super-classes
    +
    + ASSET analysis parameter + c +
    +
    is disjoint with
    +
    + distance stretch factor in ASSET clustering + c, filter shape in ASSET joint probability matrix + c, significance thresholds in ASSET mask matrix + c +
    +
    +
    +
    +

    peak resolutionc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#PeakResolution

    +
    + The parameter defines the separation of individual peaks in the output. +
    +
    +
    has super-classes
    +
    + analysis parameter + c +
    +
    is disjoint with
    +
    + ASSET analysis parameter + c, bin size + c, DBSCAN parameter + c, dithering time + c, downsample factor + c, filter order + c, firing rate + c, frequency resolution + c, high-pass frequency cutoff + c, kernel width + c, low-pass frequency cutoff + c, number of FFT samples + c, sampling frequency + c, shape factor + c, smoothing kernel + c, temporal resolution + c, wavelet center frequency + c, window function + c, window length in samples + c, window overlap factor + c, window overlap in samples + c, bin size + c, dithering time + c, downsample factor + c, filter order + c, firing rate + c, frequency resolution + c, high-pass frequency cutoff + c, low-pass frequency cutoff + c, sampling frequency + c, shape factor + c, window function + c, window length in samples + c, window overlap factor + c, window overlap in samples + c +
    +
    +
    +
    +

    sampling frequencyc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#SamplingFrequency

    +
    + The parameter determines the number of samples per time unit in sampled data. It is the inverse of the sampling period, i.e., the interval between two consecutive samples. +
    +
    +
    has super-classes
    +
    + analysis parameter + c +
    +
    is disjoint with
    +
    + ASSET analysis parameter + c, bin size + c, DBSCAN parameter + c, dithering time + c, downsample factor + c, filter order + c, firing rate + c, frequency resolution + c, high-pass frequency cutoff + c, kernel width + c, low-pass frequency cutoff + c, number of FFT samples + c, peak resolution + c, shape factor + c, smoothing kernel + c, temporal resolution + c, wavelet center frequency + c, window function + c, window length in samples + c, window overlap factor + c, window overlap in samples + c, bin size + c, dithering time + c, downsample factor + c, filter order + c, firing rate + c, frequency resolution + c, high-pass frequency cutoff + c, low-pass frequency cutoff + c, peak resolution + c, shape factor + c, window function + c, window length in samples + c, window overlap factor + c, window overlap in samples + c +
    +
    +
    +
    +

    shape factorc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#ShapeFactor

    +
    + When determining a probability distribution, the parameter affects the shape of the distribution. This is in contrast to other parameters that affect the location (e.g., mean) or scale (e.g., variance) of the distribution. +
    +
    +
    has super-classes
    +
    + analysis parameter + c +
    +
    is disjoint with
    +
    + ASSET analysis parameter + c, bin size + c, DBSCAN parameter + c, dithering time + c, downsample factor + c, filter order + c, firing rate + c, frequency resolution + c, high-pass frequency cutoff + c, kernel width + c, low-pass frequency cutoff + c, number of FFT samples + c, peak resolution + c, sampling frequency + c, smoothing kernel + c, temporal resolution + c, wavelet center frequency + c, window function + c, window length in samples + c, window overlap factor + c, window overlap in samples + c, bin size + c, dithering time + c, downsample factor + c, filter order + c, firing rate + c, frequency resolution + c, high-pass frequency cutoff + c, low-pass frequency cutoff + c, peak resolution + c, sampling frequency + c, window function + c, window length in samples + c, window overlap factor + c, window overlap in samples + c +
    +
    +
    +
    +

    significance thresholds in ASSET mask matrixc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#ASSETMaskMatrixSignificanceThresholds

    +
    + Real values (range 0-1) used as thresholds to determine if the entries in the probability matrix and joint probability matrices are significant. Entry significance is defined as a probability value greater than the threshold values specified by the parameter. Significant entries in both probability and joint probability matrices are defined as 1 in the mask matrix. +
    +
    +
    has super-classes
    +
    + ASSET analysis parameter + c +
    +
    is disjoint with
    +
    + distance stretch factor in ASSET clustering + c, filter shape in ASSET joint probability matrix + c, number of largest neighbors in ASSET joint probability matrix + c +
    +
    +
    +
    +

    smoothing kernelc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#SmoothingKernel

    +
    + A smoothing kernel can be used in non-parametric smoothing techniques such as kernel smoothing or kernel density estimation. It represents a weighting function that assigns weights to neighboring data points based on their distance from a given point (the kernel center). Closer points are given higher weights. The weighted average of the data points within the kernel is computed to produce a smoothed estimate of the underlying data (e.g., a signal or probability density function). Smoothing kernels are characterized by their shape (e.g., Boxcar, exponential) and bandwidth. The bandwidth determines the extent of influence of neighboring data points on the smoothed estimate. +
    +
    +
    has super-classes
    +
    + analysis parameter + c +
    +
    has sub-classes
    +
    + Bartlett smoothing kernel + c, Boxcar smoothing kernel + c, Hamming smoothing kernel + c, Hann smoothing kernel + c, exponential smoothing kernel + c +
    +
    is disjoint with
    +
    + ASSET analysis parameter + c, bin size + c, DBSCAN parameter + c, dithering time + c, downsample factor + c, filter order + c, firing rate + c, frequency resolution + c, high-pass frequency cutoff + c, kernel width + c, low-pass frequency cutoff + c, number of FFT samples + c, peak resolution + c, sampling frequency + c, shape factor + c, temporal resolution + c, wavelet center frequency + c, window function + c, window length in samples + c, window overlap factor + c, window overlap in samples + c +
    +
    +
    +
    +

    temporal resolutionc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#TemporalResolution

    +
    + The parameter determines the smallest time interval that can be detected or produced by the method. In sampled time series data, this equals to the sampling period, i.e, the time interval between two consecutive samples. +
    +
    +
    has super-classes
    +
    + analysis parameter + c +
    +
    is disjoint with
    +
    + ASSET analysis parameter + c, bin size + c, DBSCAN parameter + c, dithering time + c, downsample factor + c, filter order + c, firing rate + c, frequency resolution + c, high-pass frequency cutoff + c, kernel width + c, low-pass frequency cutoff + c, number of FFT samples + c, peak resolution + c, sampling frequency + c, shape factor + c, smoothing kernel + c, wavelet center frequency + c, window function + c, window length in samples + c, window overlap factor + c, window overlap in samples + c +
    +
    +
    +
    +

    wavelet center frequencyc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#WaveletCenterFrequency

    +
    + The value of the center frequency of a wavelet. This is the frequency at which the wavelet oscillates most strongly, and it influences how effectively the wavelet can capture features of a signal at different frequencies. Wavelets with higher center frequencies are better suited for analyzing high-frequency components of a signal, while those with lower center frequencies are more effective for capturing low-frequency components. +
    +
    +
    has super-classes
    +
    + analysis parameter + c +
    +
    is disjoint with
    +
    + ASSET analysis parameter + c, bin size + c, DBSCAN parameter + c, dithering time + c, downsample factor + c, filter order + c, firing rate + c, frequency resolution + c, high-pass frequency cutoff + c, kernel width + c, low-pass frequency cutoff + c, number of FFT samples + c, peak resolution + c, sampling frequency + c, shape factor + c, smoothing kernel + c, temporal resolution + c, window function + c, window length in samples + c, window overlap factor + c, window overlap in samples + c +
    +
    +
    +
    +

    window functionc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#WindowFunction

    +
    + A mathematical function that is zero-valued outside a defined interval. When multiplied by another function or sampled data, the values outside the window interval will be transformed to zero, and the values inside the window will be weighted by the window function values. + +Window functions are used to select and modify a finite segment of a signal. This is useful for applying the fast Fourier transform (FFT) to a finite set of data where the length is not an integer number of periods of the signal. In this situation, there will be discontinuities at the boundaries of the signal, and the data in the frequency domain produced by the FFT will have frequency components not present in the original signal (spectral leakage). The window function can be used to reduce this discontinuities and mitigate spectral leakage when performing spectral analysis. + +Several types of window function exist. They will vary in shape in the time domain and will have distinct frequency characteristics in the frequency domain, with a main lobe and several side lobes. The main lobe is centered at each frequency component in the time domain, and the side lobes approach zero. These characteristics can be used to control the effect of spectral leakage when performing the analysis. +
    +
    +
    has super-classes
    +
    + analysis parameter + c +
    +
    has sub-classes
    +
    + Blackman window function + c, Hamming window function + c, Hann window function + c, Kaiser window function + c, discrete prolate spheroidal sequences window function + c, exact Blackman window + c +
    +
    is disjoint with
    +
    + ASSET analysis parameter + c, bin size + c, DBSCAN parameter + c, dithering time + c, downsample factor + c, filter order + c, firing rate + c, frequency resolution + c, high-pass frequency cutoff + c, kernel width + c, low-pass frequency cutoff + c, number of FFT samples + c, peak resolution + c, sampling frequency + c, shape factor + c, smoothing kernel + c, temporal resolution + c, wavelet center frequency + c, window length in samples + c, window overlap factor + c, window overlap in samples + c, bin size + c, dithering time + c, downsample factor + c, filter order + c, firing rate + c, frequency resolution + c, high-pass frequency cutoff + c, low-pass frequency cutoff + c, peak resolution + c, sampling frequency + c, shape factor + c, window length in samples + c, window overlap factor + c, window overlap in samples + c +
    +
    +
    +
    +

    window length in samplesc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#WindowLengthSamples

    +
    + Integer value that defines the number of samples encompassed by a window in sampled data, i.e., the window length. The window corresponds to a finite interval in the sampled data (e.g., a time interval in sampled time series data). +
    +
    +
    has super-classes
    +
    + analysis parameter + c +
    +
    is disjoint with
    +
    + ASSET analysis parameter + c, bin size + c, DBSCAN parameter + c, dithering time + c, downsample factor + c, filter order + c, firing rate + c, frequency resolution + c, high-pass frequency cutoff + c, kernel width + c, low-pass frequency cutoff + c, number of FFT samples + c, peak resolution + c, sampling frequency + c, shape factor + c, smoothing kernel + c, temporal resolution + c, wavelet center frequency + c, window function + c, window overlap factor + c, window overlap in samples + c, bin size + c, dithering time + c, downsample factor + c, filter order + c, firing rate + c, frequency resolution + c, high-pass frequency cutoff + c, low-pass frequency cutoff + c, peak resolution + c, sampling frequency + c, shape factor + c, window function + c, window overlap factor + c, window overlap in samples + c +
    +
    +
    +
    +

    window overlap factorc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#WindowOverlapFactor

    +
    + Real value (range 0-1) that determines the proportion of overlap between two adjacent windows. The window is a finite interval in the data (e.g., a time interval in time series data). +
    +
    +
    has super-classes
    +
    + analysis parameter + c +
    +
    is disjoint with
    +
    + ASSET analysis parameter + c, bin size + c, DBSCAN parameter + c, dithering time + c, downsample factor + c, filter order + c, firing rate + c, frequency resolution + c, high-pass frequency cutoff + c, kernel width + c, low-pass frequency cutoff + c, number of FFT samples + c, peak resolution + c, sampling frequency + c, shape factor + c, smoothing kernel + c, temporal resolution + c, wavelet center frequency + c, window function + c, window length in samples + c, window overlap in samples + c, bin size + c, dithering time + c, downsample factor + c, filter order + c, firing rate + c, frequency resolution + c, high-pass frequency cutoff + c, low-pass frequency cutoff + c, peak resolution + c, sampling frequency + c, shape factor + c, window function + c, window length in samples + c, window overlap in samples + c +
    +
    +
    +
    +

    window overlap in samplesc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/parameters#WindowOverlapSamples

    +
    + Integer value (range 0 to the window length in samples) that determines the number of samples where two adjacent windows overlap. The window corresponds to a finite interval in sampled data (e.g., a time interval in sampled time series data). +
    +
    +
    has super-classes
    +
    + analysis parameter + c +
    +
    is disjoint with
    +
    + ASSET analysis parameter + c, bin size + c, DBSCAN parameter + c, dithering time + c, downsample factor + c, filter order + c, firing rate + c, frequency resolution + c, high-pass frequency cutoff + c, kernel width + c, low-pass frequency cutoff + c, number of FFT samples + c, peak resolution + c, sampling frequency + c, shape factor + c, smoothing kernel + c, temporal resolution + c, wavelet center frequency + c, window function + c, window length in samples + c, window overlap factor + c, bin size + c, dithering time + c, downsample factor + c, filter order + c, firing rate + c, frequency resolution + c, high-pass frequency cutoff + c, low-pass frequency cutoff + c, peak resolution + c, sampling frequency + c, shape factor + c, window function + c, window length in samples + c, window overlap factor + c +
    +
    +
    +
    +

    Legend back to ToC

    +
    +c: Classes
    +
    +
    +
    + + + + +
    +

    Acknowledgments back to ToC

    +

    This work was performed as part of the Helmholtz School for Data Science in Life, Earth and Energy (HDS-LEE) and received funding from the Helmholtz Association of German Research Centres. This project has received funding from the European Union’s Horizon 2020 Framework Programme for Research and Innovation under Specific Grant Agreement No. 945539 (Human Brain Project SGA3), the European Union’s Horizon Europe Programme under the Specific Grant Agreement No. 101147319 (EBRAINS 2.0 Project), the Ministry of Culture and Science of the State of North Rhine-Westphalia, Germany (NRW-network "iBehave", grant number: NW21-049), and the Joint Lab "Supercomputing and Modeling for the Human Brain."

    + +

    The authors would like to thank Silvio Peroni for developing LODE, a Live OWL Documentation Environment, which is used for representing the Cross Referencing Section of this document and Daniel Garijo for developing Widoco, the program used to create the template used in this documentation.

     +
    + + +
    + + + + + + + diff --git a/doc/releases/0.1.0/parameters/provenance/provenance-en.html b/doc/releases/0.1.0/parameters/provenance/provenance-en.html new file mode 100644 index 0000000..6c4e38f --- /dev/null +++ b/doc/releases/0.1.0/parameters/provenance/provenance-en.html @@ -0,0 +1,18 @@ + + + + + + + + +
    +

    Provenance for Neuroelectrophysiology Analysis Ontology - Analysis Parameters Documentation (http://purl.org/neao/0.1.0/parameters#)

    +
      +
    • Ontology created by: Cristiano Köhler (Forschungszentrum Jülich), Michael Denker (Forschungszentrum Jülich)
    • http://purl.org/neao/0.1.0/parameters# is a specialization of the generic URI http://purl.org/neao/parameters#
      • +
    • The ontology documentation was the result of using the Widoco tool (which itself uses LODE for generating the crossreference section).
      • +
    • The documentation was generated at 2024-12-06
    +
    +

    back to documentation. TTL format

    + + \ No newline at end of file diff --git a/doc/releases/0.1.0/parameters/provenance/provenance-en.ttl b/doc/releases/0.1.0/parameters/provenance/provenance-en.ttl new file mode 100644 index 0000000..b291dbb --- /dev/null +++ b/doc/releases/0.1.0/parameters/provenance/provenance-en.ttl @@ -0,0 +1,14 @@ +@prefix prov: . +@prefix dc: . +@prefix foaf: . +@prefix : <> . + a prov:Entity; + dc:title "Neuroelectrophysiology Analysis Ontology - Analysis Parameters"; + prov:wasAttributedTo ; + dc:creator ; + prov:wasAttributedTo ; + dc:creator ; + prov:wasAttributedTo ,; + prov:specializationOf ; + prov:wasGeneratedAt "2024-12-06"; +. diff --git a/doc/releases/0.1.0/parameters/resources/extra.css b/doc/releases/0.1.0/parameters/resources/extra.css new file mode 100644 index 0000000..16689d3 --- /dev/null +++ b/doc/releases/0.1.0/parameters/resources/extra.css @@ -0,0 +1,124 @@ +body { + text-align: justify; +} + +h1 { + line-height: 110%; +} + +.hlist { + border: 1px solid navy; + 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r=n[1]||n[2]||"";if(!r||""===u||this.rules.inline.punctuation.exec(u)){var i=n[0].length-1,s=i,l=0,a="*"===n[0][0]?this.rules.inline.emStrong.rDelimAst:this.rules.inline.emStrong.rDelimUnd;for(a.lastIndex=0,t=t.slice(-1*e.length+i);null!=(n=a.exec(t));)if(o=n[1]||n[2]||n[3]||n[4]||n[5]||n[6])if(o=o.length,n[3]||n[4])s+=o;else if((n[5]||n[6])&&i%3&&!((i+o)%3))l+=o;else if(!(0<(s-=o))){var o=Math.min(o,o+s+l);if(Math.min(i,o)%2)return D=e.slice(1,i+n.index+o),{type:"em",raw:e.slice(0,i+n.index+o+1),text:D,tokens:this.lexer.inlineTokens(D,[])};var D=e.slice(2,i+n.index+o-1);return{type:"strong",raw:e.slice(0,i+n.index+o+1),text:D,tokens:this.lexer.inlineTokens(D,[])}}}}},t.codespan=function(e){var t,u,n,e=this.rules.inline.code.exec(e);if(e)return n=e[2].replace(/\n/g," "),t=/[^ ]/.test(n),u=/^ /.test(n)&&/ 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Slightly larger */ + width: 26em; + height: 26em; + z-index: -1; + opacity: 0.8; + + /** From http://stackoverflow.com/questions/1080792/how-to-draw-vertical-text-with-css-cross-browser */ + + -webkit-transform: rotate(-90deg); + -moz-transform: rotate(-90deg); + -ms-transform: rotate(-90deg); + -o-transform: rotate(-90deg); + transform: rotate(-90deg); + /* also accepts left, right, top, bottom coordinates; not + * required, but a good idea for styling */ + -webkit-transform-origin: 50% 50%; + -moz-transform-origin: 50% 50%; + -ms-transform-origin: 50% 50%; + -o-transform-origin: 50% 50%; + transform-origin: 50% 50%; + + /* Should be unset in IE9+ I think. */ + filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=3); +} + +/* The actual status box */ + .status div { + display: block; + background: rgb(0, 90, 156); + color: white; + width: 24em; + padding-top: 0.3em; + padding-left: 0em; + padding-right: 5em; + padding-bottom: 0.3em; + /* Enable for debugging + border: red thin solid; + */ +} + +/* And text inside, don't confuse fonts as it breaks em above */ +.status div span { + font-family: "Tauri"; + font-size: larger; +} \ No newline at end of file diff --git a/doc/releases/0.1.0/parameters/resources/rdf.icon b/doc/releases/0.1.0/parameters/resources/rdf.icon new file mode 100644 index 0000000000000000000000000000000000000000..d54310fe20cc6b76fb0aff73bb6d208449383a25 GIT binary patch literal 421 zcmV;W0b2e?Nk%w1VI2S<0K^{vg`>{#^!YhzuNqUMXN>BW*@J zA`Biv9dKI*F$G2>5f4KUX|yqk1!f2uS!02}lx7{JW5GSZW*L7;&$lB24u2k>F$6}2 z9|sD|ao{A8dL-W3NSo?M0}Lb=Tbc$83Fs{c7y=Ux8ZuC@K!AjS1ONaeKqcb9fGD~; zJU~-qN*OvvCfI!Gf5V9$CtYa?E2W PV+=hSSm&XEyAS|7t>CRw literal 0 HcmV?d00001 diff --git a/doc/releases/0.1.0/parameters/resources/rec.css b/doc/releases/0.1.0/parameters/resources/rec.css new file mode 100644 index 0000000..d8a1ff2 --- /dev/null +++ b/doc/releases/0.1.0/parameters/resources/rec.css @@ -0,0 +1,88 @@ +/* Style for a "Recommendation" */ + +/* + Copyright 1997-2003 W3C (MIT, ERCIM, Keio). All Rights Reserved. + The following software licensing rules apply: + http://www.w3.org/Consortium/Legal/copyright-software */ + +/* $Id: base.css,v 1.25 2006/04/18 08:42:53 bbos Exp $ */ + +body { + padding: 2em 1em 2em 70px; + margin: 0; + font-family: sans-serif; + color: black; + background: white; + background-position: top left; + background-attachment: fixed; + background-repeat: no-repeat; + counter-reset:section; +} +:link { color: #00C; background: transparent } +:visited { color: #609; background: transparent } +a:active { color: #C00; background: transparent } + +a:link img, a:visited img { border-style: none } /* no border on img links */ + +a img { color: white; } /* trick to hide the border in Netscape 4 */ +@media all { /* hide the next rule from Netscape 4 */ + a img { color: inherit; } /* undo the color change above */ +} + +th, td { /* ns 4 */ + font-family: sans-serif; +} + +h1, h2, h3, h4, h5, h6 { text-align: left } +h2.list{counter-reset:subsection } +h2.list:before{counter-increment:section;content: counter(section) ". ";} +h3.list:before{counter-increment:subsection;content: counter(section) "." counter(subsection) ". "; + } +h3.list{margin-top: 20px; + border-bottom: 0px; } +/* background should be transparent, but WebTV has a bug */ +h1, h2, h3 { color: #005A9C; background: white } +h1 { font: 170% sans-serif } +h2 { font: 140% sans-serif } +h3 { font: 120% sans-serif } +h4 { font: bold 100% sans-serif } +h5 { font: italic 100% sans-serif } +h6 { font: small-caps 100% sans-serif } + +.hide { display: none } + +div.head { margin-bottom: 1em } +div.head h1 { margin-top: 2em; clear: both } +div.head table { margin-left: 2em; margin-top: 2em } + +p.copyright { font-size: small } +p.copyright small { font-size: small } + +@media screen { /* hide from IE3 */ +a[href]:hover { background: #ffa } +} + +pre { margin-left: 2em } +/* +p { + margin-top: 0.6em; + margin-bottom: 0.6em; +} +*/ +dt, dd { margin-top: 0; margin-bottom: 0 } /* opera 3.50 */ +dt { font-weight: bold } + +pre, code { font-family: monospace } /* navigator 4 requires this */ + +ul.toc, ol.toc { + list-style: disc; /* Mac NS has problem with 'none' */ + list-style: none; +} + +@media aural { + h1, h2, h3 { stress: 20; richness: 90 } + .hide { speak: none } + p.copyright { volume: x-soft; speech-rate: x-fast } + dt { pause-before: 20% } + pre { speak-punctuation: code } +} diff --git a/doc/releases/0.1.0/parameters/webvowl/css/webvowl.app.css b/doc/releases/0.1.0/parameters/webvowl/css/webvowl.app.css new file mode 100644 index 0000000..1c350ab --- /dev/null +++ b/doc/releases/0.1.0/parameters/webvowl/css/webvowl.app.css @@ -0,0 +1,2477 @@ +@import url(https://fonts.googleapis.com/css?family=Open+Sans);/*---------------------------------------------- + WebVOWL page +----------------------------------------------*/ +html { + -ms-content-zooming: none; +} + + + +#loading-progress { + width: 50%; + margin: 10px 0; +} + +#drag_dropOverlay{ + width: 100%; + height:100%; + position:absolute; + top:0; + opacity: 0.5; + background-color: #3071a9; + pointer-events: none; + +} + +#dragDropContainer{ + width: 100%; + height:100%; + position:absolute; + top:0; + pointer-events: none; +} +#drag_icon_group{ + + +} + +#drag_msg{ + width: 50%; + background-color: #fefefe; + height: 50%; + border: black 2px solid; + border-radius: 20px; + left: 25%; + position: absolute; + top: 25%; + vertical-align: middle; + line-height: 10px; + text-align: center; + pointer-events: none; + padding: 10px; + font-size: 1.5em; + white-space: nowrap; + overflow: hidden; + text-overflow: ellipsis; +} + + +#layoutLoadingProgressBarContainer { + height: 50px; + text-align: left; + line-height: 1.5; +} + +#FPS_Statistics { + /*position : absolute;*/ + /*top : 10px;*/ + /*right: 50px;*/ + padding-left: 60px; + padding-top: 60px; +} + +#reloadCachedOntology { + /*position : absolute;*/ + /*top : 10px;*/ + /*right: 50px;*/ +} + +#additionalInformationContainer { + position: absolute; + top: 10px; + right: 50px; +} + +#modeOfOperationString { + /*position: absolute;*/ + /*right: 50px;*/ + /*top : 60px;*/ + padding-left: 34px; +} + +#direct-text-input { + border: 1px solid #34495e; + width: 100%; + margin-top: 5px; + cursor: pointer; +} + +#directUploadBtn, #close_directUploadBtn { + border: 1px solid #34495e; + width: 100%; + margin-top: 5px; + cursor: pointer +} + +#di_controls { + +} + +#di_controls > ul { + list-style: none; + margin: 0; + padding: 5px 0 0 5px; + +} + +#progressBarContext { + border-radius: 10px; + background-color: #bdc3c7; + height: 25px; + border: solid 1px black; + + margin: auto; + +} + +#progressBarValue { + border-radius: 9px; + width: 0%; + background-color: #2980b9; + height: 25px; + line-height: 1.5; + text-align: center; +} + +/** adding searching Styles **/ +.dbEntry { + background-color: #ffffff; + color: #2980b9; + padding: 10px; + font-size: 14px; + border: none; + cursor: pointer; +} + +.debugOption { + +} + +.dbEntrySelected { + background-color: #bdc3c7; + color: #2980b9; + padding: 10px; + font-size: 14px; + border: none; + cursor: pointer; +} + +.dbEntry:hover, .dbEntry:focus { + background-color: #bdc3c7; +} + +.searchMenuEntry { + background-color: #ffffff; + bottom: 0; + font-size: 14px; + min-width: 50px; + margin: 0; + padding: 0; + z-index: 99; + border-radius: 4px 4px 0 0; + border: 1px solid rgba(0, 0, 0, 0.15); + -webkit-box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175); + box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175); + box-sizing: border-box; + border-bottom: none; + display: none; + position: absolute; + list-style: none; +} + +.searchInputText { + background-color: #ffffff; + color: black; + border: black; + text-decoration: none; + max-width: 150px; + overflow: hidden; + text-overflow: ellipsis; + /*height: 20px;*/ + margin: 0; +} + +img, iframe { + border: none; +} + +.hidden { + display: none !important; +} + +.clear { + clear: both; +} + +a { + color: #69c; + text-decoration: none; +} + +a:hover { + color: #3498db; +} + +#optionsArea a { + color: #2980b9; +} + +#optionsArea a.highlighted { + background-color: #d90; +} + +.toolTipMenu li.highlighted { + background-color: #feb; +} + +#browserCheck { + /* checking for IE where WebVOWL is not working */ + background-color: #f00; + padding: 5px 0; + position: absolute; + text-align: center; + width: 100%; +} + +#browserCheck a { + color: #fff; +} + +#browserCheck a:hover { + text-decoration: underline; +} + +/*---------------------------------------------- + SideBar Animation Class; +----------------------------------------------- */ +@-webkit-keyframes sbExpandAnimation { + 0% { + width: 78%; + } + 100% { + width: 100%; + } +} + +@-moz-keyframes sbExpandAnimation { + 0% { + width: 78%; + } + 100% { + width: 100%; + } +} + +@-o-keyframes sbExpandAnimation { + 0% { + width: 78%; + } + 100% { + width: 100%; + } +} + +@keyframes sbExpandAnimation { + 0% { + width: 78%; + } + 100% { + width: 100%; + } +} + +/*Collapse Animation*/ +@-webkit-keyframes sbCollapseAnimation { + 0% { + width: 100%; + } + 100% { + width: 78%; + } +} + +@-moz-keyframes sbCollapseAnimation { + 0% { + width: 100%; + } + 100% { + width: 78%; + } +} + +@-o-keyframes sbCollapseAnimation { + 0% { + width: 100%; + } + 100% { + width: 78%; + } +} + +@keyframes sbCollapseAnimation { + 0% { + width: 100%; + } + 100% { + width: 78%; + } +} + +/*---------------------------------------------- + SideBar Animation Class; +----------------------------------------------- */ +@-webkit-keyframes l_sbExpandAnimation { + 0% { + width: 0px; + } + 100% { + width: 200px; + } +} + +@-moz-keyframes l_sbExpandAnimation { + 0% { + width: 0px; + } + 100% { + width: 200px; + } +} + +@-o-keyframes l_sbExpandAnimation { + 0% { + width: 0px; + } + 100% { + width: 200px; + } +} + +@keyframes l_sbExpandAnimation { + 0% { + width: 0px; + } + 100% { + width: 200px; + } +} + +/*Collapse Animation*/ +@-webkit-keyframes l_sbCollapseAnimation { + 0% { + width: 200px; + } + 100% { + width: 0px; + } +} + +@-moz-keyframes l_sbCollapseAnimation { + 0% { + width: 200px; + } + 100% { + width: 0px; + } +} + +@-o-keyframes l_sbCollapseAnimation { + 0% { + width: 200px; + } + 100% { + width: 0px; + } +} + +@keyframes l_sbCollapseAnimation { + 0% { + width: 200px; + } + 100% { + width: 0px; + } +} + +/*----------------- WARNING ANIMATIONS-------------*/ + +/*---------------------------------------------- + SideBar Animation Class; +----------------------------------------------- */ +@-webkit-keyframes warn_ExpandAnimation { + 0% { + top: -500px; + } + 100% { + top: 0; + } +} + +@-moz-keyframes warn_ExpandAnimation { + 0% { + top: -500px; + } + 100% { + top: 0; + } +} + +@-o-keyframes warn_ExpandAnimation { + 0% { + top: -500px; + } + 100% { + top: 0; + } +} + +@keyframes warn_ExpandAnimation { + 0% { + top: -500px; + } + 100% { + top: 0; + } +} + +/*Collapse Animation*/ +@-webkit-keyframes warn_CollapseAnimation { + 0% { + top: 0; + } + 100% { + top: -400px; + } +} + +@-moz-keyframes warn_CollapseAnimation { + 0% { + top: 0; + } + 100% { + top: -400px; + } +} + +@-o-keyframes warn_CollapseAnimation { + 0% { + top: 0; + } + 100% { + top: -400px; + } +} + +@keyframes warn_CollapseAnimation { + 0% { + top: 0; + } + 100% { + top: -400px; + } +} + +@keyframes msg_CollapseAnimation { + 0% { + top: 0; + } + 100% { + top: -400px; + } +} + +/*// add expand and collaps width for the warn module*/ +@-webkit-keyframes warn_ExpandLeftBarAnimation { + 0% { + left: 0; + } + 100% { + left: 100px; + } +} + +@-moz-keyframes warn_ExpandLeftBarAnimation { + 0% { + left: 0; + } + 100% { + left: 100px; + } +} + +@-o-keyframes warn_ExpandLeftBarAnimation { + 0% { + left: 0; + } + 100% { + left: 100px; + } +} + +@keyframes warn_ExpandLeftBarAnimation { + 0% { + left: 0; + } + 100% { + left: 100px; + } +} + +/*Collapse Animation*/ +@-webkit-keyframes warn_CollapseLeftBarAnimation { + 0% { + left: 100px; + } + 100% { + left: 0; + } +} + +@-moz-keyframes warn_CollapseLeftBarAnimation { + 0% { + left: 100px; + } + 100% { + left: 0; + } +} + +@-o-keyframes warn_CollapseLeftBarAnimation { + 0% { + left: 100px; + } + 100% { + left: 0; + } +} + +@keyframes warn_CollapseLeftBarAnimation { + 0% { + left: 100px; + } + 100% { + left: 0; + } +} + +/*// same for the right side expansion*/ + +/*// add expand and collaps width for the warn module*/ +@-webkit-keyframes warn_ExpandRightBarAnimation { + 0% { + width: 100%; + } + 100% { + width: 78%; + } +} + +@-moz-keyframes warn_ExpandRightBarAnimation { + 0% { + width: 100%; + } + 100% { + width: 78%; + } +} + +@-o-keyframes warn_ExpandRightBarAnimation { + 0% { + width: 100%; + } + 100% { + width: 78%; + } +} + +@keyframes warn_ExpandRightBarAnimation { + 0% { + width: 100%; + } + 100% { + width: 78%; + } + +} + +/*Collapse Animation*/ +@-webkit-keyframes warn_CollapseRightBarAnimation { + 0% { + width: 78%; + } + 100% { + width: 100%; + } +} + +@-moz-keyframes warn_CollapseRightBarAnimation { + 0% { + width: 78%; + } + 100% { + width: 100%; + } +} + +@-o-keyframes warn_CollapseRightBarAnimation { + 0% { + width: 78%; + } + 100% { + width: 100%; + } +} + +@keyframes warn_CollapseRightBarAnimation { + 0% { + width: 78%; + } + 100% { + width: 100%; + } +} + +/*---------------------------------------------- + LAYOUT +----------------------------------------------*/ +body { + background: rgb(24, 32, 42); + height: 100%; + font-size: 14px; + font-family: 'Open Sans', Helvetica, Arial, sans-serif; + line-height: 1; + margin: 0; + overflow: hidden; + padding: 0; + position: fixed; + width: 100%; +} + +main { + height: 100%; + margin: 0; + padding: 0; + position: relative; + width: 100%; +} + +#canvasArea { + position: relative; + margin: 0; + padding: 0; + width: 78%; +} + +#canvasArea #graph { + box-sizing: border-box; + margin: 0 0 2px 0; + background-color: #ecf0f1; + overflow: hidden; + padding: 0; + width: 100%; +} + +#canvasArea svg { + box-sizing: border-box; + margin: 0; + overflow: hidden; + padding: 0; +} + +#logo { + position: fixed; + /*padding: 10px;*/ + pointer-events: none; + /*border: solid 1px red;*/ +} + +#logo h2 { + color: #3498db; + margin: 0; + line-height: 0.7; + text-align: center; + font-size: 24px; +} + +#logo h2 span { + color: #34495E; + /*font-size: min(2vmin, 24px);*/ + font-size: 16px; +} + +@media screen and (max-device-height: 800px) { + #logo h2 { + font-size: calc(8px + 1.0vmin); + } + + #logo h2 span { + font-size: calc(3px + 1.0vmin); + } +} + +@media screen and (max-height: 800px) { + #logo h2 { + font-size: calc(8px + 1.0vmin); + } + + #logo h2 span { + font-size: calc(3px + 1.0vmin); + } +} + +@media screen and (max-device-width: 1200px) { + #logo h2 { + font-size: calc(8px + 1.0vmin); + } + + #logo h2 span { + font-size: calc(3px + 1.0vmin); + } +} + +@media screen and (max-width: 1200px) { + #logo h2 { + font-size: calc(8px + 1.0vmin); + } + + #logo h2 span { + font-size: calc(3px + 1.0vmin); + } +} + +.checkboxContainer input, .checkboxContainer label { + vertical-align: middle; +} + +.selected-ontology { + background-color: #eee; +} + +#credits { + border-top: solid 1px #bdc3c7; + font-size: 0.9em; +} + +.slideOption { + position: relative; + padding: 8px 5px; + outline: none; +} + +.slideOption .value { + float: right; + outline: none; +} + +.slideOption input[type="range"] { + box-sizing: border-box; + margin: 0; + outline: none; + -webkit-appearance: none; + -moz-appearance: none; + border-radius: 3px; + height: 12px; + width: 100%; + box-shadow: none; + left: 0; + position: relative; + transition: all 0.5s ease; + background-color: #eee; +} + +/*TRACK*/ +.slideOption input[type=range]::-webkit-slider-runnable-track { + -webkit-appearance: none; + background-color: #3071a9; + height: 3px; +} + +.slideOption input[type=range]::-moz-range-track { + -webkit-appearance: none; + background-color: #3071a9; + height: 3px; +} + +.slideOption input[type="range"]:hover { + outline: none; +} + +/*THUMB*/ +.slideOption input[type="range"]::-webkit-slider-thumb { + -webkit-appearance: none; + background-color: white; + border-radius: 3px; + border: solid 1px black; + transition: all 0.5s ease; + height: 10px; + width: 30px; + outline: none; + margin-top: -3px; +} + +.slideOption input[type="range"]::-moz-range-thumb { + -webkit-appearance: none; + background-color: white; + border-radius: 3px; + border: solid 1px black; + transition: all 0.5s ease; + height: 10px; + width: 30px; + outline: none; +} + +.slideOption input[type="range"]::-moz-range-thumb:hover { + background-color: #d90; + outline: none; +} + +.slideOption input[type="range"]::-webkit-slider-thumb:hover { + background-color: #d90; + /*color: #d90;*/ + outline: none; +} + +/*focus : remove border*/ +.slideOption input[type="range"]:focus { + outline: none; +} + +.slideOption input[type="range"]:active { + outline: none; +} + +.slideOption input[type="range"]::-moz-range-thumb:focus { + outline: none; +} + +.slideOption input[type="range"]::-moz-range-thumb:active { + outline: none; +} + +.slideOption input[type="range"]::-webkit-slider-thumb:focus { + outline: none; +} + +.slideOption input[type="range"]::-webkit-slider-thumb:active { + outline: none; +} + +.slideOption input[type="range"]:disabled { + box-sizing: border-box; + margin: 0; + outline: none; + -webkit-appearance: none; + -moz-appearance: none; + border-radius: 3px; + height: 12px; + width: 100%; + box-shadow: none; + left: 0; + position: relative; + transition: all 0.5s ease; + background-color: #787878; +} + +/*TRACK*/ +.slideOption input[type=range]:disabled::-webkit-slider-runnable-track { + -webkit-appearance: none; + background-color: #373737; + height: 3px; +} + +.slideOption input[type=range]:disabled::-moz-range-track { + -webkit-appearance: none; + background-color: #373737; + height: 3px; +} + +.slideOption input[type="range"]:disabled { + outline: none; +} + +/*THUMB*/ +.slideOption input[type="range"]:disabled::-webkit-slider-thumb { + -webkit-appearance: none; + background-color: #363636; + border-radius: 3px; + border: solid 1px #aaaaaa; + transition: all 0.5s ease; + height: 10px; + width: 30px; + outline: none; + margin-top: -3px; +} + +.slideOption input[type="range"]:disabled::-moz-range-thumb { + -webkit-appearance: none; + background-color: #aaaaaa; + border-radius: 3px; + border: solid 1px black; + transition: all 0.5s ease; + height: 10px; + width: 30px; + outline: none; +} + +.slideOption input[type="range"]:disabled::-moz-range-thumb { + background-color: #aaaaaa; + outline: none; +} + +.slideOption input[type="range"]:disabled::-webkit-slider-thumb { + background-color: #aaaaaa; + /*color: #d90;*/ + outline: none; +} + +.slideOption input[type="range"]:disabled:hover::-moz-range-thumb { + background-color: #404040; + outline: none; +} + +.slideOption input[type="range"]:disabled:hover::-webkit-slider-thumb { + background-color: #404040; + /*color: #d90;*/ + outline: none; +} + +#detailsArea { + top: 0; + right: 0; + bottom: 0; + color: #bdc3c7; + height: 100%; + width: 22%; + overflow-y: auto; + overflow-x: hidden; + position: fixed; + border-left: 1px solid #34495E; +} + +#detailsArea h1 { + border-bottom: solid 1px #34495e; + color: #ecf0f1; + display: block; + font-weight: 100; + font-size: 1.5em; + margin: 0; + padding: 10px 0; + text-align: center; +} + +#generalDetails { + width: auto; + box-sizing: border-box; + height: 100%; +} + +#generalDetails span #about { + border-bottom: solid 1px #34495e; + display: block; + padding: 10px; + text-align: center; + word-wrap: break-word; + color: #69c; +} + +#generalDetails h4 { + background: rgb(27, 37, 46); + color: #ecf0f1; + display: block; + font-size: 1.1em; + font-weight: 100; + margin: 0; + padding: 10px 0; + text-align: center; +} + +#detailsArea #generalDetails h5 { + border-bottom: solid 1px #34495e; + font-size: 0.9em; + font-weight: 100; + margin: 0; + padding: 5px; + text-align: center; +} + +#description { + text-align: justify; +} + +.accordion-container p { + font-size: 0.9em; + line-height: 1.3; + margin: 5px 10px; +} + +.statisticDetails span { + font-weight: 100; + font-style: italic; + margin: 10px 0; + padding: 10px; +} + +.statisticDetails div { + font-weight: 100; + font-style: italic; + margin: 10px 0; + padding: 0 10px; + display: inline; +} + +#selection-details .propDetails a { + color: #69c; +} + +#selection-details .propDetails > span { + font-weight: 100; + font-style: italic; + padding: 0 10px; +} + +#selection-details #classEquivUri span, #selection-details #disjointNodes span { + padding: 0; +} + +#selection-details .propDetails div { + font-weight: 100; + font-style: italic; + margin: 10px 0; + padding: 0 10px; + display: inline; +} + +#selection-details .propDetails div span { + padding: 0; +} + +/* give subclass property the same background color as the canvas */ +.subclass { + fill: #ecf0f1; +} + +.accordion-trigger { + background: #24323e; + cursor: pointer; + padding: .5em; +} + +.accordion-trigger.accordion-trigger-active:before { + padding-right: 4px; + content: "\25BC" +} + +.accordion-trigger:not(.accordion-trigger-active):before { + padding-right: 4px; + content: "\25BA" +} + +.accordion-container.scrollable { + max-height: 40%; + overflow: auto; +} + +.small-whitespace-separator { + height: 3px; +} + +#language { + background: transparent; + border: 1px solid #34495E; + color: #ecf0f1; +} + +#language option { + background-color: #24323e; +} + +.converter-form:not(:first-child) { + margin-top: 5px; +} + +.converter-form label { + display: inline-block; + line-height: normal; +} + +.converter-form input { + box-sizing: border-box; + height: 20px; + width: 74%; + border: 1px solid #34495E; +} + +.converter-form button { + cursor: pointer; + float: right; + height: 20px; + padding: 0; + width: 25%; + border: 1px solid #34495E; + background-color: #ecf0f1; +} + +#file-converter-label { + border: 1px solid #34495E; + box-sizing: border-box; + cursor: pointer; + height: 20px; + width: 74%; +} + +#killWarning { + cursor: pointer; + color: #ffffff; + font-weight: bold; +} + +/*#copyBt{*/ +/*box-sizing: border-box;*/ +/*color: #000000;*/ +/*float:right;*/ +/*position:absolute;*/ +/*right:2px;*/ +/*padding: 2px 7px 3px 7px;*/ +/*border: 1px solid #000000;*/ +/*background-color: #ecf0f1;*/ +/*cursor: pointer;*/ +/*}*/ + +#copyBt { + box-sizing: border-box; + height: 20px; + width: 31%; + border: 1px solid #34495E; +} + +#sidebarExpandButton { + height: 24px; + width: 24px; + /*background-color: white;*/ + /*box-shadow: 0px 1px 1px grey;*/ + box-sizing: border-box; + top: 10px; + color: #000000; + float: right; + position: absolute; + right: 0; + border: 1px solid #000000; + + text-align: center; + font-size: 1.5em; + cursor: pointer; +} + +.dropdownMenuClass { + height: 20px; + /*width: 69%;*/ + float: right; + border: 1px solid #34495E; + background-color: #34495E; + color: white; + /*border-bottom: 1px solid #d90;*/ + text-align: left; + width: auto; +} + +#typeEditForm_datatype { + padding-top: 5px; +} + +#typeEditor { + width: 165px; +} + +#typeEditor_datatype { + width: 165px; +} + +#leftSideBarCollapseButton { + box-sizing: border-box; + top: 50px; + /*padding:5px;*/ + color: #000000; + position: absolute; + left: 200px; + border: 1px solid #000000; + /*background-color: #ecf0f1;*/ + cursor: pointer; + width: 24px; + height: 24px; + font-size: 1.5em; + text-align: center; +} + +#leftSideBarCollapseButton:hover { + background-color: #d90; +} + +#sidebarExpandButton:hover { + background-color: #d90; +} + +.spanForCharSelection { + padding-left: 25px; +} + +.nodeEditSpan { + color: #000; + background-color: #fff; + text-align: center; + /*overflow: auto;*/ + border: none; + padding-top: 6px; +} + +.nodeEditSpan:focus { + outline: none; + border: none; +} + +.foreignelements { + /*width: 80px;*/ + /*height: 3px;*/ + border: none; +} + +.foreignelements:focus { + outline: none; + border: none; +} + +#leftSideBarContent { + color: #000000; + float: left; + position: absolute; + left: 0; + /*border: 1px solid #000000;*/ + background-color: rgb(24, 32, 42); + width: 100%; + height: 100%; +} + +#leftSideBarContent > h3 { + color: #ecf0f1; + display: block; + font-size: 1.1em; + font-weight: 100; + margin: 0 0 5px 0; + padding: 10px 0; + text-align: left; +} + +#generalDetailsEdit { + /*color: #ecf0f1;*/ + color: #ecf0f1; +} + +#generalDetailsEdit > div { + padding: 5px; +} + +#generalDetailsEdit > h3 { + color: #ecf0f1; + display: block; + font-size: 1.1em; + font-weight: 100; + margin: 0 0 5px 0; + padding: 10px 0; + text-align: left; +} + +.subAccordion { + color: #ecf0f1; + display: block; + font-size: 0.8em; + font-weight: 100; + margin: 0; + padding: 5px; + text-align: left; +} + +.subAccordionDescription { + padding: 0 5px; +} + +.boxed { + padding: 0 5px; +} + +.separatorLineRight { + border-right: 1px solid #f00; +} + +.editPrefixButton:hover { + color: #ff972d; + cursor: pointer; +} + +.editPrefixIcon:hover { + stroke: #ff972d; + stroke-width: 1px; + cursor: pointer; +} + +.editPrefixIcon { + stroke: #fffff; + stroke-width: 1px; + cursor: pointer; +} + +.deletePrefixButton:hover { + color: #ff972d; + cursor: pointer; +} + +.deletePrefixButton { + color: #ff0000; + cursor: pointer; +} + +.invisiblePrefixButton { + cursor: default; + color: rgb(24, 32, 42); +} + +#containerForAddPrefixButton { + width: 100%; + margin-top: 5px; +} + +.roundedButton { + border: 1px solid #000000; + border-radius: 20px; + padding: 0 5px; + background: #fff; + cursor: pointer; + color: black; + outline: none; +} + +.roundedButton:hover { + background: #318638; + cursor: pointer; + color: #fff; + outline: none; +} + +#prefixURL_Description { + padding: 5px 0 0 0; +} + +.prefixIRIElements { + display: inline-block; + padding: 3px; + border-bottom: 1px solid #34495E; + width: 100% +} + +.prefixInput { + width: 30px; + display: inline-block; + margin-right: 5px; +} + +.prefixURL { + width: 100px; + display: inline-block; + paddig-left: 5px; +} + +.selectedDefaultElement { + text-align: left; + white-space: nowrap; + overflow: hidden; + text-overflow: ellipsis; + display: inline-block; + max-width: 200px; +} + +#editHeader { + color: #ecf0f1; + background-color: #394f5a; + display: block; + font-size: 1.1em; + font-weight: 100; + text-align: center; +} + +#leftHeader { + color: #ecf0f1; + background-color: #394f5a; + display: block; + font-size: 1.1em; + font-weight: 100; + text-align: center; + padding: 10px 0; + margin: 0; +} + +.containerForDefaultSelection { + color: #ecf0f1; + display: block; + font-size: 1.1em; + font-weight: 100; + margin: 0; + padding: 10px 20px; + text-align: left; +} + +.defaultSelected { + color: #a15d05; + background-color: #283943; +} + +.containerForDefaultSelection:hover { + color: #f19505; + background-color: #394f5a; + display: block; + cursor: pointer; +} + +#containerForLeftSideBar { + top: 50px; + float: left; + position: absolute; + background-color: #1b252e; + left: 0; + width: 200px; + height: 200px; + overflow-y: auto; + overflow-x: hidden; +} + +#leftSideBar { + width: 100%; + background-color: rgb(24, 32, 42); +} + +#loading-info { + box-sizing: border-box; + position: absolute; + text-align: center; + + width: 100%; + height: 80%; + top: 0; +} + +#loading-info > div { + display: inline-block; + color: #ffffff; + background-color: #18202A; + border-bottom-left-radius: 2px; + border-bottom-right-radius: 2px; +} + +#loading-info > * > * { + padding: 5px; +} + +#loading-info { + pointer-events: none; +} + +#loading-progress { + pointer-events: auto; + min-width: 220px; + border-radius: 10px; +} + +#show-loadingInfo-button { + font-size: 12px; + color: #fff; + cursor: pointer; + text-align: center; +} + +#loadingIndicator_closeButton:hover { + color: #ff972d; + cursor: pointer; + +} + +#loadingIndicator_closeButton { + color: #ffe30f; + cursor: pointer; + padding-bottom: 5px; + float: right; +} + +.busyProgressBar { + background-color: #000; + height: 25px; + position: relative; + animation: busy 2s linear infinite; +} + +@-webkit-keyframes busy { + 0% { + left: 0%; + } + 50% { + left: 80%; + } + 100% { + left: 0%; + } +} + +#bulletPoint_container { + padding-left: 15px; + margin-top: 0px; + margin-bottom: 0px; +} + +#bulletPoint_container > div { + margin-left: -15px; +} + +#loadingInfo-container { + box-sizing: border-box; + text-align: left; + line-height: 1.2; + padding-top: 5px; + overflow: auto; + /*white-space: nowrap;*/ + /*min-width: 250px;*/ + height: 120px; + min-height: 40px; + background-color: #3c3c3c; + +} + +#error-description-button { + margin: 5px 0 0 0; + font-size: 12px; + color: #69c; + cursor: pointer; + text-align: center; +} + +#error-description-container { + box-sizing: border-box; + text-align: left; +} + +#error-description-container pre { + background-color: #34495E; + padding: 2px; + margin: 0; + white-space: pre-wrap; + max-height: calc(100vh - 125px); + max-width: 75vw; + overflow: auto; +} + +.spin { + display: inline-block; + -webkit-animation: spin 2s infinite linear; + animation: spin 2s infinite linear; +} + +@-webkit-keyframes spin { + 0% { + -webkit-transform: rotate(0deg); + transform: rotate(0deg); + } + 100% { + -webkit-transform: rotate(359deg); + transform: rotate(359deg); + } +} + +@keyframes spin { + 0% { + -webkit-transform: rotate(0deg); + transform: rotate(0deg); + } + 100% { + -webkit-transform: rotate(359deg); + transform: rotate(359deg); + } +} + +.truncate { + max-width: 250px; + white-space: nowrap; + overflow: hidden; + text-overflow: ellipsis; +} + +.color-mode-switch { + float: right; + width: 90px; + cursor: pointer; + height: 20px; + padding: 0; + border: 0; + color: #555; + background-color: #ECEEEF; + box-shadow: 0 1px 4px rgba(0, 0, 0, 0.2), inset 0 0 3px rgba(0, 0, 0, 0.1); +} + +.color-mode-switch:focus { + outline-width: 0; +} + +.color-mode-switch.active { + color: #FFF; + background-color: #32CD32; + box-shadow: inset 0 1px 4px rgba(0, 0, 0, 0.2), inset 0 0 3px rgba(0, 0, 0, 0.1); +} + +/* adding button pulse animation*/ +.filterMenuButtonHighlight { + background-color: #d90; +} + +@-webkit-keyframes buttonAnimation { + 0% { + background-color: unset; + } + 100% { + background-color: #d90; + } +} + +@-moz-keyframes buttonAnimation { + 0% { + background-color: unset; + } + 100% { + background-color: #d90; + } +} + +@-o-keyframes buttonAnimation { + 0% { + background-color: unset; + } + 100% { + background-color: #d90; + } +} + +@keyframes buttonAnimation { + 0% { + background-color: unset; + } + 100% { + background-color: #d90; + } +} + +.buttonPulse { + -webkit-animation-name: buttonAnimation; + -moz-animation-name: buttonAnimation; + -o-animation-name: buttonAnimation; + animation-name: buttonAnimation; + + -webkit-animation-duration: 0.5s; + -moz-animation-duration: 0.5s; + -o-animation-duration: 0.5s; + animation-duration: 0.5s; + + -webkit-animation-iteration-count: 3; + -moz-animation-iteration-count: 3; + -o-animation-iteration-count: 3; + animation-iteration-count: 3; + + -webkit-animation-timing-function: linear; + -moz-animation-timing-function: linear; + -o-animation-timing-function: linear; + animation-timing-function: linear; + + +} + +/*swipe bar definition*/ + +/*Overwriting individual menu widths*/ +#m_about { + max-width: 200px; + width: 200px; + position: absolute; + +} + +#m_modes { + max-width: 160px; + width: 160px; + position: absolute; +} + +#m_filter { + max-width: 170px; + width: 170px; + position: absolute; +} + +#m_gravity { + max-width: 180px; + width: 180px; + position: absolute; +} + +#m_export { + max-width: 160px; + width: 160px; + position: absolute; + +} + +#exportedUrl { + width: 100px; +} + +#m_select { + max-width: 300px; + width: 300px; + position: absolute; +} + +#m_config { + max-width: 240px; + width: 240px; + position: absolute; +} + +#m_search { + max-width: 250px; + white-space: nowrap; + overflow: hidden; + text-overflow: ellipsis; +} + +/***************** REWRITING MENU ELEMENT CONTAINERS ***********************/ +/*Container which holds the swipeBar*/ +#swipeBarContainer { + position: fixed; + width: 77.8%; + height: 40px; + margin: 0; + padding: 0; + bottom: 0; +} + +/*Scroll-able container for the menu entries */ +#menuElementContainer { + margin: 0; + padding: 0; + overflow-x: auto; + overflow-y: hidden; + white-space: nowrap; + text-align: right; + list-style-type: none; +} + +/*Style for the individual menu entries*/ +#menuElementContainer > li { + display: inline-block; + box-sizing: border-box; + text-align: left; + position: relative; + height: 40px; + font-size: 14px; + color: #ffffff; + padding: 12px 0 0; + margin-left: -4px; +} + +/*Font-color Style for menu entries */ +#menuElementContainer > li > a { + color: #fff; + padding: 9px 12px 12px 30px; +} + +.menuElementSvgElement { + height: 20px; + width: 20px; + display: block; + position: absolute; + top: 10px; + left: 8px; +} + +.btn_shadowed { + background-color: #fefefe; + box-shadow: 1px 1px 1px gray; +} + +.reloadCachedOntologyIcon { + height: 20px; + width: 108px; + display: block; + position: absolute; + top: 20px; + left: 3px; + /*background: #ecf0f1;;*/ + border: solid 1px black; + border-radius: 10px; + cursor: pointer; +} + +.reloadCachedOntologyIcon:disabled { + background: #f4f4f4; + cursor: auto; + border: solid 1px darkgray; + +} + +.reloadCachedOntologyIcon:hover { + background: #d90; + cursor: pointer; +} + +.disabledReloadElement { + cursor: auto; + background: #F4F4F4; + pointer-events: auto; + border: solid 1px darkgray; + color: #bbbbbb; +} + +.disabledReloadElement:hover { + cursor: auto; + background: #EEEEEE; + pointer-events: auto; +} + +#menuElementContainer > li > input { + color: #000; + /*padding : 0 0.3em 0 1.5em;*/ + padding: 0.1em .3em 0.1em 1.5em; + white-space: nowrap; + overflow: hidden; + text-overflow: ellipsis; + width: 120px; +} + +/*Hovered behavior for the menu entries*/ +#menuElementContainer > li > a:hover { + box-sizing: border-box; + background: #1B252E; + /*background : #d90;*/ + color: #bdc3c7; + +} + +#empty:hover { + box-sizing: border-box; + background: #e1e1e1; + /*background : #d90;*/ + color: #2980b9; +} + +#empty.disabled { + pointer-events: none; + cursor: default; + color: #979797; +} + +.disabled { + pointer-events: none; + cursor: default; + color: #979797; +} + +/*ToolTip Menu Definition*/ +.toolTipMenu { + -webkit-box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175); + box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175); + box-sizing: border-box; + background-color: #ffffff; + border: 1px solid rgba(0, 0, 0, 0.15); + border-bottom: none; + border-radius: 4px 4px 0 0; + bottom: 0; + display: none; + font-size: 14px; + list-style: none; + /*max-width: 300px;*/ + margin: 0; + padding: 0; + white-space: normal; + position: absolute; + z-index: 99; +} + +.toolTipMenu > li:first-of-type { + border: none; +} + +.toolTipMenu a { + color: #2980b9; +} + +.toolTipMenu > li { + border-top: solid 1px #bdc3c7; +} + +.toolTipMenu li { + color: #2980b9; + display: block; +} + +/*MenuElement hovering enables the toolTip of the corresponding menu*/ +#menuElementContainer > li:hover .toolTipMenu { + display: block; +} + +#menuElementContainer li > ul.toolTipMenu li a:hover { + background: #e1e1e1; +} + +/****************************************************************************/ +/*ScrollButton behavior*/ +#scrollLeftButton { + height: 30px; + width: 30px; + padding: 5px 0 5px 10px; + color: #fff; + cursor: pointer; + position: absolute; + margin-top: -2px; + font-size: 2em; + background-color: #24323e; + left: 0; +} + +#scrollLeftButton:focus { + outline: none; +} + +#scrollLeftButton:before { + content: "<"; +} + +/*Right Scroll Button*/ +#scrollRightButton { + height: 30px; + width: 30px; + padding: 5px 0 5px 10px; + color: #fff; + cursor: pointer; + position: absolute; + margin-top: -2px; + font-size: 2em; + background-color: #24323e; + right: 0; +} + +#scrollRightButton:focus { + outline: none; +} + +#scrollRightButton:hover { + color: #bdc3c7; +} + +#scrollLeftButton:hover { + color: #bdc3c7; +} + +#scrollRightButton:before { + content: ">"; +} + +#centerGraphButton, #zoomInButton, #zoomOutButton { + border: 1px solid #000000; + text-align: center; + margin: -1px 0 0 0; + font-size: 1.5em; + padding: 0; + height: 28px; +} + +.noselect { + -webkit-touch-callout: none; /* iOS Safari */ + -webkit-user-select: none; /* Safari */ + -khtml-user-select: none; /* Konqueror HTML */ + -moz-user-select: none; /* Firefox */ + -ms-user-select: none; /* Internet Explorer/Edge */ + user-select: none; + /* Non-prefixed version, currently + supported by Chrome and Opera */ +} + +#zoomOutButton { + line-height: 22px; +} + +#centerGraphButton { + line-height: 25px; +} + +#zoomInButton { + line-height: 25px; +} + +#zoomSlider > p:hover { + background-color: #d90; +} + +#zoomSliderParagraph { + color: #000000; + padding-top: 5px; + margin: -1px 0 0 0; + border: 1px solid #000000; + /*background-color: #ecf0f1;*/ + /*width: 28px;*/ + height: 150px; +} + +p#zoomSliderParagraph:hover { + background-color: #fff; +} + +/*todo put this in a proper position*/ +#zoomSlider { + width: 28px; + margin-top: -2px; + padding: 0; + font-size: 1.5em; + cursor: pointer; + position: absolute; + right: 20px; + bottom: 20px; + color: #000; + /*background-color: #ecf0f1;*/ + box-sizing: border-box; +} + +/****************************************************************************/ +/*Definition for the Icons before*/ +#menuElementContainer > li > a::before { + font-size: 1em; + margin: 0; + padding: 0 6px 0 0; +} + +#menuElementContainer a.highlighted { + background-color: #d90; +} + +/*#search-input-text.searchInputText {*/ +/*!*padding: 0 0.2em;*!*/ +/*color: black;*/ +/*}*/ + +.inner-addon { + position: relative; +} + +.searchIcon { + position: absolute; + /*padding: 0.15em 0;*/ + width: 17px; + height: 17px; + + pointer-events: none; +} + +.gearIcon { + position: absolute; + width: 17px; + height: 17px; + pointer-events: none; + left: -5px; +} + +/*#search-input-text::before {*/ +/*!*padding: 0 0.2em;*!*/ +/*!*color: black;*!*/ +/*font-size: 1.4em; !* todo : test this *!*/ +/*!*content: "\2315";*!*/ +/*content: "⚲";*/ +/*color: white;*/ +/*padding: 0;*/ +/*-webkit-transform: rotate(-45deg);*/ +/*!*content: "\2315" or "\1F50D"*!;*/ +/*display: inline-block;*/ +/*position: relative;*/ +/*top: 2px;*/ +/*left:-5px;*/ +/*}*/ + +li#c_search { + padding: 0 5px; + margin-left: 5px; + height: 20px; +} + +/*Menu icons before the links selection */ +/*#c_select > a::before { content: "\2263"; }*/ +/*#c_export > a::before { content: "\21E4"; }*/ +/*#c_gravity > a::before { content: "\2299"; }*/ +/*#c_filter > a::before { content: "\25BD"; }*/ +/*#c_modes > a::before { content: "\2606"; }*/ +/*#c_reset > a::before { content: "\21BB"; }*/ +/*#c_about > a::before { content: "\00A9"; }*/ + +li#c_locate { + padding: 0; +} + +#c_locate > a { + font-size: 2em; + padding: 0; +} + +a#pause-button { + padding: 12px 12px; +} + +/*Pause Button has a different behavior*/ +a#pause-button.paused::before { + content: "\25BA"; +} + +a#pause-button.paused:hover { + background-color: #d90; + color: #fff; +} + +a#pause-button:not(.paused)::before { + content: "II"; +} + +.toolTipMenu li:hover { + background-color: #e1e1e1; +} + +#emptyLiHover { + background-color: #FFFFFF; +} + +#emptyLiHover:hover { + background-color: #FFFFFF; +} + +.toggleOption li:hover { + background-color: #e1e1e1; +} + +.toggleOption { + padding: 8px 5px; +} + +#converter-option:hover { + background-color: #ffffff; +} + +.toolTipMenu li a:only-child, .option { + display: block; + float: none; + padding: 8px 5px; +} + +.customLocate { + padding: 0; + background-color: #32CD32; +} + +a#locateSearchResult { + padding-bottom: 0; + padding-top: 50px; + position: relative; + top: 5px; +} + +/*#sliderRange{*/ +/*padding: 0;*/ +/*margin: 7px 0 0 0;*/ +/*width:100%;*/ +/*height:5px;*/ +/*-webkit-appearance: none;*/ +/*outline: none;*/ +/*}*/ + +#zoomSliderElement { + color: #000; + position: relative; + padding-top: 0; + width: 155px; + height: 24px; + background-color: transparent; + -webkit-transform-origin-x: 73px; + -webkit-transform-origin-y: 73px; + -webkit-transform: rotate(-90deg); + -moz-transform-origin: 73px 73px; + transform: rotate(-90deg); + transform-origin: 73px 73px; + -webkit-appearance: none; + outline: none; + margin: 4px 0; +} + +/* ------------------ Zoom Slider styles --------------------------*/ +#zoomSliderElement::-webkit-scrollbar { + height: 0; +} + +#zoomSliderElement:hover { + cursor: crosshair; +} + +/*TRACK*/ +#zoomSliderElement::-webkit-slider-runnable-track { + width: 100%; + height: 5px; + cursor: pointer; + background: #3071a9; +} + +#zoomSliderElement::-moz-range-track { + width: 100%; + height: 5px; + cursor: pointer; + background: #3071a9; +} + +/*Thumb*/ +#zoomSliderElement::-webkit-slider-thumb { + -webkit-appearance: none; + border: 1px solid #000000; + height: 10px; + width: 30px; + margin-right: 50px; + border-radius: 3px; + background: #fff; + cursor: pointer; + outline: none; + margin-top: -3px; +} + +#zoomSliderElement::-ms-thumb { + -webkit-appearance: none; + border: 1px solid #000000; + height: 10px; + width: 30px; + margin-right: 50px; + border-radius: 3px; + background: #fff; + cursor: pointer; + outline: none; + margin-top: -3px; +} + +#zoomSliderElement::-ms-thumb:hover { + -webkit-appearance: none; + border: 1px solid #000000; + height: 10px; + width: 30px; + margin-right: 50px; + border-radius: 3px; + background: #d90; + cursor: pointer; + outline: none; + margin-top: -3px; +} + +#zoomSliderElement::-webkit-slider-thumb:hover { + -webkit-appearance: none; + border: 1px solid #000000; + height: 10px; + width: 30px; + margin-right: 50px; + border-radius: 3px; + background: #d90; + cursor: pointer; + outline: none; + margin-top: -3px; +} + +#zoomSliderElement::-moz-range-thumb { + border: 1px solid #000000; + height: 10px; + width: 30px; + border-radius: 3px; + /*background: #ffffff;*/ + cursor: pointer; + outline: none; +} + +#zoomSliderElement::-moz-range-thumb:hover { + border: 1px solid #000000; + height: 10px; + width: 30px; + border-radius: 3px; + background: #d90; + cursor: pointer; + outline: none; +} + +#zoomSliderElement::-moz-focus-outer { + border: 0; +} + +#locateSearchResult:focus { + outline: none; + +} + +a#locateSearchResult.highlighted:hover { + background-color: #d90; + color: red; +} + +a#locateSearchResult { + outline: none; + padding-bottom: 0; + padding-top: 0; + position: relative; + top: 5px; +} + +/*Editor hints*/ +#editorHint { + padding: 5px 5px; + position: absolute; + text-align: center; + width: 100%; + pointer-events: none; +} + +#editorHint label { + pointer-events: auto; + float: right; + padding: 5px 5px; + color: #ffdd00; +} + +#editorHint label:hover { + text-decoration: underline; + cursor: pointer; +} + +#editorHint > div { + pointer-events: auto; + text-align: left; + display: inline-block; + color: #ffffff; + font-size: 0.8em; + background-color: #18202A; + padding: 5px 5px; + border-radius: 5px; + +} + +#WarningErrorMessagesContainer { + position: absolute; + text-align: center; + top: 0; + pointer-events: none; +} + +/*Editor hints*/ +#WarningErrorMessages { + position: relative; + /*text-align: center;*/ + width: 50%; + pointer-events: auto; + margin: 10px 0; + padding-right: 12px; + overflow-y: auto; + overflow-x: hidden; +} + +#WarningErrorMessages label { + pointer-events: auto; + float: right; + padding: 5px 5px; + color: #ffdd00; +} + +#WarningErrorMessages span { + pointer-events: auto; + float: right; + padding: 5px 5px; +} + +#WarningErrorMessages label:hover { + text-decoration: underline; + cursor: pointer; +} + +#WarningErrorMessages > div { + pointer-events: auto; + text-align: left; + display: inline-block; + color: #ffffff; + font-size: 0.8em; + background-color: #18202A; + padding: 5px 5px; + border-radius: 10px; + border: solid 1px #ecf0f1; + width: 70%; + +} + +#WarningErrorMessagesContent > ul { + -webkit-padding-start: 20px; + padding: 0 16px; + +} + +#WarningErrorMessagesContent > ul > li { + padding: 5px; +} + +.converter-form-Editor { + /*display: inline-block;*/ +} + +.textLineEditWithLabel { + display: inline-block; + width: 100%; + border-bottom: 1px solid #34495E; + padding: 2px 0; + +} + +.converter-form-Editor label { + /*//display: inline-block;*/ + line-height: normal; +} + +.descriptionTextClass { + background-color: #34495E; + color: white; +} + +.prefixIRIElements input { + border: 1px solid #34495E; + background-color: #34495E; + color: white; +} + +.prefixIRIElements input:disabled { + background-color: rgb(24, 32, 42); + border: 1px solid rgb(24, 32, 42); + color: white; +} + +.converter-form-Editor input { + /*box-sizing: border-box;*/ + /*height: 18px;*/ + /*width: 69%;*/ + float: right; + border: 1px solid #34495E; + background-color: #34495E; + color: white; + /*border-bottom: 1px solid #d90;*/ + /*text-align: center;*/ + /*display: inline-block;*/ +} + +.converter-form-Editor input:disabled { + background-color: #545350; + border: 1px solid #34495E; + color: #939798; +} + +.disabledLabelForSlider { + color: #808080; +} diff --git a/doc/releases/0.1.0/parameters/webvowl/css/webvowl.css b/doc/releases/0.1.0/parameters/webvowl/css/webvowl.css new file mode 100644 index 0000000..bd06623 --- /dev/null +++ b/doc/releases/0.1.0/parameters/webvowl/css/webvowl.css @@ -0,0 +1,296 @@ +/*----------------------------------------------------------------- + VOWL graphical elements (part of spec) - mixed CSS and SVG styles +-----------------------------------------------------------------*/ + +/*-------- Text --------*/ +.text { + font-family: Helvetica, Arial, sans-serif; + font-size: 12px; +} + +.subtext { + font-size: 9px; +} + +.text.instance-count { + fill: #666; +} + +.external + text .instance-count { + fill: #aaa; +} + +.cardinality { + font-size: 10px; +} + +.text, .embedded { + pointer-events: none; +} + +/*------- Colors ------*/ +.class, .object, .disjoint, .objectproperty, .disjointwith, .equivalentproperty, .transitiveproperty, .functionalproperty, .inversefunctionalproperty, .symmetricproperty, .allvaluesfromproperty, .somevaluesfromproperty { + fill: #acf; +} + +.label .datatype, .datatypeproperty { + fill: #9c6; +} + +.rdf, .rdfproperty { + fill: #c9c; +} + +.literal, .node .datatype { + fill: #fc3; +} + +.deprecated, .deprecatedproperty { + fill: #ccc; +} + +.external, .externalproperty { + /*fill: #36c;*/ +} + +path, .nofill { + fill: none; +} + +marker path { + fill: #000; +} + +.class, path, line, .fineline { + stroke: #000; +} + +.white, .subclass, .subclassproperty, .external + text { + fill: #fff; +} + +.class.hovered, .property.hovered, .cardinality.hovered, .cardinality.focused, .filled.hovered, .filled.focused, .values-from.filled.hovered { + fill: #f00 !important; + cursor: pointer; +} + +.hoveredForEditing { + fill: #f00 !important; + cursor: pointer; +} + +.feature { + fill: #f00; + cursor: pointer; +} + +@-webkit-keyframes pulseAnimation { + 0% { + -webkit-transform: scale(1.5); + stroke-width: 3.33; + } + 50% { + stroke-width: 4; + } + 100% { + -webkit-transform: scale(1.0); + stroke-width: 5; + } +} + +@-moz-keyframes pulseAnimation { + 0% { + -webkit-transform: scale(1.5); + stroke-width: 3.33; + } + 50% { + stroke-width: 4; + } + 100% { + -webkit-transform: scale(1.0); + stroke-width: 5; + } +} + +@-o-keyframes pulseAnimation { + 0% { + -webkit-transform: scale(1.5); + stroke-width: 3.33; + } + 50% { + stroke-width: 4; + } + 100% { + -webkit-transform: scale(1.0); + stroke-width: 5; + } +} + +@keyframes pulseAnimation { + 0% { + -webkit-transform: scale(1.5); + stroke-width: 3.33; + } + 50% { + stroke-width: 4; + } + 100% { + -webkit-transform: scale(1.0); + stroke-width: 5; + } +} + +.searchResultA { + fill: none; + stroke-width: 5; + stroke: #f00; + -webkit-animation-name: pulseAnimation; + -moz-animation-name: pulseAnimation; + -o-animation-name: pulseAnimation; + animation-name: pulseAnimation; + + -webkit-animation-duration: 0.8s; + -moz-animation-duration: 0.8s; + -o-animation-duration: 0.8s; + animation-duration: 0.8s; + + -webkit-transform: translateZ(0); + -o-transform: translateZ(0); + -webkit-animation-iteration-count: 3; + -moz-animation-iteration-count: 3; + -o-animation-iteration-count: 3; + animation-iteration-count: 3; + + -webkit-animation-timing-function: linear; + -moz-animation-timing-function: linear; + -o-animation-timing-function: linear; + animation-timing-function: linear; + +} + +/* a class for not animated search results (hovered over node)*/ +.searchResultB { + fill: none; + stroke-width: 5; + stroke: #f00; +} + +.hovered-MathSymbol { + fill: none; + stroke: #f00 !important; +} + +.focused, path.hovered { + stroke: #f00 !important; +} + +.indirect-highlighting, .feature:hover { + fill: #f90; + cursor: pointer; +} + +.feature_hover { + fill: #f90; + cursor: pointer; +} + +.values-from { + stroke: #69c; +} + +.symbol, .values-from.filled { + fill: #69c; +} + +/*------- Strokes ------*/ +.class, path, line { + stroke-width: 2; +} + +.fineline { + stroke-width: 1; +} + +.dashed, .anonymous { + stroke-dasharray: 8; +} + +.dotted { + stroke-dasharray: 3; +} + +rect.focused, circle.focused { + stroke-width: 4px; +} + +.nostroke { + stroke: none; +} + +/*----------------------------------------------------------------- + Additional elements for the WebVOWL demo (NOT part of spec) +-----------------------------------------------------------------*/ + +.addDataPropertyElement { + fill: #9c6 !important; + cursor: pointer; + stroke-width: 2; + stroke: black; +} + +.addDataPropertyElement:hover { + fill: #f90 !important; + cursor: pointer; + stroke-width: 2; + stroke: black; +} + +.superHiddenElement { + fill: rgba(255, 153, 0, 0.4); + cursor: pointer; + stroke-width: 0; + stroke: black; + /*opacity:0;*/ +} + +.superOpacityElement { + opacity: 0; +} + +.deleteParentElement:hover { + fill: #f90; + cursor: pointer; + stroke-width: 2; + stroke: black; +} + +.deleteParentElement { + fill: #f00; + cursor: pointer; + stroke-width: 2; + stroke: black; +} + +.classNodeDragPath { + stroke: black; + stroke-width: 2px; +} + +.classDraggerNodeHovered { + fill: #f90; + stroke: black; + stroke-width: 2px; + cursor: pointer; +} + +.classDraggerNode { + fill: #acf; + stroke: black; + stroke-width: 2px; +} + +marker path { + /* Safari and Chrome workaround for inheriting the style of its link. + Use any value that is larger than the length of the marker path. */ + stroke-dasharray: 100; +} diff --git a/doc/releases/0.1.0/parameters/webvowl/data/foaf.json b/doc/releases/0.1.0/parameters/webvowl/data/foaf.json new file mode 100644 index 0000000..4897985 --- /dev/null +++ b/doc/releases/0.1.0/parameters/webvowl/data/foaf.json @@ -0,0 +1,2894 @@ +{ + "_comment" : "Created with OWL2VOWL (version 0.3.7), http://vowl.visualdataweb.org", + "header" : { + "languages" : [ "undefined" ], + "baseIris" : [ "http://schema.org", "http://www.w3.org/2000/01/rdf-schema", "http://www.w3.org/2003/01/geo/wgs84_pos", "http://purl.org/dc/terms", "http://www.w3.org/2001/XMLSchema", "http://xmlns.com/foaf/0.1", "http://www.w3.org/2000/10/swap/pim/contact", "http://www.w3.org/2004/02/skos/core" ], + "prefixList" : { + "owl" : "http://www.w3.org/2002/07/owl#", + "rdf" : "http://www.w3.org/1999/02/22-rdf-syntax-ns#", + "wot" : "http://xmlns.com/wot/0.1/", + "xsd" : "http://www.w3.org/2001/XMLSchema#", + "dc" : "http://purl.org/dc/elements/1.1/", + "xml" : "http://www.w3.org/XML/1998/namespace", + "vs" : "http://www.w3.org/2003/06/sw-vocab-status/ns#", + "foaf" : "http://xmlns.com/foaf/0.1/", + "rdfs" : "http://www.w3.org/2000/01/rdf-schema#" + }, + "title" : { + "undefined" : "Friend of a Friend (FOAF) vocabulary" + }, + "iri" : "http://xmlns.com/foaf/0.1/", + "description" : { + "undefined" : "The Friend of a Friend (FOAF) RDF vocabulary, described using W3C RDF Schema and the Web Ontology Language." + }, + "other" : { + "title" : [ { + "identifier" : "title", + "language" : "undefined", + "value" : "Friend of a Friend (FOAF) vocabulary", + "type" : "label" + } ] + } + }, + "namespace" : [ ], + "class" : [ { + "id" : "3", + "type" : "owl:Thing" + }, { + "id" : "9", + "type" : "owl:Class" + }, { + "id" : "1", + "type" : "owl:equivalentClass" + }, { + "id" : "18", + "type" : "owl:Thing" + }, { + "id" : "19", + "type" : "owl:Thing" + }, { + "id" : "5", + "type" : "owl:Thing" + }, { + "id" : "20", + "type" : "rdfs:Literal" + }, { + "id" : "8", + "type" : "rdfs:Literal" + }, { + "id" : "11", + "type" : "owl:Class" + }, { + "id" : "21", + "type" : "owl:Thing" + }, { + "id" : "22", + "type" : "rdfs:Literal" + }, { + "id" : "24", + "type" : "rdfs:Literal" + }, { + "id" : "26", + "type" : "rdfs:Literal" + }, { + "id" : "27", + "type" : "rdfs:Literal" + }, { + "id" : "37", + "type" : "owl:equivalentClass" + }, { + "id" : "45", + "type" : "rdfs:Literal" + }, { + "id" : "46", + "type" : "rdfs:Literal" + }, { + "id" : "53", + "type" : "rdfs:Literal" + }, { + "id" : "56", + "type" : "rdfs:Literal" + }, { + "id" : "59", + "type" : "rdfs:Literal" + }, { + "id" : "60", + "type" : "owl:Class" + }, { + "id" : "61", + "type" : "rdfs:Literal" + }, { + "id" : "6", + "type" : "rdfs:Literal" + }, { + "id" : "62", + "type" : "rdfs:Literal" + }, { + "id" : "12", + "type" : "owl:equivalentClass" + }, { + "id" : "55", + "type" : "rdfs:Literal" + }, { + "id" : "69", + "type" : "rdfs:Literal" + }, { + "id" : "71", + "type" : "owl:Class" + }, { + "id" : "36", + "type" : "owl:Class" + }, { + "id" : "86", + "type" : "owl:Class" + }, { + "id" : "83", + "type" : "owl:Class" + }, { + "id" : "94", + "type" : "owl:Class" + }, { + "id" : "73", + "type" : "rdfs:Literal" + }, { + "id" : "68", + "type" : "rdfs:Literal" + }, { + "id" : "93", + "type" : "rdfs:Literal" + }, { + "id" 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"type" : "owl:Class" + } ], + "classAttribute" : [ { + "iri" : "http://www.w3.org/2002/07/owl#Thing", + "baseIri" : "http://owl2vowl.de", + "id" : "3", + "label" : { + "undefined" : "Thing" + } + }, { + "iri" : "http://www.w3.org/2004/02/skos/core#Concept", + "baseIri" : "http://www.w3.org/2004/02/skos/core", + "instances" : 0, + "label" : { + "IRI-based" : "Concept", + "undefined" : "Concept" + }, + "attributes" : [ "external" ], + "id" : "9" + }, { + "iri" : "http://xmlns.com/foaf/0.1/Agent", + "equivalent" : [ "13" ], + "baseIri" : "http://xmlns.com/foaf/0.1", + "instances" : 0, + "annotations" : { + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "Agent", + "undefined" : "Agent" + }, + "subClasses" : [ "10", "11", "12" ], + "comment" : { + "undefined" : "An agent (eg. person, group, software or physical artifact)." + }, + "attributes" : [ "equivalent" ], + "id" : "1" + 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+ }, { + "id" : "81", + "type" : "owl:objectProperty" + }, { + "id" : "82", + "type" : "rdfs:SubClassOf" + }, { + "id" : "34", + "type" : "owl:objectProperty" + }, { + "id" : "85", + "type" : "rdfs:SubClassOf" + }, { + "id" : "87", + "type" : "owl:datatypeProperty" + }, { + "id" : "89", + "type" : "rdfs:SubClassOf" + }, { + "id" : "90", + "type" : "rdfs:SubClassOf" + }, { + "id" : "91", + "type" : "owl:objectProperty" + }, { + "id" : "92", + "type" : "owl:datatypeProperty" + }, { + "id" : "95", + "type" : "owl:datatypeProperty" + }, { + "id" : "96", + "type" : "owl:objectProperty" + }, { + "id" : "97", + "type" : "owl:datatypeProperty" + }, { + "id" : "98", + "type" : "rdfs:SubClassOf" + }, { + "id" : "99", + "type" : "owl:datatypeProperty" + }, { + "id" : "43", + "type" : "owl:objectProperty" + }, { + "id" : "42", + "type" : "owl:objectProperty" + }, { + "id" : "103", + "type" : "owl:datatypeProperty" + }, { + "id" : "104", + "type" : "owl:objectProperty" + }, { + "id" : "105", + "type" : "owl:datatypeProperty" + }, { + "id" : "107", + "type" : "owl:objectProperty" + }, { + "id" : "108", + "type" : "owl:datatypeProperty" + }, { + "id" : "109", + "type" : "owl:objectProperty" + }, { + "id" : "110", + "type" : "owl:objectProperty" + }, { + "id" : "40", + "type" : "owl:objectProperty" + }, { + "id" : "41", + "type" : "owl:objectProperty" + }, { + "id" : "84", + "type" : "owl:objectProperty" + }, { + "id" : "111", + "type" : "owl:datatypeProperty" + }, { + "id" : "112", + "type" : "owl:datatypeProperty" + }, { + "id" : "113", + "type" : "owl:datatypeProperty" + }, { + "id" : "114", + "type" : "owl:objectProperty" + }, { + "id" : "116", + "type" : "owl:disjointWith" + }, { + "id" : "117", + "type" : "owl:disjointWith" + }, { + "id" : "119", + "type" : "owl:datatypeProperty" + }, { + "id" : "120", + "type" : "owl:disjointWith" + }, { + "id" : "121", + "type" : "owl:disjointWith" + }, { + "id" : "122", + "type" : "owl:objectProperty" + }, { + "id" : "123", + "type" : "owl:datatypeProperty" + }, { + "id" : "124", + "type" : "owl:objectProperty" + }, { + "id" : "125", + "type" : "owl:datatypeProperty" + }, { + "id" : "127", + "type" : "owl:datatypeProperty" + }, { + "id" : "115", + "type" : "owl:objectProperty" + }, { + "id" : "128", + "type" : "owl:objectProperty" + }, { + "id" : "129", + "type" : "owl:objectProperty" + } ], + "propertyAttribute" : [ { + "iri" : "http://xmlns.com/foaf/0.1/interest", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "interest", + "undefined" : "interest" + }, + "domain" : "1", + "comment" : { + "undefined" : "A page about a topic of interest to this person." + }, + "attributes" : [ "object" ], + "id" : "0" + }, { + "iri" : "http://xmlns.com/foaf/0.1/mbox_sha1sum", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "6", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "mbox_sha1sum", + "undefined" : "sha1sum of a personal mailbox URI name" + }, + "domain" : "5", + "comment" : { + "undefined" : "The sha1sum of the URI of an Internet mailbox associated with exactly one owner, the first owner of the mailbox." + }, + "attributes" : [ "datatype" ], + "id" : "4" + }, { + "iri" : "http://xmlns.com/foaf/0.1/nick", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "8", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "nick", + "undefined" : "nickname" + }, + "domain" : "5", + "comment" : { + "undefined" : "A short informal nickname characterising an agent (includes login identifiers, IRC and other chat nicknames)." + }, + "attributes" : [ "datatype" ], + "id" : "7" + }, { + "iri" : "http://xmlns.com/foaf/0.1/openid", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "openid", + "undefined" : "openid" + }, + "superproperty" : [ "15" ], + "domain" : "1", + "comment" : { + "undefined" : "An OpenID for an Agent." + }, + "attributes" : [ "inverse functional", "object" ], + "id" : "14" + }, { + "iri" : "http://xmlns.com/foaf/0.1/workInfoHomepage", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "workInfoHomepage", + "undefined" : "work info homepage" + }, + "domain" : "12", + "comment" : { + "undefined" : "A work info homepage of some person; a page about their work for some organization." + }, + "attributes" : [ "object" ], + "id" : "16" + }, { + "iri" : "http://xmlns.com/foaf/0.1/pastProject", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "3", + "annotations" : { + "isDefinedBy" : [ { 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"comment" : { + "undefined" : "A theme." + }, + "attributes" : [ "object" ], + "id" : "23" + }, { + "iri" : "http://xmlns.com/foaf/0.1/knows", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "12", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "knows", + "undefined" : "knows" + }, + "domain" : "12", + "comment" : { + "undefined" : "A person known by this person (indicating some level of reciprocated interaction between the parties)." + }, + "attributes" : [ "object" ], + "id" : "25" + }, { + "iri" : "http://xmlns.com/foaf/0.1/focus", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "29", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + 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specified using fully qualified tel: URI scheme (refs: http://www.w3.org/Addressing/schemes.html#tel)." + }, + "attributes" : [ "object" ], + "id" : "30" + }, { + "iri" : "http://xmlns.com/foaf/0.1/depicts", + "inverse" : "34", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "33", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "depicts", + "undefined" : "depicts" + }, + "domain" : "32", + "comment" : { + "undefined" : "A thing depicted in this representation." + }, + "attributes" : [ "object" ], + "id" : "31" + }, { + "iri" : "http://xmlns.com/foaf/0.1/based_near", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "36", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", 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"undefined" : "DNA checksum" + }, + "domain" : "19", + "comment" : { + "undefined" : "A checksum for the DNA of some thing. 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"identifier" : "term_status", + "language" : "undefined", + "value" : "unstable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "status", + "undefined" : "status" + }, + "domain" : "1", + "comment" : { + "undefined" : "A string expressing what the user is happy for the general public (normally) to know about their current activity." + }, + "attributes" : [ "datatype" ], + "id" : "65" + }, { + "iri" : "http://xmlns.com/foaf/0.1/yahooChatID", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "46", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "yahooChatID", + "undefined" : "Yahoo chat ID" + }, + "domain" : "19", + "comment" : { + "undefined" : "A Yahoo chat ID" + }, + "attributes" : [ 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"undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "icqChatID", + "undefined" : "ICQ chat ID" + }, + "domain" : "19", + "comment" : { + "undefined" : "An ICQ chat ID" + }, + "attributes" : [ "datatype" ], + "id" : "70" + }, { + "iri" : "http://xmlns.com/foaf/0.1/givenname", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "73", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "archaic", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "givenname", + "undefined" : "Given name" + }, + "domain" : "19", + "comment" : { + "undefined" : "The given name of some person." + }, + "attributes" : [ "datatype" ], + "id" : "72" + }, { + "iri" : "http://xmlns.com/foaf/0.1/isPrimaryTopicOf", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "isPrimaryTopicOf", + "undefined" : "is primary topic of" + }, + "superproperty" : [ "38" ], + "domain" : "39", + "subproperty" : [ "14", "43" ], + "comment" : { + "undefined" : "A document that this thing is the primary topic of." + }, + "attributes" : [ "inverse functional", "object" ], + "id" : "15" + }, { + "range" : "2", + "domain" : "32", + "attributes" : [ "anonymous", "object" ], + "id" : "74" + }, { + "range" : "2", + "domain" : "71", + "attributes" : [ "anonymous", "object" ], + "id" : "75" + }, { + "range" : "78", + "domain" : "77", + "attributes" : [ "anonymous", "object" ], + "id" : "76" + }, { + "range" : "36", + "domain" : "12", + "attributes" : [ "anonymous", "object" ], + "id" : "79" + }, { + "iri" : "http://xmlns.com/foaf/0.1/accountServiceHomepage", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "accountServiceHomepage", + "undefined" : "account service homepage" + }, + "domain" : "78", + "comment" : { + "undefined" : "Indicates a homepage of the service provide for this online account." + }, + "attributes" : [ "object" ], + "id" : "80" + }, { + "iri" : "http://xmlns.com/foaf/0.1/logo", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "19", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "logo", + "undefined" : "logo" + }, + "domain" : "19", + "comment" : { + "undefined" : "A logo representing some thing." + }, + "attributes" : [ "inverse functional", "object" ], + "id" : "81" + }, { + "range" : "78", + "domain" : "83", + "attributes" : [ "anonymous", "object" ], + "id" : "82" + }, { + "iri" : "http://xmlns.com/foaf/0.1/depiction", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "32", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "depiction", + "undefined" : "depiction" + }, + "domain" : "33", + "subproperty" : [ "84" ], + "comment" : { + "undefined" : "A depiction of some thing." + }, + "attributes" : [ "object" ], + "id" : "34" + }, { + "range" : "78", + "domain" : "86", + "attributes" : [ "anonymous", "object" ], + "id" : "85" + }, { + "iri" : "http://xmlns.com/foaf/0.1/family_name", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "88", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "archaic", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "family_name", + "undefined" : "family_name" + }, + "domain" : "12", + "comment" : { + "undefined" : "The family name of some person." + }, + "attributes" : [ "datatype" ], + "id" : "87" + }, { + "range" : "1", + "domain" : "12", + "attributes" : [ "anonymous", "object" ], + "id" : "89" + }, { + "range" : "1", + "domain" : "11", + "attributes" : [ "anonymous", "object" ], + "id" : "90" + }, { + "iri" : "http://xmlns.com/foaf/0.1/fundedBy", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "19", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "archaic", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "fundedBy", + "undefined" : "funded by" + }, + "domain" : "19", + "comment" : { + "undefined" : "An organization funding a project or person." + }, + "attributes" : [ "object" ], + "id" : "91" + }, { + "iri" : "http://xmlns.com/foaf/0.1/title", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "93", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "title", + "undefined" : "title" + }, + "domain" : "19", + "comment" : { + "undefined" : "Title (Mr, Mrs, Ms, Dr. etc)" + }, + "attributes" : [ "datatype" ], + "id" : "92" + }, { + "iri" : "http://xmlns.com/foaf/0.1/accountName", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "59", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "accountName", + "undefined" : "account name" + }, + "domain" : "78", + "comment" : { + "undefined" : "Indicates the name (identifier) associated with this online account." + }, + "attributes" : [ "datatype" ], + "id" : "95" + }, { + "iri" : "http://xmlns.com/foaf/0.1/account", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "78", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "account", + "undefined" : "account" + }, + "domain" : "1", + "comment" : { + "undefined" : "Indicates an account held by this agent." + }, + "attributes" : [ "object" ], + "id" : "96" + }, { + "iri" : "http://xmlns.com/foaf/0.1/jabberID", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "69", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "jabberID", + "undefined" : "jabber ID" + }, + "domain" : "19", + "comment" : { + "undefined" : "A jabber ID for something." + }, + "attributes" : [ "datatype" ], + "id" : "97" + }, { + "range" : "1", + "domain" : "10", + "attributes" : [ "anonymous", "object" ], + "id" : "98" + }, { + "iri" : "http://xmlns.com/foaf/0.1/age", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "100", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "unstable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "age", + "undefined" : "age" + }, + "domain" : "1", + "comment" : { + "undefined" : "The age in years of some agent." + }, + "attributes" : [ "datatype", "functional" ], + "id" : "99" + }, { + "iri" : "http://xmlns.com/foaf/0.1/homepage", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "homepage", + "undefined" : "homepage" + }, + "superproperty" : [ "15", "38" ], + "domain" : "39", + "comment" : { + "undefined" : "A homepage for some thing." + }, + "attributes" : [ "inverse functional", "object" ], + "id" : "43" + }, { + "iri" : "http://xmlns.com/foaf/0.1/tipjar", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "tipjar", + "undefined" : "tipjar" + }, + "superproperty" : [ "38" ], + "domain" : "1", + "comment" : { + "undefined" : "A tipjar document for this agent, describing means for payment and reward." + }, + "attributes" : [ "object" ], + "id" : "42" + }, { + "iri" : "http://xmlns.com/foaf/0.1/msnChatID", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "61", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "msnChatID", + "undefined" : "MSN chat ID" + }, + "domain" : "5", + "comment" : { + "undefined" : "An MSN chat ID" + }, + "attributes" : [ "datatype" ], + "id" : "103" + }, { + "iri" : "http://xmlns.com/foaf/0.1/topic_interest", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "18", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "topic_interest", + "undefined" : "topic_interest" + }, + "domain" : "1", + "comment" : { + "undefined" : "A thing of interest to this person." + }, + "attributes" : [ "object" ], + "id" : "104" + }, { + "iri" : "http://xmlns.com/foaf/0.1/aimChatID", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "106", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "aimChatID", + "undefined" : "AIM chat ID" + }, + "domain" : "19", + "comment" : { + "undefined" : "An AIM chat ID" + }, + "attributes" : [ "datatype" ], + "id" : "105" + }, { + "iri" : "http://xmlns.com/foaf/0.1/currentProject", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "3", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "currentProject", + "undefined" : "current project" + }, + "domain" : "12", + "comment" : { + "undefined" : "A current project this person works on." + }, + "attributes" : [ "object" ], + "id" : "107" + }, { + "iri" : "http://xmlns.com/foaf/0.1/skypeID", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "20", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "skypeID", + "undefined" : "Skype ID" + }, + "domain" : "1", + "comment" : { + "undefined" : "A Skype ID" + }, + "attributes" : [ "datatype" ], + "id" : "108" + }, { + "iri" : "http://xmlns.com/foaf/0.1/holdsAccount", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "78", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "archaic", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "holdsAccount", + "undefined" : "account" + }, + "domain" : "1", + "comment" : { + "undefined" : "Indicates an account held by this agent." + }, + "attributes" : [ "object" ], + "id" : "109" + }, { + "iri" : "http://xmlns.com/foaf/0.1/thumbnail", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "32", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "thumbnail", + "undefined" : "thumbnail" + }, + "domain" : "32", + "comment" : { + "undefined" : "A derived thumbnail image." + }, + "attributes" : [ "object" ], + "id" : "110" + }, { + "iri" : "http://xmlns.com/foaf/0.1/topic", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "39", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "topic", + "undefined" : "topic" + }, + "domain" : "2", + "comment" : { + "undefined" : "A topic of some page or document." + }, + "attributes" : [ "object" ], + "id" : "40" + }, { + "iri" : "http://xmlns.com/foaf/0.1/weblog", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "weblog", + "undefined" : "weblog" + }, + "superproperty" : [ "38" ], + "domain" : "1", + "comment" : { + "undefined" : "A weblog of some thing (whether person, group, company etc.)." + }, + "attributes" : [ "inverse functional", "object" ], + "id" : "41" + }, { + "iri" : "http://xmlns.com/foaf/0.1/img", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "32", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "img", + "undefined" : "image" + }, + "superproperty" : [ "34" ], + "domain" : "12", + "comment" : { + "undefined" : "An image that can be used to represent some thing (ie. those depictions which are particularly representative of something, eg. one's photo on a homepage)." + }, + "attributes" : [ "object" ], + "id" : "84" + }, { + "iri" : "http://xmlns.com/foaf/0.1/birthday", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "56", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "unstable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "birthday", + "undefined" : "birthday" + }, + "domain" : "1", + "comment" : { + "undefined" : "The birthday of this Agent, represented in mm-dd string form, eg. '12-31'." + }, + "attributes" : [ "datatype", "functional" ], + "id" : "111" + }, { + "iri" : "http://xmlns.com/foaf/0.1/sha1", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "101", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "unstable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "sha1", + "undefined" : "sha1sum (hex)" + }, + "domain" : "2", + "comment" : { + "undefined" : "A sha1sum hash, in hex." + }, + "attributes" : [ "datatype" ], + "id" : "112" + }, { + "iri" : "http://xmlns.com/foaf/0.1/firstName", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "24", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "firstName", + "undefined" : "firstName" + }, + "domain" : "12", + "comment" : { + "undefined" : "The first name of a person." + }, + "attributes" : [ "datatype" ], + "id" : "113" + }, { + "iri" : "http://xmlns.com/foaf/0.1/made", + "inverse" : "115", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "18", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "made", + "undefined" : "made" + }, + "domain" : "1", + "comment" : { + "undefined" : "Something that was made by this agent." + }, + "attributes" : [ "object" ], + "id" : "114" + }, { + "range" : "60", + "domain" : "2", + "attributes" : [ "anonymous", "object" ], + "id" : "116" + }, { + "range" : "12", + "domain" : "60", + "attributes" : [ "anonymous", "object" ], + "id" : "117" + }, { + "iri" : "http://xmlns.com/foaf/0.1/familyName", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "62", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "familyName", + "undefined" : "familyName" + }, + "domain" : "12", + "comment" : { + "undefined" : "The family name of some person." + }, + "attributes" : [ "datatype" ], + "id" : "119" + }, { + "range" : "2", + "domain" : "11", + "attributes" : [ "anonymous", "object" ], + "id" : "120" + }, { + "range" : "12", + "domain" : "11", + "attributes" : [ "anonymous", "object" ], + "id" : "121" + }, { + "iri" : "http://xmlns.com/foaf/0.1/member", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "1", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "member", + "undefined" : "member" + }, + "domain" : "10", + "comment" : { + "undefined" : "Indicates a member of a Group" + }, + "attributes" : [ "object" ], + "id" : "122" + }, { + "iri" : "http://xmlns.com/foaf/0.1/plan", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "27", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "plan", + "undefined" : "plan" + }, + "domain" : "12", + "comment" : { + "undefined" : "A .plan comment, in the tradition of finger and '.plan' files." + }, + "attributes" : [ "datatype" ], + "id" : "123" + }, { + "iri" : "http://xmlns.com/foaf/0.1/mbox", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "18", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "mbox", + "undefined" : "personal mailbox" + }, + "domain" : "1", + "comment" : { + "undefined" : "A personal mailbox, ie. an Internet mailbox associated with exactly one owner, the first owner of this mailbox. This is a 'static inverse functional property', in that there is (across time and change) at most one individual that ever has any particular value for foaf:mbox." + }, + "attributes" : [ "inverse functional", "object" ], + "id" : "124" + }, { + "iri" : "http://xmlns.com/foaf/0.1/surname", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "118", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "archaic", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "surname", + "undefined" : "Surname" + }, + "domain" : "12", + "comment" : { + "undefined" : "The surname of some person." + }, + "attributes" : [ "datatype" ], + "id" : "125" + }, { + "iri" : "http://xmlns.com/foaf/0.1/myersBriggs", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "22", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "myersBriggs", + "undefined" : "myersBriggs" + }, + "domain" : "12", + "comment" : { + "undefined" : "A Myers Briggs (MBTI) personality classification." + }, + "attributes" : [ "datatype" ], + "id" : "127" + }, { + "iri" : "http://xmlns.com/foaf/0.1/maker", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "1", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "maker", + "undefined" : "maker" + }, + "domain" : "18", + "comment" : { + "undefined" : "An agent that made this thing." + }, + "attributes" : [ "object" ], + "id" : "115" + }, { + "iri" : "http://xmlns.com/foaf/0.1/publications", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "publications", + "undefined" : "publications" + }, + "domain" : "12", + "comment" : { + "undefined" : "A link to the publications of this person." + }, + "attributes" : [ "object" ], + "id" : "128" + }, { + "iri" : "http://xmlns.com/foaf/0.1/workplaceHomepage", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "workplaceHomepage", + "undefined" : "workplace homepage" + }, + "domain" : "12", + "comment" : { + "undefined" : "A workplace homepage of some person; the homepage of an organization they work for." + }, + "attributes" : [ "object" ], + "id" : "129" + } ] +} \ No newline at end of file diff --git a/doc/releases/0.1.0/parameters/webvowl/data/ontology.json b/doc/releases/0.1.0/parameters/webvowl/data/ontology.json new file mode 100644 index 0000000..e9aebc9 --- /dev/null +++ b/doc/releases/0.1.0/parameters/webvowl/data/ontology.json @@ -0,0 +1,3404 @@ +{ + "_comment" : "Created with OWL2VOWL (version 0.3.5), http://vowl.visualdataweb.org", + "header" : { + "languages" : [ "en", "undefined" ], + "baseIris" : [ "http://www.w3.org/1999/02/22-rdf-syntax-ns", "http://purl.org/neao/parameters", "http://www.w3.org/2000/01/rdf-schema", "http://www.w3.org/2001/XMLSchema", "http://purl.org/neao/base" ], + "iri" : "http://purl.org/neao/parameters#", + "version" : "0.1.0", + "author" : [ "Michael Denker (ORCID: 0000-0003-1255-7300)", "Cristiano Köhler (ORCID: 0000-0003-0503-5264)" ], + "labels" : { + "en" : "Neuroelectrophysiology Analysis Ontology - Analysis Parameters" + }, + "comments" : { + "en" : "This module in the Neuroelectrophysiology Analysis Ontology contains classes that represent parameters in the analyses. A parameter is an information entity that controls the behavior of an analysis step, but does not provide data that is used by the step to produce the output.\n\nFor example, in a low-pass filtering step in the analysis, where a raw wideband signal is transformed to isolate the frequency components smaller than a cutoff frequency, the time series with the raw signal is the data input, and the low-pass frequency cutoff frequency value is a parameter.\n\nThe classes in this module are subclasses of the AnalysisParameter base class and are associated with the analysis steps (defined in the steps module) through the usesParameter object property." + }, + "other" : { + "license" : [ { + "identifier" : "license", + "language" : "undefined", + "value" : "https://creativecommons.org/licenses/by/4.0/", + "type" : "iri" + } ], + "creator" : [ { + "identifier" : "creator", + "language" : "undefined", + "value" : "Cristiano Köhler (ORCID: 0000-0003-0503-5264)", + "type" : "label" + }, { + "identifier" : "creator", + "language" : "undefined", + "value" : "Michael Denker (ORCID: 0000-0003-1255-7300)", + "type" : "label" + } ], + "created" : [ { + "identifier" : "created", + "language" : "undefined", + "value" : "2022-01-19", + "type" : "label" + } ], + "preferredNamespacePrefix" : [ { + "identifier" : "preferredNamespacePrefix", + "language" : "undefined", + "value" : "neao_params", + "type" : "label" + } ], + "preferredNamespaceUri" : [ { + "identifier" : "preferredNamespaceUri", + "language" : "undefined", + "value" : "http://purl.org/neao/parameters#", + "type" : "label" + } ], + "versionInfo" : [ { + "identifier" : "versionInfo", + "language" : "undefined", + "value" : "0.1.0", + "type" : "label" + } ] + } + }, + "namespace" : [ ], + "class" : [ { + "id" : "17", + "type" : "owl:Class" + }, { + "id" : "5", + "type" : "owl:Class" + }, { + "id" : "36", + "type" : "owl:Class" + }, { + "id" : "66", + "type" : "owl:Class" + }, { + "id" : "39", + "type" : "owl:Class" + }, { + "id" : "49", + "type" : "owl:Class" + }, { + "id" : "82", + "type" : "owl:Class" + }, { + "id" : "7", + "type" : "owl:Class" + }, { + "id" : "4", + "type" : "owl:Class" + }, { + "id" : "18", + "type" : "owl:Class" + }, { + "id" : "10", + "type" : "owl:Class" + }, { + "id" : "23", + "type" : "owl:Class" + }, { + "id" : "48", + "type" : "owl:Class" + }, { + "id" : "105", + "type" : "owl:Class" + }, { + "id" : "12", + "type" : "owl:Class" + }, { + "id" : "96", + "type" : "owl:Class" + }, { + "id" : "29", + "type" : "owl:Class" + }, { + "id" : "44", + "type" : "owl:Class" + }, { + "id" : "84", + "type" : "owl:Class" + }, { + "id" : "83", + "type" : "owl:Class" + }, { + "id" : "32", + "type" : "owl:Class" + }, { + "id" : "97", + "type" : "owl:Class" + }, { + "id" : "155", + "type" : "owl:Class" + }, { + "id" : "41", + "type" : "owl:Class" + }, { + "id" : "19", + "type" : "owl:Class" + }, { + "id" : "21", + "type" : "owl:Class" + }, { + "id" : "35", + "type" : "owl:Class" + }, { + "id" : "233", + "type" : "owl:Class" + }, { + "id" : "242", + "type" : "owl:Class" + }, { + "id" : "20", + "type" : "owl:Class" + }, { + "id" : "2", + "type" : "owl:Class" + }, { + "id" : "243", + "type" : "owl:Class" + }, { + "id" : "38", + "type" : "owl:Class" + }, { + "id" : "1", + "type" : "owl:Class" + }, { + "id" : "22", + "type" : "owl:Class" + }, { + "id" : "15", + "type" : "owl:Class" + }, { + "id" : "24", + "type" : "owl:Class" + }, { + "id" : "9", + "type" : "owl:Class" + }, { + "id" : "57", + "type" : "owl:Class" + }, { + "id" : "26", + "type" : "owl:Class" + } ], + "classAttribute" : [ { + "iri" : "http://purl.org/neao/parameters#WindowFunction", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "window function", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "tapering function", + "type" : "label" + }, { + "identifier" : "altLabel", + "language" : "en", + "value" : "apodization function", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "WindowFunction" + }, + "subClasses" : [ "19", "20", "21", "22", "23", "24" ], + "comment" : { + "en" : "A mathematical function that is zero-valued outside a defined interval. When multiplied by another function or sampled data, the values outside the window interval will be transformed to zero, and the values inside the window will be weighted by the window function values. \n\nWindow functions are used to select and modify a finite segment of a signal. This is useful for applying the fast Fourier transform (FFT) to a finite set of data where the length is not an integer number of periods of the signal. In this situation, there will be discontinuities at the boundaries of the signal, and the data in the frequency domain produced by the FFT will have frequency components not present in the original signal (spectral leakage). The window function can be used to reduce this discontinuities and mitigate spectral leakage when performing spectral analysis.\n\nSeveral types of window function exist. They will vary in shape in the time domain and will have distinct frequency characteristics in the frequency domain, with a main lobe and several side lobes. The main lobe is centered at each frequency component in the time domain, and the side lobes approach zero. These characteristics can be used to control the effect of spectral leakage when performing the analysis." + }, + "id" : "17", + "superClasses" : [ "18" ] + }, { + "iri" : "http://purl.org/neao/parameters#ASSETMaskMatrixSignificanceThresholds", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "significance thresholds in ASSET mask matrix", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ASSETMaskMatrixSignificanceThresholds" + }, + "comment" : { + "en" : "Real values (range 0-1) used as thresholds to determine if the entries in the probability matrix and joint probability matrices are significant. Entry significance is defined as a probability value greater than the threshold values specified by the parameter. Significant entries in both probability and joint probability matrices are defined as 1 in the mask matrix." + }, + "id" : "5", + "superClasses" : [ "36" ] + }, { + "iri" : "http://purl.org/neao/parameters#ASSETAnalysisParameter", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "ASSET analysis parameter", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ASSETAnalysisParameter" + }, + "subClasses" : [ "10", "5", "9", "4" ], + "comment" : { + "en" : "A parameter used by the Analysis of Sequences of Synchronous Events (ASSET) method, used to identify neuronal activity patterns in spike data." + }, + "id" : "36", + "superClasses" : [ "18" ] + }, { + "iri" : "http://purl.org/neao/parameters#DownsampleFactor", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "downsample factor", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "decimation factor", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "DownsampleFactor" + }, + "comment" : { + "en" : "A real value that indicates the factor by which the sampling period of a sampled time series is reduced in a downsampling operation." + }, + "id" : "66", + "superClasses" : [ "18" ] + }, { + "iri" : "http://purl.org/neao/parameters#WindowOverlapSamples", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "window overlap in samples", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "WindowOverlapSamples" + }, + "comment" : { + "en" : "Integer value (range 0 to the window length in samples) that determines the number of samples where two adjacent windows overlap. The window corresponds to a finite interval in sampled data (e.g., a time interval in sampled time series data)." + }, + "id" : "39", + "superClasses" : [ "18" ] + }, { + "iri" : "http://purl.org/neao/parameters#WindowLengthSamples", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "window length in samples", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "WindowLengthSamples" + }, + "comment" : { + "en" : "Integer value that defines the number of samples encompassed by a window in sampled data, i.e., the window length. The window corresponds to a finite interval in the sampled data (e.g., a time interval in sampled time series data)." + }, + "id" : "49", + "superClasses" : [ "18" ] + }, { + "iri" : "http://purl.org/neao/parameters#DBSCANParameter", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "DBSCAN parameter", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "DBSCANParameter" + }, + "subClasses" : [ "83", "84" ], + "comment" : { + "en" : "A parameter used by the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) data clustering method." + }, + "id" : "82", + "superClasses" : [ "18" ] + }, { + "iri" : "http://purl.org/neao/parameters#KernelWidth", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "kernel width", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "KernelWidth" + }, + "comment" : { + "en" : "The total width of a smoothing kernel." + }, + "id" : "7", + "superClasses" : [ "18" ] + }, { + "iri" : "http://purl.org/neao/parameters#ASSETClusteringDistanceStretchFactor", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "distance stretch factor in ASSET clustering", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ASSETClusteringDistanceStretchFactor" + }, + "comment" : { + "en" : "When computing the elliptical distance measure used by the DBSCAN algorithm to cluster the mask matrix entries to find the diagonal structures, the parameter value is used to stretch angular coefficients deviating from 45 degrees. This reflects into the shape of the neighborhood around a point in the DBSCAN procedure. A large stretch factor will produce neighborhoods that are narrower and closer to a line in the 45 degree direction. Smaller stretch factors will produce neighborhoods that are more elliptical, with the major axis in the 45 degree direction, and the minor axis in the 135 degree direction. Therefore, the smaller stretch factor increases the minor axis of this ellipsis. Together with the DBSCAN neighborhood radius parameter, this should be used to tweak the neighborhood ellipsis such that it is contained in the rectangular kernel used to filter the probability matrix entries when computing the joint probability matrix." + }, + "id" : "4", + "superClasses" : [ "36" ] + }, { + "iri" : "http://purl.org/neao/base#AnalysisParameter", + "baseIri" : "http://purl.org/neao/base", + "instances" : 0, + "label" : { + "IRI-based" : "AnalysisParameter" + }, + "subClasses" : [ "96", "17", "29", "57", "38", "48", "1", "41", "82", "7", "66", "44", "39", "49", "2", "32", "15", "26", "35", "36", "97", "12" ], + "attributes" : [ "external" ], + "id" : "18" + }, { + "iri" : "http://purl.org/neao/parameters#ASSETJointProbabilityMatrixNumberLargestNeighbors", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "number of largest neighbors in ASSET joint probability matrix", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ASSETJointProbabilityMatrixNumberLargestNeighbors" + }, + "comment" : { + "en" : "Defines the number of elements inside the filter kernel that are used to compute the joint probability value for a matrix entry. The probability matrix values inside the kernel for that entry are ordered from the largest to the lowest value, and the first N elements corresponding to the parameter value are taken." + }, + "id" : "10", + "superClasses" : [ "36" ] + }, { + "iri" : "http://purl.org/neao/parameters#HannWindowFunction", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "Hann window function", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "hanning window function", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "HannWindowFunction" + }, + "comment" : { + "en" : "raised-cosine window function" + }, + "id" : "23", + "superClasses" : [ "17" ] + }, { + "iri" : "http://purl.org/neao/parameters#WaveletCenterFrequency", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "wavelet center frequency", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "WaveletCenterFrequency" + }, + "comment" : { + "en" : "The value of the center frequency of a wavelet. This is the frequency at which the wavelet oscillates most strongly, and it influences how effectively the wavelet can capture features of a signal at different frequencies. Wavelets with higher center frequencies are better suited for analyzing high-frequency components of a signal, while those with lower center frequencies are more effective for capturing low-frequency components." + }, + "id" : "48", + "superClasses" : [ "18" ] + }, { + "iri" : "http://purl.org/neao/parameters#BoxcarSmoothingKernel", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "Boxcar smoothing kernel", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "BoxcarSmoothingKernel" + }, + "comment" : { + "en" : "The kernel function is zero over the entire interval except for a single (smaller) interval where it has a constant value. This non-zero interval is the total width of the kernel." + }, + "id" : "105", + "superClasses" : [ "35" ] + }, { + "iri" : "http://purl.org/neao/parameters#LowPassFrequencyCutoff", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "low-pass frequency cutoff", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "LowPassFrequencyCutoff" + }, + "comment" : { + "en" : "When applying a filter to a time series, the frequency components above this parameter value will be attenuated. Usually, the parameter value corresponds to the frequency component attenuated by 3 dB in the filter transition band." + }, + "id" : "12", + "superClasses" : [ "18" ] + }, { + "iri" : "http://purl.org/neao/parameters#BinSize", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "bin size", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "bin width", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "BinSize" + }, + "comment" : { + "en" : "When discretizing continuous data into smaller intervals (bins), the parameter value determines the width of the intervals (in the unit of the data being discretized). Bins are adjacent and can be of different sizes." + }, + "id" : "96", + "superClasses" : [ "18" ] + }, { + "iri" : "http://purl.org/neao/parameters#SamplingFrequency", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "sampling frequency", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "sampling rate", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "SamplingFrequency" + }, + "comment" : { + "en" : "The parameter determines the number of samples per time unit in sampled data. It is the inverse of the sampling period, i.e., the interval between two consecutive samples." + }, + "id" : "29", + "superClasses" : [ "18" ] + }, { + "iri" : "http://purl.org/neao/parameters#FrequencyResolution", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "frequency resolution", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "FrequencyResolution" + }, + "comment" : { + "en" : "In analyses producing estimates in the frequency domain, the parameter determines the width of the frequency bins in the output, i.e., the resolution of the output on the frequency axis." + }, + "id" : "44", + "superClasses" : [ "18" ] + }, { + "iri" : "http://purl.org/neao/parameters#DBSCANNeighborhoodRadius", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "DBSCAN neighborhood radius", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "DBSCAN maximum distance", + "type" : "label" + }, { + "identifier" : "altLabel", + "language" : "en", + "value" : "DBSCAN epsilon", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "DBSCANNeighborhoodRadius" + }, + "comment" : { + "en" : "Determines the radius around a sample point used to define its neighborhood. The parameter defines the maximum distance between two sample points such that they are considered to be in the same neighborhood." + }, + "id" : "84", + "superClasses" : [ "82" ] + }, { + "iri" : "http://purl.org/neao/parameters#DBSCANMinimumNeighbors", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "DBSCAN minimum number of neighbors", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "DBSCAN minimum samples", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "DBSCANMinimumNeighbors" + }, + "comment" : { + "en" : "Integer value that determines the minimum number of points that must be present in the neighborhood of a sample point such that it is considered a core point. The parameter value includes the sample point being evaluated." + }, + "id" : "83", + "superClasses" : [ "82" ] + }, { + "iri" : "http://purl.org/neao/parameters#ShapeFactor", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "shape factor", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ShapeFactor" + }, + "comment" : { + "en" : "When determining a probability distribution, the parameter affects the shape of the distribution. This is in contrast to other parameters that affect the location (e.g., mean) or scale (e.g., variance) of the distribution." + }, + "id" : "32", + "superClasses" : [ "18" ] + }, { + "iri" : "http://purl.org/neao/parameters#DitheringTime", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "dithering time", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "DitheringTime" + }, + "comment" : { + "en" : "A time interval that defines a dithering distribution used to draw random numbers to displace individual spike times in a spike train." + }, + "id" : "97", + "superClasses" : [ "18" ] + }, { + "iri" : "http://purl.org/neao/parameters#ExponentialSmoothingKernel", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "exponential smoothing kernel", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ExponentialSmoothingKernel" + }, + "comment" : { + "en" : "The kernel function is zero for points before the kernel center point, maximum at the center point, and decay exponentially for points greater than the center point. This kernel is asymmetric." + }, + "id" : "155", + "superClasses" : [ "35" ] + }, { + "iri" : "http://purl.org/neao/parameters#FilterOrder", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "filter order", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "FilterOrder" + }, + "comment" : { + "en" : "Integer value specifying the rate at which the filter response in the transition band falls. A higher filter order corresponds to a faster filter response decay." + }, + "id" : "41", + "superClasses" : [ "18" ] + }, { + "iri" : "http://purl.org/neao/parameters#DPSSWindowFunction", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "discrete prolate spheroidal sequences window function", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "Slepian sequences window function", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "DPSS window function", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "DPSSWindowFunction" + }, + "comment" : { + "en" : "A set of orthogonal sequences optimized to simultaneously achieve maximum concentration of energy within a defined frequency band and minimum leakage into neighboring frequency bands. They are frequently used as tapers in multiple applications (e.g., multitaper power spectral density estimation). The first sequence (order 0 or Slepian sequence) has maximal energy concentration in the main lobe." + }, + "id" : "19", + "superClasses" : [ "17" ] + }, { + "iri" : "http://purl.org/neao/parameters#KaiserWindowFunction", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "Kaiser window function", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "Kaiser-Bessel window function", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "KaiserWindowFunction" + }, + "comment" : { + "en" : "This window function approximates the DPSS window function using Bessel functions. It is easier to compute than the DPSS window function. It was developed by James Kaiser." + }, + "id" : "21", + "superClasses" : [ "17" ] + }, { + "iri" : "http://purl.org/neao/parameters#SmoothingKernel", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "smoothing kernel", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "SmoothingKernel" + }, + "subClasses" : [ "242", "243", "105", "155", "233" ], + "comment" : { + "en" : "A smoothing kernel can be used in non-parametric smoothing techniques such as kernel smoothing or kernel density estimation. It represents a weighting function that assigns weights to neighboring data points based on their distance from a given point (the kernel center). Closer points are given higher weights. The weighted average of the data points within the kernel is computed to produce a smoothed estimate of the underlying data (e.g., a signal or probability density function). Smoothing kernels are characterized by their shape (e.g., Boxcar, exponential) and bandwidth. The bandwidth determines the extent of influence of neighboring data points on the smoothed estimate." + }, + "id" : "35", + "superClasses" : [ "18" ] + }, { + "iri" : "http://purl.org/neao/parameters#HannSmoothingKernel", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "Hann smoothing kernel", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "HannSmoothingKernel" + }, + "comment" : { + "en" : "The kernel function corresponds to a raised cosine (i.e., a single period of a cosine function \"raised\" such that the negative troughs are zero). The endpoints reach zero smoothly at the boundaries." + }, + "id" : "233", + "superClasses" : [ "35" ] + }, { + "iri" : "http://purl.org/neao/parameters#BartlettSmoothingKernel", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "Bartlett smoothing kernel", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "BartlettSmoothingKernel" + }, + "comment" : { + "en" : "The kernel function has a triangular shape with end points at zero." + }, + "id" : "242", + "superClasses" : [ "35" ] + }, { + "iri" : "http://purl.org/neao/parameters#HammingWindowFunction", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "Hamming window function", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "HammingWindowFunction" + }, + "comment" : { + "en" : "A window function that corresponds to a raised cosine (i.e., a single period of a cosine function \"raised\") but with positive endpoints. Therefore, the function does not eliminate the discontinuities in the signal. It has better cancellation of the nearest side lobe, and a poorer cancellation of the others, with a wide main lobe. It is named after Richard Wesley Hamming." + }, + "id" : "20", + "superClasses" : [ "17" ] + }, { + "iri" : "http://purl.org/neao/parameters#HighPassFrequencyCutoff", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "high-pass frequency cutoff", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "HighPassFrequencyCutoff" + }, + "comment" : { + "en" : "When applying a filter to a time series, the frequency components below this parameter value will be attenuated. Usually, the parameter value corresponds to the frequency component attenuated by 3 dB in the filter transition band." + }, + "id" : "2", + "superClasses" : [ "18" ] + }, { + "iri" : "http://purl.org/neao/parameters#HammingSmoothingKernel", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "Hamming smoothing kernel", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "HammingSmoothingKernel" + }, + "comment" : { + "en" : "The kernel function corresponds to a raised cosine (i.e., a single period of a cosine function \"raised\") with positive endpoints." + }, + "id" : "243", + "superClasses" : [ "35" ] + }, { + "iri" : "http://purl.org/neao/parameters#WindowOverlapFactor", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "window overlap factor", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "WindowOverlapFactor" + }, + "comment" : { + "en" : "Real value (range 0-1) that determines the proportion of overlap between two adjacent windows. The window is a finite interval in the data (e.g., a time interval in time series data)." + }, + "id" : "38", + "superClasses" : [ "18" ] + }, { + "iri" : "http://purl.org/neao/parameters#FiringRate", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "firing rate", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "FiringRate" + }, + "comment" : { + "en" : "The parameter value determines the average number of spikes fired by a neuron per time unit. It is used to control the behavior of steps that require a firing rate to control the output (e.g., a target mean firing rate when generating an artificial spike train)." + }, + "id" : "1", + "superClasses" : [ "18" ] + }, { + "iri" : "http://purl.org/neao/parameters#BlackmanWindowFunction", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "Blackman window function", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "BlackmanWindowFunction" + }, + "comment" : { + "en" : "Window function that uses the first three terms of a summation of cosines, minimizing spectral leakage. It was proposed by Ralph Beebe Blackman. The coefficients are an approximation of the ones used in the exact Blackman window function. Therefore, this window does not remove the third and fourth side lobes but produces smoother edges." + }, + "id" : "22", + "superClasses" : [ "17" ] + }, { + "iri" : "http://purl.org/neao/parameters#NumberFFTSamples", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "number of FFT samples", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "FFT points", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "NumberFFTSamples" + }, + "comment" : { + "en" : "Length of the time series considered by application of a fast Fourier transform (FFT). The value determines the frequency bin size based on the sampling frequency of the input data, and the length of the vector representing the result of the discrete Fourier transform." + }, + "id" : "15", + "superClasses" : [ "18" ] + }, { + "iri" : "http://purl.org/neao/parameters#ExactBlackmanWindowFunction", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "exact Blackman window", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ExactBlackmanWindowFunction" + }, + "comment" : { + "en" : "Window function that uses the first three terms of a summation of cosines. It was proposed by Ralph Beebe Blackman. The coefficients are selected to remove the third and fourth side lobes, but the edges are discontinuous." + }, + "id" : "24", + "superClasses" : [ "17" ] + }, { + "iri" : "http://purl.org/neao/parameters#ASSETJointProbabilityMatrixFilterShape", + "baseIri" : "http://purl.org/neao/parameters", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "filter shape in ASSET joint probability matrix", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "kernel shape in ASSET joint probability matrix", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ASSETJointProbabilityMatrixFilterShape" + }, + "comment" : { + "en" : "A tuple of integers that determines the width and length of a rectangular kernel used to cover a diagonal structure in the intersection matrix. 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Symbol.toStringTag : undefined; + + /** + * The base implementation of `getTag` without fallbacks for buggy environments. + * + * @private + * @param {*} value The value to query. + * @returns {string} Returns the `toStringTag`. + */ + function baseGetTag(value) { + if (value == null) { + return value === undefined ? undefinedTag : nullTag; + } + return (symToStringTag && symToStringTag in Object(value)) + ? getRawTag(value) + : objectToString(value); + } + + module.exports = baseGetTag; + + +/***/ }), + +/***/ 92: +/***/ (function(module, exports, __webpack_require__) { + + var root = __webpack_require__(93); + + /** Built-in value references. */ + var Symbol = root.Symbol; + + module.exports = Symbol; + + +/***/ }), + +/***/ 93: +/***/ (function(module, exports, __webpack_require__) { + + var freeGlobal = __webpack_require__(94); + + /** Detect free variable `self`. */ + var freeSelf = typeof self == 'object' && self && self.Object === Object && self; + + /** Used as a reference to the global object. */ + var root = freeGlobal || freeSelf || Function('return this')(); + + module.exports = root; + + +/***/ }), + +/***/ 94: +/***/ (function(module, exports) { + + /* WEBPACK VAR INJECTION */(function(global) {/** Detect free variable `global` from Node.js. */ + var freeGlobal = typeof global == 'object' && global && global.Object === Object && global; + + module.exports = freeGlobal; + + /* WEBPACK VAR INJECTION */}.call(exports, (function() { return this; }()))) + +/***/ }), + +/***/ 95: +/***/ (function(module, exports, __webpack_require__) { + + var Symbol = __webpack_require__(92); + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * Used to resolve the + * [`toStringTag`](http://ecma-international.org/ecma-262/7.0/#sec-object.prototype.tostring) + * of values. + */ + var nativeObjectToString = objectProto.toString; + + /** Built-in value references. */ + var symToStringTag = Symbol ? Symbol.toStringTag : undefined; + + /** + * A specialized version of `baseGetTag` which ignores `Symbol.toStringTag` values. + * + * @private + * @param {*} value The value to query. + * @returns {string} Returns the raw `toStringTag`. + */ + function getRawTag(value) { + var isOwn = hasOwnProperty.call(value, symToStringTag), + tag = value[symToStringTag]; + + try { + value[symToStringTag] = undefined; + var unmasked = true; + } catch (e) {} + + var result = nativeObjectToString.call(value); + if (unmasked) { + if (isOwn) { + value[symToStringTag] = tag; + } else { + delete value[symToStringTag]; + } + } + return result; + } + + module.exports = getRawTag; + + +/***/ }), + +/***/ 96: +/***/ (function(module, exports) { + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** + * Used to resolve the + * [`toStringTag`](http://ecma-international.org/ecma-262/7.0/#sec-object.prototype.tostring) + * of values. + */ + var nativeObjectToString = objectProto.toString; + + /** + * Converts `value` to a string using `Object.prototype.toString`. + * + * @private + * @param {*} value The value to convert. + * @returns {string} Returns the converted string. + */ + function objectToString(value) { + return nativeObjectToString.call(value); + } + + module.exports = objectToString; + + +/***/ }), + +/***/ 103: +/***/ (function(module, exports, __webpack_require__) { + + var baseGetTag = __webpack_require__(91), + isObjectLike = __webpack_require__(104); + + /** `Object#toString` result references. */ + var symbolTag = '[object Symbol]'; + + /** + * Checks if `value` is classified as a `Symbol` primitive or object. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a symbol, else `false`. + * @example + * + * _.isSymbol(Symbol.iterator); + * // => true + * + * _.isSymbol('abc'); + * // => false + */ + function isSymbol(value) { + return typeof value == 'symbol' || + (isObjectLike(value) && baseGetTag(value) == symbolTag); + } + + module.exports = isSymbol; + + +/***/ }), + +/***/ 104: +/***/ (function(module, exports) { + + /** + * Checks if `value` is object-like. A value is object-like if it's not `null` + * and has a `typeof` result of "object". + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is object-like, else `false`. + * @example + * + * _.isObjectLike({}); + * // => true + * + * _.isObjectLike([1, 2, 3]); + * // => true + * + * _.isObjectLike(_.noop); + * // => false + * + * _.isObjectLike(null); + * // => false + */ + function isObjectLike(value) { + return value != null && typeof value == 'object'; + } + + module.exports = isObjectLike; + + +/***/ }), + +/***/ 112: +/***/ (function(module, exports) { + + /** + * Checks if `value` is classified as an `Array` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an array, else `false`. + * @example + * + * _.isArray([1, 2, 3]); + * // => true + * + * _.isArray(document.body.children); + * // => false + * + * _.isArray('abc'); + * // => false + * + * _.isArray(_.noop); + * // => false + */ + var isArray = Array.isArray; + + module.exports = isArray; + + +/***/ }), + +/***/ 154: +/***/ (function(module, exports) { + + /** + * A specialized version of `_.map` for arrays without support for iteratee + * shorthands. + * + * @private + * @param {Array} [array] The array to iterate over. + * @param {Function} iteratee The function invoked per iteration. + * @returns {Array} Returns the new mapped array. + */ + function arrayMap(array, iteratee) { + var index = -1, + length = array == null ? 0 : array.length, + result = Array(length); + + while (++index < length) { + result[index] = iteratee(array[index], index, array); + } + return result; + } + + module.exports = arrayMap; + + +/***/ }), + +/***/ 219: +/***/ (function(module, exports, __webpack_require__) { + + var baseToString = __webpack_require__(220); + + /** + * Converts `value` to a string. An empty string is returned for `null` + * and `undefined` values. The sign of `-0` is preserved. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to convert. + * @returns {string} Returns the converted string. + * @example + * + * _.toString(null); + * // => '' + * + * _.toString(-0); + * // => '-0' + * + * _.toString([1, 2, 3]); + * // => '1,2,3' + */ + function toString(value) { + return value == null ? '' : baseToString(value); + } + + module.exports = toString; + + +/***/ }), + +/***/ 220: +/***/ (function(module, exports, __webpack_require__) { + + var Symbol = __webpack_require__(92), + arrayMap = __webpack_require__(154), + isArray = __webpack_require__(112), + isSymbol = __webpack_require__(103); + + /** Used as references for various `Number` constants. */ + var INFINITY = 1 / 0; + + /** Used to convert symbols to primitives and strings. */ + var symbolProto = Symbol ? Symbol.prototype : undefined, + symbolToString = symbolProto ? symbolProto.toString : undefined; + + /** + * The base implementation of `_.toString` which doesn't convert nullish + * values to empty strings. + * + * @private + * @param {*} value The value to process. + * @returns {string} Returns the string. + */ + function baseToString(value) { + // Exit early for strings to avoid a performance hit in some environments. + if (typeof value == 'string') { + return value; + } + if (isArray(value)) { + // Recursively convert values (susceptible to call stack limits). + return arrayMap(value, baseToString) + ''; + } + if (isSymbol(value)) { + return symbolToString ? symbolToString.call(value) : ''; + } + var result = (value + ''); + return (result == '0' && (1 / value) == -INFINITY) ? 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+ } + + } + + module.exports = showBrowserWarningIfRequired; + showBrowserWarningIfRequired(); + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 322: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {String.prototype.replaceAll = function ( search, replacement ){ + var target = this; + return target.split(search).join(replacement); + }; + module.exports = function (){ + var newOntologyCounter = 1; + var app = {}, + graph = webvowl.graph(), + options = graph.graphOptions(), + languageTools = webvowl.util.languageTools(), + GRAPH_SELECTOR = "#graph", + // Modules for the webvowl app + exportMenu = __webpack_require__(323)(graph), + filterMenu = __webpack_require__(325)(graph), + gravityMenu = __webpack_require__(326)(graph), + modeMenu = __webpack_require__(327)(graph), + debugMenu = __webpack_require__(328)(graph), + ontologyMenu = __webpack_require__(329)(graph), + pauseMenu = __webpack_require__(333)(graph), + resetMenu = __webpack_require__(334)(graph), + searchMenu = __webpack_require__(335)(graph), + navigationMenu = __webpack_require__(336)(graph), + zoomSlider = __webpack_require__(337)(graph), + sidebar = __webpack_require__(338)(graph), + leftSidebar = __webpack_require__(339)(graph), + editSidebar = __webpack_require__(340)(graph), + configMenu = __webpack_require__(341)(graph), + loadingModule = __webpack_require__(342)(graph), + warningModule = __webpack_require__(343)(graph), + directInputMod = __webpack_require__(344)(graph), + + + // Graph modules + colorExternalsSwitch = webvowl.modules.colorExternalsSwitch(graph), + compactNotationSwitch = webvowl.modules.compactNotationSwitch(graph), + datatypeFilter = webvowl.modules.datatypeFilter(), + disjointFilter = webvowl.modules.disjointFilter(), + focuser = webvowl.modules.focuser(graph), + emptyLiteralFilter = webvowl.modules.emptyLiteralFilter(), + nodeDegreeFilter = webvowl.modules.nodeDegreeFilter(filterMenu), + nodeScalingSwitch = webvowl.modules.nodeScalingSwitch(graph), + objectPropertyFilter = webvowl.modules.objectPropertyFilter(), + pickAndPin = webvowl.modules.pickAndPin(), + selectionDetailDisplayer = webvowl.modules.selectionDetailsDisplayer(sidebar.updateSelectionInformation), + statistics = webvowl.modules.statistics(), + subclassFilter = webvowl.modules.subclassFilter(), + setOperatorFilter = webvowl.modules.setOperatorFilter(); + + + app.getOptions = function (){ + return webvowl.opts; + }; + app.getGraph = function (){ + return webvowl.gr; + }; + // app.afterInitializationCallback=undefined; + + + var executeFileDrop = false; + var wasMessageToShow = false; + var firstTime = false; + + function addFileDropEvents( selector ){ + var node = d3.select(selector); + + node.node().ondragover = function ( e ){ + e.preventDefault(); + + d3.select("#dragDropContainer").classed("hidden", false); + // get svg size + var w = graph.options().width(); + var h = graph.options().height(); + + // get event position; (using clientX and clientY); + var cx = e.clientX; + var cy = e.clientY; + + if ( firstTime === false ) { + var state = d3.select("#loading-info").classed("hidden"); + wasMessageToShow = !state; + firstTime = true; + d3.select("#loading-info").classed("hidden", true); // hide it so it does not conflict with drop event + var bb=d3.select("#drag_msg").node().getBoundingClientRect(); + var hs = bb.height; + var ws = bb.width; + + var icon_scale=Math.min(hs,ws); + icon_scale/=100; + + d3.select("#drag_icon_group").attr("transform", "translate ( " + 0.25 * ws + " " + 0.25 * hs + ")"); + d3.select("#drag_icon").attr("transform","matrix ("+icon_scale+",0,0,"+icon_scale+",0,0)"); + d3.select("#drag_icon_drop").attr("transform","matrix ("+icon_scale+",0,0,"+icon_scale+",0,0)"); + } + + + if ( (cx > 0.25 * w && cx < 0.75 * w) && (cy > 0.25 * h && cy < 0.75 * h) ) { + + d3.select("#drag_msg_text").node().innerHTML = "Drop it here."; + d3.select("#drag_msg").style("background-color", "#67bc0f"); + d3.select("#drag_msg").style("color", "#000000"); + executeFileDrop = true; + // d3.select("#drag_svg").transition() + // .duration(100) + // // .attr("-webkit-transform", "rotate(90)") + // // .attr("-moz-transform", "rotate(90)") + // // .attr("-o-transform", "rotate(90)") + // .attr("transform", "rotate(90)"); + + d3.select("#drag_icon").classed("hidden",true); + d3.select("#drag_icon_drop").classed("hidden",false); + + + } else { + d3.select("#drag_msg_text").node().innerHTML = "Drag ontology file here."; + d3.select("#drag_msg").style("background-color", "#fefefe"); + d3.select("#drag_msg").style("color", "#000000"); + executeFileDrop = false; + + d3.select("#drag_icon").classed("hidden",false); + d3.select("#drag_icon_drop").classed("hidden",true); + + + // d3.select("#drag_svg").transition() + // .duration(100) + // // .attr("-webkit-transform", "rotate(0)") + // // .attr("-moz-transform", "rotate(0)") + // // .attr("-o-transform", "rotate(0)") + // .attr("transform", "rotate(0)"); + // + } + + }; + node.node().ondrop = function ( ev ){ + ev.preventDefault(); + firstTime = false; + if ( executeFileDrop ) { + if ( ev.dataTransfer.items ) { + if ( ev.dataTransfer.items.length === 1 ) { + if ( ev.dataTransfer.items[0].kind === 'file' ) { + var file = ev.dataTransfer.items[0].getAsFile(); + graph.options().loadingModule().fromFileDrop(file.name, file); + } + } + else { + // >> WARNING not multiple file uploaded; + graph.options().warningModule().showMultiFileUploadWarning(); + } + } + } + d3.select("#dragDropContainer").classed("hidden", true); + }; + + node.node().ondragleave = function ( e ){ + var w = graph.options().width(); + var h = graph.options().height(); + + // get event position; (using clientX and clientY); + var cx = e.clientX; + var cy = e.clientY; + + var hidden = false; + firstTime = false; + + if ( cx < 0.1 * w || cx > 0.9 * w ) hidden = true; + if ( cy < 0.1 * h || cy > 0.9 * h ) hidden = true; + d3.select("#dragDropContainer").classed("hidden", hidden); + + d3.select("#loading-info").classed("hidden", !wasMessageToShow); // show it again + // check if it should be visible + var should_show=graph.options().loadingModule().getMessageVisibilityStatus(); + if (should_show===false){ + d3.select("#loading-info").classed("hidden", true); // hide it + } + }; + + } + + + app.initialize = function (){ + addFileDropEvents(GRAPH_SELECTOR); + + window.requestAnimationFrame = window.requestAnimationFrame || window.mozRequestAnimationFrame || window.webkitRequestAnimationFrame || window.msRequestAnimationFrame || function ( f ){ + return setTimeout(f, 1000 / 60); + }; // simulate calling code 60 + window.cancelAnimationFrame = window.cancelAnimationFrame || window.mozCancelAnimationFrame || function ( requestID ){ + clearTimeout(requestID); + }; //fall back + + options.graphContainerSelector(GRAPH_SELECTOR); + options.selectionModules().push(focuser); + options.selectionModules().push(selectionDetailDisplayer); + options.selectionModules().push(pickAndPin); + + options.filterModules().push(emptyLiteralFilter); + options.filterModules().push(statistics); + + options.filterModules().push(nodeDegreeFilter); + options.filterModules().push(datatypeFilter); + options.filterModules().push(objectPropertyFilter); + options.filterModules().push(subclassFilter); + options.filterModules().push(disjointFilter); + options.filterModules().push(setOperatorFilter); + options.filterModules().push(nodeScalingSwitch); + options.filterModules().push(compactNotationSwitch); + options.filterModules().push(colorExternalsSwitch); + + d3.select(window).on("resize", adjustSize); + + exportMenu.setup(); + gravityMenu.setup(); + filterMenu.setup(datatypeFilter, objectPropertyFilter, subclassFilter, disjointFilter, setOperatorFilter, nodeDegreeFilter); + modeMenu.setup(pickAndPin, nodeScalingSwitch, compactNotationSwitch, colorExternalsSwitch); + pauseMenu.setup(); + sidebar.setup(); + loadingModule.setup(); + leftSidebar.setup(); + editSidebar.setup(); + debugMenu.setup(); + var agentVersion = getInternetExplorerVersion(); + if ( agentVersion > 0 && agentVersion <= 11 ) { + console.log("Agent version " + agentVersion); + console.log("This agent is not supported"); + d3.select("#browserCheck").classed("hidden", false); + d3.select("#killWarning").classed("hidden", true); + d3.select("#optionsArea").classed("hidden", true); + d3.select("#logo").classed("hidden", true); + } else { + d3.select("#logo").classed("hidden", false); + if ( agentVersion === 12 ) { + // allow Mircosoft Edge Browser but with warning + d3.select("#browserCheck").classed("hidden", false); + d3.select("#killWarning").classed("hidden", false); + } else { + d3.select("#browserCheck").classed("hidden", true); + } + + resetMenu.setup([gravityMenu, filterMenu, modeMenu, focuser, selectionDetailDisplayer, pauseMenu]); + searchMenu.setup(); + navigationMenu.setup(); + zoomSlider.setup(); + + // give the options the pointer to the some menus for import and export + options.literalFilter(emptyLiteralFilter); + options.nodeDegreeFilter(nodeDegreeFilter); + options.loadingModule(loadingModule); + options.filterMenu(filterMenu); + options.modeMenu(modeMenu); + options.gravityMenu(gravityMenu); + options.pausedMenu(pauseMenu); + options.pickAndPinModule(pickAndPin); + options.resetMenu(resetMenu); + options.searchMenu(searchMenu); + options.ontologyMenu(ontologyMenu); + options.navigationMenu(navigationMenu); + options.sidebar(sidebar); + options.leftSidebar(leftSidebar); + options.editSidebar(editSidebar); + options.exportMenu(exportMenu); + options.graphObject(graph); + options.zoomSlider(zoomSlider); + options.warningModule(warningModule); + options.directInputModule(directInputMod); + options.datatypeFilter(datatypeFilter); + options.objectPropertyFilter(objectPropertyFilter); + options.subclassFilter(subclassFilter); + options.setOperatorFilter(setOperatorFilter); + options.disjointPropertyFilter(disjointFilter); + options.focuserModule(focuser); + options.colorExternalsModule(colorExternalsSwitch); + options.compactNotationModule(compactNotationSwitch); + + ontologyMenu.setup(loadOntologyFromText); + configMenu.setup(); + + leftSidebar.showSidebar(0); + leftSidebar.hideCollapseButton(true); + + + graph.start(); + + var modeOp = d3.select("#modeOfOperationString"); + modeOp.style("font-size", "0.6em"); + modeOp.style("font-style", "italic"); + + adjustSize(); + var defZoom; + var w = graph.options().width(); + var h = graph.options().height(); + defZoom = Math.min(w, h) / 1000; + + var hideDebugOptions = true; + if ( hideDebugOptions === false ) { + graph.setForceTickFunctionWithFPS(); + } + + graph.setDefaultZoom(defZoom); + d3.selectAll(".debugOption").classed("hidden", hideDebugOptions); + + // prevent backspace reloading event + var htmlBody = d3.select("body"); + d3.select(document).on("keydown", function ( e ){ + if ( d3.event.keyCode === 8 && d3.event.target === htmlBody.node() ) { + // we could add here an alert + d3.event.preventDefault(); + } + // using ctrl+Shift+d as debug option + if ( d3.event.ctrlKey && d3.event.shiftKey && d3.event.keyCode === 68 ) { + graph.options().executeHiddenDebugFeatuers(); + d3.event.preventDefault(); + } + }); + if ( d3.select("#maxLabelWidthSliderOption") ) { + var setValue = !graph.options().dynamicLabelWidth(); + d3.select("#maxLabelWidthSlider").node().disabled = setValue; + d3.select("#maxLabelWidthvalueLabel").classed("disabledLabelForSlider", setValue); + d3.select("#maxLabelWidthDescriptionLabel").classed("disabledLabelForSlider", setValue); + } + + d3.select("#blockGraphInteractions").style("position", "absolute") + .style("top", "0") + .style("background-color", "#bdbdbd") + .style("opacity", "0.5") + .style("pointer-events", "auto") + .style("width", graph.options().width() + "px") + .style("height", graph.options().height() + "px") + .on("click", function (){ + d3.event.preventDefault(); + d3.event.stopPropagation(); + }) + .on("dblclick", function (){ + d3.event.preventDefault(); + d3.event.stopPropagation(); + }); + + d3.select("#direct-text-input").on("click", function (){ + directInputMod.setDirectInputMode(); + }); + d3.select("#blockGraphInteractions").node().draggable = false; + options.prefixModule(webvowl.util.prefixTools(graph)); + adjustSize(); + sidebar.updateOntologyInformation(undefined, statistics); + loadingModule.parseUrlAndLoadOntology(); // loads automatically the ontology provided by the parameters + options.debugMenu(debugMenu); + debugMenu.updateSettings(); + + // connect the reloadCachedVersionButton + d3.select("#reloadSvgIcon").on("click", function (){ + if ( d3.select("#reloadSvgIcon").node().disabled === true ) { + graph.options().ontologyMenu().clearCachedVersion(); + return; + } + d3.select("#reloadCachedOntology").classed("hidden", true); + graph.options().ontologyMenu().reloadCachedOntology(); + + }); + // add the initialized objects + webvowl.opts = options; + webvowl.gr = graph; + + } + }; + + + function loadOntologyFromText( jsonText, filename, alternativeFilename ){ + d3.select("#reloadCachedOntology").classed("hidden", true); + pauseMenu.reset(); + graph.options().navigationMenu().hideAllMenus(); + + if ( (jsonText === undefined && filename === undefined) || (jsonText.length === 0) ) { + loadingModule.notValidJsonFile(); + return; + } + graph.editorMode(); // updates the checkbox + var data; + if ( jsonText ) { + // validate JSON FILE + var validJSON; + try { + data = JSON.parse(jsonText); + validJSON = true; + } catch ( e ) { + validJSON = false; + } + if ( validJSON === false ) { + // the server output is not a valid json file + loadingModule.notValidJsonFile(); + return; + } + + if ( !filename ) { + // First look if an ontology title exists, otherwise take the alternative filename + var ontologyNames = data.header ? data.header.title : undefined; + var ontologyName = languageTools.textInLanguage(ontologyNames); + + if ( ontologyName ) { + filename = ontologyName; + } else { + filename = alternativeFilename; + } + } + } + + + // check if we have graph data + var classCount = 0; + if ( data.class !== undefined ) { + classCount = data.class.length; + } + + var loadEmptyOntologyForEditing = false; + if ( location.hash.indexOf("#new_ontology") !== -1 ) { + loadEmptyOntologyForEditing = true; + newOntologyCounter++; + d3.select("#empty").node().href = "#opts=editorMode=true;#new_ontology" + newOntologyCounter; + } + if ( classCount === 0 && graph.editorMode() === false && loadEmptyOntologyForEditing === false ) { + // generate message for the user; + loadingModule.emptyGraphContentError(); + } else { + loadingModule.validJsonFile(); + ontologyMenu.setCachedOntology(filename, jsonText); + exportMenu.setJsonText(jsonText); + options.data(data); + graph.options().loadingModule().setPercentMode(); + if ( loadEmptyOntologyForEditing === true ) { + graph.editorMode(true); + + } + graph.load(); + sidebar.updateOntologyInformation(data, statistics); + exportMenu.setFilename(filename); + graph.updateZoomSliderValueFromOutside(); + adjustSize(); + + var flagOfCheckBox = d3.select("#editorModeModuleCheckbox").node().checked; + graph.editorMode(flagOfCheckBox);// update gui + + } + } + + function adjustSize(){ + var graphContainer = d3.select(GRAPH_SELECTOR), + svg = graphContainer.select("svg"), + height = window.innerHeight - 40, + width = window.innerWidth - (window.innerWidth * 0.22); + + if ( sidebar.getSidebarVisibility() === "0" ) { + height = window.innerHeight - 40; + width = window.innerWidth; + } + + directInputMod.updateLayout(); + d3.select("#blockGraphInteractions").style("width", window.innerWidth + "px"); + d3.select("#blockGraphInteractions").style("height", window.innerHeight + "px"); + + d3.select("#WarningErrorMessagesContainer").style("width", width + "px"); + d3.select("#WarningErrorMessagesContainer").style("height", height + "px"); + + d3.select("#WarningErrorMessages").style("max-height", (height - 12) + "px"); + + graphContainer.style("height", height + "px"); + svg.attr("width", width) + .attr("height", height); + + options.width(width) + .height(height); + + graph.updateStyle(); + + if ( isTouchDevice() === true ) { + if ( graph.isEditorMode() === true ) + d3.select("#modeOfOperationString").node().innerHTML = "touch able device detected"; + graph.setTouchDevice(true); + + } else { + if ( graph.isEditorMode() === true ) + d3.select("#modeOfOperationString").node().innerHTML = "point & click device detected"; + graph.setTouchDevice(false); + } + + d3.select("#loadingInfo-container").style("height", 0.5 * (height - 80) + "px"); + loadingModule.checkForScreenSize(); + + adjustSliderSize(); + // update also the padding options of loading and the logo positions; + var warningDiv = d3.select("#browserCheck"); + if ( warningDiv.classed("hidden") === false ) { + var offset = 10 + warningDiv.node().getBoundingClientRect().height; + d3.select("#logo").style("padding", offset + "px 10px"); + } else { + // remove the dynamic padding from the logo element; + d3.select("#logo").style("padding", "10px"); + } + + // scrollbar tests; + var element = d3.select("#menuElementContainer").node(); + var maxScrollLeft = element.scrollWidth - element.clientWidth; + var leftButton = d3.select("#scrollLeftButton"); + var rightButton = d3.select("#scrollRightButton"); + if ( maxScrollLeft > 0 ) { + // show both and then check how far is bar; + rightButton.classed("hidden", false); + leftButton.classed("hidden", false); + navigationMenu.updateScrollButtonVisibility(); + } else { + // hide both; + rightButton.classed("hidden", true); + leftButton.classed("hidden", true); + } + + // adjust height of the leftSidebar element; + editSidebar.updateElementWidth(); + + + var hs = d3.select("#drag_msg").node().getBoundingClientRect().height; + var ws = d3.select("#drag_msg").node().getBoundingClientRect().width; + d3.select("#drag_icon_group").attr("transform", "translate ( " + 0.25 * ws + " " + 0.25 * hs + ")"); + + } + + function adjustSliderSize(){ + // TODO: refactor and put this into the slider it self + var height = window.innerHeight - 40; + var fullHeight = height; + var zoomOutPos = height - 30; + var sliderHeight = 150; + + // assuming DOM elements are generated in the index.html + // todo: refactor for independent usage of graph and app + if ( fullHeight < 150 ) { + // hide the slider button; + d3.select("#zoomSliderParagraph").classed("hidden", true); + d3.select("#zoomOutButton").classed("hidden", true); + d3.select("#zoomInButton").classed("hidden", true); + d3.select("#centerGraphButton").classed("hidden", true); + return; + } + d3.select("#zoomSliderParagraph").classed("hidden", false); + d3.select("#zoomOutButton").classed("hidden", false); + d3.select("#zoomInButton").classed("hidden", false); + d3.select("#centerGraphButton").classed("hidden", false); + + var zoomInPos = zoomOutPos - 20; + var centerPos = zoomInPos - 20; + if ( fullHeight < 280 ) { + // hide the slider button; + d3.select("#zoomSliderParagraph").classed("hidden", true);//var sliderPos=zoomOutPos-sliderHeight; + d3.select("#zoomOutButton").style("top", zoomOutPos + "px"); + d3.select("#zoomInButton").style("top", zoomInPos + "px"); + d3.select("#centerGraphButton").style("top", centerPos + "px"); + return; + } + + var sliderPos = zoomOutPos - sliderHeight; + zoomInPos = sliderPos - 20; + centerPos = zoomInPos - 20; + d3.select("#zoomSliderParagraph").classed("hidden", false); + d3.select("#zoomOutButton").style("top", zoomOutPos + "px"); + d3.select("#zoomInButton").style("top", zoomInPos + "px"); + d3.select("#centerGraphButton").style("top", centerPos + "px"); + d3.select("#zoomSliderParagraph").style("top", sliderPos + "px"); + } + + function isTouchDevice(){ + try { + document.createEvent("TouchEvent"); + return true; + } catch ( e ) { + return false; + } + } + + + function getInternetExplorerVersion(){ + var ua, + re, + rv = -1; + + // check for edge + var isEdge = /(?:\b(MS)?IE\s+|\bTrident\/7\.0;.*\s+rv:|\bEdge\/)(\d+)/.test(navigator.userAgent); + if ( isEdge ) { + rv = parseInt("12"); + return rv; + } + + var isIE11 = /Trident.*rv[ :]*11\./.test(navigator.userAgent); + if ( isIE11 ) { + rv = parseInt("11"); + return rv; + } + if ( navigator.appName === "Microsoft Internet Explorer" ) { + ua = navigator.userAgent; + re = new RegExp("MSIE ([0-9]{1,}[\\.0-9]{0,})"); + if ( re.exec(ua) !== null ) { + rv = parseFloat(RegExp.$1); + } + } else if ( navigator.appName === "Netscape" ) { + ua = navigator.userAgent; + re = new RegExp("Trident/.*rv:([0-9]{1,}[\\.0-9]{0,})"); + if ( re.exec(ua) !== null ) { + rv = parseFloat(RegExp.$1); + } + } + return rv; + } + + return app; + } + ; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 323: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for the export button. + * @returns {{}} + */ + module.exports = function ( graph ){ + + var exportMenu = {}, + exportSvgButton, + exportFilename, + exportJsonButton, + exportTurtleButton, + exportTexButton, + copyButton, + exportableJsonText; + + var exportTTLModule = __webpack_require__(324)(graph); + + + String.prototype.replaceAll = function ( search, replacement ){ + var target = this; + return target.split(search).join(replacement); + }; + + + /** + * Adds the export button to the website. + */ + exportMenu.setup = function (){ + exportSvgButton = d3.select("#exportSvg") + .on("click", exportSvg); + exportJsonButton = d3.select("#exportJson") + .on("click", exportJson); + + copyButton = d3.select("#copyBt") + .on("click", copyUrl); + + exportTexButton = d3.select("#exportTex") + .on("click", exportTex); + + exportTurtleButton = d3.select("#exportTurtle") + .on("click", exportTurtle); + + var menuEntry = d3.select("#m_export"); + menuEntry.on("mouseover", function (){ + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + exportMenu.exportAsUrl(); + }); + }; + function exportTurtle(){ + var success = exportTTLModule.requestExport(); + var result = exportTTLModule.resultingTTL_Content(); + var ontoTitle = "NewOntology"; + console.log("Exporter was successful: " + success); + if ( success ) { + // console.log("The result is : " + result); + // var ontoTitle=graph.options().getGeneralMetaObjectProperty('title'); + // if (ontoTitle===undefined || ontoTitle.length===0) + // ontoTitle="NewOntology"; + // else{ + // // language object -.- + // ontoTitle.replace(" ","_") + // } + + // TODO: show TEXT in warning module? + + + // // write the data + var dataURI = "data:text/json;charset=utf-8," + encodeURIComponent(result); + + exportTurtleButton.attr("href", dataURI) + .attr("download", ontoTitle + ".ttl"); + + // okay restore old href? + // exportTurtleButton.attr("href", oldHref); + } else { + console.log("ShowWarning!"); + graph.options().warningModule().showExporterWarning(); + console.log("Stay on the page! " + window.location.href); + exportTurtleButton.attr("href", window.location.href); + d3.event.preventDefault(); // prevent the href to be called ( reloads the page otherwise ) + } + } + + exportMenu.setFilename = function ( filename ){ + exportFilename = filename || "export"; + }; + + exportMenu.setJsonText = function ( jsonText ){ + exportableJsonText = jsonText; + }; + + function copyUrl(){ + d3.select("#exportedUrl").node().focus(); + d3.select("#exportedUrl").node().select(); + document.execCommand("copy"); + graph.options().navigationMenu().hideAllMenus(); + d3.event.preventDefault(); // prevent the href to be called ( reloads the page otherwise ) + } + + function prepareOptionString( defOpts, currOpts ){ + var setOptions = 0; + var optsString = "opts="; + + for ( var name in defOpts ) { + // define key and value ; + if ( defOpts.hasOwnProperty(name) ) {// for travis warning + var def_value = defOpts[name]; + var cur_value = currOpts[name]; + if ( def_value !== cur_value ) { + optsString += name + "=" + cur_value + ";"; + setOptions++; + } + } + } + optsString += ""; + if ( setOptions === 0 ) { + return ""; + } + return optsString; + } + + exportMenu.exportAsUrl = function (){ + var currObj = {}; + currObj.sidebar = graph.options().sidebar().getSidebarVisibility(); + + // identify default value given by ontology; + var defOntValue = graph.options().filterMenu().getDefaultDegreeValue(); + var currentValue = graph.options().filterMenu().getDegreeSliderValue(); + if ( parseInt(defOntValue) === parseInt(currentValue) ) { + currObj.doc = -1; + } else { + currObj.doc = currentValue; + } + + currObj.cd = graph.options().classDistance(); + currObj.dd = graph.options().datatypeDistance(); + if ( graph.editorMode() === true ) { + currObj.editorMode = "true"; + } else { + currObj.editorMode = "false"; + } + currObj.filter_datatypes = String(graph.options().filterMenu().getCheckBoxValue("datatypeFilterCheckbox")); + currObj.filter_sco = String(graph.options().filterMenu().getCheckBoxValue("subclassFilterCheckbox")); + currObj.filter_disjoint = String(graph.options().filterMenu().getCheckBoxValue("disjointFilterCheckbox")); + currObj.filter_setOperator = String(graph.options().filterMenu().getCheckBoxValue("setoperatorFilterCheckbox")); + currObj.filter_objectProperties = String(graph.options().filterMenu().getCheckBoxValue("objectPropertyFilterCheckbox")); + currObj.mode_dynamic = String(graph.options().dynamicLabelWidth()); + currObj.mode_scaling = String(graph.options().modeMenu().getCheckBoxValue("nodescalingModuleCheckbox")); + currObj.mode_compact = String(graph.options().modeMenu().getCheckBoxValue("compactnotationModuleCheckbox")); + currObj.mode_colorExt = String(graph.options().modeMenu().getCheckBoxValue("colorexternalsModuleCheckbox")); + currObj.mode_multiColor = String(graph.options().modeMenu().colorModeState()); + currObj.mode_pnp = String(graph.options().modeMenu().getCheckBoxValue("pickandpinModuleCheckbox")); + currObj.debugFeatures = String(!graph.options().getHideDebugFeatures()); + currObj.rect = 0; + + var defObj = graph.options().initialConfig(); + var optsString = prepareOptionString(defObj, currObj); + var urlString = String(location); + var htmlElement; + // when everything is default then there is nothing to write + if ( optsString.length === 0 ) { + // building up parameter list; + + // remove the all options form location + var hashCode = location.hash; + urlString = urlString.split(hashCode)[0]; + + var lPos = hashCode.lastIndexOf("#"); + if ( lPos === -1 ) { + htmlElement = d3.select("#exportedUrl").node(); + htmlElement.value = String(location); + htmlElement.title = String(location); + return; // nothing to change in the location String + } + var newURL = hashCode.slice(lPos, hashCode.length); + htmlElement = d3.select("#exportedUrl").node(); + htmlElement.value = urlString + newURL; + htmlElement.title = urlString + newURL; + return; + } + + // generate the options string; + var numParameters = (urlString.match(/#/g) || []).length; + var newUrlString; + if ( numParameters === undefined || numParameters === 0 ) { + newUrlString = urlString + "#" + optsString; + } + if ( numParameters > 0 ) { + var tokens = urlString.split("#"); + var i; + if ( tokens[1].indexOf("opts=") >= 0 ) { + tokens[1] = optsString; + newUrlString = tokens[0]; + } else { + newUrlString = tokens[0] + "#"; + newUrlString += optsString; + } + // append parameters + for ( i = 1; i < tokens.length; i++ ) { + if ( tokens[i].length > 0 ) { + newUrlString += "#" + tokens[i]; + } + } + } + // building up parameter list; + htmlElement = d3.select("#exportedUrl").node(); + htmlElement.value = newUrlString; + htmlElement.title = newUrlString; + + }; + + function exportSvg(){ + graph.options().navigationMenu().hideAllMenus(); + // Get the d3js SVG element + var graphSvg = d3.select(graph.options().graphContainerSelector()).select("svg"), + graphSvgCode, + escapedGraphSvgCode, + dataURI; + + // inline the styles, so that the exported svg code contains the css rules + inlineVowlStyles(); + hideNonExportableElements(); + + graphSvgCode = graphSvg.attr("version", 1.1) + .attr("xmlns", "http://www.w3.org/2000/svg") + .node().parentNode.innerHTML; + + // Insert the reference to VOWL + graphSvgCode = "\n" + graphSvgCode; + + escapedGraphSvgCode = escapeUnicodeCharacters(graphSvgCode); + //btoa(); Creates a base-64 encoded ASCII string from a "string" of binary data. + dataURI = "data:image/svg+xml;base64," + btoa(escapedGraphSvgCode); + + + exportSvgButton.attr("href", dataURI) + .attr("download", exportFilename + ".svg"); + + // remove graphic styles for interaction to go back to normal + removeVowlInlineStyles(); + showNonExportableElements(); + graph.lazyRefresh(); + } + + function escapeUnicodeCharacters( text ){ + var textSnippets = [], + i, textLength = text.length, + character, + charCode; + + for ( i = 0; i < textLength; i++ ) { + character = text.charAt(i); + charCode = character.charCodeAt(0); + + if ( charCode < 128 ) { + textSnippets.push(character); + } else { + textSnippets.push("&#" + charCode + ";"); + } + } + + return textSnippets.join(""); + } + + function inlineVowlStyles(){ + setStyleSensitively(".text", [{ name: "font-family", value: "Helvetica, Arial, sans-serif" }, { + name: "font-size", + value: "12px" + }]); + setStyleSensitively(".subtext", [{ name: "font-size", value: "9px" }]); + setStyleSensitively(".text.instance-count", [{ name: "fill", value: "#666" }]); + setStyleSensitively(".external + text .instance-count", [{ name: "fill", value: "#aaa" }]); + setStyleSensitively(".cardinality", [{ name: "font-size", value: "10px" }]); + setStyleSensitively(".text, .embedded", [{ name: "pointer-events", value: "none" }]); + setStyleSensitively(".class, .object, .disjoint, .objectproperty, .disjointwith, .equivalentproperty, .transitiveproperty, .functionalproperty, .inversefunctionalproperty, .symmetricproperty, .allvaluesfromproperty, .somevaluesfromproperty", [{ + name: "fill", + value: "#acf" + }]); + setStyleSensitively(".label .datatype, .datatypeproperty", [{ name: "fill", value: "#9c6" }]); + setStyleSensitively(".rdf, .rdfproperty", [{ name: "fill", value: "#c9c" }]); + setStyleSensitively(".literal, .node .datatype", [{ name: "fill", value: "#fc3" }]); + setStyleSensitively(".deprecated, .deprecatedproperty", [{ name: "fill", value: "#ccc" }]); + setStyleSensitively(".external, .externalproperty", [{ name: "fill", value: "#36c" }]); + setStyleSensitively("path, .nofill", [{ name: "fill", value: "none" }]); + setStyleSensitively("marker path", [{ name: "fill", value: "#000" }]); + setStyleSensitively(".class, path, line, .fineline", [{ name: "stroke", value: "#000" }]); + setStyleSensitively(".white, .subclass, .subclassproperty, .external + text", [{ name: "fill", value: "#fff" }]); + setStyleSensitively(".class.hovered, .property.hovered, .cardinality.hovered, .cardinality.focused, circle.pin, .filled.hovered, .filled.focused", [{ + name: "fill", + value: "#f00" + }, { name: "cursor", value: "pointer" }]); + setStyleSensitively(".focused, path.hovered", [{ name: "stroke", value: "#f00" }]); + setStyleSensitively(".indirect-highlighting, .feature:hover", [{ name: "fill", value: "#f90" }]); + setStyleSensitively(".values-from", [{ name: "stroke", value: "#69c" }]); + setStyleSensitively(".symbol, .values-from.filled", [{ name: "fill", value: "#69c" }]); + setStyleSensitively(".class, path, line", [{ name: "stroke-width", value: "2" }]); + setStyleSensitively(".fineline", [{ name: "stroke-width", value: "1" }]); + setStyleSensitively(".dashed, .anonymous", [{ name: "stroke-dasharray", value: "8" }]); + setStyleSensitively(".dotted", [{ name: "stroke-dasharray", value: "3" }]); + setStyleSensitively("rect.focused, circle.focused", [{ name: "stroke-width", value: "4px" }]); + setStyleSensitively(".nostroke", [{ name: "stroke", value: "none" }]); + setStyleSensitively("marker path", [{ name: "stroke-dasharray", value: "100" }]); + } + + function setStyleSensitively( selector, styles ){ + var elements = d3.selectAll(selector); + if ( elements.empty() ) { + return; + } + + styles.forEach(function ( style ){ + elements.each(function (){ + var element = d3.select(this); + if ( !shouldntChangeInlineCss(element, style.name) ) { + element.style(style.name, style.value); + } + }); + }); + } + + function shouldntChangeInlineCss( element, style ){ + return style === "fill" && hasBackgroundColorSet(element); + } + + function hasBackgroundColorSet( element ){ + var data = element.datum(); + if ( data === undefined ) { + return false; + } + return data.backgroundColor && !!data.backgroundColor(); + } + + /** + * For example the pin of the pick&pin module should be invisible in the exported graphic. + */ + function hideNonExportableElements(){ + d3.selectAll(".hidden-in-export").style("display", "none"); + } + + function removeVowlInlineStyles(){ + d3.selectAll(".text, .subtext, .text.instance-count, .external + text .instance-count, .cardinality, .text, .embedded, .class, .object, .disjoint, .objectproperty, .disjointwith, .equivalentproperty, .transitiveproperty, .functionalproperty, .inversefunctionalproperty, .symmetricproperty, .allvaluesfromproperty, .somevaluesfromproperty, .label .datatype, .datatypeproperty, .rdf, .rdfproperty, .literal, .node .datatype, .deprecated, .deprecatedproperty, .external, .externalproperty, path, .nofill, .symbol, .values-from.filled, marker path, .class, path, line, .fineline, .white, .subclass, .subclassproperty, .external + text, .class.hovered, .property.hovered, .cardinality.hovered, .cardinality.focused, circle.pin, .filled.hovered, .filled.focused, .focused, path.hovered, .indirect-highlighting, .feature:hover, .values-from, .class, path, line, .fineline, .dashed, .anonymous, .dotted, rect.focused, circle.focused, .nostroke, marker path") + .each(function (){ + var element = d3.select(this); + + var inlineStyles = element.node().style; + for ( var styleName in inlineStyles ) { + if ( inlineStyles.hasOwnProperty(styleName) ) { + if ( shouldntChangeInlineCss(element, styleName) ) { + continue; + } + element.style(styleName, null); + } + } + + if ( element.datum && element.datum() !== undefined && element.datum().type ) { + if ( element.datum().type() === "rdfs:subClassOf" ) { + element.style("fill", null); + } + } + }); + + // repair svg icons in the menu; + var scrollContainer = d3.select("#menuElementContainer").node(); + var controlElements = scrollContainer.children; + var numEntries = controlElements.length; + + for ( var i = 0; i < numEntries; i++ ) { + var currentMenu = controlElements[i].id; + d3.select("#" + currentMenu).select("path").style("stroke-width", "0"); + d3.select("#" + currentMenu).select("path").style("fill", "#fff"); + } + + d3.select("#magnifyingGlass").style("stroke-width", "0"); + d3.select("#magnifyingGlass").style("fill", "#666"); + + } + + function showNonExportableElements(){ + d3.selectAll(".hidden-in-export").style("display", null); + } + + exportMenu.createJSON_exportObject = function (){ + var i, j, k; // an index variable for the for-loops + + /** get data for exporter **/ + if (!graph.options().data()) {return {};} // return an empty json object + // extract onotology information; + var unfilteredData = graph.getUnfilteredData(); + var ontologyComment = graph.options().data()._comment; + var metaObj = graph.options().getGeneralMetaObject(); + var header = graph.options().data().header; + + if ( metaObj.iri && metaObj.iri !== header.iri ) { + header.iri = metaObj.iri; + } + if ( metaObj.title && metaObj.title !== header.title ) { + header.title = metaObj.title; + } + if ( metaObj.version && metaObj.version !== header.version ) { + header.version = metaObj.version; + } + if ( metaObj.author && metaObj.author !== header.author ) { + header.author = metaObj.author; + } + if ( metaObj.description && metaObj.description !== header.description ) { + header.description = metaObj.description; + } + + + var exportText = {}; + exportText._comment = ontologyComment; + exportText.header = header; + exportText.namespace = graph.options().data().namespace; + if ( exportText.namespace === undefined ) { + exportText.namespace = []; // just an empty namespace array + } + // we do have now the unfiltered data which needs to be transfered to class/classAttribute and property/propertyAttribute + + + // var classAttributeString='classAttribute:[ \n'; + var nodes = unfilteredData.nodes; + var nLen = nodes.length; // hope for compiler unroll + var classObjects = []; + var classAttributeObjects = []; + for ( i = 0; i < nLen; i++ ) { + var classObj = {}; + var classAttr = {}; + classObj.id = nodes[i].id(); + classObj.type = nodes[i].type(); + classObjects.push(classObj); + + // define the attributes object + classAttr.id = nodes[i].id(); + classAttr.iri = nodes[i].iri(); + classAttr.baseIri = nodes[i].baseIri(); + classAttr.label = nodes[i].label(); + + if ( nodes[i].attributes().length > 0 ) { + classAttr.attributes = nodes[i].attributes(); + } + if ( nodes[i].comment() ) { + classAttr.comment = nodes[i].comment(); + } + if ( nodes[i].annotations() ) { + classAttr.annotations = nodes[i].annotations(); + } + if ( nodes[i].description() ) { + classAttr.description = nodes[i].description(); + } + + + if ( nodes[i].individuals().length > 0 ) { + var classIndividualElements = []; + var nIndividuals = nodes[i].individuals(); + for ( j = 0; j < nIndividuals.length; j++ ) { + var indObj = {}; + indObj.iri = nIndividuals[j].iri(); + indObj.baseIri = nIndividuals[j].baseIri(); + indObj.labels = nIndividuals[j].label(); + if ( nIndividuals[j].annotations() ) { + indObj.annotations = nIndividuals[j].annotations(); + } + if ( nIndividuals[j].description() ) { + indObj.description = nIndividuals[j].description(); + } + if ( nIndividuals[j].comment() ) { + indObj.comment = nIndividuals[j].comment(); + } + classIndividualElements.push(indObj); + } + classAttr.individuals = classIndividualElements; + } + + var equalsForAttributes = undefined; + if ( nodes[i].equivalents().length > 0 ) { + equalsForAttributes = []; + var equals = nodes[i].equivalents(); + for ( j = 0; j < equals.length; j++ ) { + var eqObj = {}; + var eqAttr = {}; + eqObj.id = equals[j].id(); + equalsForAttributes.push(equals[j].id()); + eqObj.type = equals[j].type(); + classObjects.push(eqObj); + + eqAttr.id = equals[j].id(); + eqAttr.iri = equals[j].iri(); + eqAttr.baseIri = equals[j].baseIri(); + eqAttr.label = equals[j].label(); + + if ( equals[j].attributes().length > 0 ) { + eqAttr.attributes = equals[j].attributes(); + } + if ( equals[j].comment() ) { + eqAttr.comment = equals[j].comment(); + } + if ( equals[j].individuals().length > 0 ) { + eqAttr.individuals = equals[j].individuals(); + } + if ( equals[j].annotations() ) { + eqAttr.annotations = equals[j].annotations(); + } + if ( equals[j].description() ) { + eqAttr.description = equals[j].description(); + } + + if ( equals[j].individuals().length > 0 ) { + var e_classIndividualElements = []; + var e_nIndividuals = equals[i].individuals(); + for ( k = 0; k < e_nIndividuals.length; k++ ) { + var e_indObj = {}; + e_indObj.iri = e_nIndividuals[k].iri(); + e_indObj.baseIri = e_nIndividuals[k].baseIri(); + e_indObj.labels = e_nIndividuals[k].label(); + + if ( e_nIndividuals[k].annotations() ) { + e_indObj.annotations = e_nIndividuals[k].annotations(); + } + if ( e_nIndividuals[k].description() ) { + e_indObj.description = e_nIndividuals[k].description(); + } + if ( e_nIndividuals[k].comment() ) { + e_indObj.comment = e_nIndividuals[k].comment(); + } + e_classIndividualElements.push(e_indObj); + } + eqAttr.individuals = e_classIndividualElements; + } + + classAttributeObjects.push(eqAttr); + } + } + if ( equalsForAttributes && equalsForAttributes.length > 0 ) { + classAttr.equivalent = equalsForAttributes; + } + + // classAttr.subClasses=nodes[i].subClasses(); // not needed + // classAttr.instances=nodes[i].instances(); + + // + // .complement(element.complement) + // .disjointUnion(element.disjointUnion) + // .description(element.description) + // .equivalents(element.equivalent) + // .intersection(element.intersection) + // .type(element.type) Ignore, because we predefined it + // .union(element.union) + classAttributeObjects.push(classAttr); + } + + /** -- properties -- **/ + var properties = unfilteredData.properties; + var pLen = properties.length; // hope for compiler unroll + var propertyObjects = []; + var propertyAttributeObjects = []; + + for ( i = 0; i < pLen; i++ ) { + var pObj = {}; + var pAttr = {}; + pObj.id = properties[i].id(); + pObj.type = properties[i].type(); + propertyObjects.push(pObj); + + // // define the attributes object + pAttr.id = properties[i].id(); + pAttr.iri = properties[i].iri(); + pAttr.baseIri = properties[i].baseIri(); + pAttr.label = properties[i].label(); + + if ( properties[i].attributes().length > 0 ) { + pAttr.attributes = properties[i].attributes(); + } + if ( properties[i].comment() ) { + pAttr.comment = properties[i].comment(); + } + + if ( properties[i].annotations() ) { + pAttr.annotations = properties[i].annotations(); + } + if ( properties[i].maxCardinality() ) { + pAttr.maxCardinality = properties[i].maxCardinality(); + } + if ( properties[i].minCardinality() ) { + pAttr.minCardinality = properties[i].minCardinality(); + } + if ( properties[i].cardinality() ) { + pAttr.cardinality = properties[i].cardinality(); + } + if ( properties[i].description() ) { + pAttr.description = properties[i].description(); + } + + pAttr.domain = properties[i].domain().id(); + pAttr.range = properties[i].range().id(); + // sub properties; + if ( properties[i].subproperties() ) { + var subProps = properties[i].subproperties(); + var subPropsIdArray = []; + for ( j = 0; j < subProps.length; j++ ) { + if ( subProps[j].id ) + subPropsIdArray.push(subProps[j].id()); + } + pAttr.subproperty = subPropsIdArray; + } + + // super properties + if ( properties[i].superproperties() ) { + var superProps = properties[i].superproperties(); + var superPropsIdArray = []; + for ( j = 0; j < superProps.length; j++ ) { + if ( superProps[j].id ) + superPropsIdArray.push(superProps[j].id()); + } + pAttr.superproperty = superPropsIdArray; + } + + // check for inverse element + if ( properties[i].inverse() ) { + if ( properties[i].inverse().id ) + pAttr.inverse = properties[i].inverse().id(); + } + propertyAttributeObjects.push(pAttr); + } + + exportText.class = classObjects; + exportText.classAttribute = classAttributeObjects; + exportText.property = propertyObjects; + exportText.propertyAttribute = propertyAttributeObjects; + + + var nodeElements = graph.graphNodeElements(); // get visible nodes + var propElements = graph.graphLabelElements(); // get visible labels + // var jsonObj = JSON.parse(exportableJsonText); // reparse the original input json + + /** modify comment **/ + var comment = exportText._comment; + var additionalString = " [Additional Information added by WebVOWL Exporter Version: " + "1.1.7" + "]"; + // adding new string to comment only if it does not exist + if ( comment.indexOf(additionalString) === -1 ) { + exportText._comment = comment + " [Additional Information added by WebVOWL Exporter Version: " + "1.1.7" + "]"; + } + + var classAttribute = exportText.classAttribute; + var propAttribute = exportText.propertyAttribute; + /** remove previously stored variables **/ + for ( i = 0; i < classAttribute.length; i++ ) { + var classObj_del = classAttribute[i]; + delete classObj_del.pos; + delete classObj_del.pinned; + } + var propertyObj; + for ( i = 0; i < propAttribute.length; i++ ) { + propertyObj = propAttribute[i]; + delete propertyObj.pos; + delete propertyObj.pinned; + } + /** add new variables to jsonObj **/ + // class attribute variables + nodeElements.each(function ( node ){ + var nodeId = node.id(); + for ( i = 0; i < classAttribute.length; i++ ) { + var classObj = classAttribute[i]; + if ( classObj.id === nodeId ) { + // store relative positions + classObj.pos = [parseFloat(node.x.toFixed(2)), parseFloat(node.y.toFixed(2))]; + if ( node.pinned() ) + classObj.pinned = true; + break; + } + } + }); + // property attribute variables + for ( j = 0; j < propElements.length; j++ ) { + var correspondingProp = propElements[j].property(); + for ( i = 0; i < propAttribute.length; i++ ) { + propertyObj = propAttribute[i]; + if ( propertyObj.id === correspondingProp.id() ) { + propertyObj.pos = [parseFloat(propElements[j].x.toFixed(2)), parseFloat(propElements[j].y.toFixed(2))]; + if ( propElements[j].pinned() ) + propertyObj.pinned = true; + break; + } + } + } + /** create the variable for settings and set their values **/ + exportText.settings = {}; + + // Global Settings + var zoom = graph.scaleFactor(); + var paused = graph.paused(); + var translation = [parseFloat(graph.translation()[0].toFixed(2)), parseFloat(graph.translation()[1].toFixed(2))]; + exportText.settings.global = {}; + exportText.settings.global.zoom = zoom.toFixed(2); + exportText.settings.global.translation = translation; + exportText.settings.global.paused = paused; + + // shared variable declaration + var cb_text; + var isEnabled; + var cb_obj; + + // Gravity Settings + var classDistance = graph.options().classDistance(); + var datatypeDistance = graph.options().datatypeDistance(); + exportText.settings.gravity = {}; + exportText.settings.gravity.classDistance = classDistance; + exportText.settings.gravity.datatypeDistance = datatypeDistance; + + // Filter Settings + var fMenu = graph.options().filterMenu(); + var fContainer = fMenu.getCheckBoxContainer(); + var cbCont = []; + for ( i = 0; i < fContainer.length; i++ ) { + cb_text = fContainer[i].checkbox.attr("id"); + isEnabled = fContainer[i].checkbox.property("checked"); + cb_obj = {}; + cb_obj.id = cb_text; + cb_obj.checked = isEnabled; + cbCont.push(cb_obj); + } + var degreeSliderVal = fMenu.getDegreeSliderValue(); + exportText.settings.filter = {}; + exportText.settings.filter.checkBox = cbCont; + exportText.settings.filter.degreeSliderValue = degreeSliderVal; + + // Modes Settings + var mMenu = graph.options().modeMenu(); + var mContainer = mMenu.getCheckBoxContainer(); + var cb_modes = []; + for ( i = 0; i < mContainer.length; i++ ) { + cb_text = mContainer[i].attr("id"); + isEnabled = mContainer[i].property("checked"); + cb_obj = {}; + cb_obj.id = cb_text; + cb_obj.checked = isEnabled; + cb_modes.push(cb_obj); + } + var colorSwitchState = mMenu.colorModeState(); + exportText.settings.modes = {}; + exportText.settings.modes.checkBox = cb_modes; + exportText.settings.modes.colorSwitchState = colorSwitchState; + + var exportObj = {}; + // todo: [ ] find better way for ordering the objects + // hack for ordering of objects, so settings is after metrics + exportObj._comment = exportText._comment; + exportObj.header = exportText.header; + exportObj.namespace = exportText.namespace; + exportObj.metrics = exportText.metrics; + exportObj.settings = exportText.settings; + exportObj.class = exportText.class; + exportObj.classAttribute = exportText.classAttribute; + exportObj.property = exportText.property; + exportObj.propertyAttribute = exportText.propertyAttribute; + + return exportObj; + }; + + function exportJson(){ + graph.options().navigationMenu().hideAllMenus(); + /** check if there is data **/ + if ( !exportableJsonText ) { + alert("No graph data available."); + // Stop the redirection to the path of the href attribute + d3.event.preventDefault(); + return; + } + + var exportObj = exportMenu.createJSON_exportObject(); + + // make a string again; + var exportText = JSON.stringify(exportObj, null, ' '); + // write the data + var dataURI = "data:text/json;charset=utf-8," + encodeURIComponent(exportText); + var jsonExportFileName = exportFilename; + + if ( !jsonExportFileName.endsWith(".json") ) + jsonExportFileName += ".json"; + exportJsonButton.attr("href", dataURI) + .attr("download", jsonExportFileName); + } + + var curveFunction = d3.svg.line() + .x(function ( d ){ + return d.x; + }) + .y(function ( d ){ + return d.y; + }) + .interpolate("cardinal"); + var loopFunction = d3.svg.line() + .x(function ( d ){ + return d.x; + }) + .y(function ( d ){ + return d.y; + }) + .interpolate("cardinal") + .tension(-1); + + function exportTex(){ + var zoom = graph.scaleFactor(); + var grTranslate = graph.translation(); + var bbox = graph.getBoundingBoxForTex(); + var comment = " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n"; + comment += " % Generated with the experimental alpha version of the TeX exporter of WebVOWL (version 1.1.3) %%% \n"; + comment += " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n\n"; + comment += " % The content can be used as import in other TeX documents. \n"; + comment += " % Parent document has to use the following packages \n"; + comment += " % \\usepackage{tikz} \n"; + comment += " % \\usepackage{helvet} \n"; + comment += " % \\usetikzlibrary{decorations.markings,decorations.shapes,decorations,arrows,automata,backgrounds,petri,shapes.geometric} \n"; + comment += " % \\usepackage{xcolor} \n\n"; + comment += " %%%%%%%%%%%%%%% Example Parent Document %%%%%%%%%%%%%%%%%%%%%%%\n"; + comment += " %\\documentclass{article} \n"; + comment += " %\\usepackage{tikz} \n"; + comment += " %\\usepackage{helvet} \n"; + comment += " %\\usetikzlibrary{decorations.markings,decorations.shapes,decorations,arrows,automata,backgrounds,petri,shapes.geometric} \n"; + comment += " %\\usepackage{xcolor} \n\n"; + comment += " %\\begin{document} \n"; + comment += " %\\section{Example} \n"; + comment += " % This is an example. \n"; + comment += " % \\begin{figure} \n"; + comment += " % \\input{} % << tex file name for the graph \n"; + comment += " % \\caption{A generated graph with TKIZ using alpha version of the TeX exporter of WebVOWL (version 1.1.3) } \n"; + comment += " % \\end{figure} \n"; + comment += " %\\end{document} \n"; + comment += " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n\n"; + + + var texString = comment + "\\definecolor{imageBGCOLOR}{HTML}{FFFFFF} \n" + + "\\definecolor{owlClassColor}{HTML}{AACCFF}\n" + + "\\definecolor{owlObjectPropertyColor}{HTML}{AACCFF}\n" + + "\\definecolor{owlExternalClassColor}{HTML}{AACCFF}\n" + + "\\definecolor{owlDatatypePropertyColor}{HTML}{99CC66}\n" + + "\\definecolor{owlDatatypeColor}{HTML}{FFCC33}\n" + + "\\definecolor{owlThingColor}{HTML}{FFFFFF}\n" + + "\\definecolor{valuesFrom}{HTML}{6699CC}\n" + + "\\definecolor{rdfPropertyColor}{HTML}{CC99CC}\n" + + "\\definecolor{unionColor}{HTML}{6699cc}\n" + + "\\begin{center} \n" + + "\\resizebox{\\linewidth}{!}{\n" + + + "\\begin{tikzpicture}[framed]\n" + + "\\clip (" + bbox[0] + "pt , " + bbox[1] + "pt ) rectangle (" + bbox[2] + "pt , " + bbox[3] + "pt);\n" + + "\\tikzstyle{dashed}=[dash pattern=on 4pt off 4pt] \n" + + "\\tikzstyle{dotted}=[dash pattern=on 2pt off 2pt] \n" + + "\\fontfamily{sans-serif}{\\fontsize{12}{12}\\selectfont}\n \n"; + + + texString += "\\tikzset{triangleBlack/.style = {fill=black, draw=black, line width=1pt,scale=0.7,regular polygon, regular polygon sides=3} }\n"; + texString += "\\tikzset{triangleWhite/.style = {fill=white, draw=black, line width=1pt,scale=0.7,regular polygon, regular polygon sides=3} }\n"; + texString += "\\tikzset{triangleBlue/.style = {fill=valuesFrom, draw=valuesFrom, line width=1pt,scale=0.7,regular polygon, regular polygon sides=3} }\n"; + + texString += "\\tikzset{Diamond/.style = {fill=white, draw=black, line width=2pt,scale=1.2,regular polygon, regular polygon sides=4} }\n"; + + + texString += "\\tikzset{Literal/.style={rectangle,align=center,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "black, draw=black, dashed, line width=1pt, fill=owlDatatypeColor, minimum width=80pt,\n" + + "minimum height = 20pt}}\n\n"; + + texString += "\\tikzset{Datatype/.style={rectangle,align=center,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "black, draw=black, line width=1pt, fill=owlDatatypeColor, minimum width=80pt,\n" + + "minimum height = 20pt}}\n\n"; + + + texString += "\\tikzset{owlClass/.style={circle, inner sep=0mm,align=center, \n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "black, draw=black, line width=1pt, fill=owlClassColor, minimum size=101pt}}\n\n"; + + texString += "\\tikzset{anonymousClass/.style={circle, inner sep=0mm,align=center, \n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "black, dashed, draw=black, line width=1pt, fill=owlClassColor, minimum size=101pt}}\n\n"; + + + texString += "\\tikzset{owlThing/.style={circle, inner sep=0mm,align=center,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "black, dashed, draw=black, line width=1pt, fill=owlThingColor, minimum size=62pt}}\n\n"; + + + texString += "\\tikzset{owlObjectProperty/.style={rectangle,align=center,\n" + + "inner sep=0mm,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "fill=owlObjectPropertyColor, minimum width=80pt,\n" + + "minimum height = 25pt}}\n\n"; + + texString += "\\tikzset{rdfProperty/.style={rectangle,align=center,\n" + + "inner sep=0mm,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "fill=rdfPropertyColor, minimum width=80pt,\n" + + "minimum height = 25pt}}\n\n"; + + + texString += "\\tikzset{owlDatatypeProperty/.style={rectangle,align=center,\n" + + "fill=owlDatatypePropertyColor, minimum width=80pt,\n" + + "inner sep=0mm,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "minimum height = 25pt}}\n\n"; + + texString += "\\tikzset{rdfsSubClassOf/.style={rectangle,align=center,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "inner sep=0mm,\n" + + "fill=imageBGCOLOR, minimum width=80pt,\n" + + "minimum height = 25pt}}\n\n"; + + texString += "\\tikzset{unionOf/.style={circle, inner sep=0mm,align=center,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "black, draw=black, line width=1pt, fill=unionColor, minimum size=25pt}}\n\n"; + + texString += "\\tikzset{disjointWith/.style={circle, inner sep=0mm,align=center,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "black, draw=black, line width=1pt, fill=unionColor, minimum size=20pt}}\n\n"; + + + texString += "\\tikzset{owlEquivalentClass/.style={circle,align=center,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "inner sep=0mm,\n" + + "black, solid, draw=black, line width=3pt, fill=owlExternalClassColor, minimum size=101pt,\n" + + "postaction = {draw,line width=1pt, white}}}\n\n"; + + // draw a bounding box; + + // get bbox coordinates; + + + graph.options().navigationMenu().hideAllMenus(); + /** check if there is data **/ + if ( !exportableJsonText ) { + alert("No graph data available."); + // Stop the redirection to the path of the href attribute + d3.event.preventDefault(); + return; + } + + var i = 0, identifier; + + /** get data for exporter **/ + var nodeElements = graph.graphNodeElements(); // get visible nodes + var propElements = graph.graphLabelElements(); // get visible labels + var links = graph.graphLinkElements(); + + // export only nodes; + // draw Links; + for ( i = 0; i < links.length; i++ ) { + var link = links[i]; + // console.log("\n****************\nInverstigating Link for property "+link.property().labelForCurrentLanguage()); + + var prop = link.property(); + var dx, dy, px, py, rx, ry; + var colorStr = "black"; + var linkDomainIntersection; + var linkRangeIntersection; + var center; + var linkStyle = ""; + var isLoop = ""; + var curvePoint; + var pathStart; + var pathEnd; + var controlPoints; + var len; + var ahAngle; + var pathLen; + var markerOffset = 7; + + var arrowType = "triangleBlack"; + var linkWidth = ",line width=2pt"; + if ( prop.linkType ) { + if ( prop.linkType() === "dotted" ) { + //stroke-dasharray: 3; + linkStyle = ", dotted "; + arrowType = "triangleWhite"; + } + if ( prop.linkType() === "dashed" ) { + //stroke-dasharray: 3; + linkStyle = ", dashed "; + } + + if ( prop.linkType() === "values-from" ) { + colorStr = "valuesFrom"; + } + + } + + var startX, startY, endX, endY, normX, normY, lg; + + if ( link.layers().length === 1 && !link.loops() ) { + + linkDomainIntersection = graph.math().calculateIntersection(link.range(), link.domain(), 1); + linkRangeIntersection = graph.math().calculateIntersection(link.domain(), link.range(), 1); + center = graph.math().calculateCenter(linkDomainIntersection, linkRangeIntersection); + dx = linkDomainIntersection.x; + dy = -linkDomainIntersection.y; + px = center.x; + py = -center.y; + rx = linkRangeIntersection.x; + ry = -linkRangeIntersection.y; + + + pathStart = linkDomainIntersection; + curvePoint = center; + pathEnd = linkRangeIntersection; + + var nx = rx - px; + var ny = ry - py; + + // normalize ; + len = Math.sqrt(nx * nx + ny * ny); + + nx = nx / len; + ny = ny / len; + + ahAngle = Math.atan2(ny, nx) * (180 / Math.PI); + normX = nx; + normY = ny; + } + else { + if ( link.isLoop() ) { + isLoop = ", tension=3"; + controlPoints = graph.math().calculateLoopPoints(link); + pathStart = controlPoints[0]; + curvePoint = controlPoints[1]; + pathEnd = controlPoints[2]; + } else { + curvePoint = link.label(); + pathStart = graph.math().calculateIntersection(curvePoint, link.domain(), 1); + pathEnd = graph.math().calculateIntersection(curvePoint, link.range(), 1); + } + dx = pathStart.x; + dy = -pathStart.y; + px = curvePoint.x; + py = -curvePoint.y; + rx = pathEnd.x; + ry = -pathEnd.y; + } + + texString += "\\draw [" + colorStr + linkStyle + linkWidth + isLoop + "] plot [smooth] coordinates {(" + + dx + "pt, " + dy + "pt) (" + px + "pt, " + py + "pt) (" + rx + "pt, " + ry + "pt)};\n"; + + + if ( link.property().markerElement() === undefined ) continue; + + // add arrow head; + + + if ( link.property().type() === "owl:someValuesFrom" || link.property().type() === "owl:allValuesFrom" ) { + arrowType = "triangleBlue"; + } + + lg = link.pathObj(); + pathLen = Math.floor(lg.node().getTotalLength()); + var p1 = lg.node().getPointAtLength(pathLen - 4); + var p2 = lg.node().getPointAtLength(pathLen); + var markerCenter = lg.node().getPointAtLength(pathLen - 6); + + if ( link.property().type() === "setOperatorProperty" ) { + p1 = lg.node().getPointAtLength(4); + p2 = lg.node().getPointAtLength(0); + markerCenter = lg.node().getPointAtLength(8); + arrowType = "Diamond"; + } + + startX = p1.x; + startY = p1.y; + endX = p2.x; + endY = p2.y; + normX = endX - startX; + normY = endY - startY; + len = Math.sqrt(normX * normX + normY * normY); + normX = normX / len; + normY = normY / len; + + ahAngle = -1.0 * Math.atan2(normY, normX) * (180 / Math.PI); + ahAngle -= 90; + if ( link.property().type() === "setOperatorProperty" ) { + ahAngle -= 45; + } + // console.log(link.property().labelForCurrentLanguage()+ ": "+normX+ " "+normY +" "+ahAngle); + rx = markerCenter.x; + ry = markerCenter.y; + if ( link.layers().length === 1 && !link.loops() ) { + // markerOffset=-1*m + ry = -1 * ry; + texString += "\\node[" + arrowType + ", rotate=" + ahAngle + "] at (" + rx + "pt, " + ry + "pt) (single_marker" + i + ") {};\n "; + } else { + ry = -1 * ry; + texString += "\\node[" + arrowType + ", rotate=" + ahAngle + "] at (" + rx + "pt, " + ry + "pt) (marker" + i + ") {};\n "; + } + + // if (link.isLoop()){ + // rotAngle=-10+angle * (180 / Math.PI); + // } + + // add cardinality; + var cardinalityText = link.property().generateCardinalityText(); + if ( cardinalityText && cardinalityText.length > 0 ) { + var cardinalityCenter = lg.node().getPointAtLength(pathLen - 18); + var cx = cardinalityCenter.x - (10 * normY); + var cy = cardinalityCenter.y + (10 * normX); // using orthonormal y Coordinate + cy *= -1.0; + var textColor = "black"; + if ( cardinalityText.indexOf("A") > -1 ) { + cardinalityText = "$\\forall$"; + } + if ( cardinalityText.indexOf("E") > -1 ) { + cardinalityText = "$\\exists$"; + } + + + texString += "\\node[font={\\fontsize{12pt}{12}\\selectfont \\sffamily },text=" + textColor + "] at (" + cx + "pt, " + cy + "pt) (cardinalityText" + i + ") {" + cardinalityText + "};\n "; + } + + + if ( link.property().inverse() ) { + lg = link.pathObj(); + pathLen = Math.floor(lg.node().getTotalLength()); + var p1_inv = lg.node().getPointAtLength(4); + var p2_inv = lg.node().getPointAtLength(0); + var markerCenter_inv = lg.node().getPointAtLength(6); + startX = p1_inv.x; + startY = p1_inv.y; + endX = p2_inv.x; + endY = p2_inv.y; + normX = endX - startX; + normY = endY - startY; + len = Math.sqrt(normX * normX + normY * normY); + normX = normX / len; + normY = normY / len; + + ahAngle = -1.0 * Math.atan2(normY, normX) * (180 / Math.PI); + ahAngle -= 90; + // console.log("INV>>\n "+link.property().inverse().labelForCurrentLanguage()+ ": "+normX+ " "+normY +" "+ahAngle); + rx = markerCenter_inv.x; + ry = markerCenter_inv.y; + if ( link.layers().length === 1 && !link.loops() ) { + // markerOffset=-1*m + ry = -1 * ry; + texString += "\\node[" + arrowType + ", rotate=" + ahAngle + "] at (" + rx + "pt, " + ry + "pt) (INV_single_marker" + i + ") {};\n "; + } else { + ry = -1 * ry; + texString += "\\node[" + arrowType + ", rotate=" + ahAngle + "] at (" + rx + "pt, " + ry + "pt) (INV_marker" + i + ") {};\n "; + } + } + + + } + + + nodeElements.each(function ( node ){ + + px = node.x; + py = -node.y; + identifier = node.labelForCurrentLanguage(); + // console.log("Writing : "+ identifier); + if ( identifier === undefined ) identifier = ""; + var qType = "owlClass"; + if ( node.type() === "owl:Thing" || node.type() === "owl:Nothing" ) + qType = "owlThing"; + + if ( node.type() === "owl:equivalentClass" ) { + qType = "owlEquivalentClass"; + } + var textColorStr = ""; + if ( node.textBlock ) { + var txtColor = node.textBlock()._textBlock().style("fill"); + if ( txtColor === "rgb(0, 0, 0)" ) { + textColorStr = ", text=black"; + } + if ( txtColor === "rgb(255, 255, 255)" ) { + textColorStr = ", text=white"; + } + + + var tspans = node.textBlock()._textBlock().node().children; + if ( tspans[0] ) { + identifier = tspans[0].innerHTML; + if ( node.individuals() && node.individuals().length === parseInt(tspans[0].innerHTML) ) { + identifier = "{\\color{gray} " + tspans[0].innerHTML + " }"; + } + for ( var t = 1; t < tspans.length; t++ ) { + if ( node.individuals() && node.individuals().length === parseInt(tspans[t].innerHTML) ) { + identifier += "\\\\ {\\color{gray} " + tspans[t].innerHTML + " }"; + } else { + identifier += "\\\\ {\\small " + tspans[t].innerHTML + " }"; + } + } + } + } + if ( node.type() === "rdfs:Literal" ) { + qType = "Literal"; + } + if ( node.type() === "rdfs:Datatype" ) { + qType = "Datatype"; + } + if ( node.attributes().indexOf("anonymous") !== -1 ) { + qType = "anonymousClass"; + } + + + if ( node.type() === "owl:unionOf" || node.type() === "owl:complementOf" || node.type() === "owl:disjointUnionOf" || node.type() === "owl:intersectionOf" ) + qType = "owlClass"; + + var bgColorStr = ""; + var widthString = ""; + + if ( node.type() === "rdfs:Literal" || node.type() === "rdfs:Datatype" ) { + var width = node.width(); + widthString = ",minimum width=" + width + "pt"; + } + else { + widthString = ",minimum size=" + 2 * node.actualRadius() + "pt"; + + } + if ( node.backgroundColor() ) { + var bgColor = node.backgroundColor(); + bgColor.toUpperCase(); + bgColor = bgColor.slice(1, bgColor.length); + texString += "\\definecolor{Node" + i + "_COLOR}{HTML}{" + bgColor + "} \n "; + bgColorStr = ", fill=Node" + i + "_COLOR "; + } + if ( node.attributes().indexOf("deprecated") > -1 ) { + texString += "\\definecolor{Node" + i + "_COLOR}{HTML}{CCCCCC} \n "; + bgColorStr = ", fill=Node" + i + "_COLOR "; + } + + var leftPos = px - 7; + var rightPos = px + 7; + var txtOffset = py + 20; + if ( node.type() !== "owl:unionOf" || node.type() !== "owl:disjointUnionOf" ) { + texString += "\\node[" + qType + " " + widthString + " " + bgColorStr + " " + textColorStr + "] at (" + px + "pt, " + py + "pt) (Node" + i + ") {" + identifier.replaceAll("_", "\\_ ") + "};\n"; + } + if ( node.type() === "owl:unionOf" ) { + // add symbol to it; + texString += "\\node[" + qType + " " + widthString + " " + bgColorStr + " " + textColorStr + "] at (" + px + "pt, " + py + "pt) (Node" + i + ") {};\n"; + texString += "\\node[unionOf , text=black] at (" + leftPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[unionOf , text=black] at (" + rightPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[unionOf ,fill=none , text=black] at (" + leftPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[text=black] at (" + px + "pt, " + py + "pt) (unionText13) {$\\mathbf{\\cup}$};\n"; + texString += "\\node[font={\\fontsize{12pt}{12}\\selectfont \\sffamily }" + textColorStr + "] at (" + px + "pt, " + txtOffset + "pt) (Node_text" + i + ") {" + identifier.replaceAll("_", "\\_ ") + "};\n"; + } + // OWL DISJOINT UNION OF + if ( node.type() === "owl:disjointUnionOf" ) { + texString += "\\node[" + qType + " " + widthString + " " + bgColorStr + " " + textColorStr + "] at (" + px + "pt, " + py + "pt) (Node" + i + ") {};\n"; + texString += "\\node[unionOf , text=black] at (" + leftPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[unionOf , text=black] at (" + rightPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[unionOf ,fill=none , text=black] at (" + leftPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[font={\\fontsize{12pt}{12}\\selectfont \\sffamily }" + textColorStr + "] at (" + px + "pt, " + py + "pt) (disjointUnoinText" + i + ") {1};\n"; + texString += "\\node[font={\\fontsize{12pt}{12}\\selectfont \\sffamily }" + textColorStr + "] at (" + px + "pt, " + txtOffset + "pt) (Node_text" + i + ") {" + identifier.replaceAll("_", "\\_ ") + "};\n"; + } + // OWL COMPLEMENT OF + if ( node.type() === "owl:complementOf" ) { + // add symbol to it; + texString += "\\node[" + qType + " " + widthString + " " + bgColorStr + " " + textColorStr + "] at (" + px + "pt, " + py + "pt) (Node" + i + ") {};\n"; + texString += "\\node[unionOf , text=black] at (" + px + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[font={\\fontsize{18pt}{18}\\selectfont \\sffamily }" + textColorStr + "] at (" + px + "pt, " + py + "pt) (unionText13) {$\\neg$};\n"; + texString += "\\node[font={\\fontsize{12pt}{12}\\selectfont \\sffamily }" + textColorStr + "] at (" + px + "pt, " + txtOffset + "pt) (Node_text" + i + ") {" + identifier.replaceAll("_", "\\_ ") + "};\n"; + } + // OWL INTERSECTION OF + if ( node.type() === "owl:intersectionOf" ) { + texString += "\\node[" + qType + " " + widthString + " " + bgColorStr + " " + textColorStr + "] at (" + px + "pt, " + py + "pt) (Node" + i + ") {};\n"; + texString += "\\node[unionOf , text=black] at (" + leftPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[unionOf , text=black] at (" + rightPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[unionOf ,fill=none , text=black] at (" + leftPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + + // add now the outer colors; + texString += "\\filldraw[even odd rule,fill=owlClassColor,line width=1pt] (" + leftPos + "pt, " + py + "pt) circle (12.5pt) (" + rightPos + "pt, " + py + "pt) circle (12.5pt);\n "; + + // add texts + texString += "\\node[font={\\fontsize{12pt}{12}\\selectfont \\sffamily }" + textColorStr + "] at (" + px + "pt, " + py + "pt) (intersectionText" + i + ") {$\\cap$};\n"; + texString += "\\node[font={\\fontsize{12pt}{12}\\selectfont \\sffamily }" + textColorStr + "] at (" + px + "pt, " + txtOffset + "pt) (Node_text" + i + ") {" + identifier.replaceAll("_", "\\_ ") + "};\n"; + + } + + + i++; + + }); + for ( i = 0; i < propElements.length; i++ ) { + var correspondingProp = propElements[i].property(); + var p_px = propElements[i].x; + var p_py = -propElements[i].y; + identifier = correspondingProp.labelForCurrentLanguage(); + if ( identifier === undefined ) identifier = ""; + var textColorStr = ""; + if ( correspondingProp.textBlock && correspondingProp.textBlock() ) { + var txtColor = correspondingProp.textBlock()._textBlock().style("fill"); + // console.log("PropertyTextColor="+txtColor); + if ( txtColor === "rgb(0, 0, 0)" ) { + textColorStr = ", text=black"; + } + if ( txtColor === "rgb(255, 255, 255)" ) { + textColorStr = ", text=white"; + } + var tspans = correspondingProp.textBlock()._textBlock().node().children; + + // identifier=node.textBlock()._textBlock().text(); + // console.log(tspans); + if ( tspans[0] ) { + identifier = tspans[0].innerHTML; + + for ( var t = 1; t < tspans.length; t++ ) { + var spanText = tspans[t].innerHTML; + if ( spanText.indexOf("(") > -1 ) { + identifier += "\\\\ {\\small " + tspans[t].innerHTML + " }"; + } + else { + identifier += "\\\\ " + tspans[t].innerHTML; + } + } + } + else { + } + } + if ( correspondingProp.type() === "setOperatorProperty" ) { + continue; // this property does not have a label + } + var qType = "owlObjectProperty"; + if ( correspondingProp.type() === "owl:DatatypeProperty" ) { + qType = "owlDatatypeProperty"; + } + if ( correspondingProp.type() === "rdfs:subClassOf" ) { + qType = "rdfsSubClassOf"; + } + if ( correspondingProp.type() === "rdf:Property" ) { + qType = "rdfProperty"; + } + + + var bgColorStr = ""; + if ( correspondingProp.backgroundColor() ) { + // console.log("Found backGround color"); + var bgColor = correspondingProp.backgroundColor(); + //console.log(bgColor); + bgColor.toUpperCase(); + bgColor = bgColor.slice(1, bgColor.length); + texString += "\\definecolor{property" + i + "_COLOR}{HTML}{" + bgColor + "} \n "; + bgColorStr = ", fill=property" + i + "_COLOR "; + } + if ( correspondingProp.attributes().indexOf("deprecated") > -1 ) { + texString += "\\definecolor{property" + i + "_COLOR}{HTML}{CCCCCC} \n "; + bgColorStr = ", fill=property" + i + "_COLOR "; + } + + var widthString = ""; + var width = correspondingProp.textWidth(); + widthString = ",minimum width=" + width + "pt"; + + + // OWL INTERSECTION OF + if ( correspondingProp.type() === "owl:disjointWith" ) { + var leftPos = p_px - 12; + var rightPos = p_px + 12; + var txtOffset = p_py - 20; + texString += "\\node[" + qType + " " + widthString + " " + bgColorStr + " " + textColorStr + "] at (" + p_px + "pt, " + p_py + "pt) (Node" + i + ") {};\n"; + texString += "\\node[disjointWith , text=black] at (" + leftPos + "pt, " + p_py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[disjointWith , text=black] at (" + rightPos + "pt, " + p_py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[font={\\fontsize{12pt}{12}\\selectfont \\sffamily }" + textColorStr + "] at (" + p_px + "pt, " + txtOffset + "pt) (Node_text" + i + ") {"; + if ( graph.options().compactNotation() === false ) { + texString += "(disjoint)"; + } + texString += "};\n"; + continue; + } + + + if ( correspondingProp.inverse() ) { + var inv_correspondingProp = correspondingProp.inverse(); + // create the rendering element for the inverse property; + var inv_identifier = inv_correspondingProp.labelForCurrentLanguage(); + if ( inv_identifier === undefined ) inv_identifier = ""; + var inv_textColorStr = ""; + //console.log(inv_correspondingProp); + //console.log(inv_correspondingProp.textBlock()); + + if ( inv_correspondingProp.textBlock && inv_correspondingProp.textBlock() ) { + + var inv_txtColor = inv_correspondingProp.textBlock()._textBlock().style("fill"); + // console.log("PropertyTextColor="+inv_txtColor); + if ( inv_txtColor === "rgb(0, 0, 0)" ) { + inv_textColorStr = ", text=black"; + } + if ( inv_txtColor === "rgb(255, 255, 255)" ) { + inv_textColorStr = ", text=white"; + } + var inv_tspans = inv_correspondingProp.textBlock()._textBlock().node().children; + + // identifier=node.textBlock()._textBlock().text(); + // console.log(inv_tspans); + if ( inv_tspans[0] ) { + inv_identifier = inv_tspans[0].innerHTML; + + for ( var inv_t = 1; inv_t < inv_tspans.length; inv_t++ ) { + var ispanText = inv_tspans[inv_t].innerHTML; + if ( ispanText.indexOf("(") > -1 ) { + inv_identifier += "\\\\ {\\small " + inv_tspans[inv_t].innerHTML + " }"; + } else { + inv_identifier += "\\\\ " + inv_tspans[inv_t].innerHTML; + } + } + } + } + var inv_qType = "owlObjectProperty"; + var inv_bgColorStr = ""; + + if ( inv_correspondingProp.backgroundColor() ) { + // console.log("Found backGround color"); + var inv_bgColor = inv_correspondingProp.backgroundColor(); + // console.log(inv_bgColor); + inv_bgColor.toUpperCase(); + inv_bgColor = inv_bgColor.slice(1, inv_bgColor.length); + texString += "\\definecolor{inv_property" + i + "_COLOR}{HTML}{" + inv_bgColor + "} \n "; + inv_bgColorStr = ", fill=inv_property" + i + "_COLOR "; + } + if ( inv_correspondingProp.attributes().indexOf("deprecated") > -1 ) { + texString += "\\definecolor{inv_property" + i + "_COLOR}{HTML}{CCCCCC} \n "; + inv_bgColorStr = ", fill=inv_property" + i + "_COLOR "; + } + + var inv_widthString = ""; + var inv_width = inv_correspondingProp.textWidth(); + + var pOY1 = p_py - 14; + var pOY2 = p_py + 14; + inv_widthString = ",minimum width=" + inv_width + "pt"; + texString += "% Createing Inverse Property \n"; + texString += "\\node[" + inv_qType + " " + inv_widthString + " " + inv_bgColorStr + " " + inv_textColorStr + "] at (" + p_px + "pt, " + pOY1 + "pt) (property" + i + ") {" + inv_identifier.replaceAll("_", "\\_ ") + "};\n"; + texString += "% " + inv_qType + " vs " + qType + "\n"; + texString += "% " + inv_widthString + " vs " + widthString + "\n"; + texString += "% " + inv_bgColorStr + " vs " + bgColorStr + "\n"; + texString += "% " + inv_textColorStr + " vs " + textColorStr + "\n"; + + texString += "\\node[" + qType + " " + widthString + " " + bgColorStr + " " + textColorStr + "] at (" + p_px + "pt, " + pOY2 + "pt) (property" + i + ") {" + identifier.replaceAll("_", "\\_ ") + "};\n"; + + } else { + texString += "\\node[" + qType + " " + widthString + " " + bgColorStr + " " + textColorStr + "] at (" + p_px + "pt, " + p_py + "pt) (property" + i + ") {" + identifier.replaceAll("_", "\\_ ") + "};\n"; + } + } + + texString += "\\end{tikzpicture}\n}\n \\end{center}\n"; + + // console.log("Tex Output\n"+ texString); + var dataURI = "data:text/json;charset=utf-8," + encodeURIComponent(texString); + exportTexButton.attr("href", dataURI) + .attr("download", exportFilename + ".tex"); + + + } + + function calculateRadian( angle ){ + angle = angle % 360; + if ( angle < 0 ) { + angle = angle + 360; + } + return (Math.PI * angle) / 180; + } + + function calculateAngle( radian ){ + return radian * (180 / Math.PI); + } + + return exportMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 324: +/***/ (function(module, exports) { + + /** + * Contains the logic for the export button. + * @returns {{}} + */ + module.exports = function ( graph ){ + var exportTTLModule = {}; + var resultingTTLContent = ""; + var currentNodes; + var currentProperties; + var currentAxioms; + var Map_ID2Node = {}; + var Map_ID2Prop = {}; + var prefixModule = webvowl.util.prefixTools(graph); + + exportTTLModule.requestExport = function (){ + prefixModule.updatePrefixModel(); + resultingTTLContent = ""; + currentNodes = graph.getClassDataForTtlExport(); + var i; + for ( i = 0; i < currentNodes.length; i++ ) { + Map_ID2Node[currentNodes[i].id()] = currentNodes[i]; + } + currentProperties = graph.getPropertyDataForTtlExport(); + + for ( i = 0; i < currentProperties.length; i++ ) { + Map_ID2Prop[currentProperties[i].id()] = currentProperties[i]; + } + + + prepareHeader(); + preparePrefixList(); + prepareOntologyDef(); + resultingTTLContent += "#################################################################\r\n\r\n"; + preparePrefixRepresentation(); + var property_success = exportProperties(); + var class_success = exportClasses(); + currentNodes = null; + currentProperties = null; + Map_ID2Node = {}; + Map_ID2Prop = {}; + if ( property_success === false || class_success === false ) + return false; + return true; + + }; + + function preparePrefixRepresentation(){ + var i; + var allNodes = graph.getUnfilteredData().nodes; + var allProps = graph.getUnfilteredData().properties; + for ( i = 0; i < allNodes.length; i++ ) { + var nodeIRI = prefixModule.getPrefixRepresentationForFullURI(allNodes[i].iri()); + if ( prefixModule.validURL(nodeIRI) === true ) + allNodes[i].prefixRepresentation = "<" + nodeIRI + ">"; + else + allNodes[i].prefixRepresentation = nodeIRI; + } + for ( i = 0; i < allProps.length; i++ ) { + var propIRI = prefixModule.getPrefixRepresentationForFullURI(allProps[i].iri()); + if ( prefixModule.validURL(propIRI) === true ) + allProps[i].prefixRepresentation = "<" + propIRI + ">"; + else + allProps[i].prefixRepresentation = propIRI; + } + } + + function exportProperties(){ + if ( currentProperties.length === 0 ) return; // we dont need to write that + resultingTTLContent += "### Property Definitions (Number of Property) " + currentProperties.length + " ###\r\n"; + for ( var i = 0; i < currentProperties.length; i++ ) { + + resultingTTLContent += "# --------------------------- Property " + i + "------------------------- \r\n"; + var addedElement = extractPropertyDescription(currentProperties[i]); + resultingTTLContent += addedElement; + //@ workaround for not supported elements + if ( addedElement.indexOf("WHYEMPTYNAME") !== -1 ) { + return false; + } + } + return true; + } + + + function exportClasses(){ + if ( currentNodes.length === 0 ) return; // we dont need to write that + resultingTTLContent += "### Class Definitions (Number of Classes) " + currentNodes.length + " ###\r\n"; + for ( var i = 0; i < currentNodes.length; i++ ) { + // check for node type here and return false + resultingTTLContent += "# --------------------------- Class " + i + "------------------------- \r\n"; + var addedElement = extractClassDescription(currentNodes[i]); + resultingTTLContent += addedElement; + + if ( addedElement.indexOf("WHYEMPTYNAME") !== -1 ) { + return false; + } + } + return true; + } + + function getPresentAttribute( selectedElement, element ){ + var attr = selectedElement.attributes(); + return (attr.indexOf(element) >= 0); + } + + function extractClassDescription( node ){ + var subject = node.prefixRepresentation; + var predicate = "rdf:type"; + var object = node.type(); + if ( node.type() === "owl:equivalentClass" ) + object = "owl:Class"; + if ( node.type() === "owl:disjointUnionOf" ) + object = "owl:Class"; + if ( node.type() === "owl:unionOf" ) + object = "owl:Class"; + var arrayOfNodes = []; + var arrayOfUnionNodes = []; + + if ( node.union() ) { + var union = node.union(); + for ( var u = 0; u < union.length; u++ ) { + var u_node = Map_ID2Node[union[u]]; + arrayOfUnionNodes.push(u_node); + } + } + + if ( node.disjointUnion() ) { + var distUnion = node.disjointUnion(); + for ( var du = 0; du < distUnion.length; du++ ) { + var du_node = Map_ID2Node[distUnion[du]]; + arrayOfNodes.push(du_node); + } + } + + var objectDef = subject + " " + predicate + " " + object; + if ( getPresentAttribute(node, "deprecated") === true ) { + objectDef += ", owl:DeprecatedProperty"; + } + // equivalent class handeled using type itself! + + // check for equivalent classes; + var indent = getIndent(subject); + objectDef += "; \r\n"; + for ( var e = 0; e < node.equivalents().length; e++ ) { + var eqIRI = prefixModule.getPrefixRepresentationForFullURI(node.equivalents()[e].iri()); + var eqNode_prefRepresentation = ""; + if ( prefixModule.validURL(eqIRI) === true ) + eqNode_prefRepresentation = "<" + eqIRI + ">"; + else + eqNode_prefRepresentation = eqIRI; + objectDef += indent + " owl:equivalentClass " + eqNode_prefRepresentation + " ;\r\n"; + } + + // if (getPresentAttribute(node,"equivalent")===true){ + // objectDef+=", owl:EquivalentClass"; + // } + + // add Comments + + if ( node.commentForCurrentLanguage() ) { + + objectDef += indent + " rdfs:comment \"" + node.commentForCurrentLanguage() + "\" ;\r\n"; + } + + if ( node.annotations() ) { + var annotations = node.annotations(); + for ( var an in annotations ) { + if ( annotations.hasOwnProperty(an) ) { + var anArrayObj = annotations[an]; + var anObj = anArrayObj[0]; + var an_ident = anObj.identifier; + var an_val = anObj.value; + + if ( an_ident === "isDefinedBy" ) { + objectDef += indent + " rdfs:isDefinedBy <" + an_val + "> ;\r\n"; + } + if ( an_ident === "term_status" ) { + objectDef += indent + " vs:term_status \"" + an_val + "\" ;\r\n"; + } + } + } + } + + + if ( arrayOfNodes.length > 0 ) { + // add disjoint unionOf + objectDef += indent + " owl:disjointUnionOf ("; + for ( var duE = 0; duE < arrayOfNodes.length; duE++ ) { + var duIri = prefixModule.getPrefixRepresentationForFullURI(arrayOfNodes[duE].iri()); + var duNode_prefRepresentation = ""; + if ( prefixModule.validURL(duIri) === true ) + duNode_prefRepresentation = "<" + duIri + ">"; + else + duNode_prefRepresentation = duIri; + objectDef += indent + indent + duNode_prefRepresentation + " \n"; + } + objectDef += ") ;\r\n"; + } + + if ( arrayOfUnionNodes.length > 0 ) { + // add disjoint unionOf + objectDef += indent + " rdfs:subClassOf [ rdf:type owl:Class ; \r\n"; + objectDef += indent + indent + " owl:unionOf ( "; + + for ( var uE = 0; uE < arrayOfUnionNodes.length; uE++ ) { + + if ( arrayOfUnionNodes[uE] && arrayOfUnionNodes[uE].iri() ) { + var uIri = prefixModule.getPrefixRepresentationForFullURI(arrayOfUnionNodes[uE].iri()); + var uNode_prefRepresentation = ""; + if ( prefixModule.validURL(uIri) === true ) + uNode_prefRepresentation = "<" + uIri + ">"; + else + uNode_prefRepresentation = uIri; + objectDef += indent + indent + indent + uNode_prefRepresentation + " \n"; + } + } + objectDef += ") ;\r\n"; + + + } + + + var allProps = graph.getUnfilteredData().properties; + var myProperties = []; + var i; + for ( i = 0; i < allProps.length; i++ ) { + if ( allProps[i].domain() === node && + ( allProps[i].type() === "rdfs:subClassOf" || + allProps[i].type() === "owl:allValuesFrom" || + allProps[i].type() === "owl:someValuesFrom") + ) { + myProperties.push(allProps[i]); + } + // special case disjoint with>> both domain and range get that property + if ( (allProps[i].domain() === node) && + allProps[i].type() === "owl:disjointWith" ) { + myProperties.push(allProps[i]); + } + + } + for ( i = 0; i < myProperties.length; i++ ) { + // depending on the property we have to do some things; + + // special case + if ( myProperties[i].type() === "owl:someValuesFrom" ) { + objectDef += indent + " rdfs:subClassOf [ rdf:type owl:Restriction ; \r\n"; + objectDef += indent + " owl:onProperty " + myProperties[i].prefixRepresentation + ";\r\n"; + if ( myProperties[i].range().type() !== "owl:Thing" ) { + objectDef += indent + " owl:someValuesFrom " + myProperties[i].range().prefixRepresentation + "\r\n"; + } + objectDef += indent + " ];\r\n"; + continue; + } + + if ( myProperties[i].type() === "owl:allValuesFrom" ) { + objectDef += indent + " rdfs:subClassOf [ rdf:type owl:Restriction ; \r\n"; + objectDef += indent + " owl:onProperty " + myProperties[i].prefixRepresentation + ";\r\n"; + if ( myProperties[i].range().type() !== "owl:Thing" ) { + objectDef += indent + " owl:allValuesFrom " + myProperties[i].range().prefixRepresentation + "\r\n"; + } + objectDef += indent + " ];\r\n"; + continue; + } + + if ( myProperties[i].range().type() !== "owl:Thing" ) { + objectDef += indent + " " + myProperties[i].prefixRepresentation + + " " + myProperties[i].range().prefixRepresentation + " ;\r\n"; + + + } + } + + + objectDef += general_Label_languageExtractor(indent, node.label(), "rdfs:label", true); + return objectDef; + + } + + function extractPropertyDescription( property ){ + var subject = property.prefixRepresentation; + if ( subject.length === 0 ) { + console.log("THIS SHOULD NOT HAPPEN"); + var propIRI = prefixModule.getPrefixRepresentationForFullURI(property.iri()); + console.log("FOUND " + propIRI); + + + } + var predicate = "rdf:type"; + var object = property.type(); + + var objectDef = subject + " " + predicate + " " + object; + if ( getPresentAttribute(property, "deprecated") === true ) { + objectDef += ", owl:DeprecatedProperty"; + } + if ( getPresentAttribute(property, "functional") === true ) { + objectDef += ", owl:FunctionalProperty"; + } + if ( getPresentAttribute(property, "inverse functional") === true ) { + objectDef += ", owl:InverseFunctionalProperty"; + } + if ( getPresentAttribute(property, "symmetric") === true ) { + objectDef += ", owl:SymmetricProperty"; + } + if ( getPresentAttribute(property, "transitive") === true ) { + objectDef += ", owl:TransitiveProperty"; + } + var indent = getIndent(subject); + + if ( property.inverse() ) { + objectDef += "; \r\n"; + objectDef += indent + " owl:inverseOf " + property.inverse().prefixRepresentation; + } + + // check for domain and range; + + + var closeStatement = false; + var domain = property.domain(); + var range = property.range(); + + + objectDef += " ;\r\n"; + + + if ( property.commentForCurrentLanguage() ) { + + objectDef += indent + " rdfs:comment \"" + property.commentForCurrentLanguage() + "\" ;\r\n"; + } + + if ( property.superproperties() ) { + var superProps = property.superproperties(); + for ( var sP = 0; sP < superProps.length; sP++ ) { + var sPelement = superProps[sP]; + objectDef += indent + "rdfs:subPropertyOf " + sPelement.prefixRepresentation + ";\r\n"; + } + // for (var an in annotations){ + // if (annotations.hasOwnProperty(an)){ + // var anArrayObj=annotations[an]; + // var anObj=anArrayObj[0]; + // var an_ident=anObj.identifier; + // var an_val=anObj.value; + // console.log(an_ident + " "+ an_val); + // + // if (an_ident==="isDefinedBy"){ + // objectDef+=indent+" rdfs:isDefinedBy <"+an_val+"> ;\r\n"; + // } + // if (an_ident==="term_status"){ + // objectDef+=indent+" vs:term_status \""+an_val+"\" ;\r\n"; + // } + // } + // } + + } + + if ( property.annotations() ) { + var annotations = property.annotations(); + for ( var an in annotations ) { + if ( annotations.hasOwnProperty(an) ) { + var anArrayObj = annotations[an]; + var anObj = anArrayObj[0]; + var an_ident = anObj.identifier; + var an_val = anObj.value; + + if ( an_ident === "isDefinedBy" ) { + objectDef += indent + " rdfs:isDefinedBy <" + an_val + "> ;\r\n"; + } + if ( an_ident === "term_status" ) { + objectDef += indent + " vs:term_status \"" + an_val + "\" ;\r\n"; + } + } + } + } + + + if ( domain.type() === "owl:Thing" && range.type() === "owl:Thing" ) { + // we do not write domain and range + if ( typeof property.label() !== "object" && property.label().length === 0 ) { + closeStatement = true; + } + } + + + if ( closeStatement === true ) { + var uobjectDef = objectDef.substring(0, objectDef.length - 2); + objectDef = uobjectDef + " . \r\n"; + return objectDef; + } + // objectDef+="; \r\n"; + var labelDescription; + + + if ( domain.type() === "owl:Thing" && range.type() === "owl:Thing" ) { + labelDescription = general_Label_languageExtractor(indent, property.label(), "rdfs:label", true); + objectDef += labelDescription; + } + else { + // do not close the statement; + labelDescription = general_Label_languageExtractor(indent, property.label(), "rdfs:label"); + objectDef += labelDescription; + if ( domain.type() !== "owl:Thing" ) { + objectDef += indent + " rdfs:domain " + domain.prefixRepresentation + ";\r\n"; + } + if ( range.type() !== "owl:Thing" ) { + objectDef += indent + " rdfs:range " + range.prefixRepresentation + ";\r\n"; + } + + // close statement now; + + var s_needUpdate = objectDef; + var s_lastPtr = s_needUpdate.lastIndexOf(";"); + objectDef = s_needUpdate.substring(0, s_lastPtr) + " . \r\n"; + } + + return objectDef; + + } + + + exportTTLModule.resultingTTL_Content = function (){ + return resultingTTLContent; + }; + + function getIndent( name ){ + if ( name === undefined ) { + return "WHYEMPTYNAME?"; + } + return new Array(name.length + 1).join(" "); + } + + function prepareHeader(){ + resultingTTLContent += "#################################################################\r\n"; + resultingTTLContent += "### Generated with the experimental alpha version of the TTL exporter of WebVOWL (version 1.1.7) " + + " http://visualdataweb.de/webvowl/ ###\r\n"; + resultingTTLContent += "#################################################################\r\n\r\n"; + + } + + function preparePrefixList(){ + var ontoIri = graph.options().getGeneralMetaObjectProperty('iri'); + var prefixList = graph.options().prefixList(); + var prefixDef = []; + prefixDef.push('@prefix : \t\t<' + ontoIri + '> .'); + for ( var name in prefixList ) { + if ( prefixList.hasOwnProperty(name) ) { + prefixDef.push('@prefix ' + name + ': \t\t<' + prefixList[name] + '> .'); + } + } + prefixDef.push('@base \t\t\t<' + ontoIri + '> .\r\n'); + + for ( var i = 0; i < prefixDef.length; i++ ) { + resultingTTLContent += prefixDef[i] + '\r\n'; + } + } + + function prepareOntologyDef(){ + var ontoIri = graph.options().getGeneralMetaObjectProperty('iri'); + var indent = getIndent('<' + ontoIri + '>'); + resultingTTLContent += '<' + ontoIri + '> rdf:type owl:Ontology ;\r\n' + + getOntologyTitle(indent) + + getOntologyDescription(indent) + + getOntologyVersion(indent) + + getOntologyAuthor(indent); + + // close the statement; + var s_needUpdate = resultingTTLContent; + var s_lastPtr = s_needUpdate.lastIndexOf(";"); + resultingTTLContent = s_needUpdate.substring(0, s_lastPtr) + " . \r\n"; + } + + function getOntologyTitle( indent ){ + return general_languageExtractor(indent, "title", "dc:title"); + } + + function getOntologyDescription( indent ){ + return general_languageExtractor(indent, "description", "dc:description"); + } + + function getOntologyAuthor( indent ){ + var languageElement = graph.options().getGeneralMetaObjectProperty('author'); + if ( languageElement ) { + if ( typeof languageElement !== "object" ) { + if ( languageElement.length === 0 ) + return ""; // an empty string + var aString = indent + " dc:creator " + '"' + languageElement + '";\r\n'; + return aString; + } + // we assume this thing is an array; + var authorString = indent + " dc:creator " + '"'; + for ( var i = 0; i < languageElement.length - 1; i++ ) { + authorString += languageElement[i] + ", "; + } + authorString += languageElement[languageElement.length - 1] + '";\r\n'; + return authorString; + } else { + return ""; // an empty string + } + } + + function getOntologyVersion( indent ){ + var languageElement = graph.options().getGeneralMetaObjectProperty('version'); + if ( languageElement ) { + if ( typeof languageElement !== "object" ) { + if ( languageElement.length === 0 ) + return ""; // an empty string + } + return general_languageExtractor(indent, "version", "owl:versionInfo"); + } else return ""; // an empty string + } + + function general_languageExtractor( indent, metaObjectDescription, annotationDescription, endStatement ){ + var languageElement = graph.options().getGeneralMetaObjectProperty(metaObjectDescription); + + if ( typeof languageElement === 'object' ) { + + var resultingLanguages = []; + for ( var name in languageElement ) { + if ( languageElement.hasOwnProperty(name) ) { + var content = languageElement[name]; + if ( name === "undefined" ) { + resultingLanguages.push(indent + " " + annotationDescription + ' "' + content + '"@en; \r\n'); + } + else { + resultingLanguages.push(indent + " " + annotationDescription + ' "' + content + '"@' + name + '; \r\n'); + } + } + } + // create resulting titles; + + var resultingString = ""; + for ( var i = 0; i < resultingLanguages.length; i++ ) { + resultingString += resultingLanguages[i]; + } + if ( endStatement && endStatement === true ) { + var needUpdate = resultingString; + var lastPtr = needUpdate.lastIndexOf(";"); + return needUpdate.substring(0, lastPtr) + ". \r\n"; + } else { + return resultingString; + } + + } else { + if ( endStatement && endStatement === true ) { + var s_needUpdate = indent + " " + annotationDescription + ' "' + languageElement + '"@en; \r\n'; + var s_lastPtr = s_needUpdate.lastIndexOf(";"); + return s_needUpdate.substring(0, s_lastPtr) + " . \r\n"; + } + return indent + " " + annotationDescription + ' "' + languageElement + '"@en;\r\n'; + } + } + + function general_Label_languageExtractor( indent, label, annotationDescription, endStatement ){ + var languageElement = label; + + if ( typeof languageElement === 'object' ) { + var resultingLanguages = []; + for ( var name in languageElement ) { + if ( languageElement.hasOwnProperty(name) ) { + var content = languageElement[name]; + if ( name === "undefined" ) { + resultingLanguages.push(indent + " " + annotationDescription + ' "' + content + '"@en; \r\n'); + } + else { + resultingLanguages.push(indent + " " + annotationDescription + ' "' + content + '"@' + name + '; \r\n'); + } + } + } + // create resulting titles; + var resultingString = ""; + for ( var i = 0; i < resultingLanguages.length; i++ ) { + resultingString += resultingLanguages[i]; + } + if ( endStatement && endStatement === true ) { + var needUpdate = resultingString; + var lastPtr = needUpdate.lastIndexOf(";"); + return needUpdate.substring(0, lastPtr) + " . \r\n"; + } else { + return resultingString; + } + + } else { + if ( endStatement && endStatement === true ) { + var s_needUpdate = indent + " " + annotationDescription + ' "' + languageElement + '"@en; \r\n'; + var s_lastPtr = s_needUpdate.lastIndexOf(";"); + return s_needUpdate.substring(0, s_lastPtr) + " . \r\n"; + } + return indent + " " + annotationDescription + ' "' + languageElement + '"@en; \r\n'; + } + } + + return exportTTLModule; + }; + + +/***/ }), + +/***/ 325: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for connecting the filters with the website. + * + * @param graph required for calling a refresh after a filter change + * @returns {{}} + */ + module.exports = function ( graph ){ + + var filterMenu = {}, + checkboxData = [], + menuElement = d3.select("#m_filter"), + menuControl = d3.select("#c_filter a"), + nodeDegreeContainer = d3.select("#nodeDegreeFilteringOption"), + graphDegreeLevel, + defaultDegreeValue = 0, + degreeSlider; + + filterMenu.setDefaultDegreeValue = function ( val ){ + defaultDegreeValue = val; + }; + filterMenu.getDefaultDegreeValue = function (){ + return defaultDegreeValue; + }; + + filterMenu.getGraphObject = function (){ + return graph; + }; + /** some getter function **/ + filterMenu.getCheckBoxContainer = function (){ + return checkboxData; + }; + + filterMenu.getDegreeSliderValue = function (){ + return degreeSlider.property("value"); + }; + /** + * Connects the website with graph filters. + * @param datatypeFilter filter for all datatypes + * @param objectPropertyFilter filter for all object properties + * @param subclassFilter filter for all subclasses + * @param disjointFilter filter for all disjoint with properties + * @param setOperatorFilter filter for all set operators with properties + * @param nodeDegreeFilter filters nodes by their degree + */ + filterMenu.setup = function ( datatypeFilter, objectPropertyFilter, subclassFilter, disjointFilter, setOperatorFilter, nodeDegreeFilter ){ + // TODO: is this here really necessarry? << new menu visualization style? + menuControl.on("mouseover", function (){ + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + }); + menuControl.on("mouseleave", function (){ + filterMenu.highlightForDegreeSlider(false); + }); + + addFilterItem(datatypeFilter, "datatype", "Datatype properties", "#datatypeFilteringOption"); + addFilterItem(objectPropertyFilter, "objectProperty", "Object properties", "#objectPropertyFilteringOption"); + addFilterItem(subclassFilter, "subclass", "Solitary subclasses", "#subclassFilteringOption"); + addFilterItem(disjointFilter, "disjoint", "Class disjointness", "#disjointFilteringOption"); + addFilterItem(setOperatorFilter, "setoperator", "Set operators", "#setOperatorFilteringOption"); + + addNodeDegreeFilter(nodeDegreeFilter, nodeDegreeContainer); + addAnimationFinishedListener(); + }; + + + function addFilterItem( filter, identifier, pluralNameOfFilteredItems, selector ){ + var filterContainer, + filterCheckbox; + + filterContainer = d3.select(selector) + .append("div") + .classed("checkboxContainer", true); + + filterCheckbox = filterContainer.append("input") + .classed("filterCheckbox", true) + .attr("id", identifier + "FilterCheckbox") + .attr("type", "checkbox") + .property("checked", filter.enabled()); + + // Store for easier resetting + checkboxData.push({ checkbox: filterCheckbox, defaultState: filter.enabled() }); + + filterCheckbox.on("click", function ( silent ){ + // There might be no parameters passed because of a manual + // invocation when resetting the filters + var isEnabled = filterCheckbox.property("checked"); + filter.enabled(isEnabled); + if ( silent !== true ) { + // updating graph when silent is false or the parameter is not given. + graph.update(); + } + }); + + filterContainer.append("label") + .attr("for", identifier + "FilterCheckbox") + .text(pluralNameOfFilteredItems); + } + + function addNodeDegreeFilter( nodeDegreeFilter, container ){ + nodeDegreeFilter.setMaxDegreeSetter(function ( maxDegree ){ + degreeSlider.attr("max", maxDegree); + setSliderValue(degreeSlider, Math.min(maxDegree, degreeSlider.property("value"))); + }); + + nodeDegreeFilter.setDegreeGetter(function (){ + return degreeSlider.property("value"); + }); + + nodeDegreeFilter.setDegreeSetter(function ( value ){ + setSliderValue(degreeSlider, value); + }); + + var sliderContainer, + sliderValueLabel; + + sliderContainer = container.append("div") + .classed("distanceSliderContainer", true); + + degreeSlider = sliderContainer.append("input") + .attr("id", "nodeDegreeDistanceSlider") + .attr("type", "range") + .attr("min", 0) + .attr("step", 1); + + sliderContainer.append("label") + .classed("description", true) + .attr("for", "nodeDegreeDistanceSlider") + .text("Degree of collapsing"); + + sliderValueLabel = sliderContainer.append("label") + .classed("value", true) + .attr("for", "nodeDegreeDistanceSlider") + .text(0); + + + degreeSlider.on("change", function ( silent ){ + if ( silent !== true ) { + graph.update(); + graphDegreeLevel = degreeSlider.property("value"); + } + }); + + + degreeSlider.on("input", function (){ + var degree = degreeSlider.property("value"); + sliderValueLabel.text(degree); + }); + + + // adding wheel events + degreeSlider.on("wheel", handleWheelEvent); + degreeSlider.on("focusout", function (){ + if ( degreeSlider.property("value") !== graphDegreeLevel ) { + graph.update(); + } + }); + } + + function handleWheelEvent(){ + var wheelEvent = d3.event; + + var offset; + if ( wheelEvent.deltaY < 0 ) offset = 1; + if ( wheelEvent.deltaY > 0 ) offset = -1; + var maxDeg = parseInt(degreeSlider.attr("max")); + var oldVal = parseInt(degreeSlider.property("value")); + var newSliderValue = oldVal + offset; + if ( oldVal !== newSliderValue && (newSliderValue >= 0 && newSliderValue <= maxDeg) ) { + // only update when they are different [reducing redundant updates] + // set the new value and emit an update signal + degreeSlider.property("value", newSliderValue); + degreeSlider.on("input")();// <<-- sets the text value + graph.update(); + } + d3.event.preventDefault(); + } + + function setSliderValue( slider, value ){ + slider.property("value", value).on("input")(); + } + + /** + * Resets the filters (and also filtered elements) to their default. + */ + filterMenu.reset = function (){ + checkboxData.forEach(function ( checkboxData ){ + var checkbox = checkboxData.checkbox, + enabledByDefault = checkboxData.defaultState, + isChecked = checkbox.property("checked"); + + if ( isChecked !== enabledByDefault ) { + checkbox.property("checked", enabledByDefault); + // Call onclick event handlers programmatically + checkbox.on("click")(); + } + }); + + setSliderValue(degreeSlider, 0); + degreeSlider.on("change")(); + }; + + function addAnimationFinishedListener(){ + menuControl.node().addEventListener("animationend", function (){ + menuControl.classed("buttonPulse", false); + menuControl.classed("filterMenuButtonHighlight", true); + + }); + } + + filterMenu.killButtonAnimation = function (){ + menuControl.classed("buttonPulse", false); + menuControl.classed("filterMenuButtonHighlight", false); + }; + + + filterMenu.highlightForDegreeSlider = function ( enable ){ + if ( !arguments.length ) { + enable = true; + } + menuControl.classed("highlighted", enable); + nodeDegreeContainer.classed("highlighted", enable); + // pulse button handling + if ( menuControl.classed("buttonPulse") === true && enable === true ) { + menuControl.classed("buttonPulse", false); + var timer = setTimeout(function (){ + menuControl.classed("buttonPulse", enable); + clearTimeout(timer); + // after the time is done, remove the pulse but stay highlighted + }, 100); + } else { + menuControl.classed("buttonPulse", enable); + menuControl.classed("filterMenuButtonHighlight", enable); + } + }; + + + /** importer functions **/ + // setting manually the values of the filter + // no update of the gui settings, these are updated in updateSettings + filterMenu.setCheckBoxValue = function ( id, checked ){ + for ( var i = 0; i < checkboxData.length; i++ ) { + var cbdId = checkboxData[i].checkbox.attr("id"); + if ( cbdId === id ) { + checkboxData[i].checkbox.property("checked", checked); + break; + } + } + }; + + filterMenu.getCheckBoxValue = function ( id ){ + for ( var i = 0; i < checkboxData.length; i++ ) { + var cbdId = checkboxData[i].checkbox.attr("id"); + if ( cbdId === id ) { + return checkboxData[i].checkbox.property("checked"); + + } + } + }; + // set the value of the slider + filterMenu.setDegreeSliderValue = function ( val ){ + degreeSlider.property("value", val); + }; + + filterMenu.getDegreeSliderValue = function (){ + return degreeSlider.property("value"); + }; + + // update the gui without invoking graph update (calling silent onclick function) + filterMenu.updateSettings = function (){ + var silent = true; + var sliderValue = degreeSlider.property("value"); + if ( sliderValue > 0 ) { + filterMenu.highlightForDegreeSlider(true); + } else { + filterMenu.highlightForDegreeSlider(false); + } + checkboxData.forEach(function ( checkboxData ){ + var checkbox = checkboxData.checkbox; + checkbox.on("click")(silent); + }); + + degreeSlider.on("input")(); + degreeSlider.on("change")(); + + }; + + return filterMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 326: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for setting up the gravity sliders. + * + * @param graph the associated webvowl graph + * @returns {{}} + */ + module.exports = function ( graph ){ + + var gravityMenu = {}, + sliders = [], + options = graph.graphOptions(), + defaultCharge = options.charge(); + + + /** + * Adds the gravity sliders to the website. + */ + gravityMenu.setup = function (){ + var menuEntry = d3.select("#m_gravity"); + menuEntry.on("mouseover", function (){ + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + }); + addDistanceSlider("#classSliderOption", "class", "Class distance", options.classDistance); + addDistanceSlider("#datatypeSliderOption", "datatype", "Datatype distance", options.datatypeDistance); + }; + + function addDistanceSlider( selector, identifier, label, distanceFunction ){ + var defaultLinkDistance = distanceFunction(); + + var sliderContainer, + sliderValueLabel; + + sliderContainer = d3.select(selector) + .append("div") + .datum({ distanceFunction: distanceFunction }) // connect the options-function with the slider + .classed("distanceSliderContainer", true); + + var slider = sliderContainer.append("input") + .attr("id", identifier + "DistanceSlider") + .attr("type", "range") + .attr("min", 10) + .attr("max", 600) + .attr("value", distanceFunction()) + .attr("step", 10); + + sliderContainer.append("label") + .classed("description", true) + .attr("for", identifier + "DistanceSlider") + .text(label); + + sliderValueLabel = sliderContainer.append("label") + .classed("value", true) + .attr("for", identifier + "DistanceSlider") + .text(distanceFunction()); + + // Store slider for easier resetting + sliders.push(slider); + + slider.on("focusout", function (){ + graph.updateStyle(); + }); + + slider.on("input", function (){ + var distance = slider.property("value"); + distanceFunction(distance); + adjustCharge(defaultLinkDistance); + sliderValueLabel.text(distance); + graph.updateStyle(); + }); + + // add wheel event to the slider + slider.on("wheel", function (){ + var wheelEvent = d3.event; + var offset; + if ( wheelEvent.deltaY < 0 ) offset = 10; + if ( wheelEvent.deltaY > 0 ) offset = -10; + var oldVal = parseInt(slider.property("value")); + var newSliderValue = oldVal + offset; + if ( newSliderValue !== oldVal ) { + slider.property("value", newSliderValue); + distanceFunction(newSliderValue); + slider.on("input")(); // << set text and update the graphStyles + } + d3.event.preventDefault(); + }); + } + + function adjustCharge( defaultLinkDistance ){ + var greaterDistance = Math.max(options.classDistance(), options.datatypeDistance()), + ratio = greaterDistance / defaultLinkDistance, + newCharge = defaultCharge * ratio; + + options.charge(newCharge); + } + + /** + * Resets the gravity sliders to their default. + */ + gravityMenu.reset = function (){ + sliders.forEach(function ( slider ){ + slider.property("value", function ( d ){ + // Simply reload the distance from the options + return d.distanceFunction(); + }); + slider.on("input")(); + }); + }; + + + return gravityMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 327: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for connecting the modes with the website. + * + * @param graph the graph that belongs to these controls + * @returns {{}} + */ + module.exports = function ( graph ){ + + var SAME_COLOR_MODE = { text: "Multicolor", type: "same" }; + var GRADIENT_COLOR_MODE = { text: "Multicolor", type: "gradient" }; + + var modeMenu = {}, + checkboxes = [], + colorModeSwitch; + + var dynamicLabelWidthCheckBox; + // getter and setter for the state of color modes + modeMenu.colorModeState = function ( s ){ + if ( !arguments.length ) return colorModeSwitch.datum().active; + colorModeSwitch.datum().active = s; + return modeMenu; + }; + + + modeMenu.setDynamicLabelWidth = function ( val ){ + dynamicLabelWidthCheckBox.property("checked", val); + }; + // getter for checkboxes + modeMenu.getCheckBoxContainer = function (){ + return checkboxes; + }; + // getter for the color switch [needed? ] + modeMenu.colorModeSwitch = function (){ + return colorModeSwitch; + }; + + /** + * Connects the website with the available graph modes. + */ + modeMenu.setup = function ( pickAndPin, nodeScaling, compactNotation, colorExternals ){ + var menuEntry = d3.select("#m_modes"); + menuEntry.on("mouseover", function (){ + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + }); + addCheckBoxD("labelWidth", "Dynamic label width", "#dynamicLabelWidth", graph.options().dynamicLabelWidth, 1); + addCheckBox("editorMode", "Editing ", "#editMode", graph.editorMode); + addModeItem(pickAndPin, "pickandpin", "Pick & pin", "#pickAndPinOption", false); + addModeItem(nodeScaling, "nodescaling", "Node scaling", "#nodeScalingOption", true); + addModeItem(compactNotation, "compactnotation", "Compact notation", "#compactNotationOption", true); + var container = addModeItem(colorExternals, "colorexternals", "Color externals", "#colorExternalsOption", true); + colorModeSwitch = addExternalModeSelection(container, colorExternals); + }; + function addCheckBoxD( identifier, modeName, selector, onChangeFunc, updateLvl ){ + var moduleOptionContainer = d3.select(selector) + .append("div") + .classed("checkboxContainer", true); + + var moduleCheckbox = moduleOptionContainer.append("input") + .classed("moduleCheckbox", true) + .attr("id", identifier + "ModuleCheckbox") + .attr("type", "checkbox") + .property("checked", onChangeFunc()); + + moduleCheckbox.on("click", function ( d ){ + var isEnabled = moduleCheckbox.property("checked"); + onChangeFunc(isEnabled); + d3.select("#maxLabelWidthSlider").node().disabled = !isEnabled; + d3.select("#maxLabelWidthvalueLabel").classed("disabledLabelForSlider", !isEnabled); + d3.select("#maxLabelWidthDescriptionLabel").classed("disabledLabelForSlider", !isEnabled); + + if ( updateLvl > 0 ) { + graph.animateDynamicLabelWidth(); + // graph.lazyRefresh(); + } + }); + moduleOptionContainer.append("label") + .attr("for", identifier + "ModuleCheckbox") + .text(modeName); + if ( identifier === "editorMode" ) { + moduleOptionContainer.append("label") + .attr("style", "font-size:10px;padding-top:3px") + .text("(experimental)"); + } + + dynamicLabelWidthCheckBox = moduleCheckbox; + } + + function addCheckBox( identifier, modeName, selector, onChangeFunc ){ + var moduleOptionContainer = d3.select(selector) + .append("div") + .classed("checkboxContainer", true); + + var moduleCheckbox = moduleOptionContainer.append("input") + .classed("moduleCheckbox", true) + .attr("id", identifier + "ModuleCheckbox") + .attr("type", "checkbox") + .property("checked", onChangeFunc()); + + moduleCheckbox.on("click", function ( d ){ + var isEnabled = moduleCheckbox.property("checked"); + onChangeFunc(isEnabled); + if ( isEnabled === true ) + graph.showEditorHintIfNeeded(); + }); + moduleOptionContainer.append("label") + .attr("for", identifier + "ModuleCheckbox") + .text(modeName); + if ( identifier === "editorMode" ) { + moduleOptionContainer.append("label") + .attr("style", "font-size:10px;padding-top:3px") + .text(" (experimental)"); + } + } + + function addModeItem( module, identifier, modeName, selector, updateGraphOnClick ){ + var moduleOptionContainer, + moduleCheckbox; + + moduleOptionContainer = d3.select(selector) + .append("div") + .classed("checkboxContainer", true) + .datum({ module: module, defaultState: module.enabled() }); + + moduleCheckbox = moduleOptionContainer.append("input") + .classed("moduleCheckbox", true) + .attr("id", identifier + "ModuleCheckbox") + .attr("type", "checkbox") + .property("checked", module.enabled()); + + // Store for easier resetting all modes + checkboxes.push(moduleCheckbox); + + moduleCheckbox.on("click", function ( d, silent ){ + var isEnabled = moduleCheckbox.property("checked"); + d.module.enabled(isEnabled); + if ( updateGraphOnClick && silent !== true ) { + graph.executeColorExternalsModule(); + graph.executeCompactNotationModule(); + graph.lazyRefresh(); + } + }); + + moduleOptionContainer.append("label") + .attr("for", identifier + "ModuleCheckbox") + .text(modeName); + + return moduleOptionContainer; + } + + function addExternalModeSelection( container, colorExternalsMode ){ + var button = container.append("button").datum({ active: false }).classed("color-mode-switch", true); + applyColorModeSwitchState(button, colorExternalsMode); + + button.on("click", function ( silent ){ + var data = button.datum(); + data.active = !data.active; + applyColorModeSwitchState(button, colorExternalsMode); + if ( colorExternalsMode.enabled() && silent !== true ) { + graph.executeColorExternalsModule(); + graph.lazyRefresh(); + } + }); + + return button; + } + + function applyColorModeSwitchState( element, colorExternalsMode ){ + var isActive = element.datum().active; + var activeColorMode = getColorModeByState(isActive); + + element.classed("active", isActive) + .text(activeColorMode.text); + + if ( colorExternalsMode ) { + colorExternalsMode.colorModeType(activeColorMode.type); + } + } + + function getColorModeByState( isActive ){ + return isActive ? GRADIENT_COLOR_MODE : SAME_COLOR_MODE; + } + + /** + * Resets the modes to their default. + */ + modeMenu.reset = function (){ + checkboxes.forEach(function ( checkbox ){ + var defaultState = checkbox.datum().defaultState, + isChecked = checkbox.property("checked"); + + if ( isChecked !== defaultState ) { + checkbox.property("checked", defaultState); + // Call onclick event handlers programmatically + checkbox.on("click")(checkbox.datum()); + } + + // Reset the module that is connected with the checkbox + checkbox.datum().module.reset(); + }); + + // set the switch to active and simulate disabling + colorModeSwitch.datum().active = true; + colorModeSwitch.on("click")(); + }; + + /** importer functions **/ + // setting manually the values of the filter + // no update of the gui settings, these are updated in updateSettings + modeMenu.setCheckBoxValue = function ( id, checked ){ + for ( var i = 0; i < checkboxes.length; i++ ) { + var cbdId = checkboxes[i].attr("id"); + + if ( cbdId === id ) { + checkboxes[i].property("checked", checked); + break; + } + } + }; + modeMenu.getCheckBoxValue = function ( id ){ + for ( var i = 0; i < checkboxes.length; i++ ) { + var cbdId = checkboxes[i].attr("id"); + if ( cbdId === id ) { + return checkboxes[i].property("checked"); + } + } + }; + + modeMenu.setColorSwitchState = function ( state ){ + // need the !state because we simulate later a click + modeMenu.colorModeState(!state); + }; + modeMenu.setColorSwitchStateUsingURL = function ( state ){ + // need the !state because we simulate later a click + modeMenu.colorModeState(!state); + colorModeSwitch.on("click")(true); + }; + + + modeMenu.updateSettingsUsingURL = function (){ + var silent = true; + checkboxes.forEach(function ( checkbox ){ + checkbox.on("click")(checkbox.datum(), silent); + }); + }; + + modeMenu.updateSettings = function (){ + var silent = true; + checkboxes.forEach(function ( checkbox ){ + checkbox.on("click")(checkbox.datum(), silent); + }); + // this simulates onclick and inverts its state + colorModeSwitch.on("click")(silent); + }; + return modeMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 328: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( graph ){ + var debugMenu = {}, + checkboxes = []; + + + var hoverFlag = false; + var specialCbx; + debugMenu.setup = function (){ + var menuEntry = d3.select("#debugMenuHref"); + + menuEntry.on("mouseover", function (){ + if ( hoverFlag === false ) { + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + specialCbx.on("click")(true); + if ( graph.editorMode() === false ) { + d3.select("#useAccuracyHelper").style("color", "#979797"); + d3.select("#useAccuracyHelper").style("pointer-events", "none"); + + // regardless the state on which useAccuracyHelper is , we are not in editing mode -> disable it + d3.select("#showDraggerObject").style("color", "#979797"); + d3.select("#showDraggerObject").style("pointer-events", "none"); + } else { + d3.select("#useAccuracyHelper").style("color", "#2980b9"); + d3.select("#useAccuracyHelper").style("pointer-events", "auto"); + } + hoverFlag = true; + } + }); + menuEntry.on("mouseout", function (){ + hoverFlag = false; + }); + + + specialCbx = addCheckBox("useAccuracyHelper", "Use accuracy helper", "#useAccuracyHelper", graph.options().useAccuracyHelper, + function ( enabled, silent ){ + if ( !enabled ) { + d3.select("#showDraggerObject").style("color", "#979797"); + d3.select("#showDraggerObject").style("pointer-events", "none"); + d3.select("#showDraggerObjectConfigCheckbox").node().checked = false; + } else { + d3.select("#showDraggerObject").style("color", "#2980b9"); + d3.select("#showDraggerObject").style("pointer-events", "auto"); + } + + if ( silent === true ) return; + graph.lazyRefresh(); + graph.updateDraggerElements(); + } + ); + addCheckBox("showDraggerObject", "Show accuracy helper", "#showDraggerObject", graph.options().showDraggerObject, + function ( enabled, silent ){ + if ( silent === true ) return; + graph.lazyRefresh(); + graph.updateDraggerElements(); + }); + addCheckBox("showFPS_Statistics", "Show rendering statistics", "#showFPS_Statistics", graph.options().showRenderingStatistic, + function ( enabled, silent ){ + + if ( graph.options().getHideDebugFeatures() === false ) { + d3.select("#FPS_Statistics").classed("hidden", !enabled); + } else { + d3.select("#FPS_Statistics").classed("hidden", true); + } + + + }); + addCheckBox("showModeOfOperation", "Show input modality", "#showModeOfOperation", graph.options().showInputModality, + function ( enabled ){ + if ( graph.options().getHideDebugFeatures() === false ) { + d3.select("#modeOfOperationString").classed("hidden", !enabled); + } else { + d3.select("#modeOfOperationString").classed("hidden", true); + } + }); + + + }; + + + function addCheckBox( identifier, modeName, selector, onChangeFunc, _callbackFunction ){ + var configOptionContainer = d3.select(selector) + .append("div") + .classed("checkboxContainer", true); + var configCheckbox = configOptionContainer.append("input") + .classed("moduleCheckbox", true) + .attr("id", identifier + "ConfigCheckbox") + .attr("type", "checkbox") + .property("checked", onChangeFunc()); + + + configCheckbox.on("click", function ( silent ){ + var isEnabled = configCheckbox.property("checked"); + onChangeFunc(isEnabled); + _callbackFunction(isEnabled, silent); + + }); + checkboxes.push(configCheckbox); + configOptionContainer.append("label") + .attr("for", identifier + "ConfigCheckbox") + .text(modeName); + + return configCheckbox; + } + + debugMenu.setCheckBoxValue = function ( identifier, value ){ + for ( var i = 0; i < checkboxes.length; i++ ) { + var cbdId = checkboxes[i].attr("id"); + if ( cbdId === identifier ) { + checkboxes[i].property("checked", value); + break; + } + } + }; + + debugMenu.getCheckBoxValue = function ( id ){ + for ( var i = 0; i < checkboxes.length; i++ ) { + var cbdId = checkboxes[i].attr("id"); + if ( cbdId === id ) { + return checkboxes[i].property("checked"); + } + } + }; + + debugMenu.updateSettings = function (){ + d3.selectAll(".debugOption").classed("hidden", graph.options().getHideDebugFeatures()); + + var silent = true; + checkboxes.forEach(function ( checkbox ){ + checkbox.on("click")(silent); + }); + if ( graph.editorMode() === false ) { + + d3.select("#useAccuracyHelper").style("color", "#979797"); + d3.select("#useAccuracyHelper").style("pointer-events", "none"); + + // regardless the state on which useAccuracyHelper is , we are not in editing mode -> disable it + d3.select("#showDraggerObject").style("color", "#979797"); + d3.select("#showDraggerObject").style("pointer-events", "none"); + } else { + + d3.select("#useAccuracyHelper").style("color", "#2980b9"); + d3.select("#useAccuracyHelper").style("pointer-events", "auto"); + } + + }; + + return debugMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 329: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var unescape = __webpack_require__(330); + + module.exports = function ( graph ){ + + var ontologyMenu = {}, + loadingInfo = d3.select("#loading-info"), + loadingProgress = d3.select("#loading-progress"), + + ontologyMenuTimeout, + fileToLoad, + stopTimer = false, + loadingError = false, + loadingStatusTimer, + conversion_sessionId, + cachedConversions = {}, + loadingModule, + loadOntologyFromText; + var currentLoadedOntologyName = ""; + + String.prototype.beginsWith = function ( string ){ + return (this.indexOf(string) === 0); + }; + + ontologyMenu.getLoadingFunction = function (){ + return loadOntologyFromText; + }; + + ontologyMenu.clearCachedVersion = function (){ + if ( cachedConversions[currentLoadedOntologyName] ) { + cachedConversions[currentLoadedOntologyName] = undefined; + } + }; + + + ontologyMenu.reloadCachedOntology = function (){ + ontologyMenu.clearCachedVersion(); + graph.clearGraphData(); + loadingModule.parseUrlAndLoadOntology(false); + }; + + ontologyMenu.cachedOntology = function ( ontoName ){ + currentLoadedOntologyName = ontoName; + if ( cachedConversions[ontoName] ) { + var locStr = String(location.hash); + d3.select("#reloadSvgIcon").node().disabled = false; + graph.showReloadButtonAfterLayoutOptimization(true); + if ( locStr.indexOf("#file") > -1 ) { + d3.select("#reloadSvgIcon").node().disabled = true; + d3.select("#reloadCachedOntology").node().title = "reloading original version not possible, please reload the file"; + d3.select("#reloadSvgIcon").classed("disabledReloadElement", true); + d3.select("#svgStringText").style("fill", "gray"); + d3.select("#svgStringText").classed("noselect", true); + } + else { + d3.select("#reloadCachedOntology").node().title = "generate new visualization and overwrite cached ontology"; + d3.select("#reloadSvgIcon").classed("disabledReloadElement", false); + d3.select("#svgStringText").style("fill", "black"); + d3.select("#svgStringText").classed("noselect", true); + } + } else { + graph.showReloadButtonAfterLayoutOptimization(false); + + } + return cachedConversions[ontoName]; + }; + ontologyMenu.setCachedOntology = function ( ontoName, ontoContent ){ + cachedConversions[ontoName] = ontoContent; + currentLoadedOntologyName = ontoName; + }; + + ontologyMenu.getErrorStatus = function (){ + return loadingError; + }; + + ontologyMenu.setup = function ( _loadOntologyFromText ){ + loadOntologyFromText = _loadOntologyFromText; + loadingModule = graph.options().loadingModule(); + var menuEntry = d3.select("#m_select"); + menuEntry.on("mouseover", function (){ + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + }); + + setupConverterButtons(); + setupUploadButton(); + + var descriptionButton = d3.select("#error-description-button").datum({ open: false }); + descriptionButton.on("click", function ( data ){ + var errorContainer = d3.select("#error-description-container"); + var errorDetailsButton = d3.select(this); + + // toggle the state + data.open = !data.open; + var descriptionVisible = data.open; + if ( descriptionVisible ) { + errorDetailsButton.text("Hide error details"); + } else { + errorDetailsButton.text("Show error details"); + } + errorContainer.classed("hidden", !descriptionVisible); + }); + + setupUriListener(); + loadingModule.setOntologyMenu(ontologyMenu); + }; + + + function setupUriListener(){ + // reload ontology when hash parameter gets changed manually + d3.select(window).on("hashchange", function (){ + var oldURL = d3.event.oldURL, newURL = d3.event.newURL; + if ( oldURL !== newURL ) { + // don't reload when just the hash parameter gets appended + if ( newURL === oldURL + "#" ) { + return; + } + updateNavigationHrefs(); + loadingModule.parseUrlAndLoadOntology(); + } + }); + updateNavigationHrefs(); + } + + ontologyMenu.stopLoadingTimer = function (){ + stopTimer = true; + clearTimeout(loadingStatusTimer); + }; + + /** + * Quick fix: update all anchor tags that are used as buttons because a click on them + * changes the url and this will load an other ontology. + */ + function updateNavigationHrefs(){ + d3.selectAll("#menuElementContainer > li > a").attr("href", location.hash || "#"); + } + + ontologyMenu.setIriText = function ( text ){ + d3.select("#iri-converter-input").node().value = text; + d3.select("#iri-converter-button").attr("disabled", false); + d3.select("#iri-converter-form").on("submit")(); + }; + + ontologyMenu.clearDetailInformation = function (){ + var bpContainer = d3.select("#bulletPoint_container"); + var htmlCollection = bpContainer.node().children; + var numEntries = htmlCollection.length; + + for ( var i = 0; i < numEntries; i++ ) { + htmlCollection[0].remove(); + } + }; + ontologyMenu.append_message = function ( msg ){ + // forward call + append_message(msg); + }; + function append_message( msg ){ + var bpContainer = d3.select("#bulletPoint_container"); + var div = bpContainer.append("div"); + div.node().innerHTML = msg; + loadingModule.scrollDownDetails(); + } + + ontologyMenu.append_message_toLastBulletPoint = function ( msg ){ + // forward call + append_message_toLastBulletPoint(msg); + }; + + ontologyMenu.append_bulletPoint = function ( msg ){ + // forward call + append_bulletPoint(msg); + }; + function append_message_toLastBulletPoint( msg ){ + var bpContainer = d3.select("#bulletPoint_container"); + var htmlCollection = bpContainer.node().getElementsByTagName("LI"); + var lastItem = htmlCollection.length - 1; + if ( lastItem >= 0 ) { + var oldText = htmlCollection[lastItem].innerHTML; + htmlCollection[lastItem].innerHTML = oldText + msg; + } + loadingModule.scrollDownDetails(); + } + + function append_bulletPoint( msg ){ + var bp_container = d3.select("#bulletPoint_container"); + var bp = bp_container.append("li"); + bp.node().innerHTML = msg; + d3.select("#currentLoadingStep").node().innerHTML = msg; + loadingModule.scrollDownDetails(); + } + + + function setupConverterButtons(){ + var iriConverterButton = d3.select("#iri-converter-button"); + var iriConverterInput = d3.select("#iri-converter-input"); + + iriConverterInput.on("input", function (){ + keepOntologySelectionOpenShortly(); + + var inputIsEmpty = iriConverterInput.property("value") === ""; + iriConverterButton.attr("disabled", inputIsEmpty || undefined); + }).on("click", function (){ + keepOntologySelectionOpenShortly(); + }); + + d3.select("#iri-converter-form").on("submit", function (){ + var inputName = iriConverterInput.property("value"); + + // remove first spaces + var clearedName = inputName.replace(/%20/g, " "); + while ( clearedName.beginsWith(" ") ) { + clearedName = clearedName.substr(1, clearedName.length); + } + // remove ending spaces + while ( clearedName.endsWith(" ") ) { + clearedName = clearedName.substr(0, clearedName.length - 1); + } + // check if iri is actually an url for a json file (ends with .json) + // create lowercase filenames; + inputName = clearedName; + var lc_iri = inputName.toLowerCase(); + if ( lc_iri.endsWith(".json") ) { + location.hash = "url=" + inputName; + iriConverterInput.property("value", ""); + iriConverterInput.on("input")(); + } else { + location.hash = "iri=" + inputName; + iriConverterInput.property("value", ""); + iriConverterInput.on("input")(); + } + d3.event.preventDefault(); + return false; + }); + } + + function setupUploadButton(){ + var input = d3.select("#file-converter-input"), + inputLabel = d3.select("#file-converter-label"), + uploadButton = d3.select("#file-converter-button"); + + input.on("change", function (){ + var selectedFiles = input.property("files"); + if ( selectedFiles.length <= 0 ) { + inputLabel.text("Select ontology file"); + uploadButton.property("disabled", true); + } else { + inputLabel.text(selectedFiles[0].name); + fileToLoad = selectedFiles[0].name; + uploadButton.property("disabled", false); + uploadButton.node().click(); + // close menu; + graph.options().navigationMenu().hideAllMenus(); + } + }); + + uploadButton.on("click", function (){ + var selectedFile = input.property("files")[0]; + if ( !selectedFile ) { + return false; + } + var newHashParameter = "file=" + selectedFile.name; + // Trigger the reupload manually, because the iri is not changing + if ( location.hash === "#" + newHashParameter ) { + loadingModule.parseUrlAndLoadOntology(); + } else { + location.hash = newHashParameter; + } + }); + } + + function setLoadingStatusInfo( message ){ + // check if there is a owl2vowl li item; + var o2vConverterContainer = d3.select("#o2vConverterContainer"); + if ( !o2vConverterContainer.node() ) { + var bp_container = d3.select("#bulletPoint_container"); + var div = bp_container.append("div"); + o2vConverterContainer = div.append("ul"); + o2vConverterContainer.attr("id", "o2vConverterContainer"); + o2vConverterContainer.style("margin-left", "-25px"); + } + // clear o2vConverterContainer; + var htmlCollection = o2vConverterContainer.node().children; + var numEntries = htmlCollection.length; + for ( var i = 0; i < numEntries; i++ ) { + htmlCollection[0].remove(); + } + // split tokens provided by o2v messages + var tokens = message.split("* "); + var liForToken; + for ( var t = 0; t < tokens.length; t++ ) { + var tokenMessage = tokens[t]; + // create li for tokens; + if ( tokenMessage.length > 0 ) { + liForToken = o2vConverterContainer.append("li"); + liForToken.attr("type", "disc"); + liForToken.node().innerHTML = tokenMessage.replace(/\n/g, "
    "); + } + } + if ( liForToken ) + liForToken.node().innerHTML += "
    "; + + loadingModule.scrollDownDetails(); + } + + ontologyMenu.setLoadingStatusInfo = function ( message ){ + // forward call + setLoadingStatusInfo(message); + }; + + function getLoadingStatusOnceCallBacked( callback, parameter ){ + d3.xhr("loadingStatus?sessionId=" + conversion_sessionId, "application/text", function ( error, request ){ + if ( error ) { + console.log("ontologyMenu getLoadingStatusOnceCallBacked throws error"); + console.log("---------Error -----------"); + console.log(error); + console.log("---------Request -----------"); + console.log(request); + } + setLoadingStatusInfo(request.responseText); + callback(parameter); + }); + } + + function getLoadingStatusTimeLooped(){ + d3.xhr("loadingStatus?sessionId=" + conversion_sessionId, "application/text", function ( error, request ){ + if ( error ) { + console.log("ontologyMenu getLoadingStatusTimeLooped throws error"); + console.log("---------Error -----------"); + console.log(error); + console.log("---------Request -----------"); + console.log(request); + } + if ( stopTimer === false ) { + setLoadingStatusInfo(request.responseText); + timedLoadingStatusLogger(); + } + }); + } + + function timedLoadingStatusLogger(){ + clearTimeout(loadingStatusTimer); + if ( stopTimer === false ) { + loadingStatusTimer = setTimeout(function (){ + getLoadingStatusTimeLooped(); + }, 1000); + } + } + + function callbackUpdateLoadingMessage( msg ){ + d3.xhr("loadingStatus", "application/text", function ( error, request ){ + if ( request !== undefined ) { + setLoadingStatusInfo(request.responseText + "
    " + msg); + } else { + append_message(msg); + } + }); + } + + ontologyMenu.setConversionID = function ( id ){ + conversion_sessionId = id; + }; + + ontologyMenu.callbackLoad_Ontology_FromIRI = function ( parameter ){ + var relativePath = parameter[0]; + var ontoName = parameter[1]; + var localThreadId = parameter[2]; + stopTimer = false; + timedLoadingStatusLogger(); + d3.xhr(relativePath, "application/json", function ( error, request ){ + var loadingSuccessful = !error; + // check if error occurred or responseText is empty + if ( (error !== null && error.status === 500) || (request && request.responseText.length === 0) ) { + clearTimeout(loadingStatusTimer); + stopTimer = true; + getLoadingStatusOnceCallBacked(callbackFromIRI_URL_ERROR, [error, request, localThreadId]); + } + var jsonText; + if ( loadingSuccessful ) { + clearTimeout(loadingStatusTimer); + stopTimer = true; + jsonText = request.responseText; + getLoadingStatusOnceCallBacked(callbackFromIRI_Success, [jsonText, ontoName, localThreadId]); + } + }); + }; + + + ontologyMenu.callbackLoad_Ontology_From_DirectInput = function ( text, parameter ){ + var input = text; + var sessionId = parameter[1]; + stopTimer = false; + timedLoadingStatusLogger(); + + var formData = new FormData(); + formData.append("input", input); + formData.append("sessionId", sessionId); + var xhr = new XMLHttpRequest(); + + xhr.open("POST", "directInput", true); + xhr.onload = function (){ + clearTimeout(loadingStatusTimer); + stopTimer = true; + getLoadingStatusOnceCallBacked(callbackForConvert, [xhr, input, sessionId]); + }; + timedLoadingStatusLogger(); + xhr.send(formData); + + }; + function callbackFromIRI_Success( parameter ){ + var local_conversionId = parameter[2]; + if ( local_conversionId !== conversion_sessionId ) { + console.log("The conversion process for file:" + parameter[1] + " has been canceled!"); + ontologyMenu.conversionFinished(local_conversionId); + return; + } + loadingModule.loadFromOWL2VOWL(parameter[0], parameter[1]); + ontologyMenu.conversionFinished(); + + } + + function callbackFromDirectInput_Success( parameter ){ + var local_conversionId = parameter[1]; + if ( local_conversionId !== conversion_sessionId ) { + console.log("The conversion process for file:" + parameter[1] + " has been canceled!"); + ontologyMenu.conversionFinished(local_conversionId); + return; + } + loadingModule.loadFromOWL2VOWL(parameter[0], "DirectInputConversionID" + local_conversionId); + ontologyMenu.conversionFinished(); + + } + + ontologyMenu.getConversionId = function (){ + return conversion_sessionId; + }; + + ontologyMenu.callbackLoad_JSON_FromURL = function ( parameter ){ + var relativePath = parameter[0]; + var ontoName = parameter[1]; + var local_conversionId = parameter[2]; + stopTimer = false; + timedLoadingStatusLogger(); + d3.xhr(relativePath, "application/json", function ( error, request ){ + var loadingSuccessful = !error; + // check if error occurred or responseText is empty + if ( (error !== null && error.status === 500) || (request && request.responseText.length === 0) ) { + clearTimeout(loadingStatusTimer); + stopTimer = true; + loadingSuccessful = false; + console.log(request); + console.log(request.responseText.length); + getLoadingStatusOnceCallBacked(callbackFromJSON_URL_ERROR, [error, request, local_conversionId]); + } + if ( loadingSuccessful ) { + clearTimeout(loadingStatusTimer); + stopTimer = true; + var jsonText = request.responseText; + getLoadingStatusOnceCallBacked(callbackFromJSON_Success, [jsonText, ontoName, local_conversionId]); + } + }); + }; + + function callbackFromJSON_Success( parameter ){ + var local_conversionId = parameter[2]; + if ( local_conversionId !== conversion_sessionId ) { + console.log("The conversion process for file:" + parameter[1] + " has been canceled!"); + return; + } + loadingModule.loadFromOWL2VOWL(parameter[0], parameter[1]); + } + + function callbackFromJSON_URL_ERROR( parameter ){ + var error = parameter[0]; + var request = parameter[1]; + var local_conversionId = parameter[2]; + if ( local_conversionId !== conversion_sessionId ) { + console.log("This thread has been canceled!!"); + ontologyMenu.conversionFinished(local_conversionId); + return; + } + callbackUpdateLoadingMessage("
    Failed to convert the file. " + + " Ontology could not be loaded.
    Is it a valid OWL ontology? Please check with OWL Validator"); + + if ( error !== null && error.status === 500 ) { + append_message("Could not find ontology at the URL"); + } + if ( request && request.responseText.length === 0 ) { + append_message("Received empty graph"); + } + graph.handleOnLoadingError(); + ontologyMenu.conversionFinished(); + } + + + function callbackFromIRI_URL_ERROR( parameter ){ + var error = parameter[0]; + var request = parameter[1]; + var local_conversionId = parameter[2]; + if ( local_conversionId !== conversion_sessionId ) { + console.log("This thread has been canceled!!"); + ontologyMenu.conversionFinished(local_conversionId); + return; + } + callbackUpdateLoadingMessage("
    Failed to convert the file. " + + " Ontology could not be loaded.
    Is it a valid OWL ontology? Please check with OWL Validator"); + + if ( error !== null && error.status === 500 ) { + append_message("Could not find ontology at the URL"); + } + if ( request && request.responseText.length === 0 ) { + append_message("Received empty graph"); + } + graph.handleOnLoadingError(); + ontologyMenu.conversionFinished(); + } + + function callbackFromDirectInput_ERROR( parameter ){ + + var error = parameter[0]; + var request = parameter[1]; + var local_conversionId = parameter[2]; + if ( local_conversionId !== conversion_sessionId ) { + console.log("The loading process for direct input has been canceled!"); + return; + } + // callbackUpdateLoadingMessage("
    Failed to convert the file. "+ + // "Ontology could not be loaded.
    Is it a valid OWL ontology? Please check with OWL Validator"); + if ( error !== null && error.status === 500 ) { + append_message("Could not convert direct input"); + } + if ( request && request.responseText.length === 0 ) { + append_message("Received empty graph"); + } + + graph.handleOnLoadingError(); + ontologyMenu.conversionFinished(); + } + + ontologyMenu.callbackLoadFromOntology = function ( selectedFile, filename, local_threadId ){ + callbackLoadFromOntology(selectedFile, filename, local_threadId); + }; + + function callbackLoadFromOntology( selectedFile, filename, local_threadId ){ + stopTimer = false; + timedLoadingStatusLogger(); + + var formData = new FormData(); + formData.append("ontology", selectedFile); + formData.append("sessionId", local_threadId); + var xhr = new XMLHttpRequest(); + + xhr.open("POST", "convert", true); + xhr.onload = function (){ + clearTimeout(loadingStatusTimer); + stopTimer = true; + console.log(xhr); + getLoadingStatusOnceCallBacked(callbackForConvert, [xhr, filename, local_threadId]); + }; + timedLoadingStatusLogger(); + xhr.send(formData); + } + + function callbackForConvert( parameter ){ + var xhr = parameter[0]; + var filename = parameter[1]; + var local_threadId = parameter[2]; + if ( local_threadId !== conversion_sessionId ) { + console.log("The conversion process for file:" + filename + " has been canceled!"); + ontologyMenu.conversionFinished(local_threadId); + return; + } + if ( xhr.status === 200 ) { + loadingModule.loadFromOWL2VOWL(xhr.responseText, filename); + ontologyMenu.conversionFinished(); + } else { + var uglyJson=xhr.responseText; + var jsonResut=JSON.parse(uglyJson); + var niceJSON=JSON.stringify(jsonResut, 'null', ' '); + niceJSON= niceJSON.replace(new RegExp('\r?\n','g'), '
    '); + callbackUpdateLoadingMessage("Failed to convert the file. " + + "
    Server answer:
    "+ + "
    "+niceJSON+ "
    "+ + "Ontology could not be loaded.
    Is it a valid OWL ontology? Please check with OWL Validator"); + + graph.handleOnLoadingError(); + ontologyMenu.conversionFinished(); + } + } + + ontologyMenu.conversionFinished = function ( id ){ + var local_id = conversion_sessionId; + if ( id ) { + local_id = id; + } + d3.xhr("conversionDone?sessionId=" + local_id, "application/text", function ( error, request ){ + if ( error ) { + console.log("ontologyMenu conversionFinished throws error"); + console.log("---------Error -----------"); + console.log(error); + console.log("---------Request -----------"); + console.log(request); + } + }); + }; + + function keepOntologySelectionOpenShortly(){ + // Events in the menu should not be considered + var ontologySelection = d3.select("#select .toolTipMenu"); + ontologySelection.on("click", function (){ + d3.event.stopPropagation(); + }).on("keydown", function (){ + d3.event.stopPropagation(); + }); + + ontologySelection.style("display", "block"); + + function disableKeepingOpen(){ + ontologySelection.style("display", undefined); + + clearTimeout(ontologyMenuTimeout); + d3.select(window).on("click", undefined).on("keydown", undefined); + ontologySelection.on("mouseover", undefined); + } + + // Clear the timeout to handle fast calls of this function + clearTimeout(ontologyMenuTimeout); + ontologyMenuTimeout = setTimeout(function (){ + disableKeepingOpen(); + }, 3000); + + // Disable forced open selection on interaction + d3.select(window).on("click", function (){ + disableKeepingOpen(); + }).on("keydown", function (){ + disableKeepingOpen(); + }); + + ontologySelection.on("mouseover", function (){ + disableKeepingOpen(); + }); + } + + ontologyMenu.showLoadingStatus = function ( visible ){ + if ( visible === true ) { + displayLoadingIndicators(); + } + else { + hideLoadingInformations(); + } + }; + + function displayLoadingIndicators(){ + d3.select("#layoutLoadingProgressBarContainer").classed("hidden", false); + loadingInfo.classed("hidden", false); + loadingProgress.classed("hidden", false); + } + + function hideLoadingInformations(){ + loadingInfo.classed("hidden", true); + } + + return ontologyMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 330: +/***/ (function(module, exports, __webpack_require__) { + + var toString = __webpack_require__(219), + unescapeHtmlChar = __webpack_require__(331); + + /** Used to match HTML entities and HTML characters. */ + var reEscapedHtml = /&(?:amp|lt|gt|quot|#39);/g, + reHasEscapedHtml = RegExp(reEscapedHtml.source); + + /** + * The inverse of `_.escape`; this method converts the HTML entities + * `&`, `<`, `>`, `"`, and `'` in `string` to + * their corresponding characters. + * + * **Note:** No other HTML entities are unescaped. To unescape additional + * HTML entities use a third-party library like [_he_](https://mths.be/he). + * + * @static + * @memberOf _ + * @since 0.6.0 + * @category String + * @param {string} [string=''] The string to unescape. + * @returns {string} Returns the unescaped string. + * @example + * + * _.unescape('fred, barney, & pebbles'); + * // => 'fred, barney, & pebbles' + */ + function unescape(string) { + string = toString(string); + return (string && reHasEscapedHtml.test(string)) + ? string.replace(reEscapedHtml, unescapeHtmlChar) + : string; + } + + module.exports = unescape; + + +/***/ }), + +/***/ 331: +/***/ (function(module, exports, __webpack_require__) { + + var basePropertyOf = __webpack_require__(332); + + /** Used to map HTML entities to characters. */ + var htmlUnescapes = { + '&': '&', + '<': '<', + '>': '>', + '"': '"', + ''': "'" + }; + + /** + * Used by `_.unescape` to convert HTML entities to characters. + * + * @private + * @param {string} chr The matched character to unescape. + * @returns {string} Returns the unescaped character. + */ + var unescapeHtmlChar = basePropertyOf(htmlUnescapes); + + module.exports = unescapeHtmlChar; + + +/***/ }), + +/***/ 332: +/***/ (function(module, exports) { + + /** + * The base implementation of `_.propertyOf` without support for deep paths. + * + * @private + * @param {Object} object The object to query. + * @returns {Function} Returns the new accessor function. + */ + function basePropertyOf(object) { + return function(key) { + return object == null ? undefined : object[key]; + }; + } + + module.exports = basePropertyOf; + + +/***/ }), + +/***/ 333: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for the pause and resume button. + * + * @param graph the associated webvowl graph + * @returns {{}} + */ + module.exports = function ( graph ){ + + var pauseMenu = {}, + pauseButton; + + + /** + * Adds the pause button to the website. + */ + pauseMenu.setup = function (){ + var menuEntry = d3.select("#pauseOption"); + menuEntry.on("mouseover", function (){ + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + }); + pauseButton = d3.select("#pause-button") + .datum({ paused: false }) + .on("click", function ( d ){ + graph.paused(!d.paused); + d.paused = !d.paused; + updatePauseButton(); + pauseButton.classed("highlighted", d.paused); + }); + // Set these properties the first time manually + updatePauseButton(); + }; + + pauseMenu.setPauseValue = function ( value ){ + pauseButton.datum().paused = value; + graph.paused(value); + pauseButton.classed("highlighted", value); + updatePauseButton(); + }; + + function updatePauseButton(){ + updatePauseButtonClass(); + updatePauseButtonText(); + } + + function updatePauseButtonClass(){ + pauseButton.classed("paused", function ( d ){ + return d.paused; + }); + } + + function updatePauseButtonText(){ + if ( pauseButton.datum().paused ) { + pauseButton.text("Resume"); + } else { + pauseButton.text("Pause"); + } + } + + pauseMenu.reset = function (){ + // resuming + pauseMenu.setPauseValue(false); + }; + + + return pauseMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 334: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for the reset button. + * + * @param graph the associated webvowl graph + * @returns {{}} + */ + module.exports = function ( graph ){ + + var resetMenu = {}, + options = graph.graphOptions(), + resettableModules, + untouchedOptions = webvowl.options(); + + + /** + * Adds the reset button to the website. + * @param _resettableModules modules that can be resetted + */ + resetMenu.setup = function ( _resettableModules ){ + resettableModules = _resettableModules; + d3.select("#reset-button").on("click", resetGraph); + var menuEntry = d3.select("#resetOption"); + menuEntry.on("mouseover", function (){ + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + }); + }; + + function resetGraph(){ + graph.resetSearchHighlight(); + graph.options().searchMenu().clearText(); + options.classDistance(untouchedOptions.classDistance()); + options.datatypeDistance(untouchedOptions.datatypeDistance()); + options.charge(untouchedOptions.charge()); + options.gravity(untouchedOptions.gravity()); + options.linkStrength(untouchedOptions.linkStrength()); + graph.reset(); + + resettableModules.forEach(function ( module ){ + module.reset(); + }); + + graph.updateStyle(); + } + + + return resetMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 335: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the search "engine" + * + * @param graph the associated webvowl graph + * @returns {{}} + */ + module.exports = function ( graph ){ + var searchMenu = {}, + dictionary = [], + entryNames = [], + searchLineEdit, + mergedStringsList, + mergedIdList, + maxEntries = 6, + dictionaryUpdateRequired = true, + labelDictionary, + inputText, + viewStatusOfSearchEntries = false; + + var results = []; + var resultID = []; + var c_locate = d3.select("#locateSearchResult"); + var c_search = d3.select("#c_search"); + var m_search = d3.select("#m_search"); // << dropdown container; + + + String.prototype.beginsWith = function ( string ){ + return (this.indexOf(string) === 0); + }; + + searchMenu.requestDictionaryUpdate = function (){ + dictionaryUpdateRequired = true; + // clear possible pre searched entries + var htmlCollection = m_search.node().children; + var numEntries = htmlCollection.length; + + for ( var i = 0; i < numEntries; i++ ) + htmlCollection[0].remove(); + searchLineEdit.node().value = ""; + }; + + + function updateSearchDictionary(){ + labelDictionary = graph.getUpdateDictionary(); + dictionaryUpdateRequired = false; + dictionary = []; + entryNames = []; + var idList = []; + var stringList = []; + + var i; + for ( i = 0; i < labelDictionary.length; i++ ) { + var lEntry = labelDictionary[i].labelForCurrentLanguage(); + idList.push(labelDictionary[i].id()); + stringList.push(lEntry); + // add all equivalents to the search space; + if ( labelDictionary[i].equivalents && labelDictionary[i].equivalents().length > 0 ) { + var eqs = labelDictionary[i].equivalentsString(); + var eqsLabels = eqs.split(", "); + for ( var e = 0; e < eqsLabels.length; e++ ) { + idList.push(labelDictionary[i].id()); + stringList.push(eqsLabels[e]); + } + } + } + + mergedStringsList = []; + mergedIdList = []; + var indexInStringList = -1; + var currentString; + var currentObjectId; + + for ( i = 0; i < stringList.length; i++ ) { + if ( i === 0 ) { + // just add the elements + mergedStringsList.push(stringList[i]); + mergedIdList.push([]); + mergedIdList[0].push(idList[i]); + continue; + } + else { + currentString = stringList[i]; + currentObjectId = idList[i]; + indexInStringList = mergedStringsList.indexOf(currentString); + } + if ( indexInStringList === -1 ) { + mergedStringsList.push(stringList[i]); + mergedIdList.push([]); + var lastEntry = mergedIdList.length; + mergedIdList[lastEntry - 1].push(currentObjectId); + } else { + mergedIdList[indexInStringList].push(currentObjectId); + } + } + + for ( i = 0; i < mergedStringsList.length; i++ ) { + var aString = mergedStringsList[i]; + var correspondingIdList = mergedIdList[i]; + var idListResult = "[ "; + for ( var j = 0; j < correspondingIdList.length; j++ ) { + idListResult = idListResult + correspondingIdList[j].toString(); + idListResult = idListResult + ", "; + } + idListResult = idListResult.substring(0, idListResult.length - 2); + idListResult = idListResult + " ]"; + + dictionary.push(aString); + entryNames.push(aString); + } + } + + searchMenu.setup = function (){ + // clear dictionary; + dictionary = []; + searchLineEdit = d3.select("#search-input-text"); + searchLineEdit.on("input", userInput); + searchLineEdit.on("keydown", userNavigation); + searchLineEdit.on("click", toggleSearchEntryView); + searchLineEdit.on("mouseover", hoverSearchEntryView); + + c_locate.on("click", function (){ + graph.locateSearchResult(); + }); + + c_locate.on("mouseover", function (){ + searchMenu.hideSearchEntries(); + }); + + }; + + function hoverSearchEntryView(){ + updateSelectionStatusFlags(); + searchMenu.showSearchEntries(); + } + + function toggleSearchEntryView(){ + if ( viewStatusOfSearchEntries ) { + searchMenu.hideSearchEntries(); + } else { + searchMenu.showSearchEntries(); + } + } + + searchMenu.hideSearchEntries = function (){ + m_search.style("display", "none"); + viewStatusOfSearchEntries = false; + }; + + searchMenu.showSearchEntries = function (){ + m_search.style("display", "block"); + viewStatusOfSearchEntries = true; + }; + + function ValidURL( str ){ + var urlregex = /^(https?|ftp):\/\/([a-zA-Z0-9.-]+(:[a-zA-Z0-9.&%$-]+)*@)*((25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9][0-9]?)(\.(25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9]?[0-9])){3}|([a-zA-Z0-9-]+\.)*[a-zA-Z0-9-]+\.(com|edu|gov|int|mil|net|org|biz|arpa|info|name|pro|aero|coop|museum|[a-zA-Z]{2}))(:[0-9]+)*(\/($|[a-zA-Z0-9.,?'\\+&%$#=~_-]+))*$/; + return urlregex.test(str); + + } + + + function updateSelectionStatusFlags(){ + if ( searchLineEdit.node().value.length === 0 ) { + createSearchEntries(); + return; + } + handleAutoCompletion(); + } + + function userNavigation(){ + if ( dictionaryUpdateRequired ) { + updateSearchDictionary(); + } + + var htmlCollection = m_search.node().children; + var numEntries = htmlCollection.length; + + + var move = 0; + var i; + var selectedEntry = -1; + for ( i = 0; i < numEntries; i++ ) { + var atr = htmlCollection[i].getAttribute('class'); + if ( atr === "dbEntrySelected" ) { + selectedEntry = i; + } + } + if ( d3.event.keyCode === 13 ) { + if ( selectedEntry >= 0 && selectedEntry < numEntries ) { + // simulate onClick event + htmlCollection[selectedEntry].onclick(); + searchMenu.hideSearchEntries(); + } + else if ( numEntries === 0 ) { + inputText = searchLineEdit.node().value; + // check if input text ends or begins with with space + // remove first spaces + var clearedText = inputText.replace(/%20/g, " "); + while ( clearedText.beginsWith(" ") ) { + clearedText = clearedText.substr(1, clearedText.length); + } + // remove ending spaces + while ( clearedText.endsWith(" ") ) { + clearedText = clearedText.substr(0, clearedText.length - 1); + } + var iri = clearedText.replace(/ /g, "%20"); + + var valid = ValidURL(iri); + // validate url: + if ( valid ) { + var ontM = graph.options().ontologyMenu(); + ontM.setIriText(iri); + searchLineEdit.node().value = ""; + } + else { + console.log(iri + " is not a valid URL!"); + } + } + } + if ( d3.event.keyCode === 38 ) { + move = -1; + searchMenu.showSearchEntries(); + } + if ( d3.event.keyCode === 40 ) { + move = +1; + searchMenu.showSearchEntries(); + } + + var newSelection = selectedEntry + move; + if ( newSelection !== selectedEntry ) { + + if ( newSelection < 0 && selectedEntry <= 0 ) { + htmlCollection[0].setAttribute('class', "dbEntrySelected"); + } + + if ( newSelection >= numEntries ) { + htmlCollection[selectedEntry].setAttribute('class', "dbEntrySelected"); + } + if ( newSelection >= 0 && newSelection < numEntries ) { + htmlCollection[newSelection].setAttribute('class', "dbEntrySelected"); + if ( selectedEntry >= 0 ) + htmlCollection[selectedEntry].setAttribute('class', "dbEntry"); + } + } + } + + searchMenu.getSearchString = function (){ + return searchLineEdit.node().value; + }; + + + function clearSearchEntries(){ + var htmlCollection = m_search.node().children; + var numEntries = htmlCollection.length; + for ( var i = 0; i < numEntries; i++ ) { + htmlCollection[0].remove(); + } + results = []; + resultID = []; + + } + + function createSearchEntries(){ + inputText = searchLineEdit.node().value; + var i; + var lc_text = inputText.toLowerCase(); + var token; + + for ( i = 0; i < dictionary.length; i++ ) { + var tokenElement = dictionary[i]; + if ( tokenElement === undefined ) { + //@WORKAROUND : nodes with undefined labels are skipped + //@FIX: these nodes are now not added to the dictionary + continue; + } + token = dictionary[i].toLowerCase(); + if ( token.indexOf(lc_text) > -1 ) { + results.push(dictionary[i]); + resultID.push(i); + } + } + } + + function measureTextWidth( text, textStyle ){ + // Set a default value + if ( !textStyle ) { + textStyle = "text"; + } + var d = d3.select("body") + .append("div") + .attr("class", textStyle) + .attr("id", "width-test") // tag this element to identify it + .attr("style", "position:absolute; float:left; white-space:nowrap; visibility:hidden;") + .text(text), + w = document.getElementById("width-test").offsetWidth; + d.remove(); + return w; + } + + function cropText( input ){ + var maxWidth = 250; + var textStyle = "dbEntry"; + var truncatedText = input; + var textWidth; + var ratio; + var newTruncatedTextLength; + while ( true ) { + textWidth = measureTextWidth(truncatedText, textStyle); + if ( textWidth <= maxWidth ) { + break; + } + + ratio = textWidth / maxWidth; + newTruncatedTextLength = Math.floor(truncatedText.length / ratio); + + // detect if nothing changes + if ( truncatedText.length === newTruncatedTextLength ) { + break; + } + + truncatedText = truncatedText.substring(0, newTruncatedTextLength); + } + + if ( input.length > truncatedText.length ) { + return input.substring(0, truncatedText.length - 6); + } + return input; + } + + function createDropDownElements(){ + var numEntries; + var copyRes = results; + var i; + var token; + var newResults = []; + var newResultsIds = []; + + var lc_text = searchLineEdit.node().value.toLowerCase(); + // set the number of shown results to be maxEntries or less; + numEntries = results.length; + if ( numEntries > maxEntries ) + numEntries = maxEntries; + + + for ( i = 0; i < numEntries; i++ ) { + // search for the best entry + var indexElement = 1000000; + var lengthElement = 1000000; + var bestElement = -1; + for ( var j = 0; j < copyRes.length; j++ ) { + token = copyRes[j].toLowerCase(); + var tIe = token.indexOf(lc_text); + var tLe = token.length; + if ( tIe > -1 && tIe <= indexElement && tLe <= lengthElement ) { + bestElement = j; + indexElement = tIe; + lengthElement = tLe; + } + } + newResults.push(copyRes[bestElement]); + newResultsIds.push(resultID[bestElement]); + copyRes[bestElement] = ""; + } + + // add the results to the entry menu + //****************************************** + numEntries = results.length; + if ( numEntries > maxEntries ) + numEntries = maxEntries; + + var filteredOutElements = 0; + for ( i = 0; i < numEntries; i++ ) { + //add results to the dropdown menu + var testEntry = document.createElement('li'); + testEntry.setAttribute('elementID', newResultsIds[i]); + testEntry.onclick = handleClick(newResultsIds[i]); + testEntry.setAttribute('class', "dbEntry"); + + var entries = mergedIdList[newResultsIds[i]]; + var eLen = entries.length; + + var croppedText = cropText(newResults[i]); + + var el0 = entries[0]; + var allSame = true; + var nodeMap = graph.getNodeMapForSearch(); + var visible = eLen; + if ( eLen > 1 ) { + for ( var q = 0; q < eLen; q++ ) { + if ( nodeMap[entries[q]] === undefined ) { + visible--; + } + } + } + + for ( var a = 0; a < eLen; a++ ) { + if ( el0 !== entries[a] ) { + allSame = false; + } + } + if ( croppedText !== newResults[i] ) { + // append ...(#numElements) if needed + if ( eLen > 1 && allSame === false ) { + if ( eLen !== visible ) + croppedText += "... (" + visible + "/" + eLen + ")"; + } + else { + croppedText += "..."; + } + testEntry.title = newResults[i]; + } + else { + if ( eLen > 1 && allSame === false ) { + if ( eLen !== visible ) + croppedText += " (" + visible + "/" + eLen + ")"; + else + croppedText += " (" + eLen + ")"; + } + } + + var searchEntryNode = d3.select(testEntry); + if ( eLen === 1 || allSame === true ) { + if ( nodeMap[entries[0]] === undefined ) { + searchEntryNode.style("color", "#979797"); + testEntry.title = newResults[i] + "\nElement is filtered out."; + testEntry.onclick = function (){ + }; + d3.select(testEntry).style("cursor", "default"); + filteredOutElements++; + } + } else { + if ( visible < 1 ) { + searchEntryNode.style("color", "#979797"); + testEntry.onclick = function (){ + }; + testEntry.title = newResults[i] + "\nAll elements are filtered out."; + d3.select(testEntry).style("cursor", "default"); + filteredOutElements++; + } else { + searchEntryNode.style("color", ""); + } + if ( visible < eLen && visible > 1 ) { + testEntry.title = newResults[i] + "\n" + visible + "/" + eLen + " elements are visible."; + } + } + searchEntryNode.node().innerHTML = croppedText; + m_search.node().appendChild(testEntry); + } + } + + + function handleAutoCompletion(){ + /** pre condition: autoCompletion has already a valid text**/ + clearSearchEntries(); + createSearchEntries(); + createDropDownElements(); + } + + function userInput(){ + c_locate.classed("highlighted", false); + c_locate.node().title = "Nothing to locate"; + + if ( dictionaryUpdateRequired ) { + updateSearchDictionary(); + } + graph.resetSearchHighlight(); + + if ( dictionary.length === 0 ) { + console.log("dictionary is empty"); + return; + } + inputText = searchLineEdit.node().value; + + clearSearchEntries(); + if ( inputText.length !== 0 ) { + createSearchEntries(); + createDropDownElements(); + } + + searchMenu.showSearchEntries(); + } + + function handleClick( elementId ){ + + return function (){ + var id = elementId; + var correspondingIds = mergedIdList[id]; + + // autoComplete the text for the user + var autoComStr = entryNames[id]; + searchLineEdit.node().value = autoComStr; + + graph.resetSearchHighlight(); + graph.highLightNodes(correspondingIds); + c_locate.node().title = "Locate search term"; + if ( autoComStr !== inputText ) { + handleAutoCompletion(); + } + searchMenu.hideSearchEntries(); + }; + } + + searchMenu.clearText = function (){ + searchLineEdit.node().value = ""; + c_locate.classed("highlighted", false); + c_locate.node().title = "Nothing to locate"; + var htmlCollection = m_search.node().children; + var numEntries = htmlCollection.length; + for ( var i = 0; i < numEntries; i++ ) { + htmlCollection[0].remove(); + } + }; + + return searchMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 336: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the navigation "engine" + * + * @param graph the associated webvowl graph + * @returns {{}} + */ + module.exports = function ( graph ){ + var navigationMenu = {}, + scrollContainer = d3.select("#menuElementContainer").node(), + menuContainer = d3.select("#menuContainer").node(), + leftButton = d3.select("#scrollLeftButton"), + rightButton = d3.select("#scrollRightButton"), + scrolLeftValue, + scrollMax, + currentlyVisibleMenu, + currentlyHoveredEntry, + touchedElement = false, + t_scrollLeft, + t_scrollRight, + c_select = [], + m_select = []; + + + function clearAllTimers(){ + cancelAnimationFrame(t_scrollLeft); + cancelAnimationFrame(t_scrollRight); + } + + function timed_scrollRight(){ + scrolLeftValue += 5; + scrollContainer.scrollLeft = scrolLeftValue; + navigationMenu.updateScrollButtonVisibility(); + if ( scrolLeftValue >= scrollMax ) { + clearAllTimers(); + return; + } + t_scrollRight = requestAnimationFrame(timed_scrollRight); + + } + + function timed_scrollLeft(){ + scrolLeftValue -= 5; + scrollContainer.scrollLeft = scrolLeftValue; + navigationMenu.updateScrollButtonVisibility(); + if ( scrolLeftValue <= 0 ) { + clearAllTimers(); + return; + } + t_scrollRight = requestAnimationFrame(timed_scrollLeft); + } + + // collect all menu entries and stuff; + function setupControlsAndMenus(){ + // HEURISTIC : to match the menus and their controllers we remove the first 2 letters and match + c_select = []; + m_select = []; + + var c_temp = []; + var m_temp = []; + var i; + var controlElements = scrollContainer.children; + var numEntries = controlElements.length; + + for ( i = 0; i < numEntries; i++ ) { + c_temp.push(controlElements[i].id.slice(2)); + } + + var menuElements = menuContainer.children; + numEntries = menuElements.length; + for ( i = 0; i < numEntries; i++ ) { + m_temp.push(menuElements[i].id.slice(2)); + } + + numEntries = controlElements.length; + for ( i = 0; i < numEntries; i++ ) { + c_select[i] = "c_" + c_temp[i]; + if ( m_temp.indexOf(c_temp[i]) > -1 ) { + m_select[i] = "m_" + c_temp[i]; + } else { + m_select[i] = undefined; + } + // create custom behavior for click, touch, and hover + d3.select("#" + c_select[i]).on("mouseover", menuElementOnHovered); + d3.select("#" + c_select[i]).on("mouseout", menuElementOutHovered); + + d3.select("#" + c_select[i]).on("click", menuElementClicked); + d3.select("#" + c_select[i]).on("touchstart", menuElementTouched); + + } + + // connect to mouseWheel + d3.select("#menuElementContainer").on("wheel", function (){ + var wheelEvent = d3.event; + var offset; + if ( wheelEvent.deltaY < 0 ) offset = 20; + if ( wheelEvent.deltaY > 0 ) offset = -20; + scrollContainer.scrollLeft += offset; + navigationMenu.hideAllMenus(); + navigationMenu.updateScrollButtonVisibility(); + }); + + // connect scrollIndicator Buttons; + d3.select("#scrollRightButton").on("mousedown", function (){ + scrolLeftValue = scrollContainer.scrollLeft; + navigationMenu.hideAllMenus(); + t_scrollRight = requestAnimationFrame(timed_scrollRight); + + }).on("touchstart", function (){ + scrolLeftValue = scrollContainer.scrollLeft; + navigationMenu.hideAllMenus(); + t_scrollRight = requestAnimationFrame(timed_scrollRight); + }).on("mouseup", clearAllTimers) + .on("touchend", clearAllTimers) + .on("touchcancel", clearAllTimers); + + d3.select("#scrollLeftButton").on("mousedown", function (){ + scrolLeftValue = scrollContainer.scrollLeft; + navigationMenu.hideAllMenus(); + t_scrollLeft = requestAnimationFrame(timed_scrollLeft); + }).on("touchstart", function (){ + scrolLeftValue = scrollContainer.scrollLeft; + navigationMenu.hideAllMenus(); + t_scrollLeft = requestAnimationFrame(timed_scrollLeft); + }).on("mouseup", clearAllTimers) + .on("touchend", clearAllTimers) + .on("touchcancel", clearAllTimers); + + // connect the scroll functionality; + d3.select("#menuElementContainer").on("scroll", function (){ + navigationMenu.updateScrollButtonVisibility(); + navigationMenu.hideAllMenus(); + }); + } + + function menuElementOnHovered(){ + navigationMenu.hideAllMenus(); + if ( touchedElement ) { + return; + } + showSingleMenu(this.id); + } + + function menuElementOutHovered(){ + hoveroutedControMenu(this.id); + } + + function menuElementClicked(){ + var m_element = m_select[c_select.indexOf(this.id)]; + if ( m_element ) { + var menuElement = d3.select("#" + m_element); + if ( menuElement ) { + if ( menuElement.style("display") === "block" ) { + menuElement.style("display", "none");// hide it + } else { + showSingleMenu(this.id); + } + } + } + } + + function menuElementTouched(){ + // it sets a flag that we have touched it, + // since d3. propagates the event for touch as hover and then click, we block the hover event + touchedElement = true; + } + + + function hoveroutedControMenu( controllerID ){ + currentlyHoveredEntry = d3.select("#" + controllerID); + if ( controllerID !== "c_search" ) { + d3.select("#" + controllerID).select("path").style("stroke-width", "0"); + d3.select("#" + controllerID).select("path").style("fill", "#fff"); + } + + } + + function showSingleMenu( controllerID ){ + currentlyHoveredEntry = d3.select("#" + controllerID).node(); + // get the corresponding menu element for this controller + var m_element = m_select[c_select.indexOf(controllerID)]; + if ( m_element ) { + if ( controllerID !== "c_search" ) { + + d3.select("#" + controllerID).select("path").style("stroke-width", "0"); + d3.select("#" + controllerID).select("path").style("fill", "#bdc3c7"); + } + // show it if we have a menu + currentlyVisibleMenu = d3.select("#" + m_element); + currentlyVisibleMenu.style("display", "block"); + if ( m_element === "m_export" ) + graph.options().exportMenu().exportAsUrl(); + updateMenuPosition(); + } + } + + function updateMenuPosition(){ + if ( currentlyHoveredEntry ) { + var leftOffset = currentlyHoveredEntry.offsetLeft; + var scrollOffset = scrollContainer.scrollLeft; + var totalOffset = leftOffset - scrollOffset; + var finalOffset = Math.max(0, totalOffset); + var fullContainer_width = scrollContainer.getBoundingClientRect().width; + var elementWidth = currentlyVisibleMenu.node().getBoundingClientRect().width; + // make priority > first check if we are right + if ( finalOffset + elementWidth > fullContainer_width ) { + finalOffset = fullContainer_width - elementWidth; + } + // fix priority; + finalOffset = Math.max(0, finalOffset); + currentlyVisibleMenu.style("left", finalOffset + "px"); + + // // check if outside the viewport + // var menuWidth=currentlyHoveredEntry.getBoundingClientRect().width; + // var bt_width=36; + // if (totalOffset+menuWidthfullContainer_width){ + // navigationMenu.hideAllMenus(); + // currentlyHoveredEntry=undefined; + // } + } + } + + navigationMenu.hideAllMenus = function (){ + d3.selectAll(".toolTipMenu").style("display", "none"); // hiding all menus + }; + + navigationMenu.updateScrollButtonVisibility = function (){ + scrollMax = scrollContainer.scrollWidth - scrollContainer.clientWidth - 2; + if ( scrollContainer.scrollLeft === 0 ) { + leftButton.classed("hidden", true); + } else { + leftButton.classed("hidden", false); + } + + if ( scrollContainer.scrollLeft > scrollMax ) { + rightButton.classed("hidden", true); + } else { + rightButton.classed("hidden", false); + } + + }; + + navigationMenu.setup = function (){ + setupControlsAndMenus(); + // make sure that the menu elements follow their controller and also their restrictions + // some hovering behavior -- lets the menu disappear when hovered in graph or sidebar; + d3.select("#graph").on("mouseover", function (){ + navigationMenu.hideAllMenus(); + }); + d3.select("#generalDetails").on("mouseover", function (){ + navigationMenu.hideAllMenus(); + }); + }; + + return navigationMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 337: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** The zoom Slider **/ + module.exports = function ( graph ){ + var zoomSlider = {}; + var minMag = graph.options().minMagnification(), + maxMag = graph.options().maxMagnification(), + defZoom, + t_zoomOut, + t_zoomIn, + zoomValue, + showSlider = true, + w = graph.options().width(), + h = graph.options().height(), + slider; + + defZoom = Math.min(w, h) / 1000; + + function clearAllTimers(){ + cancelAnimationFrame(t_zoomOut); + cancelAnimationFrame(t_zoomIn); + } + + function timed_zoomOut(){ + zoomValue = 0.98 * zoomValue; + // fail saves + if ( zoomValue < minMag ) { + zoomValue = minMag; + } + graph.setSliderZoom(zoomValue); + t_zoomOut = requestAnimationFrame(timed_zoomOut); + } + + function timed_zoomIn(){ + zoomValue = 1.02 * zoomValue; + // fail saves + if ( zoomValue > maxMag ) { + zoomValue = maxMag; + } + graph.setSliderZoom(zoomValue); + t_zoomIn = requestAnimationFrame(timed_zoomIn); + } + + zoomSlider.setup = function (){ + slider = d3.select("#zoomSliderParagraph").append("input") + .datum({}) + .attr("id", "zoomSliderElement") + .attr("type", "range") + .attr("value", defZoom) + .attr("min", minMag) + .attr("max", maxMag) + .attr("step", (maxMag - minMag) / 40) + .attr("title", "zoom factor") + .on("input", function (){ + zoomSlider.zooming(); + }); + + d3.select("#zoomOutButton").on("mousedown", function (){ + graph.options().navigationMenu().hideAllMenus(); + zoomValue = graph.scaleFactor(); + t_zoomOut = requestAnimationFrame(timed_zoomOut); + }) + .on("touchstart", function (){ + graph.options().navigationMenu().hideAllMenus(); + zoomValue = graph.scaleFactor(); + t_zoomOut = requestAnimationFrame(timed_zoomOut); + }) + .on("mouseup", clearAllTimers) + .on("touchend", clearAllTimers) + .on("touchcancel", clearAllTimers) + .attr("title", "zoom out"); + + d3.select("#zoomInButton").on("mousedown", function (){ + graph.options().navigationMenu().hideAllMenus(); + zoomValue = graph.scaleFactor(); + t_zoomIn = requestAnimationFrame(timed_zoomIn); + }) + .on("touchstart", function (){ + graph.options().navigationMenu().hideAllMenus(); + zoomValue = graph.scaleFactor(); + t_zoomIn = requestAnimationFrame(timed_zoomIn); + }) + .on("mouseup", clearAllTimers) + .on("touchend", clearAllTimers) + .on("touchcancel", clearAllTimers) + .attr("title", "zoom in"); + + d3.select("#centerGraphButton").on("click", function (){ + graph.options().navigationMenu().hideAllMenus(); + graph.forceRelocationEvent(); + }).attr("title", "center graph"); + + }; + + zoomSlider.showSlider = function ( val ){ + if ( !arguments.length ) return showSlider; + d3.select("#zoomSlider").classed("hidden", !val); + showSlider = val; + }; + + zoomSlider.zooming = function (){ + graph.options().navigationMenu().hideAllMenus(); + var zoomValue = slider.property("value"); + slider.attr("value", zoomValue); + graph.setSliderZoom(zoomValue); + }; + + zoomSlider.updateZoomSliderValue = function ( val ){ + if ( slider ) { + slider.attr("value", val); + slider.property("value", val); + } + }; + + return zoomSlider; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 338: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for the sidebar. + * @param graph the graph that belongs to these controls + * @returns {{}} + */ + module.exports = function ( graph ){ + + var sidebar = {}, + languageTools = webvowl.util.languageTools(), + elementTools = webvowl.util.elementTools(), + // Required for reloading when the language changes + ontologyInfo, + visibleSidebar = 1, + lastSelectedElement, + + detailArea = d3.select("#detailsArea"), + graphArea = d3.select("#canvasArea"), + menuArea = d3.select("#swipeBarContainer"), + collapseButton = d3.select("#sidebarExpandButton"); + + /** + * Setup the menu bar. + */ + + + function setupCollapsing(){ + // adapted version of this example: http://www.normansblog.de/simple-jquery-accordion/ + function collapseContainers( containers ){ + containers.classed("hidden", true); + } + + function expandContainers( containers ){ + containers.classed("hidden", false); + } + + var triggers = d3.selectAll(".accordion-trigger"); + + // Collapse all inactive triggers on startup + collapseContainers(d3.selectAll(".accordion-trigger:not(.accordion-trigger-active) + div")); + + triggers.on("click", function (){ + var selectedTrigger = d3.select(this), + activeTriggers = d3.selectAll(".accordion-trigger-active"); + + if ( selectedTrigger.classed("accordion-trigger-active") ) { + // Collapse the active (which is also the selected) trigger + collapseContainers(d3.select(selectedTrigger.node().nextElementSibling)); + selectedTrigger.classed("accordion-trigger-active", false); + } else { + // Collapse the other trigger ... + collapseContainers(d3.selectAll(".accordion-trigger-active + div")); + activeTriggers.classed("accordion-trigger-active", false); + // ... and expand the selected one + expandContainers(d3.select(selectedTrigger.node().nextElementSibling)); + selectedTrigger.classed("accordion-trigger-active", true); + } + }); + } + + sidebar.clearOntologyInformation = function (){ + + d3.select("#title").text("No title available"); + d3.select("#about").attr("href", "#").attr("target", "_blank").text("not given"); + d3.select("#version").text("--"); + d3.select("#authors").text("--"); + d3.select("#description").text("No description available."); + var container = d3.select("#ontology-metadata"); + container.selectAll("*").remove(); + d3.select("#classCount") + .text("0"); + d3.select("#objectPropertyCount") + .text("0"); + d3.select("#datatypePropertyCount") + .text("0"); + d3.select("#individualCount") + .text("0"); + d3.select("#nodeCount") + .text("0"); + d3.select("#edgeCount") + .text("0"); + + // clear selectedNode info + var isTriggerActive = d3.select("#selection-details-trigger").classed("accordion-trigger-active"); + if ( isTriggerActive ) { + // close accordion + d3.select("#selection-details-trigger").node().click(); + } + showSelectionAdvice(); + + }; + + /** + * Updates the information of the passed ontology. + * @param data the graph data + * @param statistics the statistics module + */ + sidebar.updateOntologyInformation = function ( data, statistics ){ + data = data || {}; + ontologyInfo = data.header || {}; + + updateGraphInformation(); + displayGraphStatistics(undefined, statistics); + displayMetadata(ontologyInfo.other); + + // Reset the sidebar selection + sidebar.updateSelectionInformation(undefined); + + setLanguages(ontologyInfo.languages); + }; + + function setLanguages( languages ){ + languages = languages || []; + + // Put the default and unset label on top of the selection labels + languages.sort(function ( a, b ){ + if ( a === webvowl.util.constants().LANG_IRIBASED ) { + return -1; + } else if ( b === webvowl.util.constants().LANG_IRIBASED ) { + return 1; + } + if ( a === webvowl.util.constants().LANG_UNDEFINED ) { + return -1; + } else if ( b === webvowl.util.constants().LANG_UNDEFINED ) { + return 1; + } + return a.localeCompare(b); + }); + + var languageSelection = d3.select("#language") + .on("change", function (){ + graph.language(d3.event.target.value); + updateGraphInformation(); + sidebar.updateSelectionInformation(lastSelectedElement); + }); + + languageSelection.selectAll("option").remove(); + languageSelection.selectAll("option") + .data(languages) + .enter().append("option") + .attr("value", function ( d ){ + return d; + }) + .text(function ( d ){ + return d; + }); + + if ( !trySelectDefaultLanguage(languageSelection, languages, "en") ) { + if ( !trySelectDefaultLanguage(languageSelection, languages, webvowl.util.constants().LANG_UNDEFINED) ) { + trySelectDefaultLanguage(languageSelection, languages, webvowl.util.constants().LANG_IRIBASED); + } + } + } + + function trySelectDefaultLanguage( selection, languages, language ){ + var langIndex = languages.indexOf(language); + if ( langIndex >= 0 ) { + selection.property("selectedIndex", langIndex); + graph.language(language); + return true; + } + + return false; + } + + function updateGraphInformation(){ + var title = languageTools.textInLanguage(ontologyInfo.title, graph.language()); + d3.select("#title").text(title || "No title available"); + d3.select("#about").attr("href", ontologyInfo.iri).attr("target", "_blank").text(ontologyInfo.iri); + d3.select("#version").text(ontologyInfo.version || "--"); + var authors = ontologyInfo.author; + if ( typeof authors === "string" ) { + // Stay compatible with author info as strings after change in january 2015 + d3.select("#authors").text(authors); + } else if ( authors instanceof Array ) { + d3.select("#authors").text(authors.join(", ")); + } else { + d3.select("#authors").text("--"); + } + + var description = languageTools.textInLanguage(ontologyInfo.description, graph.language()); + d3.select("#description").text(description || "No description available."); + } + + function displayGraphStatistics( deliveredMetrics, statistics ){ + // Metrics are optional and may be undefined + deliveredMetrics = deliveredMetrics || {}; + + d3.select("#classCount") + .text(deliveredMetrics.classCount || statistics.classCount()); + d3.select("#objectPropertyCount") + .text(deliveredMetrics.objectPropertyCount || statistics.objectPropertyCount()); + d3.select("#datatypePropertyCount") + .text(deliveredMetrics.datatypePropertyCount || statistics.datatypePropertyCount()); + d3.select("#individualCount") + .text(deliveredMetrics.totalIndividualCount || statistics.totalIndividualCount()); + d3.select("#nodeCount") + .text(statistics.nodeCount()); + d3.select("#edgeCount") + .text(statistics.edgeCount()); + } + + function displayMetadata( metadata ){ + var container = d3.select("#ontology-metadata"); + container.selectAll("*").remove(); + + listAnnotations(container, metadata); + + if ( container.selectAll(".annotation").size() <= 0 ) { + container.append("p").text("No annotations available."); + } + } + + function listAnnotations( container, annotationObject ){ + annotationObject = annotationObject || {}; //todo + + // Collect the annotations in an array for simpler processing + var annotations = []; + for ( var annotation in annotationObject ) { + if ( annotationObject.hasOwnProperty(annotation) ) { + annotations.push(annotationObject[annotation][0]); + } + } + + container.selectAll(".annotation").remove(); + container.selectAll(".annotation").data(annotations).enter().append("p") + .classed("annotation", true) + .classed("statisticDetails", true) + .text(function ( d ){ + return d.identifier + ":"; + }) + .append("span") + .each(function ( d ){ + appendIriLabel(d3.select(this), d.value, d.type === "iri" ? d.value : undefined); + }); + } + + /** + * Update the information of the selected node. + * @param selectedElement the selection or null if nothing is selected + */ + sidebar.updateSelectionInformation = function ( selectedElement ){ + lastSelectedElement = selectedElement; + + // Click event was prevented when dragging + if ( d3.event && d3.event.defaultPrevented ) { + return; + } + + var isTriggerActive = d3.select("#selection-details-trigger").classed("accordion-trigger-active"); + if ( selectedElement && !isTriggerActive ) { + d3.select("#selection-details-trigger").node().click(); + } else if ( !selectedElement && isTriggerActive ) { + showSelectionAdvice(); + return; + } + + if ( elementTools.isProperty(selectedElement) ) { + displayPropertyInformation(selectedElement); + } else if ( elementTools.isNode(selectedElement) ) { + displayNodeInformation(selectedElement); + } + }; + + function showSelectionAdvice(){ + setSelectionInformationVisibility(false, false, true); + } + + function setSelectionInformationVisibility( showClasses, showProperties, showAdvice ){ + d3.select("#classSelectionInformation").classed("hidden", !showClasses); + d3.select("#propertySelectionInformation").classed("hidden", !showProperties); + d3.select("#noSelectionInformation").classed("hidden", !showAdvice); + } + + function displayPropertyInformation( property ){ + showPropertyInformations(); + + setIriLabel(d3.select("#propname"), property.labelForCurrentLanguage(), property.iri()); + d3.select("#typeProp").text(property.type()); + + if ( property.inverse() !== undefined ) { + d3.select("#inverse").classed("hidden", false); + setIriLabel(d3.select("#inverse span"), property.inverse().labelForCurrentLanguage(), property.inverse().iri()); + } else { + d3.select("#inverse").classed("hidden", true); + } + + var equivalentIriSpan = d3.select("#propEquivUri"); + listNodeArray(equivalentIriSpan, property.equivalents()); + + listNodeArray(d3.select("#subproperties"), property.subproperties()); + listNodeArray(d3.select("#superproperties"), property.superproperties()); + + if ( property.minCardinality() !== undefined ) { + d3.select("#infoCardinality").classed("hidden", true); + d3.select("#minCardinality").classed("hidden", false); + d3.select("#minCardinality span").text(property.minCardinality()); + d3.select("#maxCardinality").classed("hidden", false); + + if ( property.maxCardinality() !== undefined ) { + d3.select("#maxCardinality span").text(property.maxCardinality()); + } else { + d3.select("#maxCardinality span").text("*"); + } + + } else if ( property.cardinality() !== undefined ) { + d3.select("#minCardinality").classed("hidden", true); + d3.select("#maxCardinality").classed("hidden", true); + d3.select("#infoCardinality").classed("hidden", false); + d3.select("#infoCardinality span").text(property.cardinality()); + } else { + d3.select("#infoCardinality").classed("hidden", true); + d3.select("#minCardinality").classed("hidden", true); + d3.select("#maxCardinality").classed("hidden", true); + } + + setIriLabel(d3.select("#domain"), property.domain().labelForCurrentLanguage(), property.domain().iri()); + setIriLabel(d3.select("#range"), property.range().labelForCurrentLanguage(), property.range().iri()); + + displayAttributes(property.attributes(), d3.select("#propAttributes")); + + setTextAndVisibility(d3.select("#propDescription"), property.descriptionForCurrentLanguage()); + setTextAndVisibility(d3.select("#propComment"), property.commentForCurrentLanguage()); + + listAnnotations(d3.select("#propertySelectionInformation"), property.annotations()); + } + + function showPropertyInformations(){ + setSelectionInformationVisibility(false, true, false); + } + + function setIriLabel( element, name, iri ){ + var parent = d3.select(element.node().parentNode); + + if ( name ) { + element.selectAll("*").remove(); + appendIriLabel(element, name, iri); + parent.classed("hidden", false); + } else { + parent.classed("hidden", true); + } + } + + function appendIriLabel( element, name, iri ){ + var tag; + + if ( iri ) { + tag = element.append("a") + .attr("href", iri) + .attr("title", iri) + .attr("target", "_blank"); + } else { + tag = element.append("span"); + } + tag.text(name); + } + + function displayAttributes( attributes, textSpan ){ + var spanParent = d3.select(textSpan.node().parentNode); + + if ( attributes && attributes.length > 0 ) { + // Remove redundant redundant attributes for sidebar + removeElementFromArray("object", attributes); + removeElementFromArray("datatype", attributes); + removeElementFromArray("rdf", attributes); + } + + if ( attributes && attributes.length > 0 ) { + textSpan.text(attributes.join(", ")); + + spanParent.classed("hidden", false); + } else { + spanParent.classed("hidden", true); + } + } + + function removeElementFromArray( element, array ){ + var index = array.indexOf(element); + if ( index > -1 ) { + array.splice(index, 1); + } + } + + function displayNodeInformation( node ){ + showClassInformations(); + + setIriLabel(d3.select("#name"), node.labelForCurrentLanguage(), node.iri()); + + /* Equivalent stuff. */ + var equivalentIriSpan = d3.select("#classEquivUri"); + listNodeArray(equivalentIriSpan, node.equivalents()); + + d3.select("#typeNode").text(node.type()); + listNodeArray(d3.select("#individuals"), node.individuals()); + + /* Disjoint stuff. */ + var disjointNodes = d3.select("#disjointNodes"); + var disjointNodesParent = d3.select(disjointNodes.node().parentNode); + + if ( node.disjointWith() !== undefined ) { + disjointNodes.selectAll("*").remove(); + + node.disjointWith().forEach(function ( element, index ){ + if ( index > 0 ) { + disjointNodes.append("span").text(", "); + } + appendIriLabel(disjointNodes, element.labelForCurrentLanguage(), element.iri()); + }); + + disjointNodesParent.classed("hidden", false); + } else { + disjointNodesParent.classed("hidden", true); + } + + displayAttributes(node.attributes(), d3.select("#classAttributes")); + + setTextAndVisibility(d3.select("#nodeDescription"), node.descriptionForCurrentLanguage()); + setTextAndVisibility(d3.select("#nodeComment"), node.commentForCurrentLanguage()); + + listAnnotations(d3.select("#classSelectionInformation"), node.annotations()); + } + + function showClassInformations(){ + setSelectionInformationVisibility(true, false, false); + } + + function listNodeArray( textSpan, nodes ){ + var spanParent = d3.select(textSpan.node().parentNode); + + if ( nodes && nodes.length ) { + textSpan.selectAll("*").remove(); + nodes.forEach(function ( element, index ){ + if ( index > 0 ) { + textSpan.append("span").text(", "); + } + appendIriLabel(textSpan, element.labelForCurrentLanguage(), element.iri()); + }); + + spanParent.classed("hidden", false); + } else { + spanParent.classed("hidden", true); + } + } + + function setTextAndVisibility( label, value ){ + var parentNode = d3.select(label.node().parentNode); + var hasValue = !!value; + if ( value ) { + label.text(value); + } + parentNode.classed("hidden", !hasValue); + } + + /** Collapsible Sidebar functions; **/ + + sidebar.showSidebar = function ( val, init ){ + // make val to bool + if ( val === 1 ) { + visibleSidebar = true; + collapseButton.node().innerHTML = ">"; + detailArea.classed("hidden", true); + if ( init === true ) { + detailArea.classed("hidden", !visibleSidebar); + graphArea.style("width", "78%"); + graphArea.style("-webkit-animation-name", "none"); + + menuArea.style("width", "78%"); + menuArea.style("-webkit-animation-name", "none"); + + d3.select("#WarningErrorMessagesContainer").style("width", "78%"); + d3.select("#WarningErrorMessagesContainer").style("-webkit-animation-name", "none"); + } else { + graphArea.style("width", "78%"); + graphArea.style("-webkit-animation-name", "sbCollapseAnimation"); + graphArea.style("-webkit-animation-duration", "0.5s"); + + menuArea.style("width", "78%"); + menuArea.style("-webkit-animation-name", "sbCollapseAnimation"); + menuArea.style("-webkit-animation-duration", "0.5s"); + + d3.select("#WarningErrorMessagesContainer").style("width", "78%"); + d3.select("#WarningErrorMessagesContainer").style("-webkit-animation-name", "warn_ExpandRightBarAnimation"); + d3.select("#WarningErrorMessagesContainer").style("-webkit-animation-duration", "0.5s"); + } + graph.options().width(window.innerWidth - (window.innerWidth * 0.22)); + graph.options().navigationMenu().updateScrollButtonVisibility(); + } + if ( val === 0 ) { + visibleSidebar = false; + detailArea.classed("hidden", true); + + collapseButton.node().innerHTML = "<"; + // adjust the layout + if ( init === true ) { + graphArea.style("width", "100%"); + graphArea.style("-webkit-animation-name", "none"); + + menuArea.style("width", "100%"); + menuArea.style("-webkit-animation-name", "none"); + + d3.select("#WarningErrorMessagesContainer").style("width", "100%"); + d3.select("#WarningErrorMessagesContainer").style("-webkit-animation-name", "none"); + } else { + graphArea.style("width", "100%"); + graphArea.style("-webkit-animation-name", "sbExpandAnimation"); + graphArea.style("-webkit-animation-duration", "0.5s"); + + menuArea.style("width", "100%"); + menuArea.style("-webkit-animation-name", "sbExpandAnimation"); + menuArea.style("-webkit-animation-duration", "0.5s"); + + d3.select("#WarningErrorMessagesContainer").style("width", "100%"); + d3.select("#WarningErrorMessagesContainer").style("-webkit-animation-name", "warn_CollapseRightBarAnimation"); + d3.select("#WarningErrorMessagesContainer").style("-webkit-animation-duration", "0.5s"); + + } + graph.options().width(window.innerWidth); + graph.updateCanvasContainerSize(); + graph.options().navigationMenu().updateScrollButtonVisibility(); + } + }; + + sidebar.isSidebarVisible = function (){ + return visibleSidebar; + }; + + sidebar.updateSideBarVis = function ( init ){ + var vis = sidebar.getSidebarVisibility(); + sidebar.showSidebar(parseInt(vis), init); + }; + + sidebar.getSidebarVisibility = function (){ + var isHidden = detailArea.classed("hidden"); + if ( isHidden === false ) return String(1); + if ( isHidden === true ) return String(0); + }; + + sidebar.initSideBarAnimation = function (){ + graphArea.node().addEventListener("animationend", function (){ + detailArea.classed("hidden", !visibleSidebar); + graph.updateCanvasContainerSize(); + graph.options().navigationMenu().updateScrollButtonVisibility(); + }); + }; + + sidebar.setup = function (){ + setupCollapsing(); + sidebar.initSideBarAnimation(); + + collapseButton.on("click", function (){ + graph.options().navigationMenu().hideAllMenus(); + var settingValue = parseInt(sidebar.getSidebarVisibility()); + if ( settingValue === 1 ) sidebar.showSidebar(0); + else sidebar.showSidebar(1); + }); + }; + + + sidebar.updateShowedInformation = function (){ + var editMode = graph.editorMode(); + d3.select("#generalDetails").classed("hidden", editMode); + d3.select("#generalDetailsEdit").classed("hidden", !editMode); + + // store the meta information in graph.options() + + // todo: update edit meta info + graph.options().editSidebar().updateGeneralOntologyInfo(); + + // todo: update showed meta info; + graph.options().sidebar().updateGeneralOntologyInfo(); + + }; + + sidebar.updateGeneralOntologyInfo = function (){ + // get it from graph.options + var generalMetaObj = graph.options().getGeneralMetaObject(); + var preferredLanguage = graph && graph.language ? graph.language() : null; + if ( generalMetaObj.hasOwnProperty("title") ) { + // title has language to it -.- + if ( typeof generalMetaObj.title === "object" ) { + d3.select("#title").node().value = languageTools.textInLanguage(generalMetaObj.title, preferredLanguage); + } else { + d3.select("#title").node().innerHTML = generalMetaObj.title; + } + + } + if ( generalMetaObj.hasOwnProperty("iri") ) d3.select("#about").node().innerHTML = generalMetaObj.iri; + if ( generalMetaObj.hasOwnProperty("iri") ) d3.select("#about").node().href = generalMetaObj.iri; + if ( generalMetaObj.hasOwnProperty("version") ) d3.select("#version").node().innerHTML = generalMetaObj.version; + if ( generalMetaObj.hasOwnProperty("author") ) d3.select("#authors").node().innerHTML = generalMetaObj.author; + // this could also be an object >> + if ( generalMetaObj.hasOwnProperty("description") ) { + if ( typeof generalMetaObj.description === "object" ) { + d3.select("#description").node().innerHTML = languageTools.textInLanguage(generalMetaObj.description, preferredLanguage); + } + else { + d3.select("#description").node().innerHTML = generalMetaObj.description; + } + } + }; + + + return sidebar; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 339: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for the sidebar. + * @param graph the graph that belongs to these controls + * @returns {{}} + */ + module.exports = function ( graph ){ + + var leftSidebar = {}, + languageTools = webvowl.util.languageTools(), + elementTools = webvowl.util.elementTools(); + var collapseButton = d3.select("#leftSideBarCollapseButton"); + var visibleSidebar = 0; + var backupVisibility = 0; + var sideBarContent = d3.select("#leftSideBarContent"); + var sideBarContainer = d3.select("#containerForLeftSideBar"); + var defaultClassSelectionContainers = []; + var defaultDatatypeSelectionContainers = []; + var defaultPropertySelectionContainers = []; + + leftSidebar.setup = function (){ + setupCollapsing(); + leftSidebar.initSideBarAnimation(); + + collapseButton.on("click", function (){ + graph.options().navigationMenu().hideAllMenus(); + var settingValue = parseInt(leftSidebar.getSidebarVisibility()); + if ( settingValue === 0 ) leftSidebar.showSidebar(1); + else leftSidebar.showSidebar(0); + backupVisibility = settingValue; + }); + + setupSelectionContainers(); + d3.select("#WarningErrorMessages").node().addEventListener("animationend", function (){ + d3.select("#WarningErrorMessages").style("-webkit-animation-name", "none"); + }); + + }; + + leftSidebar.hideCollapseButton = function ( val ){ + sideBarContainer.classed("hidden", val); + }; + + + function unselectAllElements( container ){ + for ( var i = 0; i < container.length; i++ ) + container[i].classed("defaultSelected", false); + } + + function selectThisDefaultElement( element ){ + d3.select(element).classed("defaultSelected", true); + } + + function updateDefaultNameInAccordion( element, identifier ){ + var elementDescription = ""; + if ( identifier === "defaultClass" ) elementDescription = "Class: "; + if ( identifier === "defaultDatatype" ) elementDescription = "Datatype: "; + if ( identifier === "defaultProperty" ) elementDescription = "Property: "; + + d3.select("#" + identifier).node().innerHTML = elementDescription + element.innerHTML; + d3.select("#" + identifier).node().title = element.innerHTML; + } + + function classSelectorFunction(){ + unselectAllElements(defaultClassSelectionContainers); + selectThisDefaultElement(this); + updateDefaultNameInAccordion(this, "defaultClass"); + } + + function datatypeSelectorFunction(){ + unselectAllElements(defaultDatatypeSelectionContainers); + selectThisDefaultElement(this); + updateDefaultNameInAccordion(this, "defaultDatatype"); + } + + function propertySelectorFunction(){ + unselectAllElements(defaultPropertySelectionContainers); + selectThisDefaultElement(this); + updateDefaultNameInAccordion(this, "defaultProperty"); + } + + + function setupSelectionContainers(){ + var classContainer = d3.select("#classContainer"); + var datatypeContainer = d3.select("#datatypeContainer"); + var propertyContainer = d3.select("#propertyContainer"); + // create the supported elements + + var defaultClass = "owl:Class"; + var defaultDatatype = "rdfs:Literal"; + var defaultProperty = "owl:objectProperty"; + + var supportedClasses = graph.options().supportedClasses(); + var supportedDatatypes = graph.options().supportedDatatypes(); + var supportedProperties = graph.options().supportedProperties(); + var i; + + for ( i = 0; i < supportedClasses.length; i++ ) { + var aClassSelectionContainer; + aClassSelectionContainer = classContainer.append("div"); + aClassSelectionContainer.classed("containerForDefaultSelection", true); + aClassSelectionContainer.classed("noselect", true); + aClassSelectionContainer.node().id = "selectedClass" + supportedClasses[i]; + aClassSelectionContainer.node().innerHTML = supportedClasses[i]; + + if ( supportedClasses[i] === defaultClass ) { + selectThisDefaultElement(aClassSelectionContainer.node()); + } + aClassSelectionContainer.on("click", classSelectorFunction); + defaultClassSelectionContainers.push(aClassSelectionContainer); + } + + for ( i = 0; i < supportedDatatypes.length; i++ ) { + var aDTSelectionContainer = datatypeContainer.append("div"); + aDTSelectionContainer.classed("containerForDefaultSelection", true); + aDTSelectionContainer.classed("noselect", true); + aDTSelectionContainer.node().id = "selectedDatatype" + supportedDatatypes[i]; + aDTSelectionContainer.node().innerHTML = supportedDatatypes[i]; + + if ( supportedDatatypes[i] === defaultDatatype ) { + selectThisDefaultElement(aDTSelectionContainer.node()); + } + aDTSelectionContainer.on("click", datatypeSelectorFunction); + defaultDatatypeSelectionContainers.push(aDTSelectionContainer); + } + for ( i = 0; i < supportedProperties.length; i++ ) { + var aPropSelectionContainer = propertyContainer.append("div"); + aPropSelectionContainer.classed("containerForDefaultSelection", true); + aPropSelectionContainer.classed("noselect", true); + aPropSelectionContainer.node().id = "selectedClass" + supportedProperties[i]; + aPropSelectionContainer.node().innerHTML = supportedProperties[i]; + aPropSelectionContainer.on("click", propertySelectorFunction); + if ( supportedProperties[i] === defaultProperty ) { + selectThisDefaultElement(aPropSelectionContainer.node()); + } + defaultPropertySelectionContainers.push(aPropSelectionContainer); + } + } + + function setupCollapsing(){ + // adapted version of this example: http://www.normansblog.de/simple-jquery-accordion/ + function collapseContainers( containers ){ + containers.classed("hidden", true); + } + + function expandContainers( containers ){ + containers.classed("hidden", false); + } + + var triggers = d3.selectAll(".accordion-trigger"); + + // Collapse all inactive triggers on startup + // collapseContainers(d3.selectAll(".accordion-trigger:not(.accordion-trigger-active) + div")); + + triggers.on("click", function (){ + var selectedTrigger = d3.select(this); + if ( selectedTrigger.classed("accordion-trigger-active") ) { + // Collapse the active (which is also the selected) trigger + collapseContainers(d3.select(selectedTrigger.node().nextElementSibling)); + selectedTrigger.classed("accordion-trigger-active", false); + } else { + // Collapse the other trigger ... + // collapseContainers(d3.selectAll(".accordion-trigger-active + div")); + // activeTriggers.classed("accordion-trigger-active", false); + // ... and expand the selected one + expandContainers(d3.select(selectedTrigger.node().nextElementSibling)); + selectedTrigger.classed("accordion-trigger-active", true); + } + }); + } + + + leftSidebar.isSidebarVisible = function (){ + return visibleSidebar; + }; + + leftSidebar.updateSideBarVis = function ( init ){ + var vis = leftSidebar.getSidebarVisibility(); + leftSidebar.showSidebar(parseInt(vis), init); + }; + + leftSidebar.initSideBarAnimation = function (){ + sideBarContainer.node().addEventListener("animationend", function (){ + sideBarContent.classed("hidden", !visibleSidebar); + if ( visibleSidebar === true ) { + sideBarContainer.style("width", "200px"); + sideBarContent.classed("hidden", false); + d3.select("#leftSideBarCollapseButton").style("left", "200px"); + d3.select("#leftSideBarCollapseButton").classed("hidden", false); + d3.select("#WarningErrorMessages").style("left", "100px"); + } + else { + sideBarContainer.style("width", "0px"); + d3.select("#leftSideBarCollapseButton").style("left", "0px"); + d3.select("#WarningErrorMessages").style("left", "0px"); + d3.select("#leftSideBarCollapseButton").classed("hidden", false); + + } + graph.updateCanvasContainerSize(); + graph.options().navigationMenu().updateScrollButtonVisibility(); + }); + }; + + leftSidebar.showSidebar = function ( val, init ){ + // make val to bool + var collapseButton = d3.select("#leftSideBarCollapseButton"); + if ( init === true ) { + visibleSidebar = (backupVisibility === 0); + sideBarContent.classed("hidden", !visibleSidebar); + sideBarContainer.style("-webkit-animation-name", "none"); + d3.select("#WarningErrorMessages").style("-webkit-animation-name", "none"); + if ( visibleSidebar === true ) { + sideBarContainer.style("width", "200px"); + sideBarContent.classed("hidden", false); + d3.select("#leftSideBarCollapseButton").style("left", "200px"); + d3.select("#leftSideBarCollapseButton").classed("hidden", false); + d3.select("#WarningErrorMessages").style("left", "100px"); + collapseButton.node().innerHTML = "<"; + } + + else { + sideBarContainer.style("width", "0px"); + d3.select("#WarningErrorMessages").style("left", "0px"); + d3.select("#leftSideBarCollapseButton").style("left", "0px"); + d3.select("#leftSideBarCollapseButton").classed("hidden", false); + collapseButton.node().innerHTML = ">"; + } + + graph.updateCanvasContainerSize(); + graph.options().navigationMenu().updateScrollButtonVisibility(); + return; + } + + d3.select("#leftSideBarCollapseButton").classed("hidden", true); + + if ( val === 1 ) { + visibleSidebar = true; + collapseButton.node().innerHTML = "<"; + // call expand animation; + sideBarContainer.style("-webkit-animation-name", "l_sbExpandAnimation"); + sideBarContainer.style("-webkit-animation-duration", "0.5s"); + // prepare the animation; + + d3.select("#WarningErrorMessages").style("-webkit-animation-name", "warn_ExpandLeftBarAnimation"); + d3.select("#WarningErrorMessages").style("-webkit-animation-duration", "0.5s"); + + } + if ( val === 0 ) { + visibleSidebar = false; + sideBarContent.classed("hidden", true); + collapseButton.node().innerHTML = ">"; + // call collapse animation + sideBarContainer.style("-webkit-animation-name", "l_sbCollapseAnimation"); + sideBarContainer.style("-webkit-animation-duration", "0.5s"); + d3.select("#WarningErrorMessages").style("-webkit-animation-name", "warn_CollapseLeftBarAnimation"); + d3.select("#WarningErrorMessages").style("-webkit-animation-duration", "0.5s"); + d3.select("#WarningErrorMessages").style("left", "0"); + } + + }; + + leftSidebar.getSidebarVisibility = function (){ + var isHidden = sideBarContent.classed("hidden"); + if ( isHidden === false ) return String(1); + if ( isHidden === true ) return String(0); + }; + + return leftSidebar; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 340: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for the sidebar. + * @param graph the graph that belongs to these controls + * @returns {{}} + */ + module.exports = function ( graph ){ + + var editSidebar = {}, + languageTools = webvowl.util.languageTools(), + elementTools = webvowl.util.elementTools(); + + var prefixModule = webvowl.util.prefixTools(graph); + var selectedElementForCharacteristics; + var oldPrefix, oldPrefixURL; + var prefix_editMode = false; + + + editSidebar.clearMetaObjectValue = function (){ + d3.select("#titleEditor").node().value = ""; + d3.select("#iriEditor").node().value = ""; + d3.select("#versionEditor").node().value = ""; + d3.select("#authorsEditor").node().value = ""; + d3.select("#descriptionEditor").node().value = ""; + // todo add clear description; + }; + + + editSidebar.updatePrefixUi = function (){ + editSidebar.updateElementWidth(); + var prefixListContainer = d3.select("#prefixURL_Container"); + while ( prefixListContainer.node().firstChild ) { + prefixListContainer.node().removeChild(prefixListContainer.node().firstChild); + } + setupPrefixList(); + }; + + editSidebar.setup = function (){ + setupCollapsing(); + setupPrefixList(); + setupAddPrefixButton(); + setupSupportedDatatypes(); + + + d3.select("#titleEditor") + .on("change", function (){ + graph.options().addOrUpdateGeneralObjectEntry("title", d3.select("#titleEditor").node().value); + }) + .on("keydown", function (){ + d3.event.stopPropagation(); + if ( d3.event.keyCode === 13 ) { + d3.event.preventDefault(); + graph.options().addOrUpdateGeneralObjectEntry("title", d3.select("#titleEditor").node().value); + } + }); + d3.select("#iriEditor") + .on("change", function (){ + if ( graph.options().addOrUpdateGeneralObjectEntry("iri", d3.select("#iriEditor").node().value) === false ) { + // restore value + d3.select("#iriEditor").node().value = graph.options().getGeneralMetaObjectProperty('iri'); + } + }) + .on("keydown", function (){ + d3.event.stopPropagation(); + if ( d3.event.keyCode === 13 ) { + d3.event.preventDefault(); + if ( graph.options().addOrUpdateGeneralObjectEntry("iri", d3.select("#iriEditor").node().value) === false ) { + // restore value + d3.select("#iriEditor").node().value = graph.options().getGeneralMetaObjectProperty('iri'); + } + } + }); + d3.select("#versionEditor") + .on("change", function (){ + graph.options().addOrUpdateGeneralObjectEntry("version", d3.select("#versionEditor").node().value); + }) + .on("keydown", function (){ + d3.event.stopPropagation(); + if ( d3.event.keyCode === 13 ) { + d3.event.preventDefault(); + graph.options().addOrUpdateGeneralObjectEntry("version", d3.select("#versionEditor").node().value); + } + }); + d3.select("#authorsEditor") + .on("change", function (){ + graph.options().addOrUpdateGeneralObjectEntry("author", d3.select("#authorsEditor").node().value); + }) + .on("keydown", function (){ + d3.event.stopPropagation(); + if ( d3.event.keyCode === 13 ) { + d3.event.preventDefault(); + graph.options().addOrUpdateGeneralObjectEntry("author", d3.select("#authorsEditor").node().value); + } + }); + d3.select("#descriptionEditor") + .on("change", function (){ + graph.options().addOrUpdateGeneralObjectEntry("description", d3.select("#descriptionEditor").node().value); + }); + + editSidebar.updateElementWidth(); + + }; + + function setupSupportedDatatypes(){ + var datatypeEditorSelection = d3.select("#typeEditor_datatype").node(); + var supportedDatatypes = ["undefined", "xsd:boolean", "xsd:double", "xsd:integer", "xsd:string"]; + for ( var i = 0; i < supportedDatatypes.length; i++ ) { + var optB = document.createElement('option'); + optB.innerHTML = supportedDatatypes[i]; + datatypeEditorSelection.appendChild(optB); + } + } + + function highlightDeleteButton( enable, name ){ + var deletePath = d3.select("#del_pathFor_" + name); + var deleteRect = d3.select("#del_rectFor_" + name); + + if ( enable === false ) { + deletePath.node().style = "stroke: #f00;"; + deleteRect.style("cursor", "auto"); + } else { + deletePath.node().style = "stroke: #ff972d;"; + deleteRect.style("cursor", "pointer"); + } + } + + + function highlightEditButton( enable, name, fill ){ + var editPath = d3.select("#pathFor_" + name); + var editRect = d3.select("#rectFor_" + name); + + if ( enable === false ) { + if ( fill ) + editPath.node().style = "fill: #fff; stroke : #fff; stroke-width : 1px"; + else + editPath.node().style = " stroke : #fff; stroke-width : 1px"; + + editRect.style("cursor", "auto"); + } else { + if ( fill ) + editPath.node().style = "fill: #ff972d; stroke : #ff972d; stroke-width : 1px"; + else + editPath.node().style = "stroke : #ff972d; stroke-width : 1px"; + editRect.style("cursor", "pointer"); + } + + } + + function setupAddPrefixButton(){ + var btn = d3.select("#addPrefixButton"); + btn.on("click", function (){ + + // check if we are still in editMode? + if ( prefix_editMode === false ) { + // create new line entry; + var name = "emptyPrefixEntry"; + var prefixListContainer = d3.select("#prefixURL_Container"); + var prefixEditContainer = prefixListContainer.append("div"); + prefixEditContainer.classed("prefixIRIElements", true); + prefixEditContainer.node().id = "prefixContainerFor_" + name; + + var IconContainer = prefixEditContainer.append("div"); + IconContainer.style("position", "absolute"); + IconContainer.node().id = "containerFor_" + name; + var editButton = IconContainer.append("svg"); + editButton.style("width", "14px"); + editButton.style("height", "20px"); + // editButton.classed("editPrefixButton", true); + editButton.classed("noselect", true); + //editButton.node().innerHTML = "\u2714"; + editButton.node().id = "editButtonFor_" + name; + + editButton.node().elementStyle = "save"; + editButton.node().selectorName = name; + var editIcon = editButton.append("g"); + var editRect = editIcon.append("rect"); + var editPath = editIcon.append("path"); + editIcon.node().id = "iconFor_" + name; + editPath.node().id = "pathFor_" + name; + editRect.node().id = "rectFor_" + name; + + editIcon.node().selectorName = name; + editPath.node().selectorName = name; + editRect.node().selectorName = name; + IconContainer.node().title = "Save new prefix and IRI"; + + editPath.classed("editPrefixIcon"); + editPath.style("stroke", "#fff"); + editPath.style("stroke-width", "1px"); + editPath.style("fill", "#fff"); + editRect.attr("width", "14px"); + editRect.attr("height", "14px"); + editRect.style("fill", "#18202A"); + editRect.attr("transform", "matrix(1,0,0,1,-3,4)"); + + editButton.selectAll("g").on("mouseover", function (){ + highlightEditButton(true, this.selectorName, true); + }); + editButton.selectAll("g").on("mouseout", function (){ + highlightEditButton(false, this.selectorName, true); + }); + // Check mark + // M9 16.2L4.8 12l-1.4 1.4L9 19 21 7l-1.4-1.4L9 16.2z + // pencil + // M3 17.25V21h3.75L17.81 9.94l-3.75-3.75L3 17.25zM20.71 7.04c.39-.39.39-1.02 0-1.41l-2.34-2.34c-.39-.39-1.02-.39-1.41 0l-1.83 1.83 3.75 3.75 1.83-1.83z + editPath.attr("d", "M9 16.2L4.8 12l-1.4 1.4L9 19 21 7l-1.4-1.4L9 16.2z"); + editPath.attr("transform", "matrix(0.45,0,0,0.45,0,5)"); + + var prefInput = prefixEditContainer.append("input"); + prefInput.classed("prefixInput", true); + prefInput.node().type = "text"; + prefInput.node().id = "prefixInputFor_" + name; + prefInput.node().autocomplete = "off"; + prefInput.node().value = ""; + prefInput.style("margin-left", "14px"); + + var prefURL = prefixEditContainer.append("input"); + prefURL.classed("prefixURL", true); + prefURL.node().type = "text"; + prefURL.node().id = "prefixURLFor_" + name; + prefURL.node().autocomplete = "off"; + prefURL.node().value = ""; + + prefInput.node().disabled = false; + prefURL.node().disabled = false; + prefix_editMode = true; + var deleteContainer = prefixEditContainer.append("div"); + deleteContainer.style("float", "right"); + var deleteButton = deleteContainer.append("svg"); + deleteButton.node().id = "deleteButtonFor_" + name; + deleteContainer.node().title = "Delete prefix and IRI"; + deleteButton.style("width", "10px"); + deleteButton.style("height", "20px"); + var deleteIcon = deleteButton.append("g"); + var deleteRect = deleteIcon.append("rect"); + var deletePath = deleteIcon.append("path"); + deleteIcon.node().id = "del_iconFor_" + name; + deletePath.node().id = "del_pathFor_" + name; + deleteRect.node().id = "del_rectFor_" + name; + + deleteIcon.node().selectorName = name; + deletePath.node().selectorName = name; + deleteRect.node().selectorName = name; + + + deletePath.style("stroke", "#f00"); + deleteRect.attr("width", "10px"); + deleteRect.attr("height", "14px"); + deleteRect.style("fill", "#18202A"); + deleteRect.attr("transform", "matrix(1,0,0,1,-3,4)"); + + + deletePath.attr("d", "M19 6.41L17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12z"); + deletePath.attr("transform", "matrix(0.45,0,0,0.45,0,5)"); + + deleteButton.selectAll("g").on("mouseover", function (){ + highlightDeleteButton(true, this.selectorName); + }); + deleteButton.selectAll("g").on("mouseout", function (){ + highlightDeleteButton(false, this.selectorName); + }); + + + // connect the buttons; + editButton.on("click", enablePrefixEdit); + deleteButton.on("click", deletePrefixLine); + + editSidebar.updateElementWidth(); + // swap focus to prefixInput + prefInput.node().focus(); + oldPrefix = name; + oldPrefixURL = ""; + d3.select("#addPrefixButton").node().innerHTML = "Save Prefix"; + } else { + d3.select("#editButtonFor_emptyPrefixEntry").on("click")(d3.select("#editButtonFor_emptyPrefixEntry").node()); + } + + }); + + } + + function setupPrefixList(){ + if ( graph.isEditorMode() === false ) return; + var prefixListContainer = d3.select("#prefixURL_Container"); + var prefixElements = graph.options().prefixList(); + for ( var name in prefixElements ) { + if ( prefixElements.hasOwnProperty(name) ) { + var prefixEditContainer = prefixListContainer.append("div"); + prefixEditContainer.classed("prefixIRIElements", true); + prefixEditContainer.node().id = "prefixContainerFor_" + name; + + // create edit button which enables the input fields + var IconContainer = prefixEditContainer.append("div"); + IconContainer.style("position", "absolute"); + IconContainer.node().id = "containerFor_" + name; + var editButton = IconContainer.append("svg"); + editButton.style("width", "14px"); + editButton.style("height", "20px"); + editButton.classed("noselect", true); + editButton.node().id = "editButtonFor_" + name; + IconContainer.node().title = "Edit prefix and IRI"; + editButton.node().elementStyle = "save"; + editButton.node().selectorName = name; + + editButton.node().id = "editButtonFor_" + name; + editButton.node().elementStyle = "edit"; + var editIcon = editButton.append("g"); + var editRect = editIcon.append("rect"); + var editPath = editIcon.append("path"); + editIcon.node().id = "iconFor_" + name; + editPath.node().id = "pathFor_" + name; + editRect.node().id = "rectFor_" + name; + + editIcon.node().selectorName = name; + editPath.node().selectorName = name; + editRect.node().selectorName = name; + + + editPath.classed("editPrefixIcon"); + editPath.style("stroke", "#fff"); + editPath.style("stroke-width", "1px"); + editRect.attr("width", "14px"); + editRect.attr("height", "14px"); + editRect.style("fill", "#18202A"); + editRect.attr("transform", "matrix(1,0,0,1,-3,4)"); + + editButton.selectAll("g").on("mouseover", function (){ + var sender = this; + var fill = false; + var enable = true; + var f_editPath = d3.select("#pathFor_" + sender.selectorName); + var f_editRect = d3.select("#rectFor_" + sender.selectorName); + + if ( enable === false ) { + if ( fill ) + f_editPath.node().style = "fill: #fff; stroke : #fff; stroke-width : 1px"; + else + f_editPath.node().style = " stroke : #fff; stroke-width : 1px"; + + f_editRect.style("cursor", "auto"); + } else { + if ( fill ) + f_editPath.node().style = "fill: #ff972d; stroke : #ff972d; stroke-width : 1px"; + else + f_editPath.node().style = "stroke : #ff972d; stroke-width : 1px"; + f_editRect.style("cursor", "pointer"); + } + }); + editButton.selectAll("g").on("mouseout", function (){ + var sender = this; + var fill = false; + var enable = false; + var f_editPath = d3.select("#pathFor_" + sender.selectorName); + var f_editRect = d3.select("#rectFor_" + sender.selectorName); + + if ( enable === false ) { + if ( fill ) + f_editPath.node().style = "fill: #fff; stroke : #fff; stroke-width : 1px"; + else + f_editPath.node().style = " stroke : #fff; stroke-width : 1px"; + + f_editRect.style("cursor", "auto"); + } else { + if ( fill ) + f_editPath.node().style = "fill: #ff972d; stroke : #ff972d; stroke-width : 1px"; + else + f_editPath.node().style = "stroke : #ff972d; stroke-width : 1px"; + f_editRect.style("cursor", "pointer"); + } + }); + + editPath.attr("d", "M3 17.25V21h3.75L17.81 9.94l-3.75-3.75L3 17.25zM20.71 7.04c.39-.39.39-1.02 0-1.41l-2.34-2.34c-.39-.39-1.02-.39-1.41 0l-1.83 1.83 3.75 3.75 1.83-1.83z"); + editPath.attr("transform", "matrix(-0.45,0,0,0.45,10,5)"); + + // create input field for prefix + var prefInput = prefixEditContainer.append("input"); + prefInput.classed("prefixInput", true); + prefInput.node().type = "text"; + prefInput.node().id = "prefixInputFor_" + name; + prefInput.node().autocomplete = "off"; + prefInput.node().value = name; + prefInput.style("margin-left", "14px"); + + // create input field for prefix url + var prefURL = prefixEditContainer.append("input"); + prefURL.classed("prefixURL", true); + prefURL.node().type = "text"; + prefURL.node().id = "prefixURLFor_" + name; + prefURL.node().autocomplete = "off"; + prefURL.node().value = prefixElements[name]; + prefURL.node().title = prefixElements[name]; + // disable the input fields (already defined elements can be edited later) + prefInput.node().disabled = true; + prefURL.node().disabled = true; + + // create the delete button + var deleteContainer = prefixEditContainer.append("div"); + deleteContainer.style("float", "right"); + var deleteButton = deleteContainer.append("svg"); + deleteButton.node().id = "deleteButtonFor_" + name; + deleteContainer.node().title = "Delete prefix and IRI"; + deleteButton.style("width", "10px"); + deleteButton.style("height", "20px"); + var deleteIcon = deleteButton.append("g"); + var deleteRect = deleteIcon.append("rect"); + var deletePath = deleteIcon.append("path"); + deleteIcon.node().id = "del_iconFor_" + name; + deletePath.node().id = "del_pathFor_" + name; + deleteRect.node().id = "del_rectFor_" + name; + + deleteIcon.node().selectorName = name; + deletePath.node().selectorName = name; + deleteRect.node().selectorName = name; + + + deletePath.style("stroke", "#f00"); + deleteRect.attr("width", "10px"); + deleteRect.attr("height", "14px"); + deleteRect.style("fill", "#18202A"); + deleteRect.attr("transform", "matrix(1,0,0,1,-3,4)"); + + + deletePath.attr("d", "M19 6.41L17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12z"); + deletePath.attr("transform", "matrix(0.45,0,0,0.45,0,5)"); + + deleteButton.selectAll("g").on("mouseover", function (){ + var selector = this; + var enable = true; + var f_deletePath = d3.select("#del_pathFor_" + selector.selectorName); + var f_deleteRect = d3.select("#del_rectFor_" + selector.selectorName); + + if ( enable === false ) { + f_deletePath.node().style = "stroke: #f00;"; + f_deleteRect.style("cursor", "auto"); + } else { + f_deletePath.node().style = "stroke: #ff972d;"; + f_deleteRect.style("cursor", "pointer"); + } + }); + deleteButton.selectAll("g").on("mouseout", function (){ + var selector = this; + var enable = false; + var f_deletePath = d3.select("#del_pathFor_" + selector.selectorName); + var f_deleteRect = d3.select("#del_rectFor_" + selector.selectorName); + + if ( enable === false ) { + f_deletePath.node().style = "stroke: #f00;"; + f_deleteRect.style("cursor", "auto"); + } else { + f_deletePath.node().style = "stroke: #ff972d;"; + f_deleteRect.style("cursor", "pointer"); + } + }); + + + editButton.on("click", enablePrefixEdit); + deleteButton.on("click", deletePrefixLine); + + // EXPERIMENTAL + + if ( name === "rdf" || + name === "rdfs" || + name === "xsd" || name === "dc" || + name === "owl" + ) { + // make them invis so the spacing does not change + IconContainer.classed("hidden", true); + deleteContainer.classed("hidden", true); + } + } + } + prefixModule.updatePrefixModel(); + } + + function deletePrefixLine(){ + if ( this.disabled === true ) return; + d3.select("#addPrefixButton").node().innerHTML = "Add Prefix"; + var selector = this.id.split("_")[1]; + d3.select("#prefixContainerFor_" + selector).remove(); + graph.options().removePrefix(selector); + prefix_editMode = false; // < 0 ) { + var basePref = graph.options().prefixList()[pr]; + if ( basePref === undefined ) { + console.log("ERROR __________________"); + graph.options().warningModule().showWarning("Invalid Element IRI", + "Could not resolve prefix '" + basePref + "'", + "Restoring previous IRI for Element" + element.iri(), 1, false); + d3.select("#element_iriEditor").node().value = element.iri(); + return; + + } + // check if url is not empty + + if ( name.length === 0 ) { + graph.options().warningModule().showWarning("Invalid Element IRI", + "Input IRI is EMPTY", + "Restoring previous IRI for Element" + element.iri(), 1, false); + console.log("NO INPUT PROVIDED"); + d3.select("#element_iriEditor").node().value = element.iri(); + return; + + } + url = basePref + name; + } + else { + url = base + name; + } + } else { + if ( url.length === 0 ) { + // + console.log("NO INPUT PROVIDED"); + d3.select("#element_iriEditor").node().value = element.iri(); + return; + } + // failed to identify anything useful + console.log("Tryig to use the input!"); + url = base + url; + } + } + return url; + } + + function changeIriForElement( element ){ + var url = getURLFROMPrefixedVersion(element); + var base = graph.options().getGeneralMetaObjectProperty("iri"); + var sanityCheckResult; + if ( elementTools.isNode(element) ) { + + sanityCheckResult = graph.checkIfIriClassAlreadyExist(url); + if ( sanityCheckResult === false ) { + element.iri(url); + } else { + // throw warnign + graph.options().warningModule().showWarning("Already seen this class", + "Input IRI: " + url + " for element: " + element.labelForCurrentLanguage() + " already been set", + "Restoring previous IRI for Element : " + element.iri(), 2, false, sanityCheckResult); + + editSidebar.updateSelectionInformation(element); + return; + + } + } + if ( elementTools.isProperty(element) === true ) { + sanityCheckResult = editSidebar.checkProperIriChange(element, url); + if ( sanityCheckResult !== false ) { + graph.options().warningModule().showWarning("Already seen this property", + "Input IRI: " + url + " for element: " + element.labelForCurrentLanguage() + " already been set", + "Restoring previous IRI for Element : " + element.iri(), 1, false, sanityCheckResult); + + editSidebar.updateSelectionInformation(element); + return; + } + } + + // if (element.existingPropertyIRI(url)===true){ + // console.log("I Have seen this Particular URL already "+url); + // graph.options().warningModule().showWarning("Already Seen This one ", + // "Input IRI For Element"+ element.labelForCurrentLanguage()+" already been set ", + // "Restoring previous IRI for Element"+element.iri(),1,false); + // d3.select("#element_iriEditor").node().value=graph.options().prefixModule().getPrefixRepresentationForFullURI(element.iri()); + // editSidebar.updateSelectionInformation(element); + // return; + // } + + element.iri(url); + if ( identifyExternalCharacteristicForElement(base, url) === true ) { + addAttribute(element, "external"); + // background color for external element; + element.backgroundColor("#36C"); + element.redrawElement(); + element.redrawLabelText(); + // handle visual selection + + } else { + removeAttribute(element, "external"); + // background color for external element; + element.backgroundColor(undefined); + element.redrawElement(); + element.redrawLabelText(); + + } + + if ( element.focused() ) { + graph.options().focuserModule().handle(element, true); // unfocus + graph.options().focuserModule().handle(element, true); // focus + } + // graph.options().focuserModule().handle(undefined); + + + d3.select("#element_iriEditor").node().value = prefixModule.getPrefixRepresentationForFullURI(url); + editSidebar.updateSelectionInformation(element); + } + + function validURL( str ){ + var urlregex = /^(https?|ftp):\/\/([a-zA-Z0-9.-]+(:[a-zA-Z0-9.&%$-]+)*@)*((25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9][0-9]?)(\.(25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9]?[0-9])){3}|([a-zA-Z0-9-]+\.)*[a-zA-Z0-9-]+\.(com|edu|gov|int|mil|net|org|biz|arpa|info|name|pro|aero|coop|museum|[a-zA-Z]{2}))(:[0-9]+)*(\/($|[a-zA-Z0-9.,?'\\+&%$#=~_-]+))*$/; + return urlregex.test(str); + } + + + function changeLabelForElement( element ){ + element.label(d3.select("#element_labelEditor").node().value); + element.redrawLabelText(); + } + + editSidebar.updateEditDeleteButtonIds = function ( oldPrefix, newPrefix ){ + d3.select("#prefixInputFor_" + oldPrefix).node().id = "prefixInputFor_" + newPrefix; + d3.select("#prefixURLFor_" + oldPrefix).node().id = "prefixURLFor_" + newPrefix; + d3.select("#deleteButtonFor_" + oldPrefix).node().id = "deleteButtonFor_" + newPrefix; + d3.select("#editButtonFor_" + oldPrefix).node().id = "editButtonFor_" + newPrefix; + + d3.select("#prefixContainerFor_" + oldPrefix).node().id = "prefixContainerFor_" + newPrefix; + }; + + editSidebar.checkForExistingURL = function ( url ){ + var i; + var allProps = graph.getUnfilteredData().properties; + for ( i = 0; i < allProps.length; i++ ) { + if ( allProps[i].iri() === url ) return true; + } + return false; + + }; + editSidebar.checkProperIriChange = function ( element, url ){ + console.log("Element changed Label"); + console.log("Testing URL " + url); + if ( element.type() === "rdfs:subClassOf" || element.type() === "owl:disjointWith" ) { + console.log("ignore this for now, already handled in the type and domain range changer"); + } else { + var i; + var allProps = graph.getUnfilteredData().properties; + for ( i = 0; i < allProps.length; i++ ) { + if ( allProps[i] === element ) continue; + if ( allProps[i].iri() === url ) return allProps[i]; + } + } + return false; + }; + + editSidebar.updateSelectionInformation = function ( element ){ + + if ( element === undefined ) { + // show hint; + d3.select("#selectedElementProperties").classed("hidden", true); + d3.select("#selectedElementPropertiesEmptyHint").classed("hidden", false); + selectedElementForCharacteristics = null; + editSidebar.updateElementWidth(); + } + else { + d3.select("#selectedElementProperties").classed("hidden", false); + d3.select("#selectedElementPropertiesEmptyHint").classed("hidden", true); + d3.select("#typeEditForm_datatype").classed("hidden", true); + + // set the element IRI, and labels + d3.select("#element_iriEditor").node().value = element.iri(); + d3.select("#element_labelEditor").node().value = element.labelForCurrentLanguage(); + d3.select("#element_iriEditor").node().title = element.iri(); + + d3.select("#element_iriEditor") + .on("change", function (){ + var elementIRI = element.iri(); + var prefixed = graph.options().prefixModule().getPrefixRepresentationForFullURI(elementIRI); + if ( prefixed === d3.select("#element_iriEditor").node().value ) { + console.log("Iri is identical, nothing has changed!"); + return; + } + + changeIriForElement(element); + }) + .on("keydown", function (){ + d3.event.stopPropagation(); + if ( d3.event.keyCode === 13 ) { + d3.event.preventDefault(); + console.log("IRI CHANGED Via ENTER pressed"); + changeIriForElement(element); + d3.select("#element_iriEditor").node().title = element.iri(); + } + }); + + var forceIRISync = defaultIriValue(element); + d3.select("#element_labelEditor") + .on("change", function (){ + var sanityCheckResult; + console.log("Element changed Label"); + var url = getURLFROMPrefixedVersion(element); + if ( element.iri() !== url ) { + if ( elementTools.isProperty(element) === true ) { + sanityCheckResult = editSidebar.checkProperIriChange(element, url); + if ( sanityCheckResult !== false ) { + graph.options().warningModule().showWarning("Already seen this property", + "Input IRI: " + url + " for element: " + element.labelForCurrentLanguage() + " already been set", + "Continuing with duplicate property!", 1, false, sanityCheckResult); + editSidebar.updateSelectionInformation(element); + return; + } + } + + if ( elementTools.isNode(element) === true ) { + sanityCheckResult = graph.checkIfIriClassAlreadyExist(url); + if ( sanityCheckResult !== false ) { + graph.options().warningModule().showWarning("Already seen this Class", + "Input IRI: " + url + " for element: " + element.labelForCurrentLanguage() + " already been set", + "Restoring previous IRI for Element : " + element.iri(), 2, false, sanityCheckResult); + + editSidebar.updateSelectionInformation(element); + return; + } + } + element.iri(url); + } + changeLabelForElement(element); + editSidebar.updateSelectionInformation(element); // prevents that it will be changed if node is still active + }) + .on("keydown", function (){ + d3.event.stopPropagation(); + if ( d3.event.keyCode === 13 ) { + d3.event.preventDefault(); + var sanityCheckResult; + console.log("Element changed Label"); + var url = getURLFROMPrefixedVersion(element); + if ( element.iri() !== url ) { + if ( elementTools.isProperty(element) === true ) { + sanityCheckResult = editSidebar.checkProperIriChange(element, url); + if ( sanityCheckResult !== false ) { + graph.options().warningModule().showWarning("Already seen this property", + "Input IRI: " + url + " for element: " + element.labelForCurrentLanguage() + " already been set", + "Continuing with duplicate property!", 1, false, sanityCheckResult); + + editSidebar.updateSelectionInformation(element); + return; + } + } + + if ( elementTools.isNode(element) === true ) { + sanityCheckResult = graph.checkIfIriClassAlreadyExist(url); + if ( sanityCheckResult !== false ) { + graph.options().warningModule().showWarning("Already seen this Class", + "Input IRI: " + url + " for element: " + element.labelForCurrentLanguage() + " already been set", + "Restoring previous IRI for Element : " + element.iri(), 2, false, sanityCheckResult); + + editSidebar.updateSelectionInformation(element); + return; + } + } + element.iri(url); + } + changeLabelForElement(element); + } + }) + .on("keyup", function (){ + if ( forceIRISync ) { + var labelName = d3.select("#element_labelEditor").node().value; + var resourceName = labelName.replaceAll(" ", "_"); + var syncedIRI = element.baseIri() + resourceName; + + //element.iri(syncedIRI); + d3.select("#element_iriEditor").node().title = element.iri(); + d3.select("#element_iriEditor").node().value = prefixModule.getPrefixRepresentationForFullURI(syncedIRI); + } + }); + // check if we are allowed to change IRI OR LABEL + d3.select("#element_iriEditor").node().disabled = false; + d3.select("#element_labelEditor").node().disabled = false; + + if ( element.type() === "rdfs:subClassOf" ) { + d3.select("#element_iriEditor").node().value = "http://www.w3.org/2000/01/rdf-schema#subClassOf"; + d3.select("#element_iriEditor").node().title = "http://www.w3.org/2000/01/rdf-schema#subClassOf"; + d3.select("#element_labelEditor").node().value = "Subclass of"; + d3.select("#element_iriEditor").node().disabled = true; + d3.select("#element_labelEditor").node().disabled = true; + } + if ( element.type() === "owl:Thing" ) { + d3.select("#element_iriEditor").node().value = "http://www.w3.org/2002/07/owl#Thing"; + d3.select("#element_iriEditor").node().title = "http://www.w3.org/2002/07/owl#Thing"; + d3.select("#element_labelEditor").node().value = "Thing"; + d3.select("#element_iriEditor").node().disabled = true; + d3.select("#element_labelEditor").node().disabled = true; + } + + if ( element.type() === "owl:disjointWith" ) { + d3.select("#element_iriEditor").node().value = "http://www.w3.org/2002/07/owl#disjointWith"; + d3.select("#element_iriEditor").node().title = "http://www.w3.org/2002/07/owl#disjointWith"; + d3.select("#element_iriEditor").node().disabled = true; + d3.select("#element_labelEditor").node().disabled = true; + } + + if ( element.type() === "rdfs:Literal" ) { + d3.select("#element_iriEditor").node().value = "http://www.w3.org/2000/01/rdf-schema#Literal"; + d3.select("#element_iriEditor").node().title = "http://www.w3.org/2000/01/rdf-schema#Literal"; + d3.select("#element_iriEditor").node().disabled = true; + d3.select("#element_labelEditor").node().disabled = true; + element.iri("http://www.w3.org/2000/01/rdf-schema#Literal"); + } + if ( element.type() === "rdfs:Datatype" ) { + var datatypeEditorSelection = d3.select("#typeEditor_datatype"); + d3.select("#typeEditForm_datatype").classed("hidden", false); + element.iri("http://www.w3.org/2000/01/rdf-schema#Datatype"); + d3.select("#element_iriEditor").node().value = "http://www.w3.org/2000/01/rdf-schema#Datatype"; + d3.select("#element_iriEditor").node().title = "http://www.w3.org/2000/01/rdf-schema#Datatype"; + d3.select("#element_iriEditor").node().disabled = true; + d3.select("#element_labelEditor").node().disabled = true; + + datatypeEditorSelection.node().value = element.dType(); + if ( datatypeEditorSelection.node().value === "undefined" ) { + d3.select("#element_iriEditor").node().disabled = true; // always prevent IRI modifications + d3.select("#element_labelEditor").node().disabled = false; + } + // reconnect the element + datatypeEditorSelection.on("change", function (){ + changeDatatypeType(element); + }); + } + + // add type selector + var typeEditorSelection = d3.select("#typeEditor").node(); + var htmlCollection = typeEditorSelection.children; + var numEntries = htmlCollection.length; + var i; + var elementPrototypes = getElementPrototypes(element); + for ( i = 0; i < numEntries; i++ ) + typeEditorSelection.removeChild(htmlCollection[0]); + + for ( i = 0; i < elementPrototypes.length; i++ ) { + var optA = document.createElement('option'); + optA.innerHTML = elementPrototypes[i]; + typeEditorSelection.appendChild(optA); + } + // set the proper value in the selection + typeEditorSelection.value = element.type(); + d3.select("#typeEditor").on("change", function (){ + elementTypeSelectionChanged(element); + }); + + + // add characteristics selection + var needChar = elementNeedsCharacteristics(element); + d3.select("#property_characteristics_Container").classed("hidden", !needChar); + if ( needChar === true ) { + addElementsCharacteristics(element); + } + var fullURI = d3.select("#element_iriEditor").node().value; + d3.select("#element_iriEditor").node().value = prefixModule.getPrefixRepresentationForFullURI(fullURI); + d3.select("#element_iriEditor").node().title = fullURI; + editSidebar.updateElementWidth(); + } + + }; + + editSidebar.updateGeneralOntologyInfo = function (){ + var preferredLanguage = graph && graph.language ? graph.language() : null; + + // get it from graph.options + var generalMetaObj = graph.options().getGeneralMetaObject(); + if ( generalMetaObj.hasOwnProperty("title") ) { + // title has language to it -.- + if ( typeof generalMetaObj.title === "object" ) { + d3.select("#titleEditor").node().value = languageTools.textInLanguage(generalMetaObj.title, preferredLanguage); + } else + d3.select("#titleEditor").node().value = generalMetaObj.title; + } + if ( generalMetaObj.hasOwnProperty("iri") ) d3.select("#iriEditor").node().value = generalMetaObj.iri; + if ( generalMetaObj.hasOwnProperty("version") ) d3.select("#versionEditor").node().value = generalMetaObj.version; + if ( generalMetaObj.hasOwnProperty("author") ) d3.select("#authorsEditor").node().value = generalMetaObj.author; + + + if ( generalMetaObj.hasOwnProperty("description") ) { + + if ( typeof generalMetaObj.description === "object" ) + d3.select("#descriptionEditor").node().value = + languageTools.textInLanguage(generalMetaObj.description, preferredLanguage); + else + d3.select("#descriptionEditor").node().value = generalMetaObj.description; + } + else + d3.select("#descriptionEditor").node().value = "No Description"; + }; + + editSidebar.updateElementWidth = function (){ + var height = window.innerHeight - 40; + var lsb_offset = d3.select("#logo").node().getBoundingClientRect().height + 5; + var lsb_height = height - lsb_offset; + d3.select("#containerForLeftSideBar").style("top", lsb_offset + "px"); + d3.select("#leftSideBarCollapseButton").style("top", lsb_offset + "px"); + d3.select("#containerForLeftSideBar").style("height", lsb_height + "px"); + + var div_width = d3.select("#generalDetailsEdit").node().getBoundingClientRect().width; + div_width += 10; + + var title_labelWidth = d3.select("#titleEditor-label").node().getBoundingClientRect().width + 20; + var iri_labelWidth = d3.select("#iriEditor-label").node().getBoundingClientRect().width + 20; + var version_labelWidth = d3.select("#versionEditor-label").node().getBoundingClientRect().width + 20; + var author_labelWidth = d3.select("#authorsEditor-label").node().getBoundingClientRect().width + 20; + //find max width; + var maxW = 0; + maxW = Math.max(maxW, title_labelWidth); + maxW = Math.max(maxW, iri_labelWidth); + maxW = Math.max(maxW, version_labelWidth); + maxW = Math.max(maxW, author_labelWidth); + + var meta_inputWidth = div_width - maxW - 10; + + d3.select("#titleEditor").style("width", meta_inputWidth + "px"); + d3.select("#iriEditor").style("width", meta_inputWidth + "px"); + d3.select("#versionEditor").style("width", meta_inputWidth + "px"); + d3.select("#authorsEditor").style("width", meta_inputWidth + "px"); + + + var elementIri_width = d3.select("#element_iriEditor-label").node().getBoundingClientRect().width + 20; + var elementLabel_width = d3.select("#element_labelEditor-label").node().getBoundingClientRect().width + 20; + var elementType_width = d3.select("#typeEditor-label").node().getBoundingClientRect().width + 20; + var elementDType_width = d3.select("#typeEditor_datatype-label").node().getBoundingClientRect().width + 20; + + maxW = 0; + maxW = Math.max(maxW, elementIri_width); + maxW = Math.max(maxW, elementLabel_width); + maxW = Math.max(maxW, elementType_width); + maxW = Math.max(maxW, elementDType_width); + var selectedElement_inputWidth = div_width - maxW - 10; + + d3.select("#element_iriEditor").style("width", selectedElement_inputWidth + "px"); + d3.select("#element_labelEditor").style("width", selectedElement_inputWidth + "px"); + d3.select("#typeEditor").style("width", selectedElement_inputWidth + 4 + "px"); + d3.select("#typeEditor_datatype").style("width", selectedElement_inputWidth + 4 + "px"); + + // update prefix Element width; + var containerWidth = d3.select("#containerForPrefixURL").node().getBoundingClientRect().width; + if ( containerWidth !== 0 ) { + var inputs = d3.selectAll(".prefixInput"); + if ( inputs.node() ) { + var prefixWidth = d3.selectAll(".prefixInput").node().getBoundingClientRect().width; + d3.selectAll(".prefixURL").style("width", containerWidth - prefixWidth - 45 + "px"); + } + } + }; + + function addElementsCharacteristics( element ){ + // save selected element for checkbox handler + selectedElementForCharacteristics = element; + var i; + // KILL old elements + var charSelectionNode = d3.select("#property_characteristics_Selection"); + var htmlCollection = charSelectionNode.node().children; + if ( htmlCollection ) { + var numEntries = htmlCollection.length; + for ( var q = 0; q < numEntries; q++ ) { + charSelectionNode.node().removeChild(htmlCollection[0]); + } + } + // datatypes kind of ignored by the elementsNeedCharacteristics function + // so we need to check if we are a node or not + if ( element.attributes().indexOf("external") > -1 ) { + // add external span to the div; + var externalCharSpan = charSelectionNode.append("span"); + externalCharSpan.classed("spanForCharSelection", true); + externalCharSpan.node().innerHTML = "external"; + } + var filterContainer, + filterCheckbox; + if ( elementTools.isNode(element) === true ) { + // add the deprecated characteristic; + var arrayOfNodeChars = ["deprecated"]; + for ( i = 0; i < arrayOfNodeChars.length; i++ ) { + filterContainer = charSelectionNode + .append("div") + .classed("checkboxContainer", true) + .style("padding-top", "2px"); + + filterCheckbox = filterContainer.append("input") + .classed("filterCheckbox", true) + .attr("id", "CharacteristicsCheckbox" + i) + .attr("type", "checkbox") + .attr("characteristics", arrayOfNodeChars[i]) + .property("checked", getPresentAttribute(element, arrayOfNodeChars[i])); + // + filterContainer.append("label") + .attr("for", "CharacteristicsCheckbox" + i) + .text(arrayOfNodeChars[i]); + + filterCheckbox.on("click", handleCheckBoxClick); + + } + } + + else { + // add the deprecated characteristic; + var arrayOfPropertyChars = ["deprecated", "inverse functional", "functional", "transitive"]; + if ( elementTools.isDatatypeProperty(element) === true ) { + arrayOfPropertyChars = ["deprecated", "functional"]; + } + for ( i = 0; i < arrayOfPropertyChars.length; i++ ) { + filterContainer = charSelectionNode + .append("div") + .classed("checkboxContainer", true) + .style("padding-top", "2px"); + + filterCheckbox = filterContainer.append("input") + .classed("filterCheckbox", true) + .attr("id", "CharacteristicsCheckbox" + i) + .attr("type", "checkbox") + .attr("characteristics", arrayOfPropertyChars[i]) + .property("checked", getPresentAttribute(element, arrayOfPropertyChars[i])); + // + filterContainer.append("label") + .attr("for", "CharacteristicsCheckbox" + i) + .text(arrayOfPropertyChars[i]); + + filterCheckbox.on("click", handleCheckBoxClick); + + } + } + + + } + + function getPresentAttribute( selectedElement, element ){ + return (selectedElement.attributes().indexOf(element) >= 0); + } + + function handleCheckBoxClick(){ + var checked = this.checked; + var char = this.getAttribute("characteristics"); + if ( checked === true ) { + addAttribute(selectedElementForCharacteristics, char); + } else { + removeAttribute(selectedElementForCharacteristics, char); + } + // graph.executeColorExternalsModule(); + selectedElementForCharacteristics.redrawElement(); + // workaround to have the node still be focused as rendering element + selectedElementForCharacteristics.focused(false); + selectedElementForCharacteristics.toggleFocus(); + + } + + + function addAttribute( selectedElement, char ){ + if ( selectedElement.attributes().indexOf(char) === -1 ) { + // not found add it + var attr = selectedElement.attributes(); + attr.push(char); + selectedElement.attributes(attr); + }// indications string update; + if ( selectedElement.indications().indexOf(char) === -1 ) { + var indications = selectedElement.indications(); + indications.push(char); + selectedElement.indications(indications); + } + // add visual attributes + var visAttr; + if ( selectedElement.visualAttributes().indexOf(char) === -1 ) { + visAttr = selectedElement.visualAttributes(); + visAttr.push(char); + selectedElement.visualAttributes(visAttr); + } + if ( getPresentAttribute(selectedElement, "external") && getPresentAttribute(selectedElement, "deprecated") ) { + visAttr = selectedElement.visualAttributes(); + var visInd = visAttr.indexOf("external"); + if ( visInd > -1 ) { + visAttr.splice(visInd, 1); + } + selectedElement.visualAttributes(visAttr); + } + + } + + function removeAttribute( selectedElement, element ){ + var attr = selectedElement.attributes(); + var indications = selectedElement.indications(); + var visAttr = selectedElement.visualAttributes(); + var attrInd = attr.indexOf(element); + if ( attrInd >= 0 ) { + attr.splice(attrInd, 1); + } + var indInd = indications.indexOf(element); + if ( indInd > -1 ) { + indications.splice(indInd, 1); + } + var visInd = visAttr.indexOf(element); + if ( visInd > -1 ) { + visAttr.splice(visInd, 1); + } + selectedElement.attributes(attr); + selectedElement.indications(indications); + selectedElement.visualAttributes(visAttr); + if ( element === "deprecated" ) { + // set its to its original Style + //typeBaseThign + // todo : fix all different types + if ( selectedElement.type() === "owl:Class" ) selectedElement.styleClass("class"); + if ( selectedElement.type() === "owl:DatatypeProperty" ) selectedElement.styleClass("datatypeproperty"); + if ( selectedElement.type() === "owl:ObjectProperty" ) selectedElement.styleClass("objectproperty"); + if ( selectedElement.type() === "owl:disjointWith" ) selectedElement.styleClass("disjointwith"); + } + } + + + function elementNeedsCharacteristics( element ){ + //TODO: Add more types + if ( element.type() === "owl:Thing" || + element.type() === "rdfs:subClassOf" || + element.type() === "rdfs:Literal" || + element.type() === "rdfs:Datatype" || + element.type() === "rdfs:disjointWith" ) + return false; + + // if (element.attributes().indexOf("external")|| + // element.attributes().indexOf("deprecated")) + // return true; + return true; + + } + + function elementTypeSelectionChanged( element ){ + if ( elementTools.isNode(element) ) { + if ( graph.changeNodeType(element) === false ) { + //restore old value + + if ( elementTools.isDatatype(element) === true ) { + + } + editSidebar.updateSelectionInformation(element); + } + } + + if ( elementTools.isProperty(element) ) { + if ( graph.changePropertyType(element) === false ) { + //restore old value + editSidebar.updateSelectionInformation(element); + + } + } + + } + + function getElementPrototypes( selectedElement ){ + var availiblePrototypes = []; + // TODO the text should be also complied with the prefixes loaded into the ontology + if ( elementTools.isProperty(selectedElement) ) { + if ( selectedElement.type() === "owl:DatatypeProperty" ) + availiblePrototypes.push("owl:DatatypeProperty"); + else { + availiblePrototypes.push("owl:ObjectProperty"); + // handling loops ! + if ( selectedElement.domain() !== selectedElement.range() ) { + availiblePrototypes.push("rdfs:subClassOf"); + } + availiblePrototypes.push("owl:disjointWith"); + availiblePrototypes.push("owl:allValuesFrom"); + availiblePrototypes.push("owl:someValuesFrom"); + } + return availiblePrototypes; + } + if ( selectedElement.renderType() === "rect" ) { + availiblePrototypes.push("rdfs:Literal"); + availiblePrototypes.push("rdfs:Datatype"); + } else { + availiblePrototypes.push("owl:Class"); + availiblePrototypes.push("owl:Thing"); + // TODO: ADD MORE TYPES + // availiblePrototypes.push("owl:complementOf"); + // availiblePrototypes.push("owl:disjointUnionOf"); + } + return availiblePrototypes; + } + + + function setupCollapsing(){ + // TODO : Decision , for now I want to have the control over the collapse expand operation of the + // TODO : elements, otherwise the old approach will also randomly collapse other containers + + // adapted version of this example: http://www.normansblog.de/simple-jquery-accordion/ + function collapseContainers( containers ){ + containers.classed("hidden", true); + } + + function expandContainers( containers ){ + containers.classed("hidden", false); + } + + var triggers = d3.selectAll(".accordion-trigger"); + + // Collapse all inactive triggers on startup + // collapseContainers(d3.selectAll(".accordion-trigger:not(.accordion-trigger-active) + div")); + + triggers.on("click", function (){ + var selectedTrigger = d3.select(this); + if ( selectedTrigger.classed("accordion-trigger-active") ) { + // Collapse the active (which is also the selected) trigger + collapseContainers(d3.select(selectedTrigger.node().nextElementSibling)); + selectedTrigger.classed("accordion-trigger-active", false); + } else { + // Collapse the other trigger ... + // collapseContainers(d3.selectAll(".accordion-trigger-active + div")); + + // ... and expand the selected one + expandContainers(d3.select(selectedTrigger.node().nextElementSibling)); + selectedTrigger.classed("accordion-trigger-active", true); + } + editSidebar.updateElementWidth(); + }); + } + + return editSidebar; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 341: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( graph ){ + var configMenu = {}, + checkboxes = []; + + + configMenu.setup = function (){ + var menuEntry = d3.select("#m_modes"); + menuEntry.on("mouseover", function (){ + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + }); + + addCheckBox("showZoomSlider", "Zoom controls", "#zoomSliderOption", graph.options().zoomSlider().showSlider, 0); + addLabelWidthSlider("#maxLabelWidthSliderOption", "maxLabelWidth", "Max label width", graph.options().maxLabelWidth); + }; + + + function addLabelWidthSlider( selector, identifier, label, onChangeFunction ){ + var sliderContainer, + sliderValueLabel; + + sliderContainer = d3.select(selector) + .append("div") + .classed("distanceSliderContainer", true); + + var slider = sliderContainer.append("input") + .attr("id", identifier + "Slider") + .attr("type", "range") + .attr("min", 20) + .attr("max", 600) + .attr("value", onChangeFunction()) + .attr("step", 10); + sliderContainer.append("label") + .classed("description", true) + .attr("for", identifier + "Slider") + .attr("id", identifier + "DescriptionLabel") + .text(label); + sliderValueLabel = sliderContainer.append("label") + .classed("value", true) + .attr("for", identifier + "Slider") + .attr("id", identifier + "valueLabel") + .text(onChangeFunction()); + + slider.on("input", function (){ + var value = slider.property("value"); + onChangeFunction(value); + sliderValueLabel.text(value); + if ( graph.options().dynamicLabelWidth() === true ) + graph.animateDynamicLabelWidth(); + }); + + // add wheel event to the slider + slider.on("wheel", function (){ + if ( slider.node().disabled === true ) return; + var wheelEvent = d3.event; + var offset; + if ( wheelEvent.deltaY < 0 ) offset = 10; + if ( wheelEvent.deltaY > 0 ) offset = -10; + var oldVal = parseInt(slider.property("value")); + var newSliderValue = oldVal + offset; + if ( newSliderValue !== oldVal ) { + slider.property("value", newSliderValue); + onChangeFunction(newSliderValue); + slider.on("input")(); // << set text and update the graphStyles + } + d3.event.preventDefault(); + }); + } + + function addCheckBox( identifier, modeName, selector, onChangeFunc, updateLvl ){ + var configOptionContainer = d3.select(selector) + .append("div") + .classed("checkboxContainer", true); + var configCheckbox = configOptionContainer.append("input") + .classed("moduleCheckbox", true) + .attr("id", identifier + "ConfigCheckbox") + .attr("type", "checkbox") + .property("checked", onChangeFunc()); + + + configCheckbox.on("click", function ( silent ){ + var isEnabled = configCheckbox.property("checked"); + onChangeFunc(isEnabled); + if ( silent !== true ) { + // updating graph when silent is false or the parameter is not given. + if ( updateLvl === 1 ) { + graph.lazyRefresh(); + //graph.redrawWithoutForce + } + if ( updateLvl === 2 ) { + graph.update(); + } + + if ( updateLvl === 3 ) { + graph.updateDraggerElements(); + } + } + + }); + checkboxes.push(configCheckbox); + configOptionContainer.append("label") + .attr("for", identifier + "ConfigCheckbox") + .text(modeName); + } + + configMenu.setCheckBoxValue = function ( identifier, value ){ + for ( var i = 0; i < checkboxes.length; i++ ) { + var cbdId = checkboxes[i].attr("id"); + if ( cbdId === identifier ) { + checkboxes[i].property("checked", value); + break; + } + } + }; + + configMenu.getCheckBoxValue = function ( id ){ + for ( var i = 0; i < checkboxes.length; i++ ) { + var cbdId = checkboxes[i].attr("id"); + if ( cbdId === id ) { + return checkboxes[i].property("checked"); + } + } + }; + + configMenu.updateSettings = function (){ + var silent = true; + checkboxes.forEach(function ( checkbox ){ + checkbox.on("click")(silent); + }); + }; + + return configMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 342: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( graph ){ + /** some constants **/ + var PREDEFINED = 0, + FILE_UPLOAD = 1, + JSON_URL = 2, + IRI_URL = 3; + + var PROGRESS_BAR_ERROR = 0, + PROGRESS_BAR_BUSY = 1, + PROGRESS_BAR_PERCENT = 2, + progressBarMode = 1; + + var loadingWasSuccessFul = false; + var missingImportsWarning = false; + var showLoadingDetails = false; + var visibilityStatus = true; + + var DEFAULT_JSON_NAME = "ontology"; // This file is loaded by default + var conversion_sessionId; + + /** variable defs **/ + var loadingModule = {}, + menuContainer = d3.select("#loading-info"), + loadingInfoContainer = d3.select("#loadingInfo-container"), + detailsButton = d3.select("#show-loadingInfo-button"), + closeButton = d3.select("#loadingIndicator_closeButton"), + ontologyMenu, + ontologyIdentifierFromURL; + + /** functon defs **/ + loadingModule.checkForScreenSize = function (){ + // checks for window size and adjusts the loading indicator + var w = graph.options().width(), + h = graph.options().height(); + + if ( w < 270 ) { + d3.select("#loading-info").classed("hidden", true); + } else { + // check if it should be visible + if ( visibilityStatus === true ) { + d3.select("#loading-info").classed("hidden", false); + } else { + d3.select("#loading-info").classed("hidden", true); + } + } + if ( h < 150 ) { + d3.select("#loadingInfo_msgBox").classed("hidden", true); + } else { + d3.select("#loadingInfo_msgBox").classed("hidden", false); + } + if ( h < 80 ) { + d3.select("#progressBarContext").classed("hidden", true); + d3.select("#layoutLoadingProgressBarContainer").style("height", "20px"); + } else { + d3.select("#progressBarContext").classed("hidden", false); + d3.select("#layoutLoadingProgressBarContainer").style("height", "50px"); + } + }; + + loadingModule.getMessageVisibilityStatus = function (){ + return visibilityStatus; + }; + + loadingModule.getProgressBarMode = function (){ + return progressBarMode; + }; + + loadingModule.successfullyLoadedOntology = function (){ + return loadingWasSuccessFul; + }; + + loadingModule.missingImportsWarning = function (){ + return missingImportsWarning; + }; + + loadingModule.setOntologyMenu = function ( m ){ + ontologyMenu = m; + }; + + loadingModule.showErrorDetailsMessage = function (){ + loadingModule.showLoadingIndicator(); + loadingModule.expandDetails(); + d3.select("#loadingIndicator_closeButton").classed("hidden", true); + loadingModule.scrollDownDetails(); + }; + + loadingModule.showWarningDetailsMessage = function (){ + d3.select("#currentLoadingStep").style("color", "#ff0"); + loadingModule.showLoadingIndicator(); + loadingModule.expandDetails(); + d3.select("#loadingIndicator_closeButton").classed("hidden", false); + loadingModule.scrollDownDetails(); + }; + + loadingModule.scrollDownDetails = function (){ + var scrollingElement = d3.select("#loadingInfo-container").node(); + scrollingElement.scrollTop = scrollingElement.scrollHeight; + }; + + loadingModule.hideLoadingIndicator = function (){ + d3.select("#loading-info").classed("hidden", true); + visibilityStatus = false; + }; + + loadingModule.showLoadingIndicator = function (){ + d3.select("#loading-info").classed("hidden", false); + visibilityStatus = true; + + }; + + /** -- SETUP -- **/ + loadingModule.setup = function (){ + // create connections for close and details button; + loadingInfoContainer.classed("hidden", !showLoadingDetails); + detailsButton.on("click", function (){ + showLoadingDetails = !showLoadingDetails; + loadingInfoContainer.classed("hidden", !showLoadingDetails); + detailsButton.classed("accordion-trigger-active", showLoadingDetails); + }); + + closeButton.on("click", function (){ + menuContainer.classed("hidden", true); + }); + loadingModule.setBusyMode(); + }; + + loadingModule.updateSize = function (){ + showLoadingDetails = !(loadingInfoContainer.classed("hidden")); + loadingInfoContainer.classed("hidden", !showLoadingDetails); + detailsButton.classed("accordion-trigger-active", showLoadingDetails); + }; + + loadingModule.getDetailsState = function (){ + return showLoadingDetails; + }; + + loadingModule.expandDetails = function (){ + showLoadingDetails = true; + loadingInfoContainer.classed("hidden", !showLoadingDetails); + detailsButton.classed("accordion-trigger-active", showLoadingDetails); + }; + + loadingModule.collapseDetails = function (){ + showLoadingDetails = false; + loadingInfoContainer.classed("hidden", !showLoadingDetails); + detailsButton.classed("accordion-trigger-active", showLoadingDetails); + }; + + loadingModule.setBusyMode = function (){ + d3.select("#currentLoadingStep").style("color", "#fff"); + d3.select("#progressBarValue").node().innherHTML = ""; + d3.select("#progressBarValue").style("width", "20%"); + d3.select("#progressBarValue").classed("busyProgressBar", true); + progressBarMode = PROGRESS_BAR_BUSY; + }; + + loadingModule.setSuccessful = function (){ + d3.select("#currentLoadingStep").style("color", "#0f0"); + }; + + loadingModule.setErrorMode = function (){ + d3.select("#currentLoadingStep").style("color", "#f00"); + d3.select("#progressBarValue").style("width", "0%"); + d3.select("#progressBarValue").classed("busyProgressBar", false); + d3.select("#progressBarValue").node().innherHTML = ""; + progressBarMode = PROGRESS_BAR_ERROR; + }; + + loadingModule.setPercentMode = function (){ + d3.select("#currentLoadingStep").style("color", "#fff"); + d3.select("#progressBarValue").classed("busyProgressBar", false); + d3.select("#progressBarValue").node().innherHTML = "0%"; + d3.select("#progressBarValue").style("width", "0%"); + progressBarMode = PROGRESS_BAR_PERCENT; + }; + + loadingModule.setPercentValue = function ( val ){ + d3.select("#progressBarValue").node().innherHTML = val; + }; + + loadingModule.emptyGraphContentError = function (){ + graph.clearGraphData(); + ontologyMenu.append_message_toLastBulletPoint("failed"); + ontologyMenu.append_message_toLastBulletPoint("
    Error: Received empty graph"); + loadingWasSuccessFul = false; + graph.handleOnLoadingError(); + loadingModule.setErrorMode(); + }; + + loadingModule.isThreadCanceled = function (){ + + }; + + loadingModule.initializeLoader = function ( storeCache ){ + if ( storeCache === true && graph.getCachedJsonObj() !== null ) { + // save cached ontology; + var cachedContent = JSON.stringify(graph.getCachedJsonObj()); + var cachedName = ontologyIdentifierFromURL; + ontologyMenu.setCachedOntology(cachedName, cachedContent); + } + conversion_sessionId = -10000; + ontologyMenu.setConversionID(conversion_sessionId); + ontologyMenu.stopLoadingTimer(); + graph.clearGraphData(); + loadingModule.setBusyMode(); + loadingModule.showLoadingIndicator(); + loadingModule.collapseDetails(); + missingImportsWarning = false; + d3.select("#loadingIndicator_closeButton").classed("hidden", true); + ontologyMenu.clearDetailInformation(); + }; + + /** ------------------ URL Interpreter -------------- **/ + loadingModule.parseUrlAndLoadOntology = function ( storeCache ){ + var autoStore = true; + if ( storeCache === false ) { + autoStore = false; + } + + graph.clearAllGraphData(); + loadingModule.initializeLoader(autoStore); + var urlString = String(location); + var parameterArray = identifyParameter(urlString); + ontologyIdentifierFromURL = DEFAULT_JSON_NAME; + loadGraphOptions(parameterArray); // identifies and loads configuration values + var loadingMethod = identifyOntologyLoadingMethod(ontologyIdentifierFromURL); + d3.select("#progressBarValue").node().innerHTML = " "; + switch ( loadingMethod ) { + case 0: + loadingModule.from_presetOntology(ontologyIdentifierFromURL); + break; + case 1: + loadingModule.from_FileUpload(ontologyIdentifierFromURL); + break; + case 2: + loadingModule.from_JSON_URL(ontologyIdentifierFromURL); + break; + case 3: + loadingModule.from_IRI_URL(ontologyIdentifierFromURL); + break; + default: + console.log("Could not identify loading method , or not IMPLEMENTED YET"); + } + }; + + /** ------------------- LOADING --------------------- **/ + // the loading module splits into 3 branches + // 1] PresetOntology Loading + // 2] File Upload + // 3] Load From URL / IRI + + loadingModule.from_JSON_URL = function ( fileName ){ + var filename = decodeURIComponent(fileName.slice("url=".length)); + ontologyIdentifierFromURL = filename; + + var ontologyContent = ""; + if ( ontologyMenu.cachedOntology(filename) ) { + ontologyMenu.append_bulletPoint("Loading already cached ontology: " + filename); + ontologyContent = ontologyMenu.cachedOntology(filename); + loadingWasSuccessFul = true; // cached Ontology should be true; + parseOntologyContent(ontologyContent); + + } else { + // involve the o2v conveter; + ontologyMenu.append_message("Retrieving ontology from JSON URL " + filename); + requestServerTimeStampForJSON_URL(ontologyMenu.callbackLoad_JSON_FromURL, ["read?json=" + filename, filename]); + } + }; + + function requestServerTimeStampForJSON_URL( callback, parameter ){ + d3.xhr("serverTimeStamp", "application/text", function ( error, request ){ + if ( error ) { + // could not get server timestamp -> no connection to owl2vowl + ontologyMenu.append_bulletPoint("Could not establish connection to OWL2VOWL service"); + fallbackForJSON_URL(callback, parameter); + } else { + conversion_sessionId = request.responseText; + ontologyMenu.setConversionID(conversion_sessionId); + parameter.push(conversion_sessionId); + callback(parameter); + } + }); + + } + + loadingModule.requestServerTimeStampForDirectInput = function ( callback, text ){ + d3.xhr("serverTimeStamp", "application/text", function ( error, request ){ + if ( error ) { + // could not get server timestamp -> no connection to owl2vowl + ontologyMenu.append_bulletPoint("Could not establish connection to OWL2VOWL service"); + loadingModule.setErrorMode(); + ontologyMenu.append_message_toLastBulletPoint("
    Could not connect to OWL2VOWL service "); + loadingModule.showErrorDetailsMessage(); + d3.select("#progressBarValue").style("width", "0%"); + d3.select("#progressBarValue").classed("busyProgressBar", false); + d3.select("#progressBarValue").text("0%"); + + } else { + conversion_sessionId = request.responseText; + ontologyMenu.setConversionID(conversion_sessionId); + callback(text, ["conversionID" + conversion_sessionId, conversion_sessionId]); + } + }); + }; + + loadingModule.from_IRI_URL = function ( fileName ){ + // owl2vowl converters the given ontology url and returns json file; + var filename = decodeURIComponent(fileName.slice("iri=".length)); + ontologyIdentifierFromURL = filename; + + var ontologyContent = ""; + if ( ontologyMenu.cachedOntology(filename) ) { + ontologyMenu.append_bulletPoint("Loading already cached ontology: " + filename); + ontologyContent = ontologyMenu.cachedOntology(filename); + loadingWasSuccessFul = true; // cached Ontology should be true; + parseOntologyContent(ontologyContent); + } else { + // involve the o2v conveter; + var encoded = encodeURIComponent(filename); + ontologyMenu.append_bulletPoint("Retrieving ontology from IRI: " + filename); + requestServerTimeStampForIRI_Converte(ontologyMenu.callbackLoad_Ontology_FromIRI, ["convert?iri=" + encoded, filename]); + } + }; + + loadingModule.fromFileDrop = function ( fileName, file ){ + d3.select("#progressBarValue").node().innerHTML = " "; + loadingModule.initializeLoader(false); + + ontologyMenu.append_bulletPoint("Retrieving ontology from dropped file: " + fileName); + var ontologyContent = ""; + + // two options here + //1] Direct Json Upload + if ( fileName.match(/\.json$/) ) { + ontologyMenu.setConversionID(-10000); + var reader = new FileReader(); + reader.readAsText(file); + reader.onload = function (){ + ontologyContent = reader.result; + ontologyIdentifierFromURL = fileName; + parseOntologyContent(ontologyContent); + }; + } else { + //2] File Upload to OWL2VOWL Converter + // 1) check if we can get a timeStamp; + var parameterArray = [file, fileName]; + requestServerTimeStamp(ontologyMenu.callbackLoadFromOntology, parameterArray); + } + }; + + + loadingModule.from_FileUpload = function ( fileName ){ + loadingModule.setBusyMode(); + var filename = decodeURIComponent(fileName.slice("file=".length)); + ontologyIdentifierFromURL = filename; + var ontologyContent = ""; + if ( ontologyMenu.cachedOntology(filename) ) { + ontologyMenu.append_bulletPoint("Loading already cached ontology: " + filename); + ontologyContent = ontologyMenu.cachedOntology(filename); + loadingWasSuccessFul = true; // cached Ontology should be true; + parseOntologyContent(ontologyContent); + + } else { + // d3.select("#currentLoadingStep").node().innerHTML="Loading ontology from file "+ filename; + ontologyMenu.append_bulletPoint("Retrieving ontology from file: " + filename); + // get the file + var selectedFile = d3.select("#file-converter-input").property("files")[0]; + // No selection -> this was triggered by the iri. Unequal names -> reuploading another file + if ( !selectedFile || (filename && (filename !== selectedFile.name)) ) { + ontologyMenu.append_message_toLastBulletPoint("
    No cached version of \"" + filename + "\" was found.
    Please reupload the file."); + loadingModule.setErrorMode(); + d3.select("#progressBarValue").classed("busyProgressBar", false); + graph.handleOnLoadingError(); + return; + } else { + filename = selectedFile.name; + } + + + // two options here + //1] Direct Json Upload + if ( filename.match(/\.json$/) ) { + ontologyMenu.setConversionID(-10000); + var reader = new FileReader(); + reader.readAsText(selectedFile); + reader.onload = function (){ + ontologyContent = reader.result; + ontologyIdentifierFromURL = filename; + parseOntologyContent(ontologyContent); + }; + } else { + //2] File Upload to OWL2VOWL Converter + // 1) check if we can get a timeStamp; + var parameterArray = [selectedFile, filename]; + requestServerTimeStamp(ontologyMenu.callbackLoadFromOntology, parameterArray); + } + } + }; + + function fallbackForJSON_URL( callback, parameter ){ + ontologyMenu.append_message_toLastBulletPoint("
    Trying to convert with other communication protocol."); + callback(parameter); + + } + + function fallbackConversion( parameter ){ + ontologyMenu.append_message_toLastBulletPoint("
    Trying to convert with other communication protocol."); + var file = parameter[0]; + var name = parameter[1]; + var formData = new FormData(); + formData.append("ontology", file); + + var xhr = new XMLHttpRequest(); + xhr.open("POST", "convert", true); + var ontologyContent = ""; + xhr.onload = function (){ + if ( xhr.status === 200 ) { + ontologyContent = xhr.responseText; + ontologyMenu.setCachedOntology(name, ontologyContent); + ontologyIdentifierFromURL = name; + missingImportsWarning = true; // using this variable for warnings + ontologyMenu.append_message_toLastBulletPoint("
    Success, but you are using a deprecated OWL2VOWL service!"); + parseOntologyContent(ontologyContent); + } + }; + + // check what this thing is doing; + xhr.onreadystatechange = function (){ + if ( xhr.readyState === 4 && xhr.status === 0 ) { + ontologyMenu.append_message_toLastBulletPoint("
    Old protocol also failed to establish connection to OWL2VOWL service!"); + loadingModule.setErrorMode(); + ontologyMenu.append_bulletPoint("Failed to load ontology"); + ontologyMenu.append_message_toLastBulletPoint("
    Could not connect to OWL2VOWL service "); + loadingModule.showErrorDetailsMessage(); + } + }; + xhr.send(formData); + } + + function requestServerTimeStampForIRI_Converte( callback, parameterArray ){ + d3.xhr("serverTimeStamp", "application/text", function ( error, request ){ + loadingModule.setBusyMode(); + if ( error ) { + // could not get server timestamp -> no connection to owl2vowl + ontologyMenu.append_bulletPoint("Could not establish connection to OWL2VOWL service"); + loadingModule.setErrorMode(); + ontologyMenu.append_bulletPoint("Failed to load ontology"); + ontologyMenu.append_message_toLastBulletPoint("
    Could not connect to OWL2VOWL service "); + loadingModule.showErrorDetailsMessage(); + } else { + conversion_sessionId = request.responseText; + ontologyMenu.setConversionID(conversion_sessionId); + // update paramater for new communication paradigm + parameterArray[0] = parameterArray[0] + "&sessionId=" + conversion_sessionId; + parameterArray.push(conversion_sessionId); + callback(parameterArray); + } + }); + } + + function requestServerTimeStamp( callback, parameterArray ){ + d3.xhr("serverTimeStamp", "application/text", function ( error, request ){ + if ( error ) { + // could not get server timestamp -> no connection to owl2vowl + ontologyMenu.append_bulletPoint("Could not establish connection to OWL2VOWL service"); + fallbackConversion(parameterArray); // tries o2v version0.3.4 communication + } else { + conversion_sessionId = request.responseText; + ontologyMenu.setConversionID(conversion_sessionId); + console.log("Request Session ID:" + conversion_sessionId); + callback(parameterArray[0], parameterArray[1], conversion_sessionId); + } + }); + } + + loadingModule.directInput = function ( text ){ + ontologyMenu.clearDetailInformation(); + parseOntologyContent(text); + }; + + loadingModule.loadFromOWL2VOWL = function ( ontoContent, filename ){ + loadingWasSuccessFul = false; + + var old = d3.select("#bulletPoint_container").node().innerHTML; + if ( old.indexOf("(with warnings)") !== -1 ) { + missingImportsWarning = true; + } + + if ( ontologyMenu.cachedOntology(ontoContent) ) { + ontologyMenu.append_bulletPoint("Loading already cached ontology: " + filename); + parseOntologyContent(ontoContent); + } else { // set parse the ontology content; + parseOntologyContent(ontoContent); + } + }; + + loadingModule.from_presetOntology = function ( selectedOntology ){ + ontologyMenu.append_bulletPoint("Retrieving ontology: " + selectedOntology); + loadPresetOntology(selectedOntology); + }; + + function loadPresetOntology( ontology ){ + // check if already cached in ontology menu? + var f2r; + var loadingNewOntologyForEditor=false; + if ( ontology.indexOf("new_ontology") !== -1 ) { + loadingModule.hideLoadingIndicator(); + graph.showEditorHintIfNeeded(); + f2r = "./data/new_ontology.json"; + loadingNewOntologyForEditor=true; + } + + loadingWasSuccessFul = false; + var ontologyContent = ""; + if ( ontologyMenu.cachedOntology(ontology) ) { + ontologyMenu.append_bulletPoint("Loading already cached ontology: " + ontology); + ontologyContent = ontologyMenu.cachedOntology(ontology); + loadingWasSuccessFul = true; // cached Ontology should be true; + loadingModule.showLoadingIndicator(); + parseOntologyContent(ontologyContent); + + } else { + // read the file name + + var fileToRead = "./data/" + ontology + ".json"; + if ( f2r ) { + fileToRead = f2r; + } // overwrite the newOntology Index + // read file + d3.xhr(fileToRead, "application/json", function ( error, request ){ + var loadingSuccessful = !error; + if ( loadingSuccessful ) { + ontologyContent = request.responseText; + parseOntologyContent(ontologyContent); + } else { + + if (loadingNewOntologyForEditor){ + ontologyContent = '{\n' + + ' "_comment": "Empty ontology for WebVOWL Editor",\n' + + ' "header": {\n' + + ' "languages": [\n' + + ' "en"\n' + + ' ],\n' + + ' "baseIris": [\n' + + ' "http://www.w3.org/2000/01/rdf-schema"\n' + + ' ],\n' + + ' "iri": "http://visualdataweb.org/newOntology/",\n' + + ' "title": {\n' + + ' "en": "New ontology"\n' + + ' },\n' + + ' "description": {\n' + + ' "en": "New ontology description"\n' + + ' }\n' + + ' },\n' + + ' "namespace": [],\n' + + ' "metrics": {\n' + + ' "classCount": 0,\n' + + ' "datatypeCount": 0,\n' + + ' "objectPropertyCount": 0,\n' + + ' "datatypePropertyCount": 0,\n' + + ' "propertyCount": 0,\n' + + ' "nodeCount": 0,\n' + + ' "individualCount": 0\n' + + ' }\n' + + '}\n'; + parseOntologyContent(ontologyContent); + }else{ + // some error occurred + ontologyMenu.append_bulletPoint("Failed to load: " + ontology); + if (error.status===0){ // assumption this is CORS error when running locally (error status == 0) + ontologyMenu.append_message_toLastBulletPoint(" ERROR STATUS: " + error.status); + if (window.location.toString().startsWith("file:/")){ + ontologyMenu.append_message_toLastBulletPoint("

    WebVOWL runs in a local instance.

    "); + ontologyMenu.append_message_toLastBulletPoint("

    CORS prevents to automatically load files on host system.

    "); + ontologyMenu.append_message_toLastBulletPoint("

    You can load preprocessed ontologies (i.e. VOWL-JSON files) using the upload feature in the ontology menu or by dragging the files and dropping them on the canvas.

    "); + ontologyMenu.append_message_toLastBulletPoint("

    Hint: Note that the conversion of ontologies into the VOWL-JSON format is not part of WebVOWL but requires an additional converter such as OWL2VOWL.

    "); + ontologyMenu.append_message_toLastBulletPoint("

    Ontologies can be created using the editor mode (i.e. activate editing mode in Modes menu and create a new ontology using the Ontology menu.

    "); + } + }else { + ontologyMenu.append_message_toLastBulletPoint(" ERROR STATUS: " + error.status); + } + + + + graph.handleOnLoadingError(); + loadingModule.setErrorMode(); + } + } + }); + } + } + + + /** -- PARSE JSON CONTENT -- **/ + function parseOntologyContent( content ){ + + ontologyMenu.append_bulletPoint("Reading ontology graph ... "); + var _loader = ontologyMenu.getLoadingFunction(); + _loader(content, ontologyIdentifierFromURL, "noAlternativeNameYet"); + } + + loadingModule.notValidJsonFile = function (){ + graph.clearGraphData(); + ontologyMenu.append_message_toLastBulletPoint(" failed"); + ontologyMenu.append_message_toLastBulletPoint("
    Error: Received empty graph"); + loadingWasSuccessFul = false; + graph.handleOnLoadingError(); + + }; + + loadingModule.validJsonFile = function (){ + ontologyMenu.append_message_toLastBulletPoint("done"); + loadingWasSuccessFul = true; + }; + + + /** --- HELPER FUNCTIONS **/ + + function identifyParameter( url ){ + var numParameters = (url.match(/#/g) || []).length; + // create parameters array + var paramArray = []; + if ( numParameters > 0 ) { + var tokens = url.split("#"); + // skip the first token since it is the address of the server + for ( var i = 1; i < tokens.length; i++ ) { + if ( tokens[i].length === 0 ) { + // this token belongs actually to the last paramArray + paramArray[paramArray.length - 1] = paramArray[paramArray.length - 1] + "#"; + } else { + paramArray.push(tokens[i]); + } + } + } + return paramArray; + } + + + function loadGraphOptions( parameterArray ){ + var optString = "opts="; + + function loadDefaultConfig(){ + graph.options().setOptionsFromURL(graph.options().defaultConfig(), false); + } + + function loadCustomConfig( opts ){ + var changeEditingFlag = false; + var defObj = graph.options().defaultConfig(); + for ( var i = 0; i < opts.length; i++ ) { + var keyVal = opts[i].split('='); + if ( keyVal[0] === "editorMode" ) { + changeEditingFlag = true; + } + defObj[keyVal[0]] = keyVal[1]; + } + graph.options().setOptionsFromURL(defObj, changeEditingFlag); + } + + function identifyOptions( paramArray ){ + if ( paramArray[0].indexOf(optString) >= 0 ) { + // parse the parameters; + var parameterLength = paramArray[0].length; + var givenOptionsStr = paramArray[0].substr(5, parameterLength - 6); + var optionsArray = givenOptionsStr.split(';'); + loadCustomConfig(optionsArray); + } else { + ontologyIdentifierFromURL = paramArray[0]; + loadDefaultConfig(); + } + } + + function identifyOptionsAndOntology( paramArray ){ + + if ( paramArray[0].indexOf(optString) >= 0 ) { + // parse the parameters; + var parameterLength = paramArray[0].length; + var givenOptionsStr = paramArray[0].substr(5, parameterLength - 6); + var optionsArray = givenOptionsStr.split(';'); + loadCustomConfig(optionsArray); + } else { + loadDefaultConfig(); + } + ontologyIdentifierFromURL = paramArray[1]; + } + + switch ( parameterArray.length ) { + case 0: + loadDefaultConfig(); + break; + case 1: + identifyOptions(parameterArray); + break; + case 2: + identifyOptionsAndOntology(parameterArray); + break; + default : + console.log("To many input parameters , loading default config"); + loadDefaultConfig(); + ontologyIdentifierFromURL = "ERROR_TO_MANY_INPUT_PARAMETERS"; + } + } + + + function identifyOntologyLoadingMethod( url ){ + var iriKey = "iri="; + var urlKey = "url="; + var fileKey = "file="; + + var method = -1; + if ( url.substr(0, fileKey.length) === fileKey ) { + method = FILE_UPLOAD; + } else if ( url.substr(0, urlKey.length) === urlKey ) { + method = JSON_URL; + } else if ( url.substr(0, iriKey.length) === iriKey ) { + method = IRI_URL; + } else { + method = PREDEFINED; + } + return method; + } + + return loadingModule; + } + ; + + + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 343: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( graph ){ + /** variable defs **/ + var warningModule = {}; + var superContainer = d3.select("#WarningErrorMessages"); + var _messageContainers = []; + var _messageContext = []; + var _visibleStatus = []; + + var _filterHintId; + var _editorHintId; + var _messageId = -1; + superContainer.style("display", "inline-block"); + var cssStyleIndex = 0; + var styleSelectorIndex = 2; + + + // helper for standalone webvowl in chrome + function createCSSSelector( name, rules ){ + var style = document.createElement('style'); + style.type = 'text/css'; + document.getElementsByTagName('head')[0].appendChild(style); + if ( !(style.sheet || {}).insertRule ) + (style.styleSheet || style.sheet).addRule(name, rules); + else + style.sheet.insertRule(name + "{" + rules + "}", 0); + } + + + function findCSS_Index(){ + createCSSSelector("@keyframes msg_CollapseAnimation", " 0% { top: 0; } 100% { top: -400px;}"); + console.log(document.styleSheets ); + } + + findCSS_Index(); + + warningModule.addMessageBox = function (){ + + // add a container; + _messageId++; + var messageContainer = d3.select("#WarningErrorMessages").append("div"); + messageContainer.node().id = "messageContainerId_" + _messageId; + + var messageContext = messageContainer.append("div"); + messageContext.node().id = "messageContextId_" + _messageId; + messageContext.style("top", "0"); + messageContainer.style("position", "relative"); + messageContainer.style("width", "100%"); + //save in array + _messageContainers.push(messageContainer); + _messageContext.push(messageContext); + + // add animation to the container + messageContainer.node().addEventListener("animationend", _msgContainer_animationEnd); + + // set visible flag that is used in end of animation + _visibleStatus[_messageId] = true; + return _messageId; + }; + + function _msgContainer_animationEnd(){ + var containerId = this.id; + var tokens = containerId.split("_")[1]; + var mContainer = d3.select("#" + containerId); + // get number of children + mContainer.classed("hidden", !_visibleStatus[tokens]); + // clean up DOM + if ( !_visibleStatus[tokens] ) { + mContainer.remove(); + _messageContext[tokens] = null; + _messageContainers[tokens] = null; + } + // remove event listener + var c = d3.select(this); + // c.node().removeEventListener("animationend",_msgContainer_animationEnd); + } + + warningModule.createMessageContext = function ( id ){ + var warningContainer = _messageContext[id]; + var moduleContainer = _messageContainers[id]; + var generalHint = warningContainer.append('div'); + generalHint.node().innerHTML = ""; + _editorHintId = id; + /** Editing mode activated. You can now modify an existing ontology or create a new one via the ontology menu. You can save any ontology using the export menu (and exporting it as TTL file).**/ + generalHint.node().innerHTML += "Editing mode activated.
    " + + "You can now modify an existing ontology or create a new one via the ontology menu.
    " + + "You can save any ontology using the export menu (and exporting it as TTL file)."; + + generalHint.style("padding", "5px"); + generalHint.style("line-height", "1.2em"); + generalHint.style("font-size", "1.2em"); + + + var ul = warningContainer.append('ul'); + ul.append('li').node().innerHTML = "Create a class with double click / tap on empty canvas area."; + ul.append('li').node().innerHTML = "Edit names with double click / tap on element."; + ul.append('li').node().innerHTML = "Selection of default constructors is provided in the left sidebar."; + ul.append('li').node().innerHTML = "Additional editing functionality is provided in the right sidebar."; + + + var gotItButton = warningContainer.append("label"); + gotItButton.node().id = "killWarningErrorMessages_" + id; + gotItButton.node().innerHTML = "Got It"; + gotItButton.on("click", warningModule.closeMessage); + + moduleContainer.classed("hidden", false); + moduleContainer.style("-webkit-animation-name", "warn_ExpandAnimation"); + moduleContainer.style("-webkit-animation-duration", "0.5s"); + }; + + warningModule.showMessage = function ( id ){ + var moduleContainer = _messageContainers[id]; + moduleContainer.classed("hidden", false); + moduleContainer.style("-webkit-animation-name", "warn_ExpandAnimation"); + moduleContainer.style("-webkit-animation-duration", "0.5s"); + }; + + warningModule.closeMessage = function ( id ){ + var nId; + if ( id === undefined ) { + var givenId = this.id; + nId = givenId.split("_")[1]; + } else { + nId = id; + } + if ( id && id.indexOf("_") !== -1 ) { + nId = id.split("_")[1]; + } + _visibleStatus[nId] = false; + // get module; + var moduleContainer = _messageContainers[nId]; + moduleContainer.style("-webkit-animation-name", "warn_CollapseAnimation"); + moduleContainer.style("-webkit-animation-duration", "0.5s"); + + var m_height = moduleContainer.node().getBoundingClientRect().height; + + // find my id in the children + var pNode = moduleContainer.node().parentNode; + + var followingChildren = []; + var pChild = pNode.children; + var pChild_len = pChild.length; + var containerId = moduleContainer.node().id; + var found_me = false; + for ( var i = 0; i < pChild_len; i++ ) { + if ( found_me === true ) { + followingChildren.push(pChild[i].id); + } + + if ( containerId === pChild[i].id ) { + found_me = true; + } + } + + for ( var fc = 0; fc < followingChildren.length; fc++ ) { + var child = d3.select("#" + followingChildren[fc]); + // get the document style and overwrite it; + var superCss = document.styleSheets[styleSelectorIndex].cssRules[cssStyleIndex]; + // remove the existing 0% and 100% rules + superCss.deleteRule("0%"); + superCss.deleteRule("100%"); + + superCss.appendRule("0% {top: 0;}"); + superCss.appendRule("100% {top: -" + m_height + "px;"); + + child.style("-webkit-animation-name", "msg_CollapseAnimation"); + child.style("-webkit-animation-duration", "0.5s"); + child.node().addEventListener("animationend", _child_animationEnd); + } + }; + + function _child_animationEnd(){ + var c = d3.select(this); + c.style("-webkit-animation-name", ""); + c.style("-webkit-animation-duration", ""); + c.node().removeEventListener("animationend", _child_animationEnd); + } + + warningModule.closeFilterHint = function (){ + if ( _messageContainers[_filterHintId] ) { + _messageContainers[_filterHintId].classed("hidden", true); + _messageContainers[_filterHintId].remove(); + _messageContainers[_filterHintId] = null; + _messageContext[_filterHintId] = null; + _visibleStatus[_filterHintId] = false; + } + }; + + warningModule.showEditorHint = function (){ + var id = warningModule.addMessageBox(); + warningModule.createMessageContext(id); + }; + + warningModule.showExporterWarning=function (){ + warningModule.showWarning("Can not export ontology", "Detected unsupported ontology axioms, (e.g. owl:Union)", "Ontology is not exported", 1, false); + }; + + + + warningModule.responseWarning = function ( header, reason, action, callback, parameterArray, forcedWarning ){ + var id = warningModule.addMessageBox(); + var warningContainer = _messageContext[id]; + var moduleContainer = _messageContainers[id]; + _visibleStatus[id] = true; + d3.select("#blockGraphInteractions").classed("hidden", false); + var graphWidth = 0.5 * graph.options().width(); + + if ( header.length > 0 ) { + var head = warningContainer.append("div"); + head.style("padding", "5px"); + var titleHeader = head.append("div"); + // some classes + titleHeader.style("display", "inline-flex"); + titleHeader.node().innerHTML = "Warning:"; + titleHeader.style("padding-right", "3px"); + var msgHeader = head.append("div"); + // some classes + msgHeader.style("display", "inline-flex"); + msgHeader.style("max-width", graphWidth + "px"); + + msgHeader.node().innerHTML = header; + } + if ( reason.length > 0 ) { + var reasonContainer = warningContainer.append("div"); + reasonContainer.style("padding", "5px"); + var reasonHeader = reasonContainer.append("div"); + // some classes + reasonHeader.style("display", "inline-flex"); + reasonHeader.style("padding-right", "3px"); + + reasonHeader.node().innerHTML = "Reason:"; + var msgReason = reasonContainer.append("div"); + // some classes + msgReason.style("display", "inline-flex"); + msgReason.style("max-width", graphWidth + "px"); + msgReason.node().innerHTML = reason; + } + if ( action.length > 0 ) { + var actionContainer = warningContainer.append("div"); + actionContainer.style("padding", "5px"); + var actionHeader = actionContainer.append("div"); + // some classes + actionHeader.style("display", "inline-flex"); + actionHeader.style("padding-right", "8px"); + actionHeader.node().innerHTML = "Action:"; + var msgAction = actionContainer.append("div"); + // some classes + msgAction.style("display", "inline-flex"); + msgAction.style("max-width", graphWidth + "px"); + msgAction.node().innerHTML = action; + } + + var gotItButton = warningContainer.append("label"); + gotItButton.node().id = "killWarningErrorMessages_" + id; + gotItButton.node().innerHTML = "Continue"; + gotItButton.on("click", function (){ + warningModule.closeMessage(this.id); + d3.select("#blockGraphInteractions").classed("hidden", true); + callback(parameterArray[0], parameterArray[1], parameterArray[2], parameterArray[3]); + }); + warningContainer.append("span").node().innerHTML = "|"; + var cancelButton = warningContainer.append("label"); + cancelButton.node().id = "cancelButton_" + id; + cancelButton.node().innerHTML = "Cancel"; + cancelButton.on("click", function (){ + warningModule.closeMessage(this.id); + d3.select("#blockGraphInteractions").classed("hidden", true); + }); + moduleContainer.classed("hidden", false); + moduleContainer.style("-webkit-animation-name", "warn_ExpandAnimation"); + moduleContainer.style("-webkit-animation-duration", "0.5s"); + }; + + warningModule.showFilterHint = function (){ + var id = warningModule.addMessageBox(); + var warningContainer = _messageContext[id]; + var moduleContainer = _messageContainers[id]; + _visibleStatus[id] = true; + + _filterHintId = id; + var generalHint = warningContainer.append('div'); + /** Editing mode activated. You can now modify an existing ontology or create a new one via the ontology menu. You can save any ontology using the export menu (and exporting it as TTL file).**/ + generalHint.node().innerHTML = "Collapsing filter activated.
    " + + "The number of visualized elements has been automatically reduced.
    " + + "Use the degree of collapsing slider in the filter menu to adjust the visualization.

    " + + "Note: A performance decrease could be experienced with a growing amount of visual elements in the graph."; + + + generalHint.style("padding", "5px"); + generalHint.style("line-height", "1.2em"); + generalHint.style("font-size", "1.2em"); + + var gotItButton = warningContainer.append("label"); + gotItButton.node().id = "killFilterMessages_" + id; + gotItButton.node().innerHTML = "Got It"; + gotItButton.on("click", warningModule.closeMessage); + + moduleContainer.classed("hidden", false); + moduleContainer.style("-webkit-animation-name", "warn_ExpandAnimation"); + moduleContainer.style("-webkit-animation-duration", "0.5s"); + }; + + warningModule.showMultiFileUploadWarning = function (){ + var id = warningModule.addMessageBox(); + var warningContainer = _messageContext[id]; + var moduleContainer = _messageContainers[id]; + _visibleStatus[id] = true; + + _filterHintId = id; + var generalHint = warningContainer.append('div'); + + generalHint.node().innerHTML = "Uploading multiple files is not supported.
    "; + + generalHint.style("padding", "5px"); + generalHint.style("line-height", "1.2em"); + generalHint.style("font-size", "1.2em"); + + var gotItButton = warningContainer.append("label"); + gotItButton.node().id = "killFilterMessages_" + id; + gotItButton.node().innerHTML = "Got It"; + gotItButton.on("click", warningModule.closeMessage); + + moduleContainer.classed("hidden", false); + moduleContainer.style("-webkit-animation-name", "warn_ExpandAnimation"); + moduleContainer.style("-webkit-animation-duration", "0.5s"); + }; + + warningModule.showWarning = function ( header, reason, action, type, forcedWarning, additionalOpts ){ + var id = warningModule.addMessageBox(); + var warningContainer = _messageContext[id]; + var moduleContainer = _messageContainers[id]; + _visibleStatus[id] = true; + + // add new one; + var graphWidth = 0.5 * graph.options().width(); + + if ( header.length > 0 ) { + var head = warningContainer.append("div"); + head.style("padding", "5px"); + var titleHeader = head.append("div"); + // some classes + titleHeader.style("display", "inline-flex"); + titleHeader.node().innerHTML = "Warning:"; + titleHeader.style("padding-right", "3px"); + var msgHeader = head.append("div"); + // some classes + msgHeader.style("display", "inline-flex"); + msgHeader.style("max-width", graphWidth + "px"); + + msgHeader.node().innerHTML = header; + } + if ( reason.length > 0 ) { + var reasonContainer = warningContainer.append("div"); + reasonContainer.style("padding", "5px"); + var reasonHeader = reasonContainer.append("div"); + // some classes + reasonHeader.style("display", "inline-flex"); + reasonHeader.style("padding-right", "3px"); + + reasonHeader.node().innerHTML = "Reason:"; + var msgReason = reasonContainer.append("div"); + // some classes + msgReason.style("display", "inline-flex"); + msgReason.style("max-width", graphWidth + "px"); + msgReason.node().innerHTML = reason; + } + if ( action.length > 0 ) { + var actionContainer = warningContainer.append("div"); + actionContainer.style("padding", "5px"); + var actionHeader = actionContainer.append("div"); + // some classes + actionHeader.style("display", "inline-flex"); + actionHeader.style("padding-right", "8px"); + actionHeader.node().innerHTML = "Action:"; + var msgAction = actionContainer.append("div"); + // some classes + msgAction.style("display", "inline-flex"); + msgAction.style("max-width", graphWidth + "px"); + msgAction.node().innerHTML = action; + } + + var gotItButton; + if ( type === 1 ) { + gotItButton = warningContainer.append("label"); + gotItButton.node().id = "killWarningErrorMessages_" + id; + gotItButton.node().innerHTML = "Got It"; + gotItButton.on("click", warningModule.closeMessage); + } + + if ( type === 2 ) { + gotItButton = warningContainer.append("label"); + gotItButton.node().id = "killWarningErrorMessages_" + id; + gotItButton.node().innerHTML = "Got It"; + gotItButton.on("click", warningModule.closeMessage); + warningContainer.append("span").node().innerHTML = "|"; + var zoomToElementButton = warningContainer.append("label"); + zoomToElementButton.node().id = "zoomElementThing_" + id; + zoomToElementButton.node().innerHTML = "Zoom to element "; + zoomToElementButton.on("click", function (){ + // assume the additional Element is for halo; + graph.zoomToElementInGraph(additionalOpts); + }); + warningContainer.append("span").node().innerHTML = "|"; + var ShowElementButton = warningContainer.append("label"); + ShowElementButton.node().id = "showElementThing_" + id; + ShowElementButton.node().innerHTML = "Indicate element"; + ShowElementButton.on("click", function (){ + // assume the additional Element is for halo; + if ( additionalOpts.halo() === false ) { + additionalOpts.drawHalo(); + graph.updatePulseIds([additionalOpts.id()]); + } else { + additionalOpts.removeHalo(); + additionalOpts.drawHalo(); + graph.updatePulseIds([additionalOpts.id()]); + } + }); + } + moduleContainer.classed("hidden", false); + moduleContainer.style("-webkit-animation-name", "warn_ExpandAnimation"); + moduleContainer.style("-webkit-animation-duration", "0.5s"); + moduleContainer.classed("hidden", false); + }; + + return warningModule; + }; + + + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 344: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( graph ){ + /** variable defs **/ + var directInputModule = {}; + var inputContainer = d3.select("#DirectInputContent"); + inputContainer.style("top", "0"); + inputContainer.style("position", "absolute"); + var textArea = d3.select("#directInputTextArea"); + var visibleContainer = false; + + inputContainer.style("border", "1px solid black"); + inputContainer.style("padding", "5px"); + inputContainer.style("background", "#fff"); + + + // connect upload and close button; + directInputModule.handleDirectUpload = function (){ + + var text = textArea.node().value; + var jsonOBJ; + try { + jsonOBJ = JSON.parse(text); + graph.options().loadingModule().directInput(text); + // close if successful + if ( jsonOBJ.class.length > 0 ) { + directInputModule.setDirectInputMode(false); + } + } + catch ( e ) { + try { + // Initialize; + graph.options().loadingModule().initializeLoader(); + graph.options().loadingModule().requestServerTimeStampForDirectInput( + graph.options().ontologyMenu().callbackLoad_Ontology_From_DirectInput, text + ); + } catch ( error2 ) { + console.log("Error " + error2); + d3.select("#Error_onLoad").classed("hidden", false); + d3.select("#Error_onLoad").node().innerHTML = "Failed to convert the input!"; + } + } + }; + + directInputModule.handleCloseButton = function (){ + directInputModule.setDirectInputMode(false); + }; + + directInputModule.updateLayout = function (){ + var w = graph.options().width(); + var h = graph.options().height(); + textArea.style("width", 0.4 * w + "px"); + textArea.style("height", 0.7 * h + "px"); + }; + + directInputModule.setDirectInputMode = function ( val ){ + if ( !val ) { + visibleContainer = !visibleContainer; + } + else { + visibleContainer = val; + } + // update visibility; + directInputModule.updateLayout(); + d3.select("#Error_onLoad").classed("hidden", true); + inputContainer.classed("hidden", !visibleContainer); + }; + + + d3.select("#directUploadBtn").on("click", directInputModule.handleDirectUpload); + d3.select("#close_directUploadBtn").on("click", directInputModule.handleCloseButton); + + return directInputModule; + }; + + + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }) + +/******/ }); diff --git a/doc/releases/0.1.0/parameters/webvowl/js/webvowl.js b/doc/releases/0.1.0/parameters/webvowl/js/webvowl.js new file mode 100644 index 0000000..1aba35e --- /dev/null +++ b/doc/releases/0.1.0/parameters/webvowl/js/webvowl.js @@ -0,0 +1,25345 @@ +webvowl = +/******/ (function(modules) { // webpackBootstrap +/******/ // The module cache +/******/ var installedModules = {}; + +/******/ // The require function +/******/ function __webpack_require__(moduleId) { + +/******/ // Check if module is in cache +/******/ if(installedModules[moduleId]) +/******/ return installedModules[moduleId].exports; + +/******/ // Create a new module (and put it into the cache) +/******/ var module = installedModules[moduleId] = { +/******/ exports: {}, +/******/ id: moduleId, +/******/ loaded: false +/******/ }; + +/******/ // Execute the module function +/******/ modules[moduleId].call(module.exports, module, module.exports, __webpack_require__); + +/******/ // Flag the module as loaded +/******/ module.loaded = true; + +/******/ // Return the exports of the module +/******/ return module.exports; +/******/ } + + +/******/ // expose the modules object (__webpack_modules__) +/******/ __webpack_require__.m = modules; + +/******/ // expose the module cache +/******/ __webpack_require__.c = installedModules; + +/******/ // __webpack_public_path__ +/******/ __webpack_require__.p = ""; + +/******/ // Load entry module and return exports +/******/ return __webpack_require__(0); +/******/ }) +/************************************************************************/ +/******/ ([ +/* 0 */ +/***/ (function(module, exports, __webpack_require__) { + + __webpack_require__(1); + + var nodeMap = __webpack_require__(5)(); + var propertyMap = __webpack_require__(40)(); + + + var webvowl = {}; + webvowl.graph = __webpack_require__(57); + webvowl.options = __webpack_require__(64); + webvowl.version = "1.1.7"; + + webvowl.util = {}; + webvowl.util.constants = __webpack_require__(12); + webvowl.util.languageTools = __webpack_require__(11); + webvowl.util.elementTools = __webpack_require__(63); + webvowl.util.prefixTools = __webpack_require__(72); + webvowl.modules = {}; + webvowl.modules.colorExternalsSwitch = __webpack_require__(73); + webvowl.modules.compactNotationSwitch = __webpack_require__(74); + webvowl.modules.datatypeFilter = __webpack_require__(75); + webvowl.modules.disjointFilter = __webpack_require__(77); + webvowl.modules.focuser = __webpack_require__(78); + webvowl.modules.emptyLiteralFilter = __webpack_require__(79); + webvowl.modules.nodeDegreeFilter = __webpack_require__(80); + webvowl.modules.nodeScalingSwitch = __webpack_require__(81); + webvowl.modules.objectPropertyFilter = __webpack_require__(82); + webvowl.modules.pickAndPin = __webpack_require__(83); + webvowl.modules.selectionDetailsDisplayer = __webpack_require__(315); + webvowl.modules.setOperatorFilter = __webpack_require__(316); + webvowl.modules.statistics = __webpack_require__(317); + webvowl.modules.subclassFilter = __webpack_require__(318); + + + webvowl.nodes = {}; + nodeMap.entries().forEach(function ( entry ){ + mapEntryToIdentifier(webvowl.nodes, entry); + }); + + webvowl.properties = {}; + propertyMap.entries().forEach(function ( entry ){ + mapEntryToIdentifier(webvowl.properties, entry); + }); + + function mapEntryToIdentifier( map, entry ){ + var identifier = entry.key.replace(":", "").toLowerCase(); + map[identifier] = entry.value; + } + + + module.exports = webvowl; + + +/***/ }), +/* 1 */ +/***/ (function(module, exports) { + + // removed by extract-text-webpack-plugin + +/***/ }), +/* 2 */, +/* 3 */, +/* 4 */, +/* 5 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var nodes = []; + nodes.push(__webpack_require__(7)); + nodes.push(__webpack_require__(18)); + nodes.push(__webpack_require__(19)); + nodes.push(__webpack_require__(26)); + nodes.push(__webpack_require__(27)); + nodes.push(__webpack_require__(28)); + nodes.push(__webpack_require__(29)); + nodes.push(__webpack_require__(30)); + nodes.push(__webpack_require__(31)); + nodes.push(__webpack_require__(32)); + nodes.push(__webpack_require__(33)); + nodes.push(__webpack_require__(34)); + nodes.push(__webpack_require__(38)); + nodes.push(__webpack_require__(39)); + + var map = d3.map(nodes, function ( Prototype ){ + return new Prototype().type(); + }); + + module.exports = function (){ + return map; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 6 */ +/***/ (function(module, exports) { + + module.exports = d3; + +/***/ }), +/* 7 */ +/***/ (function(module, exports, __webpack_require__) { + + var RoundNode = __webpack_require__(8); + + module.exports = (function (){ + + var o = function ( graph ){ + RoundNode.apply(this, arguments); + + this.attributes(["external"]) + .type("ExternalClass"); + }; + o.prototype = Object.create(RoundNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 8 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseNode = __webpack_require__(9); + var CenteringTextElement = __webpack_require__(14); + var drawTools = __webpack_require__(17)(); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseNode.apply(this, arguments); + + var that = this, + collapsible = false, + radius = 50, + collapsingGroupElement, + pinGroupElement, + haloGroupElement = null, + rectangularRepresentation = false, + renderingElement, + textBlock; + + this.setRectangularRepresentation = function ( val ){ + rectangularRepresentation = val; + }; + this.getRectangularRepresentation = function (){ + return rectangularRepresentation; + }; + + this.getHalos = function (){ + return haloGroupElement; + }; + + // Properties + this.collapsible = function ( p ){ + if ( !arguments.length ) return collapsible; + collapsible = p; + return this; + }; + + this.textBlock = function ( p ){ + if ( !arguments.length ) return textBlock; + textBlock = p; + return this; + }; + + /** + * This might not be equal to the actual radius, because the instance count is used for its calculation. + * @param p + * @returns {*} + */ + this.radius = function ( p ){ + if ( !arguments.length ) return radius; + radius = p; + return this; + }; + + + // Functions + this.setHoverHighlighting = function ( enable ){ + that.nodeElement().selectAll("circle").classed("hovered", enable); + }; + + this.textWidth = function ( yOffset ){ + var availableWidth = this.actualRadius() * 2; + + // if the text is not placed in the center of the circle, it can't have the full width + if ( yOffset ) { + var relativeOffset = Math.abs(yOffset) / this.actualRadius(); + var isOffsetInsideOfNode = relativeOffset <= 1; + + if ( isOffsetInsideOfNode ) { + availableWidth = Math.cos(relativeOffset) * availableWidth; + } else { + availableWidth = 0; + } + } + + return availableWidth; + }; + + this.toggleFocus = function (){ + that.focused(!that.focused()); + if ( that.nodeElement() ) + that.nodeElement().select("circle").classed("focused", that.focused()); + graph.resetSearchHighlight(); + graph.options().searchMenu().clearText(); + + }; + + this.actualRadius = function (){ + if ( !graph.options().scaleNodesByIndividuals() || that.individuals().length <= 0 ) { + return that.radius(); + } else { + // we could "listen" for radius and maxIndividualCount changes, but this is easier + var MULTIPLIER = 8, + additionalRadius = Math.log(that.individuals().length + 1) * MULTIPLIER + 5; + + return that.radius() + additionalRadius; + } + }; + + this.distanceToBorder = function (){ + return that.actualRadius(); + }; + + this.removeHalo = function (){ + if ( that.halo() ) { + that.halo(false); + if ( haloGroupElement ) { + haloGroupElement.remove(); + } + } + }; + + this.drawHalo = function ( pulseAnimation ){ + that.halo(true); + if ( rectangularRepresentation === true ) { + haloGroupElement = drawTools.drawRectHalo(that.nodeElement(), 80, 80, 5); + } else { + haloGroupElement = drawTools.drawHalo(that.nodeElement(), that.actualRadius(), this.removeHalo); + } + if ( pulseAnimation === false ) { + var pulseItem = haloGroupElement.selectAll(".searchResultA"); + pulseItem.classed("searchResultA", false); + pulseItem.classed("searchResultB", true); + pulseItem.attr("animationRunning", false); + } + }; + + /** + * Draws the pin on a round node on a position depending on its radius. + */ + this.drawPin = function (){ + that.pinned(true); + var dx = (-3.5 / 5) * that.actualRadius(), + dy = (-7 / 10) * that.actualRadius(); + pinGroupElement = drawTools.drawPin(that.nodeElement(), dx, dy, this.removePin, graph.options().showDraggerObject, graph.options().useAccuracyHelper()); + + + }; + + /** + * Removes the pin and refreshs the graph to update the force layout. + */ + this.removePin = function (){ + that.pinned(false); + if ( pinGroupElement ) { + pinGroupElement.remove(); + } + graph.updateStyle(); + }; + + this.drawCollapsingButton = function (){ + + collapsingGroupElement = that.nodeElement() + .append("g") + .classed("hidden-in-export", true) + .attr("transform", function (){ + var dx = (-2 / 5) * that.actualRadius(), + dy = (1 / 2) * that.actualRadius(); + return "translate(" + dx + "," + dy + ")"; + }); + + collapsingGroupElement.append("rect") + .classed("class pin feature", true) + .attr("x", 0) + .attr("y", 0) + .attr("width", 40) + .attr("height", 24); + + collapsingGroupElement.append("line") + .attr("x1", 13) + .attr("y1", 12) + .attr("x2", 27) + .attr("y2", 12); + + collapsingGroupElement.append("line") + .attr("x1", 20) + .attr("y1", 6) + .attr("x2", 20) + .attr("y2", 18); + }; + + /** + * Draws a circular node. + * @param parentElement the element to which this node will be appended + * @param [additionalCssClasses] additional css classes + */ + this.draw = function ( parentElement, additionalCssClasses ){ + var cssClasses = that.collectCssClasses(); + that.nodeElement(parentElement); + + var bgColor = that.backgroundColor(); + if ( bgColor === null ) bgColor = undefined; + if ( that.attributes().indexOf("deprecated") > -1 ) { + bgColor = undefined; + } + if ( additionalCssClasses instanceof Array ) { + cssClasses = cssClasses.concat(additionalCssClasses); + } + if ( rectangularRepresentation === true ) { + renderingElement = drawTools.appendRectangularClass(parentElement, 80, 80, cssClasses, that.labelForCurrentLanguage(), bgColor); + } else { + renderingElement = drawTools.appendCircularClass(parentElement, that.actualRadius(), cssClasses, that.labelForCurrentLanguage(), bgColor); + } + that.postDrawActions(parentElement); + }; + + this.redrawElement = function (){ + renderingElement.remove(); + textBlock.remove(); + var bgColor = that.backgroundColor(); + if ( that.attributes().indexOf("deprecated") > -1 ) { + bgColor = undefined; + } + + var cssClasses = that.collectCssClasses(); + + if ( rectangularRepresentation === true ) { + renderingElement = drawTools.appendRectangularClass(that.nodeElement(), 80, 80, cssClasses, that.labelForCurrentLanguage(), bgColor); + } else { + renderingElement = drawTools.appendCircularClass(that.nodeElement(), that.actualRadius(), cssClasses, that.labelForCurrentLanguage(), bgColor); + } + that.postDrawActions(that.nodeElement()); + }; + /** + * Common actions that should be invoked after drawing a node. + */ + this.postDrawActions = function (){ + that.textBlock(createTextBlock()); + + that.addMouseListeners(); + if ( that.pinned() ) { + that.drawPin(); + } + if ( that.halo() ) { + that.drawHalo(false); + } + if ( that.collapsible() ) { + that.drawCollapsingButton(); + } + }; + + this.redrawLabelText = function (){ + that.textBlock().remove(); + that.textBlock(createTextBlock()); + renderingElement.select("title").text(that.labelForCurrentLanguage()); + }; + function createTextBlock(){ + var bgColor = that.backgroundColor(); + if ( that.attributes().indexOf("deprecated") > -1 ) + bgColor = undefined; + + var textBlock = new CenteringTextElement(that.nodeElement(), bgColor); + + var equivalentsString = that.equivalentsString(); + var suffixForFollowingEquivalents = equivalentsString ? "," : ""; + + textBlock.addText(that.labelForCurrentLanguage(), "", suffixForFollowingEquivalents); + textBlock.addEquivalents(equivalentsString); + if ( !graph.options().compactNotation() ) { + textBlock.addSubText(that.indicationString()); + } + textBlock.addInstanceCount(that.individuals().length); + + return textBlock; + } + + this.equivalentsString = function (){ + var equivalentClasses = that.equivalents(); + if ( !equivalentClasses ) { + return; + } + + return equivalentClasses + .map(function ( node ){ + return node.labelForCurrentLanguage(); + }) + .join(", "); + }; + }; + o.prototype = Object.create(BaseNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 9 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var BaseElement = __webpack_require__(10); + var forceLayoutNodeFunctions = __webpack_require__(13)(); + + module.exports = (function (){ + + var Base = function ( graph ){ + BaseElement.apply(this, arguments); + + var that = this, + // Basic attributes + complement, + disjointUnion, + disjointWith, + individuals = [], + intersection, + union, + links, + rendertype = "round", + // Additional attributes + maxIndividualCount, + fobj, // foreigner object for editing + ignoreLocalHoverEvents = false, + backupFullIri, + // Element containers + nodeElement; + + // array to store my properties; // we will need this also later for semantic zooming stuff + var assignedProperties = []; + that.editingTextElement = false; + + this.isPropertyAssignedToThisElement = function ( property ){ + // this goes via IRIS + console.log("Element IRI :" + property.iri()); + if ( property.type() === "rdfs:subClassOf" ) + for ( var i = 0; i < assignedProperties.length; i++ ) { + var iriEl = assignedProperties[i].iri(); + if ( property.iri() === iriEl ) { + return true; + } + if ( property.type() === "rdfs:subClassOf" && assignedProperties[i].type() === "rdfs:subClassOf" ) + return true; + if ( property.type() === "owl:disjointWith" && assignedProperties[i].type() === "owl:disjointWith" ) + return true; + + } + return false; + }; + + + this.existingPropertyIRI = function ( url ){ + // this goes via IRIS + for ( var i = 0; i < assignedProperties.length; i++ ) { + var iriEl = assignedProperties[i].iri(); + if ( iriEl === url ) { + return true; + } + } + return false; + }; + + this.addProperty = function ( property ){ + if ( assignedProperties.indexOf(property) === -1 ) { + assignedProperties.push(property); + } + }; + + this.removePropertyElement = function ( property ){ + // console.log("Calling removing old property!"+ property.iri()); + if ( assignedProperties.indexOf(property) !== -1 ) { + // console.log("Found it!"); + assignedProperties.splice(assignedProperties.indexOf(property), 1); + } + }; + this.getMyProperties = function (){ + return assignedProperties; + }; + this.copyOtherProperties = function ( otherProperties ){ + assignedProperties = otherProperties; + }; + + this.copyInformation = function ( other ){ + console.log(other.labelForCurrentLanguage()); + if ( other.type() !== "owl:Thing" ) + that.label(other.label()); + that.complement(other.complement()); + that.iri(other.iri()); + that.copyOtherProperties(other.getMyProperties()); + that.baseIri(other.baseIri()); + if ( other.type() === "owl:Class" ) { + that.backupLabel(other.label()); + // console.log("copied backup label"+that.backupLabel()); + } + if ( other.backupLabel() !== undefined ) { + that.backupLabel(other.backupLabel()); + } + }; + + this.enableEditing = function ( autoEditing ){ + if ( autoEditing === false ) + return; + that.raiseDoubleClickEdit(true); + }; + + this.raiseDoubleClickEdit = function ( forceIRISync ){ + d3.selectAll(".foreignelements").remove(); + if ( nodeElement === undefined || this.type() === "owl:Thing" || this.type() === "rdfs:Literal" ) { + console.log("No Container found"); + return; + } + if ( fobj !== undefined ) { + nodeElement.selectAll(".foreignelements").remove(); + } + + backupFullIri = undefined; + graph.options().focuserModule().handle(undefined); + graph.options().focuserModule().handle(that); + // add again the editing elements to that one + if ( graph.isTouchDevice() === true ) { + graph.activateHoverElements(true, that, true); + } + that.editingTextElement = true; + ignoreLocalHoverEvents = true; + that.nodeElement().selectAll("circle").classed("hoveredForEditing", true); + graph.killDelayedTimer(); + graph.ignoreOtherHoverEvents(false); + fobj = nodeElement.append("foreignObject") + .attr("x", -0.5 * (that.textWidth() - 2)) + .attr("y", -12) + .attr("height", 30) + .attr("class", "foreignelements") + .on("dragstart", function (){ + return false; + }) // remove drag operations of text element) + .attr("width", that.textWidth() - 2); + + var editText = fobj.append("xhtml:input") + .attr("class", "nodeEditSpan") + .attr("id", that.id()) + .attr("align", "center") + .attr("contentEditable", "true") + .on("dragstart", function (){ + return false; + }); // remove drag operations of text element) + + var bgColor = '#f00'; + var txtWidth = that.textWidth() - 2; + editText.style({ + + 'align': 'center', + 'color': 'black', + 'width': txtWidth + "px", + 'height': '15px', + 'background-color': bgColor, + 'border-bottom': '2px solid black' + }); + var txtNode = editText.node(); + txtNode.value = that.labelForCurrentLanguage(); + txtNode.focus(); + txtNode.select(); + that.frozen(true); // << releases the not after selection + that.locked(true); + + + d3.event.stopPropagation(); + // ignoreNodeHoverEvent=true; + // // add some events that relate to this object + editText.on("click", function (){ + d3.event.stopPropagation(); + }); + // // remove hover Events for now; + editText.on("mouseout", function (){ + d3.event.stopPropagation(); + + + }); + editText.on("mousedown", function (){ + d3.event.stopPropagation(); + }) + .on("keydown", function (){ + d3.event.stopPropagation(); + if ( d3.event.keyCode === 13 ) { + this.blur(); + that.frozen(false); // << releases the not after selection + that.locked(false); + } + }) + .on("keyup", function (){ + if ( forceIRISync ) { + var labelName = editText.node().value; + var resourceName = labelName.replaceAll(" ", "_"); + var syncedIRI = that.baseIri() + resourceName; + backupFullIri = syncedIRI; + + d3.select("#element_iriEditor").node().title = syncedIRI; + d3.select("#element_iriEditor").node().value = graph.options().prefixModule().getPrefixRepresentationForFullURI(syncedIRI); + } + d3.select("#element_labelEditor").node().value = editText.node().value; + + }) + .on("blur", function (){ + that.editingTextElement = false; + ignoreLocalHoverEvents = false; + that.nodeElement().selectAll("circle").classed("hoveredForEditing", false); + var newLabel = editText.node().value; + nodeElement.selectAll(".foreignelements").remove(); + // that.setLabelForCurrentLanguage(classNameConvention(editText.node().value)); + that.label(newLabel); + that.backupLabel(newLabel); + that.redrawLabelText(); + that.frozen(graph.paused()); + that.locked(graph.paused()); + graph.ignoreOtherHoverEvents(false); + // console.log("Calling blur on Node!"); + if ( backupFullIri ) { + var sanityCheckResult = graph.checkIfIriClassAlreadyExist(backupFullIri); + if ( sanityCheckResult === false ) { + that.iri(backupFullIri); + } else { + // throw warnign + graph.options().warningModule().showWarning("Already seen this class", + "Input IRI: " + backupFullIri + " for element: " + that.labelForCurrentLanguage() + " already been set", + "Restoring previous IRI for Element : " + that.iri(), 2, false, sanityCheckResult); + + } + } + if ( graph.isADraggerActive() === false ) { + graph.options().focuserModule().handle(undefined); + graph.options().focuserModule().handle(that); + } + }); // add a foreiner element to this thing; + }; + + + this.renderType = function ( t ){ + if ( !arguments.length ) return rendertype; + rendertype = t; + return this; + }; + // Properties + this.complement = function ( p ){ + if ( !arguments.length ) return complement; + complement = p; + return this; + }; + + this.disjointUnion = function ( p ){ + if ( !arguments.length ) return disjointUnion; + disjointUnion = p; + return this; + }; + + this.disjointWith = function ( p ){ + if ( !arguments.length ) return disjointWith; + disjointWith = p; + return this; + }; + + this.individuals = function ( p ){ + if ( !arguments.length ) return individuals; + individuals = p || []; + return this; + }; + + this.intersection = function ( p ){ + if ( !arguments.length ) return intersection; + intersection = p; + return this; + }; + + this.links = function ( p ){ + if ( !arguments.length ) return links; + links = p; + return this; + }; + + this.maxIndividualCount = function ( p ){ + if ( !arguments.length ) return maxIndividualCount; + maxIndividualCount = p; + return this; + }; + + this.nodeElement = function ( p ){ + if ( !arguments.length ) return nodeElement; + nodeElement = p; + return this; + }; + + this.union = function ( p ){ + if ( !arguments.length ) return union; + union = p; + return this; + }; + + + /** + * Returns css classes generated from the data of this object. + * @returns {Array} + */ + that.collectCssClasses = function (){ + var cssClasses = []; + + if ( typeof that.styleClass() === "string" ) { + cssClasses.push(that.styleClass()); + } + + cssClasses = cssClasses.concat(that.visualAttributes()); + + return cssClasses; + }; + + + // Reused functions TODO refactor + this.addMouseListeners = function (){ + // Empty node + if ( !that.nodeElement() ) { + console.warn(this); + return; + } + + that.nodeElement().selectAll("*") + .on("mouseover", onMouseOver) + .on("mouseout", onMouseOut); + }; + + this.animationProcess = function (){ + var animRuns = false; + if ( that.getHalos() ) { + var haloGr = that.getHalos(); + var haloEls = haloGr.selectAll(".searchResultA"); + animRuns = haloGr.attr("animationRunning"); + if ( typeof animRuns !== "boolean" ) { + // parse this to a boolean value + animRuns = (animRuns === 'true'); + } + if ( animRuns === false ) { + haloEls.classed("searchResultA", false); + haloEls.classed("searchResultB", true); + } + } + return animRuns; + }; + + this.foreground = function (){ + var selectedNode = that.nodeElement().node(), + nodeContainer = selectedNode.parentNode; + // check if the halo is present and an animation is running + if ( that.animationProcess() === false ) { + // Append hovered element as last child to the container list. + nodeContainer.appendChild(selectedNode); + } + + }; + + function onMouseOver(){ + if ( that.mouseEntered() || ignoreLocalHoverEvents === true ) { + return; + } + + var selectedNode = that.nodeElement().node(), + nodeContainer = selectedNode.parentNode; + + // Append hovered element as last child to the container list. + if ( that.animationProcess() === false ) { + nodeContainer.appendChild(selectedNode); + } + if ( graph.isTouchDevice() === false ) { + that.setHoverHighlighting(true); + that.mouseEntered(true); + if ( graph.editorMode() === true && graph.ignoreOtherHoverEvents() === false ) { + graph.activateHoverElements(true, that); + } + } else { + if ( graph.editorMode() === true && graph.ignoreOtherHoverEvents() === false ) { + graph.activateHoverElements(true, that, true); + } + + } + + + } + + function onMouseOut(){ + that.setHoverHighlighting(false); + that.mouseEntered(false); + if ( graph.editorMode() === true && graph.ignoreOtherHoverEvents() === false ) { + graph.activateHoverElements(false); + } + } + + + forceLayoutNodeFunctions.addTo(this); + }; + + Base.prototype = Object.create(BaseElement.prototype); + Base.prototype.constructor = Base; + + + return Base; + }()); + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 10 */ +/***/ (function(module, exports, __webpack_require__) { + + /** + * The base element for all visual elements of webvowl. + */ + module.exports = (function (){ + + var Base = function ( graph ){ + // Basic attributes + var equivalents = [], + id, + label, + type, + iri, + baseIri, + // Additional attributes + annotations, + attributes = [], + backgroundColor, + comment, + description, + equivalentBase, + visualAttributes = [], + // Style attributes + focused = false, + indications = [], + mouseEntered = false, + styleClass, + visible = true, + + backupLabel, + // Other + languageTools = __webpack_require__(11)(); + + + this.backupLabel = function ( label ){ + if ( !arguments.length ) return backupLabel; + backupLabel = label; + }; + // Properties + this.attributes = function ( p ){ + if ( !arguments.length ) return attributes; + attributes = p; + return this; + }; + + this.annotations = function ( p ){ + if ( !arguments.length ) return annotations; + annotations = p; + return this; + }; + + this.redrawElement = function (){ + // TODO: OVERLOADED BY INDIVIDUAL ELEMENTS + }; + + this.backgroundColor = function ( p ){ + if ( !arguments.length ) return backgroundColor; + backgroundColor = p; + return this; + }; + + this.baseIri = function ( p ){ + if ( !arguments.length ) return baseIri; + baseIri = p; + return this; + }; + + this.comment = function ( p ){ + if ( !arguments.length ) return comment; + comment = p; + return this; + }; + + this.description = function ( p ){ + if ( !arguments.length ) return description; + description = p; + return this; + }; + + this.equivalents = function ( p ){ + if ( !arguments.length ) return equivalents; + equivalents = p || []; + return this; + }; + + this.equivalentBase = function ( p ){ + if ( !arguments.length ) return equivalentBase; + equivalentBase = p; + return this; + }; + + this.focused = function ( p ){ + if ( !arguments.length ) return focused; + focused = p; + return this; + }; + + this.id = function ( p ){ + if ( !arguments.length ) return id; + id = p; + return this; + }; + + this.indications = function ( p ){ + if ( !arguments.length ) return indications; + indications = p; + return this; + }; + + this.iri = function ( p ){ + if ( !arguments.length ) return iri; + iri = p; + return this; + }; + + this.label = function ( p ){ + if ( !arguments.length ) return label; + label = p; + return this; + }; + + this.mouseEntered = function ( p ){ + if ( !arguments.length ) return mouseEntered; + mouseEntered = p; + return this; + }; + + this.styleClass = function ( p ){ + if ( !arguments.length ) return styleClass; + styleClass = p; + return this; + }; + + this.type = function ( p ){ + if ( !arguments.length ) return type; + type = p; + return this; + }; + + this.visible = function ( p ){ + if ( !arguments.length ) return visible; + visible = p; + return this; + }; + + this.visualAttributes = function ( p ){ + if ( !arguments.length ) return visualAttributes; + visualAttributes = p; + return this; + }; + + + this.commentForCurrentLanguage = function (){ + return languageTools.textInLanguage(this.comment(), graph.language()); + }; + + /** + * @returns {string} the css class of this node.. + */ + this.cssClassOfNode = function (){ + return "node" + this.id(); + }; + + this.descriptionForCurrentLanguage = function (){ + return languageTools.textInLanguage(this.description(), graph.language()); + }; + + this.defaultLabel = function (){ + return languageTools.textInLanguage(this.label(), "default"); + }; + + this.indicationString = function (){ + return this.indications().join(", "); + }; + + this.labelForCurrentLanguage = function (){ + var preferredLanguage = graph && graph.language ? graph.language() : null; + return languageTools.textInLanguage(this.label(), preferredLanguage); + }; + }; + + Base.prototype.constructor = Base; + + Base.prototype.equals = function ( other ){ + return other instanceof Base && this.id() === other.id(); + }; + + Base.prototype.toString = function (){ + return this.labelForCurrentLanguage() + " (" + this.type() + ")"; + }; + + + return Base; + }()); + + +/***/ }), +/* 11 */ +/***/ (function(module, exports, __webpack_require__) { + + var constants = __webpack_require__(12)(); + + /** + * Encapsulates methods which return a label in a specific language for a preferred language. + */ + module.exports = (function (){ + + var languageTools = {}; + + + languageTools.textInLanguage = function ( textObject, preferredLanguage ){ + if ( typeof textObject === "undefined" ) { + return undefined; + } + + if ( typeof textObject === "string" ) { + return textObject; + } + + if ( preferredLanguage && textObject.hasOwnProperty(preferredLanguage) ) { + return textObject[preferredLanguage]; + } + + var textForLanguage = searchLanguage(textObject, "en"); + if ( textForLanguage ) { + return textForLanguage; + } + textForLanguage = searchLanguage(textObject, constants.LANG_UNDEFINED); + if ( textForLanguage ) { + return textForLanguage; + } + + return textObject[constants.LANG_IRIBASED]; + }; + + + function searchLanguage( textObject, preferredLanguage ){ + for ( var language in textObject ) { + if ( language === preferredLanguage && textObject.hasOwnProperty(language) ) { + return textObject[language]; + } + } + } + + return function (){ + /* Use a function here to keep a consistent style like webvowl.path.to.module() + * despite having just a single languageTools object. */ + return languageTools; + }; + })(); + + +/***/ }), +/* 12 */ +/***/ (function(module, exports) { + + module.exports = (function (){ + + var constants = {}; + + constants.LANG_IRIBASED = "IRI-based"; + constants.LANG_UNDEFINED = "undefined"; + + return function (){ + /* Use a function here to keep a consistent style like webvowl.path.to.module() + * despite having just a single object. */ + return constants; + }; + })(); + + +/***/ }), +/* 13 */ +/***/ (function(module, exports) { + + /** + * The functions for controlling attributes of nodes of the force layout can't be modelled to the element hierarchy, + * which is used for inheriting visual and OWL-like attributes. + * + * To reduce code redundancy the common functions for controlling the force layout node attributes are excluded into this + * module, which can add them to the node objects. + * + * @type {{}} + */ + var nodeFunctions = {}; + module.exports = function (){ + return nodeFunctions; + }; + + + nodeFunctions.addTo = function ( node ){ + addFixedLocationFunctions(node); + }; + + function addFixedLocationFunctions( node ){ + var locked = false, + frozen = false, + halo = false, + pinned = false; + + node.locked = function ( p ){ + if ( !arguments.length ) { + return locked; + } + locked = p; + applyFixedLocationAttributes(); + return node; + }; + + node.frozen = function ( p ){ + if ( !arguments.length ) { + return frozen; + } + frozen = p; + applyFixedLocationAttributes(); + return node; + }; + + node.halo = function ( p ){ + if ( !arguments.length ) { + return halo; + } + halo = p; + applyFixedLocationAttributes(); + return node; + }; + + node.pinned = function ( p ){ + if ( !arguments.length ) { + return pinned; + } + pinned = p; + applyFixedLocationAttributes(); + return node; + }; + + function applyFixedLocationAttributes(){ + if ( node.locked() || node.frozen() || node.pinned() ) { + node.fixed = true; + } else { + node.fixed = false; + } + } + } + + +/***/ }), +/* 14 */ +/***/ (function(module, exports, __webpack_require__) { + + var textTools = __webpack_require__(15)(); + var AbstractTextElement = __webpack_require__(16); + + module.exports = CenteringTextElement; + function CenteringTextElement( container, backgroundColor ){ + AbstractTextElement.apply(this, arguments); + this.storedFullTextLines = []; + this.storedSpanArrays = []; + this.storedStyle = []; + + } + + CenteringTextElement.prototype = Object.create(AbstractTextElement.prototype); + CenteringTextElement.prototype.constructor = CenteringTextElement; + + CenteringTextElement.prototype.addText = function ( text, prefix, suffix ){ + if ( text ) { + this.addTextline(text, this.CSS_CLASSES.default, prefix, suffix); + } + }; + + CenteringTextElement.prototype.addSubText = function ( text ){ + if ( text ) { + this.addTextline(text, this.CSS_CLASSES.subtext, "(", ")"); + } + }; + + CenteringTextElement.prototype.addEquivalents = function ( text ){ + if ( text ) { + this.addTextline(text, this.CSS_CLASSES.default); + } + }; + + CenteringTextElement.prototype.addInstanceCount = function ( instanceCount ){ + if ( instanceCount ) { + this.addTextline(instanceCount.toString(), this.CSS_CLASSES.instanceCount); + } + }; + CenteringTextElement.prototype.saveCorrespondingSpan = function ( correspondingSpan ){ + this.storedSpanArrays.push(correspondingSpan); + }; + CenteringTextElement.prototype.saveFullTextLine = function ( fullText ){ + this.storedFullTextLines.push(fullText); + }; + CenteringTextElement.prototype.saveStyle = function ( style ){ + this.storedStyle.push(style); + }; + + CenteringTextElement.prototype.updateAllTextElements = function (){ + // TODO : TEST THIS postPrefix >>> _applyPreAndPostFix + for ( var i = 0; i < this.storedSpanArrays.length; i++ ) { + var truncatedText = textTools.truncate(this.storedFullTextLines[i], this._textBlock().datum().textWidth(), this.storedStyle[i]); + this.storedSpanArrays[i].text(truncatedText); + } + }; + + + CenteringTextElement.prototype.addTextline = function ( text, style, prefix, postfix ){ + var truncatedText = textTools.truncate(text, this._textBlock().datum().textWidth(), style); + this.saveFullTextLine(text); + this.saveStyle(style); + var tspan = this._textBlock().append("tspan") + .classed(this.CSS_CLASSES.default, true) + .classed(style, true) + .text(this._applyPreAndPostFix(truncatedText, prefix, postfix)) + .attr("x", 0); + this._repositionTextLine(tspan); + this.saveCorrespondingSpan(tspan); + + this._repositionTextBlock(); + }; + + CenteringTextElement.prototype._repositionTextLine = function ( tspan ){ + var fontSizeProperty = window.getComputedStyle(tspan.node()).getPropertyValue("font-size"); + var fontSize = parseFloat(fontSizeProperty); + + var siblingCount = this._lineCount() - 1; + var lineDistance = siblingCount > 0 ? this.LINE_DISTANCE : 0; + + tspan.attr("dy", fontSize + lineDistance + "px"); + }; + + CenteringTextElement.prototype.getTextBox = function (){ + return this._textBlock(); + }; + + + CenteringTextElement.prototype._repositionTextBlock = function (){ + // Nothing to do if no child elements exist + var lineCount = this._lineCount(); + if ( lineCount < 1 ) { + this._textBlock().attr("y", 0); + return; + } + + var textBlockHeight = this._textBlock().node().getBBox().height; + this._textBlock().attr("y", -textBlockHeight * 0.5 + "px"); + }; + + CenteringTextElement.prototype._lineCount = function (){ + return this._textBlock().property("childElementCount"); + }; + + +/***/ }), +/* 15 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var ADDITIONAL_TEXT_SPACE = 4; + + var tools = {}; + + function measureTextWidth( text, textStyle ){ + // Set a default value + if ( !textStyle ) { + textStyle = "text"; + } + var d = d3.select("body") + .append("div") + .attr("class", textStyle) + .attr("id", "width-test") // tag this element to identify it + .attr("style", "position:absolute; float:left; white-space:nowrap; visibility:hidden;") + .text(text), + w = document.getElementById("width-test").offsetWidth; + d.remove(); + return w; + } + + tools.truncate = function ( text, maxWidth, textStyle, additionalTextSpace ){ + maxWidth -= isNaN(additionalTextSpace) ? ADDITIONAL_TEXT_SPACE : additionalTextSpace; + if ( isNaN(maxWidth) || maxWidth <= 0 ) { + return text; + } + + var truncatedText = text, + newTruncatedTextLength, + textWidth, + ratio; + + while ( true ) { + textWidth = measureTextWidth(truncatedText, textStyle); + if ( textWidth <= maxWidth ) { + break; + } + + ratio = textWidth / maxWidth; + newTruncatedTextLength = Math.floor(truncatedText.length / ratio); + + // detect if nothing changes + if ( truncatedText.length === newTruncatedTextLength ) { + break; + } + + truncatedText = truncatedText.substring(0, newTruncatedTextLength); + } + + if ( text.length > truncatedText.length ) { + return text.substring(0, truncatedText.length - 3) + "..."; + } + return text; + }; + + + module.exports = function (){ + return tools; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 16 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = AbstractTextElement; + + function AbstractTextElement( container, backgroundColor ){ + var textBlock = container.append("text") + .classed("text", true) + .style("fill", this._getTextColor(backgroundColor)) + .attr("text-anchor", "middle"); + + this._textBlock = function (){ + return textBlock; + }; + } + + AbstractTextElement.prototype.LINE_DISTANCE = 1; + AbstractTextElement.prototype.CSS_CLASSES = { + default: "text", + subtext: "subtext", + instanceCount: "instance-count" + }; + AbstractTextElement.prototype.DARK_TEXT_COLOR = "#000"; + AbstractTextElement.prototype.LIGHT_TEXT_COLOR = "#fff"; + + AbstractTextElement.prototype.translation = function ( x, y ){ + this._textBlock().attr("transform", "translate(" + x + ", " + y + ")"); + return this; + }; + + AbstractTextElement.prototype.remove = function (){ + this._textBlock().remove(); + return this; + }; + + AbstractTextElement.prototype._applyPreAndPostFix = function ( text, prefix, postfix ){ + if ( prefix ) { + text = prefix + text; + } + if ( postfix ) { + text += postfix; + } + return text; + }; + + AbstractTextElement.prototype._getTextColor = function ( rawBackgroundColor ){ + if ( !rawBackgroundColor ) { + return AbstractTextElement.prototype.DARK_TEXT_COLOR; + } + + var backgroundColor = d3.rgb(rawBackgroundColor); + if ( calculateLuminance(backgroundColor) > 0.5 ) { + return AbstractTextElement.prototype.DARK_TEXT_COLOR; + } else { + return AbstractTextElement.prototype.LIGHT_TEXT_COLOR; + } + }; + + function calculateLuminance( color ){ + return 0.3 * (color.r / 255) + 0.59 * (color.g / 255) + 0.11 * (color.b / 255); + } + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 17 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains reusable function for drawing nodes. + */ + module.exports = (function (){ + + var tools = {}; + + /** + * Append a circular class node with the passed attributes. + * @param parent the parent element to which the circle will be appended + * @param radius + * @param [cssClasses] an array of additional css classes + * @param [tooltip] + * @param [backgroundColor] + * @returns {*} + */ + tools.appendCircularClass = function ( parent, radius, cssClasses, tooltip, backgroundColor ){ + var circle = parent.append("circle") + .classed("class", true) + .attr("r", radius); + + addCssClasses(circle, cssClasses); + addToolTip(circle, tooltip); + addBackgroundColor(circle, backgroundColor); + + return circle; + }; + + function addCssClasses( element, cssClasses ){ + if ( cssClasses instanceof Array ) { + cssClasses.forEach(function ( cssClass ){ + element.classed(cssClass, true); + }); + } + } + + function addToolTip( element, tooltip ){ + if ( tooltip ) { + element.append("title").text(tooltip); + } + } + + function addBackgroundColor( element, backgroundColor ){ + if ( backgroundColor ) { + element.style("fill", backgroundColor); + } + } + + /** + * Appends a rectangular class node with the passed attributes. + * @param parent the parent element to which the rectangle will be appended + * @param width + * @param height + * @param [cssClasses] an array of additional css classes + * @param [tooltip] + * @param [backgroundColor] + * @returns {*} + */ + tools.appendRectangularClass = function ( parent, width, height, cssClasses, tooltip, backgroundColor ){ + var rectangle = parent.append("rect") + .classed("class", true) + .attr("x", -width / 2) + .attr("y", -height / 2) + .attr("width", width) + .attr("height", height); + + addCssClasses(rectangle, cssClasses); + addToolTip(rectangle, tooltip); + addBackgroundColor(rectangle, backgroundColor); + + return rectangle; + }; + + tools.drawPin = function ( container, dx, dy, onClick, accuraciesHelperFunction, useAccuracyHelper ){ + var pinGroupElement = container + .append("g") + .classed("hidden-in-export", true) + .attr("transform", "translate(" + dx + "," + dy + ")"); + + var base = pinGroupElement.append("circle") + .classed("class pin feature", true) + .attr("r", 12) + .on("click", function (){ + if ( onClick ) { + onClick(); + } + d3.event.stopPropagation(); + }); + + pinGroupElement.append("line") + .attr("x1", 0) + .attr("x2", 0) + .attr("y1", 12) + .attr("y2", 16); + + if ( useAccuracyHelper === true ) { + pinGroupElement.append("circle") + .attr("r", 15) + .attr("cx", -7) + .attr("cy", -7) + .classed("superHiddenElement ", true) + .classed("superOpacityElement", !accuraciesHelperFunction()) + .on("click", function (){ + if ( onClick ) { + onClick(); + } + d3.event.stopPropagation(); + }) + .on("mouseover", function (){ + base.classed("feature_hover", true); + }) + .on("mouseout", function (){ + base.classed("feature_hover", false); + }) + ; + + } + + + return pinGroupElement; + }; + + tools.drawRectHalo = function ( node, width, height, offset ){ + var container; + if ( node.nodeElement ) + container = node.nodeElement(); + else + container = node.labelElement(); + + if ( !container ) { + // console.log("no container found"); + return; + } + + var haloGroupElement = container + .append("g") + .classed("hidden-in-export", true); + + haloGroupElement.append("rect") + .classed("searchResultA", true) + .attr("x", (-width - offset) / 2) + .attr("y", (-offset - height) / 2) + .attr("width", width + offset) + .attr("height", height + offset); + haloGroupElement.attr("animationRunning", true); + + haloGroupElement.node().addEventListener("webkitAnimationEnd", function (){ + var test = haloGroupElement.selectAll(".searchResultA"); + test.classed("searchResultA", false) + .classed("searchResultB", true); + haloGroupElement.attr("animationRunning", false); + }); + haloGroupElement.node().addEventListener("animationend", function (){ + var test = haloGroupElement.selectAll(".searchResultA"); + test.classed("searchResultA", false) + .classed("searchResultB", true); + haloGroupElement.attr("animationRunning", false); + }); + + + return haloGroupElement; + + }; + tools.drawHalo = function ( container, radius ){ + if ( container === undefined ) { + return null; + // there is no element to add the halo to; + // this means the node was not rendered previously + } + + var haloGroupElement = container + .append("g") + .classed("hidden-in-export", true); + + + haloGroupElement.append("circle", ":first-child") + .classed("searchResultA", true) + .attr("r", radius + 15); + haloGroupElement.attr("animationRunning", true); + + + haloGroupElement.node().addEventListener("webkitAnimationEnd", function (){ + var test = haloGroupElement.selectAll(".searchResultA"); + test.classed("searchResultA", false) + .classed("searchResultB", true) + .attr("animationRunning", false); + haloGroupElement.attr("animationRunning", false); + }); + haloGroupElement.node().addEventListener("animationend", function (){ + var test = haloGroupElement.selectAll(".searchResultA"); + test.classed("searchResultA", false) + .classed("searchResultB", true) + .attr("animationRunning", false); + haloGroupElement.attr("animationRunning", false); + }); + + return haloGroupElement; + }; + + return function (){ + // Encapsulate into function to maintain default.module.path() + return tools; + }; + })(); + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 18 */ +/***/ (function(module, exports, __webpack_require__) { + + var RoundNode = __webpack_require__(8); + + module.exports = (function (){ + + var o = function ( graph ){ + RoundNode.apply(this, arguments); + + this.type("owl:Class"); + }; + o.prototype = Object.create(RoundNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 19 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetOperatorNode = __webpack_require__(20); + + module.exports = (function (){ + + var o = function ( graph ){ + SetOperatorNode.apply(this, arguments); + + var that = this, + superDrawFunction = that.draw; + + this.styleClass("complementof") + .type("owl:complementOf"); + + this.draw = function ( element ){ + superDrawFunction(element); + + var symbol = element.append("g").classed("embedded", true); + + symbol.append("circle") + .attr("class", "symbol") + .classed("fineline", true) + .attr("r", 10); + symbol.append("path") + .attr("class", "nofill") + .attr("d", "m -7,-1.5 12,0 0,6") + .attr("transform", "scale(.5)"); + + symbol.attr("transform", + "translate(-" + (that.radius() - 15) / 100 + ",-" + (that.radius() - 15) / 100 + ")"); + + that.postDrawActions(); + }; + }; + o.prototype = Object.create(SetOperatorNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 20 */ +/***/ (function(module, exports, __webpack_require__) { + + var AbsoluteTextElement = __webpack_require__(21); + var BoxArrowLink = __webpack_require__(22); + var RoundNode = __webpack_require__(8); + var drawTools = __webpack_require__(17)(); + + module.exports = (function (){ + + var o = function ( graph ){ + RoundNode.apply(this, arguments); + + var that = this, + superHoverHighlightingFunction = that.setHoverHighlighting, + superPostDrawActions = that.postDrawActions; + + this.setHoverHighlighting = function ( enable ){ + superHoverHighlightingFunction(enable); + + // Highlight links pointing to included nodes when hovering the set operator + that.links() + .filter(function ( link ){ + return link instanceof BoxArrowLink; + }) + .filter(function ( link ){ + return link.domain().equals(that); + }) + .forEach(function ( link ){ + link.property().setHighlighting(enable); + }); + }; + + this.draw = function ( element ){ + that.nodeElement(element); + + drawTools.appendCircularClass(element, that.actualRadius(), + that.collectCssClasses().join(" "), + that.labelForCurrentLanguage(), that.backgroundColor()); + }; + + this.postDrawActions = function (){ + superPostDrawActions(); + that.textBlock().remove(); + + var textElement = new AbsoluteTextElement(that.nodeElement(), that.backgroundColor()); + + var equivalentsString = that.equivalentsString(); + var offsetForFollowingEquivalents = equivalentsString ? -30 : -17; + var suffixForFollowingEquivalents = equivalentsString ? "," : ""; + textElement.addText(that.labelForCurrentLanguage(), offsetForFollowingEquivalents, "", + suffixForFollowingEquivalents); + + textElement.addEquivalents(equivalentsString, -17); + + + if ( !graph.options().compactNotation() ) { + + if ( that.indicationString().length > 0 ) { + textElement.addSubText(that.indicationString(), 17); + textElement.addInstanceCount(that.individuals().length, 30); + } else { + textElement.addInstanceCount(that.individuals().length, 17); + } + } else { + textElement.addInstanceCount(that.individuals().length, 17); + } + + that.textBlock(textElement); + }; + }; + o.prototype = Object.create(RoundNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 21 */ +/***/ (function(module, exports, __webpack_require__) { + + var textTools = __webpack_require__(15)(); + var AbstractTextElement = __webpack_require__(16); + + module.exports = AbsoluteTextElement; + function AbsoluteTextElement( container, backgroundColor ){ + AbstractTextElement.apply(this, arguments); + } + + AbsoluteTextElement.prototype = Object.create(AbstractTextElement.prototype); + AbsoluteTextElement.prototype.constructor = AbsoluteTextElement; + + AbsoluteTextElement.prototype.addText = function ( text, yShift, prefix, suffix ){ + if ( text ) { + this.addTextline(text, this.CSS_CLASSES.default, yShift, prefix, suffix); + } + }; + + AbsoluteTextElement.prototype.addSubText = function ( text, yShift ){ + if ( text ) { + this.addTextline(text, this.CSS_CLASSES.subtext, yShift, "(", ")"); + } + }; + + AbsoluteTextElement.prototype.addEquivalents = function ( text, yShift ){ + if ( text ) { + this.addTextline(text, this.CSS_CLASSES.default, yShift); + } + }; + + AbsoluteTextElement.prototype.addInstanceCount = function ( instanceCount, yShift ){ + if ( instanceCount ) { + this.addTextline(instanceCount.toString(), this.CSS_CLASSES.instanceCount, yShift); + } + }; + + + AbsoluteTextElement.prototype.addTextline = function ( text, style, yShift, prefix, postfix ){ + var truncatedText = textTools.truncate(text, this._textBlock().datum().textWidth(yShift), style); + + var tspan = this._textBlock().append("tspan") + .classed(this.CSS_CLASSES.default, true) + .classed(style, true) + .text(this._applyPreAndPostFix(truncatedText, prefix, postfix)) + .attr("x", 0); + this._repositionTextLine(tspan, yShift); + }; + + AbsoluteTextElement.prototype._repositionTextLine = function ( tspan, yShift ){ + var fontSizeProperty = window.getComputedStyle(tspan.node()).getPropertyValue("font-size"); + var fontSize = parseFloat(fontSizeProperty); + + /* BBox height is not supported in Firefox for tspans and dominant-baseline doesn't work in some SVG editors */ + var approximatedShiftForVerticalCentering = (1 / 3) * fontSize; + + tspan.attr("y", approximatedShiftForVerticalCentering + (yShift || 0) + "px"); + }; + + +/***/ }), +/* 22 */ +/***/ (function(module, exports, __webpack_require__) { + + var PlainLink = __webpack_require__(23); + + + module.exports = BoxArrowLink; + + function BoxArrowLink( domain, range, property ){ + PlainLink.apply(this, arguments); + } + + BoxArrowLink.prototype = Object.create(PlainLink.prototype); + BoxArrowLink.prototype.constructor = BoxArrowLink; + + + BoxArrowLink.prototype.draw = function ( linkGroup, markerContainer ){ + var property = this.label().property(); + var inverse = this.label().inverse(); + + createPropertyMarker(markerContainer, property); + if ( inverse ) { + createInverseMarker(markerContainer, inverse); + } + + PlainLink.prototype.draw.apply(this, arguments); + + // attach the markers to the link + linkGroup.attr("marker-start", "url(#" + property.markerId() + ")"); + if ( inverse ) { + linkGroup.attr("marker-end", "url(#" + inverse.markerId() + ")"); + } + }; + + + function createPropertyMarker( markerContainer, inverse ){ + var inverseMarker = appendBasicMarker(markerContainer, inverse); + inverseMarker.attr("refX", -8); + inverseMarker.append("path") + .attr("d", "M0,-8L8,0L0,8L-8,0L0,-8L8,0") + .classed(inverse.markerType(), true); + + inverse.markerElement(inverseMarker); + } + + function createInverseMarker( markerContainer, property ){ + var marker = appendBasicMarker(markerContainer, property); + marker.attr("refX", 8); + marker.append("path") + .attr("d", "M0,-8L8,0L0,8L-8,0L0,-8L8,0") + .classed(property.markerType(), true); + + property.markerElement(marker); + } + + function appendBasicMarker( markerContainer, property ){ + return markerContainer.append("marker") + .datum(property) + .attr("id", property.markerId()) + .attr("viewBox", "-10 -10 20 20") + .attr("markerWidth", 20) + .attr("markerHeight", 20) + .attr("markerUnits", "userSpaceOnUse") + .attr("orient", "auto"); + } + + +/***/ }), +/* 23 */ +/***/ (function(module, exports, __webpack_require__) { + + var Label = __webpack_require__(24); + + + module.exports = PlainLink; + + /** + * A link connects at least two VOWL nodes. + * The properties connecting the VOWL nodes are stored separately into the label. + * @param domain + * @param range + * @param property + */ + function PlainLink( domain, range, property ){ + var layers, + layerIndex, + loops, + loopIndex, + pathEl, + label = new Label(property, this); + + var backPart = __webpack_require__(25)(domain, label, this), + frontPart = __webpack_require__(25)(label, range, this); + + + this.layers = function ( p ){ + if ( !arguments.length ) return layers; + layers = p; + return this; + }; + + this.layerIndex = function ( p ){ + if ( !arguments.length ) return layerIndex; + layerIndex = p; + return this; + }; + + this.loops = function ( p ){ + if ( !arguments.length ) return loops; + loops = p; + return this; + }; + + this.loopIndex = function ( p ){ + if ( !arguments.length ) return loopIndex; + loopIndex = p; + return this; + }; + + + this.domain = function (){ + return domain; + }; + + this.label = function (){ + return label; + }; + + this.linkParts = function (){ + return [frontPart, backPart]; + }; + + this.range = function (){ + return range; + }; + this.pathObj = function ( pE ){ + if ( !arguments.length ) { + return pathEl; + } + pathEl = pE; + }; + } + + + PlainLink.prototype.draw = function ( linkGroup ){ + var property = this.label().property(); + var inverse = this.label().inverse(); + + property.linkGroup(linkGroup); + if ( inverse ) { + inverse.linkGroup(linkGroup); + } + + var pathElement = linkGroup.append("path"); + pathElement.classed("link-path", true) + .classed(this.domain().cssClassOfNode(), true) + .classed(this.range().cssClassOfNode(), true) + .classed(property.linkType(), true); + this.pathObj(pathElement); + + }; + + + PlainLink.prototype.inverse = function (){ + return this.label().inverse(); + }; + + PlainLink.prototype.isLoop = function (){ + return this.domain().equals(this.range()); + }; + + PlainLink.prototype.property = function (){ + return this.label().property(); + }; + + + +/***/ }), +/* 24 */ +/***/ (function(module, exports) { + + module.exports = Label; + + /** + * A label represents the element(s) which further describe a link. + * It encapsulates the property and its inverse property. + * @param property the property; the inverse is inferred + * @param link the link this label belongs to + */ + function Label( property, link ){ + this.link = function (){ + return link; + }; + + this.property = function (){ + return property; + }; + + // "Forward" the fixed value set on the property to avoid having to access this container + Object.defineProperty(this, "fixed", { + get: function (){ + var inverseFixed = property.inverse() ? property.inverse().fixed : false; + return property.fixed || inverseFixed; + }, + set: function ( v ){ + property.fixed = v; + if ( property.inverse() ) property.inverse().fixed = v; + } + }); + this.frozen = property.frozen; + this.locked = property.locked; + this.pinned = property.pinned; + } + + Label.prototype.actualRadius = function (){ + return this.property().actualRadius(); + }; + + Label.prototype.draw = function ( container ){ + return this.property().draw(container); + }; + + Label.prototype.inverse = function (){ + return this.property().inverse(); + }; + + Label.prototype.equals = function ( other ){ + if ( !other ) { + return false; + } + + var instance = other instanceof Label; + var equalProperty = this.property().equals(other.property()); + + var equalInverse = false; + if ( this.inverse() ) { + equalInverse = this.inverse().equals(other.inverse()); + } else if ( !other.inverse() ) { + equalInverse = true; + } + + return instance && equalProperty && equalInverse; + }; + + +/***/ }), +/* 25 */ +/***/ (function(module, exports) { + + /** + * A linkPart connects two force layout nodes. + * It reprents a link which can be used in d3's force layout. + * @param _domain + * @param _range + * @param _link + */ + module.exports = function ( _domain, _range, _link ){ + var linkPart = {}, + domain = _domain, + link = _link, + range = _range; + + // Define d3 properties + Object.defineProperties(linkPart, { + "source": { value: domain, writable: true }, + "target": { value: range, writable: true } + }); + + + linkPart.domain = function (){ + return domain; + }; + + linkPart.link = function (){ + return link; + }; + + linkPart.range = function (){ + return range; + }; + + + return linkPart; + }; + + +/***/ }), +/* 26 */ +/***/ (function(module, exports, __webpack_require__) { + + var RoundNode = __webpack_require__(8); + + module.exports = (function (){ + + var o = function ( graph ){ + RoundNode.apply(this, arguments); + + this.attributes(["deprecated"]) + .type("owl:DeprecatedClass") + .styleClass("deprecated") + .indications(["deprecated"]); + }; + o.prototype = Object.create(RoundNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 27 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetOperatorNode = __webpack_require__(20); + + module.exports = (function (){ + + var o = function ( graph ){ + SetOperatorNode.apply(this, arguments); + + var that = this, + superDrawFunction = that.draw; + + this.styleClass("disjointunionof") + .type("owl:disjointUnionOf"); + + this.draw = function ( element ){ + superDrawFunction(element); + + var symbol = element.append("g").classed("embedded", true); + + var symbolRadius = 10; + symbol.append("circle") + .attr("class", "symbol") + .attr("r", symbolRadius); + symbol.append("circle") + .attr("cx", 10) + .attr("class", "symbol") + .classed("fineline", true) + .attr("r", symbolRadius); + symbol.append("circle") + .attr("class", "nofill") + .classed("fineline", true) + .attr("r", symbolRadius); + symbol.append("text") + .attr("class", "link") + .text("1") + .attr("transform", "scale(.7)translate(3,5)"); + + symbol.attr("transform", "translate(-" + (that.radius() - 15) / 7 + ",-" + (that.radius() - 15) / 100 + ")"); + + that.postDrawActions(); + }; + }; + o.prototype = Object.create(SetOperatorNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 28 */ +/***/ (function(module, exports, __webpack_require__) { + + var RoundNode = __webpack_require__(8); + var drawTools = __webpack_require__(17)(); + + module.exports = (function (){ + + var o = function ( graph ){ + RoundNode.apply(this, arguments); + + var CIRCLE_SIZE_DIFFERENCE = 4; + var renderingElement; + var that = this, + superActualRadiusFunction = that.actualRadius; + + this.styleClass("equivalentclass") + .type("owl:equivalentClass"); + + this.actualRadius = function (){ + return superActualRadiusFunction() + CIRCLE_SIZE_DIFFERENCE; + }; + + this.redrawElement = function (){ + renderingElement.remove(); + that.textBlock().remove(); + var bgColor = that.backgroundColor(); + + if ( that.attributes().indexOf("deprecated") > -1 ) { + bgColor = undefined; + } + var cssClasses = that.collectCssClasses(); + renderingElement = that.nodeElement().append("g"); + + if ( that.getRectangularRepresentation() === true ) { + drawTools.appendRectangularClass(renderingElement, 84, 84, ["white", "embedded"]); + drawTools.appendRectangularClass(renderingElement, 80 - CIRCLE_SIZE_DIFFERENCE, 80 - CIRCLE_SIZE_DIFFERENCE, cssClasses, that.labelForCurrentLanguage(), bgColor); + } else { + drawTools.appendCircularClass(renderingElement, that.actualRadius(), ["white", "embedded"]); + console.log(cssClasses); + console.log(that.attributes()); + console.log("what is bgColor" + bgColor); + drawTools.appendCircularClass(renderingElement, that.actualRadius() - CIRCLE_SIZE_DIFFERENCE, cssClasses, that.labelForCurrentLanguage(), bgColor); + + } + that.postDrawActions(that.nodeElement()); + + }; + this.draw = function ( parentElement ){ + var cssClasses = that.collectCssClasses(); + + that.nodeElement(parentElement); + renderingElement = parentElement.append("g"); + var bgColor = that.backgroundColor(); + if ( that.attributes().indexOf("deprecated") > -1 ) { + bgColor = undefined; + } + // draw the outer circle at first and afterwards the inner circle + if ( that.getRectangularRepresentation() === true ) { + drawTools.appendRectangularClass(renderingElement, 84, 84, ["white", "embedded"]); + drawTools.appendRectangularClass(renderingElement, 80 - CIRCLE_SIZE_DIFFERENCE, 80 - CIRCLE_SIZE_DIFFERENCE, cssClasses, that.labelForCurrentLanguage(), bgColor); + } else { + drawTools.appendCircularClass(renderingElement, that.actualRadius(), ["white", "embedded"]); + drawTools.appendCircularClass(renderingElement, that.actualRadius() - CIRCLE_SIZE_DIFFERENCE, cssClasses, that.labelForCurrentLanguage(), bgColor); + + } + + that.postDrawActions(); + }; + + /** + * Sets the hover highlighting of this node. + * @param enable + */ + that.setHoverHighlighting = function ( enable ){ + that.nodeElement().selectAll("circle:last-of-type").classed("hovered", enable); + }; + }; + o.prototype = Object.create(RoundNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 29 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetOperatorNode = __webpack_require__(20); + + module.exports = (function (){ + + var o = function ( graph ){ + SetOperatorNode.apply(this, arguments); + + var that = this, + superDrawFunction = that.draw, + INTERSECTION_BACKGROUND_PATH = createIntersectionPath(); + + this.styleClass("intersectionof") + .type("owl:intersectionOf"); + + this.draw = function ( element ){ + superDrawFunction(element); + + var symbol = element.append("g").classed("embedded", true); + + var symbolRadius = 10; + symbol.append("path") + .attr("class", "nostroke") + .classed("symbol", true) + .attr("d", INTERSECTION_BACKGROUND_PATH); + symbol.append("circle") + .attr("class", "nofill") + .classed("fineline", true) + .attr("r", symbolRadius); + symbol.append("circle") + .attr("cx", 10) + .attr("class", "nofill") + .classed("fineline", true) + .attr("r", symbolRadius); + symbol.append("path") + .attr("class", "nofill") + .attr("d", "m 9,5 c 0,-2 0,-4 0,-6 0,0 0,0 0,0 0,0 0,-1.8 -1,-2.3 -0.7,-0.6 -1.7,-0.8 -2.9," + + "-0.8 -1.2,0 -2,0 -3,0.8 -0.7,0.5 -1,1.4 -1,2.3 0,2 0,4 0,6") + .attr("transform", "scale(.5)translate(5,0)"); + + symbol.attr("transform", + "translate(-" + (that.radius() - 15) / 7 + ",-" + (that.radius() - 15) / 100 + ")"); + + that.postDrawActions(); + }; + + function createIntersectionPath(){ + var height = 18; + + var offsetX = 5; + var offsetY = -(height / 2); + + var bezierX = 7; + var bezierY = 5; + var bottomBezierY = height - bezierY; + + var startPosition = "M" + offsetX + "," + offsetY; + var rightSide = "c" + bezierX + "," + bezierY + " " + bezierX + "," + bottomBezierY + " 0," + height; + var leftSide = "c" + -bezierX + "," + -bezierY + " " + -bezierX + "," + -bottomBezierY + " 0," + -height; + + return startPosition + rightSide + leftSide; + } + }; + o.prototype = Object.create(SetOperatorNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 30 */ +/***/ (function(module, exports, __webpack_require__) { + + var OwlThing = __webpack_require__(31); + + module.exports = (function (){ + + var o = function ( graph ){ + OwlThing.apply(this, arguments); + + this.label("Nothing") + .type("owl:Nothing") + .iri("http://www.w3.org/2002/07/owl#Nothing"); + }; + o.prototype = Object.create(OwlThing.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 31 */ +/***/ (function(module, exports, __webpack_require__) { + + var RoundNode = __webpack_require__(8); + + module.exports = (function (){ + + var o = function ( graph ){ + RoundNode.apply(this, arguments); + + var superDrawFunction = this.draw; + + this.label("Thing") + .type("owl:Thing") + .iri("http://www.w3.org/2002/07/owl#Thing") + .radius(30); + + this.draw = function ( element ){ + superDrawFunction(element, ["white", "dashed"]); + }; + }; + o.prototype = Object.create(RoundNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 32 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetOperatorNode = __webpack_require__(20); + + module.exports = (function (){ + + var o = function ( graph ){ + SetOperatorNode.apply(this, arguments); + + var that = this, + superDrawFunction = that.draw; + + this.styleClass("unionof") + .type("owl:unionOf"); + + this.draw = function ( element ){ + superDrawFunction(element); + + var symbol = element.append("g").classed("embedded", true); + + var symbolRadius = 10; + symbol.append("circle") + .attr("class", "symbol") + .attr("r", symbolRadius); + symbol.append("circle") + .attr("cx", 10) + .attr("class", "symbol") + .classed("fineline", true) + .attr("r", symbolRadius); + symbol.append("circle") + .attr("class", "nofill") + .classed("fineline", true) + .attr("r", symbolRadius); + symbol.append("path") + .attr("class", "link") + .attr("d", "m 1,-3 c 0,2 0,4 0,6 0,0 0,0 0,0 0,2 2,3 4,3 2,0 4,-1 4,-3 0,-2 0,-4 0,-6") + .attr("transform", "scale(.5)translate(5,0)"); + + symbol.attr("transform", "translate(-" + (that.radius() - 15) / 7 + ",-" + (that.radius() - 15) / 100 + ")"); + + that.postDrawActions(); + }; + }; + o.prototype = Object.create(SetOperatorNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 33 */ +/***/ (function(module, exports, __webpack_require__) { + + var RoundNode = __webpack_require__(8); + + module.exports = (function (){ + + var o = function ( graph ){ + RoundNode.apply(this, arguments); + + this.attributes(["rdf"]) + .type("rdfs:Class"); + }; + o.prototype = Object.create(RoundNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 34 */ +/***/ (function(module, exports, __webpack_require__) { + + var DatatypeNode = __webpack_require__(35); + + module.exports = (function (){ + + var o = function ( graph ){ + DatatypeNode.apply(this, arguments); + var dTypeString = "undefined"; + this.attributes(["datatype"]) + .type("rdfs:Datatype") + .styleClass("datatype"); + this.dType = function ( val ){ + if ( !arguments.length ) return dTypeString; + dTypeString = val; + + }; + }; + o.prototype = Object.create(DatatypeNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 35 */ +/***/ (function(module, exports, __webpack_require__) { + + var RectangularNode = __webpack_require__(36); + + module.exports = (function (){ + + var o = function ( graph ){ + RectangularNode.apply(this, arguments); + }; + o.prototype = Object.create(RectangularNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 36 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var BaseNode = __webpack_require__(9); + var CenteringTextElement = __webpack_require__(14); + var drawTools = __webpack_require__(17)(); + var rectangularElementTools = __webpack_require__(37)(); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseNode.apply(this, arguments); + + var that = this, + height = 20, + width = 60, + pinGroupElement, + haloGroupElement, + labelWidth = 80, + myWidth = 80, + defaultWidth = 80, + shapeElement, + textBlock, + smallestRadius = height / 2; + + that.renderType("rect"); + // Properties + this.height = function ( p ){ + if ( !arguments.length ) return height; + height = p; + return this; + }; + + this.width = function ( p ){ + if ( !arguments.length ) return width; + width = p; + return this; + }; + + this.getHalos = function (){ + return haloGroupElement; + }; + + // Functions + // for compatibility reasons // TODO resolve + this.actualRadius = function (){ + return smallestRadius; + }; + + this.distanceToBorder = function ( dx, dy ){ + return rectangularElementTools.distanceToBorder(that, dx, dy); + }; + + this.setHoverHighlighting = function ( enable ){ + that.nodeElement().selectAll("rect").classed("hovered", enable); + + var haloGroup = that.getHalos(); + if ( haloGroup ) { + var test = haloGroup.selectAll(".searchResultA"); + test.classed("searchResultA", false); + test.classed("searchResultB", true); + } + + }; + + + // overwrite the labelWith; + + + this.textWidth = function (){ + return labelWidth; + }; + this.width = function (){ + return labelWidth; + }; + + this.getMyWidth = function (){ + // use a simple heuristic + var text = that.labelForCurrentLanguage(); + myWidth = measureTextWidth(text, "text") + 20; + + // check for sub names; + var indicatorText = that.indicationString(); + var indicatorWidth = measureTextWidth(indicatorText, "subtext") + 20; + if ( indicatorWidth > myWidth ) + myWidth = indicatorWidth; + + return myWidth; + }; + + this.textWidth = function (){ + return that.width(); + }; + function measureTextWidth( text, textStyle ){ + // Set a default value + if ( !textStyle ) { + textStyle = "text"; + } + var d = d3.select("body") + .append("div") + .attr("class", textStyle) + .attr("id", "width-test") // tag this element to identify it + .attr("style", "position:absolute; float:left; white-space:nowrap; visibility:hidden;") + .text(text), + w = document.getElementById("width-test").offsetWidth; + d.remove(); + return w; + } + + this.toggleFocus = function (){ + that.focused(!that.focused()); + that.nodeElement().select("rect").classed("focused", that.focused()); + graph.resetSearchHighlight(); + graph.options().searchMenu().clearText(); + }; + + /** + * Draws the rectangular node. + * @param parentElement the element to which this node will be appended + * @param [additionalCssClasses] additional css classes + */ + this.draw = function ( parentElement, additionalCssClasses ){ + var cssClasses = that.collectCssClasses(); + + that.nodeElement(parentElement); + + if ( additionalCssClasses instanceof Array ) { + cssClasses = cssClasses.concat(additionalCssClasses); + } + + // set the value for that.width() + // update labelWidth Value; + if ( graph.options().dynamicLabelWidth() === true ) labelWidth = Math.min(that.getMyWidth(), graph.options().maxLabelWidth()); + else labelWidth = defaultWidth; + + width = labelWidth; + shapeElement = drawTools.appendRectangularClass(parentElement, that.width(), that.height(), cssClasses, that.labelForCurrentLanguage(), that.backgroundColor()); + + textBlock = new CenteringTextElement(parentElement, that.backgroundColor()); + textBlock.addText(that.labelForCurrentLanguage()); + + that.addMouseListeners(); + + if ( that.pinned() ) { + that.drawPin(); + } + if ( that.halo() ) { + that.drawHalo(false); + } + }; + + this.drawPin = function (){ + that.pinned(true); + // if (graph.options().dynamicLabelWidth()===true) labelWidth=that.getMyWidth(); + // else labelWidth=defaultWidth; + // width=labelWidth; + // console.log("this element label Width is "+labelWidth); + var dx = -0.5 * labelWidth + 5, + dy = -1.1 * height; + + pinGroupElement = drawTools.drawPin(that.nodeElement(), dx, dy, this.removePin, graph.options().showDraggerObject, graph.options().useAccuracyHelper()); + + }; + + this.removePin = function (){ + that.pinned(false); + if ( pinGroupElement ) { + pinGroupElement.remove(); + } + graph.updateStyle(); + }; + + this.removeHalo = function (){ + that.halo(false); + if ( haloGroupElement ) { + haloGroupElement.remove(); + haloGroupElement = null; + } + }; + + this.drawHalo = function ( pulseAnimation ){ + that.halo(true); + + var offset = 0; + haloGroupElement = drawTools.drawRectHalo(that, this.width(), this.height(), offset); + + if ( pulseAnimation === false ) { + var pulseItem = haloGroupElement.selectAll(".searchResultA"); + pulseItem.classed("searchResultA", false); + pulseItem.classed("searchResultB", true); + pulseItem.attr("animationRunning", false); + } + + if ( that.pinned() ) { + var selectedNode = pinGroupElement.node(); + var nodeContainer = selectedNode.parentNode; + nodeContainer.appendChild(selectedNode); + } + + }; + + this.updateTextElement = function (){ + textBlock.updateAllTextElements(); + + }; + + this.textBlock = function (){ + return textBlock; + }; + + this.redrawLabelText = function (){ + textBlock.remove(); + textBlock = new CenteringTextElement(that.nodeElement(), that.backgroundColor()); + textBlock.addText(that.labelForCurrentLanguage()); + that.animateDynamicLabelWidth(graph.options().dynamicLabelWidth()); + shapeElement.select("title").text(that.labelForCurrentLanguage()); + }; + + this.animateDynamicLabelWidth = function ( dynamic ){ + that.removeHalo(); + var height = that.height(); + if ( dynamic === true ) { + labelWidth = Math.min(that.getMyWidth(), graph.options().maxLabelWidth()); + shapeElement.transition().tween("attr", function (){ + }) + .ease('linear') + .duration(100) + .attr({ x: -labelWidth / 2, y: -height / 2, width: labelWidth, height: height }) + .each("end", function (){ + that.updateTextElement(); + }); + + } else { + labelWidth = defaultWidth; + that.updateTextElement(); + shapeElement.transition().tween("attr", function (){ + }) + .ease('linear') + .duration(100) + .attr({ x: -labelWidth / 2, y: -height / 2, width: labelWidth, height: height }); + + } + + // for the pin we dont need to differ between different widths -- they are already set + if ( that.pinned() === true && pinGroupElement ) { + + var dx = 0.5 * labelWidth - 10, + dy = -1.1 * height; + + pinGroupElement.transition() + .tween("attr.translate", function (){ + }) + .attr("transform", "translate(" + dx + "," + dy + ")") + .ease('linear') + .duration(100); + } + }; + + this.addTextLabelElement = function (){ + var parentElement = that.nodeElement(); + textBlock = new CenteringTextElement(parentElement, this.backgroundColor()); + textBlock.addText(that.labelForCurrentLanguage()); + }; + + + }; + o.prototype = Object.create(BaseNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 37 */ +/***/ (function(module, exports) { + + var tools = {}; + module.exports = function (){ + return tools; + }; + + tools.distanceToBorder = function ( rect, dx, dy ){ + var width = rect.width(), + height = rect.height(); + + var innerDistance, + m_link = Math.abs(dy / dx), + m_rect = height / width; + + if ( m_link <= m_rect ) { + var timesX = dx / (width / 2), + rectY = dy / timesX; + innerDistance = Math.sqrt(Math.pow(width / 2, 2) + Math.pow(rectY, 2)); + } else { + var timesY = dy / (height / 2), + rectX = dx / timesY; + innerDistance = Math.sqrt(Math.pow(height / 2, 2) + Math.pow(rectX, 2)); + } + + return innerDistance; + }; + + +/***/ }), +/* 38 */ +/***/ (function(module, exports, __webpack_require__) { + + var DatatypeNode = __webpack_require__(35); + + module.exports = (function (){ + + var o = function ( graph ){ + DatatypeNode.apply(this, arguments); + + var superDrawFunction = this.draw, + superLabelFunction = this.label; + + this.attributes(["datatype"]) + .label("Literal") + .styleClass("literal") + .type("rdfs:Literal") + .iri("http://www.w3.org/2000/01/rdf-schema#Literal"); + + this.draw = function ( element ){ + superDrawFunction(element, ["dashed"]); + }; + + this.label = function ( p ){ + if ( !arguments.length ) return superLabelFunction(); + return this; + }; + }; + o.prototype = Object.create(DatatypeNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 39 */ +/***/ (function(module, exports, __webpack_require__) { + + var RoundNode = __webpack_require__(8); + + module.exports = (function (){ + + var o = function ( graph ){ + RoundNode.apply(this, arguments); + + var superDrawFunction = this.draw; + + this.attributes(["rdf"]) + .label("Resource") + .radius(30) + .styleClass("rdfsresource") + .type("rdfs:Resource"); + + this.draw = function ( element ){ + superDrawFunction(element, ["rdf", "dashed"]); + }; + }; + o.prototype = Object.create(RoundNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 40 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var properties = []; + properties.push(__webpack_require__(41)); + properties.push(__webpack_require__(44)); + properties.push(__webpack_require__(45)); + properties.push(__webpack_require__(46)); + properties.push(__webpack_require__(47)); + properties.push(__webpack_require__(48)); + properties.push(__webpack_require__(49)); + properties.push(__webpack_require__(50)); + properties.push(__webpack_require__(51)); + properties.push(__webpack_require__(52)); + properties.push(__webpack_require__(53)); + properties.push(__webpack_require__(54)); + properties.push(__webpack_require__(55)); + properties.push(__webpack_require__(56)); + + var map = d3.map(properties, function ( Prototype ){ + return new Prototype().type(); + }); + + module.exports = function (){ + return map; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 41 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + var superGenerateCardinalityText = this.generateCardinalityText; + + this.linkType("values-from") + .markerType("filled values-from") + .styleClass("allvaluesfromproperty") + .type("owl:allValuesFrom"); + + this.generateCardinalityText = function (){ + var cardinalityText = "A"; + + var superCardinalityText = superGenerateCardinalityText(); + if ( superCardinalityText ) { + cardinalityText += ", " + superCardinalityText; + } + + return cardinalityText; + }; + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + + + +/***/ }), +/* 42 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var BaseElement = __webpack_require__(10); + var CenteringTextElement = __webpack_require__(14); + var drawTools = __webpack_require__(17)(); + var forceLayoutNodeFunctions = __webpack_require__(13)(); + var rectangularElementTools = __webpack_require__(37)(); + var math = __webpack_require__(43)(); + + module.exports = (function (){ + + // Static variables + var labelHeight = 28, + labelWidth = 80, + smallestRadius = labelHeight / 2; + + + // Constructor, private variables and privileged methods + var Base = function ( graph ){ + BaseElement.apply(this, arguments); + + var that = this, + // Basic attributes + cardinality, + domain, + inverse, + link, + minCardinality, + maxCardinality, + range, + subproperties, + superproperties, + // Style attributes + linkType = "normal", + markerType = "filled", + labelVisible = true, + // Element containers + cardinalityElement, + labelElement, + linkGroup, + markerElement, + // Other + ignoreLocalHoverEvents, + fobj, + pinGroupElement, + haloGroupElement, + myWidth = 80, + defaultWidth = 80, + shapeElement, + textElement, + parent_labelObject, + backupFullIri, + + redundantProperties = []; + + + this.existingPropertyIRI = function ( url ){ + return graph.options().editSidebar().checkForExistingURL(url); + }; + + this.getHalos = function (){ + return haloGroupElement; + }; + + this.getPin = function (){ + return pinGroupElement; + }; + this.labelObject = function ( lo, once ){ + if ( !arguments.length ) { + return parent_labelObject; + } + else { + parent_labelObject = lo; + if ( that.inverse() && once !== true ) { + that.inverse().labelObject(lo, true); + } + + } + }; + this.hide = function ( val ){ + that.labelElement().classed("hidden", val); + that.linkGroup().classed("hidden", val); + if ( that.cardinalityElement() ) + that.cardinalityElement().classed("hidden", val); + }; + + // Properties + this.cardinality = function ( p ){ + if ( !arguments.length ) return cardinality; + cardinality = p; + return this; + }; + + this.cardinalityElement = function ( p ){ + if ( !arguments.length ) return cardinalityElement; + cardinalityElement = p; + return this; + }; + + this.domain = function ( p ){ + if ( !arguments.length ) return domain; + domain = p; + return this; + }; + + this.inverse = function ( p ){ + if ( !arguments.length ) return inverse; + inverse = p; + return this; + }; + + this.labelElement = function ( p ){ + if ( !arguments.length ) return labelElement; + labelElement = p; + return this; + }; + + this.labelVisible = function ( p ){ + if ( !arguments.length ) return labelVisible; + labelVisible = p; + return this; + }; + + this.link = function ( p ){ + if ( !arguments.length ) return link; + link = p; + return this; + }; + + this.linkGroup = function ( p ){ + if ( !arguments.length ) return linkGroup; + linkGroup = p; + return this; + }; + + this.linkType = function ( p ){ + if ( !arguments.length ) return linkType; + linkType = p; + return this; + }; + + this.markerElement = function ( p ){ + if ( !arguments.length ) return markerElement; + markerElement = p; + return this; + }; + + this.markerType = function ( p ){ + if ( !arguments.length ) return markerType; + markerType = p; + return this; + }; + + this.maxCardinality = function ( p ){ + if ( !arguments.length ) return maxCardinality; + maxCardinality = p; + return this; + }; + + this.minCardinality = function ( p ){ + if ( !arguments.length ) return minCardinality; + minCardinality = p; + return this; + }; + + this.range = function ( p ){ + if ( !arguments.length ) return range; + range = p; + return this; + }; + + this.redundantProperties = function ( p ){ + if ( !arguments.length ) return redundantProperties; + redundantProperties = p; + return this; + }; + + this.subproperties = function ( p ){ + if ( !arguments.length ) return subproperties; + subproperties = p; + return this; + }; + + this.superproperties = function ( p ){ + if ( !arguments.length ) return superproperties; + superproperties = p; + return this; + }; + + + // Functions + this.distanceToBorder = function ( dx, dy ){ + return rectangularElementTools.distanceToBorder(that, dx, dy); + }; + + this.linkHasMarker = function (){ + return linkType !== "dashed"; + }; + + this.markerId = function (){ + return "marker" + that.id(); + }; + + this.toggleFocus = function (){ + that.focused(!that.focused()); + labelElement.select("rect").classed("focused", that.focused()); + graph.resetSearchHighlight(); + graph.options().searchMenu().clearText(); + }; + this.getShapeElement = function (){ + return shapeElement; + }; + + this.textBlock = function (){ + return textElement; + }; + + this.redrawElement = function (){ + shapeElement.remove(); + textElement.remove(); + + that.drawLabel(that.labelElement()); + that.animateDynamicLabelWidth(graph.options().dynamicLabelWidth()); + + + // shapeElement=this.addRect(that.labelElement()); + // + // var equivalentsString = that.equivalentsString(); + // var suffixForFollowingEquivalents = equivalentsString ? "," : ""; + // + // textElement = new CenteringTextElement(labelContainer, this.backgroundColor()); + // textElement.addText(this.labelForCurrentLanguage(), "", suffixForFollowingEquivalents); + // textElement.addEquivalents(equivalentsString); + // textElement.addSubText(this.indicationString()); + + }; + + // Reused functions TODO refactor + this.draw = function ( labelGroup ){ + function attachLabel( property ){ + var labelContainer = labelGroup.append("g") + .datum(property) + .classed("label", true) + .attr("id", property.id()); + + property.drawLabel(labelContainer); + return labelContainer; + } + + if ( !that.labelVisible() ) { + return undefined; + } + if ( graph.options().dynamicLabelWidth() === true ) myWidth = Math.min(that.getMyWidth(), graph.options().maxLabelWidth()); + else myWidth = defaultWidth; + + that.labelElement(attachLabel(that)); + // Draw an inverse label and reposition both labels if necessary + if ( that.inverse() ) { + var yTransformation = (that.height() / 2) + 1 /* additional space */; + that.inverse() + .labelElement(attachLabel(that.inverse())); + + that.labelElement() + .attr("transform", "translate(" + 0 + ",-" + yTransformation + ")"); + that.inverse() + .labelElement() + .attr("transform", "translate(" + 0 + "," + yTransformation + ")"); + } + + if ( that.pinned() ) { + that.drawPin(); + } else if ( that.inverse() && that.inverse().pinned() ) { + that.inverse().drawPin(); + } + + if ( that.halo() ) + that.drawHalo(false); + + return that.labelElement(); + }; + + this.addRect = function ( labelContainer ){ + var rect = labelContainer.append("rect") + .classed(that.styleClass(), true) + .classed("property", true) + .attr("x", -that.width() / 2) + .attr("y", -that.height() / 2) + .attr("width", that.width()) + .attr("height", that.height()) + .on("mouseover", function (){ + onMouseOver(); + }) + .on("mouseout", function (){ + onMouseOut(); + }); + + rect.append("title") + .text(that.labelForCurrentLanguage()); + + if ( that.visualAttributes() ) { + rect.classed(that.visualAttributes(), true); + } + + var bgColor = that.backgroundColor(); + + if ( that.attributes().indexOf("deprecated") > -1 ) { + bgColor = undefined; + rect.classed("deprecatedproperty", true); + } else { + rect.classed("deprecatedproperty", false); + } + rect.style("fill", bgColor); + + return rect; + }; + this.drawLabel = function ( labelContainer ){ + shapeElement = this.addRect(labelContainer); + + var equivalentsString = that.equivalentsString(); + var suffixForFollowingEquivalents = equivalentsString ? "," : ""; + + var bgColor = that.backgroundColor(); + if ( that.attributes().indexOf("deprecated") > -1 ) { + bgColor = undefined; + } + textElement = new CenteringTextElement(labelContainer, bgColor); + textElement.addText(this.labelForCurrentLanguage(), "", suffixForFollowingEquivalents); + textElement.addEquivalents(equivalentsString); + textElement.addSubText(this.indicationString()); + }; + + this.equivalentsString = function (){ + var equivalentProperties = that.equivalents(); + if ( !equivalentProperties ) { + return; + } + + return equivalentProperties + .map(function ( property ){ + if ( property === undefined || typeof(property) === "string" ) { // @WORKAROUND + return "ERROR"; + } + return property.labelForCurrentLanguage(); + }) + .join(", "); + }; + + this.drawCardinality = function ( container ){ + var cardinalityText = this.generateCardinalityText(); + + if ( cardinalityText ) { + that.cardinalityElement(container); + if ( cardinalityText.indexOf("A") === 0 && cardinalityText.length === 1 ) { + + // replacing text elements to svg elements; + container.classed("cardinality", true) + .attr("text-anchor", "middle") + .append("path") + .classed("cardinality", true) + .attr("d", "m -8.8832678,-11.303355 -7.97e-4,0 0.717374,1.833297 8.22987151,21.371761 8.66826659,-21.2123526 0.797082,-1.9927054 0.02471,0 -0.8218553,1.9927054 -2.2517565,5.4201577 -12.4444429,8e-6 -2.2019394,-5.5795821 z") + .style("fill", "none") + .attr("transform", "matrix(0.5,0,0,0.5,0.5,0.5)"); + return true; + } else if ( cardinalityText.indexOf("E") === 0 && cardinalityText.length === 1 ) { + container.classed("cardinality", true) + .attr("text-anchor", "middle") + .append("path") + .classed("cardinality", true) + .attr("d", "m -5.5788451,-8.0958763 10.8749368,0 0,8.34681523 -9.5707468,0.040132 9.5707468,-0.040132 0,8.42707237 -10.9150654,0") + .style("fill", "none") + .attr("transform", "matrix(0.5,0,0,0.5,0.5,0.5)"); + return true; + } + else { + container.append("text") + .classed("cardinality", true) + .attr("text-anchor", "middle") + .attr("dy", "0.5ex") + .text(cardinalityText); + return true; // drawing successful + } + } else { + return false; + } + }; + + this.generateCardinalityText = function (){ + if ( that.cardinality() ) { + return that.cardinality(); + } else if ( that.minCardinality() || that.maxCardinality() ) { + var minBoundary = that.minCardinality() || "*"; + var maxBoundary = that.maxCardinality() || "*"; + return minBoundary + ".." + maxBoundary; + } + }; + + that.setHighlighting = function ( enable ){ + if ( that.labelElement && that.labelElement() ) { + that.labelElement().select("rect").classed("hovered", enable); + } + that.linkGroup().selectAll("path, text").classed("hovered", enable); + if ( that.markerElement() ) { + that.markerElement().select("path").classed("hovered", enable); + if ( that.cardinalityElement() ) { + that.cardinalityElement().selectAll("path").classed("hovered-MathSymbol", enable); + that.cardinalityElement().classed("hovered", enable); + } + } + var subAndSuperProperties = getSubAndSuperProperties(); + subAndSuperProperties.forEach(function ( property ){ + + if ( property.labelElement && property.labelElement() ) { + property.labelElement().select("rect") + .classed("indirect-highlighting", enable); + } + + }); + var inversed = false; + + if ( graph.ignoreOtherHoverEvents() === false ) { + if ( that.inverse() ) { + inversed = true; + } + + if ( graph.isTouchDevice() === false ) { + graph.activateHoverElementsForProperties(enable, that, inversed); + } + else { + that.labelElement().select("rect").classed("hovered", false); + that.linkGroup().selectAll("path, text").classed("hovered", false); + if ( that.markerElement() ) { + that.markerElement().select("path").classed("hovered", false); + if ( that.cardinalityElement() ) { + that.cardinalityElement().classed("hovered", false); + } + } + graph.activateHoverElementsForProperties(enable, that, inversed, true); + } + } + }; + + /** + * Combines the sub- and superproperties into a single array, because + * they're often used equivalently. + * @returns {Array} + */ + function getSubAndSuperProperties(){ + var properties = []; + + if ( that.subproperties() ) { + properties = properties.concat(that.subproperties()); + } + if ( that.superproperties() ) { + properties = properties.concat(that.superproperties()); + } + + return properties; + } + + /** + * Foregrounds the property, its inverse and the link. + */ + this.foreground = function (){ + // check for additional objects that we can highlight + if ( !that.labelElement() ) + return; + if ( that.labelElement().node().parentNode === null ) { + return; + } + var selectedLabelGroup = that.labelElement().node().parentNode, + labelContainer = selectedLabelGroup.parentNode, + selectedLinkGroup = that.linkGroup().node(), + linkContainer = that.linkGroup().node().parentNode; + if ( that.animationProcess() === false ) { + labelContainer.appendChild(selectedLabelGroup); + } + linkContainer.appendChild(selectedLinkGroup); + }; + + /** + * Foregrounds the sub- and superproperties of this property. + * This is separated from the foreground-function to prevent endless loops. + */ + function foregroundSubAndSuperProperties(){ + var subAndSuperProperties = getSubAndSuperProperties(); + + subAndSuperProperties.forEach(function ( property ){ + if ( property.foreground ) property.foreground(); + }); + } + + function onMouseOver(){ + if ( that.mouseEntered() || ignoreLocalHoverEvents === true ) { + return; + } + that.mouseEntered(true); + that.setHighlighting(true); + that.foreground(); + foregroundSubAndSuperProperties(); + } + + function onMouseOut(){ + that.mouseEntered(false); + that.setHighlighting(false); + } + + this.drawPin = function (){ + that.pinned(true); + if ( graph.options().dynamicLabelWidth() === true ) myWidth = that.getMyWidth(); + else myWidth = defaultWidth; + + if ( that.inverse() ) { + // check which element is rendered on top and add a pin to it + var tr_that = that.labelElement().attr("transform"); + var tr_inv = that.inverse().labelElement().attr("transform"); + + var thatY = /translate\(\s*([^\s,)]+)[ ,]([^\s,)]+)/.exec(tr_that)[2]; + var invY = /translate\(\s*([^\s,)]+)[ ,]([^\s,)]+)/.exec(tr_inv)[2]; + + if ( thatY < invY ) + pinGroupElement = drawTools.drawPin(that.labelElement(), -0.5 * that.width() + 10, -25, this.removePin, graph.options().showDraggerObject, graph.options().useAccuracyHelper()); + else + pinGroupElement = drawTools.drawPin(that.inverse().labelElement(), -0.5 * that.inverse().width() + 10, -25, this.removePin, graph.options().showDraggerObject, graph.options().useAccuracyHelper()); + + } + else { + pinGroupElement = drawTools.drawPin(that.labelElement(), -0.5 * that.width() + 10, -25, this.removePin, graph.options().showDraggerObject, graph.options().useAccuracyHelper()); + } + + + }; + + /** + * Removes the pin and refreshs the graph to update the force layout. + */ + this.removePin = function (){ + that.pinned(false); + if ( pinGroupElement ) { + pinGroupElement.remove(); + } + graph.updateStyle(); + }; + + this.removeHalo = function (){ + that.halo(false); + if ( haloGroupElement ) { + haloGroupElement.remove(); + haloGroupElement = null; + } + }; + + this.animationProcess = function (){ + var animRuns = false; + if ( that.getHalos() ) { + var haloGr = that.getHalos(); + var haloEls = haloGr.selectAll(".searchResultA"); + animRuns = haloGr.attr("animationRunning"); + + if ( typeof animRuns !== "boolean" ) { + // parse this to a boolean value + animRuns = (animRuns === 'true'); + } + if ( animRuns === false ) { + haloEls.classed("searchResultA", false); + haloEls.classed("searchResultB", true); + } + } + return animRuns; + }; + + this.drawHalo = function ( pulseAnimation ){ + that.halo(true); + var offset = 0; + if ( that.labelElement() && that.labelElement().node() ) { + var labelNode = that.labelElement().node(); + var labelContainer = labelNode.parentNode; + // do this only if animation is not running + if ( that.animationProcess() === false ) + labelContainer.appendChild(labelNode); + } + haloGroupElement = drawTools.drawRectHalo(that, that.width(), that.height(), offset); + if ( haloGroupElement ) { + var haloNode = haloGroupElement.node(); + var haloContainer = haloNode.parentNode; + haloContainer.appendChild(haloNode); + } + var selectedNode; + var nodeContainer; + if ( that.pinned() ) { + selectedNode = pinGroupElement.node(); + nodeContainer = selectedNode.parentNode; + nodeContainer.appendChild(selectedNode); + } + if ( that.inverse() && that.inverse().pinned() ) { + if ( that.inverse().getPin() ) { + selectedNode = that.inverse().getPin().node(); + nodeContainer = selectedNode.parentNode; + nodeContainer.appendChild(selectedNode); + } + } + if ( pulseAnimation === false ) { + var pulseItem = haloGroupElement.selectAll(".searchResultA"); + pulseItem.classed("searchResultA", false); + pulseItem.classed("searchResultB", true); + pulseItem.attr("animationRunning", false); + } + }; + + this.getMyWidth = function (){ + var text = that.labelForCurrentLanguage(); + myWidth = measureTextWidth(text, "text") + 20; + // check for sub names; + var indicatorText = that.indicationString(); + var indicatorWidth = measureTextWidth(indicatorText, "subtext") + 20; + if ( indicatorWidth > myWidth ) + myWidth = indicatorWidth; + + return myWidth; + }; + + function measureTextWidth( text, textStyle ){ + // Set a default value + if ( !textStyle ) { + textStyle = "text"; + } + var d = d3.select("body") + .append("div") + .attr("class", textStyle) + .attr("id", "width-test") // tag this element to identify it + .attr("style", "position:absolute; float:left; white-space:nowrap; visibility:hidden;") + .text(text), + w = document.getElementById("width-test").offsetWidth; + d.remove(); + return w; + } + + this.textWidth = function (){ + return myWidth; + }; + this.width = function (){ + return myWidth; + }; + + this.animateDynamicLabelWidth = function ( dynamic ){ + that.removeHalo(); + if ( shapeElement === undefined ) {// this handles setOperatorProperties which dont have a shapeElement! + return; + } + + var h = that.height(); + if ( dynamic === true ) { + myWidth = Math.min(that.getMyWidth(), graph.options().maxLabelWidth()); + shapeElement.transition().tween("attr", function (){ + }) + .ease('linear') + .duration(100) + .attr({ x: -myWidth / 2, y: -h / 2, width: myWidth, height: h }) + .each("end", function (){ + that.updateTextElement(); + }); + } else { + // Static width for property labels = 80 + myWidth = defaultWidth; + that.updateTextElement(); + shapeElement.transition().tween("attr", function (){ + }) + .ease('linear') + .duration(100) + .attr({ x: -myWidth / 2, y: -h / 2, width: myWidth, height: h }); + } + if ( that.pinned() === true && pinGroupElement ) { + var dx = -0.5 * myWidth + 10, + dy = -25; + pinGroupElement.transition() + .tween("attr.translate", function (){ + }) + .attr("transform", "translate(" + dx + "," + dy + ")") + .ease('linear') + .duration(100); + } + }; + + this.redrawLabelText = function (){ + textElement.remove(); + that.addTextLabelElement(); + that.animateDynamicLabelWidth(graph.options().dynamicLabelWidth()); + shapeElement.select("title").text(that.labelForCurrentLanguage()); + }; + + this.addTextLabelElement = function (){ + var labelContainer = that.labelElement(); + + var equivalentsString = that.equivalentsString(); + var suffixForFollowingEquivalents = equivalentsString ? "," : ""; + + textElement = new CenteringTextElement(labelContainer, this.backgroundColor()); + textElement.addText(this.labelForCurrentLanguage(), "", suffixForFollowingEquivalents); + textElement.addEquivalents(equivalentsString); + textElement.addSubText(this.indicationString()); + }; + + this.updateTextElement = function (){ + textElement.updateAllTextElements(); + }; + this.enableEditing = function ( autoEditing ){ + if ( autoEditing === false ) + return; + that.raiseDoubleClickEdit(true); + }; + + this.raiseDoubleClickEdit = function ( forceIRISync ){ + d3.selectAll(".foreignelements").remove(); + if ( that.labelElement() === undefined || this.type() === "owl:disjointWith" || this.type() === "rdfs:subClassOf" ) { + console.log("No Container found"); + return; + } + if ( fobj !== undefined ) { + that.labelElement().selectAll(".foreignelements").remove(); + } + backupFullIri = undefined; + graph.options().focuserModule().handle(undefined); + graph.options().focuserModule().handle(that); + that.editingTextElement = true; + ignoreLocalHoverEvents = true; + that.labelElement().selectAll("rect").classed("hoveredForEditing", true); + that.frozen(true); + graph.killDelayedTimer(); + graph.ignoreOtherHoverEvents(false); + fobj = that.labelElement().append("foreignObject") + .attr("x", -0.5 * that.textWidth()) + .attr("y", -13) + .attr("height", 25) + .attr("class", "foreignelements") + .on("dragstart", function (){ + return false; + }) // remove drag operations of text element) + .attr("width", that.textWidth() - 2); + // adding a Style to the fObject + // + // + // + var editText = fobj.append("xhtml:input") + .attr("class", "nodeEditSpan") + .attr("id", that.id()) + .attr("align", "center") + .attr("contentEditable", "true") + .on("dragstart", function (){ + return false; + }); // remove drag operations of text element) + + var bgColor = '#f00'; + var txtWidth = that.textWidth() - 2; + editText.style({ + // 'line-height': '30px', + 'align': 'center', + 'color': 'black', + 'width': txtWidth + "px", + 'background-color': bgColor, + 'border-bottom': '2px solid black' + }); + var txtNode = editText.node(); + txtNode.value = that.labelForCurrentLanguage(); + txtNode.focus(); + txtNode.select(); + if ( d3.event.stopPropagation ) d3.event.stopPropagation(); + if ( d3.event.sourceEvent && d3.event.sourceEvent.stopPropagation ) d3.event.sourceEvent.stopPropagation(); + + // add some events that relate to this object + editText.on("click", function (){ + if ( d3.event.stopPropagation ) d3.event.stopPropagation(); + if ( d3.event.sourceEvent && d3.event.sourceEvent.stopPropagation ) d3.event.sourceEvent.stopPropagation(); + + }); + // // remove hover Events for now; + editText.on("mouseout", function (){ + if ( d3.event.stopPropagation ) d3.event.stopPropagation(); + if ( d3.event.sourceEvent && d3.event.sourceEvent.stopPropagation ) d3.event.sourceEvent.stopPropagation(); + }); + editText.on("mousedown", function (){ + if ( d3.event.stopPropagation ) d3.event.stopPropagation(); + if ( d3.event.sourceEvent && d3.event.sourceEvent.stopPropagation ) d3.event.sourceEvent.stopPropagation(); + }) + .on("keydown", function (){ + + if ( d3.event.keyCode === 13 ) { + this.blur(); + that.frozen(false); // << releases the not after selection + that.locked(false); + } + }) + .on("keyup", function (){ + if ( forceIRISync ) { + var labelName = editText.node().value; + var resourceName = labelName.replaceAll(" ", "_"); + var syncedIRI = that.baseIri() + resourceName; + backupFullIri = syncedIRI; + + d3.select("#element_iriEditor").node().title = syncedIRI; + d3.select("#element_iriEditor").node().value = graph.options().prefixModule().getPrefixRepresentationForFullURI(syncedIRI); + } + d3.select("#element_labelEditor").node().value = editText.node().value; + + }) + .on("blur", function (){ + + + that.editingTextElement = false; + ignoreLocalHoverEvents = false; + that.labelElement().selectAll("rect").classed("hoveredForEditing", false); + var newLabel = editText.node().value; + that.labelElement().selectAll(".foreignelements").remove(); + // that.setLabelForCurrentLanguage(classNameConvention(editText.node().value)); + that.label(newLabel); + that.backupLabel(newLabel); + that.redrawLabelText(); + updateHoverElements(true); + graph.showHoverElementsAfterAnimation(that, false); + graph.ignoreOtherHoverEvents(false); + + + that.frozen(graph.paused()); + that.locked(graph.paused()); + that.domain().frozen(graph.paused()); + that.domain().locked(graph.paused()); + that.range().frozen(graph.paused()); + that.range().locked(graph.paused()); + graph.removeEditElements(); + if ( backupFullIri ) { + // console.log("Checking if element is Identical ?"); + var sanityCheckResult = graph.options().editSidebar().checkProperIriChange(that, backupFullIri); + if ( sanityCheckResult !== false ) { + graph.options().warningModule().showWarning("Already seen this property", + "Input IRI: " + backupFullIri + " for element: " + that.labelForCurrentLanguage() + " already been set", + "Continuing with duplicate property!", 1, false, sanityCheckResult); + } + that.iri(backupFullIri); + } + graph.options().focuserModule().handle(undefined); + graph.options().focuserModule().handle(that); + graph.updatePropertyDraggerElements(that); + + + }); // add a foreiner element to this thing; + + }; + + // update hover elements + function updateHoverElements( enable ){ + if ( graph.ignoreOtherHoverEvents() === false ) { + var inversed = false; + if ( that.inverse() ) { + inversed = true; + } + if ( enable === true ) { + graph.activateHoverElementsForProperties(enable, that, inversed); + } + } + } + + that.copyInformation = function ( other ){ + that.label(other.label()); + that.iri(other.iri()); + that.baseIri(other.baseIri()); + if ( other.type() === "owl:ObjectProperty" || + other.type() === "owl:DatatypeProperty" ) { + that.backupLabel(other.label()); + // console.log("copied backup label"+that.backupLabel()); + } + if ( other.backupLabel() !== undefined ) { + that.backupLabel(other.backupLabel()); + } + }; + + forceLayoutNodeFunctions.addTo(this); + }; + + Base.prototype = Object.create(BaseElement.prototype); + Base.prototype.constructor = Base; + + Base.prototype.height = function (){ + return labelHeight; + }; + + Base.prototype.width = function (){ + return labelWidth; + }; + + Base.prototype.actualRadius = function (){ + return smallestRadius; + }; + + Base.prototype.textWidth = Base.prototype.width; + + + return Base; + }()); + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 43 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains a collection of mathematical functions with some additional data + * used for WebVOWL. + */ + module.exports = (function (){ + + var math = {}, + loopFunction = d3.svg.line() + .x(function ( d ){ + return d.x; + }) + .y(function ( d ){ + return d.y; + }) + .interpolate("cardinal") + .tension(-1); + + + /** + * Calculates the normal vector of the path between the two nodes. + * @param source the first node + * @param target the second node + * @param length the length of the calculated normal vector + * @returns {{x: number, y: number}} + */ + math.calculateNormalVector = function ( source, target, length ){ + var dx = target.x - source.x, + dy = target.y - source.y; + + var nx = -dy, + ny = dx; + + var vlength = Math.sqrt(nx * nx + ny * ny); + + var ratio = vlength !== 0 ? length / vlength : 0; + + return { "x": nx * ratio, "y": ny * ratio }; + }; + + /** + * Calculates the path for a link, if it is a loop. Currently only working for circlular nodes. + * @param link the link + * @returns {*} + */ + + + + math.getLoopPoints = function ( link ){ + var node = link.domain(), + label = link.label(); + + var fairShareLoopAngle = 360 / link.loops().length, + fairShareLoopAngleWithMargin = fairShareLoopAngle * 0.8, + loopAngle = Math.min(60, fairShareLoopAngleWithMargin); + + if ( label.increasedLoopAngle === true ) + loopAngle = 120; + + + var dx = label.x - node.x, + dy = label.y - node.y, + labelRadian = Math.atan2(dy, dx), + labelAngle = calculateAngle(labelRadian); + + var startAngle = labelAngle - loopAngle / 2, + endAngle = labelAngle + loopAngle / 2; + + + var arcFrom = calculateRadian(startAngle), + arcTo = calculateRadian(endAngle), + + x1 = Math.cos(arcFrom) * node.actualRadius(), + y1 = Math.sin(arcFrom) * node.actualRadius(), + + x2 = Math.cos(arcTo) * node.actualRadius(), + y2 = Math.sin(arcTo) * node.actualRadius(), + + fixPoint1 = { "x": node.x + x1, "y": node.y + y1 }, + fixPoint2 = { "x": node.x + x2, "y": node.y + y2 }; + + return [fixPoint1, fixPoint2]; + }; + math.calculateLoopPath = function ( link ){ + var node = link.domain(), + label = link.label(); + + + var fairShareLoopAngle = 360 / link.loops().length, + fairShareLoopAngleWithMargin = fairShareLoopAngle * 0.8, + loopAngle = Math.min(60, fairShareLoopAngleWithMargin); + + if ( label.increasedLoopAngle === true ) + loopAngle = 120; + + var dx = label.x - node.x, + dy = label.y - node.y, + labelRadian = Math.atan2(dy, dx), + labelAngle = calculateAngle(labelRadian); + + var startAngle = labelAngle - loopAngle / 2, + endAngle = labelAngle + loopAngle / 2; + + var arcFrom = calculateRadian(startAngle), + arcTo = calculateRadian(endAngle), + + x1 = Math.cos(arcFrom) * node.actualRadius(), + y1 = Math.sin(arcFrom) * node.actualRadius(), + + x2 = Math.cos(arcTo) * node.actualRadius(), + y2 = Math.sin(arcTo) * node.actualRadius(), + + fixPoint1 = { "x": node.x + x1, "y": node.y + y1 }, + fixPoint2 = { "x": node.x + x2, "y": node.y + y2 }; + + return loopFunction([fixPoint1, link.label(), fixPoint2]); + }; + + math.calculateLoopPoints = function ( link ){ + var node = link.domain(), + label = link.label(); + + var fairShareLoopAngle = 360 / link.loops().length, + fairShareLoopAngleWithMargin = fairShareLoopAngle * 0.8, + loopAngle = Math.min(60, fairShareLoopAngleWithMargin); + + var dx = label.x - node.x, + dy = label.y - node.y, + labelRadian = Math.atan2(dy, dx), + labelAngle = calculateAngle(labelRadian); + + var startAngle = labelAngle - loopAngle / 2, + endAngle = labelAngle + loopAngle / 2; + + var arcFrom = calculateRadian(startAngle), + arcTo = calculateRadian(endAngle), + + x1 = Math.cos(arcFrom) * node.actualRadius(), + y1 = Math.sin(arcFrom) * node.actualRadius(), + + x2 = Math.cos(arcTo) * (node.actualRadius()), + y2 = Math.sin(arcTo) * (node.actualRadius()), + + fixPoint1 = { "x": node.x + x1, "y": node.y + y1 }, + fixPoint2 = { "x": node.x + x2, "y": node.y + y2 }; + + return [fixPoint1, link.label(), fixPoint2]; + }; + + /** + * @param angle + * @returns {number} the radian of the angle + */ + function calculateRadian( angle ){ + angle = angle % 360; + if ( angle < 0 ) { + angle = angle + 360; + } + return (Math.PI * angle) / 180; + } + + /** + * @param radian + * @returns {number} the angle of the radian + */ + function calculateAngle( radian ){ + return radian * (180 / Math.PI); + } + + /** + * Calculates the point where the link between the source and target node + * intersects the border of the target node. + * @param source the source node + * @param target the target node + * @param additionalDistance additional distance the + * @returns {{x: number, y: number}} + */ + math.calculateIntersection = function ( source, target, additionalDistance ){ + var dx = target.x - source.x, + dy = target.y - source.y, + length = Math.sqrt(dx * dx + dy * dy); + + if ( length === 0 ) { + return { x: source.x, y: source.y }; + } + + var innerDistance = target.distanceToBorder(dx, dy); + + var ratio = (length - (innerDistance + additionalDistance)) / length, + x = dx * ratio + source.x, + y = dy * ratio + source.y; + + return { x: x, y: y }; + }; + + /** + * Calculates the position between the two points. + * @param firstPoint + * @param secondPoint + * @returns {{x: number, y: number}} + */ + math.calculateCenter = function ( firstPoint, secondPoint ){ + return { + x: (firstPoint.x + secondPoint.x) / 2, + y: (firstPoint.y + secondPoint.y) / 2 + }; + }; + + + return function (){ + /* Use a function here to keep a consistent style like webvowl.path.to.module() + * despite having just a single math object. */ + return math; + }; + })(); + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 44 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.attributes(["datatype"]) + .styleClass("datatypeproperty") + .type("owl:DatatypeProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 45 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.attributes(["deprecated"]) + .styleClass("deprecatedproperty") + .type("owl:DeprecatedProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 46 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + var CenteringTextElement = __webpack_require__(14); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + var label = "Disjoint With"; + var shapeElement; + // Disallow overwriting the label + this.label = function ( p ){ + if ( !arguments.length ) return label; + return this; + }; + + this.linkType("dashed") + .styleClass("disjointwith") + .type("owl:disjointWith"); + + this.drawLabel = function ( labelContainer ){ + shapeElement = this.addRect(labelContainer); + + labelContainer.append("circle") + .classed("symbol", true) + .classed("fineline", true) + .classed("embedded", true) + .attr("cx", -12.5) + .attr("r", 10); + + labelContainer.append("circle") + .classed("symbol", true) + .classed("fineline", true) + .classed("embedded", true) + .attr("cx", 12.5) + .attr("r", 10); + + var textElement = new CenteringTextElement(labelContainer, this.backgroundColor()); + if ( !graph.options().compactNotation() ) { + textElement.addSubText("disjoint"); + } + textElement.translation(0, 20); + }; + this.getShapeElement = function (){ + return shapeElement; + }; + this.markerElement = function (){ + return undefined; + }; + + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 47 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.styleClass("equivalentproperty") + .type("owl:equivalentProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 48 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.attributes(["functional"]) + .styleClass("functionalproperty") + .type("owl:FunctionalProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 49 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.attributes(["inverse functional"]) + .styleClass("inversefunctionalproperty") + .type("owl:InverseFunctionalProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 50 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.attributes(["object"]) + .styleClass("objectproperty") + .type("owl:ObjectProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + + + +/***/ }), +/* 51 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + var superGenerateCardinalityText = this.generateCardinalityText; + + this.linkType("values-from") + .markerType("filled values-from") + .styleClass("somevaluesfromproperty") + .type("owl:someValuesFrom"); + + this.generateCardinalityText = function (){ + var cardinalityText = "E"; + + var superCardinalityText = superGenerateCardinalityText(); + if ( superCardinalityText ) { + cardinalityText += ", " + superCardinalityText; + } + + return cardinalityText; + }; + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + + + +/***/ }), +/* 52 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.attributes(["symmetric"]) + .styleClass("symmetricproperty") + .type("owl:SymmetricProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 53 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.attributes(["transitive"]) + .styleClass("transitiveproperty") + .type("owl:TransitiveProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 54 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.attributes(["rdf"]) + .styleClass("rdfproperty") + .type("rdf:Property"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 55 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + var that = this, + superDrawFunction = that.draw, + label = "Subclass of"; + + this.draw = function ( labelGroup ){ + that.labelVisible(!graph.options().compactNotation()); + return superDrawFunction(labelGroup); + }; + + // Disallow overwriting the label + this.label = function ( p ){ + if ( !arguments.length ) return label; + return this; + }; + + this.linkType("dotted") + .markerType("white") + .styleClass("subclass") + .type("rdfs:subClassOf"); + + that.baseIri("http://www.w3.org/2000/01/rdf-schema#"); + that.iri("http://www.w3.org/2000/01/rdf-schema#subClassOf"); + + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 56 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.labelVisible(false) + .linkType("dashed") + .markerType("white") + .styleClass("setoperatorproperty") + .type("setOperatorProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 57 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var _ = __webpack_require__(58); + var math = __webpack_require__(43)(); + var linkCreator = __webpack_require__(60)(); + var elementTools = __webpack_require__(63)(); + // add some maps for nodes and properties -- used for object generation + var nodePrototypeMap = __webpack_require__(5)(); + var propertyPrototypeMap = __webpack_require__(40)(); + + + module.exports = function ( graphContainerSelector ){ + var graph = {}, + CARDINALITY_HDISTANCE = 20, + CARDINALITY_VDISTANCE = 10, + curveFunction = d3.svg.line() + .x(function ( d ){ + return d.x; + }) + .y(function ( d ){ + return d.y; + }) + .interpolate("cardinal"), + options = __webpack_require__(64)(), + parser = __webpack_require__(65)(graph), + language = "default", + paused = false, + // Container for visual elements + graphContainer, + nodeContainer, + labelContainer, + cardinalityContainer, + linkContainer, + // Visual elements + nodeElements, + initialLoad = true, + updateRenderingDuringSimulation = false, + labelGroupElements, + linkGroups, + linkPathElements, + cardinalityElements, + // Internal data + classNodes, + labelNodes, + links, + properties, + unfilteredData, + // Graph behaviour + force, + dragBehaviour, + zoomFactor = 1.0, + centerGraphViewOnLoad = false, + transformAnimation = false, + graphTranslation = [0, 0], + graphUpdateRequired = false, + pulseNodeIds = [], + nodeArrayForPulse = [], + nodeMap = [], + locationId = 0, + defaultZoom = 1.0, + defaultTargetZoom = 0.8, + global_dof = -1, + touchDevice = false, + last_touch_time, + originalD3_dblClickFunction = null, + originalD3_touchZoomFunction = null, + + // editing elements + deleteGroupElement, + addDataPropertyGroupElement, + editContainer, + draggerLayer = null, + draggerObjectsArray = [], + delayedHider, + nodeFreezer, + hoveredNodeElement = null, + currentlySelectedNode = null, + hoveredPropertyElement = null, + draggingStarted = false, + frozenDomainForPropertyDragger, + frozenRangeForPropertyDragger, + + eP = 0, // id for new properties + eN = 0, // id for new Nodes + editMode = true, + debugContainer = d3.select("#FPS_Statistics"), + finishedLoadingSequence = false, + + ignoreOtherHoverEvents = false, + forceNotZooming = false, + now, then, // used for fps computation + showFPS = false, + seenEditorHint = false, + seenFilterWarning = false, + showFilterWarning = false, + + keepDetailsCollapsedOnLoading = true, + adjustingGraphSize = false, + showReloadButtonAfterLayoutOptimization = false, + zoom; + //var prefixModule=require("./prefixRepresentationModule")(graph); + var NodePrototypeMap = createLowerCasePrototypeMap(nodePrototypeMap); + var PropertyPrototypeMap = createLowerCasePrototypeMap(propertyPrototypeMap); + var classDragger = __webpack_require__(68)(graph); + var rangeDragger = __webpack_require__(69)(graph); + var domainDragger = __webpack_require__(70)(graph); + var shadowClone = __webpack_require__(71)(graph); + + graph.math = function (){ + return math; + }; + /** --------------------------------------------------------- **/ + /** -- getter and setter definitions -- **/ + /** --------------------------------------------------------- **/ + graph.isEditorMode = function (){ + return editMode; + }; + graph.getGlobalDOF = function (){ + return global_dof; + }; + graph.setGlobalDOF = function ( val ){ + global_dof = val; + }; + + graph.updateZoomSliderValueFromOutside = function (){ + graph.options().zoomSlider().updateZoomSliderValue(zoomFactor); + }; + + graph.setDefaultZoom = function ( val ){ + defaultZoom = val; + graph.reset(); + graph.options().zoomSlider().updateZoomSliderValue(defaultZoom); + }; + graph.setTargetZoom = function ( val ){ + defaultTargetZoom = val; + }; + graph.graphOptions = function (){ + return options; + }; + + graph.scaleFactor = function (){ + return zoomFactor; + }; + graph.translation = function (){ + return graphTranslation; + }; + + // Returns the visible nodes + graph.graphNodeElements = function (){ + return nodeElements; + }; + // Returns the visible Label Nodes + graph.graphLabelElements = function (){ + return labelNodes; + }; + + graph.graphLinkElements = function (){ + return links; + }; + + graph.setSliderZoom = function ( val ){ + + var cx = 0.5 * graph.options().width(); + var cy = 0.5 * graph.options().height(); + var cp = getWorldPosFromScreen(cx, cy, graphTranslation, zoomFactor); + var sP = [cp.x, cp.y, graph.options().height() / zoomFactor]; + var eP = [cp.x, cp.y, graph.options().height() / val]; + var pos_intp = d3.interpolateZoom(sP, eP); + + graphContainer.attr("transform", transform(sP, cx, cy)) + .transition() + .duration(1) + .attrTween("transform", function (){ + return function ( t ){ + return transform(pos_intp(t), cx, cy); + }; + }) + .each("end", function (){ + graphContainer.attr("transform", "translate(" + graphTranslation + ")scale(" + zoomFactor + ")"); + zoom.translate(graphTranslation); + zoom.scale(zoomFactor); + graph.options().zoomSlider().updateZoomSliderValue(zoomFactor); + }); + }; + + + graph.setZoom = function ( value ){ + zoom.scale(value); + }; + + graph.setTranslation = function ( translation ){ + zoom.translate([translation[0], translation[1]]); + }; + + graph.options = function (){ + return options; + }; + // search functionality + graph.getUpdateDictionary = function (){ + return parser.getDictionary(); + }; + + graph.language = function ( newLanguage ){ + if ( !arguments.length ) return language; + + // Just update if the language changes + if ( language !== newLanguage ) { + language = newLanguage || "default"; + redrawContent(); + recalculatePositions(); + graph.options().searchMenu().requestDictionaryUpdate(); + graph.resetSearchHighlight(); + } + return graph; + }; + + + /** --------------------------------------------------------- **/ + /** graph / rendering related functions **/ + /** --------------------------------------------------------- **/ + + // Initializes the graph. + function initializeGraph(){ + + options.graphContainerSelector(graphContainerSelector); + var moved = false; + force = d3.layout.force() + .on("tick", hiddenRecalculatePositions); + + dragBehaviour = d3.behavior.drag() + .origin(function ( d ){ + return d; + }) + .on("dragstart", function ( d ){ + d3.event.sourceEvent.stopPropagation(); // Prevent panning + graph.ignoreOtherHoverEvents(true); + if ( d.type && d.type() === "Class_dragger" ) { + classDragger.mouseButtonPressed = true; + clearTimeout(delayedHider); + classDragger.selectedViaTouch(true); + d.parentNode().locked(true); + draggingStarted = true; + } else if ( d.type && d.type() === "Range_dragger" ) { + graph.ignoreOtherHoverEvents(true); + clearTimeout(delayedHider); + frozenDomainForPropertyDragger = shadowClone.parentNode().domain(); + frozenRangeForPropertyDragger = shadowClone.parentNode().range(); + shadowClone.setInitialPosition(); + shadowClone.hideClone(false); + shadowClone.hideParentProperty(true); + shadowClone.updateElement(); + deleteGroupElement.classed("hidden", true); + addDataPropertyGroupElement.classed("hidden", true); + frozenDomainForPropertyDragger.frozen(true); + frozenDomainForPropertyDragger.locked(true); + frozenRangeForPropertyDragger.frozen(true); + frozenRangeForPropertyDragger.locked(true); + domainDragger.updateElement(); + domainDragger.mouseButtonPressed = true; + rangeDragger.updateElement(); + rangeDragger.mouseButtonPressed = true; + // shadowClone.setPosition(d.x, d.y); + + + } else if ( d.type && d.type() === "Domain_dragger" ) { + graph.ignoreOtherHoverEvents(true); + clearTimeout(delayedHider); + frozenDomainForPropertyDragger = shadowClone.parentNode().domain(); + frozenRangeForPropertyDragger = shadowClone.parentNode().range(); + shadowClone.setInitialPosition(); + shadowClone.hideClone(false); + shadowClone.hideParentProperty(true); + shadowClone.updateElement(); + deleteGroupElement.classed("hidden", true); + addDataPropertyGroupElement.classed("hidden", true); + + frozenDomainForPropertyDragger.frozen(true); + frozenDomainForPropertyDragger.locked(true); + frozenRangeForPropertyDragger.frozen(true); + frozenRangeForPropertyDragger.locked(true); + domainDragger.updateElement(); + domainDragger.mouseButtonPressed = true; + rangeDragger.updateElement(); + rangeDragger.mouseButtonPressed = true; + } + else { + d.locked(true); + moved = false; + } + }) + .on("drag", function ( d ){ + + if ( d.type && d.type() === "Class_dragger" ) { + clearTimeout(delayedHider); + classDragger.setPosition(d3.event.x, d3.event.y); + } else if ( d.type && d.type() === "Range_dragger" ) { + clearTimeout(delayedHider); + rangeDragger.setPosition(d3.event.x, d3.event.y); + shadowClone.setPosition(d3.event.x, d3.event.y); + domainDragger.updateElementViaRangeDragger(d3.event.x, d3.event.y); + } + else if ( d.type && d.type() === "Domain_dragger" ) { + clearTimeout(delayedHider); + domainDragger.setPosition(d3.event.x, d3.event.y); + shadowClone.setPositionDomain(d3.event.x, d3.event.y); + rangeDragger.updateElementViaDomainDragger(d3.event.x, d3.event.y); + } + + else { + d.px = d3.event.x; + d.py = d3.event.y; + force.resume(); + updateHaloRadius(); + moved = true; + if ( d.renderType && d.renderType() === "round" ) { + classDragger.setParentNode(d); + } + + } + }) + .on("dragend", function ( d ){ + graph.ignoreOtherHoverEvents(false); + if ( d.type && d.type() === "Class_dragger" ) { + var nX = classDragger.x; + var nY = classDragger.y; + clearTimeout(delayedHider); + classDragger.mouseButtonPressed = false; + classDragger.selectedViaTouch(false); + d.setParentNode(d.parentNode()); + + var draggerEndPos = [nX, nY]; + var targetNode = graph.getTargetNode(draggerEndPos); + if ( targetNode ) { + createNewObjectProperty(d.parentNode(), targetNode, draggerEndPos); + } + if ( touchDevice === false ) { + editElementHoverOut(); + } + draggingStarted = false; + } else if ( d.type && d.type() === "Range_dragger" ) { + graph.ignoreOtherHoverEvents(false); + frozenDomainForPropertyDragger.frozen(false); + frozenDomainForPropertyDragger.locked(false); + frozenRangeForPropertyDragger.frozen(false); + frozenRangeForPropertyDragger.locked(false); + rangeDragger.mouseButtonPressed = false; + domainDragger.mouseButtonPressed = false; + domainDragger.updateElement(); + rangeDragger.updateElement(); + shadowClone.hideClone(true); + var rX = rangeDragger.x; + var rY = rangeDragger.y; + var rangeDraggerEndPos = [rX, rY]; + var targetRangeNode = graph.getTargetNode(rangeDraggerEndPos); + if ( elementTools.isDatatype(targetRangeNode) === true ) { + targetRangeNode = null; + console.log("---------------TARGET NODE IS A DATATYPE/ LITERAL ------------"); + } + + if ( targetRangeNode === null ) { + d.reDrawEverthing(); + shadowClone.hideParentProperty(false); + } + else { + d.updateRange(targetRangeNode); + graph.update(); + shadowClone.hideParentProperty(false); + } + } else if ( d.type && d.type() === "Domain_dragger" ) { + graph.ignoreOtherHoverEvents(false); + frozenDomainForPropertyDragger.frozen(false); + frozenDomainForPropertyDragger.locked(false); + frozenRangeForPropertyDragger.frozen(false); + frozenRangeForPropertyDragger.locked(false); + rangeDragger.mouseButtonPressed = false; + domainDragger.mouseButtonPressed = false; + domainDragger.updateElement(); + rangeDragger.updateElement(); + shadowClone.hideClone(true); + + var dX = domainDragger.x; + var dY = domainDragger.y; + var domainDraggerEndPos = [dX, dY]; + var targetDomainNode = graph.getTargetNode(domainDraggerEndPos); + if ( elementTools.isDatatype(targetDomainNode) === true ) { + targetDomainNode = null; + console.log("---------------TARGET NODE IS A DATATYPE/ LITERAL ------------"); + } + shadowClone.hideClone(true); + if ( targetDomainNode === null ) { + d.reDrawEverthing(); + shadowClone.hideParentProperty(false); + } + else { + d.updateDomain(targetDomainNode); + graph.update(); + shadowClone.hideParentProperty(false); + } + } + + else { + d.locked(false); + var pnp = graph.options().pickAndPinModule(); + if ( pnp.enabled() === true && moved === true ) { + if ( d.id ) { // node + pnp.handle(d, true); + } + if ( d.property ) { + pnp.handle(d.property(), true); + } + } + } + }); + + // Apply the zooming factor. + zoom = d3.behavior.zoom() + .duration(150) + .scaleExtent([options.minMagnification(), options.maxMagnification()]) + .on("zoom", zoomed); + + draggerObjectsArray.push(classDragger); + draggerObjectsArray.push(rangeDragger); + draggerObjectsArray.push(domainDragger); + draggerObjectsArray.push(shadowClone); + force.stop(); + } + + graph.lazyRefresh = function (){ + redrawContent(); + recalculatePositions(); + }; + + graph.adjustingGraphSize = function ( val ){ + adjustingGraphSize = val; + }; + + graph.showReloadButtonAfterLayoutOptimization = function ( show ){ + showReloadButtonAfterLayoutOptimization = show; + }; + + + function hiddenRecalculatePositions(){ + finishedLoadingSequence = false; + if ( graph.options().loadingModule().successfullyLoadedOntology() === false ) { + force.stop(); + d3.select("#progressBarValue").node().innerHTML = ""; + graph.updateProgressBarMode(); + graph.options().loadingModule().showErrorDetailsMessage(hiddenRecalculatePositions); + if ( keepDetailsCollapsedOnLoading && adjustingGraphSize === false ) { + graph.options().loadingModule().collapseDetails("hiddenRecalculatePositions"); + } + return; + } + if ( updateRenderingDuringSimulation === false ) { + var value = 1.0 - 10 * force.alpha(); + var percent = parseInt(200 * value) + "%"; + graph.options().loadingModule().setPercentValue(percent); + d3.select("#progressBarValue").style("width", percent); + d3.select("#progressBarValue").node().innerHTML = percent; + + if ( value > 0.49 ) { + updateRenderingDuringSimulation = true; + // show graph container; + if ( graphContainer ) { + graphContainer.style("opacity", "1"); + percent = "100%"; + d3.select("#progressBarValue").style("width", percent); + d3.select("#progressBarValue").node().innerHTML = percent; + graph.options().ontologyMenu().append_message_toLastBulletPoint("done"); + d3.select("#reloadCachedOntology").classed("hidden", !showReloadButtonAfterLayoutOptimization); + if ( showFilterWarning === true && seenFilterWarning === false ) { + graph.options().warningModule().showFilterHint(); + seenFilterWarning = true; + } + } + + if ( initialLoad ) { + if ( graph.paused() === false ) + force.resume(); // resume force + initialLoad = false; + + } + + + finishedLoadingSequence = true; + if ( showFPS === true ) { + force.on("tick", recalculatePositionsWithFPS); + recalculatePositionsWithFPS(); + } + else { + force.on("tick", recalculatePositions); + recalculatePositions(); + } + + if ( centerGraphViewOnLoad === true && force.nodes().length > 0 ) { + if ( force.nodes().length < 10 ) graph.forceRelocationEvent(true); // uses dynamic zoomer; + else graph.forceRelocationEvent(); + centerGraphViewOnLoad = false; + // console.log("--------------------------------------") + } + + + graph.showEditorHintIfNeeded(); + + if ( graph.options().loadingModule().missingImportsWarning() === false ) { + graph.options().loadingModule().hideLoadingIndicator(); + graph.options().ontologyMenu().append_bulletPoint("Successfully loaded ontology"); + graph.options().loadingModule().setSuccessful(); + } else { + graph.options().loadingModule().showWarningDetailsMessage(); + graph.options().ontologyMenu().append_bulletPoint("Loaded ontology with warnings"); + } + } + } + } + + graph.showEditorHintIfNeeded = function (){ + if ( seenEditorHint === false && editMode === true ) { + seenEditorHint = true; + graph.options().warningModule().showEditorHint(); + } + }; + + graph.setForceTickFunctionWithFPS = function (){ + showFPS = true; + if ( force && finishedLoadingSequence === true ) { + force.on("tick", recalculatePositionsWithFPS); + } + + }; + graph.setDefaultForceTickFunction = function (){ + showFPS = false; + if ( force && finishedLoadingSequence === true ) { + force.on("tick", recalculatePositions); + } + }; + function recalculatePositionsWithFPS(){ + // compute the fps + + recalculatePositions(); + now = Date.now(); + var diff = now - then; + var fps = (1000 / (diff)).toFixed(2); + + debugContainer.node().innerHTML = "FPS: " + fps + "
    " + "Nodes: " + force.nodes().length + "
    " + "Links: " + force.links().length; + then = Date.now(); + + } + + function recalculatePositions(){ + // Set node positions + + + // add switch for edit mode to make this faster; + if ( !editMode ) { + nodeElements.attr("transform", function ( node ){ + return "translate(" + node.x + "," + node.y + ")"; + }); + + // Set label group positions + labelGroupElements.attr("transform", function ( label ){ + var position; + + // force centered positions on single-layered links + var link = label.link(); + if ( link.layers().length === 1 && !link.loops() ) { + var linkDomainIntersection = math.calculateIntersection(link.range(), link.domain(), 0); + var linkRangeIntersection = math.calculateIntersection(link.domain(), link.range(), 0); + position = math.calculateCenter(linkDomainIntersection, linkRangeIntersection); + label.x = position.x; + label.y = position.y; + } + return "translate(" + label.x + "," + label.y + ")"; + }); + // Set link paths and calculate additional information + linkPathElements.attr("d", function ( l ){ + if ( l.isLoop() ) { + return math.calculateLoopPath(l); + } + var curvePoint = l.label(); + var pathStart = math.calculateIntersection(curvePoint, l.domain(), 1); + var pathEnd = math.calculateIntersection(curvePoint, l.range(), 1); + + return curveFunction([pathStart, curvePoint, pathEnd]); + }); + + // Set cardinality positions + cardinalityElements.attr("transform", function ( property ){ + + var label = property.link().label(), + pos = math.calculateIntersection(label, property.range(), CARDINALITY_HDISTANCE), + normalV = math.calculateNormalVector(label, property.range(), CARDINALITY_VDISTANCE); + + return "translate(" + (pos.x + normalV.x) + "," + (pos.y + normalV.y) + ")"; + }); + + + updateHaloRadius(); + return; + } + + // TODO: this is Editor redraw function // we need to make this faster!! + + + nodeElements.attr("transform", function ( node ){ + return "translate(" + node.x + "," + node.y + ")"; + }); + + // Set label group positions + labelGroupElements.attr("transform", function ( label ){ + var position; + + // force centered positions on single-layered links + var link = label.link(); + if ( link.layers().length === 1 && !link.loops() ) { + var linkDomainIntersection = math.calculateIntersection(link.range(), link.domain(), 0); + var linkRangeIntersection = math.calculateIntersection(link.domain(), link.range(), 0); + position = math.calculateCenter(linkDomainIntersection, linkRangeIntersection); + label.x = position.x; + label.y = position.y; + label.linkRangeIntersection = linkRangeIntersection; + label.linkDomainIntersection = linkDomainIntersection; + if ( link.property().focused() === true || hoveredPropertyElement !== undefined ) { + rangeDragger.updateElement(); + domainDragger.updateElement(); + // shadowClone.setPosition(link.property().range().x,link.property().range().y); + // shadowClone.setPositionDomain(link.property().domain().x,link.property().domain().y); + } + } else { + label.linkDomainIntersection = math.calculateIntersection(link.label(), link.domain(), 0); + label.linkRangeIntersection = math.calculateIntersection(link.label(), link.range(), 0); + if ( link.property().focused() === true || hoveredPropertyElement !== undefined ) { + rangeDragger.updateElement(); + domainDragger.updateElement(); + // shadowClone.setPosition(link.property().range().x,link.property().range().y); + // shadowClone.setPositionDomain(link.property().domain().x,link.property().domain().y); + } + + } + return "translate(" + label.x + "," + label.y + ")"; + }); + // Set link paths and calculate additional information + linkPathElements.attr("d", function ( l ){ + if ( l.isLoop() ) { + + var ptrAr = math.getLoopPoints(l); + l.label().linkRangeIntersection = ptrAr[1]; + l.label().linkDomainIntersection = ptrAr[0]; + + if ( l.property().focused() === true || hoveredPropertyElement !== undefined ) { + rangeDragger.updateElement(); + domainDragger.updateElement(); + } + return math.calculateLoopPath(l); + } + var curvePoint = l.label(); + var pathStart = math.calculateIntersection(curvePoint, l.domain(), 1); + var pathEnd = math.calculateIntersection(curvePoint, l.range(), 1); + l.linkRangeIntersection = pathStart; + l.linkDomainIntersection = pathEnd; + if ( l.property().focused() === true || hoveredPropertyElement !== undefined ) { + domainDragger.updateElement(); + rangeDragger.updateElement(); + // shadowClone.setPosition(l.property().range().x,l.property().range().y); + // shadowClone.setPositionDomain(l.property().domain().x,l.property().domain().y); + } + return curveFunction([pathStart, curvePoint, pathEnd]); + }); + + // Set cardinality positions + cardinalityElements.attr("transform", function ( property ){ + + var label = property.link().label(), + pos = math.calculateIntersection(label, property.range(), CARDINALITY_HDISTANCE), + normalV = math.calculateNormalVector(label, property.range(), CARDINALITY_VDISTANCE); + + return "translate(" + (pos.x + normalV.x) + "," + (pos.y + normalV.y) + ")"; + }); + + if ( hoveredNodeElement ) { + setDeleteHoverElementPosition(hoveredNodeElement); + setAddDataPropertyHoverElementPosition(hoveredNodeElement); + if ( draggingStarted === false ) { + classDragger.setParentNode(hoveredNodeElement); + } + } + if ( hoveredPropertyElement ) { + setDeleteHoverElementPositionProperty(hoveredPropertyElement); + } + + updateHaloRadius(); + } + + graph.updatePropertyDraggerElements = function ( property ){ + if ( property.type() !== "owl:DatatypeProperty" ) { + + shadowClone.setParentProperty(property); + rangeDragger.setParentProperty(property); + rangeDragger.hideDragger(false); + rangeDragger.addMouseEvents(); + domainDragger.setParentProperty(property); + domainDragger.hideDragger(false); + domainDragger.addMouseEvents(); + + } + else { + rangeDragger.hideDragger(true); + domainDragger.hideDragger(true); + shadowClone.hideClone(true); + } + }; + + function addClickEvents(){ + function executeModules( selectedElement ){ + options.selectionModules().forEach(function ( module ){ + module.handle(selectedElement); + }); + } + + nodeElements.on("click", function ( clickedNode ){ + + // manaual double clicker // helper for iphone 6 etc... + if ( touchDevice === true && doubletap() === true ) { + d3.event.stopPropagation(); + if ( editMode === true ) { + clickedNode.raiseDoubleClickEdit(defaultIriValue(clickedNode)); + } + } + else { + executeModules(clickedNode); + } + }); + + nodeElements.on("dblclick", function ( clickedNode ){ + + d3.event.stopPropagation(); + if ( editMode === true ) { + clickedNode.raiseDoubleClickEdit(defaultIriValue(clickedNode)); + } + }); + + labelGroupElements.selectAll(".label").on("click", function ( clickedProperty ){ + executeModules(clickedProperty); + + // this is for enviroments that do not define dblClick function; + if ( touchDevice === true && doubletap() === true ) { + d3.event.stopPropagation(); + if ( editMode === true ) { + clickedProperty.raiseDoubleClickEdit(defaultIriValue(clickedProperty)); + } + } + + // currently removed the selection of an element to invoke the dragger + // if (editMode===true && clickedProperty.editingTextElement!==true) { + // return; + // // We say that Datatype properties are not allowed to have domain range draggers + // if (clickedProperty.focused() && clickedProperty.type() !== "owl:DatatypeProperty") { + // shadowClone.setParentProperty(clickedProperty); + // rangeDragger.setParentProperty(clickedProperty); + // rangeDragger.hideDragger(false); + // rangeDragger.addMouseEvents(); + // domainDragger.setParentProperty(clickedProperty); + // domainDragger.hideDragger(false); + // domainDragger.addMouseEvents(); + // + // if (clickedProperty.domain()===clickedProperty.range()){ + // clickedProperty.labelObject().increasedLoopAngle=true; + // recalculatePositions(); + // + // } + // + // } else if (clickedProperty.focused() && clickedProperty.type() === "owl:DatatypeProperty") { + // shadowClone.setParentProperty(clickedProperty); + // rangeDragger.setParentProperty(clickedProperty); + // rangeDragger.hideDragger(true); + // rangeDragger.addMouseEvents(); + // domainDragger.setParentProperty(clickedProperty); + // domainDragger.hideDragger(false); + // domainDragger.addMouseEvents(); + // + // } + // else { + // rangeDragger.hideDragger(true); + // domainDragger.hideDragger(true); + // if (clickedProperty.domain()===clickedProperty.range()){ + // clickedProperty.labelObject().increasedLoopAngle=false; + // recalculatePositions(); + // + // } + // } + // } + }); + labelGroupElements.selectAll(".label").on("dblclick", function ( clickedProperty ){ + d3.event.stopPropagation(); + if ( editMode === true ) { + clickedProperty.raiseDoubleClickEdit(defaultIriValue(clickedProperty)); + } + + }); + } + + function defaultIriValue( element ){ + // get the iri of that element; + if ( graph.options().getGeneralMetaObject().iri ) { + var str2Compare = graph.options().getGeneralMetaObject().iri + element.id(); + return element.iri() === str2Compare; + } + return false; + } + + /** Adjusts the containers current scale and position. */ + function zoomed(){ + if ( forceNotZooming === true ) { + zoom.translate(graphTranslation); + zoom.scale(zoomFactor); + return; + } + + + var zoomEventByMWheel = false; + if ( d3.event.sourceEvent ) { + if ( d3.event.sourceEvent.deltaY ) zoomEventByMWheel = true; + } + if ( zoomEventByMWheel === false ) { + if ( transformAnimation === true ) { + return; + } + zoomFactor = d3.event.scale; + graphTranslation = d3.event.translate; + graphContainer.attr("transform", "translate(" + graphTranslation + ")scale(" + zoomFactor + ")"); + updateHaloRadius(); + graph.options().zoomSlider().updateZoomSliderValue(zoomFactor); + return; + } + /** animate the transition **/ + zoomFactor = d3.event.scale; + graphTranslation = d3.event.translate; + graphContainer.transition() + .tween("attr.translate", function (){ + return function ( t ){ + transformAnimation = true; + var tr = d3.transform(graphContainer.attr("transform")); + graphTranslation[0] = tr.translate[0]; + graphTranslation[1] = tr.translate[1]; + zoomFactor = tr.scale[0]; + updateHaloRadius(); + graph.options().zoomSlider().updateZoomSliderValue(zoomFactor); + }; + }) + .each("end", function (){ + transformAnimation = false; + }) + .attr("transform", "translate(" + graphTranslation + ")scale(" + zoomFactor + ")") + .ease('linear') + .duration(250); + }// end of zoomed function + + function redrawGraph(){ + remove(); + + graphContainer = d3.selectAll(options.graphContainerSelector()) + .append("svg") + .classed("vowlGraph", true) + .attr("width", options.width()) + .attr("height", options.height()) + .call(zoom) + .append("g"); + // add touch and double click functions + + var svgGraph = d3.selectAll(".vowlGraph"); + originalD3_dblClickFunction = svgGraph.on("dblclick.zoom"); + originalD3_touchZoomFunction = svgGraph.on("touchstart"); + svgGraph.on("touchstart", touchzoomed); + if ( editMode === true ) { + svgGraph.on("dblclick.zoom", graph.modified_dblClickFunction); + } + else { + svgGraph.on("dblclick.zoom", originalD3_dblClickFunction); + } + + } + + function generateEditElements(){ + addDataPropertyGroupElement = editContainer.append('g') + .classed("hidden-in-export", true) + .classed("hidden", true) + .classed("addDataPropertyElement", true) + .attr("transform", "translate(" + 0 + "," + 0 + ")"); + + + addDataPropertyGroupElement.append("circle") + // .classed("deleteElement", true) + .attr("r", 12) + .attr("cx", 0) + .attr("cy", 0) + .append("title").text("Add Datatype Property"); + + addDataPropertyGroupElement.append("line") + // .classed("deleteElementIcon ",true) + .attr("x1", -8) + .attr("y1", 0) + .attr("x2", 8) + .attr("y2", 0) + .append("title").text("Add Datatype Property"); + + addDataPropertyGroupElement.append("line") + // .classed("deleteElementIcon",true) + .attr("x1", 0) + .attr("y1", -8) + .attr("x2", 0) + .attr("y2", 8) + .append("title").text("Add Datatype Property"); + + if ( graph.options().useAccuracyHelper() ) { + addDataPropertyGroupElement.append("circle") + .attr("r", 15) + .attr("cx", -7) + .attr("cy", 7) + .classed("superHiddenElement", true) + .classed("superOpacityElement", !graph.options().showDraggerObject()); + } + + + deleteGroupElement = editContainer.append('g') + .classed("hidden-in-export", true) + .classed("hidden", true) + .classed("deleteParentElement", true) + .attr("transform", "translate(" + 0 + "," + 0 + ")"); + + deleteGroupElement.append("circle") + .attr("r", 12) + .attr("cx", 0) + .attr("cy", 0) + .append("title").text("Delete This Node"); + + var crossLen = 5; + deleteGroupElement.append("line") + .attr("x1", -crossLen) + .attr("y1", -crossLen) + .attr("x2", crossLen) + .attr("y2", crossLen) + .append("title").text("Delete This Node"); + + deleteGroupElement.append("line") + .attr("x1", crossLen) + .attr("y1", -crossLen) + .attr("x2", -crossLen) + .attr("y2", crossLen) + .append("title").text("Delete This Node"); + + if ( graph.options().useAccuracyHelper() ) { + deleteGroupElement.append("circle") + .attr("r", 15) + .attr("cx", 7) + .attr("cy", -7) + .classed("superHiddenElement", true) + .classed("superOpacityElement", !graph.options().showDraggerObject()); + } + + + } + + graph.getUnfilteredData = function (){ + return unfilteredData; + }; + + graph.getClassDataForTtlExport = function (){ + var allNodes = unfilteredData.nodes; + var nodeData = []; + for ( var i = 0; i < allNodes.length; i++ ) { + if ( allNodes[i].type() !== "rdfs:Literal" && + allNodes[i].type() !== "rdfs:Datatype" && + allNodes[i].type() !== "owl:Thing" ) { + nodeData.push(allNodes[i]); + } + } + return nodeData; + }; + + graph.getPropertyDataForTtlExport = function (){ + var propertyData = []; + var allProperties = unfilteredData.properties; + for ( var i = 0; i < allProperties.length; i++ ) { + // currently using only the object properties + if ( allProperties[i].type() === "owl:ObjectProperty" || + allProperties[i].type() === "owl:DatatypeProperty" || + allProperties[i].type() === "owl:ObjectProperty" + + ) { + propertyData.push(allProperties[i]); + } else { + if ( allProperties[i].type() === "rdfs:subClassOf" ) { + allProperties[i].baseIri("http://www.w3.org/2000/01/rdf-schema#"); + allProperties[i].iri("http://www.w3.org/2000/01/rdf-schema#subClassOf"); + } + if ( allProperties[i].type() === "owl:disjointWith" ) { + allProperties[i].baseIri("http://www.w3.org/2002/07/owl#"); + allProperties[i].iri("http://www.w3.org/2002/07/owl#disjointWith"); + } + } + } + return propertyData; + }; + + graph.getAxiomsForTtlExport = function (){ + var axioms = []; + var allProperties = unfilteredData.properties; + for ( var i = 0; i < allProperties.length; i++ ) { + // currently using only the object properties + if ( allProperties[i].type() === "owl:ObjectProperty" || + allProperties[i].type() === "owl:DatatypeProperty" || + allProperties[i].type() === "owl:ObjectProperty" || + allProperties[i].type() === "rdfs:subClassOf" + ) { + } else { + } + } + return axioms; + }; + + + graph.getUnfilteredData = function (){ + return unfilteredData; + }; + + graph.getClassDataForTtlExport = function (){ + var allNodes = unfilteredData.nodes; + var nodeData = []; + for ( var i = 0; i < allNodes.length; i++ ) { + if ( allNodes[i].type() !== "rdfs:Literal" && + allNodes[i].type() !== "rdfs:Datatype" && + allNodes[i].type() !== "owl:Thing" ) { + nodeData.push(allNodes[i]); + } + } + return nodeData; + }; + + + function redrawContent(){ + var markerContainer; + + if ( !graphContainer ) { + return; + } + + // Empty the graph container + graphContainer.selectAll("*").remove(); + + // Last container -> elements of this container overlap others + linkContainer = graphContainer.append("g").classed("linkContainer", true); + cardinalityContainer = graphContainer.append("g").classed("cardinalityContainer", true); + labelContainer = graphContainer.append("g").classed("labelContainer", true); + nodeContainer = graphContainer.append("g").classed("nodeContainer", true); + + // adding editing Elements + var draggerPathLayer = graphContainer.append("g").classed("linkContainer", true); + draggerLayer = graphContainer.append("g").classed("editContainer", true); + editContainer = graphContainer.append("g").classed("editContainer", true); + + draggerPathLayer.classed("hidden-in-export", true); + editContainer.classed("hidden-in-export", true); + draggerLayer.classed("hidden-in-export", true); + + // Add an extra container for all markers + markerContainer = linkContainer.append("defs"); + var drElement = draggerLayer.selectAll(".node") + .data(draggerObjectsArray).enter() + .append("g") + .classed("node", true) + .classed("hidden-in-export", true) + .attr("id", function ( d ){ + return d.id(); + }) + .call(dragBehaviour); + drElement.each(function ( node ){ + node.svgRoot(d3.select(this)); + node.svgPathLayer(draggerPathLayer); + if ( node.type() === "shadowClone" ) { + node.drawClone(); + node.hideClone(true); + } else { + node.drawNode(); + node.hideDragger(true); + } + }); + generateEditElements(); + + + // Add an extra container for all markers + markerContainer = linkContainer.append("defs"); + + // Draw nodes + + if ( classNodes === undefined ) classNodes = []; + + nodeElements = nodeContainer.selectAll(".node") + .data(classNodes).enter() + .append("g") + .classed("node", true) + .attr("id", function ( d ){ + return d.id(); + }) + .call(dragBehaviour); + nodeElements.each(function ( node ){ + node.draw(d3.select(this)); + }); + + + if ( labelNodes === undefined ) labelNodes = []; + + // Draw label groups (property + inverse) + labelGroupElements = labelContainer.selectAll(".labelGroup") + .data(labelNodes).enter() + .append("g") + .classed("labelGroup", true) + .call(dragBehaviour); + + labelGroupElements.each(function ( label ){ + var success = label.draw(d3.select(this)); + label.property().labelObject(label); + // Remove empty groups without a label. + if ( !success ) { + d3.select(this).remove(); + } + }); + // Place subclass label groups on the bottom of all labels + labelGroupElements.each(function ( label ){ + // the label might be hidden e.g. in compact notation + if ( !this.parentNode ) { + return; + } + + if ( elementTools.isRdfsSubClassOf(label.property()) ) { + var parentNode = this.parentNode; + parentNode.insertBefore(this, parentNode.firstChild); + } + }); + if ( properties === undefined ) properties = []; + // Draw cardinality elements + cardinalityElements = cardinalityContainer.selectAll(".cardinality") + .data(properties).enter() + .append("g") + .classed("cardinality", true); + + cardinalityElements.each(function ( property ){ + var success = property.drawCardinality(d3.select(this)); + + // Remove empty groups without a label. + if ( !success ) { + d3.select(this).remove(); + } + }); + // Draw links + if ( links === undefined ) links = []; + linkGroups = linkContainer.selectAll(".link") + .data(links).enter() + .append("g") + .classed("link", true); + + linkGroups.each(function ( link ){ + link.draw(d3.select(this), markerContainer); + }); + linkPathElements = linkGroups.selectAll("path"); + // Select the path for direct access to receive a better performance + addClickEvents(); + } + + function remove(){ + if ( graphContainer ) { + // Select the parent element because the graph container is a group (e.g. for zooming) + d3.select(graphContainer.node().parentNode).remove(); + } + } + + initializeGraph(); // << call the initialization function + + graph.updateCanvasContainerSize = function (){ + if ( graphContainer ) { + var svgElement = d3.selectAll(".vowlGraph"); + svgElement.attr("width", options.width()); + svgElement.attr("height", options.height()); + graphContainer.attr("transform", "translate(" + graphTranslation + ")scale(" + zoomFactor + ")"); + } + }; + + // Loads all settings, removes the old graph (if it exists) and draws a new one. + graph.start = function (){ + force.stop(); + loadGraphData(true); + redrawGraph(); + graph.update(true); + + if ( graph.options().loadingModule().successfullyLoadedOntology() === false ) { + graph.options().loadingModule().setErrorMode(); + } + + }; + + // Updates only the style of the graph. + graph.updateStyle = function (){ + refreshGraphStyle(); + if ( graph.options().loadingModule().successfullyLoadedOntology() === false ) { + force.stop(); + } else { + force.start(); + } + }; + + graph.reload = function (){ + loadGraphData(); + graph.update(); + + }; + + graph.load = function (){ + force.stop(); + loadGraphData(); + refreshGraphData(); + for ( var i = 0; i < labelNodes.length; i++ ) { + var label = labelNodes[i]; + if ( label.property().x && label.property().y ) { + label.x = label.property().x; + label.y = label.property().y; + // also set the prev position of the label + label.px = label.x; + label.py = label.y; + } + } + graph.update(); + }; + + graph.fastUpdate = function (){ + // fast update function for editor calls; + // -- experimental ; + quick_refreshGraphData(); + updateNodeMap(); + force.start(); + redrawContent(); + graph.updatePulseIds(nodeArrayForPulse); + refreshGraphStyle(); + updateHaloStyles(); + + }; + + graph.getNodeMapForSearch = function (){ + return nodeMap; + }; + function updateNodeMap(){ + nodeMap = []; + var node; + for ( var j = 0; j < force.nodes().length; j++ ) { + node = force.nodes()[j]; + if ( node.id ) { + nodeMap[node.id()] = j; + // check for equivalents + var eqs = node.equivalents(); + if ( eqs.length > 0 ) { + for ( var e = 0; e < eqs.length; e++ ) { + var eqObject = eqs[e]; + nodeMap[eqObject.id()] = j; + } + } + } + if ( node.property ) { + nodeMap[node.property().id()] = j; + var inverse = node.inverse(); + if ( inverse ) { + nodeMap[inverse.id()] = j; + } + } + } + } + + function updateHaloStyles(){ + var haloElement; + var halo; + var node; + for ( var j = 0; j < force.nodes().length; j++ ) { + node = force.nodes()[j]; + if ( node.id ) { + haloElement = node.getHalos(); + if ( haloElement ) { + halo = haloElement.selectAll(".searchResultA"); + halo.classed("searchResultA", false); + halo.classed("searchResultB", true); + } + } + + if ( node.property ) { + haloElement = node.property().getHalos(); + if ( haloElement ) { + halo = haloElement.selectAll(".searchResultA"); + halo.classed("searchResultA", false); + halo.classed("searchResultB", true); + } + } + } + } + + // Updates the graphs displayed data and style. + graph.update = function ( init ){ + var validOntology = graph.options().loadingModule().successfullyLoadedOntology(); + if ( validOntology === false && (init && init === true) ) { + graph.options().loadingModule().collapseDetails(); + return; + } + if ( validOntology === false ) { + return; + } + + keepDetailsCollapsedOnLoading = false; + refreshGraphData(); + // update node map + updateNodeMap(); + + force.start(); + redrawContent(); + graph.updatePulseIds(nodeArrayForPulse); + refreshGraphStyle(); + updateHaloStyles(); + }; + + graph.paused = function ( p ){ + if ( !arguments.length ) return paused; + paused = p; + graph.updateStyle(); + return graph; + }; + // resetting the graph + graph.reset = function (){ + // window size + var w = 0.5 * graph.options().width(); + var h = 0.5 * graph.options().height(); + // computing initial translation for the graph due tue the dynamic default zoom level + var tx = w - defaultZoom * w; + var ty = h - defaultZoom * h; + zoom.translate([tx, ty]) + .scale(defaultZoom); + }; + + + graph.zoomOut = function (){ + + var minMag = options.minMagnification(), + maxMag = options.maxMagnification(); + var stepSize = (maxMag - minMag) / 10; + var val = zoomFactor - stepSize; + if ( val < minMag ) val = minMag; + + var cx = 0.5 * graph.options().width(); + var cy = 0.5 * graph.options().height(); + var cp = getWorldPosFromScreen(cx, cy, graphTranslation, zoomFactor); + var sP = [cp.x, cp.y, graph.options().height() / zoomFactor]; + var eP = [cp.x, cp.y, graph.options().height() / val]; + var pos_intp = d3.interpolateZoom(sP, eP); + + graphContainer.attr("transform", transform(sP, cx, cy)) + .transition() + .duration(250) + .attrTween("transform", function (){ + return function ( t ){ + return transform(pos_intp(t), cx, cy); + }; + }) + .each("end", function (){ + graphContainer.attr("transform", "translate(" + graphTranslation + ")scale(" + zoomFactor + ")"); + zoom.translate(graphTranslation); + zoom.scale(zoomFactor); + updateHaloRadius(); + options.zoomSlider().updateZoomSliderValue(zoomFactor); + }); + + }; + + graph.zoomIn = function (){ + var minMag = options.minMagnification(), + maxMag = options.maxMagnification(); + var stepSize = (maxMag - minMag) / 10; + var val = zoomFactor + stepSize; + if ( val > maxMag ) val = maxMag; + var cx = 0.5 * graph.options().width(); + var cy = 0.5 * graph.options().height(); + var cp = getWorldPosFromScreen(cx, cy, graphTranslation, zoomFactor); + var sP = [cp.x, cp.y, graph.options().height() / zoomFactor]; + var eP = [cp.x, cp.y, graph.options().height() / val]; + var pos_intp = d3.interpolateZoom(sP, eP); + + graphContainer.attr("transform", transform(sP, cx, cy)) + .transition() + .duration(250) + .attrTween("transform", function (){ + return function ( t ){ + return transform(pos_intp(t), cx, cy); + }; + }) + .each("end", function (){ + graphContainer.attr("transform", "translate(" + graphTranslation + ")scale(" + zoomFactor + ")"); + zoom.translate(graphTranslation); + zoom.scale(zoomFactor); + updateHaloRadius(); + options.zoomSlider().updateZoomSliderValue(zoomFactor); + }); + + + }; + + /** --------------------------------------------------------- **/ + /** -- data related handling -- **/ + /** --------------------------------------------------------- **/ + + var cachedJsonOBJ = null; + graph.clearAllGraphData = function (){ + if ( graph.graphNodeElements() && graph.graphNodeElements().length > 0 ) { + cachedJsonOBJ = graph.options().exportMenu().createJSON_exportObject(); + } else { + cachedJsonOBJ = null; + } + force.stop(); + if ( unfilteredData ) { + unfilteredData.nodes = []; + unfilteredData.properties = []; + } + }; + graph.getCachedJsonObj = function (){ + return cachedJsonOBJ; + }; + + // removes data when data could not be loaded + graph.clearGraphData = function (){ + force.stop(); + var sidebar = graph.options().sidebar(); + if ( sidebar ) + sidebar.clearOntologyInformation(); + if ( graphContainer ) + redrawGraph(); + }; + + function generateDictionary( data ){ + var i; + var originalDictionary = []; + var nodes = data.nodes; + for ( i = 0; i < nodes.length; i++ ) { + // check if node has a label + if ( nodes[i].labelForCurrentLanguage() !== undefined ) + originalDictionary.push(nodes[i]); + } + var props = data.properties; + for ( i = 0; i < props.length; i++ ) { + if ( props[i].labelForCurrentLanguage() !== undefined ) + originalDictionary.push(props[i]); + } + parser.setDictionary(originalDictionary); + + var literFilter = graph.options().literalFilter(); + var idsToRemove = literFilter.removedNodes(); + var originalDict = parser.getDictionary(); + var newDict = []; + + // go through the dictionary and remove the ids; + for ( i = 0; i < originalDict.length; i++ ) { + var dictElement = originalDict[i]; + var dictElementId; + if ( dictElement.property ) + dictElementId = dictElement.property().id(); + else + dictElementId = dictElement.id(); + // compare against the removed ids; + var addToDictionary = true; + for ( var j = 0; j < idsToRemove.length; j++ ) { + var currentId = idsToRemove[j]; + if ( currentId === dictElementId ) { + addToDictionary = false; + } + } + if ( addToDictionary === true ) { + newDict.push(dictElement); + } + } + // tell the parser that the dictionary is updated + parser.setDictionary(newDict); + + } + + graph.updateProgressBarMode = function (){ + var loadingModule = graph.options().loadingModule(); + + var state = loadingModule.getProgressBarMode(); + switch ( state ) { + case 0: + loadingModule.setErrorMode(); + break; + case 1: + loadingModule.setBusyMode(); + break; + case 2: + loadingModule.setPercentMode(); + break; + default: + loadingModule.setPercentMode(); + } + }; + + graph.setFilterWarning = function ( val ){ + showFilterWarning = val; + }; + function loadGraphData( init ){ + // reset the locate button and previously selected locations and other variables + + var loadingModule = graph.options().loadingModule(); + force.stop(); + + force.nodes([]); + force.links([]); + nodeArrayForPulse = []; + pulseNodeIds = []; + locationId = 0; + d3.select("#locateSearchResult").classed("highlighted", false); + d3.select("#locateSearchResult").node().title = "Nothing to locate"; + graph.clearGraphData(); + + if ( init ) { + force.stop(); + return; + } + + showFilterWarning = false; + parser.parse(options.data()); + unfilteredData = { + nodes: parser.nodes(), + properties: parser.properties() + }; + // fixing class and property id counter for the editor + eN = unfilteredData.nodes.length + 1; + eP = unfilteredData.properties.length + 1; + + initialLoad = true; + graph.options().warningModule().closeFilterHint(); + + // loading handler + updateRenderingDuringSimulation = true; + var validOntology = graph.options().loadingModule().successfullyLoadedOntology(); + if ( graphContainer && validOntology === true ) { + + updateRenderingDuringSimulation = false; + graph.options().ontologyMenu().append_bulletPoint("Generating visualization ... "); + loadingModule.setPercentMode(); + + if ( unfilteredData.nodes.length > 0 ) { + graphContainer.style("opacity", "0"); + force.on("tick", hiddenRecalculatePositions); + } else { + graphContainer.style("opacity", "1"); + if ( showFPS === true ) { + force.on("tick", recalculatePositionsWithFPS); + } + else { + force.on("tick", recalculatePositions); + } + } + + force.start(); + } else { + force.stop(); + graph.options().ontologyMenu().append_bulletPoint("Failed to load ontology"); + loadingModule.setErrorMode(); + } + // update prefixList( + // update general MetaOBJECT + graph.options().clearMetaObject(); + graph.options().clearGeneralMetaObject(); + graph.options().editSidebar().clearMetaObjectValue(); + if ( options.data() !== undefined ) { + var header = options.data().header; + if ( header ) { + if ( header.iri ) { + graph.options().addOrUpdateGeneralObjectEntry("iri", header.iri); + } + if ( header.title ) { + graph.options().addOrUpdateGeneralObjectEntry("title", header.title); + } + if ( header.author ) { + graph.options().addOrUpdateGeneralObjectEntry("author", header.author); + } + if ( header.version ) { + graph.options().addOrUpdateGeneralObjectEntry("version", header.version); + } + if ( header.description ) { + graph.options().addOrUpdateGeneralObjectEntry("description", header.description); + } + if ( header.prefixList ) { + var pL = header.prefixList; + for ( var pr in pL ) { + if ( pL.hasOwnProperty(pr) ) { + var val = pL[pr]; + graph.options().addPrefix(pr, val); + } + } + } + // get other metadata; + if ( header.other ) { + var otherObjects = header.other; + for ( var name in otherObjects ) { + if ( otherObjects.hasOwnProperty(name) ) { + var otherObj = otherObjects[name]; + if ( otherObj.hasOwnProperty("identifier") && otherObj.hasOwnProperty("value") ) { + graph.options().addOrUpdateMetaObjectEntry(otherObj.identfier, otherObj.value); + } + } + } + } + } + } + // update more meta OBJECT + // Initialize filters with data to replicate consecutive filtering + var initializationData = _.clone(unfilteredData); + options.filterModules().forEach(function ( module ){ + initializationData = filterFunction(module, initializationData, true); + }); + // generate dictionary here ; + generateDictionary(unfilteredData); + + parser.parseSettings(); + graphUpdateRequired = parser.settingsImported(); + centerGraphViewOnLoad = true; + if ( parser.settingsImportGraphZoomAndTranslation() === true ) { + centerGraphViewOnLoad = false; + } + graph.options().searchMenu().requestDictionaryUpdate(); + graph.options().editSidebar().updateGeneralOntologyInfo(); + graph.options().editSidebar().updatePrefixUi(); + graph.options().editSidebar().updateElementWidth(); + } + + graph.handleOnLoadingError = function (){ + force.stop(); + graph.clearGraphData(); + graph.options().ontologyMenu().append_bulletPoint("Failed to load ontology"); + d3.select("#progressBarValue").node().innherHTML = ""; + d3.select("#progressBarValue").classed("busyProgressBar", false); + graph.options().loadingModule().setErrorMode(); + graph.options().loadingModule().showErrorDetailsMessage(); + }; + + function quick_refreshGraphData(){ + links = linkCreator.createLinks(properties); + labelNodes = links.map(function ( link ){ + return link.label(); + }); + + storeLinksOnNodes(classNodes, links); + setForceLayoutData(classNodes, labelNodes, links); + } + + //Applies the data of the graph options object and parses it. The graph is not redrawn. + function refreshGraphData(){ + var shouldExecuteEmptyFilter = options.literalFilter().enabled(); + graph.executeEmptyLiteralFilter(); + options.literalFilter().enabled(shouldExecuteEmptyFilter); + + var preprocessedData = _.clone(unfilteredData); + + // Filter the data + options.filterModules().forEach(function ( module ){ + preprocessedData = filterFunction(module, preprocessedData); + }); + options.focuserModule().handle(undefined, true); + classNodes = preprocessedData.nodes; + properties = preprocessedData.properties; + links = linkCreator.createLinks(properties); + labelNodes = links.map(function ( link ){ + return link.label(); + }); + storeLinksOnNodes(classNodes, links); + setForceLayoutData(classNodes, labelNodes, links); + // for (var i = 0; i < classNodes.length; i++) { + // if (classNodes[i].setRectangularRepresentation) + // classNodes[i].setRectangularRepresentation(graph.options().rectangularRepresentation()); + // } + } + + function filterFunction( module, data, initializing ){ + links = linkCreator.createLinks(data.properties); + storeLinksOnNodes(data.nodes, links); + + if ( initializing ) { + if ( module.initialize ) { + module.initialize(data.nodes, data.properties); + } + } + module.filter(data.nodes, data.properties); + return { + nodes: module.filteredNodes(), + properties: module.filteredProperties() + }; + } + + + /** --------------------------------------------------------- **/ + /** -- force-layout related functions -- **/ + /** --------------------------------------------------------- **/ + function storeLinksOnNodes( nodes, links ){ + for ( var i = 0, nodesLength = nodes.length; i < nodesLength; i++ ) { + var node = nodes[i], + connectedLinks = []; + + // look for properties where this node is the domain or range + for ( var j = 0, linksLength = links.length; j < linksLength; j++ ) { + var link = links[j]; + + if ( link.domain() === node || link.range() === node ) { + connectedLinks.push(link); + } + } + node.links(connectedLinks); + } + } + + function setForceLayoutData( classNodes, labelNodes, links ){ + var d3Links = []; + links.forEach(function ( link ){ + d3Links = d3Links.concat(link.linkParts()); + }); + + var d3Nodes = [].concat(classNodes).concat(labelNodes); + setPositionOfOldLabelsOnNewLabels(force.nodes(), labelNodes); + + force.nodes(d3Nodes) + .links(d3Links); + } + + // The label nodes are positioned randomly, because they are created from scratch if the data changes and lose + // their position information. With this hack the position of old labels is copied to the new labels. + function setPositionOfOldLabelsOnNewLabels( oldLabelNodes, labelNodes ){ + labelNodes.forEach(function ( labelNode ){ + for ( var i = 0; i < oldLabelNodes.length; i++ ) { + var oldNode = oldLabelNodes[i]; + if ( oldNode.equals(labelNode) ) { + labelNode.x = oldNode.x; + labelNode.y = oldNode.y; + labelNode.px = oldNode.px; + labelNode.py = oldNode.py; + break; + } + } + }); + } + + // Applies all options that don't change the graph data. + function refreshGraphStyle(){ + zoom = zoom.scaleExtent([options.minMagnification(), options.maxMagnification()]); + if ( graphContainer ) { + zoom.event(graphContainer); + } + + force.charge(function ( element ){ + var charge = options.charge(); + if ( elementTools.isLabel(element) ) { + charge *= 0.8; + } + return charge; + }) + .size([options.width(), options.height()]) + .linkDistance(calculateLinkPartDistance) + .gravity(options.gravity()) + .linkStrength(options.linkStrength()); // Flexibility of links + + force.nodes().forEach(function ( n ){ + n.frozen(paused); + }); + } + + function calculateLinkPartDistance( linkPart ){ + var link = linkPart.link(); + + if ( link.isLoop() ) { + return options.loopDistance(); + } + + // divide by 2 to receive the length for a single link part + var linkPartDistance = getVisibleLinkDistance(link) / 2; + linkPartDistance += linkPart.domain().actualRadius(); + linkPartDistance += linkPart.range().actualRadius(); + return linkPartDistance; + } + + function getVisibleLinkDistance( link ){ + if ( elementTools.isDatatype(link.domain()) || elementTools.isDatatype(link.range()) ) { + return options.datatypeDistance(); + } else { + return options.classDistance(); + } + } + + /** --------------------------------------------------------- **/ + /** -- animation functions for the nodes -- **/ + /** --------------------------------------------------------- **/ + + graph.animateDynamicLabelWidth = function (){ + var wantedWidth = options.dynamicLabelWidth(); + var i; + for ( i = 0; i < classNodes.length; i++ ) { + var nodeElement = classNodes[i]; + if ( elementTools.isDatatype(nodeElement) ) { + nodeElement.animateDynamicLabelWidth(wantedWidth); + } + } + for ( i = 0; i < properties.length; i++ ) { + properties[i].animateDynamicLabelWidth(wantedWidth); + } + }; + + + /** --------------------------------------------------------- **/ + /** -- halo and localization functions -- **/ + /** --------------------------------------------------------- **/ + function updateHaloRadius(){ + if ( pulseNodeIds && pulseNodeIds.length > 0 ) { + var forceNodes = force.nodes(); + for ( var i = 0; i < pulseNodeIds.length; i++ ) { + var node = forceNodes[pulseNodeIds[i]]; + if ( node ) { + if ( node.property ) { + // match search strings with property label + if ( node.property().inverse ) { + var searchString = graph.options().searchMenu().getSearchString().toLowerCase(); + var name = node.property().labelForCurrentLanguage().toLowerCase(); + if ( name === searchString ) computeDistanceToCenter(node); + else { + node.property().removeHalo(); + if ( node.property().inverse() ) { + if ( !node.property().inverse().getHalos() ) + node.property().inverse().drawHalo(); + computeDistanceToCenter(node, true); + } + if ( node.property().equivalents() ) { + var eq = node.property().equivalents(); + for ( var e = 0; e < eq.length; e++ ) { + if ( !eq[e].getHalos() ) + eq[e].drawHalo(); + } + if ( !node.property().getHalos() ) + node.property().drawHalo(); + computeDistanceToCenter(node, false); + + } + } + } + } + computeDistanceToCenter(node); + } + } + } + } + + function getScreenCoords( x, y, translate, scale ){ + var xn = translate[0] + x * scale; + var yn = translate[1] + y * scale; + return { x: xn, y: yn }; + } + + function getClickedScreenCoords( x, y, translate, scale ){ + var xn = (x - translate[0]) / scale; + var yn = (y - translate[1]) / scale; + return { x: xn, y: yn }; + } + + + function computeDistanceToCenter( node, inverse ){ + var container = node; + var w = graph.options().width(); + var h = graph.options().height(); + var posXY = getScreenCoords(node.x, node.y, graphTranslation, zoomFactor); + + var highlightOfInv = false; + + if ( inverse && inverse === true ) { + highlightOfInv = true; + posXY = getScreenCoords(node.x, node.y + 20, graphTranslation, zoomFactor); + } + var x = posXY.x; + var y = posXY.y; + var nodeIsRect = false; + var halo; + var roundHalo; + var rectHalo; + var borderPoint_x = 0; + var borderPoint_y = 0; + var defaultRadius; + var offset = 15; + var radius; + + if ( node.property && highlightOfInv === true ) { + if ( node.property().inverse() ) { + rectHalo = node.property().inverse().getHalos().select("rect"); + + } else { + if ( node.property().getHalos() ) + rectHalo = node.property().getHalos().select("rect"); + else { + node.property().drawHalo(); + rectHalo = node.property().getHalos().select("rect"); + } + } + rectHalo.classed("hidden", true); + if ( node.property().inverse() ) { + if ( node.property().inverse().getHalos() ) { + roundHalo = node.property().inverse().getHalos().select("circle"); + } + } else { + roundHalo = node.property().getHalos().select("circle"); + } + if ( roundHalo.node() === null ) { + radius = node.property().inverse().width() + 15; + + roundHalo = node.property().inverse().getHalos().append("circle") + .classed("searchResultB", true) + .classed("searchResultA", false) + .attr("r", radius + 15); + + } + halo = roundHalo; // swap the halo to be round + nodeIsRect = true; + container = node.property().inverse(); + } + + if ( node.id ) { + if ( !node.getHalos() ) return; // something went wrong before + halo = node.getHalos().select("rect"); + if ( halo.node() === null ) { + // this is a round node + nodeIsRect = false; + roundHalo = node.getHalos().select("circle"); + defaultRadius = node.actualRadius(); + roundHalo.attr("r", defaultRadius + offset); + halo = roundHalo; + } else { // this is a rect node + nodeIsRect = true; + rectHalo = node.getHalos().select("rect"); + rectHalo.classed("hidden", true); + roundHalo = node.getHalos().select("circle"); + if ( roundHalo.node() === null ) { + radius = node.width(); + roundHalo = node.getHalos().append("circle") + .classed("searchResultB", true) + .classed("searchResultA", false) + .attr("r", radius + offset); + } + halo = roundHalo; + } + } + if ( node.property && !inverse ) { + if ( !node.property().getHalos() ) return; // something went wrong before + rectHalo = node.property().getHalos().select("rect"); + rectHalo.classed("hidden", true); + + roundHalo = node.property().getHalos().select("circle"); + if ( roundHalo.node() === null ) { + radius = node.property().width(); + + roundHalo = node.property().getHalos().append("circle") + .classed("searchResultB", true) + .classed("searchResultA", false) + .attr("r", radius + 15); + + } + halo = roundHalo; // swap the halo to be round + nodeIsRect = true; + container = node.property(); + } + + if ( x < 0 || x > w || y < 0 || y > h ) { + // node outside viewport; + // check for quadrant and get the correct boarder point (intersection with viewport) + if ( x < 0 && y < 0 ) { + borderPoint_x = 0; + borderPoint_y = 0; + } else if ( x > 0 && x < w && y < 0 ) { + borderPoint_x = x; + borderPoint_y = 0; + } else if ( x > w && y < 0 ) { + borderPoint_x = w; + borderPoint_y = 0; + } else if ( x > w && y > 0 && y < h ) { + borderPoint_x = w; + borderPoint_y = y; + } else if ( x > w && y > h ) { + borderPoint_x = w; + borderPoint_y = h; + } else if ( x > 0 && x < w && y > h ) { + borderPoint_x = x; + borderPoint_y = h; + } else if ( x < 0 && y > h ) { + borderPoint_x = 0; + borderPoint_y = h; + } else if ( x < 0 && y > 0 && y < h ) { + borderPoint_x = 0; + borderPoint_y = y; + } + // kill all pulses of nodes that are outside the viewport + container.getHalos().select("rect").classed("searchResultA", false); + container.getHalos().select("circle").classed("searchResultA", false); + container.getHalos().select("rect").classed("searchResultB", true); + container.getHalos().select("circle").classed("searchResultB", true); + halo.classed("hidden", false); + // compute in pixel coordinates length of difference vector + var borderRadius_x = borderPoint_x - x; + var borderRadius_y = borderPoint_y - y; + + var len = borderRadius_x * borderRadius_x + borderRadius_y * borderRadius_y; + len = Math.sqrt(len); + + var normedX = borderRadius_x / len; + var normedY = borderRadius_y / len; + + len = len + 20; // add 20 px; + + // re-normalized vector + var newVectorX = normedX * len + x; + var newVectorY = normedY * len + y; + // compute world coordinates of this point + var wX = (newVectorX - graphTranslation[0]) / zoomFactor; + var wY = (newVectorY - graphTranslation[1]) / zoomFactor; + + // compute distance in world coordinates + var dx = wX - node.x; + var dy = wY - node.y; + if ( highlightOfInv === true ) + dy = wY - node.y - 20; + + if ( highlightOfInv === false && node.property && node.property().inverse() ) + dy = wY - node.y + 20; + + var newRadius = Math.sqrt(dx * dx + dy * dy); + halo = container.getHalos().select("circle"); + // sanity checks and setting new halo radius + if ( !nodeIsRect ) { + defaultRadius = node.actualRadius() + offset; + if ( newRadius < defaultRadius ) { + newRadius = defaultRadius; + } + halo.attr("r", newRadius); + } else { + defaultRadius = 0.5 * container.width(); + if ( newRadius < defaultRadius ) + newRadius = defaultRadius; + halo.attr("r", newRadius); + } + } else { // node is in viewport , render original; + // reset the halo to original radius + defaultRadius = node.actualRadius() + 15; + if ( !nodeIsRect ) { + halo.attr("r", defaultRadius); + } else { // this is rectangular node render as such + halo = container.getHalos().select("rect"); + halo.classed("hidden", false); + //halo.classed("searchResultB", true); + //halo.classed("searchResultA", false); + var aCircHalo = container.getHalos().select("circle"); + aCircHalo.classed("hidden", true); + + container.getHalos().select("rect").classed("hidden", false); + container.getHalos().select("circle").classed("hidden", true); + } + } + } + + function transform( p, cx, cy ){ + // one iteration step for the locate target animation + zoomFactor = graph.options().height() / p[2]; + graphTranslation = [(cx - p[0] * zoomFactor), (cy - p[1] * zoomFactor)]; + updateHaloRadius(); + // update the values in case the user wants to break the animation + zoom.translate(graphTranslation); + zoom.scale(zoomFactor); + graph.options().zoomSlider().updateZoomSliderValue(zoomFactor); + return "translate(" + graphTranslation[0] + "," + graphTranslation[1] + ")scale(" + zoomFactor + ")"; + } + + graph.zoomToElementInGraph = function ( element ){ + targetLocationZoom(element); + }; + graph.updateHaloRadius = function ( element ){ + computeDistanceToCenter(element); + }; + + function targetLocationZoom( target ){ + // store the original information + var cx = 0.5 * graph.options().width(); + var cy = 0.5 * graph.options().height(); + var cp = getWorldPosFromScreen(cx, cy, graphTranslation, zoomFactor); + var sP = [cp.x, cp.y, graph.options().height() / zoomFactor]; + + var zoomLevel = Math.max(defaultZoom + 0.5 * defaultZoom, defaultTargetZoom); + var eP = [target.x, target.y, graph.options().height() / zoomLevel]; + var pos_intp = d3.interpolateZoom(sP, eP); + + var lenAnimation = pos_intp.duration; + if ( lenAnimation > 2500 ) { + lenAnimation = 2500; + } + + graphContainer.attr("transform", transform(sP, cx, cy)) + .transition() + .duration(lenAnimation) + .attrTween("transform", function (){ + return function ( t ){ + return transform(pos_intp(t), cx, cy); + }; + }) + .each("end", function (){ + graphContainer.attr("transform", "translate(" + graphTranslation + ")scale(" + zoomFactor + ")"); + zoom.translate(graphTranslation); + zoom.scale(zoomFactor); + updateHaloRadius(); + }); + } + + function getWorldPosFromScreen( x, y, translate, scale ){ + var temp = scale[0], xn, yn; + if ( temp ) { + xn = (x - translate[0]) / temp; + yn = (y - translate[1]) / temp; + } else { + xn = (x - translate[0]) / scale; + yn = (y - translate[1]) / scale; + } + return { x: xn, y: yn }; + } + + graph.locateSearchResult = function (){ + if ( pulseNodeIds && pulseNodeIds.length > 0 ) { + // move the center of the viewport to this location + if ( transformAnimation === true ) return; // << prevents incrementing the location id if we are in an animation + var node = force.nodes()[pulseNodeIds[locationId]]; + locationId++; + locationId = locationId % pulseNodeIds.length; + if ( node.id ) node.foreground(); + if ( node.property ) node.property().foreground(); + + targetLocationZoom(node); + } + }; + + graph.resetSearchHighlight = function (){ + // get all nodes (handle also already filtered nodes ) + pulseNodeIds = []; + nodeArrayForPulse = []; + // clear from stored nodes + var nodes = unfilteredData.nodes; + var props = unfilteredData.properties; + var j; + for ( j = 0; j < nodes.length; j++ ) { + var node = nodes[j]; + if ( node.removeHalo ) + node.removeHalo(); + } + for ( j = 0; j < props.length; j++ ) { + var prop = props[j]; + if ( prop.removeHalo ) + prop.removeHalo(); + } + }; + + graph.updatePulseIds = function ( nodeIdArray ){ + pulseNodeIds = []; + for ( var i = 0; i < nodeIdArray.length; i++ ) { + var selectedId = nodeIdArray[i]; + var forceId = nodeMap[selectedId]; + if ( forceId !== undefined ) { + var le_node = force.nodes()[forceId]; + if ( le_node.id ) { + if ( pulseNodeIds.indexOf(forceId) === -1 ) { + pulseNodeIds.push(forceId); + } + } + if ( le_node.property ) { + if ( pulseNodeIds.indexOf(forceId) === -1 ) { + pulseNodeIds.push(forceId); + } + } + } + } + locationId = 0; + if ( pulseNodeIds.length > 0 ) { + d3.select("#locateSearchResult").classed("highlighted", true); + d3.select("#locateSearchResult").node().title = "Locate search term"; + } + else { + d3.select("#locateSearchResult").classed("highlighted", false); + d3.select("#locateSearchResult").node().title = "Nothing to locate"; + } + + }; + + graph.highLightNodes = function ( nodeIdArray ){ + if ( nodeIdArray.length === 0 ) { + return; // nothing to highlight + } + pulseNodeIds = []; + nodeArrayForPulse = nodeIdArray; + var missedIds = []; + + // identify the force id to highlight + for ( var i = 0; i < nodeIdArray.length; i++ ) { + var selectedId = nodeIdArray[i]; + var forceId = nodeMap[selectedId]; + if ( forceId !== undefined ) { + var le_node = force.nodes()[forceId]; + if ( le_node.id ) { + if ( pulseNodeIds.indexOf(forceId) === -1 ) { + pulseNodeIds.push(forceId); + le_node.foreground(); + le_node.drawHalo(); + } + } + if ( le_node.property ) { + if ( pulseNodeIds.indexOf(forceId) === -1 ) { + pulseNodeIds.push(forceId); + le_node.property().foreground(); + le_node.property().drawHalo(); + } + } + } + else { + missedIds.push(selectedId); + } + } + + if ( missedIds.length === nodeIdArray.length ) { + + } + // store the highlight on the missed nodes; + var s_nodes = unfilteredData.nodes; + var s_props = unfilteredData.properties; + for ( i = 0; i < missedIds.length; i++ ) { + var missedId = missedIds[i]; + // search for this in the nodes; + for ( var n = 0; n < s_nodes.length; n++ ) { + var nodeId = s_nodes[n].id(); + if ( nodeId === missedId ) { + s_nodes[n].drawHalo(); + } + } + for ( var p = 0; p < s_props.length; p++ ) { + var propId = s_props[p].id(); + if ( propId === missedId ) { + s_props[p].drawHalo(); + } + } + } + if ( missedIds.length === nodeIdArray.length ) { + d3.select("#locateSearchResult").classed("highlighted", false); + } + else { + d3.select("#locateSearchResult").classed("highlighted", true); + } + locationId = 0; + updateHaloRadius(); + }; + + graph.hideHalos = function (){ + var haloElements = d3.selectAll(".searchResultA,.searchResultB"); + haloElements.classed("hidden", true); + return haloElements; + }; + + function nodeInViewport( node, property ){ + + var w = graph.options().width(); + var h = graph.options().height(); + var posXY = getScreenCoords(node.x, node.y, graphTranslation, zoomFactor); + var x = posXY.x; + var y = posXY.y; + + var retVal = !(x < 0 || x > w || y < 0 || y > h); + return retVal; + } + + graph.getBoundingBoxForTex = function (){ + var halos = graph.hideHalos(); + var bbox = graphContainer.node().getBoundingClientRect(); + halos.classed("hidden", false); + var w = graph.options().width(); + var h = graph.options().height(); + + // get the graph coordinates + var topLeft = getWorldPosFromScreen(0, 0, graphTranslation, zoomFactor); + var botRight = getWorldPosFromScreen(w, h, graphTranslation, zoomFactor); + + + var t_topLeft = getWorldPosFromScreen(bbox.left, bbox.top, graphTranslation, zoomFactor); + var t_botRight = getWorldPosFromScreen(bbox.right, bbox.bottom, graphTranslation, zoomFactor); + + // tighten up the bounding box; + + var tX = Math.max(t_topLeft.x, topLeft.x); + var tY = Math.max(t_topLeft.y, topLeft.y); + + var bX = Math.min(t_botRight.x, botRight.x); + var bY = Math.min(t_botRight.y, botRight.y); + + + // tighten further; + var allForceNodes = force.nodes(); + var numNodes = allForceNodes.length; + var visibleNodes = []; + var bbx; + + + var contentBBox = { tx: 1000000000000, ty: 1000000000000, bx: -1000000000000, by: -1000000000000 }; + + for ( var i = 0; i < numNodes; i++ ) { + var node = allForceNodes[i]; + if ( node ) { + if ( node.property ) { + if ( nodeInViewport(node, true) ) { + if ( node.property().labelElement() === undefined ) continue; + bbx = node.property().labelElement().node().getBoundingClientRect(); + if ( bbx ) { + contentBBox.tx = Math.min(contentBBox.tx, bbx.left); + contentBBox.bx = Math.max(contentBBox.bx, bbx.right); + contentBBox.ty = Math.min(contentBBox.ty, bbx.top); + contentBBox.by = Math.max(contentBBox.by, bbx.bottom); + } + } + } else { + if ( nodeInViewport(node, false) ) { + bbx = node.nodeElement().node().getBoundingClientRect(); + if ( bbx ) { + contentBBox.tx = Math.min(contentBBox.tx, bbx.left); + contentBBox.bx = Math.max(contentBBox.bx, bbx.right); + contentBBox.ty = Math.min(contentBBox.ty, bbx.top); + contentBBox.by = Math.max(contentBBox.by, bbx.bottom); + } + } + } + } + } + + var tt_topLeft = getWorldPosFromScreen(contentBBox.tx, contentBBox.ty, graphTranslation, zoomFactor); + var tt_botRight = getWorldPosFromScreen(contentBBox.bx, contentBBox.by, graphTranslation, zoomFactor); + + tX = Math.max(tX, tt_topLeft.x); + tY = Math.max(tY, tt_topLeft.y); + + bX = Math.min(bX, tt_botRight.x); + bY = Math.min(bY, tt_botRight.y); + // y axis flip for tex + return [tX, -tY, bX, -bY]; + + }; + + var updateTargetElement = function (){ + var bbox = graphContainer.node().getBoundingClientRect(); + + + // get the graph coordinates + var bboxOffset = 50; // default radius of a node; + var topLeft = getWorldPosFromScreen(bbox.left, bbox.top, graphTranslation, zoomFactor); + var botRight = getWorldPosFromScreen(bbox.right, bbox.bottom, graphTranslation, zoomFactor); + + var w = graph.options().width(); + if ( graph.options().leftSidebar().isSidebarVisible() === true ) + w -= 200; + var h = graph.options().height(); + topLeft.x += bboxOffset; + topLeft.y -= bboxOffset; + botRight.x -= bboxOffset; + botRight.y += bboxOffset; + + var g_w = botRight.x - topLeft.x; + var g_h = botRight.y - topLeft.y; + + // endpoint position calculations + var posX = 0.5 * (topLeft.x + botRight.x); + var posY = 0.5 * (topLeft.y + botRight.y); + var cx = 0.5 * w, + cy = 0.5 * h; + + if ( graph.options().leftSidebar().isSidebarVisible() === true ) + cx += 200; + var cp = getWorldPosFromScreen(cx, cy, graphTranslation, zoomFactor); + + // zoom factor calculations and fail safes; + var newZoomFactor = 1.0; // fail save if graph and window are squares + //get the smaller one + var a = w / g_w; + var b = h / g_h; + if ( a < b ) newZoomFactor = a; + else newZoomFactor = b; + + + // fail saves + if ( newZoomFactor > zoom.scaleExtent()[1] ) { + newZoomFactor = zoom.scaleExtent()[1]; + } + if ( newZoomFactor < zoom.scaleExtent()[0] ) { + newZoomFactor = zoom.scaleExtent()[0]; + } + + // apply Zooming + var sP = [cp.x, cp.y, h / zoomFactor]; + var eP = [posX, posY, h / newZoomFactor]; + + + var pos_intp = d3.interpolateZoom(sP, eP); + return [pos_intp, cx, cy]; + + }; + + graph.forceRelocationEvent = function ( dynamic ){ + // we need to kill the halo to determine the bounding box; + var halos = graph.hideHalos(); + var bbox = graphContainer.node().getBoundingClientRect(); + halos.classed("hidden", false); + + // get the graph coordinates + var bboxOffset = 50; // default radius of a node; + var topLeft = getWorldPosFromScreen(bbox.left, bbox.top, graphTranslation, zoomFactor); + var botRight = getWorldPosFromScreen(bbox.right, bbox.bottom, graphTranslation, zoomFactor); + + var w = graph.options().width(); + if ( graph.options().leftSidebar().isSidebarVisible() === true ) + w -= 200; + var h = graph.options().height(); + topLeft.x += bboxOffset; + topLeft.y -= bboxOffset; + botRight.x -= bboxOffset; + botRight.y += bboxOffset; + + var g_w = botRight.x - topLeft.x; + var g_h = botRight.y - topLeft.y; + + // endpoint position calculations + var posX = 0.5 * (topLeft.x + botRight.x); + var posY = 0.5 * (topLeft.y + botRight.y); + var cx = 0.5 * w, + cy = 0.5 * h; + + if ( graph.options().leftSidebar().isSidebarVisible() === true ) + cx += 200; + var cp = getWorldPosFromScreen(cx, cy, graphTranslation, zoomFactor); + + // zoom factor calculations and fail safes; + var newZoomFactor = 1.0; // fail save if graph and window are squares + //get the smaller one + var a = w / g_w; + var b = h / g_h; + if ( a < b ) newZoomFactor = a; + else newZoomFactor = b; + + + // fail saves + if ( newZoomFactor > zoom.scaleExtent()[1] ) { + newZoomFactor = zoom.scaleExtent()[1]; + } + if ( newZoomFactor < zoom.scaleExtent()[0] ) { + newZoomFactor = zoom.scaleExtent()[0]; + } + + // apply Zooming + var sP = [cp.x, cp.y, h / zoomFactor]; + var eP = [posX, posY, h / newZoomFactor]; + + + var pos_intp = d3.interpolateZoom(sP, eP); + var lenAnimation = pos_intp.duration; + if ( lenAnimation > 2500 ) { + lenAnimation = 2500; + } + graphContainer.attr("transform", transform(sP, cx, cy)) + .transition() + .duration(lenAnimation) + .attrTween("transform", function (){ + return function ( t ){ + if ( dynamic ) { + var param = updateTargetElement(); + var nV = param[0](t); + return transform(nV, cx, cy); + } + return transform(pos_intp(t), cx, cy); + }; + }) + .each("end", function (){ + if ( dynamic ) { + return; + } + + graphContainer.attr("transform", "translate(" + graphTranslation + ")scale(" + zoomFactor + ")"); + zoom.translate(graphTranslation); + zoom.scale(zoomFactor); + graph.options().zoomSlider().updateZoomSliderValue(zoomFactor); + + + }); + }; + + + graph.isADraggerActive = function (){ + if ( classDragger.mouseButtonPressed === true || + domainDragger.mouseButtonPressed === true || + rangeDragger.mouseButtonPressed === true ) { + return true; + } + return false; + }; + + /** --------------------------------------------------------- **/ + /** -- VOWL EDITOR create/ edit /delete functions -- **/ + /** --------------------------------------------------------- **/ + + graph.changeNodeType = function ( element ){ + + var typeString = d3.select("#typeEditor").node().value; + + if ( graph.classesSanityCheck(element, typeString) === false ) { + // call reselection to restore previous type selection + graph.options().editSidebar().updateSelectionInformation(element); + return; + } + + var prototype = NodePrototypeMap.get(typeString.toLowerCase()); + var aNode = new prototype(graph); + + aNode.x = element.x; + aNode.y = element.y; + aNode.px = element.x; + aNode.py = element.y; + aNode.id(element.id()); + aNode.copyInformation(element); + + if ( typeString === "owl:Thing" ) { + aNode.label("Thing"); + } + else if ( elementTools.isDatatype(element) === false ) { + if ( element.backupLabel() !== undefined ) { + aNode.label(element.backupLabel()); + } else if ( aNode.backupLabel() !== undefined ) { + aNode.label(aNode.backupLabel()); + } else { + aNode.label("NewClass"); + } + } + + if ( typeString === "rdfs:Datatype" ) { + if ( aNode.dType() === "undefined" ) + aNode.label("undefined"); + else { + var identifier = aNode.dType().split(":")[1]; + aNode.label(identifier); + } + } + var i; + // updates the property domain and range + for ( i = 0; i < unfilteredData.properties.length; i++ ) { + if ( unfilteredData.properties[i].domain() === element ) { + // unfilteredData.properties[i].toString(); + unfilteredData.properties[i].domain(aNode); + } + if ( unfilteredData.properties[i].range() === element ) { + unfilteredData.properties[i].range(aNode); + // unfilteredData.properties[i].toString(); + } + } + + // update for fastUpdate: + for ( i = 0; i < properties.length; i++ ) { + if ( properties[i].domain() === element ) { + // unfilteredData.properties[i].toString(); + properties[i].domain(aNode); + } + if ( properties[i].range() === element ) { + properties[i].range(aNode); + // unfilteredData.properties[i].toString(); + } + } + + var remId = unfilteredData.nodes.indexOf(element); + if ( remId !== -1 ) + unfilteredData.nodes.splice(remId, 1); + remId = classNodes.indexOf(element); + if ( remId !== -1 ) + classNodes.splice(remId, 1); + // very important thing for selection!; + addNewNodeElement(aNode); + // handle focuser! + options.focuserModule().handle(aNode); + generateDictionary(unfilteredData); + graph.getUpdateDictionary(); + element = null; + }; + + + graph.changePropertyType = function ( element ){ + var typeString = d3.select("#typeEditor").node().value; + + // create warning + if ( graph.sanityCheckProperty(element.domain(), element.range(), typeString) === false ) return false; + + var propPrototype = PropertyPrototypeMap.get(typeString.toLowerCase()); + var aProp = new propPrototype(graph); + aProp.copyInformation(element); + aProp.id(element.id()); + + element.domain().removePropertyElement(element); + element.range().removePropertyElement(element); + aProp.domain(element.domain()); + aProp.range(element.range()); + + if ( element.backupLabel() !== undefined ) { + aProp.label(element.backupLabel()); + } else { + aProp.label("newObjectProperty"); + } + + if ( aProp.type() === "rdfs:subClassOf" ) { + aProp.iri("http://www.w3.org/2000/01/rdf-schema#subClassOf"); + } else { + if ( element.iri() === "http://www.w3.org/2000/01/rdf-schema#subClassOf" ) + aProp.iri(graph.options().getGeneralMetaObjectProperty('iri') + aProp.id()); + + } + + + if ( graph.propertyCheckExistenceChecker(aProp, element.domain(), element.range()) === false ) { + graph.options().editSidebar().updateSelectionInformation(element); + return; + } + // // TODO: change its base IRI to proper value + // var ontoIRI="http://someTest.de"; + // aProp.baseIri(ontoIRI); + // aProp.iri(aProp.baseIri()+aProp.id()); + + + // add this to the data; + unfilteredData.properties.push(aProp); + if ( properties.indexOf(aProp) === -1 ) + properties.push(aProp); + var remId = unfilteredData.properties.indexOf(element); + if ( remId !== -1 ) + unfilteredData.properties.splice(remId, 1); + if ( properties.indexOf(aProp) === -1 ) + properties.push(aProp); + remId = properties.indexOf(element); + if ( remId !== -1 ) + properties.splice(remId, 1); + graph.fastUpdate(); + aProp.domain().addProperty(aProp); + aProp.range().addProperty(aProp); + if ( element.labelObject() && aProp.labelObject() ) { + aProp.labelObject().x = element.labelObject().x; + aProp.labelObject().px = element.labelObject().px; + aProp.labelObject().y = element.labelObject().y; + aProp.labelObject().py = element.labelObject().py; + } + + options.focuserModule().handle(aProp); + element = null; + }; + + graph.removeEditElements = function (){ + // just added to be called form outside + removeEditElements(); + }; + + function removeEditElements(){ + rangeDragger.hideDragger(true); + domainDragger.hideDragger(true); + shadowClone.hideClone(true); + + classDragger.hideDragger(true); + if ( addDataPropertyGroupElement ) + addDataPropertyGroupElement.classed("hidden", true); + if ( deleteGroupElement ) + deleteGroupElement.classed("hidden", true); + + + if ( hoveredNodeElement ) { + if ( hoveredNodeElement.pinned() === false ) { + hoveredNodeElement.locked(graph.paused()); + hoveredNodeElement.frozen(graph.paused()); + } + } + if ( hoveredPropertyElement ) { + if ( hoveredPropertyElement.pinned() === false ) { + hoveredPropertyElement.locked(graph.paused()); + hoveredPropertyElement.frozen(graph.paused()); + } + } + + + } + + graph.editorMode = function ( val ){ + var create_entry = d3.select("#empty"); + var create_container = d3.select("#emptyContainer"); + + var modeOfOpString = d3.select("#modeOfOperationString").node(); + if ( !arguments.length ) { + create_entry.node().checked = editMode; + if ( editMode === false ) { + create_container.node().title = "Enable editing in modes menu to create a new ontology"; + create_entry.node().title = "Enable editing in modes menu to create a new ontology"; + create_entry.style("pointer-events", "none"); + } else { + create_container.node().title = "Creates a new empty ontology"; + create_entry.node().title = "Creates a new empty ontology"; + d3.select("#useAccuracyHelper").style("color", "#2980b9"); + d3.select("#useAccuracyHelper").style("pointer-events", "auto"); + create_entry.node().disabled = false; + create_entry.style("pointer-events", "auto"); + } + + return editMode; + } + graph.options().setEditorModeForDefaultObject(val); + + // if (seenEditorHint===false && val===true){ + // seenEditorHint=true; + // graph.options().warningModule().showEditorHint(); + // } + editMode = val; + + if ( create_entry ) { + create_entry.classed("disabled", !editMode); + if ( !editMode ) { + create_container.node().title = "Enable editing in modes menu to create a new ontology"; + create_entry.node().title = "Enable editing in modes menu to create a new ontology"; + create_entry.node().disabled = true; + d3.select("#useAccuracyHelper").style("color", "#979797"); + d3.select("#useAccuracyHelper").style("pointer-events", "none"); + create_entry.style("pointer-events", "none"); + } else { + create_container.node().title = "Creates a new empty ontology"; + create_entry.node().title = "Creates a new empty ontology"; + d3.select("#useAccuracyHelper").style("color", "#2980b9"); + d3.select("#useAccuracyHelper").style("pointer-events", "auto"); + create_entry.style("pointer-events", "auto"); + } + } + + // adjust compact notation + // selector = compactNotationOption; + // box =ModuleCheckbox + var compactNotationContainer = d3.select("#compactnotationModuleCheckbox"); + if ( compactNotationContainer ) { + compactNotationContainer.classed("disabled", !editMode); + if ( !editMode ) { + compactNotationContainer.node().title = ""; + compactNotationContainer.node().disabled = false; + compactNotationContainer.style("pointer-events", "auto"); + d3.select("#compactNotationOption").style("color", ""); + d3.select("#compactNotationOption").node().title = ""; + options.literalFilter().enabled(true); + graph.update(); + } else { + // if editor Mode + //1) uncheck the element + d3.select("#compactNotationOption").node().title = "Compact notation can only be used in view mode"; + compactNotationContainer.node().disabled = true; + compactNotationContainer.node().checked = false; + options.compactNotationModule().enabled(false); + options.literalFilter().enabled(false); + graph.executeCompactNotationModule(); + graph.executeEmptyLiteralFilter(); + graph.lazyRefresh(); + compactNotationContainer.style("pointer-events", "none"); + d3.select("#compactNotationOption").style("color", "#979797"); + } + } + + if ( modeOfOpString ) { + if ( touchDevice === true ) { + modeOfOpString.innerHTML = "touch able device detected"; + } else { + modeOfOpString.innerHTML = "point & click device detected"; + } + } + var svgGraph = d3.selectAll(".vowlGraph"); + + if ( editMode === true ) { + options.leftSidebar().showSidebar(options.leftSidebar().getSidebarVisibility(), true); + options.leftSidebar().hideCollapseButton(false); + graph.options().editSidebar().updatePrefixUi(); + graph.options().editSidebar().updateElementWidth(); + svgGraph.on("dblclick.zoom", graph.modified_dblClickFunction); + + } else { + svgGraph.on("dblclick.zoom", originalD3_dblClickFunction); + options.leftSidebar().showSidebar(0); + options.leftSidebar().hideCollapseButton(true); + // hide hovered edit elements + removeEditElements(); + } + options.sidebar().updateShowedInformation(); + options.editSidebar().updateElementWidth(); + + }; + + function createLowerCasePrototypeMap( prototypeMap ){ + return d3.map(prototypeMap.values(), function ( Prototype ){ + return new Prototype().type().toLowerCase(); + }); + } + + function createNewNodeAtPosition( pos ){ + var aNode, prototype; + var forceUpdate = true; + // create a node of that id; + + var typeToCreate = d3.select("#defaultClass").node().title; + prototype = NodePrototypeMap.get(typeToCreate.toLowerCase()); + aNode = new prototype(graph); + var autoEditElement = false; + if ( typeToCreate === "owl:Thing" ) { + aNode.label("Thing"); + } + else { + aNode.label("NewClass"); + autoEditElement = true; + } + aNode.x = pos.x; + aNode.y = pos.y; + aNode.px = aNode.x; + aNode.py = aNode.y; + aNode.id("Class" + eN++); + // aNode.paused(true); + + aNode.baseIri(d3.select("#iriEditor").node().value); + aNode.iri(aNode.baseIri() + aNode.id()); + addNewNodeElement(aNode, forceUpdate); + options.focuserModule().handle(aNode, true); + aNode.frozen(graph.paused()); + aNode.locked(graph.paused()); + aNode.enableEditing(autoEditElement); + } + + + function addNewNodeElement( element ){ + unfilteredData.nodes.push(element); + if ( classNodes.indexOf(element) === -1 ) + classNodes.push(element); + + generateDictionary(unfilteredData); + graph.getUpdateDictionary(); + graph.fastUpdate(); + } + + graph.getTargetNode = function ( position ){ + var dx = position[0]; + var dy = position[1]; + var tN = null; + var minDist = 1000000000000; + // This is a bit OVERKILL for the computation of one node >> TODO: KD-TREE SEARCH + unfilteredData.nodes.forEach(function ( el ){ + var cDist = Math.sqrt((el.x - dx) * (el.x - dx) + (el.y - dy) * (el.y - dy)); + if ( cDist < minDist ) { + minDist = cDist; + tN = el; + } + }); + if ( hoveredNodeElement ) { + var offsetDist = hoveredNodeElement.actualRadius() + 30; + if ( minDist > offsetDist ) return null; + if ( tN.renderType() === "rect" ) return null; + if ( tN === hoveredNodeElement && minDist <= hoveredNodeElement.actualRadius() ) { + return tN; + } else if ( tN === hoveredNodeElement && minDist > hoveredNodeElement.actualRadius() ) { + return null; + } + return tN; + } + else { + + if ( minDist > (tN.actualRadius() + 30) ) + return null; + else return tN; + + } + }; + + graph.genericPropertySanityCheck = function ( domain, range, typeString, header, action ){ + if ( domain === range && typeString === "rdfs:subClassOf" ) { + graph.options().warningModule().showWarning(header, + "rdfs:subClassOf can not be created as loops (domain == range)", + action, 1, false); + return false; + } + if ( domain === range && typeString === "owl:disjointWith" ) { + graph.options().warningModule().showWarning(header, + "owl:disjointWith can not be created as loops (domain == range)", + action, 1, false); + return false; + } + // allProps[i].type()==="owl:allValuesFrom" || + // allProps[i].type()==="owl:someValuesFrom" + if ( domain.type() === "owl:Thing" && typeString === "owl:allValuesFrom" ) { + graph.options().warningModule().showWarning(header, + "owl:allValuesFrom can not originate from owl:Thing", + action, 1, false); + return false; + } + if ( domain.type() === "owl:Thing" && typeString === "owl:someValuesFrom" ) { + graph.options().warningModule().showWarning(header, + "owl:someValuesFrom can not originate from owl:Thing", + action, 1, false); + return false; + } + + if ( range.type() === "owl:Thing" && typeString === "owl:allValuesFrom" ) { + graph.options().warningModule().showWarning(header, + "owl:allValuesFrom can not be connected to owl:Thing", + action, 1, false); + return false; + } + if ( range.type() === "owl:Thing" && typeString === "owl:someValuesFrom" ) { + graph.options().warningModule().showWarning(header, + "owl:someValuesFrom can not be connected to owl:Thing", + action, 1, false); + return false; + } + + return true; // we can Change the domain or range + }; + + graph.checkIfIriClassAlreadyExist = function ( url ){ + // search for a class node with this url + var allNodes = unfilteredData.nodes; + for ( var i = 0; i < allNodes.length; i++ ) { + if ( elementTools.isDatatype(allNodes[i]) === true || allNodes[i].type() === "owl:Thing" ) + continue; + + // now we are a real class; + //get class IRI + var classIRI = allNodes[i].iri(); + + // this gives me the node for halo + if ( url === classIRI ) { + return allNodes[i]; + } + } + return false; + }; + + graph.classesSanityCheck = function ( classElement, targetType ){ + // this is added due to someValuesFrom properties + // we should not be able to change a classElement to a owl:Thing + // when it has a property attached to it that uses these restrictions + // + + if ( targetType === "owl:Class" ) return true; + + else { + // collect all properties which have that one as a domain or range + var allProps = unfilteredData.properties; + for ( var i = 0; i < allProps.length; i++ ) { + if ( allProps[i].range() === classElement || allProps[i].domain() === classElement ) { + // check for the type of that property + if ( allProps[i].type() === "owl:someValuesFrom" ) { + graph.options().warningModule().showWarning("Can not change class type", + "The element has a property that is of type owl:someValuesFrom", + "Element type not changed!", 1, true); + return false; + } + if ( allProps[i].type() === "owl:allValuesFrom" ) { + graph.options().warningModule().showWarning("Can not change class type", + "The element has a property that is of type owl:allValuesFrom", + "Element type not changed!", 1, true); + return false; + } + } + } + + + } + return true; + }; + + graph.propertyCheckExistenceChecker = function ( property, domain, range ){ + var allProps = unfilteredData.properties; + var i; + if ( property.type() === "rdfs:subClassOf" || property.type() === "owl:disjointWith" ) { + + for ( i = 0; i < allProps.length; i++ ) { + if ( allProps[i] === property ) continue; + if ( allProps[i].domain() === domain && allProps[i].range() === range && allProps[i].type() === property.type() ) { + graph.options().warningModule().showWarning("Warning", + "This triple already exist!", + "Element not created!", 1, false); + return false; + } + if ( allProps[i].domain() === range && allProps[i].range() === domain && allProps[i].type() === property.type() ) { + graph.options().warningModule().showWarning("Warning", + "Inverse assignment already exist! ", + "Element not created!", 1, false); + return false; + } + } + return true; + } + return true; + }; + + // graph.checkForTripleDuplicate=function(property){ + // var domain=property.domain(); + // var range=property.range(); + // console.log("checking for duplicates"); + // var b1= domain.isPropertyAssignedToThisElement(property); + // var b2= range.isPropertyAssignedToThisElement(property); + // + // console.log("test domain results in "+ b1); + // console.log("test range results in "+ b1); + // + // if (b1 && b2 ){ + // graph.options().warningModule().showWarning("Warning", + // "This triple already exist!", + // "Element not created!",1,false); + // return false; + // } + // return true; + // }; + + graph.sanityCheckProperty = function ( domain, range, typeString ){ + + // check for duplicate triple in the element; + + + if ( typeString === "owl:objectProperty" && graph.options().objectPropertyFilter().enabled() === true ) { + graph.options().warningModule().showWarning("Warning", + "Object properties are filtered out in the visualization!", + "Element not created!", 1, false); + return false; + } + + if ( typeString === "owl:disjointWith" && graph.options().disjointPropertyFilter().enabled() === true ) { + graph.options().warningModule().showWarning("Warning", + "owl:disjointWith properties are filtered out in the visualization!", + "Element not created!", 1, false); + return false; + } + + + if ( domain === range && typeString === "rdfs:subClassOf" ) { + graph.options().warningModule().showWarning("Warning", + "rdfs:subClassOf can not be created as loops (domain == range)", + "Element not created!", 1, false); + return false; + } + if ( domain === range && typeString === "owl:disjointWith" ) { + graph.options().warningModule().showWarning("Warning", + "owl:disjointWith can not be created as loops (domain == range)", + "Element not created!", 1, false); + return false; + } + + if ( domain.type() === "owl:Thing" && typeString === "owl:someValuesFrom" ) { + graph.options().warningModule().showWarning("Warning", + "owl:someValuesFrom can not originate from owl:Thing", + "Element not created!", 1, false); + return false; + } + if ( domain.type() === "owl:Thing" && typeString === "owl:allValuesFrom" ) { + graph.options().warningModule().showWarning("Warning", + "owl:allValuesFrom can not originate from owl:Thing", + "Element not created!", 1, false); + return false; + } + + if ( range.type() === "owl:Thing" && typeString === "owl:allValuesFrom" ) { + graph.options().warningModule().showWarning("Warning", + "owl:allValuesFrom can not be connected to owl:Thing", + "Element not created!", 1, false); + return false; + } + if ( range.type() === "owl:Thing" && typeString === "owl:someValuesFrom" ) { + graph.options().warningModule().showWarning("Warning", + "owl:someValuesFrom can not be connected to owl:Thing", + "Element not created!", 1, false); + return false; + } + return true; // we can create a property + }; + + function createNewObjectProperty( domain, range, draggerEndposition ){ + // check type of the property that we want to create; + + var defaultPropertyName = d3.select("#defaultProperty").node().title; + + // check if we are allow to create that property + if ( graph.sanityCheckProperty(domain, range, defaultPropertyName) === false ) return false; + + + var propPrototype = PropertyPrototypeMap.get(defaultPropertyName.toLowerCase()); + var aProp = new propPrototype(graph); + aProp.id("objectProperty" + eP++); + aProp.domain(domain); + aProp.range(range); + aProp.label("newObjectProperty"); + aProp.baseIri(d3.select("#iriEditor").node().value); + aProp.iri(aProp.baseIri() + aProp.id()); + + // check for duplicate; + if ( graph.propertyCheckExistenceChecker(aProp, domain, range) === false ) { + // delete aProp; + // hope for garbage collection here -.- + return false; + } + + var autoEditElement = false; + + if ( defaultPropertyName === "owl:objectProperty" ) { + autoEditElement = true; + } + var pX = 0.49 * (domain.x + range.x); + var pY = 0.49 * (domain.y + range.y); + + if ( domain === range ) { + // we use the dragger endposition to determine an angle to put the loop there; + var dirD_x = draggerEndposition[0] - domain.x; + var dirD_y = draggerEndposition[1] - domain.y; + + // normalize; + var len = Math.sqrt(dirD_x * dirD_x + dirD_y * dirD_y); + // it should be very hard to set the position on the same sport but why not handling this + var nx = dirD_x / len; + var ny = dirD_y / len; + // is Nan in javascript like in c len==len returns false when it is not a number? + if ( isNaN(len) ) { + nx = 0; + ny = -1; + } + + // get domain actual raidus + var offset = 2 * domain.actualRadius() + 50; + pX = domain.x + offset * nx; + pY = domain.y + offset * ny; + } + + // add this property to domain and range; + domain.addProperty(aProp); + range.addProperty(aProp); + + + // add this to the data; + unfilteredData.properties.push(aProp); + if ( properties.indexOf(aProp) === -1 ) + properties.push(aProp); + graph.fastUpdate(); + aProp.labelObject().x = pX; + aProp.labelObject().px = pX; + aProp.labelObject().y = pY; + aProp.labelObject().py = pY; + + aProp.frozen(graph.paused()); + aProp.locked(graph.paused()); + domain.frozen(graph.paused()); + domain.locked(graph.paused()); + range.frozen(graph.paused()); + range.locked(graph.paused()); + + + generateDictionary(unfilteredData); + graph.getUpdateDictionary(); + + options.focuserModule().handle(aProp); + graph.activateHoverElementsForProperties(true, aProp, false, touchDevice); + aProp.labelObject().increasedLoopAngle = true; + aProp.enableEditing(autoEditElement); + } + + graph.createDataTypeProperty = function ( node ){ + // random postion issues; + clearTimeout(nodeFreezer); + // tells user when element is filtered out + if ( graph.options().datatypeFilter().enabled() === true ) { + graph.options().warningModule().showWarning("Warning", + "Datatype properties are filtered out in the visualization!", + "Element not created!", 1, false); + return; + } + + + var aNode, prototype; + + // create a default datatype Node >> HERE LITERAL; + var defaultDatatypeName = d3.select("#defaultDatatype").node().title; + if ( defaultDatatypeName === "rdfs:Literal" ) { + prototype = NodePrototypeMap.get("rdfs:literal"); + aNode = new prototype(graph); + aNode.label("Literal"); + aNode.iri("http://www.w3.org/2000/01/rdf-schema#Literal"); + aNode.baseIri("http://www.w3.org/2000/01/rdf-schema#"); + } else { + prototype = NodePrototypeMap.get("rdfs:datatype"); + aNode = new prototype(graph); + var identifier = ""; + if ( defaultDatatypeName === "undefined" ) { + identifier = "undefined"; + + aNode.label(identifier); + // TODO : HANDLER FOR UNDEFINED DATATYPES!!<<<>>>>>>>>>>>.. + aNode.iri("http://www.undefinedDatatype.org/#" + identifier); + aNode.baseIri("http://www.undefinedDatatype.org/#"); + aNode.dType(defaultDatatypeName); + } else { + identifier = defaultDatatypeName.split(":")[1]; + aNode.label(identifier); + aNode.dType(defaultDatatypeName); + aNode.iri("http://www.w3.org/2001/XMLSchema#" + identifier); + aNode.baseIri("http://www.w3.org/2001/XMLSchema#"); + } + } + + + var nX = node.x - node.actualRadius() - 100; + var nY = node.y + node.actualRadius() + 100; + + aNode.x = nX; + aNode.y = nY; + aNode.px = aNode.x; + aNode.py = aNode.y; + aNode.id("NodeId" + eN++); + // add this property to the nodes; + unfilteredData.nodes.push(aNode); + if ( classNodes.indexOf(aNode) === -1 ) + classNodes.push(aNode); + + + // add also the datatype Property to it + var propPrototype = PropertyPrototypeMap.get("owl:datatypeproperty"); + var aProp = new propPrototype(graph); + aProp.id("datatypeProperty" + eP++); + + // create the connection + aProp.domain(node); + aProp.range(aNode); + aProp.label("newDatatypeProperty"); + + + // TODO: change its base IRI to proper value + var ontoIri = d3.select("#iriEditor").node().value; + aProp.baseIri(ontoIri); + aProp.iri(ontoIri + aProp.id()); + // add this to the data; + unfilteredData.properties.push(aProp); + if ( properties.indexOf(aProp) === -1 ) + properties.push(aProp); + graph.fastUpdate(); + generateDictionary(unfilteredData); + graph.getUpdateDictionary(); + + nodeFreezer = setTimeout(function (){ + if ( node && node.frozen() === true && node.pinned() === false && graph.paused() === false ) { + node.frozen(graph.paused()); + node.locked(graph.paused()); + } + }, 1000); + options.focuserModule().handle(undefined); + if ( node ) { + node.frozen(true); + node.locked(true); + } + }; + + graph.removeNodesViaResponse = function ( nodesToRemove, propsToRemove ){ + var i, remId; + // splice them; + for ( i = 0; i < propsToRemove.length; i++ ) { + remId = unfilteredData.properties.indexOf(propsToRemove[i]); + if ( remId !== -1 ) + unfilteredData.properties.splice(remId, 1); + remId = properties.indexOf(propsToRemove[i]); + if ( remId !== -1 ) + properties.splice(remId, 1); + propsToRemove[i] = null; + } + for ( i = 0; i < nodesToRemove.length; i++ ) { + remId = unfilteredData.nodes.indexOf(nodesToRemove[i]); + if ( remId !== -1 ) { + unfilteredData.nodes.splice(remId, 1); + } + remId = classNodes.indexOf(nodesToRemove[i]); + if ( remId !== -1 ) + classNodes.splice(remId, 1); + nodesToRemove[i] = null; + } + graph.fastUpdate(); + generateDictionary(unfilteredData); + graph.getUpdateDictionary(); + options.focuserModule().handle(undefined); + nodesToRemove = null; + propsToRemove = null; + + }; + + graph.removeNodeViaEditor = function ( node ){ + var propsToRemove = []; + var nodesToRemove = []; + var datatypes = 0; + + var remId; + + nodesToRemove.push(node); + for ( var i = 0; i < unfilteredData.properties.length; i++ ) { + if ( unfilteredData.properties[i].domain() === node || unfilteredData.properties[i].range() === node ) { + propsToRemove.push(unfilteredData.properties[i]); + if ( unfilteredData.properties[i].type().toLocaleLowerCase() === "owl:datatypeproperty" && + unfilteredData.properties[i].range() !== node ) { + nodesToRemove.push(unfilteredData.properties[i].range()); + datatypes++; + } + } + } + var removedItems = propsToRemove.length + nodesToRemove.length; + if ( removedItems > 2 ) { + var text = "You are about to delete 1 class and " + propsToRemove.length + " properties"; + if ( datatypes !== 0 ) { + text = "You are about to delete 1 class, " + datatypes + " datatypes and " + propsToRemove.length + " properties"; + } + + + graph.options().warningModule().responseWarning( + "Removing elements", + text, + "Awaiting response!", graph.removeNodesViaResponse, [nodesToRemove, propsToRemove], false); + + + // + // if (confirm("Remove :\n"+propsToRemove.length + " properties\n"+nodesToRemove.length+" classes? ")===false){ + // return; + // }else{ + // // todo : store for undo delete button ; + // } + } else { + // splice them; + for ( i = 0; i < propsToRemove.length; i++ ) { + remId = unfilteredData.properties.indexOf(propsToRemove[i]); + if ( remId !== -1 ) + unfilteredData.properties.splice(remId, 1); + remId = properties.indexOf(propsToRemove[i]); + if ( remId !== -1 ) + properties.splice(remId, 1); + propsToRemove[i] = null; + } + for ( i = 0; i < nodesToRemove.length; i++ ) { + remId = unfilteredData.nodes.indexOf(nodesToRemove[i]); + if ( remId !== -1 ) + unfilteredData.nodes.splice(remId, 1); + remId = classNodes.indexOf(nodesToRemove[i]); + if ( remId !== -1 ) + classNodes.splice(remId, 1); + nodesToRemove[i] = null; + } + graph.fastUpdate(); + generateDictionary(unfilteredData); + graph.getUpdateDictionary(); + options.focuserModule().handle(undefined); + nodesToRemove = null; + propsToRemove = null; + } + }; + + graph.removePropertyViaEditor = function ( property ){ + property.domain().removePropertyElement(property); + property.range().removePropertyElement(property); + var remId; + + if ( property.type().toLocaleLowerCase() === "owl:datatypeproperty" ) { + var datatype = property.range(); + remId = unfilteredData.nodes.indexOf(property.range()); + if ( remId !== -1 ) + unfilteredData.nodes.splice(remId, 1); + remId = classNodes.indexOf(property.range()); + if ( remId !== -1 ) + classNodes.splice(remId, 1); + datatype = null; + } + remId = unfilteredData.properties.indexOf(property); + if ( remId !== -1 ) + unfilteredData.properties.splice(remId, 1); + remId = properties.indexOf(property); + if ( remId !== -1 ) + properties.splice(remId, 1); + if ( property.inverse() ) { + // so we have inverse + property.inverse().inverse(0); + + } + + + hoveredPropertyElement = undefined; + graph.fastUpdate(); + generateDictionary(unfilteredData); + graph.getUpdateDictionary(); + options.focuserModule().handle(undefined); + property = null; + }; + + graph.executeColorExternalsModule = function (){ + options.colorExternalsModule().filter(unfilteredData.nodes, unfilteredData.properties); + }; + + graph.executeCompactNotationModule = function (){ + if ( unfilteredData ) { + options.compactNotationModule().filter(unfilteredData.nodes, unfilteredData.properties); + } + + }; + graph.executeEmptyLiteralFilter = function (){ + + if ( unfilteredData && unfilteredData.nodes.length > 1 ) { + options.literalFilter().filter(unfilteredData.nodes, unfilteredData.properties); + unfilteredData.nodes = options.literalFilter().filteredNodes(); + unfilteredData.properties = options.literalFilter().filteredProperties(); + } + + }; + + + /** --------------------------------------------------------- **/ + /** -- animation functions for the nodes -- **/ + /** --------------------------------------------------------- **/ + + graph.animateDynamicLabelWidth = function (){ + var wantedWidth = options.dynamicLabelWidth(); + var i; + for ( i = 0; i < classNodes.length; i++ ) { + var nodeElement = classNodes[i]; + if ( elementTools.isDatatype(nodeElement) ) { + nodeElement.animateDynamicLabelWidth(wantedWidth); + } + } + for ( i = 0; i < properties.length; i++ ) { + properties[i].animateDynamicLabelWidth(wantedWidth); + } + }; + + + /** --------------------------------------------------------- **/ + /** -- Touch behaviour functions -- **/ + /** --------------------------------------------------------- **/ + + graph.setTouchDevice = function ( val ){ + touchDevice = val; + }; + + graph.isTouchDevice = function (){ + return touchDevice; + }; + + graph.modified_dblClickFunction = function (){ + + d3.event.stopPropagation(); + d3.event.preventDefault(); + // get position where we want to add the node; + var grPos = getClickedScreenCoords(d3.event.clientX, d3.event.clientY, graph.translation(), graph.scaleFactor()); + createNewNodeAtPosition(grPos); + }; + + function doubletap(){ + var touch_time = d3.event.timeStamp; + var numTouchers = 1; + if ( d3.event && d3.event.touches && d3.event.touches.length ) + numTouchers = d3.event.touches.length; + + if ( touch_time - last_touch_time < 300 && numTouchers === 1 ) { + d3.event.stopPropagation(); + if ( editMode === true ) { + //graph.modified_dblClickFunction(); + d3.event.preventDefault(); + d3.event.stopPropagation(); + last_touch_time = touch_time; + return true; + } + } + last_touch_time = touch_time; + return false; + } + + + function touchzoomed(){ + forceNotZooming = true; + + + var touch_time = d3.event.timeStamp; + if ( touch_time - last_touch_time < 300 && d3.event.touches.length === 1 ) { + d3.event.stopPropagation(); + + if ( editMode === true ) { + //graph.modified_dblClickFunction(); + d3.event.preventDefault(); + d3.event.stopPropagation(); + zoom.translate(graphTranslation); + zoom.scale(zoomFactor); + graph.modified_dblTouchFunction(); + } + else { + forceNotZooming = false; + if ( originalD3_touchZoomFunction ) + originalD3_touchZoomFunction(); + } + return; + } + forceNotZooming = false; + last_touch_time = touch_time; + // TODO: WORK AROUND TO CHECK FOR ORIGINAL FUNCTION + if ( originalD3_touchZoomFunction ) + originalD3_touchZoomFunction(); + } + + graph.modified_dblTouchFunction = function ( d ){ + d3.event.stopPropagation(); + d3.event.preventDefault(); + var xy; + if ( editMode === true ) { + xy = d3.touches(d3.selectAll(".vowlGraph").node()); + } + var grPos = getClickedScreenCoords(xy[0][0], xy[0][1], graph.translation(), graph.scaleFactor()); + createNewNodeAtPosition(grPos); + }; + + /** --------------------------------------------------------- **/ + /** -- Hover and Selection functions, adding edit elements -- **/ + /** --------------------------------------------------------- **/ + + graph.ignoreOtherHoverEvents = function ( val ){ + if ( !arguments.length ) { + return ignoreOtherHoverEvents; + } + else ignoreOtherHoverEvents = val; + }; + + function delayedHiddingHoverElements( tbh ){ + if ( tbh === true ) return; + if ( hoveredNodeElement ) { + if ( hoveredNodeElement.editingTextElement === true ) return; + delayedHider = setTimeout(function (){ + deleteGroupElement.classed("hidden", true); + addDataPropertyGroupElement.classed("hidden", true); + classDragger.hideDragger(true); + if ( hoveredNodeElement && hoveredNodeElement.pinned() === false && graph.paused() === false && hoveredNodeElement.editingTextElement === false ) { + hoveredNodeElement.frozen(false); + hoveredNodeElement.locked(false); + } + }, 1000); + } + if ( hoveredPropertyElement ) { + if ( hoveredPropertyElement.editingTextElement === true ) return; + delayedHider = setTimeout(function (){ + deleteGroupElement.classed("hidden", true); + addDataPropertyGroupElement.classed("hidden", true); + classDragger.hideDragger(true); + rangeDragger.hideDragger(true); + domainDragger.hideDragger(true); + shadowClone.hideClone(true); + if ( hoveredPropertyElement && hoveredPropertyElement.focused() === true && graph.options().drawPropertyDraggerOnHover() === true ) { + hoveredPropertyElement.labelObject().increasedLoopAngle = false; + // lazy update + recalculatePositions(); + } + + if ( hoveredPropertyElement && hoveredPropertyElement.pinned() === false && graph.paused() === false && hoveredPropertyElement.editingTextElement === false ) { + hoveredPropertyElement.frozen(false); + hoveredPropertyElement.locked(false); + } + }, 1000); + } + + } + + + // TODO : experimental code for updating dynamic label with and its hover element + graph.hideHoverPropertyElementsForAnimation = function (){ + deleteGroupElement.classed("hidden", true); + }; + graph.showHoverElementsAfterAnimation = function ( property, inversed ){ + setDeleteHoverElementPositionProperty(property, inversed); + deleteGroupElement.classed("hidden", false); + + }; + + function editElementHoverOnHidden(){ + classDragger.nodeElement.classed("classDraggerNodeHovered", true); + classDragger.nodeElement.classed("classDraggerNode", false); + editElementHoverOn(); + } + + function editElementHoverOutHidden(){ + classDragger.nodeElement.classed("classDraggerNodeHovered", false); + classDragger.nodeElement.classed("classDraggerNode", true); + editElementHoverOut(); + } + + function editElementHoverOn( touch ){ + if ( touch === true ) return; + clearTimeout(delayedHider); // ignore touch behaviour + + } + + graph.killDelayedTimer = function (){ + clearTimeout(delayedHider); + clearTimeout(nodeFreezer); + }; + + + function editElementHoverOut( tbh ){ + if ( hoveredNodeElement ) { + if ( graph.ignoreOtherHoverEvents() === true || tbh === true || hoveredNodeElement.editingTextElement === true ) return; + delayedHider = setTimeout(function (){ + if ( graph.isADraggerActive() === true ) return; + deleteGroupElement.classed("hidden", true); + addDataPropertyGroupElement.classed("hidden", true); + classDragger.hideDragger(true); + if ( hoveredNodeElement && hoveredNodeElement.pinned() === false && graph.paused() === false ) { + hoveredNodeElement.frozen(false); + hoveredNodeElement.locked(false); + } + + }, 1000); + } + if ( hoveredPropertyElement ) { + if ( graph.ignoreOtherHoverEvents() === true || tbh === true || hoveredPropertyElement.editingTextElement === true ) return; + delayedHider = setTimeout(function (){ + if ( graph.isADraggerActive() === true ) return; + deleteGroupElement.classed("hidden", true); + addDataPropertyGroupElement.classed("hidden", true); + classDragger.hideDragger(true); + if ( hoveredPropertyElement && hoveredPropertyElement.pinned() === false && graph.paused() === false ) { + hoveredPropertyElement.frozen(false); + hoveredPropertyElement.locked(false); + } + + }, 1000); + } + } + + graph.activateHoverElementsForProperties = function ( val, property, inversed, touchBehaviour ){ + if ( editMode === false ) return; // nothing to do; + + if ( touchBehaviour === undefined ) + touchBehaviour = false; + + if ( val === true ) { + clearTimeout(delayedHider); + if ( hoveredPropertyElement ) { + if ( hoveredPropertyElement.domain() === hoveredPropertyElement.range() ) { + hoveredPropertyElement.labelObject().increasedLoopAngle = false; + recalculatePositions(); + } + } + + hoveredPropertyElement = property; + if ( graph.options().drawPropertyDraggerOnHover() === true ) { + + + if ( property.type() !== "owl:DatatypeProperty" ) { + if ( property.domain() === property.range() ) { + property.labelObject().increasedLoopAngle = true; + recalculatePositions(); + } + shadowClone.setParentProperty(property, inversed); + rangeDragger.setParentProperty(property, inversed); + rangeDragger.hideDragger(false); + rangeDragger.addMouseEvents(); + domainDragger.setParentProperty(property, inversed); + domainDragger.hideDragger(false); + domainDragger.addMouseEvents(); + + + } else if ( property.type() === "owl:DatatypeProperty" ) { + shadowClone.setParentProperty(property, inversed); + rangeDragger.setParentProperty(property, inversed); + rangeDragger.hideDragger(true); + rangeDragger.addMouseEvents(); + domainDragger.setParentProperty(property, inversed); + domainDragger.hideDragger(false); + domainDragger.addMouseEvents(); + } + } + else { // hide when we dont want that option + if ( graph.options().drawPropertyDraggerOnHover() === true ) { + rangeDragger.hideDragger(true); + domainDragger.hideDragger(true); + shadowClone.hideClone(true); + if ( property.domain() === property.range() ) { + property.labelObject().increasedLoopAngle = false; + recalculatePositions(); + } + } + } + + if ( hoveredNodeElement ) { + if ( hoveredNodeElement && hoveredNodeElement.pinned() === false && graph.paused() === false ) { + hoveredNodeElement.frozen(false); + hoveredNodeElement.locked(false); + } + } + hoveredNodeElement = undefined; + deleteGroupElement.classed("hidden", false); + setDeleteHoverElementPositionProperty(property, inversed); + deleteGroupElement.selectAll("*").on("click", function (){ + if ( touchBehaviour && property.focused() === false ) { + graph.options().focuserModule().handle(property); + return; + } + graph.removePropertyViaEditor(property); + d3.event.stopPropagation(); + }); + classDragger.hideDragger(true); + addDataPropertyGroupElement.classed("hidden", true); + } else { + delayedHiddingHoverElements(); + } + }; + + graph.updateDraggerElements = function (){ + + // set opacity style for all elements + + rangeDragger.draggerObject.classed("superOpacityElement", !graph.options().showDraggerObject()); + domainDragger.draggerObject.classed("superOpacityElement", !graph.options().showDraggerObject()); + classDragger.draggerObject.classed("superOpacityElement", !graph.options().showDraggerObject()); + + nodeContainer.selectAll(".superHiddenElement").classed("superOpacityElement", !graph.options().showDraggerObject()); + labelContainer.selectAll(".superHiddenElement").classed("superOpacityElement", !graph.options().showDraggerObject()); + + deleteGroupElement.selectAll(".superHiddenElement").classed("superOpacityElement", !graph.options().showDraggerObject()); + addDataPropertyGroupElement.selectAll(".superHiddenElement").classed("superOpacityElement", !graph.options().showDraggerObject()); + + + }; + + function setAddDataPropertyHoverElementPosition( node ){ + var delX, delY = 0; + if ( node.renderType() === "round" ) { + var scale = 0.5 * Math.sqrt(2.0); + var oX = scale * node.actualRadius(); + var oY = scale * node.actualRadius(); + delX = node.x - oX; + delY = node.y + oY; + addDataPropertyGroupElement.attr("transform", "translate(" + delX + "," + delY + ")"); + } + } + + function setDeleteHoverElementPosition( node ){ + var delX, delY = 0; + if ( node.renderType() === "round" ) { + var scale = 0.5 * Math.sqrt(2.0); + var oX = scale * node.actualRadius(); + var oY = scale * node.actualRadius(); + delX = node.x + oX; + delY = node.y - oY; + } else { + delX = node.x + 0.5 * node.width() + 6; + delY = node.y - 0.5 * node.height() - 6; + } + deleteGroupElement.attr("transform", "translate(" + delX + "," + delY + ")"); + } + + function setDeleteHoverElementPositionProperty( property, inversed ){ + if ( property && property.labelElement() ) { + var pos = [property.labelObject().x, property.labelObject().y]; + var widthElement = parseFloat(property.getShapeElement().attr("width")); + var heightElement = parseFloat(property.getShapeElement().attr("height")); + var delX = pos[0] + 0.5 * widthElement + 6; + var delY = pos[1] - 0.5 * heightElement - 6; + // this is the lower element + if ( property.labelElement().attr("transform") === "translate(0,15)" ) + delY += 15; + // this is upper element + if ( property.labelElement().attr("transform") === "translate(0,-15)" ) + delY -= 15; + deleteGroupElement.attr("transform", "translate(" + delX + "," + delY + ")"); + } else { + deleteGroupElement.classed("hidden", true);// hide when there is no property + } + + + } + + graph.activateHoverElements = function ( val, node, touchBehaviour ){ + if ( editMode === false ) { + return; // nothing to do; + } + if ( touchBehaviour === undefined ) touchBehaviour = false; + if ( val === true ) { + if ( graph.options().drawPropertyDraggerOnHover() === true ) { + rangeDragger.hideDragger(true); + domainDragger.hideDragger(true); + shadowClone.hideClone(true); + } + // make them visible + clearTimeout(delayedHider); + clearTimeout(nodeFreezer); + if ( hoveredNodeElement && node.pinned() === false && graph.paused() === false ) { + hoveredNodeElement.frozen(false); + hoveredNodeElement.locked(false); + } + hoveredNodeElement = node; + if ( node && node.frozen() === false && node.pinned() === false ) { + node.frozen(true); + node.locked(false); + } + if ( hoveredPropertyElement && hoveredPropertyElement.focused() === false ) { + hoveredPropertyElement.labelObject().increasedLoopAngle = false; + recalculatePositions(); + // update the loopAngles; + + } + hoveredPropertyElement = undefined; + deleteGroupElement.classed("hidden", false); + setDeleteHoverElementPosition(node); + + + deleteGroupElement.selectAll("*").on("click", function (){ + if ( touchBehaviour && node.focused() === false ) { + graph.options().focuserModule().handle(node); + return; + } + graph.removeNodeViaEditor(node); + d3.event.stopPropagation(); + }) + .on("mouseover", function (){ + editElementHoverOn(node, touchBehaviour); + }) + .on("mouseout", function (){ + editElementHoverOut(node, touchBehaviour); + }); + + addDataPropertyGroupElement.classed("hidden", true); + classDragger.nodeElement.on("mouseover", editElementHoverOn) + .on("mouseout", editElementHoverOut); + classDragger.draggerObject.on("mouseover", editElementHoverOnHidden) + .on("mouseout", editElementHoverOutHidden); + + // add the dragger element; + if ( node.renderType() === "round" ) { + classDragger.svgRoot(draggerLayer); + classDragger.setParentNode(node); + classDragger.hideDragger(false); + addDataPropertyGroupElement.classed("hidden", false); + setAddDataPropertyHoverElementPosition(node); + addDataPropertyGroupElement.selectAll("*").on("click", function (){ + if ( touchBehaviour && node.focused() === false ) { + graph.options().focuserModule().handle(node); + return; + } + graph.createDataTypeProperty(node); + d3.event.stopPropagation(); + }) + .on("mouseover", function (){ + editElementHoverOn(node, touchBehaviour); + }) + .on("mouseout", function (){ + editElementHoverOut(node, touchBehaviour); + }); + } else { + classDragger.hideDragger(true); + + } + + } else { + delayedHiddingHoverElements(node, touchBehaviour); + + } + }; + + + return graph; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 58 */ +/***/ (function(module, exports, __webpack_require__) { + + var __WEBPACK_AMD_DEFINE_RESULT__;/* WEBPACK VAR INJECTION */(function(global, module) {/** + * @license + * Lodash (Custom Build) + * Build: `lodash core -o ./dist/lodash.core.js` + * Copyright OpenJS Foundation and other contributors + * Released under MIT license + * Based on Underscore.js 1.8.3 + * Copyright Jeremy Ashkenas, DocumentCloud and Investigative Reporters & Editors + */ + ;(function() { + + /** Used as a safe reference for `undefined` in pre-ES5 environments. */ + var undefined; + + /** Used as the semantic version number. */ + var VERSION = '4.17.15'; + + /** Error message constants. */ + var FUNC_ERROR_TEXT = 'Expected a function'; + + /** Used to compose bitmasks for value comparisons. */ + var COMPARE_PARTIAL_FLAG = 1, + COMPARE_UNORDERED_FLAG = 2; + + /** Used to compose bitmasks for function metadata. */ + var WRAP_BIND_FLAG = 1, + WRAP_PARTIAL_FLAG = 32; + + /** Used as references for various `Number` constants. */ + var INFINITY = 1 / 0, + MAX_SAFE_INTEGER = 9007199254740991; + + /** `Object#toString` result references. */ + var argsTag = '[object Arguments]', + arrayTag = '[object Array]', + asyncTag = '[object AsyncFunction]', + boolTag = '[object Boolean]', + dateTag = '[object Date]', + errorTag = '[object Error]', + funcTag = '[object Function]', + genTag = '[object GeneratorFunction]', + numberTag = '[object Number]', + objectTag = '[object Object]', + proxyTag = '[object Proxy]', + regexpTag = '[object RegExp]', + stringTag = '[object String]'; + + /** Used to match HTML entities and HTML characters. */ + var reUnescapedHtml = /[&<>"']/g, + reHasUnescapedHtml = RegExp(reUnescapedHtml.source); + + /** Used to detect unsigned integer values. */ + var reIsUint = /^(?:0|[1-9]\d*)$/; + + /** Used to map characters to HTML entities. */ + var htmlEscapes = { + '&': '&', + '<': '<', + '>': '>', + '"': '"', + "'": ''' + }; + + /** Detect free variable `global` from Node.js. */ + var freeGlobal = typeof global == 'object' && global && global.Object === Object && global; + + /** Detect free variable `self`. */ + var freeSelf = typeof self == 'object' && self && self.Object === Object && self; + + /** Used as a reference to the global object. */ + var root = freeGlobal || freeSelf || Function('return this')(); + + /** Detect free variable `exports`. */ + var freeExports = typeof exports == 'object' && exports && !exports.nodeType && exports; + + /** Detect free variable `module`. */ + var freeModule = freeExports && typeof module == 'object' && module && !module.nodeType && module; + + /*--------------------------------------------------------------------------*/ + + /** + * Appends the elements of `values` to `array`. + * + * @private + * @param {Array} array The array to modify. + * @param {Array} values The values to append. + * @returns {Array} Returns `array`. + */ + function arrayPush(array, values) { + array.push.apply(array, values); + return array; + } + + /** + * The base implementation of `_.findIndex` and `_.findLastIndex` without + * support for iteratee shorthands. + * + * @private + * @param {Array} array The array to inspect. + * @param {Function} predicate The function invoked per iteration. + * @param {number} fromIndex The index to search from. + * @param {boolean} [fromRight] Specify iterating from right to left. + * @returns {number} Returns the index of the matched value, else `-1`. + */ + function baseFindIndex(array, predicate, fromIndex, fromRight) { + var length = array.length, + index = fromIndex + (fromRight ? 1 : -1); + + while ((fromRight ? index-- : ++index < length)) { + if (predicate(array[index], index, array)) { + return index; + } + } + return -1; + } + + /** + * The base implementation of `_.property` without support for deep paths. + * + * @private + * @param {string} key The key of the property to get. + * @returns {Function} Returns the new accessor function. + */ + function baseProperty(key) { + return function(object) { + return object == null ? undefined : object[key]; + }; + } + + /** + * The base implementation of `_.propertyOf` without support for deep paths. + * + * @private + * @param {Object} object The object to query. + * @returns {Function} Returns the new accessor function. + */ + function basePropertyOf(object) { + return function(key) { + return object == null ? undefined : object[key]; + }; + } + + /** + * The base implementation of `_.reduce` and `_.reduceRight`, without support + * for iteratee shorthands, which iterates over `collection` using `eachFunc`. + * + * @private + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} iteratee The function invoked per iteration. + * @param {*} accumulator The initial value. + * @param {boolean} initAccum Specify using the first or last element of + * `collection` as the initial value. + * @param {Function} eachFunc The function to iterate over `collection`. + * @returns {*} Returns the accumulated value. + */ + function baseReduce(collection, iteratee, accumulator, initAccum, eachFunc) { + eachFunc(collection, function(value, index, collection) { + accumulator = initAccum + ? (initAccum = false, value) + : iteratee(accumulator, value, index, collection); + }); + return accumulator; + } + + /** + * The base implementation of `_.values` and `_.valuesIn` which creates an + * array of `object` property values corresponding to the property names + * of `props`. + * + * @private + * @param {Object} object The object to query. + * @param {Array} props The property names to get values for. + * @returns {Object} Returns the array of property values. + */ + function baseValues(object, props) { + return baseMap(props, function(key) { + return object[key]; + }); + } + + /** + * Used by `_.escape` to convert characters to HTML entities. + * + * @private + * @param {string} chr The matched character to escape. + * @returns {string} Returns the escaped character. + */ + var escapeHtmlChar = basePropertyOf(htmlEscapes); + + /** + * Creates a unary function that invokes `func` with its argument transformed. + * + * @private + * @param {Function} func The function to wrap. + * @param {Function} transform The argument transform. + * @returns {Function} Returns the new function. + */ + function overArg(func, transform) { + return function(arg) { + return func(transform(arg)); + }; + } + + /*--------------------------------------------------------------------------*/ + + /** Used for built-in method references. */ + var arrayProto = Array.prototype, + objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** Used to generate unique IDs. */ + var idCounter = 0; + + /** + * Used to resolve the + * [`toStringTag`](http://ecma-international.org/ecma-262/7.0/#sec-object.prototype.tostring) + * of values. + */ + var nativeObjectToString = objectProto.toString; + + /** Used to restore the original `_` reference in `_.noConflict`. */ + var oldDash = root._; + + /** Built-in value references. */ + var objectCreate = Object.create, + propertyIsEnumerable = objectProto.propertyIsEnumerable; + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeIsFinite = root.isFinite, + nativeKeys = overArg(Object.keys, Object), + nativeMax = Math.max; + + /*------------------------------------------------------------------------*/ + + /** + * Creates a `lodash` object which wraps `value` to enable implicit method + * chain sequences. Methods that operate on and return arrays, collections, + * and functions can be chained together. Methods that retrieve a single value + * or may return a primitive value will automatically end the chain sequence + * and return the unwrapped value. Otherwise, the value must be unwrapped + * with `_#value`. + * + * Explicit chain sequences, which must be unwrapped with `_#value`, may be + * enabled using `_.chain`. + * + * The execution of chained methods is lazy, that is, it's deferred until + * `_#value` is implicitly or explicitly called. + * + * Lazy evaluation allows several methods to support shortcut fusion. + * Shortcut fusion is an optimization to merge iteratee calls; this avoids + * the creation of intermediate arrays and can greatly reduce the number of + * iteratee executions. Sections of a chain sequence qualify for shortcut + * fusion if the section is applied to an array and iteratees accept only + * one argument. The heuristic for whether a section qualifies for shortcut + * fusion is subject to change. + * + * Chaining is supported in custom builds as long as the `_#value` method is + * directly or indirectly included in the build. + * + * In addition to lodash methods, wrappers have `Array` and `String` methods. + * + * The wrapper `Array` methods are: + * `concat`, `join`, `pop`, `push`, `shift`, `sort`, `splice`, and `unshift` + * + * The wrapper `String` methods are: + * `replace` and `split` + * + * The wrapper methods that support shortcut fusion are: + * `at`, `compact`, `drop`, `dropRight`, `dropWhile`, `filter`, `find`, + * `findLast`, `head`, `initial`, `last`, `map`, `reject`, `reverse`, `slice`, + * `tail`, `take`, `takeRight`, `takeRightWhile`, `takeWhile`, and `toArray` + * + * The chainable wrapper methods are: + * `after`, `ary`, `assign`, `assignIn`, `assignInWith`, `assignWith`, `at`, + * `before`, `bind`, `bindAll`, `bindKey`, `castArray`, `chain`, `chunk`, + * `commit`, `compact`, `concat`, `conforms`, `constant`, `countBy`, `create`, + * `curry`, `debounce`, `defaults`, `defaultsDeep`, `defer`, `delay`, + * `difference`, `differenceBy`, `differenceWith`, `drop`, `dropRight`, + * `dropRightWhile`, `dropWhile`, `extend`, `extendWith`, `fill`, `filter`, + * `flatMap`, `flatMapDeep`, `flatMapDepth`, `flatten`, `flattenDeep`, + * `flattenDepth`, `flip`, `flow`, `flowRight`, `fromPairs`, `functions`, + * `functionsIn`, `groupBy`, `initial`, `intersection`, `intersectionBy`, + * `intersectionWith`, `invert`, `invertBy`, `invokeMap`, `iteratee`, `keyBy`, + * `keys`, `keysIn`, `map`, `mapKeys`, `mapValues`, `matches`, `matchesProperty`, + * `memoize`, `merge`, `mergeWith`, `method`, `methodOf`, `mixin`, `negate`, + * `nthArg`, `omit`, `omitBy`, `once`, `orderBy`, `over`, `overArgs`, + * `overEvery`, `overSome`, `partial`, `partialRight`, `partition`, `pick`, + * `pickBy`, `plant`, `property`, `propertyOf`, `pull`, `pullAll`, `pullAllBy`, + * `pullAllWith`, `pullAt`, `push`, `range`, `rangeRight`, `rearg`, `reject`, + * `remove`, `rest`, `reverse`, `sampleSize`, `set`, `setWith`, `shuffle`, + * `slice`, `sort`, `sortBy`, `splice`, `spread`, `tail`, `take`, `takeRight`, + * `takeRightWhile`, `takeWhile`, `tap`, `throttle`, `thru`, `toArray`, + * `toPairs`, `toPairsIn`, `toPath`, `toPlainObject`, `transform`, `unary`, + * `union`, `unionBy`, `unionWith`, `uniq`, `uniqBy`, `uniqWith`, `unset`, + * `unshift`, `unzip`, `unzipWith`, `update`, `updateWith`, `values`, + * `valuesIn`, `without`, `wrap`, `xor`, `xorBy`, `xorWith`, `zip`, + * `zipObject`, `zipObjectDeep`, and `zipWith` + * + * The wrapper methods that are **not** chainable by default are: + * `add`, `attempt`, `camelCase`, `capitalize`, `ceil`, `clamp`, `clone`, + * `cloneDeep`, `cloneDeepWith`, `cloneWith`, `conformsTo`, `deburr`, + * `defaultTo`, `divide`, `each`, `eachRight`, `endsWith`, `eq`, `escape`, + * `escapeRegExp`, `every`, `find`, `findIndex`, `findKey`, `findLast`, + * `findLastIndex`, `findLastKey`, `first`, `floor`, `forEach`, `forEachRight`, + * `forIn`, `forInRight`, `forOwn`, `forOwnRight`, `get`, `gt`, `gte`, `has`, + * `hasIn`, `head`, `identity`, `includes`, `indexOf`, `inRange`, `invoke`, + * `isArguments`, `isArray`, `isArrayBuffer`, `isArrayLike`, `isArrayLikeObject`, + * `isBoolean`, `isBuffer`, `isDate`, `isElement`, `isEmpty`, `isEqual`, + * `isEqualWith`, `isError`, `isFinite`, `isFunction`, `isInteger`, `isLength`, + * `isMap`, `isMatch`, `isMatchWith`, `isNaN`, `isNative`, `isNil`, `isNull`, + * `isNumber`, `isObject`, `isObjectLike`, `isPlainObject`, `isRegExp`, + * `isSafeInteger`, `isSet`, `isString`, `isUndefined`, `isTypedArray`, + * `isWeakMap`, `isWeakSet`, `join`, `kebabCase`, `last`, `lastIndexOf`, + * `lowerCase`, `lowerFirst`, `lt`, `lte`, `max`, `maxBy`, `mean`, `meanBy`, + * `min`, `minBy`, `multiply`, `noConflict`, `noop`, `now`, `nth`, `pad`, + * `padEnd`, `padStart`, `parseInt`, `pop`, `random`, `reduce`, `reduceRight`, + * `repeat`, `result`, `round`, `runInContext`, `sample`, `shift`, `size`, + * `snakeCase`, `some`, `sortedIndex`, `sortedIndexBy`, `sortedLastIndex`, + * `sortedLastIndexBy`, `startCase`, `startsWith`, `stubArray`, `stubFalse`, + * `stubObject`, `stubString`, `stubTrue`, `subtract`, `sum`, `sumBy`, + * `template`, `times`, `toFinite`, `toInteger`, `toJSON`, `toLength`, + * `toLower`, `toNumber`, `toSafeInteger`, `toString`, `toUpper`, `trim`, + * `trimEnd`, `trimStart`, `truncate`, `unescape`, `uniqueId`, `upperCase`, + * `upperFirst`, `value`, and `words` + * + * @name _ + * @constructor + * @category Seq + * @param {*} value The value to wrap in a `lodash` instance. + * @returns {Object} Returns the new `lodash` wrapper instance. + * @example + * + * function square(n) { + * return n * n; + * } + * + * var wrapped = _([1, 2, 3]); + * + * // Returns an unwrapped value. + * wrapped.reduce(_.add); + * // => 6 + * + * // Returns a wrapped value. + * var squares = wrapped.map(square); + * + * _.isArray(squares); + * // => false + * + * _.isArray(squares.value()); + * // => true + */ + function lodash(value) { + return value instanceof LodashWrapper + ? value + : new LodashWrapper(value); + } + + /** + * The base implementation of `_.create` without support for assigning + * properties to the created object. + * + * @private + * @param {Object} proto The object to inherit from. + * @returns {Object} Returns the new object. + */ + var baseCreate = (function() { + function object() {} + return function(proto) { + if (!isObject(proto)) { + return {}; + } + if (objectCreate) { + return objectCreate(proto); + } + object.prototype = proto; + var result = new object; + object.prototype = undefined; + return result; + }; + }()); + + /** + * The base constructor for creating `lodash` wrapper objects. + * + * @private + * @param {*} value The value to wrap. + * @param {boolean} [chainAll] Enable explicit method chain sequences. + */ + function LodashWrapper(value, chainAll) { + this.__wrapped__ = value; + this.__actions__ = []; + this.__chain__ = !!chainAll; + } + + LodashWrapper.prototype = baseCreate(lodash.prototype); + LodashWrapper.prototype.constructor = LodashWrapper; + + /*------------------------------------------------------------------------*/ + + /** + * Assigns `value` to `key` of `object` if the existing value is not equivalent + * using [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. + * + * @private + * @param {Object} object The object to modify. + * @param {string} key The key of the property to assign. + * @param {*} value The value to assign. + */ + function assignValue(object, key, value) { + var objValue = object[key]; + if (!(hasOwnProperty.call(object, key) && eq(objValue, value)) || + (value === undefined && !(key in object))) { + baseAssignValue(object, key, value); + } + } + + /** + * The base implementation of `assignValue` and `assignMergeValue` without + * value checks. + * + * @private + * @param {Object} object The object to modify. + * @param {string} key The key of the property to assign. + * @param {*} value The value to assign. + */ + function baseAssignValue(object, key, value) { + object[key] = value; + } + + /** + * The base implementation of `_.delay` and `_.defer` which accepts `args` + * to provide to `func`. + * + * @private + * @param {Function} func The function to delay. + * @param {number} wait The number of milliseconds to delay invocation. + * @param {Array} args The arguments to provide to `func`. + * @returns {number|Object} Returns the timer id or timeout object. + */ + function baseDelay(func, wait, args) { + if (typeof func != 'function') { + throw new TypeError(FUNC_ERROR_TEXT); + } + return setTimeout(function() { func.apply(undefined, args); }, wait); + } + + /** + * The base implementation of `_.forEach` without support for iteratee shorthands. + * + * @private + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} iteratee The function invoked per iteration. + * @returns {Array|Object} Returns `collection`. + */ + var baseEach = createBaseEach(baseForOwn); + + /** + * The base implementation of `_.every` without support for iteratee shorthands. + * + * @private + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} predicate The function invoked per iteration. + * @returns {boolean} Returns `true` if all elements pass the predicate check, + * else `false` + */ + function baseEvery(collection, predicate) { + var result = true; + baseEach(collection, function(value, index, collection) { + result = !!predicate(value, index, collection); + return result; + }); + return result; + } + + /** + * The base implementation of methods like `_.max` and `_.min` which accepts a + * `comparator` to determine the extremum value. + * + * @private + * @param {Array} array The array to iterate over. + * @param {Function} iteratee The iteratee invoked per iteration. + * @param {Function} comparator The comparator used to compare values. + * @returns {*} Returns the extremum value. + */ + function baseExtremum(array, iteratee, comparator) { + var index = -1, + length = array.length; + + while (++index < length) { + var value = array[index], + current = iteratee(value); + + if (current != null && (computed === undefined + ? (current === current && !false) + : comparator(current, computed) + )) { + var computed = current, + result = value; + } + } + return result; + } + + /** + * The base implementation of `_.filter` without support for iteratee shorthands. + * + * @private + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} predicate The function invoked per iteration. + * @returns {Array} Returns the new filtered array. + */ + function baseFilter(collection, predicate) { + var result = []; + baseEach(collection, function(value, index, collection) { + if (predicate(value, index, collection)) { + result.push(value); + } + }); + return result; + } + + /** + * The base implementation of `_.flatten` with support for restricting flattening. + * + * @private + * @param {Array} array The array to flatten. + * @param {number} depth The maximum recursion depth. + * @param {boolean} [predicate=isFlattenable] The function invoked per iteration. + * @param {boolean} [isStrict] Restrict to values that pass `predicate` checks. + * @param {Array} [result=[]] The initial result value. + * @returns {Array} Returns the new flattened array. + */ + function baseFlatten(array, depth, predicate, isStrict, result) { + var index = -1, + length = array.length; + + predicate || (predicate = isFlattenable); + result || (result = []); + + while (++index < length) { + var value = array[index]; + if (depth > 0 && predicate(value)) { + if (depth > 1) { + // Recursively flatten arrays (susceptible to call stack limits). + baseFlatten(value, depth - 1, predicate, isStrict, result); + } else { + arrayPush(result, value); + } + } else if (!isStrict) { + result[result.length] = value; + } + } + return result; + } + + /** + * The base implementation of `baseForOwn` which iterates over `object` + * properties returned by `keysFunc` and invokes `iteratee` for each property. + * Iteratee functions may exit iteration early by explicitly returning `false`. + * + * @private + * @param {Object} object The object to iterate over. + * @param {Function} iteratee The function invoked per iteration. + * @param {Function} keysFunc The function to get the keys of `object`. + * @returns {Object} Returns `object`. + */ + var baseFor = createBaseFor(); + + /** + * The base implementation of `_.forOwn` without support for iteratee shorthands. + * + * @private + * @param {Object} object The object to iterate over. + * @param {Function} iteratee The function invoked per iteration. + * @returns {Object} Returns `object`. + */ + function baseForOwn(object, iteratee) { + return object && baseFor(object, iteratee, keys); + } + + /** + * The base implementation of `_.functions` which creates an array of + * `object` function property names filtered from `props`. + * + * @private + * @param {Object} object The object to inspect. + * @param {Array} props The property names to filter. + * @returns {Array} Returns the function names. + */ + function baseFunctions(object, props) { + return baseFilter(props, function(key) { + return isFunction(object[key]); + }); + } + + /** + * The base implementation of `getTag` without fallbacks for buggy environments. + * + * @private + * @param {*} value The value to query. + * @returns {string} Returns the `toStringTag`. + */ + function baseGetTag(value) { + return objectToString(value); + } + + /** + * The base implementation of `_.gt` which doesn't coerce arguments. + * + * @private + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @returns {boolean} Returns `true` if `value` is greater than `other`, + * else `false`. + */ + function baseGt(value, other) { + return value > other; + } + + /** + * The base implementation of `_.isArguments`. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an `arguments` object, + */ + var baseIsArguments = noop; + + /** + * The base implementation of `_.isDate` without Node.js optimizations. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a date object, else `false`. + */ + function baseIsDate(value) { + return isObjectLike(value) && baseGetTag(value) == dateTag; + } + + /** + * The base implementation of `_.isEqual` which supports partial comparisons + * and tracks traversed objects. + * + * @private + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @param {boolean} bitmask The bitmask flags. + * 1 - Unordered comparison + * 2 - Partial comparison + * @param {Function} [customizer] The function to customize comparisons. + * @param {Object} [stack] Tracks traversed `value` and `other` objects. + * @returns {boolean} Returns `true` if the values are equivalent, else `false`. + */ + function baseIsEqual(value, other, bitmask, customizer, stack) { + if (value === other) { + return true; + } + if (value == null || other == null || (!isObjectLike(value) && !isObjectLike(other))) { + return value !== value && other !== other; + } + return baseIsEqualDeep(value, other, bitmask, customizer, baseIsEqual, stack); + } + + /** + * A specialized version of `baseIsEqual` for arrays and objects which performs + * deep comparisons and tracks traversed objects enabling objects with circular + * references to be compared. + * + * @private + * @param {Object} object The object to compare. + * @param {Object} other The other object to compare. + * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. + * @param {Function} customizer The function to customize comparisons. + * @param {Function} equalFunc The function to determine equivalents of values. + * @param {Object} [stack] Tracks traversed `object` and `other` objects. + * @returns {boolean} Returns `true` if the objects are equivalent, else `false`. + */ + function baseIsEqualDeep(object, other, bitmask, customizer, equalFunc, stack) { + var objIsArr = isArray(object), + othIsArr = isArray(other), + objTag = objIsArr ? arrayTag : baseGetTag(object), + othTag = othIsArr ? arrayTag : baseGetTag(other); + + objTag = objTag == argsTag ? objectTag : objTag; + othTag = othTag == argsTag ? objectTag : othTag; + + var objIsObj = objTag == objectTag, + othIsObj = othTag == objectTag, + isSameTag = objTag == othTag; + + stack || (stack = []); + var objStack = find(stack, function(entry) { + return entry[0] == object; + }); + var othStack = find(stack, function(entry) { + return entry[0] == other; + }); + if (objStack && othStack) { + return objStack[1] == other; + } + stack.push([object, other]); + stack.push([other, object]); + if (isSameTag && !objIsObj) { + var result = (objIsArr) + ? equalArrays(object, other, bitmask, customizer, equalFunc, stack) + : equalByTag(object, other, objTag, bitmask, customizer, equalFunc, stack); + stack.pop(); + return result; + } + if (!(bitmask & COMPARE_PARTIAL_FLAG)) { + var objIsWrapped = objIsObj && hasOwnProperty.call(object, '__wrapped__'), + othIsWrapped = othIsObj && hasOwnProperty.call(other, '__wrapped__'); + + if (objIsWrapped || othIsWrapped) { + var objUnwrapped = objIsWrapped ? object.value() : object, + othUnwrapped = othIsWrapped ? other.value() : other; + + var result = equalFunc(objUnwrapped, othUnwrapped, bitmask, customizer, stack); + stack.pop(); + return result; + } + } + if (!isSameTag) { + return false; + } + var result = equalObjects(object, other, bitmask, customizer, equalFunc, stack); + stack.pop(); + return result; + } + + /** + * The base implementation of `_.isRegExp` without Node.js optimizations. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a regexp, else `false`. + */ + function baseIsRegExp(value) { + return isObjectLike(value) && baseGetTag(value) == regexpTag; + } + + /** + * The base implementation of `_.iteratee`. + * + * @private + * @param {*} [value=_.identity] The value to convert to an iteratee. + * @returns {Function} Returns the iteratee. + */ + function baseIteratee(func) { + if (typeof func == 'function') { + return func; + } + if (func == null) { + return identity; + } + return (typeof func == 'object' ? baseMatches : baseProperty)(func); + } + + /** + * The base implementation of `_.lt` which doesn't coerce arguments. + * + * @private + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @returns {boolean} Returns `true` if `value` is less than `other`, + * else `false`. + */ + function baseLt(value, other) { + return value < other; + } + + /** + * The base implementation of `_.map` without support for iteratee shorthands. + * + * @private + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} iteratee The function invoked per iteration. + * @returns {Array} Returns the new mapped array. + */ + function baseMap(collection, iteratee) { + var index = -1, + result = isArrayLike(collection) ? Array(collection.length) : []; + + baseEach(collection, function(value, key, collection) { + result[++index] = iteratee(value, key, collection); + }); + return result; + } + + /** + * The base implementation of `_.matches` which doesn't clone `source`. + * + * @private + * @param {Object} source The object of property values to match. + * @returns {Function} Returns the new spec function. + */ + function baseMatches(source) { + var props = nativeKeys(source); + return function(object) { + var length = props.length; + if (object == null) { + return !length; + } + object = Object(object); + while (length--) { + var key = props[length]; + if (!(key in object && + baseIsEqual(source[key], object[key], COMPARE_PARTIAL_FLAG | COMPARE_UNORDERED_FLAG) + )) { + return false; + } + } + return true; + }; + } + + /** + * The base implementation of `_.pick` without support for individual + * property identifiers. + * + * @private + * @param {Object} object The source object. + * @param {string[]} paths The property paths to pick. + * @returns {Object} Returns the new object. + */ + function basePick(object, props) { + object = Object(object); + return reduce(props, function(result, key) { + if (key in object) { + result[key] = object[key]; + } + return result; + }, {}); + } + + /** + * The base implementation of `_.rest` which doesn't validate or coerce arguments. + * + * @private + * @param {Function} func The function to apply a rest parameter to. + * @param {number} [start=func.length-1] The start position of the rest parameter. + * @returns {Function} Returns the new function. + */ + function baseRest(func, start) { + return setToString(overRest(func, start, identity), func + ''); + } + + /** + * The base implementation of `_.slice` without an iteratee call guard. + * + * @private + * @param {Array} array The array to slice. + * @param {number} [start=0] The start position. + * @param {number} [end=array.length] The end position. + * @returns {Array} Returns the slice of `array`. + */ + function baseSlice(array, start, end) { + var index = -1, + length = array.length; + + if (start < 0) { + start = -start > length ? 0 : (length + start); + } + end = end > length ? length : end; + if (end < 0) { + end += length; + } + length = start > end ? 0 : ((end - start) >>> 0); + start >>>= 0; + + var result = Array(length); + while (++index < length) { + result[index] = array[index + start]; + } + return result; + } + + /** + * Copies the values of `source` to `array`. + * + * @private + * @param {Array} source The array to copy values from. + * @param {Array} [array=[]] The array to copy values to. + * @returns {Array} Returns `array`. + */ + function copyArray(source) { + return baseSlice(source, 0, source.length); + } + + /** + * The base implementation of `_.some` without support for iteratee shorthands. + * + * @private + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} predicate The function invoked per iteration. + * @returns {boolean} Returns `true` if any element passes the predicate check, + * else `false`. + */ + function baseSome(collection, predicate) { + var result; + + baseEach(collection, function(value, index, collection) { + result = predicate(value, index, collection); + return !result; + }); + return !!result; + } + + /** + * The base implementation of `wrapperValue` which returns the result of + * performing a sequence of actions on the unwrapped `value`, where each + * successive action is supplied the return value of the previous. + * + * @private + * @param {*} value The unwrapped value. + * @param {Array} actions Actions to perform to resolve the unwrapped value. + * @returns {*} Returns the resolved value. + */ + function baseWrapperValue(value, actions) { + var result = value; + return reduce(actions, function(result, action) { + return action.func.apply(action.thisArg, arrayPush([result], action.args)); + }, result); + } + + /** + * Compares values to sort them in ascending order. + * + * @private + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @returns {number} Returns the sort order indicator for `value`. + */ + function compareAscending(value, other) { + if (value !== other) { + var valIsDefined = value !== undefined, + valIsNull = value === null, + valIsReflexive = value === value, + valIsSymbol = false; + + var othIsDefined = other !== undefined, + othIsNull = other === null, + othIsReflexive = other === other, + othIsSymbol = false; + + if ((!othIsNull && !othIsSymbol && !valIsSymbol && value > other) || + (valIsSymbol && othIsDefined && othIsReflexive && !othIsNull && !othIsSymbol) || + (valIsNull && othIsDefined && othIsReflexive) || + (!valIsDefined && othIsReflexive) || + !valIsReflexive) { + return 1; + } + if ((!valIsNull && !valIsSymbol && !othIsSymbol && value < other) || + (othIsSymbol && valIsDefined && valIsReflexive && !valIsNull && !valIsSymbol) || + (othIsNull && valIsDefined && valIsReflexive) || + (!othIsDefined && valIsReflexive) || + !othIsReflexive) { + return -1; + } + } + return 0; + } + + /** + * Copies properties of `source` to `object`. + * + * @private + * @param {Object} source The object to copy properties from. + * @param {Array} props The property identifiers to copy. + * @param {Object} [object={}] The object to copy properties to. + * @param {Function} [customizer] The function to customize copied values. + * @returns {Object} Returns `object`. + */ + function copyObject(source, props, object, customizer) { + var isNew = !object; + object || (object = {}); + + var index = -1, + length = props.length; + + while (++index < length) { + var key = props[index]; + + var newValue = customizer + ? customizer(object[key], source[key], key, object, source) + : undefined; + + if (newValue === undefined) { + newValue = source[key]; + } + if (isNew) { + baseAssignValue(object, key, newValue); + } else { + assignValue(object, key, newValue); + } + } + return object; + } + + /** + * Creates a function like `_.assign`. + * + * @private + * @param {Function} assigner The function to assign values. + * @returns {Function} Returns the new assigner function. + */ + function createAssigner(assigner) { + return baseRest(function(object, sources) { + var index = -1, + length = sources.length, + customizer = length > 1 ? sources[length - 1] : undefined; + + customizer = (assigner.length > 3 && typeof customizer == 'function') + ? (length--, customizer) + : undefined; + + object = Object(object); + while (++index < length) { + var source = sources[index]; + if (source) { + assigner(object, source, index, customizer); + } + } + return object; + }); + } + + /** + * Creates a `baseEach` or `baseEachRight` function. + * + * @private + * @param {Function} eachFunc The function to iterate over a collection. + * @param {boolean} [fromRight] Specify iterating from right to left. + * @returns {Function} Returns the new base function. + */ + function createBaseEach(eachFunc, fromRight) { + return function(collection, iteratee) { + if (collection == null) { + return collection; + } + if (!isArrayLike(collection)) { + return eachFunc(collection, iteratee); + } + var length = collection.length, + index = fromRight ? length : -1, + iterable = Object(collection); + + while ((fromRight ? index-- : ++index < length)) { + if (iteratee(iterable[index], index, iterable) === false) { + break; + } + } + return collection; + }; + } + + /** + * Creates a base function for methods like `_.forIn` and `_.forOwn`. + * + * @private + * @param {boolean} [fromRight] Specify iterating from right to left. + * @returns {Function} Returns the new base function. + */ + function createBaseFor(fromRight) { + return function(object, iteratee, keysFunc) { + var index = -1, + iterable = Object(object), + props = keysFunc(object), + length = props.length; + + while (length--) { + var key = props[fromRight ? length : ++index]; + if (iteratee(iterable[key], key, iterable) === false) { + break; + } + } + return object; + }; + } + + /** + * Creates a function that produces an instance of `Ctor` regardless of + * whether it was invoked as part of a `new` expression or by `call` or `apply`. + * + * @private + * @param {Function} Ctor The constructor to wrap. + * @returns {Function} Returns the new wrapped function. + */ + function createCtor(Ctor) { + return function() { + // Use a `switch` statement to work with class constructors. See + // http://ecma-international.org/ecma-262/7.0/#sec-ecmascript-function-objects-call-thisargument-argumentslist + // for more details. + var args = arguments; + var thisBinding = baseCreate(Ctor.prototype), + result = Ctor.apply(thisBinding, args); + + // Mimic the constructor's `return` behavior. + // See https://es5.github.io/#x13.2.2 for more details. + return isObject(result) ? result : thisBinding; + }; + } + + /** + * Creates a `_.find` or `_.findLast` function. + * + * @private + * @param {Function} findIndexFunc The function to find the collection index. + * @returns {Function} Returns the new find function. + */ + function createFind(findIndexFunc) { + return function(collection, predicate, fromIndex) { + var iterable = Object(collection); + if (!isArrayLike(collection)) { + var iteratee = baseIteratee(predicate, 3); + collection = keys(collection); + predicate = function(key) { return iteratee(iterable[key], key, iterable); }; + } + var index = findIndexFunc(collection, predicate, fromIndex); + return index > -1 ? iterable[iteratee ? collection[index] : index] : undefined; + }; + } + + /** + * Creates a function that wraps `func` to invoke it with the `this` binding + * of `thisArg` and `partials` prepended to the arguments it receives. + * + * @private + * @param {Function} func The function to wrap. + * @param {number} bitmask The bitmask flags. See `createWrap` for more details. + * @param {*} thisArg The `this` binding of `func`. + * @param {Array} partials The arguments to prepend to those provided to + * the new function. + * @returns {Function} Returns the new wrapped function. + */ + function createPartial(func, bitmask, thisArg, partials) { + if (typeof func != 'function') { + throw new TypeError(FUNC_ERROR_TEXT); + } + var isBind = bitmask & WRAP_BIND_FLAG, + Ctor = createCtor(func); + + function wrapper() { + var argsIndex = -1, + argsLength = arguments.length, + leftIndex = -1, + leftLength = partials.length, + args = Array(leftLength + argsLength), + fn = (this && this !== root && this instanceof wrapper) ? Ctor : func; + + while (++leftIndex < leftLength) { + args[leftIndex] = partials[leftIndex]; + } + while (argsLength--) { + args[leftIndex++] = arguments[++argsIndex]; + } + return fn.apply(isBind ? thisArg : this, args); + } + return wrapper; + } + + /** + * A specialized version of `baseIsEqualDeep` for arrays with support for + * partial deep comparisons. + * + * @private + * @param {Array} array The array to compare. + * @param {Array} other The other array to compare. + * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. + * @param {Function} customizer The function to customize comparisons. + * @param {Function} equalFunc The function to determine equivalents of values. + * @param {Object} stack Tracks traversed `array` and `other` objects. + * @returns {boolean} Returns `true` if the arrays are equivalent, else `false`. + */ + function equalArrays(array, other, bitmask, customizer, equalFunc, stack) { + var isPartial = bitmask & COMPARE_PARTIAL_FLAG, + arrLength = array.length, + othLength = other.length; + + if (arrLength != othLength && !(isPartial && othLength > arrLength)) { + return false; + } + var index = -1, + result = true, + seen = (bitmask & COMPARE_UNORDERED_FLAG) ? [] : undefined; + + // Ignore non-index properties. + while (++index < arrLength) { + var arrValue = array[index], + othValue = other[index]; + + var compared; + if (compared !== undefined) { + if (compared) { + continue; + } + result = false; + break; + } + // Recursively compare arrays (susceptible to call stack limits). + if (seen) { + if (!baseSome(other, function(othValue, othIndex) { + if (!indexOf(seen, othIndex) && + (arrValue === othValue || equalFunc(arrValue, othValue, bitmask, customizer, stack))) { + return seen.push(othIndex); + } + })) { + result = false; + break; + } + } else if (!( + arrValue === othValue || + equalFunc(arrValue, othValue, bitmask, customizer, stack) + )) { + result = false; + break; + } + } + return result; + } + + /** + * A specialized version of `baseIsEqualDeep` for comparing objects of + * the same `toStringTag`. + * + * **Note:** This function only supports comparing values with tags of + * `Boolean`, `Date`, `Error`, `Number`, `RegExp`, or `String`. + * + * @private + * @param {Object} object The object to compare. + * @param {Object} other The other object to compare. + * @param {string} tag The `toStringTag` of the objects to compare. + * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. + * @param {Function} customizer The function to customize comparisons. + * @param {Function} equalFunc The function to determine equivalents of values. + * @param {Object} stack Tracks traversed `object` and `other` objects. + * @returns {boolean} Returns `true` if the objects are equivalent, else `false`. + */ + function equalByTag(object, other, tag, bitmask, customizer, equalFunc, stack) { + switch (tag) { + + case boolTag: + case dateTag: + case numberTag: + // Coerce booleans to `1` or `0` and dates to milliseconds. + // Invalid dates are coerced to `NaN`. + return eq(+object, +other); + + case errorTag: + return object.name == other.name && object.message == other.message; + + case regexpTag: + case stringTag: + // Coerce regexes to strings and treat strings, primitives and objects, + // as equal. See http://www.ecma-international.org/ecma-262/7.0/#sec-regexp.prototype.tostring + // for more details. + return object == (other + ''); + + } + return false; + } + + /** + * A specialized version of `baseIsEqualDeep` for objects with support for + * partial deep comparisons. + * + * @private + * @param {Object} object The object to compare. + * @param {Object} other The other object to compare. + * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. + * @param {Function} customizer The function to customize comparisons. + * @param {Function} equalFunc The function to determine equivalents of values. + * @param {Object} stack Tracks traversed `object` and `other` objects. + * @returns {boolean} Returns `true` if the objects are equivalent, else `false`. + */ + function equalObjects(object, other, bitmask, customizer, equalFunc, stack) { + var isPartial = bitmask & COMPARE_PARTIAL_FLAG, + objProps = keys(object), + objLength = objProps.length, + othProps = keys(other), + othLength = othProps.length; + + if (objLength != othLength && !isPartial) { + return false; + } + var index = objLength; + while (index--) { + var key = objProps[index]; + if (!(isPartial ? key in other : hasOwnProperty.call(other, key))) { + return false; + } + } + var result = true; + + var skipCtor = isPartial; + while (++index < objLength) { + key = objProps[index]; + var objValue = object[key], + othValue = other[key]; + + var compared; + // Recursively compare objects (susceptible to call stack limits). + if (!(compared === undefined + ? (objValue === othValue || equalFunc(objValue, othValue, bitmask, customizer, stack)) + : compared + )) { + result = false; + break; + } + skipCtor || (skipCtor = key == 'constructor'); + } + if (result && !skipCtor) { + var objCtor = object.constructor, + othCtor = other.constructor; + + // Non `Object` object instances with different constructors are not equal. + if (objCtor != othCtor && + ('constructor' in object && 'constructor' in other) && + !(typeof objCtor == 'function' && objCtor instanceof objCtor && + typeof othCtor == 'function' && othCtor instanceof othCtor)) { + result = false; + } + } + return result; + } + + /** + * A specialized version of `baseRest` which flattens the rest array. + * + * @private + * @param {Function} func The function to apply a rest parameter to. + * @returns {Function} Returns the new function. + */ + function flatRest(func) { + return setToString(overRest(func, undefined, flatten), func + ''); + } + + /** + * Checks if `value` is a flattenable `arguments` object or array. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is flattenable, else `false`. + */ + function isFlattenable(value) { + return isArray(value) || isArguments(value); + } + + /** + * Checks if `value` is a valid array-like index. + * + * @private + * @param {*} value The value to check. + * @param {number} [length=MAX_SAFE_INTEGER] The upper bounds of a valid index. + * @returns {boolean} Returns `true` if `value` is a valid index, else `false`. + */ + function isIndex(value, length) { + var type = typeof value; + length = length == null ? MAX_SAFE_INTEGER : length; + + return !!length && + (type == 'number' || + (type != 'symbol' && reIsUint.test(value))) && + (value > -1 && value % 1 == 0 && value < length); + } + + /** + * Checks if the given arguments are from an iteratee call. + * + * @private + * @param {*} value The potential iteratee value argument. + * @param {*} index The potential iteratee index or key argument. + * @param {*} object The potential iteratee object argument. + * @returns {boolean} Returns `true` if the arguments are from an iteratee call, + * else `false`. + */ + function isIterateeCall(value, index, object) { + if (!isObject(object)) { + return false; + } + var type = typeof index; + if (type == 'number' + ? (isArrayLike(object) && isIndex(index, object.length)) + : (type == 'string' && index in object) + ) { + return eq(object[index], value); + } + return false; + } + + /** + * This function is like + * [`Object.keys`](http://ecma-international.org/ecma-262/7.0/#sec-object.keys) + * except that it includes inherited enumerable properties. + * + * @private + * @param {Object} object The object to query. + * @returns {Array} Returns the array of property names. + */ + function nativeKeysIn(object) { + var result = []; + if (object != null) { + for (var key in Object(object)) { + result.push(key); + } + } + return result; + } + + /** + * Converts `value` to a string using `Object.prototype.toString`. + * + * @private + * @param {*} value The value to convert. + * @returns {string} Returns the converted string. + */ + function objectToString(value) { + return nativeObjectToString.call(value); + } + + /** + * A specialized version of `baseRest` which transforms the rest array. + * + * @private + * @param {Function} func The function to apply a rest parameter to. + * @param {number} [start=func.length-1] The start position of the rest parameter. + * @param {Function} transform The rest array transform. + * @returns {Function} Returns the new function. + */ + function overRest(func, start, transform) { + start = nativeMax(start === undefined ? (func.length - 1) : start, 0); + return function() { + var args = arguments, + index = -1, + length = nativeMax(args.length - start, 0), + array = Array(length); + + while (++index < length) { + array[index] = args[start + index]; + } + index = -1; + var otherArgs = Array(start + 1); + while (++index < start) { + otherArgs[index] = args[index]; + } + otherArgs[start] = transform(array); + return func.apply(this, otherArgs); + }; + } + + /** + * Sets the `toString` method of `func` to return `string`. + * + * @private + * @param {Function} func The function to modify. + * @param {Function} string The `toString` result. + * @returns {Function} Returns `func`. + */ + var setToString = identity; + + /*------------------------------------------------------------------------*/ + + /** + * Creates an array with all falsey values removed. The values `false`, `null`, + * `0`, `""`, `undefined`, and `NaN` are falsey. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to compact. + * @returns {Array} Returns the new array of filtered values. + * @example + * + * _.compact([0, 1, false, 2, '', 3]); + * // => [1, 2, 3] + */ + function compact(array) { + return baseFilter(array, Boolean); + } + + /** + * Creates a new array concatenating `array` with any additional arrays + * and/or values. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to concatenate. + * @param {...*} [values] The values to concatenate. + * @returns {Array} Returns the new concatenated array. + * @example + * + * var array = [1]; + * var other = _.concat(array, 2, [3], [[4]]); + * + * console.log(other); + * // => [1, 2, 3, [4]] + * + * console.log(array); + * // => [1] + */ + function concat() { + var length = arguments.length; + if (!length) { + return []; + } + var args = Array(length - 1), + array = arguments[0], + index = length; + + while (index--) { + args[index - 1] = arguments[index]; + } + return arrayPush(isArray(array) ? copyArray(array) : [array], baseFlatten(args, 1)); + } + + /** + * This method is like `_.find` except that it returns the index of the first + * element `predicate` returns truthy for instead of the element itself. + * + * @static + * @memberOf _ + * @since 1.1.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @param {number} [fromIndex=0] The index to search from. + * @returns {number} Returns the index of the found element, else `-1`. + * @example + * + * var users = [ + * { 'user': 'barney', 'active': false }, + * { 'user': 'fred', 'active': false }, + * { 'user': 'pebbles', 'active': true } + * ]; + * + * _.findIndex(users, function(o) { return o.user == 'barney'; }); + * // => 0 + * + * // The `_.matches` iteratee shorthand. + * _.findIndex(users, { 'user': 'fred', 'active': false }); + * // => 1 + * + * // The `_.matchesProperty` iteratee shorthand. + * _.findIndex(users, ['active', false]); + * // => 0 + * + * // The `_.property` iteratee shorthand. + * _.findIndex(users, 'active'); + * // => 2 + */ + function findIndex(array, predicate, fromIndex) { + var length = array == null ? 0 : array.length; + if (!length) { + return -1; + } + var index = fromIndex == null ? 0 : toInteger(fromIndex); + if (index < 0) { + index = nativeMax(length + index, 0); + } + return baseFindIndex(array, baseIteratee(predicate, 3), index); + } + + /** + * Flattens `array` a single level deep. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to flatten. + * @returns {Array} Returns the new flattened array. + * @example + * + * _.flatten([1, [2, [3, [4]], 5]]); + * // => [1, 2, [3, [4]], 5] + */ + function flatten(array) { + var length = array == null ? 0 : array.length; + return length ? baseFlatten(array, 1) : []; + } + + /** + * Recursively flattens `array`. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to flatten. + * @returns {Array} Returns the new flattened array. + * @example + * + * _.flattenDeep([1, [2, [3, [4]], 5]]); + * // => [1, 2, 3, 4, 5] + */ + function flattenDeep(array) { + var length = array == null ? 0 : array.length; + return length ? baseFlatten(array, INFINITY) : []; + } + + /** + * Gets the first element of `array`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @alias first + * @category Array + * @param {Array} array The array to query. + * @returns {*} Returns the first element of `array`. + * @example + * + * _.head([1, 2, 3]); + * // => 1 + * + * _.head([]); + * // => undefined + */ + function head(array) { + return (array && array.length) ? array[0] : undefined; + } + + /** + * Gets the index at which the first occurrence of `value` is found in `array` + * using [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. If `fromIndex` is negative, it's used as the + * offset from the end of `array`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @param {number} [fromIndex=0] The index to search from. + * @returns {number} Returns the index of the matched value, else `-1`. + * @example + * + * _.indexOf([1, 2, 1, 2], 2); + * // => 1 + * + * // Search from the `fromIndex`. + * _.indexOf([1, 2, 1, 2], 2, 2); + * // => 3 + */ + function indexOf(array, value, fromIndex) { + var length = array == null ? 0 : array.length; + if (typeof fromIndex == 'number') { + fromIndex = fromIndex < 0 ? nativeMax(length + fromIndex, 0) : fromIndex; + } else { + fromIndex = 0; + } + var index = (fromIndex || 0) - 1, + isReflexive = value === value; + + while (++index < length) { + var other = array[index]; + if ((isReflexive ? other === value : other !== other)) { + return index; + } + } + return -1; + } + + /** + * Gets the last element of `array`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to query. + * @returns {*} Returns the last element of `array`. + * @example + * + * _.last([1, 2, 3]); + * // => 3 + */ + function last(array) { + var length = array == null ? 0 : array.length; + return length ? array[length - 1] : undefined; + } + + /** + * Creates a slice of `array` from `start` up to, but not including, `end`. + * + * **Note:** This method is used instead of + * [`Array#slice`](https://mdn.io/Array/slice) to ensure dense arrays are + * returned. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to slice. + * @param {number} [start=0] The start position. + * @param {number} [end=array.length] The end position. + * @returns {Array} Returns the slice of `array`. + */ + function slice(array, start, end) { + var length = array == null ? 0 : array.length; + start = start == null ? 0 : +start; + end = end === undefined ? length : +end; + return length ? baseSlice(array, start, end) : []; + } + + /*------------------------------------------------------------------------*/ + + /** + * Creates a `lodash` wrapper instance that wraps `value` with explicit method + * chain sequences enabled. The result of such sequences must be unwrapped + * with `_#value`. + * + * @static + * @memberOf _ + * @since 1.3.0 + * @category Seq + * @param {*} value The value to wrap. + * @returns {Object} Returns the new `lodash` wrapper instance. + * @example + * + * var users = [ + * { 'user': 'barney', 'age': 36 }, + * { 'user': 'fred', 'age': 40 }, + * { 'user': 'pebbles', 'age': 1 } + * ]; + * + * var youngest = _ + * .chain(users) + * .sortBy('age') + * .map(function(o) { + * return o.user + ' is ' + o.age; + * }) + * .head() + * .value(); + * // => 'pebbles is 1' + */ + function chain(value) { + var result = lodash(value); + result.__chain__ = true; + return result; + } + + /** + * This method invokes `interceptor` and returns `value`. The interceptor + * is invoked with one argument; (value). The purpose of this method is to + * "tap into" a method chain sequence in order to modify intermediate results. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Seq + * @param {*} value The value to provide to `interceptor`. + * @param {Function} interceptor The function to invoke. + * @returns {*} Returns `value`. + * @example + * + * _([1, 2, 3]) + * .tap(function(array) { + * // Mutate input array. + * array.pop(); + * }) + * .reverse() + * .value(); + * // => [2, 1] + */ + function tap(value, interceptor) { + interceptor(value); + return value; + } + + /** + * This method is like `_.tap` except that it returns the result of `interceptor`. + * The purpose of this method is to "pass thru" values replacing intermediate + * results in a method chain sequence. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Seq + * @param {*} value The value to provide to `interceptor`. + * @param {Function} interceptor The function to invoke. + * @returns {*} Returns the result of `interceptor`. + * @example + * + * _(' abc ') + * .chain() + * .trim() + * .thru(function(value) { + * return [value]; + * }) + * .value(); + * // => ['abc'] + */ + function thru(value, interceptor) { + return interceptor(value); + } + + /** + * Creates a `lodash` wrapper instance with explicit method chain sequences enabled. + * + * @name chain + * @memberOf _ + * @since 0.1.0 + * @category Seq + * @returns {Object} Returns the new `lodash` wrapper instance. + * @example + * + * var users = [ + * { 'user': 'barney', 'age': 36 }, + * { 'user': 'fred', 'age': 40 } + * ]; + * + * // A sequence without explicit chaining. + * _(users).head(); + * // => { 'user': 'barney', 'age': 36 } + * + * // A sequence with explicit chaining. + * _(users) + * .chain() + * .head() + * .pick('user') + * .value(); + * // => { 'user': 'barney' } + */ + function wrapperChain() { + return chain(this); + } + + /** + * Executes the chain sequence to resolve the unwrapped value. + * + * @name value + * @memberOf _ + * @since 0.1.0 + * @alias toJSON, valueOf + * @category Seq + * @returns {*} Returns the resolved unwrapped value. + * @example + * + * _([1, 2, 3]).value(); + * // => [1, 2, 3] + */ + function wrapperValue() { + return baseWrapperValue(this.__wrapped__, this.__actions__); + } + + /*------------------------------------------------------------------------*/ + + /** + * Checks if `predicate` returns truthy for **all** elements of `collection`. + * Iteration is stopped once `predicate` returns falsey. The predicate is + * invoked with three arguments: (value, index|key, collection). + * + * **Note:** This method returns `true` for + * [empty collections](https://en.wikipedia.org/wiki/Empty_set) because + * [everything is true](https://en.wikipedia.org/wiki/Vacuous_truth) of + * elements of empty collections. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Collection + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. + * @returns {boolean} Returns `true` if all elements pass the predicate check, + * else `false`. + * @example + * + * _.every([true, 1, null, 'yes'], Boolean); + * // => false + * + * var users = [ + * { 'user': 'barney', 'age': 36, 'active': false }, + * { 'user': 'fred', 'age': 40, 'active': false } + * ]; + * + * // The `_.matches` iteratee shorthand. + * _.every(users, { 'user': 'barney', 'active': false }); + * // => false + * + * // The `_.matchesProperty` iteratee shorthand. + * _.every(users, ['active', false]); + * // => true + * + * // The `_.property` iteratee shorthand. + * _.every(users, 'active'); + * // => false + */ + function every(collection, predicate, guard) { + predicate = guard ? undefined : predicate; + return baseEvery(collection, baseIteratee(predicate)); + } + + /** + * Iterates over elements of `collection`, returning an array of all elements + * `predicate` returns truthy for. The predicate is invoked with three + * arguments: (value, index|key, collection). + * + * **Note:** Unlike `_.remove`, this method returns a new array. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Collection + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @returns {Array} Returns the new filtered array. + * @see _.reject + * @example + * + * var users = [ + * { 'user': 'barney', 'age': 36, 'active': true }, + * { 'user': 'fred', 'age': 40, 'active': false } + * ]; + * + * _.filter(users, function(o) { return !o.active; }); + * // => objects for ['fred'] + * + * // The `_.matches` iteratee shorthand. + * _.filter(users, { 'age': 36, 'active': true }); + * // => objects for ['barney'] + * + * // The `_.matchesProperty` iteratee shorthand. + * _.filter(users, ['active', false]); + * // => objects for ['fred'] + * + * // The `_.property` iteratee shorthand. + * _.filter(users, 'active'); + * // => objects for ['barney'] + */ + function filter(collection, predicate) { + return baseFilter(collection, baseIteratee(predicate)); + } + + /** + * Iterates over elements of `collection`, returning the first element + * `predicate` returns truthy for. The predicate is invoked with three + * arguments: (value, index|key, collection). + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Collection + * @param {Array|Object} collection The collection to inspect. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @param {number} [fromIndex=0] The index to search from. + * @returns {*} Returns the matched element, else `undefined`. + * @example + * + * var users = [ + * { 'user': 'barney', 'age': 36, 'active': true }, + * { 'user': 'fred', 'age': 40, 'active': false }, + * { 'user': 'pebbles', 'age': 1, 'active': true } + * ]; + * + * _.find(users, function(o) { return o.age < 40; }); + * // => object for 'barney' + * + * // The `_.matches` iteratee shorthand. + * _.find(users, { 'age': 1, 'active': true }); + * // => object for 'pebbles' + * + * // The `_.matchesProperty` iteratee shorthand. + * _.find(users, ['active', false]); + * // => object for 'fred' + * + * // The `_.property` iteratee shorthand. + * _.find(users, 'active'); + * // => object for 'barney' + */ + var find = createFind(findIndex); + + /** + * Iterates over elements of `collection` and invokes `iteratee` for each element. + * The iteratee is invoked with three arguments: (value, index|key, collection). + * Iteratee functions may exit iteration early by explicitly returning `false`. + * + * **Note:** As with other "Collections" methods, objects with a "length" + * property are iterated like arrays. To avoid this behavior use `_.forIn` + * or `_.forOwn` for object iteration. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @alias each + * @category Collection + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} [iteratee=_.identity] The function invoked per iteration. + * @returns {Array|Object} Returns `collection`. + * @see _.forEachRight + * @example + * + * _.forEach([1, 2], function(value) { + * console.log(value); + * }); + * // => Logs `1` then `2`. + * + * _.forEach({ 'a': 1, 'b': 2 }, function(value, key) { + * console.log(key); + * }); + * // => Logs 'a' then 'b' (iteration order is not guaranteed). + */ + function forEach(collection, iteratee) { + return baseEach(collection, baseIteratee(iteratee)); + } + + /** + * Creates an array of values by running each element in `collection` thru + * `iteratee`. The iteratee is invoked with three arguments: + * (value, index|key, collection). + * + * Many lodash methods are guarded to work as iteratees for methods like + * `_.every`, `_.filter`, `_.map`, `_.mapValues`, `_.reject`, and `_.some`. + * + * The guarded methods are: + * `ary`, `chunk`, `curry`, `curryRight`, `drop`, `dropRight`, `every`, + * `fill`, `invert`, `parseInt`, `random`, `range`, `rangeRight`, `repeat`, + * `sampleSize`, `slice`, `some`, `sortBy`, `split`, `take`, `takeRight`, + * `template`, `trim`, `trimEnd`, `trimStart`, and `words` + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Collection + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} [iteratee=_.identity] The function invoked per iteration. + * @returns {Array} Returns the new mapped array. + * @example + * + * function square(n) { + * return n * n; + * } + * + * _.map([4, 8], square); + * // => [16, 64] + * + * _.map({ 'a': 4, 'b': 8 }, square); + * // => [16, 64] (iteration order is not guaranteed) + * + * var users = [ + * { 'user': 'barney' }, + * { 'user': 'fred' } + * ]; + * + * // The `_.property` iteratee shorthand. + * _.map(users, 'user'); + * // => ['barney', 'fred'] + */ + function map(collection, iteratee) { + return baseMap(collection, baseIteratee(iteratee)); + } + + /** + * Reduces `collection` to a value which is the accumulated result of running + * each element in `collection` thru `iteratee`, where each successive + * invocation is supplied the return value of the previous. If `accumulator` + * is not given, the first element of `collection` is used as the initial + * value. The iteratee is invoked with four arguments: + * (accumulator, value, index|key, collection). + * + * Many lodash methods are guarded to work as iteratees for methods like + * `_.reduce`, `_.reduceRight`, and `_.transform`. + * + * The guarded methods are: + * `assign`, `defaults`, `defaultsDeep`, `includes`, `merge`, `orderBy`, + * and `sortBy` + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Collection + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} [iteratee=_.identity] The function invoked per iteration. + * @param {*} [accumulator] The initial value. + * @returns {*} Returns the accumulated value. + * @see _.reduceRight + * @example + * + * _.reduce([1, 2], function(sum, n) { + * return sum + n; + * }, 0); + * // => 3 + * + * _.reduce({ 'a': 1, 'b': 2, 'c': 1 }, function(result, value, key) { + * (result[value] || (result[value] = [])).push(key); + * return result; + * }, {}); + * // => { '1': ['a', 'c'], '2': ['b'] } (iteration order is not guaranteed) + */ + function reduce(collection, iteratee, accumulator) { + return baseReduce(collection, baseIteratee(iteratee), accumulator, arguments.length < 3, baseEach); + } + + /** + * Gets the size of `collection` by returning its length for array-like + * values or the number of own enumerable string keyed properties for objects. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Collection + * @param {Array|Object|string} collection The collection to inspect. + * @returns {number} Returns the collection size. + * @example + * + * _.size([1, 2, 3]); + * // => 3 + * + * _.size({ 'a': 1, 'b': 2 }); + * // => 2 + * + * _.size('pebbles'); + * // => 7 + */ + function size(collection) { + if (collection == null) { + return 0; + } + collection = isArrayLike(collection) ? collection : nativeKeys(collection); + return collection.length; + } + + /** + * Checks if `predicate` returns truthy for **any** element of `collection`. + * Iteration is stopped once `predicate` returns truthy. The predicate is + * invoked with three arguments: (value, index|key, collection). + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Collection + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. + * @returns {boolean} Returns `true` if any element passes the predicate check, + * else `false`. + * @example + * + * _.some([null, 0, 'yes', false], Boolean); + * // => true + * + * var users = [ + * { 'user': 'barney', 'active': true }, + * { 'user': 'fred', 'active': false } + * ]; + * + * // The `_.matches` iteratee shorthand. + * _.some(users, { 'user': 'barney', 'active': false }); + * // => false + * + * // The `_.matchesProperty` iteratee shorthand. + * _.some(users, ['active', false]); + * // => true + * + * // The `_.property` iteratee shorthand. + * _.some(users, 'active'); + * // => true + */ + function some(collection, predicate, guard) { + predicate = guard ? undefined : predicate; + return baseSome(collection, baseIteratee(predicate)); + } + + /** + * Creates an array of elements, sorted in ascending order by the results of + * running each element in a collection thru each iteratee. This method + * performs a stable sort, that is, it preserves the original sort order of + * equal elements. The iteratees are invoked with one argument: (value). + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Collection + * @param {Array|Object} collection The collection to iterate over. + * @param {...(Function|Function[])} [iteratees=[_.identity]] + * The iteratees to sort by. + * @returns {Array} Returns the new sorted array. + * @example + * + * var users = [ + * { 'user': 'fred', 'age': 48 }, + * { 'user': 'barney', 'age': 36 }, + * { 'user': 'fred', 'age': 40 }, + * { 'user': 'barney', 'age': 34 } + * ]; + * + * _.sortBy(users, [function(o) { return o.user; }]); + * // => objects for [['barney', 36], ['barney', 34], ['fred', 48], ['fred', 40]] + * + * _.sortBy(users, ['user', 'age']); + * // => objects for [['barney', 34], ['barney', 36], ['fred', 40], ['fred', 48]] + */ + function sortBy(collection, iteratee) { + var index = 0; + iteratee = baseIteratee(iteratee); + + return baseMap(baseMap(collection, function(value, key, collection) { + return { 'value': value, 'index': index++, 'criteria': iteratee(value, key, collection) }; + }).sort(function(object, other) { + return compareAscending(object.criteria, other.criteria) || (object.index - other.index); + }), baseProperty('value')); + } + + /*------------------------------------------------------------------------*/ + + /** + * Creates a function that invokes `func`, with the `this` binding and arguments + * of the created function, while it's called less than `n` times. Subsequent + * calls to the created function return the result of the last `func` invocation. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Function + * @param {number} n The number of calls at which `func` is no longer invoked. + * @param {Function} func The function to restrict. + * @returns {Function} Returns the new restricted function. + * @example + * + * jQuery(element).on('click', _.before(5, addContactToList)); + * // => Allows adding up to 4 contacts to the list. + */ + function before(n, func) { + var result; + if (typeof func != 'function') { + throw new TypeError(FUNC_ERROR_TEXT); + } + n = toInteger(n); + return function() { + if (--n > 0) { + result = func.apply(this, arguments); + } + if (n <= 1) { + func = undefined; + } + return result; + }; + } + + /** + * Creates a function that invokes `func` with the `this` binding of `thisArg` + * and `partials` prepended to the arguments it receives. + * + * The `_.bind.placeholder` value, which defaults to `_` in monolithic builds, + * may be used as a placeholder for partially applied arguments. + * + * **Note:** Unlike native `Function#bind`, this method doesn't set the "length" + * property of bound functions. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Function + * @param {Function} func The function to bind. + * @param {*} thisArg The `this` binding of `func`. + * @param {...*} [partials] The arguments to be partially applied. + * @returns {Function} Returns the new bound function. + * @example + * + * function greet(greeting, punctuation) { + * return greeting + ' ' + this.user + punctuation; + * } + * + * var object = { 'user': 'fred' }; + * + * var bound = _.bind(greet, object, 'hi'); + * bound('!'); + * // => 'hi fred!' + * + * // Bound with placeholders. + * var bound = _.bind(greet, object, _, '!'); + * bound('hi'); + * // => 'hi fred!' + */ + var bind = baseRest(function(func, thisArg, partials) { + return createPartial(func, WRAP_BIND_FLAG | WRAP_PARTIAL_FLAG, thisArg, partials); + }); + + /** + * Defers invoking the `func` until the current call stack has cleared. Any + * additional arguments are provided to `func` when it's invoked. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Function + * @param {Function} func The function to defer. + * @param {...*} [args] The arguments to invoke `func` with. + * @returns {number} Returns the timer id. + * @example + * + * _.defer(function(text) { + * console.log(text); + * }, 'deferred'); + * // => Logs 'deferred' after one millisecond. + */ + var defer = baseRest(function(func, args) { + return baseDelay(func, 1, args); + }); + + /** + * Invokes `func` after `wait` milliseconds. Any additional arguments are + * provided to `func` when it's invoked. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Function + * @param {Function} func The function to delay. + * @param {number} wait The number of milliseconds to delay invocation. + * @param {...*} [args] The arguments to invoke `func` with. + * @returns {number} Returns the timer id. + * @example + * + * _.delay(function(text) { + * console.log(text); + * }, 1000, 'later'); + * // => Logs 'later' after one second. + */ + var delay = baseRest(function(func, wait, args) { + return baseDelay(func, toNumber(wait) || 0, args); + }); + + /** + * Creates a function that negates the result of the predicate `func`. The + * `func` predicate is invoked with the `this` binding and arguments of the + * created function. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Function + * @param {Function} predicate The predicate to negate. + * @returns {Function} Returns the new negated function. + * @example + * + * function isEven(n) { + * return n % 2 == 0; + * } + * + * _.filter([1, 2, 3, 4, 5, 6], _.negate(isEven)); + * // => [1, 3, 5] + */ + function negate(predicate) { + if (typeof predicate != 'function') { + throw new TypeError(FUNC_ERROR_TEXT); + } + return function() { + var args = arguments; + return !predicate.apply(this, args); + }; + } + + /** + * Creates a function that is restricted to invoking `func` once. Repeat calls + * to the function return the value of the first invocation. The `func` is + * invoked with the `this` binding and arguments of the created function. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Function + * @param {Function} func The function to restrict. + * @returns {Function} Returns the new restricted function. + * @example + * + * var initialize = _.once(createApplication); + * initialize(); + * initialize(); + * // => `createApplication` is invoked once + */ + function once(func) { + return before(2, func); + } + + /*------------------------------------------------------------------------*/ + + /** + * Creates a shallow clone of `value`. + * + * **Note:** This method is loosely based on the + * [structured clone algorithm](https://mdn.io/Structured_clone_algorithm) + * and supports cloning arrays, array buffers, booleans, date objects, maps, + * numbers, `Object` objects, regexes, sets, strings, symbols, and typed + * arrays. The own enumerable properties of `arguments` objects are cloned + * as plain objects. An empty object is returned for uncloneable values such + * as error objects, functions, DOM nodes, and WeakMaps. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to clone. + * @returns {*} Returns the cloned value. + * @see _.cloneDeep + * @example + * + * var objects = [{ 'a': 1 }, { 'b': 2 }]; + * + * var shallow = _.clone(objects); + * console.log(shallow[0] === objects[0]); + * // => true + */ + function clone(value) { + if (!isObject(value)) { + return value; + } + return isArray(value) ? copyArray(value) : copyObject(value, nativeKeys(value)); + } + + /** + * Performs a + * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * comparison between two values to determine if they are equivalent. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @returns {boolean} Returns `true` if the values are equivalent, else `false`. + * @example + * + * var object = { 'a': 1 }; + * var other = { 'a': 1 }; + * + * _.eq(object, object); + * // => true + * + * _.eq(object, other); + * // => false + * + * _.eq('a', 'a'); + * // => true + * + * _.eq('a', Object('a')); + * // => false + * + * _.eq(NaN, NaN); + * // => true + */ + function eq(value, other) { + return value === other || (value !== value && other !== other); + } + + /** + * Checks if `value` is likely an `arguments` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an `arguments` object, + * else `false`. + * @example + * + * _.isArguments(function() { return arguments; }()); + * // => true + * + * _.isArguments([1, 2, 3]); + * // => false + */ + var isArguments = baseIsArguments(function() { return arguments; }()) ? baseIsArguments : function(value) { + return isObjectLike(value) && hasOwnProperty.call(value, 'callee') && + !propertyIsEnumerable.call(value, 'callee'); + }; + + /** + * Checks if `value` is classified as an `Array` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an array, else `false`. + * @example + * + * _.isArray([1, 2, 3]); + * // => true + * + * _.isArray(document.body.children); + * // => false + * + * _.isArray('abc'); + * // => false + * + * _.isArray(_.noop); + * // => false + */ + var isArray = Array.isArray; + + /** + * Checks if `value` is array-like. A value is considered array-like if it's + * not a function and has a `value.length` that's an integer greater than or + * equal to `0` and less than or equal to `Number.MAX_SAFE_INTEGER`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is array-like, else `false`. + * @example + * + * _.isArrayLike([1, 2, 3]); + * // => true + * + * _.isArrayLike(document.body.children); + * // => true + * + * _.isArrayLike('abc'); + * // => true + * + * _.isArrayLike(_.noop); + * // => false + */ + function isArrayLike(value) { + return value != null && isLength(value.length) && !isFunction(value); + } + + /** + * Checks if `value` is classified as a boolean primitive or object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a boolean, else `false`. + * @example + * + * _.isBoolean(false); + * // => true + * + * _.isBoolean(null); + * // => false + */ + function isBoolean(value) { + return value === true || value === false || + (isObjectLike(value) && baseGetTag(value) == boolTag); + } + + /** + * Checks if `value` is classified as a `Date` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a date object, else `false`. + * @example + * + * _.isDate(new Date); + * // => true + * + * _.isDate('Mon April 23 2012'); + * // => false + */ + var isDate = baseIsDate; + + /** + * Checks if `value` is an empty object, collection, map, or set. + * + * Objects are considered empty if they have no own enumerable string keyed + * properties. + * + * Array-like values such as `arguments` objects, arrays, buffers, strings, or + * jQuery-like collections are considered empty if they have a `length` of `0`. + * Similarly, maps and sets are considered empty if they have a `size` of `0`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is empty, else `false`. + * @example + * + * _.isEmpty(null); + * // => true + * + * _.isEmpty(true); + * // => true + * + * _.isEmpty(1); + * // => true + * + * _.isEmpty([1, 2, 3]); + * // => false + * + * _.isEmpty({ 'a': 1 }); + * // => false + */ + function isEmpty(value) { + if (isArrayLike(value) && + (isArray(value) || isString(value) || + isFunction(value.splice) || isArguments(value))) { + return !value.length; + } + return !nativeKeys(value).length; + } + + /** + * Performs a deep comparison between two values to determine if they are + * equivalent. + * + * **Note:** This method supports comparing arrays, array buffers, booleans, + * date objects, error objects, maps, numbers, `Object` objects, regexes, + * sets, strings, symbols, and typed arrays. `Object` objects are compared + * by their own, not inherited, enumerable properties. Functions and DOM + * nodes are compared by strict equality, i.e. `===`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @returns {boolean} Returns `true` if the values are equivalent, else `false`. + * @example + * + * var object = { 'a': 1 }; + * var other = { 'a': 1 }; + * + * _.isEqual(object, other); + * // => true + * + * object === other; + * // => false + */ + function isEqual(value, other) { + return baseIsEqual(value, other); + } + + /** + * Checks if `value` is a finite primitive number. + * + * **Note:** This method is based on + * [`Number.isFinite`](https://mdn.io/Number/isFinite). + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a finite number, else `false`. + * @example + * + * _.isFinite(3); + * // => true + * + * _.isFinite(Number.MIN_VALUE); + * // => true + * + * _.isFinite(Infinity); + * // => false + * + * _.isFinite('3'); + * // => false + */ + function isFinite(value) { + return typeof value == 'number' && nativeIsFinite(value); + } + + /** + * Checks if `value` is classified as a `Function` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a function, else `false`. + * @example + * + * _.isFunction(_); + * // => true + * + * _.isFunction(/abc/); + * // => false + */ + function isFunction(value) { + if (!isObject(value)) { + return false; + } + // The use of `Object#toString` avoids issues with the `typeof` operator + // in Safari 9 which returns 'object' for typed arrays and other constructors. + var tag = baseGetTag(value); + return tag == funcTag || tag == genTag || tag == asyncTag || tag == proxyTag; + } + + /** + * Checks if `value` is a valid array-like length. + * + * **Note:** This method is loosely based on + * [`ToLength`](http://ecma-international.org/ecma-262/7.0/#sec-tolength). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a valid length, else `false`. + * @example + * + * _.isLength(3); + * // => true + * + * _.isLength(Number.MIN_VALUE); + * // => false + * + * _.isLength(Infinity); + * // => false + * + * _.isLength('3'); + * // => false + */ + function isLength(value) { + return typeof value == 'number' && + value > -1 && value % 1 == 0 && value <= MAX_SAFE_INTEGER; + } + + /** + * Checks if `value` is the + * [language type](http://www.ecma-international.org/ecma-262/7.0/#sec-ecmascript-language-types) + * of `Object`. (e.g. arrays, functions, objects, regexes, `new Number(0)`, and `new String('')`) + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an object, else `false`. + * @example + * + * _.isObject({}); + * // => true + * + * _.isObject([1, 2, 3]); + * // => true + * + * _.isObject(_.noop); + * // => true + * + * _.isObject(null); + * // => false + */ + function isObject(value) { + var type = typeof value; + return value != null && (type == 'object' || type == 'function'); + } + + /** + * Checks if `value` is object-like. A value is object-like if it's not `null` + * and has a `typeof` result of "object". + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is object-like, else `false`. + * @example + * + * _.isObjectLike({}); + * // => true + * + * _.isObjectLike([1, 2, 3]); + * // => true + * + * _.isObjectLike(_.noop); + * // => false + * + * _.isObjectLike(null); + * // => false + */ + function isObjectLike(value) { + return value != null && typeof value == 'object'; + } + + /** + * Checks if `value` is `NaN`. + * + * **Note:** This method is based on + * [`Number.isNaN`](https://mdn.io/Number/isNaN) and is not the same as + * global [`isNaN`](https://mdn.io/isNaN) which returns `true` for + * `undefined` and other non-number values. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is `NaN`, else `false`. + * @example + * + * _.isNaN(NaN); + * // => true + * + * _.isNaN(new Number(NaN)); + * // => true + * + * isNaN(undefined); + * // => true + * + * _.isNaN(undefined); + * // => false + */ + function isNaN(value) { + // An `NaN` primitive is the only value that is not equal to itself. + // Perform the `toStringTag` check first to avoid errors with some + // ActiveX objects in IE. + return isNumber(value) && value != +value; + } + + /** + * Checks if `value` is `null`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is `null`, else `false`. + * @example + * + * _.isNull(null); + * // => true + * + * _.isNull(void 0); + * // => false + */ + function isNull(value) { + return value === null; + } + + /** + * Checks if `value` is classified as a `Number` primitive or object. + * + * **Note:** To exclude `Infinity`, `-Infinity`, and `NaN`, which are + * classified as numbers, use the `_.isFinite` method. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a number, else `false`. + * @example + * + * _.isNumber(3); + * // => true + * + * _.isNumber(Number.MIN_VALUE); + * // => true + * + * _.isNumber(Infinity); + * // => true + * + * _.isNumber('3'); + * // => false + */ + function isNumber(value) { + return typeof value == 'number' || + (isObjectLike(value) && baseGetTag(value) == numberTag); + } + + /** + * Checks if `value` is classified as a `RegExp` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a regexp, else `false`. + * @example + * + * _.isRegExp(/abc/); + * // => true + * + * _.isRegExp('/abc/'); + * // => false + */ + var isRegExp = baseIsRegExp; + + /** + * Checks if `value` is classified as a `String` primitive or object. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a string, else `false`. + * @example + * + * _.isString('abc'); + * // => true + * + * _.isString(1); + * // => false + */ + function isString(value) { + return typeof value == 'string' || + (!isArray(value) && isObjectLike(value) && baseGetTag(value) == stringTag); + } + + /** + * Checks if `value` is `undefined`. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is `undefined`, else `false`. + * @example + * + * _.isUndefined(void 0); + * // => true + * + * _.isUndefined(null); + * // => false + */ + function isUndefined(value) { + return value === undefined; + } + + /** + * Converts `value` to an array. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Lang + * @param {*} value The value to convert. + * @returns {Array} Returns the converted array. + * @example + * + * _.toArray({ 'a': 1, 'b': 2 }); + * // => [1, 2] + * + * _.toArray('abc'); + * // => ['a', 'b', 'c'] + * + * _.toArray(1); + * // => [] + * + * _.toArray(null); + * // => [] + */ + function toArray(value) { + if (!isArrayLike(value)) { + return values(value); + } + return value.length ? copyArray(value) : []; + } + + /** + * Converts `value` to an integer. + * + * **Note:** This method is loosely based on + * [`ToInteger`](http://www.ecma-international.org/ecma-262/7.0/#sec-tointeger). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to convert. + * @returns {number} Returns the converted integer. + * @example + * + * _.toInteger(3.2); + * // => 3 + * + * _.toInteger(Number.MIN_VALUE); + * // => 0 + * + * _.toInteger(Infinity); + * // => 1.7976931348623157e+308 + * + * _.toInteger('3.2'); + * // => 3 + */ + var toInteger = Number; + + /** + * Converts `value` to a number. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to process. + * @returns {number} Returns the number. + * @example + * + * _.toNumber(3.2); + * // => 3.2 + * + * _.toNumber(Number.MIN_VALUE); + * // => 5e-324 + * + * _.toNumber(Infinity); + * // => Infinity + * + * _.toNumber('3.2'); + * // => 3.2 + */ + var toNumber = Number; + + /** + * Converts `value` to a string. An empty string is returned for `null` + * and `undefined` values. The sign of `-0` is preserved. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to convert. + * @returns {string} Returns the converted string. + * @example + * + * _.toString(null); + * // => '' + * + * _.toString(-0); + * // => '-0' + * + * _.toString([1, 2, 3]); + * // => '1,2,3' + */ + function toString(value) { + if (typeof value == 'string') { + return value; + } + return value == null ? '' : (value + ''); + } + + /*------------------------------------------------------------------------*/ + + /** + * Assigns own enumerable string keyed properties of source objects to the + * destination object. Source objects are applied from left to right. + * Subsequent sources overwrite property assignments of previous sources. + * + * **Note:** This method mutates `object` and is loosely based on + * [`Object.assign`](https://mdn.io/Object/assign). + * + * @static + * @memberOf _ + * @since 0.10.0 + * @category Object + * @param {Object} object The destination object. + * @param {...Object} [sources] The source objects. + * @returns {Object} Returns `object`. + * @see _.assignIn + * @example + * + * function Foo() { + * this.a = 1; + * } + * + * function Bar() { + * this.c = 3; + * } + * + * Foo.prototype.b = 2; + * Bar.prototype.d = 4; + * + * _.assign({ 'a': 0 }, new Foo, new Bar); + * // => { 'a': 1, 'c': 3 } + */ + var assign = createAssigner(function(object, source) { + copyObject(source, nativeKeys(source), object); + }); + + /** + * This method is like `_.assign` except that it iterates over own and + * inherited source properties. + * + * **Note:** This method mutates `object`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @alias extend + * @category Object + * @param {Object} object The destination object. + * @param {...Object} [sources] The source objects. + * @returns {Object} Returns `object`. + * @see _.assign + * @example + * + * function Foo() { + * this.a = 1; + * } + * + * function Bar() { + * this.c = 3; + * } + * + * Foo.prototype.b = 2; + * Bar.prototype.d = 4; + * + * _.assignIn({ 'a': 0 }, new Foo, new Bar); + * // => { 'a': 1, 'b': 2, 'c': 3, 'd': 4 } + */ + var assignIn = createAssigner(function(object, source) { + copyObject(source, nativeKeysIn(source), object); + }); + + /** + * Creates an object that inherits from the `prototype` object. If a + * `properties` object is given, its own enumerable string keyed properties + * are assigned to the created object. + * + * @static + * @memberOf _ + * @since 2.3.0 + * @category Object + * @param {Object} prototype The object to inherit from. + * @param {Object} [properties] The properties to assign to the object. + * @returns {Object} Returns the new object. + * @example + * + * function Shape() { + * this.x = 0; + * this.y = 0; + * } + * + * function Circle() { + * Shape.call(this); + * } + * + * Circle.prototype = _.create(Shape.prototype, { + * 'constructor': Circle + * }); + * + * var circle = new Circle; + * circle instanceof Circle; + * // => true + * + * circle instanceof Shape; + * // => true + */ + function create(prototype, properties) { + var result = baseCreate(prototype); + return properties == null ? result : assign(result, properties); + } + + /** + * Assigns own and inherited enumerable string keyed properties of source + * objects to the destination object for all destination properties that + * resolve to `undefined`. Source objects are applied from left to right. + * Once a property is set, additional values of the same property are ignored. + * + * **Note:** This method mutates `object`. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Object + * @param {Object} object The destination object. + * @param {...Object} [sources] The source objects. + * @returns {Object} Returns `object`. + * @see _.defaultsDeep + * @example + * + * _.defaults({ 'a': 1 }, { 'b': 2 }, { 'a': 3 }); + * // => { 'a': 1, 'b': 2 } + */ + var defaults = baseRest(function(object, sources) { + object = Object(object); + + var index = -1; + var length = sources.length; + var guard = length > 2 ? sources[2] : undefined; + + if (guard && isIterateeCall(sources[0], sources[1], guard)) { + length = 1; + } + + while (++index < length) { + var source = sources[index]; + var props = keysIn(source); + var propsIndex = -1; + var propsLength = props.length; + + while (++propsIndex < propsLength) { + var key = props[propsIndex]; + var value = object[key]; + + if (value === undefined || + (eq(value, objectProto[key]) && !hasOwnProperty.call(object, key))) { + object[key] = source[key]; + } + } + } + + return object; + }); + + /** + * Checks if `path` is a direct property of `object`. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Object + * @param {Object} object The object to query. + * @param {Array|string} path The path to check. + * @returns {boolean} Returns `true` if `path` exists, else `false`. + * @example + * + * var object = { 'a': { 'b': 2 } }; + * var other = _.create({ 'a': _.create({ 'b': 2 }) }); + * + * _.has(object, 'a'); + * // => true + * + * _.has(object, 'a.b'); + * // => true + * + * _.has(object, ['a', 'b']); + * // => true + * + * _.has(other, 'a'); + * // => false + */ + function has(object, path) { + return object != null && hasOwnProperty.call(object, path); + } + + /** + * Creates an array of the own enumerable property names of `object`. + * + * **Note:** Non-object values are coerced to objects. See the + * [ES spec](http://ecma-international.org/ecma-262/7.0/#sec-object.keys) + * for more details. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Object + * @param {Object} object The object to query. + * @returns {Array} Returns the array of property names. + * @example + * + * function Foo() { + * this.a = 1; + * this.b = 2; + * } + * + * Foo.prototype.c = 3; + * + * _.keys(new Foo); + * // => ['a', 'b'] (iteration order is not guaranteed) + * + * _.keys('hi'); + * // => ['0', '1'] + */ + var keys = nativeKeys; + + /** + * Creates an array of the own and inherited enumerable property names of `object`. + * + * **Note:** Non-object values are coerced to objects. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Object + * @param {Object} object The object to query. + * @returns {Array} Returns the array of property names. + * @example + * + * function Foo() { + * this.a = 1; + * this.b = 2; + * } + * + * Foo.prototype.c = 3; + * + * _.keysIn(new Foo); + * // => ['a', 'b', 'c'] (iteration order is not guaranteed) + */ + var keysIn = nativeKeysIn; + + /** + * Creates an object composed of the picked `object` properties. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Object + * @param {Object} object The source object. + * @param {...(string|string[])} [paths] The property paths to pick. + * @returns {Object} Returns the new object. + * @example + * + * var object = { 'a': 1, 'b': '2', 'c': 3 }; + * + * _.pick(object, ['a', 'c']); + * // => { 'a': 1, 'c': 3 } + */ + var pick = flatRest(function(object, paths) { + return object == null ? {} : basePick(object, paths); + }); + + /** + * This method is like `_.get` except that if the resolved value is a + * function it's invoked with the `this` binding of its parent object and + * its result is returned. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Object + * @param {Object} object The object to query. + * @param {Array|string} path The path of the property to resolve. + * @param {*} [defaultValue] The value returned for `undefined` resolved values. + * @returns {*} Returns the resolved value. + * @example + * + * var object = { 'a': [{ 'b': { 'c1': 3, 'c2': _.constant(4) } }] }; + * + * _.result(object, 'a[0].b.c1'); + * // => 3 + * + * _.result(object, 'a[0].b.c2'); + * // => 4 + * + * _.result(object, 'a[0].b.c3', 'default'); + * // => 'default' + * + * _.result(object, 'a[0].b.c3', _.constant('default')); + * // => 'default' + */ + function result(object, path, defaultValue) { + var value = object == null ? undefined : object[path]; + if (value === undefined) { + value = defaultValue; + } + return isFunction(value) ? value.call(object) : value; + } + + /** + * Creates an array of the own enumerable string keyed property values of `object`. + * + * **Note:** Non-object values are coerced to objects. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Object + * @param {Object} object The object to query. + * @returns {Array} Returns the array of property values. + * @example + * + * function Foo() { + * this.a = 1; + * this.b = 2; + * } + * + * Foo.prototype.c = 3; + * + * _.values(new Foo); + * // => [1, 2] (iteration order is not guaranteed) + * + * _.values('hi'); + * // => ['h', 'i'] + */ + function values(object) { + return object == null ? [] : baseValues(object, keys(object)); + } + + /*------------------------------------------------------------------------*/ + + /** + * Converts the characters "&", "<", ">", '"', and "'" in `string` to their + * corresponding HTML entities. + * + * **Note:** No other characters are escaped. To escape additional + * characters use a third-party library like [_he_](https://mths.be/he). + * + * Though the ">" character is escaped for symmetry, characters like + * ">" and "/" don't need escaping in HTML and have no special meaning + * unless they're part of a tag or unquoted attribute value. See + * [Mathias Bynens's article](https://mathiasbynens.be/notes/ambiguous-ampersands) + * (under "semi-related fun fact") for more details. + * + * When working with HTML you should always + * [quote attribute values](http://wonko.com/post/html-escaping) to reduce + * XSS vectors. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category String + * @param {string} [string=''] The string to escape. + * @returns {string} Returns the escaped string. + * @example + * + * _.escape('fred, barney, & pebbles'); + * // => 'fred, barney, & pebbles' + */ + function escape(string) { + string = toString(string); + return (string && reHasUnescapedHtml.test(string)) + ? string.replace(reUnescapedHtml, escapeHtmlChar) + : string; + } + + /*------------------------------------------------------------------------*/ + + /** + * This method returns the first argument it receives. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Util + * @param {*} value Any value. + * @returns {*} Returns `value`. + * @example + * + * var object = { 'a': 1 }; + * + * console.log(_.identity(object) === object); + * // => true + */ + function identity(value) { + return value; + } + + /** + * Creates a function that invokes `func` with the arguments of the created + * function. If `func` is a property name, the created function returns the + * property value for a given element. If `func` is an array or object, the + * created function returns `true` for elements that contain the equivalent + * source properties, otherwise it returns `false`. + * + * @static + * @since 4.0.0 + * @memberOf _ + * @category Util + * @param {*} [func=_.identity] The value to convert to a callback. + * @returns {Function} Returns the callback. + * @example + * + * var users = [ + * { 'user': 'barney', 'age': 36, 'active': true }, + * { 'user': 'fred', 'age': 40, 'active': false } + * ]; + * + * // The `_.matches` iteratee shorthand. + * _.filter(users, _.iteratee({ 'user': 'barney', 'active': true })); + * // => [{ 'user': 'barney', 'age': 36, 'active': true }] + * + * // The `_.matchesProperty` iteratee shorthand. + * _.filter(users, _.iteratee(['user', 'fred'])); + * // => [{ 'user': 'fred', 'age': 40 }] + * + * // The `_.property` iteratee shorthand. + * _.map(users, _.iteratee('user')); + * // => ['barney', 'fred'] + * + * // Create custom iteratee shorthands. + * _.iteratee = _.wrap(_.iteratee, function(iteratee, func) { + * return !_.isRegExp(func) ? iteratee(func) : function(string) { + * return func.test(string); + * }; + * }); + * + * _.filter(['abc', 'def'], /ef/); + * // => ['def'] + */ + var iteratee = baseIteratee; + + /** + * Creates a function that performs a partial deep comparison between a given + * object and `source`, returning `true` if the given object has equivalent + * property values, else `false`. + * + * **Note:** The created function is equivalent to `_.isMatch` with `source` + * partially applied. + * + * Partial comparisons will match empty array and empty object `source` + * values against any array or object value, respectively. See `_.isEqual` + * for a list of supported value comparisons. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Util + * @param {Object} source The object of property values to match. + * @returns {Function} Returns the new spec function. + * @example + * + * var objects = [ + * { 'a': 1, 'b': 2, 'c': 3 }, + * { 'a': 4, 'b': 5, 'c': 6 } + * ]; + * + * _.filter(objects, _.matches({ 'a': 4, 'c': 6 })); + * // => [{ 'a': 4, 'b': 5, 'c': 6 }] + */ + function matches(source) { + return baseMatches(assign({}, source)); + } + + /** + * Adds all own enumerable string keyed function properties of a source + * object to the destination object. If `object` is a function, then methods + * are added to its prototype as well. + * + * **Note:** Use `_.runInContext` to create a pristine `lodash` function to + * avoid conflicts caused by modifying the original. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Util + * @param {Function|Object} [object=lodash] The destination object. + * @param {Object} source The object of functions to add. + * @param {Object} [options={}] The options object. + * @param {boolean} [options.chain=true] Specify whether mixins are chainable. + * @returns {Function|Object} Returns `object`. + * @example + * + * function vowels(string) { + * return _.filter(string, function(v) { + * return /[aeiou]/i.test(v); + * }); + * } + * + * _.mixin({ 'vowels': vowels }); + * _.vowels('fred'); + * // => ['e'] + * + * _('fred').vowels().value(); + * // => ['e'] + * + * _.mixin({ 'vowels': vowels }, { 'chain': false }); + * _('fred').vowels(); + * // => ['e'] + */ + function mixin(object, source, options) { + var props = keys(source), + methodNames = baseFunctions(source, props); + + if (options == null && + !(isObject(source) && (methodNames.length || !props.length))) { + options = source; + source = object; + object = this; + methodNames = baseFunctions(source, keys(source)); + } + var chain = !(isObject(options) && 'chain' in options) || !!options.chain, + isFunc = isFunction(object); + + baseEach(methodNames, function(methodName) { + var func = source[methodName]; + object[methodName] = func; + if (isFunc) { + object.prototype[methodName] = function() { + var chainAll = this.__chain__; + if (chain || chainAll) { + var result = object(this.__wrapped__), + actions = result.__actions__ = copyArray(this.__actions__); + + actions.push({ 'func': func, 'args': arguments, 'thisArg': object }); + result.__chain__ = chainAll; + return result; + } + return func.apply(object, arrayPush([this.value()], arguments)); + }; + } + }); + + return object; + } + + /** + * Reverts the `_` variable to its previous value and returns a reference to + * the `lodash` function. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Util + * @returns {Function} Returns the `lodash` function. + * @example + * + * var lodash = _.noConflict(); + */ + function noConflict() { + if (root._ === this) { + root._ = oldDash; + } + return this; + } + + /** + * This method returns `undefined`. + * + * @static + * @memberOf _ + * @since 2.3.0 + * @category Util + * @example + * + * _.times(2, _.noop); + * // => [undefined, undefined] + */ + function noop() { + // No operation performed. + } + + /** + * Generates a unique ID. If `prefix` is given, the ID is appended to it. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Util + * @param {string} [prefix=''] The value to prefix the ID with. + * @returns {string} Returns the unique ID. + * @example + * + * _.uniqueId('contact_'); + * // => 'contact_104' + * + * _.uniqueId(); + * // => '105' + */ + function uniqueId(prefix) { + var id = ++idCounter; + return toString(prefix) + id; + } + + /*------------------------------------------------------------------------*/ + + /** + * Computes the maximum value of `array`. If `array` is empty or falsey, + * `undefined` is returned. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Math + * @param {Array} array The array to iterate over. + * @returns {*} Returns the maximum value. + * @example + * + * _.max([4, 2, 8, 6]); + * // => 8 + * + * _.max([]); + * // => undefined + */ + function max(array) { + return (array && array.length) + ? baseExtremum(array, identity, baseGt) + : undefined; + } + + /** + * Computes the minimum value of `array`. If `array` is empty or falsey, + * `undefined` is returned. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Math + * @param {Array} array The array to iterate over. + * @returns {*} Returns the minimum value. + * @example + * + * _.min([4, 2, 8, 6]); + * // => 2 + * + * _.min([]); + * // => undefined + */ + function min(array) { + return (array && array.length) + ? baseExtremum(array, identity, baseLt) + : undefined; + } + + /*------------------------------------------------------------------------*/ + + // Add methods that return wrapped values in chain sequences. + lodash.assignIn = assignIn; + lodash.before = before; + lodash.bind = bind; + lodash.chain = chain; + lodash.compact = compact; + lodash.concat = concat; + lodash.create = create; + lodash.defaults = defaults; + lodash.defer = defer; + lodash.delay = delay; + lodash.filter = filter; + lodash.flatten = flatten; + lodash.flattenDeep = flattenDeep; + lodash.iteratee = iteratee; + lodash.keys = keys; + lodash.map = map; + lodash.matches = matches; + lodash.mixin = mixin; + lodash.negate = negate; + lodash.once = once; + lodash.pick = pick; + lodash.slice = slice; + lodash.sortBy = sortBy; + lodash.tap = tap; + lodash.thru = thru; + lodash.toArray = toArray; + lodash.values = values; + + // Add aliases. + lodash.extend = assignIn; + + // Add methods to `lodash.prototype`. + mixin(lodash, lodash); + + /*------------------------------------------------------------------------*/ + + // Add methods that return unwrapped values in chain sequences. + lodash.clone = clone; + lodash.escape = escape; + lodash.every = every; + lodash.find = find; + lodash.forEach = forEach; + lodash.has = has; + lodash.head = head; + lodash.identity = identity; + lodash.indexOf = indexOf; + lodash.isArguments = isArguments; + lodash.isArray = isArray; + lodash.isBoolean = isBoolean; + lodash.isDate = isDate; + lodash.isEmpty = isEmpty; + lodash.isEqual = isEqual; + lodash.isFinite = isFinite; + lodash.isFunction = isFunction; + lodash.isNaN = isNaN; + lodash.isNull = isNull; + lodash.isNumber = isNumber; + lodash.isObject = isObject; + lodash.isRegExp = isRegExp; + lodash.isString = isString; + lodash.isUndefined = isUndefined; + lodash.last = last; + lodash.max = max; + lodash.min = min; + lodash.noConflict = noConflict; + lodash.noop = noop; + lodash.reduce = reduce; + lodash.result = result; + lodash.size = size; + lodash.some = some; + lodash.uniqueId = uniqueId; + + // Add aliases. + lodash.each = forEach; + lodash.first = head; + + mixin(lodash, (function() { + var source = {}; + baseForOwn(lodash, function(func, methodName) { + if (!hasOwnProperty.call(lodash.prototype, methodName)) { + source[methodName] = func; + } + }); + return source; + }()), { 'chain': false }); + + /*------------------------------------------------------------------------*/ + + /** + * The semantic version number. + * + * @static + * @memberOf _ + * @type {string} + */ + lodash.VERSION = VERSION; + + // Add `Array` methods to `lodash.prototype`. + baseEach(['pop', 'join', 'replace', 'reverse', 'split', 'push', 'shift', 'sort', 'splice', 'unshift'], function(methodName) { + var func = (/^(?:replace|split)$/.test(methodName) ? String.prototype : arrayProto)[methodName], + chainName = /^(?:push|sort|unshift)$/.test(methodName) ? 'tap' : 'thru', + retUnwrapped = /^(?:pop|join|replace|shift)$/.test(methodName); + + lodash.prototype[methodName] = function() { + var args = arguments; + if (retUnwrapped && !this.__chain__) { + var value = this.value(); + return func.apply(isArray(value) ? value : [], args); + } + return this[chainName](function(value) { + return func.apply(isArray(value) ? value : [], args); + }); + }; + }); + + // Add chain sequence methods to the `lodash` wrapper. + lodash.prototype.toJSON = lodash.prototype.valueOf = lodash.prototype.value = wrapperValue; + + /*--------------------------------------------------------------------------*/ + + // Some AMD build optimizers, like r.js, check for condition patterns like: + if (true) { + // Expose Lodash on the global object to prevent errors when Lodash is + // loaded by a script tag in the presence of an AMD loader. + // See http://requirejs.org/docs/errors.html#mismatch for more details. + // Use `_.noConflict` to remove Lodash from the global object. + root._ = lodash; + + // Define as an anonymous module so, through path mapping, it can be + // referenced as the "underscore" module. + !(__WEBPACK_AMD_DEFINE_RESULT__ = function() { + return lodash; + }.call(exports, __webpack_require__, exports, module), __WEBPACK_AMD_DEFINE_RESULT__ !== undefined && (module.exports = __WEBPACK_AMD_DEFINE_RESULT__)); + } + // Check for `exports` after `define` in case a build optimizer adds it. + else if (freeModule) { + // Export for Node.js. + (freeModule.exports = lodash)._ = lodash; + // Export for CommonJS support. + freeExports._ = lodash; + } + else { + // Export to the global object. + root._ = lodash; + } + }.call(this)); + + /* WEBPACK VAR INJECTION */}.call(exports, (function() { return this; }()), __webpack_require__(59)(module))) + +/***/ }), +/* 59 */ +/***/ (function(module, exports) { + + module.exports = function(module) { + if(!module.webpackPolyfill) { + module.deprecate = function() {}; + module.paths = []; + // module.parent = undefined by default + module.children = []; + module.webpackPolyfill = 1; + } + return module; + } + + +/***/ }), +/* 60 */ +/***/ (function(module, exports, __webpack_require__) { + + var ArrowLink = __webpack_require__(61); + var BoxArrowLink = __webpack_require__(22); + var PlainLink = __webpack_require__(23); + var OwlDisjointWith = __webpack_require__(46); + var SetOperatorProperty = __webpack_require__(56); + + /** + * Stores the passed properties in links. + * @returns {Function} + */ + module.exports = (function (){ + var linkCreator = {}; + + /** + * Creates links from the passed properties. + * @param properties + */ + linkCreator.createLinks = function ( properties ){ + var links = groupPropertiesToLinks(properties); + + for ( var i = 0, l = links.length; i < l; i++ ) { + var link = links[i]; + + countAndSetLayers(link, links); + countAndSetLoops(link, links); + } + + return links; + }; + + /** + * Creates links of properties and - if existing - their inverses. + * @param properties the properties + * @returns {Array} + */ + function groupPropertiesToLinks( properties ){ + var links = [], + property, + addedProperties = __webpack_require__(62)(); + + for ( var i = 0, l = properties.length; i < l; i++ ) { + property = properties[i]; + + if ( !addedProperties.has(property) ) { + var link = createLink(property); + + property.link(link); + if ( property.inverse() ) { + property.inverse().link(link); + } + + links.push(link); + + addedProperties.add(property); + if ( property.inverse() ) { + addedProperties.add(property.inverse()); + } + } + } + + return links; + } + + function countAndSetLayers( link, allLinks ){ + var layer, + layers, + i, l; + + if ( typeof link.layers() === "undefined" ) { + layers = []; + + // Search for other links that are another layer + for ( i = 0, l = allLinks.length; i < l; i++ ) { + var otherLink = allLinks[i]; + if ( link.domain() === otherLink.domain() && link.range() === otherLink.range() || + link.domain() === otherLink.range() && link.range() === otherLink.domain() ) { + layers.push(otherLink); + } + } + + // Set the results on each of the layers + for ( i = 0, l = layers.length; i < l; ++i ) { + layer = layers[i]; + + layer.layerIndex(i); + layer.layers(layers); + } + } + } + + function countAndSetLoops( link, allLinks ){ + var loop, + loops, + i, l; + + if ( typeof link.loops() === "undefined" ) { + loops = []; + + // Search for other links that are also loops of the same node + for ( i = 0, l = allLinks.length; i < l; i++ ) { + var otherLink = allLinks[i]; + if ( link.domain() === otherLink.domain() && link.domain() === otherLink.range() ) { + loops.push(otherLink); + } + } + + // Set the results on each of the loops + for ( i = 0, l = loops.length; i < l; ++i ) { + loop = loops[i]; + + loop.loopIndex(i); + loop.loops(loops); + } + } + } + + function createLink( property ){ + var domain = property.domain(); + var range = property.range(); + + if ( property instanceof OwlDisjointWith ) { + return new PlainLink(domain, range, property); + } else if ( property instanceof SetOperatorProperty ) { + return new BoxArrowLink(domain, range, property); + } + return new ArrowLink(domain, range, property); + } + + return function (){ + // Return a function to keep module interfaces consistent + return linkCreator; + }; + })(); + + +/***/ }), +/* 61 */ +/***/ (function(module, exports, __webpack_require__) { + + var PlainLink = __webpack_require__(23); + + + module.exports = ArrowLink; + + function ArrowLink( domain, range, property ){ + PlainLink.apply(this, arguments); + } + + ArrowLink.prototype = Object.create(PlainLink.prototype); + ArrowLink.prototype.constructor = ArrowLink; + + + ArrowLink.prototype.draw = function ( linkGroup, markerContainer ){ + var property = this.label().property(); + var inverse = this.label().inverse(); + + createPropertyMarker(markerContainer, property); + if ( inverse ) { + createInverseMarker(markerContainer, inverse); + } + + PlainLink.prototype.draw.apply(this, arguments); + + // attach the markers to the link + linkGroup.attr("marker-end", "url(#" + property.markerId() + ")"); + if ( inverse ) { + linkGroup.attr("marker-start", "url(#" + inverse.markerId() + ")"); + } + }; + + function createPropertyMarker( markerContainer, property ){ + var marker = appendBasicMarker(markerContainer, property); + //marker.attr("refX", 12); + var m1X = -12; + var m1Y = 8; + var m2X = -12; + var m2Y = -8; + marker.append("path") + //.attr("d", "M0,-8L12,0L0,8Z") + .attr("d", "M0,0L " + m1X + "," + m1Y + "L" + m2X + "," + m2Y + "L" + 0 + "," + 0) + .classed(property.markerType(), true); + + property.markerElement(marker); + } + + function createInverseMarker( markerContainer, inverse ){ + var m1X = -12; + var m1Y = 8; + var m2X = -12; + var m2Y = -8; + var inverseMarker = appendBasicMarker(markerContainer, inverse); + inverseMarker.append("path") + //.attr("d", "M12,-8L0,0L12,8Z") + .attr("d", "M0,0L " + -m1X + "," + -m1Y + "L" + -m2X + "," + -m2Y + "L" + 0 + "," + 0) + .classed(inverse.markerType(), true); + + inverse.markerElement(inverseMarker); + } + + function appendBasicMarker( markerContainer, property ){ + return markerContainer.append("marker") + .datum(property) + .attr("id", property.markerId()) + + .attr("viewBox", "-14 -10 28 20") + .attr("markerWidth", 10) + .attr("markerHeight", 10) + //.attr("markerUnits", "userSpaceOnUse") + .attr("orient", "auto"); + } + + +/***/ }), +/* 62 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * A simple incomplete encapsulation of the d3 set, which is able to store webvowl + * elements by using their id. + */ + module.exports = function ( array ){ + + var set = {}, + d3Set = d3.set(array); + + set.has = function ( webvowlElement ){ + return d3Set.has(webvowlElement.id()); + }; + + set.add = function ( webvowlElement ){ + return d3Set.add(webvowlElement.id()); + }; + + set.remove = function ( webvowlElement ){ + return d3Set.remove(webvowlElement.id()); + }; + + set.empty = function (){ + return d3Set.empty(); + }; + + set.size = function (){ + return d3Set.size(); + }; + + return set; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 63 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + var BaseNode = __webpack_require__(9); + var DatatypeNode = __webpack_require__(35); + var Thing = __webpack_require__(31); + var ObjectProperty = __webpack_require__(50); + var DatatypeProperty = __webpack_require__(44); + var RdfsSubClassOf = __webpack_require__(55); + var Label = __webpack_require__(24); + + + var tools = {}; + module.exports = function (){ + return tools; + }; + + tools.isLabel = function ( element ){ + return element instanceof Label; + }; + + tools.isNode = function ( element ){ + return element instanceof BaseNode; + }; + + tools.isDatatype = function ( node ){ + return node instanceof DatatypeNode; + }; + + tools.isThing = function ( node ){ + return node instanceof Thing; + }; + + tools.isProperty = function ( element ){ + return element instanceof BaseProperty; + }; + + tools.isObjectProperty = function ( element ){ + return element instanceof ObjectProperty; + }; + + tools.isDatatypeProperty = function ( element ){ + return element instanceof DatatypeProperty; + }; + + tools.isRdfsSubClassOf = function ( property ){ + return property instanceof RdfsSubClassOf; + }; + + +/***/ }), +/* 64 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function (){ + var options = {}, + data, + graphContainerSelector, + classDistance = 200, + datatypeDistance = 120, + loopDistance = 150, + charge = -500, + gravity = 0.025, + linkStrength = 1, + height = 600, + width = 800, + selectionModules = [], + filterModules = [], + minMagnification = 0.01, + maxMagnification = 4, + compactNotation = false, + dynamicLabelWidth = true, + // some filters + literalFilter, + // menus + gravityMenu, + filterMenu, + loadingModule, + modeMenu, + pausedMenu, + pickAndPinModule, + resetMenu, + searchMenu, + ontologyMenu, + sidebar, + leftSidebar, + editSidebar, + navigationMenu, + exportMenu, + graphObject, + zoomSlider, + datatypeFilter, + focuserModule, + colorExternalsModule, + compactNotationModule, + objectPropertyFilter, + subclassFilter, + setOperatorFilter, + maxLabelWidth = 120, + metadataObject = {}, + generalOntologyMetaData = {}, + disjointPropertyFilter, + rectangularRep = false, + warningModule, + prefixModule, + drawPropertyDraggerOnHover = true, + showDraggerObject = false, + directInputModule, + scaleNodesByIndividuals = true, + useAccuracyHelper = true, + showRenderingStatistic = true, + showInputModality = false, + hideDebugOptions = true, + nodeDegreeFilter, + debugMenu, + + supportedDatatypes = ["rdfs:Literal", "xsd:boolean", "xsd:double", "xsd:integer", "xsd:string", "undefined"], + supportedClasses = ["owl:Thing", "owl:Class", "owl:DeprecatedClass"], + supportedProperties = ["owl:objectProperty", + "rdfs:subClassOf", + "owl:disjointWith", + "owl:allValuesFrom", + "owl:someValuesFrom" + ], + prefixList = { + rdf: 'http://www.w3.org/1999/02/22-rdf-syntax-ns#', + rdfs: 'http://www.w3.org/2000/01/rdf-schema#', + owl: 'http://www.w3.org/2002/07/owl#', + xsd: 'http://www.w3.org/2001/XMLSchema#', + dc: 'http://purl.org/dc/elements/1.1/#', + xml: 'http://www.w3.org/XML/1998/namespace' + }; + + options.clearMetaObject = function (){ + generalOntologyMetaData = {}; + }; + options.clearGeneralMetaObject = function (){ + generalOntologyMetaData = {}; + }; + + options.debugMenu = function ( val ){ + if ( !arguments.length ) return debugMenu; + debugMenu = val; + }; + + options.getHideDebugFeatures = function (){ + return hideDebugOptions; + }; + options.executeHiddenDebugFeatuers = function (){ + hideDebugOptions = !hideDebugOptions; + d3.selectAll(".debugOption").classed("hidden", hideDebugOptions); + if ( hideDebugOptions === false ) { + graphObject.setForceTickFunctionWithFPS(); + } + else { + graphObject.setDefaultForceTickFunction(); + } + if ( debugMenu ) { + debugMenu.updateSettings(); + } + options.setHideDebugFeaturesForDefaultObject(hideDebugOptions); + }; + + + options.addOrUpdateGeneralObjectEntry = function ( property, value ){ + if ( generalOntologyMetaData.hasOwnProperty(property) ) { + //console.log("Updating Property:"+ property); + if ( property === "iri" ) { + if ( validURL(value) === false ) { + warningModule.showWarning("Invalid Ontology IRI", "Input IRI does not represent an URL", "Restoring previous IRI for ontology", 1, false); + return false; + } + } + generalOntologyMetaData[property] = value; + } else { + generalOntologyMetaData[property] = value; + } + return true; + }; + + options.getGeneralMetaObjectProperty = function ( property ){ + if ( generalOntologyMetaData.hasOwnProperty(property) ) { + return generalOntologyMetaData[property]; + } + }; + + options.getGeneralMetaObject = function (){ + return generalOntologyMetaData; + }; + + options.addOrUpdateMetaObjectEntry = function ( property, value ){ + + if ( metadataObject.hasOwnProperty(property) ) { + metadataObject[property] = value; + } else { + metadataObject[property] = value; + } + }; + + options.getMetaObjectProperty = function ( property ){ + if ( metadataObject.hasOwnProperty(property) ) { + return metadataObject[property]; + } + }; + options.getMetaObject = function (){ + return metadataObject; + }; + + + options.prefixList = function (){ + return prefixList; + }; + options.addPrefix = function ( prefix, url ){ + prefixList[prefix] = url; + }; + + function validURL( str ){ + var urlregex = /^(https?|ftp):\/\/([a-zA-Z0-9.-]+(:[a-zA-Z0-9.&%$-]+)*@)*((25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9][0-9]?)(\.(25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9]?[0-9])){3}|([a-zA-Z0-9-]+\.)*[a-zA-Z0-9-]+\.(com|edu|gov|int|mil|net|org|biz|arpa|info|name|pro|aero|coop|museum|[a-zA-Z]{2}))(:[0-9]+)*(\/($|[a-zA-Z0-9.,?'\\+&%$#=~_-]+))*$/; + return urlregex.test(str); + } + + options.updatePrefix = function ( oldPrefix, newPrefix, oldURL, newURL ){ + if ( oldPrefix === newPrefix && oldURL === newURL ) { + // console.log("Nothing to update"); + return true; + } + if ( oldPrefix === newPrefix && oldURL !== newURL && validURL(newURL) === true ) { + // console.log("Update URL"); + prefixList[oldPrefix] = newURL; + } else if ( oldPrefix === newPrefix && oldURL !== newURL && validURL(newURL) === false ) { + if ( validURL(newURL) === false ) { + warningModule.showWarning("Invalid Prefix IRI", "Input IRI does not represent an IRI", "You should enter a valid IRI in form of a URL", 1, false); + return false; + } + + return false; + } + if ( oldPrefix !== newPrefix && validURL(newURL) === true ) { + + // sanity check + if ( prefixList.hasOwnProperty(newPrefix) ) { + // console.log("Already have this prefix!"); + warningModule.showWarning("Prefix Already Exist", "Prefix: " + newPrefix + " is already defined", "You should use an other one", 1, false); + return false; + } + options.removePrefix(oldPrefix); + options.addPrefix(newPrefix, newURL); + editSidebar.updateEditDeleteButtonIds(oldPrefix, newPrefix); + return true; + } + + // console.log("Is new URL ("+newURL+") valid? >> "+validURL(newURL)); + if ( validURL(newURL) === false ) { + warningModule.showWarning("Invalid Prefix IRI", "Input IRI does not represent an URL", "You should enter a valid URL", 1, false); + + } + return false; + }; + + options.removePrefix = function ( prefix ){ + delete prefixList[prefix]; + }; + + + options.supportedDatatypes = function (){ + return supportedDatatypes; + }; + options.supportedClasses = function (){ + return supportedClasses; + }; + options.supportedProperties = function (){ + return supportedProperties; + }; + + options.datatypeFilter = function ( val ){ + if ( !arguments.length ) return datatypeFilter; + datatypeFilter = val; + }; + + options.showDraggerObject = function ( val ){ + if ( !arguments.length ) { + return showDraggerObject; + } + showDraggerObject = val; + }; + options.useAccuracyHelper = function ( val ){ + if ( !arguments.length ) { + return useAccuracyHelper; + } + useAccuracyHelper = val; + }; + options.showAccuracyHelper = function ( val ){ + if ( !arguments.length ) { + return options.showDraggerObject(); + } + options.showDraggerObject(val); + }; + options.showRenderingStatistic = function ( val ){ + if ( !arguments.length ) { + return showRenderingStatistic; + } + showRenderingStatistic = val; + }; + options.showInputModality = function ( val ){ + if ( !arguments.length ) { + return showInputModality; + } + showInputModality = val; + }; + + options.drawPropertyDraggerOnHover = function ( val ){ + if ( !arguments.length ) return drawPropertyDraggerOnHover; + drawPropertyDraggerOnHover = val; + }; + + options.warningModule = function ( val ){ + if ( !arguments.length ) return warningModule; + warningModule = val; + }; + options.directInputModule = function ( val ){ + if ( !arguments.length ) return directInputModule; + directInputModule = val; + }; + options.prefixModule = function ( val ){ + if ( !arguments.length ) return prefixModule; + prefixModule = val; + }; + + options.focuserModule = function ( val ){ + if ( !arguments.length ) return focuserModule; + focuserModule = val; + }; + options.colorExternalsModule = function ( val ){ + if ( !arguments.length ) return colorExternalsModule; + colorExternalsModule = val; + }; + options.compactNotationModule = function ( val ){ + if ( !arguments.length ) return compactNotationModule; + compactNotationModule = val; + }; + + options.maxLabelWidth = function ( val ){ + if ( !arguments.length ) return maxLabelWidth; + maxLabelWidth = val; + }; + options.objectPropertyFilter = function ( val ){ + if ( !arguments.length ) return objectPropertyFilter; + objectPropertyFilter = val; + }; + options.disjointPropertyFilter = function ( val ){ + if ( !arguments.length ) return disjointPropertyFilter; + disjointPropertyFilter = val; + }; + options.subclassFilter = function ( val ){ + if ( !arguments.length ) return subclassFilter; + subclassFilter = val; + }; + options.setOperatorFilter = function ( val ){ + if ( !arguments.length ) return setOperatorFilter; + setOperatorFilter = val; + }; + options.leftSidebar = function ( val ){ + if ( !arguments.length ) return leftSidebar; + leftSidebar = val; + }; + options.editSidebar = function ( val ){ + if ( !arguments.length ) return editSidebar; + editSidebar = val; + }; + + options.zoomSlider = function ( val ){ + if ( !arguments.length ) return zoomSlider; + zoomSlider = val; + }; + + options.graphObject = function ( val ){ + if ( !arguments.length ) return graphObject; + graphObject = val; + }; + + + var defaultOptionsConfig = {}; + defaultOptionsConfig.sidebar = "1"; + defaultOptionsConfig.doc = -1; + defaultOptionsConfig.cd = 200; + defaultOptionsConfig.dd = 120; + defaultOptionsConfig.editorMode = "false"; + defaultOptionsConfig.filter_datatypes = "false"; + defaultOptionsConfig.filter_objectProperties = "false"; + defaultOptionsConfig.filter_sco = "false"; + defaultOptionsConfig.filter_disjoint = "true"; + defaultOptionsConfig.filter_setOperator = "false"; + defaultOptionsConfig.mode_dynamic = "true"; + defaultOptionsConfig.mode_scaling = "true"; + defaultOptionsConfig.mode_compact = "false"; + defaultOptionsConfig.mode_colorExt = "true"; + defaultOptionsConfig.mode_multiColor = "false"; + defaultOptionsConfig.debugFeatures = "false"; + defaultOptionsConfig.rect = 0; + + + options.initialConfig = function (){ + var initCfg = {}; + initCfg.sidebar = "1"; + initCfg.doc = -1; + initCfg.cd = 200; + initCfg.dd = 120; + initCfg.editorMode = "false"; + initCfg.filter_datatypes = "false"; + initCfg.filter_objectProperties = "false"; + initCfg.filter_sco = "false"; + initCfg.filter_disjoint = "true"; + initCfg.filter_setOperator = "false"; + initCfg.mode_dynamic = "true"; + initCfg.mode_scaling = "true"; + initCfg.mode_compact = "false"; + initCfg.mode_colorExt = "true"; + initCfg.mode_multiColor = "false"; + initCfg.mode_pnp = "false"; + initCfg.debugFeatures = "false"; + initCfg.rect = 0; + return initCfg; + }; + + options.setEditorModeForDefaultObject = function ( val ){ + defaultOptionsConfig.editorMode = String(val); + }; + options.setHideDebugFeaturesForDefaultObject = function ( val ){ + defaultOptionsConfig.debugFeatures = String(!val); + }; + + function updateConfigObject(){ + defaultOptionsConfig.sidebar = options.sidebar().getSidebarVisibility(); + defaultOptionsConfig.cd = options.classDistance(); + defaultOptionsConfig.dd = options.datatypeDistance(); + defaultOptionsConfig.filter_datatypes = String(options.filterMenu().getCheckBoxValue("datatypeFilterCheckbox")); + defaultOptionsConfig.filter_sco = String(options.filterMenu().getCheckBoxValue("subclassFilterCheckbox")); + defaultOptionsConfig.filter_disjoint = String(options.filterMenu().getCheckBoxValue("disjointFilterCheckbox")); + defaultOptionsConfig.filter_setOperator = String(options.filterMenu().getCheckBoxValue("setoperatorFilterCheckbox")); + defaultOptionsConfig.filter_objectProperties = String(options.filterMenu().getCheckBoxValue("objectPropertyFilterCheckbox")); + defaultOptionsConfig.mode_dynamic = String(options.dynamicLabelWidth()); + defaultOptionsConfig.mode_scaling = String(options.modeMenu().getCheckBoxValue("nodescalingModuleCheckbox")); + defaultOptionsConfig.mode_compact = String(options.modeMenu().getCheckBoxValue("compactnotationModuleCheckbox")); + defaultOptionsConfig.mode_colorExt = String(options.modeMenu().getCheckBoxValue("colorexternalsModuleCheckbox")); + defaultOptionsConfig.mode_multiColor = String(options.modeMenu().colorModeState()); + defaultOptionsConfig.mode_pnp = String(options.modeMenu().getCheckBoxValue("pickandpinModuleCheckbox")); + defaultOptionsConfig.rect = 0; + } + + options.defaultConfig = function (){ + updateConfigObject(); + return defaultOptionsConfig; + }; + + options.exportMenu = function ( val ){ + if ( !arguments.length ) return exportMenu; + exportMenu = val; + }; + + options.rectangularRepresentation = function ( val ){ + if ( !arguments.length ) { + return rectangularRep; + } else { + var intVal = parseInt(val); + if ( intVal === 0 ) { + rectangularRep = false; + } else { + rectangularRep = true; + } + } + }; + + options.dynamicLabelWidth = function ( val ){ + if ( !arguments.length ) + return dynamicLabelWidth; + else { + dynamicLabelWidth = val; + } + }; + options.sidebar = function ( s ){ + if ( !arguments.length ) return sidebar; + sidebar = s; + return options; + + }; + + options.navigationMenu = function ( m ){ + if ( !arguments.length ) return navigationMenu; + navigationMenu = m; + return options; + + }; + + options.ontologyMenu = function ( m ){ + if ( !arguments.length ) return ontologyMenu; + ontologyMenu = m; + return options; + }; + + options.searchMenu = function ( m ){ + if ( !arguments.length ) return searchMenu; + searchMenu = m; + return options; + }; + + options.resetMenu = function ( m ){ + if ( !arguments.length ) return resetMenu; + resetMenu = m; + return options; + }; + + options.pausedMenu = function ( m ){ + if ( !arguments.length ) return pausedMenu; + pausedMenu = m; + return options; + }; + + options.pickAndPinModule = function ( m ){ + if ( !arguments.length ) return pickAndPinModule; + pickAndPinModule = m; + return options; + }; + + options.gravityMenu = function ( m ){ + if ( !arguments.length ) return gravityMenu; + gravityMenu = m; + return options; + }; + + options.filterMenu = function ( m ){ + if ( !arguments.length ) return filterMenu; + filterMenu = m; + return options; + }; + + options.modeMenu = function ( m ){ + if ( !arguments.length ) return modeMenu; + modeMenu = m; + return options; + }; + + options.charge = function ( p ){ + if ( !arguments.length ) return charge; + charge = +p; + return options; + }; + + options.classDistance = function ( p ){ + if ( !arguments.length ) return classDistance; + classDistance = +p; + return options; + }; + + options.compactNotation = function ( p ){ + + if ( !arguments.length ) return compactNotation; + compactNotation = p; + return options; + }; + + options.data = function ( p ){ + if ( !arguments.length ) return data; + data = p; + return options; + }; + + options.datatypeDistance = function ( p ){ + if ( !arguments.length ) return datatypeDistance; + datatypeDistance = +p; + return options; + }; + + options.filterModules = function ( p ){ + if ( !arguments.length ) return filterModules; + filterModules = p; + return options; + }; + + options.graphContainerSelector = function ( p ){ + if ( !arguments.length ) return graphContainerSelector; + graphContainerSelector = p; + return options; + }; + + options.gravity = function ( p ){ + if ( !arguments.length ) return gravity; + gravity = +p; + return options; + }; + + options.height = function ( p ){ + if ( !arguments.length ) return height; + height = +p; + return options; + }; + + options.linkStrength = function ( p ){ + if ( !arguments.length ) return linkStrength; + linkStrength = +p; + return options; + }; + + options.loopDistance = function ( p ){ + if ( !arguments.length ) return loopDistance; + loopDistance = p; + return options; + }; + + options.minMagnification = function ( p ){ + if ( !arguments.length ) return minMagnification; + minMagnification = +p; + return options; + }; + + options.maxMagnification = function ( p ){ + if ( !arguments.length ) return maxMagnification; + maxMagnification = +p; + return options; + }; + + options.scaleNodesByIndividuals = function ( p ){ + if ( !arguments.length ) return scaleNodesByIndividuals; + scaleNodesByIndividuals = p; + return options; + }; + + options.selectionModules = function ( p ){ + if ( !arguments.length ) return selectionModules; + selectionModules = p; + return options; + }; + + options.width = function ( p ){ + if ( !arguments.length ) return width; + width = +p; + return options; + }; + + options.literalFilter = function ( p ){ + if ( !arguments.length ) return literalFilter; + literalFilter = p; + return options; + }; + options.nodeDegreeFilter = function ( p ){ + if ( !arguments.length ) return nodeDegreeFilter; + nodeDegreeFilter = p; + return options; + }; + + options.loadingModule = function ( p ){ + if ( !arguments.length ) return loadingModule; + loadingModule = p; + return options; + }; + + // define url loadable options; + // update all set values in the default object + options.setOptionsFromURL = function ( opts, changeEditFlag ){ + if ( opts.sidebar !== undefined ) sidebar.showSidebar(parseInt(opts.sidebar), true); + if ( opts.doc ) { + var asInt = parseInt(opts.doc); + filterMenu.setDegreeSliderValue(asInt); + graphObject.setGlobalDOF(asInt); + // reset the value to be -1; + defaultOptionsConfig.doc = -1; + } + var settingFlag = false; + if ( opts.editorMode ) { + if ( opts.editorMode === "true" ) settingFlag = true; + d3.select("#editorModeModuleCheckbox").node().checked = settingFlag; + + if ( changeEditFlag && changeEditFlag === true ) { + graphObject.editorMode(settingFlag); + } + + // update config object + defaultOptionsConfig.editorMode = opts.editorMode; + + } + if ( opts.cd ) { // class distance + options.classDistance(opts.cd); // class distance + defaultOptionsConfig.cd = opts.cd; + } + if ( opts.dd ) { // data distance + options.datatypeDistance(opts.dd); + defaultOptionsConfig.cd = opts.cd; + } + if ( opts.cd || opts.dd ) options.gravityMenu().reset(); // reset the values so the slider is updated; + + + settingFlag = false; + if ( opts.filter_datatypes ) { + if ( opts.filter_datatypes === "true" ) settingFlag = true; + filterMenu.setCheckBoxValue("datatypeFilterCheckbox", settingFlag); + defaultOptionsConfig.filter_datatypes = opts.filter_datatypes; + } + if ( opts.debugFeatures ) { + if ( opts.debugFeatures === "true" ) settingFlag = true; + hideDebugOptions = settingFlag; + if ( options.getHideDebugFeatures() === false ) { + options.executeHiddenDebugFeatuers(); + } + defaultOptionsConfig.debugFeatures = opts.debugFeatures; + } + + settingFlag = false; + if ( opts.filter_objectProperties ) { + if ( opts.filter_objectProperties === "true" ) settingFlag = true; + filterMenu.setCheckBoxValue("objectPropertyFilterCheckbox", settingFlag); + defaultOptionsConfig.filter_objectProperties = opts.filter_objectProperties; + } + settingFlag = false; + if ( opts.filter_sco ) { + if ( opts.filter_sco === "true" ) settingFlag = true; + filterMenu.setCheckBoxValue("subclassFilterCheckbox", settingFlag); + defaultOptionsConfig.filter_sco = opts.filter_sco; + } + settingFlag = false; + if ( opts.filter_disjoint ) { + if ( opts.filter_disjoint === "true" ) settingFlag = true; + filterMenu.setCheckBoxValue("disjointFilterCheckbox", settingFlag); + defaultOptionsConfig.filter_disjoint = opts.filter_disjoint; + } + settingFlag = false; + if ( opts.filter_setOperator ) { + if ( opts.filter_setOperator === "true" ) settingFlag = true; + filterMenu.setCheckBoxValue("setoperatorFilterCheckbox", settingFlag); + defaultOptionsConfig.filter_setOperator = opts.filter_setOperator; + } + filterMenu.updateSettings(); + + // modesMenu + settingFlag = false; + if ( opts.mode_dynamic ) { + if ( opts.mode_dynamic === "true" ) settingFlag = true; + modeMenu.setDynamicLabelWidth(settingFlag); + dynamicLabelWidth = settingFlag; + defaultOptionsConfig.mode_dynamic = opts.mode_dynamic; + } + // settingFlag=false; + // THIS SHOULD NOT BE SET USING THE OPTIONS ON THE URL + // if (opts.mode_picnpin) { + // graph.options().filterMenu().setCheckBoxValue("pickandpin ModuleCheckbox", settingFlag); + // } + + settingFlag = false; + if ( opts.mode_pnp ) { + if ( opts.mode_pnp === "true" ) settingFlag = true; + modeMenu.setCheckBoxValue("pickandpinModuleCheckbox", settingFlag); + defaultOptionsConfig.mode_pnp = opts.mode_pnp; + } + + settingFlag = false; + if ( opts.mode_scaling ) { + if ( opts.mode_scaling === "true" ) settingFlag = true; + modeMenu.setCheckBoxValue("nodescalingModuleCheckbox", settingFlag); + defaultOptionsConfig.mode_scaling = opts.mode_scaling; + } + + settingFlag = false; + if ( opts.mode_compact ) { + if ( opts.mode_compact === "true" ) settingFlag = true; + modeMenu.setCheckBoxValue("compactnotationModuleCheckbox", settingFlag); + defaultOptionsConfig.mode_compact = opts.mode_compact; + } + + settingFlag = false; + if ( opts.mode_colorExt ) { + if ( opts.mode_colorExt === "true" ) settingFlag = true; + modeMenu.setCheckBoxValue("colorexternalsModuleCheckbox", settingFlag); + defaultOptionsConfig.mode_colorExt = opts.mode_colorExt; + } + + settingFlag = false; + if ( opts.mode_multiColor ) { + if ( opts.mode_multiColor === "true" ) settingFlag = true; + modeMenu.setColorSwitchStateUsingURL(settingFlag); + defaultOptionsConfig.mode_multiColor = opts.mode_multiColor; + } + modeMenu.updateSettingsUsingURL(); + options.rectangularRepresentation(opts.rect); + }; + + return options; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 65 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var OwlDisjointWith = __webpack_require__(46); + var attributeParser = __webpack_require__(66)(); + var equivalentPropertyMerger = __webpack_require__(67)(); + var nodePrototypeMap = __webpack_require__(5)(); + var propertyPrototypeMap = __webpack_require__(40)(); + + /** + * Encapsulates the parsing and preparation logic of the input data. + * @param graph the graph object that will be passed to the elements + * @returns {{}} + */ + module.exports = function ( graph ){ + var parser = {}, + nodes, + properties, + classMap, + settingsData, + settingsImported = false, + settingsImportGraphZoomAndTranslation = false, + dictionary = [], + propertyMap; + + parser.getDictionary = function (){ + return dictionary; + }; + + parser.setDictionary = function ( d ){ + dictionary = d; + }; + + parser.settingsImported = function (){ + return settingsImported; + }; + parser.settingsImportGraphZoomAndTranslation = function (){ + return settingsImportGraphZoomAndTranslation; + }; + + parser.parseSettings = function (){ + settingsImported = true; + settingsImportGraphZoomAndTranslation = false; + + if ( !settingsData ) { + settingsImported = false; + return; + } + /** global settings **********************************************************/ + if ( settingsData.global ) { + if ( settingsData.global.zoom ) { + var zoomFactor = settingsData.global.zoom; + graph.setZoom(zoomFactor); + settingsImportGraphZoomAndTranslation = true; + } + + if ( settingsData.global.translation ) { + var translation = settingsData.global.translation; + graph.setTranslation(translation); + settingsImportGraphZoomAndTranslation = true; + } + + if ( settingsData.global.paused ) { + var paused = settingsData.global.paused; + graph.options().pausedMenu().setPauseValue(paused); + } + } + /** Gravity Settings **********************************************************/ + if ( settingsData.gravity ) { + if ( settingsData.gravity.classDistance ) { + var classDistance = settingsData.gravity.classDistance; + graph.options().classDistance(classDistance); + } + if ( settingsData.gravity.datatypeDistance ) { + var datatypeDistance = settingsData.gravity.datatypeDistance; + graph.options().datatypeDistance(datatypeDistance); + } + graph.options().gravityMenu().reset(); // reads the options values and sets the gui values + } + + + // shared variable declaration + + var i; + var id; + var checked; + /** Filter Settings **********************************************************/ + if ( settingsData.filter ) { + // checkbox settings + if ( settingsData.filter.checkBox ) { + var filter_cb = settingsData.filter.checkBox; + for ( i = 0; i < filter_cb.length; i++ ) { + id = filter_cb[i].id; + checked = filter_cb[i].checked; + graph.options().filterMenu().setCheckBoxValue(id, checked); + } + } + // node degree filter settings + if ( settingsData.filter.degreeSliderValue ) { + var degreeSliderValue = settingsData.filter.degreeSliderValue; + graph.options().filterMenu().setDegreeSliderValue(degreeSliderValue); + } + graph.options().filterMenu().updateSettings(); + } + + /** Modes Setting **********************************************************/ + if ( settingsData.modes ) { + // checkbox settings + if ( settingsData.modes.checkBox ) { + var modes_cb = settingsData.modes.checkBox; + for ( i = 0; i < modes_cb.length; i++ ) { + id = modes_cb[i].id; + checked = modes_cb[i].checked; + graph.options().modeMenu().setCheckBoxValue(id, checked); + } + } + // color switch settings + var state = settingsData.modes.colorSwitchState; + // state could be undefined + if ( state === true || state === false ) { + graph.options().modeMenu().setColorSwitchState(state); + } + graph.options().modeMenu().updateSettings(); + } + graph.updateStyle(); // updates graph representation(setting charges and distances) + }; + + + /** + * Parses the ontology data and preprocesses it (e.g. connecting inverse properties and so on). + * @param ontologyData the loaded ontology json file + */ + parser.parse = function ( ontologyData ){ + if ( !ontologyData ) { + nodes = []; + properties = []; + dictionary = []; + return; + } + dictionary = []; + if ( ontologyData.settings ) settingsData = ontologyData.settings; + else settingsData = undefined; + + var classes = combineClasses(ontologyData.class, ontologyData.classAttribute), + datatypes = combineClasses(ontologyData.datatype, ontologyData.datatypeAttribute), + combinedClassesAndDatatypes = classes.concat(datatypes), + unparsedProperties = ontologyData.property || [], + combinedProperties; + + // Inject properties for unions, intersections, ... + addSetOperatorProperties(combinedClassesAndDatatypes, unparsedProperties); + combinedProperties = combineProperties(unparsedProperties, ontologyData.propertyAttribute); + classMap = mapElements(combinedClassesAndDatatypes); + propertyMap = mapElements(combinedProperties); + mergeRangesOfEquivalentProperties(combinedProperties, combinedClassesAndDatatypes); + + // Process the graph data + convertTypesToIris(combinedClassesAndDatatypes, ontologyData.namespace); + convertTypesToIris(combinedProperties, ontologyData.namespace); + nodes = createNodeStructure(combinedClassesAndDatatypes, classMap); + properties = createPropertyStructure(combinedProperties, classMap, propertyMap); + }; + + /** + * @return {Array} the preprocessed nodes + */ + parser.nodes = function (){ + return nodes; + }; + + /** + * @returns {Array} the preprocessed properties + */ + parser.properties = function (){ + return properties; + }; + + /** + * Combines the passed objects with its attributes and prototypes. This also applies + * attributes defined in the base of the prototype. + */ + function combineClasses( baseObjects, attributes ){ + var combinations = []; + var prototypeMap = createLowerCasePrototypeMap(nodePrototypeMap); + + if ( baseObjects ) { + baseObjects.forEach(function ( element ){ + var matchingAttribute; + + if ( attributes ) { + // Look for an attribute with the same id and merge them + for ( var i = 0; i < attributes.length; i++ ) { + var attribute = attributes[i]; + if ( element.id === attribute.id ) { + matchingAttribute = attribute; + break; + } + } + addAdditionalAttributes(element, matchingAttribute); + } + + // Then look for a prototype to add its properties + var Prototype = prototypeMap.get(element.type.toLowerCase()); + + if ( Prototype ) { + addAdditionalAttributes(element, Prototype); // TODO might be unnecessary + + var node = new Prototype(graph); + node.annotations(element.annotations) + .baseIri(element.baseIri) + .comment(element.comment) + .complement(element.complement) + .disjointUnion(element.disjointUnion) + .description(element.description) + .equivalents(element.equivalent) + .id(element.id) + .intersection(element.intersection) + .label(element.label) + // .type(element.type) Ignore, because we predefined it + .union(element.union) + .iri(element.iri); + if ( element.pos ) { + node.x = element.pos[0]; + node.y = element.pos[1]; + node.px = node.x; + node.py = node.y; + } + //class element pin + var elementPinned = element.pinned; + if ( elementPinned === true ) { + node.pinned(true); + graph.options().pickAndPinModule().addPinnedElement(node); + } + // Create node objects for all individuals + if ( element.individuals ) { + element.individuals.forEach(function ( individual ){ + var individualNode = new Prototype(graph); + individualNode.label(individual.labels) + .iri(individual.iri); + + node.individuals().push(individualNode); + }); + } + + if ( element.attributes ) { + var deduplicatedAttributes = d3.set(element.attributes.concat(node.attributes())); + node.attributes(deduplicatedAttributes.values()); + } + combinations.push(node); + } else { + console.error("Unknown element type: " + element.type); + } + }); + } + + return combinations; + } + + function combineProperties( baseObjects, attributes ){ + var combinations = []; + var prototypeMap = createLowerCasePrototypeMap(propertyPrototypeMap); + + if ( baseObjects ) { + baseObjects.forEach(function ( element ){ + var matchingAttribute; + + if ( attributes ) { + // Look for an attribute with the same id and merge them + for ( var i = 0; i < attributes.length; i++ ) { + var attribute = attributes[i]; + if ( element.id === attribute.id ) { + matchingAttribute = attribute; + break; + } + } + addAdditionalAttributes(element, matchingAttribute); + } + + // Then look for a prototype to add its properties + var Prototype = prototypeMap.get(element.type.toLowerCase()); + + if ( Prototype ) { + // Create the matching object and set the properties + var property = new Prototype(graph); + property.annotations(element.annotations) + .baseIri(element.baseIri) + .cardinality(element.cardinality) + .comment(element.comment) + .domain(element.domain) + .description(element.description) + .equivalents(element.equivalent) + .id(element.id) + .inverse(element.inverse) + .label(element.label) + .minCardinality(element.minCardinality) + .maxCardinality(element.maxCardinality) + .range(element.range) + .subproperties(element.subproperty) + .superproperties(element.superproperty) + // .type(element.type) Ignore, because we predefined it + .iri(element.iri); + + // adding property position + if ( element.pos ) { + property.x = element.pos[0]; + property.y = element.pos[1]; + property.px = element.pos[0]; + property.py = element.pos[1]; + } + var elementPinned = element.pinned; + if ( elementPinned === true ) { + property.pinned(true); + graph.options().pickAndPinModule().addPinnedElement(property); + } + + + if ( element.attributes ) { + var deduplicatedAttributes = d3.set(element.attributes.concat(property.attributes())); + property.attributes(deduplicatedAttributes.values()); + } + combinations.push(property); + } else { + console.error("Unknown element type: " + element.type); + } + + }); + } + + return combinations; + } + + function createLowerCasePrototypeMap( prototypeMap ){ + return d3.map(prototypeMap.values(), function ( Prototype ){ + return new Prototype().type().toLowerCase(); + }); + } + + function mergeRangesOfEquivalentProperties( properties, nodes ){ + // pass clones of arrays into the merger to keep the current functionality of this module + var newNodes = equivalentPropertyMerger.merge(properties.slice(), nodes.slice(), propertyMap, classMap, graph); + + // replace all the existing nodes and map the nodes again + nodes.length = 0; + Array.prototype.push.apply(nodes, newNodes); + classMap = mapElements(nodes); + } + + /** + * Checks all attributes which have to be rewritten. + * For example: + * equivalent is filled with only ID's of the corresponding nodes. It would be better to used the + * object instead of the ID so we swap the ID's with the correct object reference and can delete it from drawing + * because it is not necessary. + */ + function createNodeStructure( rawNodes, classMap ){ + var nodes = []; + + // Set the default values + var maxIndividualCount = 0; + rawNodes.forEach(function ( node ){ + maxIndividualCount = Math.max(maxIndividualCount, node.individuals().length); + node.visible(true); + }); + + rawNodes.forEach(function ( node ){ + // Merge and connect the equivalent nodes + processEquivalentIds(node, classMap); + + attributeParser.parseClassAttributes(node); + + node.maxIndividualCount(maxIndividualCount); + }); + + // Collect all nodes that should be displayed + rawNodes.forEach(function ( node ){ + if ( node.visible() ) { + nodes.push(node); + } + }); + + return nodes; + } + + /** + * Sets the disjoint attribute of the nodes if a disjoint label is found. + * @param property + */ + function processDisjoints( property ){ + if ( property instanceof OwlDisjointWith === false ) { + return; + } + + var domain = property.domain(), + range = property.range(); + + // Check the domain. + if ( !domain.disjointWith() ) { + domain.disjointWith([]); + } + + // Check the range. + if ( !range.disjointWith() ) { + range.disjointWith([]); + } + + domain.disjointWith().push(property.range()); + range.disjointWith().push(property.domain()); + } + + /** + * Connect all properties and also their sub- and superproperties. + * We iterate over the rawProperties array because it is way faster than iterating + * over an object and its attributes. + * + * @param rawProperties the properties + * @param classMap a map of all classes + * @param propertyMap the properties in a map + */ + function createPropertyStructure( rawProperties, classMap, propertyMap ){ + var properties = []; + // Set default values + rawProperties.forEach(function ( property ){ + property.visible(true); + }); + + // Connect properties + rawProperties.forEach(function ( property ){ + var domain, + range, + domainObject, + rangeObject, + inverse; + + /* Skip properties that have no information about their domain and range, like + inverse properties with optional inverse and optional domain and range attributes */ + if ( (property.domain() && property.range()) || property.inverse() ) { + + var inversePropertyId = findId(property.inverse()); + // Look if an inverse property exists + if ( inversePropertyId ) { + inverse = propertyMap[inversePropertyId]; + if ( !inverse ) { + console.warn("No inverse property was found for id: " + inversePropertyId); + property.inverse(undefined); + } + } + + // Either domain and range are set on this property or at the inverse + if ( typeof property.domain() !== "undefined" && typeof property.range() !== "undefined" ) { + domain = findId(property.domain()); + range = findId(property.range()); + + domainObject = classMap[domain]; + rangeObject = classMap[range]; + } else if ( inverse ) { + // Domain and range need to be switched + domain = findId(inverse.range()); + range = findId(inverse.domain()); + + domainObject = classMap[domain]; + rangeObject = classMap[range]; + } else { + console.warn("Domain and range not found for property: " + property.id()); + } + + // Set the references on this property + property.domain(domainObject); + property.range(rangeObject); + + // Also set the attributes of the inverse property + if ( inverse ) { + property.inverse(inverse); + inverse.inverse(property); + + // Switch domain and range + inverse.domain(rangeObject); + inverse.range(domainObject); + } + } + // Reference sub- and superproperties + referenceSubOrSuperProperties(property.subproperties()); + referenceSubOrSuperProperties(property.superproperties()); + }); + + // Merge equivalent properties and process disjoints. + rawProperties.forEach(function ( property ){ + processEquivalentIds(property, propertyMap); + processDisjoints(property); + + attributeParser.parsePropertyAttributes(property); + }); + // Add additional information to the properties + rawProperties.forEach(function ( property ){ + // Properties of merged classes should point to/from the visible equivalent class + var propertyWasRerouted = false; + + if ( property.domain() === undefined ) { + console.warn("No Domain was found for id:" + property.id()); + return; + } + + if ( wasNodeMerged(property.domain()) ) { + property.domain(property.domain().equivalentBase()); + propertyWasRerouted = true; + } + if ( property.range() === undefined ) { + console.warn("No range was found for id:" + property.id()); + return; + } + if ( wasNodeMerged(property.range()) ) { + property.range(property.range().equivalentBase()); + propertyWasRerouted = true; + } + // But there should not be two equal properties between the same domain and range + var equalProperty = getOtherEqualProperty(rawProperties, property); + + if ( propertyWasRerouted && equalProperty ) { + property.visible(false); + + equalProperty.redundantProperties().push(property); + } + + // Hide property if source or target node is hidden + if ( !property.domain().visible() || !property.range().visible() ) { + property.visible(false); + } + + // Collect all properties that should be displayed + if ( property.visible() ) { + properties.push(property); + } + }); + return properties; + } + + function referenceSubOrSuperProperties( subOrSuperPropertiesArray ){ + var i, l; + + if ( !subOrSuperPropertiesArray ) { + return; + } + + for ( i = 0, l = subOrSuperPropertiesArray.length; i < l; ++i ) { + var subOrSuperPropertyId = findId(subOrSuperPropertiesArray[i]); + var subOrSuperProperty = propertyMap[subOrSuperPropertyId]; + + if ( subOrSuperProperty ) { + // Replace id with object + subOrSuperPropertiesArray[i] = subOrSuperProperty; + } else { + console.warn("No sub-/superproperty was found for id: " + subOrSuperPropertyId); + } + } + } + + function wasNodeMerged( node ){ + return !node.visible() && node.equivalentBase(); + } + + function getOtherEqualProperty( properties, referenceProperty ){ + var i, l, property; + + for ( i = 0, l = properties.length; i < l; i++ ) { + property = properties[i]; + + if ( referenceProperty === property ) { + continue; + } + if ( referenceProperty.domain() !== property.domain() || + referenceProperty.range() !== property.range() ) { + continue; + } + + // Check for an equal IRI, if non existent compare label and type + if ( referenceProperty.iri() && property.iri() ) { + if ( referenceProperty.iri() === property.iri() ) { + return property; + } + } else if ( referenceProperty.type() === property.type() && + referenceProperty.defaultLabel() === property.defaultLabel() ) { + return property; + } + } + + return undefined; + } + + /** + * Generates and adds properties for links to set operators. + * @param classes unprocessed classes + * @param properties unprocessed properties + */ + function addSetOperatorProperties( classes, properties ){ + function addProperties( domainId, rangeIds, operatorType ){ + if ( !rangeIds ) { + return; + } + + rangeIds.forEach(function ( rangeId, index ){ + var property = { + id: "GENERATED-" + operatorType + "-" + domainId + "-" + rangeId + "-" + index, + type: "setOperatorProperty", + domain: domainId, + range: rangeId + }; + + properties.push(property); + }); + } + + classes.forEach(function ( clss ){ + addProperties(clss.id(), clss.complement(), "COMPLEMENT"); + addProperties(clss.id(), clss.intersection(), "INTERSECTION"); + addProperties(clss.id(), clss.union(), "UNION"); + addProperties(clss.id(), clss.disjointUnion(), "DISJOINTUNION"); + }); + } + + /** + * Replaces the ids of equivalent nodes/properties with the matching objects, cross references them + * and tags them as processed. + * @param element a node or a property + * @param elementMap a map where nodes/properties can be looked up + */ + function processEquivalentIds( element, elementMap ){ + var eqIds = element.equivalents(); + + if ( !eqIds || element.equivalentBase() ) { + return; + } + + // Replace ids with the corresponding objects + for ( var i = 0, l = eqIds.length; i < l; ++i ) { + var eqId = findId(eqIds[i]); + var eqObject = elementMap[eqId]; + + if ( eqObject ) { + // Cross reference both objects + eqObject.equivalents(eqObject.equivalents()); + eqObject.equivalents().push(element); + eqObject.equivalentBase(element); + eqIds[i] = eqObject; + + // Hide other equivalent nodes + eqObject.visible(false); + } else { + console.warn("No class/property was found for equivalent id: " + eqId); + } + } + } + + /** + * Tries to convert the type to an iri and sets it. + * @param elements classes or properties + * @param namespaces an array of namespaces + */ + function convertTypesToIris( elements, namespaces ){ + elements.forEach(function ( element ){ + if ( typeof element.iri() === "string" ) { + element.iri(replaceNamespace(element.iri(), namespaces)); + } + }); + } + + /** + * Creates a map by mapping the array with the passed function. + * @param array the array + * @returns {{}} + */ + function mapElements( array ){ + var map = {}; + for ( var i = 0, length = array.length; i < length; i++ ) { + var element = array[i]; + map[element.id()] = element; + } + return map; + } + + /** + * Adds the attributes of the additional object to the base object, but doesn't + * overwrite existing ones. + * + * @param base the base object + * @param addition the object with additional data + * @returns the combination is also returned + */ + function addAdditionalAttributes( base, addition ){ + // Check for an undefined value + addition = addition || {}; + + for ( var addAttribute in addition ) { + // Add the attribute if it doesn't exist + if ( !(addAttribute in base) && addition.hasOwnProperty(addAttribute) ) { + base[addAttribute] = addition[addAttribute]; + } + } + return base; + } + + /** + * Replaces the namespace (and the separator) if one exists and returns the new value. + * @param address the address with a namespace in it + * @param namespaces an array of namespaces + * @returns {string} the processed address with the (possibly) replaced namespace + */ + function replaceNamespace( address, namespaces ){ + var separatorIndex = address.indexOf(":"); + if ( separatorIndex === -1 ) { + return address; + } + var namespaceName = address.substring(0, separatorIndex); + + for ( var i = 0, length = namespaces.length; i < length; ++i ) { + var namespace = namespaces[i]; + if ( namespaceName === namespace.name ) { + return namespace.iri + address.substring(separatorIndex + 1); + } + } + + return address; + } + + /** + * Looks whether the passed object is already the id or if it was replaced + * with the object that belongs to the id. + * @param object an id, a class or a property + * @returns {string} the id of the passed object or undefined + */ + function findId( object ){ + if ( !object ) { + return undefined; + } else if ( typeof object === "string" ) { + return object; + } else if ( "id" in object ) { + return object.id(); + } else { + console.warn("No Id was found for this object: " + object); + return undefined; + } + } + + return parser; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 66 */ +/***/ (function(module, exports) { + + /** + * Parses the attributes an element has and sets the corresponding attributes. + * @returns {Function} + */ + module.exports = (function (){ + var attributeParser = {}, + // Style + ANONYMOUS = "anonymous", + DATATYPE = "datatype", + DEPRECATED = "deprecated", + EXTERNAL = "external", + OBJECT = "object", + RDF = "rdf", + // Representations + ASYMMETRIC = "asymmetric", + FUNCTIONAL = "functional", + INVERSE_FUNCTIONAL = "inverse functional", + IRREFLEXIVE = "irreflexive", + KEY = "key", + REFLEXIVE = "reflexive", + SYMMETRIC = "symmetric", + TRANSITIVE = "transitive", + // Attribute groups + VISUAL_ATTRIBUTE_GROUPS = [ + [DEPRECATED, DATATYPE, OBJECT, RDF], + [ANONYMOUS] + ], + CLASS_INDICATIONS = [DEPRECATED, EXTERNAL], + PROPERTY_INDICATIONS = [ASYMMETRIC, FUNCTIONAL, INVERSE_FUNCTIONAL, IRREFLEXIVE, KEY, REFLEXIVE, SYMMETRIC, + TRANSITIVE]; + + /** + * Parses and sets the attributes of a class. + * @param clazz + */ + attributeParser.parseClassAttributes = function ( clazz ){ + if ( !(clazz.attributes() instanceof Array) ) { + return; + } + + parseVisualAttributes(clazz); + parseClassIndications(clazz); + }; + + function parseVisualAttributes( element ){ + VISUAL_ATTRIBUTE_GROUPS.forEach(function ( attributeGroup ){ + setVisualAttributeOfGroup(element, attributeGroup); + }); + } + + function setVisualAttributeOfGroup( element, group ){ + var i, l, attribute; + + for ( i = 0, l = group.length; i < l; i++ ) { + attribute = group[i]; + if ( element.attributes().indexOf(attribute) >= 0 ) { + element.visualAttributes().push(attribute); + + // Just a single attribute is possible + break; + } + } + } + + function parseClassIndications( clazz ){ + var i, l, indication; + + for ( i = 0, l = CLASS_INDICATIONS.length; i < l; i++ ) { + indication = CLASS_INDICATIONS[i]; + + if ( clazz.attributes().indexOf(indication) >= 0 ) { + clazz.indications().push(indication); + } + } + } + + /** + * Parses and sets the attributes of a property. + * @param property + */ + attributeParser.parsePropertyAttributes = function ( property ){ + if ( !(property.attributes() instanceof Array) ) { + return; + } + + parseVisualAttributes(property); + parsePropertyIndications(property); + }; + + function parsePropertyIndications( property ){ + var i, l, indication; + + for ( i = 0, l = PROPERTY_INDICATIONS.length; i < l; i++ ) { + indication = PROPERTY_INDICATIONS[i]; + + if ( property.attributes().indexOf(indication) >= 0 ) { + property.indications().push(indication); + } + } + } + + + return function (){ + // Return a function to keep module interfaces consistent + return attributeParser; + }; + })(); + + +/***/ }), +/* 67 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var OwlThing = __webpack_require__(31); + var RdfsLiteral = __webpack_require__(38); + var elementTools = __webpack_require__(63)(); + + var equivalentPropertyMerger = {}; + module.exports = function (){ + return equivalentPropertyMerger; + }; + + var PREFIX = "GENERATED-MERGED_RANGE-"; + var OBJECT_PROPERTY_DEFAULT_RANGE_TYPE = "owl:Thing"; + var DATA_PROPERTY_DEFAULT_RANGE_TYPE = "rdfs:Literal"; + + + equivalentPropertyMerger.merge = function ( properties, nodes, propertyMap, nodeMap, graph ){ + var totalNodeIdsToHide = d3.set(); + var processedPropertyIds = d3.set(); + var mergeNodes = []; + + for ( var i = 0; i < properties.length; i++ ) { + var property = properties[i]; + var equivalents = property.equivalents().map(createIdToPropertyMapper(propertyMap)); + + if ( equivalents.length === 0 || processedPropertyIds.has(property.id()) ) { + continue; + } + + var propertyWithEquivalents = equivalents.concat(property); + + var mergeNode = findMergeNode(propertyWithEquivalents, nodeMap); + if ( !mergeNode ) { + if ( mergeNode !== undefined ) { + mergeNode = createDefaultMergeNode(property, graph); + mergeNodes.push(mergeNode); + } + } + + var nodeIdsToHide = replaceRangesAndCollectNodesToHide(propertyWithEquivalents, mergeNode, properties, + processedPropertyIds); + for ( var j = 0; j < nodeIdsToHide.length; j++ ) { + totalNodeIdsToHide.add(nodeIdsToHide[j]); + } + } + + return filterVisibleNodes(nodes.concat(mergeNodes), totalNodeIdsToHide); + }; + + + function createIdToPropertyMapper( propertyMap ){ + return function ( id ){ + return propertyMap[id]; + }; + } + + function findMergeNode( propertyWithEquivalents, nodeMap ){ + var typeMap = mapPropertiesRangesToType(propertyWithEquivalents, nodeMap); + var typeSet = d3.set(typeMap.keys()); + + // default types are the fallback values and should be ignored for the type determination + typeSet.remove(OBJECT_PROPERTY_DEFAULT_RANGE_TYPE); + typeSet.remove(DATA_PROPERTY_DEFAULT_RANGE_TYPE); + + // exactly one type to chose from -> take the node of this type as range + if ( typeSet.size() === 1 ) { + var type = typeSet.values()[0]; + var ranges = typeMap.get(type); + + if ( ranges.length === 1 ) { + return ranges[0]; + } + } + } + + function mapPropertiesRangesToType( properties, nodeMap ){ + var typeMap = d3.map(); + + properties.forEach(function ( property ){ + if ( property === undefined ) //@ WORKAROUND + return; + + var range = nodeMap[property.range()]; + var type = range.type(); + + if ( !typeMap.has(type) ) { + typeMap.set(type, []); + } + + typeMap.get(type).push(range); + }); + + return typeMap; + } + + function createDefaultMergeNode( property, graph ){ + var range; + + if ( elementTools.isDatatypeProperty(property) ) { + range = new RdfsLiteral(graph); + } else { + range = new OwlThing(graph); + } + range.id(PREFIX + property.id()); + + return range; + } + + function replaceRangesAndCollectNodesToHide( propertyWithEquivalents, mergeNode, properties, processedPropertyIds ){ + var nodesToHide = []; + + propertyWithEquivalents.forEach(function ( property ){ + + if ( property === undefined || mergeNode === undefined ) // @ WORKAROUND + return; + var oldRangeId = property.range(); + property.range(mergeNode.id()); + if ( !isDomainOrRangeOfOtherProperty(oldRangeId, properties) ) { + nodesToHide.push(oldRangeId); + } + + processedPropertyIds.add(property.id()); + }); + + return nodesToHide; + } + + function isDomainOrRangeOfOtherProperty( nodeId, properties ){ + for ( var i = 0; i < properties.length; i++ ) { + var property = properties[i]; + if ( property.domain() === nodeId || property.range() === nodeId ) { + return true; + } + } + + return false; + } + + function filterVisibleNodes( nodes, nodeIdsToHide ){ + var filteredNodes = []; + + nodes.forEach(function ( node ){ + if ( !nodeIdsToHide.has(node.id()) ) { + filteredNodes.push(node); + } + }); + + return filteredNodes; + } + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 68 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( graph ){ + /** variable defs **/ + var Class_dragger = {}; + Class_dragger.nodeId = 10001; + Class_dragger.parent = undefined; + Class_dragger.x = 0; + Class_dragger.y = 0; + Class_dragger.rootElement = undefined; + Class_dragger.rootNodeLayer = undefined; + Class_dragger.pathLayer = undefined; + Class_dragger.mouseEnteredVar = false; + Class_dragger.mouseButtonPressed = false; + Class_dragger.nodeElement = undefined; + Class_dragger.draggerObject = undefined; + Class_dragger.pathElement = undefined; + Class_dragger.typus = "Class_dragger"; + + Class_dragger.type = function (){ + return Class_dragger.typus; + }; + + Class_dragger.parentNode = function (){ + return Class_dragger.parent; + }; + + Class_dragger.hideClass_dragger = function ( val ){ + Class_dragger.pathElement.classed("hidden", val); + Class_dragger.nodeElement.classed("hidden", val); + Class_dragger.draggerObject.classed("hidden", val); + }; + + Class_dragger.setParentNode = function ( parentNode ){ + Class_dragger.parent = parentNode; + + if ( Class_dragger.mouseButtonPressed === false ) { + if ( Class_dragger.parent.actualRadius && Class_dragger.parent.actualRadius() ) { + Class_dragger.x = Class_dragger.parent.x + 10 + Class_dragger.parent.actualRadius(); + Class_dragger.y = Class_dragger.parent.y + 10 + Class_dragger.parent.actualRadius(); + } else { + Class_dragger.x = Class_dragger.parent.x + 60; + Class_dragger.y = Class_dragger.parent.y + 60; + } + } + Class_dragger.updateElement(); + }; + + Class_dragger.hideDragger = function ( val ){ + if ( Class_dragger.pathElement ) Class_dragger.pathElement.classed("hidden", val); + if ( Class_dragger.nodeElement ) Class_dragger.nodeElement.classed("hidden", val); + if ( Class_dragger.draggerObject ) Class_dragger.draggerObject.classed("hidden", val); + + }; + /** BASE HANDLING FUNCTIONS ------------------------------------------------- **/ + Class_dragger.id = function ( index ){ + if ( !arguments.length ) { + return Class_dragger.nodeId; + } + Class_dragger.nodeId = index; + }; + + Class_dragger.svgPathLayer = function ( layer ){ + Class_dragger.pathLayer = layer.append('g'); + }; + + Class_dragger.svgRoot = function ( root ){ + if ( !arguments.length ) + return Class_dragger.rootElement; + Class_dragger.rootElement = root; + Class_dragger.rootNodeLayer = Class_dragger.rootElement.append('g'); + Class_dragger.addMouseEvents(); + }; + + /** DRAWING FUNCTIONS ------------------------------------------------- **/ + Class_dragger.drawNode = function (){ + Class_dragger.pathElement = Class_dragger.pathLayer.append('line') + .classed("classNodeDragPath", true); + Class_dragger.pathElement.attr("x1", 0) + .attr("y1", 0) + .attr("x2", 0) + .attr("y2", 0); + + // var lineData = [ + // {"x": 0, "y": 0}, + // {"x": 0, "y": 40}, + // {"x": -40, "y": 0}, + // {"x": 0, "y": -40}, + // {"x": 0, "y": 0} + // ]; + + var lineData = [ + { "x": -40, "y": 0 }, // start + { "x": -20, "y": -10 }, + { "x": 20, "y": -50 }, + { "x": -10, "y": 0 }, // center + { "x": 20, "y": 50 }, + { "x": -20, "y": 10 }, + { "x": -40, "y": 0 } + ]; + + + var lineFunction = d3.svg.line() + .x(function ( d ){ + return d.x; + }) + .y(function ( d ){ + return d.y; + }) + .interpolate("basis-closed"); + var pathData = "M 20,40 C 0,15 0,-15 20,-40 L -40,0 Z"; + // var pathData="M 20,40 C 0,15 0,-15 20,-40 20,-40 -35.22907,-23.905556 -45.113897,0.06313453 -35.22907,20.095453 20,40 20,40 Z"; + // var pathData="M 39.107144,51.25 C 0,17.362169 0,-13.75 39.285715,-49.821429 c 0,0 -69.58321,34.511175 -100.714286,50.35714329 C -22.96643,20.324376 39.107144,51.25 39.107144,51.25 Z"; + + Class_dragger.nodeElement = Class_dragger.rootNodeLayer.append('path').attr("d", pathData); + Class_dragger.nodeElement.classed("classDraggerNode", true); + Class_dragger.draggerObject = Class_dragger.rootNodeLayer.append("circle"); + if ( graph.options().useAccuracyHelper() ) { + Class_dragger.draggerObject.attr("r", 40) + .attr("cx", 0) + .attr("cy", 0) + .classed("superHiddenElement", true); + Class_dragger.draggerObject.classed("superOpacityElement", !graph.options().showDraggerObject()); + } + + + }; + + Class_dragger.updateElement = function (){ + + // Class_dragger.pathLayer.attr("transform", "translate(" + Class_dragger.x + "," + Class_dragger.y + ")"); + // Class_dragger.rootElement.attr("transform", "translate(" + Class_dragger.x + "," + Class_dragger.y + ")"); + if ( Class_dragger.pathElement ) { + + // compute start point ; + + + var sX = Class_dragger.parent.x, + sY = Class_dragger.parent.y, + eX = Class_dragger.x, + eY = Class_dragger.y; + + + // this is used only when you dont have a proper layout ordering; + var dirX = eX - sX; + var dirY = eY - sY; + var len = Math.sqrt((dirX * dirX) + (dirY * dirY)); + + var nX = dirX / len; + var nY = dirY / len; + + var ppX = sX + nX * Class_dragger.parent.actualRadius(); + var ppY = sY + nY * Class_dragger.parent.actualRadius(); + + var ncx = nX * 15; + var ncy = nY * 15; + Class_dragger.draggerObject.attr("cx", ncx) + .attr("cy", ncy); + + Class_dragger.pathElement.attr("x1", ppX) + .attr("y1", ppY) + .attr("x2", eX) + .attr("y2", eY); + } + var angle = Math.atan2(Class_dragger.parent.y - Class_dragger.y, Class_dragger.parent.x - Class_dragger.x) * 180 / Math.PI; + + Class_dragger.nodeElement.attr("transform", "translate(" + Class_dragger.x + "," + Class_dragger.y + ")" + "rotate(" + angle + ")"); + Class_dragger.draggerObject.attr("transform", "translate(" + Class_dragger.x + "," + Class_dragger.y + ")"); + // console.log("update Elmenent root element"+Class_dragger.x + "," + Class_dragger.y ); + // + // Class_dragger.nodeElement.attr("transform", function (d) { + // return "rotate(" + angle + ")"; + // }); + }; + + /** MOUSE HANDLING FUNCTIONS ------------------------------------------------- **/ + + Class_dragger.addMouseEvents = function (){ + // console.log("adding mouse events"); + Class_dragger.rootNodeLayer.selectAll("*").on("mouseover", Class_dragger.onMouseOver) + .on("mouseout", Class_dragger.onMouseOut) + .on("click", function (){ + }) + .on("dblclick", function (){ + }) + .on("mousedown", Class_dragger.mouseDown) + .on("mouseup", Class_dragger.mouseUp); + }; + + Class_dragger.mouseDown = function (){ + Class_dragger.nodeElement.style("cursor", "move"); + Class_dragger.nodeElement.classed("classDraggerNodeHovered", true); + Class_dragger.mouseButtonPressed = true; + console.log("Mouse DOWN from Dragger"); + }; + + Class_dragger.mouseUp = function (){ + Class_dragger.nodeElement.style("cursor", "auto"); + Class_dragger.mouseButtonPressed = false; + console.log("Mouse UP from Dragger"); + }; + + + Class_dragger.mouseEntered = function ( p ){ + if ( !arguments.length ) return Class_dragger.mouseEnteredVar; + Class_dragger.mouseEnteredVar = p; + return Class_dragger; + }; + + Class_dragger.selectedViaTouch = function ( val ){ + Class_dragger.nodeElement.classed("classDraggerNode", !val); + Class_dragger.nodeElement.classed("classDraggerNodeHovered", val); + + }; + + Class_dragger.onMouseOver = function (){ + if ( Class_dragger.mouseEntered() ) { + return; + } + Class_dragger.nodeElement.classed("classDraggerNode", false); + Class_dragger.nodeElement.classed("classDraggerNodeHovered", true); + var selectedNode = Class_dragger.rootElement.node(), + nodeContainer = selectedNode.parentNode; + nodeContainer.appendChild(selectedNode); + + Class_dragger.mouseEntered(true); + + }; + Class_dragger.onMouseOut = function (){ + if ( Class_dragger.mouseButtonPressed === true ) + return; + Class_dragger.nodeElement.classed("classDraggerNodeHovered", false); + Class_dragger.nodeElement.classed("classDraggerNode", true); + Class_dragger.mouseEntered(false); + }; + + Class_dragger.setPosition = function ( x, y ){ + + Class_dragger.x = x; + Class_dragger.y = y; + Class_dragger.updateElement(); + }; + + Class_dragger.setAdditionalClassForClass_dragger = function ( name, val ){ + // console.log("Class_dragger should sett the class here") + // Class_dragger.nodeElement.classed(name,val); + + }; + return Class_dragger; + }; + + + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 69 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( graph ){ + /** variable defs **/ + var Range_dragger = {}; + Range_dragger.nodeId = 10002; + Range_dragger.parent = undefined; + Range_dragger.x = 0; + Range_dragger.y = 0; + Range_dragger.rootElement = undefined; + Range_dragger.rootNodeLayer = undefined; + Range_dragger.pathLayer = undefined; + Range_dragger.mouseEnteredVar = false; + Range_dragger.mouseButtonPressed = false; + Range_dragger.nodeElement = undefined; + Range_dragger.draggerObject = undefined; + + Range_dragger.pathElement = undefined; + Range_dragger.typus = "Range_dragger"; + + Range_dragger.type = function (){ + return Range_dragger.typus; + }; + + // TODO: We need the endPoint of the Link here! + Range_dragger.parentNode = function (){ + return Range_dragger.parent; + }; + + Range_dragger.hide_dragger = function ( val ){ + Range_dragger.pathElement.classed("hidden", val); + Range_dragger.nodeElement.classed("hidden", val); + Range_dragger.draggerObject.classed("hidden", val); + }; + Range_dragger.hideDragger = function ( val ){ + if ( Range_dragger.pathElement ) Range_dragger.pathElement.classed("hidden", val); + if ( Range_dragger.nodeElement ) Range_dragger.nodeElement.classed("hidden", val); + if ( Range_dragger.draggerObject ) Range_dragger.draggerObject.classed("hidden", val); + + + }; + + Range_dragger.reDrawEverthing = function (){ + Range_dragger.setParentProperty(Range_dragger.parent); + }; + Range_dragger.updateRange = function ( newRange ){ + + if ( graph.genericPropertySanityCheck(Range_dragger.parent.domain(), newRange, + Range_dragger.parent.type(), + "Could not update range", "Restoring previous range") === false ) return; + + // check for triple duplicates! + + if ( graph.propertyCheckExistenceChecker(Range_dragger.parent, Range_dragger.parent.domain(), newRange) === false ) + return; + if ( Range_dragger.parent.labelElement() === undefined ) return; + if ( Range_dragger.parent.labelElement().attr("transform") === "translate(0,15)" || + Range_dragger.parent.labelElement().attr("transform") === "translate(0,-15)" ) { + var prop = Range_dragger.parent; + Range_dragger.parent.inverse().inverse(null); + Range_dragger.parent.inverse(null); + prop.range(newRange); + } + + else { + Range_dragger.parent.range(newRange); + } + // update the position of the new range + var rX = newRange.x; + var rY = newRange.y; + + var dX = Range_dragger.parent.domain().x; + var dY = Range_dragger.parent.domain().y; + + + // center + var cX = 0.49 * (dX + rX); + var cY = 0.49 * (dY + rY); + // put position there; + Range_dragger.parent.labelElement().x = cX; + Range_dragger.parent.labelElement().px = cX; + Range_dragger.parent.labelElement().y = cY; + Range_dragger.parent.labelElement().py = cY; + + }; + + Range_dragger.setParentProperty = function ( parentProperty, inversed ){ + Range_dragger.parent = parentProperty; + var iP; + var renElem; + Range_dragger.isLoopProperty = false; + if ( parentProperty.domain() === parentProperty.range() ) Range_dragger.isLoopProperty = true; + Range_dragger.parent = parentProperty; + renElem = parentProperty.labelObject(); + if ( inversed === true ) { + if ( parentProperty.labelElement() && parentProperty.labelElement().attr("transform") === "translate(0,15)" ) { + iP = renElem.linkDomainIntersection; + if ( renElem.linkDomainIntersection ) { + Range_dragger.x = iP.x; + Range_dragger.y = iP.y; + } + } else { + iP = renElem.linkRangeIntersection; + if ( renElem.linkRangeIntersection ) { + Range_dragger.x = iP.x; + Range_dragger.y = iP.y; + } + } + } + else { + iP = renElem.linkRangeIntersection; + if ( renElem.linkRangeIntersection ) { + Range_dragger.x = iP.x; + Range_dragger.y = iP.y; + } + } + + Range_dragger.updateElement(); + }; + + + /** BASE HANDLING FUNCTIONS ------------------------------------------------- **/ + Range_dragger.id = function ( index ){ + if ( !arguments.length ) { + return Range_dragger.nodeId; + } + Range_dragger.nodeId = index; + }; + + Range_dragger.svgPathLayer = function ( layer ){ + Range_dragger.pathLayer = layer.append('g'); + }; + + Range_dragger.svgRoot = function ( root ){ + if ( !arguments.length ) + return Range_dragger.rootElement; + Range_dragger.rootElement = root; + Range_dragger.rootNodeLayer = Range_dragger.rootElement.append('g'); + Range_dragger.addMouseEvents(); + }; + + /** DRAWING FUNCTIONS ------------------------------------------------- **/ + Range_dragger.drawNode = function (){ + Range_dragger.pathElement = Range_dragger.pathLayer.append('line') + .classed("classNodeDragPath", true); + Range_dragger.pathElement.attr("x1", 0) + .attr("y1", 0) + .attr("x2", 0) + .attr("y2", 0); + + // var lineData = [ + // {"x": 0, "y": 0}, + // {"x": 0, "y": 40}, + // {"x": -40, "y": 0}, + // {"x": 0, "y": -40}, + // {"x": 0, "y": 0} + // ]; + + var lineData = [ + { "x": -40, "y": 0 }, // start + { "x": -20, "y": -10 }, + { "x": 20, "y": -50 }, + { "x": -10, "y": 0 }, // center + { "x": 20, "y": 50 }, + { "x": -20, "y": 10 }, + { "x": -40, "y": 0 } + ]; + + + var lineFunction = d3.svg.line() + .x(function ( d ){ + return d.x; + }) + .y(function ( d ){ + return d.y; + }) + .interpolate("basis-closed"); + var pathData = "M 61,40 C 41,15 41,-15 61,-40 L 1,0 Z"; + + Range_dragger.nodeElement = Range_dragger.rootNodeLayer.append('path').attr("d", pathData); + Range_dragger.nodeElement.classed("classDraggerNode", true); + if ( graph.options().useAccuracyHelper() ) { + Range_dragger.draggerObject = Range_dragger.rootNodeLayer.append("circle"); + Range_dragger.draggerObject.attr("r", 40) + .attr("cx", 0) + .attr("cy", 0) + .classed("superHiddenElement", true); + Range_dragger.draggerObject.classed("superOpacityElement", !graph.options().showDraggerObject()); + } + + + }; + + Range_dragger.updateElementViaDomainDragger = function ( x, y ){ + + var range_x = x; + var range_y = y; + + var dex = Range_dragger.parent.range().x; + var dey = Range_dragger.parent.range().y; + + var dir_X = x - dex; + var dir_Y = y - dey; + + var len = Math.sqrt(dir_X * dir_X + dir_Y * dir_Y); + + var nX = dir_X / len; + var nY = dir_Y / len; + + + var ep_range_x = dex + nX * Range_dragger.parent.range().actualRadius(); + var ep_range_y = dey + nY * Range_dragger.parent.range().actualRadius(); + + + var dx = range_x - ep_range_x; + var dy = range_y - ep_range_y; + len = Math.sqrt(dx * dx + dy * dy); + nX = dx / len; + nY = dy / len; + + var angle = Math.atan2(ep_range_y - range_y, ep_range_x - range_x) * 180 / Math.PI + 180; + Range_dragger.nodeElement.attr("transform", "translate(" + ep_range_x + "," + ep_range_y + ")" + "rotate(" + angle + ")"); + var doX = ep_range_x + nX * 40; + var doY = ep_range_y + nY * 40; + Range_dragger.draggerObject.attr("transform", "translate(" + doX + "," + doY + ")"); + + }; + + + Range_dragger.updateElement = function (){ + if ( Range_dragger.mouseButtonPressed === true || Range_dragger.parent === undefined ) return; + + var range = Range_dragger.parent.range(); + var iP = Range_dragger.parent.labelObject().linkRangeIntersection; + if ( Range_dragger.parent.labelElement() === undefined ) return; + var offsetForLoop = 48; + if ( Range_dragger.parent.labelElement().attr("transform") === "translate(0,15)" ) { + range = Range_dragger.parent.inverse().domain(); + iP = Range_dragger.parent.labelObject().linkDomainIntersection; + offsetForLoop = -48; + } + + if ( iP === undefined ) return; + var range_x = range.x; + var range_y = range.y; + + var ep_range_x = iP.x; + var ep_range_y = iP.y; + // offset for dragger object + var dx = range_x - ep_range_x; + var dy = range_y - ep_range_y; + var len = Math.sqrt(dx * dx + dy * dy); + var nX = dx / len; + var nY = dy / len; + var angle = Math.atan2(ep_range_y - range_y, ep_range_x - range_x) * 180 / Math.PI; + + var doX = ep_range_x - nX * 40; + var doY = ep_range_y - nY * 40; + + if ( Range_dragger.isLoopProperty === true ) + angle -= offsetForLoop; + + + Range_dragger.nodeElement.attr("transform", "translate(" + ep_range_x + "," + ep_range_y + ")" + "rotate(" + angle + ")"); + Range_dragger.draggerObject.attr("transform", "translate(" + doX + "," + doY + ")"); + + + }; + + /** MOUSE HANDLING FUNCTIONS ------------------------------------------------- **/ + + Range_dragger.addMouseEvents = function (){ + var rootLayer = Range_dragger.rootNodeLayer.selectAll("*"); + rootLayer.on("mouseover", Range_dragger.onMouseOver) + .on("mouseout", Range_dragger.onMouseOut) + .on("click", function (){ + }) + .on("dblclick", function (){ + }) + .on("mousedown", Range_dragger.mouseDown) + .on("mouseup", Range_dragger.mouseUp); + }; + + Range_dragger.mouseDown = function (){ + Range_dragger.nodeElement.style("cursor", "move"); + Range_dragger.nodeElement.classed("classDraggerNodeHovered", true); + Range_dragger.mouseButtonPressed = true; + }; + + Range_dragger.mouseUp = function (){ + Range_dragger.nodeElement.style("cursor", "auto"); + Range_dragger.nodeElement.classed("classDraggerNodeHovered", false); + Range_dragger.mouseButtonPressed = false; + }; + + + Range_dragger.mouseEntered = function ( p ){ + if ( !arguments.length ) return Range_dragger.mouseEnteredVar; + Range_dragger.mouseEnteredVar = p; + return Range_dragger; + }; + + Range_dragger.selectedViaTouch = function ( val ){ + Range_dragger.nodeElement.classed("classDraggerNode", !val); + Range_dragger.nodeElement.classed("classDraggerNodeHovered", val); + + }; + + Range_dragger.onMouseOver = function (){ + if ( Range_dragger.mouseEntered() ) { + return; + } + Range_dragger.nodeElement.classed("classDraggerNode", false); + Range_dragger.nodeElement.classed("classDraggerNodeHovered", true); + var selectedNode = Range_dragger.rootElement.node(), + nodeContainer = selectedNode.parentNode; + nodeContainer.appendChild(selectedNode); + + Range_dragger.mouseEntered(true); + + }; + Range_dragger.onMouseOut = function (){ + if ( Range_dragger.mouseButtonPressed === true ) + return; + Range_dragger.nodeElement.classed("classDraggerNodeHovered", false); + Range_dragger.nodeElement.classed("classDraggerNode", true); + Range_dragger.mouseEntered(false); + }; + + Range_dragger.setPosition = function ( x, y ){ + var range_x = Range_dragger.parent.domain().x; + var range_y = Range_dragger.parent.domain().y; + + // var position of the rangeEndPoint + var ep_range_x = x; + var ep_range_y = y; + + // offset for dragger object + var dx = range_x - ep_range_x; + var dy = range_y - ep_range_y; + + var len = Math.sqrt(dx * dx + dy * dy); + + var nX = dx / len; + var nY = dy / len; + + + var angle = Math.atan2(dy, dx) * 180 / Math.PI; + var doX = ep_range_x + nX * 40; + var doY = ep_range_y + nY * 40; + Range_dragger.nodeElement.attr("transform", "translate(" + ep_range_x + "," + ep_range_y + ")" + "rotate(" + angle + ")"); + Range_dragger.draggerObject.attr("transform", "translate(" + doX + "," + doY + ")"); + Range_dragger.x = x; + Range_dragger.y = y; + + }; + + Range_dragger.setAdditionalClassForClass_dragger = function ( name, val ){ + + }; + return Range_dragger; + }; + + + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 70 */ +/***/ (function(module, exports) { + + module.exports = function ( graph ){ + /** variable defs **/ + var Domain_dragger = {}; + Domain_dragger.nodeId = 10002; + Domain_dragger.parent = undefined; + Domain_dragger.x = 0; + Domain_dragger.y = 0; + Domain_dragger.rootElement = undefined; + Domain_dragger.rootNodeLayer = undefined; + Domain_dragger.pathLayer = undefined; + Domain_dragger.mouseEnteredVar = false; + Domain_dragger.mouseButtonPressed = false; + Domain_dragger.nodeElement = undefined; + Domain_dragger.draggerObject = undefined; + + Domain_dragger.pathElement = undefined; + Domain_dragger.typus = "Domain_dragger"; + + Domain_dragger.type = function (){ + return Domain_dragger.typus; + }; + + + // TODO: We need the endPoint of the Link here! + Domain_dragger.parentNode = function (){ + return Domain_dragger.parent; + }; + + Domain_dragger.hide_dragger = function ( val ){ + Domain_dragger.pathElement.classed("hidden", val); + Domain_dragger.nodeElement.classed("hidden", val); + Domain_dragger.draggerObject.classed("hidden", val); + }; + + Domain_dragger.reDrawEverthing = function (){ + Domain_dragger.setParentProperty(Domain_dragger.parent); + }; + Domain_dragger.updateDomain = function ( newDomain ){ + + if ( graph.genericPropertySanityCheck(Domain_dragger.parent.range(), newDomain, Domain_dragger.parent.type(), + "Could not update domain", "Restoring previous domain") === false ) { + Domain_dragger.updateElement(); + return; + } + + if ( graph.propertyCheckExistenceChecker(Domain_dragger.parent, newDomain, Domain_dragger.parent.range()) === false ) + return; + + + if ( Domain_dragger.parent.labelElement() === undefined ) { + Domain_dragger.updateElement(); + return; + } + if ( Domain_dragger.parent.labelElement().attr("transform") === "translate(0,15)" || + Domain_dragger.parent.labelElement().attr("transform") === "translate(0,-15)" ) { + var prop = Domain_dragger.parent; + Domain_dragger.parent.inverse().inverse(null); + Domain_dragger.parent.inverse(null); + console.log("SPLITTING ITEMS!"); + prop.domain(newDomain); + } + else { + Domain_dragger.parent.domain(newDomain); + } + + // update the position of the new range + var rX = Domain_dragger.parent.range().x; + var rY = Domain_dragger.parent.range().y; + var dX = newDomain.x; + var dY = newDomain.y; + + // center + var cX = 0.49 * (dX + rX); + var cY = 0.49 * (dY + rY); + // put position there; + Domain_dragger.parent.labelObject().x = cX; + Domain_dragger.parent.labelObject().px = cX; + Domain_dragger.parent.labelObject().y = cY; + Domain_dragger.parent.labelObject().py = cY; + Domain_dragger.updateElement(); + + }; + + Domain_dragger.setParentProperty = function ( parentProperty, inverted ){ + Domain_dragger.invertedProperty = inverted; + var renElem; + var iP; + Domain_dragger.isLoopProperty = false; + if ( parentProperty.domain() === parentProperty.range() ) + Domain_dragger.isLoopProperty = true; + + Domain_dragger.parent = parentProperty; + renElem = parentProperty.labelObject(); + if ( inverted === true ) { + + // this is the lower element + if ( parentProperty.labelElement() && parentProperty.labelElement().attr("transform") === "translate(0,15)" ) { + // console.log("This is the lower element!"); + iP = renElem.linkRangeIntersection; + if ( renElem.linkRangeIntersection ) { + Domain_dragger.x = iP.x; + Domain_dragger.y = iP.y; + } + } + else { + // console.log("This is the upper element"); + iP = renElem.linkDomainIntersection; + if ( renElem.linkDomainIntersection ) { + Domain_dragger.x = iP.x; + Domain_dragger.y = iP.y; + } + } + } + else { + // console.log("This is single element"); + iP = renElem.linkDomainIntersection; + if ( renElem.linkDomainIntersection ) { + Domain_dragger.x = iP.x; + Domain_dragger.y = iP.y; + } + } + Domain_dragger.updateElement(); + + }; + + Domain_dragger.hideDragger = function ( val ){ + if ( Domain_dragger.pathElement ) Domain_dragger.pathElement.classed("hidden", val); + if ( Domain_dragger.nodeElement ) Domain_dragger.nodeElement.classed("hidden", val); + if ( Domain_dragger.draggerObject ) Domain_dragger.draggerObject.classed("hidden", val); + + + }; + /** BASE HANDLING FUNCTIONS ------------------------------------------------- **/ + Domain_dragger.id = function ( index ){ + if ( !arguments.length ) { + return Domain_dragger.nodeId; + } + Domain_dragger.nodeId = index; + }; + + Domain_dragger.svgPathLayer = function ( layer ){ + Domain_dragger.pathLayer = layer.append('g'); + }; + + Domain_dragger.svgRoot = function ( root ){ + if ( !arguments.length ) + return Domain_dragger.rootElement; + Domain_dragger.rootElement = root; + Domain_dragger.rootNodeLayer = Domain_dragger.rootElement.append('g'); + Domain_dragger.addMouseEvents(); + }; + + /** DRAWING FUNCTIONS ------------------------------------------------- **/ + Domain_dragger.drawNode = function (){ + Domain_dragger.pathElement = Domain_dragger.pathLayer.append('line') + .classed("classNodeDragPath", true); + Domain_dragger.pathElement.attr("x1", 0) + .attr("y1", 0) + .attr("x2", 0) + .attr("y2", 0); + + var pathData = "M 10,40 C -10,15 -10,-15 10,-40 -8.8233455,-13.641384 -36.711107,-5.1228436 -50,0 -36.696429,4.9079017 -8.6403157,13.745728 10,40 Z"; + Domain_dragger.nodeElement = Domain_dragger.rootNodeLayer.append('path').attr("d", pathData); + Domain_dragger.nodeElement.classed("classDraggerNode", true); + if ( graph.options().useAccuracyHelper() ) { + Domain_dragger.draggerObject = Domain_dragger.rootNodeLayer.append("circle"); + Domain_dragger.draggerObject.attr("r", 40) + .attr("cx", 0) + .attr("cy", 0) + .classed("superHiddenElement", true); + Domain_dragger.draggerObject.classed("superOpacityElement", !graph.options().showDraggerObject()); + } + + + }; + Domain_dragger.updateElementViaRangeDragger = function ( x, y ){ + var range_x = x; + var range_y = y; + + var dex = Domain_dragger.parent.domain().x; + var dey = Domain_dragger.parent.domain().y; + + var dir_X = x - dex; + var dir_Y = y - dey; + + var len = Math.sqrt(dir_X * dir_X + dir_Y * dir_Y); + + var nX = dir_X / len; + var nY = dir_Y / len; + + + var ep_range_x = dex + nX * Domain_dragger.parent.domain().actualRadius(); + var ep_range_y = dey + nY * Domain_dragger.parent.domain().actualRadius(); + + var angle = Math.atan2(ep_range_y - range_y, ep_range_x - range_x) * 180 / Math.PI; + + Domain_dragger.nodeElement.attr("transform", "translate(" + ep_range_x + "," + ep_range_y + ")" + "rotate(" + angle + ")"); + var dox = ep_range_x + nX * 20; + var doy = ep_range_y + nY * 20; + Domain_dragger.draggerObject.attr("transform", "translate(" + dox + "," + doy + ")"); + }; + + + Domain_dragger.updateElement = function (){ + if ( Domain_dragger.mouseButtonPressed === true || Domain_dragger.parent === undefined ) return; + + var domain = Domain_dragger.parent.domain(); + var iP = Domain_dragger.parent.labelObject().linkDomainIntersection; + if ( Domain_dragger.parent.labelElement() === undefined ) return; + if ( Domain_dragger.parent.labelElement().attr("transform") === "translate(0,15)" ) { + Domain_dragger.parent.inverse().domain(); + iP = Domain_dragger.parent.labelObject().linkRangeIntersection; + + } + var range_x = domain.x; + var range_y = domain.y; + + + if ( iP === undefined ) return; + var ep_range_x = iP.x; + var ep_range_y = iP.y; + + var dx = range_x - ep_range_x; + var dy = range_y - ep_range_y; + var len = Math.sqrt(dx * dx + dy * dy); + + var nX = dx / len; + var nY = dy / len; + + var dox = ep_range_x - nX * 20; + var doy = ep_range_y - nY * 20; + var angle = Math.atan2(ep_range_y - range_y, ep_range_x - range_x) * 180 / Math.PI + 180; + + Domain_dragger.nodeElement.attr("transform", "translate(" + ep_range_x + "," + ep_range_y + ")" + "rotate(" + angle + ")"); + Domain_dragger.draggerObject.attr("transform", "translate(" + dox + "," + doy + ")"); + }; + + /** MOUSE HANDLING FUNCTIONS ------------------------------------------------- **/ + + Domain_dragger.addMouseEvents = function (){ + var rootLayer = Domain_dragger.rootNodeLayer.selectAll("*"); + rootLayer.on("mouseover", Domain_dragger.onMouseOver) + .on("mouseout", Domain_dragger.onMouseOut) + .on("click", function (){ + }) + .on("dblclick", function (){ + }) + .on("mousedown", Domain_dragger.mouseDown) + .on("mouseup", Domain_dragger.mouseUp); + }; + + Domain_dragger.mouseDown = function (){ + Domain_dragger.nodeElement.style("cursor", "move"); + Domain_dragger.nodeElement.classed("classDraggerNodeHovered", true); + Domain_dragger.mouseButtonPressed = true; + }; + + Domain_dragger.mouseUp = function (){ + Domain_dragger.nodeElement.style("cursor", "auto"); + Domain_dragger.nodeElement.classed("classDraggerNodeHovered", false); + Domain_dragger.mouseButtonPressed = false; + }; + + + Domain_dragger.mouseEntered = function ( p ){ + if ( !arguments.length ) return Domain_dragger.mouseEnteredVar; + Domain_dragger.mouseEnteredVar = p; + return Domain_dragger; + }; + + Domain_dragger.selectedViaTouch = function ( val ){ + Domain_dragger.nodeElement.classed("classDraggerNode", !val); + Domain_dragger.nodeElement.classed("classDraggerNodeHovered", val); + + }; + + Domain_dragger.onMouseOver = function (){ + if ( Domain_dragger.mouseEntered() ) { + return; + } + Domain_dragger.nodeElement.classed("classDraggerNode", false); + Domain_dragger.nodeElement.classed("classDraggerNodeHovered", true); + var selectedNode = Domain_dragger.rootElement.node(), + nodeContainer = selectedNode.parentNode; + nodeContainer.appendChild(selectedNode); + + Domain_dragger.mouseEntered(true); + + }; + Domain_dragger.onMouseOut = function (){ + if ( Domain_dragger.mouseButtonPressed === true ) + return; + Domain_dragger.nodeElement.classed("classDraggerNodeHovered", false); + Domain_dragger.nodeElement.classed("classDraggerNode", true); + Domain_dragger.mouseEntered(false); + }; + + Domain_dragger.setPosition = function ( x, y ){ + var range_x = Domain_dragger.parent.range().x; + var range_y = Domain_dragger.parent.range().y; + + // var position of the rangeEndPoint + var ep_range_x = x; + var ep_range_y = y; + + // offset for dragger object + var dx = range_x - ep_range_x; + var dy = range_y - ep_range_y; + + var len = Math.sqrt(dx * dx + dy * dy); + + var nX = dx / len; + var nY = dy / len; + var dox = ep_range_x + nX * 20; + var doy = ep_range_y + nY * 20; + + var angle = Math.atan2(range_y - ep_range_y, range_x - ep_range_x) * 180 / Math.PI + 180; + + Domain_dragger.nodeElement.attr("transform", "translate(" + ep_range_x + "," + ep_range_y + ")" + "rotate(" + angle + ")"); + Domain_dragger.draggerObject.attr("transform", "translate(" + dox + "," + doy + ")"); + + Domain_dragger.x = x; + Domain_dragger.y = y; + + }; + + Domain_dragger.setAdditionalClassForClass_dragger = function ( name, val ){ + // console.log("Class_dragger should sett the class here") + // Class_dragger.nodeElement.classed(name,val); + + }; + return Domain_dragger; + }; + + + + +/***/ }), +/* 71 */ +/***/ (function(module, exports, __webpack_require__) { + + var CenteringTextElement = __webpack_require__(14); + var elementTools = __webpack_require__(63)(); + var math = __webpack_require__(43)(); + module.exports = function ( graph ){ + /** variable defs **/ + var ShadowClone = {}; + ShadowClone.nodeId = 10003; + ShadowClone.parent = undefined; + ShadowClone.s_x = 0; + ShadowClone.s_y = 0; + ShadowClone.e_x = 0; + ShadowClone.e_y = 0; + ShadowClone.rootElement = undefined; + ShadowClone.rootNodeLayer = undefined; + ShadowClone.pathLayer = undefined; + ShadowClone.nodeElement = undefined; + ShadowClone.pathElement = undefined; + ShadowClone.typus = "shadowClone"; + + + ShadowClone.type = function (){ + return ShadowClone.typus; + }; + + // TODO: We need the endPoint of the Link here! + ShadowClone.parentNode = function (){ + return ShadowClone.parent; + }; + + ShadowClone.setParentProperty = function ( parentProperty, inverted ){ + ShadowClone.invertedProperty = inverted; + ShadowClone.parent = parentProperty; + var renElment; + if ( inverted === true ) { + renElment = parentProperty.inverse().labelObject(); + if ( renElment.linkRangeIntersection && renElment.linkDomainIntersection ) { + var iiP_range = renElment.linkDomainIntersection; + var iiP_domain = renElment.linkRangeIntersection; + ShadowClone.s_x = iiP_domain.x; + ShadowClone.s_y = iiP_domain.y; + ShadowClone.e_x = iiP_range.x; + ShadowClone.e_y = iiP_range.y; + } + } + else { + renElment = parentProperty.labelObject(); + + if ( renElment.linkRangeIntersection && renElment.linkDomainIntersection ) { + var iP_range = renElment.linkRangeIntersection; + var iP_domain = renElment.linkDomainIntersection; + ShadowClone.s_x = iP_domain.x; + ShadowClone.s_y = iP_domain.y; + ShadowClone.e_x = iP_range.x; + ShadowClone.e_y = iP_range.y; + } + + } + + ShadowClone.rootNodeLayer.remove(); + ShadowClone.rootNodeLayer = ShadowClone.rootElement.append('g'); + ShadowClone.rootNodeLayer.datum(parentProperty); + + // ShadowClone.pathElement.remove(); + // ShadowClone.pathElement = ShadowClone.pathLayer.append('line'); + // + // ShadowClone.pathElement.attr("x1", ShadowClone.s_x) + // .attr("y1", ShadowClone.s_y) + // .attr("x2", ShadowClone.e_x) + // .attr("y2", ShadowClone.e_y); + ShadowClone.pathElement.remove(); + ShadowClone.pathElement = ShadowClone.pathLayer.append('line'); + ShadowClone.markerElement = ShadowClone.pathLayer.append("marker"); + ShadowClone.markerElement.attr("id", "shadowCloneMarker"); + ShadowClone.pathElement.attr("x1", ShadowClone.e_x) + .attr("y1", ShadowClone.e_y) + .attr("x2", ShadowClone.s_x) + .attr("y2", ShadowClone.s_y); + ShadowClone.pathElement.classed(parentProperty.linkType(), true); + + if ( parentProperty.markerElement() ) { + ShadowClone.markerElement.attr("viewBox", parentProperty.markerElement().attr("viewBox")) + .attr("markerWidth", parentProperty.markerElement().attr("markerWidth")) + .attr("markerHeight", parentProperty.markerElement().attr("markerHeight")) + .attr("orient", parentProperty.markerElement().attr("orient")); + + var markerPath = parentProperty.markerElement().select("path"); + ShadowClone.markerElement.append("path") + .attr("d", markerPath.attr("d")) + .classed(parentProperty.markerType(), true); + + ShadowClone.pathElement.attr("marker-end", "url(#" + "shadowCloneMarker" + ")"); + ShadowClone.markerElement.classed("hidden", !elementTools.isDatatypeProperty(parentProperty)); + } + var rect = ShadowClone.rootNodeLayer.append("rect") + .classed(parentProperty.styleClass(), true) + .classed("property", true) + .attr("x", -parentProperty.width() / 2) + .attr("y", -parentProperty.height() / 2) + .attr("width", parentProperty.width()) + .attr("height", parentProperty.height()); + + if ( parentProperty.visualAttributes() ) { + rect.classed(parentProperty.visualAttributes(), true); + } + rect.classed("datatype", false); + var bgColor = parentProperty.backgroundColor(); + + if ( parentProperty.attributes().indexOf("deprecated") > -1 ) { + bgColor = undefined; + rect.classed("deprecatedproperty", true); + } else { + rect.classed("deprecatedproperty", false); + } + rect.style("fill", bgColor); + + // add Text; + var equivalentsString = parentProperty.equivalentsString(); + var suffixForFollowingEquivalents = equivalentsString ? "," : ""; + + + var textElement = new CenteringTextElement(ShadowClone.rootNodeLayer, bgColor); + textElement.addText(parentProperty.labelForCurrentLanguage(), "", suffixForFollowingEquivalents); + textElement.addEquivalents(equivalentsString); + textElement.addSubText(parentProperty.indicationString()); + + + var cx = 0.5 * (ShadowClone.s_x + ShadowClone.e_x); + var cy = 0.5 * (ShadowClone.s_y + ShadowClone.e_y); + ShadowClone.rootNodeLayer.attr("transform", "translate(" + cx + "," + cy + ")"); + ShadowClone.rootNodeLayer.classed("hidden", true); + ShadowClone.pathElement.classed("hidden", true); + + + }; + + ShadowClone.hideClone = function ( val ){ + if ( ShadowClone.rootNodeLayer ) ShadowClone.rootNodeLayer.classed("hidden", val); + if ( ShadowClone.pathElement ) ShadowClone.pathElement.classed("hidden", val); + }; + + ShadowClone.hideParentProperty = function ( val ){ + + var labelObj = ShadowClone.parent.labelObject(); + if ( labelObj ) { + if ( ShadowClone.parent.labelElement().attr("transform") === "translate(0,15)" || + ShadowClone.parent.labelElement().attr("transform") === "translate(0,-15)" ) + ShadowClone.parent.inverse().hide(val); + + + } + ShadowClone.parent.hide(val); + + + }; + + /** BASE HANDLING FUNCTIONS ------------------------------------------------- **/ + ShadowClone.id = function ( index ){ + if ( !arguments.length ) { + return ShadowClone.nodeId; + } + ShadowClone.nodeId = index; + }; + + ShadowClone.svgPathLayer = function ( layer ){ + ShadowClone.pathLayer = layer.append('g'); + }; + + ShadowClone.svgRoot = function ( root ){ + if ( !arguments.length ) + return ShadowClone.rootElement; + ShadowClone.rootElement = root; + ShadowClone.rootNodeLayer = ShadowClone.rootElement.append('g'); + + }; + + /** DRAWING FUNCTIONS ------------------------------------------------- **/ + ShadowClone.drawClone = function (){ + ShadowClone.pathElement = ShadowClone.pathLayer.append('line'); + + ShadowClone.pathElement.attr("x1", 0) + .attr("y1", 0) + .attr("x2", 0) + .attr("y2", 0); + + }; + + + ShadowClone.updateElement = function (){ + ShadowClone.pathElement.attr("x1", ShadowClone.e_x) + .attr("y1", ShadowClone.e_y) + .attr("x2", ShadowClone.s_x) + .attr("y2", ShadowClone.s_y); + + var cx = 0.5 * (ShadowClone.s_x + ShadowClone.e_x); + var cy = 0.5 * (ShadowClone.s_y + ShadowClone.e_y); + ShadowClone.rootNodeLayer.attr("transform", "translate(" + cx + "," + cy + ")"); + }; + + ShadowClone.setInitialPosition = function (){ + + var renElment = ShadowClone.parent.labelObject(); + if ( renElment.linkRangeIntersection && renElment.linkDomainIntersection ) { + var iP_range = renElment.linkRangeIntersection; + var iP_domain = renElment.linkDomainIntersection; + ShadowClone.e_x = iP_domain.x; + ShadowClone.e_y = iP_domain.y; + ShadowClone.s_x = iP_range.x; + ShadowClone.s_y = iP_range.y; + } + ShadowClone.updateElement(); + return; + // + // var rex=ShadowClone.parent.range().x; + // var rey=ShadowClone.parent.range().y; + // + // + // var dex=ShadowClone.parent.domain().x; + // var dey=ShadowClone.parent.domain().y; + // + // + // var dir_X= rex-dex; + // var dir_Y= rey-dey; + // + // var len=Math.sqrt(dir_X*dir_X+dir_Y*dir_Y); + // var nX=dir_X/len; + // var nY=dir_Y/len; + // ShadowClone.s_x=rex-nX*ShadowClone.parent.range().actualRadius(); + // ShadowClone.s_y=rey-nY*ShadowClone.parent.range().actualRadius(); + // + // ShadowClone.e_x=dex+nX*ShadowClone.parent.domain().actualRadius(); + // ShadowClone.e_y=dey+nY*ShadowClone.parent.domain().actualRadius(); + // ShadowClone.updateElement(); + + }; + ShadowClone.setPositionDomain = function ( e_x, e_y ){ + + var rex = ShadowClone.parent.range().x; + var rey = ShadowClone.parent.range().y; + + + if ( elementTools.isDatatype(ShadowClone.parent.range()) === true ) { + var intersection = math.calculateIntersection({ x: e_x, y: e_y }, ShadowClone.parent.range(), 0); + ShadowClone.s_x = intersection.x; + ShadowClone.s_y = intersection.y; + } else { + var dir_X = rex - e_x; + var dir_Y = rey - e_y; + + var len = Math.sqrt(dir_X * dir_X + dir_Y * dir_Y); + + var nX = dir_X / len; + var nY = dir_Y / len; + ShadowClone.s_x = rex - nX * ShadowClone.parent.range().actualRadius(); + ShadowClone.s_y = rey - nY * ShadowClone.parent.range().actualRadius(); + + } + + + ShadowClone.e_x = e_x; + ShadowClone.e_y = e_y; + ShadowClone.updateElement(); + }; + + ShadowClone.setPosition = function ( s_x, s_y ){ + ShadowClone.s_x = s_x; + ShadowClone.s_y = s_y; + + // add normalized dir; + + var dex = ShadowClone.parent.domain().x; + var dey = ShadowClone.parent.domain().y; + + var dir_X = s_x - dex; + var dir_Y = s_y - dey; + + var len = Math.sqrt(dir_X * dir_X + dir_Y * dir_Y); + + var nX = dir_X / len; + var nY = dir_Y / len; + + + ShadowClone.e_x = dex + nX * ShadowClone.parent.domain().actualRadius(); + ShadowClone.e_y = dey + nY * ShadowClone.parent.domain().actualRadius(); + + + ShadowClone.updateElement(); + + + }; + + + /** MOUSE HANDLING FUNCTIONS ------------------------------------------------- **/ + + return ShadowClone; + }; + + + + +/***/ }), +/* 72 */ +/***/ (function(module, exports) { + + module.exports = function ( graph ){ + /** variable defs **/ + var prefixRepresentationModule = {}; + + var currentPrefixModel; + + prefixRepresentationModule.updatePrefixModel = function (){ + currentPrefixModel = graph.options().prefixList(); + }; + + + prefixRepresentationModule.validURL = function ( url ){ + return validURL(url); + }; + function validURL( str ){ + var urlregex = /^(https?|ftp):\/\/([a-zA-Z0-9.-]+(:[a-zA-Z0-9.&%$-]+)*@)*((25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9][0-9]?)(\.(25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9]?[0-9])){3}|([a-zA-Z0-9-]+\.)*[a-zA-Z0-9-]+\.(com|edu|gov|int|mil|net|org|biz|arpa|info|name|pro|aero|coop|museum|[a-zA-Z]{2}))(:[0-9]+)*(\/($|[a-zA-Z0-9.,?'\\+&%$#=~_-]+))*$/; + return urlregex.test(str); + } + + function splitURLIntoBaseAndResource( fullURL ){ + var splitedURL = { base: "", resource: "" }; + if ( fullURL === undefined ) { + splitedURL = { base: "ERROR", resource: "NOT FOUND" }; + return splitedURL; + } + + var resource, base; + // check if there is a last hashTag + if ( fullURL.indexOf("#") > -1 ) { + resource = fullURL.substring(fullURL.lastIndexOf('#') + 1); + base = fullURL.substring(0, fullURL.length - resource.length); + // overwrite base if it is ontologyIri; + if ( base === graph.options().getGeneralMetaObjectProperty('iri') ) { + base = ":"; + } + splitedURL.base = base; + splitedURL.resource = resource; + } else { + resource = fullURL.substring(fullURL.lastIndexOf('/') + 1); + base = fullURL.substring(0, fullURL.length - resource.length); + // overwrite base if it is ontologyIri; + if ( base === graph.options().getGeneralMetaObjectProperty('iri') ) { + base = ":"; + } + splitedURL.base = base; + splitedURL.resource = resource; + } + return splitedURL; + } + + prefixRepresentationModule.getPrefixRepresentationForFullURI = function ( fullURL ){ + prefixRepresentationModule.updatePrefixModel(); + var splittedURL = splitURLIntoBaseAndResource(fullURL); + + // lazy approach , for + // loop over prefix model + for ( var name in currentPrefixModel ) { + if ( currentPrefixModel.hasOwnProperty(name) ) { + // THIS IS CASE SENSITIVE! + if ( currentPrefixModel[name] === splittedURL.base ) { + return name + ":" + splittedURL.resource; + } + } + } + + if ( splittedURL.base === ":" ) { + return ":" + splittedURL.resource; + } + + return fullURL; + }; + + + return prefixRepresentationModule; + }; + + + + +/***/ }), +/* 73 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var _ = __webpack_require__(58); + + module.exports = function (){ + + var DEFAULT_STATE = true; + var COLOR_MODES = [ + { type: "same", range: [d3.rgb("#36C"), d3.rgb("#36C")] }, + { type: "gradient", range: [d3.rgb("#36C"), d3.rgb("#EE2867")] } // taken from LD-VOWL + ]; + + var filter = {}, + nodes, + properties, + enabled = DEFAULT_STATE, + filteredNodes, + filteredProperties, + colorModeType = "same"; + + + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + + var externalElements = filterExternalElements(nodes.concat(properties)); + + if ( enabled ) { + setColorsForExternals(externalElements); + } else { + resetBackgroundColors(externalElements); + } + + filteredNodes = nodes; + filteredProperties = properties; + }; + + function filterExternalElements( elements ){ + return elements.filter(function ( element ){ + if ( element.visualAttributes().indexOf("deprecated") >= 0 ) { + // deprecated is the only attribute which has preference over external + return false; + } + + return element.attributes().indexOf("external") >= 0; + }); + } + + function setColorsForExternals( elements ){ + var iriMap = mapExternalsToBaseUri(elements); + var entries = iriMap.entries(); + + var colorScale = d3.scale.linear() + .domain([0, entries.length - 1]) + .range(_.find(COLOR_MODES, { type: colorModeType }).range) + .interpolate(d3.interpolateHsl); + + for ( var i = 0; i < entries.length; i++ ) { + var groupedElements = entries[i].value; + setBackgroundColorForElements(groupedElements, colorScale(i)); + } + } + + function mapExternalsToBaseUri( elements ){ + var map = d3.map(); + + elements.forEach(function ( element ){ + var baseIri = element.baseIri(); + + if ( !map.has(baseIri) ) { + map.set(baseIri, []); + } + map.get(baseIri).push(element); + }); + + return map; + } + + function setBackgroundColorForElements( elements, backgroundColor ){ + elements.forEach(function ( element ){ + element.backgroundColor(backgroundColor); + }); + } + + function resetBackgroundColors( elements ){ + console.log("Resetting color"); + elements.forEach(function ( element ){ + element.backgroundColor(null); + }); + } + + filter.colorModeType = function ( p ){ + if ( !arguments.length ) return colorModeType; + colorModeType = p; + return filter; + }; + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + filter.reset = function (){ + enabled = DEFAULT_STATE; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 74 */ +/***/ (function(module, exports) { + + /** + * This module abuses the filter function a bit like the statistics module. Nothing is filtered. + * + * @returns {{}} + */ + + + module.exports = function ( graph ){ + + var DEFAULT_STATE = false; + + var filter = {}, + nodes, + properties, + enabled = DEFAULT_STATE, + filteredNodes, + filteredProperties; + + + /** + * If enabled, redundant details won't be drawn anymore. + * @param untouchedNodes + * @param untouchedProperties + */ + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + graph.options().compactNotation(enabled); + filteredNodes = nodes; + filteredProperties = properties; + }; + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + filter.reset = function (){ + enabled = DEFAULT_STATE; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }), +/* 75 */ +/***/ (function(module, exports, __webpack_require__) { + + var elementTools = __webpack_require__(63)(); + var filterTools = __webpack_require__(76)(); + + module.exports = function (){ + + var filter = {}, + nodes, + properties, + enabled = false, + filteredNodes, + filteredProperties; + + + /** + * If enabled, all datatypes and literals including connected properties are filtered. + * @param untouchedNodes + * @param untouchedProperties + */ + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + + if ( this.enabled() ) { + removeDatatypesAndLiterals(); + } + + filteredNodes = nodes; + filteredProperties = properties; + }; + + function removeDatatypesAndLiterals(){ + var filteredData = filterTools.filterNodesAndTidy(nodes, properties, isNoDatatypeOrLiteral); + + nodes = filteredData.nodes; + properties = filteredData.properties; + } + + function isNoDatatypeOrLiteral( node ){ + return !elementTools.isDatatype(node); + } + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }), +/* 76 */ +/***/ (function(module, exports, __webpack_require__) { + + var elementTools = __webpack_require__(63)(); + + module.exports = (function (){ + + var tools = {}; + + /** + * Filters the passed nodes and removes dangling properties. + * @param nodes + * @param properties + * @param shouldKeepNode function that returns true if the node should be kept + * @returns {{nodes: Array, properties: Array}} the filtered nodes and properties + */ + tools.filterNodesAndTidy = function ( nodes, properties, shouldKeepNode ){ + var removedNodes = __webpack_require__(62)(), + cleanedNodes = [], + cleanedProperties = []; + + nodes.forEach(function ( node ){ + if ( shouldKeepNode(node) ) { + cleanedNodes.push(node); + } else { + removedNodes.add(node); + } + }); + + properties.forEach(function ( property ){ + if ( propertyHasVisibleNodes(removedNodes, property) ) { + cleanedProperties.push(property); + } else if ( elementTools.isDatatypeProperty(property) ) { + // Remove floating datatypes/literals, because they belong to their datatype property + var index = cleanedNodes.indexOf(property.range()); + if ( index >= 0 ) { + cleanedNodes.splice(index, 1); + } + } + }); + + return { + nodes: cleanedNodes, + properties: cleanedProperties + }; + }; + + /** + * Returns true, if the domain and the range of this property have not been removed. + * @param removedNodes + * @param property + * @returns {boolean} true if property isn't dangling + */ + function propertyHasVisibleNodes( removedNodes, property ){ + return !removedNodes.has(property.domain()) && !removedNodes.has(property.range()); + } + + + return function (){ + return tools; + }; + })(); + + +/***/ }), +/* 77 */ +/***/ (function(module, exports, __webpack_require__) { + + var OwlDisjointWith = __webpack_require__(46); + + module.exports = function (){ + + var filter = {}, + nodes, + properties, + // According to the specification enabled by default + enabled = true, + filteredNodes, + filteredProperties; + + + /** + * If enabled, all disjoint with properties are filtered. + * @param untouchedNodes + * @param untouchedProperties + */ + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + + if ( this.enabled() ) { + removeDisjointWithProperties(); + } + + filteredNodes = nodes; + filteredProperties = properties; + }; + + function removeDisjointWithProperties(){ + var cleanedProperties = [], + i, l, property; + + for ( i = 0, l = properties.length; i < l; i++ ) { + property = properties[i]; + + if ( !(property instanceof OwlDisjointWith) ) { + cleanedProperties.push(property); + } + } + + properties = cleanedProperties; + } + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }), +/* 78 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( graph ){ + var focuser = {}, + focusedElement; + var elementTools = webvowl.util.elementTools(); + focuser.handle = function ( selectedElement, forced ){ + // Don't display details on a drag event, which will be prevented + if ( d3.event && d3.event.defaultPrevented && forced === undefined ) { + return; + } + + if ( focusedElement !== undefined ) { + focusedElement.toggleFocus(); + } + + if ( focusedElement !== selectedElement && selectedElement ) { + selectedElement.toggleFocus(); + focusedElement = selectedElement; + } else { + focusedElement = undefined; + } + if ( focusedElement && focusedElement.focused() ) { + graph.options().editSidebar().updateSelectionInformation(focusedElement); + if ( elementTools.isProperty(selectedElement) === true ) { + var inversed = false; + if ( selectedElement.inverse() ) { + inversed = true; + } + graph.activateHoverElementsForProperties(true, selectedElement, inversed, graph.isTouchDevice()); + } + else { + graph.activateHoverElements(true, selectedElement, graph.isTouchDevice()); + } + } + else { + graph.options().editSidebar().updateSelectionInformation(undefined); + graph.removeEditElements(); + } + }; + + /** + * Removes the focus if an element is focussed. + */ + focuser.reset = function (){ + if ( focusedElement ) { + focusedElement.toggleFocus(); + focusedElement = undefined; + } + }; + + return focuser; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 79 */ +/***/ (function(module, exports) { + + /** @WORKAROUND CODE: + * clears empty literals that are provided by owl2vowl: 0.2.2x*/ + + + module.exports = function (){ + + var filter = {}, + enabled = true, + filteredNodes, + removedNodes, + filteredProperties; + + filter.enabled = function ( val ){ + if ( !arguments.length ) { + return enabled; + } + enabled = val; + }; + + filter.filter = function ( nodes, properties ){ + if ( enabled === false ) { + filteredNodes = nodes; + filteredProperties = properties; + removedNodes = []; + return; + } + var literalUsageMap = []; + var thingUsageMap = []; + var node; + for ( var i = 0; i < properties.length; i++ ) { + // get property range; + var prop = properties[i]; + + // checking for literals + if ( prop.range() ) { + node = prop.range(); + if ( node.type() === "rdfs:Literal" ) { + literalUsageMap[node.id()] = 1; + } + } + // checking for thing + if ( prop.range() ) { + node = prop.range(); + if ( node.type() === "owl:Thing" ) { + thingUsageMap[node.id()] = 1; + } + } + if ( prop.domain() ) { + node = prop.domain(); + if ( node.type() === "owl:Thing" ) { + thingUsageMap[node.id()] = 1; + } + } + + } + var nodesToRemove = []; + var newNodes = []; + // todo: test and make it faster + for ( i = 0; i < nodes.length; i++ ) { + var nodeId = nodes[i].id(); + if ( nodes[i].type() === "rdfs:Literal" ) { + if ( literalUsageMap[nodeId] === undefined ) { + nodesToRemove.push(nodeId); + } + else { + newNodes.push(nodes[i]); + } + // check for node type == OWL:THING + } else if ( nodes[i].type() === "owl:Thing" ) { + if ( thingUsageMap[nodeId] === undefined ) { + nodesToRemove.push(nodeId); + } + else { + newNodes.push(nodes[i]); + } + } else { + newNodes.push(nodes[i]); + } + } + + filteredNodes = newNodes; + filteredProperties = properties; + removedNodes = nodesToRemove; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.removedNodes = function (){ + return removedNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }), +/* 80 */ +/***/ (function(module, exports, __webpack_require__) { + + var elementTools = __webpack_require__(63)(); + var filterTools = __webpack_require__(76)(); + + module.exports = function ( menu ){ + + var filter = {}, + nodes, + properties, + enabled = true, + filteredNodes, + filteredProperties, + maxDegreeSetter, + degreeGetter, + lastFiltedDegree, + degreeSetter; + + + var NODE_COUNT_LIMIT_FOR_AUTO_ENABLING = 50; + + + filter.initialize = function ( nodes, properties ){ + lastFiltedDegree = -1; + var maxLinkCount = findMaxLinkCount(nodes); + if ( maxDegreeSetter instanceof Function ) { + maxDegreeSetter(maxLinkCount); + } + + menu.setDefaultDegreeValue(findAutoDefaultDegree(nodes, properties, maxLinkCount)); + var defaultDegree = findDefaultDegree(maxLinkCount); + if ( degreeSetter instanceof Function ) { + degreeSetter(defaultDegree); + if ( defaultDegree > 0 ) { + menu.highlightForDegreeSlider(true); + menu.getGraphObject().setFilterWarning(true); + + } + } else { + console.error("No degree setter function set."); + } + }; + + function findAutoDefaultDegree( nodes, properties, maxDegree ){ + for ( var degree = 0; degree < maxDegree; degree++ ) { + var filteredData = filterByNodeDegree(nodes, properties, degree); + + if ( filteredData.nodes.length <= NODE_COUNT_LIMIT_FOR_AUTO_ENABLING ) { + return degree; + } + } + return 0; + } + + function findDefaultDegree( maxDegree ){ + var globalDegOfFilter = menu.getGraphObject().getGlobalDOF(); + if ( globalDegOfFilter >= 0 ) { + if ( globalDegOfFilter <= maxDegree ) { + return globalDegOfFilter; + } else { + menu.getGraphObject().setGlobalDOF(maxDegree); + return maxDegree; + } + } + return menu.getDefaultDegreeValue(); + } + + /** + * If enabled, all nodes are filter by their node degree. + * @param untouchedNodes + * @param untouchedProperties + */ + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + + if ( this.enabled() ) { + if ( degreeGetter instanceof Function ) { + filterByNodeDegreeAndApply(degreeGetter()); + } else { + console.error("No degree query function set."); + } + } + + filteredNodes = nodes; + filteredProperties = properties; + + if ( filteredNodes.length === 0 ) { + degreeSetter(0); + filteredNodes = untouchedNodes; + filteredProperties = untouchedProperties; + } + lastFiltedDegree = degreeGetter(); + }; + + function findMaxLinkCount( nodes ){ + var maxLinkCount = 0; + for ( var i = 0, l = nodes.length; i < l; i++ ) { + var linksWithoutDatatypes = filterOutDatatypes(nodes[i].links()); + + maxLinkCount = Math.max(maxLinkCount, linksWithoutDatatypes.length); + } + return maxLinkCount; + } + + function filterOutDatatypes( links ){ + return links.filter(function ( link ){ + return !elementTools.isDatatypeProperty(link.property()); + }); + } + + function filterByNodeDegreeAndApply( minDegree ){ + var filteredData = filterByNodeDegree(nodes, properties, minDegree); + nodes = filteredData.nodes; + properties = filteredData.properties; + } + + function filterByNodeDegree( nodes, properties, minDegree ){ + return filterTools.filterNodesAndTidy(nodes, properties, hasRequiredDegree(minDegree)); + } + + function hasRequiredDegree( minDegree ){ + return function ( node ){ + return filterOutDatatypes(node.links()).length >= minDegree; + }; + } + + filter.setMaxDegreeSetter = function ( _maxDegreeSetter ){ + maxDegreeSetter = _maxDegreeSetter; + }; + + filter.setDegreeGetter = function ( _degreeGetter ){ + degreeGetter = _degreeGetter; + }; + + filter.setDegreeSetter = function ( _degreeSetter ){ + degreeSetter = _degreeSetter; + }; + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }), +/* 81 */ +/***/ (function(module, exports) { + + /** + * This module abuses the filter function a bit like the statistics module. Nothing is filtered. + * + * @returns {{}} + */ + module.exports = function ( graph ){ + + var DEFAULT_STATE = true; + + var filter = {}, + nodes, + properties, + enabled = DEFAULT_STATE, + filteredNodes, + filteredProperties; + + + /** + * If enabled, the scaling of nodes according to individuals will be enabled. + * @param untouchedNodes + * @param untouchedProperties + */ + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + + graph.options().scaleNodesByIndividuals(enabled); + + filteredNodes = nodes; + filteredProperties = properties; + }; + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + filter.reset = function (){ + enabled = DEFAULT_STATE; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }), +/* 82 */ +/***/ (function(module, exports, __webpack_require__) { + + var elementTools = __webpack_require__(63)(); + + + module.exports = function (){ + + var filter = {}, + nodes, + properties, + enabled = false, + filteredNodes, + filteredProperties; + + + /** + * If enabled, all object properties and things without any other property are filtered. + * @param untouchedNodes + * @param untouchedProperties + */ + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + + if ( this.enabled() ) { + removeObjectProperties(); + } + + filteredNodes = nodes; + filteredProperties = properties; + }; + + function removeObjectProperties(){ + properties = properties.filter(isNoObjectProperty); + nodes = nodes.filter(isNoFloatingThing); + } + + function isNoObjectProperty( property ){ + return !elementTools.isObjectProperty(property); + } + + function isNoFloatingThing( node ){ + var isNoThing = !elementTools.isThing(node); + var hasNonFilteredProperties = hasPropertiesOtherThanObjectProperties(node, properties); + return isNoThing || hasNonFilteredProperties; + } + + function hasPropertiesOtherThanObjectProperties( node, properties ){ + for ( var i = 0; i < properties.length; i++ ) { + var property = properties[i]; + if ( property.domain() !== node && property.range() !== node ) { + continue; + } + + if ( isNoObjectProperty(property) ) { + return true; + } + } + + return false; + } + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }), +/* 83 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var _ = __webpack_require__(84); + var elementTools = __webpack_require__(63)(); + + module.exports = function (){ + var pap = {}, + enabled = false, + pinnedElements = []; + + pap.addPinnedElement = function ( element ){ + // check if element is already in list + var indexInArray = pinnedElements.indexOf(element); + if ( indexInArray === -1 ) { + pinnedElements.push(element); + } + }; + + pap.handle = function ( selection, forced ){ + if ( !enabled ) { + return; + } + + if ( !forced ) { + if ( wasNotDragged() ) { + return; + } + } + if ( elementTools.isProperty(selection) ) { + if ( selection.inverse() && selection.inverse().pinned() ) { + return; + } else if ( hasNoParallelProperties(selection) ) { + return; + } + } + + if ( !selection.pinned() ) { + selection.drawPin(); + pap.addPinnedElement(selection); + } + }; + + function wasNotDragged(){ + return !d3.event.defaultPrevented; + } + + function hasNoParallelProperties( property ){ + return _.intersection(property.domain().links(), property.range().links()).length === 1; + } + + pap.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return pap; + }; + + pap.reset = function (){ + pinnedElements.forEach(function ( element ){ + element.removePin(); + }); + // Clear the array of stored nodes + pinnedElements.length = 0; + }; + + return pap; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 84 */ +/***/ (function(module, exports, __webpack_require__) { + + module.exports = { + 'chunk': __webpack_require__(85), + 'compact': __webpack_require__(105), + 'concat': __webpack_require__(106), + 'difference': __webpack_require__(114), + 'differenceBy': __webpack_require__(167), + 'differenceWith': __webpack_require__(229), + 'drop': __webpack_require__(230), + 'dropRight': __webpack_require__(231), + 'dropRightWhile': __webpack_require__(232), + 'dropWhile': __webpack_require__(234), + 'fill': __webpack_require__(235), + 'findIndex': __webpack_require__(239), + 'findLastIndex': __webpack_require__(240), + 'first': __webpack_require__(241), + 'flatten': __webpack_require__(243), + 'flattenDeep': __webpack_require__(244), + 'flattenDepth': __webpack_require__(245), + 'fromPairs': __webpack_require__(246), + 'head': __webpack_require__(242), + 'indexOf': __webpack_require__(247), + 'initial': __webpack_require__(248), + 'intersection': __webpack_require__(249), + 'intersectionBy': __webpack_require__(252), + 'intersectionWith': __webpack_require__(253), + 'join': __webpack_require__(254), + 'last': __webpack_require__(228), + 'lastIndexOf': __webpack_require__(255), + 'nth': __webpack_require__(257), + 'pull': __webpack_require__(259), + 'pullAll': __webpack_require__(260), + 'pullAllBy': __webpack_require__(263), + 'pullAllWith': __webpack_require__(264), + 'pullAt': __webpack_require__(265), + 'remove': __webpack_require__(272), + 'reverse': __webpack_require__(273), + 'slice': __webpack_require__(274), + 'sortedIndex': __webpack_require__(275), + 'sortedIndexBy': __webpack_require__(278), + 'sortedIndexOf': __webpack_require__(279), + 'sortedLastIndex': __webpack_require__(280), + 'sortedLastIndexBy': __webpack_require__(281), + 'sortedLastIndexOf': __webpack_require__(282), + 'sortedUniq': __webpack_require__(283), + 'sortedUniqBy': __webpack_require__(285), + 'tail': __webpack_require__(286), + 'take': __webpack_require__(287), + 'takeRight': __webpack_require__(288), + 'takeRightWhile': __webpack_require__(289), + 'takeWhile': __webpack_require__(290), + 'union': __webpack_require__(291), + 'unionBy': __webpack_require__(295), + 'unionWith': __webpack_require__(296), + 'uniq': __webpack_require__(297), + 'uniqBy': __webpack_require__(298), + 'uniqWith': __webpack_require__(299), + 'unzip': __webpack_require__(300), + 'unzipWith': __webpack_require__(301), + 'without': __webpack_require__(302), + 'xor': __webpack_require__(303), + 'xorBy': __webpack_require__(305), + 'xorWith': __webpack_require__(306), + 'zip': __webpack_require__(307), + 'zipObject': __webpack_require__(308), + 'zipObjectDeep': __webpack_require__(312), + 'zipWith': __webpack_require__(314) + }; + + +/***/ }), +/* 85 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86), + isIterateeCall = __webpack_require__(87), + toInteger = __webpack_require__(100); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeCeil = Math.ceil, + nativeMax = Math.max; + + /** + * Creates an array of elements split into groups the length of `size`. + * If `array` can't be split evenly, the final chunk will be the remaining + * elements. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to process. + * @param {number} [size=1] The length of each chunk + * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. + * @returns {Array} Returns the new array of chunks. + * @example + * + * _.chunk(['a', 'b', 'c', 'd'], 2); + * // => [['a', 'b'], ['c', 'd']] + * + * _.chunk(['a', 'b', 'c', 'd'], 3); + * // => [['a', 'b', 'c'], ['d']] + */ + function chunk(array, size, guard) { + if ((guard ? isIterateeCall(array, size, guard) : size === undefined)) { + size = 1; + } else { + size = nativeMax(toInteger(size), 0); + } + var length = array == null ? 0 : array.length; + if (!length || size < 1) { + return []; + } + var index = 0, + resIndex = 0, + result = Array(nativeCeil(length / size)); + + while (index < length) { + result[resIndex++] = baseSlice(array, index, (index += size)); + } + return result; + } + + module.exports = chunk; + + +/***/ }), +/* 86 */ +/***/ (function(module, exports) { + + /** + * The base implementation of `_.slice` without an iteratee call guard. + * + * @private + * @param {Array} array The array to slice. + * @param {number} [start=0] The start position. + * @param {number} [end=array.length] The end position. + * @returns {Array} Returns the slice of `array`. + */ + function baseSlice(array, start, end) { + var index = -1, + length = array.length; + + if (start < 0) { + start = -start > length ? 0 : (length + start); + } + end = end > length ? length : end; + if (end < 0) { + end += length; + } + length = start > end ? 0 : ((end - start) >>> 0); + start >>>= 0; + + var result = Array(length); + while (++index < length) { + result[index] = array[index + start]; + } + return result; + } + + module.exports = baseSlice; + + +/***/ }), +/* 87 */ +/***/ (function(module, exports, __webpack_require__) { + + var eq = __webpack_require__(88), + isArrayLike = __webpack_require__(89), + isIndex = __webpack_require__(99), + isObject = __webpack_require__(97); + + /** + * Checks if the given arguments are from an iteratee call. + * + * @private + * @param {*} value The potential iteratee value argument. + * @param {*} index The potential iteratee index or key argument. + * @param {*} object The potential iteratee object argument. + * @returns {boolean} Returns `true` if the arguments are from an iteratee call, + * else `false`. + */ + function isIterateeCall(value, index, object) { + if (!isObject(object)) { + return false; + } + var type = typeof index; + if (type == 'number' + ? (isArrayLike(object) && isIndex(index, object.length)) + : (type == 'string' && index in object) + ) { + return eq(object[index], value); + } + return false; + } + + module.exports = isIterateeCall; + + +/***/ }), +/* 88 */ +/***/ (function(module, exports) { + + /** + * Performs a + * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * comparison between two values to determine if they are equivalent. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @returns {boolean} Returns `true` if the values are equivalent, else `false`. + * @example + * + * var object = { 'a': 1 }; + * var other = { 'a': 1 }; + * + * _.eq(object, object); + * // => true + * + * _.eq(object, other); + * // => false + * + * _.eq('a', 'a'); + * // => true + * + * _.eq('a', Object('a')); + * // => false + * + * _.eq(NaN, NaN); + * // => true + */ + function eq(value, other) { + return value === other || (value !== value && other !== other); + } + + module.exports = eq; + + +/***/ }), +/* 89 */ +/***/ (function(module, exports, __webpack_require__) { + + var isFunction = __webpack_require__(90), + isLength = __webpack_require__(98); + + /** + * Checks if `value` is array-like. A value is considered array-like if it's + * not a function and has a `value.length` that's an integer greater than or + * equal to `0` and less than or equal to `Number.MAX_SAFE_INTEGER`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is array-like, else `false`. + * @example + * + * _.isArrayLike([1, 2, 3]); + * // => true + * + * _.isArrayLike(document.body.children); + * // => true + * + * _.isArrayLike('abc'); + * // => true + * + * _.isArrayLike(_.noop); + * // => false + */ + function isArrayLike(value) { + return value != null && isLength(value.length) && !isFunction(value); + } + + module.exports = isArrayLike; + + +/***/ }), +/* 90 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseGetTag = __webpack_require__(91), + isObject = __webpack_require__(97); + + /** `Object#toString` result references. */ + var asyncTag = '[object AsyncFunction]', + funcTag = '[object Function]', + genTag = '[object GeneratorFunction]', + proxyTag = '[object Proxy]'; + + /** + * Checks if `value` is classified as a `Function` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a function, else `false`. + * @example + * + * _.isFunction(_); + * // => true + * + * _.isFunction(/abc/); + * // => false + */ + function isFunction(value) { + if (!isObject(value)) { + return false; + } + // The use of `Object#toString` avoids issues with the `typeof` operator + // in Safari 9 which returns 'object' for typed arrays and other constructors. + var tag = baseGetTag(value); + return tag == funcTag || tag == genTag || tag == asyncTag || tag == proxyTag; + } + + module.exports = isFunction; + + +/***/ }), +/* 91 */ +/***/ (function(module, exports, __webpack_require__) { + + var Symbol = __webpack_require__(92), + getRawTag = __webpack_require__(95), + objectToString = __webpack_require__(96); + + /** `Object#toString` result references. */ + var nullTag = '[object Null]', + undefinedTag = '[object Undefined]'; + + /** Built-in value references. */ + var symToStringTag = Symbol ? Symbol.toStringTag : undefined; + + /** + * The base implementation of `getTag` without fallbacks for buggy environments. + * + * @private + * @param {*} value The value to query. + * @returns {string} Returns the `toStringTag`. + */ + function baseGetTag(value) { + if (value == null) { + return value === undefined ? undefinedTag : nullTag; + } + return (symToStringTag && symToStringTag in Object(value)) + ? getRawTag(value) + : objectToString(value); + } + + module.exports = baseGetTag; + + +/***/ }), +/* 92 */ +/***/ (function(module, exports, __webpack_require__) { + + var root = __webpack_require__(93); + + /** Built-in value references. */ + var Symbol = root.Symbol; + + module.exports = Symbol; + + +/***/ }), +/* 93 */ +/***/ (function(module, exports, __webpack_require__) { + + var freeGlobal = __webpack_require__(94); + + /** Detect free variable `self`. */ + var freeSelf = typeof self == 'object' && self && self.Object === Object && self; + + /** Used as a reference to the global object. */ + var root = freeGlobal || freeSelf || Function('return this')(); + + module.exports = root; + + +/***/ }), +/* 94 */ +/***/ (function(module, exports) { + + /* WEBPACK VAR INJECTION */(function(global) {/** Detect free variable `global` from Node.js. */ + var freeGlobal = typeof global == 'object' && global && global.Object === Object && global; + + module.exports = freeGlobal; + + /* WEBPACK VAR INJECTION */}.call(exports, (function() { return this; }()))) + +/***/ }), +/* 95 */ +/***/ (function(module, exports, __webpack_require__) { + + var Symbol = __webpack_require__(92); + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * Used to resolve the + * [`toStringTag`](http://ecma-international.org/ecma-262/7.0/#sec-object.prototype.tostring) + * of values. + */ + var nativeObjectToString = objectProto.toString; + + /** Built-in value references. */ + var symToStringTag = Symbol ? Symbol.toStringTag : undefined; + + /** + * A specialized version of `baseGetTag` which ignores `Symbol.toStringTag` values. + * + * @private + * @param {*} value The value to query. + * @returns {string} Returns the raw `toStringTag`. + */ + function getRawTag(value) { + var isOwn = hasOwnProperty.call(value, symToStringTag), + tag = value[symToStringTag]; + + try { + value[symToStringTag] = undefined; + var unmasked = true; + } catch (e) {} + + var result = nativeObjectToString.call(value); + if (unmasked) { + if (isOwn) { + value[symToStringTag] = tag; + } else { + delete value[symToStringTag]; + } + } + return result; + } + + module.exports = getRawTag; + + +/***/ }), +/* 96 */ +/***/ (function(module, exports) { + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** + * Used to resolve the + * [`toStringTag`](http://ecma-international.org/ecma-262/7.0/#sec-object.prototype.tostring) + * of values. + */ + var nativeObjectToString = objectProto.toString; + + /** + * Converts `value` to a string using `Object.prototype.toString`. + * + * @private + * @param {*} value The value to convert. + * @returns {string} Returns the converted string. + */ + function objectToString(value) { + return nativeObjectToString.call(value); + } + + module.exports = objectToString; + + +/***/ }), +/* 97 */ +/***/ (function(module, exports) { + + /** + * Checks if `value` is the + * [language type](http://www.ecma-international.org/ecma-262/7.0/#sec-ecmascript-language-types) + * of `Object`. (e.g. arrays, functions, objects, regexes, `new Number(0)`, and `new String('')`) + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an object, else `false`. + * @example + * + * _.isObject({}); + * // => true + * + * _.isObject([1, 2, 3]); + * // => true + * + * _.isObject(_.noop); + * // => true + * + * _.isObject(null); + * // => false + */ + function isObject(value) { + var type = typeof value; + return value != null && (type == 'object' || type == 'function'); + } + + module.exports = isObject; + + +/***/ }), +/* 98 */ +/***/ (function(module, exports) { + + /** Used as references for various `Number` constants. */ + var MAX_SAFE_INTEGER = 9007199254740991; + + /** + * Checks if `value` is a valid array-like length. + * + * **Note:** This method is loosely based on + * [`ToLength`](http://ecma-international.org/ecma-262/7.0/#sec-tolength). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a valid length, else `false`. + * @example + * + * _.isLength(3); + * // => true + * + * _.isLength(Number.MIN_VALUE); + * // => false + * + * _.isLength(Infinity); + * // => false + * + * _.isLength('3'); + * // => false + */ + function isLength(value) { + return typeof value == 'number' && + value > -1 && value % 1 == 0 && value <= MAX_SAFE_INTEGER; + } + + module.exports = isLength; + + +/***/ }), +/* 99 */ +/***/ (function(module, exports) { + + /** Used as references for various `Number` constants. */ + var MAX_SAFE_INTEGER = 9007199254740991; + + /** Used to detect unsigned integer values. */ + var reIsUint = /^(?:0|[1-9]\d*)$/; + + /** + * Checks if `value` is a valid array-like index. + * + * @private + * @param {*} value The value to check. + * @param {number} [length=MAX_SAFE_INTEGER] The upper bounds of a valid index. + * @returns {boolean} Returns `true` if `value` is a valid index, else `false`. + */ + function isIndex(value, length) { + var type = typeof value; + length = length == null ? MAX_SAFE_INTEGER : length; + + return !!length && + (type == 'number' || + (type != 'symbol' && reIsUint.test(value))) && + (value > -1 && value % 1 == 0 && value < length); + } + + module.exports = isIndex; + + +/***/ }), +/* 100 */ +/***/ (function(module, exports, __webpack_require__) { + + var toFinite = __webpack_require__(101); + + /** + * Converts `value` to an integer. + * + * **Note:** This method is loosely based on + * [`ToInteger`](http://www.ecma-international.org/ecma-262/7.0/#sec-tointeger). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to convert. + * @returns {number} Returns the converted integer. + * @example + * + * _.toInteger(3.2); + * // => 3 + * + * _.toInteger(Number.MIN_VALUE); + * // => 0 + * + * _.toInteger(Infinity); + * // => 1.7976931348623157e+308 + * + * _.toInteger('3.2'); + * // => 3 + */ + function toInteger(value) { + var result = toFinite(value), + remainder = result % 1; + + return result === result ? (remainder ? result - remainder : result) : 0; + } + + module.exports = toInteger; + + +/***/ }), +/* 101 */ +/***/ (function(module, exports, __webpack_require__) { + + var toNumber = __webpack_require__(102); + + /** Used as references for various `Number` constants. */ + var INFINITY = 1 / 0, + MAX_INTEGER = 1.7976931348623157e+308; + + /** + * Converts `value` to a finite number. + * + * @static + * @memberOf _ + * @since 4.12.0 + * @category Lang + * @param {*} value The value to convert. + * @returns {number} Returns the converted number. + * @example + * + * _.toFinite(3.2); + * // => 3.2 + * + * _.toFinite(Number.MIN_VALUE); + * // => 5e-324 + * + * _.toFinite(Infinity); + * // => 1.7976931348623157e+308 + * + * _.toFinite('3.2'); + * // => 3.2 + */ + function toFinite(value) { + if (!value) { + return value === 0 ? value : 0; + } + value = toNumber(value); + if (value === INFINITY || value === -INFINITY) { + var sign = (value < 0 ? -1 : 1); + return sign * MAX_INTEGER; + } + return value === value ? value : 0; + } + + module.exports = toFinite; + + +/***/ }), +/* 102 */ +/***/ (function(module, exports, __webpack_require__) { + + var isObject = __webpack_require__(97), + isSymbol = __webpack_require__(103); + + /** Used as references for various `Number` constants. */ + var NAN = 0 / 0; + + /** Used to match leading and trailing whitespace. */ + var reTrim = /^\s+|\s+$/g; + + /** Used to detect bad signed hexadecimal string values. */ + var reIsBadHex = /^[-+]0x[0-9a-f]+$/i; + + /** Used to detect binary string values. */ + var reIsBinary = /^0b[01]+$/i; + + /** Used to detect octal string values. */ + var reIsOctal = /^0o[0-7]+$/i; + + /** Built-in method references without a dependency on `root`. */ + var freeParseInt = parseInt; + + /** + * Converts `value` to a number. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to process. + * @returns {number} Returns the number. + * @example + * + * _.toNumber(3.2); + * // => 3.2 + * + * _.toNumber(Number.MIN_VALUE); + * // => 5e-324 + * + * _.toNumber(Infinity); + * // => Infinity + * + * _.toNumber('3.2'); + * // => 3.2 + */ + function toNumber(value) { + if (typeof value == 'number') { + return value; + } + if (isSymbol(value)) { + return NAN; + } + if (isObject(value)) { + var other = typeof value.valueOf == 'function' ? value.valueOf() : value; + value = isObject(other) ? (other + '') : other; + } + if (typeof value != 'string') { + return value === 0 ? value : +value; + } + value = value.replace(reTrim, ''); + var isBinary = reIsBinary.test(value); + return (isBinary || reIsOctal.test(value)) + ? freeParseInt(value.slice(2), isBinary ? 2 : 8) + : (reIsBadHex.test(value) ? NAN : +value); + } + + module.exports = toNumber; + + +/***/ }), +/* 103 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseGetTag = __webpack_require__(91), + isObjectLike = __webpack_require__(104); + + /** `Object#toString` result references. */ + var symbolTag = '[object Symbol]'; + + /** + * Checks if `value` is classified as a `Symbol` primitive or object. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a symbol, else `false`. + * @example + * + * _.isSymbol(Symbol.iterator); + * // => true + * + * _.isSymbol('abc'); + * // => false + */ + function isSymbol(value) { + return typeof value == 'symbol' || + (isObjectLike(value) && baseGetTag(value) == symbolTag); + } + + module.exports = isSymbol; + + +/***/ }), +/* 104 */ +/***/ (function(module, exports) { + + /** + * Checks if `value` is object-like. A value is object-like if it's not `null` + * and has a `typeof` result of "object". + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is object-like, else `false`. + * @example + * + * _.isObjectLike({}); + * // => true + * + * _.isObjectLike([1, 2, 3]); + * // => true + * + * _.isObjectLike(_.noop); + * // => false + * + * _.isObjectLike(null); + * // => false + */ + function isObjectLike(value) { + return value != null && typeof value == 'object'; + } + + module.exports = isObjectLike; + + +/***/ }), +/* 105 */ +/***/ (function(module, exports) { + + /** + * Creates an array with all falsey values removed. The values `false`, `null`, + * `0`, `""`, `undefined`, and `NaN` are falsey. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to compact. + * @returns {Array} Returns the new array of filtered values. + * @example + * + * _.compact([0, 1, false, 2, '', 3]); + * // => [1, 2, 3] + */ + function compact(array) { + var index = -1, + length = array == null ? 0 : array.length, + resIndex = 0, + result = []; + + while (++index < length) { + var value = array[index]; + if (value) { + result[resIndex++] = value; + } + } + return result; + } + + module.exports = compact; + + +/***/ }), +/* 106 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayPush = __webpack_require__(107), + baseFlatten = __webpack_require__(108), + copyArray = __webpack_require__(113), + isArray = __webpack_require__(112); + + /** + * Creates a new array concatenating `array` with any additional arrays + * and/or values. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to concatenate. + * @param {...*} [values] The values to concatenate. + * @returns {Array} Returns the new concatenated array. + * @example + * + * var array = [1]; + * var other = _.concat(array, 2, [3], [[4]]); + * + * console.log(other); + * // => [1, 2, 3, [4]] + * + * console.log(array); + * // => [1] + */ + function concat() { + var length = arguments.length; + if (!length) { + return []; + } + var args = Array(length - 1), + array = arguments[0], + index = length; + + while (index--) { + args[index - 1] = arguments[index]; + } + return arrayPush(isArray(array) ? copyArray(array) : [array], baseFlatten(args, 1)); + } + + module.exports = concat; + + +/***/ }), +/* 107 */ +/***/ (function(module, exports) { + + /** + * Appends the elements of `values` to `array`. + * + * @private + * @param {Array} array The array to modify. + * @param {Array} values The values to append. + * @returns {Array} Returns `array`. + */ + function arrayPush(array, values) { + var index = -1, + length = values.length, + offset = array.length; + + while (++index < length) { + array[offset + index] = values[index]; + } + return array; + } + + module.exports = arrayPush; + + +/***/ }), +/* 108 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayPush = __webpack_require__(107), + isFlattenable = __webpack_require__(109); + + /** + * The base implementation of `_.flatten` with support for restricting flattening. + * + * @private + * @param {Array} array The array to flatten. + * @param {number} depth The maximum recursion depth. + * @param {boolean} [predicate=isFlattenable] The function invoked per iteration. + * @param {boolean} [isStrict] Restrict to values that pass `predicate` checks. + * @param {Array} [result=[]] The initial result value. + * @returns {Array} Returns the new flattened array. + */ + function baseFlatten(array, depth, predicate, isStrict, result) { + var index = -1, + length = array.length; + + predicate || (predicate = isFlattenable); + result || (result = []); + + while (++index < length) { + var value = array[index]; + if (depth > 0 && predicate(value)) { + if (depth > 1) { + // Recursively flatten arrays (susceptible to call stack limits). + baseFlatten(value, depth - 1, predicate, isStrict, result); + } else { + arrayPush(result, value); + } + } else if (!isStrict) { + result[result.length] = value; + } + } + return result; + } + + module.exports = baseFlatten; + + +/***/ }), +/* 109 */ +/***/ (function(module, exports, __webpack_require__) { + + var Symbol = __webpack_require__(92), + isArguments = __webpack_require__(110), + isArray = __webpack_require__(112); + + /** Built-in value references. */ + var spreadableSymbol = Symbol ? Symbol.isConcatSpreadable : undefined; + + /** + * Checks if `value` is a flattenable `arguments` object or array. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is flattenable, else `false`. + */ + function isFlattenable(value) { + return isArray(value) || isArguments(value) || + !!(spreadableSymbol && value && value[spreadableSymbol]); + } + + module.exports = isFlattenable; + + +/***/ }), +/* 110 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIsArguments = __webpack_require__(111), + isObjectLike = __webpack_require__(104); + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** Built-in value references. */ + var propertyIsEnumerable = objectProto.propertyIsEnumerable; + + /** + * Checks if `value` is likely an `arguments` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an `arguments` object, + * else `false`. + * @example + * + * _.isArguments(function() { return arguments; }()); + * // => true + * + * _.isArguments([1, 2, 3]); + * // => false + */ + var isArguments = baseIsArguments(function() { return arguments; }()) ? baseIsArguments : function(value) { + return isObjectLike(value) && hasOwnProperty.call(value, 'callee') && + !propertyIsEnumerable.call(value, 'callee'); + }; + + module.exports = isArguments; + + +/***/ }), +/* 111 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseGetTag = __webpack_require__(91), + isObjectLike = __webpack_require__(104); + + /** `Object#toString` result references. */ + var argsTag = '[object Arguments]'; + + /** + * The base implementation of `_.isArguments`. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an `arguments` object, + */ + function baseIsArguments(value) { + return isObjectLike(value) && baseGetTag(value) == argsTag; + } + + module.exports = baseIsArguments; + + +/***/ }), +/* 112 */ +/***/ (function(module, exports) { + + /** + * Checks if `value` is classified as an `Array` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an array, else `false`. + * @example + * + * _.isArray([1, 2, 3]); + * // => true + * + * _.isArray(document.body.children); + * // => false + * + * _.isArray('abc'); + * // => false + * + * _.isArray(_.noop); + * // => false + */ + var isArray = Array.isArray; + + module.exports = isArray; + + +/***/ }), +/* 113 */ +/***/ (function(module, exports) { + + /** + * Copies the values of `source` to `array`. + * + * @private + * @param {Array} source The array to copy values from. + * @param {Array} [array=[]] The array to copy values to. + * @returns {Array} Returns `array`. + */ + function copyArray(source, array) { + var index = -1, + length = source.length; + + array || (array = Array(length)); + while (++index < length) { + array[index] = source[index]; + } + return array; + } + + module.exports = copyArray; + + +/***/ }), +/* 114 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseDifference = __webpack_require__(115), + baseFlatten = __webpack_require__(108), + baseRest = __webpack_require__(157), + isArrayLikeObject = __webpack_require__(166); + + /** + * Creates an array of `array` values not included in the other given arrays + * using [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. The order and references of result values are + * determined by the first array. + * + * **Note:** Unlike `_.pullAll`, this method returns a new array. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {...Array} [values] The values to exclude. + * @returns {Array} Returns the new array of filtered values. + * @see _.without, _.xor + * @example + * + * _.difference([2, 1], [2, 3]); + * // => [1] + */ + var difference = baseRest(function(array, values) { + return isArrayLikeObject(array) + ? baseDifference(array, baseFlatten(values, 1, isArrayLikeObject, true)) + : []; + }); + + module.exports = difference; + + +/***/ }), +/* 115 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetCache = __webpack_require__(116), + arrayIncludes = __webpack_require__(148), + arrayIncludesWith = __webpack_require__(153), + arrayMap = __webpack_require__(154), + baseUnary = __webpack_require__(155), + cacheHas = __webpack_require__(156); + + /** Used as the size to enable large array optimizations. */ + var LARGE_ARRAY_SIZE = 200; + + /** + * The base implementation of methods like `_.difference` without support + * for excluding multiple arrays or iteratee shorthands. + * + * @private + * @param {Array} array The array to inspect. + * @param {Array} values The values to exclude. + * @param {Function} [iteratee] The iteratee invoked per element. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new array of filtered values. + */ + function baseDifference(array, values, iteratee, comparator) { + var index = -1, + includes = arrayIncludes, + isCommon = true, + length = array.length, + result = [], + valuesLength = values.length; + + if (!length) { + return result; + } + if (iteratee) { + values = arrayMap(values, baseUnary(iteratee)); + } + if (comparator) { + includes = arrayIncludesWith; + isCommon = false; + } + else if (values.length >= LARGE_ARRAY_SIZE) { + includes = cacheHas; + isCommon = false; + values = new SetCache(values); + } + outer: + while (++index < length) { + var value = array[index], + computed = iteratee == null ? value : iteratee(value); + + value = (comparator || value !== 0) ? value : 0; + if (isCommon && computed === computed) { + var valuesIndex = valuesLength; + while (valuesIndex--) { + if (values[valuesIndex] === computed) { + continue outer; + } + } + result.push(value); + } + else if (!includes(values, computed, comparator)) { + result.push(value); + } + } + return result; + } + + module.exports = baseDifference; + + +/***/ }), +/* 116 */ +/***/ (function(module, exports, __webpack_require__) { + + var MapCache = __webpack_require__(117), + setCacheAdd = __webpack_require__(146), + setCacheHas = __webpack_require__(147); + + /** + * + * Creates an array cache object to store unique values. + * + * @private + * @constructor + * @param {Array} [values] The values to cache. + */ + function SetCache(values) { + var index = -1, + length = values == null ? 0 : values.length; + + this.__data__ = new MapCache; + while (++index < length) { + this.add(values[index]); + } + } + + // Add methods to `SetCache`. + SetCache.prototype.add = SetCache.prototype.push = setCacheAdd; + SetCache.prototype.has = setCacheHas; + + module.exports = SetCache; + + +/***/ }), +/* 117 */ +/***/ (function(module, exports, __webpack_require__) { + + var mapCacheClear = __webpack_require__(118), + mapCacheDelete = __webpack_require__(140), + mapCacheGet = __webpack_require__(143), + mapCacheHas = __webpack_require__(144), + mapCacheSet = __webpack_require__(145); + + /** + * Creates a map cache object to store key-value pairs. + * + * @private + * @constructor + * @param {Array} [entries] The key-value pairs to cache. + */ + function MapCache(entries) { + var index = -1, + length = entries == null ? 0 : entries.length; + + this.clear(); + while (++index < length) { + var entry = entries[index]; + this.set(entry[0], entry[1]); + } + } + + // Add methods to `MapCache`. + MapCache.prototype.clear = mapCacheClear; + MapCache.prototype['delete'] = mapCacheDelete; + MapCache.prototype.get = mapCacheGet; + MapCache.prototype.has = mapCacheHas; + MapCache.prototype.set = mapCacheSet; + + module.exports = MapCache; + + +/***/ }), +/* 118 */ +/***/ (function(module, exports, __webpack_require__) { + + var Hash = __webpack_require__(119), + ListCache = __webpack_require__(132), + Map = __webpack_require__(139); + + /** + * Removes all key-value entries from the map. + * + * @private + * @name clear + * @memberOf MapCache + */ + function mapCacheClear() { + this.size = 0; + this.__data__ = { + 'hash': new Hash, + 'map': new (Map || ListCache), + 'string': new Hash + }; + } + + module.exports = mapCacheClear; + + +/***/ }), +/* 119 */ +/***/ (function(module, exports, __webpack_require__) { + + var hashClear = __webpack_require__(120), + hashDelete = __webpack_require__(128), + hashGet = __webpack_require__(129), + hashHas = __webpack_require__(130), + hashSet = __webpack_require__(131); + + /** + * Creates a hash object. + * + * @private + * @constructor + * @param {Array} [entries] The key-value pairs to cache. + */ + function Hash(entries) { + var index = -1, + length = entries == null ? 0 : entries.length; + + this.clear(); + while (++index < length) { + var entry = entries[index]; + this.set(entry[0], entry[1]); + } + } + + // Add methods to `Hash`. + Hash.prototype.clear = hashClear; + Hash.prototype['delete'] = hashDelete; + Hash.prototype.get = hashGet; + Hash.prototype.has = hashHas; + Hash.prototype.set = hashSet; + + module.exports = Hash; + + +/***/ }), +/* 120 */ +/***/ (function(module, exports, __webpack_require__) { + + var nativeCreate = __webpack_require__(121); + + /** + * Removes all key-value entries from the hash. + * + * @private + * @name clear + * @memberOf Hash + */ + function hashClear() { + this.__data__ = nativeCreate ? nativeCreate(null) : {}; + this.size = 0; + } + + module.exports = hashClear; + + +/***/ }), +/* 121 */ +/***/ (function(module, exports, __webpack_require__) { + + var getNative = __webpack_require__(122); + + /* Built-in method references that are verified to be native. */ + var nativeCreate = getNative(Object, 'create'); + + module.exports = nativeCreate; + + +/***/ }), +/* 122 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIsNative = __webpack_require__(123), + getValue = __webpack_require__(127); + + /** + * Gets the native function at `key` of `object`. + * + * @private + * @param {Object} object The object to query. + * @param {string} key The key of the method to get. + * @returns {*} Returns the function if it's native, else `undefined`. + */ + function getNative(object, key) { + var value = getValue(object, key); + return baseIsNative(value) ? value : undefined; + } + + module.exports = getNative; + + +/***/ }), +/* 123 */ +/***/ (function(module, exports, __webpack_require__) { + + var isFunction = __webpack_require__(90), + isMasked = __webpack_require__(124), + isObject = __webpack_require__(97), + toSource = __webpack_require__(126); + + /** + * Used to match `RegExp` + * [syntax characters](http://ecma-international.org/ecma-262/7.0/#sec-patterns). + */ + var reRegExpChar = /[\\^$.*+?()[\]{}|]/g; + + /** Used to detect host constructors (Safari). */ + var reIsHostCtor = /^\[object .+?Constructor\]$/; + + /** Used for built-in method references. */ + var funcProto = Function.prototype, + objectProto = Object.prototype; + + /** Used to resolve the decompiled source of functions. */ + var funcToString = funcProto.toString; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** Used to detect if a method is native. */ + var reIsNative = RegExp('^' + + funcToString.call(hasOwnProperty).replace(reRegExpChar, '\\$&') + .replace(/hasOwnProperty|(function).*?(?=\\\()| for .+?(?=\\\])/g, '$1.*?') + '$' + ); + + /** + * The base implementation of `_.isNative` without bad shim checks. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a native function, + * else `false`. + */ + function baseIsNative(value) { + if (!isObject(value) || isMasked(value)) { + return false; + } + var pattern = isFunction(value) ? reIsNative : reIsHostCtor; + return pattern.test(toSource(value)); + } + + module.exports = baseIsNative; + + +/***/ }), +/* 124 */ +/***/ (function(module, exports, __webpack_require__) { + + var coreJsData = __webpack_require__(125); + + /** Used to detect methods masquerading as native. */ + var maskSrcKey = (function() { + var uid = /[^.]+$/.exec(coreJsData && coreJsData.keys && coreJsData.keys.IE_PROTO || ''); + return uid ? ('Symbol(src)_1.' + uid) : ''; + }()); + + /** + * Checks if `func` has its source masked. + * + * @private + * @param {Function} func The function to check. + * @returns {boolean} Returns `true` if `func` is masked, else `false`. + */ + function isMasked(func) { + return !!maskSrcKey && (maskSrcKey in func); + } + + module.exports = isMasked; + + +/***/ }), +/* 125 */ +/***/ (function(module, exports, __webpack_require__) { + + var root = __webpack_require__(93); + + /** Used to detect overreaching core-js shims. */ + var coreJsData = root['__core-js_shared__']; + + module.exports = coreJsData; + + +/***/ }), +/* 126 */ +/***/ (function(module, exports) { + + /** Used for built-in method references. */ + var funcProto = Function.prototype; + + /** Used to resolve the decompiled source of functions. */ + var funcToString = funcProto.toString; + + /** + * Converts `func` to its source code. + * + * @private + * @param {Function} func The function to convert. + * @returns {string} Returns the source code. + */ + function toSource(func) { + if (func != null) { + try { + return funcToString.call(func); + } catch (e) {} + try { + return (func + ''); + } catch (e) {} + } + return ''; + } + + module.exports = toSource; + + +/***/ }), +/* 127 */ +/***/ (function(module, exports) { + + /** + * Gets the value at `key` of `object`. + * + * @private + * @param {Object} [object] The object to query. + * @param {string} key The key of the property to get. + * @returns {*} Returns the property value. + */ + function getValue(object, key) { + return object == null ? undefined : object[key]; + } + + module.exports = getValue; + + +/***/ }), +/* 128 */ +/***/ (function(module, exports) { + + /** + * Removes `key` and its value from the hash. + * + * @private + * @name delete + * @memberOf Hash + * @param {Object} hash The hash to modify. + * @param {string} key The key of the value to remove. + * @returns {boolean} Returns `true` if the entry was removed, else `false`. + */ + function hashDelete(key) { + var result = this.has(key) && delete this.__data__[key]; + this.size -= result ? 1 : 0; + return result; + } + + module.exports = hashDelete; + + +/***/ }), +/* 129 */ +/***/ (function(module, exports, __webpack_require__) { + + var nativeCreate = __webpack_require__(121); + + /** Used to stand-in for `undefined` hash values. */ + var HASH_UNDEFINED = '__lodash_hash_undefined__'; + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * Gets the hash value for `key`. + * + * @private + * @name get + * @memberOf Hash + * @param {string} key The key of the value to get. + * @returns {*} Returns the entry value. + */ + function hashGet(key) { + var data = this.__data__; + if (nativeCreate) { + var result = data[key]; + return result === HASH_UNDEFINED ? undefined : result; + } + return hasOwnProperty.call(data, key) ? data[key] : undefined; + } + + module.exports = hashGet; + + +/***/ }), +/* 130 */ +/***/ (function(module, exports, __webpack_require__) { + + var nativeCreate = __webpack_require__(121); + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * Checks if a hash value for `key` exists. + * + * @private + * @name has + * @memberOf Hash + * @param {string} key The key of the entry to check. + * @returns {boolean} Returns `true` if an entry for `key` exists, else `false`. + */ + function hashHas(key) { + var data = this.__data__; + return nativeCreate ? (data[key] !== undefined) : hasOwnProperty.call(data, key); + } + + module.exports = hashHas; + + +/***/ }), +/* 131 */ +/***/ (function(module, exports, __webpack_require__) { + + var nativeCreate = __webpack_require__(121); + + /** Used to stand-in for `undefined` hash values. */ + var HASH_UNDEFINED = '__lodash_hash_undefined__'; + + /** + * Sets the hash `key` to `value`. + * + * @private + * @name set + * @memberOf Hash + * @param {string} key The key of the value to set. + * @param {*} value The value to set. + * @returns {Object} Returns the hash instance. + */ + function hashSet(key, value) { + var data = this.__data__; + this.size += this.has(key) ? 0 : 1; + data[key] = (nativeCreate && value === undefined) ? HASH_UNDEFINED : value; + return this; + } + + module.exports = hashSet; + + +/***/ }), +/* 132 */ +/***/ (function(module, exports, __webpack_require__) { + + var listCacheClear = __webpack_require__(133), + listCacheDelete = __webpack_require__(134), + listCacheGet = __webpack_require__(136), + listCacheHas = __webpack_require__(137), + listCacheSet = __webpack_require__(138); + + /** + * Creates an list cache object. + * + * @private + * @constructor + * @param {Array} [entries] The key-value pairs to cache. + */ + function ListCache(entries) { + var index = -1, + length = entries == null ? 0 : entries.length; + + this.clear(); + while (++index < length) { + var entry = entries[index]; + this.set(entry[0], entry[1]); + } + } + + // Add methods to `ListCache`. + ListCache.prototype.clear = listCacheClear; + ListCache.prototype['delete'] = listCacheDelete; + ListCache.prototype.get = listCacheGet; + ListCache.prototype.has = listCacheHas; + ListCache.prototype.set = listCacheSet; + + module.exports = ListCache; + + +/***/ }), +/* 133 */ +/***/ (function(module, exports) { + + /** + * Removes all key-value entries from the list cache. + * + * @private + * @name clear + * @memberOf ListCache + */ + function listCacheClear() { + this.__data__ = []; + this.size = 0; + } + + module.exports = listCacheClear; + + +/***/ }), +/* 134 */ +/***/ (function(module, exports, __webpack_require__) { + + var assocIndexOf = __webpack_require__(135); + + /** Used for built-in method references. */ + var arrayProto = Array.prototype; + + /** Built-in value references. */ + var splice = arrayProto.splice; + + /** + * Removes `key` and its value from the list cache. + * + * @private + * @name delete + * @memberOf ListCache + * @param {string} key The key of the value to remove. + * @returns {boolean} Returns `true` if the entry was removed, else `false`. + */ + function listCacheDelete(key) { + var data = this.__data__, + index = assocIndexOf(data, key); + + if (index < 0) { + return false; + } + var lastIndex = data.length - 1; + if (index == lastIndex) { + data.pop(); + } else { + splice.call(data, index, 1); + } + --this.size; + return true; + } + + module.exports = listCacheDelete; + + +/***/ }), +/* 135 */ +/***/ (function(module, exports, __webpack_require__) { + + var eq = __webpack_require__(88); + + /** + * Gets the index at which the `key` is found in `array` of key-value pairs. + * + * @private + * @param {Array} array The array to inspect. + * @param {*} key The key to search for. + * @returns {number} Returns the index of the matched value, else `-1`. + */ + function assocIndexOf(array, key) { + var length = array.length; + while (length--) { + if (eq(array[length][0], key)) { + return length; + } + } + return -1; + } + + module.exports = assocIndexOf; + + +/***/ }), +/* 136 */ +/***/ (function(module, exports, __webpack_require__) { + + var assocIndexOf = __webpack_require__(135); + + /** + * Gets the list cache value for `key`. + * + * @private + * @name get + * @memberOf ListCache + * @param {string} key The key of the value to get. + * @returns {*} Returns the entry value. + */ + function listCacheGet(key) { + var data = this.__data__, + index = assocIndexOf(data, key); + + return index < 0 ? undefined : data[index][1]; + } + + module.exports = listCacheGet; + + +/***/ }), +/* 137 */ +/***/ (function(module, exports, __webpack_require__) { + + var assocIndexOf = __webpack_require__(135); + + /** + * Checks if a list cache value for `key` exists. + * + * @private + * @name has + * @memberOf ListCache + * @param {string} key The key of the entry to check. + * @returns {boolean} Returns `true` if an entry for `key` exists, else `false`. + */ + function listCacheHas(key) { + return assocIndexOf(this.__data__, key) > -1; + } + + module.exports = listCacheHas; + + +/***/ }), +/* 138 */ +/***/ (function(module, exports, __webpack_require__) { + + var assocIndexOf = __webpack_require__(135); + + /** + * Sets the list cache `key` to `value`. + * + * @private + * @name set + * @memberOf ListCache + * @param {string} key The key of the value to set. + * @param {*} value The value to set. + * @returns {Object} Returns the list cache instance. + */ + function listCacheSet(key, value) { + var data = this.__data__, + index = assocIndexOf(data, key); + + if (index < 0) { + ++this.size; + data.push([key, value]); + } else { + data[index][1] = value; + } + return this; + } + + module.exports = listCacheSet; + + +/***/ }), +/* 139 */ +/***/ (function(module, exports, __webpack_require__) { + + var getNative = __webpack_require__(122), + root = __webpack_require__(93); + + /* Built-in method references that are verified to be native. */ + var Map = getNative(root, 'Map'); + + module.exports = Map; + + +/***/ }), +/* 140 */ +/***/ (function(module, exports, __webpack_require__) { + + var getMapData = __webpack_require__(141); + + /** + * Removes `key` and its value from the map. + * + * @private + * @name delete + * @memberOf MapCache + * @param {string} key The key of the value to remove. + * @returns {boolean} Returns `true` if the entry was removed, else `false`. + */ + function mapCacheDelete(key) { + var result = getMapData(this, key)['delete'](key); + this.size -= result ? 1 : 0; + return result; + } + + module.exports = mapCacheDelete; + + +/***/ }), +/* 141 */ +/***/ (function(module, exports, __webpack_require__) { + + var isKeyable = __webpack_require__(142); + + /** + * Gets the data for `map`. + * + * @private + * @param {Object} map The map to query. + * @param {string} key The reference key. + * @returns {*} Returns the map data. + */ + function getMapData(map, key) { + var data = map.__data__; + return isKeyable(key) + ? data[typeof key == 'string' ? 'string' : 'hash'] + : data.map; + } + + module.exports = getMapData; + + +/***/ }), +/* 142 */ +/***/ (function(module, exports) { + + /** + * Checks if `value` is suitable for use as unique object key. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is suitable, else `false`. + */ + function isKeyable(value) { + var type = typeof value; + return (type == 'string' || type == 'number' || type == 'symbol' || type == 'boolean') + ? (value !== '__proto__') + : (value === null); + } + + module.exports = isKeyable; + + +/***/ }), +/* 143 */ +/***/ (function(module, exports, __webpack_require__) { + + var getMapData = __webpack_require__(141); + + /** + * Gets the map value for `key`. + * + * @private + * @name get + * @memberOf MapCache + * @param {string} key The key of the value to get. + * @returns {*} Returns the entry value. + */ + function mapCacheGet(key) { + return getMapData(this, key).get(key); + } + + module.exports = mapCacheGet; + + +/***/ }), +/* 144 */ +/***/ (function(module, exports, __webpack_require__) { + + var getMapData = __webpack_require__(141); + + /** + * Checks if a map value for `key` exists. + * + * @private + * @name has + * @memberOf MapCache + * @param {string} key The key of the entry to check. + * @returns {boolean} Returns `true` if an entry for `key` exists, else `false`. + */ + function mapCacheHas(key) { + return getMapData(this, key).has(key); + } + + module.exports = mapCacheHas; + + +/***/ }), +/* 145 */ +/***/ (function(module, exports, __webpack_require__) { + + var getMapData = __webpack_require__(141); + + /** + * Sets the map `key` to `value`. + * + * @private + * @name set + * @memberOf MapCache + * @param {string} key The key of the value to set. + * @param {*} value The value to set. + * @returns {Object} Returns the map cache instance. + */ + function mapCacheSet(key, value) { + var data = getMapData(this, key), + size = data.size; + + data.set(key, value); + this.size += data.size == size ? 0 : 1; + return this; + } + + module.exports = mapCacheSet; + + +/***/ }), +/* 146 */ +/***/ (function(module, exports) { + + /** Used to stand-in for `undefined` hash values. */ + var HASH_UNDEFINED = '__lodash_hash_undefined__'; + + /** + * Adds `value` to the array cache. + * + * @private + * @name add + * @memberOf SetCache + * @alias push + * @param {*} value The value to cache. + * @returns {Object} Returns the cache instance. + */ + function setCacheAdd(value) { + this.__data__.set(value, HASH_UNDEFINED); + return this; + } + + module.exports = setCacheAdd; + + +/***/ }), +/* 147 */ +/***/ (function(module, exports) { + + /** + * Checks if `value` is in the array cache. + * + * @private + * @name has + * @memberOf SetCache + * @param {*} value The value to search for. + * @returns {number} Returns `true` if `value` is found, else `false`. + */ + function setCacheHas(value) { + return this.__data__.has(value); + } + + module.exports = setCacheHas; + + +/***/ }), +/* 148 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIndexOf = __webpack_require__(149); + + /** + * A specialized version of `_.includes` for arrays without support for + * specifying an index to search from. + * + * @private + * @param {Array} [array] The array to inspect. + * @param {*} target The value to search for. + * @returns {boolean} Returns `true` if `target` is found, else `false`. + */ + function arrayIncludes(array, value) { + var length = array == null ? 0 : array.length; + return !!length && baseIndexOf(array, value, 0) > -1; + } + + module.exports = arrayIncludes; + + +/***/ }), +/* 149 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFindIndex = __webpack_require__(150), + baseIsNaN = __webpack_require__(151), + strictIndexOf = __webpack_require__(152); + + /** + * The base implementation of `_.indexOf` without `fromIndex` bounds checks. + * + * @private + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @param {number} fromIndex The index to search from. + * @returns {number} Returns the index of the matched value, else `-1`. + */ + function baseIndexOf(array, value, fromIndex) { + return value === value + ? strictIndexOf(array, value, fromIndex) + : baseFindIndex(array, baseIsNaN, fromIndex); + } + + module.exports = baseIndexOf; + + +/***/ }), +/* 150 */ +/***/ (function(module, exports) { + + /** + * The base implementation of `_.findIndex` and `_.findLastIndex` without + * support for iteratee shorthands. + * + * @private + * @param {Array} array The array to inspect. + * @param {Function} predicate The function invoked per iteration. + * @param {number} fromIndex The index to search from. + * @param {boolean} [fromRight] Specify iterating from right to left. + * @returns {number} Returns the index of the matched value, else `-1`. + */ + function baseFindIndex(array, predicate, fromIndex, fromRight) { + var length = array.length, + index = fromIndex + (fromRight ? 1 : -1); + + while ((fromRight ? index-- : ++index < length)) { + if (predicate(array[index], index, array)) { + return index; + } + } + return -1; + } + + module.exports = baseFindIndex; + + +/***/ }), +/* 151 */ +/***/ (function(module, exports) { + + /** + * The base implementation of `_.isNaN` without support for number objects. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is `NaN`, else `false`. + */ + function baseIsNaN(value) { + return value !== value; + } + + module.exports = baseIsNaN; + + +/***/ }), +/* 152 */ +/***/ (function(module, exports) { + + /** + * A specialized version of `_.indexOf` which performs strict equality + * comparisons of values, i.e. `===`. + * + * @private + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @param {number} fromIndex The index to search from. + * @returns {number} Returns the index of the matched value, else `-1`. + */ + function strictIndexOf(array, value, fromIndex) { + var index = fromIndex - 1, + length = array.length; + + while (++index < length) { + if (array[index] === value) { + return index; + } + } + return -1; + } + + module.exports = strictIndexOf; + + +/***/ }), +/* 153 */ +/***/ (function(module, exports) { + + /** + * This function is like `arrayIncludes` except that it accepts a comparator. + * + * @private + * @param {Array} [array] The array to inspect. + * @param {*} target The value to search for. + * @param {Function} comparator The comparator invoked per element. + * @returns {boolean} Returns `true` if `target` is found, else `false`. + */ + function arrayIncludesWith(array, value, comparator) { + var index = -1, + length = array == null ? 0 : array.length; + + while (++index < length) { + if (comparator(value, array[index])) { + return true; + } + } + return false; + } + + module.exports = arrayIncludesWith; + + +/***/ }), +/* 154 */ +/***/ (function(module, exports) { + + /** + * A specialized version of `_.map` for arrays without support for iteratee + * shorthands. + * + * @private + * @param {Array} [array] The array to iterate over. + * @param {Function} iteratee The function invoked per iteration. + * @returns {Array} Returns the new mapped array. + */ + function arrayMap(array, iteratee) { + var index = -1, + length = array == null ? 0 : array.length, + result = Array(length); + + while (++index < length) { + result[index] = iteratee(array[index], index, array); + } + return result; + } + + module.exports = arrayMap; + + +/***/ }), +/* 155 */ +/***/ (function(module, exports) { + + /** + * The base implementation of `_.unary` without support for storing metadata. + * + * @private + * @param {Function} func The function to cap arguments for. + * @returns {Function} Returns the new capped function. + */ + function baseUnary(func) { + return function(value) { + return func(value); + }; + } + + module.exports = baseUnary; + + +/***/ }), +/* 156 */ +/***/ (function(module, exports) { + + /** + * Checks if a `cache` value for `key` exists. + * + * @private + * @param {Object} cache The cache to query. + * @param {string} key The key of the entry to check. + * @returns {boolean} Returns `true` if an entry for `key` exists, else `false`. + */ + function cacheHas(cache, key) { + return cache.has(key); + } + + module.exports = cacheHas; + + +/***/ }), +/* 157 */ +/***/ (function(module, exports, __webpack_require__) { + + var identity = __webpack_require__(158), + overRest = __webpack_require__(159), + setToString = __webpack_require__(161); + + /** + * The base implementation of `_.rest` which doesn't validate or coerce arguments. + * + * @private + * @param {Function} func The function to apply a rest parameter to. + * @param {number} [start=func.length-1] The start position of the rest parameter. + * @returns {Function} Returns the new function. + */ + function baseRest(func, start) { + return setToString(overRest(func, start, identity), func + ''); + } + + module.exports = baseRest; + + +/***/ }), +/* 158 */ +/***/ (function(module, exports) { + + /** + * This method returns the first argument it receives. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Util + * @param {*} value Any value. + * @returns {*} Returns `value`. + * @example + * + * var object = { 'a': 1 }; + * + * console.log(_.identity(object) === object); + * // => true + */ + function identity(value) { + return value; + } + + module.exports = identity; + + +/***/ }), +/* 159 */ +/***/ (function(module, exports, __webpack_require__) { + + var apply = __webpack_require__(160); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeMax = Math.max; + + /** + * A specialized version of `baseRest` which transforms the rest array. + * + * @private + * @param {Function} func The function to apply a rest parameter to. + * @param {number} [start=func.length-1] The start position of the rest parameter. + * @param {Function} transform The rest array transform. + * @returns {Function} Returns the new function. + */ + function overRest(func, start, transform) { + start = nativeMax(start === undefined ? (func.length - 1) : start, 0); + return function() { + var args = arguments, + index = -1, + length = nativeMax(args.length - start, 0), + array = Array(length); + + while (++index < length) { + array[index] = args[start + index]; + } + index = -1; + var otherArgs = Array(start + 1); + while (++index < start) { + otherArgs[index] = args[index]; + } + otherArgs[start] = transform(array); + return apply(func, this, otherArgs); + }; + } + + module.exports = overRest; + + +/***/ }), +/* 160 */ +/***/ (function(module, exports) { + + /** + * A faster alternative to `Function#apply`, this function invokes `func` + * with the `this` binding of `thisArg` and the arguments of `args`. + * + * @private + * @param {Function} func The function to invoke. + * @param {*} thisArg The `this` binding of `func`. + * @param {Array} args The arguments to invoke `func` with. + * @returns {*} Returns the result of `func`. + */ + function apply(func, thisArg, args) { + switch (args.length) { + case 0: return func.call(thisArg); + case 1: return func.call(thisArg, args[0]); + case 2: return func.call(thisArg, args[0], args[1]); + case 3: return func.call(thisArg, args[0], args[1], args[2]); + } + return func.apply(thisArg, args); + } + + module.exports = apply; + + +/***/ }), +/* 161 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSetToString = __webpack_require__(162), + shortOut = __webpack_require__(165); + + /** + * Sets the `toString` method of `func` to return `string`. + * + * @private + * @param {Function} func The function to modify. + * @param {Function} string The `toString` result. + * @returns {Function} Returns `func`. + */ + var setToString = shortOut(baseSetToString); + + module.exports = setToString; + + +/***/ }), +/* 162 */ +/***/ (function(module, exports, __webpack_require__) { + + var constant = __webpack_require__(163), + defineProperty = __webpack_require__(164), + identity = __webpack_require__(158); + + /** + * The base implementation of `setToString` without support for hot loop shorting. + * + * @private + * @param {Function} func The function to modify. + * @param {Function} string The `toString` result. + * @returns {Function} Returns `func`. + */ + var baseSetToString = !defineProperty ? identity : function(func, string) { + return defineProperty(func, 'toString', { + 'configurable': true, + 'enumerable': false, + 'value': constant(string), + 'writable': true + }); + }; + + module.exports = baseSetToString; + + +/***/ }), +/* 163 */ +/***/ (function(module, exports) { + + /** + * Creates a function that returns `value`. + * + * @static + * @memberOf _ + * @since 2.4.0 + * @category Util + * @param {*} value The value to return from the new function. + * @returns {Function} Returns the new constant function. + * @example + * + * var objects = _.times(2, _.constant({ 'a': 1 })); + * + * console.log(objects); + * // => [{ 'a': 1 }, { 'a': 1 }] + * + * console.log(objects[0] === objects[1]); + * // => true + */ + function constant(value) { + return function() { + return value; + }; + } + + module.exports = constant; + + +/***/ }), +/* 164 */ +/***/ (function(module, exports, __webpack_require__) { + + var getNative = __webpack_require__(122); + + var defineProperty = (function() { + try { + var func = getNative(Object, 'defineProperty'); + func({}, '', {}); + return func; + } catch (e) {} + }()); + + module.exports = defineProperty; + + +/***/ }), +/* 165 */ +/***/ (function(module, exports) { + + /** Used to detect hot functions by number of calls within a span of milliseconds. */ + var HOT_COUNT = 800, + HOT_SPAN = 16; + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeNow = Date.now; + + /** + * Creates a function that'll short out and invoke `identity` instead + * of `func` when it's called `HOT_COUNT` or more times in `HOT_SPAN` + * milliseconds. + * + * @private + * @param {Function} func The function to restrict. + * @returns {Function} Returns the new shortable function. + */ + function shortOut(func) { + var count = 0, + lastCalled = 0; + + return function() { + var stamp = nativeNow(), + remaining = HOT_SPAN - (stamp - lastCalled); + + lastCalled = stamp; + if (remaining > 0) { + if (++count >= HOT_COUNT) { + return arguments[0]; + } + } else { + count = 0; + } + return func.apply(undefined, arguments); + }; + } + + module.exports = shortOut; + + +/***/ }), +/* 166 */ +/***/ (function(module, exports, __webpack_require__) { + + var isArrayLike = __webpack_require__(89), + isObjectLike = __webpack_require__(104); + + /** + * This method is like `_.isArrayLike` except that it also checks if `value` + * is an object. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an array-like object, + * else `false`. + * @example + * + * _.isArrayLikeObject([1, 2, 3]); + * // => true + * + * _.isArrayLikeObject(document.body.children); + * // => true + * + * _.isArrayLikeObject('abc'); + * // => false + * + * _.isArrayLikeObject(_.noop); + * // => false + */ + function isArrayLikeObject(value) { + return isObjectLike(value) && isArrayLike(value); + } + + module.exports = isArrayLikeObject; + + +/***/ }), +/* 167 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseDifference = __webpack_require__(115), + baseFlatten = __webpack_require__(108), + baseIteratee = __webpack_require__(168), + baseRest = __webpack_require__(157), + isArrayLikeObject = __webpack_require__(166), + last = __webpack_require__(228); + + /** + * This method is like `_.difference` except that it accepts `iteratee` which + * is invoked for each element of `array` and `values` to generate the criterion + * by which they're compared. The order and references of result values are + * determined by the first array. The iteratee is invoked with one argument: + * (value). + * + * **Note:** Unlike `_.pullAllBy`, this method returns a new array. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {...Array} [values] The values to exclude. + * @param {Function} [iteratee=_.identity] The iteratee invoked per element. + * @returns {Array} Returns the new array of filtered values. + * @example + * + * _.differenceBy([2.1, 1.2], [2.3, 3.4], Math.floor); + * // => [1.2] + * + * // The `_.property` iteratee shorthand. + * _.differenceBy([{ 'x': 2 }, { 'x': 1 }], [{ 'x': 1 }], 'x'); + * // => [{ 'x': 2 }] + */ + var differenceBy = baseRest(function(array, values) { + var iteratee = last(values); + if (isArrayLikeObject(iteratee)) { + iteratee = undefined; + } + return isArrayLikeObject(array) + ? baseDifference(array, baseFlatten(values, 1, isArrayLikeObject, true), baseIteratee(iteratee, 2)) + : []; + }); + + module.exports = differenceBy; + + +/***/ }), +/* 168 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseMatches = __webpack_require__(169), + baseMatchesProperty = __webpack_require__(211), + identity = __webpack_require__(158), + isArray = __webpack_require__(112), + property = __webpack_require__(225); + + /** + * The base implementation of `_.iteratee`. + * + * @private + * @param {*} [value=_.identity] The value to convert to an iteratee. + * @returns {Function} Returns the iteratee. + */ + function baseIteratee(value) { + // Don't store the `typeof` result in a variable to avoid a JIT bug in Safari 9. + // See https://bugs.webkit.org/show_bug.cgi?id=156034 for more details. + if (typeof value == 'function') { + return value; + } + if (value == null) { + return identity; + } + if (typeof value == 'object') { + return isArray(value) + ? baseMatchesProperty(value[0], value[1]) + : baseMatches(value); + } + return property(value); + } + + module.exports = baseIteratee; + + +/***/ }), +/* 169 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIsMatch = __webpack_require__(170), + getMatchData = __webpack_require__(208), + matchesStrictComparable = __webpack_require__(210); + + /** + * The base implementation of `_.matches` which doesn't clone `source`. + * + * @private + * @param {Object} source The object of property values to match. + * @returns {Function} Returns the new spec function. + */ + function baseMatches(source) { + var matchData = getMatchData(source); + if (matchData.length == 1 && matchData[0][2]) { + return matchesStrictComparable(matchData[0][0], matchData[0][1]); + } + return function(object) { + return object === source || baseIsMatch(object, source, matchData); + }; + } + + module.exports = baseMatches; + + +/***/ }), +/* 170 */ +/***/ (function(module, exports, __webpack_require__) { + + var Stack = __webpack_require__(171), + baseIsEqual = __webpack_require__(177); + + /** Used to compose bitmasks for value comparisons. */ + var COMPARE_PARTIAL_FLAG = 1, + COMPARE_UNORDERED_FLAG = 2; + + /** + * The base implementation of `_.isMatch` without support for iteratee shorthands. + * + * @private + * @param {Object} object The object to inspect. + * @param {Object} source The object of property values to match. + * @param {Array} matchData The property names, values, and compare flags to match. + * @param {Function} [customizer] The function to customize comparisons. + * @returns {boolean} Returns `true` if `object` is a match, else `false`. + */ + function baseIsMatch(object, source, matchData, customizer) { + var index = matchData.length, + length = index, + noCustomizer = !customizer; + + if (object == null) { + return !length; + } + object = Object(object); + while (index--) { + var data = matchData[index]; + if ((noCustomizer && data[2]) + ? data[1] !== object[data[0]] + : !(data[0] in object) + ) { + return false; + } + } + while (++index < length) { + data = matchData[index]; + var key = data[0], + objValue = object[key], + srcValue = data[1]; + + if (noCustomizer && data[2]) { + if (objValue === undefined && !(key in object)) { + return false; + } + } else { + var stack = new Stack; + if (customizer) { + var result = customizer(objValue, srcValue, key, object, source, stack); + } + if (!(result === undefined + ? baseIsEqual(srcValue, objValue, COMPARE_PARTIAL_FLAG | COMPARE_UNORDERED_FLAG, customizer, stack) + : result + )) { + return false; + } + } + } + return true; + } + + module.exports = baseIsMatch; + + +/***/ }), +/* 171 */ +/***/ (function(module, exports, __webpack_require__) { + + var ListCache = __webpack_require__(132), + stackClear = __webpack_require__(172), + stackDelete = __webpack_require__(173), + stackGet = __webpack_require__(174), + stackHas = __webpack_require__(175), + stackSet = __webpack_require__(176); + + /** + * Creates a stack cache object to store key-value pairs. + * + * @private + * @constructor + * @param {Array} [entries] The key-value pairs to cache. + */ + function Stack(entries) { + var data = this.__data__ = new ListCache(entries); + this.size = data.size; + } + + // Add methods to `Stack`. + Stack.prototype.clear = stackClear; + Stack.prototype['delete'] = stackDelete; + Stack.prototype.get = stackGet; + Stack.prototype.has = stackHas; + Stack.prototype.set = stackSet; + + module.exports = Stack; + + +/***/ }), +/* 172 */ +/***/ (function(module, exports, __webpack_require__) { + + var ListCache = __webpack_require__(132); + + /** + * Removes all key-value entries from the stack. + * + * @private + * @name clear + * @memberOf Stack + */ + function stackClear() { + this.__data__ = new ListCache; + this.size = 0; + } + + module.exports = stackClear; + + +/***/ }), +/* 173 */ +/***/ (function(module, exports) { + + /** + * Removes `key` and its value from the stack. + * + * @private + * @name delete + * @memberOf Stack + * @param {string} key The key of the value to remove. + * @returns {boolean} Returns `true` if the entry was removed, else `false`. + */ + function stackDelete(key) { + var data = this.__data__, + result = data['delete'](key); + + this.size = data.size; + return result; + } + + module.exports = stackDelete; + + +/***/ }), +/* 174 */ +/***/ (function(module, exports) { + + /** + * Gets the stack value for `key`. + * + * @private + * @name get + * @memberOf Stack + * @param {string} key The key of the value to get. + * @returns {*} Returns the entry value. + */ + function stackGet(key) { + return this.__data__.get(key); + } + + module.exports = stackGet; + + +/***/ }), +/* 175 */ +/***/ (function(module, exports) { + + /** + * Checks if a stack value for `key` exists. + * + * @private + * @name has + * @memberOf Stack + * @param {string} key The key of the entry to check. + * @returns {boolean} Returns `true` if an entry for `key` exists, else `false`. + */ + function stackHas(key) { + return this.__data__.has(key); + } + + module.exports = stackHas; + + +/***/ }), +/* 176 */ +/***/ (function(module, exports, __webpack_require__) { + + var ListCache = __webpack_require__(132), + Map = __webpack_require__(139), + MapCache = __webpack_require__(117); + + /** Used as the size to enable large array optimizations. */ + var LARGE_ARRAY_SIZE = 200; + + /** + * Sets the stack `key` to `value`. + * + * @private + * @name set + * @memberOf Stack + * @param {string} key The key of the value to set. + * @param {*} value The value to set. + * @returns {Object} Returns the stack cache instance. + */ + function stackSet(key, value) { + var data = this.__data__; + if (data instanceof ListCache) { + var pairs = data.__data__; + if (!Map || (pairs.length < LARGE_ARRAY_SIZE - 1)) { + pairs.push([key, value]); + this.size = ++data.size; + return this; + } + data = this.__data__ = new MapCache(pairs); + } + data.set(key, value); + this.size = data.size; + return this; + } + + module.exports = stackSet; + + +/***/ }), +/* 177 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIsEqualDeep = __webpack_require__(178), + isObjectLike = __webpack_require__(104); + + /** + * The base implementation of `_.isEqual` which supports partial comparisons + * and tracks traversed objects. + * + * @private + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @param {boolean} bitmask The bitmask flags. + * 1 - Unordered comparison + * 2 - Partial comparison + * @param {Function} [customizer] The function to customize comparisons. + * @param {Object} [stack] Tracks traversed `value` and `other` objects. + * @returns {boolean} Returns `true` if the values are equivalent, else `false`. + */ + function baseIsEqual(value, other, bitmask, customizer, stack) { + if (value === other) { + return true; + } + if (value == null || other == null || (!isObjectLike(value) && !isObjectLike(other))) { + return value !== value && other !== other; + } + return baseIsEqualDeep(value, other, bitmask, customizer, baseIsEqual, stack); + } + + module.exports = baseIsEqual; + + +/***/ }), +/* 178 */ +/***/ (function(module, exports, __webpack_require__) { + + var Stack = __webpack_require__(171), + equalArrays = __webpack_require__(179), + equalByTag = __webpack_require__(181), + equalObjects = __webpack_require__(185), + getTag = __webpack_require__(203), + isArray = __webpack_require__(112), + isBuffer = __webpack_require__(194), + isTypedArray = __webpack_require__(196); + + /** Used to compose bitmasks for value comparisons. */ + var COMPARE_PARTIAL_FLAG = 1; + + /** `Object#toString` result references. */ + var argsTag = '[object Arguments]', + arrayTag = '[object Array]', + objectTag = '[object Object]'; + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * A specialized version of `baseIsEqual` for arrays and objects which performs + * deep comparisons and tracks traversed objects enabling objects with circular + * references to be compared. + * + * @private + * @param {Object} object The object to compare. + * @param {Object} other The other object to compare. + * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. + * @param {Function} customizer The function to customize comparisons. + * @param {Function} equalFunc The function to determine equivalents of values. + * @param {Object} [stack] Tracks traversed `object` and `other` objects. + * @returns {boolean} Returns `true` if the objects are equivalent, else `false`. + */ + function baseIsEqualDeep(object, other, bitmask, customizer, equalFunc, stack) { + var objIsArr = isArray(object), + othIsArr = isArray(other), + objTag = objIsArr ? arrayTag : getTag(object), + othTag = othIsArr ? arrayTag : getTag(other); + + objTag = objTag == argsTag ? objectTag : objTag; + othTag = othTag == argsTag ? objectTag : othTag; + + var objIsObj = objTag == objectTag, + othIsObj = othTag == objectTag, + isSameTag = objTag == othTag; + + if (isSameTag && isBuffer(object)) { + if (!isBuffer(other)) { + return false; + } + objIsArr = true; + objIsObj = false; + } + if (isSameTag && !objIsObj) { + stack || (stack = new Stack); + return (objIsArr || isTypedArray(object)) + ? equalArrays(object, other, bitmask, customizer, equalFunc, stack) + : equalByTag(object, other, objTag, bitmask, customizer, equalFunc, stack); + } + if (!(bitmask & COMPARE_PARTIAL_FLAG)) { + var objIsWrapped = objIsObj && hasOwnProperty.call(object, '__wrapped__'), + othIsWrapped = othIsObj && hasOwnProperty.call(other, '__wrapped__'); + + if (objIsWrapped || othIsWrapped) { + var objUnwrapped = objIsWrapped ? object.value() : object, + othUnwrapped = othIsWrapped ? other.value() : other; + + stack || (stack = new Stack); + return equalFunc(objUnwrapped, othUnwrapped, bitmask, customizer, stack); + } + } + if (!isSameTag) { + return false; + } + stack || (stack = new Stack); + return equalObjects(object, other, bitmask, customizer, equalFunc, stack); + } + + module.exports = baseIsEqualDeep; + + +/***/ }), +/* 179 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetCache = __webpack_require__(116), + arraySome = __webpack_require__(180), + cacheHas = __webpack_require__(156); + + /** Used to compose bitmasks for value comparisons. */ + var COMPARE_PARTIAL_FLAG = 1, + COMPARE_UNORDERED_FLAG = 2; + + /** + * A specialized version of `baseIsEqualDeep` for arrays with support for + * partial deep comparisons. + * + * @private + * @param {Array} array The array to compare. + * @param {Array} other The other array to compare. + * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. + * @param {Function} customizer The function to customize comparisons. + * @param {Function} equalFunc The function to determine equivalents of values. + * @param {Object} stack Tracks traversed `array` and `other` objects. + * @returns {boolean} Returns `true` if the arrays are equivalent, else `false`. + */ + function equalArrays(array, other, bitmask, customizer, equalFunc, stack) { + var isPartial = bitmask & COMPARE_PARTIAL_FLAG, + arrLength = array.length, + othLength = other.length; + + if (arrLength != othLength && !(isPartial && othLength > arrLength)) { + return false; + } + // Assume cyclic values are equal. + var stacked = stack.get(array); + if (stacked && stack.get(other)) { + return stacked == other; + } + var index = -1, + result = true, + seen = (bitmask & COMPARE_UNORDERED_FLAG) ? new SetCache : undefined; + + stack.set(array, other); + stack.set(other, array); + + // Ignore non-index properties. + while (++index < arrLength) { + var arrValue = array[index], + othValue = other[index]; + + if (customizer) { + var compared = isPartial + ? customizer(othValue, arrValue, index, other, array, stack) + : customizer(arrValue, othValue, index, array, other, stack); + } + if (compared !== undefined) { + if (compared) { + continue; + } + result = false; + break; + } + // Recursively compare arrays (susceptible to call stack limits). + if (seen) { + if (!arraySome(other, function(othValue, othIndex) { + if (!cacheHas(seen, othIndex) && + (arrValue === othValue || equalFunc(arrValue, othValue, bitmask, customizer, stack))) { + return seen.push(othIndex); + } + })) { + result = false; + break; + } + } else if (!( + arrValue === othValue || + equalFunc(arrValue, othValue, bitmask, customizer, stack) + )) { + result = false; + break; + } + } + stack['delete'](array); + stack['delete'](other); + return result; + } + + module.exports = equalArrays; + + +/***/ }), +/* 180 */ +/***/ (function(module, exports) { + + /** + * A specialized version of `_.some` for arrays without support for iteratee + * shorthands. + * + * @private + * @param {Array} [array] The array to iterate over. + * @param {Function} predicate The function invoked per iteration. + * @returns {boolean} Returns `true` if any element passes the predicate check, + * else `false`. + */ + function arraySome(array, predicate) { + var index = -1, + length = array == null ? 0 : array.length; + + while (++index < length) { + if (predicate(array[index], index, array)) { + return true; + } + } + return false; + } + + module.exports = arraySome; + + +/***/ }), +/* 181 */ +/***/ (function(module, exports, __webpack_require__) { + + var Symbol = __webpack_require__(92), + Uint8Array = __webpack_require__(182), + eq = __webpack_require__(88), + equalArrays = __webpack_require__(179), + mapToArray = __webpack_require__(183), + setToArray = __webpack_require__(184); + + /** Used to compose bitmasks for value comparisons. */ + var COMPARE_PARTIAL_FLAG = 1, + COMPARE_UNORDERED_FLAG = 2; + + /** `Object#toString` result references. */ + var boolTag = '[object Boolean]', + dateTag = '[object Date]', + errorTag = '[object Error]', + mapTag = '[object Map]', + numberTag = '[object Number]', + regexpTag = '[object RegExp]', + setTag = '[object Set]', + stringTag = '[object String]', + symbolTag = '[object Symbol]'; + + var arrayBufferTag = '[object ArrayBuffer]', + dataViewTag = '[object DataView]'; + + /** Used to convert symbols to primitives and strings. */ + var symbolProto = Symbol ? Symbol.prototype : undefined, + symbolValueOf = symbolProto ? symbolProto.valueOf : undefined; + + /** + * A specialized version of `baseIsEqualDeep` for comparing objects of + * the same `toStringTag`. + * + * **Note:** This function only supports comparing values with tags of + * `Boolean`, `Date`, `Error`, `Number`, `RegExp`, or `String`. + * + * @private + * @param {Object} object The object to compare. + * @param {Object} other The other object to compare. + * @param {string} tag The `toStringTag` of the objects to compare. + * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. + * @param {Function} customizer The function to customize comparisons. + * @param {Function} equalFunc The function to determine equivalents of values. + * @param {Object} stack Tracks traversed `object` and `other` objects. + * @returns {boolean} Returns `true` if the objects are equivalent, else `false`. + */ + function equalByTag(object, other, tag, bitmask, customizer, equalFunc, stack) { + switch (tag) { + case dataViewTag: + if ((object.byteLength != other.byteLength) || + (object.byteOffset != other.byteOffset)) { + return false; + } + object = object.buffer; + other = other.buffer; + + case arrayBufferTag: + if ((object.byteLength != other.byteLength) || + !equalFunc(new Uint8Array(object), new Uint8Array(other))) { + return false; + } + return true; + + case boolTag: + case dateTag: + case numberTag: + // Coerce booleans to `1` or `0` and dates to milliseconds. + // Invalid dates are coerced to `NaN`. + return eq(+object, +other); + + case errorTag: + return object.name == other.name && object.message == other.message; + + case regexpTag: + case stringTag: + // Coerce regexes to strings and treat strings, primitives and objects, + // as equal. See http://www.ecma-international.org/ecma-262/7.0/#sec-regexp.prototype.tostring + // for more details. + return object == (other + ''); + + case mapTag: + var convert = mapToArray; + + case setTag: + var isPartial = bitmask & COMPARE_PARTIAL_FLAG; + convert || (convert = setToArray); + + if (object.size != other.size && !isPartial) { + return false; + } + // Assume cyclic values are equal. + var stacked = stack.get(object); + if (stacked) { + return stacked == other; + } + bitmask |= COMPARE_UNORDERED_FLAG; + + // Recursively compare objects (susceptible to call stack limits). + stack.set(object, other); + var result = equalArrays(convert(object), convert(other), bitmask, customizer, equalFunc, stack); + stack['delete'](object); + return result; + + case symbolTag: + if (symbolValueOf) { + return symbolValueOf.call(object) == symbolValueOf.call(other); + } + } + return false; + } + + module.exports = equalByTag; + + +/***/ }), +/* 182 */ +/***/ (function(module, exports, __webpack_require__) { + + var root = __webpack_require__(93); + + /** Built-in value references. */ + var Uint8Array = root.Uint8Array; + + module.exports = Uint8Array; + + +/***/ }), +/* 183 */ +/***/ (function(module, exports) { + + /** + * Converts `map` to its key-value pairs. + * + * @private + * @param {Object} map The map to convert. + * @returns {Array} Returns the key-value pairs. + */ + function mapToArray(map) { + var index = -1, + result = Array(map.size); + + map.forEach(function(value, key) { + result[++index] = [key, value]; + }); + return result; + } + + module.exports = mapToArray; + + +/***/ }), +/* 184 */ +/***/ (function(module, exports) { + + /** + * Converts `set` to an array of its values. + * + * @private + * @param {Object} set The set to convert. + * @returns {Array} Returns the values. + */ + function setToArray(set) { + var index = -1, + result = Array(set.size); + + set.forEach(function(value) { + result[++index] = value; + }); + return result; + } + + module.exports = setToArray; + + +/***/ }), +/* 185 */ +/***/ (function(module, exports, __webpack_require__) { + + var getAllKeys = __webpack_require__(186); + + /** Used to compose bitmasks for value comparisons. */ + var COMPARE_PARTIAL_FLAG = 1; + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * A specialized version of `baseIsEqualDeep` for objects with support for + * partial deep comparisons. + * + * @private + * @param {Object} object The object to compare. + * @param {Object} other The other object to compare. + * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. + * @param {Function} customizer The function to customize comparisons. + * @param {Function} equalFunc The function to determine equivalents of values. + * @param {Object} stack Tracks traversed `object` and `other` objects. + * @returns {boolean} Returns `true` if the objects are equivalent, else `false`. + */ + function equalObjects(object, other, bitmask, customizer, equalFunc, stack) { + var isPartial = bitmask & COMPARE_PARTIAL_FLAG, + objProps = getAllKeys(object), + objLength = objProps.length, + othProps = getAllKeys(other), + othLength = othProps.length; + + if (objLength != othLength && !isPartial) { + return false; + } + var index = objLength; + while (index--) { + var key = objProps[index]; + if (!(isPartial ? key in other : hasOwnProperty.call(other, key))) { + return false; + } + } + // Assume cyclic values are equal. + var stacked = stack.get(object); + if (stacked && stack.get(other)) { + return stacked == other; + } + var result = true; + stack.set(object, other); + stack.set(other, object); + + var skipCtor = isPartial; + while (++index < objLength) { + key = objProps[index]; + var objValue = object[key], + othValue = other[key]; + + if (customizer) { + var compared = isPartial + ? customizer(othValue, objValue, key, other, object, stack) + : customizer(objValue, othValue, key, object, other, stack); + } + // Recursively compare objects (susceptible to call stack limits). + if (!(compared === undefined + ? (objValue === othValue || equalFunc(objValue, othValue, bitmask, customizer, stack)) + : compared + )) { + result = false; + break; + } + skipCtor || (skipCtor = key == 'constructor'); + } + if (result && !skipCtor) { + var objCtor = object.constructor, + othCtor = other.constructor; + + // Non `Object` object instances with different constructors are not equal. + if (objCtor != othCtor && + ('constructor' in object && 'constructor' in other) && + !(typeof objCtor == 'function' && objCtor instanceof objCtor && + typeof othCtor == 'function' && othCtor instanceof othCtor)) { + result = false; + } + } + stack['delete'](object); + stack['delete'](other); + return result; + } + + module.exports = equalObjects; + + +/***/ }), +/* 186 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseGetAllKeys = __webpack_require__(187), + getSymbols = __webpack_require__(188), + keys = __webpack_require__(191); + + /** + * Creates an array of own enumerable property names and symbols of `object`. + * + * @private + * @param {Object} object The object to query. + * @returns {Array} Returns the array of property names and symbols. + */ + function getAllKeys(object) { + return baseGetAllKeys(object, keys, getSymbols); + } + + module.exports = getAllKeys; + + +/***/ }), +/* 187 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayPush = __webpack_require__(107), + isArray = __webpack_require__(112); + + /** + * The base implementation of `getAllKeys` and `getAllKeysIn` which uses + * `keysFunc` and `symbolsFunc` to get the enumerable property names and + * symbols of `object`. + * + * @private + * @param {Object} object The object to query. + * @param {Function} keysFunc The function to get the keys of `object`. + * @param {Function} symbolsFunc The function to get the symbols of `object`. + * @returns {Array} Returns the array of property names and symbols. + */ + function baseGetAllKeys(object, keysFunc, symbolsFunc) { + var result = keysFunc(object); + return isArray(object) ? result : arrayPush(result, symbolsFunc(object)); + } + + module.exports = baseGetAllKeys; + + +/***/ }), +/* 188 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayFilter = __webpack_require__(189), + stubArray = __webpack_require__(190); + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Built-in value references. */ + var propertyIsEnumerable = objectProto.propertyIsEnumerable; + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeGetSymbols = Object.getOwnPropertySymbols; + + /** + * Creates an array of the own enumerable symbols of `object`. + * + * @private + * @param {Object} object The object to query. + * @returns {Array} Returns the array of symbols. + */ + var getSymbols = !nativeGetSymbols ? stubArray : function(object) { + if (object == null) { + return []; + } + object = Object(object); + return arrayFilter(nativeGetSymbols(object), function(symbol) { + return propertyIsEnumerable.call(object, symbol); + }); + }; + + module.exports = getSymbols; + + +/***/ }), +/* 189 */ +/***/ (function(module, exports) { + + /** + * A specialized version of `_.filter` for arrays without support for + * iteratee shorthands. + * + * @private + * @param {Array} [array] The array to iterate over. + * @param {Function} predicate The function invoked per iteration. + * @returns {Array} Returns the new filtered array. + */ + function arrayFilter(array, predicate) { + var index = -1, + length = array == null ? 0 : array.length, + resIndex = 0, + result = []; + + while (++index < length) { + var value = array[index]; + if (predicate(value, index, array)) { + result[resIndex++] = value; + } + } + return result; + } + + module.exports = arrayFilter; + + +/***/ }), +/* 190 */ +/***/ (function(module, exports) { + + /** + * This method returns a new empty array. + * + * @static + * @memberOf _ + * @since 4.13.0 + * @category Util + * @returns {Array} Returns the new empty array. + * @example + * + * var arrays = _.times(2, _.stubArray); + * + * console.log(arrays); + * // => [[], []] + * + * console.log(arrays[0] === arrays[1]); + * // => false + */ + function stubArray() { + return []; + } + + module.exports = stubArray; + + +/***/ }), +/* 191 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayLikeKeys = __webpack_require__(192), + baseKeys = __webpack_require__(199), + isArrayLike = __webpack_require__(89); + + /** + * Creates an array of the own enumerable property names of `object`. + * + * **Note:** Non-object values are coerced to objects. See the + * [ES spec](http://ecma-international.org/ecma-262/7.0/#sec-object.keys) + * for more details. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Object + * @param {Object} object The object to query. + * @returns {Array} Returns the array of property names. + * @example + * + * function Foo() { + * this.a = 1; + * this.b = 2; + * } + * + * Foo.prototype.c = 3; + * + * _.keys(new Foo); + * // => ['a', 'b'] (iteration order is not guaranteed) + * + * _.keys('hi'); + * // => ['0', '1'] + */ + function keys(object) { + return isArrayLike(object) ? arrayLikeKeys(object) : baseKeys(object); + } + + module.exports = keys; + + +/***/ }), +/* 192 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseTimes = __webpack_require__(193), + isArguments = __webpack_require__(110), + isArray = __webpack_require__(112), + isBuffer = __webpack_require__(194), + isIndex = __webpack_require__(99), + isTypedArray = __webpack_require__(196); + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * Creates an array of the enumerable property names of the array-like `value`. + * + * @private + * @param {*} value The value to query. + * @param {boolean} inherited Specify returning inherited property names. + * @returns {Array} Returns the array of property names. + */ + function arrayLikeKeys(value, inherited) { + var isArr = isArray(value), + isArg = !isArr && isArguments(value), + isBuff = !isArr && !isArg && isBuffer(value), + isType = !isArr && !isArg && !isBuff && isTypedArray(value), + skipIndexes = isArr || isArg || isBuff || isType, + result = skipIndexes ? baseTimes(value.length, String) : [], + length = result.length; + + for (var key in value) { + if ((inherited || hasOwnProperty.call(value, key)) && + !(skipIndexes && ( + // Safari 9 has enumerable `arguments.length` in strict mode. + key == 'length' || + // Node.js 0.10 has enumerable non-index properties on buffers. + (isBuff && (key == 'offset' || key == 'parent')) || + // PhantomJS 2 has enumerable non-index properties on typed arrays. + (isType && (key == 'buffer' || key == 'byteLength' || key == 'byteOffset')) || + // Skip index properties. + isIndex(key, length) + ))) { + result.push(key); + } + } + return result; + } + + module.exports = arrayLikeKeys; + + +/***/ }), +/* 193 */ +/***/ (function(module, exports) { + + /** + * The base implementation of `_.times` without support for iteratee shorthands + * or max array length checks. + * + * @private + * @param {number} n The number of times to invoke `iteratee`. + * @param {Function} iteratee The function invoked per iteration. + * @returns {Array} Returns the array of results. + */ + function baseTimes(n, iteratee) { + var index = -1, + result = Array(n); + + while (++index < n) { + result[index] = iteratee(index); + } + return result; + } + + module.exports = baseTimes; + + +/***/ }), +/* 194 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(module) {var root = __webpack_require__(93), + stubFalse = __webpack_require__(195); + + /** Detect free variable `exports`. */ + var freeExports = typeof exports == 'object' && exports && !exports.nodeType && exports; + + /** Detect free variable `module`. */ + var freeModule = freeExports && typeof module == 'object' && module && !module.nodeType && module; + + /** Detect the popular CommonJS extension `module.exports`. */ + var moduleExports = freeModule && freeModule.exports === freeExports; + + /** Built-in value references. */ + var Buffer = moduleExports ? root.Buffer : undefined; + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeIsBuffer = Buffer ? Buffer.isBuffer : undefined; + + /** + * Checks if `value` is a buffer. + * + * @static + * @memberOf _ + * @since 4.3.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a buffer, else `false`. + * @example + * + * _.isBuffer(new Buffer(2)); + * // => true + * + * _.isBuffer(new Uint8Array(2)); + * // => false + */ + var isBuffer = nativeIsBuffer || stubFalse; + + module.exports = isBuffer; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(59)(module))) + +/***/ }), +/* 195 */ +/***/ (function(module, exports) { + + /** + * This method returns `false`. + * + * @static + * @memberOf _ + * @since 4.13.0 + * @category Util + * @returns {boolean} Returns `false`. + * @example + * + * _.times(2, _.stubFalse); + * // => [false, false] + */ + function stubFalse() { + return false; + } + + module.exports = stubFalse; + + +/***/ }), +/* 196 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIsTypedArray = __webpack_require__(197), + baseUnary = __webpack_require__(155), + nodeUtil = __webpack_require__(198); + + /* Node.js helper references. */ + var nodeIsTypedArray = nodeUtil && nodeUtil.isTypedArray; + + /** + * Checks if `value` is classified as a typed array. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a typed array, else `false`. + * @example + * + * _.isTypedArray(new Uint8Array); + * // => true + * + * _.isTypedArray([]); + * // => false + */ + var isTypedArray = nodeIsTypedArray ? baseUnary(nodeIsTypedArray) : baseIsTypedArray; + + module.exports = isTypedArray; + + +/***/ }), +/* 197 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseGetTag = __webpack_require__(91), + isLength = __webpack_require__(98), + isObjectLike = __webpack_require__(104); + + /** `Object#toString` result references. */ + var argsTag = '[object Arguments]', + arrayTag = '[object Array]', + boolTag = '[object Boolean]', + dateTag = '[object Date]', + errorTag = '[object Error]', + funcTag = '[object Function]', + mapTag = '[object Map]', + numberTag = '[object Number]', + objectTag = '[object Object]', + regexpTag = '[object RegExp]', + setTag = '[object Set]', + stringTag = '[object String]', + weakMapTag = '[object WeakMap]'; + + var arrayBufferTag = '[object ArrayBuffer]', + dataViewTag = '[object DataView]', + float32Tag = '[object Float32Array]', + float64Tag = '[object Float64Array]', + int8Tag = '[object Int8Array]', + int16Tag = '[object Int16Array]', + int32Tag = '[object Int32Array]', + uint8Tag = '[object Uint8Array]', + uint8ClampedTag = '[object Uint8ClampedArray]', + uint16Tag = '[object Uint16Array]', + uint32Tag = '[object Uint32Array]'; + + /** Used to identify `toStringTag` values of typed arrays. */ + var typedArrayTags = {}; + typedArrayTags[float32Tag] = typedArrayTags[float64Tag] = + typedArrayTags[int8Tag] = typedArrayTags[int16Tag] = + typedArrayTags[int32Tag] = typedArrayTags[uint8Tag] = + typedArrayTags[uint8ClampedTag] = typedArrayTags[uint16Tag] = + typedArrayTags[uint32Tag] = true; + typedArrayTags[argsTag] = typedArrayTags[arrayTag] = + typedArrayTags[arrayBufferTag] = typedArrayTags[boolTag] = + typedArrayTags[dataViewTag] = typedArrayTags[dateTag] = + typedArrayTags[errorTag] = typedArrayTags[funcTag] = + typedArrayTags[mapTag] = typedArrayTags[numberTag] = + typedArrayTags[objectTag] = typedArrayTags[regexpTag] = + typedArrayTags[setTag] = typedArrayTags[stringTag] = + typedArrayTags[weakMapTag] = false; + + /** + * The base implementation of `_.isTypedArray` without Node.js optimizations. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a typed array, else `false`. + */ + function baseIsTypedArray(value) { + return isObjectLike(value) && + isLength(value.length) && !!typedArrayTags[baseGetTag(value)]; + } + + module.exports = baseIsTypedArray; + + +/***/ }), +/* 198 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(module) {var freeGlobal = __webpack_require__(94); + + /** Detect free variable `exports`. */ + var freeExports = typeof exports == 'object' && exports && !exports.nodeType && exports; + + /** Detect free variable `module`. */ + var freeModule = freeExports && typeof module == 'object' && module && !module.nodeType && module; + + /** Detect the popular CommonJS extension `module.exports`. */ + var moduleExports = freeModule && freeModule.exports === freeExports; + + /** Detect free variable `process` from Node.js. */ + var freeProcess = moduleExports && freeGlobal.process; + + /** Used to access faster Node.js helpers. */ + var nodeUtil = (function() { + try { + // Use `util.types` for Node.js 10+. + var types = freeModule && freeModule.require && freeModule.require('util').types; + + if (types) { + return types; + } + + // Legacy `process.binding('util')` for Node.js < 10. + return freeProcess && freeProcess.binding && freeProcess.binding('util'); + } catch (e) {} + }()); + + module.exports = nodeUtil; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(59)(module))) + +/***/ }), +/* 199 */ +/***/ (function(module, exports, __webpack_require__) { + + var isPrototype = __webpack_require__(200), + nativeKeys = __webpack_require__(201); + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * The base implementation of `_.keys` which doesn't treat sparse arrays as dense. + * + * @private + * @param {Object} object The object to query. + * @returns {Array} Returns the array of property names. + */ + function baseKeys(object) { + if (!isPrototype(object)) { + return nativeKeys(object); + } + var result = []; + for (var key in Object(object)) { + if (hasOwnProperty.call(object, key) && key != 'constructor') { + result.push(key); + } + } + return result; + } + + module.exports = baseKeys; + + +/***/ }), +/* 200 */ +/***/ (function(module, exports) { + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** + * Checks if `value` is likely a prototype object. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a prototype, else `false`. + */ + function isPrototype(value) { + var Ctor = value && value.constructor, + proto = (typeof Ctor == 'function' && Ctor.prototype) || objectProto; + + return value === proto; + } + + module.exports = isPrototype; + + +/***/ }), +/* 201 */ +/***/ (function(module, exports, __webpack_require__) { + + var overArg = __webpack_require__(202); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeKeys = overArg(Object.keys, Object); + + module.exports = nativeKeys; + + +/***/ }), +/* 202 */ +/***/ (function(module, exports) { + + /** + * Creates a unary function that invokes `func` with its argument transformed. + * + * @private + * @param {Function} func The function to wrap. + * @param {Function} transform The argument transform. + * @returns {Function} Returns the new function. + */ + function overArg(func, transform) { + return function(arg) { + return func(transform(arg)); + }; + } + + module.exports = overArg; + + +/***/ }), +/* 203 */ +/***/ (function(module, exports, __webpack_require__) { + + var DataView = __webpack_require__(204), + Map = __webpack_require__(139), + Promise = __webpack_require__(205), + Set = __webpack_require__(206), + WeakMap = __webpack_require__(207), + baseGetTag = __webpack_require__(91), + toSource = __webpack_require__(126); + + /** `Object#toString` result references. */ + var mapTag = '[object Map]', + objectTag = '[object Object]', + promiseTag = '[object Promise]', + setTag = '[object Set]', + weakMapTag = '[object WeakMap]'; + + var dataViewTag = '[object DataView]'; + + /** Used to detect maps, sets, and weakmaps. */ + var dataViewCtorString = toSource(DataView), + mapCtorString = toSource(Map), + promiseCtorString = toSource(Promise), + setCtorString = toSource(Set), + weakMapCtorString = toSource(WeakMap); + + /** + * Gets the `toStringTag` of `value`. + * + * @private + * @param {*} value The value to query. + * @returns {string} Returns the `toStringTag`. + */ + var getTag = baseGetTag; + + // Fallback for data views, maps, sets, and weak maps in IE 11 and promises in Node.js < 6. + if ((DataView && getTag(new DataView(new ArrayBuffer(1))) != dataViewTag) || + (Map && getTag(new Map) != mapTag) || + (Promise && getTag(Promise.resolve()) != promiseTag) || + (Set && getTag(new Set) != setTag) || + (WeakMap && getTag(new WeakMap) != weakMapTag)) { + getTag = function(value) { + var result = baseGetTag(value), + Ctor = result == objectTag ? value.constructor : undefined, + ctorString = Ctor ? toSource(Ctor) : ''; + + if (ctorString) { + switch (ctorString) { + case dataViewCtorString: return dataViewTag; + case mapCtorString: return mapTag; + case promiseCtorString: return promiseTag; + case setCtorString: return setTag; + case weakMapCtorString: return weakMapTag; + } + } + return result; + }; + } + + module.exports = getTag; + + +/***/ }), +/* 204 */ +/***/ (function(module, exports, __webpack_require__) { + + var getNative = __webpack_require__(122), + root = __webpack_require__(93); + + /* Built-in method references that are verified to be native. */ + var DataView = getNative(root, 'DataView'); + + module.exports = DataView; + + +/***/ }), +/* 205 */ +/***/ (function(module, exports, __webpack_require__) { + + var getNative = __webpack_require__(122), + root = __webpack_require__(93); + + /* Built-in method references that are verified to be native. */ + var Promise = getNative(root, 'Promise'); + + module.exports = Promise; + + +/***/ }), +/* 206 */ +/***/ (function(module, exports, __webpack_require__) { + + var getNative = __webpack_require__(122), + root = __webpack_require__(93); + + /* Built-in method references that are verified to be native. */ + var Set = getNative(root, 'Set'); + + module.exports = Set; + + +/***/ }), +/* 207 */ +/***/ (function(module, exports, __webpack_require__) { + + var getNative = __webpack_require__(122), + root = __webpack_require__(93); + + /* Built-in method references that are verified to be native. */ + var WeakMap = getNative(root, 'WeakMap'); + + module.exports = WeakMap; + + +/***/ }), +/* 208 */ +/***/ (function(module, exports, __webpack_require__) { + + var isStrictComparable = __webpack_require__(209), + keys = __webpack_require__(191); + + /** + * Gets the property names, values, and compare flags of `object`. + * + * @private + * @param {Object} object The object to query. + * @returns {Array} Returns the match data of `object`. + */ + function getMatchData(object) { + var result = keys(object), + length = result.length; + + while (length--) { + var key = result[length], + value = object[key]; + + result[length] = [key, value, isStrictComparable(value)]; + } + return result; + } + + module.exports = getMatchData; + + +/***/ }), +/* 209 */ +/***/ (function(module, exports, __webpack_require__) { + + var isObject = __webpack_require__(97); + + /** + * Checks if `value` is suitable for strict equality comparisons, i.e. `===`. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` if suitable for strict + * equality comparisons, else `false`. + */ + function isStrictComparable(value) { + return value === value && !isObject(value); + } + + module.exports = isStrictComparable; + + +/***/ }), +/* 210 */ +/***/ (function(module, exports) { + + /** + * A specialized version of `matchesProperty` for source values suitable + * for strict equality comparisons, i.e. `===`. + * + * @private + * @param {string} key The key of the property to get. + * @param {*} srcValue The value to match. + * @returns {Function} Returns the new spec function. + */ + function matchesStrictComparable(key, srcValue) { + return function(object) { + if (object == null) { + return false; + } + return object[key] === srcValue && + (srcValue !== undefined || (key in Object(object))); + }; + } + + module.exports = matchesStrictComparable; + + +/***/ }), +/* 211 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIsEqual = __webpack_require__(177), + get = __webpack_require__(212), + hasIn = __webpack_require__(222), + isKey = __webpack_require__(215), + isStrictComparable = __webpack_require__(209), + matchesStrictComparable = __webpack_require__(210), + toKey = __webpack_require__(221); + + /** Used to compose bitmasks for value comparisons. */ + var COMPARE_PARTIAL_FLAG = 1, + COMPARE_UNORDERED_FLAG = 2; + + /** + * The base implementation of `_.matchesProperty` which doesn't clone `srcValue`. + * + * @private + * @param {string} path The path of the property to get. + * @param {*} srcValue The value to match. + * @returns {Function} Returns the new spec function. + */ + function baseMatchesProperty(path, srcValue) { + if (isKey(path) && isStrictComparable(srcValue)) { + return matchesStrictComparable(toKey(path), srcValue); + } + return function(object) { + var objValue = get(object, path); + return (objValue === undefined && objValue === srcValue) + ? hasIn(object, path) + : baseIsEqual(srcValue, objValue, COMPARE_PARTIAL_FLAG | COMPARE_UNORDERED_FLAG); + }; + } + + module.exports = baseMatchesProperty; + + +/***/ }), +/* 212 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseGet = __webpack_require__(213); + + /** + * Gets the value at `path` of `object`. If the resolved value is + * `undefined`, the `defaultValue` is returned in its place. + * + * @static + * @memberOf _ + * @since 3.7.0 + * @category Object + * @param {Object} object The object to query. + * @param {Array|string} path The path of the property to get. + * @param {*} [defaultValue] The value returned for `undefined` resolved values. + * @returns {*} Returns the resolved value. + * @example + * + * var object = { 'a': [{ 'b': { 'c': 3 } }] }; + * + * _.get(object, 'a[0].b.c'); + * // => 3 + * + * _.get(object, ['a', '0', 'b', 'c']); + * // => 3 + * + * _.get(object, 'a.b.c', 'default'); + * // => 'default' + */ + function get(object, path, defaultValue) { + var result = object == null ? undefined : baseGet(object, path); + return result === undefined ? defaultValue : result; + } + + module.exports = get; + + +/***/ }), +/* 213 */ +/***/ (function(module, exports, __webpack_require__) { + + var castPath = __webpack_require__(214), + toKey = __webpack_require__(221); + + /** + * The base implementation of `_.get` without support for default values. + * + * @private + * @param {Object} object The object to query. + * @param {Array|string} path The path of the property to get. + * @returns {*} Returns the resolved value. + */ + function baseGet(object, path) { + path = castPath(path, object); + + var index = 0, + length = path.length; + + while (object != null && index < length) { + object = object[toKey(path[index++])]; + } + return (index && index == length) ? object : undefined; + } + + module.exports = baseGet; + + +/***/ }), +/* 214 */ +/***/ (function(module, exports, __webpack_require__) { + + var isArray = __webpack_require__(112), + isKey = __webpack_require__(215), + stringToPath = __webpack_require__(216), + toString = __webpack_require__(219); + + /** + * Casts `value` to a path array if it's not one. + * + * @private + * @param {*} value The value to inspect. + * @param {Object} [object] The object to query keys on. + * @returns {Array} Returns the cast property path array. + */ + function castPath(value, object) { + if (isArray(value)) { + return value; + } + return isKey(value, object) ? [value] : stringToPath(toString(value)); + } + + module.exports = castPath; + + +/***/ }), +/* 215 */ +/***/ (function(module, exports, __webpack_require__) { + + var isArray = __webpack_require__(112), + isSymbol = __webpack_require__(103); + + /** Used to match property names within property paths. */ + var reIsDeepProp = /\.|\[(?:[^[\]]*|(["'])(?:(?!\1)[^\\]|\\.)*?\1)\]/, + reIsPlainProp = /^\w*$/; + + /** + * Checks if `value` is a property name and not a property path. + * + * @private + * @param {*} value The value to check. + * @param {Object} [object] The object to query keys on. + * @returns {boolean} Returns `true` if `value` is a property name, else `false`. + */ + function isKey(value, object) { + if (isArray(value)) { + return false; + } + var type = typeof value; + if (type == 'number' || type == 'symbol' || type == 'boolean' || + value == null || isSymbol(value)) { + return true; + } + return reIsPlainProp.test(value) || !reIsDeepProp.test(value) || + (object != null && value in Object(object)); + } + + module.exports = isKey; + + +/***/ }), +/* 216 */ +/***/ (function(module, exports, __webpack_require__) { + + var memoizeCapped = __webpack_require__(217); + + /** Used to match property names within property paths. */ + var rePropName = /[^.[\]]+|\[(?:(-?\d+(?:\.\d+)?)|(["'])((?:(?!\2)[^\\]|\\.)*?)\2)\]|(?=(?:\.|\[\])(?:\.|\[\]|$))/g; + + /** Used to match backslashes in property paths. */ + var reEscapeChar = /\\(\\)?/g; + + /** + * Converts `string` to a property path array. + * + * @private + * @param {string} string The string to convert. + * @returns {Array} Returns the property path array. + */ + var stringToPath = memoizeCapped(function(string) { + var result = []; + if (string.charCodeAt(0) === 46 /* . */) { + result.push(''); + } + string.replace(rePropName, function(match, number, quote, subString) { + result.push(quote ? subString.replace(reEscapeChar, '$1') : (number || match)); + }); + return result; + }); + + module.exports = stringToPath; + + +/***/ }), +/* 217 */ +/***/ (function(module, exports, __webpack_require__) { + + var memoize = __webpack_require__(218); + + /** Used as the maximum memoize cache size. */ + var MAX_MEMOIZE_SIZE = 500; + + /** + * A specialized version of `_.memoize` which clears the memoized function's + * cache when it exceeds `MAX_MEMOIZE_SIZE`. + * + * @private + * @param {Function} func The function to have its output memoized. + * @returns {Function} Returns the new memoized function. + */ + function memoizeCapped(func) { + var result = memoize(func, function(key) { + if (cache.size === MAX_MEMOIZE_SIZE) { + cache.clear(); + } + return key; + }); + + var cache = result.cache; + return result; + } + + module.exports = memoizeCapped; + + +/***/ }), +/* 218 */ +/***/ (function(module, exports, __webpack_require__) { + + var MapCache = __webpack_require__(117); + + /** Error message constants. */ + var FUNC_ERROR_TEXT = 'Expected a function'; + + /** + * Creates a function that memoizes the result of `func`. If `resolver` is + * provided, it determines the cache key for storing the result based on the + * arguments provided to the memoized function. By default, the first argument + * provided to the memoized function is used as the map cache key. The `func` + * is invoked with the `this` binding of the memoized function. + * + * **Note:** The cache is exposed as the `cache` property on the memoized + * function. Its creation may be customized by replacing the `_.memoize.Cache` + * constructor with one whose instances implement the + * [`Map`](http://ecma-international.org/ecma-262/7.0/#sec-properties-of-the-map-prototype-object) + * method interface of `clear`, `delete`, `get`, `has`, and `set`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Function + * @param {Function} func The function to have its output memoized. + * @param {Function} [resolver] The function to resolve the cache key. + * @returns {Function} Returns the new memoized function. + * @example + * + * var object = { 'a': 1, 'b': 2 }; + * var other = { 'c': 3, 'd': 4 }; + * + * var values = _.memoize(_.values); + * values(object); + * // => [1, 2] + * + * values(other); + * // => [3, 4] + * + * object.a = 2; + * values(object); + * // => [1, 2] + * + * // Modify the result cache. + * values.cache.set(object, ['a', 'b']); + * values(object); + * // => ['a', 'b'] + * + * // Replace `_.memoize.Cache`. + * _.memoize.Cache = WeakMap; + */ + function memoize(func, resolver) { + if (typeof func != 'function' || (resolver != null && typeof resolver != 'function')) { + throw new TypeError(FUNC_ERROR_TEXT); + } + var memoized = function() { + var args = arguments, + key = resolver ? resolver.apply(this, args) : args[0], + cache = memoized.cache; + + if (cache.has(key)) { + return cache.get(key); + } + var result = func.apply(this, args); + memoized.cache = cache.set(key, result) || cache; + return result; + }; + memoized.cache = new (memoize.Cache || MapCache); + return memoized; + } + + // Expose `MapCache`. + memoize.Cache = MapCache; + + module.exports = memoize; + + +/***/ }), +/* 219 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseToString = __webpack_require__(220); + + /** + * Converts `value` to a string. An empty string is returned for `null` + * and `undefined` values. The sign of `-0` is preserved. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to convert. + * @returns {string} Returns the converted string. + * @example + * + * _.toString(null); + * // => '' + * + * _.toString(-0); + * // => '-0' + * + * _.toString([1, 2, 3]); + * // => '1,2,3' + */ + function toString(value) { + return value == null ? '' : baseToString(value); + } + + module.exports = toString; + + +/***/ }), +/* 220 */ +/***/ (function(module, exports, __webpack_require__) { + + var Symbol = __webpack_require__(92), + arrayMap = __webpack_require__(154), + isArray = __webpack_require__(112), + isSymbol = __webpack_require__(103); + + /** Used as references for various `Number` constants. */ + var INFINITY = 1 / 0; + + /** Used to convert symbols to primitives and strings. */ + var symbolProto = Symbol ? Symbol.prototype : undefined, + symbolToString = symbolProto ? symbolProto.toString : undefined; + + /** + * The base implementation of `_.toString` which doesn't convert nullish + * values to empty strings. + * + * @private + * @param {*} value The value to process. + * @returns {string} Returns the string. + */ + function baseToString(value) { + // Exit early for strings to avoid a performance hit in some environments. + if (typeof value == 'string') { + return value; + } + if (isArray(value)) { + // Recursively convert values (susceptible to call stack limits). + return arrayMap(value, baseToString) + ''; + } + if (isSymbol(value)) { + return symbolToString ? symbolToString.call(value) : ''; + } + var result = (value + ''); + return (result == '0' && (1 / value) == -INFINITY) ? '-0' : result; + } + + module.exports = baseToString; + + +/***/ }), +/* 221 */ +/***/ (function(module, exports, __webpack_require__) { + + var isSymbol = __webpack_require__(103); + + /** Used as references for various `Number` constants. */ + var INFINITY = 1 / 0; + + /** + * Converts `value` to a string key if it's not a string or symbol. + * + * @private + * @param {*} value The value to inspect. + * @returns {string|symbol} Returns the key. + */ + function toKey(value) { + if (typeof value == 'string' || isSymbol(value)) { + return value; + } + var result = (value + ''); + return (result == '0' && (1 / value) == -INFINITY) ? '-0' : result; + } + + module.exports = toKey; + + +/***/ }), +/* 222 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseHasIn = __webpack_require__(223), + hasPath = __webpack_require__(224); + + /** + * Checks if `path` is a direct or inherited property of `object`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Object + * @param {Object} object The object to query. + * @param {Array|string} path The path to check. + * @returns {boolean} Returns `true` if `path` exists, else `false`. + * @example + * + * var object = _.create({ 'a': _.create({ 'b': 2 }) }); + * + * _.hasIn(object, 'a'); + * // => true + * + * _.hasIn(object, 'a.b'); + * // => true + * + * _.hasIn(object, ['a', 'b']); + * // => true + * + * _.hasIn(object, 'b'); + * // => false + */ + function hasIn(object, path) { + return object != null && hasPath(object, path, baseHasIn); + } + + module.exports = hasIn; + + +/***/ }), +/* 223 */ +/***/ (function(module, exports) { + + /** + * The base implementation of `_.hasIn` without support for deep paths. + * + * @private + * @param {Object} [object] The object to query. + * @param {Array|string} key The key to check. + * @returns {boolean} Returns `true` if `key` exists, else `false`. + */ + function baseHasIn(object, key) { + return object != null && key in Object(object); + } + + module.exports = baseHasIn; + + +/***/ }), +/* 224 */ +/***/ (function(module, exports, __webpack_require__) { + + var castPath = __webpack_require__(214), + isArguments = __webpack_require__(110), + isArray = __webpack_require__(112), + isIndex = __webpack_require__(99), + isLength = __webpack_require__(98), + toKey = __webpack_require__(221); + + /** + * Checks if `path` exists on `object`. + * + * @private + * @param {Object} object The object to query. + * @param {Array|string} path The path to check. + * @param {Function} hasFunc The function to check properties. + * @returns {boolean} Returns `true` if `path` exists, else `false`. + */ + function hasPath(object, path, hasFunc) { + path = castPath(path, object); + + var index = -1, + length = path.length, + result = false; + + while (++index < length) { + var key = toKey(path[index]); + if (!(result = object != null && hasFunc(object, key))) { + break; + } + object = object[key]; + } + if (result || ++index != length) { + return result; + } + length = object == null ? 0 : object.length; + return !!length && isLength(length) && isIndex(key, length) && + (isArray(object) || isArguments(object)); + } + + module.exports = hasPath; + + +/***/ }), +/* 225 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseProperty = __webpack_require__(226), + basePropertyDeep = __webpack_require__(227), + isKey = __webpack_require__(215), + toKey = __webpack_require__(221); + + /** + * Creates a function that returns the value at `path` of a given object. + * + * @static + * @memberOf _ + * @since 2.4.0 + * @category Util + * @param {Array|string} path The path of the property to get. + * @returns {Function} Returns the new accessor function. + * @example + * + * var objects = [ + * { 'a': { 'b': 2 } }, + * { 'a': { 'b': 1 } } + * ]; + * + * _.map(objects, _.property('a.b')); + * // => [2, 1] + * + * _.map(_.sortBy(objects, _.property(['a', 'b'])), 'a.b'); + * // => [1, 2] + */ + function property(path) { + return isKey(path) ? baseProperty(toKey(path)) : basePropertyDeep(path); + } + + module.exports = property; + + +/***/ }), +/* 226 */ +/***/ (function(module, exports) { + + /** + * The base implementation of `_.property` without support for deep paths. + * + * @private + * @param {string} key The key of the property to get. + * @returns {Function} Returns the new accessor function. + */ + function baseProperty(key) { + return function(object) { + return object == null ? undefined : object[key]; + }; + } + + module.exports = baseProperty; + + +/***/ }), +/* 227 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseGet = __webpack_require__(213); + + /** + * A specialized version of `baseProperty` which supports deep paths. + * + * @private + * @param {Array|string} path The path of the property to get. + * @returns {Function} Returns the new accessor function. + */ + function basePropertyDeep(path) { + return function(object) { + return baseGet(object, path); + }; + } + + module.exports = basePropertyDeep; + + +/***/ }), +/* 228 */ +/***/ (function(module, exports) { + + /** + * Gets the last element of `array`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to query. + * @returns {*} Returns the last element of `array`. + * @example + * + * _.last([1, 2, 3]); + * // => 3 + */ + function last(array) { + var length = array == null ? 0 : array.length; + return length ? array[length - 1] : undefined; + } + + module.exports = last; + + +/***/ }), +/* 229 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseDifference = __webpack_require__(115), + baseFlatten = __webpack_require__(108), + baseRest = __webpack_require__(157), + isArrayLikeObject = __webpack_require__(166), + last = __webpack_require__(228); + + /** + * This method is like `_.difference` except that it accepts `comparator` + * which is invoked to compare elements of `array` to `values`. The order and + * references of result values are determined by the first array. The comparator + * is invoked with two arguments: (arrVal, othVal). + * + * **Note:** Unlike `_.pullAllWith`, this method returns a new array. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {...Array} [values] The values to exclude. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new array of filtered values. + * @example + * + * var objects = [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }]; + * + * _.differenceWith(objects, [{ 'x': 1, 'y': 2 }], _.isEqual); + * // => [{ 'x': 2, 'y': 1 }] + */ + var differenceWith = baseRest(function(array, values) { + var comparator = last(values); + if (isArrayLikeObject(comparator)) { + comparator = undefined; + } + return isArrayLikeObject(array) + ? baseDifference(array, baseFlatten(values, 1, isArrayLikeObject, true), undefined, comparator) + : []; + }); + + module.exports = differenceWith; + + +/***/ }), +/* 230 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86), + toInteger = __webpack_require__(100); + + /** + * Creates a slice of `array` with `n` elements dropped from the beginning. + * + * @static + * @memberOf _ + * @since 0.5.0 + * @category Array + * @param {Array} array The array to query. + * @param {number} [n=1] The number of elements to drop. + * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. + * @returns {Array} Returns the slice of `array`. + * @example + * + * _.drop([1, 2, 3]); + * // => [2, 3] + * + * _.drop([1, 2, 3], 2); + * // => [3] + * + * _.drop([1, 2, 3], 5); + * // => [] + * + * _.drop([1, 2, 3], 0); + * // => [1, 2, 3] + */ + function drop(array, n, guard) { + var length = array == null ? 0 : array.length; + if (!length) { + return []; + } + n = (guard || n === undefined) ? 1 : toInteger(n); + return baseSlice(array, n < 0 ? 0 : n, length); + } + + module.exports = drop; + + +/***/ }), +/* 231 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86), + toInteger = __webpack_require__(100); + + /** + * Creates a slice of `array` with `n` elements dropped from the end. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to query. + * @param {number} [n=1] The number of elements to drop. + * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. + * @returns {Array} Returns the slice of `array`. + * @example + * + * _.dropRight([1, 2, 3]); + * // => [1, 2] + * + * _.dropRight([1, 2, 3], 2); + * // => [1] + * + * _.dropRight([1, 2, 3], 5); + * // => [] + * + * _.dropRight([1, 2, 3], 0); + * // => [1, 2, 3] + */ + function dropRight(array, n, guard) { + var length = array == null ? 0 : array.length; + if (!length) { + return []; + } + n = (guard || n === undefined) ? 1 : toInteger(n); + n = length - n; + return baseSlice(array, 0, n < 0 ? 0 : n); + } + + module.exports = dropRight; + + +/***/ }), +/* 232 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + baseWhile = __webpack_require__(233); + + /** + * Creates a slice of `array` excluding elements dropped from the end. + * Elements are dropped until `predicate` returns falsey. The predicate is + * invoked with three arguments: (value, index, array). + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to query. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @returns {Array} Returns the slice of `array`. + * @example + * + * var users = [ + * { 'user': 'barney', 'active': true }, + * { 'user': 'fred', 'active': false }, + * { 'user': 'pebbles', 'active': false } + * ]; + * + * _.dropRightWhile(users, function(o) { return !o.active; }); + * // => objects for ['barney'] + * + * // The `_.matches` iteratee shorthand. + * _.dropRightWhile(users, { 'user': 'pebbles', 'active': false }); + * // => objects for ['barney', 'fred'] + * + * // The `_.matchesProperty` iteratee shorthand. + * _.dropRightWhile(users, ['active', false]); + * // => objects for ['barney'] + * + * // The `_.property` iteratee shorthand. + * _.dropRightWhile(users, 'active'); + * // => objects for ['barney', 'fred', 'pebbles'] + */ + function dropRightWhile(array, predicate) { + return (array && array.length) + ? baseWhile(array, baseIteratee(predicate, 3), true, true) + : []; + } + + module.exports = dropRightWhile; + + +/***/ }), +/* 233 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86); + + /** + * The base implementation of methods like `_.dropWhile` and `_.takeWhile` + * without support for iteratee shorthands. + * + * @private + * @param {Array} array The array to query. + * @param {Function} predicate The function invoked per iteration. + * @param {boolean} [isDrop] Specify dropping elements instead of taking them. + * @param {boolean} [fromRight] Specify iterating from right to left. + * @returns {Array} Returns the slice of `array`. + */ + function baseWhile(array, predicate, isDrop, fromRight) { + var length = array.length, + index = fromRight ? length : -1; + + while ((fromRight ? index-- : ++index < length) && + predicate(array[index], index, array)) {} + + return isDrop + ? baseSlice(array, (fromRight ? 0 : index), (fromRight ? index + 1 : length)) + : baseSlice(array, (fromRight ? index + 1 : 0), (fromRight ? length : index)); + } + + module.exports = baseWhile; + + +/***/ }), +/* 234 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + baseWhile = __webpack_require__(233); + + /** + * Creates a slice of `array` excluding elements dropped from the beginning. + * Elements are dropped until `predicate` returns falsey. The predicate is + * invoked with three arguments: (value, index, array). + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to query. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @returns {Array} Returns the slice of `array`. + * @example + * + * var users = [ + * { 'user': 'barney', 'active': false }, + * { 'user': 'fred', 'active': false }, + * { 'user': 'pebbles', 'active': true } + * ]; + * + * _.dropWhile(users, function(o) { return !o.active; }); + * // => objects for ['pebbles'] + * + * // The `_.matches` iteratee shorthand. + * _.dropWhile(users, { 'user': 'barney', 'active': false }); + * // => objects for ['fred', 'pebbles'] + * + * // The `_.matchesProperty` iteratee shorthand. + * _.dropWhile(users, ['active', false]); + * // => objects for ['pebbles'] + * + * // The `_.property` iteratee shorthand. + * _.dropWhile(users, 'active'); + * // => objects for ['barney', 'fred', 'pebbles'] + */ + function dropWhile(array, predicate) { + return (array && array.length) + ? baseWhile(array, baseIteratee(predicate, 3), true) + : []; + } + + module.exports = dropWhile; + + +/***/ }), +/* 235 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFill = __webpack_require__(236), + isIterateeCall = __webpack_require__(87); + + /** + * Fills elements of `array` with `value` from `start` up to, but not + * including, `end`. + * + * **Note:** This method mutates `array`. + * + * @static + * @memberOf _ + * @since 3.2.0 + * @category Array + * @param {Array} array The array to fill. + * @param {*} value The value to fill `array` with. + * @param {number} [start=0] The start position. + * @param {number} [end=array.length] The end position. + * @returns {Array} Returns `array`. + * @example + * + * var array = [1, 2, 3]; + * + * _.fill(array, 'a'); + * console.log(array); + * // => ['a', 'a', 'a'] + * + * _.fill(Array(3), 2); + * // => [2, 2, 2] + * + * _.fill([4, 6, 8, 10], '*', 1, 3); + * // => [4, '*', '*', 10] + */ + function fill(array, value, start, end) { + var length = array == null ? 0 : array.length; + if (!length) { + return []; + } + if (start && typeof start != 'number' && isIterateeCall(array, value, start)) { + start = 0; + end = length; + } + return baseFill(array, value, start, end); + } + + module.exports = fill; + + +/***/ }), +/* 236 */ +/***/ (function(module, exports, __webpack_require__) { + + var toInteger = __webpack_require__(100), + toLength = __webpack_require__(237); + + /** + * The base implementation of `_.fill` without an iteratee call guard. + * + * @private + * @param {Array} array The array to fill. + * @param {*} value The value to fill `array` with. + * @param {number} [start=0] The start position. + * @param {number} [end=array.length] The end position. + * @returns {Array} Returns `array`. + */ + function baseFill(array, value, start, end) { + var length = array.length; + + start = toInteger(start); + if (start < 0) { + start = -start > length ? 0 : (length + start); + } + end = (end === undefined || end > length) ? length : toInteger(end); + if (end < 0) { + end += length; + } + end = start > end ? 0 : toLength(end); + while (start < end) { + array[start++] = value; + } + return array; + } + + module.exports = baseFill; + + +/***/ }), +/* 237 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseClamp = __webpack_require__(238), + toInteger = __webpack_require__(100); + + /** Used as references for the maximum length and index of an array. */ + var MAX_ARRAY_LENGTH = 4294967295; + + /** + * Converts `value` to an integer suitable for use as the length of an + * array-like object. + * + * **Note:** This method is based on + * [`ToLength`](http://ecma-international.org/ecma-262/7.0/#sec-tolength). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to convert. + * @returns {number} Returns the converted integer. + * @example + * + * _.toLength(3.2); + * // => 3 + * + * _.toLength(Number.MIN_VALUE); + * // => 0 + * + * _.toLength(Infinity); + * // => 4294967295 + * + * _.toLength('3.2'); + * // => 3 + */ + function toLength(value) { + return value ? baseClamp(toInteger(value), 0, MAX_ARRAY_LENGTH) : 0; + } + + module.exports = toLength; + + +/***/ }), +/* 238 */ +/***/ (function(module, exports) { + + /** + * The base implementation of `_.clamp` which doesn't coerce arguments. + * + * @private + * @param {number} number The number to clamp. + * @param {number} [lower] The lower bound. + * @param {number} upper The upper bound. + * @returns {number} Returns the clamped number. + */ + function baseClamp(number, lower, upper) { + if (number === number) { + if (upper !== undefined) { + number = number <= upper ? number : upper; + } + if (lower !== undefined) { + number = number >= lower ? number : lower; + } + } + return number; + } + + module.exports = baseClamp; + + +/***/ }), +/* 239 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFindIndex = __webpack_require__(150), + baseIteratee = __webpack_require__(168), + toInteger = __webpack_require__(100); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeMax = Math.max; + + /** + * This method is like `_.find` except that it returns the index of the first + * element `predicate` returns truthy for instead of the element itself. + * + * @static + * @memberOf _ + * @since 1.1.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @param {number} [fromIndex=0] The index to search from. + * @returns {number} Returns the index of the found element, else `-1`. + * @example + * + * var users = [ + * { 'user': 'barney', 'active': false }, + * { 'user': 'fred', 'active': false }, + * { 'user': 'pebbles', 'active': true } + * ]; + * + * _.findIndex(users, function(o) { return o.user == 'barney'; }); + * // => 0 + * + * // The `_.matches` iteratee shorthand. + * _.findIndex(users, { 'user': 'fred', 'active': false }); + * // => 1 + * + * // The `_.matchesProperty` iteratee shorthand. + * _.findIndex(users, ['active', false]); + * // => 0 + * + * // The `_.property` iteratee shorthand. + * _.findIndex(users, 'active'); + * // => 2 + */ + function findIndex(array, predicate, fromIndex) { + var length = array == null ? 0 : array.length; + if (!length) { + return -1; + } + var index = fromIndex == null ? 0 : toInteger(fromIndex); + if (index < 0) { + index = nativeMax(length + index, 0); + } + return baseFindIndex(array, baseIteratee(predicate, 3), index); + } + + module.exports = findIndex; + + +/***/ }), +/* 240 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFindIndex = __webpack_require__(150), + baseIteratee = __webpack_require__(168), + toInteger = __webpack_require__(100); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeMax = Math.max, + nativeMin = Math.min; + + /** + * This method is like `_.findIndex` except that it iterates over elements + * of `collection` from right to left. + * + * @static + * @memberOf _ + * @since 2.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @param {number} [fromIndex=array.length-1] The index to search from. + * @returns {number} Returns the index of the found element, else `-1`. + * @example + * + * var users = [ + * { 'user': 'barney', 'active': true }, + * { 'user': 'fred', 'active': false }, + * { 'user': 'pebbles', 'active': false } + * ]; + * + * _.findLastIndex(users, function(o) { return o.user == 'pebbles'; }); + * // => 2 + * + * // The `_.matches` iteratee shorthand. + * _.findLastIndex(users, { 'user': 'barney', 'active': true }); + * // => 0 + * + * // The `_.matchesProperty` iteratee shorthand. + * _.findLastIndex(users, ['active', false]); + * // => 2 + * + * // The `_.property` iteratee shorthand. + * _.findLastIndex(users, 'active'); + * // => 0 + */ + function findLastIndex(array, predicate, fromIndex) { + var length = array == null ? 0 : array.length; + if (!length) { + return -1; + } + var index = length - 1; + if (fromIndex !== undefined) { + index = toInteger(fromIndex); + index = fromIndex < 0 + ? nativeMax(length + index, 0) + : nativeMin(index, length - 1); + } + return baseFindIndex(array, baseIteratee(predicate, 3), index, true); + } + + module.exports = findLastIndex; + + +/***/ }), +/* 241 */ +/***/ (function(module, exports, __webpack_require__) { + + module.exports = __webpack_require__(242); + + +/***/ }), +/* 242 */ +/***/ (function(module, exports) { + + /** + * Gets the first element of `array`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @alias first + * @category Array + * @param {Array} array The array to query. + * @returns {*} Returns the first element of `array`. + * @example + * + * _.head([1, 2, 3]); + * // => 1 + * + * _.head([]); + * // => undefined + */ + function head(array) { + return (array && array.length) ? array[0] : undefined; + } + + module.exports = head; + + +/***/ }), +/* 243 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFlatten = __webpack_require__(108); + + /** + * Flattens `array` a single level deep. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to flatten. + * @returns {Array} Returns the new flattened array. + * @example + * + * _.flatten([1, [2, [3, [4]], 5]]); + * // => [1, 2, [3, [4]], 5] + */ + function flatten(array) { + var length = array == null ? 0 : array.length; + return length ? baseFlatten(array, 1) : []; + } + + module.exports = flatten; + + +/***/ }), +/* 244 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFlatten = __webpack_require__(108); + + /** Used as references for various `Number` constants. */ + var INFINITY = 1 / 0; + + /** + * Recursively flattens `array`. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to flatten. + * @returns {Array} Returns the new flattened array. + * @example + * + * _.flattenDeep([1, [2, [3, [4]], 5]]); + * // => [1, 2, 3, 4, 5] + */ + function flattenDeep(array) { + var length = array == null ? 0 : array.length; + return length ? baseFlatten(array, INFINITY) : []; + } + + module.exports = flattenDeep; + + +/***/ }), +/* 245 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFlatten = __webpack_require__(108), + toInteger = __webpack_require__(100); + + /** + * Recursively flatten `array` up to `depth` times. + * + * @static + * @memberOf _ + * @since 4.4.0 + * @category Array + * @param {Array} array The array to flatten. + * @param {number} [depth=1] The maximum recursion depth. + * @returns {Array} Returns the new flattened array. + * @example + * + * var array = [1, [2, [3, [4]], 5]]; + * + * _.flattenDepth(array, 1); + * // => [1, 2, [3, [4]], 5] + * + * _.flattenDepth(array, 2); + * // => [1, 2, 3, [4], 5] + */ + function flattenDepth(array, depth) { + var length = array == null ? 0 : array.length; + if (!length) { + return []; + } + depth = depth === undefined ? 1 : toInteger(depth); + return baseFlatten(array, depth); + } + + module.exports = flattenDepth; + + +/***/ }), +/* 246 */ +/***/ (function(module, exports) { + + /** + * The inverse of `_.toPairs`; this method returns an object composed + * from key-value `pairs`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} pairs The key-value pairs. + * @returns {Object} Returns the new object. + * @example + * + * _.fromPairs([['a', 1], ['b', 2]]); + * // => { 'a': 1, 'b': 2 } + */ + function fromPairs(pairs) { + var index = -1, + length = pairs == null ? 0 : pairs.length, + result = {}; + + while (++index < length) { + var pair = pairs[index]; + result[pair[0]] = pair[1]; + } + return result; + } + + module.exports = fromPairs; + + +/***/ }), +/* 247 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIndexOf = __webpack_require__(149), + toInteger = __webpack_require__(100); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeMax = Math.max; + + /** + * Gets the index at which the first occurrence of `value` is found in `array` + * using [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. If `fromIndex` is negative, it's used as the + * offset from the end of `array`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @param {number} [fromIndex=0] The index to search from. + * @returns {number} Returns the index of the matched value, else `-1`. + * @example + * + * _.indexOf([1, 2, 1, 2], 2); + * // => 1 + * + * // Search from the `fromIndex`. + * _.indexOf([1, 2, 1, 2], 2, 2); + * // => 3 + */ + function indexOf(array, value, fromIndex) { + var length = array == null ? 0 : array.length; + if (!length) { + return -1; + } + var index = fromIndex == null ? 0 : toInteger(fromIndex); + if (index < 0) { + index = nativeMax(length + index, 0); + } + return baseIndexOf(array, value, index); + } + + module.exports = indexOf; + + +/***/ }), +/* 248 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86); + + /** + * Gets all but the last element of `array`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to query. + * @returns {Array} Returns the slice of `array`. + * @example + * + * _.initial([1, 2, 3]); + * // => [1, 2] + */ + function initial(array) { + var length = array == null ? 0 : array.length; + return length ? baseSlice(array, 0, -1) : []; + } + + module.exports = initial; + + +/***/ }), +/* 249 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayMap = __webpack_require__(154), + baseIntersection = __webpack_require__(250), + baseRest = __webpack_require__(157), + castArrayLikeObject = __webpack_require__(251); + + /** + * Creates an array of unique values that are included in all given arrays + * using [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. The order and references of result values are + * determined by the first array. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @returns {Array} Returns the new array of intersecting values. + * @example + * + * _.intersection([2, 1], [2, 3]); + * // => [2] + */ + var intersection = baseRest(function(arrays) { + var mapped = arrayMap(arrays, castArrayLikeObject); + return (mapped.length && mapped[0] === arrays[0]) + ? baseIntersection(mapped) + : []; + }); + + module.exports = intersection; + + +/***/ }), +/* 250 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetCache = __webpack_require__(116), + arrayIncludes = __webpack_require__(148), + arrayIncludesWith = __webpack_require__(153), + arrayMap = __webpack_require__(154), + baseUnary = __webpack_require__(155), + cacheHas = __webpack_require__(156); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeMin = Math.min; + + /** + * The base implementation of methods like `_.intersection`, without support + * for iteratee shorthands, that accepts an array of arrays to inspect. + * + * @private + * @param {Array} arrays The arrays to inspect. + * @param {Function} [iteratee] The iteratee invoked per element. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new array of shared values. + */ + function baseIntersection(arrays, iteratee, comparator) { + var includes = comparator ? arrayIncludesWith : arrayIncludes, + length = arrays[0].length, + othLength = arrays.length, + othIndex = othLength, + caches = Array(othLength), + maxLength = Infinity, + result = []; + + while (othIndex--) { + var array = arrays[othIndex]; + if (othIndex && iteratee) { + array = arrayMap(array, baseUnary(iteratee)); + } + maxLength = nativeMin(array.length, maxLength); + caches[othIndex] = !comparator && (iteratee || (length >= 120 && array.length >= 120)) + ? new SetCache(othIndex && array) + : undefined; + } + array = arrays[0]; + + var index = -1, + seen = caches[0]; + + outer: + while (++index < length && result.length < maxLength) { + var value = array[index], + computed = iteratee ? iteratee(value) : value; + + value = (comparator || value !== 0) ? value : 0; + if (!(seen + ? cacheHas(seen, computed) + : includes(result, computed, comparator) + )) { + othIndex = othLength; + while (--othIndex) { + var cache = caches[othIndex]; + if (!(cache + ? cacheHas(cache, computed) + : includes(arrays[othIndex], computed, comparator)) + ) { + continue outer; + } + } + if (seen) { + seen.push(computed); + } + result.push(value); + } + } + return result; + } + + module.exports = baseIntersection; + + +/***/ }), +/* 251 */ +/***/ (function(module, exports, __webpack_require__) { + + var isArrayLikeObject = __webpack_require__(166); + + /** + * Casts `value` to an empty array if it's not an array like object. + * + * @private + * @param {*} value The value to inspect. + * @returns {Array|Object} Returns the cast array-like object. + */ + function castArrayLikeObject(value) { + return isArrayLikeObject(value) ? value : []; + } + + module.exports = castArrayLikeObject; + + +/***/ }), +/* 252 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayMap = __webpack_require__(154), + baseIntersection = __webpack_require__(250), + baseIteratee = __webpack_require__(168), + baseRest = __webpack_require__(157), + castArrayLikeObject = __webpack_require__(251), + last = __webpack_require__(228); + + /** + * This method is like `_.intersection` except that it accepts `iteratee` + * which is invoked for each element of each `arrays` to generate the criterion + * by which they're compared. The order and references of result values are + * determined by the first array. The iteratee is invoked with one argument: + * (value). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @param {Function} [iteratee=_.identity] The iteratee invoked per element. + * @returns {Array} Returns the new array of intersecting values. + * @example + * + * _.intersectionBy([2.1, 1.2], [2.3, 3.4], Math.floor); + * // => [2.1] + * + * // The `_.property` iteratee shorthand. + * _.intersectionBy([{ 'x': 1 }], [{ 'x': 2 }, { 'x': 1 }], 'x'); + * // => [{ 'x': 1 }] + */ + var intersectionBy = baseRest(function(arrays) { + var iteratee = last(arrays), + mapped = arrayMap(arrays, castArrayLikeObject); + + if (iteratee === last(mapped)) { + iteratee = undefined; + } else { + mapped.pop(); + } + return (mapped.length && mapped[0] === arrays[0]) + ? baseIntersection(mapped, baseIteratee(iteratee, 2)) + : []; + }); + + module.exports = intersectionBy; + + +/***/ }), +/* 253 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayMap = __webpack_require__(154), + baseIntersection = __webpack_require__(250), + baseRest = __webpack_require__(157), + castArrayLikeObject = __webpack_require__(251), + last = __webpack_require__(228); + + /** + * This method is like `_.intersection` except that it accepts `comparator` + * which is invoked to compare elements of `arrays`. The order and references + * of result values are determined by the first array. The comparator is + * invoked with two arguments: (arrVal, othVal). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new array of intersecting values. + * @example + * + * var objects = [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }]; + * var others = [{ 'x': 1, 'y': 1 }, { 'x': 1, 'y': 2 }]; + * + * _.intersectionWith(objects, others, _.isEqual); + * // => [{ 'x': 1, 'y': 2 }] + */ + var intersectionWith = baseRest(function(arrays) { + var comparator = last(arrays), + mapped = arrayMap(arrays, castArrayLikeObject); + + comparator = typeof comparator == 'function' ? comparator : undefined; + if (comparator) { + mapped.pop(); + } + return (mapped.length && mapped[0] === arrays[0]) + ? baseIntersection(mapped, undefined, comparator) + : []; + }); + + module.exports = intersectionWith; + + +/***/ }), +/* 254 */ +/***/ (function(module, exports) { + + /** Used for built-in method references. */ + var arrayProto = Array.prototype; + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeJoin = arrayProto.join; + + /** + * Converts all elements in `array` into a string separated by `separator`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to convert. + * @param {string} [separator=','] The element separator. + * @returns {string} Returns the joined string. + * @example + * + * _.join(['a', 'b', 'c'], '~'); + * // => 'a~b~c' + */ + function join(array, separator) { + return array == null ? '' : nativeJoin.call(array, separator); + } + + module.exports = join; + + +/***/ }), +/* 255 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFindIndex = __webpack_require__(150), + baseIsNaN = __webpack_require__(151), + strictLastIndexOf = __webpack_require__(256), + toInteger = __webpack_require__(100); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeMax = Math.max, + nativeMin = Math.min; + + /** + * This method is like `_.indexOf` except that it iterates over elements of + * `array` from right to left. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @param {number} [fromIndex=array.length-1] The index to search from. + * @returns {number} Returns the index of the matched value, else `-1`. + * @example + * + * _.lastIndexOf([1, 2, 1, 2], 2); + * // => 3 + * + * // Search from the `fromIndex`. + * _.lastIndexOf([1, 2, 1, 2], 2, 2); + * // => 1 + */ + function lastIndexOf(array, value, fromIndex) { + var length = array == null ? 0 : array.length; + if (!length) { + return -1; + } + var index = length; + if (fromIndex !== undefined) { + index = toInteger(fromIndex); + index = index < 0 ? nativeMax(length + index, 0) : nativeMin(index, length - 1); + } + return value === value + ? strictLastIndexOf(array, value, index) + : baseFindIndex(array, baseIsNaN, index, true); + } + + module.exports = lastIndexOf; + + +/***/ }), +/* 256 */ +/***/ (function(module, exports) { + + /** + * A specialized version of `_.lastIndexOf` which performs strict equality + * comparisons of values, i.e. `===`. + * + * @private + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @param {number} fromIndex The index to search from. + * @returns {number} Returns the index of the matched value, else `-1`. + */ + function strictLastIndexOf(array, value, fromIndex) { + var index = fromIndex + 1; + while (index--) { + if (array[index] === value) { + return index; + } + } + return index; + } + + module.exports = strictLastIndexOf; + + +/***/ }), +/* 257 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseNth = __webpack_require__(258), + toInteger = __webpack_require__(100); + + /** + * Gets the element at index `n` of `array`. If `n` is negative, the nth + * element from the end is returned. + * + * @static + * @memberOf _ + * @since 4.11.0 + * @category Array + * @param {Array} array The array to query. + * @param {number} [n=0] The index of the element to return. + * @returns {*} Returns the nth element of `array`. + * @example + * + * var array = ['a', 'b', 'c', 'd']; + * + * _.nth(array, 1); + * // => 'b' + * + * _.nth(array, -2); + * // => 'c'; + */ + function nth(array, n) { + return (array && array.length) ? baseNth(array, toInteger(n)) : undefined; + } + + module.exports = nth; + + +/***/ }), +/* 258 */ +/***/ (function(module, exports, __webpack_require__) { + + var isIndex = __webpack_require__(99); + + /** + * The base implementation of `_.nth` which doesn't coerce arguments. + * + * @private + * @param {Array} array The array to query. + * @param {number} n The index of the element to return. + * @returns {*} Returns the nth element of `array`. + */ + function baseNth(array, n) { + var length = array.length; + if (!length) { + return; + } + n += n < 0 ? length : 0; + return isIndex(n, length) ? array[n] : undefined; + } + + module.exports = baseNth; + + +/***/ }), +/* 259 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseRest = __webpack_require__(157), + pullAll = __webpack_require__(260); + + /** + * Removes all given values from `array` using + * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. + * + * **Note:** Unlike `_.without`, this method mutates `array`. Use `_.remove` + * to remove elements from an array by predicate. + * + * @static + * @memberOf _ + * @since 2.0.0 + * @category Array + * @param {Array} array The array to modify. + * @param {...*} [values] The values to remove. + * @returns {Array} Returns `array`. + * @example + * + * var array = ['a', 'b', 'c', 'a', 'b', 'c']; + * + * _.pull(array, 'a', 'c'); + * console.log(array); + * // => ['b', 'b'] + */ + var pull = baseRest(pullAll); + + module.exports = pull; + + +/***/ }), +/* 260 */ +/***/ (function(module, exports, __webpack_require__) { + + var basePullAll = __webpack_require__(261); + + /** + * This method is like `_.pull` except that it accepts an array of values to remove. + * + * **Note:** Unlike `_.difference`, this method mutates `array`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to modify. + * @param {Array} values The values to remove. + * @returns {Array} Returns `array`. + * @example + * + * var array = ['a', 'b', 'c', 'a', 'b', 'c']; + * + * _.pullAll(array, ['a', 'c']); + * console.log(array); + * // => ['b', 'b'] + */ + function pullAll(array, values) { + return (array && array.length && values && values.length) + ? basePullAll(array, values) + : array; + } + + module.exports = pullAll; + + +/***/ }), +/* 261 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayMap = __webpack_require__(154), + baseIndexOf = __webpack_require__(149), + baseIndexOfWith = __webpack_require__(262), + baseUnary = __webpack_require__(155), + copyArray = __webpack_require__(113); + + /** Used for built-in method references. */ + var arrayProto = Array.prototype; + + /** Built-in value references. */ + var splice = arrayProto.splice; + + /** + * The base implementation of `_.pullAllBy` without support for iteratee + * shorthands. + * + * @private + * @param {Array} array The array to modify. + * @param {Array} values The values to remove. + * @param {Function} [iteratee] The iteratee invoked per element. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns `array`. + */ + function basePullAll(array, values, iteratee, comparator) { + var indexOf = comparator ? baseIndexOfWith : baseIndexOf, + index = -1, + length = values.length, + seen = array; + + if (array === values) { + values = copyArray(values); + } + if (iteratee) { + seen = arrayMap(array, baseUnary(iteratee)); + } + while (++index < length) { + var fromIndex = 0, + value = values[index], + computed = iteratee ? iteratee(value) : value; + + while ((fromIndex = indexOf(seen, computed, fromIndex, comparator)) > -1) { + if (seen !== array) { + splice.call(seen, fromIndex, 1); + } + splice.call(array, fromIndex, 1); + } + } + return array; + } + + module.exports = basePullAll; + + +/***/ }), +/* 262 */ +/***/ (function(module, exports) { + + /** + * This function is like `baseIndexOf` except that it accepts a comparator. + * + * @private + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @param {number} fromIndex The index to search from. + * @param {Function} comparator The comparator invoked per element. + * @returns {number} Returns the index of the matched value, else `-1`. + */ + function baseIndexOfWith(array, value, fromIndex, comparator) { + var index = fromIndex - 1, + length = array.length; + + while (++index < length) { + if (comparator(array[index], value)) { + return index; + } + } + return -1; + } + + module.exports = baseIndexOfWith; + + +/***/ }), +/* 263 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + basePullAll = __webpack_require__(261); + + /** + * This method is like `_.pullAll` except that it accepts `iteratee` which is + * invoked for each element of `array` and `values` to generate the criterion + * by which they're compared. The iteratee is invoked with one argument: (value). + * + * **Note:** Unlike `_.differenceBy`, this method mutates `array`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to modify. + * @param {Array} values The values to remove. + * @param {Function} [iteratee=_.identity] The iteratee invoked per element. + * @returns {Array} Returns `array`. + * @example + * + * var array = [{ 'x': 1 }, { 'x': 2 }, { 'x': 3 }, { 'x': 1 }]; + * + * _.pullAllBy(array, [{ 'x': 1 }, { 'x': 3 }], 'x'); + * console.log(array); + * // => [{ 'x': 2 }] + */ + function pullAllBy(array, values, iteratee) { + return (array && array.length && values && values.length) + ? basePullAll(array, values, baseIteratee(iteratee, 2)) + : array; + } + + module.exports = pullAllBy; + + +/***/ }), +/* 264 */ +/***/ (function(module, exports, __webpack_require__) { + + var basePullAll = __webpack_require__(261); + + /** + * This method is like `_.pullAll` except that it accepts `comparator` which + * is invoked to compare elements of `array` to `values`. The comparator is + * invoked with two arguments: (arrVal, othVal). + * + * **Note:** Unlike `_.differenceWith`, this method mutates `array`. + * + * @static + * @memberOf _ + * @since 4.6.0 + * @category Array + * @param {Array} array The array to modify. + * @param {Array} values The values to remove. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns `array`. + * @example + * + * var array = [{ 'x': 1, 'y': 2 }, { 'x': 3, 'y': 4 }, { 'x': 5, 'y': 6 }]; + * + * _.pullAllWith(array, [{ 'x': 3, 'y': 4 }], _.isEqual); + * console.log(array); + * // => [{ 'x': 1, 'y': 2 }, { 'x': 5, 'y': 6 }] + */ + function pullAllWith(array, values, comparator) { + return (array && array.length && values && values.length) + ? basePullAll(array, values, undefined, comparator) + : array; + } + + module.exports = pullAllWith; + + +/***/ }), +/* 265 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayMap = __webpack_require__(154), + baseAt = __webpack_require__(266), + basePullAt = __webpack_require__(267), + compareAscending = __webpack_require__(270), + flatRest = __webpack_require__(271), + isIndex = __webpack_require__(99); + + /** + * Removes elements from `array` corresponding to `indexes` and returns an + * array of removed elements. + * + * **Note:** Unlike `_.at`, this method mutates `array`. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to modify. + * @param {...(number|number[])} [indexes] The indexes of elements to remove. + * @returns {Array} Returns the new array of removed elements. + * @example + * + * var array = ['a', 'b', 'c', 'd']; + * var pulled = _.pullAt(array, [1, 3]); + * + * console.log(array); + * // => ['a', 'c'] + * + * console.log(pulled); + * // => ['b', 'd'] + */ + var pullAt = flatRest(function(array, indexes) { + var length = array == null ? 0 : array.length, + result = baseAt(array, indexes); + + basePullAt(array, arrayMap(indexes, function(index) { + return isIndex(index, length) ? +index : index; + }).sort(compareAscending)); + + return result; + }); + + module.exports = pullAt; + + +/***/ }), +/* 266 */ +/***/ (function(module, exports, __webpack_require__) { + + var get = __webpack_require__(212); + + /** + * The base implementation of `_.at` without support for individual paths. + * + * @private + * @param {Object} object The object to iterate over. + * @param {string[]} paths The property paths to pick. + * @returns {Array} Returns the picked elements. + */ + function baseAt(object, paths) { + var index = -1, + length = paths.length, + result = Array(length), + skip = object == null; + + while (++index < length) { + result[index] = skip ? undefined : get(object, paths[index]); + } + return result; + } + + module.exports = baseAt; + + +/***/ }), +/* 267 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseUnset = __webpack_require__(268), + isIndex = __webpack_require__(99); + + /** Used for built-in method references. */ + var arrayProto = Array.prototype; + + /** Built-in value references. */ + var splice = arrayProto.splice; + + /** + * The base implementation of `_.pullAt` without support for individual + * indexes or capturing the removed elements. + * + * @private + * @param {Array} array The array to modify. + * @param {number[]} indexes The indexes of elements to remove. + * @returns {Array} Returns `array`. + */ + function basePullAt(array, indexes) { + var length = array ? indexes.length : 0, + lastIndex = length - 1; + + while (length--) { + var index = indexes[length]; + if (length == lastIndex || index !== previous) { + var previous = index; + if (isIndex(index)) { + splice.call(array, index, 1); + } else { + baseUnset(array, index); + } + } + } + return array; + } + + module.exports = basePullAt; + + +/***/ }), +/* 268 */ +/***/ (function(module, exports, __webpack_require__) { + + var castPath = __webpack_require__(214), + last = __webpack_require__(228), + parent = __webpack_require__(269), + toKey = __webpack_require__(221); + + /** + * The base implementation of `_.unset`. + * + * @private + * @param {Object} object The object to modify. + * @param {Array|string} path The property path to unset. + * @returns {boolean} Returns `true` if the property is deleted, else `false`. + */ + function baseUnset(object, path) { + path = castPath(path, object); + object = parent(object, path); + return object == null || delete object[toKey(last(path))]; + } + + module.exports = baseUnset; + + +/***/ }), +/* 269 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseGet = __webpack_require__(213), + baseSlice = __webpack_require__(86); + + /** + * Gets the parent value at `path` of `object`. + * + * @private + * @param {Object} object The object to query. + * @param {Array} path The path to get the parent value of. + * @returns {*} Returns the parent value. + */ + function parent(object, path) { + return path.length < 2 ? object : baseGet(object, baseSlice(path, 0, -1)); + } + + module.exports = parent; + + +/***/ }), +/* 270 */ +/***/ (function(module, exports, __webpack_require__) { + + var isSymbol = __webpack_require__(103); + + /** + * Compares values to sort them in ascending order. + * + * @private + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @returns {number} Returns the sort order indicator for `value`. + */ + function compareAscending(value, other) { + if (value !== other) { + var valIsDefined = value !== undefined, + valIsNull = value === null, + valIsReflexive = value === value, + valIsSymbol = isSymbol(value); + + var othIsDefined = other !== undefined, + othIsNull = other === null, + othIsReflexive = other === other, + othIsSymbol = isSymbol(other); + + if ((!othIsNull && !othIsSymbol && !valIsSymbol && value > other) || + (valIsSymbol && othIsDefined && othIsReflexive && !othIsNull && !othIsSymbol) || + (valIsNull && othIsDefined && othIsReflexive) || + (!valIsDefined && othIsReflexive) || + !valIsReflexive) { + return 1; + } + if ((!valIsNull && !valIsSymbol && !othIsSymbol && value < other) || + (othIsSymbol && valIsDefined && valIsReflexive && !valIsNull && !valIsSymbol) || + (othIsNull && valIsDefined && valIsReflexive) || + (!othIsDefined && valIsReflexive) || + !othIsReflexive) { + return -1; + } + } + return 0; + } + + module.exports = compareAscending; + + +/***/ }), +/* 271 */ +/***/ (function(module, exports, __webpack_require__) { + + var flatten = __webpack_require__(243), + overRest = __webpack_require__(159), + setToString = __webpack_require__(161); + + /** + * A specialized version of `baseRest` which flattens the rest array. + * + * @private + * @param {Function} func The function to apply a rest parameter to. + * @returns {Function} Returns the new function. + */ + function flatRest(func) { + return setToString(overRest(func, undefined, flatten), func + ''); + } + + module.exports = flatRest; + + +/***/ }), +/* 272 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + basePullAt = __webpack_require__(267); + + /** + * Removes all elements from `array` that `predicate` returns truthy for + * and returns an array of the removed elements. The predicate is invoked + * with three arguments: (value, index, array). + * + * **Note:** Unlike `_.filter`, this method mutates `array`. Use `_.pull` + * to pull elements from an array by value. + * + * @static + * @memberOf _ + * @since 2.0.0 + * @category Array + * @param {Array} array The array to modify. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @returns {Array} Returns the new array of removed elements. + * @example + * + * var array = [1, 2, 3, 4]; + * var evens = _.remove(array, function(n) { + * return n % 2 == 0; + * }); + * + * console.log(array); + * // => [1, 3] + * + * console.log(evens); + * // => [2, 4] + */ + function remove(array, predicate) { + var result = []; + if (!(array && array.length)) { + return result; + } + var index = -1, + indexes = [], + length = array.length; + + predicate = baseIteratee(predicate, 3); + while (++index < length) { + var value = array[index]; + if (predicate(value, index, array)) { + result.push(value); + indexes.push(index); + } + } + basePullAt(array, indexes); + return result; + } + + module.exports = remove; + + +/***/ }), +/* 273 */ +/***/ (function(module, exports) { + + /** Used for built-in method references. */ + var arrayProto = Array.prototype; + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeReverse = arrayProto.reverse; + + /** + * Reverses `array` so that the first element becomes the last, the second + * element becomes the second to last, and so on. + * + * **Note:** This method mutates `array` and is based on + * [`Array#reverse`](https://mdn.io/Array/reverse). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to modify. + * @returns {Array} Returns `array`. + * @example + * + * var array = [1, 2, 3]; + * + * _.reverse(array); + * // => [3, 2, 1] + * + * console.log(array); + * // => [3, 2, 1] + */ + function reverse(array) { + return array == null ? array : nativeReverse.call(array); + } + + module.exports = reverse; + + +/***/ }), +/* 274 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86), + isIterateeCall = __webpack_require__(87), + toInteger = __webpack_require__(100); + + /** + * Creates a slice of `array` from `start` up to, but not including, `end`. + * + * **Note:** This method is used instead of + * [`Array#slice`](https://mdn.io/Array/slice) to ensure dense arrays are + * returned. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to slice. + * @param {number} [start=0] The start position. + * @param {number} [end=array.length] The end position. + * @returns {Array} Returns the slice of `array`. + */ + function slice(array, start, end) { + var length = array == null ? 0 : array.length; + if (!length) { + return []; + } + if (end && typeof end != 'number' && isIterateeCall(array, start, end)) { + start = 0; + end = length; + } + else { + start = start == null ? 0 : toInteger(start); + end = end === undefined ? length : toInteger(end); + } + return baseSlice(array, start, end); + } + + module.exports = slice; + + +/***/ }), +/* 275 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSortedIndex = __webpack_require__(276); + + /** + * Uses a binary search to determine the lowest index at which `value` + * should be inserted into `array` in order to maintain its sort order. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The sorted array to inspect. + * @param {*} value The value to evaluate. + * @returns {number} Returns the index at which `value` should be inserted + * into `array`. + * @example + * + * _.sortedIndex([30, 50], 40); + * // => 1 + */ + function sortedIndex(array, value) { + return baseSortedIndex(array, value); + } + + module.exports = sortedIndex; + + +/***/ }), +/* 276 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSortedIndexBy = __webpack_require__(277), + identity = __webpack_require__(158), + isSymbol = __webpack_require__(103); + + /** Used as references for the maximum length and index of an array. */ + var MAX_ARRAY_LENGTH = 4294967295, + HALF_MAX_ARRAY_LENGTH = MAX_ARRAY_LENGTH >>> 1; + + /** + * The base implementation of `_.sortedIndex` and `_.sortedLastIndex` which + * performs a binary search of `array` to determine the index at which `value` + * should be inserted into `array` in order to maintain its sort order. + * + * @private + * @param {Array} array The sorted array to inspect. + * @param {*} value The value to evaluate. + * @param {boolean} [retHighest] Specify returning the highest qualified index. + * @returns {number} Returns the index at which `value` should be inserted + * into `array`. + */ + function baseSortedIndex(array, value, retHighest) { + var low = 0, + high = array == null ? low : array.length; + + if (typeof value == 'number' && value === value && high <= HALF_MAX_ARRAY_LENGTH) { + while (low < high) { + var mid = (low + high) >>> 1, + computed = array[mid]; + + if (computed !== null && !isSymbol(computed) && + (retHighest ? (computed <= value) : (computed < value))) { + low = mid + 1; + } else { + high = mid; + } + } + return high; + } + return baseSortedIndexBy(array, value, identity, retHighest); + } + + module.exports = baseSortedIndex; + + +/***/ }), +/* 277 */ +/***/ (function(module, exports, __webpack_require__) { + + var isSymbol = __webpack_require__(103); + + /** Used as references for the maximum length and index of an array. */ + var MAX_ARRAY_LENGTH = 4294967295, + MAX_ARRAY_INDEX = MAX_ARRAY_LENGTH - 1; + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeFloor = Math.floor, + nativeMin = Math.min; + + /** + * The base implementation of `_.sortedIndexBy` and `_.sortedLastIndexBy` + * which invokes `iteratee` for `value` and each element of `array` to compute + * their sort ranking. The iteratee is invoked with one argument; (value). + * + * @private + * @param {Array} array The sorted array to inspect. + * @param {*} value The value to evaluate. + * @param {Function} iteratee The iteratee invoked per element. + * @param {boolean} [retHighest] Specify returning the highest qualified index. + * @returns {number} Returns the index at which `value` should be inserted + * into `array`. + */ + function baseSortedIndexBy(array, value, iteratee, retHighest) { + value = iteratee(value); + + var low = 0, + high = array == null ? 0 : array.length, + valIsNaN = value !== value, + valIsNull = value === null, + valIsSymbol = isSymbol(value), + valIsUndefined = value === undefined; + + while (low < high) { + var mid = nativeFloor((low + high) / 2), + computed = iteratee(array[mid]), + othIsDefined = computed !== undefined, + othIsNull = computed === null, + othIsReflexive = computed === computed, + othIsSymbol = isSymbol(computed); + + if (valIsNaN) { + var setLow = retHighest || othIsReflexive; + } else if (valIsUndefined) { + setLow = othIsReflexive && (retHighest || othIsDefined); + } else if (valIsNull) { + setLow = othIsReflexive && othIsDefined && (retHighest || !othIsNull); + } else if (valIsSymbol) { + setLow = othIsReflexive && othIsDefined && !othIsNull && (retHighest || !othIsSymbol); + } else if (othIsNull || othIsSymbol) { + setLow = false; + } else { + setLow = retHighest ? (computed <= value) : (computed < value); + } + if (setLow) { + low = mid + 1; + } else { + high = mid; + } + } + return nativeMin(high, MAX_ARRAY_INDEX); + } + + module.exports = baseSortedIndexBy; + + +/***/ }), +/* 278 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + baseSortedIndexBy = __webpack_require__(277); + + /** + * This method is like `_.sortedIndex` except that it accepts `iteratee` + * which is invoked for `value` and each element of `array` to compute their + * sort ranking. The iteratee is invoked with one argument: (value). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The sorted array to inspect. + * @param {*} value The value to evaluate. + * @param {Function} [iteratee=_.identity] The iteratee invoked per element. + * @returns {number} Returns the index at which `value` should be inserted + * into `array`. + * @example + * + * var objects = [{ 'x': 4 }, { 'x': 5 }]; + * + * _.sortedIndexBy(objects, { 'x': 4 }, function(o) { return o.x; }); + * // => 0 + * + * // The `_.property` iteratee shorthand. + * _.sortedIndexBy(objects, { 'x': 4 }, 'x'); + * // => 0 + */ + function sortedIndexBy(array, value, iteratee) { + return baseSortedIndexBy(array, value, baseIteratee(iteratee, 2)); + } + + module.exports = sortedIndexBy; + + +/***/ }), +/* 279 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSortedIndex = __webpack_require__(276), + eq = __webpack_require__(88); + + /** + * This method is like `_.indexOf` except that it performs a binary + * search on a sorted `array`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @returns {number} Returns the index of the matched value, else `-1`. + * @example + * + * _.sortedIndexOf([4, 5, 5, 5, 6], 5); + * // => 1 + */ + function sortedIndexOf(array, value) { + var length = array == null ? 0 : array.length; + if (length) { + var index = baseSortedIndex(array, value); + if (index < length && eq(array[index], value)) { + return index; + } + } + return -1; + } + + module.exports = sortedIndexOf; + + +/***/ }), +/* 280 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSortedIndex = __webpack_require__(276); + + /** + * This method is like `_.sortedIndex` except that it returns the highest + * index at which `value` should be inserted into `array` in order to + * maintain its sort order. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The sorted array to inspect. + * @param {*} value The value to evaluate. + * @returns {number} Returns the index at which `value` should be inserted + * into `array`. + * @example + * + * _.sortedLastIndex([4, 5, 5, 5, 6], 5); + * // => 4 + */ + function sortedLastIndex(array, value) { + return baseSortedIndex(array, value, true); + } + + module.exports = sortedLastIndex; + + +/***/ }), +/* 281 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + baseSortedIndexBy = __webpack_require__(277); + + /** + * This method is like `_.sortedLastIndex` except that it accepts `iteratee` + * which is invoked for `value` and each element of `array` to compute their + * sort ranking. The iteratee is invoked with one argument: (value). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The sorted array to inspect. + * @param {*} value The value to evaluate. + * @param {Function} [iteratee=_.identity] The iteratee invoked per element. + * @returns {number} Returns the index at which `value` should be inserted + * into `array`. + * @example + * + * var objects = [{ 'x': 4 }, { 'x': 5 }]; + * + * _.sortedLastIndexBy(objects, { 'x': 4 }, function(o) { return o.x; }); + * // => 1 + * + * // The `_.property` iteratee shorthand. + * _.sortedLastIndexBy(objects, { 'x': 4 }, 'x'); + * // => 1 + */ + function sortedLastIndexBy(array, value, iteratee) { + return baseSortedIndexBy(array, value, baseIteratee(iteratee, 2), true); + } + + module.exports = sortedLastIndexBy; + + +/***/ }), +/* 282 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSortedIndex = __webpack_require__(276), + eq = __webpack_require__(88); + + /** + * This method is like `_.lastIndexOf` except that it performs a binary + * search on a sorted `array`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @returns {number} Returns the index of the matched value, else `-1`. + * @example + * + * _.sortedLastIndexOf([4, 5, 5, 5, 6], 5); + * // => 3 + */ + function sortedLastIndexOf(array, value) { + var length = array == null ? 0 : array.length; + if (length) { + var index = baseSortedIndex(array, value, true) - 1; + if (eq(array[index], value)) { + return index; + } + } + return -1; + } + + module.exports = sortedLastIndexOf; + + +/***/ }), +/* 283 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSortedUniq = __webpack_require__(284); + + /** + * This method is like `_.uniq` except that it's designed and optimized + * for sorted arrays. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @returns {Array} Returns the new duplicate free array. + * @example + * + * _.sortedUniq([1, 1, 2]); + * // => [1, 2] + */ + function sortedUniq(array) { + return (array && array.length) + ? baseSortedUniq(array) + : []; + } + + module.exports = sortedUniq; + + +/***/ }), +/* 284 */ +/***/ (function(module, exports, __webpack_require__) { + + var eq = __webpack_require__(88); + + /** + * The base implementation of `_.sortedUniq` and `_.sortedUniqBy` without + * support for iteratee shorthands. + * + * @private + * @param {Array} array The array to inspect. + * @param {Function} [iteratee] The iteratee invoked per element. + * @returns {Array} Returns the new duplicate free array. + */ + function baseSortedUniq(array, iteratee) { + var index = -1, + length = array.length, + resIndex = 0, + result = []; + + while (++index < length) { + var value = array[index], + computed = iteratee ? iteratee(value) : value; + + if (!index || !eq(computed, seen)) { + var seen = computed; + result[resIndex++] = value === 0 ? 0 : value; + } + } + return result; + } + + module.exports = baseSortedUniq; + + +/***/ }), +/* 285 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + baseSortedUniq = __webpack_require__(284); + + /** + * This method is like `_.uniqBy` except that it's designed and optimized + * for sorted arrays. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {Function} [iteratee] The iteratee invoked per element. + * @returns {Array} Returns the new duplicate free array. + * @example + * + * _.sortedUniqBy([1.1, 1.2, 2.3, 2.4], Math.floor); + * // => [1.1, 2.3] + */ + function sortedUniqBy(array, iteratee) { + return (array && array.length) + ? baseSortedUniq(array, baseIteratee(iteratee, 2)) + : []; + } + + module.exports = sortedUniqBy; + + +/***/ }), +/* 286 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86); + + /** + * Gets all but the first element of `array`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to query. + * @returns {Array} Returns the slice of `array`. + * @example + * + * _.tail([1, 2, 3]); + * // => [2, 3] + */ + function tail(array) { + var length = array == null ? 0 : array.length; + return length ? baseSlice(array, 1, length) : []; + } + + module.exports = tail; + + +/***/ }), +/* 287 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86), + toInteger = __webpack_require__(100); + + /** + * Creates a slice of `array` with `n` elements taken from the beginning. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to query. + * @param {number} [n=1] The number of elements to take. + * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. + * @returns {Array} Returns the slice of `array`. + * @example + * + * _.take([1, 2, 3]); + * // => [1] + * + * _.take([1, 2, 3], 2); + * // => [1, 2] + * + * _.take([1, 2, 3], 5); + * // => [1, 2, 3] + * + * _.take([1, 2, 3], 0); + * // => [] + */ + function take(array, n, guard) { + if (!(array && array.length)) { + return []; + } + n = (guard || n === undefined) ? 1 : toInteger(n); + return baseSlice(array, 0, n < 0 ? 0 : n); + } + + module.exports = take; + + +/***/ }), +/* 288 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86), + toInteger = __webpack_require__(100); + + /** + * Creates a slice of `array` with `n` elements taken from the end. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to query. + * @param {number} [n=1] The number of elements to take. + * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. + * @returns {Array} Returns the slice of `array`. + * @example + * + * _.takeRight([1, 2, 3]); + * // => [3] + * + * _.takeRight([1, 2, 3], 2); + * // => [2, 3] + * + * _.takeRight([1, 2, 3], 5); + * // => [1, 2, 3] + * + * _.takeRight([1, 2, 3], 0); + * // => [] + */ + function takeRight(array, n, guard) { + var length = array == null ? 0 : array.length; + if (!length) { + return []; + } + n = (guard || n === undefined) ? 1 : toInteger(n); + n = length - n; + return baseSlice(array, n < 0 ? 0 : n, length); + } + + module.exports = takeRight; + + +/***/ }), +/* 289 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + baseWhile = __webpack_require__(233); + + /** + * Creates a slice of `array` with elements taken from the end. Elements are + * taken until `predicate` returns falsey. The predicate is invoked with + * three arguments: (value, index, array). + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to query. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @returns {Array} Returns the slice of `array`. + * @example + * + * var users = [ + * { 'user': 'barney', 'active': true }, + * { 'user': 'fred', 'active': false }, + * { 'user': 'pebbles', 'active': false } + * ]; + * + * _.takeRightWhile(users, function(o) { return !o.active; }); + * // => objects for ['fred', 'pebbles'] + * + * // The `_.matches` iteratee shorthand. + * _.takeRightWhile(users, { 'user': 'pebbles', 'active': false }); + * // => objects for ['pebbles'] + * + * // The `_.matchesProperty` iteratee shorthand. + * _.takeRightWhile(users, ['active', false]); + * // => objects for ['fred', 'pebbles'] + * + * // The `_.property` iteratee shorthand. + * _.takeRightWhile(users, 'active'); + * // => [] + */ + function takeRightWhile(array, predicate) { + return (array && array.length) + ? baseWhile(array, baseIteratee(predicate, 3), false, true) + : []; + } + + module.exports = takeRightWhile; + + +/***/ }), +/* 290 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + baseWhile = __webpack_require__(233); + + /** + * Creates a slice of `array` with elements taken from the beginning. Elements + * are taken until `predicate` returns falsey. The predicate is invoked with + * three arguments: (value, index, array). + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to query. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @returns {Array} Returns the slice of `array`. + * @example + * + * var users = [ + * { 'user': 'barney', 'active': false }, + * { 'user': 'fred', 'active': false }, + * { 'user': 'pebbles', 'active': true } + * ]; + * + * _.takeWhile(users, function(o) { return !o.active; }); + * // => objects for ['barney', 'fred'] + * + * // The `_.matches` iteratee shorthand. + * _.takeWhile(users, { 'user': 'barney', 'active': false }); + * // => objects for ['barney'] + * + * // The `_.matchesProperty` iteratee shorthand. + * _.takeWhile(users, ['active', false]); + * // => objects for ['barney', 'fred'] + * + * // The `_.property` iteratee shorthand. + * _.takeWhile(users, 'active'); + * // => [] + */ + function takeWhile(array, predicate) { + return (array && array.length) + ? baseWhile(array, baseIteratee(predicate, 3)) + : []; + } + + module.exports = takeWhile; + + +/***/ }), +/* 291 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFlatten = __webpack_require__(108), + baseRest = __webpack_require__(157), + baseUniq = __webpack_require__(292), + isArrayLikeObject = __webpack_require__(166); + + /** + * Creates an array of unique values, in order, from all given arrays using + * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @returns {Array} Returns the new array of combined values. + * @example + * + * _.union([2], [1, 2]); + * // => [2, 1] + */ + var union = baseRest(function(arrays) { + return baseUniq(baseFlatten(arrays, 1, isArrayLikeObject, true)); + }); + + module.exports = union; + + +/***/ }), +/* 292 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetCache = __webpack_require__(116), + arrayIncludes = __webpack_require__(148), + arrayIncludesWith = __webpack_require__(153), + cacheHas = __webpack_require__(156), + createSet = __webpack_require__(293), + setToArray = __webpack_require__(184); + + /** Used as the size to enable large array optimizations. */ + var LARGE_ARRAY_SIZE = 200; + + /** + * The base implementation of `_.uniqBy` without support for iteratee shorthands. + * + * @private + * @param {Array} array The array to inspect. + * @param {Function} [iteratee] The iteratee invoked per element. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new duplicate free array. + */ + function baseUniq(array, iteratee, comparator) { + var index = -1, + includes = arrayIncludes, + length = array.length, + isCommon = true, + result = [], + seen = result; + + if (comparator) { + isCommon = false; + includes = arrayIncludesWith; + } + else if (length >= LARGE_ARRAY_SIZE) { + var set = iteratee ? null : createSet(array); + if (set) { + return setToArray(set); + } + isCommon = false; + includes = cacheHas; + seen = new SetCache; + } + else { + seen = iteratee ? [] : result; + } + outer: + while (++index < length) { + var value = array[index], + computed = iteratee ? iteratee(value) : value; + + value = (comparator || value !== 0) ? value : 0; + if (isCommon && computed === computed) { + var seenIndex = seen.length; + while (seenIndex--) { + if (seen[seenIndex] === computed) { + continue outer; + } + } + if (iteratee) { + seen.push(computed); + } + result.push(value); + } + else if (!includes(seen, computed, comparator)) { + if (seen !== result) { + seen.push(computed); + } + result.push(value); + } + } + return result; + } + + module.exports = baseUniq; + + +/***/ }), +/* 293 */ +/***/ (function(module, exports, __webpack_require__) { + + var Set = __webpack_require__(206), + noop = __webpack_require__(294), + setToArray = __webpack_require__(184); + + /** Used as references for various `Number` constants. */ + var INFINITY = 1 / 0; + + /** + * Creates a set object of `values`. + * + * @private + * @param {Array} values The values to add to the set. + * @returns {Object} Returns the new set. + */ + var createSet = !(Set && (1 / setToArray(new Set([,-0]))[1]) == INFINITY) ? noop : function(values) { + return new Set(values); + }; + + module.exports = createSet; + + +/***/ }), +/* 294 */ +/***/ (function(module, exports) { + + /** + * This method returns `undefined`. + * + * @static + * @memberOf _ + * @since 2.3.0 + * @category Util + * @example + * + * _.times(2, _.noop); + * // => [undefined, undefined] + */ + function noop() { + // No operation performed. + } + + module.exports = noop; + + +/***/ }), +/* 295 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFlatten = __webpack_require__(108), + baseIteratee = __webpack_require__(168), + baseRest = __webpack_require__(157), + baseUniq = __webpack_require__(292), + isArrayLikeObject = __webpack_require__(166), + last = __webpack_require__(228); + + /** + * This method is like `_.union` except that it accepts `iteratee` which is + * invoked for each element of each `arrays` to generate the criterion by + * which uniqueness is computed. Result values are chosen from the first + * array in which the value occurs. The iteratee is invoked with one argument: + * (value). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @param {Function} [iteratee=_.identity] The iteratee invoked per element. + * @returns {Array} Returns the new array of combined values. + * @example + * + * _.unionBy([2.1], [1.2, 2.3], Math.floor); + * // => [2.1, 1.2] + * + * // The `_.property` iteratee shorthand. + * _.unionBy([{ 'x': 1 }], [{ 'x': 2 }, { 'x': 1 }], 'x'); + * // => [{ 'x': 1 }, { 'x': 2 }] + */ + var unionBy = baseRest(function(arrays) { + var iteratee = last(arrays); + if (isArrayLikeObject(iteratee)) { + iteratee = undefined; + } + return baseUniq(baseFlatten(arrays, 1, isArrayLikeObject, true), baseIteratee(iteratee, 2)); + }); + + module.exports = unionBy; + + +/***/ }), +/* 296 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFlatten = __webpack_require__(108), + baseRest = __webpack_require__(157), + baseUniq = __webpack_require__(292), + isArrayLikeObject = __webpack_require__(166), + last = __webpack_require__(228); + + /** + * This method is like `_.union` except that it accepts `comparator` which + * is invoked to compare elements of `arrays`. Result values are chosen from + * the first array in which the value occurs. The comparator is invoked + * with two arguments: (arrVal, othVal). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new array of combined values. + * @example + * + * var objects = [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }]; + * var others = [{ 'x': 1, 'y': 1 }, { 'x': 1, 'y': 2 }]; + * + * _.unionWith(objects, others, _.isEqual); + * // => [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }, { 'x': 1, 'y': 1 }] + */ + var unionWith = baseRest(function(arrays) { + var comparator = last(arrays); + comparator = typeof comparator == 'function' ? comparator : undefined; + return baseUniq(baseFlatten(arrays, 1, isArrayLikeObject, true), undefined, comparator); + }); + + module.exports = unionWith; + + +/***/ }), +/* 297 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseUniq = __webpack_require__(292); + + /** + * Creates a duplicate-free version of an array, using + * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons, in which only the first occurrence of each element + * is kept. The order of result values is determined by the order they occur + * in the array. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to inspect. + * @returns {Array} Returns the new duplicate free array. + * @example + * + * _.uniq([2, 1, 2]); + * // => [2, 1] + */ + function uniq(array) { + return (array && array.length) ? baseUniq(array) : []; + } + + module.exports = uniq; + + +/***/ }), +/* 298 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + baseUniq = __webpack_require__(292); + + /** + * This method is like `_.uniq` except that it accepts `iteratee` which is + * invoked for each element in `array` to generate the criterion by which + * uniqueness is computed. The order of result values is determined by the + * order they occur in the array. The iteratee is invoked with one argument: + * (value). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {Function} [iteratee=_.identity] The iteratee invoked per element. + * @returns {Array} Returns the new duplicate free array. + * @example + * + * _.uniqBy([2.1, 1.2, 2.3], Math.floor); + * // => [2.1, 1.2] + * + * // The `_.property` iteratee shorthand. + * _.uniqBy([{ 'x': 1 }, { 'x': 2 }, { 'x': 1 }], 'x'); + * // => [{ 'x': 1 }, { 'x': 2 }] + */ + function uniqBy(array, iteratee) { + return (array && array.length) ? baseUniq(array, baseIteratee(iteratee, 2)) : []; + } + + module.exports = uniqBy; + + +/***/ }), +/* 299 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseUniq = __webpack_require__(292); + + /** + * This method is like `_.uniq` except that it accepts `comparator` which + * is invoked to compare elements of `array`. The order of result values is + * determined by the order they occur in the array.The comparator is invoked + * with two arguments: (arrVal, othVal). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new duplicate free array. + * @example + * + * var objects = [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }, { 'x': 1, 'y': 2 }]; + * + * _.uniqWith(objects, _.isEqual); + * // => [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }] + */ + function uniqWith(array, comparator) { + comparator = typeof comparator == 'function' ? comparator : undefined; + return (array && array.length) ? baseUniq(array, undefined, comparator) : []; + } + + module.exports = uniqWith; + + +/***/ }), +/* 300 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayFilter = __webpack_require__(189), + arrayMap = __webpack_require__(154), + baseProperty = __webpack_require__(226), + baseTimes = __webpack_require__(193), + isArrayLikeObject = __webpack_require__(166); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeMax = Math.max; + + /** + * This method is like `_.zip` except that it accepts an array of grouped + * elements and creates an array regrouping the elements to their pre-zip + * configuration. + * + * @static + * @memberOf _ + * @since 1.2.0 + * @category Array + * @param {Array} array The array of grouped elements to process. + * @returns {Array} Returns the new array of regrouped elements. + * @example + * + * var zipped = _.zip(['a', 'b'], [1, 2], [true, false]); + * // => [['a', 1, true], ['b', 2, false]] + * + * _.unzip(zipped); + * // => [['a', 'b'], [1, 2], [true, false]] + */ + function unzip(array) { + if (!(array && array.length)) { + return []; + } + var length = 0; + array = arrayFilter(array, function(group) { + if (isArrayLikeObject(group)) { + length = nativeMax(group.length, length); + return true; + } + }); + return baseTimes(length, function(index) { + return arrayMap(array, baseProperty(index)); + }); + } + + module.exports = unzip; + + +/***/ }), +/* 301 */ +/***/ (function(module, exports, __webpack_require__) { + + var apply = __webpack_require__(160), + arrayMap = __webpack_require__(154), + unzip = __webpack_require__(300); + + /** + * This method is like `_.unzip` except that it accepts `iteratee` to specify + * how regrouped values should be combined. The iteratee is invoked with the + * elements of each group: (...group). + * + * @static + * @memberOf _ + * @since 3.8.0 + * @category Array + * @param {Array} array The array of grouped elements to process. + * @param {Function} [iteratee=_.identity] The function to combine + * regrouped values. + * @returns {Array} Returns the new array of regrouped elements. + * @example + * + * var zipped = _.zip([1, 2], [10, 20], [100, 200]); + * // => [[1, 10, 100], [2, 20, 200]] + * + * _.unzipWith(zipped, _.add); + * // => [3, 30, 300] + */ + function unzipWith(array, iteratee) { + if (!(array && array.length)) { + return []; + } + var result = unzip(array); + if (iteratee == null) { + return result; + } + return arrayMap(result, function(group) { + return apply(iteratee, undefined, group); + }); + } + + module.exports = unzipWith; + + +/***/ }), +/* 302 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseDifference = __webpack_require__(115), + baseRest = __webpack_require__(157), + isArrayLikeObject = __webpack_require__(166); + + /** + * Creates an array excluding all given values using + * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. + * + * **Note:** Unlike `_.pull`, this method returns a new array. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {...*} [values] The values to exclude. + * @returns {Array} Returns the new array of filtered values. + * @see _.difference, _.xor + * @example + * + * _.without([2, 1, 2, 3], 1, 2); + * // => [3] + */ + var without = baseRest(function(array, values) { + return isArrayLikeObject(array) + ? baseDifference(array, values) + : []; + }); + + module.exports = without; + + +/***/ }), +/* 303 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayFilter = __webpack_require__(189), + baseRest = __webpack_require__(157), + baseXor = __webpack_require__(304), + isArrayLikeObject = __webpack_require__(166); + + /** + * Creates an array of unique values that is the + * [symmetric difference](https://en.wikipedia.org/wiki/Symmetric_difference) + * of the given arrays. The order of result values is determined by the order + * they occur in the arrays. + * + * @static + * @memberOf _ + * @since 2.4.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @returns {Array} Returns the new array of filtered values. + * @see _.difference, _.without + * @example + * + * _.xor([2, 1], [2, 3]); + * // => [1, 3] + */ + var xor = baseRest(function(arrays) { + return baseXor(arrayFilter(arrays, isArrayLikeObject)); + }); + + module.exports = xor; + + +/***/ }), +/* 304 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseDifference = __webpack_require__(115), + baseFlatten = __webpack_require__(108), + baseUniq = __webpack_require__(292); + + /** + * The base implementation of methods like `_.xor`, without support for + * iteratee shorthands, that accepts an array of arrays to inspect. + * + * @private + * @param {Array} arrays The arrays to inspect. + * @param {Function} [iteratee] The iteratee invoked per element. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new array of values. + */ + function baseXor(arrays, iteratee, comparator) { + var length = arrays.length; + if (length < 2) { + return length ? baseUniq(arrays[0]) : []; + } + var index = -1, + result = Array(length); + + while (++index < length) { + var array = arrays[index], + othIndex = -1; + + while (++othIndex < length) { + if (othIndex != index) { + result[index] = baseDifference(result[index] || array, arrays[othIndex], iteratee, comparator); + } + } + } + return baseUniq(baseFlatten(result, 1), iteratee, comparator); + } + + module.exports = baseXor; + + +/***/ }), +/* 305 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayFilter = __webpack_require__(189), + baseIteratee = __webpack_require__(168), + baseRest = __webpack_require__(157), + baseXor = __webpack_require__(304), + isArrayLikeObject = __webpack_require__(166), + last = __webpack_require__(228); + + /** + * This method is like `_.xor` except that it accepts `iteratee` which is + * invoked for each element of each `arrays` to generate the criterion by + * which by which they're compared. The order of result values is determined + * by the order they occur in the arrays. The iteratee is invoked with one + * argument: (value). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @param {Function} [iteratee=_.identity] The iteratee invoked per element. + * @returns {Array} Returns the new array of filtered values. + * @example + * + * _.xorBy([2.1, 1.2], [2.3, 3.4], Math.floor); + * // => [1.2, 3.4] + * + * // The `_.property` iteratee shorthand. + * _.xorBy([{ 'x': 1 }], [{ 'x': 2 }, { 'x': 1 }], 'x'); + * // => [{ 'x': 2 }] + */ + var xorBy = baseRest(function(arrays) { + var iteratee = last(arrays); + if (isArrayLikeObject(iteratee)) { + iteratee = undefined; + } + return baseXor(arrayFilter(arrays, isArrayLikeObject), baseIteratee(iteratee, 2)); + }); + + module.exports = xorBy; + + +/***/ }), +/* 306 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayFilter = __webpack_require__(189), + baseRest = __webpack_require__(157), + baseXor = __webpack_require__(304), + isArrayLikeObject = __webpack_require__(166), + last = __webpack_require__(228); + + /** + * This method is like `_.xor` except that it accepts `comparator` which is + * invoked to compare elements of `arrays`. The order of result values is + * determined by the order they occur in the arrays. The comparator is invoked + * with two arguments: (arrVal, othVal). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new array of filtered values. + * @example + * + * var objects = [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }]; + * var others = [{ 'x': 1, 'y': 1 }, { 'x': 1, 'y': 2 }]; + * + * _.xorWith(objects, others, _.isEqual); + * // => [{ 'x': 2, 'y': 1 }, { 'x': 1, 'y': 1 }] + */ + var xorWith = baseRest(function(arrays) { + var comparator = last(arrays); + comparator = typeof comparator == 'function' ? comparator : undefined; + return baseXor(arrayFilter(arrays, isArrayLikeObject), undefined, comparator); + }); + + module.exports = xorWith; + + +/***/ }), +/* 307 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseRest = __webpack_require__(157), + unzip = __webpack_require__(300); + + /** + * Creates an array of grouped elements, the first of which contains the + * first elements of the given arrays, the second of which contains the + * second elements of the given arrays, and so on. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {...Array} [arrays] The arrays to process. + * @returns {Array} Returns the new array of grouped elements. + * @example + * + * _.zip(['a', 'b'], [1, 2], [true, false]); + * // => [['a', 1, true], ['b', 2, false]] + */ + var zip = baseRest(unzip); + + module.exports = zip; + + +/***/ }), +/* 308 */ +/***/ (function(module, exports, __webpack_require__) { + + var assignValue = __webpack_require__(309), + baseZipObject = __webpack_require__(311); + + /** + * This method is like `_.fromPairs` except that it accepts two arrays, + * one of property identifiers and one of corresponding values. + * + * @static + * @memberOf _ + * @since 0.4.0 + * @category Array + * @param {Array} [props=[]] The property identifiers. + * @param {Array} [values=[]] The property values. + * @returns {Object} Returns the new object. + * @example + * + * _.zipObject(['a', 'b'], [1, 2]); + * // => { 'a': 1, 'b': 2 } + */ + function zipObject(props, values) { + return baseZipObject(props || [], values || [], assignValue); + } + + module.exports = zipObject; + + +/***/ }), +/* 309 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseAssignValue = __webpack_require__(310), + eq = __webpack_require__(88); + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * Assigns `value` to `key` of `object` if the existing value is not equivalent + * using [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. + * + * @private + * @param {Object} object The object to modify. + * @param {string} key The key of the property to assign. + * @param {*} value The value to assign. + */ + function assignValue(object, key, value) { + var objValue = object[key]; + if (!(hasOwnProperty.call(object, key) && eq(objValue, value)) || + (value === undefined && !(key in object))) { + baseAssignValue(object, key, value); + } + } + + module.exports = assignValue; + + +/***/ }), +/* 310 */ +/***/ (function(module, exports, __webpack_require__) { + + var defineProperty = __webpack_require__(164); + + /** + * The base implementation of `assignValue` and `assignMergeValue` without + * value checks. + * + * @private + * @param {Object} object The object to modify. + * @param {string} key The key of the property to assign. + * @param {*} value The value to assign. + */ + function baseAssignValue(object, key, value) { + if (key == '__proto__' && defineProperty) { + defineProperty(object, key, { + 'configurable': true, + 'enumerable': true, + 'value': value, + 'writable': true + }); + } else { + object[key] = value; + } + } + + module.exports = baseAssignValue; + + +/***/ }), +/* 311 */ +/***/ (function(module, exports) { + + /** + * This base implementation of `_.zipObject` which assigns values using `assignFunc`. + * + * @private + * @param {Array} props The property identifiers. + * @param {Array} values The property values. + * @param {Function} assignFunc The function to assign values. + * @returns {Object} Returns the new object. + */ + function baseZipObject(props, values, assignFunc) { + var index = -1, + length = props.length, + valsLength = values.length, + result = {}; + + while (++index < length) { + var value = index < valsLength ? values[index] : undefined; + assignFunc(result, props[index], value); + } + return result; + } + + module.exports = baseZipObject; + + +/***/ }), +/* 312 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSet = __webpack_require__(313), + baseZipObject = __webpack_require__(311); + + /** + * This method is like `_.zipObject` except that it supports property paths. + * + * @static + * @memberOf _ + * @since 4.1.0 + * @category Array + * @param {Array} [props=[]] The property identifiers. + * @param {Array} [values=[]] The property values. + * @returns {Object} Returns the new object. + * @example + * + * _.zipObjectDeep(['a.b[0].c', 'a.b[1].d'], [1, 2]); + * // => { 'a': { 'b': [{ 'c': 1 }, { 'd': 2 }] } } + */ + function zipObjectDeep(props, values) { + return baseZipObject(props || [], values || [], baseSet); + } + + module.exports = zipObjectDeep; + + +/***/ }), +/* 313 */ +/***/ (function(module, exports, __webpack_require__) { + + var assignValue = __webpack_require__(309), + castPath = __webpack_require__(214), + isIndex = __webpack_require__(99), + isObject = __webpack_require__(97), + toKey = __webpack_require__(221); + + /** + * The base implementation of `_.set`. + * + * @private + * @param {Object} object The object to modify. + * @param {Array|string} path The path of the property to set. + * @param {*} value The value to set. + * @param {Function} [customizer] The function to customize path creation. + * @returns {Object} Returns `object`. + */ + function baseSet(object, path, value, customizer) { + if (!isObject(object)) { + return object; + } + path = castPath(path, object); + + var index = -1, + length = path.length, + lastIndex = length - 1, + nested = object; + + while (nested != null && ++index < length) { + var key = toKey(path[index]), + newValue = value; + + if (index != lastIndex) { + var objValue = nested[key]; + newValue = customizer ? customizer(objValue, key, nested) : undefined; + if (newValue === undefined) { + newValue = isObject(objValue) + ? objValue + : (isIndex(path[index + 1]) ? [] : {}); + } + } + assignValue(nested, key, newValue); + nested = nested[key]; + } + return object; + } + + module.exports = baseSet; + + +/***/ }), +/* 314 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseRest = __webpack_require__(157), + unzipWith = __webpack_require__(301); + + /** + * This method is like `_.zip` except that it accepts `iteratee` to specify + * how grouped values should be combined. The iteratee is invoked with the + * elements of each group: (...group). + * + * @static + * @memberOf _ + * @since 3.8.0 + * @category Array + * @param {...Array} [arrays] The arrays to process. + * @param {Function} [iteratee=_.identity] The function to combine + * grouped values. + * @returns {Array} Returns the new array of grouped elements. + * @example + * + * _.zipWith([1, 2], [10, 20], [100, 200], function(a, b, c) { + * return a + b + c; + * }); + * // => [111, 222] + */ + var zipWith = baseRest(function(arrays) { + var length = arrays.length, + iteratee = length > 1 ? arrays[length - 1] : undefined; + + iteratee = typeof iteratee == 'function' ? (arrays.pop(), iteratee) : undefined; + return unzipWith(arrays, iteratee); + }); + + module.exports = zipWith; + + +/***/ }), +/* 315 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( handlerFunction ){ + var viewer = {}, + lastSelectedElement; + + viewer.handle = function ( selectedElement ){ + // Don't display details on a drag event, which will be prevented + if ( d3.event.defaultPrevented ) { + return; + } + + var isSelection = true; + + // Deselection of the focused element + if ( lastSelectedElement === selectedElement ) { + isSelection = false; + } + + if ( handlerFunction instanceof Function ) { + if ( isSelection ) { + handlerFunction(selectedElement); + } else { + handlerFunction(undefined); + } + } + + if ( isSelection ) { + lastSelectedElement = selectedElement; + } else { + lastSelectedElement = undefined; + } + }; + + /** + * Resets the displayed information to its default. + */ + viewer.reset = function (){ + if ( lastSelectedElement ) { + handlerFunction(undefined); + lastSelectedElement = undefined; + } + }; + + return viewer; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 316 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetOperatorNode = __webpack_require__(20); + + module.exports = function (){ + + var filter = {}, + nodes, + properties, + enabled = false, + filteredNodes, + filteredProperties, + filterTools = __webpack_require__(76)(); + + + /** + * If enabled, all set operators including connected properties are filtered. + * @param untouchedNodes + * @param untouchedProperties + */ + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + + if ( this.enabled() ) { + removeSetOperators(); + } + + filteredNodes = nodes; + filteredProperties = properties; + }; + + function removeSetOperators(){ + var filteredData = filterTools.filterNodesAndTidy(nodes, properties, isNoSetOperator); + + nodes = filteredData.nodes; + properties = filteredData.properties; + } + + function isNoSetOperator( node ){ + return !(node instanceof SetOperatorNode); + } + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }), +/* 317 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var SetOperatorNode = __webpack_require__(20); + var OwlThing = __webpack_require__(31); + var OwlNothing = __webpack_require__(30); + var elementTools = __webpack_require__(63)(); + + module.exports = function (){ + + var statistics = {}, + nodeCount, + occurencesOfClassAndDatatypeTypes = {}, + edgeCount, + occurencesOfPropertyTypes = {}, + classCount, + datatypeCount, + datatypePropertyCount, + objectPropertyCount, + propertyCount, + totalIndividualCount, + filteredNodes, + filteredProperties; + + + statistics.filter = function ( classesAndDatatypes, properties ){ + resetStoredData(); + + storeTotalCounts(classesAndDatatypes, properties); + storeClassAndDatatypeCount(classesAndDatatypes); + storePropertyCount(properties); + + storeOccurencesOfTypes(classesAndDatatypes, occurencesOfClassAndDatatypeTypes); + storeOccurencesOfTypes(properties, occurencesOfPropertyTypes); + + storeTotalIndividualCount(classesAndDatatypes); + + filteredNodes = classesAndDatatypes; + filteredProperties = properties; + }; + + function resetStoredData(){ + nodeCount = 0; + edgeCount = 0; + classCount = 0; + datatypeCount = 0; + datatypePropertyCount = 0; + objectPropertyCount = 0; + propertyCount = 0; + totalIndividualCount = 0; + } + + function storeTotalCounts( classesAndDatatypes, properties ){ + nodeCount = classesAndDatatypes.length; + + var seenProperties = __webpack_require__(62)(), i, l, property; + for ( i = 0, l = properties.length; i < l; i++ ) { + property = properties[i]; + if ( !seenProperties.has(property) ) { + edgeCount += 1; + } + + seenProperties.add(property); + if ( property.inverse() ) { + seenProperties.add(property.inverse()); + } + } + } + + function storeClassAndDatatypeCount( classesAndDatatypes ){ + // Each datatype should be counted just a single time + var datatypeSet = d3.set(), + hasThing = false, + hasNothing = false; + classCount = 0; + var old = 0, newcc = 0; + classesAndDatatypes.forEach(function ( node ){ + if ( elementTools.isDatatype(node) ) { + datatypeSet.add(node.defaultLabel()); + } else if ( !(node instanceof SetOperatorNode) ) { + if ( node instanceof OwlThing ) { + hasThing = true; + } else if ( node instanceof OwlNothing ) { + hasNothing = true; + } else { + old = classCount; + var adds = 1 + countElementArray(node.equivalents()); + classCount += adds; + newcc = classCount; + } + } else if ( node instanceof SetOperatorNode ) { + old = classCount; + classCount += 1; + newcc = classCount; + } + }); + + // count things and nothings just a single time + // classCount += hasThing ? 1 : 0; + // classCount += hasNothing ? 1 : 0; + + datatypeCount = datatypeSet.size(); + } + + function storePropertyCount( properties ){ + for ( var i = 0, l = properties.length; i < l; i++ ) { + var property = properties[i]; + var attr; + var result = false; + if ( property.attributes ) { + attr = property.attributes(); + if ( attr && attr.indexOf("datatype") !== -1 ) { + result = true; + } + } + if ( result === true ) { + datatypePropertyCount += getExtendedPropertyCount(property); + } else if ( elementTools.isObjectProperty(property) ) { + objectPropertyCount += getExtendedPropertyCount(property); + } + } + propertyCount = objectPropertyCount + datatypePropertyCount; + } + + function getExtendedPropertyCount( property ){ + // count the property itself + var count = 1; + + // and count properties this property represents + count += countElementArray(property.equivalents()); + count += countElementArray(property.redundantProperties()); + + return count; + } + + function countElementArray( properties ){ + if ( properties ) { + return properties.length; + } + return 0; + } + + function storeOccurencesOfTypes( elements, storage ){ + elements.forEach(function ( element ){ + var type = element.type(), + typeCount = storage[type]; + + if ( typeof typeCount === "undefined" ) { + typeCount = 0; + } else { + typeCount += 1; + } + storage[type] = typeCount; + }); + } + + function storeTotalIndividualCount( nodes ){ + var sawIndividuals = {}; + var totalCount = 0; + for ( var i = 0, l = nodes.length; i < l; i++ ) { + var individuals = nodes[i].individuals(); + + var tempCount = 0; + for ( var iA = 0; iA < individuals.length; iA++ ) { + if ( sawIndividuals[individuals[iA].iri()] === undefined ) { + sawIndividuals[individuals[iA].iri()] = 1; // this iri for that individual is now set to 1 >> seen it + tempCount++; + } + } + totalCount += tempCount; + } + totalIndividualCount = totalCount; + sawIndividuals = {}; // clear the object + + } + + + statistics.nodeCount = function (){ + return nodeCount; + }; + + statistics.occurencesOfClassAndDatatypeTypes = function (){ + return occurencesOfClassAndDatatypeTypes; + }; + + statistics.edgeCount = function (){ + return edgeCount; + }; + + statistics.occurencesOfPropertyTypes = function (){ + return occurencesOfPropertyTypes; + }; + + statistics.classCount = function (){ + return classCount; + }; + + statistics.datatypeCount = function (){ + return datatypeCount; + }; + + statistics.datatypePropertyCount = function (){ + return datatypePropertyCount; + }; + + statistics.objectPropertyCount = function (){ + return objectPropertyCount; + }; + + statistics.propertyCount = function (){ + return propertyCount; + }; + + statistics.totalIndividualCount = function (){ + return totalIndividualCount; + }; + + + // Functions a filter must have + statistics.filteredNodes = function (){ + return filteredNodes; + }; + + statistics.filteredProperties = function (){ + return filteredProperties; + }; + + + return statistics; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 318 */ +/***/ (function(module, exports, __webpack_require__) { + + var elementTools = __webpack_require__(63)(); + + module.exports = function (){ + + var filter = {}, + nodes, + properties, + enabled = false, + filteredNodes, + filteredProperties; + + + /** + * If enabled subclasses that have only subclass properties are filtered. + * @param untouchedNodes + * @param untouchedProperties + */ + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + + if ( this.enabled() ) { + hideSubclassesWithoutOwnProperties(); + } + + filteredNodes = nodes; + filteredProperties = properties; + }; + + function hideSubclassesWithoutOwnProperties(){ + var unneededProperties = [], + unneededClasses = [], + subclasses = [], + connectedProperties, + subclass, + property, + i, // index, + l; // length + + + for ( i = 0, l = properties.length; i < l; i++ ) { + property = properties[i]; + if ( elementTools.isRdfsSubClassOf(property) ) { + subclasses.push(property.domain()); + } + } + + for ( i = 0, l = subclasses.length; i < l; i++ ) { + subclass = subclasses[i]; + connectedProperties = findRelevantConnectedProperties(subclass, properties); + + // Only remove the node and its properties, if they're all subclassOf properties + if ( areOnlySubclassProperties(connectedProperties) && + doesNotInheritFromMultipleClasses(subclass, connectedProperties) ) { + + unneededProperties = unneededProperties.concat(connectedProperties); + unneededClasses.push(subclass); + } + } + + nodes = removeUnneededElements(nodes, unneededClasses); + properties = removeUnneededElements(properties, unneededProperties); + } + + /** + * Looks recursively for connected properties. Because just subclasses are relevant, + * we just look recursively for their properties. + * + * @param node + * @param allProperties + * @param visitedNodes a visited nodes which is used on recursive invocation + * @returns {Array} + */ + function findRelevantConnectedProperties( node, allProperties, visitedNodes ){ + var connectedProperties = [], + property, + i, + l; + + for ( i = 0, l = allProperties.length; i < l; i++ ) { + property = allProperties[i]; + if ( property.domain() === node || + property.range() === node ) { + + connectedProperties.push(property); + + + /* Special case: SuperClass <-(1) Subclass <-(2) Subclass ->(3) e.g. Datatype + * We need to find the last property recursively. Otherwise, we would remove the subClassOf + * property (1) because we didn't see the datatype property (3). + */ + + // Look only for subclass properties, because these are the relevant properties + if ( elementTools.isRdfsSubClassOf(property) ) { + var domain = property.domain(); + visitedNodes = visitedNodes || __webpack_require__(62)(); + + // If we have the range, there might be a nested property on the domain + if ( node === property.range() && !visitedNodes.has(domain) ) { + visitedNodes.add(domain); + var nestedConnectedProperties = findRelevantConnectedProperties(domain, allProperties, visitedNodes); + connectedProperties = connectedProperties.concat(nestedConnectedProperties); + } + } + } + } + + return connectedProperties; + } + + function areOnlySubclassProperties( connectedProperties ){ + var onlySubclassProperties = true, + property, + i, + l; + + for ( i = 0, l = connectedProperties.length; i < l; i++ ) { + property = connectedProperties[i]; + + if ( !elementTools.isRdfsSubClassOf(property) ) { + onlySubclassProperties = false; + break; + } + } + + return onlySubclassProperties; + } + + function doesNotInheritFromMultipleClasses( subclass, connectedProperties ){ + var superClassCount = 0; + + for ( var i = 0, l = connectedProperties.length; i < l; i++ ) { + var property = connectedProperties[i]; + + if ( property.domain() === subclass ) { + superClassCount += 1; + } + + if ( superClassCount > 1 ) { + return false; + } + } + + return true; + } + + function removeUnneededElements( array, removableElements ){ + var disjoint = [], + element, + i, + l; + + for ( i = 0, l = array.length; i < l; i++ ) { + element = array[i]; + if ( removableElements.indexOf(element) === -1 ) { + disjoint.push(element); + } + } + return disjoint; + } + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }) +/******/ ]); \ No newline at end of file diff --git a/doc/releases/0.1.0/parameters/webvowl/license.txt b/doc/releases/0.1.0/parameters/webvowl/license.txt new file mode 100644 index 0000000..008e54c --- /dev/null +++ b/doc/releases/0.1.0/parameters/webvowl/license.txt @@ -0,0 +1,21 @@ +The MIT License (MIT) + +Copyright (c) 2014-2019 Vincent Link, Steffen Lohmann, Eduard Marbach, Stefan Negru, Vitalis Wiens + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in +all copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN +THE SOFTWARE. diff --git a/doc/releases/0.1.0/provenance/provenance-en.html b/doc/releases/0.1.0/provenance/provenance-en.html new file mode 100644 index 0000000..91c5a2e --- /dev/null +++ b/doc/releases/0.1.0/provenance/provenance-en.html @@ -0,0 +1,18 @@ + + + + + + + + +
    +

    Provenance for Neuroelectrophysiology Analysis Ontology Documentation (http://purl.org/neao/0.1.0/)

    +
      +
    • Ontology created by: Cristiano Köhler (Forschungszentrum Jülich), Michael Denker (Forschungszentrum Jülich)
    • http://purl.org/neao/0.1.0/ is a specialization of the generic URI http://purl.org/neao/
      • +
    • The ontology documentation was the result of using the Widoco tool (which itself uses LODE for generating the crossreference section).
      • +
    • The documentation was generated at 2024-12-06
    +
    +

    back to documentation. TTL format

    + + \ No newline at end of file diff --git a/doc/releases/0.1.0/provenance/provenance-en.ttl b/doc/releases/0.1.0/provenance/provenance-en.ttl new file mode 100644 index 0000000..bd321cb --- /dev/null +++ b/doc/releases/0.1.0/provenance/provenance-en.ttl @@ -0,0 +1,14 @@ +@prefix prov: . +@prefix dc: . +@prefix foaf: . +@prefix : <> . + a prov:Entity; + dc:title "Neuroelectrophysiology Analysis Ontology"; + prov:wasAttributedTo ; + dc:creator ; + prov:wasAttributedTo ; + dc:creator ; + prov:wasAttributedTo ,; + prov:specializationOf ; + prov:wasGeneratedAt "2024-12-06"; +. diff --git a/doc/releases/0.1.0/resources/extra.css b/doc/releases/0.1.0/resources/extra.css new file mode 100644 index 0000000..16689d3 --- /dev/null +++ b/doc/releases/0.1.0/resources/extra.css @@ -0,0 +1,124 @@ +body { + text-align: justify; +} + +h1 { + line-height: 110%; +} + +.hlist { + border: 1px solid navy; + padding:5px; + background-color: #F4FFFF; +} + +.hlist li { + display: inline; + display: 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r=n[1]||n[2]||"";if(!r||""===u||this.rules.inline.punctuation.exec(u)){var i=n[0].length-1,s=i,l=0,a="*"===n[0][0]?this.rules.inline.emStrong.rDelimAst:this.rules.inline.emStrong.rDelimUnd;for(a.lastIndex=0,t=t.slice(-1*e.length+i);null!=(n=a.exec(t));)if(o=n[1]||n[2]||n[3]||n[4]||n[5]||n[6])if(o=o.length,n[3]||n[4])s+=o;else if((n[5]||n[6])&&i%3&&!((i+o)%3))l+=o;else if(!(0<(s-=o))){var o=Math.min(o,o+s+l);if(Math.min(i,o)%2)return D=e.slice(1,i+n.index+o),{type:"em",raw:e.slice(0,i+n.index+o+1),text:D,tokens:this.lexer.inlineTokens(D,[])};var D=e.slice(2,i+n.index+o-1);return{type:"strong",raw:e.slice(0,i+n.index+o+1),text:D,tokens:this.lexer.inlineTokens(D,[])}}}}},t.codespan=function(e){var t,u,n,e=this.rules.inline.code.exec(e);if(e)return n=e[2].replace(/\n/g," "),t=/[^ ]/.test(n),u=/^ /.test(n)&&/ 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    +
    + +

    Neuroelectrophysiology Analysis Ontology - Analysis Steps

    +

    Release: 2024-12-06

    + + +
    +
    This version:
    +
    http://purl.org/neao/0.1.0/steps#
    +
    Latest version:
    +
    http://purl.org/neao/steps#
    +
    Revision:
    +
    0.1.0
    +
    Issued on:
    +
    2024-12-06
    +
    Authors:
    +
    Cristiano Köhler, Forschungszentrum Jülich
    Michael Denker, Forschungszentrum Jülich
    + +
    License:
    https://creativecommons.org/licenses/by/4.0/ +
    Visualization:
    Visualize with WebVowl
    +
    + +Provenance of this page
    +
    +
    +
    +Ontology Specification Draft +
    +
    +
    + + +

    Introduction back to ToC

    +

    This module in the Neuroelectrophysiology Analysis Ontology (NEAO) contains classes that represent (atomic) steps in the analysis of neuroelectrophysiology data.

     +
    +

    Namespace declarations

    +
    + + + + + + + + + + + + + + + + + +
    Table 1: Namespaces used in the document
    biro<http://purl.org/spar/biro/>
    dcterms<http://purl.org/dc/terms/>
    neao_base<http://purl.org/neao/base#>
    neao_bib<http://purl.org/neao/bibliography#>
    neao_data<http://purl.org/neao/data#>
    neao_steps<http://purl.org/neao/steps#>
    owl<http://www.w3.org/2002/07/owl#>
    rdf<http://www.w3.org/1999/02/22-rdf-syntax-ns#>
    rdfs<http://www.w3.org/2000/01/rdf-schema#>
    skos<http://www.w3.org/2004/02/skos/core#>
    vann<http://purl.org/vocab/vann/>
    xml<http://www.w3.org/XML/1998/namespace>
    xsd<http://www.w3.org/2001/XMLSchema#>
    +
    +
    +
    + + + +

    NEAO Analysis Steps: Overview back to ToC

    + +This ontology has the following classes and properties. +

    Classes

    +

    Object Properties

    Data Properties

    +
    + + + +

    NEAO Analysis Steps: Description back to ToC

    + +

    The main classes are subclasses of the AnalysisStep class (defined in the base module), and represent the different methods and procedures used in the analysis to generate new data or to perform specific operations aimed to transform or extract additional information from the input(s). The classes are organized in a taxonomy, and the lowest level of the hierarchy represent specific, fine-grained descriptions of a step used in the analysis.

    + +

    Grouping classes are provided to identify analysis steps according to their semantic similarities. This is used to keep the fine-grained descriptions associated with specific analysis methods (e.g., a step that used either the Welch or multitaper method to compute the power spectral density) while providing the ability to identify the steps in a more general nature (e.g., a step that computed a power spectral density). The grouping classes are defined in the taxonomy hierarchy by subclasses, and also as classes inferred by reasoning with the hasPurpose object property (that points to individuals of the AnalysisPurpose class, such as FunctionalConnectivityPurpose) or data properties defining boolean values (e.g., isBivariate). Therefore, groupings across multiple semantic dimensions are available (e.g., bivariate analyses or functional connectivity analyses).

    + +

    The information regarding the inputs and outputs can be associated with each step by the hasInput and hasOutput object properties that point to individuals that represent data entities (using the classes defined in the data module).

    + +

    The parameters used to control the behavior of the analysis step are defined with the usesParameter object property that points to individuals that represent specific parameters (using the classes defined in the parameters module).

    + +

    The relevant bibliographic references are provided with the hasBibliographicReference annotation property that points to individuals of the biro:BibliographicReference class (defined in the bibliography module). This structures the specific information associated with the analysis step represented by the class, and helps to disambiguate the description of the diversity of methods that are available to analyze neuroelectrophysiology data. This would be the case, for example, of different algorithms and assumptions (e.g., computing the power spectral density using either the Welch or multitaper approach), and the evolution/modifications of a method (e.g., different computations of phase lag index estimates).

    + +

    The details of the software code associated with each analysis step can be provided by the isImplementedIn object property, that points to individuals of the SoftwareImplementation class (defined in the base module).

    + +

    Finally, the hasSubstep object property is used to describe compound analyses. These analyses involve the execution of multiple smaller steps (substeps) that are associated with specific parameters and intermediary data inputs and outputs. The main compound process can point to other individuals of the AnalysisStep class using the hasSubstep property. Therefore, the appropriate semantic information and description associated with either the compound analysis or each individual substep can be provided in the ontology.

    + + + +

    Cross-reference for NEAO Analysis Steps classes, object properties and data properties back to ToC

    +This section provides details for each class and property defined by NEAO Analysis Steps. +
    +

    Classes

    + +
    +

    analysis purposec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#AnalysisPurpose

    +
    + Analysis purpose refers to the specific objective or goal that an analysis is intended to achieve. It outlines what the analysis step aims to discover, understand, or demonstrate. This class is intended for grouping steps that perform analyses with similar goals/outputs but with distinct methodological or algorithmic approaches. It is used as a normalization class via the hasPurpose object property. +
    +
    +
    is in range of
    +
    + has purpose + op +
    +
    has members
    +
    + correlation purpose + ni, data smoothing purpose + ni, distance purpose + ni, field-field coupling purpose + ni, functional connectivity purpose + ni, instantaneous firing rate purpose + ni, latent dynamics purpose + ni, neural synchronization purpose + ni, neuronal firing regularity purpose + ni, spike-field coupling purpose + ni, spike-spike coupling purpose + ni +
    +
    +
    +
    +

    apply adaptive kernel smoothingc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyAdaptiveKernelSmoothing

    +
    + A kernel smoothing that uses a variable-width kernel. The kernel width varies adaptively depending on the local density of the data. This method takes into consideration local variations in data density, resulting in a more accurate representation of the underlying patterns and structures. +
    +
    +
    has super-classes
    +
    + kernel smoothing + c +
    +
    +
    +
    +

    apply analytic signal conversionc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyAnalyticSignalConversion

    +
    + A data transformation that uses the Hilbert transform of a real-valued input time series to construct the analytic signal, a complex-valued time series where the real part is the original real-valued signal and the imaginary part is the Hilbert transform. The analytic signal does not have negative frequency components. +
    +
    +
    has super-classes
    +
    + data transformation + c +
    +
    +
    +
    +

    apply Butterworth filterc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyButterworthFilter

    +
    + An infinite impulse response filtering that uses a Butterworth type filter, i.e., a filter designed to have a maximally flat frequency response in the passband (no ripples). The frequency response gradually decreases to zero in the stopband, and the steepness of the decrease (roll-off) is controlled by the order of the filter. +
    +
    +
    has super-classes
    +
    + infinite impulse response filtering + c +
    +
    +
    +
    +

    apply canonical polyadic tensor decompositionc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyCanonicalPolyadicTensorDecomposition

    +
    + A tensor component analysis (TCA) that expresses the input high-dimensional tensor as a sum of rank-one tensors (tensor components). Each dimension in the tensor component corresponds to a dimension in the input high-dimensional tensor. For neural data, a tensor could be used to represent trial-by-trial spiking activity, with neurons, time, and trials as dimensions. Therefore, each tensor component produced from that input will have a rank-one tensor for the neurons, time, and trial, which describes both within- and between-trial changes. +
    +
    +
    has super-classes
    +
    + tensor component analysis + c +
    +
    is disjoint with
    +
    + apply coupled canonical polyadic tensor decomposition + c, apply non-negative tensor component analysis + c +
    +
    +
    +
    +

    apply coupled canonical polyadic tensor decompositionc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyCoupledCanonicalPolyadicTensorDecomposition

    +
    + A tensor component analysis (TCA) that expresses multiple high-dimensional input tensors as a sum of rank one tensors (tensor components). The output tensor components have shared vectors that summarize an input dimension across all input tensors. For example, if analyzing two tensors, each representing trial-by-trial spiking activity obtained from a distinct experimental subject (neurons X time X trials), the coupled canonical polyadic tensor decomposition (CCPD) could produce tensor components for each dataset where the vector for the trial and time dimensions are the same, but the neuron dimension is unique for each dataset (hence, each subject). Therefore, CCPD is useful for scenarios with multiple and related datasets, allowing for the exploitation of shared information to enhance the decomposition results. +
    +
    +
    has super-classes
    +
    + tensor component analysis + c +
    +
    is disjoint with
    +
    + apply canonical polyadic tensor decomposition + c, apply non-negative tensor component analysis + c +
    +
    +
    +
    +

    apply data concatenationc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyDataConcatenation

    +
    + A data transformation that joins two or more data inputs into a single data element. For example, in a multitrial experimental session, where data was acquired separately as one epoch per trial, a continuous data segment for the session can be constructed by concatenating all trial epochs together. +
    +
    +
    has super-classes
    +
    + data transformation + c +
    +
    +
    +
    +

    apply demixed principal component analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyDemixedPrincipalComponentAnalysis

    +
    + A principal component analysis (PCA) that uses a modified version of the standard PCA for neural activity data analysis. Demixed PCA (dPCA) not only obtains a low-dimensional representation of the input data, but it also demixes the dependencies of the population activity on the task parameters. Therefore, dPCA can show the dependence of the neural representation on parameters such as stimuli, subject decisions, or rewards. +
    +
    +
    has super-classes
    +
    + principal component analysis + c +
    +
    is disjoint with
    +
    + apply probabilistic principal component analysis + c, apply standard principal component analysis + c +
    +
    +
    +
    +

    apply discrete Fourier transformc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyDiscreteFourierTransform

    +
    + A frequency-domain transformation that applies the discrete Fourier transform (DFT) to an input time series acquired in equally-spaced samples. The DFT is used to obtain the frequency representation of the time-domain input. The DFT output is a sequence of coefficients of complex sinusoids, each representing a frequency component in the input signal. Each frequency component consists of an interval (or bin), and the width of the bin determines the frequency resolution of the DFT. The number of frequency components and the frequency resolution is determined by the length of the input signal (number of samples) and the sampling frequency. For large datasets, the computation is computationally expensive (O(N^2) complexity). +
    +
    +
    has super-classes
    +
    + frequency domain transformation + c +
    +
    has sub-classes
    +
    + apply fast Fourier transform + c +
    +
    +
    +
    +

    apply discrete Fourier transform noise removalc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyDFTNoiseRemoval

    +
    + A line noise removal that uses a discrete Fourier transform (DFT) filter and estimates the power line component amplitude in the input data by fitting a sine and cosine at a user-specified line noise frequency (e.g., 50 Hz), followed by the subtraction of those components from the input. +
    +
    +
    has super-classes
    +
    + line noise removal + c +
    +
    +
    +
    +

    apply distance covariance analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyDistanceCovarianceAnalysis

    +
    + A dimensionality reduction that identifies linear and nonlinear relationships between multiple input datasets. The method identifies linear projections (DCA dimensions) that maximize the distance covariance statistic (an Euclidean-based correlational statistic). For example, for recordings from different brain regions (two neuronal populations), the distance covariance analysis (DCA) can identify the dimensions in the population activity in the different brain areas that are related to each other. The dimensionality reduction can also take other dependent variables into account (e.g., stimulus or behavioral variables). +
    +
    +
    has super-classes
    +
    + dimensionality reduction + c +
    +
    +
    +
    +

    apply downsamplingc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyDownsampling

    +
    + A resampling that reduces the number of samples in the input data (i.e., reduces the sampling frequency). This is often accomplished after applying an anti-aliasing filter (i.e., to remove frequencies above half the value of the new sampling frequency). +
    +
    +
    has super-classes
    +
    + resampling + c +
    +
    is disjoint with
    +
    + apply upsampling + c +
    +
    +
    +
    +

    apply fast Fourier transformc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyFastFourierTransform

    +
    + A frequency-domain transformation that uses the fast Fourier transform (FFT) algorithm to compute the discrete Fourier transform (DFT). The computation of the DFT is computationally expensive for large datasets. The FFT reduces the number of computations significantly by using a divide-and-conquer approach, leveraging the symmetry and periodicity properties of the DFT. The complexity is O(N log N). The output of the method is similar to the DFT, i.e., a sequence of coefficients of complex sinusoids, each representing a frequency component in the input signal. The FFT takes a size parameter, that refers to the number of points in the input data sequence that is used for the computation. The FFT size determines the frequency resolution, and, for maximal efficiency, should be a multiple of 2. +
    +
    +
    has super-classes
    +
    + apply discrete Fourier transform + c +
    +
    +
    +
    +

    apply finite impulse response filterc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyFiniteImpulseResponseFilter

    +
    + A finite impulse response (FIR) filtering where a custom-designed FIR filter is applied to the input data. +
    +
    +
    has super-classes
    +
    + finite impulse response filtering + c +
    +
    +
    +
    +

    apply finite impulse response filter with Kaiser windowc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyFiniteImpulseResponseFilterKaiserWindow

    +
    + A finite impulse response (FIR) filtering that uses a FIR filter whose impulse response is controlled by applying a Kaiser window function. +
    +
    +
    has super-classes
    +
    + finite impulse response filtering + c +
    +
    +
    +
    +

    apply fixed kernel smoothingc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyFixedKernelSmoothing

    +
    + A kernel smoothing that uses a fixed-width kernel. The kernel type and kernel width can be specified as parameters. +
    +
    +
    has super-classes
    +
    + kernel smoothing + c +
    +
    +
    +
    +

    apply general linear model polynomial detrendingc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyGeneralLinearModelPolynomialDetrending

    +
    + A detrending that uses a general linear model to fit a polynomial from the input data and remove the mean and linear trend. +
    +
    +
    has super-classes
    +
    + detrending + c +
    +
    +
    +
    +

    apply Hilbert transformc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyHilbertTransform

    +
    + A data transformation that applies the Hilbert transform to a real-valued time series. The Hilbert transform shifts the phase of each frequency component of the signal by 90 degrees: positive frequencies are shifted by -90 degrees, and negative frequencies are shifted by +90 degrees. This can be used to construct the analytic signal. +
    +
    +
    has super-classes
    +
    + data transformation + c +
    +
    +
    +
    +

    apply independent component analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyIndependentComponentAnalysis

    +
    + A data transformation that separates a multivariate input signal into additive subcomponents (independent components). The independent components are statistically independent from each other. +
    +
    +
    has super-classes
    +
    + data transformation + c +
    +
    +
    +
    +

    apply infinite impulse response filterc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyInfiniteImpulseResponseFilter

    +
    + An infinite impulse response (IIR) filtering where a custom-designed IIR filter is applied to the input data. +
    +
    +
    has super-classes
    +
    + infinite impulse response filtering + c +
    +
    +
    +
    +

    apply interpolationc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyInterpolation

    +
    + A data transformation that estimates new (intermediate) values between the known values in the input data. This can be accomplished using several methods, such as linear interpolation (i.e., estimating the values along a straight line connecting adjacent points), polynomial interpolation (i.e., using polynomials to estimate the values between points), or spline Interpolation (i.e., using piecewise polynomials that pass through the known data points and provide a smooth curve). +
    +
    +
    has super-classes
    +
    + data transformation + c +
    +
    has sub-classes
    +
    + apply spike waveform interpolation + c +
    +
    +
    +
    +

    apply linear discriminant analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyLinearDiscriminantAnalysis

    +
    + A dimensionality reduction that finds a linear combination of features that separates two or more classes defined in the input data. The input data must have a variable that defines the class for each observation, and continuous variables that are used for the linear discriminant analysis (LDA). LDA finds an optimal projection vector that maximizes the distance between the means of the different classes, and minimizes the variance within each class. LDA projects the input data into the lower-dimensional space, therefore reducing the number of features while retaining the information needed for classification. The optimal projection vectors found by LDA are the Fisher linear discriminants. +
    +
    +
    has super-classes
    +
    + dimensionality reduction + c +
    +
    +
    +
    +

    apply local linear regression detrendingc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyLocalLinearRegressionDetrending

    +
    + A detrending that removes a running line fit using local linear regression. Local linear regression estimates a function by fitting a low-order polynomial to data within a sliding window (local neighborhood) across the input data. +
    +
    +
    has super-classes
    +
    + detrending + c +
    +
    +
    +
    +

    apply local regression and likelihood smoothingc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyLocalRegressionAndLikelihoodSmoothing

    +
    + A data smoothing that estimates a low-order polynomial in a local neighborhood (window) of any value in the input data. Polynomial coefficients are estimated using the least mean squares method. Contrary to kernel smoothing methods, this is a non-parametric approach and has reduced bias at the boundaries of the input data. +
    +
    +
    has super-classes
    +
    + data smoothing + c +
    +
    +
    +
    +

    apply median rescalingc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyMedianRescaling

    +
    + A data normalization that uses the median and interquartile range (IQR) to rescale the values of the input data. This method is less sensitive to outliers (compared to the z-score transform), and therefore is known as robust scaling. +
    +
    +
    has super-classes
    +
    + data normalization + c +
    +
    +
    +
    +

    apply min-max normalizationc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyMinMaxNormalization

    +
    + A data normalization that adjusts the range and distribution of values in the data input such that they fall within a fixed range, based on the minimum and maximum values in the input data. In the typical case, the values are normalized to the [0, 1] interval. +
    +
    +
    has super-classes
    +
    + data normalization + c +
    +
    +
    +
    +

    apply movement artifact removalc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyMovementArtifactRemoval

    +
    + An artifact removal that identifies and removes artifacts originating from movements of the experimental subject (e.g., eye movement, head movement). +
    +
    +
    has super-classes
    +
    + artifact removal + c +
    +
    +
    +
    +

    apply neural trajectory Gaussian process factor analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyNeuralTrajectoryGaussianProcessFactorAnalysis

    +
    + A dimensionality reduction that uses the Gaussian process factor analysis (GPFA) method described by Yu et al. (2009). GPFA extracts smooth, low-dimensional neural trajectories that summarize the activity recorded simultaneously from many neurons on individual experimental trials over time. The input is a set of spike trains representing multitrial activity of multiple neurons recorded in parallel. The input spike trains are binned, and factor analysis is applied to reduce the dimensionality while smoothing the resulting low-dimensional trajectories by fitting a Gaussian process (GP) model to them. The identified trajectories are called neural trajectories, and show the evolution of the activity of the population of neurons over time. +
    +
    +
    has super-classes
    +
    + dimensionality reduction + c +
    +
    +
    +
    +

    apply non-negative tensor component analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyNonNegativeTensorComponentAnalysis

    +
    + A tensor component analysis (TCA) where a non-negative constraint is applied to the decomposition. This is desirable when the underlying components have physical interpretation and negative values are not possible. +
    +
    +
    has super-classes
    +
    + tensor component analysis + c +
    +
    is disjoint with
    +
    + apply canonical polyadic tensor decomposition + c, apply coupled canonical polyadic tensor decomposition + c +
    +
    +
    +
    +

    apply notch filterc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyNotchFilter

    +
    + An infinite impulse response filtering that uses a filter designed to attenuate or eliminate a narrow band of frequencies in the input data (stopband) while allowing other frequencies to pass through relatively unaffected. +
    +
    +
    has super-classes
    +
    + infinite impulse response filtering + c +
    +
    +
    +
    +

    apply notch filter noise removalc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyNotchFilterNoiseRemoval

    +
    + A line noise removal that employs a notch filter to remove line noise. A notch filter is designed to attenuate or eliminate a narrow band of frequencies in the input data (stopband) while allowing other frequencies to pass through relatively unaffected. The notch filter stop band is usually centered at the power line frequency (i.e., 50 Hz or 60 Hz depending on the location). +
    +
    +
    has super-classes
    +
    + line noise removal + c +
    +
    +
    +
    +

    apply outlier removalc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyOutlierRemoval

    +
    + An artifact removal that identifies and removes values in the input data that differs significantly from other values (outliers). Outliers may arise from the variability in the measurement or be the result of experimental error. +
    +
    +
    has super-classes
    +
    + artifact removal + c +
    +
    +
    +
    +

    apply paddingc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyPadding

    +
    + A data transformation that adds extra data (often zeros or other predefined values) to the beginning, end, or both sides of the input data. +
    +
    +
    has super-classes
    +
    + data transformation + c +
    +
    +
    +
    +

    apply probabilistic principal component analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyProbabilisticPrincipalComponentAnalysis

    +
    + A principal component analysis (PCA) that assumes a probabilistic model for the generation of the observed data, according to Tipping & Bishop (1999). The model assumes that the values in the data input are generated from the lower-dimensional subspace of latent variables (principal components) plus an additive Gaussian noise. This generalizes the standard PCA for the case where the noise covariance approaches zero. The probabilistic PCA (pPCA) allows for uncertainty estimation and modeling of the data generation process, and can be employed when there are missing values in the input data. +
    +
    +
    has super-classes
    +
    + principal component analysis + c +
    +
    is disjoint with
    +
    + apply demixed principal component analysis + c, apply standard principal component analysis + c +
    +
    +
    +
    +

    apply rectificationc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyRectification

    +
    + A data transformation that computes the absolute value of the input data (rectification). +
    +
    +
    has super-classes
    +
    + data transformation + c +
    +
    +
    +
    +

    apply rereferencec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyRereference

    +
    + A data transformation that changes the reference point of the data recorded from an electrode. This can be performed by calculating the average across the data obtained from all electrodes and subtracting it from each individual electrode’s data (reducing common noise) or referencing each electrode to its nearest neighbor or a defined pair, subtracting one signal from another (bipolar referencing). +
    +
    +
    has super-classes
    +
    + data transformation + c +
    +
    +
    +
    +

    apply spectrum interpolation noise removalc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplySpectrumInterpolationNoiseRemoval

    +
    + A line noise removal that uses spectral interpolation to remove power line noise. After obtaining the discrete Fourier transform (DFT) of the input signal with noise, the original frequency component at the power line oscillation frequency can be estimated by interpolating the amplitude spectrum (obtained from the DFT) at the power line frequency (e.g., 50 Hz), followed by the inverse DFT to reconstruct the signal. +
    +
    +
    has super-classes
    +
    + line noise removal + c +
    +
    +
    +
    +

    apply spike extraction from time seriesc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplySpikeExtractionFromTimeSeries

    +
    + A data transformation that obtains a series of spike times (i.e., a spike train) from an input time series (e.g., voltages recorded from an electrode). The spike times can be estimated, for example, by taking all the time points where the values in the input data are greater or lower than a threshold value. +
    +
    +
    has super-classes
    +
    + data transformation + c +
    +
    +
    +
    +

    apply spike train binarizationc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplySpikeTrainBinarization

    +
    + A data transformation that takes an input spike train and returns an array of boolean values indicating if at least one spike occurred at individual time points. +
    +
    +
    has super-classes
    +
    + data transformation + c +
    +
    +
    +
    +

    apply spike train binningc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplySpikeTrainBinning

    +
    + A data transformation that performs a binning operation on the input spike train data. The transformation discretizes the duration of the input spike train(s) into smaller time intervals (bins), and obtains the number of spikes occurring into each bin (binned spike train). Additionally, the occurrence of spikes into each bin can be converted into a binary form (i.e., bins with or without spikes). This is known as clipping. The width of the bin interval is specified by a parameter (bin size). +
    +
    +
    has super-classes
    +
    + data transformation + c +
    +
    +
    +
    +

    apply spike waveform interpolationc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplySpikeWaveformInterpolation

    +
    + A data transformation that estimates additional (unknown) values between sample points of a spike waveform input. +
    +
    +
    has super-classes
    +
    + apply interpolation + c +
    +
    +
    +
    +

    apply spike waveform outlier rejectionc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplySpikeWaveformOutlierRejection

    +
    + An artifact removal that identifies and removes spike waveforms that differ significantly from the other spike waveforms in the input. This usually involves identifying waveforms with too late peaks, or in which the rising phase of the potential does not align with the peaks of all other waveforms in the input. +
    +
    +
    has super-classes
    +
    + artifact removal + c +
    +
    +
    +
    +

    apply spike waveform peak alignmentc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplySpikeWaveformPeakAlignment

    +
    + A data transformation that modifies input spike waveforms in order to align their peak values in time. +
    +
    +
    has super-classes
    +
    + data transformation + c +
    +
    +
    +
    +

    apply standard principal component analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyStandardPrincipalComponentAnalysis

    +
    + A principal component analysis (PCA) that operates by computing the covariance matrix of the input data, which is then decomposed into its eigenvectors and eigenvalues. The eigenvectors, corresponding to the principal components (PCs), are sorted by the magnitude of their associated eigenvalues. The eigenvectors with the largest eigenvalues explain the most variance in the data and thus form the primary PCs. +
    +
    +
    has super-classes
    +
    + principal component analysis + c +
    +
    is disjoint with
    +
    + apply demixed principal component analysis + c, apply probabilistic principal component analysis + c +
    +
    +
    +
    +

    apply stimulation artifact removalc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyStimulationArtifactRemoval

    +
    + An artifact removal that identifies and removes artifacts originating from presenting a stimulus during the recording (e.g., electrical stimulation). +
    +
    +
    has super-classes
    +
    + artifact removal + c +
    +
    +
    +
    +

    apply sumc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplySum

    +
    + A data transformation that performs the addition of two or more data inputs to obtain a sum. +
    +
    +
    has super-classes
    +
    + data transformation + c +
    +
    +
    +
    +

    apply synchronous spike removalc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplySynchronousSpikeRemoval

    +
    + An artifact removal that identifies and removes spikes across two or more spike train inputs that occurred simultaneously within a temporal precision specified by a parameter. The temporal precision is usually the sampling rate used by the recording equipment: if different neurons fired within an interval equal to or smaller than the sampling period, this suggests that this synchronous activity does not come from temporal synchronization of the neurons but rather due to an interference in the recording (e.g., electrical noise picked simultaneously by multiple channels). +
    +
    +
    has super-classes
    +
    + artifact removal + c +
    +
    +
    +
    +

    apply Thomson regression noise removalc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyThomsonRegressionNoiseRemoval

    +
    + A line noise removal that uses Thomson's regression method (1982) for detecting sinusoids, that identifies and removes significant sine waves from the input data. The desired frequencies can be specified by parameter, or determined using an F-statistic. +
    +
    +
    has super-classes
    +
    + line noise removal + c +
    +
    +
    +
    +

    apply trial extractionc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyTrialExtraction

    +
    + A data transformation that extracts trial segments from an input data entity storing a longer and continuous data stream. A trial is a single instance of a repeated experimental procedure. For example, during an electrophysiology experiment, a visual stimulus might be presented several times, with neural activity recorded each time. Each presentation of the stimulus defines a trial. Since the data is recorded continuously, this data transformation identifies and isolates the segments of data corresponding to each individual stimulus presentation, returning them as separate data entities. +
    +
    +
    has super-classes
    +
    + data transformation + c +
    +
    +
    +
    +

    apply upsamplingc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyUpsampling

    +
    + A resampling that increases the number of samples in the data (i.e., increases the sampling frequency). This is often accomplished by adding new (zero-valued) samples between existing ones followed by applying a lowpass filter to replace the zeros and smooth out the discontinuities. +
    +
    +
    has super-classes
    +
    + resampling + c +
    +
    is disjoint with
    +
    + apply downsampling + c +
    +
    +
    +
    +

    apply windowed-sinc filterc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyWindowedSincFilter

    +
    + A finite impulse response filtering that employs the convolution with a sinc function kernel multiplied by a window function (e.g., Blackman or Hamming). The kernel is obtained by evaluating the sinc function for the cutoff frequencies specified as parameters, followed by truncation of the filter skirt, and applying the window to reduce the artifacts introduced from the truncation. The windowed-sinc filter is stable and very efficient to separate one band of frequencies from another. +
    +
    +
    has super-classes
    +
    + finite impulse response filtering + c +
    +
    +
    +
    +

    apply z-score transformc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ApplyZscoreTransform

    +
    + A data normalization that transforms the values of the input data to have zero mean and unit variance. +
    +
    +
    has super-classes
    +
    + data normalization + c +
    +
    +
    +
    +

    artifact removalc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ArtifactRemoval

    +
    + A data transformation that aims to identify and remove artifacts from the input data. Artifacts are unwanted disturbances that distorts the data. In an electrophysiology experiment, they can arise from various sources: environmental interference (e.g., electromagnetic interference from nearby equipment), physiological processes (e.g., eye movement, heart beat), and technical instrumentation issues (e.g., baseline drift of the recorded potentials). +
    +
    +
    has super-classes
    +
    + data transformation + c +
    +
    has sub-classes
    +
    + apply movement artifact removal + c, apply outlier removal + c, apply spike waveform outlier rejection + c, apply stimulation artifact removal + c, apply synchronous spike removal + c +
    +
    +
    +
    +

    artificial data generationc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ArtificialDataGeneration

    +
    + A data generation that produces artificial data. Artificial data refers to data that is generated programmatically rather than obtained from experimental recordings (e.g., neural simulations or by using specific statistical procedures). The artificial data generation procedure does not take experimentally-recorded data as input, and the generation of the output data depends only on parameters to the method employed. The isArtificial data property is defined as True for outputs of artificial data generation steps. +
    +
    +
    is equivalent to
    +
    + has output + op + some + artificial data + c +
    +
    has super-classes
    +
    + data generation + c +
    +
    +
    +
    +

    ASSET analysis probability matrix substepc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ASSETAnalysisProbabilityMatrixSubstep

    +
    + ASSET analysis substep that computes the probability matrix (PMAT). The probability matrix contains, for each entry in the intersection matrix, the cumulative probability representing the probability of having the overlap in the IMAT under the assumption that the spike trains are independent. If an entry in the PMAT is large, the null hypothesis of independence is rejected, and the alternative hypothesis that the observed overlap reflects active synchronization between the involved neurons at the time bins of the intersection is accepted. The PMAT computation can be done with either an analytical or Monte Carlo approach. +
    +
    +
    has super-classes
    +
    + ASSET analysis substep + c +
    +
    has sub-classes
    +
    + compute ASSET probability matrix (Monte Carlo method) + c, compute ASSET probability matrix (analytical method) + c +
    +
    +
    +
    +

    ASSET analysis substepc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ASSETAnalysisSubstep

    +
    + An analysis step that is an individual part of the ASSET analysis method to identify neuronal activity patterns in spike train data. +
    +
    +
    has super-classes
    +
    + analysis step + c +
    +
    has sub-classes
    +
    + ASSET analysis probability matrix substep + c, compute ASSET cluster matrix + c, compute ASSET intersection matrix + c, compute ASSET joint probability matrix + c, compute ASSET mask matrix + c, compute ASSET sequence of synchronous events extraction + c +
    +
    +
    +
    +

    autocorrelation analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#AutocorrelationAnalysis

    +
    + An analysis step used to compute a measure of autocorrelation, i.e., the correlation of the input with displaced (lagged or advanced) versions of itself. The computation produces the autocorrelation value for every lag considered. +
    +
    +
    has super-classes
    +
    + analysis step + c +
    +
    has sub-classes
    +
    + compute autocorrelation function + c, compute spike train autocorrelation histogram + c +
    +
    +
    +
    +

    bivariate analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#BivariateAnalysis

    +
    + An analysis step that has only two distinct inputs considered for the computation of the output (e.g., the two time series with the local field potential recorded from two electrodes used to compute a cross-correlation). +
    +
    +
    is equivalent to
    +
    + is bivariate + dp + value true
    +
    has super-classes
    +
    + analysis step + c +
    +
    is disjoint with
    +
    + multivariate analysis + c +
    +
    +
    +
    +

    central tendency statistical analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#CentralTendencyStatisticalAnalysis

    +
    + A statistical analysis to compute a measure of central tendency, i.e., that represents the center or typical value of the input data. +
    +
    +
    has super-classes
    +
    + statistical analysis + c +
    +
    has sub-classes
    +
    + compute mean + c, compute median + c +
    +
    +
    +
    +

    coherence analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#CoherenceAnalysis

    +
    + A spectral analysis that computes a measure of coherence between two or more inputs. Coherence is a real measure that describes the linear association of the distinct inputs (e.g., two time series) in different frequency bands. It corresponds to the absolute value of the coherency. +
    +
    +
    has super-classes
    +
    + spectral analysis + c +
    +
    has sub-classes
    +
    + compute canonical coherence + c, compute coherence + c, compute partial coherence + c +
    +
    +
    +
    +

    coherency analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#CoherencyAnalysis

    +
    + A spectral analysis that computes a measure of coherency between two inputs. Coherency is a complex-valued measure that describes the linear association of the distinct inputs (e.g., two time series) in different frequency bands. +
    +
    +
    has super-classes
    +
    + spectral analysis + c +
    +
    has sub-classes
    +
    + compute coherency + c, compute imaginary coherency + c, compute maximized imaginary coherency + c +
    +
    +
    +
    +

    compound analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#CompoundAnalysis

    +
    + An analysis step that is composed by two or more substeps, each performing a part of the analysis with its own data inputs/outputs and analysis parameters. +
    +
    +
    is equivalent to
    +
    + has substep + op + some + analysis step + c +
    +
    has super-classes
    +
    + analysis step + c +
    +
    +
    +
    +

    compute angular mean of spike phasesc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeAngularMeanSpikePhases

    +
    + A phase analysis that computes the angle obtained from averaging the phases of an input signal at the time points where spikes occurred. For the computation, the phases are represented as vectors in the unit circle, the mean phase vector is computed, and the angle is extracted. +
    +
    +
    has super-classes
    +
    + phase analysis + c +
    +
    +
    +
    +

    compute ASSET cluster matrixc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeASSETClusterMatrix

    +
    + ASSET analysis substep that computes the cluster matrix (CMAT) in the ASSET analysis, using DBSCAN with a modified distance metric. It takes the mask matrix (MMAT) as input. The cluster matrix groups the significant entries in the MMAT according to each diagonal structure that they belong to. For each significant entry in the MMAT, the CMAT will have an integer value: -1 for significant entries that do not belong to any diagonal structure, or any value greater than zero with the identification of the cluster that the entry belongs to. +
    +
    +
    has super-classes
    +
    + ASSET analysis substep + c +
    +
    +
    +
    +

    compute ASSET intersection matrixc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeASSETIntersectionMatrix

    +
    + ASSET analysis substep that computes the intersection matrix (IMAT). For a set of input spike trains, binned with a bin width, each entry in the IMAT corresponds to a pair of distinct bins (i.e., distinct time points in the data). The value in the entry corresponds to the number of neurons that fired in both bins corresponding to that entry. When groups of neurons fire in a sequence that repeats in time, the IMAT will show patterns that follow a diagonal direction (diagonal structure). The ASSET method aims to identify the diagonal structures by automated statistical testing and clustering procedures. +
    +
    +
    has super-classes
    +
    + ASSET analysis substep + c +
    +
    +
    +
    +

    compute ASSET joint probability matrixc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeASSETJointProbabilityMatrix

    +
    + ASSET analysis substep that computes the joint probability matrix (JMAT). For every entry in the probability matrix (PMAT), the computation produces the combined probability of a fixed number of neighbors in a rectangular kernel (with fixed length and width as parameters) covering a diagonal structure. A value in the JMAT reflects how likely entries with high probability in the PMAT are to be located in the same diagonal structure. +
    +
    +
    has super-classes
    +
    + ASSET analysis substep + c +
    +
    +
    +
    +

    compute ASSET mask matrixc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeASSETMaskMatrix

    +
    + ASSET analysis substep that computes the mask matrix (MMAT). The parameters are the threshold values that are used to determine if the entries in the probability matrix (PMAT) and joint probability matrix (JMAT) are significant. Entry significance in either matrix is defined as a probability value greater than the provided threshold value. Significant entries in both probability and joint probability matrices are defined as 1 in the mask matrix. +
    +
    +
    has super-classes
    +
    + ASSET analysis substep + c +
    +
    +
    +
    +

    compute ASSET probability matrix (analytical method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeASSETProbabilityMatrixAnalytical

    +
    + ASSET analysis probability matrix substep that computes the probability matrix (PMAT) using the assumption that the input spike trains are independent and Poisson. The computation can take as input the firing rate profiles of the spike trains used for the intersection matrix (IMAT), or those will be automatically computed using convolution with a boxcar kernel of specified width. The probability distribution of the value in the intersection matrix (IMAT) is approximated by a Poisson distribution computed using LeCam's approximation. The output is a matrix with the cumulative probabilities representing the probability of having each overlap in the IMAT strictly lower than the observed overlap, under the null hypothesis of independence of the input spike trains. +
    +
    +
    has super-classes
    +
    + ASSET analysis probability matrix substep + c +
    +
    is disjoint with
    +
    + compute ASSET probability matrix (Monte Carlo method) + c +
    +
    +
    +
    +

    compute ASSET probability matrix (Monte Carlo method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeASSETProbabilityMatrixMonteCarlo

    +
    + ASSET analysis probability matrix substep that computes the probability matrix (PMAT) employing a Monte Carlo approach using surrogate data obtained from the input spike trains. Different than the analytical method of computation, the null hypothesis in this method does not incorporate the assumptions that the spike trains are Poisson. Spike train surrogates can be generated using distinct methods. +
    +
    +
    has super-classes
    +
    + ASSET analysis probability matrix substep + c +
    +
    is disjoint with
    +
    + compute ASSET probability matrix (analytical method) + c +
    +
    +
    +
    +

    compute ASSET sequence of synchronous events extractionc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeASSETSequenceSynchronousEventsExtraction

    +
    + Last substep of the ASSET analysis method. Given the cluster matrix (CMAT), the identity of the neurons present in each bin of the repeated sequence in the identified diagonal structures is extracted (considering the input spike trains for the computation of the intersection matrix). The output of this substep is the final description of the ASSET pattern for each diagonal structure in the CMAT. +
    +
    +
    has super-classes
    +
    + ASSET analysis substep + c +
    +
    +
    +
    +

    compute autocorrelation functionc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeAutocorrelationFunction

    +
    + An autocorrelation analysis that computes the estimator for the autocorrelation function, i.e. the autocorrelation values of a time series input for a number of lags. The autocorrelation function shows temporal dependencies and repetitive patterns within the input data. The value of the autocorrelation at a specific lag shows how similar the values in the time series input are when separated by a number of time units equal to that lag. The autocorrelation value of 0 indicates no correlation. The autocorrelation varies between 1 and -1 (positive and negative correlation, respectively). +
    +
    +
    has super-classes
    +
    + autocorrelation analysis + c +
    +
    +
    +
    +

    compute canonical coherencec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeCanonicalCoherence

    +
    + A coherence analysis that computes the canonical coherence (caCOH) according to Vidaurre et al. (2019). The computation maximizes the coherence between two inputs (e.g., distinct datasets with electroencephalogram, electromyogram or local field potential recordings). The absolute value of the coherence between the two multivariate spaces of the inputs in the frequency domain is maximized. The caCOH aims to maximize the strength of the synchronization of oscillatory signals when two multichannel datasets are present (e.g., multiple subjects). The method then finds two spatial projections maximizing the strength of synchronization. +
    +
    +
    has super-classes
    +
    + coherence analysis + c +
    +
    +
    +
    +

    compute coefficient of variationc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeCV

    +
    + A dispersion statistical analysis that computes the coefficient of variation (CV). The CV is the ratio of the standard deviation to the mean. It is useful to compare different inputs, as the measure is unitless and indicates the relative variability in the input data. +
    +
    +
    has super-classes
    +
    + dispersion statistical analysis + c +
    +
    +
    +
    +

    compute coefficient of variation of the interspike intervalsc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeCVInterspikeIntervals

    +
    + An interspike interval variability analysis that computes the coefficient of variation (CV) of the interspike intervals (ISIs). The CV is computed as the ratio of the standard deviation of the ISIs to their mean. +
    +
    +
    has super-classes
    +
    + interspike interval variability analysis + c +
    +
    +
    +
    +

    compute coherencec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeCoherence

    +
    + A coherence analysis that computes the coherence value between two inputs. It is obtained from the magnitude of the complex-valued cross power spectral density obtained for the two inputs normalized by their power spectral density (i.e., auto spectral density). Several frequency decomposition approaches can be used to obtain the cross and auto power spectral densities from the inputs. The computation can return the magnitude coherence (i.e., by taking the absolute value of the cross power spectral density and normalizing by the square root of the product of the two auto spectral densities) or the magnitude squared coherence (i.e., by computing the squared magnitude of the cross power spectral density and normalizing by the product of the two auto spectral densities). +
    +
    +
    has super-classes
    +
    + coherence analysis + c +
    +
    has sub-classes
    +
    + compute coherence (Carter method) + c, compute coherence (Rosenberg method) + c, compute coherence (Welch method) + c, compute coherence (multitaper method) + c +
    +
    +
    +
    +

    compute coherence (Carter method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeCoherenceCarter

    +
    + A coherence analysis that computes the coherence from two inputs according to Carter (1987). The computation produces the magnitude squared coherence. +
    +
    +
    has super-classes
    +
    + compute coherence + c +
    +
    is disjoint with
    +
    + compute coherence (multitaper method) + c, compute coherence (Rosenberg method) + c, compute coherence (Welch method) + c +
    +
    +
    +
    +

    compute coherence (multitaper method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeCoherenceMultitaper

    +
    + A coherence analysis where the coherence value between the two inputs is computed using cross and auto power spectral densities obtained using a multitaper approach according to Thomson (1982). +
    +
    +
    has super-classes
    +
    + compute coherence + c +
    +
    is disjoint with
    +
    + compute coherence (Carter method) + c, compute coherence (Rosenberg method) + c, compute coherence (Welch method) + c +
    +
    +
    +
    +

    compute coherence (Rosenberg method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeCoherenceRosenberg

    +
    + A coherence analysis that computes the coherence from two inputs according to Rosenberg et al. (1989). The method is described for point processes (i.e., spike trains). The computation produces the magnitude squared coherence. +
    +
    +
    has super-classes
    +
    + compute coherence + c +
    +
    is disjoint with
    +
    + compute coherence (Carter method) + c, compute coherence (multitaper method) + c, compute coherence (Welch method) + c +
    +
    +
    +
    +

    compute coherence (Welch method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeCoherenceWelch

    +
    + A coherence analysis where the coherence value between the two inputs is obtained from cross and auto power spectral densities obtained using the method described by Welch (1967). For the computation, the inputs are divided into multiple overlapping segments, and the overall cross and power spectral densities for computing the coherence are obtained from averaging the single-segment estimates. +
    +
    +
    has super-classes
    +
    + compute coherence + c +
    +
    is disjoint with
    +
    + compute coherence (Carter method) + c, compute coherence (multitaper method) + c, compute coherence (Rosenberg method) + c +
    +
    +
    +
    +

    compute coherencyc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeCoherency

    +
    + A coherency analysis that computes the coherency for two inputs. It is computed from the complex-valued cross power spectral density obtained for the two inputs normalized by the square root of the product of their power spectral densities (i.e., auto spectral densities). For each frequency, the magnitude of the complex-valued coherency describes the strength of the association and the angle describes the phase lag between the two inputs. If the inputs contain multi-epoch data (e.g., multiple trial repetitions), the cross and auto spectral densities are averaged across epochs. +
    +
    +
    has super-classes
    +
    + coherency analysis + c +
    +
    +
    +
    +

    compute complexity distributionc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeComplexityDistribution

    +
    + A spike train synchrony analysis that computes the complexity distribution across a set of input spike trains that typically contain the activity of different neurons. In a neuronal population, the complexity represents the total number of neurons that were spiking within a discrete time interval. For the computation, the binarized population histogram (i.e., a spike time histogram computed across spike trains, where each bin will have the count of spike trains that had at least one spike within the bin interval) is obtained using a bin size specified as a parameter. The value at each bin is the complexity. The complexity distribution is obtained by finding the frequency of each complexity value (complexity histogram) and corresponding probability density function (PDF). The complexity PDF describes the likelihood of different complexity values occurring within the neuronal population. +
    +
    +
    has super-classes
    +
    + spike train synchrony analysis + c +
    +
    +
    +
    +

    compute confidence interval (bootstrap resampling)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeConfidenceIntervalBootstrap

    +
    + A confidence interval resampling analysis that computes the confidence interval using bootstrapping techniques to create many simulated samples (bootstrap samples). It involves repeatedly sampling, with replacement, from the input (observed) data. The total number of bootstrap samples is defined as a parameter. Bootstrapping makes minimal assumptions about the underlying distribution of the data, making it especially useful for small samples or when the data do not meet the assumptions of traditional parametric (non-resampling) methods. +
    +
    +
    has super-classes
    +
    + confidence interval with resampling analysis + c +
    +
    is disjoint with
    +
    + compute confidence interval (jackknife resampling) + c +
    +
    +
    +
    +

    compute confidence interval (jackknife resampling)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeConfidenceIntervalJackknife

    +
    + A confidence interval resampling analysis that computes the confidence interval using jackknife techniques. It involves systematically leaving out one observation at a time from the input (sample) set and calculating the statistic of interest on each of these "leave-one-out" samples. The confidence interval is computed based on statistics obtained from those jackknife samples. Jackknife is useful for small samples or when the data do not meet the assumptions of traditional parametric (non-resampling) methods. +
    +
    +
    has super-classes
    +
    + confidence interval with resampling analysis + c +
    +
    is disjoint with
    +
    + compute confidence interval (bootstrap resampling) + c +
    +
    +
    +
    +

    compute confidence interval (non-resampling)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeConfidenceIntervalNonResampling

    +
    + A confidence interval statistical analysis that computes the confidence interval assuming a statistical distribution of the input data, and uses measures of central tendency and dispersion obtained from the data points in the input(s) (e.g., mean and standard error of the mean when assuming a normal distribution). The computation relies on theoretical distributions and established statistical formulas. +
    +
    +
    has super-classes
    +
    + confidence interval statistical analysis + c +
    +
    is disjoint with
    +
    + confidence interval with resampling analysis + c +
    +
    +
    +
    +

    compute continuous wavelet transformc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeContinuousWaveletTransform

    +
    + A wavelet transform analysis that convolves the input time series with scaled and translated versions of the mother wavelet. The scale parameter can be non-dyadic (i.e., can take values that are not powers of 2). The mother wavelet used is passed as a parameter, and several types can be used (e.g., Morlet, Mexican hat, Hermitian, Meyer, Poisson). The continuous wavelet transform (CWT) is ideal for analyzing non-stationary signals, with transient behavior, rapidly changing frequencies or slowly varying changes. It is comparable to the short-time Fourier transform (STFT). +
    +
    +
    has super-classes
    +
    + wavelet transform analysis + c +
    +
    is disjoint with
    +
    + compute Morlet wavelet transform + c +
    +
    +
    +
    +

    compute corrected imaginary phase locking valuec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeCorrectedImaginaryPhaseLockingValue

    +
    + A phase locking value analysis that computes the corrected imaginary phase locking value (ciPLV), following the implementation from Bruña & Maestú (2018). It re-formulates the original phase locking value (PLV) for computational efficiency. The computation uses the imaginary part of the PLV, to make the metric insensitive to zero lag synchronizations (that can be the result of volume conduction). +
    +
    +
    has super-classes
    +
    + phase locking value analysis + c +
    +
    +
    +
    +

    compute covariancec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeCovariance

    +
    + A covariance analysis that computes the values of covariance in pairwise input data. +
    +
    +
    has super-classes
    +
    + covariance analysis + c +
    +
    has sub-classes
    +
    + compute regularized covariance + c +
    +
    +
    +
    +

    compute cross power spectral density (Morlet wavelet method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeCrossPowerSpectralDensityMorletWavelet

    +
    + A cross power spectral density analysis that uses the Morlet wavelet transform to obtain the frequency information of the two inputs used to compute the cross power spectral density. +
    +
    +
    has super-classes
    +
    + cross power spectral density analysis + c +
    +
    is disjoint with
    +
    + compute cross power spectral density (multitaper method) + c, compute cross power spectral density (periodogram method) + c, compute cross power spectral density (Welch method) + c +
    +
    +
    +
    +

    compute cross power spectral density (multitaper method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeCrossPowerSpectralDensityMultitaper

    +
    + A cross power spectral density (CPSD) analysis that uses a multitaper approach to compute the CPSD, according to Thomson (1982). The multitaper method uses discrete prolate spheroidal functions (DPSS, also known as Slepian sequences) as tapers applied to the inputs. For the computation, a CPSD using the periodogram method is obtained for each pair of tapered signals. The DPSS functions are orthogonal, and therefore applying multiple DPSS tapers result in independent estimates of the CPSD. The final CPSD is obtained by averaging the CPSDs across all tapers. The multitaper method reduces variance and bias in the CPSD, and has a high frequency resolution. However, it is computationally expensive. The number of tapers used is passed as parameter, or estimated from the desired resolution. +
    +
    +
    has super-classes
    +
    + cross power spectral density analysis + c +
    +
    is disjoint with
    +
    + compute cross power spectral density (Morlet wavelet method) + c, compute cross power spectral density (periodogram method) + c, compute cross power spectral density (Welch method) + c +
    +
    +
    +
    +

    compute cross power spectral density (periodogram method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeCrossPowerSpectralDensityPeriodogram

    +
    + A cross power spectral density (CPSD) analysis that uses the periodogram method. For the computation, the discrete Fourier transform of each input is obtained and their cross-power spectrum is obtained. A window function can be applied to the inputs before the Fourier transform, to reduce spectral leakage. The final CPSD is obtained by normalizing the cross-power spectrum to the unit frequency using the equivalent noise bandwidth (a factor that depends on the coefficients of the window function and the sampling rate). If no window function is used or a window that does not attenuate the signal is used (e.g., Boxcar or rectangular window) the equivalent noise bandwidth is equal to the frequency resolution. +
    +
    +
    has super-classes
    +
    + cross power spectral density analysis + c +
    +
    is disjoint with
    +
    + compute cross power spectral density (Morlet wavelet method) + c, compute cross power spectral density (multitaper method) + c, compute cross power spectral density (Welch method) + c +
    +
    +
    +
    +

    compute cross power spectral density (Welch method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeCrossPowerSpectralDensityWelch

    +
    + A cross power spectral density (CPSD) analysis that uses the method defined by Welch (1967). For the computation, the two inputs are divided into several overlapping segments (length and overlap passed as parameters, or computed for the desired frequency resolution based on the input length and sampling frequency). A window function (e.g., Hann) is applied to each segment, and the cross power spectral density using the periodogram method is computed. The final CPSD is obtained by averaging all the periodograms with the individual CPSDs. +
    +
    +
    has super-classes
    +
    + cross power spectral density analysis + c +
    +
    is disjoint with
    +
    + compute cross power spectral density (Morlet wavelet method) + c, compute cross power spectral density (multitaper method) + c, compute cross power spectral density (periodogram method) + c +
    +
    +
    +
    +

    compute cross-correlation functionc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeCrossCorrelationFunction

    +
    + A cross-correlation analysis that computes an estimate of the cross-correlation function, i.e. the cross-correlation values of two time series inputs for a number of lags. The cross-correlation function shows temporal dependencies of the first input series with respect to the second. The value of the cross-correlation at a specific lag shows how similar the values in the first input series are to values in the second input at time points separated by a number of time units equal to that lag. The cross-correlation value of 0 indicates no correlation. The cross-correlation varies between 1 and -1 (positive and negative correlation, respectively). +
    +
    +
    has super-classes
    +
    + cross-correlation analysis + c +
    +
    has sub-classes
    +
    + compute cross-correlation function (biased) + c, compute cross-correlation function (unbiased) + c +
    +
    +
    +
    +

    compute cross-correlation function (biased)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeCrossCorrelationFunctionBiased

    +
    + An analysis step that computes the biased estimator for the cross-correlation function. The biased estimator produces cross-correlation values that deviate from the true cross-correlation. +
    +
    +
    has super-classes
    +
    + compute cross-correlation function + c +
    +
    is disjoint with
    +
    + compute cross-correlation function (unbiased) + c +
    +
    +
    +
    +

    compute cross-correlation function (unbiased)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeCrossCorrelationFunctionUnbiased

    +
    + An analysis step that computes the unbiased estimator for the cross-correlation function, using the formula in Stoica & Moses (2005). The unbiased estimation uses a correction for the bias due to zero-padding in the computation, applied to the normalization coefficient. Therefore, the resultant cross-correlation values are closer to the true cross-correlation. +
    +
    +
    has super-classes
    +
    + compute cross-correlation function + c +
    +
    is disjoint with
    +
    + compute cross-correlation function (biased) + c +
    +
    +
    +
    +

    compute cross-spectrogram (short-time Fourier transform method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeCrossSpectrogramShortTimeFourierTransform

    +
    + A spectrogram analysis that computes a cross-spectrogram using the short-time Fourier transform (STFT). The cross-spectrogram is the time-resolved description of the power of a pair of distinct inputs across the different frequency components. This can be used to investigate how common activity between the two inputs is distributed across the frequency components, and how it varies over time. +
    +
    +
    has super-classes
    +
    + spectrogram analysis + c +
    +
    is disjoint with
    +
    + compute spectrogram (Morlet wavelet method) + c, compute spectrogram (multitaper method) + c, compute spectrogram (short-time Fourier transform method) + c +
    +
    +
    +
    +

    compute CuBIC analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeCubicAnalysis

    +
    + A spike train synchrony analysis that uses the Cumulant Based Inference of higher-order Correlation (CuBIC) test described in Staude et al. (2010). CuBIC is a statistical method to detect the presence of higher order correlations in parallel spike trains from a neuronal population (i.e., correlations among three or more neurons). It is based on the analysis of the cumulants of the population spike count. The test takes a population histogram as input data (i.e., a spike train time histogram computed across spike trains with the activity of distinct neurons). A null hypothesis that the third cumulant of the data is less than or equal to the maximized third cumulant for a correlation order is iteratively tested (with increasing orders of correlation). The output is the minimum correlation order necessary to explain the value of the third cumulant calculated from the population spike count, together with the p-values of the hypothesis tests performed. +
    +
    +
    has super-classes
    +
    + spike train synchrony analysis + c +
    +
    +
    +
    +

    compute current source density (inverse method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeCurrentSourceDensityICSD

    +
    + A current source density (CSD) analysis that uses the inverse current source density (iCSD) estimation method described by Pettersen et al. (2006). The iCSD is based on the inversion of the electrostatic forward solution and can be applied to data obtained from electrodes with multiple configurations. The method can handle cases with spatially confined cortical activity and spatially varying extracellular conductivity. + +Three options for CSD estimation using the iCSD exist. The CSD is assumed to have cylindrical symmetry and follows one of three possible assumptions: +1. is localized in infinitely thin discs; +2. is step-wise constant; +3. is continuous and smoothly varying (using cubic splines) in the vertical direction. +
    +
    +
    has super-classes
    +
    + current source density analysis + c +
    +
    is disjoint with
    +
    + compute current source density (kernel method) + c, compute current source density (standard method) + c +
    +
    +
    +
    +

    compute current source density (kernel method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeCurrentSourceDensityKCSD

    +
    + A current source density (CSD) analysis that uses kernel methods to compute the CSD (kCSD), described by Potworowski et al. (2012). kCSD is non parametric and can estimate the CSD using signals recorded from arbitrarily distributed electrodes, as the assumption of regular electrode placement is not necessary. The method can handle 1D, 2D or 3D electrode configurations. The kCSD can also estimate CSD at any location, as it is not limited to the electrode positions, and uses cross-validation to ensure no overfitting. +
    +
    +
    has super-classes
    +
    + current source density analysis + c +
    +
    is disjoint with
    +
    + compute current source density (inverse method) + c, compute current source density (standard method) + c +
    +
    +
    +
    +

    compute current source density (standard method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeCurrentSourceDensityStandard

    +
    + A current source density (CSD) analysis that uses a double spatial derivative of the recorded extracellular potentials to compute the CSD. The original method by Freeman & Nicholson (1975) assumes homogeneous cortical in-plane activity, constant extracellular electrical conductivity and equidistant electrode contacts, and can only predict the CSD at interior electrode positions. Vaknin et al. (1988) suggested a procedure to obtain the CSD for the first and last electrodes by copying the outmost recordings, therefore extending the grid beyond the electrode contacts. This is based on the assumption that the potential varies negligibly above the first and below the last electrode. +
    +
    +
    has super-classes
    +
    + current source density analysis + c +
    +
    is disjoint with
    +
    + compute current source density (inverse method) + c, compute current source density (kernel method) + c +
    +
    +
    +
    +

    compute CV2c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeCV2

    +
    + An interspike interval variability analysis that computes the CV2, a measure of the intrinsic variability of a spike train that considers adjacent interspike intervals. The CV2 is more robust against fluctuations in the firing rate than the usual approach of taking the coefficient of variation of the interspike intervals of the spike train. +
    +
    +
    has super-classes
    +
    + interspike interval variability analysis + c +
    +
    +
    +
    +

    compute debiased squared weighted phase lag indexc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeDebiasedSquaredWeightedPhaseLagIndex

    +
    + A phase lag index (PLI) analysis that computes the debiased squared weighted PLI (WPLI) following Vinck et al. (2011). The direct PLI estimator is positively biased, especially when the sample sizes (i.e., number of trials) are small. The debiased squared WPLI is computed by computing the imaginary components of the cross spectral densities, computing the average imaginary component of the cross spectral densities, and normalizing by the computed average over the magnitudes of the imaginary component of the cross spectral densities. +
    +
    +
    has super-classes
    +
    + phase lag index analysis + c +
    +
    +
    +
    +

    compute directed phase lag indexc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeDirectedPhaseLagIndex

    +
    + A phase lag index (PLI) analysis that computes the directed PLI (DPLI) according to Stam & van Straaten (2012). The DPLI uses the Heaviside step function on the imaginary part of the cross power spectral density, and provides the ability to discriminate whether the first time series is leading or lagging the second. The DPLI ranges between 0 and 1. A DPLI value of 0.5 means that the first time series leads and lags the second time series equally often. A DPLI value greater than 0.5 means that the first time series leads the second more often than it lags. A value of 1 means that the first time series always leads. On the contrary, a DPLI value smaller than 0.5 means that the first time series lags the second more often than it leads. A DPLI value of zero means that the first time series always lags. The PLI can be computed from the DPLI. +
    +
    +
    has super-classes
    +
    + phase lag index analysis + c +
    +
    +
    +
    +

    compute directed transfer functionc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeDirectedTransferFunction

    +
    + A functional connectivity analysis that computes the directed transfer function (DTF) according to Kaminski & Blinowska (1991). DTF can estimate the direction and frequency content of the brain activity flow. The DTF measure is obtained from the spectral transfer matrix computed from multivariate time series input data. For the DTF computation, the spectral transfer matrix is obtained from a multivariate autoregressive model. The DTF estimate is obtained by using a normalization factor computed by the sum along the rows of the spectral transfer matrix. The DTF can have values in the range from 0 to 1. +
    +
    +
    has super-classes
    +
    + functional connectivity analysis + c +
    +
    +
    +
    +

    compute event-related potentialc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeEventRelatedPotential

    +
    + An analysis step that computes the event-related potential (ERP). The ERP is the neural activity (e.g., local field potential or electroencephalogram voltages) around a presented stimulus or spontaneous behavioral event. Usually, the event is presented/occurs repeatedly across multiple trials, obtaining multiple event-related potential waveforms that can be averaged to cancel the noise. +
    +
    +
    has super-classes
    +
    + analysis step + c +
    +
    has sub-classes
    +
    + compute evoked potential + c +
    +
    +
    +
    +

    compute event-triggered averagec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeEventTriggeredAverage

    +
    + A triggered average analysis that uses an event of interest such as an external stimulus (e.g., electrical, visual, auditory) or a spontaneous behavior (e.g., eye blink) as a trigger to average a signal. The output of the method will provide the average value of the signal around the time where each event occurred (event-triggered average). +
    +
    +
    has super-classes
    +
    + triggered average analysis + c +
    +
    +
    +
    +

    compute evoked potentialc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputedEvokedPotential

    +
    + An analysis step that computes the evoked potential (EP). The EP is the neural activity (e.g., local field potential or electroencephalogram voltages) around a presented stimulus (e.g., auditory, visual, electrical). Usually, the stimulus is presented repeatedly across multiple trials, obtaining multiple evoked potential waveforms that can be averaged to cancel the noise. It is an event-related potential (ERP) obtained from presenting a stimulus rather than spontaneous behavioral events. +
    +
    +
    has super-classes
    +
    + compute event-related potential + c +
    +
    +
    +
    +

    compute frequency domain conditional Granger causalityc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeFrequencyDomainConditionalGrangerCausality

    +
    + A conditional Granger causality (GC) analysis that computes the GC measures in the frequency domain. +
    +
    +
    has super-classes
    +
    + conditional Granger causality analysis + c +
    +
    is disjoint with
    +
    + compute time domain conditional Granger causality + c +
    +
    +
    +
    +

    compute frequency domain pairwise Granger causality (Brovelli method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeFrequencyDomainPairwiseGrangerCausalityBrovelli

    +
    + A frequency domain pairwise Granger causality (GC) analysis that uses the parametric approach according to Brovelli et al. (2004). It uses an MVAR (multivariate autoregressive model) to obtain the coefficients used for the computation of the spectral transfer matrix needed for GC estimation according to the frequency domain GC formulation by Geweke (1982). +
    +
    +
    has super-classes
    +
    + frequency domain pairwise granger causality analysis + c +
    +
    is disjoint with
    +
    + compute frequency domain pairwise Granger causality (Dhamala method) + c, compute frequency domain pairwise Granger causality (Hafner method) + c, compute frequency domain pairwise Granger causality (Wen method) + c +
    +
    +
    +
    +

    compute frequency domain pairwise Granger causality (Dhamala method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeFrequencyDomainPairwiseGrangerCausalityDhamala

    +
    + A frequency domain pairwise Granger causality (GC) analysis that uses the non-parametric approach according to Dhamala et al. (2008). It is based on Fourier and wavelet transforms to obtain the spectral density matrix and the algorithm from Wilson (1972) for its factorization. +
    +
    +
    has super-classes
    +
    + frequency domain pairwise granger causality analysis + c +
    +
    is disjoint with
    +
    + compute frequency domain pairwise Granger causality (Brovelli method) + c, compute frequency domain pairwise Granger causality (Hafner method) + c, compute frequency domain pairwise Granger causality (Wen method) + c +
    +
    +
    +
    +

    compute frequency domain pairwise Granger causality (Hafner method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeFrequencyDomainPairwiseGrangerCausalityHafner

    +
    + A frequency domain pairwise Granger causality (GC) analysis that uses the parametric approach according to Hafner & Herwartz (2008). It uses a multivariate GARCH (generalized autoregressive conditional heteroskedasticity) model and constructs a Wald test on noncausality in variance. This is an alternative to methods based on the residuals of estimated univariate models. The Wald test has superior power properties. +
    +
    +
    has super-classes
    +
    + frequency domain pairwise granger causality analysis + c +
    +
    is disjoint with
    +
    + compute frequency domain pairwise Granger causality (Brovelli method) + c, compute frequency domain pairwise Granger causality (Dhamala method) + c, compute frequency domain pairwise Granger causality (Wen method) + c +
    +
    +
    +
    +

    compute frequency domain pairwise Granger causality (Wen method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeFrequencyDomainPairwiseGrangerCausalityWen

    +
    + A frequency domain pairwise Granger causality (GC) analysis that uses the non-parametric approach according to Wen et al. (2013). It is a multivariate framework for estimating GC based on spectral density matrix factorization. The approach requires only a single estimation of the spectral density matrix for the entire dataset (e.g., multiple time series inputs). GC for the subsets (i.e., pairs of inputs) can then be calculated by factorizing the relevant submatrix of this overall spectral density matrix. +
    +
    +
    has super-classes
    +
    + frequency domain pairwise granger causality analysis + c +
    +
    is disjoint with
    +
    + compute frequency domain pairwise Granger causality (Brovelli method) + c, compute frequency domain pairwise Granger causality (Dhamala method) + c, compute frequency domain pairwise Granger causality (Hafner method) + c +
    +
    +
    +
    +

    compute imaginary coherencyc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeImaginaryCoherency

    +
    + A coherency analysis that computes the imaginary part of the coherency for two inputs according to Nolte et al. (2004). For the computation, the imaginary part of the complex-valued cross power spectral density obtained for the two inputs is normalized by the square root of the product of their power spectral densities (i.e., auto spectral densities). If the inputs contain multi-epoch data (e.g., multiple trial repetitions), the cross and auto spectral densities are averaged across epochs. The imaginary part of the coherency is less affected by volume conduction than the (complex) coherency. +
    +
    +
    has super-classes
    +
    + coherency analysis + c +
    +
    +
    +
    +

    compute instantaneous firing rate (interspike interval method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeInstantaneousFiringRateInterspikeInterval

    +
    + An instantaneous firing rate analysis that computes the instantaneous firing rate by using the reciprocal of the interspike intervals. +
    +
    +
    has super-classes
    +
    + instantaneous firing rate analysis + c +
    +
    is disjoint with
    +
    + compute instantaneous firing rate (kernel density estimation method) + c, compute instantaneous firing rate (local regression method) + c +
    +
    +
    +
    +

    compute instantaneous firing rate (kernel density estimation method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeInstantaneousFiringRateKernelDensityEstimation

    +
    + An instantaneous firing rate analysis that computes the instantaneous firing rate by convolution of spike times with a kernel function. The output of the computation is a weighted average of the spikes around the kernel. +
    +
    +
    has super-classes
    +
    + instantaneous firing rate analysis + c +
    +
    is disjoint with
    +
    + compute instantaneous firing rate (interspike interval method) + c, compute instantaneous firing rate (local regression method) + c +
    +
    +
    +
    +

    compute instantaneous firing rate (local regression method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeInstantaneousFiringRateLocalRegression

    +
    + An instantaneous firing rate analysis that computes the instantaneous firing rate using local regression methods. The estimation procedure approximates the log of the firing rate using a low-order polynomial within a moving window (local neighborhood). +
    +
    +
    has super-classes
    +
    + instantaneous firing rate analysis + c +
    +
    is disjoint with
    +
    + compute instantaneous firing rate (interspike interval method) + c, compute instantaneous firing rate (kernel density estimation method) + c +
    +
    +
    +
    +

    compute interquartile rangec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeInterquartileRange

    +
    + A dispersion statistical analysis that computes the interquartile range (IQR). The IQR is the difference between the 75th and 25th percentiles (i.e., the range within which the central 50% of the data points lie). +
    +
    +
    has super-classes
    +
    + dispersion statistical analysis + c +
    +
    +
    +
    +

    compute interspike interval histogramc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeInterspikeIntervalHistogram

    +
    + An interspike interval analysis that computes the histogram of interspike intervals. For the computation, a time interval with fixed duration starting from zero is discretized into smaller intervals (bins). The count of input interspike intervals whose values fall into each bin is obtained. Therefore, the output contains a representation of the distribution of the interspike intervals in the input. +
    +
    +
    has super-classes
    +
    + interspike interval analysis + c +
    +
    +
    +
    +

    compute interspike intervalsc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeInterspikeIntervals

    +
    + An interspike interval analysis that computes the intervals between successive spikes in a spike train (interspike intervals; ISIs). +
    +
    +
    has super-classes
    +
    + interspike interval analysis + c +
    +
    +
    +
    +

    compute ISI-distancec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeISIDistance

    +
    + A time-scale independent spike train distance analysis that computes the ISI-distance, described in Kreuz et al. (2007). For the computation, the discrete sequence of spike times is transformed into a continuous temporal profile with one value per sample point. The values at each time point are derived from the interspike intervals. The distance is then obtained as the temporal average of the time profile. ISI-distance is well-designed to describe similarities in the firing rate profile of the input spike trains, but it is not optimal to capture neuronal synchrony. +
    +
    +
    has super-classes
    +
    + time-scale independent spike train distance analysis + c +
    +
    +
    +
    +

    compute joint peristimulus time histogramc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeJointPeristimulusTimeHistogram

    +
    + A spike train synchrony analysis that computes the joint peristimulus time histogram (JPSTH) from trial-by-trial spike train inputs obtained from two different neurons, after the repeated presentation of a stimulus. The JPSTH provides a representation of the timing relationship between the firing of the two neurons in response to the stimulus. It combines the peristimulus time histograms (PSTHs) of each neuron to illustrate how their firing rates co-vary over time relative to the stimulus event. This helps in understanding the temporal correlation between the neurons. + +The computation can produce three outputs: + +* the JPSTH matrix (i.e., a matrix whose bins contain the counts of coincidences in the firing of the two neurons); +* the peristimulus coincidence histogram (i.e., a histogram obtained from a cross-section along the main diagonal of the JPSTH matrix); +* the cross-correlation histogram computed by summing the bins along the main and each paradiagonal of the JPSTH matrix (after normalizing by the bin length, as the paradiagonals in the JPSTH matrix are of different lengths). +
    +
    +
    has super-classes
    +
    + spike train synchrony analysis + c +
    +
    +
    +
    +

    compute local variationc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeLV

    +
    + An interspike interval variability analysis that computes the local variation (LV) of the interspike intervals. LV reflects the stepwise variability of a sequence of spikes, and is able to extract the spiking characteristics of individual neurons even in the presence of external modulations of the firing rate. +
    +
    +
    has super-classes
    +
    + interspike interval variability analysis + c +
    +
    +
    +
    +

    compute maximized imaginary coherencyc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeMaximizedImaginaryCoherency

    +
    + A coherency analysis that computes the maximized imaginary coherency (MIC) according to Ewald et al. (2012). The computation uses an eigenvalue-based optimization to find weight vectors that maximize the imaginary part of coherency computed between virtual channels derived from the input data. The weights are optimized for each frequency component. After the weights are obtained, the final MIC measure is obtained for each frequency. +
    +
    +
    has super-classes
    +
    + coherency analysis + c +
    +
    +
    +
    +

    compute meanc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeMean

    +
    + A central tendency statistical analysis that computes the mean of the input data. The mean is the arithmetic average of all data points. +
    +
    +
    has super-classes
    +
    + central tendency statistical analysis + c +
    +
    +
    +
    +

    compute mean firing ratec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeMeanFiringRate

    +
    + A firing rate analysis that computes the mean firing rate, defined as the number of spikes in a time interval divided by the duration of the interval. The mean firing rate is the temporal average of the neuronal activity over that interval. +
    +
    +
    has super-classes
    +
    + firing rate analysis + c +
    +
    +
    +
    +

    compute mean phase vectorc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeMeanPhaseVector

    +
    + A phase analysis that computes the mean among two or more input phases. For the computation, the input phases are represented as vectors in the unit circle, and the mean phase vector is computed. The analysis can return the mean phase vector (i.e., angle and length), the vector angle, or the vector length. +
    +
    +
    has super-classes
    +
    + phase analysis + c +
    +
    +
    +
    +

    compute mean vector length (Canolty method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeMeanVectorLengthCanolty

    +
    + A mean vector length (MVL) analysis that computes the mean vector length as described in Canolty et al. (2006). For the computation, phase is extracted from the low-frequency analytic signal, and amplitude is extracted from the high-frequency analytic signal. The phase angle and magnitude is used to define a complex-valued time series, and each complex value is a vector in the polar plane. Averaging all vectors yields a mean vector whose length indicates the coupling strength and whose direction indicates the phase where amplitude is strongest. Without coupling, the vectors cancel out, resulting in a short mean vector without meaningful phase direction. If phase-amplitude coupling exists, the magnitude of a subset of vectors is especially high at a specific phase or narrow phase range. +
    +
    +
    has super-classes
    +
    + mean vector length analysis + c +
    +
    is disjoint with
    +
    + compute mean vector length (Özkurt method) + c +
    +
    +
    +
    +

    compute mean vector length (Özkurt method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeMeanVectorLengthOzkurt

    +
    + A mean vector length (MVL) analysis that computes the MVL as described in Özkurt & Schnitzler (2011). The original MVL (Canolty et al., 2006) may be affected by factors in the input data (e.g., amplitude outliers or non-uniform distribution of phase angles). This computation estimates a direct MVL that is amplitude-normalized to obtain values in the 0 to 1 range, and that takes care of possible amplitude differences in the raw data. +
    +
    +
    has super-classes
    +
    + mean vector length analysis + c +
    +
    is disjoint with
    +
    + compute mean vector length (Canolty method) + c +
    +
    +
    +
    +

    compute medianc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeMedian

    +
    + A central tendency statistical analysis that computes the median of the input data. The median is the middle value when data points are arranged in ascending order (i.e., it divides the data points in two equal halves, with 50% of the data points below it and 50% above it). If there is an even number of data points, the median is the average of the two middle values. +
    +
    +
    has super-classes
    +
    + central tendency statistical analysis + c +
    +
    +
    +
    +

    compute modulation indexc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeModulationIndex

    +
    + A phase-amplitude coupling (PAC) analysis that computes the modulation index (MI) as described in Tort et al. (2010). For the computation, the Hilbert transform is used to obtain the instantaneous phase from the input time series with the low-frequency oscillation, and the instantaneous amplitude from the input time series with the high-frequency oscillation. The phase of the low-frequency oscillation is discretized into bins and the amplitude of the high-frequency oscillation is averaged within each bin to create a distribution. This distribution is then compared to a uniform distribution using the Kullback-Leibler divergence, normalized by the maximum possible divergence, resulting in the MI. +
    +
    +
    has super-classes
    +
    + phase-amplitude coupling analysis + c +
    +
    +
    +
    +

    compute Morlet wavelet transformc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeMorletWaveletTransform

    +
    + A wavelet transform analysis based on the complex-valued Morlet wavelet. The transform can be performed either in the time domain (by convolution) or in the frequency domain (by multiplication). +
    +
    +
    has super-classes
    +
    + wavelet transform analysis + c +
    +
    has sub-classes
    +
    + compute Morlet wavelet transform (Le Van Quyen method) + c, compute Morlet wavelet transform (Tallon-Baudry method) + c +
    +
    is disjoint with
    +
    + compute continuous wavelet transform + c +
    +
    +
    +
    +

    compute Morlet wavelet transform (Le Van Quyen method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeMorletWaveletTransformLeVanQuyen

    +
    + A wavelet transform analysis using the Morlet wavelet where the parametrization of the mother wavelet is done according to Le Van Quyen et al. (2001). The size of the mother wavelet is determined in number of cycles to control the frequency and temporal resolutions (approximate number of oscillation cycles within a wavelet). +
    +
    +
    has super-classes
    +
    + compute Morlet wavelet transform + c +
    +
    is disjoint with
    +
    + compute Morlet wavelet transform (Tallon-Baudry method) + c +
    +
    +
    +
    +

    compute Morlet wavelet transform (Tallon-Baudry method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeMorletWaveletTransformTallonBaudry

    +
    + A wavelet transform analysis using the Morlet wavelet based on the methods described in Tallon-Baudry et al. (1997). The ratio of the central frequency to the spectral bandwidth is 7, with central frequencies ranging from 20 to 100 Hz in 1 Hz steps. This resulted in varying time/frequency resolution across the spectrum: time resolution increases with frequency, while frequency resolution decreases. +
    +
    +
    has super-classes
    +
    + compute Morlet wavelet transform + c +
    +
    is disjoint with
    +
    + compute Morlet wavelet transform (Le Van Quyen method) + c +
    +
    +
    +
    +

    compute multivariate interaction measurec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeMultivariateInteractionMeasure

    +
    + A functional connectivity analysis that computes the multivariate interaction measure (MIM) as defined by Ewald et al. (2012). MIM is constructed from the maximization of imaginary coherency. +
    +
    +
    has super-classes
    +
    + functional connectivity analysis + c +
    +
    +
    +
    +

    compute mutual informationc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeMutualInformation

    +
    + A functional connectivity analysis that computes a mutual information (MI) measure. MI is based on Shannon information theory, and quantifies the amount of information from one input that is obtained from another input. Therefore, it can be used to determine how the neuronal activity provides information about a variable (e.g., behavioral stimulus) or how the information flows between different brain regions or neurons. The MI is measured in bits. +
    +
    +
    has super-classes
    +
    + functional connectivity analysis + c +
    +
    +
    +
    +

    compute neuronal population vectorc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeNeuronalPopulationVector

    +
    + An analysis step that computes the neuronal population vector, used to describe the collective activity of a group of neurons. The neuronal population vector is obtained taking as inputs the multiple responses of a neuronal population in the context of distinct values of a behavioral measure (e.g., tuning curves showing the response of each individual neuron to different arm movement directions in the 2-D space). The analysis step obtains a weighted vectorial sum of the neural activities, which will result in an estimate of the behavioral measure considering the collective activity of the population (e.g., the movement direction given the neuronal activity). +
    +
    +
    has super-classes
    +
    + analysis step + c +
    +
    +
    +
    +

    compute noise correlationsc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeNoiseCorrelations

    +
    + A spike train correlation analysis that computes the noise correlations (NC) between two input spike trains. The NC is the Pearson's correlation coefficient of spike count responses to repeated presentations of identical stimuli, under the same behavioral conditions. The spike counts are typically measured over the time scale of a stimulus presentation or a behavioral trial, which range from a few hundred milliseconds to several seconds. NC assesses whether neurons exhibit trial-by-trial fluctuations in firing rates that are not influenced by varying sensory or behavioral conditions. +
    +
    +
    has super-classes
    +
    + spike train correlation analysis + c +
    +
    +
    +
    +

    compute noise covariancec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeNoiseCovariance

    +
    + A covariance analysis that computes the noise covariance, i.e., how much two noise signals vary together. The noise data inputs can be non-subject recordings (e.g., recordings from the empty experimental room) or are obtained from periods without stimulation or meaningful experimental manipulations (e.g., prestimulus intervals). These reflect random variations or disturbances that are not part of the actual signal or data of interest. +
    +
    +
    has super-classes
    +
    + covariance analysis + c +
    +
    +
    +
    +

    compute optimal bin sizec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeOptimalBinSize

    +
    + An analysis step that finds the optimal bin size considering the input data when discretizing data into smaller intervals (bins). The computation uses the formula from Scott (1979). +
    +
    +
    has super-classes
    +
    + analysis step + c +
    +
    +
    +
    +

    compute optimal kernel bandwidthc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeOptimalKernelBandwidth

    +
    + An analysis step that computes the optimal fixed bandwidth (width) for a Gaussian kernel used for the estimation of the firing rate using kernel density estimation. The analysis step uses the input spike train for which the firing rate will be computed, and follows the implementation by Shimazaki & Shinomoto (2010). +
    +
    +
    has super-classes
    +
    + analysis step + c +
    +
    +
    +
    +

    compute orthogonalized power envelope correlationc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeOrthogonalizedPowerEnvelopeCorrelation

    +
    + A functional connectivity analysis that computes the orthogonalized power envelope correlation, according to Hipp et al. (2012). This method relies on correlations between the instantaneous amplitudes of cross-region input signals (power envelopes). The instantaneous amplitudes of the two input time series are orthogonalized aiming to remove spurious correlations of signal power (e.g., due to limited spatial resolution of electrophysiological measures). +
    +
    +
    has super-classes
    +
    + correlation analysis + c +
    +
    +
    +
    +

    compute pairwise phase consistencyc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputePairwisePhaseConsistency

    +
    + A phase analysis that computes the pairwise phase consistency (PPC) measure according to Vinck et al. (2010). The PPC quantifies the distribution of phase differences across the inputs, but is less biased by the number of observations in comparison to the phase locking value (PLV). For the computation, the phase difference (angular distance) is obtained for all pairs of observations in the input (that can be represented as vectors in the unit circle, where the angle is the relative phase). The cosine of the angular distance (an estimate of the dot product of the vectors corresponding to each element in a pair) is computed for every pair, and the PPC estimate is obtained from the average of all pairwise dot products. With phase synchronization, the distribution of the pairwise dot products is centered around an average value, while without synchronization it will be distributed across the unit circle. The PPC provides an unbiased estimate of the squared PLV. +
    +
    +
    has super-classes
    +
    + phase analysis + c +
    +
    +
    +
    +

    compute partial coherencec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputePartialCoherence

    +
    + A coherence analysis that computes the partial coherence, i.e., the coherence value between a pair of inputs (e.g., time series with recordings from two distinct electrode channels) after removing the influence of one or more additional inputs (e.g., the time series with the recordings from all remaining channels). The partial coherence is computed according to Rosenberg et al. (1998). The partial coherence reflects the linear association in the frequency domain (for each frequency component) between the pair of inputs of interest, removing spurious coherence caused by confounding factors such as shared inputs to the pair of interest or volume conduction. +
    +
    +
    has super-classes
    +
    + coherence analysis + c +
    +
    +
    +
    +

    compute partial directed coherencec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputePartialDirectedCoherence

    +
    + A coherence analysis that computes the partial directed coherence (PDC) according to Baccalá & Sameshima (2001). The PDC describes the relationships between multivariate time series inputs (direction of information flow). To compute the PDC, the multivariate partial coherences obtained from multivariate autoregressive models are decomposed. The PDC reflects a frequency-domain representation of the concept associated with Granger causality. +
    +
    +
    has super-classes
    +
    + spectral analysis + c +
    +
    +
    +
    +

    compute peristimulus time histogram (adaptive kernel smoothing)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputePeristimulusTimeHistogramAdaptiveKernelSmoothing

    +
    + A peristimulus time histogram (PSTH) analysis that computes the PSTH using kernel density smoothing with an adaptive kernel width. The adaptive kernel is obtained by first computing the PSTH with a fixed-width kernel, and then modifying the kernel width in order to have a constant but time-dependent average number of spikes under the kernel (i.e., segments of the data with a high density of spikes will have a reduced kernel width). +
    +
    +
    has super-classes
    +
    + peristimulus time histogram analysis + c +
    +
    is disjoint with
    +
    + compute peristimulus time histogram (fixed kernel smoothing) + c, compute peristimulus time histogram (optimal bin size) + c, compute peristimulus time histogram (user-selected bin size) + c +
    +
    +
    +
    +

    compute peristimulus time histogram (fixed kernel smoothing)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputePeristimulusTimeHistogramFixedKernelSmoothing

    +
    + A peristimulus time histogram (PSTH) analysis that computes the PSTH using kernel density smoothing with a fixed kernel width specified as parameter. +
    +
    +
    has super-classes
    +
    + peristimulus time histogram analysis + c +
    +
    is disjoint with
    +
    + compute peristimulus time histogram (adaptive kernel smoothing) + c, compute peristimulus time histogram (optimal bin size) + c, compute peristimulus time histogram (user-selected bin size) + c +
    +
    +
    +
    +

    compute peristimulus time histogram (optimal bin size)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputePeristimulusTimeHistogramOptimalBinSize

    +
    + A peristimulus time histogram (PSTH) analysis that computes the PSTH finding the optimal bin size from the input spike train data, using the formula from Scott (1979). +
    +
    +
    has super-classes
    +
    + peristimulus time histogram analysis + c +
    +
    is disjoint with
    +
    + compute peristimulus time histogram (adaptive kernel smoothing) + c, compute peristimulus time histogram (fixed kernel smoothing) + c, compute peristimulus time histogram (user-selected bin size) + c +
    +
    +
    +
    +

    compute peristimulus time histogram (user-selected bin size)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputePeristimulusTimeHistogramUserSelectedBinSize

    +
    + A peristimulus time histogram (PSTH) analysis that computes the PSTH using a fixed bin size specified as a parameter. +
    +
    +
    has super-classes
    +
    + peristimulus time histogram analysis + c +
    +
    is disjoint with
    +
    + compute peristimulus time histogram (adaptive kernel smoothing) + c, compute peristimulus time histogram (fixed kernel smoothing) + c, compute peristimulus time histogram (optimal bin size) + c +
    +
    +
    +
    +

    compute phase differencec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputePhaseDifference

    +
    + A phase analysis that computes the difference between two input phases. +
    +
    +
    has super-classes
    +
    + phase analysis + c +
    +
    +
    +
    +

    compute phase lag indexc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputePhaseLagIndex

    +
    + A phase lag index (PLI) analysis that computes the PLI following Stam et al. (2007). The input data contains multiple repetitions of a pair of signals (e.g., time series with recordings from a pair of electrodes across multiple trials). For each repetition, the sign of the phase differences between the two time series is obtained from the imaginary part of the cross power spectral density (CPSD). The PLI value is the absolute value of the average of the signs of all repetitions. The PLI ranges between 0 and 1. A PLI of zero means that the first time series leads the second equally often (i.e., indicates either no coupling or coupling with a phase difference centered around 0 mod π, which could be from common sources such as volume conduction). A value greater than zero means an imbalance in the likelihood of the first time series to be either leading or lagging the second time series. A PLI of 1 indicates perfect phase locking, and that the first time series only leads or only lags (at a value of phase differences different from 0 mod π). +
    +
    +
    has super-classes
    +
    + phase lag index analysis + c +
    +
    +
    +
    +

    compute phase locking valuec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputePhaseLockingValue

    +
    + A phase locking value (PLV) analysis that computes the PLV value as originally described by Lachaux et al. (1999). The input data is a set of pairs of time series (e.g., the trial-by-trial local field potential recorded from two different electrodes). For each time series pair, the instantaneous phase is obtained (e.g., using the Hilbert transform or wavelet decomposition), and the phase difference for each time point is obtained. The PLV value is computed by averaging the complex phase differences across all pairs, obtaining one PLV value per time point. The PLV ranges from 0 to 1. A PLV of 1 indicates perfect phase locking, meaning the phase difference between the two time series is constant over time. A PLV of 0 indicates no phase locking, meaning the phase difference is randomly distributed over time. +
    +
    +
    has super-classes
    +
    + phase locking value analysis + c +
    +
    +
    +
    +

    compute phase slope indexc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputePhaseSlopeIndex

    +
    + A functional connectivity analysis that computes the phase slope index (PSI) according to Nolte et al. (2008). The PSI is based on the slope of the phase of the cross-spectral density between two time series inputs, considering how the phase difference between two signals changes as you move from one frequency bin to the next. It is computed from the complex-valued coherency using a bandwidth specified as parameter. For the computation, the change in phase difference between neighboring frequency bins is obtained (considering the specified bandwidth) and weighted. The PSI value deviates from zero when the phase difference changes consistently across frequencies and there is substantial coherence. The sign of the PSI indicates the temporal order of the two signals (i.e., which signal is leading the other one). +
    +
    +
    has super-classes
    +
    + phase analysis + c +
    +
    +
    +
    +

    compute population histogramc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputePopulationHistogram

    +
    + A spike train time histogram analysis that computes a histogram across two or more spike trains that contain the activity of different neurons (i.e., a neuronal population), recorded at fully-overlapping time intervals. The activity in each histogram bin reflects the combined activity of the population at that time, and the distribution of the histogram corresponds to the population activity over time. +
    +
    +
    has super-classes
    +
    + spike train time histogram analysis + c +
    +
    is disjoint with
    +
    + peristimulus time histogram analysis + c +
    +
    +
    +
    +

    compute power spectral density (Bartlett method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputePowerSpectralDensityBartlett

    +
    + A power spectral density (PSD) analysis that uses the method defined by Bartlett (1950). For the computation, the input time is divided into non-overlapping segments, with length specified as a parameter. A periodogram is computed for each segment to obtain the single-segment PSD. The final PSD is obtained by averaging all the single-segment PSDs. A window function can be applied to each segment before computing the periodograms. The PSD obtained with the Bartlett method is less noisy than a single periodogram obtained from the entire signal, although the frequency resolution of the estimates is reduced due to segmenting. It is equivalent to the Welch method without any segment overlap. +
    +
    +
    has super-classes
    +
    + power spectral density analysis + c +
    +
    is disjoint with
    +
    + compute power spectral density (multitaper method) + c, compute power spectral density (periodogram method) + c, compute power spectral density (Welch method) + c +
    +
    +
    +
    +

    compute power spectral density (multitaper method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputePowerSpectralDensityMultitaper

    +
    + A power spectral density (PSD) analysis that uses a multitaper approach to compute the PSD, according to Thomson (1982). The multitaper method uses discrete prolate spheroidal functions (DPSS, also known as Slepian sequences) as tapers applied to the input signal. For the computation, a PSD using the periodogram method is obtained for each tapered signal. The DPSS functions are orthogonal, and therefore applying multiple DPSS tapers result in independent estimates of the PSD. The final PSD is obtained by averaging the periodograms across all tapers. The multitaper method reduces variance and bias in the PSD, and has a high frequency resolution. However, it is computationally expensive. The number of tapers used is passed as parameter, or estimated from the desired resolution. +
    +
    +
    has super-classes
    +
    + power spectral density analysis + c +
    +
    is disjoint with
    +
    + compute power spectral density (Bartlett method) + c, compute power spectral density (periodogram method) + c, compute power spectral density (Welch method) + c +
    +
    +
    +
    +

    compute power spectral density (periodogram method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputePowerSpectralDensityPeriodogram

    +
    + A power spectral density (PSD) analysis that uses the periodogram method. For the computation, the discrete Fourier transform is applied to the full length of the input, and the power spectrum is obtained. To reduce spectral leakage, a window function can be applied to the input before the computation of the Fourier transform (this is referred as the modified periodogram). The power spectrum is then normalized to the unit frequency, using the equivalent noise bandwidth (a factor that depends on the coefficients of the window function and the sampling rate). If no window function is used or a window that does not attenuate the signal is used (e.g., Boxcar or rectangular window) the equivalent noise bandwidth is equal to the frequency resolution. The PSD using the periodogram is computationally simple to obtain. +
    +
    +
    has super-classes
    +
    + power spectral density analysis + c +
    +
    is disjoint with
    +
    + compute power spectral density (Bartlett method) + c, compute power spectral density (multitaper method) + c, compute power spectral density (Welch method) + c +
    +
    +
    +
    +

    compute power spectral density (Welch method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputePowerSpectralDensityWelch

    +
    + A power spectral density (PSD) analysis that uses the method defined by Welch (1967). For the computation, the input is divided into several overlapping segments (length and overlap passed as parameters, or computed for the desired frequency resolution based on the input length and sampling frequency). A window function (e.g., Hann) is applied to each segment, and a periodogram is computed to obtain the PSD for the segment. The final PSD is obtained by averaging all the periodograms with the single-segment PSDs. If there is no overlap between segments, this is equivalent to the Bartlett method. +
    +
    +
    has super-classes
    +
    + power spectral density analysis + c +
    +
    is disjoint with
    +
    + compute power spectral density (Bartlett method) + c, compute power spectral density (multitaper method) + c, compute power spectral density (periodogram method) + c +
    +
    +
    +
    +

    compute rate change detection multiple filter testc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeRateChangeDetectionMultipleFilterTest

    +
    + An analysis step that uses the change point detection algorithm from Messer et al. (2014) to determine if a input spike train has constant firing rate (stationary) or has one or more points in which the firing rate decreases or increases (change point). In the latter case, the spike train is considered non-stationary. The analysis step outputs one or more change points in the case of non-stationarity. +
    +
    +
    has super-classes
    +
    + analysis step + c +
    +
    +
    +
    +

    compute rectified area under the curvec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeRectifiedAreaUnderCurve

    +
    + An analysis step that computes the rectified area under the curve (RAUC). For the computation, the input signal is rectified (i.e., the absolute value is obtained) and the area under the curve is computed by integration using the composite trapezoidal rule. +
    +
    +
    has super-classes
    +
    + analysis step + c +
    +
    +
    +
    +

    compute regularized covariancec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeRegularizedCovariance

    +
    + A covariance analysis where the computation of the covariance values incorporates regularization techniques to improve the numerical stability, especially if the number of samples is small. +
    +
    +
    has super-classes
    +
    + compute covariance + c +
    +
    +
    +
    +

    compute revised local variationc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeLVR

    +
    + An interspike interval variability analysis that computes the revised local variation (LvR) of interspike intervals. Compared to the original local variation (LV) measure, LvR has better invariance to fluctuations in the firing rate fluctuations. This is achieved by using a refractoriness constant in the computation of the measure. +
    +
    +
    has super-classes
    +
    + interspike interval variability analysis + c +
    +
    +
    +
    +

    compute short-time Fourier transformc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeShortTimeFourierTransform

    +
    + A time-frequency analysis that computes the short-time Fourier transform (STFT) of the input time series. The analysis divides the input time-domain signal into short segments with equal time and computes the Fourier transform for each segment. The output is a sequence of coefficients of complex sinusoids, each representing a frequency component in the input signal at a distinct time segment. Therefore, this provides the the time-localized frequency and phase information of the input. The segments can be windowed using a window function. +
    +
    +
    has super-classes
    +
    + time-frequency analysis + c +
    +
    +
    +
    +

    compute spectrogram (Morlet wavelet method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeSpectrogramMorletWavelet

    +
    + A spectrogram analysis that uses the Morlet wavelet transform on the input to obtain the time-frequency information used to build the spectrogram. +
    +
    +
    has super-classes
    +
    + spectrogram analysis + c +
    +
    is disjoint with
    +
    + compute cross-spectrogram (short-time Fourier transform method) + c, compute spectrogram (multitaper method) + c, compute spectrogram (short-time Fourier transform method) + c +
    +
    +
    +
    +

    compute spectrogram (multitaper method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeSpectrogramMultitaper

    +
    + A spectrogram analysis that uses a multitaper approach to obtain the time-frequency information from the input and that is used to build the spectrogram. +
    +
    +
    has super-classes
    +
    + spectrogram analysis + c +
    +
    is disjoint with
    +
    + compute cross-spectrogram (short-time Fourier transform method) + c, compute spectrogram (Morlet wavelet method) + c, compute spectrogram (short-time Fourier transform method) + c +
    +
    +
    +
    +

    compute spectrogram (short-time Fourier transform method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeSpectrogramShortTimeFourierTransform

    +
    + A spectrogram analysis that uses the short-time Fourier transform (STFT) on the input to obtain the time-frequency information used to build the spectrogram. +
    +
    +
    has super-classes
    +
    + spectrogram analysis + c +
    +
    is disjoint with
    +
    + compute cross-spectrogram (short-time Fourier transform method) + c, compute spectrogram (Morlet wavelet method) + c, compute spectrogram (multitaper method) + c +
    +
    +
    +
    +

    compute SPIKE distancec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeSPIKEDistance

    +
    + A time-scale independent spike train distance analysis that computes the SPIKE-distance, described in Kreuz et al. (2012). For the computation, the discrete sequence of spike times is transformed in a continuous temporal profile with one value per sample point. The values at each time point are derived from the differences in the spike times of the two input spike trains. Compared to the ISI-distance, the SPIKE-distance is more sensitive to spike timing. +
    +
    +
    has super-classes
    +
    + time-scale independent spike train distance analysis + c +
    +
    +
    +
    +

    compute SPIKE synchronizationc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeSPIKESynchronization

    +
    + A time-scale independent spike train distance analysis that computes the SPIKE synchronization distance, described in Kreuz et al. (2015). The distance detects coincidences in the spiking activity and can quantify the degree of synchrony in the input spike trains. The metric quantifies the overall fraction of coincidences. It is zero-valued if and only if the input spike trains do not contain any coincidences. It has a value of 1 if and only if each spike in every input spike train has one matching spike in all the other spike trains. +
    +
    +
    has super-classes
    +
    + time-scale independent spike train distance analysis + c +
    +
    +
    +
    +

    compute spike time tiling coefficientc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeSpikeTimeTilingCoefficient

    +
    + A spike train correlation analysis that computes the spike time tiling coefficient (STTC) as described by Cutts and Eglen (2014). The STTC measures the pairwise correlation between two input spike trains, and has advantages over the related correlation index: it is not confounded by the firing rate, it distinguishes lack of correlation from anti-correlation, periods without neural activity don't add to the correlation, and it is sensitive to firing patterns. The computation is based on a synchronicity window parameter, that is used to define short time windows around each spike that are used in the computation (spike time tiling). +
    +
    +
    has super-classes
    +
    + spike train correlation analysis + c +
    +
    +
    +
    +

    compute spike train autocorrelation histogramc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeSpikeTrainAutocorrelationHistogram

    +
    + An autocorrelation analysis that computes the autocorrelation histogram for a input spike train. The histogram is obtained by sliding a time window that is discretized into smaller time intervals (bins) centered on a spike (corresponding to the lag zero). The spike count in each bin is obtained. Therefore, this binning process measures the number of spikes occurring at various time lags relative to the center spike. The histogram window is slidden over each spike in the input spike train, and the spike count in each bin is accumulated to produce the autocorrelation histogram output. The width of the bin interval is controlled by a parameter. +
    +
    +
    has super-classes
    +
    + autocorrelation analysis + c +
    +
    +
    +
    +

    compute spike train autocorrelation time scalec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeSpikeTrainAutocorrelationTimeScale

    +
    + An analysis step that computes the autocorrelation time of a binned spike train input (spike train autocorrelation time scale). The computation follows the method described by Wieland et al. (2015). +
    +
    +
    has super-classes
    +
    + analysis step + c +
    +
    +
    +
    +

    compute spike train cross-correlation histogramc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeSpikeTrainCrossCorrelationHistogram

    +
    + A cross-correlation analysis that computes the cross-correlation histogram (CCH) for a pair of input spike trains. The CCH shows how often spikes in the reference spike train occur before or after spikes in the reference spike train, at distinct lag intervals. For the computation, the spike trains are aligned in time. The histogram is obtained by sliding a time window that is discretized into smaller time intervals (bins) centered on a spike of the first (reference) input spike train (corresponding to the lag zero). The spike count of the second (target) spike train input is then obtained in each bin. Therefore, this binning process measures the number of spikes in the target spike train occurring at various time lags relative to the spikes in the reference spike train. The histogram window is slidden over each spike in the reference spike train, and the spike count in each bin is accumulated to produce the CCH output. The width of the bin interval is controlled by a parameter. +
    +
    +
    has super-classes
    +
    + cross-correlation analysis + c +
    +
    has sub-classes
    +
    + compute spike train cross-correlation histogram (Eggermont method) + c +
    +
    +
    +
    +

    compute spike train cross-correlation histogram (Eggermont method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeSpikeTrainCrossCorrelationHistogramEggermont

    +
    + A computation of the cross-correlation histogram (CCH) for a pair of binned input spike trains using the method described in Eggermont (2010). The formula is valid for binned spike train inputs with at most one spike per bin, and returns the cross-correlation coefficient for the lags considered (range -1 to 1). +
    +
    +
    has super-classes
    +
    + compute spike train cross-correlation histogram + c +
    +
    +
    +
    +

    compute spike train Fano factorc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeSpikeTrainFanoFactor

    +
    + An analysis step that computes the Fano factor (FF) for a set of input spike trains. For each input spike train, the spike count is obtained. The Fano factor is defined as the ratio of the variance of the spike count to the mean spike count, across all spike trains. The Fano factor is usually computed for spike trains representing the activity of the same neuron over different trials. The value is interpreted as the higher the Fano factor value, the larger the cross-trial non-stationarity. For a stationary Poisson process, the Fano factor has value equal to 1. +
    +
    +
    has super-classes
    +
    + neuronal firing regularity analysis + c +
    +
    +
    +
    +

    compute spike train Pearson correlation coefficientc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeSpikeTrainPearsonCorrelationCoefficient

    +
    + A spike train correlation analysis that computes the Pearson correlation coefficient between two spike train inputs. The Pearson correlation coefficient is a real value that quantifies the linear relationship between the two spike trains. It has range [-1, 1], where 1 indicates a perfect positive linear relationship, -1 indicates a perfect negative linear relationship, and 0 indicates no linear relationship. For the computation, the input spike trains are discretized into time intervals (bins), and the spike count is obtained in each bin. The Pearson correlation coefficient is obtained by normalizing the covariance between the binned spike trains: the covariance is divided by the product of the standard deviation of each. +
    +
    +
    has super-classes
    +
    + spike train correlation analysis + c +
    +
    +
    +
    +

    compute spike train time histogramc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeSpikeTrainTimeHistogram

    +
    + An analysis step that computes the time histogram of a spike train. If the spike count in a bin is divided by the duration of the bin, this can be used to estimate the instantaneous firing rate at the bin interval. +
    +
    +
    has super-classes
    +
    + spike train time histogram analysis + c +
    +
    +
    +
    +

    compute spike waveform averagec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeSpikeWaveformAverage

    +
    + A spike waveform analysis that computes the average across two or more spike waveform inputs. For the computation, the mean value across all inputs is obtained for each time point in the sampled spike waveform. This is frequently used to reduce noise across multiple spike waveform samples of a single neuron. +
    +
    +
    has super-classes
    +
    + spike waveform analysis + c +
    +
    +
    +
    +

    compute spike waveform signal-to-noise ratioc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeSpikeWaveformSNR

    +
    + A spike waveform analysis that computes the signal-to-noise ratio (SNR) for a set of input spike waveforms according to Hatsopoulos (2007). The SNR is defined as the difference in mean peak-to-trough voltage divided by twice the mean standard deviation (SD).The mean SD is obtained by averaging the SDs computed for each time point in the spike waveform. +
    +
    +
    has super-classes
    +
    + spike waveform analysis + c +
    +
    +
    +
    +

    compute spike waveform variancec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeSpikeWaveformVariance

    +
    + A spike waveform analysis that computes the variance across two or more spike waveform inputs. For the computation, the value of the variance across all inputs is obtained for each time point in the spike waveform. +
    +
    +
    has super-classes
    +
    + spike waveform analysis + c +
    +
    +
    +
    +

    compute spike waveform widthc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeSpikeWaveformWidth

    +
    + A spike waveform analysis that computes the width of a spike waveform input. The computation takes two time points of interest (e.g, the times of the peak and the trough), and the width is the difference with respect to the time points (e.g., number of time points in between or time interval). +
    +
    +
    has super-classes
    +
    + spike waveform analysis + c +
    +
    +
    +
    +

    compute Spike-contrastc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeSpikeContrast

    +
    + A spike train synchrony analysis that computes the Spike-contrast measure using the method described by Ciba et al. (2018). Spike-contrast is a time-scale independent measure of spike synchrony. The input is a set of parallel spike train data recorded from a population of neurons. The algorithm is based on the temporal "contrast" (activity vs. non-activity in certain time bins). The computation outputs a single synchrony value (comparable to a spike train distance) and a synchrony curve showing the value of Spike-contrast as a function of the bin size. +
    +
    +
    has super-classes
    +
    + spike train synchrony analysis + c +
    +
    +
    +
    +

    compute spike-field coherence (Fries method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeSpikeFieldCoherenceFries

    +
    + A spike-field coherence analysis that uses the method described in Fries et al. (2001) to compute the coherence between the spike train and the LFP. For the computation, first a spike-triggered average (STA) is obtained between the spike train and the LFP time series. Then, the power spectrum is obtained for each of the LFP segments used for the computation of the STA. These spectra are averaged to obtain the spike-triggered power spectrum. The SFC is then computed as the ratio of the power spectrum of the STA over the spike-triggered power spectrum. +
    +
    +
    has super-classes
    +
    + spike-field coherence analysis + c +
    +
    is disjoint with
    +
    + compute spike-field coherence (multitaper method) + c, compute spike-field coherence (Welch method) + c +
    +
    +
    +
    +

    compute spike-field coherence (multitaper method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeSpikeFieldCoherenceMultitaper

    +
    + A spike-field coherence analysis that uses a multitaper approach to compute the coherence between the spike train and the LFP. +
    +
    +
    has super-classes
    +
    + spike-field coherence analysis + c +
    +
    is disjoint with
    +
    + compute spike-field coherence (Fries method) + c, compute spike-field coherence (Welch method) + c +
    +
    +
    +
    +

    compute spike-field coherence (Welch method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeSpikeFieldCoherenceWelch

    +
    + A spike-field coherence analysis step that uses the method by Welch (1967) to compute the coherence between the spike train and the LFP. +
    +
    +
    has super-classes
    +
    + spike-field coherence analysis + c +
    +
    is disjoint with
    +
    + compute spike-field coherence (Fries method) + c, compute spike-field coherence (multitaper method) + c +
    +
    +
    +
    +

    compute spike-triggered averagec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeSpikeTriggeredAverage

    +
    + A triggered average analysis that uses spike times as triggers to obtain the average of a signal around each spike (spike-triggered average). +
    +
    +
    has super-classes
    +
    + triggered average analysis + c +
    +
    has sub-classes
    +
    + compute spike-triggered local field potential average + c +
    +
    +
    +
    +

    compute spike-triggered local field potential averagec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeSpikeTriggeredLFPAverage

    +
    + A triggered average analysis that uses spike times as triggers to average the local field potential (LFP) signal. The LFP is the low-frequency component of the potential recorded within a specific region of the brain using extracellular electrodes. The output of the method will provide an estimation of the average LFP voltage around each spike, i.e., the spike-triggered average of the LFP signal. +
    +
    +
    has super-classes
    +
    + compute spike-triggered average + c +
    +
    +
    +
    +

    compute spike-triggered phasec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeSpikeTriggeredPhase

    +
    + A phase analysis that computes the phase angle values of an analytic signal input (or from the analytic signal obtained from an input time series) at the time points where spikes occurred. The spike times are defined in a spike train input. The output is an array with the phase angle at each spike time in the input spike train (spike-triggered phases). +
    +
    +
    has super-classes
    +
    + phase analysis + c +
    +
    +
    +
    +

    compute standard deviationc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeStandardDeviation

    +
    + A dispersion statistical analysis that computes the standard deviation (SD), i.e., the square root of the variance. The SD indicates the average distance of each data point from the mean. +
    +
    +
    has super-classes
    +
    + dispersion statistical analysis + c +
    +
    +
    +
    +

    compute standard error of the meanc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeStandardErrorMean

    +
    + A dispersion statistical analysis that computes the standard error of the mean (SEM). The SEM is the standard deviation of the sampling distribution of the sample mean. It provides an estimate of how much the sample mean is expected to fluctuate around the true population mean. Smaller SEM values indicates that the sample mean is a more accurate estimate of the population mean. The SEM decreases as the sample size increases, as larger samples provide a more reliable estimate of the population mean. +
    +
    +
    has super-classes
    +
    + dispersion statistical analysis + c +
    +
    +
    +
    +

    compute Stockwell transformc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeStockwellTransform

    +
    + A time-frequency analysis that computes the Stockwell transform (S transform) of the input time series. The S transform generalizes the short-time Fourier transform (STFT) and extends the continuous wavelet transform (CWT). The main difference is that STFT uses a constant window width for all frequencies. The S transform is based on a moving and scalable localizing Gaussian window. Therefore, the window is frequency-dependent (adaptive windowing), which results in better time resolution in higher frequencies and better frequency resolution at lower frequencies. This makes the S transform more suitable to detect transient signals in high frequencies. The computation is computationally expensive, although fast algorithms are available. +
    +
    +
    has super-classes
    +
    + time-frequency analysis + c +
    +
    +
    +
    +

    compute time domain conditional Granger causalityc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeTimeDomainConditionalGrangerCausality

    +
    + A conditional Granger causality (GC) analysis that computes the GC measures in the time domain. +
    +
    +
    has super-classes
    +
    + conditional Granger causality analysis + c +
    +
    is disjoint with
    +
    + compute frequency domain conditional Granger causality + c +
    +
    +
    +
    +

    compute time domain pairwise Granger causalityc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeTimeDomainPairwiseGrangerCausality

    +
    + A pairwise Granger causality (GC) analysis that computes measures of GC between two inputs in the time domain. The computation involves fitting two separate autoregressive (AR) models to the input data and comparing their fit to determine if one time series can predict the other. The quality of the fit is assessed by the variance of the residuals, with GC defined as the natural logarithm of the ratio of the residual variances from the two AR models. The first AR model is univariate, predicting the future values of one time series (e.g., the first) only from its past values. The second AR model is bivariate, predicting the future values of the first time series from its past values as well as the past values of the second time series. If the bivariate model reduces the variance of the residuals (ratio greater than 1), the GC value will be positive, indicating that the second time series Granger causes the first (directional GC estimate from the second to the first). The same method is used to predict the second time series from the first, yielding the directional GC estimate from the first to the second time series. The order of the AR model is defined as parameter, and optimal values can be estimated using optimization techniques. +
    +
    +
    has super-classes
    +
    + pairwise Granger causality analysis + c +
    +
    is disjoint with
    +
    + frequency domain pairwise granger causality analysis + c +
    +
    +
    +
    +

    compute transfer entropyc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeTransferEntropy

    +
    + A functional connectivity analysis that computes a measure of transfer entropy (TE) between two input time series. TE measures the directional transfer of information between the time series. It extends Granger causality, and is able to detect non-linear forms of interaction. +
    +
    +
    has super-classes
    +
    + functional connectivity analysis + c +
    +
    +
    +
    +

    compute tuning curvec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeTuningCurve

    +
    + A firing rate analysis that computes a tuning curve. The tuning curve describes the firing rate of a neuron as a function of a continuous attribute (e.g., orientation of a visual grating stimulus). +
    +
    +
    has super-classes
    +
    + firing rate analysis + c +
    +
    +
    +
    +

    compute unbiased squared phase lag indexc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeUnbiasedSquaredPhaseLagIndex

    +
    + A phase lag index (PLI) analysis that computes an unbiased estimate for the squared PLI following Vinck et al. (2011). The direct PLI estimator is positively biased, especially when the sample sizes (i.e., number of trials) are small. The unbiased squared PLI is computed by averaging all pairwise products of the signs computed across the repetitions. Pairs with identical observations are excluded. The unbiased squared PLI is less affected by small-sample size biases. +
    +
    +
    has super-classes
    +
    + phase lag index analysis + c +
    +
    +
    +
    +

    compute van Rossum distancec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeVanRossumDistance

    +
    + A time-scale dependent spike train distance analysis that computes the van Rossum distance introduced in van Rossum (2001). For the computation, each spike in the input spike trains is convolved with an exponential kernel, producing continuous function representations of the input spike trains. The time scale parameter of the distance is set by the time constant of the exponential kernel. The distance is then obtained as the Euclidean distance of the convolved spike trains. +
    +
    +
    has super-classes
    +
    + time-scale dependent spike train distance analysis + c +
    +
    +
    +
    +

    compute variancec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeVariance

    +
    + A dispersion statistical analysis that computes the variance, i.e., the average of the squared differences from the mean. +
    +
    +
    has super-classes
    +
    + dispersion statistical analysis + c +
    +
    +
    +
    +

    compute Victor-Purpura distancec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeVictorPurpuraDistance

    +
    + A time-scale dependent spike train distance analysis that computes the Victor-Purpura distance, introduced in Victor & Purpura (1996). The metric defines the distance between two spike train inputs with respect to the minimum cost of transforming one spike train into the order considering three operations: spike insertion, spike deletion and shifting a spike by some interval. The first two operations have a fixed cost equal to 1. The latter depends on a cost per time unit parameter, which sets the time scale of the analysis. +
    +
    +
    has super-classes
    +
    + time-scale dependent spike train distance analysis + c +
    +
    +
    +
    +

    compute weighted phase lag indexc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ComputeWeightedPhaseLagIndex

    +
    + A phase lag index (PLI) analysis that computes the weighted PLI (WPLI) following Vinck et al. (2011). The original PLI (Stam, 2007) is discontinuous, and small perturbations can turn phase lags into leads (and vice versa). Therefore, this hinders its capacity to detect changes in phase synchronization of small magnitude. The WPLI extends the PLI to weight the contributions of the phase leads and lags by the magnitude of the imaginary component of the cross spectral density. Therefore, these increases the power to detect changes in phase synchronization. The WPLI ranges between 0 and 1. A WPLI of zero means that there is no imbalance in the first time series leading or lagging the second (i.e., the total weight of all leading relationships is equal to the total weight of lagging relationships). A value greater than zero means an imbalance in the likelihood of leading or lagging. A WPLI of 1 indicates perfect phase locking, and that the first time series only leads or only lags. +
    +
    +
    has super-classes
    +
    + phase lag index analysis + c +
    +
    +
    +
    +

    conditional Granger causality analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ConditionalGrangerCausalityAnalysis

    +
    + A Granger causality (GC) analysis that computes a measure of conditional GC between the inputs. The conditional GC is the causality between two inputs (e.g., two time series) while controlling for the influence of an additional input (e.g., a third time series). This allows a more complete understanding of the causal relationships in multivariate time series data. +
    +
    +
    has super-classes
    +
    + Granger causality analysis + c +
    +
    has sub-classes
    +
    + compute frequency domain conditional Granger causality + c, compute time domain conditional Granger causality + c +
    +
    is disjoint with
    +
    + pairwise Granger causality analysis + c +
    +
    +
    +
    +

    confidence interval statistical analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ConfidenceIntervalStatisticalAnalysis

    +
    + A statistical analysis that computes a confidence interval (CI). The CI is a measure providing a range of values of a parameter, derived from the input (sample) data, that is likely to contain the true value of the parameter in the population with a specified level of confidence. The level of confidence is specified as a parameter to the method. For example, a 95% confidence interval means that if the same population is sampled multiple times, approximately 95% of the intervals calculated from those samples will contain the true population parameter. Confidence intervals are used to estimate parameters such as the mean and are essential for making inferences about the population based on sample data. The output contains the upper and lower limits of the CI. +
    +
    +
    has super-classes
    +
    + statistical analysis + c +
    +
    has sub-classes
    +
    + compute confidence interval (non-resampling) + c, confidence interval with resampling analysis + c +
    +
    +
    +
    +

    confidence interval with resampling analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ConfidenceIntervalResamplingAnalysis

    +
    + A confidence interval statistical analysis that computes the confidence interval using techniques to generate multiple samples from the (observed) data input(s). +
    +
    +
    has super-classes
    +
    + confidence interval statistical analysis + c +
    +
    has sub-classes
    +
    + compute confidence interval (bootstrap resampling) + c, compute confidence interval (jackknife resampling) + c +
    +
    is disjoint with
    +
    + compute confidence interval (non-resampling) + c +
    +
    +
    +
    +

    correlated spike times generationc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#CorrelatedSpikeTimesGeneration

    +
    + A spike train generation where the output spike trains will have spikes that are correlated in time. These methods can be used to generate spike trains with patterns in their activity. +
    +
    +
    has super-classes
    +
    + spike train generation + c +
    +
    has sub-classes
    +
    + generate compound Poisson process + c, generate single interaction process + c +
    +
    is disjoint with
    +
    + random spike times generation + c +
    +
    +
    +
    +

    correlation analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#CorrelationAnalysis

    +
    + An analysis step that computes a measure of correlation between two inputs. Correlation is a measure that quantifies the strength to which two variables change together. It is a scaled version of the covariance, and the values are restricted to the -1 to +1 interval. Between time series, it is computed in the time domain. +
    +
    +
    is equivalent to
    +
    + has purpose + op + value + correlation purpose +
    +
    has super-classes
    +
    + analysis step + c +
    +
    has sub-classes
    +
    + compute orthogonalized power envelope correlation + c +
    +
    +
    +
    +

    covariance analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#CovarianceAnalysis

    +
    + An analysis step used to compute a measure of covariance from two inputs. The covariance indicates the extent to which the two inputs change together. If the greater values of one variable mainly correspond with the greater values of the other variable, and the same applies to the lesser values, then the covariance is positive. Conversely, if greater values of one variable mainly correspond to the lesser values of the other variable, then the covariance is negative. +
    +
    +
    has super-classes
    +
    + analysis step + c +
    +
    has sub-classes
    +
    + compute covariance + c, compute noise covariance + c +
    +
    +
    +
    +

    cross power spectral density analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#CrossPowerSpectralDensityAnalysis

    +
    + A spectral density analysis that computes the cross power spectral density (CPSD) of two inputs, i.e., the distribution of their power across the different frequency components per unit frequency. The CPSD shows in the frequency domain how the two inputs are correlated in the time domain, and is equivalent to the Fourier transform of the cross-correlation function between the two signals. If the inputs are not correlated, the CPSD will be flat across the frequencies. A peak suggests that the signals are correlated at that frequency. The CPSD is often referred to as cross-spectrum. +
    +
    +
    has super-classes
    +
    + spectral density analysis + c +
    +
    has sub-classes
    +
    + compute cross power spectral density (Morlet wavelet method) + c, compute cross power spectral density (Welch method) + c, compute cross power spectral density (multitaper method) + c, compute cross power spectral density (periodogram method) + c +
    +
    +
    +
    +

    cross-correlation analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#CrossCorrelationAnalysis

    +
    + An analysis step used to compute a measure of cross-correlation, i.e., the correlation of two inputs computed for distinct time lags of the first to the second. The computation produces the cross-correlation value for every lag considered. +
    +
    +
    has super-classes
    +
    + analysis step + c +
    +
    has sub-classes
    +
    + compute cross-correlation function + c, compute spike train cross-correlation histogram + c +
    +
    +
    +
    +

    current source density analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#CurrentSourceDensityAnalysis

    +
    + An analysis step used to analyze extracellular electrical potentials (e.g., local field potentials or evoked potentials) recorded from multiple locations, enabling the estimation of the current sources responsible for generating these potentials. The methods can be applied to data recorded from different electrode configurations: laminar probe-like electrodes (1D methods), microelectrode array-like electrodes (2D methods) or electrodes configurations recording from a volume (e.g., multiple laminar probes or array electrodes with shanks with multiple depths; 3D methods). The output of the current source analysis provides the spatial map showing where currents are entering (sources) and leaving (sinks) the neural tissue. For each point in the map, a quantitative value indicates the magnitude of the current density at that point. +
    +
    +
    has super-classes
    +
    + analysis step + c +
    +
    has sub-classes
    +
    + compute current source density (inverse method) + c, compute current source density (kernel method) + c, compute current source density (standard method) + c +
    +
    +
    +
    +

    data generationc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#DataGeneration

    +
    + An analysis step that generates new data entities. This can be done using other input data as a start (e.g., generating a spike train surrogate from spike trains obtained from experimental recordings) or generate new data using algorithms that take specific parameters (e.g., generating a spike train using a probability distribution defined by specific parameters). +
    +
    +
    has super-classes
    +
    + analysis step + c +
    +
    has sub-classes
    +
    + artificial data generation + c, generate Morlet wavelet + c, spike train generation + c, spike train surrogate generation + c +
    +
    +
    +
    +

    data normalizationc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#DataNormalization

    +
    + A data transformation that adjusts the ranges and distributions of the values in the input data. This can be used to transform data measured in distinct (i.e. not directly comparable) scales to a common (i.e. comparable) scale. +
    +
    +
    has super-classes
    +
    + data transformation + c +
    +
    has sub-classes
    +
    + apply median rescaling + c, apply min-max normalization + c, apply z-score transform + c +
    +
    +
    +
    +

    data smoothingc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#DataSmoothing

    +
    + A data transformation that uses statistical techniques to remove noise and fluctuations from the input data to reveal underlying trends and patterns. +
    +
    +
    has super-classes
    +
    + data transformation + c +
    +
    has sub-classes
    +
    + apply local regression and likelihood smoothing + c, kernel smoothing + c +
    +
    +
    +
    +

    data transformationc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#DataTransformation

    +
    + An analysis step that takes one or more inputs and modifies the contents, such that it fits a particular purpose. The data transformation steps are frequently used during pre-processing the input data for the analyses. Usually, a data transformation will not change the main representation or quality of the inputs. For example, a digital filtering step will remove certain frequency components from a time series. However, the output will resemble the original input with respect to shape or physical units. In addition, the inputs can also be converted to other formats or representations that are needed for a particular analysis step. For example, spike trains can be discretized into small intervals (binning) or the dimensionality of the input can be reduced using principal component analysis. The data transformation is in contrast to steps that perform computations that take the input and generate a derived measure with new information. For example, when computing the mean firing rate from a spike train, a single scalar value is obtained from the spike count in the input data. +
    +
    +
    has super-classes
    +
    + analysis step + c +
    +
    has sub-classes
    +
    + apply Hilbert transform + c, apply analytic signal conversion + c, apply data concatenation + c, apply independent component analysis + c, apply interpolation + c, apply padding + c, apply rectification + c, apply rereference + c, apply spike extraction from time series + c, apply spike train binarization + c, apply spike train binning + c, apply spike waveform peak alignment + c, apply sum + c, apply trial extraction + c, artifact removal + c, data normalization + c, data smoothing + c, detrending + c, digital filtering + c, dimensionality reduction + c, frequency domain transformation + c, line noise removal + c, resampling + c +
    +
    +
    +
    +

    detrendingc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#Detrending

    +
    + A data transformation that removes a trend (i.e., a change in the mean over time) from an input time series. +
    +
    +
    has super-classes
    +
    + data transformation + c +
    +
    has sub-classes
    +
    + apply general linear model polynomial detrending + c, apply local linear regression detrending + c +
    +
    +
    +
    +

    digital filteringc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#DigitalFiltering

    +
    + A data transformation that processes digital signal inputs (i.e., sampled time series) to attenuate or amplify specific frequency components. Digital filters can be designed using various methods, achieving distinct frequency responses and stability. +
    +
    +
    has super-classes
    +
    + data transformation + c +
    +
    has sub-classes
    +
    + finite impulse response filtering + c, infinite impulse response filtering + c +
    +
    +
    +
    +

    dimensionality reductionc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#DimensionalityReduction

    +
    + A data transformation that obtains a low-dimensional (simplified) representation of the high-dimensional input data. This step retains important information in the input data while minimizing redundancy and noise. +
    +
    +
    has super-classes
    +
    + data transformation + c +
    +
    has sub-classes
    +
    + apply distance covariance analysis + c, apply linear discriminant analysis + c, apply neural trajectory Gaussian process factor analysis + c, principal component analysis + c, tensor component analysis + c +
    +
    +
    +
    +

    directed analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#DirectedAnalysis

    +
    + An analysis step where the output provides information on the direction of influence in the relationships among the inputs (e.g., in the cross-correlation histogram, it is possible to analyze the timing of the spikes of the first input spike train with respect to the timing of the spikes of the second input spike train, i.e., whether they likely occur before or after). +
    +
    +
    is equivalent to
    +
    + is directed + dp + value true
    +
    has super-classes
    +
    + analysis step + c +
    +
    is disjoint with
    +
    + non-directed analysis + c +
    +
    +
    +
    +

    dispersion statistical analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#DispersionStatisticalAnalysis

    +
    + A statistical analysis that computes a measure that represents the variability in the input data. It indicated the degree to which the data points differ from the central tendency. +
    +
    +
    has super-classes
    +
    + statistical analysis + c +
    +
    has sub-classes
    +
    + compute coefficient of variation + c, compute interquartile range + c, compute standard deviation + c, compute standard error of the mean + c, compute variance + c +
    +
    +
    +
    +

    distance analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#DistanceAnalysis

    +
    +
    is equivalent to
    +
    + has purpose + op + value + distance purpose +
    +
    has super-classes
    +
    + analysis step + c +
    +
    +
    +
    +

    execute 3d-SPADE analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#Execute3dSPADEAnalysis

    +
    + A SPADE analysis that uses the 3d-SPADE implementation as defined in Stella et al. (2019). The 3d-SPADE analysis considers spatio-temporal patterns (i.e., not restricted to synchronous patterns), and the pattern signature used for statistical testing considers the size, number of occurrences and duration of a pattern. +
    +
    +
    has super-classes
    +
    + SPADE analysis + c +
    +
    is disjoint with
    +
    + execute non-3d-SPADE analysis + c +
    +
    +
    +
    +

    execute ASSET analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ExecuteASSETAnalysis

    +
    + A neuronal activity pattern detection analysis that uses the Analysis of Sequences of Synchronous EvenTs (ASSET) method defined in Torre et al. (2016). ASSET is an automatized test to identify the sequential activations of groups of neurons that repeat in time. The identification of the repeated sequences is possible by computing the intersection matrix. The input spike data is discretized into smaller intervals (bins), and the overlap of neuronal activity at each bin pair is obtained as a matrix. When a sequence of activations exists and repeats in time, a characteristic diagonal structure appears in the matrix. + +The ASSET analysis provides a robust statistical test to automatically identify the diagonal structures and to provide the neurons and their activation pattern in each repeated sequence. Overall, the analysis is composed by 6 substeps: + +1. Compute the intersection matrix (IMAT) from a set of input spike trains, using a specified bin size to discretize the data. +2. Obtain the probability matrix (PMAT). +3. Obtain the joint probability matrix (JMAT). +4. Extract significant entries in both PMAT and JMAT using specified thresholds, obtaining the mask matrix (MMAT). +5. Obtain the cluster matrix (CMAT) by using DBSCAN to cluster the significant entries in the MMAT to find each diagonal structure. Parameters for DBSCAN control the clustering result. A modified distance metric is used. +6. From the identified clusters (each a single diagonal structure in the IMAT), obtain the neuronal composition and the order of activation, producing the final neuronal activity patterns as output. +
    +
    +
    has super-classes
    +
    + neuronal activity pattern detection analysis + c +
    +
    +
    +
    +

    execute Cell Assembly Detection analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ExecuteCellAssemblyDetectionAnalysis

    +
    + A neuronal activity pattern detection analysis that uses the Cell Assembly Detection (CAD) method as defined in Russo & Durstewitz (2017). CAD allows detecting spatio-temporal spike patterns at different time scales, levels of precision, and with arbitrary internal organization. The analysis identifies patterns with different delays between the spikes (within a window determining the minimum and maximum lags), and is performed in two steps using an agglomerative clustering algorithm. First, significant pairwise correlations are identified, which is followed by the clustering procedure that progressively finds interactions of higher order. At each agglomeration step, the method can filter out patterns involving the same neurons, keeping the most significant pattern (significance pruning). In an additional pruning step, assemblies part of a larger assembly can also be eliminated (controlled by the subgroup pruning parameter). The algorithm stops when the detected assemblies reach their maximum size (determined by a parameter). The statistical test assumes independence under non-stationarity and Poisson distribution of the input spike trains. +
    +
    +
    has super-classes
    +
    + neuronal activity pattern detection analysis + c +
    +
    +
    +
    +

    execute non-3d-SPADE analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ExecuteNon3dSPADEAnalysis

    +
    + A SPADE analysis that uses the SPADE implementation as defined in Quaglio et al. (2017). This is the extension of SPADE to consider spatio-temporal patterns (i.e., patterns not restricted to synchronous spiking). In the non-3d SPADE analysis, the pattern signature used for statistical testing considers only the size and number of occurrences of a pattern. +
    +
    +
    has super-classes
    +
    + SPADE analysis + c +
    +
    is disjoint with
    +
    + execute 3d-SPADE analysis + c +
    +
    +
    +
    +

    execute Unitary Event analysis (analytical method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ExecuteUnitaryEventAnalysisAnalytical

    +
    + A unitary event (UE) analysis that uses the analytical approach to determine the significance of the empirical coincidences in binned spike train data, as defined in Grün et al. (1999, 2002a, 2002b, and 2003). The analytical method tests if the number of empirical coincidences is consistent with the coincidence distribution resulting from independent processes. This distribution can be expressed analytically assuming that the input spike trains follow Poisson statistics. The UEs can be determined trial by trial, where the analytical expectancy is computed for each trial and then summed over all trials, or by averaging over all trials (according to Grün, 2003). +
    +
    +
    has super-classes
    +
    + Unitary Event analysis + c +
    +
    is disjoint with
    +
    + execute Unitary Event analysis (Monte Carlo method) + c +
    +
    +
    +
    +

    execute Unitary Event analysis (Monte Carlo method)c + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ExecuteUnitaryEventAnalysisMonteCarlo

    +
    + A unitary event (UE) analysis that uses a Monte Carlo approach based on spike train surrogates to determine the significance of the empirical coincidences in binned spike train data, according to Grün (2009). The Monte Carlo method does not rely on the assumption that the input spike data follows Poisson statistics. For the assessment of significance, the distribution of expected coincidences is determined by surrogates (spike train randomization) in each trial, and then summed over trials. The number of surrogates is determined by a parameter. +
    +
    +
    has super-classes
    +
    + Unitary Event analysis + c +
    +
    is disjoint with
    +
    + execute Unitary Event analysis (analytical method) + c +
    +
    +
    +
    +

    field-field coupling analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#FieldFieldCouplingAnalysis

    +
    + An analysis step that computes interactions between the neural activity represented by distinct local field potential (LFP) signals (e.g., LFP obtained from different electrodes, or distinct LFP frequency bands). +
    +
    +
    is equivalent to
    +
    + has purpose + op + value + field-field coupling purpose +
    +
    has super-classes
    +
    + analysis step + c +
    +
    is disjoint with
    +
    + spike-spike coupling analysis + c +
    +
    +
    +
    +

    finite impulse response filteringc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#FiniteImpulseResponseFiltering

    +
    + A digital filtering that uses a filter whose impulse response (i.e., the response of the filter to a brief input impulse) decays to zero after a finite amount of time. Therefore, the output of the filter depends on a finite number of past samples. The finite impulse response (FIR) filters are stable and can be designed such that they do not distort the phase of the signal. However, they have a higher computational cost. +
    +
    +
    has super-classes
    +
    + digital filtering + c +
    +
    has sub-classes
    +
    + apply finite impulse response filter + c, apply finite impulse response filter with Kaiser window + c, apply windowed-sinc filter + c +
    +
    +
    +
    +

    firing rate analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#FiringRateAnalysis

    +
    + An analysis step used to compute a measure quantifying the firing rate of one or more neurons. The firing rate is the number of action potential (spikes) that a neuron fires per time unit and is defined with a unit of frequency (e.g., Hz or spikes/s). +
    +
    +
    has super-classes
    +
    + analysis step + c +
    +
    has sub-classes
    +
    + compute mean firing rate + c, compute tuning curve + c, instantaneous firing rate analysis + c, spike train time histogram analysis + c +
    +
    +
    +
    +

    frequency domain analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#FrequencyDomainAnalysis

    +
    + An analysis step that analyzes the input(s) with respect to its(their) frequency content. +
    +
    +
    is equivalent to
    +
    + is frequency domain + dp + value true
    +
    has super-classes
    +
    + analysis step + c +
    +
    is disjoint with
    +
    + time domain analysis + c +
    +
    +
    +
    +

    frequency domain pairwise granger causality analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#FrequencyDomainPairwiseGrangerCausalityAnalysis

    +
    + A pairwise Granger causality (GC) analysis that computes measures of GC between two inputs in the frequency domain. This is an extension of the GC concept in the time domain, and the measures of GC are obtained for the different frequency components of the inputs, according to Geweke (1982). The computation of the frequency-domain GC measures is based on two elements: the noise covariance matrix and the spectral transfer matrix. These can be estimated either with parametric or non-parametric methods. For the parametric estimation, an autoregressive model is fit and the Fourier transform of the autoregressive coefficients is used to obtain the spectral transfer matrix. For the non-parametric estimation, the cross-spectral density (CSD) matrix is obtained (using methods for CSD estimation such as multitapering or wavelet), and the CSD matrix is factorized to obtain the noise covariance and spectral transfer matrices. +
    +
    +
    has super-classes
    +
    + pairwise Granger causality analysis + c +
    +
    has sub-classes
    +
    + compute frequency domain pairwise Granger causality (Brovelli method) + c, compute frequency domain pairwise Granger causality (Dhamala method) + c, compute frequency domain pairwise Granger causality (Hafner method) + c, compute frequency domain pairwise Granger causality (Wen method) + c +
    +
    is disjoint with
    +
    + compute time domain pairwise Granger causality + c +
    +
    +
    +
    +

    frequency domain transformationc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#FrequencyDomainTransformation

    +
    + A data transformation that converts a time series input from the time to the frequency domain, i.e., reveal the different frequency components that make up the original signal. +
    +
    +
    has super-classes
    +
    + data transformation + c +
    +
    has sub-classes
    +
    + apply discrete Fourier transform + c +
    +
    +
    +
    +

    functional connectivity analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#FunctionalConnectivityAnalysis

    +
    + An analysis step that computes measures of functional connectivity. Functional connectivity refers to statistical dependencies and patterns of synchronization between the neural activity that indicate the functional interactions and co-activations that are relevant for the function of the nervous system (e.g., the interactions between different brain regions). It does not imply direct physical connections. +
    +
    +
    is equivalent to
    +
    + has purpose + op + value + functional connectivity purpose +
    +
    has super-classes
    +
    + analysis step + c +
    +
    has sub-classes
    +
    + Granger causality analysis + c, compute directed transfer function + c, compute multivariate interaction measure + c, compute mutual information + c, compute transfer entropy + c +
    +
    +
    +
    +

    generate compound Poisson processc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#GenerateCompoundPoissonProcess

    +
    + A correlated spike times generation that produces spike trains using a compound Poisson process (CPP) according to Staude et al. (2010). The CPP is a model for parallel and correlated processes with Poisson spiking statistics at predefined firing rates. +
    +
    +
    has super-classes
    +
    + correlated spike times generation + c +
    +
    is disjoint with
    +
    + generate single interaction process + c +
    +
    +
    +
    +

    generate interspike interval shuffling surrogatec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#GenerateISIShufflingSurrogate

    +
    + A spike train surrogate generation step where the interspike intervals (ISIs) of the input spike train is randomly sorted. This preserves the ISI distribution and spike count as in the original spike train input, but destroys temporal dependencies and firing rate profile. +
    +
    +
    has super-classes
    +
    + spike train surrogate generation + c +
    +
    is disjoint with
    +
    + generate joint interspike interval dithering surrogate + c, generate joint interspike interval dithering surrogate + c, generate spike time randomization surrogate + c, generate spike train dithering surrogate + c, generate trial shifting surrogate + c, generate trial shuffling surrogate + c, generate uniform spike dithering surrogate + c, generate uniform spike dithering surrogate with dead time + c, generate window shuffling surrogate + c +
    +
    +
    +
    +

    generate joint interspike interval dithering surrogatec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#GenerateISIDitheringSurrogate

    +
    + A spike train surrogate generation step where each spike is displaced according to the interspike interval (ISI) distribution sampled from the input spike train. +
    +
    +
    has super-classes
    +
    + spike train surrogate generation + c +
    +
    is disjoint with
    +
    + generate interspike interval shuffling surrogate + c, generate joint interspike interval dithering surrogate + c, generate spike time randomization surrogate + c, generate spike train dithering surrogate + c, generate trial shifting surrogate + c, generate trial shuffling surrogate + c, generate uniform spike dithering surrogate + c, generate uniform spike dithering surrogate with dead time + c, generate window shuffling surrogate + c +
    +
    +
    +
    +

    generate joint interspike interval dithering surrogatec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#GenerateJointISIDitheringSurrogate

    +
    + A spike train surrogate generation step where spikes from adjacent interspike intervals (ISIs) are dithered according to the joint-ISI (JISI) probability distribution. The distribution is obtained from the input spike train by computing the JISI histogram (i.e., a two-dimensional histogram that shows the frequency of ISIs with a given duration that are immediately followed by intervals with another duration). Due to non-stationarities in the input spike train and/or its limited duration, it is difficult to accurately estimate the underlying JISI probability distribution. Therefore, a 2D-Gaussian smoothing is applied to the JISI histogram (with a variance determined by parameter). Dithering a spike according to this (smoothed) two-dimensional histogram involves moving the spike along the anti-diagonal of the JISI distribution. The dithering time is defined by a parameter. +
    +
    +
    has super-classes
    +
    + spike train surrogate generation + c +
    +
    is disjoint with
    +
    + generate joint interspike interval dithering surrogate + c, generate interspike interval shuffling surrogate + c, generate spike time randomization surrogate + c, generate spike train dithering surrogate + c, generate trial shifting surrogate + c, generate trial shuffling surrogate + c, generate uniform spike dithering surrogate + c, generate uniform spike dithering surrogate with dead time + c, generate window shuffling surrogate + c +
    +
    +
    +
    +

    generate Morlet waveletc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#GenerateMorletWavelet

    +
    + A data generation that constructs a Morlet wavelet considering the selected parameters (i.e., sampling frequency, fundamental frequency, and number of cycles per frequency). The Morlet wavelet is composed by a complex exponential multiplied by a Gaussian window. The output data contains the discrete time points and the corresponding wavelet values. +
    +
    +
    has super-classes
    +
    + data generation + c +
    +
    +
    +
    +

    generate non-stationary gamma processc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#GenerateNonStationaryGammaProcess

    +
    + A random spike times generation that uses a gamma probability distribution to produce spike trains where the firing rate varies over time. +
    +
    +
    has super-classes
    +
    + random spike times generation + c +
    +
    is disjoint with
    +
    + generate non-stationary Poisson process + c, generate stationary gamma process + c, generate stationary inverse Gaussian process + c, generate stationary log-normal process + c, generate stationary Poisson process + c +
    +
    +
    +
    +

    generate non-stationary Poisson processc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#GenerateNonStationaryPoissonProcess

    +
    + A random spike times generation that uses a Poisson probability distribution to produce spike trains where the firing rate varies over time. A dead time can be specified as parameter (i.e., an interval where no spikes can occur, which is analogous to the neuronal refractory period). +
    +
    +
    has super-classes
    +
    + random spike times generation + c +
    +
    is disjoint with
    +
    + generate non-stationary gamma process + c, generate stationary gamma process + c, generate stationary inverse Gaussian process + c, generate stationary log-normal process + c, generate stationary Poisson process + c +
    +
    +
    +
    +

    generate single interaction processc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#GenerateSingleInteractionProcess

    +
    + A correlated spike times generation that produces a multidimensional Poisson single interaction process (SIP) plus independent Poisson processes, according to Kuhn et al. (2003). The Poisson SIP consists of Poisson time series that are independent except for events that are simultaneous in all of them. +
    +
    +
    has super-classes
    +
    + correlated spike times generation + c +
    +
    is disjoint with
    +
    + generate compound Poisson process + c +
    +
    +
    +
    +

    generate spike time randomization surrogatec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#GenerateSpikeTimeRandomizationSurrogate

    +
    + A spike train surrogate generation step that keeps the spike count of the input spike train, but the spike times in the surrogate spike train output are randomly chosen within the duration interval of the input spike train. +
    +
    +
    has super-classes
    +
    + spike train surrogate generation + c +
    +
    is disjoint with
    +
    + generate joint interspike interval dithering surrogate + c, generate interspike interval shuffling surrogate + c, generate joint interspike interval dithering surrogate + c, generate spike train dithering surrogate + c, generate trial shifting surrogate + c, generate trial shuffling surrogate + c, generate uniform spike dithering surrogate + c, generate uniform spike dithering surrogate with dead time + c, generate window shuffling surrogate + c +
    +
    +
    +
    +

    generate spike train dithering surrogatec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#GenerateSpikeTrainDitheringSurrogate

    +
    + A spike train surrogate generation step that displaces the whole input spike train by a random amount of time (independent for each surrogate generated). The amount of displacement is specified as a parameter (dither time), and occurs in a window (-dither time, dither time). This surrogate maintains the ISIs and the temporal correlations within the spike train. +
    +
    +
    has super-classes
    +
    + spike train surrogate generation + c +
    +
    is disjoint with
    +
    + generate joint interspike interval dithering surrogate + c, generate interspike interval shuffling surrogate + c, generate joint interspike interval dithering surrogate + c, generate spike time randomization surrogate + c, generate trial shifting surrogate + c, generate trial shuffling surrogate + c, generate uniform spike dithering surrogate + c, generate uniform spike dithering surrogate with dead time + c, generate window shuffling surrogate + c +
    +
    +
    +
    +

    generate stationary gamma processc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#GenerateStationaryGammaProcess

    +
    + A random spike times generation that uses a gamma probability distribution to produce spike trains with a constant firing rate. +
    +
    +
    has super-classes
    +
    + random spike times generation + c +
    +
    is disjoint with
    +
    + generate non-stationary gamma process + c, generate non-stationary Poisson process + c, generate stationary inverse Gaussian process + c, generate stationary log-normal process + c, generate stationary Poisson process + c +
    +
    +
    +
    +

    generate stationary inverse Gaussian processc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#GenerateStationaryInverseGaussianProcess

    +
    + A random spike times generation that uses a inverse Gaussian probability distribution to produce spike trains with a constant firing rate. +
    +
    +
    has super-classes
    +
    + random spike times generation + c +
    +
    is disjoint with
    +
    + generate non-stationary gamma process + c, generate non-stationary Poisson process + c, generate stationary gamma process + c, generate stationary log-normal process + c, generate stationary Poisson process + c +
    +
    +
    +
    +

    generate stationary log-normal processc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#GenerateStationaryLogNormalProcess

    +
    + A random spike times generation that uses a log-normal probability distribution to produce spike trains with a constant firing rate. +
    +
    +
    has super-classes
    +
    + random spike times generation + c +
    +
    is disjoint with
    +
    + generate non-stationary gamma process + c, generate non-stationary Poisson process + c, generate stationary gamma process + c, generate stationary inverse Gaussian process + c, generate stationary Poisson process + c +
    +
    +
    +
    +

    generate stationary Poisson processc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#GenerateStationaryPoissonProcess

    +
    + A random spike times generation that uses a Poisson probability distribution to produce spike trains with a constant firing rate. A dead time can be specified as parameter (i.e., an interval where no spikes can occur, which is analogous to the neuronal refractory period). +
    +
    +
    has super-classes
    +
    + random spike times generation + c +
    +
    is disjoint with
    +
    + generate non-stationary gamma process + c, generate non-stationary Poisson process + c, generate stationary gamma process + c, generate stationary inverse Gaussian process + c, generate stationary log-normal process + c +
    +
    +
    +
    +

    generate trial shifting surrogatec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#GenerateTrialShiftingSurrogate

    +
    + A spike train surrogate generation step that shifts the entire spike train (containing the data of a single experimental trial) by an amount randomly chosen from a uniform distribution. The amount of displacement is specified as a parameter (dither time), and occurs in a window (-dither time, dither time). The input is a collection of spike trains of the same neuron, containing the spiking activity during different experimental trials. The amount of shift is independently chosen across trials and neurons. This surrogate preserves the ISI distribution and temporal correlations within the single-trial spike train. +
    +
    +
    has super-classes
    +
    + spike train surrogate generation + c +
    +
    is disjoint with
    +
    + generate joint interspike interval dithering surrogate + c, generate interspike interval shuffling surrogate + c, generate joint interspike interval dithering surrogate + c, generate spike time randomization surrogate + c, generate spike train dithering surrogate + c, generate trial shuffling surrogate + c, generate uniform spike dithering surrogate + c, generate uniform spike dithering surrogate with dead time + c, generate window shuffling surrogate + c +
    +
    +
    +
    +

    generate trial shuffling surrogatec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#GenerateTrialShufflingSurrogate

    +
    + A spike train surrogate generation step where the the spike trains of single-trial activity of one of the neurons are randomly permuted, so that each trial is no longer paired with the corresponding trial of the other neuron, but with a randomly selected one. The input is a collection of spike trains with multitrial activity data of multiple neurons recorded in parallel. +
    +
    +
    has super-classes
    +
    + spike train surrogate generation + c +
    +
    is disjoint with
    +
    + generate joint interspike interval dithering surrogate + c, generate interspike interval shuffling surrogate + c, generate joint interspike interval dithering surrogate + c, generate spike time randomization surrogate + c, generate spike train dithering surrogate + c, generate trial shifting surrogate + c, generate uniform spike dithering surrogate + c, generate uniform spike dithering surrogate with dead time + c, generate window shuffling surrogate + c +
    +
    +
    +
    +

    generate uniform spike dithering surrogatec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#GenerateUniformSpikeDitheringSurrogate

    +
    + A spike train surrogate generation step that displaces each spike time in the input spike train according to a uniform distribution centered on the spike. The displacement occurs in a time window around the spike defined by a parameter (dither time). +
    +
    +
    has super-classes
    +
    + spike train surrogate generation + c +
    +
    is disjoint with
    +
    + generate joint interspike interval dithering surrogate + c, generate interspike interval shuffling surrogate + c, generate joint interspike interval dithering surrogate + c, generate spike time randomization surrogate + c, generate spike train dithering surrogate + c, generate trial shifting surrogate + c, generate trial shuffling surrogate + c, generate uniform spike dithering surrogate with dead time + c, generate window shuffling surrogate + c +
    +
    +
    +
    +

    generate uniform spike dithering surrogate with dead timec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#GenerateUniformSpikeDitheringSurrogateWithDeadTime

    +
    + A spike train surrogate generation step that displaces each spike time in the input spike train according to a uniform distribution centered on the spike. The displacement occurs in a time window around the spike defined by a parameter (dither time) that is constrained to the intervals between adjacent spikes to avoid two spikes closer than a dead time (specified by parameter). This mimics the refractory period behavior of neurons, where the neuron cannot fire additional spikes for a short interval after one spike. +
    +
    +
    has super-classes
    +
    + spike train surrogate generation + c +
    +
    is disjoint with
    +
    + generate joint interspike interval dithering surrogate + c, generate interspike interval shuffling surrogate + c, generate joint interspike interval dithering surrogate + c, generate spike time randomization surrogate + c, generate spike train dithering surrogate + c, generate trial shifting surrogate + c, generate trial shuffling surrogate + c, generate uniform spike dithering surrogate + c, generate window shuffling surrogate + c +
    +
    +
    +
    +

    generate window shuffling surrogatec + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#GenerateWindowShufflingSurrogate

    +
    + A spike train surrogate generation step that shuffles the entries of a binned spike train within exclusive maximal displacement windows. The maximal displacement is specified by parameter, and represents the maximum number of bins that a spike can be displaced within the window. +
    +
    +
    has super-classes
    +
    + spike train surrogate generation + c +
    +
    is disjoint with
    +
    + generate joint interspike interval dithering surrogate + c, generate interspike interval shuffling surrogate + c, generate joint interspike interval dithering surrogate + c, generate spike time randomization surrogate + c, generate spike train dithering surrogate + c, generate trial shifting surrogate + c, generate trial shuffling surrogate + c, generate uniform spike dithering surrogate + c, generate uniform spike dithering surrogate with dead time + c +
    +
    +
    +
    +

    Granger causality analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#GrangerCausalityAnalysis

    +
    + A functional connectivity analysis that computes measures of Granger causality (GC). GC is a statistical concept where the future values of a time series are predicted based on its past values and the past values of other time series. GC quantifies bi-directional interactions between the inputs, determining the directional influence from one input to another. For example, with two inputs, GC measures how much the first input influences the second and vice versa (directional GC measure). This provides estimates of the directed connectivity between the inputs. It is also possible to compute associated measures, such as the instantaneous GC (a measure of interdependence between the inputs not accounted by their bi-directional interactions, such as shared neural input) and the total interdependence (the sum of all directional and instantaneous interactions between the inputs). The analysis can be performed in the time or frequency domains, and can take two (bivariate) or more inputs (multivariate). +
    +
    +
    has super-classes
    +
    + functional connectivity analysis + c +
    +
    has sub-classes
    +
    + conditional Granger causality analysis + c, pairwise Granger causality analysis + c +
    +
    +
    +
    +

    infinite impulse response filteringc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#InfiniteImpulseResponseFiltering

    +
    + A digital filtering that uses a filter whose impulse response (i.e., the response of the filter to a brief input impulse) persists infinitely. Therefore, the output of the filter can depend on an infinite number of past samples. The infinite impulse response (IIR) filters can become unstable and distort the phase of the signal, but have a lower computational cost. +
    +
    +
    has super-classes
    +
    + digital filtering + c +
    +
    has sub-classes
    +
    + apply Butterworth filter + c, apply infinite impulse response filter + c, apply notch filter + c +
    +
    +
    +
    +

    instantaneous firing rate analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#InstantaneousFiringRateAnalysis

    +
    + A firing rate analysis that computes the instantaneous firing rate, which is the estimate of the firing rate at a specific point in time. The instantaneous firing rate value can be obtained by several methods. +
    +
    +
    is equivalent to
    +
    + has purpose + op + value + instantaneous firing rate purpose +
    +
    has super-classes
    +
    + firing rate analysis + c +
    +
    has sub-classes
    +
    + compute instantaneous firing rate (interspike interval method) + c, compute instantaneous firing rate (kernel density estimation method) + c, compute instantaneous firing rate (local regression method) + c +
    +
    +
    +
    +

    interspike interval analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#InterspikeIntervalAnalysis

    +
    + An analysis step that computes or analyzes the interval between successive spikes in a spike train (interspike interval; ISI). +
    +
    +
    has super-classes
    +
    + analysis step + c +
    +
    has sub-classes
    +
    + compute interspike interval histogram + c, compute interspike intervals + c, interspike interval variability analysis + c +
    +
    +
    +
    +

    interspike interval variability analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#InterspikeIntervalVariabilityAnalysis

    +
    + An interspike interval analysis that computes a measure describing the variability of the interspike intervals. The measure can assess how regular a neuron is firing. +
    +
    +
    has super-classes
    +
    + interspike interval analysis + c +
    +
    has sub-classes
    +
    + compute CV2 + c, compute coefficient of variation of the interspike intervals + c, compute local variation + c, compute revised local variation + c +
    +
    +
    +
    +

    kernel smoothingc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#KernelSmoothing

    +
    + A data smoothing that performs a convolution of the input data with a kernel function. This computes a weighted average of the data around the kernel. Several kernel types can be used for the smoothing (e.g., Gaussian, exponential) and the kernel shape is controlled by a width parameter. +
    +
    +
    has super-classes
    +
    + data smoothing + c +
    +
    has sub-classes
    +
    + apply adaptive kernel smoothing + c, apply fixed kernel smoothing + c +
    +
    +
    +
    +

    latent dynamics analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#LatentDynamicsAnalysis

    +
    + An analysis step that aims to identify underlying patterns and structures within time series or sequential data that are not directly observable. It involves modeling hidden (latent) variables that influence the observed data and their evolution over time. The analysis captures temporal dependencies and dynamics within the data, providing insights into the processes that generate the observed sequences. +
    +
    +
    is equivalent to
    +
    + has purpose + op + value + latent dynamics purpose +
    +
    has super-classes
    +
    + analysis step + c +
    +
    +
    +
    +

    line noise removalc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#LineNoiseRemoval

    +
    + A data transformation that removes noise induced by the power line. +
    +
    +
    has super-classes
    +
    + data transformation + c +
    +
    has sub-classes
    +
    + apply Thomson regression noise removal + c, apply discrete Fourier transform noise removal + c, apply notch filter noise removal + c, apply spectrum interpolation noise removal + c +
    +
    +
    +
    +

    mean vector length analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#MeanVectorLengthAnalysis

    +
    + A phase-amplitude coupling (PAC) analysis that computes the mean vector length (MVL) measure. The MVL is based on a mean vector obtained from a time series defined in the complex plane, where the amplitude is taken from the high-frequency oscillation input and the phase from the low-frequency oscillation input. +
    +
    +
    has super-classes
    +
    + phase-amplitude coupling analysis + c +
    +
    has sub-classes
    +
    + compute mean vector length (Canolty method) + c, compute mean vector length (Özkurt method) + c +
    +
    +
    +
    +

    model-based analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ModelBasedAnalysis

    +
    + An analysis step that depends on assumptions on the interactions between the inputs to perform the computations. For example, the Granger causality analysis assumes linear relationships between the input signals. +
    +
    +
    is equivalent to
    +
    + is model-based + dp + value true
    +
    has super-classes
    +
    + analysis step + c +
    +
    +
    +
    +

    model-free analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#ModelFreeAnalysis

    +
    + An analysis step that does not depend on assumptions on the interactions between the inputs to perform the computations. For example, it can consider probability distributions obtained from the input data. +
    +
    +
    is equivalent to
    +
    + is model-based + dp + value false
    +
    has super-classes
    +
    + analysis step + c +
    +
    +
    +
    +

    multivariate analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#MultivariateAnalysis

    +
    + An analysis step that has three or more distinct inputs considered for the computation of the output (e.g., the time series with the local field potential signals recorded from three or more electrodes, used to compute the partial directed coherence). +
    +
    +
    is equivalent to
    +
    + is multivariate + dp + value true
    +
    has super-classes
    +
    + analysis step + c +
    +
    is disjoint with
    +
    + bivariate analysis + c +
    +
    +
    +
    +

    neuronal activity pattern detection analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#NeuronalActivityPatternDetectionAnalysis

    +
    + An analysis step that aims to identify a neuronal activity pattern, i.e., spikes of a group of neurons that occur in a specific spatio-temporal configuration. +
    +
    +
    has super-classes
    +
    + analysis step + c +
    +
    has sub-classes
    +
    + SPADE analysis + c, Unitary Event analysis + c, execute ASSET analysis + c, execute Cell Assembly Detection analysis + c +
    +
    +
    +
    +

    neuronal firing regularity analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#NeuronalFiringRegularityAnalysis

    +
    + An analysis step that computes measures to assess the regularity in the firing of a neuron. Neuronal firing regularity refers to the consistency or variability in the timing of action potentials (spikes) generated by a neuron. +
    +
    +
    is equivalent to
    +
    + has purpose + op + value + neuronal firing regularity purpose +
    +
    has super-classes
    +
    + analysis step + c +
    +
    has sub-classes
    +
    + compute spike train Fano factor + c +
    +
    +
    +
    +

    non-directed analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#NonDirectedAnalysis

    +
    + An analysis step where the output does not provide information on the direction of influence in the relationships among the inputs (e.g., in the Pearson correlation coefficient computed between two spike trains, it is possible to know how strongly they tend to fire together. However, it is not possible to analyze the timing of the spikes of the first input spike with respect to the timing of the spikes of the second input spike train). +
    +
    +
    is equivalent to
    +
    + is directed + dp + value false
    +
    has super-classes
    +
    + analysis step + c +
    +
    is disjoint with
    +
    + directed analysis + c +
    +
    +
    +
    +

    pairwise Granger causality analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#PairwiseGrangerCausalityAnalysis

    +
    + A Granger causality (GC) analysis that computes a measure of GC between two inputs. +
    +
    +
    has super-classes
    +
    + Granger causality analysis + c +
    +
    has sub-classes
    +
    + compute time domain pairwise Granger causality + c, frequency domain pairwise granger causality analysis + c +
    +
    is disjoint with
    +
    + conditional Granger causality analysis + c +
    +
    +
    +
    +

    peristimulus time histogram analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#PeristimulusTimeHistogramAnalysis

    +
    + A spike train time histogram analysis that computes the peristimulus time histogram (PSTH). PSTH is the time histogram of two or more spike trains containing repeated recordings of a single neuron around the time when an event of interest occurred. The event of interest can occur at any time point during the duration of the source spike trains. The distribution of the histogram corresponds to the distribution of the activity of the neuron with respect to the event across the repeated recordings. The event of interest can be an externally presented stimulus or a spontaneous behavioral event. If the histogram represents the neuronal activity after the stimulus presentation or event occurrence, this can be referred as post-stimulus time histogram. Conversely, if the histogram shows the activity of the neuron before the stimulus presentation or event, this can be referred as prestimulus time histogram. Finally, if the histogram considers a behavioral event (or an event that is not an externally presented stimulus), the histogram can be referred to as perievent time histogram (PETH). +
    +
    +
    has super-classes
    +
    + spike train time histogram analysis + c +
    +
    has sub-classes
    +
    + compute peristimulus time histogram (adaptive kernel smoothing) + c, compute peristimulus time histogram (fixed kernel smoothing) + c, compute peristimulus time histogram (optimal bin size) + c, compute peristimulus time histogram (user-selected bin size) + c +
    +
    is disjoint with
    +
    + compute population histogram + c +
    +
    +
    +
    +

    phase analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#PhaseAnalysis

    +
    + An analysis step that computes measures related to the phase in the input data. Phase expresses the position of a time-varying signal relative to a fixed reference point in time. For periodic and oscillatory signals (e.g., a sine waveform), phase analysis involves determining the angle on the unit circle that corresponds to the current position within the waveform's cycle. This helps understanding the timing and synchronization of the oscillations in the input data. +
    +
    +
    has super-classes
    +
    + analysis step + c +
    +
    has sub-classes
    +
    + compute angular mean of spike phases + c, compute mean phase vector + c, compute pairwise phase consistency + c, compute phase difference + c, compute phase slope index + c, compute spike-triggered phase + c, phase lag index analysis + c, phase locking value analysis + c, phase-amplitude coupling analysis + c +
    +
    +
    +
    +

    phase lag index analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#PhaseLagIndexAnalysis

    +
    + A phase analysis that computes the phase lag index (PLI). The PLI measures the asymmetry of the distribution of the phase differences between two input time series, i.e., if there is an imbalance in the likelihood of the first time series leading or lagging the second time series. It is designed to be invariant to common sources, such as volume conduction and/or active reference electrodes. +
    +
    +
    has super-classes
    +
    + phase analysis + c +
    +
    has sub-classes
    +
    + compute debiased squared weighted phase lag index + c, compute directed phase lag index + c, compute phase lag index + c, compute unbiased squared phase lag index + c, compute weighted phase lag index + c +
    +
    +
    +
    +

    phase locking value analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#PhaseLockingValueAnalysis

    +
    + A phase analysis that computes the phase locking value (PLV). The PLV quantifies the consistency of the phase difference between two input time series across time (e.g., multiple experimental trials). +
    +
    +
    has super-classes
    +
    + phase analysis + c +
    +
    has sub-classes
    +
    + compute corrected imaginary phase locking value + c, compute phase locking value + c +
    +
    +
    +
    +

    phase-amplitude coupling analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#PhaseAmplitudeCouplingAnalysis

    +
    + A phase analysis that computes measures describing how the phase of a low-frequency oscillation modulates the amplitude of a high-frequency oscillation. Phase-amplitude coupling (PAC) can be used to investigate interactions between different frequency bands in the neural activity. +
    +
    +
    has super-classes
    +
    + phase analysis + c +
    +
    has sub-classes
    +
    + compute modulation index + c, mean vector length analysis + c +
    +
    +
    +
    +

    power spectral density analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#PowerSpectralDensityAnalysis

    +
    + A spectral density analysis that computes the power spectral density of an input, i.e., the distribution of power across the different frequency components of the input signal per unit frequency. It is equivalent to the Fourier transform of the autocorrelation function of the input signal. The computed power spectral density values can be corrected depending on the analysis returning the two-sided (i.e., with negative frequencies) or one-sided (i.e., positive frequencies only) PSD. The PSD is often referred to as spectrum. +
    +
    +
    has super-classes
    +
    + spectral density analysis + c +
    +
    has sub-classes
    +
    + compute power spectral density (Bartlett method) + c, compute power spectral density (Welch method) + c, compute power spectral density (multitaper method) + c, compute power spectral density (periodogram method) + c +
    +
    +
    +
    +

    principal component analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#PrincipalComponentAnalysis

    +
    + A dimensionality reduction that reduces the dimensionality of the input data represented as a matrix with numerous rows and columns. It transforms the data into a set of principal components (PCs) that capture the maximum variance in the input. Each PC is a linear combination of the original variables and serves as a new axis in a lower-dimensional space. The PCs are orthogonal to each other, meaning they capture independent aspects of the input data's variability. +
    +
    +
    has super-classes
    +
    + dimensionality reduction + c +
    +
    has sub-classes
    +
    + apply demixed principal component analysis + c, apply probabilistic principal component analysis + c, apply standard principal component analysis + c +
    +
    +
    +
    +

    random spike times generationc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#RandomSpikeTimesGeneration

    +
    + A spike train generation where the output spike trains will have random spike times, taken from a specific probability distribution. The generation process can produce spike trains where the firing rate is constant (stationary) or varies (non-stationary) over time. +
    +
    +
    has super-classes
    +
    + spike train generation + c +
    +
    has sub-classes
    +
    + generate non-stationary Poisson process + c, generate non-stationary gamma process + c, generate stationary Poisson process + c, generate stationary gamma process + c, generate stationary inverse Gaussian process + c, generate stationary log-normal process + c +
    +
    is disjoint with
    +
    + correlated spike times generation + c +
    +
    +
    +
    +

    resamplingc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#Resampling

    +
    + A data transformation that changes the number of samples in the input data. +
    +
    +
    has super-classes
    +
    + data transformation + c +
    +
    has sub-classes
    +
    + apply downsampling + c, apply upsampling + c +
    +
    +
    +
    +

    SPADE analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#SPADEAnalysis

    +
    + A neuronal activity pattern detection analysis that uses the Spatio-temporal PAttern Detection and Evaluation (SPADE) method. The SPADE analysis takes a set of parallel spike trains as input, and returns significant spatio-temporal neuronal activity (spike) patterns. + +The SPADE method consists of three substeps: + +1. Detect all putative patterns in the input data using the frequent item set mining (FIM) algorithm. This step requires the discretization of the input spike train data (binning). The bin size determines the temporal resolution of the analysis. + +2. The detected FIM patterns are evaluated for statistical significance, considering the null hypothesis of independence of the spike trains given the modulations by the firing rate. This substep is called Pattern Spectrum Filtering (PSF). For the testing, the patterns are pooled based on their signature: size and occurrence count (non-3d-SPADE) or size, occurrence count and pattern duration (3d-SPADE). The pattern spectrum collects the counts of patterns from each signature. The statistical test is done by a Monte Carlo approach, using spike train surrogates generated from the original data. The final output of this substep is the p-value spectrum, which has the same dimensions as the pattern spectrum. The p-value is computed as the ratio of surrogates containing patterns with that signature to the total number of realizations. + +3. Conditional test on the significant patterns to remove patterns arising from the overlap of true pattern spikes and chance spikes (pattern set reduction; PSR). +
    +
    +
    has super-classes
    +
    + neuronal activity pattern detection analysis + c +
    +
    has sub-classes
    +
    + execute 3d-SPADE analysis + c, execute non-3d-SPADE analysis + c +
    +
    +
    +
    +

    spectral analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#SpectralAnalysis

    +
    + An analysis step that computes measures describing the input data with respect to its frequency contents. +
    +
    +
    has super-classes
    +
    + analysis step + c +
    +
    has sub-classes
    +
    + coherence analysis + c, coherency analysis + c, compute partial directed coherence + c, spectral density analysis + c, time-frequency analysis + c +
    +
    +
    +
    +

    spectral density analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#SpectralDensityAnalysis

    +
    + A spectral analysis that computes the density of a measure of the input(s) over the frequency spectrum. Density means that the measure value (e.g., power) for each frequency component is expressed per unit frequency. For example, for an input time series with voltages recorded from an electrode (measured in V), the power for each frequency component of the signal will be in V**2, while the power density will be in V**2/Hz. Therefore, the power values are normalized per unit frequency. This normalization allows for consistent comparisons of results from analyses with different frequency resolutions, as the spectral density remains unaffected by these variations. +
    +
    +
    has super-classes
    +
    + spectral analysis + c +
    +
    has sub-classes
    +
    + cross power spectral density analysis + c, power spectral density analysis + c +
    +
    +
    +
    +

    spectrogram analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#SpectrogramAnalysis

    +
    + A time-frequency analysis that shows the power (or power density) of different frequency components of the input(s) as they change over time. This can be obtained for a single input (spectrogram) or for two distinct inputs (cross-spectrogram). +
    +
    +
    has super-classes
    +
    + time-frequency analysis + c +
    +
    has sub-classes
    +
    + compute cross-spectrogram (short-time Fourier transform method) + c, compute spectrogram (Morlet wavelet method) + c, compute spectrogram (multitaper method) + c, compute spectrogram (short-time Fourier transform method) + c +
    +
    +
    +
    +

    spike train correlation analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#SpikeTrainCorrelationAnalysis

    +
    + An analysis step that computes measures estimating the correlation between spike train inputs. The correlation value is a normalized measure of covariation in the input spike train data, and reflects the strength and direction of the association: positive values mean that the inputs vary in the same direction, and negative values mean that the inputs vary in opposite directions (e.g., if the activity in one spike train increases, it decreases in the other). +
    +
    +
    has super-classes
    +
    + analysis step + c +
    +
    has sub-classes
    +
    + compute noise correlations + c, compute spike time tiling coefficient + c, compute spike train Pearson correlation coefficient + c +
    +
    +
    +
    +

    spike train dissimilarity analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#SpikeTrainDissimilarityAnalysis

    +
    + An analysis step that computes a measure comparing spike train inputs and providing an estimation of their similarity/dissimilarity. This is frequently done by computing spike train distances, which are measures that assign the notion of distance, i.e., the input spike trains are considered as elements in a space and, if similar, will be close together. +
    +
    +
    has super-classes
    +
    + analysis step + c +
    +
    has sub-classes
    +
    + time-scale dependent spike train distance analysis + c, time-scale independent spike train distance analysis + c +
    +
    +
    +
    +

    spike train generationc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#SpikeTrainGeneration

    +
    + A data generation that produces one or more artificial spike trains using distinct statistical procedures to determine the spike times. +
    +
    +
    has super-classes
    +
    + data generation + c +
    +
    has sub-classes
    +
    + correlated spike times generation + c, random spike times generation + c +
    +
    +
    +
    +

    spike train surrogate generationc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#SpikeTrainSurrogateGeneration

    +
    + A data generation that produces one or more spike train surrogates. A spike train surrogate is a new spike train derived from an input spike train (usually experimentally recorded). This is done using methods that alter the original spike times while trying to maintain specific statistical features of the original spike train (e.g., firing rate, interspike interval distribution). This is used to destroy fine temporal correlations in the spiking activity. +
    +
    +
    has super-classes
    +
    + data generation + c +
    +
    has sub-classes
    +
    + generate interspike interval shuffling surrogate + c, generate joint interspike interval dithering surrogate + c, generate joint interspike interval dithering surrogate + c, generate spike time randomization surrogate + c, generate spike train dithering surrogate + c, generate trial shifting surrogate + c, generate trial shuffling surrogate + c, generate uniform spike dithering surrogate + c, generate uniform spike dithering surrogate with dead time + c, generate window shuffling surrogate + c +
    +
    +
    +
    +

    spike train synchrony analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#SpikeTrainSynchronyAnalysis

    +
    + An analysis step to assess synchronization in two or more spike train inputs that typically represent the activity of different neurons. Spike train synchronization refers to the temporal coordination of action potentials (spikes) between neurons, and describes the degree to which their spikes tend to occur at the same time. +
    +
    +
    has super-classes
    +
    + analysis step + c +
    +
    has sub-classes
    +
    + compute CuBIC analysis + c, compute Spike-contrast + c, compute complexity distribution + c, compute joint peristimulus time histogram + c +
    +
    +
    +
    +

    spike train time histogram analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#SpikeTrainTimeHistogramAnalysis

    +
    + A firing rate analysis that computes histograms of spike train data over time. The time histogram is obtained by discretizing the duration of the spike train into distinct time intervals (bins), and obtaining the spike count inside each bin. + +The histogram can show one of three different measures: + +* the spike count at each bin (across all spike trains); +* the mean spike count per bin (spike count in the bin divided by the number of spike trains); +* the firing rate (mean spike count in the bin divided by bin width). +
    +
    +
    has super-classes
    +
    + firing rate analysis + c +
    +
    has sub-classes
    +
    + compute population histogram + c, compute spike train time histogram + c, peristimulus time histogram analysis + c +
    +
    +
    +
    +

    spike waveform analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#SpikeWaveformAnalysis

    +
    + An analysis step that is used to compute measures to describe or make inferences from spike waveform input data. A spike waveform refers to the shape of an electrical signal produced by a neuron when it fires an action potential. +
    +
    +
    has super-classes
    +
    + analysis step + c +
    +
    has sub-classes
    +
    + compute spike waveform average + c, compute spike waveform signal-to-noise ratio + c, compute spike waveform variance + c, compute spike waveform width + c +
    +
    +
    +
    +

    spike-field coherence analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#SpikeFieldCoherenceAnalysis

    +
    + An analysis step that computes the spike-field coherence (SFC), which is the coherence computed between an input spike train and an input time series with the local field potential (LFP). Coherence is a measure of the association between the two inputs in the frequency domain. SFC can be used to quantify the relationship between the spiking activity of neurons and the oscillatory activity in the LFP. It represents the similarity of dynamics between the spike train and the voltage fluctuations produced by the neural activity in the local environment where the spiking activity was recorded. +
    +
    +
    has super-classes
    +
    + analysis step + c +
    +
    has sub-classes
    +
    + compute spike-field coherence (Fries method) + c, compute spike-field coherence (Welch method) + c, compute spike-field coherence (multitaper method) + c +
    +
    +
    +
    +

    spike-field coupling analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#SpikeFieldCouplingAnalysis

    +
    + An analysis step that computes interactions between the spiking activity of neurons (individual or population) and the local field potential (LFP). +
    +
    +
    is equivalent to
    +
    + has purpose + op + value + spike-field coupling purpose +
    +
    has super-classes
    +
    + analysis step + c +
    +
    is disjoint with
    +
    + spike-spike coupling analysis + c +
    +
    +
    +
    +

    spike-spike coupling analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#SpikeSpikeCouplingAnalysis

    +
    + An analysis step that computes interactions between the spiking activity of one or more neurons. +
    +
    +
    is equivalent to
    +
    + has purpose + op + value + spike-spike coupling purpose +
    +
    has super-classes
    +
    + analysis step + c +
    +
    is disjoint with
    +
    + field-field coupling analysis + c, spike-field coupling analysis + c +
    +
    +
    +
    +

    statistical analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#StatisticalAnalysis

    +
    + A generic analysis step that computes measures to summarize and make inferences about the data input. These include measures of central tendency, dispersion and confidence intervals. The subclasses represent analysis steps that are usually used for aggregation of data and description of samples (e.g., compute the mean and standard deviation of the output of trial-by-trial analyses or across subjects). All analysis steps for specific applications related to the analysis of neuroelectrophysiology data itself (e.g., analyzing interspike interval variability) are covered by separate, independent classes. +
    +
    +
    has super-classes
    +
    + analysis step + c +
    +
    has sub-classes
    +
    + central tendency statistical analysis + c, confidence interval statistical analysis + c, dispersion statistical analysis + c +
    +
    +
    +
    +

    tensor component analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#TensorComponentAnalysis

    +
    + A dimensionality reduction that reduces the dimensionality of the input data represented as a tensor (i.e., an array with multiple dimensions). The tensor component analysis (TCA) transforms the data into a set of low-dimensional tensors that capture the maximum variance in the input (tensor components). +
    +
    +
    has super-classes
    +
    + dimensionality reduction + c +
    +
    has sub-classes
    +
    + apply canonical polyadic tensor decomposition + c, apply coupled canonical polyadic tensor decomposition + c, apply non-negative tensor component analysis + c +
    +
    +
    +
    +

    time domain analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#TimeDomainAnalysis

    +
    + An analysis step that analyzes the input(s) with respect to time. +
    +
    +
    is equivalent to
    +
    + is time domain + dp + value true
    +
    has super-classes
    +
    + analysis step + c +
    +
    is disjoint with
    +
    + frequency domain analysis + c +
    +
    +
    +
    +

    time-frequency analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#TimeFrequencyAnalysis

    +
    + A spectral analysis that computes measures describing the frequency content of the input(s) in a time-resolved manner. It allows the analysis of how different frequency components evolve over time, which is essential for non-stationary signals whose spectral characteristics change. The joint time-frequency representation helps in identifying transient features, frequency shifts, and other dynamic behaviors in the input(s). +
    +
    +
    has super-classes
    +
    + spectral analysis + c +
    +
    has sub-classes
    +
    + compute Stockwell transform + c, compute short-time Fourier transform + c, spectrogram analysis + c, wavelet transform analysis + c +
    +
    +
    +
    +

    time-scale dependent spike train distance analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#TimeScaleDependentSpikeTrainDistanceAnalysis

    +
    + A spike train dissimilarity analysis that computes a spike train distance that depends on a parameter that determines a temporal scale in the spike trains to which the distance is sensitive. By computing the spike train distance for different time scale parameter values, it is possible to make inferences on the time scale that is discriminative in the neural activity. +
    +
    +
    has super-classes
    +
    + spike train dissimilarity analysis + c +
    +
    has sub-classes
    +
    + compute Victor-Purpura distance + c, compute van Rossum distance + c +
    +
    +
    +
    +

    time-scale independent spike train distance analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#TimeScaleIndependentSpikeTrainDistanceAnalysis

    +
    + A spike train dissimilarity analysis that computes a spike train distance that does not depend on a time scale parameter and that are time-scale adaptive. They can be used in scenarios where there are no previous knowledge of the relevant time scales in the input spike trains. +
    +
    +
    has super-classes
    +
    + spike train dissimilarity analysis + c +
    +
    has sub-classes
    +
    + compute ISI-distance + c, compute SPIKE distance + c, compute SPIKE synchronization + c +
    +
    +
    +
    +

    triggered average analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#TriggeredAverageAnalysis

    +
    + An analysis step where a signal is averaged to obtain a value around a point in time representing an event of interest (i.e., a trigger). For each event time, a finite duration window of the input time series is selected around the event time. An average for each time point is then obtained across all windows. +
    +
    +
    has super-classes
    +
    + analysis step + c +
    +
    has sub-classes
    +
    + compute event-triggered average + c, compute spike-triggered average + c +
    +
    +
    +
    +

    Unitary Event analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#UnitaryEventAnalysis

    +
    + A neuronal activity pattern detection analysis that uses the Unitary Event (UE) method. UE is a statistical technique focused on identifying synchronous activity among neurons, known as unitary events (UEs), which occur more frequently than an expectation based solely on firing rates. The input can contain spike trains from one or more neurons and one or more trials. For the computation, the input spike train data is discretized into small time intervals (bins), and coincidences across the different spike trains are computed. The significance of the number of observed (empirical) coincidences is determined by comparing to an expected number given the firing rates of the neurons. To account for possible non-stationarities in the firing rates, the method uses a sliding temporal window over the data, whose width is specified as parameter. Therefore, a measure of significant spike synchrony (joint surprise) is obtained for each window. The statistical evaluation can be done using either analytical methods or Monte-Carlo testing with surrogate spike data. The output presents the significant coincidences (UE patterns) and the participant neurons. +
    +
    +
    has super-classes
    +
    + neuronal activity pattern detection analysis + c +
    +
    has sub-classes
    +
    + execute Unitary Event analysis (Monte Carlo method) + c, execute Unitary Event analysis (analytical method) + c +
    +
    +
    +
    +

    wavelet transform analysisc + back to ToC or Class ToC + +

    +

    + IRI: http://purl.org/neao/steps#WaveletTransformAnalysis

    +
    + A time-frequency analysis that uses wavelets to obtain the time-frequency representation of the time series input. The wavelet is a rapidly decaying oscillation. The wavelet transform breaks the signal into shifted and scaled versions of the wavelet (mother wavelet), and the output contains the information on both the frequencies present in the signal and the time. The wavelets provide good localization in time and frequency, making them suitable to analyze signals with transient features. Different types of wavelets exist, with distinct properties. They can be chosen to tailor the analysis to particular purposes. The output of the wavelet transform is often referred to as scaleogram. +
    +
    +
    has super-classes
    +
    + time-frequency analysis + c +
    +
    has sub-classes
    +
    + compute Morlet wavelet transform + c, compute continuous wavelet transform + c +
    +
    +
    +
    +

    Object Properties

    + +
    +

    has purposeop + back to ToC or Object Property ToC + +

    +

    + IRI: http://purl.org/neao/steps#hasPurpose

    +
    + Defines an analysis purpose for the analysis step. This property is used to group analysis steps according to their similarity. +
    +
    +
    +
    has domain
    +
    + analysis step + c +
    +
    has range
    +
    + analysis purpose + c +
    +
    +
    +
    +
    +

    Data Properties

    + +
    +

    is bivariatedp + back to ToC or Data Property ToC + +

    +

    + IRI: http://purl.org/neao/steps#isBivariate

    +
    + Defines if the analysis step uses two data inputs (true). +
    +
    +
    +
    has super-properties
    +
    + top data property +
    +
    has domain
    +
    + analysis step + c +
    +
    has range
    +
    + boolean +
    +
    +
    +
    +
    +

    is directeddp + back to ToC or Data Property ToC + +

    +

    + IRI: http://purl.org/neao/steps#isDirected

    +
    + Defines if the analysis step is used to perform an analysis providing information on the direction of the association between the inputs (true) opposed to no direction information (false). +
    +
    +
    +
    has super-properties
    +
    + top data property +
    +
    has domain
    +
    + analysis step + c +
    +
    has range
    +
    + boolean +
    +
    +
    +
    +
    +

    is frequency domaindp + back to ToC or Data Property ToC + +

    +

    + IRI: http://purl.org/neao/steps#isFrequencyDomain

    +
    + Defines if the analysis in the step is performed in the frequency domain (true). +
    +
    +
    +
    has super-properties
    +
    + top data property +
    +
    has domain
    +
    + analysis step + c +
    +
    has range
    +
    + boolean +
    +
    +
    +
    +
    +

    is model-baseddp + back to ToC or Data Property ToC + +

    +

    + IRI: http://purl.org/neao/steps#isModelBased

    +
    + Defines if the step performs a model-based (true) or model-free analysis (false). +
    +
    +
    +
    has super-properties
    +
    + top data property +
    +
    has domain
    +
    + analysis step + c +
    +
    has range
    +
    + boolean +
    +
    +
    +
    +
    +

    is multivariatedp + back to ToC or Data Property ToC + +

    +

    + IRI: http://purl.org/neao/steps#isMultivariate

    +
    + Defines if the analysis step uses three or more data inputs (true). +
    +
    +
    +
    has super-properties
    +
    + top data property +
    +
    has domain
    +
    + analysis step + c +
    +
    has range
    +
    + boolean +
    +
    +
    +
    +
    +

    is time domaindp + back to ToC or Data Property ToC + +

    +

    + IRI: http://purl.org/neao/steps#isTimeDomain

    +
    + Defines if the analysis in the step is performed in the time domain (true). +
    +
    +
    +
    has super-properties
    +
    + top data property +
    +
    has domain
    +
    + analysis step + c +
    +
    has range
    +
    + boolean +
    +
    +
    +
    +
    +

    Legend back to ToC

    +
    +c: Classes
    +op: Object Properties
    +dp: Data Properties
    +
    +
    +
    + + + + +
    +

    Acknowledgments back to ToC

    +

    This work was performed as part of the Helmholtz School for Data Science in Life, Earth and Energy (HDS-LEE) and received funding from the Helmholtz Association of German Research Centres. This project has received funding from the European Union’s Horizon 2020 Framework Programme for Research and Innovation under Specific Grant Agreement No. 945539 (Human Brain Project SGA3), the European Union’s Horizon Europe Programme under the Specific Grant Agreement No. 101147319 (EBRAINS 2.0 Project), the Ministry of Culture and Science of the State of North Rhine-Westphalia, Germany (NRW-network "iBehave", grant number: NW21-049), and the Joint Lab "Supercomputing and Modeling for the Human Brain."

    + +

    The authors would like to thank Silvio Peroni for developing LODE, a Live OWL Documentation Environment, which is used for representing the Cross Referencing Section of this document and Daniel Garijo for developing Widoco, the program used to create the template used in this documentation.

     +
    + + +
    + + + + + + + diff --git a/doc/releases/0.1.0/steps/provenance/provenance-en.html b/doc/releases/0.1.0/steps/provenance/provenance-en.html new file mode 100644 index 0000000..83690c7 --- /dev/null +++ b/doc/releases/0.1.0/steps/provenance/provenance-en.html @@ -0,0 +1,18 @@ + + + + + + + + +
    +

    Provenance for Neuroelectrophysiology Analysis Ontology - Analysis Steps Documentation (http://purl.org/neao/0.1.0/steps#)

    +
      +
    • Ontology created by: Cristiano Köhler (Forschungszentrum Jülich), Michael Denker (Forschungszentrum Jülich)
    • http://purl.org/neao/0.1.0/steps# is a specialization of the generic URI http://purl.org/neao/steps#
      • +
    • The ontology documentation was the result of using the Widoco tool (which itself uses LODE for generating the crossreference section).
      • +
    • The documentation was generated at 2024-12-06
    +
    +

    back to documentation. TTL format

    + + \ No newline at end of file diff --git a/doc/releases/0.1.0/steps/provenance/provenance-en.ttl b/doc/releases/0.1.0/steps/provenance/provenance-en.ttl new file mode 100644 index 0000000..0f00a76 --- /dev/null +++ b/doc/releases/0.1.0/steps/provenance/provenance-en.ttl @@ -0,0 +1,14 @@ +@prefix prov: . +@prefix dc: . +@prefix foaf: . +@prefix : <> . + a prov:Entity; + dc:title "Neuroelectrophysiology Analysis Ontology - Analysis Steps"; + prov:wasAttributedTo ; + dc:creator ; + prov:wasAttributedTo ; + dc:creator ; + prov:wasAttributedTo ,; + prov:specializationOf ; + prov:wasGeneratedAt "2024-12-06"; +. diff --git a/doc/releases/0.1.0/steps/resources/extra.css b/doc/releases/0.1.0/steps/resources/extra.css new file mode 100644 index 0000000..16689d3 --- /dev/null +++ b/doc/releases/0.1.0/steps/resources/extra.css @@ -0,0 +1,124 @@ +body { + text-align: justify; +} + +h1 { + line-height: 110%; +} + +.hlist { + border: 1px solid navy; + padding:5px; + background-color: #F4FFFF; 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r=n[1]||n[2]||"";if(!r||""===u||this.rules.inline.punctuation.exec(u)){var i=n[0].length-1,s=i,l=0,a="*"===n[0][0]?this.rules.inline.emStrong.rDelimAst:this.rules.inline.emStrong.rDelimUnd;for(a.lastIndex=0,t=t.slice(-1*e.length+i);null!=(n=a.exec(t));)if(o=n[1]||n[2]||n[3]||n[4]||n[5]||n[6])if(o=o.length,n[3]||n[4])s+=o;else if((n[5]||n[6])&&i%3&&!((i+o)%3))l+=o;else if(!(0<(s-=o))){var o=Math.min(o,o+s+l);if(Math.min(i,o)%2)return D=e.slice(1,i+n.index+o),{type:"em",raw:e.slice(0,i+n.index+o+1),text:D,tokens:this.lexer.inlineTokens(D,[])};var D=e.slice(2,i+n.index+o-1);return{type:"strong",raw:e.slice(0,i+n.index+o+1),text:D,tokens:this.lexer.inlineTokens(D,[])}}}}},t.codespan=function(e){var t,u,n,e=this.rules.inline.code.exec(e);if(e)return n=e[2].replace(/\n/g," "),t=/[^ ]/.test(n),u=/^ /.test(n)&&/ 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Slightly larger */ + width: 26em; + height: 26em; + z-index: -1; + opacity: 0.8; + + /** From http://stackoverflow.com/questions/1080792/how-to-draw-vertical-text-with-css-cross-browser */ + + -webkit-transform: rotate(-90deg); + -moz-transform: rotate(-90deg); + -ms-transform: rotate(-90deg); + -o-transform: rotate(-90deg); + transform: rotate(-90deg); + /* also accepts left, right, top, bottom coordinates; not + * required, but a good idea for styling */ + -webkit-transform-origin: 50% 50%; + -moz-transform-origin: 50% 50%; + -ms-transform-origin: 50% 50%; + -o-transform-origin: 50% 50%; + transform-origin: 50% 50%; + + /* Should be unset in IE9+ I think. */ + filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=3); +} + +/* The actual status box */ + .status div { + display: block; + background: rgb(0, 90, 156); + color: white; + width: 24em; + padding-top: 0.3em; + padding-left: 0em; + padding-right: 5em; + padding-bottom: 0.3em; + /* Enable for debugging + border: red thin solid; + */ +} + +/* And text inside, don't confuse fonts as it breaks em above */ +.status div span { + font-family: "Tauri"; + font-size: larger; +} \ No newline at end of file diff --git a/doc/releases/0.1.0/steps/resources/rdf.icon b/doc/releases/0.1.0/steps/resources/rdf.icon new file mode 100644 index 0000000000000000000000000000000000000000..d54310fe20cc6b76fb0aff73bb6d208449383a25 GIT binary patch literal 421 zcmV;W0b2e?Nk%w1VI2S<0K^{vg`>{#^!YhzuNqUMXN>BW*@J zA`Biv9dKI*F$G2>5f4KUX|yqk1!f2uS!02}lx7{JW5GSZW*L7;&$lB24u2k>F$6}2 z9|sD|ao{A8dL-W3NSo?M0}Lb=Tbc$83Fs{c7y=Ux8ZuC@K!AjS1ONaeKqcb9fGD~; zJU~-qN*OvvCfI!Gf5V9$CtYa?E2W PV+=hSSm&XEyAS|7t>CRw literal 0 HcmV?d00001 diff --git a/doc/releases/0.1.0/steps/resources/rec.css b/doc/releases/0.1.0/steps/resources/rec.css new file mode 100644 index 0000000..d8a1ff2 --- /dev/null +++ b/doc/releases/0.1.0/steps/resources/rec.css @@ -0,0 +1,88 @@ +/* Style for a "Recommendation" */ + +/* + Copyright 1997-2003 W3C (MIT, ERCIM, Keio). All Rights Reserved. + The following software licensing rules apply: + http://www.w3.org/Consortium/Legal/copyright-software */ + +/* $Id: base.css,v 1.25 2006/04/18 08:42:53 bbos Exp $ */ + +body { + padding: 2em 1em 2em 70px; + margin: 0; + font-family: sans-serif; + color: black; + background: white; + background-position: top left; + background-attachment: fixed; + background-repeat: no-repeat; + counter-reset:section; +} +:link { color: #00C; background: transparent } +:visited { color: #609; background: transparent } +a:active { color: #C00; background: transparent } + +a:link img, a:visited img { border-style: none } /* no border on img links */ + +a img { color: white; } /* trick to hide the border in Netscape 4 */ +@media all { /* hide the next rule from Netscape 4 */ + a img { color: inherit; } /* undo the color change above */ +} + +th, td { /* ns 4 */ + font-family: sans-serif; +} + +h1, h2, h3, h4, h5, h6 { text-align: left } +h2.list{counter-reset:subsection } +h2.list:before{counter-increment:section;content: counter(section) ". ";} +h3.list:before{counter-increment:subsection;content: counter(section) "." counter(subsection) ". "; + } +h3.list{margin-top: 20px; + border-bottom: 0px; } +/* background should be transparent, but WebTV has a bug */ +h1, h2, h3 { color: #005A9C; background: white } +h1 { font: 170% sans-serif } +h2 { font: 140% sans-serif } +h3 { font: 120% sans-serif } +h4 { font: bold 100% sans-serif } +h5 { font: italic 100% sans-serif } +h6 { font: small-caps 100% sans-serif } + +.hide { display: none } + +div.head { margin-bottom: 1em } +div.head h1 { margin-top: 2em; clear: both } +div.head table { margin-left: 2em; margin-top: 2em } + +p.copyright { font-size: small } +p.copyright small { font-size: small } + +@media screen { /* hide from IE3 */ +a[href]:hover { background: #ffa } +} + +pre { margin-left: 2em } +/* +p { + margin-top: 0.6em; + margin-bottom: 0.6em; +} +*/ +dt, dd { margin-top: 0; margin-bottom: 0 } /* opera 3.50 */ +dt { font-weight: bold } + +pre, code { font-family: monospace } /* navigator 4 requires this */ + +ul.toc, ol.toc { + list-style: disc; /* Mac NS has problem with 'none' */ + list-style: none; +} + +@media aural { + h1, h2, h3 { stress: 20; richness: 90 } + .hide { speak: none } + p.copyright { volume: x-soft; speech-rate: x-fast } + dt { pause-before: 20% } + pre { speak-punctuation: code } +} diff --git a/doc/releases/0.1.0/steps/webvowl/css/webvowl.app.css b/doc/releases/0.1.0/steps/webvowl/css/webvowl.app.css new file mode 100644 index 0000000..1c350ab --- /dev/null +++ b/doc/releases/0.1.0/steps/webvowl/css/webvowl.app.css @@ -0,0 +1,2477 @@ +@import url(https://fonts.googleapis.com/css?family=Open+Sans);/*---------------------------------------------- + WebVOWL page +----------------------------------------------*/ +html { + -ms-content-zooming: none; +} + + + +#loading-progress { + width: 50%; + margin: 10px 0; +} + +#drag_dropOverlay{ + width: 100%; + height:100%; + position:absolute; + top:0; + opacity: 0.5; + background-color: #3071a9; + pointer-events: none; + +} + +#dragDropContainer{ + width: 100%; + height:100%; + position:absolute; + top:0; + pointer-events: none; +} +#drag_icon_group{ + + +} + +#drag_msg{ + width: 50%; + background-color: #fefefe; + height: 50%; + border: black 2px solid; + border-radius: 20px; + left: 25%; + position: absolute; + top: 25%; + vertical-align: middle; + line-height: 10px; + text-align: center; + pointer-events: none; + padding: 10px; + font-size: 1.5em; + white-space: nowrap; + overflow: hidden; + text-overflow: ellipsis; +} + + +#layoutLoadingProgressBarContainer { + height: 50px; + text-align: left; + line-height: 1.5; +} + +#FPS_Statistics { + /*position : absolute;*/ + /*top : 10px;*/ + /*right: 50px;*/ + padding-left: 60px; + padding-top: 60px; +} + +#reloadCachedOntology { + /*position : absolute;*/ + /*top : 10px;*/ + /*right: 50px;*/ +} + +#additionalInformationContainer { + position: absolute; + top: 10px; + right: 50px; +} + +#modeOfOperationString { + /*position: absolute;*/ + /*right: 50px;*/ + /*top : 60px;*/ + padding-left: 34px; +} + +#direct-text-input { + border: 1px solid #34495e; + width: 100%; + margin-top: 5px; + cursor: pointer; +} + +#directUploadBtn, #close_directUploadBtn { + border: 1px solid #34495e; + width: 100%; + margin-top: 5px; + cursor: pointer +} + +#di_controls { + +} + +#di_controls > ul { + list-style: none; + margin: 0; + padding: 5px 0 0 5px; + +} + +#progressBarContext { + border-radius: 10px; + background-color: #bdc3c7; + height: 25px; + border: solid 1px black; + + margin: auto; + +} + +#progressBarValue { + border-radius: 9px; + width: 0%; + background-color: #2980b9; + height: 25px; + line-height: 1.5; + text-align: center; +} + +/** adding searching Styles **/ +.dbEntry { + background-color: #ffffff; + color: #2980b9; + padding: 10px; + font-size: 14px; + border: none; + cursor: pointer; +} + +.debugOption { + +} + +.dbEntrySelected { + background-color: #bdc3c7; + color: #2980b9; + padding: 10px; + font-size: 14px; + border: none; + cursor: pointer; +} + +.dbEntry:hover, .dbEntry:focus { + background-color: #bdc3c7; +} + +.searchMenuEntry { + background-color: #ffffff; + bottom: 0; + font-size: 14px; + min-width: 50px; + margin: 0; + padding: 0; + z-index: 99; + border-radius: 4px 4px 0 0; + border: 1px solid rgba(0, 0, 0, 0.15); + -webkit-box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175); + box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175); + box-sizing: border-box; + border-bottom: none; + display: none; + position: absolute; + list-style: none; +} + +.searchInputText { + background-color: #ffffff; + color: black; + border: black; + text-decoration: none; + max-width: 150px; + overflow: hidden; + text-overflow: ellipsis; + /*height: 20px;*/ + margin: 0; +} + +img, iframe { + border: none; +} + +.hidden { + display: none !important; +} + +.clear { + clear: both; +} + +a { + color: #69c; + text-decoration: none; +} + +a:hover { + color: #3498db; +} + +#optionsArea a { + color: #2980b9; +} + +#optionsArea a.highlighted { + background-color: #d90; +} + +.toolTipMenu li.highlighted { + background-color: #feb; +} + +#browserCheck { + /* checking for IE where WebVOWL is not working */ + background-color: #f00; + padding: 5px 0; + position: absolute; + text-align: center; + width: 100%; +} + +#browserCheck a { + color: #fff; +} + +#browserCheck a:hover { + text-decoration: underline; +} + +/*---------------------------------------------- + SideBar Animation Class; +----------------------------------------------- */ +@-webkit-keyframes sbExpandAnimation { + 0% { + width: 78%; + } + 100% { + width: 100%; + } +} + +@-moz-keyframes sbExpandAnimation { + 0% { + width: 78%; + } + 100% { + width: 100%; + } +} + +@-o-keyframes sbExpandAnimation { + 0% { + width: 78%; + } + 100% { + width: 100%; + } +} + +@keyframes sbExpandAnimation { + 0% { + width: 78%; + } + 100% { + width: 100%; + } +} + +/*Collapse Animation*/ +@-webkit-keyframes sbCollapseAnimation { + 0% { + width: 100%; + } + 100% { + width: 78%; + } +} + +@-moz-keyframes sbCollapseAnimation { + 0% { + width: 100%; + } + 100% { + width: 78%; + } +} + +@-o-keyframes sbCollapseAnimation { + 0% { + width: 100%; + } + 100% { + width: 78%; + } +} + +@keyframes sbCollapseAnimation { + 0% { + width: 100%; + } + 100% { + width: 78%; + } +} + +/*---------------------------------------------- + SideBar Animation Class; +----------------------------------------------- */ +@-webkit-keyframes l_sbExpandAnimation { + 0% { + width: 0px; + } + 100% { + width: 200px; + } +} + +@-moz-keyframes l_sbExpandAnimation { + 0% { + width: 0px; + } + 100% { + width: 200px; + } +} + +@-o-keyframes l_sbExpandAnimation { + 0% { + width: 0px; + } + 100% { + width: 200px; + } +} + +@keyframes l_sbExpandAnimation { + 0% { + width: 0px; + } + 100% { + width: 200px; + } +} + +/*Collapse Animation*/ +@-webkit-keyframes l_sbCollapseAnimation { + 0% { + width: 200px; + } + 100% { + width: 0px; + } +} + +@-moz-keyframes l_sbCollapseAnimation { + 0% { + width: 200px; + } + 100% { + width: 0px; + } +} + +@-o-keyframes l_sbCollapseAnimation { + 0% { + width: 200px; + } + 100% { + width: 0px; + } +} + +@keyframes l_sbCollapseAnimation { + 0% { + width: 200px; + } + 100% { + width: 0px; + } +} + +/*----------------- WARNING ANIMATIONS-------------*/ + +/*---------------------------------------------- + SideBar Animation Class; +----------------------------------------------- */ +@-webkit-keyframes warn_ExpandAnimation { + 0% { + top: -500px; + } + 100% { + top: 0; + } +} + +@-moz-keyframes warn_ExpandAnimation { + 0% { + top: -500px; + } + 100% { + top: 0; + } +} + +@-o-keyframes warn_ExpandAnimation { + 0% { + top: -500px; + } + 100% { + top: 0; + } +} + +@keyframes warn_ExpandAnimation { + 0% { + top: -500px; + } + 100% { + top: 0; + } +} + +/*Collapse Animation*/ +@-webkit-keyframes warn_CollapseAnimation { + 0% { + top: 0; + } + 100% { + top: -400px; + } +} + +@-moz-keyframes warn_CollapseAnimation { + 0% { + top: 0; + } + 100% { + top: -400px; + } +} + +@-o-keyframes warn_CollapseAnimation { + 0% { + top: 0; + } + 100% { + top: -400px; + } +} + +@keyframes warn_CollapseAnimation { + 0% { + top: 0; + } + 100% { + top: -400px; + } +} + +@keyframes msg_CollapseAnimation { + 0% { + top: 0; + } + 100% { + top: -400px; + } +} + +/*// add expand and collaps width for the warn module*/ +@-webkit-keyframes warn_ExpandLeftBarAnimation { + 0% { + left: 0; + } + 100% { + left: 100px; + } +} + +@-moz-keyframes warn_ExpandLeftBarAnimation { + 0% { + left: 0; + } + 100% { + left: 100px; + } +} + +@-o-keyframes warn_ExpandLeftBarAnimation { + 0% { + left: 0; + } + 100% { + left: 100px; + } +} + +@keyframes warn_ExpandLeftBarAnimation { + 0% { + left: 0; + } + 100% { + left: 100px; + } +} + +/*Collapse Animation*/ +@-webkit-keyframes warn_CollapseLeftBarAnimation { + 0% { + left: 100px; + } + 100% { + left: 0; + } +} + +@-moz-keyframes warn_CollapseLeftBarAnimation { + 0% { + left: 100px; + } + 100% { + left: 0; + } +} + +@-o-keyframes warn_CollapseLeftBarAnimation { + 0% { + left: 100px; + } + 100% { + left: 0; + } +} + +@keyframes warn_CollapseLeftBarAnimation { + 0% { + left: 100px; + } + 100% { + left: 0; + } +} + +/*// same for the right side expansion*/ + +/*// add expand and collaps width for the warn module*/ +@-webkit-keyframes warn_ExpandRightBarAnimation { + 0% { + width: 100%; + } + 100% { + width: 78%; + } +} + +@-moz-keyframes warn_ExpandRightBarAnimation { + 0% { + width: 100%; + } + 100% { + width: 78%; + } +} + +@-o-keyframes warn_ExpandRightBarAnimation { + 0% { + width: 100%; + } + 100% { + width: 78%; + } +} + +@keyframes warn_ExpandRightBarAnimation { + 0% { + width: 100%; + } + 100% { + width: 78%; + } + +} + +/*Collapse Animation*/ +@-webkit-keyframes warn_CollapseRightBarAnimation { + 0% { + width: 78%; + } + 100% { + width: 100%; + } +} + +@-moz-keyframes warn_CollapseRightBarAnimation { + 0% { + width: 78%; + } + 100% { + width: 100%; + } +} + +@-o-keyframes warn_CollapseRightBarAnimation { + 0% { + width: 78%; + } + 100% { + width: 100%; + } +} + +@keyframes warn_CollapseRightBarAnimation { + 0% { + width: 78%; + } + 100% { + width: 100%; + } +} + +/*---------------------------------------------- + LAYOUT +----------------------------------------------*/ +body { + background: rgb(24, 32, 42); + height: 100%; + font-size: 14px; + font-family: 'Open Sans', Helvetica, Arial, sans-serif; + line-height: 1; + margin: 0; + overflow: hidden; + padding: 0; + position: fixed; + width: 100%; +} + +main { + height: 100%; + margin: 0; + padding: 0; + position: relative; + width: 100%; +} + +#canvasArea { + position: relative; + margin: 0; + padding: 0; + width: 78%; +} + +#canvasArea #graph { + box-sizing: border-box; + margin: 0 0 2px 0; + background-color: #ecf0f1; + overflow: hidden; + padding: 0; + width: 100%; +} + +#canvasArea svg { + box-sizing: border-box; + margin: 0; + overflow: hidden; + padding: 0; +} + +#logo { + position: fixed; + /*padding: 10px;*/ + pointer-events: none; + /*border: solid 1px red;*/ +} + +#logo h2 { + color: #3498db; + margin: 0; + line-height: 0.7; + text-align: center; + font-size: 24px; +} + +#logo h2 span { + color: #34495E; + /*font-size: min(2vmin, 24px);*/ + font-size: 16px; +} + +@media screen and (max-device-height: 800px) { + #logo h2 { + font-size: calc(8px + 1.0vmin); + } + + #logo h2 span { + font-size: calc(3px + 1.0vmin); + } +} + +@media screen and (max-height: 800px) { + #logo h2 { + font-size: calc(8px + 1.0vmin); + } + + #logo h2 span { + font-size: calc(3px + 1.0vmin); + } +} + +@media screen and (max-device-width: 1200px) { + #logo h2 { + font-size: calc(8px + 1.0vmin); + } + + #logo h2 span { + font-size: calc(3px + 1.0vmin); + } +} + +@media screen and (max-width: 1200px) { + #logo h2 { + font-size: calc(8px + 1.0vmin); + } + + #logo h2 span { + font-size: calc(3px + 1.0vmin); + } +} + +.checkboxContainer input, .checkboxContainer label { + vertical-align: middle; +} + +.selected-ontology { + background-color: #eee; +} + +#credits { + border-top: solid 1px #bdc3c7; + font-size: 0.9em; +} + +.slideOption { + position: relative; + padding: 8px 5px; + outline: none; +} + +.slideOption .value { + float: right; + outline: none; +} + +.slideOption input[type="range"] { + box-sizing: border-box; + margin: 0; + outline: none; + -webkit-appearance: none; + -moz-appearance: none; + border-radius: 3px; + height: 12px; + width: 100%; + box-shadow: none; + left: 0; + position: relative; + transition: all 0.5s ease; + background-color: #eee; +} + +/*TRACK*/ +.slideOption input[type=range]::-webkit-slider-runnable-track { + -webkit-appearance: none; + background-color: #3071a9; + height: 3px; +} + +.slideOption input[type=range]::-moz-range-track { + -webkit-appearance: none; + background-color: #3071a9; + height: 3px; +} + +.slideOption input[type="range"]:hover { + outline: none; +} + +/*THUMB*/ +.slideOption input[type="range"]::-webkit-slider-thumb { + -webkit-appearance: none; + background-color: white; + border-radius: 3px; + border: solid 1px black; + transition: all 0.5s ease; + height: 10px; + width: 30px; + outline: none; + margin-top: -3px; +} + +.slideOption input[type="range"]::-moz-range-thumb { + -webkit-appearance: none; + background-color: white; + border-radius: 3px; + border: solid 1px black; + transition: all 0.5s ease; + height: 10px; + width: 30px; + outline: none; +} + +.slideOption input[type="range"]::-moz-range-thumb:hover { + background-color: #d90; + outline: none; +} + +.slideOption input[type="range"]::-webkit-slider-thumb:hover { + background-color: #d90; + /*color: #d90;*/ + outline: none; +} + +/*focus : remove border*/ +.slideOption input[type="range"]:focus { + outline: none; +} + +.slideOption input[type="range"]:active { + outline: none; +} + +.slideOption input[type="range"]::-moz-range-thumb:focus { + outline: none; +} + +.slideOption input[type="range"]::-moz-range-thumb:active { + outline: none; +} + +.slideOption input[type="range"]::-webkit-slider-thumb:focus { + outline: none; +} + +.slideOption input[type="range"]::-webkit-slider-thumb:active { + outline: none; +} + +.slideOption input[type="range"]:disabled { + box-sizing: border-box; + margin: 0; + outline: none; + -webkit-appearance: none; + -moz-appearance: none; + border-radius: 3px; + height: 12px; + width: 100%; + box-shadow: none; + left: 0; + position: relative; + transition: all 0.5s ease; + background-color: #787878; +} + +/*TRACK*/ +.slideOption input[type=range]:disabled::-webkit-slider-runnable-track { + -webkit-appearance: none; + background-color: #373737; + height: 3px; +} + +.slideOption input[type=range]:disabled::-moz-range-track { + -webkit-appearance: none; + background-color: #373737; + height: 3px; +} + +.slideOption input[type="range"]:disabled { + outline: none; +} + +/*THUMB*/ +.slideOption input[type="range"]:disabled::-webkit-slider-thumb { + -webkit-appearance: none; + background-color: #363636; + border-radius: 3px; + border: solid 1px #aaaaaa; + transition: all 0.5s ease; + height: 10px; + width: 30px; + outline: none; + margin-top: -3px; +} + +.slideOption input[type="range"]:disabled::-moz-range-thumb { + -webkit-appearance: none; + background-color: #aaaaaa; + border-radius: 3px; + border: solid 1px black; + transition: all 0.5s ease; + height: 10px; + width: 30px; + outline: none; +} + +.slideOption input[type="range"]:disabled::-moz-range-thumb { + background-color: #aaaaaa; + outline: none; +} + +.slideOption input[type="range"]:disabled::-webkit-slider-thumb { + background-color: #aaaaaa; + /*color: #d90;*/ + outline: none; +} + +.slideOption input[type="range"]:disabled:hover::-moz-range-thumb { + background-color: #404040; + outline: none; +} + +.slideOption input[type="range"]:disabled:hover::-webkit-slider-thumb { + background-color: #404040; + /*color: #d90;*/ + outline: none; +} + +#detailsArea { + top: 0; + right: 0; + bottom: 0; + color: #bdc3c7; + height: 100%; + width: 22%; + overflow-y: auto; + overflow-x: hidden; + position: fixed; + border-left: 1px solid #34495E; +} + +#detailsArea h1 { + border-bottom: solid 1px #34495e; + color: #ecf0f1; + display: block; + font-weight: 100; + font-size: 1.5em; + margin: 0; + padding: 10px 0; + text-align: center; +} + +#generalDetails { + width: auto; + box-sizing: border-box; + height: 100%; +} + +#generalDetails span #about { + border-bottom: solid 1px #34495e; + display: block; + padding: 10px; + text-align: center; + word-wrap: break-word; + color: #69c; +} + +#generalDetails h4 { + background: rgb(27, 37, 46); + color: #ecf0f1; + display: block; + font-size: 1.1em; + font-weight: 100; + margin: 0; + padding: 10px 0; + text-align: center; +} + +#detailsArea #generalDetails h5 { + border-bottom: solid 1px #34495e; + font-size: 0.9em; + font-weight: 100; + margin: 0; + padding: 5px; + text-align: center; +} + +#description { + text-align: justify; +} + +.accordion-container p { + font-size: 0.9em; + line-height: 1.3; + margin: 5px 10px; +} + +.statisticDetails span { + font-weight: 100; + font-style: italic; + margin: 10px 0; + padding: 10px; +} + +.statisticDetails div { + font-weight: 100; + font-style: italic; + margin: 10px 0; + padding: 0 10px; + display: inline; +} + +#selection-details .propDetails a { + color: #69c; +} + +#selection-details .propDetails > span { + font-weight: 100; + font-style: italic; + padding: 0 10px; +} + +#selection-details #classEquivUri span, #selection-details #disjointNodes span { + padding: 0; +} + +#selection-details .propDetails div { + font-weight: 100; + font-style: italic; + margin: 10px 0; + padding: 0 10px; + display: inline; +} + +#selection-details .propDetails div span { + padding: 0; +} + +/* give subclass property the same background color as the canvas */ +.subclass { + fill: #ecf0f1; +} + +.accordion-trigger { + background: #24323e; + cursor: pointer; + padding: .5em; +} + +.accordion-trigger.accordion-trigger-active:before { + padding-right: 4px; + content: "\25BC" +} + +.accordion-trigger:not(.accordion-trigger-active):before { + padding-right: 4px; + content: "\25BA" +} + +.accordion-container.scrollable { + max-height: 40%; + overflow: auto; +} + +.small-whitespace-separator { + height: 3px; +} + +#language { + background: transparent; + border: 1px solid #34495E; + color: #ecf0f1; +} + +#language option { + background-color: #24323e; +} + +.converter-form:not(:first-child) { + margin-top: 5px; +} + +.converter-form label { + display: inline-block; + line-height: normal; +} + +.converter-form input { + box-sizing: border-box; + height: 20px; + width: 74%; + border: 1px solid #34495E; +} + +.converter-form button { + cursor: pointer; + float: right; + height: 20px; + padding: 0; + width: 25%; + border: 1px solid #34495E; + background-color: #ecf0f1; +} + +#file-converter-label { + border: 1px solid #34495E; + box-sizing: border-box; + cursor: pointer; + height: 20px; + width: 74%; +} + +#killWarning { + cursor: pointer; + color: #ffffff; + font-weight: bold; +} + +/*#copyBt{*/ +/*box-sizing: border-box;*/ +/*color: #000000;*/ +/*float:right;*/ +/*position:absolute;*/ +/*right:2px;*/ +/*padding: 2px 7px 3px 7px;*/ +/*border: 1px solid #000000;*/ +/*background-color: #ecf0f1;*/ +/*cursor: pointer;*/ +/*}*/ + +#copyBt { + box-sizing: border-box; + height: 20px; + width: 31%; + border: 1px solid #34495E; +} + +#sidebarExpandButton { + height: 24px; + width: 24px; + /*background-color: white;*/ + /*box-shadow: 0px 1px 1px grey;*/ + box-sizing: border-box; + top: 10px; + color: #000000; + float: right; + position: absolute; + right: 0; + border: 1px solid #000000; + + text-align: center; + font-size: 1.5em; + cursor: pointer; +} + +.dropdownMenuClass { + height: 20px; + /*width: 69%;*/ + float: right; + border: 1px solid #34495E; + background-color: #34495E; + color: white; + /*border-bottom: 1px solid #d90;*/ + text-align: left; + width: auto; +} + +#typeEditForm_datatype { + padding-top: 5px; +} + +#typeEditor { + width: 165px; +} + +#typeEditor_datatype { + width: 165px; +} + +#leftSideBarCollapseButton { + box-sizing: border-box; + top: 50px; + /*padding:5px;*/ + color: #000000; + position: absolute; + left: 200px; + border: 1px solid #000000; + /*background-color: #ecf0f1;*/ + cursor: pointer; + width: 24px; + height: 24px; + font-size: 1.5em; + text-align: center; +} + +#leftSideBarCollapseButton:hover { + background-color: #d90; +} + +#sidebarExpandButton:hover { + background-color: #d90; +} + +.spanForCharSelection { + padding-left: 25px; +} + +.nodeEditSpan { + color: #000; + background-color: #fff; + text-align: center; + /*overflow: auto;*/ + border: none; + padding-top: 6px; +} + +.nodeEditSpan:focus { + outline: none; + border: none; +} + +.foreignelements { + /*width: 80px;*/ + /*height: 3px;*/ + border: none; +} + +.foreignelements:focus { + outline: none; + border: none; +} + +#leftSideBarContent { + color: #000000; + float: left; + position: absolute; + left: 0; + /*border: 1px solid #000000;*/ + background-color: rgb(24, 32, 42); + width: 100%; + height: 100%; +} + +#leftSideBarContent > h3 { + color: #ecf0f1; + display: block; + font-size: 1.1em; + font-weight: 100; + margin: 0 0 5px 0; + padding: 10px 0; + text-align: left; +} + +#generalDetailsEdit { + /*color: #ecf0f1;*/ + color: #ecf0f1; +} + +#generalDetailsEdit > div { + padding: 5px; +} + +#generalDetailsEdit > h3 { + color: #ecf0f1; + display: block; + font-size: 1.1em; + font-weight: 100; + margin: 0 0 5px 0; + padding: 10px 0; + text-align: left; +} + +.subAccordion { + color: #ecf0f1; + display: block; + font-size: 0.8em; + font-weight: 100; + margin: 0; + padding: 5px; + text-align: left; +} + +.subAccordionDescription { + padding: 0 5px; +} + +.boxed { + padding: 0 5px; +} + +.separatorLineRight { + border-right: 1px solid #f00; +} + +.editPrefixButton:hover { + color: #ff972d; + cursor: pointer; +} + +.editPrefixIcon:hover { + stroke: #ff972d; + stroke-width: 1px; + cursor: pointer; +} + +.editPrefixIcon { + stroke: #fffff; + stroke-width: 1px; + cursor: pointer; +} + +.deletePrefixButton:hover { + color: #ff972d; + cursor: pointer; +} + +.deletePrefixButton { + color: #ff0000; + cursor: pointer; +} + +.invisiblePrefixButton { + cursor: default; + color: rgb(24, 32, 42); +} + +#containerForAddPrefixButton { + width: 100%; + margin-top: 5px; +} + +.roundedButton { + border: 1px solid #000000; + border-radius: 20px; + padding: 0 5px; + background: #fff; + cursor: pointer; + color: black; + outline: none; +} + +.roundedButton:hover { + background: #318638; + cursor: pointer; + color: #fff; + outline: none; +} + +#prefixURL_Description { + padding: 5px 0 0 0; +} + +.prefixIRIElements { + display: inline-block; + padding: 3px; + border-bottom: 1px solid #34495E; + width: 100% +} + +.prefixInput { + width: 30px; + display: inline-block; + margin-right: 5px; +} + +.prefixURL { + width: 100px; + display: inline-block; + paddig-left: 5px; +} + +.selectedDefaultElement { + text-align: left; + white-space: nowrap; + overflow: hidden; + text-overflow: ellipsis; + display: inline-block; + max-width: 200px; +} + +#editHeader { + color: #ecf0f1; + background-color: #394f5a; + display: block; + font-size: 1.1em; + font-weight: 100; + text-align: center; +} + +#leftHeader { + color: #ecf0f1; + background-color: #394f5a; + display: block; + font-size: 1.1em; + font-weight: 100; + text-align: center; + padding: 10px 0; + margin: 0; +} + +.containerForDefaultSelection { + color: #ecf0f1; + display: block; + font-size: 1.1em; + font-weight: 100; + margin: 0; + padding: 10px 20px; + text-align: left; +} + +.defaultSelected { + color: #a15d05; + background-color: #283943; +} + +.containerForDefaultSelection:hover { + color: #f19505; + background-color: #394f5a; + display: block; + cursor: pointer; +} + +#containerForLeftSideBar { + top: 50px; + float: left; + position: absolute; + background-color: #1b252e; + left: 0; + width: 200px; + height: 200px; + overflow-y: auto; + overflow-x: hidden; +} + +#leftSideBar { + width: 100%; + background-color: rgb(24, 32, 42); +} + +#loading-info { + box-sizing: border-box; + position: absolute; + text-align: center; + + width: 100%; + height: 80%; + top: 0; +} + +#loading-info > div { + display: inline-block; + color: #ffffff; + background-color: #18202A; + border-bottom-left-radius: 2px; + border-bottom-right-radius: 2px; +} + +#loading-info > * > * { + padding: 5px; +} + +#loading-info { + pointer-events: none; +} + +#loading-progress { + pointer-events: auto; + min-width: 220px; + border-radius: 10px; +} + +#show-loadingInfo-button { + font-size: 12px; + color: #fff; + cursor: pointer; + text-align: center; +} + +#loadingIndicator_closeButton:hover { + color: #ff972d; + cursor: pointer; + +} + +#loadingIndicator_closeButton { + color: #ffe30f; + cursor: pointer; + padding-bottom: 5px; + float: right; +} + +.busyProgressBar { + background-color: #000; + height: 25px; + position: relative; + animation: busy 2s linear infinite; +} + +@-webkit-keyframes busy { + 0% { + left: 0%; + } + 50% { + left: 80%; + } + 100% { + left: 0%; + } +} + +#bulletPoint_container { + padding-left: 15px; + margin-top: 0px; + margin-bottom: 0px; +} + +#bulletPoint_container > div { + margin-left: -15px; +} + +#loadingInfo-container { + box-sizing: border-box; + text-align: left; + line-height: 1.2; + padding-top: 5px; + overflow: auto; + /*white-space: nowrap;*/ + /*min-width: 250px;*/ + height: 120px; + min-height: 40px; + background-color: #3c3c3c; + +} + +#error-description-button { + margin: 5px 0 0 0; + font-size: 12px; + color: #69c; + cursor: pointer; + text-align: center; +} + +#error-description-container { + box-sizing: border-box; + text-align: left; +} + +#error-description-container pre { + background-color: #34495E; + padding: 2px; + margin: 0; + white-space: pre-wrap; + max-height: calc(100vh - 125px); + max-width: 75vw; + overflow: auto; +} + +.spin { + display: inline-block; + -webkit-animation: spin 2s infinite linear; + animation: spin 2s infinite linear; +} + +@-webkit-keyframes spin { + 0% { + -webkit-transform: rotate(0deg); + transform: rotate(0deg); + } + 100% { + -webkit-transform: rotate(359deg); + transform: rotate(359deg); + } +} + +@keyframes spin { + 0% { + -webkit-transform: rotate(0deg); + transform: rotate(0deg); + } + 100% { + -webkit-transform: rotate(359deg); + transform: rotate(359deg); + } +} + +.truncate { + max-width: 250px; + white-space: nowrap; + overflow: hidden; + text-overflow: ellipsis; +} + +.color-mode-switch { + float: right; + width: 90px; + cursor: pointer; + height: 20px; + padding: 0; + border: 0; + color: #555; + background-color: #ECEEEF; + box-shadow: 0 1px 4px rgba(0, 0, 0, 0.2), inset 0 0 3px rgba(0, 0, 0, 0.1); +} + +.color-mode-switch:focus { + outline-width: 0; +} + +.color-mode-switch.active { + color: #FFF; + background-color: #32CD32; + box-shadow: inset 0 1px 4px rgba(0, 0, 0, 0.2), inset 0 0 3px rgba(0, 0, 0, 0.1); +} + +/* adding button pulse animation*/ +.filterMenuButtonHighlight { + background-color: #d90; +} + +@-webkit-keyframes buttonAnimation { + 0% { + background-color: unset; + } + 100% { + background-color: #d90; + } +} + +@-moz-keyframes buttonAnimation { + 0% { + background-color: unset; + } + 100% { + background-color: #d90; + } +} + +@-o-keyframes buttonAnimation { + 0% { + background-color: unset; + } + 100% { + background-color: #d90; + } +} + +@keyframes buttonAnimation { + 0% { + background-color: unset; + } + 100% { + background-color: #d90; + } +} + +.buttonPulse { + -webkit-animation-name: buttonAnimation; + -moz-animation-name: buttonAnimation; + -o-animation-name: buttonAnimation; + animation-name: buttonAnimation; + + -webkit-animation-duration: 0.5s; + -moz-animation-duration: 0.5s; + -o-animation-duration: 0.5s; + animation-duration: 0.5s; + + -webkit-animation-iteration-count: 3; + -moz-animation-iteration-count: 3; + -o-animation-iteration-count: 3; + animation-iteration-count: 3; + + -webkit-animation-timing-function: linear; + -moz-animation-timing-function: linear; + -o-animation-timing-function: linear; + animation-timing-function: linear; + + +} + +/*swipe bar definition*/ + +/*Overwriting individual menu widths*/ +#m_about { + max-width: 200px; + width: 200px; + position: absolute; + +} + +#m_modes { + max-width: 160px; + width: 160px; + position: absolute; +} + +#m_filter { + max-width: 170px; + width: 170px; + position: absolute; +} + +#m_gravity { + max-width: 180px; + width: 180px; + position: absolute; +} + +#m_export { + max-width: 160px; + width: 160px; + position: absolute; + +} + +#exportedUrl { + width: 100px; +} + +#m_select { + max-width: 300px; + width: 300px; + position: absolute; +} + +#m_config { + max-width: 240px; + width: 240px; + position: absolute; +} + +#m_search { + max-width: 250px; + white-space: nowrap; + overflow: hidden; + text-overflow: ellipsis; +} + +/***************** REWRITING MENU ELEMENT CONTAINERS ***********************/ +/*Container which holds the swipeBar*/ +#swipeBarContainer { + position: fixed; + width: 77.8%; + height: 40px; + margin: 0; + padding: 0; + bottom: 0; +} + +/*Scroll-able container for the menu entries */ +#menuElementContainer { + margin: 0; + padding: 0; + overflow-x: auto; + overflow-y: hidden; + white-space: nowrap; + text-align: right; + list-style-type: none; +} + +/*Style for the individual menu entries*/ +#menuElementContainer > li { + display: inline-block; + box-sizing: border-box; + text-align: left; + position: relative; + height: 40px; + font-size: 14px; + color: #ffffff; + padding: 12px 0 0; + margin-left: -4px; +} + +/*Font-color Style for menu entries */ +#menuElementContainer > li > a { + color: #fff; + padding: 9px 12px 12px 30px; +} + +.menuElementSvgElement { + height: 20px; + width: 20px; + display: block; + position: absolute; + top: 10px; + left: 8px; +} + +.btn_shadowed { + background-color: #fefefe; + box-shadow: 1px 1px 1px gray; +} + +.reloadCachedOntologyIcon { + height: 20px; + width: 108px; + display: block; + position: absolute; + top: 20px; + left: 3px; + /*background: #ecf0f1;;*/ + border: solid 1px black; + border-radius: 10px; + cursor: pointer; +} + +.reloadCachedOntologyIcon:disabled { + background: #f4f4f4; + cursor: auto; + border: solid 1px darkgray; + +} + +.reloadCachedOntologyIcon:hover { + background: #d90; + cursor: pointer; +} + +.disabledReloadElement { + cursor: auto; + background: #F4F4F4; + pointer-events: auto; + border: solid 1px darkgray; + color: #bbbbbb; +} + +.disabledReloadElement:hover { + cursor: auto; + background: #EEEEEE; + pointer-events: auto; +} + +#menuElementContainer > li > input { + color: #000; + /*padding : 0 0.3em 0 1.5em;*/ + padding: 0.1em .3em 0.1em 1.5em; + white-space: nowrap; + overflow: hidden; + text-overflow: ellipsis; + width: 120px; +} + +/*Hovered behavior for the menu entries*/ +#menuElementContainer > li > a:hover { + box-sizing: border-box; + background: #1B252E; + /*background : #d90;*/ + color: #bdc3c7; + +} + +#empty:hover { + box-sizing: border-box; + background: #e1e1e1; + /*background : #d90;*/ + color: #2980b9; +} + +#empty.disabled { + pointer-events: none; + cursor: default; + color: #979797; +} + +.disabled { + pointer-events: none; + cursor: default; + color: #979797; +} + +/*ToolTip Menu Definition*/ +.toolTipMenu { + -webkit-box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175); + box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175); + box-sizing: border-box; + background-color: #ffffff; + border: 1px solid rgba(0, 0, 0, 0.15); + border-bottom: none; + border-radius: 4px 4px 0 0; + bottom: 0; + display: none; + font-size: 14px; + list-style: none; + /*max-width: 300px;*/ + margin: 0; + padding: 0; + white-space: normal; + position: absolute; + z-index: 99; +} + +.toolTipMenu > li:first-of-type { + border: none; +} + +.toolTipMenu a { + color: #2980b9; +} + +.toolTipMenu > li { + border-top: solid 1px #bdc3c7; +} + +.toolTipMenu li { + color: #2980b9; + display: block; +} + +/*MenuElement hovering enables the toolTip of the corresponding menu*/ +#menuElementContainer > li:hover .toolTipMenu { + display: block; +} + +#menuElementContainer li > ul.toolTipMenu li a:hover { + background: #e1e1e1; +} + +/****************************************************************************/ +/*ScrollButton behavior*/ +#scrollLeftButton { + height: 30px; + width: 30px; + padding: 5px 0 5px 10px; + color: #fff; + cursor: pointer; + position: absolute; + margin-top: -2px; + font-size: 2em; + background-color: #24323e; + left: 0; +} + +#scrollLeftButton:focus { + outline: none; +} + +#scrollLeftButton:before { + content: "<"; +} + +/*Right Scroll Button*/ +#scrollRightButton { + height: 30px; + width: 30px; + padding: 5px 0 5px 10px; + color: #fff; + cursor: pointer; + position: absolute; + margin-top: -2px; + font-size: 2em; + background-color: #24323e; + right: 0; +} + +#scrollRightButton:focus { + outline: none; +} + +#scrollRightButton:hover { + color: #bdc3c7; +} + +#scrollLeftButton:hover { + color: #bdc3c7; +} + +#scrollRightButton:before { + content: ">"; +} + +#centerGraphButton, #zoomInButton, #zoomOutButton { + border: 1px solid #000000; + text-align: center; + margin: -1px 0 0 0; + font-size: 1.5em; + padding: 0; + height: 28px; +} + +.noselect { + -webkit-touch-callout: none; /* iOS Safari */ + -webkit-user-select: none; /* Safari */ + -khtml-user-select: none; /* Konqueror HTML */ + -moz-user-select: none; /* Firefox */ + -ms-user-select: none; /* Internet Explorer/Edge */ + user-select: none; + /* Non-prefixed version, currently + supported by Chrome and Opera */ +} + +#zoomOutButton { + line-height: 22px; +} + +#centerGraphButton { + line-height: 25px; +} + +#zoomInButton { + line-height: 25px; +} + +#zoomSlider > p:hover { + background-color: #d90; +} + +#zoomSliderParagraph { + color: #000000; + padding-top: 5px; + margin: -1px 0 0 0; + border: 1px solid #000000; + /*background-color: #ecf0f1;*/ + /*width: 28px;*/ + height: 150px; +} + +p#zoomSliderParagraph:hover { + background-color: #fff; +} + +/*todo put this in a proper position*/ +#zoomSlider { + width: 28px; + margin-top: -2px; + padding: 0; + font-size: 1.5em; + cursor: pointer; + position: absolute; + right: 20px; + bottom: 20px; + color: #000; + /*background-color: #ecf0f1;*/ + box-sizing: border-box; +} + +/****************************************************************************/ +/*Definition for the Icons before*/ +#menuElementContainer > li > a::before { + font-size: 1em; + margin: 0; + padding: 0 6px 0 0; +} + +#menuElementContainer a.highlighted { + background-color: #d90; +} + +/*#search-input-text.searchInputText {*/ +/*!*padding: 0 0.2em;*!*/ +/*color: black;*/ +/*}*/ + +.inner-addon { + position: relative; +} + +.searchIcon { + position: absolute; + /*padding: 0.15em 0;*/ + width: 17px; + height: 17px; + + pointer-events: none; +} + +.gearIcon { + position: absolute; + width: 17px; + height: 17px; + pointer-events: none; + left: -5px; +} + +/*#search-input-text::before {*/ +/*!*padding: 0 0.2em;*!*/ +/*!*color: black;*!*/ +/*font-size: 1.4em; !* todo : test this *!*/ +/*!*content: "\2315";*!*/ +/*content: "⚲";*/ +/*color: white;*/ +/*padding: 0;*/ +/*-webkit-transform: rotate(-45deg);*/ +/*!*content: "\2315" or "\1F50D"*!;*/ +/*display: inline-block;*/ +/*position: relative;*/ +/*top: 2px;*/ +/*left:-5px;*/ +/*}*/ + +li#c_search { + padding: 0 5px; + margin-left: 5px; + height: 20px; +} + +/*Menu icons before the links selection */ +/*#c_select > a::before { content: "\2263"; }*/ +/*#c_export > a::before { content: "\21E4"; }*/ +/*#c_gravity > a::before { content: "\2299"; }*/ +/*#c_filter > a::before { content: "\25BD"; }*/ +/*#c_modes > a::before { content: "\2606"; }*/ +/*#c_reset > a::before { content: "\21BB"; }*/ +/*#c_about > a::before { content: "\00A9"; }*/ + +li#c_locate { + padding: 0; +} + +#c_locate > a { + font-size: 2em; + padding: 0; +} + +a#pause-button { + padding: 12px 12px; +} + +/*Pause Button has a different behavior*/ +a#pause-button.paused::before { + content: "\25BA"; +} + +a#pause-button.paused:hover { + background-color: #d90; + color: #fff; +} + +a#pause-button:not(.paused)::before { + content: "II"; +} + +.toolTipMenu li:hover { + background-color: #e1e1e1; +} + +#emptyLiHover { + background-color: #FFFFFF; +} + +#emptyLiHover:hover { + background-color: #FFFFFF; +} + +.toggleOption li:hover { + background-color: #e1e1e1; +} + +.toggleOption { + padding: 8px 5px; +} + +#converter-option:hover { + background-color: #ffffff; +} + +.toolTipMenu li a:only-child, .option { + display: block; + float: none; + padding: 8px 5px; +} + +.customLocate { + padding: 0; + background-color: #32CD32; +} + +a#locateSearchResult { + padding-bottom: 0; + padding-top: 50px; + position: relative; + top: 5px; +} + +/*#sliderRange{*/ +/*padding: 0;*/ +/*margin: 7px 0 0 0;*/ +/*width:100%;*/ +/*height:5px;*/ +/*-webkit-appearance: none;*/ +/*outline: none;*/ +/*}*/ + +#zoomSliderElement { + color: #000; + position: relative; + padding-top: 0; + width: 155px; + height: 24px; + background-color: transparent; + -webkit-transform-origin-x: 73px; + -webkit-transform-origin-y: 73px; + -webkit-transform: rotate(-90deg); + -moz-transform-origin: 73px 73px; + transform: rotate(-90deg); + transform-origin: 73px 73px; + -webkit-appearance: none; + outline: none; + margin: 4px 0; +} + +/* ------------------ Zoom Slider styles --------------------------*/ +#zoomSliderElement::-webkit-scrollbar { + height: 0; +} + +#zoomSliderElement:hover { + cursor: crosshair; +} + +/*TRACK*/ +#zoomSliderElement::-webkit-slider-runnable-track { + width: 100%; + height: 5px; + cursor: pointer; + background: #3071a9; +} + +#zoomSliderElement::-moz-range-track { + width: 100%; + height: 5px; + cursor: pointer; + background: #3071a9; +} + +/*Thumb*/ +#zoomSliderElement::-webkit-slider-thumb { + -webkit-appearance: none; + border: 1px solid #000000; + height: 10px; + width: 30px; + margin-right: 50px; + border-radius: 3px; + background: #fff; + cursor: pointer; + outline: none; + margin-top: -3px; +} + +#zoomSliderElement::-ms-thumb { + -webkit-appearance: none; + border: 1px solid #000000; + height: 10px; + width: 30px; + margin-right: 50px; + border-radius: 3px; + background: #fff; + cursor: pointer; + outline: none; + margin-top: -3px; +} + +#zoomSliderElement::-ms-thumb:hover { + -webkit-appearance: none; + border: 1px solid #000000; + height: 10px; + width: 30px; + margin-right: 50px; + border-radius: 3px; + background: #d90; + cursor: pointer; + outline: none; + margin-top: -3px; +} + +#zoomSliderElement::-webkit-slider-thumb:hover { + -webkit-appearance: none; + border: 1px solid #000000; + height: 10px; + width: 30px; + margin-right: 50px; + border-radius: 3px; + background: #d90; + cursor: pointer; + outline: none; + margin-top: -3px; +} + +#zoomSliderElement::-moz-range-thumb { + border: 1px solid #000000; + height: 10px; + width: 30px; + border-radius: 3px; + /*background: #ffffff;*/ + cursor: pointer; + outline: none; +} + +#zoomSliderElement::-moz-range-thumb:hover { + border: 1px solid #000000; + height: 10px; + width: 30px; + border-radius: 3px; + background: #d90; + cursor: pointer; + outline: none; +} + +#zoomSliderElement::-moz-focus-outer { + border: 0; +} + +#locateSearchResult:focus { + outline: none; + +} + +a#locateSearchResult.highlighted:hover { + background-color: #d90; + color: red; +} + +a#locateSearchResult { + outline: none; + padding-bottom: 0; + padding-top: 0; + position: relative; + top: 5px; +} + +/*Editor hints*/ +#editorHint { + padding: 5px 5px; + position: absolute; + text-align: center; + width: 100%; + pointer-events: none; +} + +#editorHint label { + pointer-events: auto; + float: right; + padding: 5px 5px; + color: #ffdd00; +} + +#editorHint label:hover { + text-decoration: underline; + cursor: pointer; +} + +#editorHint > div { + pointer-events: auto; + text-align: left; + display: inline-block; + color: #ffffff; + font-size: 0.8em; + background-color: #18202A; + padding: 5px 5px; + border-radius: 5px; + +} + +#WarningErrorMessagesContainer { + position: absolute; + text-align: center; + top: 0; + pointer-events: none; +} + +/*Editor hints*/ +#WarningErrorMessages { + position: relative; + /*text-align: center;*/ + width: 50%; + pointer-events: auto; + margin: 10px 0; + padding-right: 12px; + overflow-y: auto; + overflow-x: hidden; +} + +#WarningErrorMessages label { + pointer-events: auto; + float: right; + padding: 5px 5px; + color: #ffdd00; +} + +#WarningErrorMessages span { + pointer-events: auto; + float: right; + padding: 5px 5px; +} + +#WarningErrorMessages label:hover { + text-decoration: underline; + cursor: pointer; +} + +#WarningErrorMessages > div { + pointer-events: auto; + text-align: left; + display: inline-block; + color: #ffffff; + font-size: 0.8em; + background-color: #18202A; + padding: 5px 5px; + border-radius: 10px; + border: solid 1px #ecf0f1; + width: 70%; + +} + +#WarningErrorMessagesContent > ul { + -webkit-padding-start: 20px; + padding: 0 16px; + +} + +#WarningErrorMessagesContent > ul > li { + padding: 5px; +} + +.converter-form-Editor { + /*display: inline-block;*/ +} + +.textLineEditWithLabel { + display: inline-block; + width: 100%; + border-bottom: 1px solid #34495E; + padding: 2px 0; + +} + +.converter-form-Editor label { + /*//display: inline-block;*/ + line-height: normal; +} + +.descriptionTextClass { + background-color: #34495E; + color: white; +} + +.prefixIRIElements input { + border: 1px solid #34495E; + background-color: #34495E; + color: white; +} + +.prefixIRIElements input:disabled { + background-color: rgb(24, 32, 42); + border: 1px solid rgb(24, 32, 42); + color: white; +} + +.converter-form-Editor input { + /*box-sizing: border-box;*/ + /*height: 18px;*/ + /*width: 69%;*/ + float: right; + border: 1px solid #34495E; + background-color: #34495E; + color: white; + /*border-bottom: 1px solid #d90;*/ + /*text-align: center;*/ + /*display: inline-block;*/ +} + +.converter-form-Editor input:disabled { + background-color: #545350; + border: 1px solid #34495E; + color: #939798; +} + +.disabledLabelForSlider { + color: #808080; +} diff --git a/doc/releases/0.1.0/steps/webvowl/css/webvowl.css b/doc/releases/0.1.0/steps/webvowl/css/webvowl.css new file mode 100644 index 0000000..bd06623 --- /dev/null +++ b/doc/releases/0.1.0/steps/webvowl/css/webvowl.css @@ -0,0 +1,296 @@ +/*----------------------------------------------------------------- + VOWL graphical elements (part of spec) - mixed CSS and SVG styles +-----------------------------------------------------------------*/ + +/*-------- Text --------*/ +.text { + font-family: Helvetica, Arial, sans-serif; + font-size: 12px; +} + +.subtext { + font-size: 9px; +} + +.text.instance-count { + fill: #666; +} + +.external + text .instance-count { + fill: #aaa; +} + +.cardinality { + font-size: 10px; +} + +.text, .embedded { + pointer-events: none; +} + +/*------- Colors ------*/ +.class, .object, .disjoint, .objectproperty, .disjointwith, .equivalentproperty, .transitiveproperty, .functionalproperty, .inversefunctionalproperty, .symmetricproperty, .allvaluesfromproperty, .somevaluesfromproperty { + fill: #acf; +} + +.label .datatype, .datatypeproperty { + fill: #9c6; +} + +.rdf, .rdfproperty { + fill: #c9c; +} + +.literal, .node .datatype { + fill: #fc3; +} + +.deprecated, .deprecatedproperty { + fill: #ccc; +} + +.external, .externalproperty { + /*fill: #36c;*/ +} + +path, .nofill { + fill: none; +} + +marker path { + fill: #000; +} + +.class, path, line, .fineline { + stroke: #000; +} + +.white, .subclass, .subclassproperty, .external + text { + fill: #fff; +} + +.class.hovered, .property.hovered, .cardinality.hovered, .cardinality.focused, .filled.hovered, .filled.focused, .values-from.filled.hovered { + fill: #f00 !important; + cursor: pointer; +} + +.hoveredForEditing { + fill: #f00 !important; + cursor: pointer; +} + +.feature { + fill: #f00; + cursor: pointer; +} + +@-webkit-keyframes pulseAnimation { + 0% { + -webkit-transform: scale(1.5); + stroke-width: 3.33; + } + 50% { + stroke-width: 4; + } + 100% { + -webkit-transform: scale(1.0); + stroke-width: 5; + } +} + +@-moz-keyframes pulseAnimation { + 0% { + -webkit-transform: scale(1.5); + stroke-width: 3.33; + } + 50% { + stroke-width: 4; + } + 100% { + -webkit-transform: scale(1.0); + stroke-width: 5; + } +} + +@-o-keyframes pulseAnimation { + 0% { + -webkit-transform: scale(1.5); + stroke-width: 3.33; + } + 50% { + stroke-width: 4; + } + 100% { + -webkit-transform: scale(1.0); + stroke-width: 5; + } +} + +@keyframes pulseAnimation { + 0% { + -webkit-transform: scale(1.5); + stroke-width: 3.33; + } + 50% { + stroke-width: 4; + } + 100% { + -webkit-transform: scale(1.0); + stroke-width: 5; + } +} + +.searchResultA { + fill: none; + stroke-width: 5; + stroke: #f00; + -webkit-animation-name: pulseAnimation; + -moz-animation-name: pulseAnimation; + -o-animation-name: pulseAnimation; + animation-name: pulseAnimation; + + -webkit-animation-duration: 0.8s; + -moz-animation-duration: 0.8s; + -o-animation-duration: 0.8s; + animation-duration: 0.8s; + + -webkit-transform: translateZ(0); + -o-transform: translateZ(0); + -webkit-animation-iteration-count: 3; + -moz-animation-iteration-count: 3; + -o-animation-iteration-count: 3; + animation-iteration-count: 3; + + -webkit-animation-timing-function: linear; + -moz-animation-timing-function: linear; + -o-animation-timing-function: linear; + animation-timing-function: linear; + +} + +/* a class for not animated search results (hovered over node)*/ +.searchResultB { + fill: none; + stroke-width: 5; + stroke: #f00; +} + +.hovered-MathSymbol { + fill: none; + stroke: #f00 !important; +} + +.focused, path.hovered { + stroke: #f00 !important; +} + +.indirect-highlighting, .feature:hover { + fill: #f90; + cursor: pointer; +} + +.feature_hover { + fill: #f90; + cursor: pointer; +} + +.values-from { + stroke: #69c; +} + +.symbol, .values-from.filled { + fill: #69c; +} + +/*------- Strokes ------*/ +.class, path, line { + stroke-width: 2; +} + +.fineline { + stroke-width: 1; +} + +.dashed, .anonymous { + stroke-dasharray: 8; +} + +.dotted { + stroke-dasharray: 3; +} + +rect.focused, circle.focused { + stroke-width: 4px; +} + +.nostroke { + stroke: none; +} + +/*----------------------------------------------------------------- + Additional elements for the WebVOWL demo (NOT part of spec) +-----------------------------------------------------------------*/ + +.addDataPropertyElement { + fill: #9c6 !important; + cursor: pointer; + stroke-width: 2; + stroke: black; +} + +.addDataPropertyElement:hover { + fill: #f90 !important; + cursor: pointer; + stroke-width: 2; + stroke: black; +} + +.superHiddenElement { + fill: rgba(255, 153, 0, 0.4); + cursor: pointer; + stroke-width: 0; + stroke: black; + /*opacity:0;*/ +} + +.superOpacityElement { + opacity: 0; +} + +.deleteParentElement:hover { + fill: #f90; + cursor: pointer; + stroke-width: 2; + stroke: black; +} + +.deleteParentElement { + fill: #f00; + cursor: pointer; + stroke-width: 2; + stroke: black; +} + +.classNodeDragPath { + stroke: black; + stroke-width: 2px; +} + +.classDraggerNodeHovered { + fill: #f90; + stroke: black; + stroke-width: 2px; + cursor: pointer; +} + +.classDraggerNode { + fill: #acf; + stroke: black; + stroke-width: 2px; +} + +marker path { + /* Safari and Chrome workaround for inheriting the style of its link. + Use any value that is larger than the length of the marker path. */ + stroke-dasharray: 100; +} diff --git a/doc/releases/0.1.0/steps/webvowl/data/foaf.json b/doc/releases/0.1.0/steps/webvowl/data/foaf.json new file mode 100644 index 0000000..4897985 --- /dev/null +++ b/doc/releases/0.1.0/steps/webvowl/data/foaf.json @@ -0,0 +1,2894 @@ +{ + "_comment" : "Created with OWL2VOWL (version 0.3.7), http://vowl.visualdataweb.org", + "header" : { + "languages" : [ "undefined" ], + "baseIris" : [ "http://schema.org", "http://www.w3.org/2000/01/rdf-schema", "http://www.w3.org/2003/01/geo/wgs84_pos", "http://purl.org/dc/terms", "http://www.w3.org/2001/XMLSchema", "http://xmlns.com/foaf/0.1", "http://www.w3.org/2000/10/swap/pim/contact", "http://www.w3.org/2004/02/skos/core" ], + "prefixList" : { + "owl" : "http://www.w3.org/2002/07/owl#", + "rdf" : "http://www.w3.org/1999/02/22-rdf-syntax-ns#", + "wot" : "http://xmlns.com/wot/0.1/", + "xsd" : "http://www.w3.org/2001/XMLSchema#", + "dc" : "http://purl.org/dc/elements/1.1/", + "xml" : "http://www.w3.org/XML/1998/namespace", + "vs" : "http://www.w3.org/2003/06/sw-vocab-status/ns#", + "foaf" : "http://xmlns.com/foaf/0.1/", + "rdfs" : "http://www.w3.org/2000/01/rdf-schema#" + }, + "title" : { + "undefined" : "Friend of a Friend (FOAF) vocabulary" + }, + "iri" : "http://xmlns.com/foaf/0.1/", + "description" : { + "undefined" : "The Friend of a Friend (FOAF) RDF vocabulary, described using W3C RDF Schema and the Web Ontology Language." + }, + "other" : { + "title" : [ { + "identifier" : "title", + "language" : "undefined", + "value" : "Friend of a Friend (FOAF) vocabulary", + "type" : "label" + } ] + } + }, + "namespace" : [ ], + "class" : [ { + "id" : "3", + "type" : "owl:Thing" + }, { + "id" : "9", + "type" : "owl:Class" + }, { + "id" : "1", + "type" : "owl:equivalentClass" + }, { + "id" : "18", + "type" : "owl:Thing" + }, { + "id" : "19", + "type" : "owl:Thing" + }, { + "id" : "5", + "type" : "owl:Thing" + }, { + "id" : "20", + "type" : "rdfs:Literal" + }, { + "id" : "8", + "type" : "rdfs:Literal" + }, { + "id" : "11", + "type" : "owl:Class" + }, { + "id" : "21", + "type" : "owl:Thing" + }, { + "id" : "22", + "type" : "rdfs:Literal" + }, { + "id" : "24", + "type" : "rdfs:Literal" + }, { + "id" : "26", + "type" : "rdfs:Literal" + }, { + "id" : "27", + "type" : "rdfs:Literal" + }, { + "id" : "37", + "type" : "owl:equivalentClass" + }, { + "id" : "45", + "type" : "rdfs:Literal" + }, { + "id" : "46", + "type" : "rdfs:Literal" + }, { + "id" : "53", + "type" : "rdfs:Literal" + }, { + "id" : "56", + "type" : "rdfs:Literal" + }, { + "id" : "59", + "type" : "rdfs:Literal" + }, { + "id" : "60", + "type" : "owl:Class" + }, { + "id" : "61", + "type" : "rdfs:Literal" + }, { + "id" : "6", + "type" : "rdfs:Literal" + }, { + "id" : "62", + "type" : "rdfs:Literal" + }, { + "id" : "12", + "type" : "owl:equivalentClass" + }, { + "id" : "55", + "type" : "rdfs:Literal" + }, { + "id" : "69", + "type" : "rdfs:Literal" + }, { + "id" : "71", + "type" : "owl:Class" + }, { + "id" : "36", + "type" : "owl:Class" + }, { + "id" : "86", + "type" : "owl:Class" + }, { + "id" : "83", + "type" : "owl:Class" + }, { + "id" : "94", + "type" : "owl:Class" + }, { + "id" : "73", + "type" : "rdfs:Literal" + }, { + "id" : "68", + "type" : "rdfs:Literal" + }, { + "id" : "93", + "type" : "rdfs:Literal" + }, { + "id" : "33", + "type" : "owl:Thing" + }, { + "id" : "49", + "type" : "rdfs:Literal" + }, { + "id" : "29", + "type" : "owl:Thing" + }, { + "id" : "101", + "type" : "rdfs:Literal" + }, { + "id" : "39", + "type" : "owl:Thing" + }, { + "id" : "63", + "type" : "owl:equivalentClass" + }, { + "id" : "64", + "type" : "owl:equivalentClass" + }, { + "id" : "102", + "type" : "owl:equivalentClass" + }, { + "id" : "78", + "type" : "owl:Class" + }, { + "id" : "77", + "type" : "owl:Class" + }, { + "id" : "13", + "type" : "owl:equivalentClass" + }, { + "id" : "58", + "type" : "rdfs:Literal" + }, { + "id" : "100", + "type" : "rdfs:Literal" + }, { + "id" : "106", + "type" : "rdfs:Literal" + }, { + "id" : "52", + "type" : "rdfs:Literal" + }, { + "id" : "88", + "type" : "rdfs:Literal" + }, { + "id" : "118", + "type" : "rdfs:Literal" + }, { + "id" : "126", + "type" : "owl:Class" + }, { + "id" : "2", + "type" : "owl:equivalentClass" + }, { + "id" : "32", + "type" : "owl:equivalentClass" + }, { + "id" : "10", + "type" : "owl:Class" + } ], + "classAttribute" : [ { + "iri" : "http://www.w3.org/2002/07/owl#Thing", + "baseIri" : "http://owl2vowl.de", + "id" : "3", + "label" : { + "undefined" : "Thing" + } + }, { + "iri" : "http://www.w3.org/2004/02/skos/core#Concept", + "baseIri" : "http://www.w3.org/2004/02/skos/core", + "instances" : 0, + "label" : { + "IRI-based" : "Concept", + "undefined" : "Concept" + }, + "attributes" : [ "external" ], + "id" : "9" + }, { + "iri" : "http://xmlns.com/foaf/0.1/Agent", + "equivalent" : [ "13" ], + "baseIri" : "http://xmlns.com/foaf/0.1", + "instances" : 0, + "annotations" : { + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "Agent", + "undefined" : "Agent" + }, + "subClasses" : [ "10", "11", "12" ], + "comment" : { + "undefined" : "An agent (eg. person, group, software or physical artifact)." + }, + "attributes" : [ "equivalent" ], + "id" : "1" + }, { + 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+ }, { + "id" : "81", + "type" : "owl:objectProperty" + }, { + "id" : "82", + "type" : "rdfs:SubClassOf" + }, { + "id" : "34", + "type" : "owl:objectProperty" + }, { + "id" : "85", + "type" : "rdfs:SubClassOf" + }, { + "id" : "87", + "type" : "owl:datatypeProperty" + }, { + "id" : "89", + "type" : "rdfs:SubClassOf" + }, { + "id" : "90", + "type" : "rdfs:SubClassOf" + }, { + "id" : "91", + "type" : "owl:objectProperty" + }, { + "id" : "92", + "type" : "owl:datatypeProperty" + }, { + "id" : "95", + "type" : "owl:datatypeProperty" + }, { + "id" : "96", + "type" : "owl:objectProperty" + }, { + "id" : "97", + "type" : "owl:datatypeProperty" + }, { + "id" : "98", + "type" : "rdfs:SubClassOf" + }, { + "id" : "99", + "type" : "owl:datatypeProperty" + }, { + "id" : "43", + "type" : "owl:objectProperty" + }, { + "id" : "42", + "type" : "owl:objectProperty" + }, { + "id" : "103", + "type" : "owl:datatypeProperty" + }, { + "id" : "104", + "type" : "owl:objectProperty" + }, { + "id" : "105", + "type" : "owl:datatypeProperty" + }, { + "id" : "107", + "type" : "owl:objectProperty" + }, { + "id" : "108", + "type" : "owl:datatypeProperty" + }, { + "id" : "109", + "type" : "owl:objectProperty" + }, { + "id" : "110", + "type" : "owl:objectProperty" + }, { + "id" : "40", + "type" : "owl:objectProperty" + }, { + "id" : "41", + "type" : "owl:objectProperty" + }, { + "id" : "84", + "type" : "owl:objectProperty" + }, { + "id" : "111", + "type" : "owl:datatypeProperty" + }, { + "id" : "112", + "type" : "owl:datatypeProperty" + }, { + "id" : "113", + "type" : "owl:datatypeProperty" + }, { + "id" : "114", + "type" : "owl:objectProperty" + }, { + "id" : "116", + "type" : "owl:disjointWith" + }, { + "id" : "117", + "type" : "owl:disjointWith" + }, { + "id" : "119", + "type" : "owl:datatypeProperty" + }, { + "id" : "120", + "type" : "owl:disjointWith" + }, { + "id" : "121", + "type" : "owl:disjointWith" + }, { + "id" : "122", + "type" : "owl:objectProperty" + }, { + "id" : "123", + "type" : "owl:datatypeProperty" + }, { + "id" : "124", + "type" : "owl:objectProperty" + }, { + "id" : "125", + "type" : "owl:datatypeProperty" + }, { + "id" : "127", + "type" : "owl:datatypeProperty" + }, { + "id" : "115", + "type" : "owl:objectProperty" + }, { + "id" : "128", + "type" : "owl:objectProperty" + }, { + "id" : "129", + "type" : "owl:objectProperty" + } ], + "propertyAttribute" : [ { + "iri" : "http://xmlns.com/foaf/0.1/interest", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "interest", + "undefined" : "interest" + }, + "domain" : "1", + "comment" : { + "undefined" : "A page about a topic of interest to this person." + }, + "attributes" : [ "object" ], + "id" : "0" + }, { + "iri" : "http://xmlns.com/foaf/0.1/mbox_sha1sum", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "6", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "mbox_sha1sum", + "undefined" : "sha1sum of a personal mailbox URI name" + }, + "domain" : "5", + "comment" : { + "undefined" : "The sha1sum of the URI of an Internet mailbox associated with exactly one owner, the first owner of the mailbox." + }, + "attributes" : [ "datatype" ], + "id" : "4" + }, { + "iri" : "http://xmlns.com/foaf/0.1/nick", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "8", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "nick", + "undefined" : "nickname" + }, + "domain" : "5", + "comment" : { + "undefined" : "A short informal nickname characterising an agent (includes login identifiers, IRC and other chat nicknames)." + }, + "attributes" : [ "datatype" ], + "id" : "7" + }, { + "iri" : "http://xmlns.com/foaf/0.1/openid", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "openid", + "undefined" : "openid" + }, + "superproperty" : [ "15" ], + "domain" : "1", + "comment" : { + "undefined" : "An OpenID for an Agent." + }, + "attributes" : [ "inverse functional", "object" ], + "id" : "14" + }, { + "iri" : "http://xmlns.com/foaf/0.1/workInfoHomepage", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "workInfoHomepage", + "undefined" : "work info homepage" + }, + "domain" : "12", + "comment" : { + "undefined" : "A work info homepage of some person; a page about their work for some organization." + }, + "attributes" : [ "object" ], + "id" : "16" + }, { + "iri" : "http://xmlns.com/foaf/0.1/pastProject", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "3", + "annotations" : { + "isDefinedBy" : [ { 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"comment" : { + "undefined" : "A theme." + }, + "attributes" : [ "object" ], + "id" : "23" + }, { + "iri" : "http://xmlns.com/foaf/0.1/knows", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "12", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "knows", + "undefined" : "knows" + }, + "domain" : "12", + "comment" : { + "undefined" : "A person known by this person (indicating some level of reciprocated interaction between the parties)." + }, + "attributes" : [ "object" ], + "id" : "25" + }, { + "iri" : "http://xmlns.com/foaf/0.1/focus", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "29", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + 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specified using fully qualified tel: URI scheme (refs: http://www.w3.org/Addressing/schemes.html#tel)." + }, + "attributes" : [ "object" ], + "id" : "30" + }, { + "iri" : "http://xmlns.com/foaf/0.1/depicts", + "inverse" : "34", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "33", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "depicts", + "undefined" : "depicts" + }, + "domain" : "32", + "comment" : { + "undefined" : "A thing depicted in this representation." + }, + "attributes" : [ "object" ], + "id" : "31" + }, { + "iri" : "http://xmlns.com/foaf/0.1/based_near", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "36", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", 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"undefined" : "DNA checksum" + }, + "domain" : "19", + "comment" : { + "undefined" : "A checksum for the DNA of some thing. 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"identifier" : "term_status", + "language" : "undefined", + "value" : "unstable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "status", + "undefined" : "status" + }, + "domain" : "1", + "comment" : { + "undefined" : "A string expressing what the user is happy for the general public (normally) to know about their current activity." + }, + "attributes" : [ "datatype" ], + "id" : "65" + }, { + "iri" : "http://xmlns.com/foaf/0.1/yahooChatID", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "46", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "yahooChatID", + "undefined" : "Yahoo chat ID" + }, + "domain" : "19", + "comment" : { + "undefined" : "A Yahoo chat ID" + }, + "attributes" : [ 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"undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "icqChatID", + "undefined" : "ICQ chat ID" + }, + "domain" : "19", + "comment" : { + "undefined" : "An ICQ chat ID" + }, + "attributes" : [ "datatype" ], + "id" : "70" + }, { + "iri" : "http://xmlns.com/foaf/0.1/givenname", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "73", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "archaic", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "givenname", + "undefined" : "Given name" + }, + "domain" : "19", + "comment" : { + "undefined" : "The given name of some person." + }, + "attributes" : [ "datatype" ], + "id" : "72" + }, { + "iri" : "http://xmlns.com/foaf/0.1/isPrimaryTopicOf", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "isPrimaryTopicOf", + "undefined" : "is primary topic of" + }, + "superproperty" : [ "38" ], + "domain" : "39", + "subproperty" : [ "14", "43" ], + "comment" : { + "undefined" : "A document that this thing is the primary topic of." + }, + "attributes" : [ "inverse functional", "object" ], + "id" : "15" + }, { + "range" : "2", + "domain" : "32", + "attributes" : [ "anonymous", "object" ], + "id" : "74" + }, { + "range" : "2", + "domain" : "71", + "attributes" : [ "anonymous", "object" ], + "id" : "75" + }, { + "range" : "78", + "domain" : "77", + "attributes" : [ "anonymous", "object" ], + "id" : "76" + }, { + "range" : "36", + "domain" : "12", + "attributes" : [ "anonymous", "object" ], + "id" : "79" + }, { + "iri" : "http://xmlns.com/foaf/0.1/accountServiceHomepage", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "accountServiceHomepage", + "undefined" : "account service homepage" + }, + "domain" : "78", + "comment" : { + "undefined" : "Indicates a homepage of the service provide for this online account." + }, + "attributes" : [ "object" ], + "id" : "80" + }, { + "iri" : "http://xmlns.com/foaf/0.1/logo", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "19", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "logo", + "undefined" : "logo" + }, + "domain" : "19", + "comment" : { + "undefined" : "A logo representing some thing." + }, + "attributes" : [ "inverse functional", "object" ], + "id" : "81" + }, { + "range" : "78", + "domain" : "83", + "attributes" : [ "anonymous", "object" ], + "id" : "82" + }, { + "iri" : "http://xmlns.com/foaf/0.1/depiction", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "32", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "depiction", + "undefined" : "depiction" + }, + "domain" : "33", + "subproperty" : [ "84" ], + "comment" : { + "undefined" : "A depiction of some thing." + }, + "attributes" : [ "object" ], + "id" : "34" + }, { + "range" : "78", + "domain" : "86", + "attributes" : [ "anonymous", "object" ], + "id" : "85" + }, { + "iri" : "http://xmlns.com/foaf/0.1/family_name", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "88", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "archaic", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "family_name", + "undefined" : "family_name" + }, + "domain" : "12", + "comment" : { + "undefined" : "The family name of some person." + }, + "attributes" : [ "datatype" ], + "id" : "87" + }, { + "range" : "1", + "domain" : "12", + "attributes" : [ "anonymous", "object" ], + "id" : "89" + }, { + "range" : "1", + "domain" : "11", + "attributes" : [ "anonymous", "object" ], + "id" : "90" + }, { + "iri" : "http://xmlns.com/foaf/0.1/fundedBy", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "19", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "archaic", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "fundedBy", + "undefined" : "funded by" + }, + "domain" : "19", + "comment" : { + "undefined" : "An organization funding a project or person." + }, + "attributes" : [ "object" ], + "id" : "91" + }, { + "iri" : "http://xmlns.com/foaf/0.1/title", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "93", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "title", + "undefined" : "title" + }, + "domain" : "19", + "comment" : { + "undefined" : "Title (Mr, Mrs, Ms, Dr. etc)" + }, + "attributes" : [ "datatype" ], + "id" : "92" + }, { + "iri" : "http://xmlns.com/foaf/0.1/accountName", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "59", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "accountName", + "undefined" : "account name" + }, + "domain" : "78", + "comment" : { + "undefined" : "Indicates the name (identifier) associated with this online account." + }, + "attributes" : [ "datatype" ], + "id" : "95" + }, { + "iri" : "http://xmlns.com/foaf/0.1/account", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "78", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "account", + "undefined" : "account" + }, + "domain" : "1", + "comment" : { + "undefined" : "Indicates an account held by this agent." + }, + "attributes" : [ "object" ], + "id" : "96" + }, { + "iri" : "http://xmlns.com/foaf/0.1/jabberID", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "69", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "jabberID", + "undefined" : "jabber ID" + }, + "domain" : "19", + "comment" : { + "undefined" : "A jabber ID for something." + }, + "attributes" : [ "datatype" ], + "id" : "97" + }, { + "range" : "1", + "domain" : "10", + "attributes" : [ "anonymous", "object" ], + "id" : "98" + }, { + "iri" : "http://xmlns.com/foaf/0.1/age", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "100", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "unstable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "age", + "undefined" : "age" + }, + "domain" : "1", + "comment" : { + "undefined" : "The age in years of some agent." + }, + "attributes" : [ "datatype", "functional" ], + "id" : "99" + }, { + "iri" : "http://xmlns.com/foaf/0.1/homepage", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "homepage", + "undefined" : "homepage" + }, + "superproperty" : [ "15", "38" ], + "domain" : "39", + "comment" : { + "undefined" : "A homepage for some thing." + }, + "attributes" : [ "inverse functional", "object" ], + "id" : "43" + }, { + "iri" : "http://xmlns.com/foaf/0.1/tipjar", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "tipjar", + "undefined" : "tipjar" + }, + "superproperty" : [ "38" ], + "domain" : "1", + "comment" : { + "undefined" : "A tipjar document for this agent, describing means for payment and reward." + }, + "attributes" : [ "object" ], + "id" : "42" + }, { + "iri" : "http://xmlns.com/foaf/0.1/msnChatID", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "61", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "msnChatID", + "undefined" : "MSN chat ID" + }, + "domain" : "5", + "comment" : { + "undefined" : "An MSN chat ID" + }, + "attributes" : [ "datatype" ], + "id" : "103" + }, { + "iri" : "http://xmlns.com/foaf/0.1/topic_interest", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "18", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "topic_interest", + "undefined" : "topic_interest" + }, + "domain" : "1", + "comment" : { + "undefined" : "A thing of interest to this person." + }, + "attributes" : [ "object" ], + "id" : "104" + }, { + "iri" : "http://xmlns.com/foaf/0.1/aimChatID", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "106", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "aimChatID", + "undefined" : "AIM chat ID" + }, + "domain" : "19", + "comment" : { + "undefined" : "An AIM chat ID" + }, + "attributes" : [ "datatype" ], + "id" : "105" + }, { + "iri" : "http://xmlns.com/foaf/0.1/currentProject", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "3", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "currentProject", + "undefined" : "current project" + }, + "domain" : "12", + "comment" : { + "undefined" : "A current project this person works on." + }, + "attributes" : [ "object" ], + "id" : "107" + }, { + "iri" : "http://xmlns.com/foaf/0.1/skypeID", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "20", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "skypeID", + "undefined" : "Skype ID" + }, + "domain" : "1", + "comment" : { + "undefined" : "A Skype ID" + }, + "attributes" : [ "datatype" ], + "id" : "108" + }, { + "iri" : "http://xmlns.com/foaf/0.1/holdsAccount", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "78", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "archaic", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "holdsAccount", + "undefined" : "account" + }, + "domain" : "1", + "comment" : { + "undefined" : "Indicates an account held by this agent." + }, + "attributes" : [ "object" ], + "id" : "109" + }, { + "iri" : "http://xmlns.com/foaf/0.1/thumbnail", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "32", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "thumbnail", + "undefined" : "thumbnail" + }, + "domain" : "32", + "comment" : { + "undefined" : "A derived thumbnail image." + }, + "attributes" : [ "object" ], + "id" : "110" + }, { + "iri" : "http://xmlns.com/foaf/0.1/topic", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "39", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "topic", + "undefined" : "topic" + }, + "domain" : "2", + "comment" : { + "undefined" : "A topic of some page or document." + }, + "attributes" : [ "object" ], + "id" : "40" + }, { + "iri" : "http://xmlns.com/foaf/0.1/weblog", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "weblog", + "undefined" : "weblog" + }, + "superproperty" : [ "38" ], + "domain" : "1", + "comment" : { + "undefined" : "A weblog of some thing (whether person, group, company etc.)." + }, + "attributes" : [ "inverse functional", "object" ], + "id" : "41" + }, { + "iri" : "http://xmlns.com/foaf/0.1/img", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "32", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "img", + "undefined" : "image" + }, + "superproperty" : [ "34" ], + "domain" : "12", + "comment" : { + "undefined" : "An image that can be used to represent some thing (ie. those depictions which are particularly representative of something, eg. one's photo on a homepage)." + }, + "attributes" : [ "object" ], + "id" : "84" + }, { + "iri" : "http://xmlns.com/foaf/0.1/birthday", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "56", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "unstable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "birthday", + "undefined" : "birthday" + }, + "domain" : "1", + "comment" : { + "undefined" : "The birthday of this Agent, represented in mm-dd string form, eg. '12-31'." + }, + "attributes" : [ "datatype", "functional" ], + "id" : "111" + }, { + "iri" : "http://xmlns.com/foaf/0.1/sha1", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "101", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "unstable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "sha1", + "undefined" : "sha1sum (hex)" + }, + "domain" : "2", + "comment" : { + "undefined" : "A sha1sum hash, in hex." + }, + "attributes" : [ "datatype" ], + "id" : "112" + }, { + "iri" : "http://xmlns.com/foaf/0.1/firstName", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "24", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "firstName", + "undefined" : "firstName" + }, + "domain" : "12", + "comment" : { + "undefined" : "The first name of a person." + }, + "attributes" : [ "datatype" ], + "id" : "113" + }, { + "iri" : "http://xmlns.com/foaf/0.1/made", + "inverse" : "115", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "18", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "made", + "undefined" : "made" + }, + "domain" : "1", + "comment" : { + "undefined" : "Something that was made by this agent." + }, + "attributes" : [ "object" ], + "id" : "114" + }, { + "range" : "60", + "domain" : "2", + "attributes" : [ "anonymous", "object" ], + "id" : "116" + }, { + "range" : "12", + "domain" : "60", + "attributes" : [ "anonymous", "object" ], + "id" : "117" + }, { + "iri" : "http://xmlns.com/foaf/0.1/familyName", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "62", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "familyName", + "undefined" : "familyName" + }, + "domain" : "12", + "comment" : { + "undefined" : "The family name of some person." + }, + "attributes" : [ "datatype" ], + "id" : "119" + }, { + "range" : "2", + "domain" : "11", + "attributes" : [ "anonymous", "object" ], + "id" : "120" + }, { + "range" : "12", + "domain" : "11", + "attributes" : [ "anonymous", "object" ], + "id" : "121" + }, { + "iri" : "http://xmlns.com/foaf/0.1/member", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "1", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "member", + "undefined" : "member" + }, + "domain" : "10", + "comment" : { + "undefined" : "Indicates a member of a Group" + }, + "attributes" : [ "object" ], + "id" : "122" + }, { + "iri" : "http://xmlns.com/foaf/0.1/plan", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "27", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "plan", + "undefined" : "plan" + }, + "domain" : "12", + "comment" : { + "undefined" : "A .plan comment, in the tradition of finger and '.plan' files." + }, + "attributes" : [ "datatype" ], + "id" : "123" + }, { + "iri" : "http://xmlns.com/foaf/0.1/mbox", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "18", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "mbox", + "undefined" : "personal mailbox" + }, + "domain" : "1", + "comment" : { + "undefined" : "A personal mailbox, ie. an Internet mailbox associated with exactly one owner, the first owner of this mailbox. This is a 'static inverse functional property', in that there is (across time and change) at most one individual that ever has any particular value for foaf:mbox." + }, + "attributes" : [ "inverse functional", "object" ], + "id" : "124" + }, { + "iri" : "http://xmlns.com/foaf/0.1/surname", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "118", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "archaic", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "surname", + "undefined" : "Surname" + }, + "domain" : "12", + "comment" : { + "undefined" : "The surname of some person." + }, + "attributes" : [ "datatype" ], + "id" : "125" + }, { + "iri" : "http://xmlns.com/foaf/0.1/myersBriggs", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "22", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "myersBriggs", + "undefined" : "myersBriggs" + }, + "domain" : "12", + "comment" : { + "undefined" : "A Myers Briggs (MBTI) personality classification." + }, + "attributes" : [ "datatype" ], + "id" : "127" + }, { + "iri" : "http://xmlns.com/foaf/0.1/maker", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "1", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "stable", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "maker", + "undefined" : "maker" + }, + "domain" : "18", + "comment" : { + "undefined" : "An agent that made this thing." + }, + "attributes" : [ "object" ], + "id" : "115" + }, { + "iri" : "http://xmlns.com/foaf/0.1/publications", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "publications", + "undefined" : "publications" + }, + "domain" : "12", + "comment" : { + "undefined" : "A link to the publications of this person." + }, + "attributes" : [ "object" ], + "id" : "128" + }, { + "iri" : "http://xmlns.com/foaf/0.1/workplaceHomepage", + "baseIri" : "http://xmlns.com/foaf/0.1", + "range" : "2", + "annotations" : { + "isDefinedBy" : [ { + "identifier" : "isDefinedBy", + "language" : "undefined", + "value" : "http://xmlns.com/foaf/0.1/", + "type" : "iri" + } ], + "term_status" : [ { + "identifier" : "term_status", + "language" : "undefined", + "value" : "testing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "workplaceHomepage", + "undefined" : "workplace homepage" + }, + "domain" : "12", + "comment" : { + "undefined" : "A workplace homepage of some person; the homepage of an organization they work for." + }, + "attributes" : [ "object" ], + "id" : "129" + } ] +} \ No newline at end of file diff --git a/doc/releases/0.1.0/steps/webvowl/data/ontology.json b/doc/releases/0.1.0/steps/webvowl/data/ontology.json new file mode 100644 index 0000000..a4d3fb0 --- /dev/null +++ b/doc/releases/0.1.0/steps/webvowl/data/ontology.json @@ -0,0 +1,12533 @@ +{ + "_comment" : "Created with OWL2VOWL (version 0.3.5), http://vowl.visualdataweb.org", + "header" : { + "languages" : [ "en", "undefined" ], + "baseIris" : [ "http://www.w3.org/1999/02/22-rdf-syntax-ns", "http://purl.org/neao/data", "http://www.w3.org/2002/07/owl", "http://www.w3.org/2000/01/rdf-schema", "http://www.w3.org/2001/XMLSchema", "http://purl.org/neao/base", "http://purl.org/neao/steps" ], + "iri" : "http://purl.org/neao/steps#", + "version" : "0.1.0", + "author" : [ "Michael Denker (ORCID: 0000-0003-1255-7300)", "Cristiano Köhler (ORCID: 0000-0003-0503-5264)" ], + "labels" : { + "en" : "Neuroelectrophysiology Analysis Ontology - Analysis Steps" + }, + "comments" : { + "en" : "This module in the Neuroelectrophysiology Analysis Ontology contains classes that represent (atomic) steps in the analysis of neuroelectrophysiology data.\n\nThe main classes are subclasses of the AnalysisStep class (defined in the base module), and represent the different methods and procedures used in the analysis to generate new data or to perform specific operations aimed to transform or extract additional information from the input(s). The classes are organized in a taxonomy, and the lowest level of the hierarchy represent specific, fine-grained descriptions of a step used in the analysis.\n\nGrouping classes are provided to identify analysis steps according to their semantic similarities. This is used to keep the fine-grained descriptions associated with specific analysis methods (e.g., a step that used either the Welch or multitaper method to compute the power spectral density) while providing the ability to identify the steps in a more general nature (e.g., a step that computed a power spectral density). The grouping classes are defined in the taxonomy hierarchy by subclasses, and also as classes inferred by reasoning with the hasPurpose object property (that points to individuals of the AnalysisPurpose class, such as FunctionalConnectivityPurpose) or data properties defining boolean values (e.g., isBivariate). Therefore, groupings across multiple semantic dimensions are available (e.g., bivariate analyses or functional connectivity analyses). \n\nThe information regarding the inputs and outputs can be associated with each step by the hasInput and hasOutput object properties that point to individuals that represent data entities (using the classes defined in the data module).\n\nThe parameters used to control the behavior of the analysis step are defined with the usesParameter object property that points to individuals that represent specific parameters (using the classes defined in the parameters module).\n\nThe relevant bibliographic references are provided with the hasBibliographicReference annotation property that points to individuals of the BiRO BibliographicReference class (defined in the bibliography module). This structures the specific information associated with the analysis step represented by the class, and helps to disambiguate the description of the diversity of methods that are available to analyze neuroelectrophysiology data. This would be the case, for example, of different algorithms and assumptions (e.g., computing the power spectral density using either the Welch or multitaper approach), and the evolution/modifications of a method (e.g., different computations of phase lag index estimates). \n\nThe details of the software code associated with each analysis step can be provided by the isImplementedIn object property, that points to individuals of the SoftwareImplementation class (defined in the base module).\n\nFinally, the hasSubstep object property is used to describe compound analyses. These analyses involve the execution of multiple smaller steps (substeps) that are associated with specific parameters and intermediary data inputs and outputs. The main compound process can point to other individuals of the AnalysisStep class using the hasSubstep property. Therefore, the appropriate semantic information and description associated with either the compound analysis or each individual substep can be provided in the ontology." + }, + "other" : { + "license" : [ { + "identifier" : "license", + "language" : "undefined", + "value" : "https://creativecommons.org/licenses/by/4.0/", + "type" : "iri" + } ], + "creator" : [ { + "identifier" : "creator", + "language" : "undefined", + "value" : "Cristiano Köhler (ORCID: 0000-0003-0503-5264)", + "type" : "label" + }, { + "identifier" : "creator", + "language" : "undefined", + "value" : "Michael Denker (ORCID: 0000-0003-1255-7300)", + "type" : "label" + } ], + "created" : [ { + "identifier" : "created", + "language" : "undefined", + "value" : "2022-01-19", + "type" : "label" + } ], + "preferredNamespacePrefix" : [ { + "identifier" : "preferredNamespacePrefix", + "language" : "undefined", + "value" : "neao_steps", + "type" : "label" + } ], + "preferredNamespaceUri" : [ { + "identifier" : "preferredNamespaceUri", + "language" : "undefined", + "value" : "http://purl.org/neao/steps#", + "type" : "label" + } ], + "versionInfo" : [ { + "identifier" : "versionInfo", + "language" : "undefined", + "value" : "0.1.0", + "type" : "label" + } ] + } + }, + "namespace" : [ ], + "class" : [ { + "id" : "9", + "type" : "owl:Class" + }, { + "id" : "43", + "type" : "owl:Class" + }, { + "id" : "45", + "type" : "owl:Class" + }, { + "id" : "46", + "type" : "owl:Class" + }, { + "id" : "48", + "type" : "owl:Class" + }, { + "id" : "50", + "type" : "owl:Class" + }, { + "id" : "52", + "type" : "owl:Class" + }, { + "id" : "26", + "type" : "owl:Class" + }, { + "id" : "65", + "type" : "owl:Class" + }, { + "id" : "67", + "type" : "owl:Class" + }, { + "id" : "7", + "type" : "owl:Class" + }, { + "id" : "116", + "type" : "owl:Class" + }, { + "id" : "118", + "type" : "owl:Class" + }, { + "id" : "62", + "type" : "owl:Class" + }, { + "id" : "120", + "type" : "owl:Class" + }, { + "id" : "12", + "type" : 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The unbiased estimation uses a correction for the bias due to zero-padding in the computation, applied to the normalization coefficient. Therefore, the resultant cross-correlation values are closer to the true cross-correlation." + }, + "id" : "116", + "superClasses" : [ "117" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeConfidenceIntervalBootstrap", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute confidence interval (bootstrap resampling)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeConfidenceIntervalBootstrap" + }, + "comment" : { + "en" : "A confidence interval resampling analysis that computes the confidence interval using bootstrapping techniques to create many simulated samples (bootstrap samples). It involves repeatedly sampling, with replacement, from the input (observed) data. The total number of bootstrap samples is defined as a parameter. Bootstrapping makes minimal assumptions about the underlying distribution of the data, making it especially useful for small samples or when the data do not meet the assumptions of traditional parametric (non-resampling) methods." + }, + "id" : "118", + "superClasses" : [ "119" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplySum", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply sum", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplySum" + }, + "comment" : { + "en" : "A data transformation that performs the addition of two or more data inputs to obtain a sum." + }, + "id" : "62", + "superClasses" : [ "5" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplyNonNegativeTensorComponentAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply non-negative tensor component analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplyNonNegativeTensorComponentAnalysis" + }, + "comment" : { + "en" : "A tensor component analysis (TCA) where a non-negative constraint is applied to the decomposition. This is desirable when the underlying components have physical interpretation and negative values are not possible." + }, + "id" : "120", + "superClasses" : [ "49" ] + }, { + "iri" : "http://purl.org/neao/steps#GenerateTrialShufflingSurrogate", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Louis2010_359", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "generate trial shuffling surrogate", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "GenerateTrialShufflingSurrogate" + }, + "comment" : { + "en" : "A spike train surrogate generation step where the the spike trains of single-trial activity of one of the neurons are randomly permuted, so that each trial is no longer paired with the corresponding trial of the other neuron, but with a randomly selected one. The input is a collection of spike trains with multitrial activity data of multiple neurons recorded in parallel." + }, + "id" : "12", + "superClasses" : [ "121" ] + }, { + "iri" : "http://purl.org/neao/steps#DataGeneration", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "data generation", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "DataGeneration" + }, + "subClasses" : [ "124", "97", "121", "125" ], + "comment" : { + "en" : "An analysis step that generates new data entities. This can be done using other input data as a start (e.g., generating a spike train surrogate from spike trains obtained from experimental recordings) or generate new data using algorithms that take specific parameters (e.g., generating a spike train using a probability distribution defined by specific parameters)." + }, + "id" : "122", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#ASSETAnalysisProbabilityMatrixSubstep", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Torre2016_e1004939", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "ASSET analysis probability matrix substep", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ASSETAnalysisProbabilityMatrixSubstep" + }, + "subClasses" : [ "126", "127" ], + "comment" : { + "en" : "ASSET analysis substep that computes the probability matrix (PMAT). The probability matrix contains, for each entry in the intersection matrix, the cumulative probability representing the probability of having the overlap in the IMAT under the assumption that the spike trains are independent. If an entry in the PMAT is large, the null hypothesis of independence is rejected, and the alternative hypothesis that the observed overlap reflects active synchronization between the involved neurons at the time bins of the intersection is accepted. The PMAT computation can be done with either an analytical or Monte Carlo approach." + }, + "id" : "64", + "superClasses" : [ "55" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeLVR", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Shinomoto2009_e1000433", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute revised local variation", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute LvR", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeLVR" + }, + "comment" : { + "en" : "An interspike interval variability analysis that computes the revised local variation (LvR) of interspike intervals. Compared to the original local variation (LV) measure, LvR has better invariance to fluctuations in the firing rate fluctuations. This is achieved by using a refractoriness constant in the computation of the measure." + }, + "id" : "128", + "superClasses" : [ "129" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeSpikeWaveformAverage", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute spike waveform average", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeSpikeWaveformAverage" + }, + "comment" : { + "en" : "A spike waveform analysis that computes the average across two or more spike waveform inputs. For the computation, the mean value across all inputs is obtained for each time point in the sampled spike waveform. This is frequently used to reduce noise across multiple spike waveform samples of a single neuron." + }, + "id" : "164", + "superClasses" : [ "165" ] + }, { + "iri" : "http://purl.org/neao/steps#CentralTendencyStatisticalAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "central tendency statistical analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "CentralTendencyStatisticalAnalysis" + }, + "subClasses" : [ "181", "182" ], + "comment" : { + "en" : "A statistical analysis to compute a measure of central tendency, i.e., that represents the center or typical value of the input data." + }, + "id" : "179", + "superClasses" : [ "180" ] + }, { + "iri" : "http://purl.org/neao/data#CurrentSourceDensity", + "baseIri" : "http://purl.org/neao/data", + "instances" : 0, + "label" : { + "IRI-based" : "CurrentSourceDensity" + }, + "attributes" : [ "external" ], + "id" : "183" + }, { + "iri" : "http://purl.org/neao/steps#GenerateISIDitheringSurrogate", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Stella2022_ENEURO", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "generate joint interspike interval dithering surrogate", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "generate ISI-D surrogate", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "GenerateISIDitheringSurrogate" + }, + "comment" : { + "en" : "A spike train surrogate generation step where each spike is displaced according to the interspike interval (ISI) distribution sampled from the input spike train." + }, + "id" : "184", + "superClasses" : [ "121" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeCanonicalCoherence", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Vidaurre2019_116009", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute canonical coherence", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute caCOH", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeCanonicalCoherence" + }, + "comment" : { + "en" : "A coherence analysis that computes the canonical coherence (caCOH) according to Vidaurre et al. (2019). The computation maximizes the coherence between two inputs (e.g., distinct datasets with electroencephalogram, electromyogram or local field potential recordings). The absolute value of the coherence between the two multivariate spaces of the inputs in the frequency domain is maximized. The caCOH aims to maximize the strength of the synchronization of oscillatory signals when two multichannel datasets are present (e.g., multiple subjects). The method then finds two spatial projections maximizing the strength of synchronization." + }, + "id" : "185", + "superClasses" : [ "136" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeOptimalBinSize", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Scott1979_605", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute optimal bin size", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeOptimalBinSize" + }, + "comment" : { + "en" : "An analysis step that finds the optimal bin size considering the input data when discretizing data into smaller intervals (bins). The computation uses the formula from Scott (1979)." + }, + "id" : "202", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#CompoundAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compound analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "CompoundAnalysis" + }, + "comment" : { + "en" : "An analysis step that is composed by two or more substeps, each performing a part of the analysis with its own data inputs/outputs and analysis parameters." + }, + "id" : "229", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplyLinearDiscriminantAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply linear discriminant analysis", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "apply LDA", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplyLinearDiscriminantAnalysis" + }, + "comment" : { + "en" : "A dimensionality reduction that finds a linear combination of features that separates two or more classes defined in the input data. The input data must have a variable that defines the class for each observation, and continuous variables that are used for the linear discriminant analysis (LDA). LDA finds an optimal projection vector that maximizes the distance between the means of the different classes, and minimizes the variance within each class. LDA projects the input data into the lower-dimensional space, therefore reducing the number of features while retaining the information needed for classification. The optimal projection vectors found by LDA are the Fisher linear discriminants." + }, + "id" : "234", + "superClasses" : [ "51" ] + }, { + "iri" : "http://purl.org/neao/steps#DispersionStatisticalAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "dispersion statistical analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "DispersionStatisticalAnalysis" + }, + "subClasses" : [ "235", "46", "236", "237", "238" ], + "comment" : { + "en" : "A statistical analysis that computes a measure that represents the variability in the input data. 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This can be accomplished using several methods, such as linear interpolation (i.e., estimating the values along a straight line connecting adjacent points), polynomial interpolation (i.e., using polynomials to estimate the values between points), or spline Interpolation (i.e., using piecewise polynomials that pass through the known data points and provide a smooth curve)." + }, + "id" : "21", + "superClasses" : [ "5" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeSpikeTimeTilingCoefficient", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Cutts2014_14288", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute spike time tiling coefficient", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute STTC", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeSpikeTimeTilingCoefficient" + }, + "comment" : { + "en" : "A spike train correlation analysis that computes the spike time tiling coefficient (STTC) as described by Cutts and Eglen (2014). The STTC measures the pairwise correlation between two input spike trains, and has advantages over the related correlation index: it is not confounded by the firing rate, it distinguishes lack of correlation from anti-correlation, periods without neural activity don't add to the correlation, and it is sensitive to firing patterns. The computation is based on a synchronicity window parameter, that is used to define short time windows around each spike that are used in the computation (spike time tiling)." + }, + "id" : "243", + "superClasses" : [ "244" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeCurrentSourceDensityKCSD", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Potworowski2012_541", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute current source density (kernel method)", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute kCSD", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeCurrentSourceDensityKCSD" + }, + "comment" : { + "en" : "A current source density (CSD) analysis that uses kernel methods to compute the CSD (kCSD), described by Potworowski et al. (2012). kCSD is non parametric and can estimate the CSD using signals recorded from arbitrarily distributed electrodes, as the assumption of regular electrode placement is not necessary. The method can handle 1D, 2D or 3D electrode configurations. The kCSD can also estimate CSD at any location, as it is not limited to the electrode positions, and uses cross-validation to ensure no overfitting." + }, + "id" : "245", + "superClasses" : [ "246" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeCurrentSourceDensityStandard", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Vaknin1988_131", + "type" : "iri" + }, { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Freeman1975_369", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute current source density (standard method)", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute CSD", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeCurrentSourceDensityStandard" + }, + "comment" : { + "en" : "A current source density (CSD) analysis that uses a double spatial derivative of the recorded extracellular potentials to compute the CSD. The original method by Freeman & Nicholson (1975) assumes homogeneous cortical in-plane activity, constant extracellular electrical conductivity and equidistant electrode contacts, and can only predict the CSD at interior electrode positions. Vaknin et al. (1988) suggested a procedure to obtain the CSD for the first and last electrodes by copying the outmost recordings, therefore extending the grid beyond the electrode contacts. This is based on the assumption that the potential varies negligibly above the first and below the last electrode." + }, + "id" : "249", + "superClasses" : [ "246" ] + }, { + "iri" : "http://purl.org/neao/steps#GrangerCausalityAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "Granger causality analysis", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "GC analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "GrangerCausalityAnalysis" + }, + "subClasses" : [ "201", "264" ], + "comment" : { + "en" : "A functional connectivity analysis that computes measures of Granger causality (GC). GC is a statistical concept where the future values of a time series are predicted based on its past values and the past values of other time series. GC quantifies bi-directional interactions between the inputs, determining the directional influence from one input to another. For example, with two inputs, GC measures how much the first input influences the second and vice versa (directional GC measure). This provides estimates of the directed connectivity between the inputs. It is also possible to compute associated measures, such as the instantaneous GC (a measure of interdependence between the inputs not accounted by their bi-directional interactions, such as shared neural input) and the total interdependence (the sum of all directional and instantaneous interactions between the inputs). The analysis can be performed in the time or frequency domains, and can take two (bivariate) or more inputs (multivariate)." + }, + "id" : "139", + "superClasses" : [ "77" ] + }, { + "iri" : "http://purl.org/neao/steps#TimeDomainAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "time domain analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "TimeDomainAnalysis" + }, + "comment" : { + "en" : "An analysis step that analyzes the input(s) with respect to time." + }, + "id" : "265", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplyAdaptiveKernelSmoothing", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply adaptive kernel smoothing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplyAdaptiveKernelSmoothing" + }, + "comment" : { + "en" : "A kernel smoothing that uses a variable-width kernel. The kernel width varies adaptively depending on the local density of the data. This method takes into consideration local variations in data density, resulting in a more accurate representation of the underlying patterns and structures." + }, + "id" : "266", + "superClasses" : [ "267" ] + }, { + "iri" : "http://purl.org/neao/steps#ArtificialDataGeneration", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "artificial data generation", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ArtificialDataGeneration" + }, + "comment" : { + "en" : "A data generation that produces artificial data. Artificial data refers to data that is generated programmatically rather than obtained from experimental recordings (e.g., neural simulations or by using specific statistical procedures). The artificial data generation procedure does not take experimentally-recorded data as input, and the generation of the output data depends only on parameters to the method employed. The isArtificial data property is defined as True for outputs of artificial data generation steps." + }, + "id" : "125", + "superClasses" : [ "122" ] + }, { + "iri" : "http://purl.org/neao/steps#MeanVectorLengthAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "mean vector length analysis", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "MVL analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "MeanVectorLengthAnalysis" + }, + "subClasses" : [ "270", "271" ], + "comment" : { + "en" : "A phase-amplitude coupling (PAC) analysis that computes the mean vector length (MVL) measure. The MVL is based on a mean vector obtained from a time series defined in the complex plane, where the amplitude is taken from the high-frequency oscillation input and the phase from the low-frequency oscillation input." + }, + "id" : "268", + "superClasses" : [ "269" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeSpikeWaveformVariance", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute spike waveform variance", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeSpikeWaveformVariance" + }, + "comment" : { + "en" : "A spike waveform analysis that computes the variance across two or more spike waveform inputs. For the computation, the value of the variance across all inputs is obtained for each time point in the spike waveform." + }, + "id" : "233", + "superClasses" : [ "165" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeInstantaneousFiringRateInterspikeInterval", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute instantaneous firing rate (interspike interval method)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeInstantaneousFiringRateInterspikeInterval" + }, + "comment" : { + "en" : "An instantaneous firing rate analysis that computes the instantaneous firing rate by using the reciprocal of the interspike intervals." + }, + "id" : "297", + "superClasses" : [ "163" ] + }, { + "iri" : "http://purl.org/neao/steps#TimeFrequencyAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "time-frequency analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "TimeFrequencyAnalysis" + }, + "subClasses" : [ "80", "315", "316", "276" ], + "comment" : { + "en" : "A spectral analysis that computes measures describing the frequency content of the input(s) in a time-resolved manner. It allows the analysis of how different frequency components evolve over time, which is essential for non-stationary signals whose spectral characteristics change. The joint time-frequency representation helps in identifying transient features, frequency shifts, and other dynamic behaviors in the input(s)." + }, + "id" : "131", + "superClasses" : [ "132" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeSpikeTrainTimeHistogram", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute spike train time histogram", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeSpikeTrainTimeHistogram" + }, + "comment" : { + "en" : "An analysis step that computes the time histogram of a spike train. If the spike count in a bin is divided by the duration of the bin, this can be used to estimate the instantaneous firing rate at the bin interval." + }, + "id" : "324", + "superClasses" : [ "154" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeNoiseCorrelations", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Cohen2011_811", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute noise correlations", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute NC", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeNoiseCorrelations" + }, + "comment" : { + "en" : "A spike train correlation analysis that computes the noise correlations (NC) between two input spike trains. The NC is the Pearson's correlation coefficient of spike count responses to repeated presentations of identical stimuli, under the same behavioral conditions. The spike counts are typically measured over the time scale of a stimulus presentation or a behavioral trial, which range from a few hundred milliseconds to several seconds. NC assesses whether neurons exhibit trial-by-trial fluctuations in firing rates that are not influenced by varying sensory or behavioral conditions." + }, + "id" : "292", + "superClasses" : [ "244" ] + }, { + "iri" : "http://purl.org/neao/steps#ExecuteCellAssemblyDetectionAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Russo2017_e19428", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "execute Cell Assembly Detection analysis", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "execute CAD analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ExecuteCellAssemblyDetectionAnalysis" + }, + "comment" : { + "en" : "A neuronal activity pattern detection analysis that uses the Cell Assembly Detection (CAD) method as defined in Russo & Durstewitz (2017). CAD allows detecting spatio-temporal spike patterns at different time scales, levels of precision, and with arbitrary internal organization. The analysis identifies patterns with different delays between the spikes (within a window determining the minimum and maximum lags), and is performed in two steps using an agglomerative clustering algorithm. First, significant pairwise correlations are identified, which is followed by the clustering procedure that progressively finds interactions of higher order. At each agglomeration step, the method can filter out patterns involving the same neurons, keeping the most significant pattern (significance pruning). In an additional pruning step, assemblies part of a larger assembly can also be eliminated (controlled by the subgroup pruning parameter). The algorithm stops when the detected assemblies reach their maximum size (determined by a parameter). The statistical test assumes independence under non-stationarity and Poisson distribution of the input spike trains." + }, + "id" : "220", + "superClasses" : [ "216" ] + }, { + "iri" : "http://purl.org/neao/steps#DimensionalityReduction", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "dimensionality reduction", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "DimensionalityReduction" + }, + "subClasses" : [ "326", "234", "327", "50", "49" ], + "comment" : { + "en" : "A data transformation that obtains a low-dimensional (simplified) representation of the high-dimensional input data. 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The eigenvectors, corresponding to the principal components (PCs), are sorted by the magnitude of their associated eigenvalues. The eigenvectors with the largest eigenvalues explain the most variance in the data and thus form the primary PCs." + }, + "id" : "329", + "superClasses" : [ "327" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeISIDistance", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Kreuz2007_151", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute ISI-distance", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeISIDistance" + }, + "comment" : { + "en" : "A time-scale independent spike train distance analysis that computes the ISI-distance, described in Kreuz et al. (2007). For the computation, the discrete sequence of spike times is transformed into a continuous temporal profile with one value per sample point. The values at each time point are derived from the interspike intervals. The distance is then obtained as the temporal average of the time profile. ISI-distance is well-designed to describe similarities in the firing rate profile of the input spike trains, but it is not optimal to capture neuronal synchrony." + }, + "id" : "330", + "superClasses" : [ "288" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputePowerSpectralDensityMultitaper", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Thomson1982_1055", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute power spectral density (multitaper method)", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute PSD (multitaper method)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputePowerSpectralDensityMultitaper" + }, + "comment" : { + "en" : "A power spectral density (PSD) analysis that uses a multitaper approach to compute the PSD, according to Thomson (1982). The multitaper method uses discrete prolate spheroidal functions (DPSS, also known as Slepian sequences) as tapers applied to the input signal. For the computation, a PSD using the periodogram method is obtained for each tapered signal. The DPSS functions are orthogonal, and therefore applying multiple DPSS tapers result in independent estimates of the PSD. The final PSD is obtained by averaging the periodograms across all tapers. The multitaper method reduces variance and bias in the PSD, and has a high frequency resolution. However, it is computationally expensive. The number of tapers used is passed as parameter, or estimated from the desired resolution." + }, + "id" : "331", + "superClasses" : [ "192" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeSpikeContrast", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Ciba2018_136", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute Spike-contrast", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeSpikeContrast" + }, + "comment" : { + "en" : "A spike train synchrony analysis that computes the Spike-contrast measure using the method described by Ciba et al. (2018). Spike-contrast is a time-scale independent measure of spike synchrony. The input is a set of parallel spike train data recorded from a population of neurons. The algorithm is based on the temporal \"contrast\" (activity vs. non-activity in certain time bins). The computation outputs a single synchrony value (comparable to a spike train distance) and a synchrony curve showing the value of Spike-contrast as a function of the bin size." + }, + "id" : "207", + "superClasses" : [ "208" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeSpikeTrainAutocorrelationTimeScale", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Wieland2015_040901", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute spike train autocorrelation time scale", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeSpikeTrainAutocorrelationTimeScale" + }, + "comment" : { + "en" : "An analysis step that computes the autocorrelation time of a binned spike train input (spike train autocorrelation time scale). The computation follows the method described by Wieland et al. (2015)." + }, + "id" : "332", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeComplexityDistribution", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Gruen2007_96", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute complexity distribution", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeComplexityDistribution" + }, + "comment" : { + "en" : "A spike train synchrony analysis that computes the complexity distribution across a set of input spike trains that typically contain the activity of different neurons. In a neuronal population, the complexity represents the total number of neurons that were spiking within a discrete time interval. For the computation, the binarized population histogram (i.e., a spike time histogram computed across spike trains, where each bin will have the count of spike trains that had at least one spike within the bin interval) is obtained using a bin size specified as a parameter. The value at each bin is the complexity. The complexity distribution is obtained by finding the frequency of each complexity value (complexity histogram) and corresponding probability density function (PDF). The complexity PDF describes the likelihood of different complexity values occurring within the neuronal population." + }, + "id" : "222", + "superClasses" : [ "208" ] + }, { + "iri" : "http://www.w3.org/2001/XMLSchema#boolean", + "baseIri" : "http://www.w3.org/2001/XMLSchema", + "id" : "339", + "label" : { + "IRI-based" : "boolean" + } + }, { + "iri" : "http://www.w3.org/2001/XMLSchema#boolean", + "baseIri" : "http://www.w3.org/2001/XMLSchema", + "id" : "344", + "label" : { + "IRI-based" : "boolean" + } + }, { + "iri" : "http://www.w3.org/2002/07/owl#Thing", + "baseIri" : "http://owl2vowl.de", + "id" : "241", + "label" : { + "undefined" : "Thing" + } + }, { + "iri" : "http://www.w3.org/2000/01/rdf-schema#Literal", + "id" : "242", + "label" : { + "IRI-based" : "Literal", + "undefined" : "Literal" + } + }, { + "iri" : "http://www.w3.org/2001/XMLSchema#boolean", + "baseIri" : "http://www.w3.org/2001/XMLSchema", + "id" : "369", + "label" : { + "IRI-based" : "boolean" + } + }, { + "iri" : "http://www.w3.org/2001/XMLSchema#boolean", + "baseIri" : "http://www.w3.org/2001/XMLSchema", + "id" : "374", + "label" : { + "IRI-based" : "boolean" + } + }, { + "iri" : "http://www.w3.org/2001/XMLSchema#boolean", + "baseIri" : "http://www.w3.org/2001/XMLSchema", + "id" : "377", + "label" : { + "IRI-based" : "boolean" + } + }, { + "iri" : "http://www.w3.org/2001/XMLSchema#boolean", + "baseIri" : "http://www.w3.org/2001/XMLSchema", + "id" : "380", + "label" : { + "IRI-based" : "boolean" + } + }, { + "iri" : "http://purl.org/neao/steps#ComputePowerSpectralDensityBartlett", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Bartlett1950_1", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute power spectral density (Bartlett method)", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute PSD (Bartlett method)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputePowerSpectralDensityBartlett" + }, + "comment" : { + "en" : "A power spectral density (PSD) analysis that uses the method defined by Bartlett (1950). For the computation, the input time is divided into non-overlapping segments, with length specified as a parameter. A periodogram is computed for each segment to obtain the single-segment PSD. The final PSD is obtained by averaging all the single-segment PSDs. A window function can be applied to each segment before computing the periodograms. The PSD obtained with the Bartlett method is less noisy than a single periodogram obtained from the entire signal, although the frequency resolution of the estimates is reduced due to segmenting. It is equivalent to the Welch method without any segment overlap." + }, + "id" : "368", + "superClasses" : [ "192" ] + }, { + "iri" : "http://purl.org/neao/data#LVR", + "baseIri" : "http://purl.org/neao/data", + "instances" : 0, + "label" : { + "IRI-based" : "LVR" + }, + "attributes" : [ "external" ], + "id" : "381" + }, { + "iri" : "http://purl.org/neao/steps#PhaseAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "phase analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "PhaseAnalysis" + }, + "subClasses" : [ "269", "383", "257", "384", "385", "386", "387", "388", "389" ], + "comment" : { + "en" : "An analysis step that computes measures related to the phase in the input data. Phase expresses the position of a time-varying signal relative to a fixed reference point in time. For periodic and oscillatory signals (e.g., a sine waveform), phase analysis involves determining the angle on the unit circle that corresponds to the current position within the waveform's cycle. This helps understanding the timing and synchronization of the oscillations in the input data." + }, + "id" : "382", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#ModelBasedAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "model-based analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ModelBasedAnalysis" + }, + "comment" : { + "en" : "An analysis step that depends on assumptions on the interactions between the inputs to perform the computations. For example, the Granger causality analysis assumes linear relationships between the input signals." + }, + "id" : "390", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeSpikeTrainAutocorrelationHistogram", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute spike train autocorrelation histogram", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeSpikeTrainAutocorrelationHistogram" + }, + "comment" : { + "en" : "An autocorrelation analysis that computes the autocorrelation histogram for a input spike train. The histogram is obtained by sliding a time window that is discretized into smaller time intervals (bins) centered on a spike (corresponding to the lag zero). The spike count in each bin is obtained. Therefore, this binning process measures the number of spikes occurring at various time lags relative to the center spike. The histogram window is slidden over each spike in the input spike train, and the spike count in each bin is accumulated to produce the autocorrelation histogram output. The width of the bin interval is controlled by a parameter." + }, + "id" : "439", + "superClasses" : [ "303" ] + }, { + "iri" : "http://purl.org/neao/steps#CoherencyAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "coherency analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "CoherencyAnalysis" + }, + "subClasses" : [ "441", "442", "443" ], + "comment" : { + "en" : "A spectral analysis that computes a measure of coherency between two inputs. Coherency is a complex-valued measure that describes the linear association of the distinct inputs (e.g., two time series) in different frequency bands." + }, + "id" : "169", + "superClasses" : [ "132" ] + }, { + "iri" : "http://purl.org/neao/steps#ArtifactRemoval", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "artifact removal", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ArtifactRemoval" + }, + "subClasses" : [ "444", "445", "446", "447", "67" ], + "comment" : { + "en" : "A data transformation that aims to identify and remove artifacts from the input data. Artifacts are unwanted disturbances that distorts the data. In an electrophysiology experiment, they can arise from various sources: environmental interference (e.g., electromagnetic interference from nearby equipment), physiological processes (e.g., eye movement, heart beat), and technical instrumentation issues (e.g., baseline drift of the recorded potentials)." + }, + "id" : "36", + "superClasses" : [ "5" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeASSETClusterMatrix", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Torre2016_e1004939", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute ASSET cluster matrix", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeASSETClusterMatrix" + }, + "comment" : { + "en" : "ASSET analysis substep that computes the cluster matrix (CMAT) in the ASSET analysis, using DBSCAN with a modified distance metric. It takes the mask matrix (MMAT) as input. The cluster matrix groups the significant entries in the MMAT according to each diagonal structure that they belong to. For each significant entry in the MMAT, the CMAT will have an integer value: -1 for significant entries that do not belong to any diagonal structure, or any value greater than zero with the identification of the cluster that the entry belongs to." + }, + "id" : "59", + "superClasses" : [ "55" ] + }, { + "iri" : "http://purl.org/neao/steps#CorrelatedSpikeTimesGeneration", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "correlated spike times generation", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "CorrelatedSpikeTimesGeneration" + }, + "subClasses" : [ "470", "471" ], + "comment" : { + "en" : "A spike train generation where the output spike trains will have spikes that are correlated in time. These methods can be used to generate spike trains with patterns in their activity." + }, + "id" : "102", + "superClasses" : [ "97" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeDirectedPhaseLagIndex", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Stam2012_1415", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute directed phase lag index", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute DPLI", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeDirectedPhaseLagIndex" + }, + "comment" : { + "en" : "A phase lag index (PLI) analysis that computes the directed PLI (DPLI) according to Stam & van Straaten (2012). The DPLI uses the Heaviside step function on the imaginary part of the cross power spectral density, and provides the ability to discriminate whether the first time series is leading or lagging the second. The DPLI ranges between 0 and 1. A DPLI value of 0.5 means that the first time series leads and lags the second time series equally often. A DPLI value greater than 0.5 means that the first time series leads the second more often than it lags. A value of 1 means that the first time series always leads. On the contrary, a DPLI value smaller than 0.5 means that the first time series lags the second more often than it leads. A DPLI value of zero means that the first time series always lags. The PLI can be computed from the DPLI." + }, + "id" : "472", + "superClasses" : [ "257" ] + }, { + "iri" : "http://purl.org/neao/steps#PhaseLockingValueAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "phase locking value analysis", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "PLV analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "PhaseLockingValueAnalysis" + }, + "subClasses" : [ "473", "474" ], + "comment" : { + "en" : "A phase analysis that computes the phase locking value (PLV). The PLV quantifies the consistency of the phase difference between two input time series across time (e.g., multiple experimental trials)." + }, + "id" : "385", + "superClasses" : [ "382" ] + }, { + "iri" : "http://purl.org/neao/steps#CrossPowerSpectralDensityAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "cross power spectral density analysis", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "CPSD analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "CrossPowerSpectralDensityAnalysis" + }, + "subClasses" : [ "480", "479", "478", "481" ], + "comment" : { + "en" : "A spectral density analysis that computes the cross power spectral density (CPSD) of two inputs, i.e., the distribution of their power across the different frequency components per unit frequency. The CPSD shows in the frequency domain how the two inputs are correlated in the time domain, and is equivalent to the Fourier transform of the cross-correlation function between the two signals. If the inputs are not correlated, the CPSD will be flat across the frequencies. A peak suggests that the signals are correlated at that frequency. The CPSD is often referred to as cross-spectrum." + }, + "id" : "145", + "superClasses" : [ "146" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeCrossPowerSpectralDensityPeriodogram", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute cross power spectral density (periodogram method)", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "compute cross-periodogram", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute CPSD (periodogram method)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeCrossPowerSpectralDensityPeriodogram" + }, + "comment" : { + "en" : "A cross power spectral density (CPSD) analysis that uses the periodogram method. For the computation, the discrete Fourier transform of each input is obtained and their cross-power spectrum is obtained. A window function can be applied to the inputs before the Fourier transform, to reduce spectral leakage. The final CPSD is obtained by normalizing the cross-power spectrum to the unit frequency using the equivalent noise bandwidth (a factor that depends on the coefficients of the window function and the sampling rate). If no window function is used or a window that does not attenuate the signal is used (e.g., Boxcar or rectangular window) the equivalent noise bandwidth is equal to the frequency resolution." + }, + "id" : "481", + "superClasses" : [ "145" ] + }, { + "iri" : "http://purl.org/neao/steps#KernelSmoothing", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "kernel smoothing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "KernelSmoothing" + }, + "subClasses" : [ "486", "266" ], + "comment" : { + "en" : "A data smoothing that performs a convolution of the input data with a kernel function. This computes a weighted average of the data around the kernel. Several kernel types can be used for the smoothing (e.g., Gaussian, exponential) and the kernel shape is controlled by a width parameter." + }, + "id" : "267", + "superClasses" : [ "95" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeDirectedTransferFunction", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Kaminski1991_203", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute directed transfer function", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute DTF", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeDirectedTransferFunction" + }, + "comment" : { + "en" : "A functional connectivity analysis that computes the directed transfer function (DTF) according to Kaminski & Blinowska (1991). DTF can estimate the direction and frequency content of the brain activity flow. The DTF measure is obtained from the spectral transfer matrix computed from multivariate time series input data. For the DTF computation, the spectral transfer matrix is obtained from a multivariate autoregressive model. The DTF estimate is obtained by using a normalization factor computed by the sum along the rows of the spectral transfer matrix. The DTF can have values in the range from 0 to 1." + }, + "id" : "76", + "superClasses" : [ "77" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeASSETJointProbabilityMatrix", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Torre2016_e1004939", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute ASSET joint probability matrix", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeASSETJointProbabilityMatrix" + }, + "comment" : { + "en" : "ASSET analysis substep that computes the joint probability matrix (JMAT). For every entry in the probability matrix (PMAT), the computation produces the combined probability of a fixed number of neighbors in a rectangular kernel (with fixed length and width as parameters) covering a diagonal structure. A value in the JMAT reflects how likely entries with high probability in the PMAT are to be located in the same diagonal structure." + }, + "id" : "106", + "superClasses" : [ "55" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputePeristimulusTimeHistogramUserSelectedBinSize", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute peristimulus time histogram (user-selected bin size)", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute PSTH (user-selected bin size)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputePeristimulusTimeHistogramUserSelectedBinSize" + }, + "comment" : { + "en" : "A peristimulus time histogram (PSTH) analysis that computes the PSTH using a fixed bin size specified as a parameter." + }, + "id" : "434", + "superClasses" : [ "44" ] + }, { + "iri" : "http://purl.org/neao/steps#GenerateWindowShufflingSurrogate", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Stella2022_ENEURO", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "generate window shuffling surrogate", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "generate bin shuffling within exclusive windows surrogate", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "GenerateWindowShufflingSurrogate" + }, + "comment" : { + "en" : "A spike train surrogate generation step that shuffles the entries of a binned spike train within exclusive maximal displacement windows. The maximal displacement is specified by parameter, and represents the maximum number of bins that a spike can be displaced within the window." + }, + "id" : "2", + "superClasses" : [ "121" ] + }, { + "iri" : "http://purl.org/neao/steps#FieldFieldCouplingAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "field-field coupling analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "FieldFieldCouplingAnalysis" + }, + "comment" : { + "en" : "An analysis step that computes interactions between the neural activity represented by distinct local field potential (LFP) signals (e.g., LFP obtained from different electrodes, or distinct LFP frequency bands)." + }, + "id" : "491", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#ConfidenceIntervalResamplingAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "confidence interval with resampling analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ConfidenceIntervalResamplingAnalysis" + }, + "subClasses" : [ "194", "118" ], + "comment" : { + "en" : "A confidence interval statistical analysis that computes the confidence interval using techniques to generate multiple samples from the (observed) data input(s)." + }, + "id" : "119", + "superClasses" : [ "188" ] + }, { + "iri" : "http://purl.org/neao/steps#GenerateStationaryInverseGaussianProcess", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "generate stationary inverse Gaussian process", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "GenerateStationaryInverseGaussianProcess" + }, + "comment" : { + "en" : "A random spike times generation that uses a inverse Gaussian probability distribution to produce spike trains with a constant firing rate." + }, + "id" : "33", + "superClasses" : [ "8" ] + }, { + "iri" : "http://purl.org/neao/steps#GenerateTrialShiftingSurrogate", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Stella2022_ENEURO", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "generate trial shifting surrogate", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "GenerateTrialShiftingSurrogate" + }, + "comment" : { + "en" : "A spike train surrogate generation step that shifts the entire spike train (containing the data of a single experimental trial) by an amount randomly chosen from a uniform distribution. The amount of displacement is specified as a parameter (dither time), and occurs in a window (-dither time, dither time). The input is a collection of spike trains of the same neuron, containing the spiking activity during different experimental trials. The amount of shift is independently chosen across trials and neurons. This surrogate preserves the ISI distribution and temporal correlations within the single-trial spike train." + }, + "id" : "1", + "superClasses" : [ "121" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeSpikeTrainCrossCorrelationHistogram", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute spike train cross-correlation histogram", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "compute cross-correlogram", + "type" : "label" + }, { + "identifier" : "altLabel", + "language" : "en", + "value" : "compute correlogram", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute CCH", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeSpikeTrainCrossCorrelationHistogram" + }, + "subClasses" : [ "65" ], + "comment" : { + "en" : "A cross-correlation analysis that computes the cross-correlation histogram (CCH) for a pair of input spike trains. The CCH shows how often spikes in the reference spike train occur before or after spikes in the reference spike train, at distinct lag intervals. For the computation, the spike trains are aligned in time. The histogram is obtained by sliding a time window that is discretized into smaller time intervals (bins) centered on a spike of the first (reference) input spike train (corresponding to the lag zero). The spike count of the second (target) spike train input is then obtained in each bin. Therefore, this binning process measures the number of spikes in the target spike train occurring at various time lags relative to the spikes in the reference spike train. The histogram window is slidden over each spike in the reference spike train, and the spike count in each bin is accumulated to produce the CCH output. The width of the bin interval is controlled by a parameter." + }, + "id" : "66", + "superClasses" : [ "143" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplyLocalLinearRegressionDetrending", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Bokil2010_146", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply local linear regression detrending", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplyLocalLinearRegressionDetrending" + }, + "comment" : { + "en" : "A detrending that removes a running line fit using local linear regression. Local linear regression estimates a function by fitting a low-order polynomial to data within a sliding window (local neighborhood) across the input data." + }, + "id" : "156", + "superClasses" : [ "100" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeInstantaneousFiringRateKernelDensityEstimation", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute instantaneous firing rate (kernel density estimation method)", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "compute instantaneous firing rate (kernel smoothing method)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeInstantaneousFiringRateKernelDensityEstimation" + }, + "comment" : { + "en" : "An instantaneous firing rate analysis that computes the instantaneous firing rate by convolution of spike times with a kernel function. The output of the computation is a weighted average of the spikes around the kernel." + }, + "id" : "501", + "superClasses" : [ "163" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplyRectification", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply rectification", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplyRectification" + }, + "comment" : { + "en" : "A data transformation that computes the absolute value of the input data (rectification)." + }, + "id" : "89", + "superClasses" : [ "5" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplyUpsampling", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply upsampling", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "apply upscaling", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplyUpsampling" + }, + "comment" : { + "en" : "A resampling that increases the number of samples in the data (i.e., increases the sampling frequency). This is often accomplished by adding new (zero-valued) samples between existing ones followed by applying a lowpass filter to replace the zeros and smooth out the discontinuities." + }, + "id" : "160", + "superClasses" : [ "161" ] + }, { + "iri" : "http://purl.org/neao/steps#ExecuteUnitaryEventAnalysisMonteCarlo", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Gruen2009_1126", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "execute Unitary Event analysis (Monte Carlo method)", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "execute UE analysis (Monte Carlo method)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ExecuteUnitaryEventAnalysisMonteCarlo" + }, + "comment" : { + "en" : "A unitary event (UE) analysis that uses a Monte Carlo approach based on spike train surrogates to determine the significance of the empirical coincidences in binned spike train data, according to Grün (2009). The Monte Carlo method does not rely on the assumption that the input spike data follows Poisson statistics. For the assessment of significance, the distribution of expected coincidences is determined by surrogates (spike train randomization) in each trial, and then summed over trials. The number of surrogates is determined by a parameter." + }, + "id" : "306", + "superClasses" : [ "215" ] + }, { + "iri" : "http://purl.org/neao/steps#SpikeTrainSynchronyAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "spike train synchrony analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "SpikeTrainSynchronyAnalysis" + }, + "subClasses" : [ "207", "213", "218", "222" ], + "comment" : { + "en" : "An analysis step to assess synchronization in two or more spike train inputs that typically represent the activity of different neurons. Spike train synchronization refers to the temporal coordination of action potentials (spikes) between neurons, and describes the degree to which their spikes tend to occur at the same time." + }, + "id" : "208", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#SpikeWaveformAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "spike waveform analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "SpikeWaveformAnalysis" + }, + "subClasses" : [ "226", "164", "233", "190" ], + "comment" : { + "en" : "An analysis step that is used to compute measures to describe or make inferences from spike waveform input data. A spike waveform refers to the shape of an electrical signal produced by a neuron when it fires an action potential." + }, + "id" : "165", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputePhaseSlopeIndex", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Nolte2008_234101", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute phase slope index", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute PSI", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputePhaseSlopeIndex" + }, + "comment" : { + "en" : "A functional connectivity analysis that computes the phase slope index (PSI) according to Nolte et al. (2008). The PSI is based on the slope of the phase of the cross-spectral density between two time series inputs, considering how the phase difference between two signals changes as you move from one frequency bin to the next. It is computed from the complex-valued coherency using a bandwidth specified as parameter. For the computation, the change in phase difference between neighboring frequency bins is obtained (considering the specified bandwidth) and weighted. The PSI value deviates from zero when the phase difference changes consistently across frequencies and there is substantial coherence. The sign of the PSI indicates the temporal order of the two signals (i.e., which signal is leading the other one)." + }, + "id" : "389", + "superClasses" : [ "382" ] + }, { + "iri" : "http://purl.org/neao/steps#CrossCorrelationAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "cross-correlation analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "CrossCorrelationAnalysis" + }, + "subClasses" : [ "117", "66" ], + "comment" : { + "en" : "An analysis step used to compute a measure of cross-correlation, i.e., the correlation of two inputs computed for distinct time lags of the first to the second. The computation produces the cross-correlation value for every lag considered." + }, + "id" : "143", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeCrossSpectrogramShortTimeFourierTransform", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute cross-spectrogram (short-time Fourier transform method)", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute cross-spectrogram (STFT method)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeCrossSpectrogramShortTimeFourierTransform" + }, + "comment" : { + "en" : "A spectrogram analysis that computes a cross-spectrogram using the short-time Fourier transform (STFT). The cross-spectrogram is the time-resolved description of the power of a pair of distinct inputs across the different frequency components. This can be used to investigate how common activity between the two inputs is distributed across the frequency components, and how it varies over time." + }, + "id" : "319", + "superClasses" : [ "276" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeCoherenceRosenberg", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Rosenberg1989_1", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute coherence (Rosenberg method)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeCoherenceRosenberg" + }, + "comment" : { + "en" : "A coherence analysis that computes the coherence from two inputs according to Rosenberg et al. (1989). The method is described for point processes (i.e., spike trains). The computation produces the magnitude squared coherence." + }, + "id" : "416", + "superClasses" : [ "417" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplyPadding", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply padding", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplyPadding" + }, + "comment" : { + "en" : "A data transformation that adds extra data (often zeros or other predefined values) to the beginning, end, or both sides of the input data." + }, + "id" : "455", + "superClasses" : [ "5" ] + }, { + "iri" : "http://purl.org/neao/steps#GenerateCompoundPoissonProcess", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "generate compound Poisson process", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "generate CPP", + "type" : "label" + } ], + "bibliographicCitation" : [ { + "identifier" : "bibliographicCitation", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Staude2010_327", + "type" : "iri" + } ] + }, + "label" : { + "IRI-based" : "GenerateCompoundPoissonProcess" + }, + "comment" : { + "en" : "A correlated spike times generation that produces spike trains using a compound Poisson process (CPP) according to Staude et al. (2010). The CPP is a model for parallel and correlated processes with Poisson spiking statistics at predefined firing rates." + }, + "id" : "471", + "superClasses" : [ "102" ] + }, { + "iri" : "http://purl.org/neao/data#ComplexityDistribution", + "baseIri" : "http://purl.org/neao/data", + "instances" : 0, + "label" : { + "IRI-based" : "ComplexityDistribution" + }, + "attributes" : [ "external" ], + "id" : "513" + }, { + "iri" : "http://purl.org/neao/steps#ComputeSpikeFieldCoherenceMultitaper", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute spike-field coherence (multitaper method)", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute SFC (multitaper method)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeSpikeFieldCoherenceMultitaper" + }, + "comment" : { + "en" : "A spike-field coherence analysis that uses a multitaper approach to compute the coherence between the spike train and the LFP." + }, + "id" : "520", + "superClasses" : [ "521" ] + }, { + "iri" : "http://purl.org/neao/steps#Detrending", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "detrending", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "Detrending" + }, + "subClasses" : [ "152", "156" ], + "comment" : { + "en" : "A data transformation that removes a trend (i.e., a change in the mean over time) from an input time series." + }, + "id" : "100", + "superClasses" : [ "5" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeContinuousWaveletTransform", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute continuous wavelet transform", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute CWT", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeContinuousWaveletTransform" + }, + "comment" : { + "en" : "A wavelet transform analysis that convolves the input time series with scaled and translated versions of the mother wavelet. The scale parameter can be non-dyadic (i.e., can take values that are not powers of 2). The mother wavelet used is passed as a parameter, and several types can be used (e.g., Morlet, Mexican hat, Hermitian, Meyer, Poisson). The continuous wavelet transform (CWT) is ideal for analyzing non-stationary signals, with transient behavior, rapidly changing frequencies or slowly varying changes. It is comparable to the short-time Fourier transform (STFT)." + }, + "id" : "141", + "superClasses" : [ "80" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplyStimulationArtifactRemoval", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply stimulation artifact removal", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplyStimulationArtifactRemoval" + }, + "comment" : { + "en" : "An artifact removal that identifies and removes artifacts originating from presenting a stimulus during the recording (e.g., electrical stimulation)." + }, + "id" : "446", + "superClasses" : [ "36" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeStandardErrorMean", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute standard error of the mean", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute SEM", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeStandardErrorMean" + }, + "comment" : { + "en" : "A dispersion statistical analysis that computes the standard error of the mean (SEM). The SEM is the standard deviation of the sampling distribution of the sample mean. It provides an estimate of how much the sample mean is expected to fluctuate around the true population mean. Smaller SEM values indicates that the sample mean is a more accurate estimate of the population mean. The SEM decreases as the sample size increases, as larger samples provide a more reliable estimate of the population mean." + }, + "id" : "237", + "superClasses" : [ "47" ] + }, { + "iri" : "http://purl.org/neao/steps#Resampling", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "resampling", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "Resampling" + }, + "subClasses" : [ "160", "167" ], + "comment" : { + "en" : "A data transformation that changes the number of samples in the input data." + }, + "id" : "161", + "superClasses" : [ "5" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeCovariance", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute covariance", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeCovariance" + }, + "subClasses" : [ "171" ], + "comment" : { + "en" : "A covariance analysis that computes the values of covariance in pairwise input data." + }, + "id" : "85", + "superClasses" : [ "86" ] + }, { + "iri" : "http://purl.org/neao/steps#FunctionalConnectivityAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "functional connectivity analysis", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "FCA", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "FunctionalConnectivityAnalysis" + }, + "subClasses" : [ "175", "178", "134", "139", "76" ], + "comment" : { + "en" : "An analysis step that computes measures of functional connectivity. 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It does not imply direct physical connections." + }, + "id" : "77", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#DataTransformation", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "data transformation", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "DataTransformation" + }, + "subClasses" : [ "83", "89", "95", "100", "51", "109", "114", "57", "62", "70", "4", "15", "21", "26", "31", "36", "41", "161", "455", "460", "466", "414", "420" ], + "comment" : { + "en" : "An analysis step that takes one or more inputs and modifies the contents, such that it fits a particular purpose. The data transformation steps are frequently used during pre-processing the input data for the analyses. Usually, a data transformation will not change the main representation or quality of the inputs. For example, a digital filtering step will remove certain frequency components from a time series. However, the output will resemble the original input with respect to shape or physical units. In addition, the inputs can also be converted to other formats or representations that are needed for a particular analysis step. For example, spike trains can be discretized into small intervals (binning) or the dimensionality of the input can be reduced using principal component analysis. The data transformation is in contrast to steps that perform computations that take the input and generate a derived measure with new information. For example, when computing the mean firing rate from a spike train, a single scalar value is obtained from the spike count in the input data." + }, + "id" : "5", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplyDemixedPrincipalComponentAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Kobak2016_e10989", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply demixed principal component analysis", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "apply dPCA", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplyDemixedPrincipalComponentAnalysis" + }, + "comment" : { + "en" : "A principal component analysis (PCA) that uses a modified version of the standard PCA for neural activity data analysis. Demixed PCA (dPCA) not only obtains a low-dimensional representation of the input data, but it also demixes the dependencies of the population activity on the task parameters. Therefore, dPCA can show the dependence of the neural representation on parameters such as stimuli, subject decisions, or rewards." + }, + "id" : "562", + "superClasses" : [ "327" ] + }, { + "iri" : "http://purl.org/neao/steps#PeristimulusTimeHistogramAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "peristimulus time histogram analysis", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "PSTH analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "PeristimulusTimeHistogramAnalysis" + }, + "subClasses" : [ "425", "52", "434", "43" ], + "comment" : { + "en" : "A spike train time histogram analysis that computes the peristimulus time histogram (PSTH). PSTH is the time histogram of two or more spike trains containing repeated recordings of a single neuron around the time when an event of interest occurred. The event of interest can occur at any time point during the duration of the source spike trains. The distribution of the histogram corresponds to the distribution of the activity of the neuron with respect to the event across the repeated recordings. The event of interest can be an externally presented stimulus or a spontaneous behavioral event. If the histogram represents the neuronal activity after the stimulus presentation or event occurrence, this can be referred as post-stimulus time histogram. Conversely, if the histogram shows the activity of the neuron before the stimulus presentation or event, this can be referred as prestimulus time histogram. Finally, if the histogram considers a behavioral event (or an event that is not an externally presented stimulus), the histogram can be referred to as perievent time histogram (PETH)." + }, + "id" : "44", + "superClasses" : [ "154" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeMaximizedImaginaryCoherency", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Ewald2012_476", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute maximized imaginary coherency", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute MIC", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeMaximizedImaginaryCoherency" + }, + "comment" : { + "en" : "A coherency analysis that computes the maximized imaginary coherency (MIC) according to Ewald et al. (2012). The computation uses an eigenvalue-based optimization to find weight vectors that maximize the imaginary part of coherency computed between virtual channels derived from the input data. The weights are optimized for each frequency component. After the weights are obtained, the final MIC measure is obtained for each frequency." + }, + "id" : "443", + "superClasses" : [ "169" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeCV", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute coefficient of variation", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute CV", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeCV" + }, + "comment" : { + "en" : "A dispersion statistical analysis that computes the coefficient of variation (CV). The CV is the ratio of the standard deviation to the mean. It is useful to compare different inputs, as the measure is unitless and indicates the relative variability in the input data." + }, + "id" : "238", + "superClasses" : [ "47" ] + }, { + "iri" : "http://purl.org/neao/steps#InfiniteImpulseResponseFiltering", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "infinite impulse response filtering", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "IIR filtering", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "InfiniteImpulseResponseFiltering" + }, + "subClasses" : [ "393", "398", "403" ], + "comment" : { + "en" : "A digital filtering that uses a filter whose impulse response (i.e., the response of the filter to a brief input impulse) persists infinitely. Therefore, the output of the filter can depend on an infinite number of past samples. The infinite impulse response (IIR) filters can become unstable and distort the phase of the signal, but have a lower computational cost." + }, + "id" : "283", + "superClasses" : [ "57" ] + }, { + "iri" : "http://purl.org/neao/steps#PhaseAmplitudeCouplingAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "phase-amplitude coupling analysis", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "PAC analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "PhaseAmplitudeCouplingAnalysis" + }, + "subClasses" : [ "268", "410" ], + "comment" : { + "en" : "A phase analysis that computes measures describing how the phase of a low-frequency oscillation modulates the amplitude of a high-frequency oscillation. 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The analysis can return the mean phase vector (i.e., angle and length), the vector angle, or the vector length." + }, + "id" : "383", + "superClasses" : [ "382" ] + }, { + "iri" : "http://purl.org/neao/steps#FrequencyDomainAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "frequency domain analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "FrequencyDomainAnalysis" + }, + "comment" : { + "en" : "An analysis step that analyzes the input(s) with respect to its(their) frequency content." + }, + "id" : "533", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#InterspikeIntervalAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "interspike interval analysis", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "ISI analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "InterspikeIntervalAnalysis" + }, + "subClasses" : [ "129", "366", "371" ], + "comment" : { + "en" : "An analysis step that computes or analyzes the interval between successive spikes in a spike train (interspike interval; ISI)." + }, + "id" : "360", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplyMedianRescaling", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply median rescaling", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "apply robust scaling", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplyMedianRescaling" + }, + "comment" : { + "en" : "A data normalization that uses the median and interquartile range (IQR) to rescale the values of the input data. This method is less sensitive to outliers (compared to the z-score transform), and therefore is known as robust scaling." + }, + "id" : "606", + "superClasses" : [ "109" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeCVInterspikeIntervals", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute coefficient of variation of the interspike intervals", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute CV ISIs", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeCVInterspikeIntervals" + }, + "comment" : { + "en" : "An interspike interval variability analysis that computes the coefficient of variation (CV) of the interspike intervals (ISIs). The CV is computed as the ratio of the standard deviation of the ISIs to their mean." + }, + "id" : "598", + "superClasses" : [ "129" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeSpikeTrainPearsonCorrelationCoefficient", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute spike train Pearson correlation coefficient", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeSpikeTrainPearsonCorrelationCoefficient" + }, + "comment" : { + "en" : "A spike train correlation analysis that computes the Pearson correlation coefficient between two spike train inputs. The Pearson correlation coefficient is a real value that quantifies the linear relationship between the two spike trains. It has range [-1, 1], where 1 indicates a perfect positive linear relationship, -1 indicates a perfect negative linear relationship, and 0 indicates no linear relationship. For the computation, the input spike trains are discretized into time intervals (bins), and the spike count is obtained in each bin. The Pearson correlation coefficient is obtained by normalizing the covariance between the binned spike trains: the covariance is divided by the product of the standard deviation of each." + }, + "id" : "286", + "superClasses" : [ "244" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeJointPeristimulusTimeHistogram", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Aertsen1987_1", + "type" : "iri" + }, { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Brown2004_456", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute joint peristimulus time histogram", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute JPSTH", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeJointPeristimulusTimeHistogram" + }, + "comment" : { + "en" : "A spike train synchrony analysis that computes the joint peristimulus time histogram (JPSTH) from trial-by-trial spike train inputs obtained from two different neurons, after the repeated presentation of a stimulus. The JPSTH provides a representation of the timing relationship between the firing of the two neurons in response to the stimulus. It combines the peristimulus time histograms (PSTHs) of each neuron to illustrate how their firing rates co-vary over time relative to the stimulus event. This helps in understanding the temporal correlation between the neurons.\n\nThe computation can produce three outputs: \n\n* the JPSTH matrix (i.e., a matrix whose bins contain the counts of coincidences in the firing of the two neurons);\n* the peristimulus coincidence histogram (i.e., a histogram obtained from a cross-section along the main diagonal of the JPSTH matrix);\n* the cross-correlation histogram computed by summing the bins along the main and each paradiagonal of the JPSTH matrix (after normalizing by the bin length, as the paradiagonals in the JPSTH matrix are of different lengths)." + }, + "id" : "218", + "superClasses" : [ "208" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeMeanFiringRate", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute mean firing rate", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute MFR", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeMeanFiringRate" + }, + "comment" : { + "en" : "A firing rate analysis that computes the mean firing rate, defined as the number of spikes in a time interval divided by the duration of the interval. The mean firing rate is the temporal average of the neuronal activity over that interval." + }, + "id" : "158", + "superClasses" : [ "150" ] + }, { + "iri" : "http://purl.org/neao/steps#SpikeTrainSurrogateGeneration", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "spike train surrogate generation", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "SpikeTrainSurrogateGeneration" + }, + "subClasses" : [ "184", "379", "2", "341", "12", "74", "13", "1", "19", "93" ], + "comment" : { + "en" : "A data generation that produces one or more spike train surrogates. A spike train surrogate is a new spike train derived from an input spike train (usually experimentally recorded). This is done using methods that alter the original spike times while trying to maintain specific statistical features of the original spike train (e.g., firing rate, interspike interval distribution). This is used to destroy fine temporal correlations in the spiking activity." + }, + "id" : "121", + "superClasses" : [ "122" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputedEvokedPotential", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute evoked potential", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute EP", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputedEvokedPotential" + }, + "comment" : { + "en" : "An analysis step that computes the evoked potential (EP). The EP is the neural activity (e.g., local field potential or electroencephalogram voltages) around a presented stimulus (e.g., auditory, visual, electrical). Usually, the stimulus is presented repeatedly across multiple trials, obtaining multiple evoked potential waveforms that can be averaged to cancel the noise. It is an event-related potential (ERP) obtained from presenting a stimulus rather than spontaneous behavioral events." + }, + "id" : "621", + "superClasses" : [ "622" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeRectifiedAreaUnderCurve", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute rectified area under the curve", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute RAUC", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeRectifiedAreaUnderCurve" + }, + "comment" : { + "en" : "An analysis step that computes the rectified area under the curve (RAUC). For the computation, the input signal is rectified (i.e., the absolute value is obtained) and the area under the curve is computed by integration using the composite trapezoidal rule." + }, + "id" : "259", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#GenerateUniformSpikeDitheringSurrogate", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Louis2010_359", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "generate uniform spike dithering surrogate", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "generate UD surrogate", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "GenerateUniformSpikeDitheringSurrogate" + }, + "comment" : { + "en" : "A spike train surrogate generation step that displaces each spike time in the input spike train according to a uniform distribution centered on the spike. The displacement occurs in a time window around the spike defined by a parameter (dither time)." + }, + "id" : "13", + "superClasses" : [ "121" ] + }, { + "iri" : "http://purl.org/neao/steps#SpectrogramAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "spectrogram analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "SpectrogramAnalysis" + }, + "subClasses" : [ "319", "323", "275", "281" ], + "comment" : { + "en" : "A time-frequency analysis that shows the power (or power density) of different frequency components of the input(s) as they change over time. This can be obtained for a single input (spectrogram) or for two distinct inputs (cross-spectrogram)." + }, + "id" : "276", + "superClasses" : [ "131" ] + }, { + "iri" : "http://purl.org/neao/steps#ExecuteASSETAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Torre2016_e1004939", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "execute ASSET analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ExecuteASSETAnalysis" + }, + "comment" : { + "en" : "A neuronal activity pattern detection analysis that uses the Analysis of Sequences of Synchronous EvenTs (ASSET) method defined in Torre et al. (2016). ASSET is an automatized test to identify the sequential activations of groups of neurons that repeat in time. The identification of the repeated sequences is possible by computing the intersection matrix. The input spike data is discretized into smaller intervals (bins), and the overlap of neuronal activity at each bin pair is obtained as a matrix. When a sequence of activations exists and repeats in time, a characteristic diagonal structure appears in the matrix.\n\nThe ASSET analysis provides a robust statistical test to automatically identify the diagonal structures and to provide the neurons and their activation pattern in each repeated sequence. Overall, the analysis is composed by 6 substeps:\n\n1. Compute the intersection matrix (IMAT) from a set of input spike trains, using a specified bin size to discretize the data.\n2. Obtain the probability matrix (PMAT).\n3. Obtain the joint probability matrix (JMAT).\n4. Extract significant entries in both PMAT and JMAT using specified thresholds, obtaining the mask matrix (MMAT).\n5. Obtain the cluster matrix (CMAT) by using DBSCAN to cluster the significant entries in the MMAT to find each diagonal structure. Parameters for DBSCAN control the clustering result. A modified distance metric is used.\n6. From the identified clusters (each a single diagonal structure in the IMAT), obtain the neuronal composition and the order of activation, producing the final neuronal activity patterns as output." + }, + "id" : "228", + "superClasses" : [ "216" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeSpikeWaveformSNR", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Hatsopoulos2007_5105", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute spike waveform signal-to-noise ratio", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute spike waveform SNR", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeSpikeWaveformSNR" + }, + "comment" : { + "en" : "A spike waveform analysis that computes the signal-to-noise ratio (SNR) for a set of input spike waveforms according to Hatsopoulos (2007). The SNR is defined as the difference in mean peak-to-trough voltage divided by twice the mean standard deviation (SD).The mean SD is obtained by averaging the SDs computed for each time point in the spike waveform." + }, + "id" : "190", + "superClasses" : [ "165" ] + }, { + "iri" : "http://purl.org/neao/steps#SpikeTrainCorrelationAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "spike train correlation analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "SpikeTrainCorrelationAnalysis" + }, + "subClasses" : [ "286", "292", "243" ], + "comment" : { + "en" : "An analysis step that computes measures estimating the correlation between spike train inputs. The correlation value is a normalized measure of covariation in the input spike train data, and reflects the strength and direction of the association: positive values mean that the inputs vary in the same direction, and negative values mean that the inputs vary in opposite directions (e.g., if the activity in one spike train increases, it decreases in the other)." + }, + "id" : "244", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeFrequencyDomainConditionalGrangerCausality", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Dhamala2008_354", + "type" : "iri" + }, { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Ding2006_0608035", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute frequency domain conditional Granger causality", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeFrequencyDomainConditionalGrangerCausality" + }, + "comment" : { + "en" : "A conditional Granger causality (GC) analysis that computes the GC measures in the frequency domain." + }, + "id" : "200", + "superClasses" : [ "201" ] + }, { + "iri" : "http://purl.org/neao/steps#CorrelationAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "correlation analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "CorrelationAnalysis" + }, + "subClasses" : [ "300" ], + "comment" : { + "en" : "An analysis step that computes a measure of correlation between two inputs. Correlation is a measure that quantifies the strength to which two variables change together. It is a scaled version of the covariance, and the values are restricted to the -1 to +1 interval. Between time series, it is computed in the time domain." + }, + "id" : "301", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputePhaseDifference", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute phase difference", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputePhaseDifference" + }, + "comment" : { + "en" : "A phase analysis that computes the difference between two input phases." + }, + "id" : "388", + "superClasses" : [ "382" ] + }, { + "iri" : "http://purl.org/neao/steps#GenerateSpikeTrainDitheringSurrogate", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Louis2010_359", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "generate spike train dithering surrogate", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "GenerateSpikeTrainDitheringSurrogate" + }, + "comment" : { + "en" : "A spike train surrogate generation step that displaces the whole input spike train by a random amount of time (independent for each surrogate generated). The amount of displacement is specified as a parameter (dither time), and occurs in a window (-dither time, dither time). This surrogate maintains the ISIs and the temporal correlations within the spike train." + }, + "id" : "93", + "superClasses" : [ "121" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeSpikeFieldCoherenceFries", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Fries2001_1560", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute spike-field coherence (Fries method)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeSpikeFieldCoherenceFries" + }, + "comment" : { + "en" : "A spike-field coherence analysis that uses the method described in Fries et al. (2001) to compute the coherence between the spike train and the LFP. For the computation, first a spike-triggered average (STA) is obtained between the spike train and the LFP time series. Then, the power spectrum is obtained for each of the LFP segments used for the computation of the STA. These spectra are averaged to obtain the spike-triggered power spectrum. The SFC is then computed as the ratio of the power spectrum of the STA over the spike-triggered power spectrum." + }, + "id" : "549", + "superClasses" : [ "521" ] + }, { + "iri" : "http://purl.org/neao/steps#UnitaryEventAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Riehle1997_1950", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "Unitary Event analysis", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "UE analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "UnitaryEventAnalysis" + }, + "subClasses" : [ "306", "252" ], + "comment" : { + "en" : "A neuronal activity pattern detection analysis that uses the Unitary Event (UE) method. UE is a statistical technique focused on identifying synchronous activity among neurons, known as unitary events (UEs), which occur more frequently than an expectation based solely on firing rates. The input can contain spike trains from one or more neurons and one or more trials. For the computation, the input spike train data is discretized into small time intervals (bins), and coincidences across the different spike trains are computed. The significance of the number of observed (empirical) coincidences is determined by comparing to an expected number given the firing rates of the neurons. To account for possible non-stationarities in the firing rates, the method uses a sliding temporal window over the data, whose width is specified as parameter. Therefore, a measure of significant spike synchrony (joint surprise) is obtained for each window. The statistical evaluation can be done using either analytical methods or Monte-Carlo testing with surrogate spike data. The output presents the significant coincidences (UE patterns) and the participant neurons." + }, + "id" : "215", + "superClasses" : [ "216" ] + }, { + "iri" : "http://purl.org/neao/steps#PhaseLagIndexAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "phase lag index analysis", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "PLI analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "PhaseLagIndexAnalysis" + }, + "subClasses" : [ "256", "262", "646", "472", "647" ], + "comment" : { + "en" : "A phase analysis that computes the phase lag index (PLI). The PLI measures the asymmetry of the distribution of the phase differences between two input time series, i.e., if there is an imbalance in the likelihood of the first time series leading or lagging the second time series. It is designed to be invariant to common sources, such as volume conduction and/or active reference electrodes." + }, + "id" : "257", + "superClasses" : [ "382" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeMorletWaveletTransform", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute Morlet wavelet transform", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeMorletWaveletTransform" + }, + "subClasses" : [ "508", "507" ], + "comment" : { + "en" : "A wavelet transform analysis based on the complex-valued Morlet wavelet. The transform can be performed either in the time domain (by convolution) or in the frequency domain (by multiplication)." + }, + "id" : "79", + "superClasses" : [ "80" ] + }, { + "iri" : "http://purl.org/neao/steps#GenerateSingleInteractionProcess", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Kuhn2003_67", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "generate single interaction process", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "generate SIP", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "GenerateSingleInteractionProcess" + }, + "comment" : { + "en" : "A correlated spike times generation that produces a multidimensional Poisson single interaction process (SIP) plus independent Poisson processes, according to Kuhn et al. (2003). The Poisson SIP consists of Poisson time series that are independent except for events that are simultaneous in all of them." + }, + "id" : "470", + "superClasses" : [ "102" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeSPIKESynchronization", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Kreuz2015_3432", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute SPIKE synchronization", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeSPIKESynchronization" + }, + "comment" : { + "en" : "A time-scale independent spike train distance analysis that computes the SPIKE synchronization distance, described in Kreuz et al. (2015). The distance detects coincidences in the spiking activity and can quantify the degree of synchrony in the input spike trains. The metric quantifies the overall fraction of coincidences. It is zero-valued if and only if the input spike trains do not contain any coincidences. It has a value of 1 if and only if each spike in every input spike train has one matching spike in all the other spike trains." + }, + "id" : "431", + "superClasses" : [ "288" ] + }, { + "iri" : "http://purl.org/neao/steps#GenerateMorletWavelet", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "generate Morlet wavelet", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "GenerateMorletWavelet" + }, + "comment" : { + "en" : "A data generation that constructs a Morlet wavelet considering the selected parameters (i.e., sampling frequency, fundamental frequency, and number of cycles per frequency). The Morlet wavelet is composed by a complex exponential multiplied by a Gaussian window. The output data contains the discrete time points and the corresponding wavelet values." + }, + "id" : "124", + "superClasses" : [ "122" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplyFiniteImpulseResponseFilterKaiserWindow", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply finite impulse response filter with Kaiser window", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "apply FIR filter with Kaiser window", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplyFiniteImpulseResponseFilterKaiserWindow" + }, + "comment" : { + "en" : "A finite impulse response (FIR) filtering that uses a FIR filter whose impulse response is controlled by applying a Kaiser window function." + }, + "id" : "452", + "superClasses" : [ "278" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeMorletWaveletTransformLeVanQuyen", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#LeVanQuyen2001_83", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute Morlet wavelet transform (Le Van Quyen method)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeMorletWaveletTransformLeVanQuyen" + }, + "comment" : { + "en" : "A wavelet transform analysis using the Morlet wavelet where the parametrization of the mother wavelet is done according to Le Van Quyen et al. (2001). The size of the mother wavelet is determined in number of cycles to control the frequency and temporal resolutions (approximate number of oscillation cycles within a wavelet)." + }, + "id" : "507", + "superClasses" : [ "79" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeShortTimeFourierTransform", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute short-time Fourier transform", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute STFT", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeShortTimeFourierTransform" + }, + "comment" : { + "en" : "A time-frequency analysis that computes the short-time Fourier transform (STFT) of the input time series. The analysis divides the input time-domain signal into short segments with equal time and computes the Fourier transform for each segment. The output is a sequence of coefficients of complex sinusoids, each representing a frequency component in the input signal at a distinct time segment. Therefore, this provides the the time-localized frequency and phase information of the input. The segments can be windowed using a window function." + }, + "id" : "316", + "superClasses" : [ "131" ] + }, { + "iri" : "http://purl.org/neao/steps#DataNormalization", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "data normalization", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "DataNormalization" + }, + "subClasses" : [ "663", "664", "606" ], + "comment" : { + "en" : "A data transformation that adjusts the ranges and distributions of the values in the input data. This can be used to transform data measured in distinct (i.e. not directly comparable) scales to a common (i.e. comparable) scale." + }, + "id" : "109", + "superClasses" : [ "5" ] + }, { + "iri" : "http://purl.org/neao/steps#MultivariateAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "multivariate analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "MultivariateAnalysis" + }, + "comment" : { + "en" : "An analysis step that has three or more distinct inputs considered for the computation of the output (e.g., the time series with the local field potential signals recorded from three or more electrodes, used to compute the partial directed coherence)." + }, + "id" : "644", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#GenerateUniformSpikeDitheringSurrogateWithDeadTime", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Stella2022_ENEURO", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "generate uniform spike dithering surrogate with dead time", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "generate UDD surrogate", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "GenerateUniformSpikeDitheringSurrogateWithDeadTime" + }, + "comment" : { + "en" : "A spike train surrogate generation step that displaces each spike time in the input spike train according to a uniform distribution centered on the spike. The displacement occurs in a time window around the spike defined by a parameter (dither time) that is constrained to the intervals between adjacent spikes to avoid two spikes closer than a dead time (specified by parameter). This mimics the refractory period behavior of neurons, where the neuron cannot fire additional spikes for a short interval after one spike." + }, + "id" : "19", + "superClasses" : [ "121" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeEventRelatedPotential", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute event-related potential", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute ERP", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeEventRelatedPotential" + }, + "subClasses" : [ "621" ], + "comment" : { + "en" : "An analysis step that computes the event-related potential (ERP). The ERP is the neural activity (e.g., local field potential or electroencephalogram voltages) around a presented stimulus or spontaneous behavioral event. Usually, the event is presented/occurs repeatedly across multiple trials, obtaining multiple event-related potential waveforms that can be averaged to cancel the noise." + }, + "id" : "622", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#CurrentSourceDensityAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "current source density analysis", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "source imaging analysis", + "type" : "label" + }, { + "identifier" : "altLabel", + "language" : "en", + "value" : "source localization analysis", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "CSD analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "CurrentSourceDensityAnalysis" + }, + "subClasses" : [ "249", "530", "245" ], + "comment" : { + "en" : "An analysis step used to analyze extracellular electrical potentials (e.g., local field potentials or evoked potentials) recorded from multiple locations, enabling the estimation of the current sources responsible for generating these potentials. The methods can be applied to data recorded from different electrode configurations: laminar probe-like electrodes (1D methods), microelectrode array-like electrodes (2D methods) or electrodes configurations recording from a volume (e.g., multiple laminar probes or array electrodes with shanks with multiple depths; 3D methods). The output of the current source analysis provides the spatial map showing where currents are entering (sources) and leaving (sinks) the neural tissue. For each point in the map, a quantitative value indicates the magnitude of the current density at that point." + }, + "id" : "246", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#PrincipalComponentAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "principal component analysis", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "PCA", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "PrincipalComponentAnalysis" + }, + "subClasses" : [ "665", "329", "562" ], + "comment" : { + "en" : "A dimensionality reduction that reduces the dimensionality of the input data represented as a matrix with numerous rows and columns. It transforms the data into a set of principal components (PCs) that capture the maximum variance in the input. Each PC is a linear combination of the original variables and serves as a new axis in a lower-dimensional space. The PCs are orthogonal to each other, meaning they capture independent aspects of the input data's variability." + }, + "id" : "327", + "superClasses" : [ "51" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeCV2", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Holt1996_1806", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute CV2", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeCV2" + }, + "comment" : { + "en" : "An interspike interval variability analysis that computes the CV2, a measure of the intrinsic variability of a spike train that considers adjacent interspike intervals. The CV2 is more robust against fluctuations in the firing rate than the usual approach of taking the coefficient of variation of the interspike intervals of the spike train." + }, + "id" : "602", + "superClasses" : [ "129" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplyMinMaxNormalization", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply min-max normalization", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "apply rescaling", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplyMinMaxNormalization" + }, + "comment" : { + "en" : "A data normalization that adjusts the range and distribution of values in the data input such that they fall within a fixed range, based on the minimum and maximum values in the input data. In the typical case, the values are normalized to the [0, 1] interval." + }, + "id" : "664", + "superClasses" : [ "109" ] + }, { + "iri" : "http://purl.org/neao/steps#GenerateSpikeTimeRandomizationSurrogate", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Louis2010_359", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "generate spike time randomization surrogate", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "GenerateSpikeTimeRandomizationSurrogate" + }, + "comment" : { + "en" : "A spike train surrogate generation step that keeps the spike count of the input spike train, but the spike times in the surrogate spike train output are randomly chosen within the duration interval of the input spike train." + }, + "id" : "74", + "superClasses" : [ "121" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeTimeDomainConditionalGrangerCausality", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Ding2006_0608035", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute time domain conditional Granger causality", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeTimeDomainConditionalGrangerCausality" + }, + "comment" : { + "en" : "A conditional Granger causality (GC) analysis that computes the GC measures in the time domain." + }, + "id" : "205", + "superClasses" : [ "201" ] + }, { + "iri" : "http://purl.org/neao/data#InterspikeIntervals", + "baseIri" : "http://purl.org/neao/data", + "instances" : 0, + "label" : { + "IRI-based" : "InterspikeIntervals" + }, + "attributes" : [ "external" ], + "id" : "666" + }, { + "iri" : "http://purl.org/neao/steps#NonDirectedAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "non-directed analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "NonDirectedAnalysis" + }, + "comment" : { + "en" : "An analysis step where the output does not provide information on the direction of influence in the relationships among the inputs (e.g., in the Pearson correlation coefficient computed between two spike trains, it is possible to know how strongly they tend to fire together. However, it is not possible to analyze the timing of the spikes of the first input spike with respect to the timing of the spikes of the second input spike train)." + }, + "id" : "571", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputePhaseLagIndex", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Stam2007_1178", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute phase lag index", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute PLI", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputePhaseLagIndex" + }, + "comment" : { + "en" : "A phase lag index (PLI) analysis that computes the PLI following Stam et al. (2007). The input data contains multiple repetitions of a pair of signals (e.g., time series with recordings from a pair of electrodes across multiple trials). For each repetition, the sign of the phase differences between the two time series is obtained from the imaginary part of the cross power spectral density (CPSD). The PLI value is the absolute value of the average of the signs of all repetitions. The PLI ranges between 0 and 1. A PLI of zero means that the first time series leads the second equally often (i.e., indicates either no coupling or coupling with a phase difference centered around 0 mod π, which could be from common sources such as volume conduction). A value greater than zero means an imbalance in the likelihood of the first time series to be either leading or lagging the second time series. A PLI of 1 indicates perfect phase locking, and that the first time series only leads or only lags (at a value of phase differences different from 0 mod π)." + }, + "id" : "647", + "superClasses" : [ "257" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplyDiscreteFourierTransform", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply discrete Fourier transform", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "apply DFT", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplyDiscreteFourierTransform" + }, + "subClasses" : [ "667" ], + "comment" : { + "en" : "A frequency-domain transformation that applies the discrete Fourier transform (DFT) to an input time series acquired in equally-spaced samples. The DFT is used to obtain the frequency representation of the time-domain input. The DFT output is a sequence of coefficients of complex sinusoids, each representing a frequency component in the input signal. Each frequency component consists of an interval (or bin), and the width of the bin determines the frequency resolution of the DFT. The number of frequency components and the frequency resolution is determined by the length of the input signal (number of samples) and the sampling frequency. For large datasets, the computation is computationally expensive (O(N^2) complexity)." + }, + "id" : "400", + "superClasses" : [ "70" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputePartialCoherence", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Rosenberg1998_57", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute partial coherence", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputePartialCoherence" + }, + "comment" : { + "en" : "A coherence analysis that computes the partial coherence, i.e., the coherence value between a pair of inputs (e.g., time series with recordings from two distinct electrode channels) after removing the influence of one or more additional inputs (e.g., the time series with the recordings from all remaining channels). The partial coherence is computed according to Rosenberg et al. (1998). The partial coherence reflects the linear association in the frequency domain (for each frequency component) between the pair of inputs of interest, removing spurious coherence caused by confounding factors such as shared inputs to the pair of interest or volume conduction." + }, + "id" : "545", + "superClasses" : [ "136" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeSpikeWaveformWidth", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute spike waveform width", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeSpikeWaveformWidth" + }, + "comment" : { + "en" : "A spike waveform analysis that computes the width of a spike waveform input. The computation takes two time points of interest (e.g, the times of the peak and the trough), and the width is the difference with respect to the time points (e.g., number of time points in between or time interval)." + }, + "id" : "226", + "superClasses" : [ "165" ] + }, { + "iri" : "http://purl.org/neao/steps#LineNoiseRemoval", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "line noise removal", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "line noise cancellation", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "LineNoiseRemoval" + }, + "subClasses" : [ "668", "669", "670", "671" ], + "comment" : { + "en" : "A data transformation that removes noise induced by the power line." + }, + "id" : "4", + "superClasses" : [ "5" ] + }, { + "iri" : "http://purl.org/neao/steps#SPADEAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "SPADE analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "SPADEAnalysis" + }, + "subClasses" : [ "565", "566" ], + "comment" : { + "en" : "A neuronal activity pattern detection analysis that uses the Spatio-temporal PAttern Detection and Evaluation (SPADE) method. The SPADE analysis takes a set of parallel spike trains as input, and returns significant spatio-temporal neuronal activity (spike) patterns. \n\nThe SPADE method consists of three substeps:\n\n1. Detect all putative patterns in the input data using the frequent item set mining (FIM) algorithm. This step requires the discretization of the input spike train data (binning). The bin size determines the temporal resolution of the analysis.\n\n2. The detected FIM patterns are evaluated for statistical significance, considering the null hypothesis of independence of the spike trains given the modulations by the firing rate. This substep is called Pattern Spectrum Filtering (PSF). For the testing, the patterns are pooled based on their signature: size and occurrence count (non-3d-SPADE) or size, occurrence count and pattern duration (3d-SPADE). The pattern spectrum collects the counts of patterns from each signature. The statistical test is done by a Monte Carlo approach, using spike train surrogates generated from the original data. The final output of this substep is the p-value spectrum, which has the same dimensions as the pattern spectrum. The p-value is computed as the ratio of surrogates containing patterns with that signature to the total number of realizations.\n\n3. Conditional test on the significant patterns to remove patterns arising from the overlap of true pattern spikes and chance spikes (pattern set reduction; PSR)." + }, + "id" : "224", + "superClasses" : [ "216" ] + }, { + "iri" : "http://purl.org/neao/steps#GenerateStationaryPoissonProcess", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Deger2012_443", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "generate stationary Poisson process", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "GenerateStationaryPoissonProcess" + }, + "comment" : { + "en" : "A random spike times generation that uses a Poisson probability distribution to produce spike trains with a constant firing rate. A dead time can be specified as parameter (i.e., an interval where no spikes can occur, which is analogous to the neuronal refractory period)." + }, + "id" : "28", + "superClasses" : [ "8" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplyIndependentComponentAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Jutten1991_1", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply independent component analysis", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "apply ICA", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplyIndependentComponentAnalysis" + }, + "comment" : { + "en" : "A data transformation that separates a multivariate input signal into additive subcomponents (independent components). The independent components are statistically independent from each other." + }, + "id" : "414", + "superClasses" : [ "5" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputePopulationHistogram", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute population histogram", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputePopulationHistogram" + }, + "comment" : { + "en" : "A spike train time histogram analysis that computes a histogram across two or more spike trains that contain the activity of different neurons (i.e., a neuronal population), recorded at fully-overlapping time intervals. The activity in each histogram bin reflects the combined activity of the population at that time, and the distribution of the histogram corresponds to the population activity over time." + }, + "id" : "314", + "superClasses" : [ "154" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplyProbabilisticPrincipalComponentAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Tipping1999_611", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply probabilistic principal component analysis", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "apply pPCA", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplyProbabilisticPrincipalComponentAnalysis" + }, + "comment" : { + "en" : "A principal component analysis (PCA) that assumes a probabilistic model for the generation of the observed data, according to Tipping & Bishop (1999). The model assumes that the values in the data input are generated from the lower-dimensional subspace of latent variables (principal components) plus an additive Gaussian noise. This generalizes the standard PCA for the case where the noise covariance approaches zero. The probabilistic PCA (pPCA) allows for uncertainty estimation and modeling of the data generation process, and can be employed when there are missing values in the input data." + }, + "id" : "665", + "superClasses" : [ "327" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplySpikeWaveformOutlierRejection", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply spike waveform outlier rejection", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplySpikeWaveformOutlierRejection" + }, + "comment" : { + "en" : "An artifact removal that identifies and removes spike waveforms that differ significantly from the other spike waveforms in the input. This usually involves identifying waveforms with too late peaks, or in which the rising phase of the potential does not align with the peaks of all other waveforms in the input." + }, + "id" : "444", + "superClasses" : [ "36" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeMutualInformation", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Cover2012", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute mutual information", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute MI", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeMutualInformation" + }, + "comment" : { + "en" : "A functional connectivity analysis that computes a mutual information (MI) measure. MI is based on Shannon information theory, and quantifies the amount of information from one input that is obtained from another input. Therefore, it can be used to determine how the neuronal activity provides information about a variable (e.g., behavioral stimulus) or how the information flows between different brain regions or neurons. The MI is measured in bits." + }, + "id" : "134", + "superClasses" : [ "77" ] + }, { + "iri" : "http://purl.org/neao/steps#AutocorrelationAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "autocorrelation analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "AutocorrelationAnalysis" + }, + "subClasses" : [ "585", "439" ], + "comment" : { + "en" : "An analysis step used to compute a measure of autocorrelation, i.e., the correlation of the input with displaced (lagged or advanced) versions of itself. The computation produces the autocorrelation value for every lag considered." + }, + "id" : "303", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplyMovementArtifactRemoval", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply movement artifact removal", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplyMovementArtifactRemoval" + }, + "comment" : { + "en" : "An artifact removal that identifies and removes artifacts originating from movements of the experimental subject (e.g., eye movement, head movement)." + }, + "id" : "445", + "superClasses" : [ "36" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeMean", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute mean", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeMean" + }, + "comment" : { + "en" : "A central tendency statistical analysis that computes the mean of the input data. The mean is the arithmetic average of all data points." + }, + "id" : "181", + "superClasses" : [ "179" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeVanRossumDistance", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Rossum2001_751", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute van Rossum distance", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeVanRossumDistance" + }, + "comment" : { + "en" : "A time-scale dependent spike train distance analysis that computes the van Rossum distance introduced in van Rossum (2001). For the computation, each spike in the input spike trains is convolved with an exponential kernel, producing continuous function representations of the input spike trains. The time scale parameter of the distance is set by the time constant of the exponential kernel. The distance is then obtained as the Euclidean distance of the convolved spike trains." + }, + "id" : "196", + "superClasses" : [ "197" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputePartialDirectedCoherence", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Baccala2001_463", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute partial directed coherence", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute PDC", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputePartialDirectedCoherence" + }, + "comment" : { + "en" : "A coherence analysis that computes the partial directed coherence (PDC) according to Baccalá & Sameshima (2001). The PDC describes the relationships between multivariate time series inputs (direction of information flow). To compute the PDC, the multivariate partial coherences obtained from multivariate autoregressive models are decomposed. The PDC reflects a frequency-domain representation of the concept associated with Granger causality." + }, + "id" : "173", + "superClasses" : [ "132" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeMultivariateInteractionMeasure", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Ewald2012_476", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute multivariate interaction measure", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute MIM", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeMultivariateInteractionMeasure" + }, + "comment" : { + "en" : "A functional connectivity analysis that computes the multivariate interaction measure (MIM) as defined by Ewald et al. (2012). MIM is constructed from the maximization of imaginary coherency." + }, + "id" : "178", + "superClasses" : [ "77" ] + }, { + "iri" : "http://purl.org/neao/steps#TensorComponentAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "tensor component analysis", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "tensor principal component analysis", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "TCA", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "TensorComponentAnalysis" + }, + "subClasses" : [ "48", "120", "595" ], + "comment" : { + "en" : "A dimensionality reduction that reduces the dimensionality of the input data represented as a tensor (i.e., an array with multiple dimensions). The tensor component analysis (TCA) transforms the data into a set of low-dimensional tensors that capture the maximum variance in the input (tensor components)." + }, + "id" : "49", + "superClasses" : [ "51" ] + }, { + "iri" : "http://purl.org/neao/steps#BivariateAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "bivariate analysis", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "pairwise analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "BivariateAnalysis" + }, + "comment" : { + "en" : "An analysis step that has only two distinct inputs considered for the computation of the output (e.g., the two time series with the local field potential recorded from two electrodes used to compute a cross-correlation)." + }, + "id" : "625", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeSpectrogramMultitaper", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute spectrogram (multitaper method)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeSpectrogramMultitaper" + }, + "comment" : { + "en" : "A spectrogram analysis that uses a multitaper approach to obtain the time-frequency information from the input and that is used to build the spectrogram." + }, + "id" : "323", + "superClasses" : [ "276" ] + }, { + "iri" : "http://purl.org/neao/steps#GenerateStationaryLogNormalProcess", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "generate stationary log-normal process", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "GenerateStationaryLogNormalProcess" + }, + "comment" : { + "en" : "A random spike times generation that uses a log-normal probability distribution to produce spike trains with a constant firing rate." + }, + "id" : "38", + "superClasses" : [ "8" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeASSETProbabilityMatrixAnalytical", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Torre2016_e1004939", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute ASSET probability matrix (analytical method)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeASSETProbabilityMatrixAnalytical" + }, + "comment" : { + "en" : "ASSET analysis probability matrix substep that computes the probability matrix (PMAT) using the assumption that the input spike trains are independent and Poisson. The computation can take as input the firing rate profiles of the spike trains used for the intersection matrix (IMAT), or those will be automatically computed using convolution with a boxcar kernel of specified width. The probability distribution of the value in the intersection matrix (IMAT) is approximated by a Poisson distribution computed using LeCam's approximation. The output is a matrix with the cumulative probabilities representing the probability of having each overlap in the IMAT strictly lower than the observed overlap, under the null hypothesis of independence of the input spike trains." + }, + "id" : "127", + "superClasses" : [ "64" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeRateChangeDetectionMultipleFilterTest", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Messer2014_2027", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute rate change detection multiple filter test", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeRateChangeDetectionMultipleFilterTest" + }, + "comment" : { + "en" : "An analysis step that uses the change point detection algorithm from Messer et al. (2014) to determine if a input spike train has constant firing rate (stationary) or has one or more points in which the firing rate decreases or increases (change point). In the latter case, the spike train is considered non-stationary. The analysis step outputs one or more change points in the case of non-stationarity." + }, + "id" : "591", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#DistanceAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "label" : { + "IRI-based" : "DistanceAnalysis" + }, + "id" : "539", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#InterspikeIntervalVariabilityAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "interspike interval variability analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "InterspikeIntervalVariabilityAnalysis" + }, + "subClasses" : [ "598", "602", "605", "128" ], + "comment" : { + "en" : "An interspike interval analysis that computes a measure describing the variability of the interspike intervals. The measure can assess how regular a neuron is firing." + }, + "id" : "129", + "superClasses" : [ "360" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplySpikeWaveformPeakAlignment", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply spike waveform peak alignment", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplySpikeWaveformPeakAlignment" + }, + "comment" : { + "en" : "A data transformation that modifies input spike waveforms in order to align their peak values in time." + }, + "id" : "15", + "superClasses" : [ "5" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeModulationIndex", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Tort2010_1195", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute modulation index", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute MI", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeModulationIndex" + }, + "comment" : { + "en" : "A phase-amplitude coupling (PAC) analysis that computes the modulation index (MI) as described in Tort et al. (2010). For the computation, the Hilbert transform is used to obtain the instantaneous phase from the input time series with the low-frequency oscillation, and the instantaneous amplitude from the input time series with the high-frequency oscillation. The phase of the low-frequency oscillation is discretized into bins and the amplitude of the high-frequency oscillation is averaged within each bin to create a distribution. This distribution is then compared to a uniform distribution using the Kullback-Leibler divergence, normalized by the maximum possible divergence, resulting in the MI." + }, + "id" : "410", + "superClasses" : [ "269" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplySpikeTrainBinarization", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply spike train binarization", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplySpikeTrainBinarization" + }, + "comment" : { + "en" : "A data transformation that takes an input spike train and returns an array of boolean values indicating if at least one spike occurred at individual time points." + }, + "id" : "31", + "superClasses" : [ "5" ] + }, { + "iri" : "http://purl.org/neao/steps#CoherenceAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "coherence analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "CoherenceAnalysis" + }, + "subClasses" : [ "417", "185", "545" ], + "comment" : { + "en" : "A spectral analysis that computes a measure of coherence between two or more inputs. 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For example, in a multitrial experimental session, where data was acquired separately as one epoch per trial, a continuous data segment for the session can be constructed by concatenating all trial epochs together." + }, + "id" : "466", + "superClasses" : [ "5" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeFrequencyDomainPairwiseGrangerCausalityDhamala", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Dhamala2008_354", + "type" : "iri" + }, { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Wilson1972_420", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute frequency domain pairwise Granger causality (Dhamala method)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeFrequencyDomainPairwiseGrangerCausalityDhamala" + }, + "comment" : { + "en" : "A frequency domain pairwise Granger causality (GC) analysis that uses the non-parametric approach according to Dhamala et al. 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It is based on Fourier and wavelet transforms to obtain the spectral density matrix and the algorithm from Wilson (1972) for its factorization." + }, + "id" : "343", + "superClasses" : [ "10" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeASSETProbabilityMatrixMonteCarlo", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Torre2016_e1004939", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute ASSET probability matrix (Monte Carlo method)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeASSETProbabilityMatrixMonteCarlo" + }, + "comment" : { + "en" : "ASSET analysis probability matrix substep that computes the probability matrix (PMAT) employing a Monte Carlo approach using surrogate data obtained from the input spike trains. Different than the analytical method of computation, the null hypothesis in this method does not incorporate the assumptions that the spike trains are Poisson. Spike train surrogates can be generated using distinct methods." + }, + "id" : "126", + "superClasses" : [ "64" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeLV", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Shinomoto2003_2823", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute local variation", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute LV", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeLV" + }, + "comment" : { + "en" : "An interspike interval variability analysis that computes the local variation (LV) of the interspike intervals. LV reflects the stepwise variability of a sequence of spikes, and is able to extract the spiking characteristics of individual neurons even in the presence of external modulations of the firing rate." + }, + "id" : "605", + "superClasses" : [ "129" ] + }, { + "iri" : "http://purl.org/neao/data#ArtificialData", + "baseIri" : "http://purl.org/neao/data", + "instances" : 0, + "label" : { + "IRI-based" : "ArtificialData" + }, + "attributes" : [ "external" ], + "id" : "364" + }, { + "iri" : "http://purl.org/neao/steps#ComputeCoherenceCarter", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Carter1987_236", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute coherence (Carter method)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeCoherenceCarter" + }, + "comment" : { + "en" : "A coherence analysis that computes the coherence from two inputs according to Carter (1987). 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If phase-amplitude coupling exists, the magnitude of a subset of vectors is especially high at a specific phase or narrow phase range." + }, + "id" : "271", + "superClasses" : [ "268" ] + }, { + "iri" : "http://purl.org/neao/steps#LatentDynamicsAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "latent dynamics analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "LatentDynamicsAnalysis" + }, + "comment" : { + "en" : "An analysis step that aims to identify underlying patterns and structures within time series or sequential data that are not directly observable. It involves modeling hidden (latent) variables that influence the observed data and their evolution over time. The analysis captures temporal dependencies and dynamics within the data, providing insights into the processes that generate the observed sequences." + }, + "id" : "576", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#GenerateStationaryGammaProcess", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "generate stationary gamma process", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "GenerateStationaryGammaProcess" + }, + "comment" : { + "en" : "A random spike times generation that uses a gamma probability distribution to produce spike trains with a constant firing rate." + }, + "id" : "23", + "superClasses" : [ "8" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeSpectrogramShortTimeFourierTransform", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute spectrogram (short-time Fourier transform method)", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute spectrogram (STFT method)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeSpectrogramShortTimeFourierTransform" + }, + "comment" : { + "en" : "A spectrogram analysis that uses the short-time Fourier transform (STFT) on the input to obtain the time-frequency information used to build the spectrogram." + }, + "id" : "275", + "superClasses" : [ "276" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeWeightedPhaseLagIndex", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Vinck2011_1548", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute weighted phase lag index", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute WPLI", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeWeightedPhaseLagIndex" + }, + "comment" : { + "en" : "A phase lag index (PLI) analysis that computes the weighted PLI (WPLI) following Vinck et al. (2011). The original PLI (Stam, 2007) is discontinuous, and small perturbations can turn phase lags into leads (and vice versa). Therefore, this hinders its capacity to detect changes in phase synchronization of small magnitude. The WPLI extends the PLI to weight the contributions of the phase leads and lags by the magnitude of the imaginary component of the cross spectral density. Therefore, these increases the power to detect changes in phase synchronization. The WPLI ranges between 0 and 1. A WPLI of zero means that there is no imbalance in the first time series leading or lagging the second (i.e., the total weight of all leading relationships is equal to the total weight of lagging relationships). A value greater than zero means an imbalance in the likelihood of leading or lagging. A WPLI of 1 indicates perfect phase locking, and that the first time series only leads or only lags." + }, + "id" : "646", + "superClasses" : [ "257" ] + }, { + "iri" : "http://purl.org/neao/steps#SpikeFieldCoherenceAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "spike-field coherence analysis", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "SFC analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "SpikeFieldCoherenceAnalysis" + }, + "subClasses" : [ "549", "552", "520" ], + "comment" : { + "en" : "An analysis step that computes the spike-field coherence (SFC), which is the coherence computed between an input spike train and an input time series with the local field potential (LFP). Coherence is a measure of the association between the two inputs in the frequency domain. SFC can be used to quantify the relationship between the spiking activity of neurons and the oscillatory activity in the LFP. It represents the similarity of dynamics between the spike train and the voltage fluctuations produced by the neural activity in the local environment where the spiking activity was recorded." + }, + "id" : "521", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplyButterworthFilter", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply Butterworth filter", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "apply maximally flat magnitude filter", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplyButterworthFilter" + }, + "comment" : { + "en" : "An infinite impulse response filtering that uses a Butterworth type filter, i.e., a filter designed to have a maximally flat frequency response in the passband (no ripples). The frequency response gradually decreases to zero in the stopband, and the steepness of the decrease (roll-off) is controlled by the order of the filter." + }, + "id" : "398", + "superClasses" : [ "283" ] + }, { + "iri" : "http://purl.org/neao/data#SpikeWaveformSNR", + "baseIri" : "http://purl.org/neao/data", + "instances" : 0, + "label" : { + "IRI-based" : "SpikeWaveformSNR" + }, + "attributes" : [ "external" ], + "id" : "676" + }, { + "iri" : "http://purl.org/neao/steps#ComputeCrossCorrelationFunctionBiased", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute cross-correlation function (biased)", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute CCF (biased)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeCrossCorrelationFunctionBiased" + }, + "comment" : { + "en" : "An analysis step that computes the biased estimator for the cross-correlation function. The biased estimator produces cross-correlation values that deviate from the true cross-correlation." + }, + "id" : "273", + "superClasses" : [ "117" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeInterquartileRange", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute interquartile range", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute IQR", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeInterquartileRange" + }, + "comment" : { + "en" : "A dispersion statistical analysis that computes the interquartile range (IQR). The IQR is the difference between the 75th and 25th percentiles (i.e., the range within which the central 50% of the data points lie)." + }, + "id" : "235", + "superClasses" : [ "47" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeCoherenceWelch", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Welch1967_70", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute coherence (Welch method)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeCoherenceWelch" + }, + "comment" : { + "en" : "A coherence analysis where the coherence value between the two inputs is obtained from cross and auto power spectral densities obtained using the method described by Welch (1967). For the computation, the inputs are divided into multiple overlapping segments, and the overall cross and power spectral densities for computing the coherence are obtained from averaging the single-segment estimates." + }, + "id" : "422", + "superClasses" : [ "417" ] + }, { + "iri" : "http://purl.org/neao/steps#InstantaneousFiringRateAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "instantaneous firing rate analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "InstantaneousFiringRateAnalysis" + }, + "subClasses" : [ "516", "297", "501" ], + "comment" : { + "en" : "A firing rate analysis that computes the instantaneous firing rate, which is the estimate of the firing rate at a specific point in time. The instantaneous firing rate value can be obtained by several methods." + }, + "id" : "163", + "superClasses" : [ "150" ] + }, { + "iri" : "http://purl.org/neao/steps#TimeScaleDependentSpikeTrainDistanceAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "time-scale dependent spike train distance analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "TimeScaleDependentSpikeTrainDistanceAnalysis" + }, + "subClasses" : [ "248", "196" ], + "comment" : { + "en" : "A spike train dissimilarity analysis that computes a spike train distance that depends on a parameter that determines a temporal scale in the spike trains to which the distance is sensitive. By computing the spike train distance for different time scale parameter values, it is possible to make inferences on the time scale that is discriminative in the neural activity." + }, + "id" : "197", + "superClasses" : [ "289" ] + }, { + "iri" : "http://purl.org/neao/steps#SpikeSpikeCouplingAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "spike-spike coupling analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "SpikeSpikeCouplingAnalysis" + }, + "comment" : { + "en" : "An analysis step that computes interactions between the spiking activity of one or more neurons." + }, + "id" : "358", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeASSETIntersectionMatrix", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Torre2016_e1004939", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute ASSET intersection matrix", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeASSETIntersectionMatrix" + }, + "comment" : { + "en" : "ASSET analysis substep that computes the intersection matrix (IMAT). For a set of input spike trains, binned with a bin width, each entry in the IMAT corresponds to a pair of distinct bins (i.e., distinct time points in the data). The value in the entry corresponds to the number of neurons that fired in both bins corresponding to that entry. When groups of neurons fire in a sequence that repeats in time, the IMAT will show patterns that follow a diagonal direction (diagonal structure). The ASSET method aims to identify the diagonal structures by automated statistical testing and clustering procedures." + }, + "id" : "72", + "superClasses" : [ "55" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplyInfiniteImpulseResponseFilter", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply infinite impulse response filter", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "apply IIR filter", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplyInfiniteImpulseResponseFilter" + }, + "comment" : { + "en" : "An infinite impulse response (IIR) filtering where a custom-designed IIR filter is applied to the input data." + }, + "id" : "403", + "superClasses" : [ "283" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeFrequencyDomainPairwiseGrangerCausalityWen", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Wen2013_20110610", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute frequency domain pairwise Granger causality (Wen method)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeFrequencyDomainPairwiseGrangerCausalityWen" + }, + "comment" : { + "en" : "A frequency domain pairwise Granger causality (GC) analysis that uses the non-parametric approach according to Wen et al. (2013). It is a multivariate framework for estimating GC based on spectral density matrix factorization. The approach requires only a single estimation of the spectral density matrix for the entire dataset (e.g., multiple time series inputs). GC for the subsets (i.e., pairs of inputs) can then be calculated by factorizing the relevant submatrix of this overall spectral density matrix." + }, + "id" : "347", + "superClasses" : [ "10" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeOptimalKernelBandwidth", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Shimazaki2010_171", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute optimal kernel bandwidth", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeOptimalKernelBandwidth" + }, + "comment" : { + "en" : "An analysis step that computes the optimal fixed bandwidth (width) for a Gaussian kernel used for the estimation of the firing rate using kernel density estimation. The analysis step uses the input spike train for which the firing rate will be computed, and follows the implementation by Shimazaki & Shinomoto (2010)." + }, + "id" : "657", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputePeristimulusTimeHistogramAdaptiveKernelSmoothing", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute peristimulus time histogram (adaptive kernel smoothing)", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute PSTH (adaptive kernel smoothing)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputePeristimulusTimeHistogramAdaptiveKernelSmoothing" + }, + "comment" : { + "en" : "A peristimulus time histogram (PSTH) analysis that computes the PSTH using kernel density smoothing with an adaptive kernel width. The adaptive kernel is obtained by first computing the PSTH with a fixed-width kernel, and then modifying the kernel width in order to have a constant but time-dependent average number of spikes under the kernel (i.e., segments of the data with a high density of spikes will have a reduced kernel width)." + }, + "id" : "425", + "superClasses" : [ "44" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeMeanVectorLengthOzkurt", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Ozkurt2011_438", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute mean vector length (Özkurt method)", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute MVL (Özkurt method)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeMeanVectorLengthOzkurt" + }, + "comment" : { + "en" : "A mean vector length (MVL) analysis that computes the MVL as described in Özkurt & Schnitzler (2011). The original MVL (Canolty et al., 2006) may be affected by factors in the input data (e.g., amplitude outliers or non-uniform distribution of phase angles). This computation estimates a direct MVL that is amplitude-normalized to obtain values in the 0 to 1 range, and that takes care of possible amplitude differences in the raw data." + }, + "id" : "270", + "superClasses" : [ "268" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplyDFTNoiseRemoval", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply discrete Fourier transform noise removal", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "apply DFT noise removal", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplyDFTNoiseRemoval" + }, + "comment" : { + "en" : "A line noise removal that uses a discrete Fourier transform (DFT) filter and estimates the power line component amplitude in the input data by fitting a sine and cosine at a user-specified line noise frequency (e.g., 50 Hz), followed by the subtraction of those components from the input." + }, + "id" : "669", + "superClasses" : [ "4" ] + }, { + "iri" : "http://purl.org/neao/steps#Execute3dSPADEAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Stella2019_104022", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "execute 3d-SPADE analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "Execute3dSPADEAnalysis" + }, + "comment" : { + "en" : "A SPADE analysis that uses the 3d-SPADE implementation as defined in Stella et al. (2019). The 3d-SPADE analysis considers spatio-temporal patterns (i.e., not restricted to synchronous patterns), and the pattern signature used for statistical testing considers the size, number of occurrences and duration of a pattern." + }, + "id" : "565", + "superClasses" : [ "224" ] + }, { + "iri" : "http://purl.org/neao/steps#ConditionalGrangerCausalityAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "conditional Granger causality analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ConditionalGrangerCausalityAnalysis" + }, + "subClasses" : [ "200", "205" ], + "comment" : { + "en" : "A Granger causality (GC) analysis that computes a measure of conditional GC between the inputs. The conditional GC is the causality between two inputs (e.g., two time series) while controlling for the influence of an additional input (e.g., a third time series). This allows a more complete understanding of the causal relationships in multivariate time series data." + }, + "id" : "201", + "superClasses" : [ "139" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplySpikeTrainBinning", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply spike train binning", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplySpikeTrainBinning" + }, + "comment" : { + "en" : "A data transformation that performs a binning operation on the input spike train data. The transformation discretizes the duration of the input spike train(s) into smaller time intervals (bins), and obtains the number of spikes occurring into each bin (binned spike train). Additionally, the occurrence of spikes into each bin can be converted into a binary form (i.e., bins with or without spikes). This is known as clipping. The width of the bin interval is specified by a parameter (bin size)." + }, + "id" : "420", + "superClasses" : [ "5" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplyDistanceCovarianceAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Cowley2017_242", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply distance covariance analysis", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "apply DCA", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplyDistanceCovarianceAnalysis" + }, + "comment" : { + "en" : "A dimensionality reduction that identifies linear and nonlinear relationships between multiple input datasets. The method identifies linear projections (DCA dimensions) that maximize the distance covariance statistic (an Euclidean-based correlational statistic). For example, for recordings from different brain regions (two neuronal populations), the distance covariance analysis (DCA) can identify the dimensions in the population activity in the different brain areas that are related to each other. The dimensionality reduction can also take other dependent variables into account (e.g., stimulus or behavioral variables)." + }, + "id" : "326", + "superClasses" : [ "51" ] + }, { + "iri" : "http://purl.org/neao/steps#NeuronalFiringRegularityAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "neuronal firing regularity analysis", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "spike time variability analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "NeuronalFiringRegularityAnalysis" + }, + "subClasses" : [ "210" ], + "comment" : { + "en" : "An analysis step that computes measures to assess the regularity in the firing of a neuron. Neuronal firing regularity refers to the consistency or variability in the timing of action potentials (spikes) generated by a neuron." + }, + "id" : "211", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplyNotchFilterNoiseRemoval", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply notch filter noise removal", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplyNotchFilterNoiseRemoval" + }, + "comment" : { + "en" : "A line noise removal that employs a notch filter to remove line noise. A notch filter is designed to attenuate or eliminate a narrow band of frequencies in the input data (stopband) while allowing other frequencies to pass through relatively unaffected. The notch filter stop band is usually centered at the power line frequency (i.e., 50 Hz or 60 Hz depending on the location)." + }, + "id" : "670", + "superClasses" : [ "4" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplyThomsonRegressionNoiseRemoval", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Thomson1982_1055", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply Thomson regression noise removal", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplyThomsonRegressionNoiseRemoval" + }, + "comment" : { + "en" : "A line noise removal that uses Thomson's regression method (1982) for detecting sinusoids, that identifies and removes significant sine waves from the input data. The desired frequencies can be specified by parameter, or determined using an F-statistic." + }, + "id" : "671", + "superClasses" : [ "4" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeSpikeTrainFanoFactor", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Nawrot2008_374", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute spike train Fano factor", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeSpikeTrainFanoFactor" + }, + "comment" : { + "en" : "An analysis step that computes the Fano factor (FF) for a set of input spike trains. For each input spike train, the spike count is obtained. The Fano factor is defined as the ratio of the variance of the spike count to the mean spike count, across all spike trains. The Fano factor is usually computed for spike trains representing the activity of the same neuron over different trials. The value is interpreted as the higher the Fano factor value, the larger the cross-trial non-stationarity. For a stationary Poisson process, the Fano factor has value equal to 1." + }, + "id" : "210", + "superClasses" : [ "211" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeTimeDomainPairwiseGrangerCausality", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Ding2006_0608035", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute time domain pairwise Granger causality", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeTimeDomainPairwiseGrangerCausality" + }, + "comment" : { + "en" : "A pairwise Granger causality (GC) analysis that computes measures of GC between two inputs in the time domain. The computation involves fitting two separate autoregressive (AR) models to the input data and comparing their fit to determine if one time series can predict the other. The quality of the fit is assessed by the variance of the residuals, with GC defined as the natural logarithm of the ratio of the residual variances from the two AR models. The first AR model is univariate, predicting the future values of one time series (e.g., the first) only from its past values. The second AR model is bivariate, predicting the future values of the first time series from its past values as well as the past values of the second time series. If the bivariate model reduces the variance of the residuals (ratio greater than 1), the GC value will be positive, indicating that the second time series Granger causes the first (directional GC estimate from the second to the first). The same method is used to predict the second time series from the first, yielding the directional GC estimate from the first to the second time series. The order of the AR model is defined as parameter, and optimal values can be estimated using optimization techniques." + }, + "id" : "395", + "superClasses" : [ "264" ] + }, { + "iri" : "http://purl.org/neao/steps#NeuronalActivityPatternDetectionAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "neuronal activity pattern detection analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "NeuronalActivityPatternDetectionAnalysis" + }, + "subClasses" : [ "215", "220", "224", "228" ], + "comment" : { + "en" : "An analysis step that aims to identify a neuronal activity pattern, i.e., spikes of a group of neurons that occur in a specific spatio-temporal configuration." + }, + "id" : "216", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeEventTriggeredAverage", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute event-triggered average", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeEventTriggeredAverage" + }, + "comment" : { + "en" : "A triggered average analysis that uses an event of interest such as an external stimulus (e.g., electrical, visual, auditory) or a spontaneous behavior (e.g., eye blink) as a trigger to average a signal. The output of the method will provide the average value of the signal around the time where each event occurred (event-triggered average)." + }, + "id" : "334", + "superClasses" : [ "335" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplyFiniteImpulseResponseFilter", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply finite impulse response filter", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "apply FIR filter", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplyFiniteImpulseResponseFilter" + }, + "comment" : { + "en" : "A finite impulse response (FIR) filtering where a custom-designed FIR filter is applied to the input data." + }, + "id" : "449", + "superClasses" : [ "278" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeImaginaryCoherency", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Nolte2004_2292", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute imaginary coherency", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeImaginaryCoherency" + }, + "comment" : { + "en" : "A coherency analysis that computes the imaginary part of the coherency for two inputs according to Nolte et al. (2004). For the computation, the imaginary part of the complex-valued cross power spectral density obtained for the two inputs is normalized by the square root of the product of their power spectral densities (i.e., auto spectral densities). If the inputs contain multi-epoch data (e.g., multiple trial repetitions), the cross and auto spectral densities are averaged across epochs. The imaginary part of the coherency is less affected by volume conduction than the (complex) coherency." + }, + "id" : "441", + "superClasses" : [ "169" ] + }, { + "iri" : "http://purl.org/neao/steps#ConfidenceIntervalStatisticalAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "confidence interval statistical analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ConfidenceIntervalStatisticalAnalysis" + }, + "subClasses" : [ "119", "187" ], + "comment" : { + "en" : "A statistical analysis that computes a confidence interval (CI). The CI is a measure providing a range of values of a parameter, derived from the input (sample) data, that is likely to contain the true value of the parameter in the population with a specified level of confidence. The level of confidence is specified as a parameter to the method. For example, a 95% confidence interval means that if the same population is sampled multiple times, approximately 95% of the intervals calculated from those samples will contain the true population parameter. Confidence intervals are used to estimate parameters such as the mean and are essential for making inferences about the population based on sample data. The output contains the upper and lower limits of the CI." + }, + "id" : "188", + "superClasses" : [ "180" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputePowerSpectralDensityPeriodogram", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute power spectral density (periodogram method)", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "compute periodogram", + "type" : "label" + }, { + "identifier" : "altLabel", + "language" : "en", + "value" : "compute FFT power spectral density", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute PSD (periodogram method)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputePowerSpectralDensityPeriodogram" + }, + "comment" : { + "en" : "A power spectral density (PSD) analysis that uses the periodogram method. For the computation, the discrete Fourier transform is applied to the full length of the input, and the power spectrum is obtained. To reduce spectral leakage, a window function can be applied to the input before the computation of the Fourier transform (this is referred as the modified periodogram). The power spectrum is then normalized to the unit frequency, using the equivalent noise bandwidth (a factor that depends on the coefficients of the window function and the sampling rate). If no window function is used or a window that does not attenuate the signal is used (e.g., Boxcar or rectangular window) the equivalent noise bandwidth is equal to the frequency resolution. The PSD using the periodogram is computationally simple to obtain." + }, + "id" : "373", + "superClasses" : [ "192" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplySynchronousSpikeRemoval", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply synchronous spike removal", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplySynchronousSpikeRemoval" + }, + "comment" : { + "en" : "An artifact removal that identifies and removes spikes across two or more spike train inputs that occurred simultaneously within a temporal precision specified by a parameter. The temporal precision is usually the sampling rate used by the recording equipment: if different neurons fired within an interval equal to or smaller than the sampling period, this suggests that this synchronous activity does not come from temporal synchronization of the neurons but rather due to an interference in the recording (e.g., electrical noise picked simultaneously by multiple channels)." + }, + "id" : "447", + "superClasses" : [ "36" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplyCanonicalPolyadicTensorDecomposition", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Williams2018_1099", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply canonical polyadic tensor decomposition", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "apply tensor rank decomposition", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "apply CPD", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplyCanonicalPolyadicTensorDecomposition" + }, + "comment" : { + "en" : "A tensor component analysis (TCA) that expresses the input high-dimensional tensor as a sum of rank-one tensors (tensor components). Each dimension in the tensor component corresponds to a dimension in the input high-dimensional tensor. For neural data, a tensor could be used to represent trial-by-trial spiking activity, with neurons, time, and trials as dimensions. Therefore, each tensor component produced from that input will have a rank-one tensor for the neurons, time, and trial, which describes both within- and between-trial changes." + }, + "id" : "595", + "superClasses" : [ "49" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeDebiasedSquaredWeightedPhaseLagIndex", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Vinck2011_1548", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute debiased squared weighted phase lag index", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute debiased squared WPLI", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeDebiasedSquaredWeightedPhaseLagIndex" + }, + "comment" : { + "en" : "A phase lag index (PLI) analysis that computes the debiased squared weighted PLI (WPLI) following Vinck et al. (2011). The direct PLI estimator is positively biased, especially when the sample sizes (i.e., number of trials) are small. The debiased squared WPLI is computed by computing the imaginary components of the cross spectral densities, computing the average imaginary component of the cross spectral densities, and normalizing by the computed average over the magnitudes of the imaginary component of the cross spectral densities." + }, + "id" : "256", + "superClasses" : [ "257" ] + }, { + "iri" : "http://purl.org/neao/steps#SpectralDensityAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "spectral density analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "SpectralDensityAnalysis" + }, + "subClasses" : [ "192", "145" ], + "comment" : { + "en" : "A spectral analysis that computes the density of a measure of the input(s) over the frequency spectrum. Density means that the measure value (e.g., power) for each frequency component is expressed per unit frequency. For example, for an input time series with voltages recorded from an electrode (measured in V), the power for each frequency component of the signal will be in V**2, while the power density will be in V**2/Hz. Therefore, the power values are normalized per unit frequency. This normalization allows for consistent comparisons of results from analyses with different frequency resolutions, as the spectral density remains unaffected by these variations." + }, + "id" : "146", + "superClasses" : [ "132" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeTuningCurve", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute tuning curve", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeTuningCurve" + }, + "comment" : { + "en" : "A firing rate analysis that computes a tuning curve. The tuning curve describes the firing rate of a neuron as a function of a continuous attribute (e.g., orientation of a visual grating stimulus)." + }, + "id" : "149", + "superClasses" : [ "150" ] + }, { + "iri" : "http://purl.org/neao/steps#GenerateISIShufflingSurrogate", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Louis2010_359", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "generate interspike interval shuffling surrogate", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "GenerateISIShufflingSurrogate" + }, + "comment" : { + "en" : "A spike train surrogate generation step where the interspike intervals (ISIs) of the input spike train is randomly sorted. This preserves the ISI distribution and spike count as in the original spike train input, but destroys temporal dependencies and firing rate profile." + }, + "id" : "341", + "superClasses" : [ "121" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplyFastFourierTransform", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply fast Fourier transform", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "apply FFT", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplyFastFourierTransform" + }, + "comment" : { + "en" : "A frequency-domain transformation that uses the fast Fourier transform (FFT) algorithm to compute the discrete Fourier transform (DFT). The computation of the DFT is computationally expensive for large datasets. The FFT reduces the number of computations significantly by using a divide-and-conquer approach, leveraging the symmetry and periodicity properties of the DFT. The complexity is O(N log N). The output of the method is similar to the DFT, i.e., a sequence of coefficients of complex sinusoids, each representing a frequency component in the input signal. The FFT takes a size parameter, that refers to the number of points in the input data sequence that is used for the computation. The FFT size determines the frequency resolution, and, for maximal efficiency, should be a multiple of 2." + }, + "id" : "667", + "superClasses" : [ "400" ] + }, { + "iri" : "http://purl.org/neao/steps#ExecuteUnitaryEventAnalysisAnalytical", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Gruen1999_67", + "type" : "iri" + }, { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Gruen2003_335", + "type" : "iri" + }, { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Gruen2002_43", + "type" : "iri" + }, { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Gruen2002_81", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "execute Unitary Event analysis (analytical method)", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "execute UE analysis (analytical method)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ExecuteUnitaryEventAnalysisAnalytical" + }, + "comment" : { + "en" : "A unitary event (UE) analysis that uses the analytical approach to determine the significance of the empirical coincidences in binned spike train data, as defined in Grün et al. (1999, 2002a, 2002b, and 2003). The analytical method tests if the number of empirical coincidences is consistent with the coincidence distribution resulting from independent processes. This distribution can be expressed analytically assuming that the input spike trains follow Poisson statistics. The UEs can be determined trial by trial, where the analytical expectancy is computed for each trial and then summed over all trials, or by averaging over all trials (according to Grün, 2003)." + }, + "id" : "252", + "superClasses" : [ "215" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeNeuronalPopulationVector", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Georgopoulos1983_327", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute neuronal population vector", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "compute population vector", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeNeuronalPopulationVector" + }, + "comment" : { + "en" : "An analysis step that computes the neuronal population vector, used to describe the collective activity of a group of neurons. The neuronal population vector is obtained taking as inputs the multiple responses of a neuronal population in the context of distinct values of a behavioral measure (e.g., tuning curves showing the response of each individual neuron to different arm movement directions in the 2-D space). The analysis step obtains a weighted vectorial sum of the neural activities, which will result in an estimate of the behavioral measure considering the collective activity of the population (e.g., the movement direction given the neuronal activity)." + }, + "id" : "600", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#FiringRateAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "firing rate analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "FiringRateAnalysis" + }, + "subClasses" : [ "149", "154", "158", "163" ], + "comment" : { + "en" : "An analysis step used to compute a measure quantifying the firing rate of one or more neurons. The firing rate is the number of action potential (spikes) that a neuron fires per time unit and is defined with a unit of frequency (e.g., Hz or spikes/s)." + }, + "id" : "150", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeSPIKEDistance", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Kreuz2012_1457", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute SPIKE distance", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeSPIKEDistance" + }, + "comment" : { + "en" : "A time-scale independent spike train distance analysis that computes the SPIKE-distance, described in Kreuz et al. (2012). For the computation, the discrete sequence of spike times is transformed in a continuous temporal profile with one value per sample point. The values at each time point are derived from the differences in the spike times of the two input spike trains. Compared to the ISI-distance, the SPIKE-distance is more sensitive to spike timing." + }, + "id" : "427", + "superClasses" : [ "288" ] + }, { + "iri" : "http://purl.org/neao/steps#GenerateNonStationaryPoissonProcess", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "generate non-stationary Poisson process", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "GenerateNonStationaryPoissonProcess" + }, + "comment" : { + "en" : "A random spike times generation that uses a Poisson probability distribution to produce spike trains where the firing rate varies over time. A dead time can be specified as parameter (i.e., an interval where no spikes can occur, which is analogous to the neuronal refractory period)." + }, + "id" : "17", + "superClasses" : [ "8" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeRegularizedCovariance", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute regularized covariance", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeRegularizedCovariance" + }, + "comment" : { + "en" : "A covariance analysis where the computation of the covariance values incorporates regularization techniques to improve the numerical stability, especially if the number of samples is small." + }, + "id" : "171", + "superClasses" : [ "85" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeCurrentSourceDensityICSD", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Leski2011_401", + "type" : "iri" + }, { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Pettersen2006_116", + "type" : "iri" + }, { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Leski2007_207", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute current source density (inverse method)", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute iCSD", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeCurrentSourceDensityICSD" + }, + "comment" : { + "en" : "A current source density (CSD) analysis that uses the inverse current source density (iCSD) estimation method described by Pettersen et al. (2006). The iCSD is based on the inversion of the electrostatic forward solution and can be applied to data obtained from electrodes with multiple configurations. The method can handle cases with spatially confined cortical activity and spatially varying extracellular conductivity.\n \nThree options for CSD estimation using the iCSD exist. The CSD is assumed to have cylindrical symmetry and follows one of three possible assumptions:\n1. is localized in infinitely thin discs;\n2. is step-wise constant;\n3. is continuous and smoothly varying (using cubic splines) in the vertical direction." + }, + "id" : "530", + "superClasses" : [ "246" ] + }, { + "iri" : "http://purl.org/neao/steps#SpectralAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "spectral analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "SpectralAnalysis" + }, + "subClasses" : [ "169", "173", "146", "131", "136" ], + "comment" : { + "en" : "An analysis step that computes measures describing the input data with respect to its frequency contents." + }, + "id" : "132", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplyNotchFilter", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply notch filter", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplyNotchFilter" + }, + "comment" : { + "en" : "An infinite impulse response filtering that uses a filter designed to attenuate or eliminate a narrow band of frequencies in the input data (stopband) while allowing other frequencies to pass through relatively unaffected." + }, + "id" : "393", + "superClasses" : [ "283" ] + }, { + "iri" : "http://purl.org/neao/data#SpikeWaveformWidth", + "baseIri" : "http://purl.org/neao/data", + "instances" : 0, + "label" : { + "IRI-based" : "SpikeWaveformWidth" + }, + "attributes" : [ "external" ], + "id" : "698" + }, { + "iri" : "http://purl.org/neao/steps#ApplyZscoreTransform", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply z-score transform", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "apply standardization", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplyZscoreTransform" + }, + "comment" : { + "en" : "A data normalization that transforms the values of the input data to have zero mean and unit variance." + }, + "id" : "663", + "superClasses" : [ "109" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplySpikeExtractionFromTimeSeries", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply spike extraction from time series", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplySpikeExtractionFromTimeSeries" + }, + "comment" : { + "en" : "A data transformation that obtains a series of spike times (i.e., a spike train) from an input time series (e.g., voltages recorded from an electrode). 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Given the cluster matrix (CMAT), the identity of the neurons present in each bin of the repeated sequence in the identified diagonal structures is extracted (considering the input spike trains for the computation of the intersection matrix). The output of this substep is the final description of the ASSET pattern for each diagonal structure in the CMAT." + }, + "id" : "54", + "superClasses" : [ "55" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeStockwellTransform", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Stockwell1996_998", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute Stockwell transform", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "compute S transform", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeStockwellTransform" + }, + "comment" : { + "en" : "A time-frequency analysis that computes the Stockwell transform (S transform) of the input time series. 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The computation is computationally expensive, although fast algorithms are available." + }, + "id" : "315", + "superClasses" : [ "131" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeCoherenceMultitaper", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Thomson1982_1055", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute coherence (multitaper method)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeCoherenceMultitaper" + }, + "comment" : { + "en" : "A coherence analysis where the coherence value between the two inputs is computed using cross and auto power spectral densities obtained using a multitaper approach according to Thomson (1982)." + }, + "id" : "468", + "superClasses" : [ "417" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeCrossPowerSpectralDensityMultitaper", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Thomson1982_1055", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute cross power spectral density (multitaper method)", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute CPSD (multitaper method)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeCrossPowerSpectralDensityMultitaper" + }, + "comment" : { + "en" : "A cross power spectral density (CPSD) analysis that uses a multitaper approach to compute the CPSD, according to Thomson (1982). The multitaper method uses discrete prolate spheroidal functions (DPSS, also known as Slepian sequences) as tapers applied to the inputs. For the computation, a CPSD using the periodogram method is obtained for each pair of tapered signals. The DPSS functions are orthogonal, and therefore applying multiple DPSS tapers result in independent estimates of the CPSD. The final CPSD is obtained by averaging the CPSDs across all tapers. The multitaper method reduces variance and bias in the CPSD, and has a high frequency resolution. However, it is computationally expensive. The number of tapers used is passed as parameter, or estimated from the desired resolution." + }, + "id" : "478", + "superClasses" : [ "145" ] + }, { + "iri" : "http://purl.org/neao/steps#WaveletTransformAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Farge1992_395", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "wavelet transform analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "WaveletTransformAnalysis" + }, + "subClasses" : [ "141", "79" ], + "comment" : { + "en" : "A time-frequency analysis that uses wavelets to obtain the time-frequency representation of the time series input. The wavelet is a rapidly decaying oscillation. 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This method relies on correlations between the instantaneous amplitudes of cross-region input signals (power envelopes). The instantaneous amplitudes of the two input time series are orthogonalized aiming to remove spurious correlations of signal power (e.g., due to limited spatial resolution of electrophysiological measures)." + }, + "id" : "300", + "superClasses" : [ "301" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeNoiseCovariance", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute noise covariance", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeNoiseCovariance" + }, + "comment" : { + "en" : "A covariance analysis that computes the noise covariance, i.e., how much two noise signals vary together. The noise data inputs can be non-subject recordings (e.g., recordings from the empty experimental room) or are obtained from periods without stimulation or meaningful experimental manipulations (e.g., prestimulus intervals). 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It uses an MVAR (multivariate autoregressive model) to obtain the coefficients used for the computation of the spectral transfer matrix needed for GC estimation according to the frequency domain GC formulation by Geweke (1982)." + }, + "id" : "352", + "superClasses" : [ "10" ] + }, { + "iri" : "http://purl.org/neao/steps#DirectedAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "directed analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "DirectedAnalysis" + }, + "comment" : { + "en" : "An analysis step where the output provides information on the direction of influence in the relationships among the inputs (e.g., in the cross-correlation histogram, it is possible to analyze the timing of the spikes of the first input spike train with respect to the timing of the spikes of the second input spike train, i.e., whether they likely occur before or after)." + }, + "id" : "570", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplyFixedKernelSmoothing", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply fixed kernel smoothing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplyFixedKernelSmoothing" + }, + "comment" : { + "en" : "A kernel smoothing that uses a fixed-width kernel. 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"label" + } ] + }, + "comment" : { + "en" : "The analysis purpose of estimating functional connectivity." + }, + "labels" : { + "IRI-based" : "FunctionalConnectivityPurpose" + } + }, { + "iri" : "http://purl.org/neao/steps#DataSmoothingPurpose", + "baseIri" : "http://purl.org/neao/steps", + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "data smoothing purpose", + "type" : "label" + } ] + }, + "comment" : { + "en" : "The analysis purpose of smoothing the data." + }, + "labels" : { + "IRI-based" : "DataSmoothingPurpose" + } + } ], + "comment" : { + "en" : "Analysis purpose refers to the specific objective or goal that an analysis is intended to achieve. It outlines what the analysis step aims to discover, understand, or demonstrate. This class is intended for grouping steps that perform analyses with similar goals/outputs but with distinct methodological or algorithmic approaches. It is used as a normalization class via the hasPurpose object property." + }, + "id" : "725" + }, { + "iri" : "http://purl.org/neao/steps#ApplyLocalRegressionAndLikelihoodSmoothing", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Loader2006", + "type" : "iri" + }, { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Bokil2010_146", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply local regression and likelihood smoothing", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplyLocalRegressionAndLikelihoodSmoothing" + }, + "comment" : { + "en" : "A data smoothing that estimates a low-order polynomial in a local neighborhood (window) of any value in the input data. Polynomial coefficients are estimated using the least mean squares method. Contrary to kernel smoothing methods, this is a non-parametric approach and has reduced bias at the boundaries of the input data." + }, + "id" : "328", + "superClasses" : [ "95" ] + }, { + "iri" : "http://purl.org/neao/steps#CovarianceAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "covariance analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "CovarianceAnalysis" + }, + "subClasses" : [ "85", "91" ], + "comment" : { + "en" : "An analysis step used to compute a measure of covariance from two inputs. The covariance indicates the extent to which the two inputs change together. If the greater values of one variable mainly correspond with the greater values of the other variable, and the same applies to the lesser values, then the covariance is positive. Conversely, if greater values of one variable mainly correspond to the lesser values of the other variable, then the covariance is negative." + }, + "id" : "86", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeCrossPowerSpectralDensityMorletWavelet", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute cross power spectral density (Morlet wavelet method)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeCrossPowerSpectralDensityMorletWavelet" + }, + "comment" : { + "en" : "A cross power spectral density analysis that uses the Morlet wavelet transform to obtain the frequency information of the two inputs used to compute the cross power spectral density." + }, + "id" : "480", + "superClasses" : [ "145" ] + }, { + "iri" : "http://purl.org/neao/steps#SpikeTrainGeneration", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "spike train generation", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "SpikeTrainGeneration" + }, + "subClasses" : [ "8", "102" ], + "comment" : { + "en" : "A data generation that produces one or more artificial spike trains using distinct statistical procedures to determine the spike times." + }, + "id" : "97", + "superClasses" : [ "122" ] + }, { + "iri" : "http://purl.org/neao/steps#ASSETAnalysisSubstep", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Torre2016_e1004939", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "ASSET analysis substep", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ASSETAnalysisSubstep" + }, + "subClasses" : [ "106", "111", "54", "59", "64", "72" ], + "comment" : { + "en" : "An analysis step that is an individual part of the ASSET analysis method to identify neuronal activity patterns in spike train data." + }, + "id" : "55", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeASSETMaskMatrix", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Torre2016_e1004939", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute ASSET mask matrix", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeASSETMaskMatrix" + }, + "comment" : { + "en" : "ASSET analysis substep that computes the mask matrix (MMAT). The parameters are the threshold values that are used to determine if the entries in the probability matrix (PMAT) and joint probability matrix (JMAT) are significant. Entry significance in either matrix is defined as a probability value greater than the provided threshold value. Significant entries in both probability and joint probability matrices are defined as 1 in the mask matrix." + }, + "id" : "111", + "superClasses" : [ "55" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeCoherency", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute coherency", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "compute complex coherency", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeCoherency" + }, + "comment" : { + "en" : "A coherency analysis that computes the coherency for two inputs. It is computed from the complex-valued cross power spectral density obtained for the two inputs normalized by the square root of the product of their power spectral densities (i.e., auto spectral densities). For each frequency, the magnitude of the complex-valued coherency describes the strength of the association and the angle describes the phase lag between the two inputs. If the inputs contain multi-epoch data (e.g., multiple trial repetitions), the cross and auto spectral densities are averaged across epochs." + }, + "id" : "442", + "superClasses" : [ "169" ] + }, { + "iri" : "http://purl.org/neao/steps#RandomSpikeTimesGeneration", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "random spike times generation", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "RandomSpikeTimesGeneration" + }, + "subClasses" : [ "7", "17", "23", "28", "33", "38" ], + "comment" : { + "en" : "A spike train generation where the output spike trains will have random spike times, taken from a specific probability distribution. The generation process can produce spike trains where the firing rate is constant (stationary) or varies (non-stationary) over time." + }, + "id" : "8", + "superClasses" : [ "97" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplyTrialExtraction", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply trial extraction", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplyTrialExtraction" + }, + "comment" : { + "en" : "A data transformation that extracts trial segments from an input data entity storing a longer and continuous data stream. A trial is a single instance of a repeated experimental procedure. For example, during an electrophysiology experiment, a visual stimulus might be presented several times, with neural activity recorded each time. Each presentation of the stimulus defines a trial. Since the data is recorded continuously, this data transformation identifies and isolates the segments of data corresponding to each individual stimulus presentation, returning them as separate data entities." + }, + "id" : "41", + "superClasses" : [ "5" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeConfidenceIntervalJackknife", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute confidence interval (jackknife resampling)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeConfidenceIntervalJackknife" + }, + "comment" : { + "en" : "A confidence interval resampling analysis that computes the confidence interval using jackknife techniques. It involves systematically leaving out one observation at a time from the input (sample) set and calculating the statistic of interest on each of these \"leave-one-out\" samples. The confidence interval is computed based on statistics obtained from those jackknife samples. Jackknife is useful for small samples or when the data do not meet the assumptions of traditional parametric (non-resampling) methods." + }, + "id" : "194", + "superClasses" : [ "119" ] + }, { + "iri" : "http://purl.org/neao/steps#FiniteImpulseResponseFiltering", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "finite impulse response filtering", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "FIR filtering", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "FiniteImpulseResponseFiltering" + }, + "subClasses" : [ "449", "452", "457" ], + "comment" : { + "en" : "A digital filtering that uses a filter whose impulse response (i.e., the response of the filter to a brief input impulse) decays to zero after a finite amount of time. Therefore, the output of the filter depends on a finite number of past samples. The finite impulse response (FIR) filters are stable and can be designed such that they do not distort the phase of the signal. However, they have a higher computational cost." + }, + "id" : "278", + "superClasses" : [ "57" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeAngularMeanSpikePhases", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Vinck2012_53", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute angular mean of spike phases", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeAngularMeanSpikePhases" + }, + "comment" : { + "en" : "A phase analysis that computes the angle obtained from averaging the phases of an input signal at the time points where spikes occurred. For the computation, the phases are represented as vectors in the unit circle, the mean phase vector is computed, and the angle is extracted." + }, + "id" : "386", + "superClasses" : [ "382" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputePairwisePhaseConsistency", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Vinck2010_112", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute pairwise phase consistency", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute PPC", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputePairwisePhaseConsistency" + }, + "comment" : { + "en" : "A phase analysis that computes the pairwise phase consistency (PPC) measure according to Vinck et al. (2010). The PPC quantifies the distribution of phase differences across the inputs, but is less biased by the number of observations in comparison to the phase locking value (PLV). For the computation, the phase difference (angular distance) is obtained for all pairs of observations in the input (that can be represented as vectors in the unit circle, where the angle is the relative phase). The cosine of the angular distance (an estimate of the dot product of the vectors corresponding to each element in a pair) is computed for every pair, and the PPC estimate is obtained from the average of all pairwise dot products. With phase synchronization, the distribution of the pairwise dot products is centered around an average value, while without synchronization it will be distributed across the unit circle. The PPC provides an unbiased estimate of the squared PLV." + }, + "id" : "387", + "superClasses" : [ "382" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeCoherence", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute coherence", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeCoherence" + }, + "subClasses" : [ "462", "468", "416", "422" ], + "comment" : { + "en" : "A coherence analysis that computes the coherence value between two inputs. It is obtained from the magnitude of the complex-valued cross power spectral density obtained for the two inputs normalized by their power spectral density (i.e., auto spectral density). Several frequency decomposition approaches can be used to obtain the cross and auto power spectral densities from the inputs. The computation can return the magnitude coherence (i.e., by taking the absolute value of the cross power spectral density and normalizing by the square root of the product of the two auto spectral densities) or the magnitude squared coherence (i.e., by computing the squared magnitude of the cross power spectral density and normalizing by the product of the two auto spectral densities)." + }, + "id" : "417", + "superClasses" : [ "136" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeTransferEntropy", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Schreiber2000_461", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute transfer entropy", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute TE", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeTransferEntropy" + }, + "comment" : { + "en" : "A functional connectivity analysis that computes a measure of transfer entropy (TE) between two input time series. TE measures the directional transfer of information between the time series. It extends Granger causality, and is able to detect non-linear forms of interaction." + }, + "id" : "175", + "superClasses" : [ "77" ] + }, { + "iri" : "http://purl.org/neao/steps#TimeScaleIndependentSpikeTrainDistanceAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "time-scale independent spike train distance analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "TimeScaleIndependentSpikeTrainDistanceAnalysis" + }, + "subClasses" : [ "427", "431", "330" ], + "comment" : { + "en" : "A spike train dissimilarity analysis that computes a spike train distance that does not depend on a time scale parameter and that are time-scale adaptive. They can be used in scenarios where there are no previous knowledge of the relevant time scales in the input spike trains." + }, + "id" : "288", + "superClasses" : [ "289" ] + }, { + "iri" : "http://purl.org/neao/steps#PairwiseGrangerCausalityAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "pairwise Granger causality analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "PairwiseGrangerCausalityAnalysis" + }, + "subClasses" : [ "10", "395" ], + "comment" : { + "en" : "A Granger causality (GC) analysis that computes a measure of GC between two inputs." + }, + "id" : "264", + "superClasses" : [ "139" ] + }, { + "iri" : "http://purl.org/neao/steps#FrequencyDomainTransformation", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "frequency domain transformation", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "FrequencyDomainTransformation" + }, + "subClasses" : [ "400" ], + "comment" : { + "en" : "A data transformation that converts a time series input from the time to the frequency domain, i.e., reveal the different frequency components that make up the original signal." + }, + "id" : "70", + "superClasses" : [ "5" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplyWindowedSincFilter", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply windowed-sinc filter", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplyWindowedSincFilter" + }, + "comment" : { + "en" : "A finite impulse response filtering that employs the convolution with a sinc function kernel multiplied by a window function (e.g., Blackman or Hamming). The kernel is obtained by evaluating the sinc function for the cutoff frequencies specified as parameters, followed by truncation of the filter skirt, and applying the window to reduce the artifacts introduced from the truncation. The windowed-sinc filter is stable and very efficient to separate one band of frequencies from another." + }, + "id" : "457", + "superClasses" : [ "278" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputePhaseLockingValue", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Lachaux1999_194", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute phase locking value", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute PLV", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputePhaseLockingValue" + }, + "comment" : { + "en" : "A phase locking value (PLV) analysis that computes the PLV value as originally described by Lachaux et al. (1999). The input data is a set of pairs of time series (e.g., the trial-by-trial local field potential recorded from two different electrodes). For each time series pair, the instantaneous phase is obtained (e.g., using the Hilbert transform or wavelet decomposition), and the phase difference for each time point is obtained. The PLV value is computed by averaging the complex phase differences across all pairs, obtaining one PLV value per time point. The PLV ranges from 0 to 1. A PLV of 1 indicates perfect phase locking, meaning the phase difference between the two time series is constant over time. A PLV of 0 indicates no phase locking, meaning the phase difference is randomly distributed over time." + }, + "id" : "474", + "superClasses" : [ "385" ] + }, { + "iri" : "http://purl.org/neao/data#SpikeWaveform", + "baseIri" : "http://purl.org/neao/data", + "instances" : 0, + "label" : { + "IRI-based" : "SpikeWaveform" + }, + "attributes" : [ "external" ], + "id" : "742" + }, { + "iri" : "http://purl.org/neao/steps#ComputeSpectrogramMorletWavelet", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute spectrogram (Morlet wavelet method)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeSpectrogramMorletWavelet" + }, + "comment" : { + "en" : "A spectrogram analysis that uses the Morlet wavelet transform on the input to obtain the time-frequency information used to build the spectrogram." + }, + "id" : "281", + "superClasses" : [ "276" ] + }, { + "iri" : "http://purl.org/neao/steps#ExecuteNon3dSPADEAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Quaglio2017_41", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "execute non-3d-SPADE analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ExecuteNon3dSPADEAnalysis" + }, + "comment" : { + "en" : "A SPADE analysis that uses the SPADE implementation as defined in Quaglio et al. (2017). This is the extension of SPADE to consider spatio-temporal patterns (i.e., patterns not restricted to synchronous spiking). In the non-3d SPADE analysis, the pattern signature used for statistical testing considers only the size and number of occurrences of a pattern." + }, + "id" : "566", + "superClasses" : [ "224" ] + }, { + "iri" : "http://purl.org/neao/steps#StatisticalAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "statistical analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "StatisticalAnalysis" + }, + "subClasses" : [ "188", "47", "179" ], + "comment" : { + "en" : "A generic analysis step that computes measures to summarize and make inferences about the data input. These include measures of central tendency, dispersion and confidence intervals. The subclasses represent analysis steps that are usually used for aggregation of data and description of samples (e.g., compute the mean and standard deviation of the output of trial-by-trial analyses or across subjects). All analysis steps for specific applications related to the analysis of neuroelectrophysiology data itself (e.g., analyzing interspike interval variability) are covered by separate, independent classes." + }, + "id" : "180", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeCubicAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Staude2010_327", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute CuBIC analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeCubicAnalysis" + }, + "comment" : { + "en" : "A spike train synchrony analysis that uses the Cumulant Based Inference of higher-order Correlation (CuBIC) test described in Staude et al. (2010). CuBIC is a statistical method to detect the presence of higher order correlations in parallel spike trains from a neuronal population (i.e., correlations among three or more neurons). It is based on the analysis of the cumulants of the population spike count. The test takes a population histogram as input data (i.e., a spike train time histogram computed across spike trains with the activity of distinct neurons). A null hypothesis that the third cumulant of the data is less than or equal to the maximized third cumulant for a correlation order is iteratively tested (with increasing orders of correlation). The output is the minimum correlation order necessary to explain the value of the third cumulant calculated from the population spike count, together with the p-values of the hypothesis tests performed." + }, + "id" : "213", + "superClasses" : [ "208" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplyHilbertTransform", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply Hilbert transform", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplyHilbertTransform" + }, + "comment" : { + "en" : "A data transformation that applies the Hilbert transform to a real-valued time series. The Hilbert transform shifts the phase of each frequency component of the signal by 90 degrees: positive frequencies are shifted by -90 degrees, and negative frequencies are shifted by +90 degrees. This can be used to construct the analytic signal." + }, + "id" : "114", + "superClasses" : [ "5" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeInterspikeIntervalHistogram", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute interspike interval histogram", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute ISIH", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeInterspikeIntervalHistogram" + }, + "comment" : { + "en" : "An interspike interval analysis that computes the histogram of interspike intervals. For the computation, a time interval with fixed duration starting from zero is discretized into smaller intervals (bins). The count of input interspike intervals whose values fall into each bin is obtained. Therefore, the output contains a representation of the distribution of the interspike intervals in the input." + }, + "id" : "366", + "superClasses" : [ "360" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeCrossPowerSpectralDensityWelch", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Welch1967_70", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute cross power spectral density (Welch method)", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute CPSD (Welch method)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeCrossPowerSpectralDensityWelch" + }, + "comment" : { + "en" : "A cross power spectral density (CPSD) analysis that uses the method defined by Welch (1967). For the computation, the two inputs are divided into several overlapping segments (length and overlap passed as parameters, or computed for the desired frequency resolution based on the input length and sampling frequency). A window function (e.g., Hann) is applied to each segment, and the cross power spectral density using the periodogram method is computed. The final CPSD is obtained by averaging all the periodograms with the individual CPSDs." + }, + "id" : "479", + "superClasses" : [ "145" ] + }, { + "iri" : "http://purl.org/neao/steps#GenerateJointISIDitheringSurrogate", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Louis2010_127", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "generate joint interspike interval dithering surrogate", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "generate JISI-D surrogate", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "GenerateJointISIDitheringSurrogate" + }, + "comment" : { + "en" : "A spike train surrogate generation step where spikes from adjacent interspike intervals (ISIs) are dithered according to the joint-ISI (JISI) probability distribution. The distribution is obtained from the input spike train by computing the JISI histogram (i.e., a two-dimensional histogram that shows the frequency of ISIs with a given duration that are immediately followed by intervals with another duration). Due to non-stationarities in the input spike train and/or its limited duration, it is difficult to accurately estimate the underlying JISI probability distribution. Therefore, a 2D-Gaussian smoothing is applied to the JISI histogram (with a variance determined by parameter). Dithering a spike according to this (smoothed) two-dimensional histogram involves moving the spike along the anti-diagonal of the JISI distribution. The dithering time is defined by a parameter." + }, + "id" : "379", + "superClasses" : [ "121" ] + }, { + "iri" : "http://purl.org/neao/steps#PowerSpectralDensityAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "power spectral density analysis", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "auto spectral density analysis", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "PSD analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "PowerSpectralDensityAnalysis" + }, + "subClasses" : [ "362", "368", "373", "331" ], + "comment" : { + "en" : "A spectral density analysis that computes the power spectral density of an input, i.e., the distribution of power across the different frequency components of the input signal per unit frequency. It is equivalent to the Fourier transform of the autocorrelation function of the input signal. The computed power spectral density values can be corrected depending on the analysis returning the two-sided (i.e., with negative frequencies) or one-sided (i.e., positive frequencies only) PSD. The PSD is often referred to as spectrum." + }, + "id" : "192", + "superClasses" : [ "146" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeMorletWaveletTransformTallonBaudry", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#TallonBaudry1997_722", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute Morlet wavelet transform (Tallon-Baudry method)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeMorletWaveletTransformTallonBaudry" + }, + "comment" : { + "en" : "A wavelet transform analysis using the Morlet wavelet based on the methods described in Tallon-Baudry et al. (1997). The ratio of the central frequency to the spectral bandwidth is 7, with central frequencies ranging from 20 to 100 Hz in 1 Hz steps. This resulted in varying time/frequency resolution across the spectrum: time resolution increases with frequency, while frequency resolution decreases." + }, + "id" : "508", + "superClasses" : [ "79" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeAutocorrelationFunction", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute autocorrelation function", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute ACF", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeAutocorrelationFunction" + }, + "comment" : { + "en" : "An autocorrelation analysis that computes the estimator for the autocorrelation function, i.e. the autocorrelation values of a time series input for a number of lags. The autocorrelation function shows temporal dependencies and repetitive patterns within the input data. The value of the autocorrelation at a specific lag shows how similar the values in the time series input are when separated by a number of time units equal to that lag. The autocorrelation value of 0 indicates no correlation. The autocorrelation varies between 1 and -1 (positive and negative correlation, respectively)." + }, + "id" : "585", + "superClasses" : [ "303" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplySpikeWaveformInterpolation", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply spike waveform interpolation", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplySpikeWaveformInterpolation" + }, + "comment" : { + "en" : "A data transformation that estimates additional (unknown) values between sample points of a spike waveform input." + }, + "id" : "239", + "superClasses" : [ "21" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeInstantaneousFiringRateLocalRegression", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Bokil2010_146", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute instantaneous firing rate (local regression method)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeInstantaneousFiringRateLocalRegression" + }, + "comment" : { + "en" : "An instantaneous firing rate analysis that computes the instantaneous firing rate using local regression methods. The estimation procedure approximates the log of the firing rate using a low-order polynomial within a moving window (local neighborhood)." + }, + "id" : "516", + "superClasses" : [ "163" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeConfidenceIntervalNonResampling", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute confidence interval (non-resampling)", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeConfidenceIntervalNonResampling" + }, + "comment" : { + "en" : "A confidence interval statistical analysis that computes the confidence interval assuming a statistical distribution of the input data, and uses measures of central tendency and dispersion obtained from the data points in the input(s) (e.g., mean and standard error of the mean when assuming a normal distribution). The computation relies on theoretical distributions and established statistical formulas." + }, + "id" : "187", + "superClasses" : [ "188" ] + }, { + "iri" : "http://purl.org/neao/steps#TriggeredAverageAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "triggered average analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "TriggeredAverageAnalysis" + }, + "subClasses" : [ "334", "338" ], + "comment" : { + "en" : "An analysis step where a signal is averaged to obtain a value around a point in time representing an event of interest (i.e., a trigger). For each event time, a finite duration window of the input time series is selected around the event time. An average for each time point is then obtained across all windows." + }, + "id" : "335", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#FrequencyDomainPairwiseGrangerCausalityAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Geweke1982_304", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "frequency domain pairwise granger causality analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "FrequencyDomainPairwiseGrangerCausalityAnalysis" + }, + "subClasses" : [ "343", "347", "9", "352" ], + "comment" : { + "en" : "A pairwise Granger causality (GC) analysis that computes measures of GC between two inputs in the frequency domain. This is an extension of the GC concept in the time domain, and the measures of GC are obtained for the different frequency components of the inputs, according to Geweke (1982). The computation of the frequency-domain GC measures is based on two elements: the noise covariance matrix and the spectral transfer matrix. These can be estimated either with parametric or non-parametric methods. For the parametric estimation, an autoregressive model is fit and the Fourier transform of the autoregressive coefficients is used to obtain the spectral transfer matrix. For the non-parametric estimation, the cross-spectral density (CSD) matrix is obtained (using methods for CSD estimation such as multitapering or wavelet), and the CSD matrix is factorized to obtain the noise covariance and spectral transfer matrices." + }, + "id" : "10", + "superClasses" : [ "264" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeCorrectedImaginaryPhaseLockingValue", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "hasBibliographicReference" : [ { + "identifier" : "hasBibliographicReference", + "language" : "undefined", + "value" : "http://purl.org/neao/bibliography#Bruna2018_056011", + "type" : "iri" + } ], + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute corrected imaginary phase locking value", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute ciPLV", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeCorrectedImaginaryPhaseLockingValue" + }, + "comment" : { + "en" : "A phase locking value analysis that computes the corrected imaginary phase locking value (ciPLV), following the implementation from Bruña & Maestú (2018). It re-formulates the original phase locking value (PLV) for computational efficiency. The computation uses the imaginary part of the PLV, to make the metric insensitive to zero lag synchronizations (that can be the result of volume conduction)." + }, + "id" : "473", + "superClasses" : [ "385" ] + }, { + "iri" : "http://purl.org/neao/steps#SpikeTrainTimeHistogramAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "spike train time histogram analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "SpikeTrainTimeHistogramAnalysis" + }, + "subClasses" : [ "324", "44", "314" ], + "comment" : { + "en" : "A firing rate analysis that computes histograms of spike train data over time. The time histogram is obtained by discretizing the duration of the spike train into distinct time intervals (bins), and obtaining the spike count inside each bin. \n\nThe histogram can show one of three different measures:\n\n* the spike count at each bin (across all spike trains);\n* the mean spike count per bin (spike count in the bin divided by the number of spike trains);\n* the firing rate (mean spike count in the bin divided by bin width)." + }, + "id" : "154", + "superClasses" : [ "150" ] + }, { + "iri" : "http://purl.org/neao/steps#ApplyDownsampling", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "apply downsampling", + "type" : "label" + } ], + "altLabel" : [ { + "identifier" : "altLabel", + "language" : "en", + "value" : "apply decimation", + "type" : "label" + }, { + "identifier" : "altLabel", + "language" : "en", + "value" : "apply downscaling", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ApplyDownsampling" + }, + "comment" : { + "en" : "A resampling that reduces the number of samples in the input data (i.e., reduces the sampling frequency). This is often accomplished after applying an anti-aliasing filter (i.e., to remove frequencies above half the value of the new sampling frequency)." + }, + "id" : "167", + "superClasses" : [ "161" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeVariance", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute variance", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeVariance" + }, + "comment" : { + "en" : "A dispersion statistical analysis that computes the variance, i.e., the average of the squared differences from the mean." + }, + "id" : "236", + "superClasses" : [ "47" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeCrossCorrelationFunction", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute cross-correlation function", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute CCF", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeCrossCorrelationFunction" + }, + "subClasses" : [ "116", "273" ], + "comment" : { + "en" : "A cross-correlation analysis that computes an estimate of the cross-correlation function, i.e. the cross-correlation values of two time series inputs for a number of lags. The cross-correlation function shows temporal dependencies of the first input series with respect to the second. The value of the cross-correlation at a specific lag shows how similar the values in the first input series are to values in the second input at time points separated by a number of time units equal to that lag. The cross-correlation value of 0 indicates no correlation. The cross-correlation varies between 1 and -1 (positive and negative correlation, respectively)." + }, + "id" : "117", + "superClasses" : [ "143" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeSpikeTriggeredLFPAverage", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute spike-triggered local field potential average", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute STA", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeSpikeTriggeredLFPAverage" + }, + "comment" : { + "en" : "A triggered average analysis that uses spike times as triggers to average the local field potential (LFP) signal. The LFP is the low-frequency component of the potential recorded within a specific region of the brain using extracellular electrodes. The output of the method will provide an estimation of the average LFP voltage around each spike, i.e., the spike-triggered average of the LFP signal." + }, + "id" : "559", + "superClasses" : [ "338" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeMedian", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute median", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeMedian" + }, + "comment" : { + "en" : "A central tendency statistical analysis that computes the median of the input data. The median is the middle value when data points are arranged in ascending order (i.e., it divides the data points in two equal halves, with 50% of the data points below it and 50% above it). If there is an even number of data points, the median is the average of the two middle values." + }, + "id" : "182", + "superClasses" : [ "179" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeSpikeTriggeredPhase", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute spike-triggered phase", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeSpikeTriggeredPhase" + }, + "comment" : { + "en" : "A phase analysis that computes the phase angle values of an analytic signal input (or from the analytic signal obtained from an input time series) at the time points where spikes occurred. The spike times are defined in a spike train input. The output is an array with the phase angle at each spike time in the input spike train (spike-triggered phases)." + }, + "id" : "384", + "superClasses" : [ "382" ] + }, { + "iri" : "http://purl.org/neao/steps#ComputeInterspikeIntervals", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "compute interspike intervals", + "type" : "label" + } ], + "abbreviation" : [ { + "identifier" : "abbreviation", + "language" : "en", + "value" : "compute ISIs", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "ComputeInterspikeIntervals" + }, + "comment" : { + "en" : "An interspike interval analysis that computes the intervals between successive spikes in a spike train (interspike intervals; ISIs)." + }, + "id" : "371", + "superClasses" : [ "360" ] + }, { + "iri" : "http://purl.org/neao/steps#SpikeFieldCouplingAnalysis", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "spike-field coupling analysis", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "SpikeFieldCouplingAnalysis" + }, + "comment" : { + "en" : "An analysis step that computes interactions between the spiking activity of neurons (individual or population) and the local field potential (LFP)." + }, + "id" : "357", + "superClasses" : [ "123" ] + }, { + "iri" : "http://purl.org/neao/steps#DigitalFiltering", + "baseIri" : "http://purl.org/neao/steps", + "instances" : 0, + "annotations" : { + "prefLabel" : [ { + "identifier" : "prefLabel", + "language" : "en", + "value" : "digital filtering", + "type" : "label" + } ] + }, + "label" : { + "IRI-based" : "DigitalFiltering" + }, + "subClasses" : [ "278", "283" ], + "comment" : { + "en" : "A data transformation that processes digital signal inputs (i.e., sampled time series) to attenuate or amplify specific frequency components. 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100644 index 0000000..d82eddd --- /dev/null +++ b/doc/releases/0.1.0/steps/webvowl/js/webvowl.app.js @@ -0,0 +1,9457 @@ +webvowl.app = +/******/ (function(modules) { // webpackBootstrap +/******/ // The module cache +/******/ var installedModules = {}; + +/******/ // The require function +/******/ function __webpack_require__(moduleId) { + +/******/ // Check if module is in cache +/******/ if(installedModules[moduleId]) +/******/ return installedModules[moduleId].exports; + +/******/ // Create a new module (and put it into the cache) +/******/ var module = installedModules[moduleId] = { +/******/ exports: {}, +/******/ id: moduleId, +/******/ loaded: false +/******/ }; + +/******/ // Execute the module function +/******/ modules[moduleId].call(module.exports, module, module.exports, __webpack_require__); + +/******/ // Flag the module as loaded +/******/ module.loaded = true; + +/******/ // Return the exports of the module +/******/ return module.exports; +/******/ } + + +/******/ // expose the modules object (__webpack_modules__) +/******/ __webpack_require__.m = modules; + +/******/ // expose the module cache +/******/ __webpack_require__.c = installedModules; + +/******/ // __webpack_public_path__ +/******/ __webpack_require__.p = ""; + +/******/ // Load entry module and return exports +/******/ return __webpack_require__(0); +/******/ }) +/************************************************************************/ +/******/ ({ + +/***/ 0: +/***/ (function(module, exports, __webpack_require__) { + + __webpack_require__(319); + __webpack_require__(321); + + module.exports = __webpack_require__(322); + + +/***/ }), + +/***/ 6: +/***/ (function(module, exports) { + + module.exports = d3; + +/***/ }), + +/***/ 91: +/***/ (function(module, exports, __webpack_require__) { + + var Symbol = __webpack_require__(92), + getRawTag = __webpack_require__(95), + objectToString = __webpack_require__(96); + + /** `Object#toString` result references. */ + var nullTag = '[object Null]', + undefinedTag = '[object Undefined]'; + + /** Built-in value references. */ + var symToStringTag = Symbol ? Symbol.toStringTag : undefined; + + /** + * The base implementation of `getTag` without fallbacks for buggy environments. + * + * @private + * @param {*} value The value to query. + * @returns {string} Returns the `toStringTag`. + */ + function baseGetTag(value) { + if (value == null) { + return value === undefined ? undefinedTag : nullTag; + } + return (symToStringTag && symToStringTag in Object(value)) + ? getRawTag(value) + : objectToString(value); + } + + module.exports = baseGetTag; + + +/***/ }), + +/***/ 92: +/***/ (function(module, exports, __webpack_require__) { + + var root = __webpack_require__(93); + + /** Built-in value references. */ + var Symbol = root.Symbol; + + module.exports = Symbol; + + +/***/ }), + +/***/ 93: +/***/ (function(module, exports, __webpack_require__) { + + var freeGlobal = __webpack_require__(94); + + /** Detect free variable `self`. */ + var freeSelf = typeof self == 'object' && self && self.Object === Object && self; + + /** Used as a reference to the global object. */ + var root = freeGlobal || freeSelf || Function('return this')(); + + module.exports = root; + + +/***/ }), + +/***/ 94: +/***/ (function(module, exports) { + + /* WEBPACK VAR INJECTION */(function(global) {/** Detect free variable `global` from Node.js. */ + var freeGlobal = typeof global == 'object' && global && global.Object === Object && global; + + module.exports = freeGlobal; + + /* WEBPACK VAR INJECTION */}.call(exports, (function() { return this; }()))) + +/***/ }), + +/***/ 95: +/***/ (function(module, exports, __webpack_require__) { + + var Symbol = __webpack_require__(92); + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * Used to resolve the + * [`toStringTag`](http://ecma-international.org/ecma-262/7.0/#sec-object.prototype.tostring) + * of values. + */ + var nativeObjectToString = objectProto.toString; + + /** Built-in value references. */ + var symToStringTag = Symbol ? Symbol.toStringTag : undefined; + + /** + * A specialized version of `baseGetTag` which ignores `Symbol.toStringTag` values. + * + * @private + * @param {*} value The value to query. + * @returns {string} Returns the raw `toStringTag`. + */ + function getRawTag(value) { + var isOwn = hasOwnProperty.call(value, symToStringTag), + tag = value[symToStringTag]; + + try { + value[symToStringTag] = undefined; + var unmasked = true; + } catch (e) {} + + var result = nativeObjectToString.call(value); + if (unmasked) { + if (isOwn) { + value[symToStringTag] = tag; + } else { + delete value[symToStringTag]; + } + } + return result; + } + + module.exports = getRawTag; + + +/***/ }), + +/***/ 96: +/***/ (function(module, exports) { + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** + * Used to resolve the + * [`toStringTag`](http://ecma-international.org/ecma-262/7.0/#sec-object.prototype.tostring) + * of values. + */ + var nativeObjectToString = objectProto.toString; + + /** + * Converts `value` to a string using `Object.prototype.toString`. + * + * @private + * @param {*} value The value to convert. + * @returns {string} Returns the converted string. + */ + function objectToString(value) { + return nativeObjectToString.call(value); + } + + module.exports = objectToString; + + +/***/ }), + +/***/ 103: +/***/ (function(module, exports, __webpack_require__) { + + var baseGetTag = __webpack_require__(91), + isObjectLike = __webpack_require__(104); + + /** `Object#toString` result references. */ + var symbolTag = '[object Symbol]'; + + /** + * Checks if `value` is classified as a `Symbol` primitive or object. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a symbol, else `false`. + * @example + * + * _.isSymbol(Symbol.iterator); + * // => true + * + * _.isSymbol('abc'); + * // => false + */ + function isSymbol(value) { + return typeof value == 'symbol' || + (isObjectLike(value) && baseGetTag(value) == symbolTag); + } + + module.exports = isSymbol; + + +/***/ }), + +/***/ 104: +/***/ (function(module, exports) { + + /** + * Checks if `value` is object-like. A value is object-like if it's not `null` + * and has a `typeof` result of "object". + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is object-like, else `false`. + * @example + * + * _.isObjectLike({}); + * // => true + * + * _.isObjectLike([1, 2, 3]); + * // => true + * + * _.isObjectLike(_.noop); + * // => false + * + * _.isObjectLike(null); + * // => false + */ + function isObjectLike(value) { + return value != null && typeof value == 'object'; + } + + module.exports = isObjectLike; + + +/***/ }), + +/***/ 112: +/***/ (function(module, exports) { + + /** + * Checks if `value` is classified as an `Array` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an array, else `false`. + * @example + * + * _.isArray([1, 2, 3]); + * // => true + * + * _.isArray(document.body.children); + * // => false + * + * _.isArray('abc'); + * // => false + * + * _.isArray(_.noop); + * // => false + */ + var isArray = Array.isArray; + + module.exports = isArray; + + +/***/ }), + +/***/ 154: +/***/ (function(module, exports) { + + /** + * A specialized version of `_.map` for arrays without support for iteratee + * shorthands. + * + * @private + * @param {Array} [array] The array to iterate over. + * @param {Function} iteratee The function invoked per iteration. + * @returns {Array} Returns the new mapped array. + */ + function arrayMap(array, iteratee) { + var index = -1, + length = array == null ? 0 : array.length, + result = Array(length); + + while (++index < length) { + result[index] = iteratee(array[index], index, array); + } + return result; + } + + module.exports = arrayMap; + + +/***/ }), + +/***/ 219: +/***/ (function(module, exports, __webpack_require__) { + + var baseToString = __webpack_require__(220); + + /** + * Converts `value` to a string. An empty string is returned for `null` + * and `undefined` values. The sign of `-0` is preserved. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to convert. + * @returns {string} Returns the converted string. + * @example + * + * _.toString(null); + * // => '' + * + * _.toString(-0); + * // => '-0' + * + * _.toString([1, 2, 3]); + * // => '1,2,3' + */ + function toString(value) { + return value == null ? '' : baseToString(value); + } + + module.exports = toString; + + +/***/ }), + +/***/ 220: +/***/ (function(module, exports, __webpack_require__) { + + var Symbol = __webpack_require__(92), + arrayMap = __webpack_require__(154), + isArray = __webpack_require__(112), + isSymbol = __webpack_require__(103); + + /** Used as references for various `Number` constants. */ + var INFINITY = 1 / 0; + + /** Used to convert symbols to primitives and strings. */ + var symbolProto = Symbol ? Symbol.prototype : undefined, + symbolToString = symbolProto ? symbolProto.toString : undefined; + + /** + * The base implementation of `_.toString` which doesn't convert nullish + * values to empty strings. + * + * @private + * @param {*} value The value to process. + * @returns {string} Returns the string. + */ + function baseToString(value) { + // Exit early for strings to avoid a performance hit in some environments. + if (typeof value == 'string') { + return value; + } + if (isArray(value)) { + // Recursively convert values (susceptible to call stack limits). + return arrayMap(value, baseToString) + ''; + } + if (isSymbol(value)) { + return symbolToString ? symbolToString.call(value) : ''; + } + var result = (value + ''); + return (result == '0' && (1 / value) == -INFINITY) ? '-0' : result; + } + + module.exports = baseToString; + + +/***/ }), + +/***/ 319: +/***/ (function(module, exports) { + + // removed by extract-text-webpack-plugin + +/***/ }), + +/***/ 321: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/* Taken from here: http://stackoverflow.com/a/17907562 */ + function getInternetExplorerVersion(){ + var ua, + re, + rv = -1; + + // check for edge + var isEdge = /(?:\b(MS)?IE\s+|\bTrident\/7\.0;.*\s+rv:|\bEdge\/)(\d+)/.test(navigator.userAgent); + if ( isEdge ) { + rv = parseInt("12"); + return rv; + } + + var isIE11 = /Trident.*rv[ :]*11\./.test(navigator.userAgent); + if ( isIE11 ) { + rv = parseInt("11"); + return rv; + } + if ( navigator.appName === "Microsoft Internet Explorer" ) { + ua = navigator.userAgent; + re = new RegExp("MSIE ([0-9]{1,}[\\.0-9]{0,})"); + if ( re.exec(ua) !== null ) { + rv = parseFloat(RegExp.$1); + } + } else if ( navigator.appName === "Netscape" ) { + ua = navigator.userAgent; + re = new RegExp("Trident/.*rv:([0-9]{1,}[\\.0-9]{0,})"); + if ( re.exec(ua) !== null ) { + rv = parseFloat(RegExp.$1); + } + } + return rv; + } + + function showBrowserWarningIfRequired(){ + var version = getInternetExplorerVersion(); + console.log("Browser Version =" + version); + if ( version > 0 && version <= 11 ) { + d3.select("#browserCheck").classed("hidden", false); + d3.select("#killWarning").classed("hidden", true); + d3.select("#optionsArea").classed("hidden", true); + d3.select("#logo").classed("hidden", true); + } + if ( version == 12 ) { + d3.select("#logo").classed("hidden", false); + d3.select("#browserCheck").classed("hidden", false); + // connect the button; + var pb_kill = d3.select("#killWarning"); + pb_kill.on("click", function (){ + console.log("hide the warning please"); + d3.select("#browserCheck").classed("hidden", true); + d3.select("#logo").style("padding", "10px"); + }); + } + else { + d3.select("#logo").classed("hidden", false); + d3.select("#browserCheck").classed("hidden", true); + } + + } + + module.exports = showBrowserWarningIfRequired; + showBrowserWarningIfRequired(); + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 322: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {String.prototype.replaceAll = function ( search, replacement ){ + var target = this; + return target.split(search).join(replacement); + }; + module.exports = function (){ + var newOntologyCounter = 1; + var app = {}, + graph = webvowl.graph(), + options = graph.graphOptions(), + languageTools = webvowl.util.languageTools(), + GRAPH_SELECTOR = "#graph", + // Modules for the webvowl app + exportMenu = __webpack_require__(323)(graph), + filterMenu = __webpack_require__(325)(graph), + gravityMenu = __webpack_require__(326)(graph), + modeMenu = __webpack_require__(327)(graph), + debugMenu = __webpack_require__(328)(graph), + ontologyMenu = __webpack_require__(329)(graph), + pauseMenu = __webpack_require__(333)(graph), + resetMenu = __webpack_require__(334)(graph), + searchMenu = __webpack_require__(335)(graph), + navigationMenu = __webpack_require__(336)(graph), + zoomSlider = __webpack_require__(337)(graph), + sidebar = __webpack_require__(338)(graph), + leftSidebar = __webpack_require__(339)(graph), + editSidebar = __webpack_require__(340)(graph), + configMenu = __webpack_require__(341)(graph), + loadingModule = __webpack_require__(342)(graph), + warningModule = __webpack_require__(343)(graph), + directInputMod = __webpack_require__(344)(graph), + + + // Graph modules + colorExternalsSwitch = webvowl.modules.colorExternalsSwitch(graph), + compactNotationSwitch = webvowl.modules.compactNotationSwitch(graph), + datatypeFilter = webvowl.modules.datatypeFilter(), + disjointFilter = webvowl.modules.disjointFilter(), + focuser = webvowl.modules.focuser(graph), + emptyLiteralFilter = webvowl.modules.emptyLiteralFilter(), + nodeDegreeFilter = webvowl.modules.nodeDegreeFilter(filterMenu), + nodeScalingSwitch = webvowl.modules.nodeScalingSwitch(graph), + objectPropertyFilter = webvowl.modules.objectPropertyFilter(), + pickAndPin = webvowl.modules.pickAndPin(), + selectionDetailDisplayer = webvowl.modules.selectionDetailsDisplayer(sidebar.updateSelectionInformation), + statistics = webvowl.modules.statistics(), + subclassFilter = webvowl.modules.subclassFilter(), + setOperatorFilter = webvowl.modules.setOperatorFilter(); + + + app.getOptions = function (){ + return webvowl.opts; + }; + app.getGraph = function (){ + return webvowl.gr; + }; + // app.afterInitializationCallback=undefined; + + + var executeFileDrop = false; + var wasMessageToShow = false; + var firstTime = false; + + function addFileDropEvents( selector ){ + var node = d3.select(selector); + + node.node().ondragover = function ( e ){ + e.preventDefault(); + + d3.select("#dragDropContainer").classed("hidden", false); + // get svg size + var w = graph.options().width(); + var h = graph.options().height(); + + // get event position; (using clientX and clientY); + var cx = e.clientX; + var cy = e.clientY; + + if ( firstTime === false ) { + var state = d3.select("#loading-info").classed("hidden"); + wasMessageToShow = !state; + firstTime = true; + d3.select("#loading-info").classed("hidden", true); // hide it so it does not conflict with drop event + var bb=d3.select("#drag_msg").node().getBoundingClientRect(); + var hs = bb.height; + var ws = bb.width; + + var icon_scale=Math.min(hs,ws); + icon_scale/=100; + + d3.select("#drag_icon_group").attr("transform", "translate ( " + 0.25 * ws + " " + 0.25 * hs + ")"); + d3.select("#drag_icon").attr("transform","matrix ("+icon_scale+",0,0,"+icon_scale+",0,0)"); + d3.select("#drag_icon_drop").attr("transform","matrix ("+icon_scale+",0,0,"+icon_scale+",0,0)"); + } + + + if ( (cx > 0.25 * w && cx < 0.75 * w) && (cy > 0.25 * h && cy < 0.75 * h) ) { + + d3.select("#drag_msg_text").node().innerHTML = "Drop it here."; + d3.select("#drag_msg").style("background-color", "#67bc0f"); + d3.select("#drag_msg").style("color", "#000000"); + executeFileDrop = true; + // d3.select("#drag_svg").transition() + // .duration(100) + // // .attr("-webkit-transform", "rotate(90)") + // // .attr("-moz-transform", "rotate(90)") + // // .attr("-o-transform", "rotate(90)") + // .attr("transform", "rotate(90)"); + + d3.select("#drag_icon").classed("hidden",true); + d3.select("#drag_icon_drop").classed("hidden",false); + + + } else { + d3.select("#drag_msg_text").node().innerHTML = "Drag ontology file here."; + d3.select("#drag_msg").style("background-color", "#fefefe"); + d3.select("#drag_msg").style("color", "#000000"); + executeFileDrop = false; + + d3.select("#drag_icon").classed("hidden",false); + d3.select("#drag_icon_drop").classed("hidden",true); + + + // d3.select("#drag_svg").transition() + // .duration(100) + // // .attr("-webkit-transform", "rotate(0)") + // // .attr("-moz-transform", "rotate(0)") + // // .attr("-o-transform", "rotate(0)") + // .attr("transform", "rotate(0)"); + // + } + + }; + node.node().ondrop = function ( ev ){ + ev.preventDefault(); + firstTime = false; + if ( executeFileDrop ) { + if ( ev.dataTransfer.items ) { + if ( ev.dataTransfer.items.length === 1 ) { + if ( ev.dataTransfer.items[0].kind === 'file' ) { + var file = ev.dataTransfer.items[0].getAsFile(); + graph.options().loadingModule().fromFileDrop(file.name, file); + } + } + else { + // >> WARNING not multiple file uploaded; + graph.options().warningModule().showMultiFileUploadWarning(); + } + } + } + d3.select("#dragDropContainer").classed("hidden", true); + }; + + node.node().ondragleave = function ( e ){ + var w = graph.options().width(); + var h = graph.options().height(); + + // get event position; (using clientX and clientY); + var cx = e.clientX; + var cy = e.clientY; + + var hidden = false; + firstTime = false; + + if ( cx < 0.1 * w || cx > 0.9 * w ) hidden = true; + if ( cy < 0.1 * h || cy > 0.9 * h ) hidden = true; + d3.select("#dragDropContainer").classed("hidden", hidden); + + d3.select("#loading-info").classed("hidden", !wasMessageToShow); // show it again + // check if it should be visible + var should_show=graph.options().loadingModule().getMessageVisibilityStatus(); + if (should_show===false){ + d3.select("#loading-info").classed("hidden", true); // hide it + } + }; + + } + + + app.initialize = function (){ + addFileDropEvents(GRAPH_SELECTOR); + + window.requestAnimationFrame = window.requestAnimationFrame || window.mozRequestAnimationFrame || window.webkitRequestAnimationFrame || window.msRequestAnimationFrame || function ( f ){ + return setTimeout(f, 1000 / 60); + }; // simulate calling code 60 + window.cancelAnimationFrame = window.cancelAnimationFrame || window.mozCancelAnimationFrame || function ( requestID ){ + clearTimeout(requestID); + }; //fall back + + options.graphContainerSelector(GRAPH_SELECTOR); + options.selectionModules().push(focuser); + options.selectionModules().push(selectionDetailDisplayer); + options.selectionModules().push(pickAndPin); + + options.filterModules().push(emptyLiteralFilter); + options.filterModules().push(statistics); + + options.filterModules().push(nodeDegreeFilter); + options.filterModules().push(datatypeFilter); + options.filterModules().push(objectPropertyFilter); + options.filterModules().push(subclassFilter); + options.filterModules().push(disjointFilter); + options.filterModules().push(setOperatorFilter); + options.filterModules().push(nodeScalingSwitch); + options.filterModules().push(compactNotationSwitch); + options.filterModules().push(colorExternalsSwitch); + + d3.select(window).on("resize", adjustSize); + + exportMenu.setup(); + gravityMenu.setup(); + filterMenu.setup(datatypeFilter, objectPropertyFilter, subclassFilter, disjointFilter, setOperatorFilter, nodeDegreeFilter); + modeMenu.setup(pickAndPin, nodeScalingSwitch, compactNotationSwitch, colorExternalsSwitch); + pauseMenu.setup(); + sidebar.setup(); + loadingModule.setup(); + leftSidebar.setup(); + editSidebar.setup(); + debugMenu.setup(); + var agentVersion = getInternetExplorerVersion(); + if ( agentVersion > 0 && agentVersion <= 11 ) { + console.log("Agent version " + agentVersion); + console.log("This agent is not supported"); + d3.select("#browserCheck").classed("hidden", false); + d3.select("#killWarning").classed("hidden", true); + d3.select("#optionsArea").classed("hidden", true); + d3.select("#logo").classed("hidden", true); + } else { + d3.select("#logo").classed("hidden", false); + if ( agentVersion === 12 ) { + // allow Mircosoft Edge Browser but with warning + d3.select("#browserCheck").classed("hidden", false); + d3.select("#killWarning").classed("hidden", false); + } else { + d3.select("#browserCheck").classed("hidden", true); + } + + resetMenu.setup([gravityMenu, filterMenu, modeMenu, focuser, selectionDetailDisplayer, pauseMenu]); + searchMenu.setup(); + navigationMenu.setup(); + zoomSlider.setup(); + + // give the options the pointer to the some menus for import and export + options.literalFilter(emptyLiteralFilter); + options.nodeDegreeFilter(nodeDegreeFilter); + options.loadingModule(loadingModule); + options.filterMenu(filterMenu); + options.modeMenu(modeMenu); + options.gravityMenu(gravityMenu); + options.pausedMenu(pauseMenu); + options.pickAndPinModule(pickAndPin); + options.resetMenu(resetMenu); + options.searchMenu(searchMenu); + options.ontologyMenu(ontologyMenu); + options.navigationMenu(navigationMenu); + options.sidebar(sidebar); + options.leftSidebar(leftSidebar); + options.editSidebar(editSidebar); + options.exportMenu(exportMenu); + options.graphObject(graph); + options.zoomSlider(zoomSlider); + options.warningModule(warningModule); + options.directInputModule(directInputMod); + options.datatypeFilter(datatypeFilter); + options.objectPropertyFilter(objectPropertyFilter); + options.subclassFilter(subclassFilter); + options.setOperatorFilter(setOperatorFilter); + options.disjointPropertyFilter(disjointFilter); + options.focuserModule(focuser); + options.colorExternalsModule(colorExternalsSwitch); + options.compactNotationModule(compactNotationSwitch); + + ontologyMenu.setup(loadOntologyFromText); + configMenu.setup(); + + leftSidebar.showSidebar(0); + leftSidebar.hideCollapseButton(true); + + + graph.start(); + + var modeOp = d3.select("#modeOfOperationString"); + modeOp.style("font-size", "0.6em"); + modeOp.style("font-style", "italic"); + + adjustSize(); + var defZoom; + var w = graph.options().width(); + var h = graph.options().height(); + defZoom = Math.min(w, h) / 1000; + + var hideDebugOptions = true; + if ( hideDebugOptions === false ) { + graph.setForceTickFunctionWithFPS(); + } + + graph.setDefaultZoom(defZoom); + d3.selectAll(".debugOption").classed("hidden", hideDebugOptions); + + // prevent backspace reloading event + var htmlBody = d3.select("body"); + d3.select(document).on("keydown", function ( e ){ + if ( d3.event.keyCode === 8 && d3.event.target === htmlBody.node() ) { + // we could add here an alert + d3.event.preventDefault(); + } + // using ctrl+Shift+d as debug option + if ( d3.event.ctrlKey && d3.event.shiftKey && d3.event.keyCode === 68 ) { + graph.options().executeHiddenDebugFeatuers(); + d3.event.preventDefault(); + } + }); + if ( d3.select("#maxLabelWidthSliderOption") ) { + var setValue = !graph.options().dynamicLabelWidth(); + d3.select("#maxLabelWidthSlider").node().disabled = setValue; + d3.select("#maxLabelWidthvalueLabel").classed("disabledLabelForSlider", setValue); + d3.select("#maxLabelWidthDescriptionLabel").classed("disabledLabelForSlider", setValue); + } + + d3.select("#blockGraphInteractions").style("position", "absolute") + .style("top", "0") + .style("background-color", "#bdbdbd") + .style("opacity", "0.5") + .style("pointer-events", "auto") + .style("width", graph.options().width() + "px") + .style("height", graph.options().height() + "px") + .on("click", function (){ + d3.event.preventDefault(); + d3.event.stopPropagation(); + }) + .on("dblclick", function (){ + d3.event.preventDefault(); + d3.event.stopPropagation(); + }); + + d3.select("#direct-text-input").on("click", function (){ + directInputMod.setDirectInputMode(); + }); + d3.select("#blockGraphInteractions").node().draggable = false; + options.prefixModule(webvowl.util.prefixTools(graph)); + adjustSize(); + sidebar.updateOntologyInformation(undefined, statistics); + loadingModule.parseUrlAndLoadOntology(); // loads automatically the ontology provided by the parameters + options.debugMenu(debugMenu); + debugMenu.updateSettings(); + + // connect the reloadCachedVersionButton + d3.select("#reloadSvgIcon").on("click", function (){ + if ( d3.select("#reloadSvgIcon").node().disabled === true ) { + graph.options().ontologyMenu().clearCachedVersion(); + return; + } + d3.select("#reloadCachedOntology").classed("hidden", true); + graph.options().ontologyMenu().reloadCachedOntology(); + + }); + // add the initialized objects + webvowl.opts = options; + webvowl.gr = graph; + + } + }; + + + function loadOntologyFromText( jsonText, filename, alternativeFilename ){ + d3.select("#reloadCachedOntology").classed("hidden", true); + pauseMenu.reset(); + graph.options().navigationMenu().hideAllMenus(); + + if ( (jsonText === undefined && filename === undefined) || (jsonText.length === 0) ) { + loadingModule.notValidJsonFile(); + return; + } + graph.editorMode(); // updates the checkbox + var data; + if ( jsonText ) { + // validate JSON FILE + var validJSON; + try { + data = JSON.parse(jsonText); + validJSON = true; + } catch ( e ) { + validJSON = false; + } + if ( validJSON === false ) { + // the server output is not a valid json file + loadingModule.notValidJsonFile(); + return; + } + + if ( !filename ) { + // First look if an ontology title exists, otherwise take the alternative filename + var ontologyNames = data.header ? data.header.title : undefined; + var ontologyName = languageTools.textInLanguage(ontologyNames); + + if ( ontologyName ) { + filename = ontologyName; + } else { + filename = alternativeFilename; + } + } + } + + + // check if we have graph data + var classCount = 0; + if ( data.class !== undefined ) { + classCount = data.class.length; + } + + var loadEmptyOntologyForEditing = false; + if ( location.hash.indexOf("#new_ontology") !== -1 ) { + loadEmptyOntologyForEditing = true; + newOntologyCounter++; + d3.select("#empty").node().href = "#opts=editorMode=true;#new_ontology" + newOntologyCounter; + } + if ( classCount === 0 && graph.editorMode() === false && loadEmptyOntologyForEditing === false ) { + // generate message for the user; + loadingModule.emptyGraphContentError(); + } else { + loadingModule.validJsonFile(); + ontologyMenu.setCachedOntology(filename, jsonText); + exportMenu.setJsonText(jsonText); + options.data(data); + graph.options().loadingModule().setPercentMode(); + if ( loadEmptyOntologyForEditing === true ) { + graph.editorMode(true); + + } + graph.load(); + sidebar.updateOntologyInformation(data, statistics); + exportMenu.setFilename(filename); + graph.updateZoomSliderValueFromOutside(); + adjustSize(); + + var flagOfCheckBox = d3.select("#editorModeModuleCheckbox").node().checked; + graph.editorMode(flagOfCheckBox);// update gui + + } + } + + function adjustSize(){ + var graphContainer = d3.select(GRAPH_SELECTOR), + svg = graphContainer.select("svg"), + height = window.innerHeight - 40, + width = window.innerWidth - (window.innerWidth * 0.22); + + if ( sidebar.getSidebarVisibility() === "0" ) { + height = window.innerHeight - 40; + width = window.innerWidth; + } + + directInputMod.updateLayout(); + d3.select("#blockGraphInteractions").style("width", window.innerWidth + "px"); + d3.select("#blockGraphInteractions").style("height", window.innerHeight + "px"); + + d3.select("#WarningErrorMessagesContainer").style("width", width + "px"); + d3.select("#WarningErrorMessagesContainer").style("height", height + "px"); + + d3.select("#WarningErrorMessages").style("max-height", (height - 12) + "px"); + + graphContainer.style("height", height + "px"); + svg.attr("width", width) + .attr("height", height); + + options.width(width) + .height(height); + + graph.updateStyle(); + + if ( isTouchDevice() === true ) { + if ( graph.isEditorMode() === true ) + d3.select("#modeOfOperationString").node().innerHTML = "touch able device detected"; + graph.setTouchDevice(true); + + } else { + if ( graph.isEditorMode() === true ) + d3.select("#modeOfOperationString").node().innerHTML = "point & click device detected"; + graph.setTouchDevice(false); + } + + d3.select("#loadingInfo-container").style("height", 0.5 * (height - 80) + "px"); + loadingModule.checkForScreenSize(); + + adjustSliderSize(); + // update also the padding options of loading and the logo positions; + var warningDiv = d3.select("#browserCheck"); + if ( warningDiv.classed("hidden") === false ) { + var offset = 10 + warningDiv.node().getBoundingClientRect().height; + d3.select("#logo").style("padding", offset + "px 10px"); + } else { + // remove the dynamic padding from the logo element; + d3.select("#logo").style("padding", "10px"); + } + + // scrollbar tests; + var element = d3.select("#menuElementContainer").node(); + var maxScrollLeft = element.scrollWidth - element.clientWidth; + var leftButton = d3.select("#scrollLeftButton"); + var rightButton = d3.select("#scrollRightButton"); + if ( maxScrollLeft > 0 ) { + // show both and then check how far is bar; + rightButton.classed("hidden", false); + leftButton.classed("hidden", false); + navigationMenu.updateScrollButtonVisibility(); + } else { + // hide both; + rightButton.classed("hidden", true); + leftButton.classed("hidden", true); + } + + // adjust height of the leftSidebar element; + editSidebar.updateElementWidth(); + + + var hs = d3.select("#drag_msg").node().getBoundingClientRect().height; + var ws = d3.select("#drag_msg").node().getBoundingClientRect().width; + d3.select("#drag_icon_group").attr("transform", "translate ( " + 0.25 * ws + " " + 0.25 * hs + ")"); + + } + + function adjustSliderSize(){ + // TODO: refactor and put this into the slider it self + var height = window.innerHeight - 40; + var fullHeight = height; + var zoomOutPos = height - 30; + var sliderHeight = 150; + + // assuming DOM elements are generated in the index.html + // todo: refactor for independent usage of graph and app + if ( fullHeight < 150 ) { + // hide the slider button; + d3.select("#zoomSliderParagraph").classed("hidden", true); + d3.select("#zoomOutButton").classed("hidden", true); + d3.select("#zoomInButton").classed("hidden", true); + d3.select("#centerGraphButton").classed("hidden", true); + return; + } + d3.select("#zoomSliderParagraph").classed("hidden", false); + d3.select("#zoomOutButton").classed("hidden", false); + d3.select("#zoomInButton").classed("hidden", false); + d3.select("#centerGraphButton").classed("hidden", false); + + var zoomInPos = zoomOutPos - 20; + var centerPos = zoomInPos - 20; + if ( fullHeight < 280 ) { + // hide the slider button; + d3.select("#zoomSliderParagraph").classed("hidden", true);//var sliderPos=zoomOutPos-sliderHeight; + d3.select("#zoomOutButton").style("top", zoomOutPos + "px"); + d3.select("#zoomInButton").style("top", zoomInPos + "px"); + d3.select("#centerGraphButton").style("top", centerPos + "px"); + return; + } + + var sliderPos = zoomOutPos - sliderHeight; + zoomInPos = sliderPos - 20; + centerPos = zoomInPos - 20; + d3.select("#zoomSliderParagraph").classed("hidden", false); + d3.select("#zoomOutButton").style("top", zoomOutPos + "px"); + d3.select("#zoomInButton").style("top", zoomInPos + "px"); + d3.select("#centerGraphButton").style("top", centerPos + "px"); + d3.select("#zoomSliderParagraph").style("top", sliderPos + "px"); + } + + function isTouchDevice(){ + try { + document.createEvent("TouchEvent"); + return true; + } catch ( e ) { + return false; + } + } + + + function getInternetExplorerVersion(){ + var ua, + re, + rv = -1; + + // check for edge + var isEdge = /(?:\b(MS)?IE\s+|\bTrident\/7\.0;.*\s+rv:|\bEdge\/)(\d+)/.test(navigator.userAgent); + if ( isEdge ) { + rv = parseInt("12"); + return rv; + } + + var isIE11 = /Trident.*rv[ :]*11\./.test(navigator.userAgent); + if ( isIE11 ) { + rv = parseInt("11"); + return rv; + } + if ( navigator.appName === "Microsoft Internet Explorer" ) { + ua = navigator.userAgent; + re = new RegExp("MSIE ([0-9]{1,}[\\.0-9]{0,})"); + if ( re.exec(ua) !== null ) { + rv = parseFloat(RegExp.$1); + } + } else if ( navigator.appName === "Netscape" ) { + ua = navigator.userAgent; + re = new RegExp("Trident/.*rv:([0-9]{1,}[\\.0-9]{0,})"); + if ( re.exec(ua) !== null ) { + rv = parseFloat(RegExp.$1); + } + } + return rv; + } + + return app; + } + ; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 323: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for the export button. + * @returns {{}} + */ + module.exports = function ( graph ){ + + var exportMenu = {}, + exportSvgButton, + exportFilename, + exportJsonButton, + exportTurtleButton, + exportTexButton, + copyButton, + exportableJsonText; + + var exportTTLModule = __webpack_require__(324)(graph); + + + String.prototype.replaceAll = function ( search, replacement ){ + var target = this; + return target.split(search).join(replacement); + }; + + + /** + * Adds the export button to the website. + */ + exportMenu.setup = function (){ + exportSvgButton = d3.select("#exportSvg") + .on("click", exportSvg); + exportJsonButton = d3.select("#exportJson") + .on("click", exportJson); + + copyButton = d3.select("#copyBt") + .on("click", copyUrl); + + exportTexButton = d3.select("#exportTex") + .on("click", exportTex); + + exportTurtleButton = d3.select("#exportTurtle") + .on("click", exportTurtle); + + var menuEntry = d3.select("#m_export"); + menuEntry.on("mouseover", function (){ + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + exportMenu.exportAsUrl(); + }); + }; + function exportTurtle(){ + var success = exportTTLModule.requestExport(); + var result = exportTTLModule.resultingTTL_Content(); + var ontoTitle = "NewOntology"; + console.log("Exporter was successful: " + success); + if ( success ) { + // console.log("The result is : " + result); + // var ontoTitle=graph.options().getGeneralMetaObjectProperty('title'); + // if (ontoTitle===undefined || ontoTitle.length===0) + // ontoTitle="NewOntology"; + // else{ + // // language object -.- + // ontoTitle.replace(" ","_") + // } + + // TODO: show TEXT in warning module? + + + // // write the data + var dataURI = "data:text/json;charset=utf-8," + encodeURIComponent(result); + + exportTurtleButton.attr("href", dataURI) + .attr("download", ontoTitle + ".ttl"); + + // okay restore old href? + // exportTurtleButton.attr("href", oldHref); + } else { + console.log("ShowWarning!"); + graph.options().warningModule().showExporterWarning(); + console.log("Stay on the page! " + window.location.href); + exportTurtleButton.attr("href", window.location.href); + d3.event.preventDefault(); // prevent the href to be called ( reloads the page otherwise ) + } + } + + exportMenu.setFilename = function ( filename ){ + exportFilename = filename || "export"; + }; + + exportMenu.setJsonText = function ( jsonText ){ + exportableJsonText = jsonText; + }; + + function copyUrl(){ + d3.select("#exportedUrl").node().focus(); + d3.select("#exportedUrl").node().select(); + document.execCommand("copy"); + graph.options().navigationMenu().hideAllMenus(); + d3.event.preventDefault(); // prevent the href to be called ( reloads the page otherwise ) + } + + function prepareOptionString( defOpts, currOpts ){ + var setOptions = 0; + var optsString = "opts="; + + for ( var name in defOpts ) { + // define key and value ; + if ( defOpts.hasOwnProperty(name) ) {// for travis warning + var def_value = defOpts[name]; + var cur_value = currOpts[name]; + if ( def_value !== cur_value ) { + optsString += name + "=" + cur_value + ";"; + setOptions++; + } + } + } + optsString += ""; + if ( setOptions === 0 ) { + return ""; + } + return optsString; + } + + exportMenu.exportAsUrl = function (){ + var currObj = {}; + currObj.sidebar = graph.options().sidebar().getSidebarVisibility(); + + // identify default value given by ontology; + var defOntValue = graph.options().filterMenu().getDefaultDegreeValue(); + var currentValue = graph.options().filterMenu().getDegreeSliderValue(); + if ( parseInt(defOntValue) === parseInt(currentValue) ) { + currObj.doc = -1; + } else { + currObj.doc = currentValue; + } + + currObj.cd = graph.options().classDistance(); + currObj.dd = graph.options().datatypeDistance(); + if ( graph.editorMode() === true ) { + currObj.editorMode = "true"; + } else { + currObj.editorMode = "false"; + } + currObj.filter_datatypes = String(graph.options().filterMenu().getCheckBoxValue("datatypeFilterCheckbox")); + currObj.filter_sco = String(graph.options().filterMenu().getCheckBoxValue("subclassFilterCheckbox")); + currObj.filter_disjoint = String(graph.options().filterMenu().getCheckBoxValue("disjointFilterCheckbox")); + currObj.filter_setOperator = String(graph.options().filterMenu().getCheckBoxValue("setoperatorFilterCheckbox")); + currObj.filter_objectProperties = String(graph.options().filterMenu().getCheckBoxValue("objectPropertyFilterCheckbox")); + currObj.mode_dynamic = String(graph.options().dynamicLabelWidth()); + currObj.mode_scaling = String(graph.options().modeMenu().getCheckBoxValue("nodescalingModuleCheckbox")); + currObj.mode_compact = String(graph.options().modeMenu().getCheckBoxValue("compactnotationModuleCheckbox")); + currObj.mode_colorExt = String(graph.options().modeMenu().getCheckBoxValue("colorexternalsModuleCheckbox")); + currObj.mode_multiColor = String(graph.options().modeMenu().colorModeState()); + currObj.mode_pnp = String(graph.options().modeMenu().getCheckBoxValue("pickandpinModuleCheckbox")); + currObj.debugFeatures = String(!graph.options().getHideDebugFeatures()); + currObj.rect = 0; + + var defObj = graph.options().initialConfig(); + var optsString = prepareOptionString(defObj, currObj); + var urlString = String(location); + var htmlElement; + // when everything is default then there is nothing to write + if ( optsString.length === 0 ) { + // building up parameter list; + + // remove the all options form location + var hashCode = location.hash; + urlString = urlString.split(hashCode)[0]; + + var lPos = hashCode.lastIndexOf("#"); + if ( lPos === -1 ) { + htmlElement = d3.select("#exportedUrl").node(); + htmlElement.value = String(location); + htmlElement.title = String(location); + return; // nothing to change in the location String + } + var newURL = hashCode.slice(lPos, hashCode.length); + htmlElement = d3.select("#exportedUrl").node(); + htmlElement.value = urlString + newURL; + htmlElement.title = urlString + newURL; + return; + } + + // generate the options string; + var numParameters = (urlString.match(/#/g) || []).length; + var newUrlString; + if ( numParameters === undefined || numParameters === 0 ) { + newUrlString = urlString + "#" + optsString; + } + if ( numParameters > 0 ) { + var tokens = urlString.split("#"); + var i; + if ( tokens[1].indexOf("opts=") >= 0 ) { + tokens[1] = optsString; + newUrlString = tokens[0]; + } else { + newUrlString = tokens[0] + "#"; + newUrlString += optsString; + } + // append parameters + for ( i = 1; i < tokens.length; i++ ) { + if ( tokens[i].length > 0 ) { + newUrlString += "#" + tokens[i]; + } + } + } + // building up parameter list; + htmlElement = d3.select("#exportedUrl").node(); + htmlElement.value = newUrlString; + htmlElement.title = newUrlString; + + }; + + function exportSvg(){ + graph.options().navigationMenu().hideAllMenus(); + // Get the d3js SVG element + var graphSvg = d3.select(graph.options().graphContainerSelector()).select("svg"), + graphSvgCode, + escapedGraphSvgCode, + dataURI; + + // inline the styles, so that the exported svg code contains the css rules + inlineVowlStyles(); + hideNonExportableElements(); + + graphSvgCode = graphSvg.attr("version", 1.1) + .attr("xmlns", "http://www.w3.org/2000/svg") + .node().parentNode.innerHTML; + + // Insert the reference to VOWL + graphSvgCode = "\n" + graphSvgCode; + + escapedGraphSvgCode = escapeUnicodeCharacters(graphSvgCode); + //btoa(); Creates a base-64 encoded ASCII string from a "string" of binary data. + dataURI = "data:image/svg+xml;base64," + btoa(escapedGraphSvgCode); + + + exportSvgButton.attr("href", dataURI) + .attr("download", exportFilename + ".svg"); + + // remove graphic styles for interaction to go back to normal + removeVowlInlineStyles(); + showNonExportableElements(); + graph.lazyRefresh(); + } + + function escapeUnicodeCharacters( text ){ + var textSnippets = [], + i, textLength = text.length, + character, + charCode; + + for ( i = 0; i < textLength; i++ ) { + character = text.charAt(i); + charCode = character.charCodeAt(0); + + if ( charCode < 128 ) { + textSnippets.push(character); + } else { + textSnippets.push("&#" + charCode + ";"); + } + } + + return textSnippets.join(""); + } + + function inlineVowlStyles(){ + setStyleSensitively(".text", [{ name: "font-family", value: "Helvetica, Arial, sans-serif" }, { + name: "font-size", + value: "12px" + }]); + setStyleSensitively(".subtext", [{ name: "font-size", value: "9px" }]); + setStyleSensitively(".text.instance-count", [{ name: "fill", value: "#666" }]); + setStyleSensitively(".external + text .instance-count", [{ name: "fill", value: "#aaa" }]); + setStyleSensitively(".cardinality", [{ name: "font-size", value: "10px" }]); + setStyleSensitively(".text, .embedded", [{ name: "pointer-events", value: "none" }]); + setStyleSensitively(".class, .object, .disjoint, .objectproperty, .disjointwith, .equivalentproperty, .transitiveproperty, .functionalproperty, .inversefunctionalproperty, .symmetricproperty, .allvaluesfromproperty, .somevaluesfromproperty", [{ + name: "fill", + value: "#acf" + }]); + setStyleSensitively(".label .datatype, .datatypeproperty", [{ name: "fill", value: "#9c6" }]); + setStyleSensitively(".rdf, .rdfproperty", [{ name: "fill", value: "#c9c" }]); + setStyleSensitively(".literal, .node .datatype", [{ name: "fill", value: "#fc3" }]); + setStyleSensitively(".deprecated, .deprecatedproperty", [{ name: "fill", value: "#ccc" }]); + setStyleSensitively(".external, .externalproperty", [{ name: "fill", value: "#36c" }]); + setStyleSensitively("path, .nofill", [{ name: "fill", value: "none" }]); + setStyleSensitively("marker path", [{ name: "fill", value: "#000" }]); + setStyleSensitively(".class, path, line, .fineline", [{ name: "stroke", value: "#000" }]); + setStyleSensitively(".white, .subclass, .subclassproperty, .external + text", [{ name: "fill", value: "#fff" }]); + setStyleSensitively(".class.hovered, .property.hovered, .cardinality.hovered, .cardinality.focused, circle.pin, .filled.hovered, .filled.focused", [{ + name: "fill", + value: "#f00" + }, { name: "cursor", value: "pointer" }]); + setStyleSensitively(".focused, path.hovered", [{ name: "stroke", value: "#f00" }]); + setStyleSensitively(".indirect-highlighting, .feature:hover", [{ name: "fill", value: "#f90" }]); + setStyleSensitively(".values-from", [{ name: "stroke", value: "#69c" }]); + setStyleSensitively(".symbol, .values-from.filled", [{ name: "fill", value: "#69c" }]); + setStyleSensitively(".class, path, line", [{ name: "stroke-width", value: "2" }]); + setStyleSensitively(".fineline", [{ name: "stroke-width", value: "1" }]); + setStyleSensitively(".dashed, .anonymous", [{ name: "stroke-dasharray", value: "8" }]); + setStyleSensitively(".dotted", [{ name: "stroke-dasharray", value: "3" }]); + setStyleSensitively("rect.focused, circle.focused", [{ name: "stroke-width", value: "4px" }]); + setStyleSensitively(".nostroke", [{ name: "stroke", value: "none" }]); + setStyleSensitively("marker path", [{ name: "stroke-dasharray", value: "100" }]); + } + + function setStyleSensitively( selector, styles ){ + var elements = d3.selectAll(selector); + if ( elements.empty() ) { + return; + } + + styles.forEach(function ( style ){ + elements.each(function (){ + var element = d3.select(this); + if ( !shouldntChangeInlineCss(element, style.name) ) { + element.style(style.name, style.value); + } + }); + }); + } + + function shouldntChangeInlineCss( element, style ){ + return style === "fill" && hasBackgroundColorSet(element); + } + + function hasBackgroundColorSet( element ){ + var data = element.datum(); + if ( data === undefined ) { + return false; + } + return data.backgroundColor && !!data.backgroundColor(); + } + + /** + * For example the pin of the pick&pin module should be invisible in the exported graphic. + */ + function hideNonExportableElements(){ + d3.selectAll(".hidden-in-export").style("display", "none"); + } + + function removeVowlInlineStyles(){ + d3.selectAll(".text, .subtext, .text.instance-count, .external + text .instance-count, .cardinality, .text, .embedded, .class, .object, .disjoint, .objectproperty, .disjointwith, .equivalentproperty, .transitiveproperty, .functionalproperty, .inversefunctionalproperty, .symmetricproperty, .allvaluesfromproperty, .somevaluesfromproperty, .label .datatype, .datatypeproperty, .rdf, .rdfproperty, .literal, .node .datatype, .deprecated, .deprecatedproperty, .external, .externalproperty, path, .nofill, .symbol, .values-from.filled, marker path, .class, path, line, .fineline, .white, .subclass, .subclassproperty, .external + text, .class.hovered, .property.hovered, .cardinality.hovered, .cardinality.focused, circle.pin, .filled.hovered, .filled.focused, .focused, path.hovered, .indirect-highlighting, .feature:hover, .values-from, .class, path, line, .fineline, .dashed, .anonymous, .dotted, rect.focused, circle.focused, .nostroke, marker path") + .each(function (){ + var element = d3.select(this); + + var inlineStyles = element.node().style; + for ( var styleName in inlineStyles ) { + if ( inlineStyles.hasOwnProperty(styleName) ) { + if ( shouldntChangeInlineCss(element, styleName) ) { + continue; + } + element.style(styleName, null); + } + } + + if ( element.datum && element.datum() !== undefined && element.datum().type ) { + if ( element.datum().type() === "rdfs:subClassOf" ) { + element.style("fill", null); + } + } + }); + + // repair svg icons in the menu; + var scrollContainer = d3.select("#menuElementContainer").node(); + var controlElements = scrollContainer.children; + var numEntries = controlElements.length; + + for ( var i = 0; i < numEntries; i++ ) { + var currentMenu = controlElements[i].id; + d3.select("#" + currentMenu).select("path").style("stroke-width", "0"); + d3.select("#" + currentMenu).select("path").style("fill", "#fff"); + } + + d3.select("#magnifyingGlass").style("stroke-width", "0"); + d3.select("#magnifyingGlass").style("fill", "#666"); + + } + + function showNonExportableElements(){ + d3.selectAll(".hidden-in-export").style("display", null); + } + + exportMenu.createJSON_exportObject = function (){ + var i, j, k; // an index variable for the for-loops + + /** get data for exporter **/ + if (!graph.options().data()) {return {};} // return an empty json object + // extract onotology information; + var unfilteredData = graph.getUnfilteredData(); + var ontologyComment = graph.options().data()._comment; + var metaObj = graph.options().getGeneralMetaObject(); + var header = graph.options().data().header; + + if ( metaObj.iri && metaObj.iri !== header.iri ) { + header.iri = metaObj.iri; + } + if ( metaObj.title && metaObj.title !== header.title ) { + header.title = metaObj.title; + } + if ( metaObj.version && metaObj.version !== header.version ) { + header.version = metaObj.version; + } + if ( metaObj.author && metaObj.author !== header.author ) { + header.author = metaObj.author; + } + if ( metaObj.description && metaObj.description !== header.description ) { + header.description = metaObj.description; + } + + + var exportText = {}; + exportText._comment = ontologyComment; + exportText.header = header; + exportText.namespace = graph.options().data().namespace; + if ( exportText.namespace === undefined ) { + exportText.namespace = []; // just an empty namespace array + } + // we do have now the unfiltered data which needs to be transfered to class/classAttribute and property/propertyAttribute + + + // var classAttributeString='classAttribute:[ \n'; + var nodes = unfilteredData.nodes; + var nLen = nodes.length; // hope for compiler unroll + var classObjects = []; + var classAttributeObjects = []; + for ( i = 0; i < nLen; i++ ) { + var classObj = {}; + var classAttr = {}; + classObj.id = nodes[i].id(); + classObj.type = nodes[i].type(); + classObjects.push(classObj); + + // define the attributes object + classAttr.id = nodes[i].id(); + classAttr.iri = nodes[i].iri(); + classAttr.baseIri = nodes[i].baseIri(); + classAttr.label = nodes[i].label(); + + if ( nodes[i].attributes().length > 0 ) { + classAttr.attributes = nodes[i].attributes(); + } + if ( nodes[i].comment() ) { + classAttr.comment = nodes[i].comment(); + } + if ( nodes[i].annotations() ) { + classAttr.annotations = nodes[i].annotations(); + } + if ( nodes[i].description() ) { + classAttr.description = nodes[i].description(); + } + + + if ( nodes[i].individuals().length > 0 ) { + var classIndividualElements = []; + var nIndividuals = nodes[i].individuals(); + for ( j = 0; j < nIndividuals.length; j++ ) { + var indObj = {}; + indObj.iri = nIndividuals[j].iri(); + indObj.baseIri = nIndividuals[j].baseIri(); + indObj.labels = nIndividuals[j].label(); + if ( nIndividuals[j].annotations() ) { + indObj.annotations = nIndividuals[j].annotations(); + } + if ( nIndividuals[j].description() ) { + indObj.description = nIndividuals[j].description(); + } + if ( nIndividuals[j].comment() ) { + indObj.comment = nIndividuals[j].comment(); + } + classIndividualElements.push(indObj); + } + classAttr.individuals = classIndividualElements; + } + + var equalsForAttributes = undefined; + if ( nodes[i].equivalents().length > 0 ) { + equalsForAttributes = []; + var equals = nodes[i].equivalents(); + for ( j = 0; j < equals.length; j++ ) { + var eqObj = {}; + var eqAttr = {}; + eqObj.id = equals[j].id(); + equalsForAttributes.push(equals[j].id()); + eqObj.type = equals[j].type(); + classObjects.push(eqObj); + + eqAttr.id = equals[j].id(); + eqAttr.iri = equals[j].iri(); + eqAttr.baseIri = equals[j].baseIri(); + eqAttr.label = equals[j].label(); + + if ( equals[j].attributes().length > 0 ) { + eqAttr.attributes = equals[j].attributes(); + } + if ( equals[j].comment() ) { + eqAttr.comment = equals[j].comment(); + } + if ( equals[j].individuals().length > 0 ) { + eqAttr.individuals = equals[j].individuals(); + } + if ( equals[j].annotations() ) { + eqAttr.annotations = equals[j].annotations(); + } + if ( equals[j].description() ) { + eqAttr.description = equals[j].description(); + } + + if ( equals[j].individuals().length > 0 ) { + var e_classIndividualElements = []; + var e_nIndividuals = equals[i].individuals(); + for ( k = 0; k < e_nIndividuals.length; k++ ) { + var e_indObj = {}; + e_indObj.iri = e_nIndividuals[k].iri(); + e_indObj.baseIri = e_nIndividuals[k].baseIri(); + e_indObj.labels = e_nIndividuals[k].label(); + + if ( e_nIndividuals[k].annotations() ) { + e_indObj.annotations = e_nIndividuals[k].annotations(); + } + if ( e_nIndividuals[k].description() ) { + e_indObj.description = e_nIndividuals[k].description(); + } + if ( e_nIndividuals[k].comment() ) { + e_indObj.comment = e_nIndividuals[k].comment(); + } + e_classIndividualElements.push(e_indObj); + } + eqAttr.individuals = e_classIndividualElements; + } + + classAttributeObjects.push(eqAttr); + } + } + if ( equalsForAttributes && equalsForAttributes.length > 0 ) { + classAttr.equivalent = equalsForAttributes; + } + + // classAttr.subClasses=nodes[i].subClasses(); // not needed + // classAttr.instances=nodes[i].instances(); + + // + // .complement(element.complement) + // .disjointUnion(element.disjointUnion) + // .description(element.description) + // .equivalents(element.equivalent) + // .intersection(element.intersection) + // .type(element.type) Ignore, because we predefined it + // .union(element.union) + classAttributeObjects.push(classAttr); + } + + /** -- properties -- **/ + var properties = unfilteredData.properties; + var pLen = properties.length; // hope for compiler unroll + var propertyObjects = []; + var propertyAttributeObjects = []; + + for ( i = 0; i < pLen; i++ ) { + var pObj = {}; + var pAttr = {}; + pObj.id = properties[i].id(); + pObj.type = properties[i].type(); + propertyObjects.push(pObj); + + // // define the attributes object + pAttr.id = properties[i].id(); + pAttr.iri = properties[i].iri(); + pAttr.baseIri = properties[i].baseIri(); + pAttr.label = properties[i].label(); + + if ( properties[i].attributes().length > 0 ) { + pAttr.attributes = properties[i].attributes(); + } + if ( properties[i].comment() ) { + pAttr.comment = properties[i].comment(); + } + + if ( properties[i].annotations() ) { + pAttr.annotations = properties[i].annotations(); + } + if ( properties[i].maxCardinality() ) { + pAttr.maxCardinality = properties[i].maxCardinality(); + } + if ( properties[i].minCardinality() ) { + pAttr.minCardinality = properties[i].minCardinality(); + } + if ( properties[i].cardinality() ) { + pAttr.cardinality = properties[i].cardinality(); + } + if ( properties[i].description() ) { + pAttr.description = properties[i].description(); + } + + pAttr.domain = properties[i].domain().id(); + pAttr.range = properties[i].range().id(); + // sub properties; + if ( properties[i].subproperties() ) { + var subProps = properties[i].subproperties(); + var subPropsIdArray = []; + for ( j = 0; j < subProps.length; j++ ) { + if ( subProps[j].id ) + subPropsIdArray.push(subProps[j].id()); + } + pAttr.subproperty = subPropsIdArray; + } + + // super properties + if ( properties[i].superproperties() ) { + var superProps = properties[i].superproperties(); + var superPropsIdArray = []; + for ( j = 0; j < superProps.length; j++ ) { + if ( superProps[j].id ) + superPropsIdArray.push(superProps[j].id()); + } + pAttr.superproperty = superPropsIdArray; + } + + // check for inverse element + if ( properties[i].inverse() ) { + if ( properties[i].inverse().id ) + pAttr.inverse = properties[i].inverse().id(); + } + propertyAttributeObjects.push(pAttr); + } + + exportText.class = classObjects; + exportText.classAttribute = classAttributeObjects; + exportText.property = propertyObjects; + exportText.propertyAttribute = propertyAttributeObjects; + + + var nodeElements = graph.graphNodeElements(); // get visible nodes + var propElements = graph.graphLabelElements(); // get visible labels + // var jsonObj = JSON.parse(exportableJsonText); // reparse the original input json + + /** modify comment **/ + var comment = exportText._comment; + var additionalString = " [Additional Information added by WebVOWL Exporter Version: " + "1.1.7" + "]"; + // adding new string to comment only if it does not exist + if ( comment.indexOf(additionalString) === -1 ) { + exportText._comment = comment + " [Additional Information added by WebVOWL Exporter Version: " + "1.1.7" + "]"; + } + + var classAttribute = exportText.classAttribute; + var propAttribute = exportText.propertyAttribute; + /** remove previously stored variables **/ + for ( i = 0; i < classAttribute.length; i++ ) { + var classObj_del = classAttribute[i]; + delete classObj_del.pos; + delete classObj_del.pinned; + } + var propertyObj; + for ( i = 0; i < propAttribute.length; i++ ) { + propertyObj = propAttribute[i]; + delete propertyObj.pos; + delete propertyObj.pinned; + } + /** add new variables to jsonObj **/ + // class attribute variables + nodeElements.each(function ( node ){ + var nodeId = node.id(); + for ( i = 0; i < classAttribute.length; i++ ) { + var classObj = classAttribute[i]; + if ( classObj.id === nodeId ) { + // store relative positions + classObj.pos = [parseFloat(node.x.toFixed(2)), parseFloat(node.y.toFixed(2))]; + if ( node.pinned() ) + classObj.pinned = true; + break; + } + } + }); + // property attribute variables + for ( j = 0; j < propElements.length; j++ ) { + var correspondingProp = propElements[j].property(); + for ( i = 0; i < propAttribute.length; i++ ) { + propertyObj = propAttribute[i]; + if ( propertyObj.id === correspondingProp.id() ) { + propertyObj.pos = [parseFloat(propElements[j].x.toFixed(2)), parseFloat(propElements[j].y.toFixed(2))]; + if ( propElements[j].pinned() ) + propertyObj.pinned = true; + break; + } + } + } + /** create the variable for settings and set their values **/ + exportText.settings = {}; + + // Global Settings + var zoom = graph.scaleFactor(); + var paused = graph.paused(); + var translation = [parseFloat(graph.translation()[0].toFixed(2)), parseFloat(graph.translation()[1].toFixed(2))]; + exportText.settings.global = {}; + exportText.settings.global.zoom = zoom.toFixed(2); + exportText.settings.global.translation = translation; + exportText.settings.global.paused = paused; + + // shared variable declaration + var cb_text; + var isEnabled; + var cb_obj; + + // Gravity Settings + var classDistance = graph.options().classDistance(); + var datatypeDistance = graph.options().datatypeDistance(); + exportText.settings.gravity = {}; + exportText.settings.gravity.classDistance = classDistance; + exportText.settings.gravity.datatypeDistance = datatypeDistance; + + // Filter Settings + var fMenu = graph.options().filterMenu(); + var fContainer = fMenu.getCheckBoxContainer(); + var cbCont = []; + for ( i = 0; i < fContainer.length; i++ ) { + cb_text = fContainer[i].checkbox.attr("id"); + isEnabled = fContainer[i].checkbox.property("checked"); + cb_obj = {}; + cb_obj.id = cb_text; + cb_obj.checked = isEnabled; + cbCont.push(cb_obj); + } + var degreeSliderVal = fMenu.getDegreeSliderValue(); + exportText.settings.filter = {}; + exportText.settings.filter.checkBox = cbCont; + exportText.settings.filter.degreeSliderValue = degreeSliderVal; + + // Modes Settings + var mMenu = graph.options().modeMenu(); + var mContainer = mMenu.getCheckBoxContainer(); + var cb_modes = []; + for ( i = 0; i < mContainer.length; i++ ) { + cb_text = mContainer[i].attr("id"); + isEnabled = mContainer[i].property("checked"); + cb_obj = {}; + cb_obj.id = cb_text; + cb_obj.checked = isEnabled; + cb_modes.push(cb_obj); + } + var colorSwitchState = mMenu.colorModeState(); + exportText.settings.modes = {}; + exportText.settings.modes.checkBox = cb_modes; + exportText.settings.modes.colorSwitchState = colorSwitchState; + + var exportObj = {}; + // todo: [ ] find better way for ordering the objects + // hack for ordering of objects, so settings is after metrics + exportObj._comment = exportText._comment; + exportObj.header = exportText.header; + exportObj.namespace = exportText.namespace; + exportObj.metrics = exportText.metrics; + exportObj.settings = exportText.settings; + exportObj.class = exportText.class; + exportObj.classAttribute = exportText.classAttribute; + exportObj.property = exportText.property; + exportObj.propertyAttribute = exportText.propertyAttribute; + + return exportObj; + }; + + function exportJson(){ + graph.options().navigationMenu().hideAllMenus(); + /** check if there is data **/ + if ( !exportableJsonText ) { + alert("No graph data available."); + // Stop the redirection to the path of the href attribute + d3.event.preventDefault(); + return; + } + + var exportObj = exportMenu.createJSON_exportObject(); + + // make a string again; + var exportText = JSON.stringify(exportObj, null, ' '); + // write the data + var dataURI = "data:text/json;charset=utf-8," + encodeURIComponent(exportText); + var jsonExportFileName = exportFilename; + + if ( !jsonExportFileName.endsWith(".json") ) + jsonExportFileName += ".json"; + exportJsonButton.attr("href", dataURI) + .attr("download", jsonExportFileName); + } + + var curveFunction = d3.svg.line() + .x(function ( d ){ + return d.x; + }) + .y(function ( d ){ + return d.y; + }) + .interpolate("cardinal"); + var loopFunction = d3.svg.line() + .x(function ( d ){ + return d.x; + }) + .y(function ( d ){ + return d.y; + }) + .interpolate("cardinal") + .tension(-1); + + function exportTex(){ + var zoom = graph.scaleFactor(); + var grTranslate = graph.translation(); + var bbox = graph.getBoundingBoxForTex(); + var comment = " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n"; + comment += " % Generated with the experimental alpha version of the TeX exporter of WebVOWL (version 1.1.3) %%% \n"; + comment += " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n\n"; + comment += " % The content can be used as import in other TeX documents. \n"; + comment += " % Parent document has to use the following packages \n"; + comment += " % \\usepackage{tikz} \n"; + comment += " % \\usepackage{helvet} \n"; + comment += " % \\usetikzlibrary{decorations.markings,decorations.shapes,decorations,arrows,automata,backgrounds,petri,shapes.geometric} \n"; + comment += " % \\usepackage{xcolor} \n\n"; + comment += " %%%%%%%%%%%%%%% Example Parent Document %%%%%%%%%%%%%%%%%%%%%%%\n"; + comment += " %\\documentclass{article} \n"; + comment += " %\\usepackage{tikz} \n"; + comment += " %\\usepackage{helvet} \n"; + comment += " %\\usetikzlibrary{decorations.markings,decorations.shapes,decorations,arrows,automata,backgrounds,petri,shapes.geometric} \n"; + comment += " %\\usepackage{xcolor} \n\n"; + comment += " %\\begin{document} \n"; + comment += " %\\section{Example} \n"; + comment += " % This is an example. \n"; + comment += " % \\begin{figure} \n"; + comment += " % \\input{} % << tex file name for the graph \n"; + comment += " % \\caption{A generated graph with TKIZ using alpha version of the TeX exporter of WebVOWL (version 1.1.3) } \n"; + comment += " % \\end{figure} \n"; + comment += " %\\end{document} \n"; + comment += " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n\n"; + + + var texString = comment + "\\definecolor{imageBGCOLOR}{HTML}{FFFFFF} \n" + + "\\definecolor{owlClassColor}{HTML}{AACCFF}\n" + + "\\definecolor{owlObjectPropertyColor}{HTML}{AACCFF}\n" + + "\\definecolor{owlExternalClassColor}{HTML}{AACCFF}\n" + + "\\definecolor{owlDatatypePropertyColor}{HTML}{99CC66}\n" + + "\\definecolor{owlDatatypeColor}{HTML}{FFCC33}\n" + + "\\definecolor{owlThingColor}{HTML}{FFFFFF}\n" + + "\\definecolor{valuesFrom}{HTML}{6699CC}\n" + + "\\definecolor{rdfPropertyColor}{HTML}{CC99CC}\n" + + "\\definecolor{unionColor}{HTML}{6699cc}\n" + + "\\begin{center} \n" + + "\\resizebox{\\linewidth}{!}{\n" + + + "\\begin{tikzpicture}[framed]\n" + + "\\clip (" + bbox[0] + "pt , " + bbox[1] + "pt ) rectangle (" + bbox[2] + "pt , " + bbox[3] + "pt);\n" + + "\\tikzstyle{dashed}=[dash pattern=on 4pt off 4pt] \n" + + "\\tikzstyle{dotted}=[dash pattern=on 2pt off 2pt] \n" + + "\\fontfamily{sans-serif}{\\fontsize{12}{12}\\selectfont}\n \n"; + + + texString += "\\tikzset{triangleBlack/.style = {fill=black, draw=black, line width=1pt,scale=0.7,regular polygon, regular polygon sides=3} }\n"; + texString += "\\tikzset{triangleWhite/.style = {fill=white, draw=black, line width=1pt,scale=0.7,regular polygon, regular polygon sides=3} }\n"; + texString += "\\tikzset{triangleBlue/.style = {fill=valuesFrom, draw=valuesFrom, line width=1pt,scale=0.7,regular polygon, regular polygon sides=3} }\n"; + + texString += "\\tikzset{Diamond/.style = {fill=white, draw=black, line width=2pt,scale=1.2,regular polygon, regular polygon sides=4} }\n"; + + + texString += "\\tikzset{Literal/.style={rectangle,align=center,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "black, draw=black, dashed, line width=1pt, fill=owlDatatypeColor, minimum width=80pt,\n" + + "minimum height = 20pt}}\n\n"; + + texString += "\\tikzset{Datatype/.style={rectangle,align=center,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "black, draw=black, line width=1pt, fill=owlDatatypeColor, minimum width=80pt,\n" + + "minimum height = 20pt}}\n\n"; + + + texString += "\\tikzset{owlClass/.style={circle, inner sep=0mm,align=center, \n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "black, draw=black, line width=1pt, fill=owlClassColor, minimum size=101pt}}\n\n"; + + texString += "\\tikzset{anonymousClass/.style={circle, inner sep=0mm,align=center, \n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "black, dashed, draw=black, line width=1pt, fill=owlClassColor, minimum size=101pt}}\n\n"; + + + texString += "\\tikzset{owlThing/.style={circle, inner sep=0mm,align=center,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "black, dashed, draw=black, line width=1pt, fill=owlThingColor, minimum size=62pt}}\n\n"; + + + texString += "\\tikzset{owlObjectProperty/.style={rectangle,align=center,\n" + + "inner sep=0mm,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "fill=owlObjectPropertyColor, minimum width=80pt,\n" + + "minimum height = 25pt}}\n\n"; + + texString += "\\tikzset{rdfProperty/.style={rectangle,align=center,\n" + + "inner sep=0mm,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "fill=rdfPropertyColor, minimum width=80pt,\n" + + "minimum height = 25pt}}\n\n"; + + + texString += "\\tikzset{owlDatatypeProperty/.style={rectangle,align=center,\n" + + "fill=owlDatatypePropertyColor, minimum width=80pt,\n" + + "inner sep=0mm,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "minimum height = 25pt}}\n\n"; + + texString += "\\tikzset{rdfsSubClassOf/.style={rectangle,align=center,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "inner sep=0mm,\n" + + "fill=imageBGCOLOR, minimum width=80pt,\n" + + "minimum height = 25pt}}\n\n"; + + texString += "\\tikzset{unionOf/.style={circle, inner sep=0mm,align=center,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "black, draw=black, line width=1pt, fill=unionColor, minimum size=25pt}}\n\n"; + + texString += "\\tikzset{disjointWith/.style={circle, inner sep=0mm,align=center,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "black, draw=black, line width=1pt, fill=unionColor, minimum size=20pt}}\n\n"; + + + texString += "\\tikzset{owlEquivalentClass/.style={circle,align=center,\n" + + "font={\\fontsize{12pt}{12}\\selectfont \\sffamily },\n" + + "inner sep=0mm,\n" + + "black, solid, draw=black, line width=3pt, fill=owlExternalClassColor, minimum size=101pt,\n" + + "postaction = {draw,line width=1pt, white}}}\n\n"; + + // draw a bounding box; + + // get bbox coordinates; + + + graph.options().navigationMenu().hideAllMenus(); + /** check if there is data **/ + if ( !exportableJsonText ) { + alert("No graph data available."); + // Stop the redirection to the path of the href attribute + d3.event.preventDefault(); + return; + } + + var i = 0, identifier; + + /** get data for exporter **/ + var nodeElements = graph.graphNodeElements(); // get visible nodes + var propElements = graph.graphLabelElements(); // get visible labels + var links = graph.graphLinkElements(); + + // export only nodes; + // draw Links; + for ( i = 0; i < links.length; i++ ) { + var link = links[i]; + // console.log("\n****************\nInverstigating Link for property "+link.property().labelForCurrentLanguage()); + + var prop = link.property(); + var dx, dy, px, py, rx, ry; + var colorStr = "black"; + var linkDomainIntersection; + var linkRangeIntersection; + var center; + var linkStyle = ""; + var isLoop = ""; + var curvePoint; + var pathStart; + var pathEnd; + var controlPoints; + var len; + var ahAngle; + var pathLen; + var markerOffset = 7; + + var arrowType = "triangleBlack"; + var linkWidth = ",line width=2pt"; + if ( prop.linkType ) { + if ( prop.linkType() === "dotted" ) { + //stroke-dasharray: 3; + linkStyle = ", dotted "; + arrowType = "triangleWhite"; + } + if ( prop.linkType() === "dashed" ) { + //stroke-dasharray: 3; + linkStyle = ", dashed "; + } + + if ( prop.linkType() === "values-from" ) { + colorStr = "valuesFrom"; + } + + } + + var startX, startY, endX, endY, normX, normY, lg; + + if ( link.layers().length === 1 && !link.loops() ) { + + linkDomainIntersection = graph.math().calculateIntersection(link.range(), link.domain(), 1); + linkRangeIntersection = graph.math().calculateIntersection(link.domain(), link.range(), 1); + center = graph.math().calculateCenter(linkDomainIntersection, linkRangeIntersection); + dx = linkDomainIntersection.x; + dy = -linkDomainIntersection.y; + px = center.x; + py = -center.y; + rx = linkRangeIntersection.x; + ry = -linkRangeIntersection.y; + + + pathStart = linkDomainIntersection; + curvePoint = center; + pathEnd = linkRangeIntersection; + + var nx = rx - px; + var ny = ry - py; + + // normalize ; + len = Math.sqrt(nx * nx + ny * ny); + + nx = nx / len; + ny = ny / len; + + ahAngle = Math.atan2(ny, nx) * (180 / Math.PI); + normX = nx; + normY = ny; + } + else { + if ( link.isLoop() ) { + isLoop = ", tension=3"; + controlPoints = graph.math().calculateLoopPoints(link); + pathStart = controlPoints[0]; + curvePoint = controlPoints[1]; + pathEnd = controlPoints[2]; + } else { + curvePoint = link.label(); + pathStart = graph.math().calculateIntersection(curvePoint, link.domain(), 1); + pathEnd = graph.math().calculateIntersection(curvePoint, link.range(), 1); + } + dx = pathStart.x; + dy = -pathStart.y; + px = curvePoint.x; + py = -curvePoint.y; + rx = pathEnd.x; + ry = -pathEnd.y; + } + + texString += "\\draw [" + colorStr + linkStyle + linkWidth + isLoop + "] plot [smooth] coordinates {(" + + dx + "pt, " + dy + "pt) (" + px + "pt, " + py + "pt) (" + rx + "pt, " + ry + "pt)};\n"; + + + if ( link.property().markerElement() === undefined ) continue; + + // add arrow head; + + + if ( link.property().type() === "owl:someValuesFrom" || link.property().type() === "owl:allValuesFrom" ) { + arrowType = "triangleBlue"; + } + + lg = link.pathObj(); + pathLen = Math.floor(lg.node().getTotalLength()); + var p1 = lg.node().getPointAtLength(pathLen - 4); + var p2 = lg.node().getPointAtLength(pathLen); + var markerCenter = lg.node().getPointAtLength(pathLen - 6); + + if ( link.property().type() === "setOperatorProperty" ) { + p1 = lg.node().getPointAtLength(4); + p2 = lg.node().getPointAtLength(0); + markerCenter = lg.node().getPointAtLength(8); + arrowType = "Diamond"; + } + + startX = p1.x; + startY = p1.y; + endX = p2.x; + endY = p2.y; + normX = endX - startX; + normY = endY - startY; + len = Math.sqrt(normX * normX + normY * normY); + normX = normX / len; + normY = normY / len; + + ahAngle = -1.0 * Math.atan2(normY, normX) * (180 / Math.PI); + ahAngle -= 90; + if ( link.property().type() === "setOperatorProperty" ) { + ahAngle -= 45; + } + // console.log(link.property().labelForCurrentLanguage()+ ": "+normX+ " "+normY +" "+ahAngle); + rx = markerCenter.x; + ry = markerCenter.y; + if ( link.layers().length === 1 && !link.loops() ) { + // markerOffset=-1*m + ry = -1 * ry; + texString += "\\node[" + arrowType + ", rotate=" + ahAngle + "] at (" + rx + "pt, " + ry + "pt) (single_marker" + i + ") {};\n "; + } else { + ry = -1 * ry; + texString += "\\node[" + arrowType + ", rotate=" + ahAngle + "] at (" + rx + "pt, " + ry + "pt) (marker" + i + ") {};\n "; + } + + // if (link.isLoop()){ + // rotAngle=-10+angle * (180 / Math.PI); + // } + + // add cardinality; + var cardinalityText = link.property().generateCardinalityText(); + if ( cardinalityText && cardinalityText.length > 0 ) { + var cardinalityCenter = lg.node().getPointAtLength(pathLen - 18); + var cx = cardinalityCenter.x - (10 * normY); + var cy = cardinalityCenter.y + (10 * normX); // using orthonormal y Coordinate + cy *= -1.0; + var textColor = "black"; + if ( cardinalityText.indexOf("A") > -1 ) { + cardinalityText = "$\\forall$"; + } + if ( cardinalityText.indexOf("E") > -1 ) { + cardinalityText = "$\\exists$"; + } + + + texString += "\\node[font={\\fontsize{12pt}{12}\\selectfont \\sffamily },text=" + textColor + "] at (" + cx + "pt, " + cy + "pt) (cardinalityText" + i + ") {" + cardinalityText + "};\n "; + } + + + if ( link.property().inverse() ) { + lg = link.pathObj(); + pathLen = Math.floor(lg.node().getTotalLength()); + var p1_inv = lg.node().getPointAtLength(4); + var p2_inv = lg.node().getPointAtLength(0); + var markerCenter_inv = lg.node().getPointAtLength(6); + startX = p1_inv.x; + startY = p1_inv.y; + endX = p2_inv.x; + endY = p2_inv.y; + normX = endX - startX; + normY = endY - startY; + len = Math.sqrt(normX * normX + normY * normY); + normX = normX / len; + normY = normY / len; + + ahAngle = -1.0 * Math.atan2(normY, normX) * (180 / Math.PI); + ahAngle -= 90; + // console.log("INV>>\n "+link.property().inverse().labelForCurrentLanguage()+ ": "+normX+ " "+normY +" "+ahAngle); + rx = markerCenter_inv.x; + ry = markerCenter_inv.y; + if ( link.layers().length === 1 && !link.loops() ) { + // markerOffset=-1*m + ry = -1 * ry; + texString += "\\node[" + arrowType + ", rotate=" + ahAngle + "] at (" + rx + "pt, " + ry + "pt) (INV_single_marker" + i + ") {};\n "; + } else { + ry = -1 * ry; + texString += "\\node[" + arrowType + ", rotate=" + ahAngle + "] at (" + rx + "pt, " + ry + "pt) (INV_marker" + i + ") {};\n "; + } + } + + + } + + + nodeElements.each(function ( node ){ + + px = node.x; + py = -node.y; + identifier = node.labelForCurrentLanguage(); + // console.log("Writing : "+ identifier); + if ( identifier === undefined ) identifier = ""; + var qType = "owlClass"; + if ( node.type() === "owl:Thing" || node.type() === "owl:Nothing" ) + qType = "owlThing"; + + if ( node.type() === "owl:equivalentClass" ) { + qType = "owlEquivalentClass"; + } + var textColorStr = ""; + if ( node.textBlock ) { + var txtColor = node.textBlock()._textBlock().style("fill"); + if ( txtColor === "rgb(0, 0, 0)" ) { + textColorStr = ", text=black"; + } + if ( txtColor === "rgb(255, 255, 255)" ) { + textColorStr = ", text=white"; + } + + + var tspans = node.textBlock()._textBlock().node().children; + if ( tspans[0] ) { + identifier = tspans[0].innerHTML; + if ( node.individuals() && node.individuals().length === parseInt(tspans[0].innerHTML) ) { + identifier = "{\\color{gray} " + tspans[0].innerHTML + " }"; + } + for ( var t = 1; t < tspans.length; t++ ) { + if ( node.individuals() && node.individuals().length === parseInt(tspans[t].innerHTML) ) { + identifier += "\\\\ {\\color{gray} " + tspans[t].innerHTML + " }"; + } else { + identifier += "\\\\ {\\small " + tspans[t].innerHTML + " }"; + } + } + } + } + if ( node.type() === "rdfs:Literal" ) { + qType = "Literal"; + } + if ( node.type() === "rdfs:Datatype" ) { + qType = "Datatype"; + } + if ( node.attributes().indexOf("anonymous") !== -1 ) { + qType = "anonymousClass"; + } + + + if ( node.type() === "owl:unionOf" || node.type() === "owl:complementOf" || node.type() === "owl:disjointUnionOf" || node.type() === "owl:intersectionOf" ) + qType = "owlClass"; + + var bgColorStr = ""; + var widthString = ""; + + if ( node.type() === "rdfs:Literal" || node.type() === "rdfs:Datatype" ) { + var width = node.width(); + widthString = ",minimum width=" + width + "pt"; + } + else { + widthString = ",minimum size=" + 2 * node.actualRadius() + "pt"; + + } + if ( node.backgroundColor() ) { + var bgColor = node.backgroundColor(); + bgColor.toUpperCase(); + bgColor = bgColor.slice(1, bgColor.length); + texString += "\\definecolor{Node" + i + "_COLOR}{HTML}{" + bgColor + "} \n "; + bgColorStr = ", fill=Node" + i + "_COLOR "; + } + if ( node.attributes().indexOf("deprecated") > -1 ) { + texString += "\\definecolor{Node" + i + "_COLOR}{HTML}{CCCCCC} \n "; + bgColorStr = ", fill=Node" + i + "_COLOR "; + } + + var leftPos = px - 7; + var rightPos = px + 7; + var txtOffset = py + 20; + if ( node.type() !== "owl:unionOf" || node.type() !== "owl:disjointUnionOf" ) { + texString += "\\node[" + qType + " " + widthString + " " + bgColorStr + " " + textColorStr + "] at (" + px + "pt, " + py + "pt) (Node" + i + ") {" + identifier.replaceAll("_", "\\_ ") + "};\n"; + } + if ( node.type() === "owl:unionOf" ) { + // add symbol to it; + texString += "\\node[" + qType + " " + widthString + " " + bgColorStr + " " + textColorStr + "] at (" + px + "pt, " + py + "pt) (Node" + i + ") {};\n"; + texString += "\\node[unionOf , text=black] at (" + leftPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[unionOf , text=black] at (" + rightPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[unionOf ,fill=none , text=black] at (" + leftPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[text=black] at (" + px + "pt, " + py + "pt) (unionText13) {$\\mathbf{\\cup}$};\n"; + texString += "\\node[font={\\fontsize{12pt}{12}\\selectfont \\sffamily }" + textColorStr + "] at (" + px + "pt, " + txtOffset + "pt) (Node_text" + i + ") {" + identifier.replaceAll("_", "\\_ ") + "};\n"; + } + // OWL DISJOINT UNION OF + if ( node.type() === "owl:disjointUnionOf" ) { + texString += "\\node[" + qType + " " + widthString + " " + bgColorStr + " " + textColorStr + "] at (" + px + "pt, " + py + "pt) (Node" + i + ") {};\n"; + texString += "\\node[unionOf , text=black] at (" + leftPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[unionOf , text=black] at (" + rightPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[unionOf ,fill=none , text=black] at (" + leftPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[font={\\fontsize{12pt}{12}\\selectfont \\sffamily }" + textColorStr + "] at (" + px + "pt, " + py + "pt) (disjointUnoinText" + i + ") {1};\n"; + texString += "\\node[font={\\fontsize{12pt}{12}\\selectfont \\sffamily }" + textColorStr + "] at (" + px + "pt, " + txtOffset + "pt) (Node_text" + i + ") {" + identifier.replaceAll("_", "\\_ ") + "};\n"; + } + // OWL COMPLEMENT OF + if ( node.type() === "owl:complementOf" ) { + // add symbol to it; + texString += "\\node[" + qType + " " + widthString + " " + bgColorStr + " " + textColorStr + "] at (" + px + "pt, " + py + "pt) (Node" + i + ") {};\n"; + texString += "\\node[unionOf , text=black] at (" + px + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[font={\\fontsize{18pt}{18}\\selectfont \\sffamily }" + textColorStr + "] at (" + px + "pt, " + py + "pt) (unionText13) {$\\neg$};\n"; + texString += "\\node[font={\\fontsize{12pt}{12}\\selectfont \\sffamily }" + textColorStr + "] at (" + px + "pt, " + txtOffset + "pt) (Node_text" + i + ") {" + identifier.replaceAll("_", "\\_ ") + "};\n"; + } + // OWL INTERSECTION OF + if ( node.type() === "owl:intersectionOf" ) { + texString += "\\node[" + qType + " " + widthString + " " + bgColorStr + " " + textColorStr + "] at (" + px + "pt, " + py + "pt) (Node" + i + ") {};\n"; + texString += "\\node[unionOf , text=black] at (" + leftPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[unionOf , text=black] at (" + rightPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[unionOf ,fill=none , text=black] at (" + leftPos + "pt, " + py + "pt) (SymbolNode" + i + ") {};\n"; + + // add now the outer colors; + texString += "\\filldraw[even odd rule,fill=owlClassColor,line width=1pt] (" + leftPos + "pt, " + py + "pt) circle (12.5pt) (" + rightPos + "pt, " + py + "pt) circle (12.5pt);\n "; + + // add texts + texString += "\\node[font={\\fontsize{12pt}{12}\\selectfont \\sffamily }" + textColorStr + "] at (" + px + "pt, " + py + "pt) (intersectionText" + i + ") {$\\cap$};\n"; + texString += "\\node[font={\\fontsize{12pt}{12}\\selectfont \\sffamily }" + textColorStr + "] at (" + px + "pt, " + txtOffset + "pt) (Node_text" + i + ") {" + identifier.replaceAll("_", "\\_ ") + "};\n"; + + } + + + i++; + + }); + for ( i = 0; i < propElements.length; i++ ) { + var correspondingProp = propElements[i].property(); + var p_px = propElements[i].x; + var p_py = -propElements[i].y; + identifier = correspondingProp.labelForCurrentLanguage(); + if ( identifier === undefined ) identifier = ""; + var textColorStr = ""; + if ( correspondingProp.textBlock && correspondingProp.textBlock() ) { + var txtColor = correspondingProp.textBlock()._textBlock().style("fill"); + // console.log("PropertyTextColor="+txtColor); + if ( txtColor === "rgb(0, 0, 0)" ) { + textColorStr = ", text=black"; + } + if ( txtColor === "rgb(255, 255, 255)" ) { + textColorStr = ", text=white"; + } + var tspans = correspondingProp.textBlock()._textBlock().node().children; + + // identifier=node.textBlock()._textBlock().text(); + // console.log(tspans); + if ( tspans[0] ) { + identifier = tspans[0].innerHTML; + + for ( var t = 1; t < tspans.length; t++ ) { + var spanText = tspans[t].innerHTML; + if ( spanText.indexOf("(") > -1 ) { + identifier += "\\\\ {\\small " + tspans[t].innerHTML + " }"; + } + else { + identifier += "\\\\ " + tspans[t].innerHTML; + } + } + } + else { + } + } + if ( correspondingProp.type() === "setOperatorProperty" ) { + continue; // this property does not have a label + } + var qType = "owlObjectProperty"; + if ( correspondingProp.type() === "owl:DatatypeProperty" ) { + qType = "owlDatatypeProperty"; + } + if ( correspondingProp.type() === "rdfs:subClassOf" ) { + qType = "rdfsSubClassOf"; + } + if ( correspondingProp.type() === "rdf:Property" ) { + qType = "rdfProperty"; + } + + + var bgColorStr = ""; + if ( correspondingProp.backgroundColor() ) { + // console.log("Found backGround color"); + var bgColor = correspondingProp.backgroundColor(); + //console.log(bgColor); + bgColor.toUpperCase(); + bgColor = bgColor.slice(1, bgColor.length); + texString += "\\definecolor{property" + i + "_COLOR}{HTML}{" + bgColor + "} \n "; + bgColorStr = ", fill=property" + i + "_COLOR "; + } + if ( correspondingProp.attributes().indexOf("deprecated") > -1 ) { + texString += "\\definecolor{property" + i + "_COLOR}{HTML}{CCCCCC} \n "; + bgColorStr = ", fill=property" + i + "_COLOR "; + } + + var widthString = ""; + var width = correspondingProp.textWidth(); + widthString = ",minimum width=" + width + "pt"; + + + // OWL INTERSECTION OF + if ( correspondingProp.type() === "owl:disjointWith" ) { + var leftPos = p_px - 12; + var rightPos = p_px + 12; + var txtOffset = p_py - 20; + texString += "\\node[" + qType + " " + widthString + " " + bgColorStr + " " + textColorStr + "] at (" + p_px + "pt, " + p_py + "pt) (Node" + i + ") {};\n"; + texString += "\\node[disjointWith , text=black] at (" + leftPos + "pt, " + p_py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[disjointWith , text=black] at (" + rightPos + "pt, " + p_py + "pt) (SymbolNode" + i + ") {};\n"; + texString += "\\node[font={\\fontsize{12pt}{12}\\selectfont \\sffamily }" + textColorStr + "] at (" + p_px + "pt, " + txtOffset + "pt) (Node_text" + i + ") {"; + if ( graph.options().compactNotation() === false ) { + texString += "(disjoint)"; + } + texString += "};\n"; + continue; + } + + + if ( correspondingProp.inverse() ) { + var inv_correspondingProp = correspondingProp.inverse(); + // create the rendering element for the inverse property; + var inv_identifier = inv_correspondingProp.labelForCurrentLanguage(); + if ( inv_identifier === undefined ) inv_identifier = ""; + var inv_textColorStr = ""; + //console.log(inv_correspondingProp); + //console.log(inv_correspondingProp.textBlock()); + + if ( inv_correspondingProp.textBlock && inv_correspondingProp.textBlock() ) { + + var inv_txtColor = inv_correspondingProp.textBlock()._textBlock().style("fill"); + // console.log("PropertyTextColor="+inv_txtColor); + if ( inv_txtColor === "rgb(0, 0, 0)" ) { + inv_textColorStr = ", text=black"; + } + if ( inv_txtColor === "rgb(255, 255, 255)" ) { + inv_textColorStr = ", text=white"; + } + var inv_tspans = inv_correspondingProp.textBlock()._textBlock().node().children; + + // identifier=node.textBlock()._textBlock().text(); + // console.log(inv_tspans); + if ( inv_tspans[0] ) { + inv_identifier = inv_tspans[0].innerHTML; + + for ( var inv_t = 1; inv_t < inv_tspans.length; inv_t++ ) { + var ispanText = inv_tspans[inv_t].innerHTML; + if ( ispanText.indexOf("(") > -1 ) { + inv_identifier += "\\\\ {\\small " + inv_tspans[inv_t].innerHTML + " }"; + } else { + inv_identifier += "\\\\ " + inv_tspans[inv_t].innerHTML; + } + } + } + } + var inv_qType = "owlObjectProperty"; + var inv_bgColorStr = ""; + + if ( inv_correspondingProp.backgroundColor() ) { + // console.log("Found backGround color"); + var inv_bgColor = inv_correspondingProp.backgroundColor(); + // console.log(inv_bgColor); + inv_bgColor.toUpperCase(); + inv_bgColor = inv_bgColor.slice(1, inv_bgColor.length); + texString += "\\definecolor{inv_property" + i + "_COLOR}{HTML}{" + inv_bgColor + "} \n "; + inv_bgColorStr = ", fill=inv_property" + i + "_COLOR "; + } + if ( inv_correspondingProp.attributes().indexOf("deprecated") > -1 ) { + texString += "\\definecolor{inv_property" + i + "_COLOR}{HTML}{CCCCCC} \n "; + inv_bgColorStr = ", fill=inv_property" + i + "_COLOR "; + } + + var inv_widthString = ""; + var inv_width = inv_correspondingProp.textWidth(); + + var pOY1 = p_py - 14; + var pOY2 = p_py + 14; + inv_widthString = ",minimum width=" + inv_width + "pt"; + texString += "% Createing Inverse Property \n"; + texString += "\\node[" + inv_qType + " " + inv_widthString + " " + inv_bgColorStr + " " + inv_textColorStr + "] at (" + p_px + "pt, " + pOY1 + "pt) (property" + i + ") {" + inv_identifier.replaceAll("_", "\\_ ") + "};\n"; + texString += "% " + inv_qType + " vs " + qType + "\n"; + texString += "% " + inv_widthString + " vs " + widthString + "\n"; + texString += "% " + inv_bgColorStr + " vs " + bgColorStr + "\n"; + texString += "% " + inv_textColorStr + " vs " + textColorStr + "\n"; + + texString += "\\node[" + qType + " " + widthString + " " + bgColorStr + " " + textColorStr + "] at (" + p_px + "pt, " + pOY2 + "pt) (property" + i + ") {" + identifier.replaceAll("_", "\\_ ") + "};\n"; + + } else { + texString += "\\node[" + qType + " " + widthString + " " + bgColorStr + " " + textColorStr + "] at (" + p_px + "pt, " + p_py + "pt) (property" + i + ") {" + identifier.replaceAll("_", "\\_ ") + "};\n"; + } + } + + texString += "\\end{tikzpicture}\n}\n \\end{center}\n"; + + // console.log("Tex Output\n"+ texString); + var dataURI = "data:text/json;charset=utf-8," + encodeURIComponent(texString); + exportTexButton.attr("href", dataURI) + .attr("download", exportFilename + ".tex"); + + + } + + function calculateRadian( angle ){ + angle = angle % 360; + if ( angle < 0 ) { + angle = angle + 360; + } + return (Math.PI * angle) / 180; + } + + function calculateAngle( radian ){ + return radian * (180 / Math.PI); + } + + return exportMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 324: +/***/ (function(module, exports) { + + /** + * Contains the logic for the export button. + * @returns {{}} + */ + module.exports = function ( graph ){ + var exportTTLModule = {}; + var resultingTTLContent = ""; + var currentNodes; + var currentProperties; + var currentAxioms; + var Map_ID2Node = {}; + var Map_ID2Prop = {}; + var prefixModule = webvowl.util.prefixTools(graph); + + exportTTLModule.requestExport = function (){ + prefixModule.updatePrefixModel(); + resultingTTLContent = ""; + currentNodes = graph.getClassDataForTtlExport(); + var i; + for ( i = 0; i < currentNodes.length; i++ ) { + Map_ID2Node[currentNodes[i].id()] = currentNodes[i]; + } + currentProperties = graph.getPropertyDataForTtlExport(); + + for ( i = 0; i < currentProperties.length; i++ ) { + Map_ID2Prop[currentProperties[i].id()] = currentProperties[i]; + } + + + prepareHeader(); + preparePrefixList(); + prepareOntologyDef(); + resultingTTLContent += "#################################################################\r\n\r\n"; + preparePrefixRepresentation(); + var property_success = exportProperties(); + var class_success = exportClasses(); + currentNodes = null; + currentProperties = null; + Map_ID2Node = {}; + Map_ID2Prop = {}; + if ( property_success === false || class_success === false ) + return false; + return true; + + }; + + function preparePrefixRepresentation(){ + var i; + var allNodes = graph.getUnfilteredData().nodes; + var allProps = graph.getUnfilteredData().properties; + for ( i = 0; i < allNodes.length; i++ ) { + var nodeIRI = prefixModule.getPrefixRepresentationForFullURI(allNodes[i].iri()); + if ( prefixModule.validURL(nodeIRI) === true ) + allNodes[i].prefixRepresentation = "<" + nodeIRI + ">"; + else + allNodes[i].prefixRepresentation = nodeIRI; + } + for ( i = 0; i < allProps.length; i++ ) { + var propIRI = prefixModule.getPrefixRepresentationForFullURI(allProps[i].iri()); + if ( prefixModule.validURL(propIRI) === true ) + allProps[i].prefixRepresentation = "<" + propIRI + ">"; + else + allProps[i].prefixRepresentation = propIRI; + } + } + + function exportProperties(){ + if ( currentProperties.length === 0 ) return; // we dont need to write that + resultingTTLContent += "### Property Definitions (Number of Property) " + currentProperties.length + " ###\r\n"; + for ( var i = 0; i < currentProperties.length; i++ ) { + + resultingTTLContent += "# --------------------------- Property " + i + "------------------------- \r\n"; + var addedElement = extractPropertyDescription(currentProperties[i]); + resultingTTLContent += addedElement; + //@ workaround for not supported elements + if ( addedElement.indexOf("WHYEMPTYNAME") !== -1 ) { + return false; + } + } + return true; + } + + + function exportClasses(){ + if ( currentNodes.length === 0 ) return; // we dont need to write that + resultingTTLContent += "### Class Definitions (Number of Classes) " + currentNodes.length + " ###\r\n"; + for ( var i = 0; i < currentNodes.length; i++ ) { + // check for node type here and return false + resultingTTLContent += "# --------------------------- Class " + i + "------------------------- \r\n"; + var addedElement = extractClassDescription(currentNodes[i]); + resultingTTLContent += addedElement; + + if ( addedElement.indexOf("WHYEMPTYNAME") !== -1 ) { + return false; + } + } + return true; + } + + function getPresentAttribute( selectedElement, element ){ + var attr = selectedElement.attributes(); + return (attr.indexOf(element) >= 0); + } + + function extractClassDescription( node ){ + var subject = node.prefixRepresentation; + var predicate = "rdf:type"; + var object = node.type(); + if ( node.type() === "owl:equivalentClass" ) + object = "owl:Class"; + if ( node.type() === "owl:disjointUnionOf" ) + object = "owl:Class"; + if ( node.type() === "owl:unionOf" ) + object = "owl:Class"; + var arrayOfNodes = []; + var arrayOfUnionNodes = []; + + if ( node.union() ) { + var union = node.union(); + for ( var u = 0; u < union.length; u++ ) { + var u_node = Map_ID2Node[union[u]]; + arrayOfUnionNodes.push(u_node); + } + } + + if ( node.disjointUnion() ) { + var distUnion = node.disjointUnion(); + for ( var du = 0; du < distUnion.length; du++ ) { + var du_node = Map_ID2Node[distUnion[du]]; + arrayOfNodes.push(du_node); + } + } + + var objectDef = subject + " " + predicate + " " + object; + if ( getPresentAttribute(node, "deprecated") === true ) { + objectDef += ", owl:DeprecatedProperty"; + } + // equivalent class handeled using type itself! + + // check for equivalent classes; + var indent = getIndent(subject); + objectDef += "; \r\n"; + for ( var e = 0; e < node.equivalents().length; e++ ) { + var eqIRI = prefixModule.getPrefixRepresentationForFullURI(node.equivalents()[e].iri()); + var eqNode_prefRepresentation = ""; + if ( prefixModule.validURL(eqIRI) === true ) + eqNode_prefRepresentation = "<" + eqIRI + ">"; + else + eqNode_prefRepresentation = eqIRI; + objectDef += indent + " owl:equivalentClass " + eqNode_prefRepresentation + " ;\r\n"; + } + + // if (getPresentAttribute(node,"equivalent")===true){ + // objectDef+=", owl:EquivalentClass"; + // } + + // add Comments + + if ( node.commentForCurrentLanguage() ) { + + objectDef += indent + " rdfs:comment \"" + node.commentForCurrentLanguage() + "\" ;\r\n"; + } + + if ( node.annotations() ) { + var annotations = node.annotations(); + for ( var an in annotations ) { + if ( annotations.hasOwnProperty(an) ) { + var anArrayObj = annotations[an]; + var anObj = anArrayObj[0]; + var an_ident = anObj.identifier; + var an_val = anObj.value; + + if ( an_ident === "isDefinedBy" ) { + objectDef += indent + " rdfs:isDefinedBy <" + an_val + "> ;\r\n"; + } + if ( an_ident === "term_status" ) { + objectDef += indent + " vs:term_status \"" + an_val + "\" ;\r\n"; + } + } + } + } + + + if ( arrayOfNodes.length > 0 ) { + // add disjoint unionOf + objectDef += indent + " owl:disjointUnionOf ("; + for ( var duE = 0; duE < arrayOfNodes.length; duE++ ) { + var duIri = prefixModule.getPrefixRepresentationForFullURI(arrayOfNodes[duE].iri()); + var duNode_prefRepresentation = ""; + if ( prefixModule.validURL(duIri) === true ) + duNode_prefRepresentation = "<" + duIri + ">"; + else + duNode_prefRepresentation = duIri; + objectDef += indent + indent + duNode_prefRepresentation + " \n"; + } + objectDef += ") ;\r\n"; + } + + if ( arrayOfUnionNodes.length > 0 ) { + // add disjoint unionOf + objectDef += indent + " rdfs:subClassOf [ rdf:type owl:Class ; \r\n"; + objectDef += indent + indent + " owl:unionOf ( "; + + for ( var uE = 0; uE < arrayOfUnionNodes.length; uE++ ) { + + if ( arrayOfUnionNodes[uE] && arrayOfUnionNodes[uE].iri() ) { + var uIri = prefixModule.getPrefixRepresentationForFullURI(arrayOfUnionNodes[uE].iri()); + var uNode_prefRepresentation = ""; + if ( prefixModule.validURL(uIri) === true ) + uNode_prefRepresentation = "<" + uIri + ">"; + else + uNode_prefRepresentation = uIri; + objectDef += indent + indent + indent + uNode_prefRepresentation + " \n"; + } + } + objectDef += ") ;\r\n"; + + + } + + + var allProps = graph.getUnfilteredData().properties; + var myProperties = []; + var i; + for ( i = 0; i < allProps.length; i++ ) { + if ( allProps[i].domain() === node && + ( allProps[i].type() === "rdfs:subClassOf" || + allProps[i].type() === "owl:allValuesFrom" || + allProps[i].type() === "owl:someValuesFrom") + ) { + myProperties.push(allProps[i]); + } + // special case disjoint with>> both domain and range get that property + if ( (allProps[i].domain() === node) && + allProps[i].type() === "owl:disjointWith" ) { + myProperties.push(allProps[i]); + } + + } + for ( i = 0; i < myProperties.length; i++ ) { + // depending on the property we have to do some things; + + // special case + if ( myProperties[i].type() === "owl:someValuesFrom" ) { + objectDef += indent + " rdfs:subClassOf [ rdf:type owl:Restriction ; \r\n"; + objectDef += indent + " owl:onProperty " + myProperties[i].prefixRepresentation + ";\r\n"; + if ( myProperties[i].range().type() !== "owl:Thing" ) { + objectDef += indent + " owl:someValuesFrom " + myProperties[i].range().prefixRepresentation + "\r\n"; + } + objectDef += indent + " ];\r\n"; + continue; + } + + if ( myProperties[i].type() === "owl:allValuesFrom" ) { + objectDef += indent + " rdfs:subClassOf [ rdf:type owl:Restriction ; \r\n"; + objectDef += indent + " owl:onProperty " + myProperties[i].prefixRepresentation + ";\r\n"; + if ( myProperties[i].range().type() !== "owl:Thing" ) { + objectDef += indent + " owl:allValuesFrom " + myProperties[i].range().prefixRepresentation + "\r\n"; + } + objectDef += indent + " ];\r\n"; + continue; + } + + if ( myProperties[i].range().type() !== "owl:Thing" ) { + objectDef += indent + " " + myProperties[i].prefixRepresentation + + " " + myProperties[i].range().prefixRepresentation + " ;\r\n"; + + + } + } + + + objectDef += general_Label_languageExtractor(indent, node.label(), "rdfs:label", true); + return objectDef; + + } + + function extractPropertyDescription( property ){ + var subject = property.prefixRepresentation; + if ( subject.length === 0 ) { + console.log("THIS SHOULD NOT HAPPEN"); + var propIRI = prefixModule.getPrefixRepresentationForFullURI(property.iri()); + console.log("FOUND " + propIRI); + + + } + var predicate = "rdf:type"; + var object = property.type(); + + var objectDef = subject + " " + predicate + " " + object; + if ( getPresentAttribute(property, "deprecated") === true ) { + objectDef += ", owl:DeprecatedProperty"; + } + if ( getPresentAttribute(property, "functional") === true ) { + objectDef += ", owl:FunctionalProperty"; + } + if ( getPresentAttribute(property, "inverse functional") === true ) { + objectDef += ", owl:InverseFunctionalProperty"; + } + if ( getPresentAttribute(property, "symmetric") === true ) { + objectDef += ", owl:SymmetricProperty"; + } + if ( getPresentAttribute(property, "transitive") === true ) { + objectDef += ", owl:TransitiveProperty"; + } + var indent = getIndent(subject); + + if ( property.inverse() ) { + objectDef += "; \r\n"; + objectDef += indent + " owl:inverseOf " + property.inverse().prefixRepresentation; + } + + // check for domain and range; + + + var closeStatement = false; + var domain = property.domain(); + var range = property.range(); + + + objectDef += " ;\r\n"; + + + if ( property.commentForCurrentLanguage() ) { + + objectDef += indent + " rdfs:comment \"" + property.commentForCurrentLanguage() + "\" ;\r\n"; + } + + if ( property.superproperties() ) { + var superProps = property.superproperties(); + for ( var sP = 0; sP < superProps.length; sP++ ) { + var sPelement = superProps[sP]; + objectDef += indent + "rdfs:subPropertyOf " + sPelement.prefixRepresentation + ";\r\n"; + } + // for (var an in annotations){ + // if (annotations.hasOwnProperty(an)){ + // var anArrayObj=annotations[an]; + // var anObj=anArrayObj[0]; + // var an_ident=anObj.identifier; + // var an_val=anObj.value; + // console.log(an_ident + " "+ an_val); + // + // if (an_ident==="isDefinedBy"){ + // objectDef+=indent+" rdfs:isDefinedBy <"+an_val+"> ;\r\n"; + // } + // if (an_ident==="term_status"){ + // objectDef+=indent+" vs:term_status \""+an_val+"\" ;\r\n"; + // } + // } + // } + + } + + if ( property.annotations() ) { + var annotations = property.annotations(); + for ( var an in annotations ) { + if ( annotations.hasOwnProperty(an) ) { + var anArrayObj = annotations[an]; + var anObj = anArrayObj[0]; + var an_ident = anObj.identifier; + var an_val = anObj.value; + + if ( an_ident === "isDefinedBy" ) { + objectDef += indent + " rdfs:isDefinedBy <" + an_val + "> ;\r\n"; + } + if ( an_ident === "term_status" ) { + objectDef += indent + " vs:term_status \"" + an_val + "\" ;\r\n"; + } + } + } + } + + + if ( domain.type() === "owl:Thing" && range.type() === "owl:Thing" ) { + // we do not write domain and range + if ( typeof property.label() !== "object" && property.label().length === 0 ) { + closeStatement = true; + } + } + + + if ( closeStatement === true ) { + var uobjectDef = objectDef.substring(0, objectDef.length - 2); + objectDef = uobjectDef + " . \r\n"; + return objectDef; + } + // objectDef+="; \r\n"; + var labelDescription; + + + if ( domain.type() === "owl:Thing" && range.type() === "owl:Thing" ) { + labelDescription = general_Label_languageExtractor(indent, property.label(), "rdfs:label", true); + objectDef += labelDescription; + } + else { + // do not close the statement; + labelDescription = general_Label_languageExtractor(indent, property.label(), "rdfs:label"); + objectDef += labelDescription; + if ( domain.type() !== "owl:Thing" ) { + objectDef += indent + " rdfs:domain " + domain.prefixRepresentation + ";\r\n"; + } + if ( range.type() !== "owl:Thing" ) { + objectDef += indent + " rdfs:range " + range.prefixRepresentation + ";\r\n"; + } + + // close statement now; + + var s_needUpdate = objectDef; + var s_lastPtr = s_needUpdate.lastIndexOf(";"); + objectDef = s_needUpdate.substring(0, s_lastPtr) + " . \r\n"; + } + + return objectDef; + + } + + + exportTTLModule.resultingTTL_Content = function (){ + return resultingTTLContent; + }; + + function getIndent( name ){ + if ( name === undefined ) { + return "WHYEMPTYNAME?"; + } + return new Array(name.length + 1).join(" "); + } + + function prepareHeader(){ + resultingTTLContent += "#################################################################\r\n"; + resultingTTLContent += "### Generated with the experimental alpha version of the TTL exporter of WebVOWL (version 1.1.7) " + + " http://visualdataweb.de/webvowl/ ###\r\n"; + resultingTTLContent += "#################################################################\r\n\r\n"; + + } + + function preparePrefixList(){ + var ontoIri = graph.options().getGeneralMetaObjectProperty('iri'); + var prefixList = graph.options().prefixList(); + var prefixDef = []; + prefixDef.push('@prefix : \t\t<' + ontoIri + '> .'); + for ( var name in prefixList ) { + if ( prefixList.hasOwnProperty(name) ) { + prefixDef.push('@prefix ' + name + ': \t\t<' + prefixList[name] + '> .'); + } + } + prefixDef.push('@base \t\t\t<' + ontoIri + '> .\r\n'); + + for ( var i = 0; i < prefixDef.length; i++ ) { + resultingTTLContent += prefixDef[i] + '\r\n'; + } + } + + function prepareOntologyDef(){ + var ontoIri = graph.options().getGeneralMetaObjectProperty('iri'); + var indent = getIndent('<' + ontoIri + '>'); + resultingTTLContent += '<' + ontoIri + '> rdf:type owl:Ontology ;\r\n' + + getOntologyTitle(indent) + + getOntologyDescription(indent) + + getOntologyVersion(indent) + + getOntologyAuthor(indent); + + // close the statement; + var s_needUpdate = resultingTTLContent; + var s_lastPtr = s_needUpdate.lastIndexOf(";"); + resultingTTLContent = s_needUpdate.substring(0, s_lastPtr) + " . \r\n"; + } + + function getOntologyTitle( indent ){ + return general_languageExtractor(indent, "title", "dc:title"); + } + + function getOntologyDescription( indent ){ + return general_languageExtractor(indent, "description", "dc:description"); + } + + function getOntologyAuthor( indent ){ + var languageElement = graph.options().getGeneralMetaObjectProperty('author'); + if ( languageElement ) { + if ( typeof languageElement !== "object" ) { + if ( languageElement.length === 0 ) + return ""; // an empty string + var aString = indent + " dc:creator " + '"' + languageElement + '";\r\n'; + return aString; + } + // we assume this thing is an array; + var authorString = indent + " dc:creator " + '"'; + for ( var i = 0; i < languageElement.length - 1; i++ ) { + authorString += languageElement[i] + ", "; + } + authorString += languageElement[languageElement.length - 1] + '";\r\n'; + return authorString; + } else { + return ""; // an empty string + } + } + + function getOntologyVersion( indent ){ + var languageElement = graph.options().getGeneralMetaObjectProperty('version'); + if ( languageElement ) { + if ( typeof languageElement !== "object" ) { + if ( languageElement.length === 0 ) + return ""; // an empty string + } + return general_languageExtractor(indent, "version", "owl:versionInfo"); + } else return ""; // an empty string + } + + function general_languageExtractor( indent, metaObjectDescription, annotationDescription, endStatement ){ + var languageElement = graph.options().getGeneralMetaObjectProperty(metaObjectDescription); + + if ( typeof languageElement === 'object' ) { + + var resultingLanguages = []; + for ( var name in languageElement ) { + if ( languageElement.hasOwnProperty(name) ) { + var content = languageElement[name]; + if ( name === "undefined" ) { + resultingLanguages.push(indent + " " + annotationDescription + ' "' + content + '"@en; \r\n'); + } + else { + resultingLanguages.push(indent + " " + annotationDescription + ' "' + content + '"@' + name + '; \r\n'); + } + } + } + // create resulting titles; + + var resultingString = ""; + for ( var i = 0; i < resultingLanguages.length; i++ ) { + resultingString += resultingLanguages[i]; + } + if ( endStatement && endStatement === true ) { + var needUpdate = resultingString; + var lastPtr = needUpdate.lastIndexOf(";"); + return needUpdate.substring(0, lastPtr) + ". \r\n"; + } else { + return resultingString; + } + + } else { + if ( endStatement && endStatement === true ) { + var s_needUpdate = indent + " " + annotationDescription + ' "' + languageElement + '"@en; \r\n'; + var s_lastPtr = s_needUpdate.lastIndexOf(";"); + return s_needUpdate.substring(0, s_lastPtr) + " . \r\n"; + } + return indent + " " + annotationDescription + ' "' + languageElement + '"@en;\r\n'; + } + } + + function general_Label_languageExtractor( indent, label, annotationDescription, endStatement ){ + var languageElement = label; + + if ( typeof languageElement === 'object' ) { + var resultingLanguages = []; + for ( var name in languageElement ) { + if ( languageElement.hasOwnProperty(name) ) { + var content = languageElement[name]; + if ( name === "undefined" ) { + resultingLanguages.push(indent + " " + annotationDescription + ' "' + content + '"@en; \r\n'); + } + else { + resultingLanguages.push(indent + " " + annotationDescription + ' "' + content + '"@' + name + '; \r\n'); + } + } + } + // create resulting titles; + var resultingString = ""; + for ( var i = 0; i < resultingLanguages.length; i++ ) { + resultingString += resultingLanguages[i]; + } + if ( endStatement && endStatement === true ) { + var needUpdate = resultingString; + var lastPtr = needUpdate.lastIndexOf(";"); + return needUpdate.substring(0, lastPtr) + " . \r\n"; + } else { + return resultingString; + } + + } else { + if ( endStatement && endStatement === true ) { + var s_needUpdate = indent + " " + annotationDescription + ' "' + languageElement + '"@en; \r\n'; + var s_lastPtr = s_needUpdate.lastIndexOf(";"); + return s_needUpdate.substring(0, s_lastPtr) + " . \r\n"; + } + return indent + " " + annotationDescription + ' "' + languageElement + '"@en; \r\n'; + } + } + + return exportTTLModule; + }; + + +/***/ }), + +/***/ 325: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for connecting the filters with the website. + * + * @param graph required for calling a refresh after a filter change + * @returns {{}} + */ + module.exports = function ( graph ){ + + var filterMenu = {}, + checkboxData = [], + menuElement = d3.select("#m_filter"), + menuControl = d3.select("#c_filter a"), + nodeDegreeContainer = d3.select("#nodeDegreeFilteringOption"), + graphDegreeLevel, + defaultDegreeValue = 0, + degreeSlider; + + filterMenu.setDefaultDegreeValue = function ( val ){ + defaultDegreeValue = val; + }; + filterMenu.getDefaultDegreeValue = function (){ + return defaultDegreeValue; + }; + + filterMenu.getGraphObject = function (){ + return graph; + }; + /** some getter function **/ + filterMenu.getCheckBoxContainer = function (){ + return checkboxData; + }; + + filterMenu.getDegreeSliderValue = function (){ + return degreeSlider.property("value"); + }; + /** + * Connects the website with graph filters. + * @param datatypeFilter filter for all datatypes + * @param objectPropertyFilter filter for all object properties + * @param subclassFilter filter for all subclasses + * @param disjointFilter filter for all disjoint with properties + * @param setOperatorFilter filter for all set operators with properties + * @param nodeDegreeFilter filters nodes by their degree + */ + filterMenu.setup = function ( datatypeFilter, objectPropertyFilter, subclassFilter, disjointFilter, setOperatorFilter, nodeDegreeFilter ){ + // TODO: is this here really necessarry? << new menu visualization style? + menuControl.on("mouseover", function (){ + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + }); + menuControl.on("mouseleave", function (){ + filterMenu.highlightForDegreeSlider(false); + }); + + addFilterItem(datatypeFilter, "datatype", "Datatype properties", "#datatypeFilteringOption"); + addFilterItem(objectPropertyFilter, "objectProperty", "Object properties", "#objectPropertyFilteringOption"); + addFilterItem(subclassFilter, "subclass", "Solitary subclasses", "#subclassFilteringOption"); + addFilterItem(disjointFilter, "disjoint", "Class disjointness", "#disjointFilteringOption"); + addFilterItem(setOperatorFilter, "setoperator", "Set operators", "#setOperatorFilteringOption"); + + addNodeDegreeFilter(nodeDegreeFilter, nodeDegreeContainer); + addAnimationFinishedListener(); + }; + + + function addFilterItem( filter, identifier, pluralNameOfFilteredItems, selector ){ + var filterContainer, + filterCheckbox; + + filterContainer = d3.select(selector) + .append("div") + .classed("checkboxContainer", true); + + filterCheckbox = filterContainer.append("input") + .classed("filterCheckbox", true) + .attr("id", identifier + "FilterCheckbox") + .attr("type", "checkbox") + .property("checked", filter.enabled()); + + // Store for easier resetting + checkboxData.push({ checkbox: filterCheckbox, defaultState: filter.enabled() }); + + filterCheckbox.on("click", function ( silent ){ + // There might be no parameters passed because of a manual + // invocation when resetting the filters + var isEnabled = filterCheckbox.property("checked"); + filter.enabled(isEnabled); + if ( silent !== true ) { + // updating graph when silent is false or the parameter is not given. + graph.update(); + } + }); + + filterContainer.append("label") + .attr("for", identifier + "FilterCheckbox") + .text(pluralNameOfFilteredItems); + } + + function addNodeDegreeFilter( nodeDegreeFilter, container ){ + nodeDegreeFilter.setMaxDegreeSetter(function ( maxDegree ){ + degreeSlider.attr("max", maxDegree); + setSliderValue(degreeSlider, Math.min(maxDegree, degreeSlider.property("value"))); + }); + + nodeDegreeFilter.setDegreeGetter(function (){ + return degreeSlider.property("value"); + }); + + nodeDegreeFilter.setDegreeSetter(function ( value ){ + setSliderValue(degreeSlider, value); + }); + + var sliderContainer, + sliderValueLabel; + + sliderContainer = container.append("div") + .classed("distanceSliderContainer", true); + + degreeSlider = sliderContainer.append("input") + .attr("id", "nodeDegreeDistanceSlider") + .attr("type", "range") + .attr("min", 0) + .attr("step", 1); + + sliderContainer.append("label") + .classed("description", true) + .attr("for", "nodeDegreeDistanceSlider") + .text("Degree of collapsing"); + + sliderValueLabel = sliderContainer.append("label") + .classed("value", true) + .attr("for", "nodeDegreeDistanceSlider") + .text(0); + + + degreeSlider.on("change", function ( silent ){ + if ( silent !== true ) { + graph.update(); + graphDegreeLevel = degreeSlider.property("value"); + } + }); + + + degreeSlider.on("input", function (){ + var degree = degreeSlider.property("value"); + sliderValueLabel.text(degree); + }); + + + // adding wheel events + degreeSlider.on("wheel", handleWheelEvent); + degreeSlider.on("focusout", function (){ + if ( degreeSlider.property("value") !== graphDegreeLevel ) { + graph.update(); + } + }); + } + + function handleWheelEvent(){ + var wheelEvent = d3.event; + + var offset; + if ( wheelEvent.deltaY < 0 ) offset = 1; + if ( wheelEvent.deltaY > 0 ) offset = -1; + var maxDeg = parseInt(degreeSlider.attr("max")); + var oldVal = parseInt(degreeSlider.property("value")); + var newSliderValue = oldVal + offset; + if ( oldVal !== newSliderValue && (newSliderValue >= 0 && newSliderValue <= maxDeg) ) { + // only update when they are different [reducing redundant updates] + // set the new value and emit an update signal + degreeSlider.property("value", newSliderValue); + degreeSlider.on("input")();// <<-- sets the text value + graph.update(); + } + d3.event.preventDefault(); + } + + function setSliderValue( slider, value ){ + slider.property("value", value).on("input")(); + } + + /** + * Resets the filters (and also filtered elements) to their default. + */ + filterMenu.reset = function (){ + checkboxData.forEach(function ( checkboxData ){ + var checkbox = checkboxData.checkbox, + enabledByDefault = checkboxData.defaultState, + isChecked = checkbox.property("checked"); + + if ( isChecked !== enabledByDefault ) { + checkbox.property("checked", enabledByDefault); + // Call onclick event handlers programmatically + checkbox.on("click")(); + } + }); + + setSliderValue(degreeSlider, 0); + degreeSlider.on("change")(); + }; + + function addAnimationFinishedListener(){ + menuControl.node().addEventListener("animationend", function (){ + menuControl.classed("buttonPulse", false); + menuControl.classed("filterMenuButtonHighlight", true); + + }); + } + + filterMenu.killButtonAnimation = function (){ + menuControl.classed("buttonPulse", false); + menuControl.classed("filterMenuButtonHighlight", false); + }; + + + filterMenu.highlightForDegreeSlider = function ( enable ){ + if ( !arguments.length ) { + enable = true; + } + menuControl.classed("highlighted", enable); + nodeDegreeContainer.classed("highlighted", enable); + // pulse button handling + if ( menuControl.classed("buttonPulse") === true && enable === true ) { + menuControl.classed("buttonPulse", false); + var timer = setTimeout(function (){ + menuControl.classed("buttonPulse", enable); + clearTimeout(timer); + // after the time is done, remove the pulse but stay highlighted + }, 100); + } else { + menuControl.classed("buttonPulse", enable); + menuControl.classed("filterMenuButtonHighlight", enable); + } + }; + + + /** importer functions **/ + // setting manually the values of the filter + // no update of the gui settings, these are updated in updateSettings + filterMenu.setCheckBoxValue = function ( id, checked ){ + for ( var i = 0; i < checkboxData.length; i++ ) { + var cbdId = checkboxData[i].checkbox.attr("id"); + if ( cbdId === id ) { + checkboxData[i].checkbox.property("checked", checked); + break; + } + } + }; + + filterMenu.getCheckBoxValue = function ( id ){ + for ( var i = 0; i < checkboxData.length; i++ ) { + var cbdId = checkboxData[i].checkbox.attr("id"); + if ( cbdId === id ) { + return checkboxData[i].checkbox.property("checked"); + + } + } + }; + // set the value of the slider + filterMenu.setDegreeSliderValue = function ( val ){ + degreeSlider.property("value", val); + }; + + filterMenu.getDegreeSliderValue = function (){ + return degreeSlider.property("value"); + }; + + // update the gui without invoking graph update (calling silent onclick function) + filterMenu.updateSettings = function (){ + var silent = true; + var sliderValue = degreeSlider.property("value"); + if ( sliderValue > 0 ) { + filterMenu.highlightForDegreeSlider(true); + } else { + filterMenu.highlightForDegreeSlider(false); + } + checkboxData.forEach(function ( checkboxData ){ + var checkbox = checkboxData.checkbox; + checkbox.on("click")(silent); + }); + + degreeSlider.on("input")(); + degreeSlider.on("change")(); + + }; + + return filterMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 326: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for setting up the gravity sliders. + * + * @param graph the associated webvowl graph + * @returns {{}} + */ + module.exports = function ( graph ){ + + var gravityMenu = {}, + sliders = [], + options = graph.graphOptions(), + defaultCharge = options.charge(); + + + /** + * Adds the gravity sliders to the website. + */ + gravityMenu.setup = function (){ + var menuEntry = d3.select("#m_gravity"); + menuEntry.on("mouseover", function (){ + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + }); + addDistanceSlider("#classSliderOption", "class", "Class distance", options.classDistance); + addDistanceSlider("#datatypeSliderOption", "datatype", "Datatype distance", options.datatypeDistance); + }; + + function addDistanceSlider( selector, identifier, label, distanceFunction ){ + var defaultLinkDistance = distanceFunction(); + + var sliderContainer, + sliderValueLabel; + + sliderContainer = d3.select(selector) + .append("div") + .datum({ distanceFunction: distanceFunction }) // connect the options-function with the slider + .classed("distanceSliderContainer", true); + + var slider = sliderContainer.append("input") + .attr("id", identifier + "DistanceSlider") + .attr("type", "range") + .attr("min", 10) + .attr("max", 600) + .attr("value", distanceFunction()) + .attr("step", 10); + + sliderContainer.append("label") + .classed("description", true) + .attr("for", identifier + "DistanceSlider") + .text(label); + + sliderValueLabel = sliderContainer.append("label") + .classed("value", true) + .attr("for", identifier + "DistanceSlider") + .text(distanceFunction()); + + // Store slider for easier resetting + sliders.push(slider); + + slider.on("focusout", function (){ + graph.updateStyle(); + }); + + slider.on("input", function (){ + var distance = slider.property("value"); + distanceFunction(distance); + adjustCharge(defaultLinkDistance); + sliderValueLabel.text(distance); + graph.updateStyle(); + }); + + // add wheel event to the slider + slider.on("wheel", function (){ + var wheelEvent = d3.event; + var offset; + if ( wheelEvent.deltaY < 0 ) offset = 10; + if ( wheelEvent.deltaY > 0 ) offset = -10; + var oldVal = parseInt(slider.property("value")); + var newSliderValue = oldVal + offset; + if ( newSliderValue !== oldVal ) { + slider.property("value", newSliderValue); + distanceFunction(newSliderValue); + slider.on("input")(); // << set text and update the graphStyles + } + d3.event.preventDefault(); + }); + } + + function adjustCharge( defaultLinkDistance ){ + var greaterDistance = Math.max(options.classDistance(), options.datatypeDistance()), + ratio = greaterDistance / defaultLinkDistance, + newCharge = defaultCharge * ratio; + + options.charge(newCharge); + } + + /** + * Resets the gravity sliders to their default. + */ + gravityMenu.reset = function (){ + sliders.forEach(function ( slider ){ + slider.property("value", function ( d ){ + // Simply reload the distance from the options + return d.distanceFunction(); + }); + slider.on("input")(); + }); + }; + + + return gravityMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 327: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for connecting the modes with the website. + * + * @param graph the graph that belongs to these controls + * @returns {{}} + */ + module.exports = function ( graph ){ + + var SAME_COLOR_MODE = { text: "Multicolor", type: "same" }; + var GRADIENT_COLOR_MODE = { text: "Multicolor", type: "gradient" }; + + var modeMenu = {}, + checkboxes = [], + colorModeSwitch; + + var dynamicLabelWidthCheckBox; + // getter and setter for the state of color modes + modeMenu.colorModeState = function ( s ){ + if ( !arguments.length ) return colorModeSwitch.datum().active; + colorModeSwitch.datum().active = s; + return modeMenu; + }; + + + modeMenu.setDynamicLabelWidth = function ( val ){ + dynamicLabelWidthCheckBox.property("checked", val); + }; + // getter for checkboxes + modeMenu.getCheckBoxContainer = function (){ + return checkboxes; + }; + // getter for the color switch [needed? ] + modeMenu.colorModeSwitch = function (){ + return colorModeSwitch; + }; + + /** + * Connects the website with the available graph modes. + */ + modeMenu.setup = function ( pickAndPin, nodeScaling, compactNotation, colorExternals ){ + var menuEntry = d3.select("#m_modes"); + menuEntry.on("mouseover", function (){ + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + }); + addCheckBoxD("labelWidth", "Dynamic label width", "#dynamicLabelWidth", graph.options().dynamicLabelWidth, 1); + addCheckBox("editorMode", "Editing ", "#editMode", graph.editorMode); + addModeItem(pickAndPin, "pickandpin", "Pick & pin", "#pickAndPinOption", false); + addModeItem(nodeScaling, "nodescaling", "Node scaling", "#nodeScalingOption", true); + addModeItem(compactNotation, "compactnotation", "Compact notation", "#compactNotationOption", true); + var container = addModeItem(colorExternals, "colorexternals", "Color externals", "#colorExternalsOption", true); + colorModeSwitch = addExternalModeSelection(container, colorExternals); + }; + function addCheckBoxD( identifier, modeName, selector, onChangeFunc, updateLvl ){ + var moduleOptionContainer = d3.select(selector) + .append("div") + .classed("checkboxContainer", true); + + var moduleCheckbox = moduleOptionContainer.append("input") + .classed("moduleCheckbox", true) + .attr("id", identifier + "ModuleCheckbox") + .attr("type", "checkbox") + .property("checked", onChangeFunc()); + + moduleCheckbox.on("click", function ( d ){ + var isEnabled = moduleCheckbox.property("checked"); + onChangeFunc(isEnabled); + d3.select("#maxLabelWidthSlider").node().disabled = !isEnabled; + d3.select("#maxLabelWidthvalueLabel").classed("disabledLabelForSlider", !isEnabled); + d3.select("#maxLabelWidthDescriptionLabel").classed("disabledLabelForSlider", !isEnabled); + + if ( updateLvl > 0 ) { + graph.animateDynamicLabelWidth(); + // graph.lazyRefresh(); + } + }); + moduleOptionContainer.append("label") + .attr("for", identifier + "ModuleCheckbox") + .text(modeName); + if ( identifier === "editorMode" ) { + moduleOptionContainer.append("label") + .attr("style", "font-size:10px;padding-top:3px") + .text("(experimental)"); + } + + dynamicLabelWidthCheckBox = moduleCheckbox; + } + + function addCheckBox( identifier, modeName, selector, onChangeFunc ){ + var moduleOptionContainer = d3.select(selector) + .append("div") + .classed("checkboxContainer", true); + + var moduleCheckbox = moduleOptionContainer.append("input") + .classed("moduleCheckbox", true) + .attr("id", identifier + "ModuleCheckbox") + .attr("type", "checkbox") + .property("checked", onChangeFunc()); + + moduleCheckbox.on("click", function ( d ){ + var isEnabled = moduleCheckbox.property("checked"); + onChangeFunc(isEnabled); + if ( isEnabled === true ) + graph.showEditorHintIfNeeded(); + }); + moduleOptionContainer.append("label") + .attr("for", identifier + "ModuleCheckbox") + .text(modeName); + if ( identifier === "editorMode" ) { + moduleOptionContainer.append("label") + .attr("style", "font-size:10px;padding-top:3px") + .text(" (experimental)"); + } + } + + function addModeItem( module, identifier, modeName, selector, updateGraphOnClick ){ + var moduleOptionContainer, + moduleCheckbox; + + moduleOptionContainer = d3.select(selector) + .append("div") + .classed("checkboxContainer", true) + .datum({ module: module, defaultState: module.enabled() }); + + moduleCheckbox = moduleOptionContainer.append("input") + .classed("moduleCheckbox", true) + .attr("id", identifier + "ModuleCheckbox") + .attr("type", "checkbox") + .property("checked", module.enabled()); + + // Store for easier resetting all modes + checkboxes.push(moduleCheckbox); + + moduleCheckbox.on("click", function ( d, silent ){ + var isEnabled = moduleCheckbox.property("checked"); + d.module.enabled(isEnabled); + if ( updateGraphOnClick && silent !== true ) { + graph.executeColorExternalsModule(); + graph.executeCompactNotationModule(); + graph.lazyRefresh(); + } + }); + + moduleOptionContainer.append("label") + .attr("for", identifier + "ModuleCheckbox") + .text(modeName); + + return moduleOptionContainer; + } + + function addExternalModeSelection( container, colorExternalsMode ){ + var button = container.append("button").datum({ active: false }).classed("color-mode-switch", true); + applyColorModeSwitchState(button, colorExternalsMode); + + button.on("click", function ( silent ){ + var data = button.datum(); + data.active = !data.active; + applyColorModeSwitchState(button, colorExternalsMode); + if ( colorExternalsMode.enabled() && silent !== true ) { + graph.executeColorExternalsModule(); + graph.lazyRefresh(); + } + }); + + return button; + } + + function applyColorModeSwitchState( element, colorExternalsMode ){ + var isActive = element.datum().active; + var activeColorMode = getColorModeByState(isActive); + + element.classed("active", isActive) + .text(activeColorMode.text); + + if ( colorExternalsMode ) { + colorExternalsMode.colorModeType(activeColorMode.type); + } + } + + function getColorModeByState( isActive ){ + return isActive ? GRADIENT_COLOR_MODE : SAME_COLOR_MODE; + } + + /** + * Resets the modes to their default. + */ + modeMenu.reset = function (){ + checkboxes.forEach(function ( checkbox ){ + var defaultState = checkbox.datum().defaultState, + isChecked = checkbox.property("checked"); + + if ( isChecked !== defaultState ) { + checkbox.property("checked", defaultState); + // Call onclick event handlers programmatically + checkbox.on("click")(checkbox.datum()); + } + + // Reset the module that is connected with the checkbox + checkbox.datum().module.reset(); + }); + + // set the switch to active and simulate disabling + colorModeSwitch.datum().active = true; + colorModeSwitch.on("click")(); + }; + + /** importer functions **/ + // setting manually the values of the filter + // no update of the gui settings, these are updated in updateSettings + modeMenu.setCheckBoxValue = function ( id, checked ){ + for ( var i = 0; i < checkboxes.length; i++ ) { + var cbdId = checkboxes[i].attr("id"); + + if ( cbdId === id ) { + checkboxes[i].property("checked", checked); + break; + } + } + }; + modeMenu.getCheckBoxValue = function ( id ){ + for ( var i = 0; i < checkboxes.length; i++ ) { + var cbdId = checkboxes[i].attr("id"); + if ( cbdId === id ) { + return checkboxes[i].property("checked"); + } + } + }; + + modeMenu.setColorSwitchState = function ( state ){ + // need the !state because we simulate later a click + modeMenu.colorModeState(!state); + }; + modeMenu.setColorSwitchStateUsingURL = function ( state ){ + // need the !state because we simulate later a click + modeMenu.colorModeState(!state); + colorModeSwitch.on("click")(true); + }; + + + modeMenu.updateSettingsUsingURL = function (){ + var silent = true; + checkboxes.forEach(function ( checkbox ){ + checkbox.on("click")(checkbox.datum(), silent); + }); + }; + + modeMenu.updateSettings = function (){ + var silent = true; + checkboxes.forEach(function ( checkbox ){ + checkbox.on("click")(checkbox.datum(), silent); + }); + // this simulates onclick and inverts its state + colorModeSwitch.on("click")(silent); + }; + return modeMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 328: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( graph ){ + var debugMenu = {}, + checkboxes = []; + + + var hoverFlag = false; + var specialCbx; + debugMenu.setup = function (){ + var menuEntry = d3.select("#debugMenuHref"); + + menuEntry.on("mouseover", function (){ + if ( hoverFlag === false ) { + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + specialCbx.on("click")(true); + if ( graph.editorMode() === false ) { + d3.select("#useAccuracyHelper").style("color", "#979797"); + d3.select("#useAccuracyHelper").style("pointer-events", "none"); + + // regardless the state on which useAccuracyHelper is , we are not in editing mode -> disable it + d3.select("#showDraggerObject").style("color", "#979797"); + d3.select("#showDraggerObject").style("pointer-events", "none"); + } else { + d3.select("#useAccuracyHelper").style("color", "#2980b9"); + d3.select("#useAccuracyHelper").style("pointer-events", "auto"); + } + hoverFlag = true; + } + }); + menuEntry.on("mouseout", function (){ + hoverFlag = false; + }); + + + specialCbx = addCheckBox("useAccuracyHelper", "Use accuracy helper", "#useAccuracyHelper", graph.options().useAccuracyHelper, + function ( enabled, silent ){ + if ( !enabled ) { + d3.select("#showDraggerObject").style("color", "#979797"); + d3.select("#showDraggerObject").style("pointer-events", "none"); + d3.select("#showDraggerObjectConfigCheckbox").node().checked = false; + } else { + d3.select("#showDraggerObject").style("color", "#2980b9"); + d3.select("#showDraggerObject").style("pointer-events", "auto"); + } + + if ( silent === true ) return; + graph.lazyRefresh(); + graph.updateDraggerElements(); + } + ); + addCheckBox("showDraggerObject", "Show accuracy helper", "#showDraggerObject", graph.options().showDraggerObject, + function ( enabled, silent ){ + if ( silent === true ) return; + graph.lazyRefresh(); + graph.updateDraggerElements(); + }); + addCheckBox("showFPS_Statistics", "Show rendering statistics", "#showFPS_Statistics", graph.options().showRenderingStatistic, + function ( enabled, silent ){ + + if ( graph.options().getHideDebugFeatures() === false ) { + d3.select("#FPS_Statistics").classed("hidden", !enabled); + } else { + d3.select("#FPS_Statistics").classed("hidden", true); + } + + + }); + addCheckBox("showModeOfOperation", "Show input modality", "#showModeOfOperation", graph.options().showInputModality, + function ( enabled ){ + if ( graph.options().getHideDebugFeatures() === false ) { + d3.select("#modeOfOperationString").classed("hidden", !enabled); + } else { + d3.select("#modeOfOperationString").classed("hidden", true); + } + }); + + + }; + + + function addCheckBox( identifier, modeName, selector, onChangeFunc, _callbackFunction ){ + var configOptionContainer = d3.select(selector) + .append("div") + .classed("checkboxContainer", true); + var configCheckbox = configOptionContainer.append("input") + .classed("moduleCheckbox", true) + .attr("id", identifier + "ConfigCheckbox") + .attr("type", "checkbox") + .property("checked", onChangeFunc()); + + + configCheckbox.on("click", function ( silent ){ + var isEnabled = configCheckbox.property("checked"); + onChangeFunc(isEnabled); + _callbackFunction(isEnabled, silent); + + }); + checkboxes.push(configCheckbox); + configOptionContainer.append("label") + .attr("for", identifier + "ConfigCheckbox") + .text(modeName); + + return configCheckbox; + } + + debugMenu.setCheckBoxValue = function ( identifier, value ){ + for ( var i = 0; i < checkboxes.length; i++ ) { + var cbdId = checkboxes[i].attr("id"); + if ( cbdId === identifier ) { + checkboxes[i].property("checked", value); + break; + } + } + }; + + debugMenu.getCheckBoxValue = function ( id ){ + for ( var i = 0; i < checkboxes.length; i++ ) { + var cbdId = checkboxes[i].attr("id"); + if ( cbdId === id ) { + return checkboxes[i].property("checked"); + } + } + }; + + debugMenu.updateSettings = function (){ + d3.selectAll(".debugOption").classed("hidden", graph.options().getHideDebugFeatures()); + + var silent = true; + checkboxes.forEach(function ( checkbox ){ + checkbox.on("click")(silent); + }); + if ( graph.editorMode() === false ) { + + d3.select("#useAccuracyHelper").style("color", "#979797"); + d3.select("#useAccuracyHelper").style("pointer-events", "none"); + + // regardless the state on which useAccuracyHelper is , we are not in editing mode -> disable it + d3.select("#showDraggerObject").style("color", "#979797"); + d3.select("#showDraggerObject").style("pointer-events", "none"); + } else { + + d3.select("#useAccuracyHelper").style("color", "#2980b9"); + d3.select("#useAccuracyHelper").style("pointer-events", "auto"); + } + + }; + + return debugMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 329: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var unescape = __webpack_require__(330); + + module.exports = function ( graph ){ + + var ontologyMenu = {}, + loadingInfo = d3.select("#loading-info"), + loadingProgress = d3.select("#loading-progress"), + + ontologyMenuTimeout, + fileToLoad, + stopTimer = false, + loadingError = false, + loadingStatusTimer, + conversion_sessionId, + cachedConversions = {}, + loadingModule, + loadOntologyFromText; + var currentLoadedOntologyName = ""; + + String.prototype.beginsWith = function ( string ){ + return (this.indexOf(string) === 0); + }; + + ontologyMenu.getLoadingFunction = function (){ + return loadOntologyFromText; + }; + + ontologyMenu.clearCachedVersion = function (){ + if ( cachedConversions[currentLoadedOntologyName] ) { + cachedConversions[currentLoadedOntologyName] = undefined; + } + }; + + + ontologyMenu.reloadCachedOntology = function (){ + ontologyMenu.clearCachedVersion(); + graph.clearGraphData(); + loadingModule.parseUrlAndLoadOntology(false); + }; + + ontologyMenu.cachedOntology = function ( ontoName ){ + currentLoadedOntologyName = ontoName; + if ( cachedConversions[ontoName] ) { + var locStr = String(location.hash); + d3.select("#reloadSvgIcon").node().disabled = false; + graph.showReloadButtonAfterLayoutOptimization(true); + if ( locStr.indexOf("#file") > -1 ) { + d3.select("#reloadSvgIcon").node().disabled = true; + d3.select("#reloadCachedOntology").node().title = "reloading original version not possible, please reload the file"; + d3.select("#reloadSvgIcon").classed("disabledReloadElement", true); + d3.select("#svgStringText").style("fill", "gray"); + d3.select("#svgStringText").classed("noselect", true); + } + else { + d3.select("#reloadCachedOntology").node().title = "generate new visualization and overwrite cached ontology"; + d3.select("#reloadSvgIcon").classed("disabledReloadElement", false); + d3.select("#svgStringText").style("fill", "black"); + d3.select("#svgStringText").classed("noselect", true); + } + } else { + graph.showReloadButtonAfterLayoutOptimization(false); + + } + return cachedConversions[ontoName]; + }; + ontologyMenu.setCachedOntology = function ( ontoName, ontoContent ){ + cachedConversions[ontoName] = ontoContent; + currentLoadedOntologyName = ontoName; + }; + + ontologyMenu.getErrorStatus = function (){ + return loadingError; + }; + + ontologyMenu.setup = function ( _loadOntologyFromText ){ + loadOntologyFromText = _loadOntologyFromText; + loadingModule = graph.options().loadingModule(); + var menuEntry = d3.select("#m_select"); + menuEntry.on("mouseover", function (){ + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + }); + + setupConverterButtons(); + setupUploadButton(); + + var descriptionButton = d3.select("#error-description-button").datum({ open: false }); + descriptionButton.on("click", function ( data ){ + var errorContainer = d3.select("#error-description-container"); + var errorDetailsButton = d3.select(this); + + // toggle the state + data.open = !data.open; + var descriptionVisible = data.open; + if ( descriptionVisible ) { + errorDetailsButton.text("Hide error details"); + } else { + errorDetailsButton.text("Show error details"); + } + errorContainer.classed("hidden", !descriptionVisible); + }); + + setupUriListener(); + loadingModule.setOntologyMenu(ontologyMenu); + }; + + + function setupUriListener(){ + // reload ontology when hash parameter gets changed manually + d3.select(window).on("hashchange", function (){ + var oldURL = d3.event.oldURL, newURL = d3.event.newURL; + if ( oldURL !== newURL ) { + // don't reload when just the hash parameter gets appended + if ( newURL === oldURL + "#" ) { + return; + } + updateNavigationHrefs(); + loadingModule.parseUrlAndLoadOntology(); + } + }); + updateNavigationHrefs(); + } + + ontologyMenu.stopLoadingTimer = function (){ + stopTimer = true; + clearTimeout(loadingStatusTimer); + }; + + /** + * Quick fix: update all anchor tags that are used as buttons because a click on them + * changes the url and this will load an other ontology. + */ + function updateNavigationHrefs(){ + d3.selectAll("#menuElementContainer > li > a").attr("href", location.hash || "#"); + } + + ontologyMenu.setIriText = function ( text ){ + d3.select("#iri-converter-input").node().value = text; + d3.select("#iri-converter-button").attr("disabled", false); + d3.select("#iri-converter-form").on("submit")(); + }; + + ontologyMenu.clearDetailInformation = function (){ + var bpContainer = d3.select("#bulletPoint_container"); + var htmlCollection = bpContainer.node().children; + var numEntries = htmlCollection.length; + + for ( var i = 0; i < numEntries; i++ ) { + htmlCollection[0].remove(); + } + }; + ontologyMenu.append_message = function ( msg ){ + // forward call + append_message(msg); + }; + function append_message( msg ){ + var bpContainer = d3.select("#bulletPoint_container"); + var div = bpContainer.append("div"); + div.node().innerHTML = msg; + loadingModule.scrollDownDetails(); + } + + ontologyMenu.append_message_toLastBulletPoint = function ( msg ){ + // forward call + append_message_toLastBulletPoint(msg); + }; + + ontologyMenu.append_bulletPoint = function ( msg ){ + // forward call + append_bulletPoint(msg); + }; + function append_message_toLastBulletPoint( msg ){ + var bpContainer = d3.select("#bulletPoint_container"); + var htmlCollection = bpContainer.node().getElementsByTagName("LI"); + var lastItem = htmlCollection.length - 1; + if ( lastItem >= 0 ) { + var oldText = htmlCollection[lastItem].innerHTML; + htmlCollection[lastItem].innerHTML = oldText + msg; + } + loadingModule.scrollDownDetails(); + } + + function append_bulletPoint( msg ){ + var bp_container = d3.select("#bulletPoint_container"); + var bp = bp_container.append("li"); + bp.node().innerHTML = msg; + d3.select("#currentLoadingStep").node().innerHTML = msg; + loadingModule.scrollDownDetails(); + } + + + function setupConverterButtons(){ + var iriConverterButton = d3.select("#iri-converter-button"); + var iriConverterInput = d3.select("#iri-converter-input"); + + iriConverterInput.on("input", function (){ + keepOntologySelectionOpenShortly(); + + var inputIsEmpty = iriConverterInput.property("value") === ""; + iriConverterButton.attr("disabled", inputIsEmpty || undefined); + }).on("click", function (){ + keepOntologySelectionOpenShortly(); + }); + + d3.select("#iri-converter-form").on("submit", function (){ + var inputName = iriConverterInput.property("value"); + + // remove first spaces + var clearedName = inputName.replace(/%20/g, " "); + while ( clearedName.beginsWith(" ") ) { + clearedName = clearedName.substr(1, clearedName.length); + } + // remove ending spaces + while ( clearedName.endsWith(" ") ) { + clearedName = clearedName.substr(0, clearedName.length - 1); + } + // check if iri is actually an url for a json file (ends with .json) + // create lowercase filenames; + inputName = clearedName; + var lc_iri = inputName.toLowerCase(); + if ( lc_iri.endsWith(".json") ) { + location.hash = "url=" + inputName; + iriConverterInput.property("value", ""); + iriConverterInput.on("input")(); + } else { + location.hash = "iri=" + inputName; + iriConverterInput.property("value", ""); + iriConverterInput.on("input")(); + } + d3.event.preventDefault(); + return false; + }); + } + + function setupUploadButton(){ + var input = d3.select("#file-converter-input"), + inputLabel = d3.select("#file-converter-label"), + uploadButton = d3.select("#file-converter-button"); + + input.on("change", function (){ + var selectedFiles = input.property("files"); + if ( selectedFiles.length <= 0 ) { + inputLabel.text("Select ontology file"); + uploadButton.property("disabled", true); + } else { + inputLabel.text(selectedFiles[0].name); + fileToLoad = selectedFiles[0].name; + uploadButton.property("disabled", false); + uploadButton.node().click(); + // close menu; + graph.options().navigationMenu().hideAllMenus(); + } + }); + + uploadButton.on("click", function (){ + var selectedFile = input.property("files")[0]; + if ( !selectedFile ) { + return false; + } + var newHashParameter = "file=" + selectedFile.name; + // Trigger the reupload manually, because the iri is not changing + if ( location.hash === "#" + newHashParameter ) { + loadingModule.parseUrlAndLoadOntology(); + } else { + location.hash = newHashParameter; + } + }); + } + + function setLoadingStatusInfo( message ){ + // check if there is a owl2vowl li item; + var o2vConverterContainer = d3.select("#o2vConverterContainer"); + if ( !o2vConverterContainer.node() ) { + var bp_container = d3.select("#bulletPoint_container"); + var div = bp_container.append("div"); + o2vConverterContainer = div.append("ul"); + o2vConverterContainer.attr("id", "o2vConverterContainer"); + o2vConverterContainer.style("margin-left", "-25px"); + } + // clear o2vConverterContainer; + var htmlCollection = o2vConverterContainer.node().children; + var numEntries = htmlCollection.length; + for ( var i = 0; i < numEntries; i++ ) { + htmlCollection[0].remove(); + } + // split tokens provided by o2v messages + var tokens = message.split("* "); + var liForToken; + for ( var t = 0; t < tokens.length; t++ ) { + var tokenMessage = tokens[t]; + // create li for tokens; + if ( tokenMessage.length > 0 ) { + liForToken = o2vConverterContainer.append("li"); + liForToken.attr("type", "disc"); + liForToken.node().innerHTML = tokenMessage.replace(/\n/g, "
    "); + } + } + if ( liForToken ) + liForToken.node().innerHTML += "
    "; + + loadingModule.scrollDownDetails(); + } + + ontologyMenu.setLoadingStatusInfo = function ( message ){ + // forward call + setLoadingStatusInfo(message); + }; + + function getLoadingStatusOnceCallBacked( callback, parameter ){ + d3.xhr("loadingStatus?sessionId=" + conversion_sessionId, "application/text", function ( error, request ){ + if ( error ) { + console.log("ontologyMenu getLoadingStatusOnceCallBacked throws error"); + console.log("---------Error -----------"); + console.log(error); + console.log("---------Request -----------"); + console.log(request); + } + setLoadingStatusInfo(request.responseText); + callback(parameter); + }); + } + + function getLoadingStatusTimeLooped(){ + d3.xhr("loadingStatus?sessionId=" + conversion_sessionId, "application/text", function ( error, request ){ + if ( error ) { + console.log("ontologyMenu getLoadingStatusTimeLooped throws error"); + console.log("---------Error -----------"); + console.log(error); + console.log("---------Request -----------"); + console.log(request); + } + if ( stopTimer === false ) { + setLoadingStatusInfo(request.responseText); + timedLoadingStatusLogger(); + } + }); + } + + function timedLoadingStatusLogger(){ + clearTimeout(loadingStatusTimer); + if ( stopTimer === false ) { + loadingStatusTimer = setTimeout(function (){ + getLoadingStatusTimeLooped(); + }, 1000); + } + } + + function callbackUpdateLoadingMessage( msg ){ + d3.xhr("loadingStatus", "application/text", function ( error, request ){ + if ( request !== undefined ) { + setLoadingStatusInfo(request.responseText + "
    " + msg); + } else { + append_message(msg); + } + }); + } + + ontologyMenu.setConversionID = function ( id ){ + conversion_sessionId = id; + }; + + ontologyMenu.callbackLoad_Ontology_FromIRI = function ( parameter ){ + var relativePath = parameter[0]; + var ontoName = parameter[1]; + var localThreadId = parameter[2]; + stopTimer = false; + timedLoadingStatusLogger(); + d3.xhr(relativePath, "application/json", function ( error, request ){ + var loadingSuccessful = !error; + // check if error occurred or responseText is empty + if ( (error !== null && error.status === 500) || (request && request.responseText.length === 0) ) { + clearTimeout(loadingStatusTimer); + stopTimer = true; + getLoadingStatusOnceCallBacked(callbackFromIRI_URL_ERROR, [error, request, localThreadId]); + } + var jsonText; + if ( loadingSuccessful ) { + clearTimeout(loadingStatusTimer); + stopTimer = true; + jsonText = request.responseText; + getLoadingStatusOnceCallBacked(callbackFromIRI_Success, [jsonText, ontoName, localThreadId]); + } + }); + }; + + + ontologyMenu.callbackLoad_Ontology_From_DirectInput = function ( text, parameter ){ + var input = text; + var sessionId = parameter[1]; + stopTimer = false; + timedLoadingStatusLogger(); + + var formData = new FormData(); + formData.append("input", input); + formData.append("sessionId", sessionId); + var xhr = new XMLHttpRequest(); + + xhr.open("POST", "directInput", true); + xhr.onload = function (){ + clearTimeout(loadingStatusTimer); + stopTimer = true; + getLoadingStatusOnceCallBacked(callbackForConvert, [xhr, input, sessionId]); + }; + timedLoadingStatusLogger(); + xhr.send(formData); + + }; + function callbackFromIRI_Success( parameter ){ + var local_conversionId = parameter[2]; + if ( local_conversionId !== conversion_sessionId ) { + console.log("The conversion process for file:" + parameter[1] + " has been canceled!"); + ontologyMenu.conversionFinished(local_conversionId); + return; + } + loadingModule.loadFromOWL2VOWL(parameter[0], parameter[1]); + ontologyMenu.conversionFinished(); + + } + + function callbackFromDirectInput_Success( parameter ){ + var local_conversionId = parameter[1]; + if ( local_conversionId !== conversion_sessionId ) { + console.log("The conversion process for file:" + parameter[1] + " has been canceled!"); + ontologyMenu.conversionFinished(local_conversionId); + return; + } + loadingModule.loadFromOWL2VOWL(parameter[0], "DirectInputConversionID" + local_conversionId); + ontologyMenu.conversionFinished(); + + } + + ontologyMenu.getConversionId = function (){ + return conversion_sessionId; + }; + + ontologyMenu.callbackLoad_JSON_FromURL = function ( parameter ){ + var relativePath = parameter[0]; + var ontoName = parameter[1]; + var local_conversionId = parameter[2]; + stopTimer = false; + timedLoadingStatusLogger(); + d3.xhr(relativePath, "application/json", function ( error, request ){ + var loadingSuccessful = !error; + // check if error occurred or responseText is empty + if ( (error !== null && error.status === 500) || (request && request.responseText.length === 0) ) { + clearTimeout(loadingStatusTimer); + stopTimer = true; + loadingSuccessful = false; + console.log(request); + console.log(request.responseText.length); + getLoadingStatusOnceCallBacked(callbackFromJSON_URL_ERROR, [error, request, local_conversionId]); + } + if ( loadingSuccessful ) { + clearTimeout(loadingStatusTimer); + stopTimer = true; + var jsonText = request.responseText; + getLoadingStatusOnceCallBacked(callbackFromJSON_Success, [jsonText, ontoName, local_conversionId]); + } + }); + }; + + function callbackFromJSON_Success( parameter ){ + var local_conversionId = parameter[2]; + if ( local_conversionId !== conversion_sessionId ) { + console.log("The conversion process for file:" + parameter[1] + " has been canceled!"); + return; + } + loadingModule.loadFromOWL2VOWL(parameter[0], parameter[1]); + } + + function callbackFromJSON_URL_ERROR( parameter ){ + var error = parameter[0]; + var request = parameter[1]; + var local_conversionId = parameter[2]; + if ( local_conversionId !== conversion_sessionId ) { + console.log("This thread has been canceled!!"); + ontologyMenu.conversionFinished(local_conversionId); + return; + } + callbackUpdateLoadingMessage("
    Failed to convert the file. " + + " Ontology could not be loaded.
    Is it a valid OWL ontology? Please check with OWL Validator"); + + if ( error !== null && error.status === 500 ) { + append_message("Could not find ontology at the URL"); + } + if ( request && request.responseText.length === 0 ) { + append_message("Received empty graph"); + } + graph.handleOnLoadingError(); + ontologyMenu.conversionFinished(); + } + + + function callbackFromIRI_URL_ERROR( parameter ){ + var error = parameter[0]; + var request = parameter[1]; + var local_conversionId = parameter[2]; + if ( local_conversionId !== conversion_sessionId ) { + console.log("This thread has been canceled!!"); + ontologyMenu.conversionFinished(local_conversionId); + return; + } + callbackUpdateLoadingMessage("
    Failed to convert the file. " + + " Ontology could not be loaded.
    Is it a valid OWL ontology? Please check with OWL Validator"); + + if ( error !== null && error.status === 500 ) { + append_message("Could not find ontology at the URL"); + } + if ( request && request.responseText.length === 0 ) { + append_message("Received empty graph"); + } + graph.handleOnLoadingError(); + ontologyMenu.conversionFinished(); + } + + function callbackFromDirectInput_ERROR( parameter ){ + + var error = parameter[0]; + var request = parameter[1]; + var local_conversionId = parameter[2]; + if ( local_conversionId !== conversion_sessionId ) { + console.log("The loading process for direct input has been canceled!"); + return; + } + // callbackUpdateLoadingMessage("
    Failed to convert the file. "+ + // "Ontology could not be loaded.
    Is it a valid OWL ontology? Please check with OWL Validator"); + if ( error !== null && error.status === 500 ) { + append_message("Could not convert direct input"); + } + if ( request && request.responseText.length === 0 ) { + append_message("Received empty graph"); + } + + graph.handleOnLoadingError(); + ontologyMenu.conversionFinished(); + } + + ontologyMenu.callbackLoadFromOntology = function ( selectedFile, filename, local_threadId ){ + callbackLoadFromOntology(selectedFile, filename, local_threadId); + }; + + function callbackLoadFromOntology( selectedFile, filename, local_threadId ){ + stopTimer = false; + timedLoadingStatusLogger(); + + var formData = new FormData(); + formData.append("ontology", selectedFile); + formData.append("sessionId", local_threadId); + var xhr = new XMLHttpRequest(); + + xhr.open("POST", "convert", true); + xhr.onload = function (){ + clearTimeout(loadingStatusTimer); + stopTimer = true; + console.log(xhr); + getLoadingStatusOnceCallBacked(callbackForConvert, [xhr, filename, local_threadId]); + }; + timedLoadingStatusLogger(); + xhr.send(formData); + } + + function callbackForConvert( parameter ){ + var xhr = parameter[0]; + var filename = parameter[1]; + var local_threadId = parameter[2]; + if ( local_threadId !== conversion_sessionId ) { + console.log("The conversion process for file:" + filename + " has been canceled!"); + ontologyMenu.conversionFinished(local_threadId); + return; + } + if ( xhr.status === 200 ) { + loadingModule.loadFromOWL2VOWL(xhr.responseText, filename); + ontologyMenu.conversionFinished(); + } else { + var uglyJson=xhr.responseText; + var jsonResut=JSON.parse(uglyJson); + var niceJSON=JSON.stringify(jsonResut, 'null', ' '); + niceJSON= niceJSON.replace(new RegExp('\r?\n','g'), '
    '); + callbackUpdateLoadingMessage("Failed to convert the file. " + + "
    Server answer:
    "+ + "
    "+niceJSON+ "
    "+ + "Ontology could not be loaded.
    Is it a valid OWL ontology? Please check with OWL Validator"); + + graph.handleOnLoadingError(); + ontologyMenu.conversionFinished(); + } + } + + ontologyMenu.conversionFinished = function ( id ){ + var local_id = conversion_sessionId; + if ( id ) { + local_id = id; + } + d3.xhr("conversionDone?sessionId=" + local_id, "application/text", function ( error, request ){ + if ( error ) { + console.log("ontologyMenu conversionFinished throws error"); + console.log("---------Error -----------"); + console.log(error); + console.log("---------Request -----------"); + console.log(request); + } + }); + }; + + function keepOntologySelectionOpenShortly(){ + // Events in the menu should not be considered + var ontologySelection = d3.select("#select .toolTipMenu"); + ontologySelection.on("click", function (){ + d3.event.stopPropagation(); + }).on("keydown", function (){ + d3.event.stopPropagation(); + }); + + ontologySelection.style("display", "block"); + + function disableKeepingOpen(){ + ontologySelection.style("display", undefined); + + clearTimeout(ontologyMenuTimeout); + d3.select(window).on("click", undefined).on("keydown", undefined); + ontologySelection.on("mouseover", undefined); + } + + // Clear the timeout to handle fast calls of this function + clearTimeout(ontologyMenuTimeout); + ontologyMenuTimeout = setTimeout(function (){ + disableKeepingOpen(); + }, 3000); + + // Disable forced open selection on interaction + d3.select(window).on("click", function (){ + disableKeepingOpen(); + }).on("keydown", function (){ + disableKeepingOpen(); + }); + + ontologySelection.on("mouseover", function (){ + disableKeepingOpen(); + }); + } + + ontologyMenu.showLoadingStatus = function ( visible ){ + if ( visible === true ) { + displayLoadingIndicators(); + } + else { + hideLoadingInformations(); + } + }; + + function displayLoadingIndicators(){ + d3.select("#layoutLoadingProgressBarContainer").classed("hidden", false); + loadingInfo.classed("hidden", false); + loadingProgress.classed("hidden", false); + } + + function hideLoadingInformations(){ + loadingInfo.classed("hidden", true); + } + + return ontologyMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 330: +/***/ (function(module, exports, __webpack_require__) { + + var toString = __webpack_require__(219), + unescapeHtmlChar = __webpack_require__(331); + + /** Used to match HTML entities and HTML characters. */ + var reEscapedHtml = /&(?:amp|lt|gt|quot|#39);/g, + reHasEscapedHtml = RegExp(reEscapedHtml.source); + + /** + * The inverse of `_.escape`; this method converts the HTML entities + * `&`, `<`, `>`, `"`, and `'` in `string` to + * their corresponding characters. + * + * **Note:** No other HTML entities are unescaped. To unescape additional + * HTML entities use a third-party library like [_he_](https://mths.be/he). + * + * @static + * @memberOf _ + * @since 0.6.0 + * @category String + * @param {string} [string=''] The string to unescape. + * @returns {string} Returns the unescaped string. + * @example + * + * _.unescape('fred, barney, & pebbles'); + * // => 'fred, barney, & pebbles' + */ + function unescape(string) { + string = toString(string); + return (string && reHasEscapedHtml.test(string)) + ? string.replace(reEscapedHtml, unescapeHtmlChar) + : string; + } + + module.exports = unescape; + + +/***/ }), + +/***/ 331: +/***/ (function(module, exports, __webpack_require__) { + + var basePropertyOf = __webpack_require__(332); + + /** Used to map HTML entities to characters. */ + var htmlUnescapes = { + '&': '&', + '<': '<', + '>': '>', + '"': '"', + ''': "'" + }; + + /** + * Used by `_.unescape` to convert HTML entities to characters. + * + * @private + * @param {string} chr The matched character to unescape. + * @returns {string} Returns the unescaped character. + */ + var unescapeHtmlChar = basePropertyOf(htmlUnescapes); + + module.exports = unescapeHtmlChar; + + +/***/ }), + +/***/ 332: +/***/ (function(module, exports) { + + /** + * The base implementation of `_.propertyOf` without support for deep paths. + * + * @private + * @param {Object} object The object to query. + * @returns {Function} Returns the new accessor function. + */ + function basePropertyOf(object) { + return function(key) { + return object == null ? undefined : object[key]; + }; + } + + module.exports = basePropertyOf; + + +/***/ }), + +/***/ 333: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for the pause and resume button. + * + * @param graph the associated webvowl graph + * @returns {{}} + */ + module.exports = function ( graph ){ + + var pauseMenu = {}, + pauseButton; + + + /** + * Adds the pause button to the website. + */ + pauseMenu.setup = function (){ + var menuEntry = d3.select("#pauseOption"); + menuEntry.on("mouseover", function (){ + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + }); + pauseButton = d3.select("#pause-button") + .datum({ paused: false }) + .on("click", function ( d ){ + graph.paused(!d.paused); + d.paused = !d.paused; + updatePauseButton(); + pauseButton.classed("highlighted", d.paused); + }); + // Set these properties the first time manually + updatePauseButton(); + }; + + pauseMenu.setPauseValue = function ( value ){ + pauseButton.datum().paused = value; + graph.paused(value); + pauseButton.classed("highlighted", value); + updatePauseButton(); + }; + + function updatePauseButton(){ + updatePauseButtonClass(); + updatePauseButtonText(); + } + + function updatePauseButtonClass(){ + pauseButton.classed("paused", function ( d ){ + return d.paused; + }); + } + + function updatePauseButtonText(){ + if ( pauseButton.datum().paused ) { + pauseButton.text("Resume"); + } else { + pauseButton.text("Pause"); + } + } + + pauseMenu.reset = function (){ + // resuming + pauseMenu.setPauseValue(false); + }; + + + return pauseMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 334: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for the reset button. + * + * @param graph the associated webvowl graph + * @returns {{}} + */ + module.exports = function ( graph ){ + + var resetMenu = {}, + options = graph.graphOptions(), + resettableModules, + untouchedOptions = webvowl.options(); + + + /** + * Adds the reset button to the website. + * @param _resettableModules modules that can be resetted + */ + resetMenu.setup = function ( _resettableModules ){ + resettableModules = _resettableModules; + d3.select("#reset-button").on("click", resetGraph); + var menuEntry = d3.select("#resetOption"); + menuEntry.on("mouseover", function (){ + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + }); + }; + + function resetGraph(){ + graph.resetSearchHighlight(); + graph.options().searchMenu().clearText(); + options.classDistance(untouchedOptions.classDistance()); + options.datatypeDistance(untouchedOptions.datatypeDistance()); + options.charge(untouchedOptions.charge()); + options.gravity(untouchedOptions.gravity()); + options.linkStrength(untouchedOptions.linkStrength()); + graph.reset(); + + resettableModules.forEach(function ( module ){ + module.reset(); + }); + + graph.updateStyle(); + } + + + return resetMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 335: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the search "engine" + * + * @param graph the associated webvowl graph + * @returns {{}} + */ + module.exports = function ( graph ){ + var searchMenu = {}, + dictionary = [], + entryNames = [], + searchLineEdit, + mergedStringsList, + mergedIdList, + maxEntries = 6, + dictionaryUpdateRequired = true, + labelDictionary, + inputText, + viewStatusOfSearchEntries = false; + + var results = []; + var resultID = []; + var c_locate = d3.select("#locateSearchResult"); + var c_search = d3.select("#c_search"); + var m_search = d3.select("#m_search"); // << dropdown container; + + + String.prototype.beginsWith = function ( string ){ + return (this.indexOf(string) === 0); + }; + + searchMenu.requestDictionaryUpdate = function (){ + dictionaryUpdateRequired = true; + // clear possible pre searched entries + var htmlCollection = m_search.node().children; + var numEntries = htmlCollection.length; + + for ( var i = 0; i < numEntries; i++ ) + htmlCollection[0].remove(); + searchLineEdit.node().value = ""; + }; + + + function updateSearchDictionary(){ + labelDictionary = graph.getUpdateDictionary(); + dictionaryUpdateRequired = false; + dictionary = []; + entryNames = []; + var idList = []; + var stringList = []; + + var i; + for ( i = 0; i < labelDictionary.length; i++ ) { + var lEntry = labelDictionary[i].labelForCurrentLanguage(); + idList.push(labelDictionary[i].id()); + stringList.push(lEntry); + // add all equivalents to the search space; + if ( labelDictionary[i].equivalents && labelDictionary[i].equivalents().length > 0 ) { + var eqs = labelDictionary[i].equivalentsString(); + var eqsLabels = eqs.split(", "); + for ( var e = 0; e < eqsLabels.length; e++ ) { + idList.push(labelDictionary[i].id()); + stringList.push(eqsLabels[e]); + } + } + } + + mergedStringsList = []; + mergedIdList = []; + var indexInStringList = -1; + var currentString; + var currentObjectId; + + for ( i = 0; i < stringList.length; i++ ) { + if ( i === 0 ) { + // just add the elements + mergedStringsList.push(stringList[i]); + mergedIdList.push([]); + mergedIdList[0].push(idList[i]); + continue; + } + else { + currentString = stringList[i]; + currentObjectId = idList[i]; + indexInStringList = mergedStringsList.indexOf(currentString); + } + if ( indexInStringList === -1 ) { + mergedStringsList.push(stringList[i]); + mergedIdList.push([]); + var lastEntry = mergedIdList.length; + mergedIdList[lastEntry - 1].push(currentObjectId); + } else { + mergedIdList[indexInStringList].push(currentObjectId); + } + } + + for ( i = 0; i < mergedStringsList.length; i++ ) { + var aString = mergedStringsList[i]; + var correspondingIdList = mergedIdList[i]; + var idListResult = "[ "; + for ( var j = 0; j < correspondingIdList.length; j++ ) { + idListResult = idListResult + correspondingIdList[j].toString(); + idListResult = idListResult + ", "; + } + idListResult = idListResult.substring(0, idListResult.length - 2); + idListResult = idListResult + " ]"; + + dictionary.push(aString); + entryNames.push(aString); + } + } + + searchMenu.setup = function (){ + // clear dictionary; + dictionary = []; + searchLineEdit = d3.select("#search-input-text"); + searchLineEdit.on("input", userInput); + searchLineEdit.on("keydown", userNavigation); + searchLineEdit.on("click", toggleSearchEntryView); + searchLineEdit.on("mouseover", hoverSearchEntryView); + + c_locate.on("click", function (){ + graph.locateSearchResult(); + }); + + c_locate.on("mouseover", function (){ + searchMenu.hideSearchEntries(); + }); + + }; + + function hoverSearchEntryView(){ + updateSelectionStatusFlags(); + searchMenu.showSearchEntries(); + } + + function toggleSearchEntryView(){ + if ( viewStatusOfSearchEntries ) { + searchMenu.hideSearchEntries(); + } else { + searchMenu.showSearchEntries(); + } + } + + searchMenu.hideSearchEntries = function (){ + m_search.style("display", "none"); + viewStatusOfSearchEntries = false; + }; + + searchMenu.showSearchEntries = function (){ + m_search.style("display", "block"); + viewStatusOfSearchEntries = true; + }; + + function ValidURL( str ){ + var urlregex = /^(https?|ftp):\/\/([a-zA-Z0-9.-]+(:[a-zA-Z0-9.&%$-]+)*@)*((25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9][0-9]?)(\.(25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9]?[0-9])){3}|([a-zA-Z0-9-]+\.)*[a-zA-Z0-9-]+\.(com|edu|gov|int|mil|net|org|biz|arpa|info|name|pro|aero|coop|museum|[a-zA-Z]{2}))(:[0-9]+)*(\/($|[a-zA-Z0-9.,?'\\+&%$#=~_-]+))*$/; + return urlregex.test(str); + + } + + + function updateSelectionStatusFlags(){ + if ( searchLineEdit.node().value.length === 0 ) { + createSearchEntries(); + return; + } + handleAutoCompletion(); + } + + function userNavigation(){ + if ( dictionaryUpdateRequired ) { + updateSearchDictionary(); + } + + var htmlCollection = m_search.node().children; + var numEntries = htmlCollection.length; + + + var move = 0; + var i; + var selectedEntry = -1; + for ( i = 0; i < numEntries; i++ ) { + var atr = htmlCollection[i].getAttribute('class'); + if ( atr === "dbEntrySelected" ) { + selectedEntry = i; + } + } + if ( d3.event.keyCode === 13 ) { + if ( selectedEntry >= 0 && selectedEntry < numEntries ) { + // simulate onClick event + htmlCollection[selectedEntry].onclick(); + searchMenu.hideSearchEntries(); + } + else if ( numEntries === 0 ) { + inputText = searchLineEdit.node().value; + // check if input text ends or begins with with space + // remove first spaces + var clearedText = inputText.replace(/%20/g, " "); + while ( clearedText.beginsWith(" ") ) { + clearedText = clearedText.substr(1, clearedText.length); + } + // remove ending spaces + while ( clearedText.endsWith(" ") ) { + clearedText = clearedText.substr(0, clearedText.length - 1); + } + var iri = clearedText.replace(/ /g, "%20"); + + var valid = ValidURL(iri); + // validate url: + if ( valid ) { + var ontM = graph.options().ontologyMenu(); + ontM.setIriText(iri); + searchLineEdit.node().value = ""; + } + else { + console.log(iri + " is not a valid URL!"); + } + } + } + if ( d3.event.keyCode === 38 ) { + move = -1; + searchMenu.showSearchEntries(); + } + if ( d3.event.keyCode === 40 ) { + move = +1; + searchMenu.showSearchEntries(); + } + + var newSelection = selectedEntry + move; + if ( newSelection !== selectedEntry ) { + + if ( newSelection < 0 && selectedEntry <= 0 ) { + htmlCollection[0].setAttribute('class', "dbEntrySelected"); + } + + if ( newSelection >= numEntries ) { + htmlCollection[selectedEntry].setAttribute('class', "dbEntrySelected"); + } + if ( newSelection >= 0 && newSelection < numEntries ) { + htmlCollection[newSelection].setAttribute('class', "dbEntrySelected"); + if ( selectedEntry >= 0 ) + htmlCollection[selectedEntry].setAttribute('class', "dbEntry"); + } + } + } + + searchMenu.getSearchString = function (){ + return searchLineEdit.node().value; + }; + + + function clearSearchEntries(){ + var htmlCollection = m_search.node().children; + var numEntries = htmlCollection.length; + for ( var i = 0; i < numEntries; i++ ) { + htmlCollection[0].remove(); + } + results = []; + resultID = []; + + } + + function createSearchEntries(){ + inputText = searchLineEdit.node().value; + var i; + var lc_text = inputText.toLowerCase(); + var token; + + for ( i = 0; i < dictionary.length; i++ ) { + var tokenElement = dictionary[i]; + if ( tokenElement === undefined ) { + //@WORKAROUND : nodes with undefined labels are skipped + //@FIX: these nodes are now not added to the dictionary + continue; + } + token = dictionary[i].toLowerCase(); + if ( token.indexOf(lc_text) > -1 ) { + results.push(dictionary[i]); + resultID.push(i); + } + } + } + + function measureTextWidth( text, textStyle ){ + // Set a default value + if ( !textStyle ) { + textStyle = "text"; + } + var d = d3.select("body") + .append("div") + .attr("class", textStyle) + .attr("id", "width-test") // tag this element to identify it + .attr("style", "position:absolute; float:left; white-space:nowrap; visibility:hidden;") + .text(text), + w = document.getElementById("width-test").offsetWidth; + d.remove(); + return w; + } + + function cropText( input ){ + var maxWidth = 250; + var textStyle = "dbEntry"; + var truncatedText = input; + var textWidth; + var ratio; + var newTruncatedTextLength; + while ( true ) { + textWidth = measureTextWidth(truncatedText, textStyle); + if ( textWidth <= maxWidth ) { + break; + } + + ratio = textWidth / maxWidth; + newTruncatedTextLength = Math.floor(truncatedText.length / ratio); + + // detect if nothing changes + if ( truncatedText.length === newTruncatedTextLength ) { + break; + } + + truncatedText = truncatedText.substring(0, newTruncatedTextLength); + } + + if ( input.length > truncatedText.length ) { + return input.substring(0, truncatedText.length - 6); + } + return input; + } + + function createDropDownElements(){ + var numEntries; + var copyRes = results; + var i; + var token; + var newResults = []; + var newResultsIds = []; + + var lc_text = searchLineEdit.node().value.toLowerCase(); + // set the number of shown results to be maxEntries or less; + numEntries = results.length; + if ( numEntries > maxEntries ) + numEntries = maxEntries; + + + for ( i = 0; i < numEntries; i++ ) { + // search for the best entry + var indexElement = 1000000; + var lengthElement = 1000000; + var bestElement = -1; + for ( var j = 0; j < copyRes.length; j++ ) { + token = copyRes[j].toLowerCase(); + var tIe = token.indexOf(lc_text); + var tLe = token.length; + if ( tIe > -1 && tIe <= indexElement && tLe <= lengthElement ) { + bestElement = j; + indexElement = tIe; + lengthElement = tLe; + } + } + newResults.push(copyRes[bestElement]); + newResultsIds.push(resultID[bestElement]); + copyRes[bestElement] = ""; + } + + // add the results to the entry menu + //****************************************** + numEntries = results.length; + if ( numEntries > maxEntries ) + numEntries = maxEntries; + + var filteredOutElements = 0; + for ( i = 0; i < numEntries; i++ ) { + //add results to the dropdown menu + var testEntry = document.createElement('li'); + testEntry.setAttribute('elementID', newResultsIds[i]); + testEntry.onclick = handleClick(newResultsIds[i]); + testEntry.setAttribute('class', "dbEntry"); + + var entries = mergedIdList[newResultsIds[i]]; + var eLen = entries.length; + + var croppedText = cropText(newResults[i]); + + var el0 = entries[0]; + var allSame = true; + var nodeMap = graph.getNodeMapForSearch(); + var visible = eLen; + if ( eLen > 1 ) { + for ( var q = 0; q < eLen; q++ ) { + if ( nodeMap[entries[q]] === undefined ) { + visible--; + } + } + } + + for ( var a = 0; a < eLen; a++ ) { + if ( el0 !== entries[a] ) { + allSame = false; + } + } + if ( croppedText !== newResults[i] ) { + // append ...(#numElements) if needed + if ( eLen > 1 && allSame === false ) { + if ( eLen !== visible ) + croppedText += "... (" + visible + "/" + eLen + ")"; + } + else { + croppedText += "..."; + } + testEntry.title = newResults[i]; + } + else { + if ( eLen > 1 && allSame === false ) { + if ( eLen !== visible ) + croppedText += " (" + visible + "/" + eLen + ")"; + else + croppedText += " (" + eLen + ")"; + } + } + + var searchEntryNode = d3.select(testEntry); + if ( eLen === 1 || allSame === true ) { + if ( nodeMap[entries[0]] === undefined ) { + searchEntryNode.style("color", "#979797"); + testEntry.title = newResults[i] + "\nElement is filtered out."; + testEntry.onclick = function (){ + }; + d3.select(testEntry).style("cursor", "default"); + filteredOutElements++; + } + } else { + if ( visible < 1 ) { + searchEntryNode.style("color", "#979797"); + testEntry.onclick = function (){ + }; + testEntry.title = newResults[i] + "\nAll elements are filtered out."; + d3.select(testEntry).style("cursor", "default"); + filteredOutElements++; + } else { + searchEntryNode.style("color", ""); + } + if ( visible < eLen && visible > 1 ) { + testEntry.title = newResults[i] + "\n" + visible + "/" + eLen + " elements are visible."; + } + } + searchEntryNode.node().innerHTML = croppedText; + m_search.node().appendChild(testEntry); + } + } + + + function handleAutoCompletion(){ + /** pre condition: autoCompletion has already a valid text**/ + clearSearchEntries(); + createSearchEntries(); + createDropDownElements(); + } + + function userInput(){ + c_locate.classed("highlighted", false); + c_locate.node().title = "Nothing to locate"; + + if ( dictionaryUpdateRequired ) { + updateSearchDictionary(); + } + graph.resetSearchHighlight(); + + if ( dictionary.length === 0 ) { + console.log("dictionary is empty"); + return; + } + inputText = searchLineEdit.node().value; + + clearSearchEntries(); + if ( inputText.length !== 0 ) { + createSearchEntries(); + createDropDownElements(); + } + + searchMenu.showSearchEntries(); + } + + function handleClick( elementId ){ + + return function (){ + var id = elementId; + var correspondingIds = mergedIdList[id]; + + // autoComplete the text for the user + var autoComStr = entryNames[id]; + searchLineEdit.node().value = autoComStr; + + graph.resetSearchHighlight(); + graph.highLightNodes(correspondingIds); + c_locate.node().title = "Locate search term"; + if ( autoComStr !== inputText ) { + handleAutoCompletion(); + } + searchMenu.hideSearchEntries(); + }; + } + + searchMenu.clearText = function (){ + searchLineEdit.node().value = ""; + c_locate.classed("highlighted", false); + c_locate.node().title = "Nothing to locate"; + var htmlCollection = m_search.node().children; + var numEntries = htmlCollection.length; + for ( var i = 0; i < numEntries; i++ ) { + htmlCollection[0].remove(); + } + }; + + return searchMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 336: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the navigation "engine" + * + * @param graph the associated webvowl graph + * @returns {{}} + */ + module.exports = function ( graph ){ + var navigationMenu = {}, + scrollContainer = d3.select("#menuElementContainer").node(), + menuContainer = d3.select("#menuContainer").node(), + leftButton = d3.select("#scrollLeftButton"), + rightButton = d3.select("#scrollRightButton"), + scrolLeftValue, + scrollMax, + currentlyVisibleMenu, + currentlyHoveredEntry, + touchedElement = false, + t_scrollLeft, + t_scrollRight, + c_select = [], + m_select = []; + + + function clearAllTimers(){ + cancelAnimationFrame(t_scrollLeft); + cancelAnimationFrame(t_scrollRight); + } + + function timed_scrollRight(){ + scrolLeftValue += 5; + scrollContainer.scrollLeft = scrolLeftValue; + navigationMenu.updateScrollButtonVisibility(); + if ( scrolLeftValue >= scrollMax ) { + clearAllTimers(); + return; + } + t_scrollRight = requestAnimationFrame(timed_scrollRight); + + } + + function timed_scrollLeft(){ + scrolLeftValue -= 5; + scrollContainer.scrollLeft = scrolLeftValue; + navigationMenu.updateScrollButtonVisibility(); + if ( scrolLeftValue <= 0 ) { + clearAllTimers(); + return; + } + t_scrollRight = requestAnimationFrame(timed_scrollLeft); + } + + // collect all menu entries and stuff; + function setupControlsAndMenus(){ + // HEURISTIC : to match the menus and their controllers we remove the first 2 letters and match + c_select = []; + m_select = []; + + var c_temp = []; + var m_temp = []; + var i; + var controlElements = scrollContainer.children; + var numEntries = controlElements.length; + + for ( i = 0; i < numEntries; i++ ) { + c_temp.push(controlElements[i].id.slice(2)); + } + + var menuElements = menuContainer.children; + numEntries = menuElements.length; + for ( i = 0; i < numEntries; i++ ) { + m_temp.push(menuElements[i].id.slice(2)); + } + + numEntries = controlElements.length; + for ( i = 0; i < numEntries; i++ ) { + c_select[i] = "c_" + c_temp[i]; + if ( m_temp.indexOf(c_temp[i]) > -1 ) { + m_select[i] = "m_" + c_temp[i]; + } else { + m_select[i] = undefined; + } + // create custom behavior for click, touch, and hover + d3.select("#" + c_select[i]).on("mouseover", menuElementOnHovered); + d3.select("#" + c_select[i]).on("mouseout", menuElementOutHovered); + + d3.select("#" + c_select[i]).on("click", menuElementClicked); + d3.select("#" + c_select[i]).on("touchstart", menuElementTouched); + + } + + // connect to mouseWheel + d3.select("#menuElementContainer").on("wheel", function (){ + var wheelEvent = d3.event; + var offset; + if ( wheelEvent.deltaY < 0 ) offset = 20; + if ( wheelEvent.deltaY > 0 ) offset = -20; + scrollContainer.scrollLeft += offset; + navigationMenu.hideAllMenus(); + navigationMenu.updateScrollButtonVisibility(); + }); + + // connect scrollIndicator Buttons; + d3.select("#scrollRightButton").on("mousedown", function (){ + scrolLeftValue = scrollContainer.scrollLeft; + navigationMenu.hideAllMenus(); + t_scrollRight = requestAnimationFrame(timed_scrollRight); + + }).on("touchstart", function (){ + scrolLeftValue = scrollContainer.scrollLeft; + navigationMenu.hideAllMenus(); + t_scrollRight = requestAnimationFrame(timed_scrollRight); + }).on("mouseup", clearAllTimers) + .on("touchend", clearAllTimers) + .on("touchcancel", clearAllTimers); + + d3.select("#scrollLeftButton").on("mousedown", function (){ + scrolLeftValue = scrollContainer.scrollLeft; + navigationMenu.hideAllMenus(); + t_scrollLeft = requestAnimationFrame(timed_scrollLeft); + }).on("touchstart", function (){ + scrolLeftValue = scrollContainer.scrollLeft; + navigationMenu.hideAllMenus(); + t_scrollLeft = requestAnimationFrame(timed_scrollLeft); + }).on("mouseup", clearAllTimers) + .on("touchend", clearAllTimers) + .on("touchcancel", clearAllTimers); + + // connect the scroll functionality; + d3.select("#menuElementContainer").on("scroll", function (){ + navigationMenu.updateScrollButtonVisibility(); + navigationMenu.hideAllMenus(); + }); + } + + function menuElementOnHovered(){ + navigationMenu.hideAllMenus(); + if ( touchedElement ) { + return; + } + showSingleMenu(this.id); + } + + function menuElementOutHovered(){ + hoveroutedControMenu(this.id); + } + + function menuElementClicked(){ + var m_element = m_select[c_select.indexOf(this.id)]; + if ( m_element ) { + var menuElement = d3.select("#" + m_element); + if ( menuElement ) { + if ( menuElement.style("display") === "block" ) { + menuElement.style("display", "none");// hide it + } else { + showSingleMenu(this.id); + } + } + } + } + + function menuElementTouched(){ + // it sets a flag that we have touched it, + // since d3. propagates the event for touch as hover and then click, we block the hover event + touchedElement = true; + } + + + function hoveroutedControMenu( controllerID ){ + currentlyHoveredEntry = d3.select("#" + controllerID); + if ( controllerID !== "c_search" ) { + d3.select("#" + controllerID).select("path").style("stroke-width", "0"); + d3.select("#" + controllerID).select("path").style("fill", "#fff"); + } + + } + + function showSingleMenu( controllerID ){ + currentlyHoveredEntry = d3.select("#" + controllerID).node(); + // get the corresponding menu element for this controller + var m_element = m_select[c_select.indexOf(controllerID)]; + if ( m_element ) { + if ( controllerID !== "c_search" ) { + + d3.select("#" + controllerID).select("path").style("stroke-width", "0"); + d3.select("#" + controllerID).select("path").style("fill", "#bdc3c7"); + } + // show it if we have a menu + currentlyVisibleMenu = d3.select("#" + m_element); + currentlyVisibleMenu.style("display", "block"); + if ( m_element === "m_export" ) + graph.options().exportMenu().exportAsUrl(); + updateMenuPosition(); + } + } + + function updateMenuPosition(){ + if ( currentlyHoveredEntry ) { + var leftOffset = currentlyHoveredEntry.offsetLeft; + var scrollOffset = scrollContainer.scrollLeft; + var totalOffset = leftOffset - scrollOffset; + var finalOffset = Math.max(0, totalOffset); + var fullContainer_width = scrollContainer.getBoundingClientRect().width; + var elementWidth = currentlyVisibleMenu.node().getBoundingClientRect().width; + // make priority > first check if we are right + if ( finalOffset + elementWidth > fullContainer_width ) { + finalOffset = fullContainer_width - elementWidth; + } + // fix priority; + finalOffset = Math.max(0, finalOffset); + currentlyVisibleMenu.style("left", finalOffset + "px"); + + // // check if outside the viewport + // var menuWidth=currentlyHoveredEntry.getBoundingClientRect().width; + // var bt_width=36; + // if (totalOffset+menuWidthfullContainer_width){ + // navigationMenu.hideAllMenus(); + // currentlyHoveredEntry=undefined; + // } + } + } + + navigationMenu.hideAllMenus = function (){ + d3.selectAll(".toolTipMenu").style("display", "none"); // hiding all menus + }; + + navigationMenu.updateScrollButtonVisibility = function (){ + scrollMax = scrollContainer.scrollWidth - scrollContainer.clientWidth - 2; + if ( scrollContainer.scrollLeft === 0 ) { + leftButton.classed("hidden", true); + } else { + leftButton.classed("hidden", false); + } + + if ( scrollContainer.scrollLeft > scrollMax ) { + rightButton.classed("hidden", true); + } else { + rightButton.classed("hidden", false); + } + + }; + + navigationMenu.setup = function (){ + setupControlsAndMenus(); + // make sure that the menu elements follow their controller and also their restrictions + // some hovering behavior -- lets the menu disappear when hovered in graph or sidebar; + d3.select("#graph").on("mouseover", function (){ + navigationMenu.hideAllMenus(); + }); + d3.select("#generalDetails").on("mouseover", function (){ + navigationMenu.hideAllMenus(); + }); + }; + + return navigationMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 337: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** The zoom Slider **/ + module.exports = function ( graph ){ + var zoomSlider = {}; + var minMag = graph.options().minMagnification(), + maxMag = graph.options().maxMagnification(), + defZoom, + t_zoomOut, + t_zoomIn, + zoomValue, + showSlider = true, + w = graph.options().width(), + h = graph.options().height(), + slider; + + defZoom = Math.min(w, h) / 1000; + + function clearAllTimers(){ + cancelAnimationFrame(t_zoomOut); + cancelAnimationFrame(t_zoomIn); + } + + function timed_zoomOut(){ + zoomValue = 0.98 * zoomValue; + // fail saves + if ( zoomValue < minMag ) { + zoomValue = minMag; + } + graph.setSliderZoom(zoomValue); + t_zoomOut = requestAnimationFrame(timed_zoomOut); + } + + function timed_zoomIn(){ + zoomValue = 1.02 * zoomValue; + // fail saves + if ( zoomValue > maxMag ) { + zoomValue = maxMag; + } + graph.setSliderZoom(zoomValue); + t_zoomIn = requestAnimationFrame(timed_zoomIn); + } + + zoomSlider.setup = function (){ + slider = d3.select("#zoomSliderParagraph").append("input") + .datum({}) + .attr("id", "zoomSliderElement") + .attr("type", "range") + .attr("value", defZoom) + .attr("min", minMag) + .attr("max", maxMag) + .attr("step", (maxMag - minMag) / 40) + .attr("title", "zoom factor") + .on("input", function (){ + zoomSlider.zooming(); + }); + + d3.select("#zoomOutButton").on("mousedown", function (){ + graph.options().navigationMenu().hideAllMenus(); + zoomValue = graph.scaleFactor(); + t_zoomOut = requestAnimationFrame(timed_zoomOut); + }) + .on("touchstart", function (){ + graph.options().navigationMenu().hideAllMenus(); + zoomValue = graph.scaleFactor(); + t_zoomOut = requestAnimationFrame(timed_zoomOut); + }) + .on("mouseup", clearAllTimers) + .on("touchend", clearAllTimers) + .on("touchcancel", clearAllTimers) + .attr("title", "zoom out"); + + d3.select("#zoomInButton").on("mousedown", function (){ + graph.options().navigationMenu().hideAllMenus(); + zoomValue = graph.scaleFactor(); + t_zoomIn = requestAnimationFrame(timed_zoomIn); + }) + .on("touchstart", function (){ + graph.options().navigationMenu().hideAllMenus(); + zoomValue = graph.scaleFactor(); + t_zoomIn = requestAnimationFrame(timed_zoomIn); + }) + .on("mouseup", clearAllTimers) + .on("touchend", clearAllTimers) + .on("touchcancel", clearAllTimers) + .attr("title", "zoom in"); + + d3.select("#centerGraphButton").on("click", function (){ + graph.options().navigationMenu().hideAllMenus(); + graph.forceRelocationEvent(); + }).attr("title", "center graph"); + + }; + + zoomSlider.showSlider = function ( val ){ + if ( !arguments.length ) return showSlider; + d3.select("#zoomSlider").classed("hidden", !val); + showSlider = val; + }; + + zoomSlider.zooming = function (){ + graph.options().navigationMenu().hideAllMenus(); + var zoomValue = slider.property("value"); + slider.attr("value", zoomValue); + graph.setSliderZoom(zoomValue); + }; + + zoomSlider.updateZoomSliderValue = function ( val ){ + if ( slider ) { + slider.attr("value", val); + slider.property("value", val); + } + }; + + return zoomSlider; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 338: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for the sidebar. + * @param graph the graph that belongs to these controls + * @returns {{}} + */ + module.exports = function ( graph ){ + + var sidebar = {}, + languageTools = webvowl.util.languageTools(), + elementTools = webvowl.util.elementTools(), + // Required for reloading when the language changes + ontologyInfo, + visibleSidebar = 1, + lastSelectedElement, + + detailArea = d3.select("#detailsArea"), + graphArea = d3.select("#canvasArea"), + menuArea = d3.select("#swipeBarContainer"), + collapseButton = d3.select("#sidebarExpandButton"); + + /** + * Setup the menu bar. + */ + + + function setupCollapsing(){ + // adapted version of this example: http://www.normansblog.de/simple-jquery-accordion/ + function collapseContainers( containers ){ + containers.classed("hidden", true); + } + + function expandContainers( containers ){ + containers.classed("hidden", false); + } + + var triggers = d3.selectAll(".accordion-trigger"); + + // Collapse all inactive triggers on startup + collapseContainers(d3.selectAll(".accordion-trigger:not(.accordion-trigger-active) + div")); + + triggers.on("click", function (){ + var selectedTrigger = d3.select(this), + activeTriggers = d3.selectAll(".accordion-trigger-active"); + + if ( selectedTrigger.classed("accordion-trigger-active") ) { + // Collapse the active (which is also the selected) trigger + collapseContainers(d3.select(selectedTrigger.node().nextElementSibling)); + selectedTrigger.classed("accordion-trigger-active", false); + } else { + // Collapse the other trigger ... + collapseContainers(d3.selectAll(".accordion-trigger-active + div")); + activeTriggers.classed("accordion-trigger-active", false); + // ... and expand the selected one + expandContainers(d3.select(selectedTrigger.node().nextElementSibling)); + selectedTrigger.classed("accordion-trigger-active", true); + } + }); + } + + sidebar.clearOntologyInformation = function (){ + + d3.select("#title").text("No title available"); + d3.select("#about").attr("href", "#").attr("target", "_blank").text("not given"); + d3.select("#version").text("--"); + d3.select("#authors").text("--"); + d3.select("#description").text("No description available."); + var container = d3.select("#ontology-metadata"); + container.selectAll("*").remove(); + d3.select("#classCount") + .text("0"); + d3.select("#objectPropertyCount") + .text("0"); + d3.select("#datatypePropertyCount") + .text("0"); + d3.select("#individualCount") + .text("0"); + d3.select("#nodeCount") + .text("0"); + d3.select("#edgeCount") + .text("0"); + + // clear selectedNode info + var isTriggerActive = d3.select("#selection-details-trigger").classed("accordion-trigger-active"); + if ( isTriggerActive ) { + // close accordion + d3.select("#selection-details-trigger").node().click(); + } + showSelectionAdvice(); + + }; + + /** + * Updates the information of the passed ontology. + * @param data the graph data + * @param statistics the statistics module + */ + sidebar.updateOntologyInformation = function ( data, statistics ){ + data = data || {}; + ontologyInfo = data.header || {}; + + updateGraphInformation(); + displayGraphStatistics(undefined, statistics); + displayMetadata(ontologyInfo.other); + + // Reset the sidebar selection + sidebar.updateSelectionInformation(undefined); + + setLanguages(ontologyInfo.languages); + }; + + function setLanguages( languages ){ + languages = languages || []; + + // Put the default and unset label on top of the selection labels + languages.sort(function ( a, b ){ + if ( a === webvowl.util.constants().LANG_IRIBASED ) { + return -1; + } else if ( b === webvowl.util.constants().LANG_IRIBASED ) { + return 1; + } + if ( a === webvowl.util.constants().LANG_UNDEFINED ) { + return -1; + } else if ( b === webvowl.util.constants().LANG_UNDEFINED ) { + return 1; + } + return a.localeCompare(b); + }); + + var languageSelection = d3.select("#language") + .on("change", function (){ + graph.language(d3.event.target.value); + updateGraphInformation(); + sidebar.updateSelectionInformation(lastSelectedElement); + }); + + languageSelection.selectAll("option").remove(); + languageSelection.selectAll("option") + .data(languages) + .enter().append("option") + .attr("value", function ( d ){ + return d; + }) + .text(function ( d ){ + return d; + }); + + if ( !trySelectDefaultLanguage(languageSelection, languages, "en") ) { + if ( !trySelectDefaultLanguage(languageSelection, languages, webvowl.util.constants().LANG_UNDEFINED) ) { + trySelectDefaultLanguage(languageSelection, languages, webvowl.util.constants().LANG_IRIBASED); + } + } + } + + function trySelectDefaultLanguage( selection, languages, language ){ + var langIndex = languages.indexOf(language); + if ( langIndex >= 0 ) { + selection.property("selectedIndex", langIndex); + graph.language(language); + return true; + } + + return false; + } + + function updateGraphInformation(){ + var title = languageTools.textInLanguage(ontologyInfo.title, graph.language()); + d3.select("#title").text(title || "No title available"); + d3.select("#about").attr("href", ontologyInfo.iri).attr("target", "_blank").text(ontologyInfo.iri); + d3.select("#version").text(ontologyInfo.version || "--"); + var authors = ontologyInfo.author; + if ( typeof authors === "string" ) { + // Stay compatible with author info as strings after change in january 2015 + d3.select("#authors").text(authors); + } else if ( authors instanceof Array ) { + d3.select("#authors").text(authors.join(", ")); + } else { + d3.select("#authors").text("--"); + } + + var description = languageTools.textInLanguage(ontologyInfo.description, graph.language()); + d3.select("#description").text(description || "No description available."); + } + + function displayGraphStatistics( deliveredMetrics, statistics ){ + // Metrics are optional and may be undefined + deliveredMetrics = deliveredMetrics || {}; + + d3.select("#classCount") + .text(deliveredMetrics.classCount || statistics.classCount()); + d3.select("#objectPropertyCount") + .text(deliveredMetrics.objectPropertyCount || statistics.objectPropertyCount()); + d3.select("#datatypePropertyCount") + .text(deliveredMetrics.datatypePropertyCount || statistics.datatypePropertyCount()); + d3.select("#individualCount") + .text(deliveredMetrics.totalIndividualCount || statistics.totalIndividualCount()); + d3.select("#nodeCount") + .text(statistics.nodeCount()); + d3.select("#edgeCount") + .text(statistics.edgeCount()); + } + + function displayMetadata( metadata ){ + var container = d3.select("#ontology-metadata"); + container.selectAll("*").remove(); + + listAnnotations(container, metadata); + + if ( container.selectAll(".annotation").size() <= 0 ) { + container.append("p").text("No annotations available."); + } + } + + function listAnnotations( container, annotationObject ){ + annotationObject = annotationObject || {}; //todo + + // Collect the annotations in an array for simpler processing + var annotations = []; + for ( var annotation in annotationObject ) { + if ( annotationObject.hasOwnProperty(annotation) ) { + annotations.push(annotationObject[annotation][0]); + } + } + + container.selectAll(".annotation").remove(); + container.selectAll(".annotation").data(annotations).enter().append("p") + .classed("annotation", true) + .classed("statisticDetails", true) + .text(function ( d ){ + return d.identifier + ":"; + }) + .append("span") + .each(function ( d ){ + appendIriLabel(d3.select(this), d.value, d.type === "iri" ? d.value : undefined); + }); + } + + /** + * Update the information of the selected node. + * @param selectedElement the selection or null if nothing is selected + */ + sidebar.updateSelectionInformation = function ( selectedElement ){ + lastSelectedElement = selectedElement; + + // Click event was prevented when dragging + if ( d3.event && d3.event.defaultPrevented ) { + return; + } + + var isTriggerActive = d3.select("#selection-details-trigger").classed("accordion-trigger-active"); + if ( selectedElement && !isTriggerActive ) { + d3.select("#selection-details-trigger").node().click(); + } else if ( !selectedElement && isTriggerActive ) { + showSelectionAdvice(); + return; + } + + if ( elementTools.isProperty(selectedElement) ) { + displayPropertyInformation(selectedElement); + } else if ( elementTools.isNode(selectedElement) ) { + displayNodeInformation(selectedElement); + } + }; + + function showSelectionAdvice(){ + setSelectionInformationVisibility(false, false, true); + } + + function setSelectionInformationVisibility( showClasses, showProperties, showAdvice ){ + d3.select("#classSelectionInformation").classed("hidden", !showClasses); + d3.select("#propertySelectionInformation").classed("hidden", !showProperties); + d3.select("#noSelectionInformation").classed("hidden", !showAdvice); + } + + function displayPropertyInformation( property ){ + showPropertyInformations(); + + setIriLabel(d3.select("#propname"), property.labelForCurrentLanguage(), property.iri()); + d3.select("#typeProp").text(property.type()); + + if ( property.inverse() !== undefined ) { + d3.select("#inverse").classed("hidden", false); + setIriLabel(d3.select("#inverse span"), property.inverse().labelForCurrentLanguage(), property.inverse().iri()); + } else { + d3.select("#inverse").classed("hidden", true); + } + + var equivalentIriSpan = d3.select("#propEquivUri"); + listNodeArray(equivalentIriSpan, property.equivalents()); + + listNodeArray(d3.select("#subproperties"), property.subproperties()); + listNodeArray(d3.select("#superproperties"), property.superproperties()); + + if ( property.minCardinality() !== undefined ) { + d3.select("#infoCardinality").classed("hidden", true); + d3.select("#minCardinality").classed("hidden", false); + d3.select("#minCardinality span").text(property.minCardinality()); + d3.select("#maxCardinality").classed("hidden", false); + + if ( property.maxCardinality() !== undefined ) { + d3.select("#maxCardinality span").text(property.maxCardinality()); + } else { + d3.select("#maxCardinality span").text("*"); + } + + } else if ( property.cardinality() !== undefined ) { + d3.select("#minCardinality").classed("hidden", true); + d3.select("#maxCardinality").classed("hidden", true); + d3.select("#infoCardinality").classed("hidden", false); + d3.select("#infoCardinality span").text(property.cardinality()); + } else { + d3.select("#infoCardinality").classed("hidden", true); + d3.select("#minCardinality").classed("hidden", true); + d3.select("#maxCardinality").classed("hidden", true); + } + + setIriLabel(d3.select("#domain"), property.domain().labelForCurrentLanguage(), property.domain().iri()); + setIriLabel(d3.select("#range"), property.range().labelForCurrentLanguage(), property.range().iri()); + + displayAttributes(property.attributes(), d3.select("#propAttributes")); + + setTextAndVisibility(d3.select("#propDescription"), property.descriptionForCurrentLanguage()); + setTextAndVisibility(d3.select("#propComment"), property.commentForCurrentLanguage()); + + listAnnotations(d3.select("#propertySelectionInformation"), property.annotations()); + } + + function showPropertyInformations(){ + setSelectionInformationVisibility(false, true, false); + } + + function setIriLabel( element, name, iri ){ + var parent = d3.select(element.node().parentNode); + + if ( name ) { + element.selectAll("*").remove(); + appendIriLabel(element, name, iri); + parent.classed("hidden", false); + } else { + parent.classed("hidden", true); + } + } + + function appendIriLabel( element, name, iri ){ + var tag; + + if ( iri ) { + tag = element.append("a") + .attr("href", iri) + .attr("title", iri) + .attr("target", "_blank"); + } else { + tag = element.append("span"); + } + tag.text(name); + } + + function displayAttributes( attributes, textSpan ){ + var spanParent = d3.select(textSpan.node().parentNode); + + if ( attributes && attributes.length > 0 ) { + // Remove redundant redundant attributes for sidebar + removeElementFromArray("object", attributes); + removeElementFromArray("datatype", attributes); + removeElementFromArray("rdf", attributes); + } + + if ( attributes && attributes.length > 0 ) { + textSpan.text(attributes.join(", ")); + + spanParent.classed("hidden", false); + } else { + spanParent.classed("hidden", true); + } + } + + function removeElementFromArray( element, array ){ + var index = array.indexOf(element); + if ( index > -1 ) { + array.splice(index, 1); + } + } + + function displayNodeInformation( node ){ + showClassInformations(); + + setIriLabel(d3.select("#name"), node.labelForCurrentLanguage(), node.iri()); + + /* Equivalent stuff. */ + var equivalentIriSpan = d3.select("#classEquivUri"); + listNodeArray(equivalentIriSpan, node.equivalents()); + + d3.select("#typeNode").text(node.type()); + listNodeArray(d3.select("#individuals"), node.individuals()); + + /* Disjoint stuff. */ + var disjointNodes = d3.select("#disjointNodes"); + var disjointNodesParent = d3.select(disjointNodes.node().parentNode); + + if ( node.disjointWith() !== undefined ) { + disjointNodes.selectAll("*").remove(); + + node.disjointWith().forEach(function ( element, index ){ + if ( index > 0 ) { + disjointNodes.append("span").text(", "); + } + appendIriLabel(disjointNodes, element.labelForCurrentLanguage(), element.iri()); + }); + + disjointNodesParent.classed("hidden", false); + } else { + disjointNodesParent.classed("hidden", true); + } + + displayAttributes(node.attributes(), d3.select("#classAttributes")); + + setTextAndVisibility(d3.select("#nodeDescription"), node.descriptionForCurrentLanguage()); + setTextAndVisibility(d3.select("#nodeComment"), node.commentForCurrentLanguage()); + + listAnnotations(d3.select("#classSelectionInformation"), node.annotations()); + } + + function showClassInformations(){ + setSelectionInformationVisibility(true, false, false); + } + + function listNodeArray( textSpan, nodes ){ + var spanParent = d3.select(textSpan.node().parentNode); + + if ( nodes && nodes.length ) { + textSpan.selectAll("*").remove(); + nodes.forEach(function ( element, index ){ + if ( index > 0 ) { + textSpan.append("span").text(", "); + } + appendIriLabel(textSpan, element.labelForCurrentLanguage(), element.iri()); + }); + + spanParent.classed("hidden", false); + } else { + spanParent.classed("hidden", true); + } + } + + function setTextAndVisibility( label, value ){ + var parentNode = d3.select(label.node().parentNode); + var hasValue = !!value; + if ( value ) { + label.text(value); + } + parentNode.classed("hidden", !hasValue); + } + + /** Collapsible Sidebar functions; **/ + + sidebar.showSidebar = function ( val, init ){ + // make val to bool + if ( val === 1 ) { + visibleSidebar = true; + collapseButton.node().innerHTML = ">"; + detailArea.classed("hidden", true); + if ( init === true ) { + detailArea.classed("hidden", !visibleSidebar); + graphArea.style("width", "78%"); + graphArea.style("-webkit-animation-name", "none"); + + menuArea.style("width", "78%"); + menuArea.style("-webkit-animation-name", "none"); + + d3.select("#WarningErrorMessagesContainer").style("width", "78%"); + d3.select("#WarningErrorMessagesContainer").style("-webkit-animation-name", "none"); + } else { + graphArea.style("width", "78%"); + graphArea.style("-webkit-animation-name", "sbCollapseAnimation"); + graphArea.style("-webkit-animation-duration", "0.5s"); + + menuArea.style("width", "78%"); + menuArea.style("-webkit-animation-name", "sbCollapseAnimation"); + menuArea.style("-webkit-animation-duration", "0.5s"); + + d3.select("#WarningErrorMessagesContainer").style("width", "78%"); + d3.select("#WarningErrorMessagesContainer").style("-webkit-animation-name", "warn_ExpandRightBarAnimation"); + d3.select("#WarningErrorMessagesContainer").style("-webkit-animation-duration", "0.5s"); + } + graph.options().width(window.innerWidth - (window.innerWidth * 0.22)); + graph.options().navigationMenu().updateScrollButtonVisibility(); + } + if ( val === 0 ) { + visibleSidebar = false; + detailArea.classed("hidden", true); + + collapseButton.node().innerHTML = "<"; + // adjust the layout + if ( init === true ) { + graphArea.style("width", "100%"); + graphArea.style("-webkit-animation-name", "none"); + + menuArea.style("width", "100%"); + menuArea.style("-webkit-animation-name", "none"); + + d3.select("#WarningErrorMessagesContainer").style("width", "100%"); + d3.select("#WarningErrorMessagesContainer").style("-webkit-animation-name", "none"); + } else { + graphArea.style("width", "100%"); + graphArea.style("-webkit-animation-name", "sbExpandAnimation"); + graphArea.style("-webkit-animation-duration", "0.5s"); + + menuArea.style("width", "100%"); + menuArea.style("-webkit-animation-name", "sbExpandAnimation"); + menuArea.style("-webkit-animation-duration", "0.5s"); + + d3.select("#WarningErrorMessagesContainer").style("width", "100%"); + d3.select("#WarningErrorMessagesContainer").style("-webkit-animation-name", "warn_CollapseRightBarAnimation"); + d3.select("#WarningErrorMessagesContainer").style("-webkit-animation-duration", "0.5s"); + + } + graph.options().width(window.innerWidth); + graph.updateCanvasContainerSize(); + graph.options().navigationMenu().updateScrollButtonVisibility(); + } + }; + + sidebar.isSidebarVisible = function (){ + return visibleSidebar; + }; + + sidebar.updateSideBarVis = function ( init ){ + var vis = sidebar.getSidebarVisibility(); + sidebar.showSidebar(parseInt(vis), init); + }; + + sidebar.getSidebarVisibility = function (){ + var isHidden = detailArea.classed("hidden"); + if ( isHidden === false ) return String(1); + if ( isHidden === true ) return String(0); + }; + + sidebar.initSideBarAnimation = function (){ + graphArea.node().addEventListener("animationend", function (){ + detailArea.classed("hidden", !visibleSidebar); + graph.updateCanvasContainerSize(); + graph.options().navigationMenu().updateScrollButtonVisibility(); + }); + }; + + sidebar.setup = function (){ + setupCollapsing(); + sidebar.initSideBarAnimation(); + + collapseButton.on("click", function (){ + graph.options().navigationMenu().hideAllMenus(); + var settingValue = parseInt(sidebar.getSidebarVisibility()); + if ( settingValue === 1 ) sidebar.showSidebar(0); + else sidebar.showSidebar(1); + }); + }; + + + sidebar.updateShowedInformation = function (){ + var editMode = graph.editorMode(); + d3.select("#generalDetails").classed("hidden", editMode); + d3.select("#generalDetailsEdit").classed("hidden", !editMode); + + // store the meta information in graph.options() + + // todo: update edit meta info + graph.options().editSidebar().updateGeneralOntologyInfo(); + + // todo: update showed meta info; + graph.options().sidebar().updateGeneralOntologyInfo(); + + }; + + sidebar.updateGeneralOntologyInfo = function (){ + // get it from graph.options + var generalMetaObj = graph.options().getGeneralMetaObject(); + var preferredLanguage = graph && graph.language ? graph.language() : null; + if ( generalMetaObj.hasOwnProperty("title") ) { + // title has language to it -.- + if ( typeof generalMetaObj.title === "object" ) { + d3.select("#title").node().value = languageTools.textInLanguage(generalMetaObj.title, preferredLanguage); + } else { + d3.select("#title").node().innerHTML = generalMetaObj.title; + } + + } + if ( generalMetaObj.hasOwnProperty("iri") ) d3.select("#about").node().innerHTML = generalMetaObj.iri; + if ( generalMetaObj.hasOwnProperty("iri") ) d3.select("#about").node().href = generalMetaObj.iri; + if ( generalMetaObj.hasOwnProperty("version") ) d3.select("#version").node().innerHTML = generalMetaObj.version; + if ( generalMetaObj.hasOwnProperty("author") ) d3.select("#authors").node().innerHTML = generalMetaObj.author; + // this could also be an object >> + if ( generalMetaObj.hasOwnProperty("description") ) { + if ( typeof generalMetaObj.description === "object" ) { + d3.select("#description").node().innerHTML = languageTools.textInLanguage(generalMetaObj.description, preferredLanguage); + } + else { + d3.select("#description").node().innerHTML = generalMetaObj.description; + } + } + }; + + + return sidebar; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 339: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for the sidebar. + * @param graph the graph that belongs to these controls + * @returns {{}} + */ + module.exports = function ( graph ){ + + var leftSidebar = {}, + languageTools = webvowl.util.languageTools(), + elementTools = webvowl.util.elementTools(); + var collapseButton = d3.select("#leftSideBarCollapseButton"); + var visibleSidebar = 0; + var backupVisibility = 0; + var sideBarContent = d3.select("#leftSideBarContent"); + var sideBarContainer = d3.select("#containerForLeftSideBar"); + var defaultClassSelectionContainers = []; + var defaultDatatypeSelectionContainers = []; + var defaultPropertySelectionContainers = []; + + leftSidebar.setup = function (){ + setupCollapsing(); + leftSidebar.initSideBarAnimation(); + + collapseButton.on("click", function (){ + graph.options().navigationMenu().hideAllMenus(); + var settingValue = parseInt(leftSidebar.getSidebarVisibility()); + if ( settingValue === 0 ) leftSidebar.showSidebar(1); + else leftSidebar.showSidebar(0); + backupVisibility = settingValue; + }); + + setupSelectionContainers(); + d3.select("#WarningErrorMessages").node().addEventListener("animationend", function (){ + d3.select("#WarningErrorMessages").style("-webkit-animation-name", "none"); + }); + + }; + + leftSidebar.hideCollapseButton = function ( val ){ + sideBarContainer.classed("hidden", val); + }; + + + function unselectAllElements( container ){ + for ( var i = 0; i < container.length; i++ ) + container[i].classed("defaultSelected", false); + } + + function selectThisDefaultElement( element ){ + d3.select(element).classed("defaultSelected", true); + } + + function updateDefaultNameInAccordion( element, identifier ){ + var elementDescription = ""; + if ( identifier === "defaultClass" ) elementDescription = "Class: "; + if ( identifier === "defaultDatatype" ) elementDescription = "Datatype: "; + if ( identifier === "defaultProperty" ) elementDescription = "Property: "; + + d3.select("#" + identifier).node().innerHTML = elementDescription + element.innerHTML; + d3.select("#" + identifier).node().title = element.innerHTML; + } + + function classSelectorFunction(){ + unselectAllElements(defaultClassSelectionContainers); + selectThisDefaultElement(this); + updateDefaultNameInAccordion(this, "defaultClass"); + } + + function datatypeSelectorFunction(){ + unselectAllElements(defaultDatatypeSelectionContainers); + selectThisDefaultElement(this); + updateDefaultNameInAccordion(this, "defaultDatatype"); + } + + function propertySelectorFunction(){ + unselectAllElements(defaultPropertySelectionContainers); + selectThisDefaultElement(this); + updateDefaultNameInAccordion(this, "defaultProperty"); + } + + + function setupSelectionContainers(){ + var classContainer = d3.select("#classContainer"); + var datatypeContainer = d3.select("#datatypeContainer"); + var propertyContainer = d3.select("#propertyContainer"); + // create the supported elements + + var defaultClass = "owl:Class"; + var defaultDatatype = "rdfs:Literal"; + var defaultProperty = "owl:objectProperty"; + + var supportedClasses = graph.options().supportedClasses(); + var supportedDatatypes = graph.options().supportedDatatypes(); + var supportedProperties = graph.options().supportedProperties(); + var i; + + for ( i = 0; i < supportedClasses.length; i++ ) { + var aClassSelectionContainer; + aClassSelectionContainer = classContainer.append("div"); + aClassSelectionContainer.classed("containerForDefaultSelection", true); + aClassSelectionContainer.classed("noselect", true); + aClassSelectionContainer.node().id = "selectedClass" + supportedClasses[i]; + aClassSelectionContainer.node().innerHTML = supportedClasses[i]; + + if ( supportedClasses[i] === defaultClass ) { + selectThisDefaultElement(aClassSelectionContainer.node()); + } + aClassSelectionContainer.on("click", classSelectorFunction); + defaultClassSelectionContainers.push(aClassSelectionContainer); + } + + for ( i = 0; i < supportedDatatypes.length; i++ ) { + var aDTSelectionContainer = datatypeContainer.append("div"); + aDTSelectionContainer.classed("containerForDefaultSelection", true); + aDTSelectionContainer.classed("noselect", true); + aDTSelectionContainer.node().id = "selectedDatatype" + supportedDatatypes[i]; + aDTSelectionContainer.node().innerHTML = supportedDatatypes[i]; + + if ( supportedDatatypes[i] === defaultDatatype ) { + selectThisDefaultElement(aDTSelectionContainer.node()); + } + aDTSelectionContainer.on("click", datatypeSelectorFunction); + defaultDatatypeSelectionContainers.push(aDTSelectionContainer); + } + for ( i = 0; i < supportedProperties.length; i++ ) { + var aPropSelectionContainer = propertyContainer.append("div"); + aPropSelectionContainer.classed("containerForDefaultSelection", true); + aPropSelectionContainer.classed("noselect", true); + aPropSelectionContainer.node().id = "selectedClass" + supportedProperties[i]; + aPropSelectionContainer.node().innerHTML = supportedProperties[i]; + aPropSelectionContainer.on("click", propertySelectorFunction); + if ( supportedProperties[i] === defaultProperty ) { + selectThisDefaultElement(aPropSelectionContainer.node()); + } + defaultPropertySelectionContainers.push(aPropSelectionContainer); + } + } + + function setupCollapsing(){ + // adapted version of this example: http://www.normansblog.de/simple-jquery-accordion/ + function collapseContainers( containers ){ + containers.classed("hidden", true); + } + + function expandContainers( containers ){ + containers.classed("hidden", false); + } + + var triggers = d3.selectAll(".accordion-trigger"); + + // Collapse all inactive triggers on startup + // collapseContainers(d3.selectAll(".accordion-trigger:not(.accordion-trigger-active) + div")); + + triggers.on("click", function (){ + var selectedTrigger = d3.select(this); + if ( selectedTrigger.classed("accordion-trigger-active") ) { + // Collapse the active (which is also the selected) trigger + collapseContainers(d3.select(selectedTrigger.node().nextElementSibling)); + selectedTrigger.classed("accordion-trigger-active", false); + } else { + // Collapse the other trigger ... + // collapseContainers(d3.selectAll(".accordion-trigger-active + div")); + // activeTriggers.classed("accordion-trigger-active", false); + // ... and expand the selected one + expandContainers(d3.select(selectedTrigger.node().nextElementSibling)); + selectedTrigger.classed("accordion-trigger-active", true); + } + }); + } + + + leftSidebar.isSidebarVisible = function (){ + return visibleSidebar; + }; + + leftSidebar.updateSideBarVis = function ( init ){ + var vis = leftSidebar.getSidebarVisibility(); + leftSidebar.showSidebar(parseInt(vis), init); + }; + + leftSidebar.initSideBarAnimation = function (){ + sideBarContainer.node().addEventListener("animationend", function (){ + sideBarContent.classed("hidden", !visibleSidebar); + if ( visibleSidebar === true ) { + sideBarContainer.style("width", "200px"); + sideBarContent.classed("hidden", false); + d3.select("#leftSideBarCollapseButton").style("left", "200px"); + d3.select("#leftSideBarCollapseButton").classed("hidden", false); + d3.select("#WarningErrorMessages").style("left", "100px"); + } + else { + sideBarContainer.style("width", "0px"); + d3.select("#leftSideBarCollapseButton").style("left", "0px"); + d3.select("#WarningErrorMessages").style("left", "0px"); + d3.select("#leftSideBarCollapseButton").classed("hidden", false); + + } + graph.updateCanvasContainerSize(); + graph.options().navigationMenu().updateScrollButtonVisibility(); + }); + }; + + leftSidebar.showSidebar = function ( val, init ){ + // make val to bool + var collapseButton = d3.select("#leftSideBarCollapseButton"); + if ( init === true ) { + visibleSidebar = (backupVisibility === 0); + sideBarContent.classed("hidden", !visibleSidebar); + sideBarContainer.style("-webkit-animation-name", "none"); + d3.select("#WarningErrorMessages").style("-webkit-animation-name", "none"); + if ( visibleSidebar === true ) { + sideBarContainer.style("width", "200px"); + sideBarContent.classed("hidden", false); + d3.select("#leftSideBarCollapseButton").style("left", "200px"); + d3.select("#leftSideBarCollapseButton").classed("hidden", false); + d3.select("#WarningErrorMessages").style("left", "100px"); + collapseButton.node().innerHTML = "<"; + } + + else { + sideBarContainer.style("width", "0px"); + d3.select("#WarningErrorMessages").style("left", "0px"); + d3.select("#leftSideBarCollapseButton").style("left", "0px"); + d3.select("#leftSideBarCollapseButton").classed("hidden", false); + collapseButton.node().innerHTML = ">"; + } + + graph.updateCanvasContainerSize(); + graph.options().navigationMenu().updateScrollButtonVisibility(); + return; + } + + d3.select("#leftSideBarCollapseButton").classed("hidden", true); + + if ( val === 1 ) { + visibleSidebar = true; + collapseButton.node().innerHTML = "<"; + // call expand animation; + sideBarContainer.style("-webkit-animation-name", "l_sbExpandAnimation"); + sideBarContainer.style("-webkit-animation-duration", "0.5s"); + // prepare the animation; + + d3.select("#WarningErrorMessages").style("-webkit-animation-name", "warn_ExpandLeftBarAnimation"); + d3.select("#WarningErrorMessages").style("-webkit-animation-duration", "0.5s"); + + } + if ( val === 0 ) { + visibleSidebar = false; + sideBarContent.classed("hidden", true); + collapseButton.node().innerHTML = ">"; + // call collapse animation + sideBarContainer.style("-webkit-animation-name", "l_sbCollapseAnimation"); + sideBarContainer.style("-webkit-animation-duration", "0.5s"); + d3.select("#WarningErrorMessages").style("-webkit-animation-name", "warn_CollapseLeftBarAnimation"); + d3.select("#WarningErrorMessages").style("-webkit-animation-duration", "0.5s"); + d3.select("#WarningErrorMessages").style("left", "0"); + } + + }; + + leftSidebar.getSidebarVisibility = function (){ + var isHidden = sideBarContent.classed("hidden"); + if ( isHidden === false ) return String(1); + if ( isHidden === true ) return String(0); + }; + + return leftSidebar; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 340: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains the logic for the sidebar. + * @param graph the graph that belongs to these controls + * @returns {{}} + */ + module.exports = function ( graph ){ + + var editSidebar = {}, + languageTools = webvowl.util.languageTools(), + elementTools = webvowl.util.elementTools(); + + var prefixModule = webvowl.util.prefixTools(graph); + var selectedElementForCharacteristics; + var oldPrefix, oldPrefixURL; + var prefix_editMode = false; + + + editSidebar.clearMetaObjectValue = function (){ + d3.select("#titleEditor").node().value = ""; + d3.select("#iriEditor").node().value = ""; + d3.select("#versionEditor").node().value = ""; + d3.select("#authorsEditor").node().value = ""; + d3.select("#descriptionEditor").node().value = ""; + // todo add clear description; + }; + + + editSidebar.updatePrefixUi = function (){ + editSidebar.updateElementWidth(); + var prefixListContainer = d3.select("#prefixURL_Container"); + while ( prefixListContainer.node().firstChild ) { + prefixListContainer.node().removeChild(prefixListContainer.node().firstChild); + } + setupPrefixList(); + }; + + editSidebar.setup = function (){ + setupCollapsing(); + setupPrefixList(); + setupAddPrefixButton(); + setupSupportedDatatypes(); + + + d3.select("#titleEditor") + .on("change", function (){ + graph.options().addOrUpdateGeneralObjectEntry("title", d3.select("#titleEditor").node().value); + }) + .on("keydown", function (){ + d3.event.stopPropagation(); + if ( d3.event.keyCode === 13 ) { + d3.event.preventDefault(); + graph.options().addOrUpdateGeneralObjectEntry("title", d3.select("#titleEditor").node().value); + } + }); + d3.select("#iriEditor") + .on("change", function (){ + if ( graph.options().addOrUpdateGeneralObjectEntry("iri", d3.select("#iriEditor").node().value) === false ) { + // restore value + d3.select("#iriEditor").node().value = graph.options().getGeneralMetaObjectProperty('iri'); + } + }) + .on("keydown", function (){ + d3.event.stopPropagation(); + if ( d3.event.keyCode === 13 ) { + d3.event.preventDefault(); + if ( graph.options().addOrUpdateGeneralObjectEntry("iri", d3.select("#iriEditor").node().value) === false ) { + // restore value + d3.select("#iriEditor").node().value = graph.options().getGeneralMetaObjectProperty('iri'); + } + } + }); + d3.select("#versionEditor") + .on("change", function (){ + graph.options().addOrUpdateGeneralObjectEntry("version", d3.select("#versionEditor").node().value); + }) + .on("keydown", function (){ + d3.event.stopPropagation(); + if ( d3.event.keyCode === 13 ) { + d3.event.preventDefault(); + graph.options().addOrUpdateGeneralObjectEntry("version", d3.select("#versionEditor").node().value); + } + }); + d3.select("#authorsEditor") + .on("change", function (){ + graph.options().addOrUpdateGeneralObjectEntry("author", d3.select("#authorsEditor").node().value); + }) + .on("keydown", function (){ + d3.event.stopPropagation(); + if ( d3.event.keyCode === 13 ) { + d3.event.preventDefault(); + graph.options().addOrUpdateGeneralObjectEntry("author", d3.select("#authorsEditor").node().value); + } + }); + d3.select("#descriptionEditor") + .on("change", function (){ + graph.options().addOrUpdateGeneralObjectEntry("description", d3.select("#descriptionEditor").node().value); + }); + + editSidebar.updateElementWidth(); + + }; + + function setupSupportedDatatypes(){ + var datatypeEditorSelection = d3.select("#typeEditor_datatype").node(); + var supportedDatatypes = ["undefined", "xsd:boolean", "xsd:double", "xsd:integer", "xsd:string"]; + for ( var i = 0; i < supportedDatatypes.length; i++ ) { + var optB = document.createElement('option'); + optB.innerHTML = supportedDatatypes[i]; + datatypeEditorSelection.appendChild(optB); + } + } + + function highlightDeleteButton( enable, name ){ + var deletePath = d3.select("#del_pathFor_" + name); + var deleteRect = d3.select("#del_rectFor_" + name); + + if ( enable === false ) { + deletePath.node().style = "stroke: #f00;"; + deleteRect.style("cursor", "auto"); + } else { + deletePath.node().style = "stroke: #ff972d;"; + deleteRect.style("cursor", "pointer"); + } + } + + + function highlightEditButton( enable, name, fill ){ + var editPath = d3.select("#pathFor_" + name); + var editRect = d3.select("#rectFor_" + name); + + if ( enable === false ) { + if ( fill ) + editPath.node().style = "fill: #fff; stroke : #fff; stroke-width : 1px"; + else + editPath.node().style = " stroke : #fff; stroke-width : 1px"; + + editRect.style("cursor", "auto"); + } else { + if ( fill ) + editPath.node().style = "fill: #ff972d; stroke : #ff972d; stroke-width : 1px"; + else + editPath.node().style = "stroke : #ff972d; stroke-width : 1px"; + editRect.style("cursor", "pointer"); + } + + } + + function setupAddPrefixButton(){ + var btn = d3.select("#addPrefixButton"); + btn.on("click", function (){ + + // check if we are still in editMode? + if ( prefix_editMode === false ) { + // create new line entry; + var name = "emptyPrefixEntry"; + var prefixListContainer = d3.select("#prefixURL_Container"); + var prefixEditContainer = prefixListContainer.append("div"); + prefixEditContainer.classed("prefixIRIElements", true); + prefixEditContainer.node().id = "prefixContainerFor_" + name; + + var IconContainer = prefixEditContainer.append("div"); + IconContainer.style("position", "absolute"); + IconContainer.node().id = "containerFor_" + name; + var editButton = IconContainer.append("svg"); + editButton.style("width", "14px"); + editButton.style("height", "20px"); + // editButton.classed("editPrefixButton", true); + editButton.classed("noselect", true); + //editButton.node().innerHTML = "\u2714"; + editButton.node().id = "editButtonFor_" + name; + + editButton.node().elementStyle = "save"; + editButton.node().selectorName = name; + var editIcon = editButton.append("g"); + var editRect = editIcon.append("rect"); + var editPath = editIcon.append("path"); + editIcon.node().id = "iconFor_" + name; + editPath.node().id = "pathFor_" + name; + editRect.node().id = "rectFor_" + name; + + editIcon.node().selectorName = name; + editPath.node().selectorName = name; + editRect.node().selectorName = name; + IconContainer.node().title = "Save new prefix and IRI"; + + editPath.classed("editPrefixIcon"); + editPath.style("stroke", "#fff"); + editPath.style("stroke-width", "1px"); + editPath.style("fill", "#fff"); + editRect.attr("width", "14px"); + editRect.attr("height", "14px"); + editRect.style("fill", "#18202A"); + editRect.attr("transform", "matrix(1,0,0,1,-3,4)"); + + editButton.selectAll("g").on("mouseover", function (){ + highlightEditButton(true, this.selectorName, true); + }); + editButton.selectAll("g").on("mouseout", function (){ + highlightEditButton(false, this.selectorName, true); + }); + // Check mark + // M9 16.2L4.8 12l-1.4 1.4L9 19 21 7l-1.4-1.4L9 16.2z + // pencil + // M3 17.25V21h3.75L17.81 9.94l-3.75-3.75L3 17.25zM20.71 7.04c.39-.39.39-1.02 0-1.41l-2.34-2.34c-.39-.39-1.02-.39-1.41 0l-1.83 1.83 3.75 3.75 1.83-1.83z + editPath.attr("d", "M9 16.2L4.8 12l-1.4 1.4L9 19 21 7l-1.4-1.4L9 16.2z"); + editPath.attr("transform", "matrix(0.45,0,0,0.45,0,5)"); + + var prefInput = prefixEditContainer.append("input"); + prefInput.classed("prefixInput", true); + prefInput.node().type = "text"; + prefInput.node().id = "prefixInputFor_" + name; + prefInput.node().autocomplete = "off"; + prefInput.node().value = ""; + prefInput.style("margin-left", "14px"); + + var prefURL = prefixEditContainer.append("input"); + prefURL.classed("prefixURL", true); + prefURL.node().type = "text"; + prefURL.node().id = "prefixURLFor_" + name; + prefURL.node().autocomplete = "off"; + prefURL.node().value = ""; + + prefInput.node().disabled = false; + prefURL.node().disabled = false; + prefix_editMode = true; + var deleteContainer = prefixEditContainer.append("div"); + deleteContainer.style("float", "right"); + var deleteButton = deleteContainer.append("svg"); + deleteButton.node().id = "deleteButtonFor_" + name; + deleteContainer.node().title = "Delete prefix and IRI"; + deleteButton.style("width", "10px"); + deleteButton.style("height", "20px"); + var deleteIcon = deleteButton.append("g"); + var deleteRect = deleteIcon.append("rect"); + var deletePath = deleteIcon.append("path"); + deleteIcon.node().id = "del_iconFor_" + name; + deletePath.node().id = "del_pathFor_" + name; + deleteRect.node().id = "del_rectFor_" + name; + + deleteIcon.node().selectorName = name; + deletePath.node().selectorName = name; + deleteRect.node().selectorName = name; + + + deletePath.style("stroke", "#f00"); + deleteRect.attr("width", "10px"); + deleteRect.attr("height", "14px"); + deleteRect.style("fill", "#18202A"); + deleteRect.attr("transform", "matrix(1,0,0,1,-3,4)"); + + + deletePath.attr("d", "M19 6.41L17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12z"); + deletePath.attr("transform", "matrix(0.45,0,0,0.45,0,5)"); + + deleteButton.selectAll("g").on("mouseover", function (){ + highlightDeleteButton(true, this.selectorName); + }); + deleteButton.selectAll("g").on("mouseout", function (){ + highlightDeleteButton(false, this.selectorName); + }); + + + // connect the buttons; + editButton.on("click", enablePrefixEdit); + deleteButton.on("click", deletePrefixLine); + + editSidebar.updateElementWidth(); + // swap focus to prefixInput + prefInput.node().focus(); + oldPrefix = name; + oldPrefixURL = ""; + d3.select("#addPrefixButton").node().innerHTML = "Save Prefix"; + } else { + d3.select("#editButtonFor_emptyPrefixEntry").on("click")(d3.select("#editButtonFor_emptyPrefixEntry").node()); + } + + }); + + } + + function setupPrefixList(){ + if ( graph.isEditorMode() === false ) return; + var prefixListContainer = d3.select("#prefixURL_Container"); + var prefixElements = graph.options().prefixList(); + for ( var name in prefixElements ) { + if ( prefixElements.hasOwnProperty(name) ) { + var prefixEditContainer = prefixListContainer.append("div"); + prefixEditContainer.classed("prefixIRIElements", true); + prefixEditContainer.node().id = "prefixContainerFor_" + name; + + // create edit button which enables the input fields + var IconContainer = prefixEditContainer.append("div"); + IconContainer.style("position", "absolute"); + IconContainer.node().id = "containerFor_" + name; + var editButton = IconContainer.append("svg"); + editButton.style("width", "14px"); + editButton.style("height", "20px"); + editButton.classed("noselect", true); + editButton.node().id = "editButtonFor_" + name; + IconContainer.node().title = "Edit prefix and IRI"; + editButton.node().elementStyle = "save"; + editButton.node().selectorName = name; + + editButton.node().id = "editButtonFor_" + name; + editButton.node().elementStyle = "edit"; + var editIcon = editButton.append("g"); + var editRect = editIcon.append("rect"); + var editPath = editIcon.append("path"); + editIcon.node().id = "iconFor_" + name; + editPath.node().id = "pathFor_" + name; + editRect.node().id = "rectFor_" + name; + + editIcon.node().selectorName = name; + editPath.node().selectorName = name; + editRect.node().selectorName = name; + + + editPath.classed("editPrefixIcon"); + editPath.style("stroke", "#fff"); + editPath.style("stroke-width", "1px"); + editRect.attr("width", "14px"); + editRect.attr("height", "14px"); + editRect.style("fill", "#18202A"); + editRect.attr("transform", "matrix(1,0,0,1,-3,4)"); + + editButton.selectAll("g").on("mouseover", function (){ + var sender = this; + var fill = false; + var enable = true; + var f_editPath = d3.select("#pathFor_" + sender.selectorName); + var f_editRect = d3.select("#rectFor_" + sender.selectorName); + + if ( enable === false ) { + if ( fill ) + f_editPath.node().style = "fill: #fff; stroke : #fff; stroke-width : 1px"; + else + f_editPath.node().style = " stroke : #fff; stroke-width : 1px"; + + f_editRect.style("cursor", "auto"); + } else { + if ( fill ) + f_editPath.node().style = "fill: #ff972d; stroke : #ff972d; stroke-width : 1px"; + else + f_editPath.node().style = "stroke : #ff972d; stroke-width : 1px"; + f_editRect.style("cursor", "pointer"); + } + }); + editButton.selectAll("g").on("mouseout", function (){ + var sender = this; + var fill = false; + var enable = false; + var f_editPath = d3.select("#pathFor_" + sender.selectorName); + var f_editRect = d3.select("#rectFor_" + sender.selectorName); + + if ( enable === false ) { + if ( fill ) + f_editPath.node().style = "fill: #fff; stroke : #fff; stroke-width : 1px"; + else + f_editPath.node().style = " stroke : #fff; stroke-width : 1px"; + + f_editRect.style("cursor", "auto"); + } else { + if ( fill ) + f_editPath.node().style = "fill: #ff972d; stroke : #ff972d; stroke-width : 1px"; + else + f_editPath.node().style = "stroke : #ff972d; stroke-width : 1px"; + f_editRect.style("cursor", "pointer"); + } + }); + + editPath.attr("d", "M3 17.25V21h3.75L17.81 9.94l-3.75-3.75L3 17.25zM20.71 7.04c.39-.39.39-1.02 0-1.41l-2.34-2.34c-.39-.39-1.02-.39-1.41 0l-1.83 1.83 3.75 3.75 1.83-1.83z"); + editPath.attr("transform", "matrix(-0.45,0,0,0.45,10,5)"); + + // create input field for prefix + var prefInput = prefixEditContainer.append("input"); + prefInput.classed("prefixInput", true); + prefInput.node().type = "text"; + prefInput.node().id = "prefixInputFor_" + name; + prefInput.node().autocomplete = "off"; + prefInput.node().value = name; + prefInput.style("margin-left", "14px"); + + // create input field for prefix url + var prefURL = prefixEditContainer.append("input"); + prefURL.classed("prefixURL", true); + prefURL.node().type = "text"; + prefURL.node().id = "prefixURLFor_" + name; + prefURL.node().autocomplete = "off"; + prefURL.node().value = prefixElements[name]; + prefURL.node().title = prefixElements[name]; + // disable the input fields (already defined elements can be edited later) + prefInput.node().disabled = true; + prefURL.node().disabled = true; + + // create the delete button + var deleteContainer = prefixEditContainer.append("div"); + deleteContainer.style("float", "right"); + var deleteButton = deleteContainer.append("svg"); + deleteButton.node().id = "deleteButtonFor_" + name; + deleteContainer.node().title = "Delete prefix and IRI"; + deleteButton.style("width", "10px"); + deleteButton.style("height", "20px"); + var deleteIcon = deleteButton.append("g"); + var deleteRect = deleteIcon.append("rect"); + var deletePath = deleteIcon.append("path"); + deleteIcon.node().id = "del_iconFor_" + name; + deletePath.node().id = "del_pathFor_" + name; + deleteRect.node().id = "del_rectFor_" + name; + + deleteIcon.node().selectorName = name; + deletePath.node().selectorName = name; + deleteRect.node().selectorName = name; + + + deletePath.style("stroke", "#f00"); + deleteRect.attr("width", "10px"); + deleteRect.attr("height", "14px"); + deleteRect.style("fill", "#18202A"); + deleteRect.attr("transform", "matrix(1,0,0,1,-3,4)"); + + + deletePath.attr("d", "M19 6.41L17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12z"); + deletePath.attr("transform", "matrix(0.45,0,0,0.45,0,5)"); + + deleteButton.selectAll("g").on("mouseover", function (){ + var selector = this; + var enable = true; + var f_deletePath = d3.select("#del_pathFor_" + selector.selectorName); + var f_deleteRect = d3.select("#del_rectFor_" + selector.selectorName); + + if ( enable === false ) { + f_deletePath.node().style = "stroke: #f00;"; + f_deleteRect.style("cursor", "auto"); + } else { + f_deletePath.node().style = "stroke: #ff972d;"; + f_deleteRect.style("cursor", "pointer"); + } + }); + deleteButton.selectAll("g").on("mouseout", function (){ + var selector = this; + var enable = false; + var f_deletePath = d3.select("#del_pathFor_" + selector.selectorName); + var f_deleteRect = d3.select("#del_rectFor_" + selector.selectorName); + + if ( enable === false ) { + f_deletePath.node().style = "stroke: #f00;"; + f_deleteRect.style("cursor", "auto"); + } else { + f_deletePath.node().style = "stroke: #ff972d;"; + f_deleteRect.style("cursor", "pointer"); + } + }); + + + editButton.on("click", enablePrefixEdit); + deleteButton.on("click", deletePrefixLine); + + // EXPERIMENTAL + + if ( name === "rdf" || + name === "rdfs" || + name === "xsd" || name === "dc" || + name === "owl" + ) { + // make them invis so the spacing does not change + IconContainer.classed("hidden", true); + deleteContainer.classed("hidden", true); + } + } + } + prefixModule.updatePrefixModel(); + } + + function deletePrefixLine(){ + if ( this.disabled === true ) return; + d3.select("#addPrefixButton").node().innerHTML = "Add Prefix"; + var selector = this.id.split("_")[1]; + d3.select("#prefixContainerFor_" + selector).remove(); + graph.options().removePrefix(selector); + prefix_editMode = false; // < 0 ) { + var basePref = graph.options().prefixList()[pr]; + if ( basePref === undefined ) { + console.log("ERROR __________________"); + graph.options().warningModule().showWarning("Invalid Element IRI", + "Could not resolve prefix '" + basePref + "'", + "Restoring previous IRI for Element" + element.iri(), 1, false); + d3.select("#element_iriEditor").node().value = element.iri(); + return; + + } + // check if url is not empty + + if ( name.length === 0 ) { + graph.options().warningModule().showWarning("Invalid Element IRI", + "Input IRI is EMPTY", + "Restoring previous IRI for Element" + element.iri(), 1, false); + console.log("NO INPUT PROVIDED"); + d3.select("#element_iriEditor").node().value = element.iri(); + return; + + } + url = basePref + name; + } + else { + url = base + name; + } + } else { + if ( url.length === 0 ) { + // + console.log("NO INPUT PROVIDED"); + d3.select("#element_iriEditor").node().value = element.iri(); + return; + } + // failed to identify anything useful + console.log("Tryig to use the input!"); + url = base + url; + } + } + return url; + } + + function changeIriForElement( element ){ + var url = getURLFROMPrefixedVersion(element); + var base = graph.options().getGeneralMetaObjectProperty("iri"); + var sanityCheckResult; + if ( elementTools.isNode(element) ) { + + sanityCheckResult = graph.checkIfIriClassAlreadyExist(url); + if ( sanityCheckResult === false ) { + element.iri(url); + } else { + // throw warnign + graph.options().warningModule().showWarning("Already seen this class", + "Input IRI: " + url + " for element: " + element.labelForCurrentLanguage() + " already been set", + "Restoring previous IRI for Element : " + element.iri(), 2, false, sanityCheckResult); + + editSidebar.updateSelectionInformation(element); + return; + + } + } + if ( elementTools.isProperty(element) === true ) { + sanityCheckResult = editSidebar.checkProperIriChange(element, url); + if ( sanityCheckResult !== false ) { + graph.options().warningModule().showWarning("Already seen this property", + "Input IRI: " + url + " for element: " + element.labelForCurrentLanguage() + " already been set", + "Restoring previous IRI for Element : " + element.iri(), 1, false, sanityCheckResult); + + editSidebar.updateSelectionInformation(element); + return; + } + } + + // if (element.existingPropertyIRI(url)===true){ + // console.log("I Have seen this Particular URL already "+url); + // graph.options().warningModule().showWarning("Already Seen This one ", + // "Input IRI For Element"+ element.labelForCurrentLanguage()+" already been set ", + // "Restoring previous IRI for Element"+element.iri(),1,false); + // d3.select("#element_iriEditor").node().value=graph.options().prefixModule().getPrefixRepresentationForFullURI(element.iri()); + // editSidebar.updateSelectionInformation(element); + // return; + // } + + element.iri(url); + if ( identifyExternalCharacteristicForElement(base, url) === true ) { + addAttribute(element, "external"); + // background color for external element; + element.backgroundColor("#36C"); + element.redrawElement(); + element.redrawLabelText(); + // handle visual selection + + } else { + removeAttribute(element, "external"); + // background color for external element; + element.backgroundColor(undefined); + element.redrawElement(); + element.redrawLabelText(); + + } + + if ( element.focused() ) { + graph.options().focuserModule().handle(element, true); // unfocus + graph.options().focuserModule().handle(element, true); // focus + } + // graph.options().focuserModule().handle(undefined); + + + d3.select("#element_iriEditor").node().value = prefixModule.getPrefixRepresentationForFullURI(url); + editSidebar.updateSelectionInformation(element); + } + + function validURL( str ){ + var urlregex = /^(https?|ftp):\/\/([a-zA-Z0-9.-]+(:[a-zA-Z0-9.&%$-]+)*@)*((25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9][0-9]?)(\.(25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9]?[0-9])){3}|([a-zA-Z0-9-]+\.)*[a-zA-Z0-9-]+\.(com|edu|gov|int|mil|net|org|biz|arpa|info|name|pro|aero|coop|museum|[a-zA-Z]{2}))(:[0-9]+)*(\/($|[a-zA-Z0-9.,?'\\+&%$#=~_-]+))*$/; + return urlregex.test(str); + } + + + function changeLabelForElement( element ){ + element.label(d3.select("#element_labelEditor").node().value); + element.redrawLabelText(); + } + + editSidebar.updateEditDeleteButtonIds = function ( oldPrefix, newPrefix ){ + d3.select("#prefixInputFor_" + oldPrefix).node().id = "prefixInputFor_" + newPrefix; + d3.select("#prefixURLFor_" + oldPrefix).node().id = "prefixURLFor_" + newPrefix; + d3.select("#deleteButtonFor_" + oldPrefix).node().id = "deleteButtonFor_" + newPrefix; + d3.select("#editButtonFor_" + oldPrefix).node().id = "editButtonFor_" + newPrefix; + + d3.select("#prefixContainerFor_" + oldPrefix).node().id = "prefixContainerFor_" + newPrefix; + }; + + editSidebar.checkForExistingURL = function ( url ){ + var i; + var allProps = graph.getUnfilteredData().properties; + for ( i = 0; i < allProps.length; i++ ) { + if ( allProps[i].iri() === url ) return true; + } + return false; + + }; + editSidebar.checkProperIriChange = function ( element, url ){ + console.log("Element changed Label"); + console.log("Testing URL " + url); + if ( element.type() === "rdfs:subClassOf" || element.type() === "owl:disjointWith" ) { + console.log("ignore this for now, already handled in the type and domain range changer"); + } else { + var i; + var allProps = graph.getUnfilteredData().properties; + for ( i = 0; i < allProps.length; i++ ) { + if ( allProps[i] === element ) continue; + if ( allProps[i].iri() === url ) return allProps[i]; + } + } + return false; + }; + + editSidebar.updateSelectionInformation = function ( element ){ + + if ( element === undefined ) { + // show hint; + d3.select("#selectedElementProperties").classed("hidden", true); + d3.select("#selectedElementPropertiesEmptyHint").classed("hidden", false); + selectedElementForCharacteristics = null; + editSidebar.updateElementWidth(); + } + else { + d3.select("#selectedElementProperties").classed("hidden", false); + d3.select("#selectedElementPropertiesEmptyHint").classed("hidden", true); + d3.select("#typeEditForm_datatype").classed("hidden", true); + + // set the element IRI, and labels + d3.select("#element_iriEditor").node().value = element.iri(); + d3.select("#element_labelEditor").node().value = element.labelForCurrentLanguage(); + d3.select("#element_iriEditor").node().title = element.iri(); + + d3.select("#element_iriEditor") + .on("change", function (){ + var elementIRI = element.iri(); + var prefixed = graph.options().prefixModule().getPrefixRepresentationForFullURI(elementIRI); + if ( prefixed === d3.select("#element_iriEditor").node().value ) { + console.log("Iri is identical, nothing has changed!"); + return; + } + + changeIriForElement(element); + }) + .on("keydown", function (){ + d3.event.stopPropagation(); + if ( d3.event.keyCode === 13 ) { + d3.event.preventDefault(); + console.log("IRI CHANGED Via ENTER pressed"); + changeIriForElement(element); + d3.select("#element_iriEditor").node().title = element.iri(); + } + }); + + var forceIRISync = defaultIriValue(element); + d3.select("#element_labelEditor") + .on("change", function (){ + var sanityCheckResult; + console.log("Element changed Label"); + var url = getURLFROMPrefixedVersion(element); + if ( element.iri() !== url ) { + if ( elementTools.isProperty(element) === true ) { + sanityCheckResult = editSidebar.checkProperIriChange(element, url); + if ( sanityCheckResult !== false ) { + graph.options().warningModule().showWarning("Already seen this property", + "Input IRI: " + url + " for element: " + element.labelForCurrentLanguage() + " already been set", + "Continuing with duplicate property!", 1, false, sanityCheckResult); + editSidebar.updateSelectionInformation(element); + return; + } + } + + if ( elementTools.isNode(element) === true ) { + sanityCheckResult = graph.checkIfIriClassAlreadyExist(url); + if ( sanityCheckResult !== false ) { + graph.options().warningModule().showWarning("Already seen this Class", + "Input IRI: " + url + " for element: " + element.labelForCurrentLanguage() + " already been set", + "Restoring previous IRI for Element : " + element.iri(), 2, false, sanityCheckResult); + + editSidebar.updateSelectionInformation(element); + return; + } + } + element.iri(url); + } + changeLabelForElement(element); + editSidebar.updateSelectionInformation(element); // prevents that it will be changed if node is still active + }) + .on("keydown", function (){ + d3.event.stopPropagation(); + if ( d3.event.keyCode === 13 ) { + d3.event.preventDefault(); + var sanityCheckResult; + console.log("Element changed Label"); + var url = getURLFROMPrefixedVersion(element); + if ( element.iri() !== url ) { + if ( elementTools.isProperty(element) === true ) { + sanityCheckResult = editSidebar.checkProperIriChange(element, url); + if ( sanityCheckResult !== false ) { + graph.options().warningModule().showWarning("Already seen this property", + "Input IRI: " + url + " for element: " + element.labelForCurrentLanguage() + " already been set", + "Continuing with duplicate property!", 1, false, sanityCheckResult); + + editSidebar.updateSelectionInformation(element); + return; + } + } + + if ( elementTools.isNode(element) === true ) { + sanityCheckResult = graph.checkIfIriClassAlreadyExist(url); + if ( sanityCheckResult !== false ) { + graph.options().warningModule().showWarning("Already seen this Class", + "Input IRI: " + url + " for element: " + element.labelForCurrentLanguage() + " already been set", + "Restoring previous IRI for Element : " + element.iri(), 2, false, sanityCheckResult); + + editSidebar.updateSelectionInformation(element); + return; + } + } + element.iri(url); + } + changeLabelForElement(element); + } + }) + .on("keyup", function (){ + if ( forceIRISync ) { + var labelName = d3.select("#element_labelEditor").node().value; + var resourceName = labelName.replaceAll(" ", "_"); + var syncedIRI = element.baseIri() + resourceName; + + //element.iri(syncedIRI); + d3.select("#element_iriEditor").node().title = element.iri(); + d3.select("#element_iriEditor").node().value = prefixModule.getPrefixRepresentationForFullURI(syncedIRI); + } + }); + // check if we are allowed to change IRI OR LABEL + d3.select("#element_iriEditor").node().disabled = false; + d3.select("#element_labelEditor").node().disabled = false; + + if ( element.type() === "rdfs:subClassOf" ) { + d3.select("#element_iriEditor").node().value = "http://www.w3.org/2000/01/rdf-schema#subClassOf"; + d3.select("#element_iriEditor").node().title = "http://www.w3.org/2000/01/rdf-schema#subClassOf"; + d3.select("#element_labelEditor").node().value = "Subclass of"; + d3.select("#element_iriEditor").node().disabled = true; + d3.select("#element_labelEditor").node().disabled = true; + } + if ( element.type() === "owl:Thing" ) { + d3.select("#element_iriEditor").node().value = "http://www.w3.org/2002/07/owl#Thing"; + d3.select("#element_iriEditor").node().title = "http://www.w3.org/2002/07/owl#Thing"; + d3.select("#element_labelEditor").node().value = "Thing"; + d3.select("#element_iriEditor").node().disabled = true; + d3.select("#element_labelEditor").node().disabled = true; + } + + if ( element.type() === "owl:disjointWith" ) { + d3.select("#element_iriEditor").node().value = "http://www.w3.org/2002/07/owl#disjointWith"; + d3.select("#element_iriEditor").node().title = "http://www.w3.org/2002/07/owl#disjointWith"; + d3.select("#element_iriEditor").node().disabled = true; + d3.select("#element_labelEditor").node().disabled = true; + } + + if ( element.type() === "rdfs:Literal" ) { + d3.select("#element_iriEditor").node().value = "http://www.w3.org/2000/01/rdf-schema#Literal"; + d3.select("#element_iriEditor").node().title = "http://www.w3.org/2000/01/rdf-schema#Literal"; + d3.select("#element_iriEditor").node().disabled = true; + d3.select("#element_labelEditor").node().disabled = true; + element.iri("http://www.w3.org/2000/01/rdf-schema#Literal"); + } + if ( element.type() === "rdfs:Datatype" ) { + var datatypeEditorSelection = d3.select("#typeEditor_datatype"); + d3.select("#typeEditForm_datatype").classed("hidden", false); + element.iri("http://www.w3.org/2000/01/rdf-schema#Datatype"); + d3.select("#element_iriEditor").node().value = "http://www.w3.org/2000/01/rdf-schema#Datatype"; + d3.select("#element_iriEditor").node().title = "http://www.w3.org/2000/01/rdf-schema#Datatype"; + d3.select("#element_iriEditor").node().disabled = true; + d3.select("#element_labelEditor").node().disabled = true; + + datatypeEditorSelection.node().value = element.dType(); + if ( datatypeEditorSelection.node().value === "undefined" ) { + d3.select("#element_iriEditor").node().disabled = true; // always prevent IRI modifications + d3.select("#element_labelEditor").node().disabled = false; + } + // reconnect the element + datatypeEditorSelection.on("change", function (){ + changeDatatypeType(element); + }); + } + + // add type selector + var typeEditorSelection = d3.select("#typeEditor").node(); + var htmlCollection = typeEditorSelection.children; + var numEntries = htmlCollection.length; + var i; + var elementPrototypes = getElementPrototypes(element); + for ( i = 0; i < numEntries; i++ ) + typeEditorSelection.removeChild(htmlCollection[0]); + + for ( i = 0; i < elementPrototypes.length; i++ ) { + var optA = document.createElement('option'); + optA.innerHTML = elementPrototypes[i]; + typeEditorSelection.appendChild(optA); + } + // set the proper value in the selection + typeEditorSelection.value = element.type(); + d3.select("#typeEditor").on("change", function (){ + elementTypeSelectionChanged(element); + }); + + + // add characteristics selection + var needChar = elementNeedsCharacteristics(element); + d3.select("#property_characteristics_Container").classed("hidden", !needChar); + if ( needChar === true ) { + addElementsCharacteristics(element); + } + var fullURI = d3.select("#element_iriEditor").node().value; + d3.select("#element_iriEditor").node().value = prefixModule.getPrefixRepresentationForFullURI(fullURI); + d3.select("#element_iriEditor").node().title = fullURI; + editSidebar.updateElementWidth(); + } + + }; + + editSidebar.updateGeneralOntologyInfo = function (){ + var preferredLanguage = graph && graph.language ? graph.language() : null; + + // get it from graph.options + var generalMetaObj = graph.options().getGeneralMetaObject(); + if ( generalMetaObj.hasOwnProperty("title") ) { + // title has language to it -.- + if ( typeof generalMetaObj.title === "object" ) { + d3.select("#titleEditor").node().value = languageTools.textInLanguage(generalMetaObj.title, preferredLanguage); + } else + d3.select("#titleEditor").node().value = generalMetaObj.title; + } + if ( generalMetaObj.hasOwnProperty("iri") ) d3.select("#iriEditor").node().value = generalMetaObj.iri; + if ( generalMetaObj.hasOwnProperty("version") ) d3.select("#versionEditor").node().value = generalMetaObj.version; + if ( generalMetaObj.hasOwnProperty("author") ) d3.select("#authorsEditor").node().value = generalMetaObj.author; + + + if ( generalMetaObj.hasOwnProperty("description") ) { + + if ( typeof generalMetaObj.description === "object" ) + d3.select("#descriptionEditor").node().value = + languageTools.textInLanguage(generalMetaObj.description, preferredLanguage); + else + d3.select("#descriptionEditor").node().value = generalMetaObj.description; + } + else + d3.select("#descriptionEditor").node().value = "No Description"; + }; + + editSidebar.updateElementWidth = function (){ + var height = window.innerHeight - 40; + var lsb_offset = d3.select("#logo").node().getBoundingClientRect().height + 5; + var lsb_height = height - lsb_offset; + d3.select("#containerForLeftSideBar").style("top", lsb_offset + "px"); + d3.select("#leftSideBarCollapseButton").style("top", lsb_offset + "px"); + d3.select("#containerForLeftSideBar").style("height", lsb_height + "px"); + + var div_width = d3.select("#generalDetailsEdit").node().getBoundingClientRect().width; + div_width += 10; + + var title_labelWidth = d3.select("#titleEditor-label").node().getBoundingClientRect().width + 20; + var iri_labelWidth = d3.select("#iriEditor-label").node().getBoundingClientRect().width + 20; + var version_labelWidth = d3.select("#versionEditor-label").node().getBoundingClientRect().width + 20; + var author_labelWidth = d3.select("#authorsEditor-label").node().getBoundingClientRect().width + 20; + //find max width; + var maxW = 0; + maxW = Math.max(maxW, title_labelWidth); + maxW = Math.max(maxW, iri_labelWidth); + maxW = Math.max(maxW, version_labelWidth); + maxW = Math.max(maxW, author_labelWidth); + + var meta_inputWidth = div_width - maxW - 10; + + d3.select("#titleEditor").style("width", meta_inputWidth + "px"); + d3.select("#iriEditor").style("width", meta_inputWidth + "px"); + d3.select("#versionEditor").style("width", meta_inputWidth + "px"); + d3.select("#authorsEditor").style("width", meta_inputWidth + "px"); + + + var elementIri_width = d3.select("#element_iriEditor-label").node().getBoundingClientRect().width + 20; + var elementLabel_width = d3.select("#element_labelEditor-label").node().getBoundingClientRect().width + 20; + var elementType_width = d3.select("#typeEditor-label").node().getBoundingClientRect().width + 20; + var elementDType_width = d3.select("#typeEditor_datatype-label").node().getBoundingClientRect().width + 20; + + maxW = 0; + maxW = Math.max(maxW, elementIri_width); + maxW = Math.max(maxW, elementLabel_width); + maxW = Math.max(maxW, elementType_width); + maxW = Math.max(maxW, elementDType_width); + var selectedElement_inputWidth = div_width - maxW - 10; + + d3.select("#element_iriEditor").style("width", selectedElement_inputWidth + "px"); + d3.select("#element_labelEditor").style("width", selectedElement_inputWidth + "px"); + d3.select("#typeEditor").style("width", selectedElement_inputWidth + 4 + "px"); + d3.select("#typeEditor_datatype").style("width", selectedElement_inputWidth + 4 + "px"); + + // update prefix Element width; + var containerWidth = d3.select("#containerForPrefixURL").node().getBoundingClientRect().width; + if ( containerWidth !== 0 ) { + var inputs = d3.selectAll(".prefixInput"); + if ( inputs.node() ) { + var prefixWidth = d3.selectAll(".prefixInput").node().getBoundingClientRect().width; + d3.selectAll(".prefixURL").style("width", containerWidth - prefixWidth - 45 + "px"); + } + } + }; + + function addElementsCharacteristics( element ){ + // save selected element for checkbox handler + selectedElementForCharacteristics = element; + var i; + // KILL old elements + var charSelectionNode = d3.select("#property_characteristics_Selection"); + var htmlCollection = charSelectionNode.node().children; + if ( htmlCollection ) { + var numEntries = htmlCollection.length; + for ( var q = 0; q < numEntries; q++ ) { + charSelectionNode.node().removeChild(htmlCollection[0]); + } + } + // datatypes kind of ignored by the elementsNeedCharacteristics function + // so we need to check if we are a node or not + if ( element.attributes().indexOf("external") > -1 ) { + // add external span to the div; + var externalCharSpan = charSelectionNode.append("span"); + externalCharSpan.classed("spanForCharSelection", true); + externalCharSpan.node().innerHTML = "external"; + } + var filterContainer, + filterCheckbox; + if ( elementTools.isNode(element) === true ) { + // add the deprecated characteristic; + var arrayOfNodeChars = ["deprecated"]; + for ( i = 0; i < arrayOfNodeChars.length; i++ ) { + filterContainer = charSelectionNode + .append("div") + .classed("checkboxContainer", true) + .style("padding-top", "2px"); + + filterCheckbox = filterContainer.append("input") + .classed("filterCheckbox", true) + .attr("id", "CharacteristicsCheckbox" + i) + .attr("type", "checkbox") + .attr("characteristics", arrayOfNodeChars[i]) + .property("checked", getPresentAttribute(element, arrayOfNodeChars[i])); + // + filterContainer.append("label") + .attr("for", "CharacteristicsCheckbox" + i) + .text(arrayOfNodeChars[i]); + + filterCheckbox.on("click", handleCheckBoxClick); + + } + } + + else { + // add the deprecated characteristic; + var arrayOfPropertyChars = ["deprecated", "inverse functional", "functional", "transitive"]; + if ( elementTools.isDatatypeProperty(element) === true ) { + arrayOfPropertyChars = ["deprecated", "functional"]; + } + for ( i = 0; i < arrayOfPropertyChars.length; i++ ) { + filterContainer = charSelectionNode + .append("div") + .classed("checkboxContainer", true) + .style("padding-top", "2px"); + + filterCheckbox = filterContainer.append("input") + .classed("filterCheckbox", true) + .attr("id", "CharacteristicsCheckbox" + i) + .attr("type", "checkbox") + .attr("characteristics", arrayOfPropertyChars[i]) + .property("checked", getPresentAttribute(element, arrayOfPropertyChars[i])); + // + filterContainer.append("label") + .attr("for", "CharacteristicsCheckbox" + i) + .text(arrayOfPropertyChars[i]); + + filterCheckbox.on("click", handleCheckBoxClick); + + } + } + + + } + + function getPresentAttribute( selectedElement, element ){ + return (selectedElement.attributes().indexOf(element) >= 0); + } + + function handleCheckBoxClick(){ + var checked = this.checked; + var char = this.getAttribute("characteristics"); + if ( checked === true ) { + addAttribute(selectedElementForCharacteristics, char); + } else { + removeAttribute(selectedElementForCharacteristics, char); + } + // graph.executeColorExternalsModule(); + selectedElementForCharacteristics.redrawElement(); + // workaround to have the node still be focused as rendering element + selectedElementForCharacteristics.focused(false); + selectedElementForCharacteristics.toggleFocus(); + + } + + + function addAttribute( selectedElement, char ){ + if ( selectedElement.attributes().indexOf(char) === -1 ) { + // not found add it + var attr = selectedElement.attributes(); + attr.push(char); + selectedElement.attributes(attr); + }// indications string update; + if ( selectedElement.indications().indexOf(char) === -1 ) { + var indications = selectedElement.indications(); + indications.push(char); + selectedElement.indications(indications); + } + // add visual attributes + var visAttr; + if ( selectedElement.visualAttributes().indexOf(char) === -1 ) { + visAttr = selectedElement.visualAttributes(); + visAttr.push(char); + selectedElement.visualAttributes(visAttr); + } + if ( getPresentAttribute(selectedElement, "external") && getPresentAttribute(selectedElement, "deprecated") ) { + visAttr = selectedElement.visualAttributes(); + var visInd = visAttr.indexOf("external"); + if ( visInd > -1 ) { + visAttr.splice(visInd, 1); + } + selectedElement.visualAttributes(visAttr); + } + + } + + function removeAttribute( selectedElement, element ){ + var attr = selectedElement.attributes(); + var indications = selectedElement.indications(); + var visAttr = selectedElement.visualAttributes(); + var attrInd = attr.indexOf(element); + if ( attrInd >= 0 ) { + attr.splice(attrInd, 1); + } + var indInd = indications.indexOf(element); + if ( indInd > -1 ) { + indications.splice(indInd, 1); + } + var visInd = visAttr.indexOf(element); + if ( visInd > -1 ) { + visAttr.splice(visInd, 1); + } + selectedElement.attributes(attr); + selectedElement.indications(indications); + selectedElement.visualAttributes(visAttr); + if ( element === "deprecated" ) { + // set its to its original Style + //typeBaseThign + // todo : fix all different types + if ( selectedElement.type() === "owl:Class" ) selectedElement.styleClass("class"); + if ( selectedElement.type() === "owl:DatatypeProperty" ) selectedElement.styleClass("datatypeproperty"); + if ( selectedElement.type() === "owl:ObjectProperty" ) selectedElement.styleClass("objectproperty"); + if ( selectedElement.type() === "owl:disjointWith" ) selectedElement.styleClass("disjointwith"); + } + } + + + function elementNeedsCharacteristics( element ){ + //TODO: Add more types + if ( element.type() === "owl:Thing" || + element.type() === "rdfs:subClassOf" || + element.type() === "rdfs:Literal" || + element.type() === "rdfs:Datatype" || + element.type() === "rdfs:disjointWith" ) + return false; + + // if (element.attributes().indexOf("external")|| + // element.attributes().indexOf("deprecated")) + // return true; + return true; + + } + + function elementTypeSelectionChanged( element ){ + if ( elementTools.isNode(element) ) { + if ( graph.changeNodeType(element) === false ) { + //restore old value + + if ( elementTools.isDatatype(element) === true ) { + + } + editSidebar.updateSelectionInformation(element); + } + } + + if ( elementTools.isProperty(element) ) { + if ( graph.changePropertyType(element) === false ) { + //restore old value + editSidebar.updateSelectionInformation(element); + + } + } + + } + + function getElementPrototypes( selectedElement ){ + var availiblePrototypes = []; + // TODO the text should be also complied with the prefixes loaded into the ontology + if ( elementTools.isProperty(selectedElement) ) { + if ( selectedElement.type() === "owl:DatatypeProperty" ) + availiblePrototypes.push("owl:DatatypeProperty"); + else { + availiblePrototypes.push("owl:ObjectProperty"); + // handling loops ! + if ( selectedElement.domain() !== selectedElement.range() ) { + availiblePrototypes.push("rdfs:subClassOf"); + } + availiblePrototypes.push("owl:disjointWith"); + availiblePrototypes.push("owl:allValuesFrom"); + availiblePrototypes.push("owl:someValuesFrom"); + } + return availiblePrototypes; + } + if ( selectedElement.renderType() === "rect" ) { + availiblePrototypes.push("rdfs:Literal"); + availiblePrototypes.push("rdfs:Datatype"); + } else { + availiblePrototypes.push("owl:Class"); + availiblePrototypes.push("owl:Thing"); + // TODO: ADD MORE TYPES + // availiblePrototypes.push("owl:complementOf"); + // availiblePrototypes.push("owl:disjointUnionOf"); + } + return availiblePrototypes; + } + + + function setupCollapsing(){ + // TODO : Decision , for now I want to have the control over the collapse expand operation of the + // TODO : elements, otherwise the old approach will also randomly collapse other containers + + // adapted version of this example: http://www.normansblog.de/simple-jquery-accordion/ + function collapseContainers( containers ){ + containers.classed("hidden", true); + } + + function expandContainers( containers ){ + containers.classed("hidden", false); + } + + var triggers = d3.selectAll(".accordion-trigger"); + + // Collapse all inactive triggers on startup + // collapseContainers(d3.selectAll(".accordion-trigger:not(.accordion-trigger-active) + div")); + + triggers.on("click", function (){ + var selectedTrigger = d3.select(this); + if ( selectedTrigger.classed("accordion-trigger-active") ) { + // Collapse the active (which is also the selected) trigger + collapseContainers(d3.select(selectedTrigger.node().nextElementSibling)); + selectedTrigger.classed("accordion-trigger-active", false); + } else { + // Collapse the other trigger ... + // collapseContainers(d3.selectAll(".accordion-trigger-active + div")); + + // ... and expand the selected one + expandContainers(d3.select(selectedTrigger.node().nextElementSibling)); + selectedTrigger.classed("accordion-trigger-active", true); + } + editSidebar.updateElementWidth(); + }); + } + + return editSidebar; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 341: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( graph ){ + var configMenu = {}, + checkboxes = []; + + + configMenu.setup = function (){ + var menuEntry = d3.select("#m_modes"); + menuEntry.on("mouseover", function (){ + var searchMenu = graph.options().searchMenu(); + searchMenu.hideSearchEntries(); + }); + + addCheckBox("showZoomSlider", "Zoom controls", "#zoomSliderOption", graph.options().zoomSlider().showSlider, 0); + addLabelWidthSlider("#maxLabelWidthSliderOption", "maxLabelWidth", "Max label width", graph.options().maxLabelWidth); + }; + + + function addLabelWidthSlider( selector, identifier, label, onChangeFunction ){ + var sliderContainer, + sliderValueLabel; + + sliderContainer = d3.select(selector) + .append("div") + .classed("distanceSliderContainer", true); + + var slider = sliderContainer.append("input") + .attr("id", identifier + "Slider") + .attr("type", "range") + .attr("min", 20) + .attr("max", 600) + .attr("value", onChangeFunction()) + .attr("step", 10); + sliderContainer.append("label") + .classed("description", true) + .attr("for", identifier + "Slider") + .attr("id", identifier + "DescriptionLabel") + .text(label); + sliderValueLabel = sliderContainer.append("label") + .classed("value", true) + .attr("for", identifier + "Slider") + .attr("id", identifier + "valueLabel") + .text(onChangeFunction()); + + slider.on("input", function (){ + var value = slider.property("value"); + onChangeFunction(value); + sliderValueLabel.text(value); + if ( graph.options().dynamicLabelWidth() === true ) + graph.animateDynamicLabelWidth(); + }); + + // add wheel event to the slider + slider.on("wheel", function (){ + if ( slider.node().disabled === true ) return; + var wheelEvent = d3.event; + var offset; + if ( wheelEvent.deltaY < 0 ) offset = 10; + if ( wheelEvent.deltaY > 0 ) offset = -10; + var oldVal = parseInt(slider.property("value")); + var newSliderValue = oldVal + offset; + if ( newSliderValue !== oldVal ) { + slider.property("value", newSliderValue); + onChangeFunction(newSliderValue); + slider.on("input")(); // << set text and update the graphStyles + } + d3.event.preventDefault(); + }); + } + + function addCheckBox( identifier, modeName, selector, onChangeFunc, updateLvl ){ + var configOptionContainer = d3.select(selector) + .append("div") + .classed("checkboxContainer", true); + var configCheckbox = configOptionContainer.append("input") + .classed("moduleCheckbox", true) + .attr("id", identifier + "ConfigCheckbox") + .attr("type", "checkbox") + .property("checked", onChangeFunc()); + + + configCheckbox.on("click", function ( silent ){ + var isEnabled = configCheckbox.property("checked"); + onChangeFunc(isEnabled); + if ( silent !== true ) { + // updating graph when silent is false or the parameter is not given. + if ( updateLvl === 1 ) { + graph.lazyRefresh(); + //graph.redrawWithoutForce + } + if ( updateLvl === 2 ) { + graph.update(); + } + + if ( updateLvl === 3 ) { + graph.updateDraggerElements(); + } + } + + }); + checkboxes.push(configCheckbox); + configOptionContainer.append("label") + .attr("for", identifier + "ConfigCheckbox") + .text(modeName); + } + + configMenu.setCheckBoxValue = function ( identifier, value ){ + for ( var i = 0; i < checkboxes.length; i++ ) { + var cbdId = checkboxes[i].attr("id"); + if ( cbdId === identifier ) { + checkboxes[i].property("checked", value); + break; + } + } + }; + + configMenu.getCheckBoxValue = function ( id ){ + for ( var i = 0; i < checkboxes.length; i++ ) { + var cbdId = checkboxes[i].attr("id"); + if ( cbdId === id ) { + return checkboxes[i].property("checked"); + } + } + }; + + configMenu.updateSettings = function (){ + var silent = true; + checkboxes.forEach(function ( checkbox ){ + checkbox.on("click")(silent); + }); + }; + + return configMenu; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 342: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( graph ){ + /** some constants **/ + var PREDEFINED = 0, + FILE_UPLOAD = 1, + JSON_URL = 2, + IRI_URL = 3; + + var PROGRESS_BAR_ERROR = 0, + PROGRESS_BAR_BUSY = 1, + PROGRESS_BAR_PERCENT = 2, + progressBarMode = 1; + + var loadingWasSuccessFul = false; + var missingImportsWarning = false; + var showLoadingDetails = false; + var visibilityStatus = true; + + var DEFAULT_JSON_NAME = "ontology"; // This file is loaded by default + var conversion_sessionId; + + /** variable defs **/ + var loadingModule = {}, + menuContainer = d3.select("#loading-info"), + loadingInfoContainer = d3.select("#loadingInfo-container"), + detailsButton = d3.select("#show-loadingInfo-button"), + closeButton = d3.select("#loadingIndicator_closeButton"), + ontologyMenu, + ontologyIdentifierFromURL; + + /** functon defs **/ + loadingModule.checkForScreenSize = function (){ + // checks for window size and adjusts the loading indicator + var w = graph.options().width(), + h = graph.options().height(); + + if ( w < 270 ) { + d3.select("#loading-info").classed("hidden", true); + } else { + // check if it should be visible + if ( visibilityStatus === true ) { + d3.select("#loading-info").classed("hidden", false); + } else { + d3.select("#loading-info").classed("hidden", true); + } + } + if ( h < 150 ) { + d3.select("#loadingInfo_msgBox").classed("hidden", true); + } else { + d3.select("#loadingInfo_msgBox").classed("hidden", false); + } + if ( h < 80 ) { + d3.select("#progressBarContext").classed("hidden", true); + d3.select("#layoutLoadingProgressBarContainer").style("height", "20px"); + } else { + d3.select("#progressBarContext").classed("hidden", false); + d3.select("#layoutLoadingProgressBarContainer").style("height", "50px"); + } + }; + + loadingModule.getMessageVisibilityStatus = function (){ + return visibilityStatus; + }; + + loadingModule.getProgressBarMode = function (){ + return progressBarMode; + }; + + loadingModule.successfullyLoadedOntology = function (){ + return loadingWasSuccessFul; + }; + + loadingModule.missingImportsWarning = function (){ + return missingImportsWarning; + }; + + loadingModule.setOntologyMenu = function ( m ){ + ontologyMenu = m; + }; + + loadingModule.showErrorDetailsMessage = function (){ + loadingModule.showLoadingIndicator(); + loadingModule.expandDetails(); + d3.select("#loadingIndicator_closeButton").classed("hidden", true); + loadingModule.scrollDownDetails(); + }; + + loadingModule.showWarningDetailsMessage = function (){ + d3.select("#currentLoadingStep").style("color", "#ff0"); + loadingModule.showLoadingIndicator(); + loadingModule.expandDetails(); + d3.select("#loadingIndicator_closeButton").classed("hidden", false); + loadingModule.scrollDownDetails(); + }; + + loadingModule.scrollDownDetails = function (){ + var scrollingElement = d3.select("#loadingInfo-container").node(); + scrollingElement.scrollTop = scrollingElement.scrollHeight; + }; + + loadingModule.hideLoadingIndicator = function (){ + d3.select("#loading-info").classed("hidden", true); + visibilityStatus = false; + }; + + loadingModule.showLoadingIndicator = function (){ + d3.select("#loading-info").classed("hidden", false); + visibilityStatus = true; + + }; + + /** -- SETUP -- **/ + loadingModule.setup = function (){ + // create connections for close and details button; + loadingInfoContainer.classed("hidden", !showLoadingDetails); + detailsButton.on("click", function (){ + showLoadingDetails = !showLoadingDetails; + loadingInfoContainer.classed("hidden", !showLoadingDetails); + detailsButton.classed("accordion-trigger-active", showLoadingDetails); + }); + + closeButton.on("click", function (){ + menuContainer.classed("hidden", true); + }); + loadingModule.setBusyMode(); + }; + + loadingModule.updateSize = function (){ + showLoadingDetails = !(loadingInfoContainer.classed("hidden")); + loadingInfoContainer.classed("hidden", !showLoadingDetails); + detailsButton.classed("accordion-trigger-active", showLoadingDetails); + }; + + loadingModule.getDetailsState = function (){ + return showLoadingDetails; + }; + + loadingModule.expandDetails = function (){ + showLoadingDetails = true; + loadingInfoContainer.classed("hidden", !showLoadingDetails); + detailsButton.classed("accordion-trigger-active", showLoadingDetails); + }; + + loadingModule.collapseDetails = function (){ + showLoadingDetails = false; + loadingInfoContainer.classed("hidden", !showLoadingDetails); + detailsButton.classed("accordion-trigger-active", showLoadingDetails); + }; + + loadingModule.setBusyMode = function (){ + d3.select("#currentLoadingStep").style("color", "#fff"); + d3.select("#progressBarValue").node().innherHTML = ""; + d3.select("#progressBarValue").style("width", "20%"); + d3.select("#progressBarValue").classed("busyProgressBar", true); + progressBarMode = PROGRESS_BAR_BUSY; + }; + + loadingModule.setSuccessful = function (){ + d3.select("#currentLoadingStep").style("color", "#0f0"); + }; + + loadingModule.setErrorMode = function (){ + d3.select("#currentLoadingStep").style("color", "#f00"); + d3.select("#progressBarValue").style("width", "0%"); + d3.select("#progressBarValue").classed("busyProgressBar", false); + d3.select("#progressBarValue").node().innherHTML = ""; + progressBarMode = PROGRESS_BAR_ERROR; + }; + + loadingModule.setPercentMode = function (){ + d3.select("#currentLoadingStep").style("color", "#fff"); + d3.select("#progressBarValue").classed("busyProgressBar", false); + d3.select("#progressBarValue").node().innherHTML = "0%"; + d3.select("#progressBarValue").style("width", "0%"); + progressBarMode = PROGRESS_BAR_PERCENT; + }; + + loadingModule.setPercentValue = function ( val ){ + d3.select("#progressBarValue").node().innherHTML = val; + }; + + loadingModule.emptyGraphContentError = function (){ + graph.clearGraphData(); + ontologyMenu.append_message_toLastBulletPoint("failed"); + ontologyMenu.append_message_toLastBulletPoint("
    Error: Received empty graph"); + loadingWasSuccessFul = false; + graph.handleOnLoadingError(); + loadingModule.setErrorMode(); + }; + + loadingModule.isThreadCanceled = function (){ + + }; + + loadingModule.initializeLoader = function ( storeCache ){ + if ( storeCache === true && graph.getCachedJsonObj() !== null ) { + // save cached ontology; + var cachedContent = JSON.stringify(graph.getCachedJsonObj()); + var cachedName = ontologyIdentifierFromURL; + ontologyMenu.setCachedOntology(cachedName, cachedContent); + } + conversion_sessionId = -10000; + ontologyMenu.setConversionID(conversion_sessionId); + ontologyMenu.stopLoadingTimer(); + graph.clearGraphData(); + loadingModule.setBusyMode(); + loadingModule.showLoadingIndicator(); + loadingModule.collapseDetails(); + missingImportsWarning = false; + d3.select("#loadingIndicator_closeButton").classed("hidden", true); + ontologyMenu.clearDetailInformation(); + }; + + /** ------------------ URL Interpreter -------------- **/ + loadingModule.parseUrlAndLoadOntology = function ( storeCache ){ + var autoStore = true; + if ( storeCache === false ) { + autoStore = false; + } + + graph.clearAllGraphData(); + loadingModule.initializeLoader(autoStore); + var urlString = String(location); + var parameterArray = identifyParameter(urlString); + ontologyIdentifierFromURL = DEFAULT_JSON_NAME; + loadGraphOptions(parameterArray); // identifies and loads configuration values + var loadingMethod = identifyOntologyLoadingMethod(ontologyIdentifierFromURL); + d3.select("#progressBarValue").node().innerHTML = " "; + switch ( loadingMethod ) { + case 0: + loadingModule.from_presetOntology(ontologyIdentifierFromURL); + break; + case 1: + loadingModule.from_FileUpload(ontologyIdentifierFromURL); + break; + case 2: + loadingModule.from_JSON_URL(ontologyIdentifierFromURL); + break; + case 3: + loadingModule.from_IRI_URL(ontologyIdentifierFromURL); + break; + default: + console.log("Could not identify loading method , or not IMPLEMENTED YET"); + } + }; + + /** ------------------- LOADING --------------------- **/ + // the loading module splits into 3 branches + // 1] PresetOntology Loading + // 2] File Upload + // 3] Load From URL / IRI + + loadingModule.from_JSON_URL = function ( fileName ){ + var filename = decodeURIComponent(fileName.slice("url=".length)); + ontologyIdentifierFromURL = filename; + + var ontologyContent = ""; + if ( ontologyMenu.cachedOntology(filename) ) { + ontologyMenu.append_bulletPoint("Loading already cached ontology: " + filename); + ontologyContent = ontologyMenu.cachedOntology(filename); + loadingWasSuccessFul = true; // cached Ontology should be true; + parseOntologyContent(ontologyContent); + + } else { + // involve the o2v conveter; + ontologyMenu.append_message("Retrieving ontology from JSON URL " + filename); + requestServerTimeStampForJSON_URL(ontologyMenu.callbackLoad_JSON_FromURL, ["read?json=" + filename, filename]); + } + }; + + function requestServerTimeStampForJSON_URL( callback, parameter ){ + d3.xhr("serverTimeStamp", "application/text", function ( error, request ){ + if ( error ) { + // could not get server timestamp -> no connection to owl2vowl + ontologyMenu.append_bulletPoint("Could not establish connection to OWL2VOWL service"); + fallbackForJSON_URL(callback, parameter); + } else { + conversion_sessionId = request.responseText; + ontologyMenu.setConversionID(conversion_sessionId); + parameter.push(conversion_sessionId); + callback(parameter); + } + }); + + } + + loadingModule.requestServerTimeStampForDirectInput = function ( callback, text ){ + d3.xhr("serverTimeStamp", "application/text", function ( error, request ){ + if ( error ) { + // could not get server timestamp -> no connection to owl2vowl + ontologyMenu.append_bulletPoint("Could not establish connection to OWL2VOWL service"); + loadingModule.setErrorMode(); + ontologyMenu.append_message_toLastBulletPoint("
    Could not connect to OWL2VOWL service "); + loadingModule.showErrorDetailsMessage(); + d3.select("#progressBarValue").style("width", "0%"); + d3.select("#progressBarValue").classed("busyProgressBar", false); + d3.select("#progressBarValue").text("0%"); + + } else { + conversion_sessionId = request.responseText; + ontologyMenu.setConversionID(conversion_sessionId); + callback(text, ["conversionID" + conversion_sessionId, conversion_sessionId]); + } + }); + }; + + loadingModule.from_IRI_URL = function ( fileName ){ + // owl2vowl converters the given ontology url and returns json file; + var filename = decodeURIComponent(fileName.slice("iri=".length)); + ontologyIdentifierFromURL = filename; + + var ontologyContent = ""; + if ( ontologyMenu.cachedOntology(filename) ) { + ontologyMenu.append_bulletPoint("Loading already cached ontology: " + filename); + ontologyContent = ontologyMenu.cachedOntology(filename); + loadingWasSuccessFul = true; // cached Ontology should be true; + parseOntologyContent(ontologyContent); + } else { + // involve the o2v conveter; + var encoded = encodeURIComponent(filename); + ontologyMenu.append_bulletPoint("Retrieving ontology from IRI: " + filename); + requestServerTimeStampForIRI_Converte(ontologyMenu.callbackLoad_Ontology_FromIRI, ["convert?iri=" + encoded, filename]); + } + }; + + loadingModule.fromFileDrop = function ( fileName, file ){ + d3.select("#progressBarValue").node().innerHTML = " "; + loadingModule.initializeLoader(false); + + ontologyMenu.append_bulletPoint("Retrieving ontology from dropped file: " + fileName); + var ontologyContent = ""; + + // two options here + //1] Direct Json Upload + if ( fileName.match(/\.json$/) ) { + ontologyMenu.setConversionID(-10000); + var reader = new FileReader(); + reader.readAsText(file); + reader.onload = function (){ + ontologyContent = reader.result; + ontologyIdentifierFromURL = fileName; + parseOntologyContent(ontologyContent); + }; + } else { + //2] File Upload to OWL2VOWL Converter + // 1) check if we can get a timeStamp; + var parameterArray = [file, fileName]; + requestServerTimeStamp(ontologyMenu.callbackLoadFromOntology, parameterArray); + } + }; + + + loadingModule.from_FileUpload = function ( fileName ){ + loadingModule.setBusyMode(); + var filename = decodeURIComponent(fileName.slice("file=".length)); + ontologyIdentifierFromURL = filename; + var ontologyContent = ""; + if ( ontologyMenu.cachedOntology(filename) ) { + ontologyMenu.append_bulletPoint("Loading already cached ontology: " + filename); + ontologyContent = ontologyMenu.cachedOntology(filename); + loadingWasSuccessFul = true; // cached Ontology should be true; + parseOntologyContent(ontologyContent); + + } else { + // d3.select("#currentLoadingStep").node().innerHTML="Loading ontology from file "+ filename; + ontologyMenu.append_bulletPoint("Retrieving ontology from file: " + filename); + // get the file + var selectedFile = d3.select("#file-converter-input").property("files")[0]; + // No selection -> this was triggered by the iri. Unequal names -> reuploading another file + if ( !selectedFile || (filename && (filename !== selectedFile.name)) ) { + ontologyMenu.append_message_toLastBulletPoint("
    No cached version of \"" + filename + "\" was found.
    Please reupload the file."); + loadingModule.setErrorMode(); + d3.select("#progressBarValue").classed("busyProgressBar", false); + graph.handleOnLoadingError(); + return; + } else { + filename = selectedFile.name; + } + + + // two options here + //1] Direct Json Upload + if ( filename.match(/\.json$/) ) { + ontologyMenu.setConversionID(-10000); + var reader = new FileReader(); + reader.readAsText(selectedFile); + reader.onload = function (){ + ontologyContent = reader.result; + ontologyIdentifierFromURL = filename; + parseOntologyContent(ontologyContent); + }; + } else { + //2] File Upload to OWL2VOWL Converter + // 1) check if we can get a timeStamp; + var parameterArray = [selectedFile, filename]; + requestServerTimeStamp(ontologyMenu.callbackLoadFromOntology, parameterArray); + } + } + }; + + function fallbackForJSON_URL( callback, parameter ){ + ontologyMenu.append_message_toLastBulletPoint("
    Trying to convert with other communication protocol."); + callback(parameter); + + } + + function fallbackConversion( parameter ){ + ontologyMenu.append_message_toLastBulletPoint("
    Trying to convert with other communication protocol."); + var file = parameter[0]; + var name = parameter[1]; + var formData = new FormData(); + formData.append("ontology", file); + + var xhr = new XMLHttpRequest(); + xhr.open("POST", "convert", true); + var ontologyContent = ""; + xhr.onload = function (){ + if ( xhr.status === 200 ) { + ontologyContent = xhr.responseText; + ontologyMenu.setCachedOntology(name, ontologyContent); + ontologyIdentifierFromURL = name; + missingImportsWarning = true; // using this variable for warnings + ontologyMenu.append_message_toLastBulletPoint("
    Success, but you are using a deprecated OWL2VOWL service!"); + parseOntologyContent(ontologyContent); + } + }; + + // check what this thing is doing; + xhr.onreadystatechange = function (){ + if ( xhr.readyState === 4 && xhr.status === 0 ) { + ontologyMenu.append_message_toLastBulletPoint("
    Old protocol also failed to establish connection to OWL2VOWL service!"); + loadingModule.setErrorMode(); + ontologyMenu.append_bulletPoint("Failed to load ontology"); + ontologyMenu.append_message_toLastBulletPoint("
    Could not connect to OWL2VOWL service "); + loadingModule.showErrorDetailsMessage(); + } + }; + xhr.send(formData); + } + + function requestServerTimeStampForIRI_Converte( callback, parameterArray ){ + d3.xhr("serverTimeStamp", "application/text", function ( error, request ){ + loadingModule.setBusyMode(); + if ( error ) { + // could not get server timestamp -> no connection to owl2vowl + ontologyMenu.append_bulletPoint("Could not establish connection to OWL2VOWL service"); + loadingModule.setErrorMode(); + ontologyMenu.append_bulletPoint("Failed to load ontology"); + ontologyMenu.append_message_toLastBulletPoint("
    Could not connect to OWL2VOWL service "); + loadingModule.showErrorDetailsMessage(); + } else { + conversion_sessionId = request.responseText; + ontologyMenu.setConversionID(conversion_sessionId); + // update paramater for new communication paradigm + parameterArray[0] = parameterArray[0] + "&sessionId=" + conversion_sessionId; + parameterArray.push(conversion_sessionId); + callback(parameterArray); + } + }); + } + + function requestServerTimeStamp( callback, parameterArray ){ + d3.xhr("serverTimeStamp", "application/text", function ( error, request ){ + if ( error ) { + // could not get server timestamp -> no connection to owl2vowl + ontologyMenu.append_bulletPoint("Could not establish connection to OWL2VOWL service"); + fallbackConversion(parameterArray); // tries o2v version0.3.4 communication + } else { + conversion_sessionId = request.responseText; + ontologyMenu.setConversionID(conversion_sessionId); + console.log("Request Session ID:" + conversion_sessionId); + callback(parameterArray[0], parameterArray[1], conversion_sessionId); + } + }); + } + + loadingModule.directInput = function ( text ){ + ontologyMenu.clearDetailInformation(); + parseOntologyContent(text); + }; + + loadingModule.loadFromOWL2VOWL = function ( ontoContent, filename ){ + loadingWasSuccessFul = false; + + var old = d3.select("#bulletPoint_container").node().innerHTML; + if ( old.indexOf("(with warnings)") !== -1 ) { + missingImportsWarning = true; + } + + if ( ontologyMenu.cachedOntology(ontoContent) ) { + ontologyMenu.append_bulletPoint("Loading already cached ontology: " + filename); + parseOntologyContent(ontoContent); + } else { // set parse the ontology content; + parseOntologyContent(ontoContent); + } + }; + + loadingModule.from_presetOntology = function ( selectedOntology ){ + ontologyMenu.append_bulletPoint("Retrieving ontology: " + selectedOntology); + loadPresetOntology(selectedOntology); + }; + + function loadPresetOntology( ontology ){ + // check if already cached in ontology menu? + var f2r; + var loadingNewOntologyForEditor=false; + if ( ontology.indexOf("new_ontology") !== -1 ) { + loadingModule.hideLoadingIndicator(); + graph.showEditorHintIfNeeded(); + f2r = "./data/new_ontology.json"; + loadingNewOntologyForEditor=true; + } + + loadingWasSuccessFul = false; + var ontologyContent = ""; + if ( ontologyMenu.cachedOntology(ontology) ) { + ontologyMenu.append_bulletPoint("Loading already cached ontology: " + ontology); + ontologyContent = ontologyMenu.cachedOntology(ontology); + loadingWasSuccessFul = true; // cached Ontology should be true; + loadingModule.showLoadingIndicator(); + parseOntologyContent(ontologyContent); + + } else { + // read the file name + + var fileToRead = "./data/" + ontology + ".json"; + if ( f2r ) { + fileToRead = f2r; + } // overwrite the newOntology Index + // read file + d3.xhr(fileToRead, "application/json", function ( error, request ){ + var loadingSuccessful = !error; + if ( loadingSuccessful ) { + ontologyContent = request.responseText; + parseOntologyContent(ontologyContent); + } else { + + if (loadingNewOntologyForEditor){ + ontologyContent = '{\n' + + ' "_comment": "Empty ontology for WebVOWL Editor",\n' + + ' "header": {\n' + + ' "languages": [\n' + + ' "en"\n' + + ' ],\n' + + ' "baseIris": [\n' + + ' "http://www.w3.org/2000/01/rdf-schema"\n' + + ' ],\n' + + ' "iri": "http://visualdataweb.org/newOntology/",\n' + + ' "title": {\n' + + ' "en": "New ontology"\n' + + ' },\n' + + ' "description": {\n' + + ' "en": "New ontology description"\n' + + ' }\n' + + ' },\n' + + ' "namespace": [],\n' + + ' "metrics": {\n' + + ' "classCount": 0,\n' + + ' "datatypeCount": 0,\n' + + ' "objectPropertyCount": 0,\n' + + ' "datatypePropertyCount": 0,\n' + + ' "propertyCount": 0,\n' + + ' "nodeCount": 0,\n' + + ' "individualCount": 0\n' + + ' }\n' + + '}\n'; + parseOntologyContent(ontologyContent); + }else{ + // some error occurred + ontologyMenu.append_bulletPoint("Failed to load: " + ontology); + if (error.status===0){ // assumption this is CORS error when running locally (error status == 0) + ontologyMenu.append_message_toLastBulletPoint(" ERROR STATUS: " + error.status); + if (window.location.toString().startsWith("file:/")){ + ontologyMenu.append_message_toLastBulletPoint("

    WebVOWL runs in a local instance.

    "); + ontologyMenu.append_message_toLastBulletPoint("

    CORS prevents to automatically load files on host system.

    "); + ontologyMenu.append_message_toLastBulletPoint("

    You can load preprocessed ontologies (i.e. VOWL-JSON files) using the upload feature in the ontology menu or by dragging the files and dropping them on the canvas.

    "); + ontologyMenu.append_message_toLastBulletPoint("

    Hint: Note that the conversion of ontologies into the VOWL-JSON format is not part of WebVOWL but requires an additional converter such as OWL2VOWL.

    "); + ontologyMenu.append_message_toLastBulletPoint("

    Ontologies can be created using the editor mode (i.e. activate editing mode in Modes menu and create a new ontology using the Ontology menu.

    "); + } + }else { + ontologyMenu.append_message_toLastBulletPoint(" ERROR STATUS: " + error.status); + } + + + + graph.handleOnLoadingError(); + loadingModule.setErrorMode(); + } + } + }); + } + } + + + /** -- PARSE JSON CONTENT -- **/ + function parseOntologyContent( content ){ + + ontologyMenu.append_bulletPoint("Reading ontology graph ... "); + var _loader = ontologyMenu.getLoadingFunction(); + _loader(content, ontologyIdentifierFromURL, "noAlternativeNameYet"); + } + + loadingModule.notValidJsonFile = function (){ + graph.clearGraphData(); + ontologyMenu.append_message_toLastBulletPoint(" failed"); + ontologyMenu.append_message_toLastBulletPoint("
    Error: Received empty graph"); + loadingWasSuccessFul = false; + graph.handleOnLoadingError(); + + }; + + loadingModule.validJsonFile = function (){ + ontologyMenu.append_message_toLastBulletPoint("done"); + loadingWasSuccessFul = true; + }; + + + /** --- HELPER FUNCTIONS **/ + + function identifyParameter( url ){ + var numParameters = (url.match(/#/g) || []).length; + // create parameters array + var paramArray = []; + if ( numParameters > 0 ) { + var tokens = url.split("#"); + // skip the first token since it is the address of the server + for ( var i = 1; i < tokens.length; i++ ) { + if ( tokens[i].length === 0 ) { + // this token belongs actually to the last paramArray + paramArray[paramArray.length - 1] = paramArray[paramArray.length - 1] + "#"; + } else { + paramArray.push(tokens[i]); + } + } + } + return paramArray; + } + + + function loadGraphOptions( parameterArray ){ + var optString = "opts="; + + function loadDefaultConfig(){ + graph.options().setOptionsFromURL(graph.options().defaultConfig(), false); + } + + function loadCustomConfig( opts ){ + var changeEditingFlag = false; + var defObj = graph.options().defaultConfig(); + for ( var i = 0; i < opts.length; i++ ) { + var keyVal = opts[i].split('='); + if ( keyVal[0] === "editorMode" ) { + changeEditingFlag = true; + } + defObj[keyVal[0]] = keyVal[1]; + } + graph.options().setOptionsFromURL(defObj, changeEditingFlag); + } + + function identifyOptions( paramArray ){ + if ( paramArray[0].indexOf(optString) >= 0 ) { + // parse the parameters; + var parameterLength = paramArray[0].length; + var givenOptionsStr = paramArray[0].substr(5, parameterLength - 6); + var optionsArray = givenOptionsStr.split(';'); + loadCustomConfig(optionsArray); + } else { + ontologyIdentifierFromURL = paramArray[0]; + loadDefaultConfig(); + } + } + + function identifyOptionsAndOntology( paramArray ){ + + if ( paramArray[0].indexOf(optString) >= 0 ) { + // parse the parameters; + var parameterLength = paramArray[0].length; + var givenOptionsStr = paramArray[0].substr(5, parameterLength - 6); + var optionsArray = givenOptionsStr.split(';'); + loadCustomConfig(optionsArray); + } else { + loadDefaultConfig(); + } + ontologyIdentifierFromURL = paramArray[1]; + } + + switch ( parameterArray.length ) { + case 0: + loadDefaultConfig(); + break; + case 1: + identifyOptions(parameterArray); + break; + case 2: + identifyOptionsAndOntology(parameterArray); + break; + default : + console.log("To many input parameters , loading default config"); + loadDefaultConfig(); + ontologyIdentifierFromURL = "ERROR_TO_MANY_INPUT_PARAMETERS"; + } + } + + + function identifyOntologyLoadingMethod( url ){ + var iriKey = "iri="; + var urlKey = "url="; + var fileKey = "file="; + + var method = -1; + if ( url.substr(0, fileKey.length) === fileKey ) { + method = FILE_UPLOAD; + } else if ( url.substr(0, urlKey.length) === urlKey ) { + method = JSON_URL; + } else if ( url.substr(0, iriKey.length) === iriKey ) { + method = IRI_URL; + } else { + method = PREDEFINED; + } + return method; + } + + return loadingModule; + } + ; + + + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 343: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( graph ){ + /** variable defs **/ + var warningModule = {}; + var superContainer = d3.select("#WarningErrorMessages"); + var _messageContainers = []; + var _messageContext = []; + var _visibleStatus = []; + + var _filterHintId; + var _editorHintId; + var _messageId = -1; + superContainer.style("display", "inline-block"); + var cssStyleIndex = 0; + var styleSelectorIndex = 2; + + + // helper for standalone webvowl in chrome + function createCSSSelector( name, rules ){ + var style = document.createElement('style'); + style.type = 'text/css'; + document.getElementsByTagName('head')[0].appendChild(style); + if ( !(style.sheet || {}).insertRule ) + (style.styleSheet || style.sheet).addRule(name, rules); + else + style.sheet.insertRule(name + "{" + rules + "}", 0); + } + + + function findCSS_Index(){ + createCSSSelector("@keyframes msg_CollapseAnimation", " 0% { top: 0; } 100% { top: -400px;}"); + console.log(document.styleSheets ); + } + + findCSS_Index(); + + warningModule.addMessageBox = function (){ + + // add a container; + _messageId++; + var messageContainer = d3.select("#WarningErrorMessages").append("div"); + messageContainer.node().id = "messageContainerId_" + _messageId; + + var messageContext = messageContainer.append("div"); + messageContext.node().id = "messageContextId_" + _messageId; + messageContext.style("top", "0"); + messageContainer.style("position", "relative"); + messageContainer.style("width", "100%"); + //save in array + _messageContainers.push(messageContainer); + _messageContext.push(messageContext); + + // add animation to the container + messageContainer.node().addEventListener("animationend", _msgContainer_animationEnd); + + // set visible flag that is used in end of animation + _visibleStatus[_messageId] = true; + return _messageId; + }; + + function _msgContainer_animationEnd(){ + var containerId = this.id; + var tokens = containerId.split("_")[1]; + var mContainer = d3.select("#" + containerId); + // get number of children + mContainer.classed("hidden", !_visibleStatus[tokens]); + // clean up DOM + if ( !_visibleStatus[tokens] ) { + mContainer.remove(); + _messageContext[tokens] = null; + _messageContainers[tokens] = null; + } + // remove event listener + var c = d3.select(this); + // c.node().removeEventListener("animationend",_msgContainer_animationEnd); + } + + warningModule.createMessageContext = function ( id ){ + var warningContainer = _messageContext[id]; + var moduleContainer = _messageContainers[id]; + var generalHint = warningContainer.append('div'); + generalHint.node().innerHTML = ""; + _editorHintId = id; + /** Editing mode activated. You can now modify an existing ontology or create a new one via the ontology menu. You can save any ontology using the export menu (and exporting it as TTL file).**/ + generalHint.node().innerHTML += "Editing mode activated.
    " + + "You can now modify an existing ontology or create a new one via the ontology menu.
    " + + "You can save any ontology using the export menu (and exporting it as TTL file)."; + + generalHint.style("padding", "5px"); + generalHint.style("line-height", "1.2em"); + generalHint.style("font-size", "1.2em"); + + + var ul = warningContainer.append('ul'); + ul.append('li').node().innerHTML = "Create a class with double click / tap on empty canvas area."; + ul.append('li').node().innerHTML = "Edit names with double click / tap on element."; + ul.append('li').node().innerHTML = "Selection of default constructors is provided in the left sidebar."; + ul.append('li').node().innerHTML = "Additional editing functionality is provided in the right sidebar."; + + + var gotItButton = warningContainer.append("label"); + gotItButton.node().id = "killWarningErrorMessages_" + id; + gotItButton.node().innerHTML = "Got It"; + gotItButton.on("click", warningModule.closeMessage); + + moduleContainer.classed("hidden", false); + moduleContainer.style("-webkit-animation-name", "warn_ExpandAnimation"); + moduleContainer.style("-webkit-animation-duration", "0.5s"); + }; + + warningModule.showMessage = function ( id ){ + var moduleContainer = _messageContainers[id]; + moduleContainer.classed("hidden", false); + moduleContainer.style("-webkit-animation-name", "warn_ExpandAnimation"); + moduleContainer.style("-webkit-animation-duration", "0.5s"); + }; + + warningModule.closeMessage = function ( id ){ + var nId; + if ( id === undefined ) { + var givenId = this.id; + nId = givenId.split("_")[1]; + } else { + nId = id; + } + if ( id && id.indexOf("_") !== -1 ) { + nId = id.split("_")[1]; + } + _visibleStatus[nId] = false; + // get module; + var moduleContainer = _messageContainers[nId]; + moduleContainer.style("-webkit-animation-name", "warn_CollapseAnimation"); + moduleContainer.style("-webkit-animation-duration", "0.5s"); + + var m_height = moduleContainer.node().getBoundingClientRect().height; + + // find my id in the children + var pNode = moduleContainer.node().parentNode; + + var followingChildren = []; + var pChild = pNode.children; + var pChild_len = pChild.length; + var containerId = moduleContainer.node().id; + var found_me = false; + for ( var i = 0; i < pChild_len; i++ ) { + if ( found_me === true ) { + followingChildren.push(pChild[i].id); + } + + if ( containerId === pChild[i].id ) { + found_me = true; + } + } + + for ( var fc = 0; fc < followingChildren.length; fc++ ) { + var child = d3.select("#" + followingChildren[fc]); + // get the document style and overwrite it; + var superCss = document.styleSheets[styleSelectorIndex].cssRules[cssStyleIndex]; + // remove the existing 0% and 100% rules + superCss.deleteRule("0%"); + superCss.deleteRule("100%"); + + superCss.appendRule("0% {top: 0;}"); + superCss.appendRule("100% {top: -" + m_height + "px;"); + + child.style("-webkit-animation-name", "msg_CollapseAnimation"); + child.style("-webkit-animation-duration", "0.5s"); + child.node().addEventListener("animationend", _child_animationEnd); + } + }; + + function _child_animationEnd(){ + var c = d3.select(this); + c.style("-webkit-animation-name", ""); + c.style("-webkit-animation-duration", ""); + c.node().removeEventListener("animationend", _child_animationEnd); + } + + warningModule.closeFilterHint = function (){ + if ( _messageContainers[_filterHintId] ) { + _messageContainers[_filterHintId].classed("hidden", true); + _messageContainers[_filterHintId].remove(); + _messageContainers[_filterHintId] = null; + _messageContext[_filterHintId] = null; + _visibleStatus[_filterHintId] = false; + } + }; + + warningModule.showEditorHint = function (){ + var id = warningModule.addMessageBox(); + warningModule.createMessageContext(id); + }; + + warningModule.showExporterWarning=function (){ + warningModule.showWarning("Can not export ontology", "Detected unsupported ontology axioms, (e.g. owl:Union)", "Ontology is not exported", 1, false); + }; + + + + warningModule.responseWarning = function ( header, reason, action, callback, parameterArray, forcedWarning ){ + var id = warningModule.addMessageBox(); + var warningContainer = _messageContext[id]; + var moduleContainer = _messageContainers[id]; + _visibleStatus[id] = true; + d3.select("#blockGraphInteractions").classed("hidden", false); + var graphWidth = 0.5 * graph.options().width(); + + if ( header.length > 0 ) { + var head = warningContainer.append("div"); + head.style("padding", "5px"); + var titleHeader = head.append("div"); + // some classes + titleHeader.style("display", "inline-flex"); + titleHeader.node().innerHTML = "Warning:"; + titleHeader.style("padding-right", "3px"); + var msgHeader = head.append("div"); + // some classes + msgHeader.style("display", "inline-flex"); + msgHeader.style("max-width", graphWidth + "px"); + + msgHeader.node().innerHTML = header; + } + if ( reason.length > 0 ) { + var reasonContainer = warningContainer.append("div"); + reasonContainer.style("padding", "5px"); + var reasonHeader = reasonContainer.append("div"); + // some classes + reasonHeader.style("display", "inline-flex"); + reasonHeader.style("padding-right", "3px"); + + reasonHeader.node().innerHTML = "Reason:"; + var msgReason = reasonContainer.append("div"); + // some classes + msgReason.style("display", "inline-flex"); + msgReason.style("max-width", graphWidth + "px"); + msgReason.node().innerHTML = reason; + } + if ( action.length > 0 ) { + var actionContainer = warningContainer.append("div"); + actionContainer.style("padding", "5px"); + var actionHeader = actionContainer.append("div"); + // some classes + actionHeader.style("display", "inline-flex"); + actionHeader.style("padding-right", "8px"); + actionHeader.node().innerHTML = "Action:"; + var msgAction = actionContainer.append("div"); + // some classes + msgAction.style("display", "inline-flex"); + msgAction.style("max-width", graphWidth + "px"); + msgAction.node().innerHTML = action; + } + + var gotItButton = warningContainer.append("label"); + gotItButton.node().id = "killWarningErrorMessages_" + id; + gotItButton.node().innerHTML = "Continue"; + gotItButton.on("click", function (){ + warningModule.closeMessage(this.id); + d3.select("#blockGraphInteractions").classed("hidden", true); + callback(parameterArray[0], parameterArray[1], parameterArray[2], parameterArray[3]); + }); + warningContainer.append("span").node().innerHTML = "|"; + var cancelButton = warningContainer.append("label"); + cancelButton.node().id = "cancelButton_" + id; + cancelButton.node().innerHTML = "Cancel"; + cancelButton.on("click", function (){ + warningModule.closeMessage(this.id); + d3.select("#blockGraphInteractions").classed("hidden", true); + }); + moduleContainer.classed("hidden", false); + moduleContainer.style("-webkit-animation-name", "warn_ExpandAnimation"); + moduleContainer.style("-webkit-animation-duration", "0.5s"); + }; + + warningModule.showFilterHint = function (){ + var id = warningModule.addMessageBox(); + var warningContainer = _messageContext[id]; + var moduleContainer = _messageContainers[id]; + _visibleStatus[id] = true; + + _filterHintId = id; + var generalHint = warningContainer.append('div'); + /** Editing mode activated. You can now modify an existing ontology or create a new one via the ontology menu. You can save any ontology using the export menu (and exporting it as TTL file).**/ + generalHint.node().innerHTML = "Collapsing filter activated.
    " + + "The number of visualized elements has been automatically reduced.
    " + + "Use the degree of collapsing slider in the filter menu to adjust the visualization.

    " + + "Note: A performance decrease could be experienced with a growing amount of visual elements in the graph."; + + + generalHint.style("padding", "5px"); + generalHint.style("line-height", "1.2em"); + generalHint.style("font-size", "1.2em"); + + var gotItButton = warningContainer.append("label"); + gotItButton.node().id = "killFilterMessages_" + id; + gotItButton.node().innerHTML = "Got It"; + gotItButton.on("click", warningModule.closeMessage); + + moduleContainer.classed("hidden", false); + moduleContainer.style("-webkit-animation-name", "warn_ExpandAnimation"); + moduleContainer.style("-webkit-animation-duration", "0.5s"); + }; + + warningModule.showMultiFileUploadWarning = function (){ + var id = warningModule.addMessageBox(); + var warningContainer = _messageContext[id]; + var moduleContainer = _messageContainers[id]; + _visibleStatus[id] = true; + + _filterHintId = id; + var generalHint = warningContainer.append('div'); + + generalHint.node().innerHTML = "Uploading multiple files is not supported.
    "; + + generalHint.style("padding", "5px"); + generalHint.style("line-height", "1.2em"); + generalHint.style("font-size", "1.2em"); + + var gotItButton = warningContainer.append("label"); + gotItButton.node().id = "killFilterMessages_" + id; + gotItButton.node().innerHTML = "Got It"; + gotItButton.on("click", warningModule.closeMessage); + + moduleContainer.classed("hidden", false); + moduleContainer.style("-webkit-animation-name", "warn_ExpandAnimation"); + moduleContainer.style("-webkit-animation-duration", "0.5s"); + }; + + warningModule.showWarning = function ( header, reason, action, type, forcedWarning, additionalOpts ){ + var id = warningModule.addMessageBox(); + var warningContainer = _messageContext[id]; + var moduleContainer = _messageContainers[id]; + _visibleStatus[id] = true; + + // add new one; + var graphWidth = 0.5 * graph.options().width(); + + if ( header.length > 0 ) { + var head = warningContainer.append("div"); + head.style("padding", "5px"); + var titleHeader = head.append("div"); + // some classes + titleHeader.style("display", "inline-flex"); + titleHeader.node().innerHTML = "Warning:"; + titleHeader.style("padding-right", "3px"); + var msgHeader = head.append("div"); + // some classes + msgHeader.style("display", "inline-flex"); + msgHeader.style("max-width", graphWidth + "px"); + + msgHeader.node().innerHTML = header; + } + if ( reason.length > 0 ) { + var reasonContainer = warningContainer.append("div"); + reasonContainer.style("padding", "5px"); + var reasonHeader = reasonContainer.append("div"); + // some classes + reasonHeader.style("display", "inline-flex"); + reasonHeader.style("padding-right", "3px"); + + reasonHeader.node().innerHTML = "Reason:"; + var msgReason = reasonContainer.append("div"); + // some classes + msgReason.style("display", "inline-flex"); + msgReason.style("max-width", graphWidth + "px"); + msgReason.node().innerHTML = reason; + } + if ( action.length > 0 ) { + var actionContainer = warningContainer.append("div"); + actionContainer.style("padding", "5px"); + var actionHeader = actionContainer.append("div"); + // some classes + actionHeader.style("display", "inline-flex"); + actionHeader.style("padding-right", "8px"); + actionHeader.node().innerHTML = "Action:"; + var msgAction = actionContainer.append("div"); + // some classes + msgAction.style("display", "inline-flex"); + msgAction.style("max-width", graphWidth + "px"); + msgAction.node().innerHTML = action; + } + + var gotItButton; + if ( type === 1 ) { + gotItButton = warningContainer.append("label"); + gotItButton.node().id = "killWarningErrorMessages_" + id; + gotItButton.node().innerHTML = "Got It"; + gotItButton.on("click", warningModule.closeMessage); + } + + if ( type === 2 ) { + gotItButton = warningContainer.append("label"); + gotItButton.node().id = "killWarningErrorMessages_" + id; + gotItButton.node().innerHTML = "Got It"; + gotItButton.on("click", warningModule.closeMessage); + warningContainer.append("span").node().innerHTML = "|"; + var zoomToElementButton = warningContainer.append("label"); + zoomToElementButton.node().id = "zoomElementThing_" + id; + zoomToElementButton.node().innerHTML = "Zoom to element "; + zoomToElementButton.on("click", function (){ + // assume the additional Element is for halo; + graph.zoomToElementInGraph(additionalOpts); + }); + warningContainer.append("span").node().innerHTML = "|"; + var ShowElementButton = warningContainer.append("label"); + ShowElementButton.node().id = "showElementThing_" + id; + ShowElementButton.node().innerHTML = "Indicate element"; + ShowElementButton.on("click", function (){ + // assume the additional Element is for halo; + if ( additionalOpts.halo() === false ) { + additionalOpts.drawHalo(); + graph.updatePulseIds([additionalOpts.id()]); + } else { + additionalOpts.removeHalo(); + additionalOpts.drawHalo(); + graph.updatePulseIds([additionalOpts.id()]); + } + }); + } + moduleContainer.classed("hidden", false); + moduleContainer.style("-webkit-animation-name", "warn_ExpandAnimation"); + moduleContainer.style("-webkit-animation-duration", "0.5s"); + moduleContainer.classed("hidden", false); + }; + + return warningModule; + }; + + + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), + +/***/ 344: +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( graph ){ + /** variable defs **/ + var directInputModule = {}; + var inputContainer = d3.select("#DirectInputContent"); + inputContainer.style("top", "0"); + inputContainer.style("position", "absolute"); + var textArea = d3.select("#directInputTextArea"); + var visibleContainer = false; + + inputContainer.style("border", "1px solid black"); + inputContainer.style("padding", "5px"); + inputContainer.style("background", "#fff"); + + + // connect upload and close button; + directInputModule.handleDirectUpload = function (){ + + var text = textArea.node().value; + var jsonOBJ; + try { + jsonOBJ = JSON.parse(text); + graph.options().loadingModule().directInput(text); + // close if successful + if ( jsonOBJ.class.length > 0 ) { + directInputModule.setDirectInputMode(false); + } + } + catch ( e ) { + try { + // Initialize; + graph.options().loadingModule().initializeLoader(); + graph.options().loadingModule().requestServerTimeStampForDirectInput( + graph.options().ontologyMenu().callbackLoad_Ontology_From_DirectInput, text + ); + } catch ( error2 ) { + console.log("Error " + error2); + d3.select("#Error_onLoad").classed("hidden", false); + d3.select("#Error_onLoad").node().innerHTML = "Failed to convert the input!"; + } + } + }; + + directInputModule.handleCloseButton = function (){ + directInputModule.setDirectInputMode(false); + }; + + directInputModule.updateLayout = function (){ + var w = graph.options().width(); + var h = graph.options().height(); + textArea.style("width", 0.4 * w + "px"); + textArea.style("height", 0.7 * h + "px"); + }; + + directInputModule.setDirectInputMode = function ( val ){ + if ( !val ) { + visibleContainer = !visibleContainer; + } + else { + visibleContainer = val; + } + // update visibility; + directInputModule.updateLayout(); + d3.select("#Error_onLoad").classed("hidden", true); + inputContainer.classed("hidden", !visibleContainer); + }; + + + d3.select("#directUploadBtn").on("click", directInputModule.handleDirectUpload); + d3.select("#close_directUploadBtn").on("click", directInputModule.handleCloseButton); + + return directInputModule; + }; + + + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }) + +/******/ }); diff --git a/doc/releases/0.1.0/steps/webvowl/js/webvowl.js b/doc/releases/0.1.0/steps/webvowl/js/webvowl.js new file mode 100644 index 0000000..1aba35e --- /dev/null +++ b/doc/releases/0.1.0/steps/webvowl/js/webvowl.js @@ -0,0 +1,25345 @@ +webvowl = +/******/ (function(modules) { // webpackBootstrap +/******/ // The module cache +/******/ var installedModules = {}; + +/******/ // The require function +/******/ function __webpack_require__(moduleId) { + +/******/ // Check if module is in cache +/******/ if(installedModules[moduleId]) +/******/ return installedModules[moduleId].exports; + +/******/ // Create a new module (and put it into the cache) +/******/ var module = installedModules[moduleId] = { +/******/ exports: {}, +/******/ id: moduleId, +/******/ loaded: false +/******/ }; + +/******/ // Execute the module function +/******/ modules[moduleId].call(module.exports, module, module.exports, __webpack_require__); + +/******/ // Flag the module as loaded +/******/ module.loaded = true; + +/******/ // Return the exports of the module +/******/ return module.exports; +/******/ } + + +/******/ // expose the modules object (__webpack_modules__) +/******/ __webpack_require__.m = modules; + +/******/ // expose the module cache +/******/ __webpack_require__.c = installedModules; + +/******/ // __webpack_public_path__ +/******/ __webpack_require__.p = ""; + +/******/ // Load entry module and return exports +/******/ return __webpack_require__(0); +/******/ }) +/************************************************************************/ +/******/ ([ +/* 0 */ +/***/ (function(module, exports, __webpack_require__) { + + __webpack_require__(1); + + var nodeMap = __webpack_require__(5)(); + var propertyMap = __webpack_require__(40)(); + + + var webvowl = {}; + webvowl.graph = __webpack_require__(57); + webvowl.options = __webpack_require__(64); + webvowl.version = "1.1.7"; + + webvowl.util = {}; + webvowl.util.constants = __webpack_require__(12); + webvowl.util.languageTools = __webpack_require__(11); + webvowl.util.elementTools = __webpack_require__(63); + webvowl.util.prefixTools = __webpack_require__(72); + webvowl.modules = {}; + webvowl.modules.colorExternalsSwitch = __webpack_require__(73); + webvowl.modules.compactNotationSwitch = __webpack_require__(74); + webvowl.modules.datatypeFilter = __webpack_require__(75); + webvowl.modules.disjointFilter = __webpack_require__(77); + webvowl.modules.focuser = __webpack_require__(78); + webvowl.modules.emptyLiteralFilter = __webpack_require__(79); + webvowl.modules.nodeDegreeFilter = __webpack_require__(80); + webvowl.modules.nodeScalingSwitch = __webpack_require__(81); + webvowl.modules.objectPropertyFilter = __webpack_require__(82); + webvowl.modules.pickAndPin = __webpack_require__(83); + webvowl.modules.selectionDetailsDisplayer = __webpack_require__(315); + webvowl.modules.setOperatorFilter = __webpack_require__(316); + webvowl.modules.statistics = __webpack_require__(317); + webvowl.modules.subclassFilter = __webpack_require__(318); + + + webvowl.nodes = {}; + nodeMap.entries().forEach(function ( entry ){ + mapEntryToIdentifier(webvowl.nodes, entry); + }); + + webvowl.properties = {}; + propertyMap.entries().forEach(function ( entry ){ + mapEntryToIdentifier(webvowl.properties, entry); + }); + + function mapEntryToIdentifier( map, entry ){ + var identifier = entry.key.replace(":", "").toLowerCase(); + map[identifier] = entry.value; + } + + + module.exports = webvowl; + + +/***/ }), +/* 1 */ +/***/ (function(module, exports) { + + // removed by extract-text-webpack-plugin + +/***/ }), +/* 2 */, +/* 3 */, +/* 4 */, +/* 5 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var nodes = []; + nodes.push(__webpack_require__(7)); + nodes.push(__webpack_require__(18)); + nodes.push(__webpack_require__(19)); + nodes.push(__webpack_require__(26)); + nodes.push(__webpack_require__(27)); + nodes.push(__webpack_require__(28)); + nodes.push(__webpack_require__(29)); + nodes.push(__webpack_require__(30)); + nodes.push(__webpack_require__(31)); + nodes.push(__webpack_require__(32)); + nodes.push(__webpack_require__(33)); + nodes.push(__webpack_require__(34)); + nodes.push(__webpack_require__(38)); + nodes.push(__webpack_require__(39)); + + var map = d3.map(nodes, function ( Prototype ){ + return new Prototype().type(); + }); + + module.exports = function (){ + return map; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 6 */ +/***/ (function(module, exports) { + + module.exports = d3; + +/***/ }), +/* 7 */ +/***/ (function(module, exports, __webpack_require__) { + + var RoundNode = __webpack_require__(8); + + module.exports = (function (){ + + var o = function ( graph ){ + RoundNode.apply(this, arguments); + + this.attributes(["external"]) + .type("ExternalClass"); + }; + o.prototype = Object.create(RoundNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 8 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseNode = __webpack_require__(9); + var CenteringTextElement = __webpack_require__(14); + var drawTools = __webpack_require__(17)(); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseNode.apply(this, arguments); + + var that = this, + collapsible = false, + radius = 50, + collapsingGroupElement, + pinGroupElement, + haloGroupElement = null, + rectangularRepresentation = false, + renderingElement, + textBlock; + + this.setRectangularRepresentation = function ( val ){ + rectangularRepresentation = val; + }; + this.getRectangularRepresentation = function (){ + return rectangularRepresentation; + }; + + this.getHalos = function (){ + return haloGroupElement; + }; + + // Properties + this.collapsible = function ( p ){ + if ( !arguments.length ) return collapsible; + collapsible = p; + return this; + }; + + this.textBlock = function ( p ){ + if ( !arguments.length ) return textBlock; + textBlock = p; + return this; + }; + + /** + * This might not be equal to the actual radius, because the instance count is used for its calculation. + * @param p + * @returns {*} + */ + this.radius = function ( p ){ + if ( !arguments.length ) return radius; + radius = p; + return this; + }; + + + // Functions + this.setHoverHighlighting = function ( enable ){ + that.nodeElement().selectAll("circle").classed("hovered", enable); + }; + + this.textWidth = function ( yOffset ){ + var availableWidth = this.actualRadius() * 2; + + // if the text is not placed in the center of the circle, it can't have the full width + if ( yOffset ) { + var relativeOffset = Math.abs(yOffset) / this.actualRadius(); + var isOffsetInsideOfNode = relativeOffset <= 1; + + if ( isOffsetInsideOfNode ) { + availableWidth = Math.cos(relativeOffset) * availableWidth; + } else { + availableWidth = 0; + } + } + + return availableWidth; + }; + + this.toggleFocus = function (){ + that.focused(!that.focused()); + if ( that.nodeElement() ) + that.nodeElement().select("circle").classed("focused", that.focused()); + graph.resetSearchHighlight(); + graph.options().searchMenu().clearText(); + + }; + + this.actualRadius = function (){ + if ( !graph.options().scaleNodesByIndividuals() || that.individuals().length <= 0 ) { + return that.radius(); + } else { + // we could "listen" for radius and maxIndividualCount changes, but this is easier + var MULTIPLIER = 8, + additionalRadius = Math.log(that.individuals().length + 1) * MULTIPLIER + 5; + + return that.radius() + additionalRadius; + } + }; + + this.distanceToBorder = function (){ + return that.actualRadius(); + }; + + this.removeHalo = function (){ + if ( that.halo() ) { + that.halo(false); + if ( haloGroupElement ) { + haloGroupElement.remove(); + } + } + }; + + this.drawHalo = function ( pulseAnimation ){ + that.halo(true); + if ( rectangularRepresentation === true ) { + haloGroupElement = drawTools.drawRectHalo(that.nodeElement(), 80, 80, 5); + } else { + haloGroupElement = drawTools.drawHalo(that.nodeElement(), that.actualRadius(), this.removeHalo); + } + if ( pulseAnimation === false ) { + var pulseItem = haloGroupElement.selectAll(".searchResultA"); + pulseItem.classed("searchResultA", false); + pulseItem.classed("searchResultB", true); + pulseItem.attr("animationRunning", false); + } + }; + + /** + * Draws the pin on a round node on a position depending on its radius. + */ + this.drawPin = function (){ + that.pinned(true); + var dx = (-3.5 / 5) * that.actualRadius(), + dy = (-7 / 10) * that.actualRadius(); + pinGroupElement = drawTools.drawPin(that.nodeElement(), dx, dy, this.removePin, graph.options().showDraggerObject, graph.options().useAccuracyHelper()); + + + }; + + /** + * Removes the pin and refreshs the graph to update the force layout. + */ + this.removePin = function (){ + that.pinned(false); + if ( pinGroupElement ) { + pinGroupElement.remove(); + } + graph.updateStyle(); + }; + + this.drawCollapsingButton = function (){ + + collapsingGroupElement = that.nodeElement() + .append("g") + .classed("hidden-in-export", true) + .attr("transform", function (){ + var dx = (-2 / 5) * that.actualRadius(), + dy = (1 / 2) * that.actualRadius(); + return "translate(" + dx + "," + dy + ")"; + }); + + collapsingGroupElement.append("rect") + .classed("class pin feature", true) + .attr("x", 0) + .attr("y", 0) + .attr("width", 40) + .attr("height", 24); + + collapsingGroupElement.append("line") + .attr("x1", 13) + .attr("y1", 12) + .attr("x2", 27) + .attr("y2", 12); + + collapsingGroupElement.append("line") + .attr("x1", 20) + .attr("y1", 6) + .attr("x2", 20) + .attr("y2", 18); + }; + + /** + * Draws a circular node. + * @param parentElement the element to which this node will be appended + * @param [additionalCssClasses] additional css classes + */ + this.draw = function ( parentElement, additionalCssClasses ){ + var cssClasses = that.collectCssClasses(); + that.nodeElement(parentElement); + + var bgColor = that.backgroundColor(); + if ( bgColor === null ) bgColor = undefined; + if ( that.attributes().indexOf("deprecated") > -1 ) { + bgColor = undefined; + } + if ( additionalCssClasses instanceof Array ) { + cssClasses = cssClasses.concat(additionalCssClasses); + } + if ( rectangularRepresentation === true ) { + renderingElement = drawTools.appendRectangularClass(parentElement, 80, 80, cssClasses, that.labelForCurrentLanguage(), bgColor); + } else { + renderingElement = drawTools.appendCircularClass(parentElement, that.actualRadius(), cssClasses, that.labelForCurrentLanguage(), bgColor); + } + that.postDrawActions(parentElement); + }; + + this.redrawElement = function (){ + renderingElement.remove(); + textBlock.remove(); + var bgColor = that.backgroundColor(); + if ( that.attributes().indexOf("deprecated") > -1 ) { + bgColor = undefined; + } + + var cssClasses = that.collectCssClasses(); + + if ( rectangularRepresentation === true ) { + renderingElement = drawTools.appendRectangularClass(that.nodeElement(), 80, 80, cssClasses, that.labelForCurrentLanguage(), bgColor); + } else { + renderingElement = drawTools.appendCircularClass(that.nodeElement(), that.actualRadius(), cssClasses, that.labelForCurrentLanguage(), bgColor); + } + that.postDrawActions(that.nodeElement()); + }; + /** + * Common actions that should be invoked after drawing a node. + */ + this.postDrawActions = function (){ + that.textBlock(createTextBlock()); + + that.addMouseListeners(); + if ( that.pinned() ) { + that.drawPin(); + } + if ( that.halo() ) { + that.drawHalo(false); + } + if ( that.collapsible() ) { + that.drawCollapsingButton(); + } + }; + + this.redrawLabelText = function (){ + that.textBlock().remove(); + that.textBlock(createTextBlock()); + renderingElement.select("title").text(that.labelForCurrentLanguage()); + }; + function createTextBlock(){ + var bgColor = that.backgroundColor(); + if ( that.attributes().indexOf("deprecated") > -1 ) + bgColor = undefined; + + var textBlock = new CenteringTextElement(that.nodeElement(), bgColor); + + var equivalentsString = that.equivalentsString(); + var suffixForFollowingEquivalents = equivalentsString ? "," : ""; + + textBlock.addText(that.labelForCurrentLanguage(), "", suffixForFollowingEquivalents); + textBlock.addEquivalents(equivalentsString); + if ( !graph.options().compactNotation() ) { + textBlock.addSubText(that.indicationString()); + } + textBlock.addInstanceCount(that.individuals().length); + + return textBlock; + } + + this.equivalentsString = function (){ + var equivalentClasses = that.equivalents(); + if ( !equivalentClasses ) { + return; + } + + return equivalentClasses + .map(function ( node ){ + return node.labelForCurrentLanguage(); + }) + .join(", "); + }; + }; + o.prototype = Object.create(BaseNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 9 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var BaseElement = __webpack_require__(10); + var forceLayoutNodeFunctions = __webpack_require__(13)(); + + module.exports = (function (){ + + var Base = function ( graph ){ + BaseElement.apply(this, arguments); + + var that = this, + // Basic attributes + complement, + disjointUnion, + disjointWith, + individuals = [], + intersection, + union, + links, + rendertype = "round", + // Additional attributes + maxIndividualCount, + fobj, // foreigner object for editing + ignoreLocalHoverEvents = false, + backupFullIri, + // Element containers + nodeElement; + + // array to store my properties; // we will need this also later for semantic zooming stuff + var assignedProperties = []; + that.editingTextElement = false; + + this.isPropertyAssignedToThisElement = function ( property ){ + // this goes via IRIS + console.log("Element IRI :" + property.iri()); + if ( property.type() === "rdfs:subClassOf" ) + for ( var i = 0; i < assignedProperties.length; i++ ) { + var iriEl = assignedProperties[i].iri(); + if ( property.iri() === iriEl ) { + return true; + } + if ( property.type() === "rdfs:subClassOf" && assignedProperties[i].type() === "rdfs:subClassOf" ) + return true; + if ( property.type() === "owl:disjointWith" && assignedProperties[i].type() === "owl:disjointWith" ) + return true; + + } + return false; + }; + + + this.existingPropertyIRI = function ( url ){ + // this goes via IRIS + for ( var i = 0; i < assignedProperties.length; i++ ) { + var iriEl = assignedProperties[i].iri(); + if ( iriEl === url ) { + return true; + } + } + return false; + }; + + this.addProperty = function ( property ){ + if ( assignedProperties.indexOf(property) === -1 ) { + assignedProperties.push(property); + } + }; + + this.removePropertyElement = function ( property ){ + // console.log("Calling removing old property!"+ property.iri()); + if ( assignedProperties.indexOf(property) !== -1 ) { + // console.log("Found it!"); + assignedProperties.splice(assignedProperties.indexOf(property), 1); + } + }; + this.getMyProperties = function (){ + return assignedProperties; + }; + this.copyOtherProperties = function ( otherProperties ){ + assignedProperties = otherProperties; + }; + + this.copyInformation = function ( other ){ + console.log(other.labelForCurrentLanguage()); + if ( other.type() !== "owl:Thing" ) + that.label(other.label()); + that.complement(other.complement()); + that.iri(other.iri()); + that.copyOtherProperties(other.getMyProperties()); + that.baseIri(other.baseIri()); + if ( other.type() === "owl:Class" ) { + that.backupLabel(other.label()); + // console.log("copied backup label"+that.backupLabel()); + } + if ( other.backupLabel() !== undefined ) { + that.backupLabel(other.backupLabel()); + } + }; + + this.enableEditing = function ( autoEditing ){ + if ( autoEditing === false ) + return; + that.raiseDoubleClickEdit(true); + }; + + this.raiseDoubleClickEdit = function ( forceIRISync ){ + d3.selectAll(".foreignelements").remove(); + if ( nodeElement === undefined || this.type() === "owl:Thing" || this.type() === "rdfs:Literal" ) { + console.log("No Container found"); + return; + } + if ( fobj !== undefined ) { + nodeElement.selectAll(".foreignelements").remove(); + } + + backupFullIri = undefined; + graph.options().focuserModule().handle(undefined); + graph.options().focuserModule().handle(that); + // add again the editing elements to that one + if ( graph.isTouchDevice() === true ) { + graph.activateHoverElements(true, that, true); + } + that.editingTextElement = true; + ignoreLocalHoverEvents = true; + that.nodeElement().selectAll("circle").classed("hoveredForEditing", true); + graph.killDelayedTimer(); + graph.ignoreOtherHoverEvents(false); + fobj = nodeElement.append("foreignObject") + .attr("x", -0.5 * (that.textWidth() - 2)) + .attr("y", -12) + .attr("height", 30) + .attr("class", "foreignelements") + .on("dragstart", function (){ + return false; + }) // remove drag operations of text element) + .attr("width", that.textWidth() - 2); + + var editText = fobj.append("xhtml:input") + .attr("class", "nodeEditSpan") + .attr("id", that.id()) + .attr("align", "center") + .attr("contentEditable", "true") + .on("dragstart", function (){ + return false; + }); // remove drag operations of text element) + + var bgColor = '#f00'; + var txtWidth = that.textWidth() - 2; + editText.style({ + + 'align': 'center', + 'color': 'black', + 'width': txtWidth + "px", + 'height': '15px', + 'background-color': bgColor, + 'border-bottom': '2px solid black' + }); + var txtNode = editText.node(); + txtNode.value = that.labelForCurrentLanguage(); + txtNode.focus(); + txtNode.select(); + that.frozen(true); // << releases the not after selection + that.locked(true); + + + d3.event.stopPropagation(); + // ignoreNodeHoverEvent=true; + // // add some events that relate to this object + editText.on("click", function (){ + d3.event.stopPropagation(); + }); + // // remove hover Events for now; + editText.on("mouseout", function (){ + d3.event.stopPropagation(); + + + }); + editText.on("mousedown", function (){ + d3.event.stopPropagation(); + }) + .on("keydown", function (){ + d3.event.stopPropagation(); + if ( d3.event.keyCode === 13 ) { + this.blur(); + that.frozen(false); // << releases the not after selection + that.locked(false); + } + }) + .on("keyup", function (){ + if ( forceIRISync ) { + var labelName = editText.node().value; + var resourceName = labelName.replaceAll(" ", "_"); + var syncedIRI = that.baseIri() + resourceName; + backupFullIri = syncedIRI; + + d3.select("#element_iriEditor").node().title = syncedIRI; + d3.select("#element_iriEditor").node().value = graph.options().prefixModule().getPrefixRepresentationForFullURI(syncedIRI); + } + d3.select("#element_labelEditor").node().value = editText.node().value; + + }) + .on("blur", function (){ + that.editingTextElement = false; + ignoreLocalHoverEvents = false; + that.nodeElement().selectAll("circle").classed("hoveredForEditing", false); + var newLabel = editText.node().value; + nodeElement.selectAll(".foreignelements").remove(); + // that.setLabelForCurrentLanguage(classNameConvention(editText.node().value)); + that.label(newLabel); + that.backupLabel(newLabel); + that.redrawLabelText(); + that.frozen(graph.paused()); + that.locked(graph.paused()); + graph.ignoreOtherHoverEvents(false); + // console.log("Calling blur on Node!"); + if ( backupFullIri ) { + var sanityCheckResult = graph.checkIfIriClassAlreadyExist(backupFullIri); + if ( sanityCheckResult === false ) { + that.iri(backupFullIri); + } else { + // throw warnign + graph.options().warningModule().showWarning("Already seen this class", + "Input IRI: " + backupFullIri + " for element: " + that.labelForCurrentLanguage() + " already been set", + "Restoring previous IRI for Element : " + that.iri(), 2, false, sanityCheckResult); + + } + } + if ( graph.isADraggerActive() === false ) { + graph.options().focuserModule().handle(undefined); + graph.options().focuserModule().handle(that); + } + }); // add a foreiner element to this thing; + }; + + + this.renderType = function ( t ){ + if ( !arguments.length ) return rendertype; + rendertype = t; + return this; + }; + // Properties + this.complement = function ( p ){ + if ( !arguments.length ) return complement; + complement = p; + return this; + }; + + this.disjointUnion = function ( p ){ + if ( !arguments.length ) return disjointUnion; + disjointUnion = p; + return this; + }; + + this.disjointWith = function ( p ){ + if ( !arguments.length ) return disjointWith; + disjointWith = p; + return this; + }; + + this.individuals = function ( p ){ + if ( !arguments.length ) return individuals; + individuals = p || []; + return this; + }; + + this.intersection = function ( p ){ + if ( !arguments.length ) return intersection; + intersection = p; + return this; + }; + + this.links = function ( p ){ + if ( !arguments.length ) return links; + links = p; + return this; + }; + + this.maxIndividualCount = function ( p ){ + if ( !arguments.length ) return maxIndividualCount; + maxIndividualCount = p; + return this; + }; + + this.nodeElement = function ( p ){ + if ( !arguments.length ) return nodeElement; + nodeElement = p; + return this; + }; + + this.union = function ( p ){ + if ( !arguments.length ) return union; + union = p; + return this; + }; + + + /** + * Returns css classes generated from the data of this object. + * @returns {Array} + */ + that.collectCssClasses = function (){ + var cssClasses = []; + + if ( typeof that.styleClass() === "string" ) { + cssClasses.push(that.styleClass()); + } + + cssClasses = cssClasses.concat(that.visualAttributes()); + + return cssClasses; + }; + + + // Reused functions TODO refactor + this.addMouseListeners = function (){ + // Empty node + if ( !that.nodeElement() ) { + console.warn(this); + return; + } + + that.nodeElement().selectAll("*") + .on("mouseover", onMouseOver) + .on("mouseout", onMouseOut); + }; + + this.animationProcess = function (){ + var animRuns = false; + if ( that.getHalos() ) { + var haloGr = that.getHalos(); + var haloEls = haloGr.selectAll(".searchResultA"); + animRuns = haloGr.attr("animationRunning"); + if ( typeof animRuns !== "boolean" ) { + // parse this to a boolean value + animRuns = (animRuns === 'true'); + } + if ( animRuns === false ) { + haloEls.classed("searchResultA", false); + haloEls.classed("searchResultB", true); + } + } + return animRuns; + }; + + this.foreground = function (){ + var selectedNode = that.nodeElement().node(), + nodeContainer = selectedNode.parentNode; + // check if the halo is present and an animation is running + if ( that.animationProcess() === false ) { + // Append hovered element as last child to the container list. + nodeContainer.appendChild(selectedNode); + } + + }; + + function onMouseOver(){ + if ( that.mouseEntered() || ignoreLocalHoverEvents === true ) { + return; + } + + var selectedNode = that.nodeElement().node(), + nodeContainer = selectedNode.parentNode; + + // Append hovered element as last child to the container list. + if ( that.animationProcess() === false ) { + nodeContainer.appendChild(selectedNode); + } + if ( graph.isTouchDevice() === false ) { + that.setHoverHighlighting(true); + that.mouseEntered(true); + if ( graph.editorMode() === true && graph.ignoreOtherHoverEvents() === false ) { + graph.activateHoverElements(true, that); + } + } else { + if ( graph.editorMode() === true && graph.ignoreOtherHoverEvents() === false ) { + graph.activateHoverElements(true, that, true); + } + + } + + + } + + function onMouseOut(){ + that.setHoverHighlighting(false); + that.mouseEntered(false); + if ( graph.editorMode() === true && graph.ignoreOtherHoverEvents() === false ) { + graph.activateHoverElements(false); + } + } + + + forceLayoutNodeFunctions.addTo(this); + }; + + Base.prototype = Object.create(BaseElement.prototype); + Base.prototype.constructor = Base; + + + return Base; + }()); + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 10 */ +/***/ (function(module, exports, __webpack_require__) { + + /** + * The base element for all visual elements of webvowl. + */ + module.exports = (function (){ + + var Base = function ( graph ){ + // Basic attributes + var equivalents = [], + id, + label, + type, + iri, + baseIri, + // Additional attributes + annotations, + attributes = [], + backgroundColor, + comment, + description, + equivalentBase, + visualAttributes = [], + // Style attributes + focused = false, + indications = [], + mouseEntered = false, + styleClass, + visible = true, + + backupLabel, + // Other + languageTools = __webpack_require__(11)(); + + + this.backupLabel = function ( label ){ + if ( !arguments.length ) return backupLabel; + backupLabel = label; + }; + // Properties + this.attributes = function ( p ){ + if ( !arguments.length ) return attributes; + attributes = p; + return this; + }; + + this.annotations = function ( p ){ + if ( !arguments.length ) return annotations; + annotations = p; + return this; + }; + + this.redrawElement = function (){ + // TODO: OVERLOADED BY INDIVIDUAL ELEMENTS + }; + + this.backgroundColor = function ( p ){ + if ( !arguments.length ) return backgroundColor; + backgroundColor = p; + return this; + }; + + this.baseIri = function ( p ){ + if ( !arguments.length ) return baseIri; + baseIri = p; + return this; + }; + + this.comment = function ( p ){ + if ( !arguments.length ) return comment; + comment = p; + return this; + }; + + this.description = function ( p ){ + if ( !arguments.length ) return description; + description = p; + return this; + }; + + this.equivalents = function ( p ){ + if ( !arguments.length ) return equivalents; + equivalents = p || []; + return this; + }; + + this.equivalentBase = function ( p ){ + if ( !arguments.length ) return equivalentBase; + equivalentBase = p; + return this; + }; + + this.focused = function ( p ){ + if ( !arguments.length ) return focused; + focused = p; + return this; + }; + + this.id = function ( p ){ + if ( !arguments.length ) return id; + id = p; + return this; + }; + + this.indications = function ( p ){ + if ( !arguments.length ) return indications; + indications = p; + return this; + }; + + this.iri = function ( p ){ + if ( !arguments.length ) return iri; + iri = p; + return this; + }; + + this.label = function ( p ){ + if ( !arguments.length ) return label; + label = p; + return this; + }; + + this.mouseEntered = function ( p ){ + if ( !arguments.length ) return mouseEntered; + mouseEntered = p; + return this; + }; + + this.styleClass = function ( p ){ + if ( !arguments.length ) return styleClass; + styleClass = p; + return this; + }; + + this.type = function ( p ){ + if ( !arguments.length ) return type; + type = p; + return this; + }; + + this.visible = function ( p ){ + if ( !arguments.length ) return visible; + visible = p; + return this; + }; + + this.visualAttributes = function ( p ){ + if ( !arguments.length ) return visualAttributes; + visualAttributes = p; + return this; + }; + + + this.commentForCurrentLanguage = function (){ + return languageTools.textInLanguage(this.comment(), graph.language()); + }; + + /** + * @returns {string} the css class of this node.. + */ + this.cssClassOfNode = function (){ + return "node" + this.id(); + }; + + this.descriptionForCurrentLanguage = function (){ + return languageTools.textInLanguage(this.description(), graph.language()); + }; + + this.defaultLabel = function (){ + return languageTools.textInLanguage(this.label(), "default"); + }; + + this.indicationString = function (){ + return this.indications().join(", "); + }; + + this.labelForCurrentLanguage = function (){ + var preferredLanguage = graph && graph.language ? graph.language() : null; + return languageTools.textInLanguage(this.label(), preferredLanguage); + }; + }; + + Base.prototype.constructor = Base; + + Base.prototype.equals = function ( other ){ + return other instanceof Base && this.id() === other.id(); + }; + + Base.prototype.toString = function (){ + return this.labelForCurrentLanguage() + " (" + this.type() + ")"; + }; + + + return Base; + }()); + + +/***/ }), +/* 11 */ +/***/ (function(module, exports, __webpack_require__) { + + var constants = __webpack_require__(12)(); + + /** + * Encapsulates methods which return a label in a specific language for a preferred language. + */ + module.exports = (function (){ + + var languageTools = {}; + + + languageTools.textInLanguage = function ( textObject, preferredLanguage ){ + if ( typeof textObject === "undefined" ) { + return undefined; + } + + if ( typeof textObject === "string" ) { + return textObject; + } + + if ( preferredLanguage && textObject.hasOwnProperty(preferredLanguage) ) { + return textObject[preferredLanguage]; + } + + var textForLanguage = searchLanguage(textObject, "en"); + if ( textForLanguage ) { + return textForLanguage; + } + textForLanguage = searchLanguage(textObject, constants.LANG_UNDEFINED); + if ( textForLanguage ) { + return textForLanguage; + } + + return textObject[constants.LANG_IRIBASED]; + }; + + + function searchLanguage( textObject, preferredLanguage ){ + for ( var language in textObject ) { + if ( language === preferredLanguage && textObject.hasOwnProperty(language) ) { + return textObject[language]; + } + } + } + + return function (){ + /* Use a function here to keep a consistent style like webvowl.path.to.module() + * despite having just a single languageTools object. */ + return languageTools; + }; + })(); + + +/***/ }), +/* 12 */ +/***/ (function(module, exports) { + + module.exports = (function (){ + + var constants = {}; + + constants.LANG_IRIBASED = "IRI-based"; + constants.LANG_UNDEFINED = "undefined"; + + return function (){ + /* Use a function here to keep a consistent style like webvowl.path.to.module() + * despite having just a single object. */ + return constants; + }; + })(); + + +/***/ }), +/* 13 */ +/***/ (function(module, exports) { + + /** + * The functions for controlling attributes of nodes of the force layout can't be modelled to the element hierarchy, + * which is used for inheriting visual and OWL-like attributes. + * + * To reduce code redundancy the common functions for controlling the force layout node attributes are excluded into this + * module, which can add them to the node objects. + * + * @type {{}} + */ + var nodeFunctions = {}; + module.exports = function (){ + return nodeFunctions; + }; + + + nodeFunctions.addTo = function ( node ){ + addFixedLocationFunctions(node); + }; + + function addFixedLocationFunctions( node ){ + var locked = false, + frozen = false, + halo = false, + pinned = false; + + node.locked = function ( p ){ + if ( !arguments.length ) { + return locked; + } + locked = p; + applyFixedLocationAttributes(); + return node; + }; + + node.frozen = function ( p ){ + if ( !arguments.length ) { + return frozen; + } + frozen = p; + applyFixedLocationAttributes(); + return node; + }; + + node.halo = function ( p ){ + if ( !arguments.length ) { + return halo; + } + halo = p; + applyFixedLocationAttributes(); + return node; + }; + + node.pinned = function ( p ){ + if ( !arguments.length ) { + return pinned; + } + pinned = p; + applyFixedLocationAttributes(); + return node; + }; + + function applyFixedLocationAttributes(){ + if ( node.locked() || node.frozen() || node.pinned() ) { + node.fixed = true; + } else { + node.fixed = false; + } + } + } + + +/***/ }), +/* 14 */ +/***/ (function(module, exports, __webpack_require__) { + + var textTools = __webpack_require__(15)(); + var AbstractTextElement = __webpack_require__(16); + + module.exports = CenteringTextElement; + function CenteringTextElement( container, backgroundColor ){ + AbstractTextElement.apply(this, arguments); + this.storedFullTextLines = []; + this.storedSpanArrays = []; + this.storedStyle = []; + + } + + CenteringTextElement.prototype = Object.create(AbstractTextElement.prototype); + CenteringTextElement.prototype.constructor = CenteringTextElement; + + CenteringTextElement.prototype.addText = function ( text, prefix, suffix ){ + if ( text ) { + this.addTextline(text, this.CSS_CLASSES.default, prefix, suffix); + } + }; + + CenteringTextElement.prototype.addSubText = function ( text ){ + if ( text ) { + this.addTextline(text, this.CSS_CLASSES.subtext, "(", ")"); + } + }; + + CenteringTextElement.prototype.addEquivalents = function ( text ){ + if ( text ) { + this.addTextline(text, this.CSS_CLASSES.default); + } + }; + + CenteringTextElement.prototype.addInstanceCount = function ( instanceCount ){ + if ( instanceCount ) { + this.addTextline(instanceCount.toString(), this.CSS_CLASSES.instanceCount); + } + }; + CenteringTextElement.prototype.saveCorrespondingSpan = function ( correspondingSpan ){ + this.storedSpanArrays.push(correspondingSpan); + }; + CenteringTextElement.prototype.saveFullTextLine = function ( fullText ){ + this.storedFullTextLines.push(fullText); + }; + CenteringTextElement.prototype.saveStyle = function ( style ){ + this.storedStyle.push(style); + }; + + CenteringTextElement.prototype.updateAllTextElements = function (){ + // TODO : TEST THIS postPrefix >>> _applyPreAndPostFix + for ( var i = 0; i < this.storedSpanArrays.length; i++ ) { + var truncatedText = textTools.truncate(this.storedFullTextLines[i], this._textBlock().datum().textWidth(), this.storedStyle[i]); + this.storedSpanArrays[i].text(truncatedText); + } + }; + + + CenteringTextElement.prototype.addTextline = function ( text, style, prefix, postfix ){ + var truncatedText = textTools.truncate(text, this._textBlock().datum().textWidth(), style); + this.saveFullTextLine(text); + this.saveStyle(style); + var tspan = this._textBlock().append("tspan") + .classed(this.CSS_CLASSES.default, true) + .classed(style, true) + .text(this._applyPreAndPostFix(truncatedText, prefix, postfix)) + .attr("x", 0); + this._repositionTextLine(tspan); + this.saveCorrespondingSpan(tspan); + + this._repositionTextBlock(); + }; + + CenteringTextElement.prototype._repositionTextLine = function ( tspan ){ + var fontSizeProperty = window.getComputedStyle(tspan.node()).getPropertyValue("font-size"); + var fontSize = parseFloat(fontSizeProperty); + + var siblingCount = this._lineCount() - 1; + var lineDistance = siblingCount > 0 ? this.LINE_DISTANCE : 0; + + tspan.attr("dy", fontSize + lineDistance + "px"); + }; + + CenteringTextElement.prototype.getTextBox = function (){ + return this._textBlock(); + }; + + + CenteringTextElement.prototype._repositionTextBlock = function (){ + // Nothing to do if no child elements exist + var lineCount = this._lineCount(); + if ( lineCount < 1 ) { + this._textBlock().attr("y", 0); + return; + } + + var textBlockHeight = this._textBlock().node().getBBox().height; + this._textBlock().attr("y", -textBlockHeight * 0.5 + "px"); + }; + + CenteringTextElement.prototype._lineCount = function (){ + return this._textBlock().property("childElementCount"); + }; + + +/***/ }), +/* 15 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var ADDITIONAL_TEXT_SPACE = 4; + + var tools = {}; + + function measureTextWidth( text, textStyle ){ + // Set a default value + if ( !textStyle ) { + textStyle = "text"; + } + var d = d3.select("body") + .append("div") + .attr("class", textStyle) + .attr("id", "width-test") // tag this element to identify it + .attr("style", "position:absolute; float:left; white-space:nowrap; visibility:hidden;") + .text(text), + w = document.getElementById("width-test").offsetWidth; + d.remove(); + return w; + } + + tools.truncate = function ( text, maxWidth, textStyle, additionalTextSpace ){ + maxWidth -= isNaN(additionalTextSpace) ? ADDITIONAL_TEXT_SPACE : additionalTextSpace; + if ( isNaN(maxWidth) || maxWidth <= 0 ) { + return text; + } + + var truncatedText = text, + newTruncatedTextLength, + textWidth, + ratio; + + while ( true ) { + textWidth = measureTextWidth(truncatedText, textStyle); + if ( textWidth <= maxWidth ) { + break; + } + + ratio = textWidth / maxWidth; + newTruncatedTextLength = Math.floor(truncatedText.length / ratio); + + // detect if nothing changes + if ( truncatedText.length === newTruncatedTextLength ) { + break; + } + + truncatedText = truncatedText.substring(0, newTruncatedTextLength); + } + + if ( text.length > truncatedText.length ) { + return text.substring(0, truncatedText.length - 3) + "..."; + } + return text; + }; + + + module.exports = function (){ + return tools; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 16 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = AbstractTextElement; + + function AbstractTextElement( container, backgroundColor ){ + var textBlock = container.append("text") + .classed("text", true) + .style("fill", this._getTextColor(backgroundColor)) + .attr("text-anchor", "middle"); + + this._textBlock = function (){ + return textBlock; + }; + } + + AbstractTextElement.prototype.LINE_DISTANCE = 1; + AbstractTextElement.prototype.CSS_CLASSES = { + default: "text", + subtext: "subtext", + instanceCount: "instance-count" + }; + AbstractTextElement.prototype.DARK_TEXT_COLOR = "#000"; + AbstractTextElement.prototype.LIGHT_TEXT_COLOR = "#fff"; + + AbstractTextElement.prototype.translation = function ( x, y ){ + this._textBlock().attr("transform", "translate(" + x + ", " + y + ")"); + return this; + }; + + AbstractTextElement.prototype.remove = function (){ + this._textBlock().remove(); + return this; + }; + + AbstractTextElement.prototype._applyPreAndPostFix = function ( text, prefix, postfix ){ + if ( prefix ) { + text = prefix + text; + } + if ( postfix ) { + text += postfix; + } + return text; + }; + + AbstractTextElement.prototype._getTextColor = function ( rawBackgroundColor ){ + if ( !rawBackgroundColor ) { + return AbstractTextElement.prototype.DARK_TEXT_COLOR; + } + + var backgroundColor = d3.rgb(rawBackgroundColor); + if ( calculateLuminance(backgroundColor) > 0.5 ) { + return AbstractTextElement.prototype.DARK_TEXT_COLOR; + } else { + return AbstractTextElement.prototype.LIGHT_TEXT_COLOR; + } + }; + + function calculateLuminance( color ){ + return 0.3 * (color.r / 255) + 0.59 * (color.g / 255) + 0.11 * (color.b / 255); + } + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 17 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains reusable function for drawing nodes. + */ + module.exports = (function (){ + + var tools = {}; + + /** + * Append a circular class node with the passed attributes. + * @param parent the parent element to which the circle will be appended + * @param radius + * @param [cssClasses] an array of additional css classes + * @param [tooltip] + * @param [backgroundColor] + * @returns {*} + */ + tools.appendCircularClass = function ( parent, radius, cssClasses, tooltip, backgroundColor ){ + var circle = parent.append("circle") + .classed("class", true) + .attr("r", radius); + + addCssClasses(circle, cssClasses); + addToolTip(circle, tooltip); + addBackgroundColor(circle, backgroundColor); + + return circle; + }; + + function addCssClasses( element, cssClasses ){ + if ( cssClasses instanceof Array ) { + cssClasses.forEach(function ( cssClass ){ + element.classed(cssClass, true); + }); + } + } + + function addToolTip( element, tooltip ){ + if ( tooltip ) { + element.append("title").text(tooltip); + } + } + + function addBackgroundColor( element, backgroundColor ){ + if ( backgroundColor ) { + element.style("fill", backgroundColor); + } + } + + /** + * Appends a rectangular class node with the passed attributes. + * @param parent the parent element to which the rectangle will be appended + * @param width + * @param height + * @param [cssClasses] an array of additional css classes + * @param [tooltip] + * @param [backgroundColor] + * @returns {*} + */ + tools.appendRectangularClass = function ( parent, width, height, cssClasses, tooltip, backgroundColor ){ + var rectangle = parent.append("rect") + .classed("class", true) + .attr("x", -width / 2) + .attr("y", -height / 2) + .attr("width", width) + .attr("height", height); + + addCssClasses(rectangle, cssClasses); + addToolTip(rectangle, tooltip); + addBackgroundColor(rectangle, backgroundColor); + + return rectangle; + }; + + tools.drawPin = function ( container, dx, dy, onClick, accuraciesHelperFunction, useAccuracyHelper ){ + var pinGroupElement = container + .append("g") + .classed("hidden-in-export", true) + .attr("transform", "translate(" + dx + "," + dy + ")"); + + var base = pinGroupElement.append("circle") + .classed("class pin feature", true) + .attr("r", 12) + .on("click", function (){ + if ( onClick ) { + onClick(); + } + d3.event.stopPropagation(); + }); + + pinGroupElement.append("line") + .attr("x1", 0) + .attr("x2", 0) + .attr("y1", 12) + .attr("y2", 16); + + if ( useAccuracyHelper === true ) { + pinGroupElement.append("circle") + .attr("r", 15) + .attr("cx", -7) + .attr("cy", -7) + .classed("superHiddenElement ", true) + .classed("superOpacityElement", !accuraciesHelperFunction()) + .on("click", function (){ + if ( onClick ) { + onClick(); + } + d3.event.stopPropagation(); + }) + .on("mouseover", function (){ + base.classed("feature_hover", true); + }) + .on("mouseout", function (){ + base.classed("feature_hover", false); + }) + ; + + } + + + return pinGroupElement; + }; + + tools.drawRectHalo = function ( node, width, height, offset ){ + var container; + if ( node.nodeElement ) + container = node.nodeElement(); + else + container = node.labelElement(); + + if ( !container ) { + // console.log("no container found"); + return; + } + + var haloGroupElement = container + .append("g") + .classed("hidden-in-export", true); + + haloGroupElement.append("rect") + .classed("searchResultA", true) + .attr("x", (-width - offset) / 2) + .attr("y", (-offset - height) / 2) + .attr("width", width + offset) + .attr("height", height + offset); + haloGroupElement.attr("animationRunning", true); + + haloGroupElement.node().addEventListener("webkitAnimationEnd", function (){ + var test = haloGroupElement.selectAll(".searchResultA"); + test.classed("searchResultA", false) + .classed("searchResultB", true); + haloGroupElement.attr("animationRunning", false); + }); + haloGroupElement.node().addEventListener("animationend", function (){ + var test = haloGroupElement.selectAll(".searchResultA"); + test.classed("searchResultA", false) + .classed("searchResultB", true); + haloGroupElement.attr("animationRunning", false); + }); + + + return haloGroupElement; + + }; + tools.drawHalo = function ( container, radius ){ + if ( container === undefined ) { + return null; + // there is no element to add the halo to; + // this means the node was not rendered previously + } + + var haloGroupElement = container + .append("g") + .classed("hidden-in-export", true); + + + haloGroupElement.append("circle", ":first-child") + .classed("searchResultA", true) + .attr("r", radius + 15); + haloGroupElement.attr("animationRunning", true); + + + haloGroupElement.node().addEventListener("webkitAnimationEnd", function (){ + var test = haloGroupElement.selectAll(".searchResultA"); + test.classed("searchResultA", false) + .classed("searchResultB", true) + .attr("animationRunning", false); + haloGroupElement.attr("animationRunning", false); + }); + haloGroupElement.node().addEventListener("animationend", function (){ + var test = haloGroupElement.selectAll(".searchResultA"); + test.classed("searchResultA", false) + .classed("searchResultB", true) + .attr("animationRunning", false); + haloGroupElement.attr("animationRunning", false); + }); + + return haloGroupElement; + }; + + return function (){ + // Encapsulate into function to maintain default.module.path() + return tools; + }; + })(); + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 18 */ +/***/ (function(module, exports, __webpack_require__) { + + var RoundNode = __webpack_require__(8); + + module.exports = (function (){ + + var o = function ( graph ){ + RoundNode.apply(this, arguments); + + this.type("owl:Class"); + }; + o.prototype = Object.create(RoundNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 19 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetOperatorNode = __webpack_require__(20); + + module.exports = (function (){ + + var o = function ( graph ){ + SetOperatorNode.apply(this, arguments); + + var that = this, + superDrawFunction = that.draw; + + this.styleClass("complementof") + .type("owl:complementOf"); + + this.draw = function ( element ){ + superDrawFunction(element); + + var symbol = element.append("g").classed("embedded", true); + + symbol.append("circle") + .attr("class", "symbol") + .classed("fineline", true) + .attr("r", 10); + symbol.append("path") + .attr("class", "nofill") + .attr("d", "m -7,-1.5 12,0 0,6") + .attr("transform", "scale(.5)"); + + symbol.attr("transform", + "translate(-" + (that.radius() - 15) / 100 + ",-" + (that.radius() - 15) / 100 + ")"); + + that.postDrawActions(); + }; + }; + o.prototype = Object.create(SetOperatorNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 20 */ +/***/ (function(module, exports, __webpack_require__) { + + var AbsoluteTextElement = __webpack_require__(21); + var BoxArrowLink = __webpack_require__(22); + var RoundNode = __webpack_require__(8); + var drawTools = __webpack_require__(17)(); + + module.exports = (function (){ + + var o = function ( graph ){ + RoundNode.apply(this, arguments); + + var that = this, + superHoverHighlightingFunction = that.setHoverHighlighting, + superPostDrawActions = that.postDrawActions; + + this.setHoverHighlighting = function ( enable ){ + superHoverHighlightingFunction(enable); + + // Highlight links pointing to included nodes when hovering the set operator + that.links() + .filter(function ( link ){ + return link instanceof BoxArrowLink; + }) + .filter(function ( link ){ + return link.domain().equals(that); + }) + .forEach(function ( link ){ + link.property().setHighlighting(enable); + }); + }; + + this.draw = function ( element ){ + that.nodeElement(element); + + drawTools.appendCircularClass(element, that.actualRadius(), + that.collectCssClasses().join(" "), + that.labelForCurrentLanguage(), that.backgroundColor()); + }; + + this.postDrawActions = function (){ + superPostDrawActions(); + that.textBlock().remove(); + + var textElement = new AbsoluteTextElement(that.nodeElement(), that.backgroundColor()); + + var equivalentsString = that.equivalentsString(); + var offsetForFollowingEquivalents = equivalentsString ? -30 : -17; + var suffixForFollowingEquivalents = equivalentsString ? "," : ""; + textElement.addText(that.labelForCurrentLanguage(), offsetForFollowingEquivalents, "", + suffixForFollowingEquivalents); + + textElement.addEquivalents(equivalentsString, -17); + + + if ( !graph.options().compactNotation() ) { + + if ( that.indicationString().length > 0 ) { + textElement.addSubText(that.indicationString(), 17); + textElement.addInstanceCount(that.individuals().length, 30); + } else { + textElement.addInstanceCount(that.individuals().length, 17); + } + } else { + textElement.addInstanceCount(that.individuals().length, 17); + } + + that.textBlock(textElement); + }; + }; + o.prototype = Object.create(RoundNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 21 */ +/***/ (function(module, exports, __webpack_require__) { + + var textTools = __webpack_require__(15)(); + var AbstractTextElement = __webpack_require__(16); + + module.exports = AbsoluteTextElement; + function AbsoluteTextElement( container, backgroundColor ){ + AbstractTextElement.apply(this, arguments); + } + + AbsoluteTextElement.prototype = Object.create(AbstractTextElement.prototype); + AbsoluteTextElement.prototype.constructor = AbsoluteTextElement; + + AbsoluteTextElement.prototype.addText = function ( text, yShift, prefix, suffix ){ + if ( text ) { + this.addTextline(text, this.CSS_CLASSES.default, yShift, prefix, suffix); + } + }; + + AbsoluteTextElement.prototype.addSubText = function ( text, yShift ){ + if ( text ) { + this.addTextline(text, this.CSS_CLASSES.subtext, yShift, "(", ")"); + } + }; + + AbsoluteTextElement.prototype.addEquivalents = function ( text, yShift ){ + if ( text ) { + this.addTextline(text, this.CSS_CLASSES.default, yShift); + } + }; + + AbsoluteTextElement.prototype.addInstanceCount = function ( instanceCount, yShift ){ + if ( instanceCount ) { + this.addTextline(instanceCount.toString(), this.CSS_CLASSES.instanceCount, yShift); + } + }; + + + AbsoluteTextElement.prototype.addTextline = function ( text, style, yShift, prefix, postfix ){ + var truncatedText = textTools.truncate(text, this._textBlock().datum().textWidth(yShift), style); + + var tspan = this._textBlock().append("tspan") + .classed(this.CSS_CLASSES.default, true) + .classed(style, true) + .text(this._applyPreAndPostFix(truncatedText, prefix, postfix)) + .attr("x", 0); + this._repositionTextLine(tspan, yShift); + }; + + AbsoluteTextElement.prototype._repositionTextLine = function ( tspan, yShift ){ + var fontSizeProperty = window.getComputedStyle(tspan.node()).getPropertyValue("font-size"); + var fontSize = parseFloat(fontSizeProperty); + + /* BBox height is not supported in Firefox for tspans and dominant-baseline doesn't work in some SVG editors */ + var approximatedShiftForVerticalCentering = (1 / 3) * fontSize; + + tspan.attr("y", approximatedShiftForVerticalCentering + (yShift || 0) + "px"); + }; + + +/***/ }), +/* 22 */ +/***/ (function(module, exports, __webpack_require__) { + + var PlainLink = __webpack_require__(23); + + + module.exports = BoxArrowLink; + + function BoxArrowLink( domain, range, property ){ + PlainLink.apply(this, arguments); + } + + BoxArrowLink.prototype = Object.create(PlainLink.prototype); + BoxArrowLink.prototype.constructor = BoxArrowLink; + + + BoxArrowLink.prototype.draw = function ( linkGroup, markerContainer ){ + var property = this.label().property(); + var inverse = this.label().inverse(); + + createPropertyMarker(markerContainer, property); + if ( inverse ) { + createInverseMarker(markerContainer, inverse); + } + + PlainLink.prototype.draw.apply(this, arguments); + + // attach the markers to the link + linkGroup.attr("marker-start", "url(#" + property.markerId() + ")"); + if ( inverse ) { + linkGroup.attr("marker-end", "url(#" + inverse.markerId() + ")"); + } + }; + + + function createPropertyMarker( markerContainer, inverse ){ + var inverseMarker = appendBasicMarker(markerContainer, inverse); + inverseMarker.attr("refX", -8); + inverseMarker.append("path") + .attr("d", "M0,-8L8,0L0,8L-8,0L0,-8L8,0") + .classed(inverse.markerType(), true); + + inverse.markerElement(inverseMarker); + } + + function createInverseMarker( markerContainer, property ){ + var marker = appendBasicMarker(markerContainer, property); + marker.attr("refX", 8); + marker.append("path") + .attr("d", "M0,-8L8,0L0,8L-8,0L0,-8L8,0") + .classed(property.markerType(), true); + + property.markerElement(marker); + } + + function appendBasicMarker( markerContainer, property ){ + return markerContainer.append("marker") + .datum(property) + .attr("id", property.markerId()) + .attr("viewBox", "-10 -10 20 20") + .attr("markerWidth", 20) + .attr("markerHeight", 20) + .attr("markerUnits", "userSpaceOnUse") + .attr("orient", "auto"); + } + + +/***/ }), +/* 23 */ +/***/ (function(module, exports, __webpack_require__) { + + var Label = __webpack_require__(24); + + + module.exports = PlainLink; + + /** + * A link connects at least two VOWL nodes. + * The properties connecting the VOWL nodes are stored separately into the label. + * @param domain + * @param range + * @param property + */ + function PlainLink( domain, range, property ){ + var layers, + layerIndex, + loops, + loopIndex, + pathEl, + label = new Label(property, this); + + var backPart = __webpack_require__(25)(domain, label, this), + frontPart = __webpack_require__(25)(label, range, this); + + + this.layers = function ( p ){ + if ( !arguments.length ) return layers; + layers = p; + return this; + }; + + this.layerIndex = function ( p ){ + if ( !arguments.length ) return layerIndex; + layerIndex = p; + return this; + }; + + this.loops = function ( p ){ + if ( !arguments.length ) return loops; + loops = p; + return this; + }; + + this.loopIndex = function ( p ){ + if ( !arguments.length ) return loopIndex; + loopIndex = p; + return this; + }; + + + this.domain = function (){ + return domain; + }; + + this.label = function (){ + return label; + }; + + this.linkParts = function (){ + return [frontPart, backPart]; + }; + + this.range = function (){ + return range; + }; + this.pathObj = function ( pE ){ + if ( !arguments.length ) { + return pathEl; + } + pathEl = pE; + }; + } + + + PlainLink.prototype.draw = function ( linkGroup ){ + var property = this.label().property(); + var inverse = this.label().inverse(); + + property.linkGroup(linkGroup); + if ( inverse ) { + inverse.linkGroup(linkGroup); + } + + var pathElement = linkGroup.append("path"); + pathElement.classed("link-path", true) + .classed(this.domain().cssClassOfNode(), true) + .classed(this.range().cssClassOfNode(), true) + .classed(property.linkType(), true); + this.pathObj(pathElement); + + }; + + + PlainLink.prototype.inverse = function (){ + return this.label().inverse(); + }; + + PlainLink.prototype.isLoop = function (){ + return this.domain().equals(this.range()); + }; + + PlainLink.prototype.property = function (){ + return this.label().property(); + }; + + + +/***/ }), +/* 24 */ +/***/ (function(module, exports) { + + module.exports = Label; + + /** + * A label represents the element(s) which further describe a link. + * It encapsulates the property and its inverse property. + * @param property the property; the inverse is inferred + * @param link the link this label belongs to + */ + function Label( property, link ){ + this.link = function (){ + return link; + }; + + this.property = function (){ + return property; + }; + + // "Forward" the fixed value set on the property to avoid having to access this container + Object.defineProperty(this, "fixed", { + get: function (){ + var inverseFixed = property.inverse() ? property.inverse().fixed : false; + return property.fixed || inverseFixed; + }, + set: function ( v ){ + property.fixed = v; + if ( property.inverse() ) property.inverse().fixed = v; + } + }); + this.frozen = property.frozen; + this.locked = property.locked; + this.pinned = property.pinned; + } + + Label.prototype.actualRadius = function (){ + return this.property().actualRadius(); + }; + + Label.prototype.draw = function ( container ){ + return this.property().draw(container); + }; + + Label.prototype.inverse = function (){ + return this.property().inverse(); + }; + + Label.prototype.equals = function ( other ){ + if ( !other ) { + return false; + } + + var instance = other instanceof Label; + var equalProperty = this.property().equals(other.property()); + + var equalInverse = false; + if ( this.inverse() ) { + equalInverse = this.inverse().equals(other.inverse()); + } else if ( !other.inverse() ) { + equalInverse = true; + } + + return instance && equalProperty && equalInverse; + }; + + +/***/ }), +/* 25 */ +/***/ (function(module, exports) { + + /** + * A linkPart connects two force layout nodes. + * It reprents a link which can be used in d3's force layout. + * @param _domain + * @param _range + * @param _link + */ + module.exports = function ( _domain, _range, _link ){ + var linkPart = {}, + domain = _domain, + link = _link, + range = _range; + + // Define d3 properties + Object.defineProperties(linkPart, { + "source": { value: domain, writable: true }, + "target": { value: range, writable: true } + }); + + + linkPart.domain = function (){ + return domain; + }; + + linkPart.link = function (){ + return link; + }; + + linkPart.range = function (){ + return range; + }; + + + return linkPart; + }; + + +/***/ }), +/* 26 */ +/***/ (function(module, exports, __webpack_require__) { + + var RoundNode = __webpack_require__(8); + + module.exports = (function (){ + + var o = function ( graph ){ + RoundNode.apply(this, arguments); + + this.attributes(["deprecated"]) + .type("owl:DeprecatedClass") + .styleClass("deprecated") + .indications(["deprecated"]); + }; + o.prototype = Object.create(RoundNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 27 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetOperatorNode = __webpack_require__(20); + + module.exports = (function (){ + + var o = function ( graph ){ + SetOperatorNode.apply(this, arguments); + + var that = this, + superDrawFunction = that.draw; + + this.styleClass("disjointunionof") + .type("owl:disjointUnionOf"); + + this.draw = function ( element ){ + superDrawFunction(element); + + var symbol = element.append("g").classed("embedded", true); + + var symbolRadius = 10; + symbol.append("circle") + .attr("class", "symbol") + .attr("r", symbolRadius); + symbol.append("circle") + .attr("cx", 10) + .attr("class", "symbol") + .classed("fineline", true) + .attr("r", symbolRadius); + symbol.append("circle") + .attr("class", "nofill") + .classed("fineline", true) + .attr("r", symbolRadius); + symbol.append("text") + .attr("class", "link") + .text("1") + .attr("transform", "scale(.7)translate(3,5)"); + + symbol.attr("transform", "translate(-" + (that.radius() - 15) / 7 + ",-" + (that.radius() - 15) / 100 + ")"); + + that.postDrawActions(); + }; + }; + o.prototype = Object.create(SetOperatorNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 28 */ +/***/ (function(module, exports, __webpack_require__) { + + var RoundNode = __webpack_require__(8); + var drawTools = __webpack_require__(17)(); + + module.exports = (function (){ + + var o = function ( graph ){ + RoundNode.apply(this, arguments); + + var CIRCLE_SIZE_DIFFERENCE = 4; + var renderingElement; + var that = this, + superActualRadiusFunction = that.actualRadius; + + this.styleClass("equivalentclass") + .type("owl:equivalentClass"); + + this.actualRadius = function (){ + return superActualRadiusFunction() + CIRCLE_SIZE_DIFFERENCE; + }; + + this.redrawElement = function (){ + renderingElement.remove(); + that.textBlock().remove(); + var bgColor = that.backgroundColor(); + + if ( that.attributes().indexOf("deprecated") > -1 ) { + bgColor = undefined; + } + var cssClasses = that.collectCssClasses(); + renderingElement = that.nodeElement().append("g"); + + if ( that.getRectangularRepresentation() === true ) { + drawTools.appendRectangularClass(renderingElement, 84, 84, ["white", "embedded"]); + drawTools.appendRectangularClass(renderingElement, 80 - CIRCLE_SIZE_DIFFERENCE, 80 - CIRCLE_SIZE_DIFFERENCE, cssClasses, that.labelForCurrentLanguage(), bgColor); + } else { + drawTools.appendCircularClass(renderingElement, that.actualRadius(), ["white", "embedded"]); + console.log(cssClasses); + console.log(that.attributes()); + console.log("what is bgColor" + bgColor); + drawTools.appendCircularClass(renderingElement, that.actualRadius() - CIRCLE_SIZE_DIFFERENCE, cssClasses, that.labelForCurrentLanguage(), bgColor); + + } + that.postDrawActions(that.nodeElement()); + + }; + this.draw = function ( parentElement ){ + var cssClasses = that.collectCssClasses(); + + that.nodeElement(parentElement); + renderingElement = parentElement.append("g"); + var bgColor = that.backgroundColor(); + if ( that.attributes().indexOf("deprecated") > -1 ) { + bgColor = undefined; + } + // draw the outer circle at first and afterwards the inner circle + if ( that.getRectangularRepresentation() === true ) { + drawTools.appendRectangularClass(renderingElement, 84, 84, ["white", "embedded"]); + drawTools.appendRectangularClass(renderingElement, 80 - CIRCLE_SIZE_DIFFERENCE, 80 - CIRCLE_SIZE_DIFFERENCE, cssClasses, that.labelForCurrentLanguage(), bgColor); + } else { + drawTools.appendCircularClass(renderingElement, that.actualRadius(), ["white", "embedded"]); + drawTools.appendCircularClass(renderingElement, that.actualRadius() - CIRCLE_SIZE_DIFFERENCE, cssClasses, that.labelForCurrentLanguage(), bgColor); + + } + + that.postDrawActions(); + }; + + /** + * Sets the hover highlighting of this node. + * @param enable + */ + that.setHoverHighlighting = function ( enable ){ + that.nodeElement().selectAll("circle:last-of-type").classed("hovered", enable); + }; + }; + o.prototype = Object.create(RoundNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 29 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetOperatorNode = __webpack_require__(20); + + module.exports = (function (){ + + var o = function ( graph ){ + SetOperatorNode.apply(this, arguments); + + var that = this, + superDrawFunction = that.draw, + INTERSECTION_BACKGROUND_PATH = createIntersectionPath(); + + this.styleClass("intersectionof") + .type("owl:intersectionOf"); + + this.draw = function ( element ){ + superDrawFunction(element); + + var symbol = element.append("g").classed("embedded", true); + + var symbolRadius = 10; + symbol.append("path") + .attr("class", "nostroke") + .classed("symbol", true) + .attr("d", INTERSECTION_BACKGROUND_PATH); + symbol.append("circle") + .attr("class", "nofill") + .classed("fineline", true) + .attr("r", symbolRadius); + symbol.append("circle") + .attr("cx", 10) + .attr("class", "nofill") + .classed("fineline", true) + .attr("r", symbolRadius); + symbol.append("path") + .attr("class", "nofill") + .attr("d", "m 9,5 c 0,-2 0,-4 0,-6 0,0 0,0 0,0 0,0 0,-1.8 -1,-2.3 -0.7,-0.6 -1.7,-0.8 -2.9," + + "-0.8 -1.2,0 -2,0 -3,0.8 -0.7,0.5 -1,1.4 -1,2.3 0,2 0,4 0,6") + .attr("transform", "scale(.5)translate(5,0)"); + + symbol.attr("transform", + "translate(-" + (that.radius() - 15) / 7 + ",-" + (that.radius() - 15) / 100 + ")"); + + that.postDrawActions(); + }; + + function createIntersectionPath(){ + var height = 18; + + var offsetX = 5; + var offsetY = -(height / 2); + + var bezierX = 7; + var bezierY = 5; + var bottomBezierY = height - bezierY; + + var startPosition = "M" + offsetX + "," + offsetY; + var rightSide = "c" + bezierX + "," + bezierY + " " + bezierX + "," + bottomBezierY + " 0," + height; + var leftSide = "c" + -bezierX + "," + -bezierY + " " + -bezierX + "," + -bottomBezierY + " 0," + -height; + + return startPosition + rightSide + leftSide; + } + }; + o.prototype = Object.create(SetOperatorNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 30 */ +/***/ (function(module, exports, __webpack_require__) { + + var OwlThing = __webpack_require__(31); + + module.exports = (function (){ + + var o = function ( graph ){ + OwlThing.apply(this, arguments); + + this.label("Nothing") + .type("owl:Nothing") + .iri("http://www.w3.org/2002/07/owl#Nothing"); + }; + o.prototype = Object.create(OwlThing.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 31 */ +/***/ (function(module, exports, __webpack_require__) { + + var RoundNode = __webpack_require__(8); + + module.exports = (function (){ + + var o = function ( graph ){ + RoundNode.apply(this, arguments); + + var superDrawFunction = this.draw; + + this.label("Thing") + .type("owl:Thing") + .iri("http://www.w3.org/2002/07/owl#Thing") + .radius(30); + + this.draw = function ( element ){ + superDrawFunction(element, ["white", "dashed"]); + }; + }; + o.prototype = Object.create(RoundNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 32 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetOperatorNode = __webpack_require__(20); + + module.exports = (function (){ + + var o = function ( graph ){ + SetOperatorNode.apply(this, arguments); + + var that = this, + superDrawFunction = that.draw; + + this.styleClass("unionof") + .type("owl:unionOf"); + + this.draw = function ( element ){ + superDrawFunction(element); + + var symbol = element.append("g").classed("embedded", true); + + var symbolRadius = 10; + symbol.append("circle") + .attr("class", "symbol") + .attr("r", symbolRadius); + symbol.append("circle") + .attr("cx", 10) + .attr("class", "symbol") + .classed("fineline", true) + .attr("r", symbolRadius); + symbol.append("circle") + .attr("class", "nofill") + .classed("fineline", true) + .attr("r", symbolRadius); + symbol.append("path") + .attr("class", "link") + .attr("d", "m 1,-3 c 0,2 0,4 0,6 0,0 0,0 0,0 0,2 2,3 4,3 2,0 4,-1 4,-3 0,-2 0,-4 0,-6") + .attr("transform", "scale(.5)translate(5,0)"); + + symbol.attr("transform", "translate(-" + (that.radius() - 15) / 7 + ",-" + (that.radius() - 15) / 100 + ")"); + + that.postDrawActions(); + }; + }; + o.prototype = Object.create(SetOperatorNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 33 */ +/***/ (function(module, exports, __webpack_require__) { + + var RoundNode = __webpack_require__(8); + + module.exports = (function (){ + + var o = function ( graph ){ + RoundNode.apply(this, arguments); + + this.attributes(["rdf"]) + .type("rdfs:Class"); + }; + o.prototype = Object.create(RoundNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 34 */ +/***/ (function(module, exports, __webpack_require__) { + + var DatatypeNode = __webpack_require__(35); + + module.exports = (function (){ + + var o = function ( graph ){ + DatatypeNode.apply(this, arguments); + var dTypeString = "undefined"; + this.attributes(["datatype"]) + .type("rdfs:Datatype") + .styleClass("datatype"); + this.dType = function ( val ){ + if ( !arguments.length ) return dTypeString; + dTypeString = val; + + }; + }; + o.prototype = Object.create(DatatypeNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 35 */ +/***/ (function(module, exports, __webpack_require__) { + + var RectangularNode = __webpack_require__(36); + + module.exports = (function (){ + + var o = function ( graph ){ + RectangularNode.apply(this, arguments); + }; + o.prototype = Object.create(RectangularNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 36 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var BaseNode = __webpack_require__(9); + var CenteringTextElement = __webpack_require__(14); + var drawTools = __webpack_require__(17)(); + var rectangularElementTools = __webpack_require__(37)(); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseNode.apply(this, arguments); + + var that = this, + height = 20, + width = 60, + pinGroupElement, + haloGroupElement, + labelWidth = 80, + myWidth = 80, + defaultWidth = 80, + shapeElement, + textBlock, + smallestRadius = height / 2; + + that.renderType("rect"); + // Properties + this.height = function ( p ){ + if ( !arguments.length ) return height; + height = p; + return this; + }; + + this.width = function ( p ){ + if ( !arguments.length ) return width; + width = p; + return this; + }; + + this.getHalos = function (){ + return haloGroupElement; + }; + + // Functions + // for compatibility reasons // TODO resolve + this.actualRadius = function (){ + return smallestRadius; + }; + + this.distanceToBorder = function ( dx, dy ){ + return rectangularElementTools.distanceToBorder(that, dx, dy); + }; + + this.setHoverHighlighting = function ( enable ){ + that.nodeElement().selectAll("rect").classed("hovered", enable); + + var haloGroup = that.getHalos(); + if ( haloGroup ) { + var test = haloGroup.selectAll(".searchResultA"); + test.classed("searchResultA", false); + test.classed("searchResultB", true); + } + + }; + + + // overwrite the labelWith; + + + this.textWidth = function (){ + return labelWidth; + }; + this.width = function (){ + return labelWidth; + }; + + this.getMyWidth = function (){ + // use a simple heuristic + var text = that.labelForCurrentLanguage(); + myWidth = measureTextWidth(text, "text") + 20; + + // check for sub names; + var indicatorText = that.indicationString(); + var indicatorWidth = measureTextWidth(indicatorText, "subtext") + 20; + if ( indicatorWidth > myWidth ) + myWidth = indicatorWidth; + + return myWidth; + }; + + this.textWidth = function (){ + return that.width(); + }; + function measureTextWidth( text, textStyle ){ + // Set a default value + if ( !textStyle ) { + textStyle = "text"; + } + var d = d3.select("body") + .append("div") + .attr("class", textStyle) + .attr("id", "width-test") // tag this element to identify it + .attr("style", "position:absolute; float:left; white-space:nowrap; visibility:hidden;") + .text(text), + w = document.getElementById("width-test").offsetWidth; + d.remove(); + return w; + } + + this.toggleFocus = function (){ + that.focused(!that.focused()); + that.nodeElement().select("rect").classed("focused", that.focused()); + graph.resetSearchHighlight(); + graph.options().searchMenu().clearText(); + }; + + /** + * Draws the rectangular node. + * @param parentElement the element to which this node will be appended + * @param [additionalCssClasses] additional css classes + */ + this.draw = function ( parentElement, additionalCssClasses ){ + var cssClasses = that.collectCssClasses(); + + that.nodeElement(parentElement); + + if ( additionalCssClasses instanceof Array ) { + cssClasses = cssClasses.concat(additionalCssClasses); + } + + // set the value for that.width() + // update labelWidth Value; + if ( graph.options().dynamicLabelWidth() === true ) labelWidth = Math.min(that.getMyWidth(), graph.options().maxLabelWidth()); + else labelWidth = defaultWidth; + + width = labelWidth; + shapeElement = drawTools.appendRectangularClass(parentElement, that.width(), that.height(), cssClasses, that.labelForCurrentLanguage(), that.backgroundColor()); + + textBlock = new CenteringTextElement(parentElement, that.backgroundColor()); + textBlock.addText(that.labelForCurrentLanguage()); + + that.addMouseListeners(); + + if ( that.pinned() ) { + that.drawPin(); + } + if ( that.halo() ) { + that.drawHalo(false); + } + }; + + this.drawPin = function (){ + that.pinned(true); + // if (graph.options().dynamicLabelWidth()===true) labelWidth=that.getMyWidth(); + // else labelWidth=defaultWidth; + // width=labelWidth; + // console.log("this element label Width is "+labelWidth); + var dx = -0.5 * labelWidth + 5, + dy = -1.1 * height; + + pinGroupElement = drawTools.drawPin(that.nodeElement(), dx, dy, this.removePin, graph.options().showDraggerObject, graph.options().useAccuracyHelper()); + + }; + + this.removePin = function (){ + that.pinned(false); + if ( pinGroupElement ) { + pinGroupElement.remove(); + } + graph.updateStyle(); + }; + + this.removeHalo = function (){ + that.halo(false); + if ( haloGroupElement ) { + haloGroupElement.remove(); + haloGroupElement = null; + } + }; + + this.drawHalo = function ( pulseAnimation ){ + that.halo(true); + + var offset = 0; + haloGroupElement = drawTools.drawRectHalo(that, this.width(), this.height(), offset); + + if ( pulseAnimation === false ) { + var pulseItem = haloGroupElement.selectAll(".searchResultA"); + pulseItem.classed("searchResultA", false); + pulseItem.classed("searchResultB", true); + pulseItem.attr("animationRunning", false); + } + + if ( that.pinned() ) { + var selectedNode = pinGroupElement.node(); + var nodeContainer = selectedNode.parentNode; + nodeContainer.appendChild(selectedNode); + } + + }; + + this.updateTextElement = function (){ + textBlock.updateAllTextElements(); + + }; + + this.textBlock = function (){ + return textBlock; + }; + + this.redrawLabelText = function (){ + textBlock.remove(); + textBlock = new CenteringTextElement(that.nodeElement(), that.backgroundColor()); + textBlock.addText(that.labelForCurrentLanguage()); + that.animateDynamicLabelWidth(graph.options().dynamicLabelWidth()); + shapeElement.select("title").text(that.labelForCurrentLanguage()); + }; + + this.animateDynamicLabelWidth = function ( dynamic ){ + that.removeHalo(); + var height = that.height(); + if ( dynamic === true ) { + labelWidth = Math.min(that.getMyWidth(), graph.options().maxLabelWidth()); + shapeElement.transition().tween("attr", function (){ + }) + .ease('linear') + .duration(100) + .attr({ x: -labelWidth / 2, y: -height / 2, width: labelWidth, height: height }) + .each("end", function (){ + that.updateTextElement(); + }); + + } else { + labelWidth = defaultWidth; + that.updateTextElement(); + shapeElement.transition().tween("attr", function (){ + }) + .ease('linear') + .duration(100) + .attr({ x: -labelWidth / 2, y: -height / 2, width: labelWidth, height: height }); + + } + + // for the pin we dont need to differ between different widths -- they are already set + if ( that.pinned() === true && pinGroupElement ) { + + var dx = 0.5 * labelWidth - 10, + dy = -1.1 * height; + + pinGroupElement.transition() + .tween("attr.translate", function (){ + }) + .attr("transform", "translate(" + dx + "," + dy + ")") + .ease('linear') + .duration(100); + } + }; + + this.addTextLabelElement = function (){ + var parentElement = that.nodeElement(); + textBlock = new CenteringTextElement(parentElement, this.backgroundColor()); + textBlock.addText(that.labelForCurrentLanguage()); + }; + + + }; + o.prototype = Object.create(BaseNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 37 */ +/***/ (function(module, exports) { + + var tools = {}; + module.exports = function (){ + return tools; + }; + + tools.distanceToBorder = function ( rect, dx, dy ){ + var width = rect.width(), + height = rect.height(); + + var innerDistance, + m_link = Math.abs(dy / dx), + m_rect = height / width; + + if ( m_link <= m_rect ) { + var timesX = dx / (width / 2), + rectY = dy / timesX; + innerDistance = Math.sqrt(Math.pow(width / 2, 2) + Math.pow(rectY, 2)); + } else { + var timesY = dy / (height / 2), + rectX = dx / timesY; + innerDistance = Math.sqrt(Math.pow(height / 2, 2) + Math.pow(rectX, 2)); + } + + return innerDistance; + }; + + +/***/ }), +/* 38 */ +/***/ (function(module, exports, __webpack_require__) { + + var DatatypeNode = __webpack_require__(35); + + module.exports = (function (){ + + var o = function ( graph ){ + DatatypeNode.apply(this, arguments); + + var superDrawFunction = this.draw, + superLabelFunction = this.label; + + this.attributes(["datatype"]) + .label("Literal") + .styleClass("literal") + .type("rdfs:Literal") + .iri("http://www.w3.org/2000/01/rdf-schema#Literal"); + + this.draw = function ( element ){ + superDrawFunction(element, ["dashed"]); + }; + + this.label = function ( p ){ + if ( !arguments.length ) return superLabelFunction(); + return this; + }; + }; + o.prototype = Object.create(DatatypeNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 39 */ +/***/ (function(module, exports, __webpack_require__) { + + var RoundNode = __webpack_require__(8); + + module.exports = (function (){ + + var o = function ( graph ){ + RoundNode.apply(this, arguments); + + var superDrawFunction = this.draw; + + this.attributes(["rdf"]) + .label("Resource") + .radius(30) + .styleClass("rdfsresource") + .type("rdfs:Resource"); + + this.draw = function ( element ){ + superDrawFunction(element, ["rdf", "dashed"]); + }; + }; + o.prototype = Object.create(RoundNode.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 40 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var properties = []; + properties.push(__webpack_require__(41)); + properties.push(__webpack_require__(44)); + properties.push(__webpack_require__(45)); + properties.push(__webpack_require__(46)); + properties.push(__webpack_require__(47)); + properties.push(__webpack_require__(48)); + properties.push(__webpack_require__(49)); + properties.push(__webpack_require__(50)); + properties.push(__webpack_require__(51)); + properties.push(__webpack_require__(52)); + properties.push(__webpack_require__(53)); + properties.push(__webpack_require__(54)); + properties.push(__webpack_require__(55)); + properties.push(__webpack_require__(56)); + + var map = d3.map(properties, function ( Prototype ){ + return new Prototype().type(); + }); + + module.exports = function (){ + return map; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 41 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + var superGenerateCardinalityText = this.generateCardinalityText; + + this.linkType("values-from") + .markerType("filled values-from") + .styleClass("allvaluesfromproperty") + .type("owl:allValuesFrom"); + + this.generateCardinalityText = function (){ + var cardinalityText = "A"; + + var superCardinalityText = superGenerateCardinalityText(); + if ( superCardinalityText ) { + cardinalityText += ", " + superCardinalityText; + } + + return cardinalityText; + }; + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + + + +/***/ }), +/* 42 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var BaseElement = __webpack_require__(10); + var CenteringTextElement = __webpack_require__(14); + var drawTools = __webpack_require__(17)(); + var forceLayoutNodeFunctions = __webpack_require__(13)(); + var rectangularElementTools = __webpack_require__(37)(); + var math = __webpack_require__(43)(); + + module.exports = (function (){ + + // Static variables + var labelHeight = 28, + labelWidth = 80, + smallestRadius = labelHeight / 2; + + + // Constructor, private variables and privileged methods + var Base = function ( graph ){ + BaseElement.apply(this, arguments); + + var that = this, + // Basic attributes + cardinality, + domain, + inverse, + link, + minCardinality, + maxCardinality, + range, + subproperties, + superproperties, + // Style attributes + linkType = "normal", + markerType = "filled", + labelVisible = true, + // Element containers + cardinalityElement, + labelElement, + linkGroup, + markerElement, + // Other + ignoreLocalHoverEvents, + fobj, + pinGroupElement, + haloGroupElement, + myWidth = 80, + defaultWidth = 80, + shapeElement, + textElement, + parent_labelObject, + backupFullIri, + + redundantProperties = []; + + + this.existingPropertyIRI = function ( url ){ + return graph.options().editSidebar().checkForExistingURL(url); + }; + + this.getHalos = function (){ + return haloGroupElement; + }; + + this.getPin = function (){ + return pinGroupElement; + }; + this.labelObject = function ( lo, once ){ + if ( !arguments.length ) { + return parent_labelObject; + } + else { + parent_labelObject = lo; + if ( that.inverse() && once !== true ) { + that.inverse().labelObject(lo, true); + } + + } + }; + this.hide = function ( val ){ + that.labelElement().classed("hidden", val); + that.linkGroup().classed("hidden", val); + if ( that.cardinalityElement() ) + that.cardinalityElement().classed("hidden", val); + }; + + // Properties + this.cardinality = function ( p ){ + if ( !arguments.length ) return cardinality; + cardinality = p; + return this; + }; + + this.cardinalityElement = function ( p ){ + if ( !arguments.length ) return cardinalityElement; + cardinalityElement = p; + return this; + }; + + this.domain = function ( p ){ + if ( !arguments.length ) return domain; + domain = p; + return this; + }; + + this.inverse = function ( p ){ + if ( !arguments.length ) return inverse; + inverse = p; + return this; + }; + + this.labelElement = function ( p ){ + if ( !arguments.length ) return labelElement; + labelElement = p; + return this; + }; + + this.labelVisible = function ( p ){ + if ( !arguments.length ) return labelVisible; + labelVisible = p; + return this; + }; + + this.link = function ( p ){ + if ( !arguments.length ) return link; + link = p; + return this; + }; + + this.linkGroup = function ( p ){ + if ( !arguments.length ) return linkGroup; + linkGroup = p; + return this; + }; + + this.linkType = function ( p ){ + if ( !arguments.length ) return linkType; + linkType = p; + return this; + }; + + this.markerElement = function ( p ){ + if ( !arguments.length ) return markerElement; + markerElement = p; + return this; + }; + + this.markerType = function ( p ){ + if ( !arguments.length ) return markerType; + markerType = p; + return this; + }; + + this.maxCardinality = function ( p ){ + if ( !arguments.length ) return maxCardinality; + maxCardinality = p; + return this; + }; + + this.minCardinality = function ( p ){ + if ( !arguments.length ) return minCardinality; + minCardinality = p; + return this; + }; + + this.range = function ( p ){ + if ( !arguments.length ) return range; + range = p; + return this; + }; + + this.redundantProperties = function ( p ){ + if ( !arguments.length ) return redundantProperties; + redundantProperties = p; + return this; + }; + + this.subproperties = function ( p ){ + if ( !arguments.length ) return subproperties; + subproperties = p; + return this; + }; + + this.superproperties = function ( p ){ + if ( !arguments.length ) return superproperties; + superproperties = p; + return this; + }; + + + // Functions + this.distanceToBorder = function ( dx, dy ){ + return rectangularElementTools.distanceToBorder(that, dx, dy); + }; + + this.linkHasMarker = function (){ + return linkType !== "dashed"; + }; + + this.markerId = function (){ + return "marker" + that.id(); + }; + + this.toggleFocus = function (){ + that.focused(!that.focused()); + labelElement.select("rect").classed("focused", that.focused()); + graph.resetSearchHighlight(); + graph.options().searchMenu().clearText(); + }; + this.getShapeElement = function (){ + return shapeElement; + }; + + this.textBlock = function (){ + return textElement; + }; + + this.redrawElement = function (){ + shapeElement.remove(); + textElement.remove(); + + that.drawLabel(that.labelElement()); + that.animateDynamicLabelWidth(graph.options().dynamicLabelWidth()); + + + // shapeElement=this.addRect(that.labelElement()); + // + // var equivalentsString = that.equivalentsString(); + // var suffixForFollowingEquivalents = equivalentsString ? "," : ""; + // + // textElement = new CenteringTextElement(labelContainer, this.backgroundColor()); + // textElement.addText(this.labelForCurrentLanguage(), "", suffixForFollowingEquivalents); + // textElement.addEquivalents(equivalentsString); + // textElement.addSubText(this.indicationString()); + + }; + + // Reused functions TODO refactor + this.draw = function ( labelGroup ){ + function attachLabel( property ){ + var labelContainer = labelGroup.append("g") + .datum(property) + .classed("label", true) + .attr("id", property.id()); + + property.drawLabel(labelContainer); + return labelContainer; + } + + if ( !that.labelVisible() ) { + return undefined; + } + if ( graph.options().dynamicLabelWidth() === true ) myWidth = Math.min(that.getMyWidth(), graph.options().maxLabelWidth()); + else myWidth = defaultWidth; + + that.labelElement(attachLabel(that)); + // Draw an inverse label and reposition both labels if necessary + if ( that.inverse() ) { + var yTransformation = (that.height() / 2) + 1 /* additional space */; + that.inverse() + .labelElement(attachLabel(that.inverse())); + + that.labelElement() + .attr("transform", "translate(" + 0 + ",-" + yTransformation + ")"); + that.inverse() + .labelElement() + .attr("transform", "translate(" + 0 + "," + yTransformation + ")"); + } + + if ( that.pinned() ) { + that.drawPin(); + } else if ( that.inverse() && that.inverse().pinned() ) { + that.inverse().drawPin(); + } + + if ( that.halo() ) + that.drawHalo(false); + + return that.labelElement(); + }; + + this.addRect = function ( labelContainer ){ + var rect = labelContainer.append("rect") + .classed(that.styleClass(), true) + .classed("property", true) + .attr("x", -that.width() / 2) + .attr("y", -that.height() / 2) + .attr("width", that.width()) + .attr("height", that.height()) + .on("mouseover", function (){ + onMouseOver(); + }) + .on("mouseout", function (){ + onMouseOut(); + }); + + rect.append("title") + .text(that.labelForCurrentLanguage()); + + if ( that.visualAttributes() ) { + rect.classed(that.visualAttributes(), true); + } + + var bgColor = that.backgroundColor(); + + if ( that.attributes().indexOf("deprecated") > -1 ) { + bgColor = undefined; + rect.classed("deprecatedproperty", true); + } else { + rect.classed("deprecatedproperty", false); + } + rect.style("fill", bgColor); + + return rect; + }; + this.drawLabel = function ( labelContainer ){ + shapeElement = this.addRect(labelContainer); + + var equivalentsString = that.equivalentsString(); + var suffixForFollowingEquivalents = equivalentsString ? "," : ""; + + var bgColor = that.backgroundColor(); + if ( that.attributes().indexOf("deprecated") > -1 ) { + bgColor = undefined; + } + textElement = new CenteringTextElement(labelContainer, bgColor); + textElement.addText(this.labelForCurrentLanguage(), "", suffixForFollowingEquivalents); + textElement.addEquivalents(equivalentsString); + textElement.addSubText(this.indicationString()); + }; + + this.equivalentsString = function (){ + var equivalentProperties = that.equivalents(); + if ( !equivalentProperties ) { + return; + } + + return equivalentProperties + .map(function ( property ){ + if ( property === undefined || typeof(property) === "string" ) { // @WORKAROUND + return "ERROR"; + } + return property.labelForCurrentLanguage(); + }) + .join(", "); + }; + + this.drawCardinality = function ( container ){ + var cardinalityText = this.generateCardinalityText(); + + if ( cardinalityText ) { + that.cardinalityElement(container); + if ( cardinalityText.indexOf("A") === 0 && cardinalityText.length === 1 ) { + + // replacing text elements to svg elements; + container.classed("cardinality", true) + .attr("text-anchor", "middle") + .append("path") + .classed("cardinality", true) + .attr("d", "m -8.8832678,-11.303355 -7.97e-4,0 0.717374,1.833297 8.22987151,21.371761 8.66826659,-21.2123526 0.797082,-1.9927054 0.02471,0 -0.8218553,1.9927054 -2.2517565,5.4201577 -12.4444429,8e-6 -2.2019394,-5.5795821 z") + .style("fill", "none") + .attr("transform", "matrix(0.5,0,0,0.5,0.5,0.5)"); + return true; + } else if ( cardinalityText.indexOf("E") === 0 && cardinalityText.length === 1 ) { + container.classed("cardinality", true) + .attr("text-anchor", "middle") + .append("path") + .classed("cardinality", true) + .attr("d", "m -5.5788451,-8.0958763 10.8749368,0 0,8.34681523 -9.5707468,0.040132 9.5707468,-0.040132 0,8.42707237 -10.9150654,0") + .style("fill", "none") + .attr("transform", "matrix(0.5,0,0,0.5,0.5,0.5)"); + return true; + } + else { + container.append("text") + .classed("cardinality", true) + .attr("text-anchor", "middle") + .attr("dy", "0.5ex") + .text(cardinalityText); + return true; // drawing successful + } + } else { + return false; + } + }; + + this.generateCardinalityText = function (){ + if ( that.cardinality() ) { + return that.cardinality(); + } else if ( that.minCardinality() || that.maxCardinality() ) { + var minBoundary = that.minCardinality() || "*"; + var maxBoundary = that.maxCardinality() || "*"; + return minBoundary + ".." + maxBoundary; + } + }; + + that.setHighlighting = function ( enable ){ + if ( that.labelElement && that.labelElement() ) { + that.labelElement().select("rect").classed("hovered", enable); + } + that.linkGroup().selectAll("path, text").classed("hovered", enable); + if ( that.markerElement() ) { + that.markerElement().select("path").classed("hovered", enable); + if ( that.cardinalityElement() ) { + that.cardinalityElement().selectAll("path").classed("hovered-MathSymbol", enable); + that.cardinalityElement().classed("hovered", enable); + } + } + var subAndSuperProperties = getSubAndSuperProperties(); + subAndSuperProperties.forEach(function ( property ){ + + if ( property.labelElement && property.labelElement() ) { + property.labelElement().select("rect") + .classed("indirect-highlighting", enable); + } + + }); + var inversed = false; + + if ( graph.ignoreOtherHoverEvents() === false ) { + if ( that.inverse() ) { + inversed = true; + } + + if ( graph.isTouchDevice() === false ) { + graph.activateHoverElementsForProperties(enable, that, inversed); + } + else { + that.labelElement().select("rect").classed("hovered", false); + that.linkGroup().selectAll("path, text").classed("hovered", false); + if ( that.markerElement() ) { + that.markerElement().select("path").classed("hovered", false); + if ( that.cardinalityElement() ) { + that.cardinalityElement().classed("hovered", false); + } + } + graph.activateHoverElementsForProperties(enable, that, inversed, true); + } + } + }; + + /** + * Combines the sub- and superproperties into a single array, because + * they're often used equivalently. + * @returns {Array} + */ + function getSubAndSuperProperties(){ + var properties = []; + + if ( that.subproperties() ) { + properties = properties.concat(that.subproperties()); + } + if ( that.superproperties() ) { + properties = properties.concat(that.superproperties()); + } + + return properties; + } + + /** + * Foregrounds the property, its inverse and the link. + */ + this.foreground = function (){ + // check for additional objects that we can highlight + if ( !that.labelElement() ) + return; + if ( that.labelElement().node().parentNode === null ) { + return; + } + var selectedLabelGroup = that.labelElement().node().parentNode, + labelContainer = selectedLabelGroup.parentNode, + selectedLinkGroup = that.linkGroup().node(), + linkContainer = that.linkGroup().node().parentNode; + if ( that.animationProcess() === false ) { + labelContainer.appendChild(selectedLabelGroup); + } + linkContainer.appendChild(selectedLinkGroup); + }; + + /** + * Foregrounds the sub- and superproperties of this property. + * This is separated from the foreground-function to prevent endless loops. + */ + function foregroundSubAndSuperProperties(){ + var subAndSuperProperties = getSubAndSuperProperties(); + + subAndSuperProperties.forEach(function ( property ){ + if ( property.foreground ) property.foreground(); + }); + } + + function onMouseOver(){ + if ( that.mouseEntered() || ignoreLocalHoverEvents === true ) { + return; + } + that.mouseEntered(true); + that.setHighlighting(true); + that.foreground(); + foregroundSubAndSuperProperties(); + } + + function onMouseOut(){ + that.mouseEntered(false); + that.setHighlighting(false); + } + + this.drawPin = function (){ + that.pinned(true); + if ( graph.options().dynamicLabelWidth() === true ) myWidth = that.getMyWidth(); + else myWidth = defaultWidth; + + if ( that.inverse() ) { + // check which element is rendered on top and add a pin to it + var tr_that = that.labelElement().attr("transform"); + var tr_inv = that.inverse().labelElement().attr("transform"); + + var thatY = /translate\(\s*([^\s,)]+)[ ,]([^\s,)]+)/.exec(tr_that)[2]; + var invY = /translate\(\s*([^\s,)]+)[ ,]([^\s,)]+)/.exec(tr_inv)[2]; + + if ( thatY < invY ) + pinGroupElement = drawTools.drawPin(that.labelElement(), -0.5 * that.width() + 10, -25, this.removePin, graph.options().showDraggerObject, graph.options().useAccuracyHelper()); + else + pinGroupElement = drawTools.drawPin(that.inverse().labelElement(), -0.5 * that.inverse().width() + 10, -25, this.removePin, graph.options().showDraggerObject, graph.options().useAccuracyHelper()); + + } + else { + pinGroupElement = drawTools.drawPin(that.labelElement(), -0.5 * that.width() + 10, -25, this.removePin, graph.options().showDraggerObject, graph.options().useAccuracyHelper()); + } + + + }; + + /** + * Removes the pin and refreshs the graph to update the force layout. + */ + this.removePin = function (){ + that.pinned(false); + if ( pinGroupElement ) { + pinGroupElement.remove(); + } + graph.updateStyle(); + }; + + this.removeHalo = function (){ + that.halo(false); + if ( haloGroupElement ) { + haloGroupElement.remove(); + haloGroupElement = null; + } + }; + + this.animationProcess = function (){ + var animRuns = false; + if ( that.getHalos() ) { + var haloGr = that.getHalos(); + var haloEls = haloGr.selectAll(".searchResultA"); + animRuns = haloGr.attr("animationRunning"); + + if ( typeof animRuns !== "boolean" ) { + // parse this to a boolean value + animRuns = (animRuns === 'true'); + } + if ( animRuns === false ) { + haloEls.classed("searchResultA", false); + haloEls.classed("searchResultB", true); + } + } + return animRuns; + }; + + this.drawHalo = function ( pulseAnimation ){ + that.halo(true); + var offset = 0; + if ( that.labelElement() && that.labelElement().node() ) { + var labelNode = that.labelElement().node(); + var labelContainer = labelNode.parentNode; + // do this only if animation is not running + if ( that.animationProcess() === false ) + labelContainer.appendChild(labelNode); + } + haloGroupElement = drawTools.drawRectHalo(that, that.width(), that.height(), offset); + if ( haloGroupElement ) { + var haloNode = haloGroupElement.node(); + var haloContainer = haloNode.parentNode; + haloContainer.appendChild(haloNode); + } + var selectedNode; + var nodeContainer; + if ( that.pinned() ) { + selectedNode = pinGroupElement.node(); + nodeContainer = selectedNode.parentNode; + nodeContainer.appendChild(selectedNode); + } + if ( that.inverse() && that.inverse().pinned() ) { + if ( that.inverse().getPin() ) { + selectedNode = that.inverse().getPin().node(); + nodeContainer = selectedNode.parentNode; + nodeContainer.appendChild(selectedNode); + } + } + if ( pulseAnimation === false ) { + var pulseItem = haloGroupElement.selectAll(".searchResultA"); + pulseItem.classed("searchResultA", false); + pulseItem.classed("searchResultB", true); + pulseItem.attr("animationRunning", false); + } + }; + + this.getMyWidth = function (){ + var text = that.labelForCurrentLanguage(); + myWidth = measureTextWidth(text, "text") + 20; + // check for sub names; + var indicatorText = that.indicationString(); + var indicatorWidth = measureTextWidth(indicatorText, "subtext") + 20; + if ( indicatorWidth > myWidth ) + myWidth = indicatorWidth; + + return myWidth; + }; + + function measureTextWidth( text, textStyle ){ + // Set a default value + if ( !textStyle ) { + textStyle = "text"; + } + var d = d3.select("body") + .append("div") + .attr("class", textStyle) + .attr("id", "width-test") // tag this element to identify it + .attr("style", "position:absolute; float:left; white-space:nowrap; visibility:hidden;") + .text(text), + w = document.getElementById("width-test").offsetWidth; + d.remove(); + return w; + } + + this.textWidth = function (){ + return myWidth; + }; + this.width = function (){ + return myWidth; + }; + + this.animateDynamicLabelWidth = function ( dynamic ){ + that.removeHalo(); + if ( shapeElement === undefined ) {// this handles setOperatorProperties which dont have a shapeElement! + return; + } + + var h = that.height(); + if ( dynamic === true ) { + myWidth = Math.min(that.getMyWidth(), graph.options().maxLabelWidth()); + shapeElement.transition().tween("attr", function (){ + }) + .ease('linear') + .duration(100) + .attr({ x: -myWidth / 2, y: -h / 2, width: myWidth, height: h }) + .each("end", function (){ + that.updateTextElement(); + }); + } else { + // Static width for property labels = 80 + myWidth = defaultWidth; + that.updateTextElement(); + shapeElement.transition().tween("attr", function (){ + }) + .ease('linear') + .duration(100) + .attr({ x: -myWidth / 2, y: -h / 2, width: myWidth, height: h }); + } + if ( that.pinned() === true && pinGroupElement ) { + var dx = -0.5 * myWidth + 10, + dy = -25; + pinGroupElement.transition() + .tween("attr.translate", function (){ + }) + .attr("transform", "translate(" + dx + "," + dy + ")") + .ease('linear') + .duration(100); + } + }; + + this.redrawLabelText = function (){ + textElement.remove(); + that.addTextLabelElement(); + that.animateDynamicLabelWidth(graph.options().dynamicLabelWidth()); + shapeElement.select("title").text(that.labelForCurrentLanguage()); + }; + + this.addTextLabelElement = function (){ + var labelContainer = that.labelElement(); + + var equivalentsString = that.equivalentsString(); + var suffixForFollowingEquivalents = equivalentsString ? "," : ""; + + textElement = new CenteringTextElement(labelContainer, this.backgroundColor()); + textElement.addText(this.labelForCurrentLanguage(), "", suffixForFollowingEquivalents); + textElement.addEquivalents(equivalentsString); + textElement.addSubText(this.indicationString()); + }; + + this.updateTextElement = function (){ + textElement.updateAllTextElements(); + }; + this.enableEditing = function ( autoEditing ){ + if ( autoEditing === false ) + return; + that.raiseDoubleClickEdit(true); + }; + + this.raiseDoubleClickEdit = function ( forceIRISync ){ + d3.selectAll(".foreignelements").remove(); + if ( that.labelElement() === undefined || this.type() === "owl:disjointWith" || this.type() === "rdfs:subClassOf" ) { + console.log("No Container found"); + return; + } + if ( fobj !== undefined ) { + that.labelElement().selectAll(".foreignelements").remove(); + } + backupFullIri = undefined; + graph.options().focuserModule().handle(undefined); + graph.options().focuserModule().handle(that); + that.editingTextElement = true; + ignoreLocalHoverEvents = true; + that.labelElement().selectAll("rect").classed("hoveredForEditing", true); + that.frozen(true); + graph.killDelayedTimer(); + graph.ignoreOtherHoverEvents(false); + fobj = that.labelElement().append("foreignObject") + .attr("x", -0.5 * that.textWidth()) + .attr("y", -13) + .attr("height", 25) + .attr("class", "foreignelements") + .on("dragstart", function (){ + return false; + }) // remove drag operations of text element) + .attr("width", that.textWidth() - 2); + // adding a Style to the fObject + // + // + // + var editText = fobj.append("xhtml:input") + .attr("class", "nodeEditSpan") + .attr("id", that.id()) + .attr("align", "center") + .attr("contentEditable", "true") + .on("dragstart", function (){ + return false; + }); // remove drag operations of text element) + + var bgColor = '#f00'; + var txtWidth = that.textWidth() - 2; + editText.style({ + // 'line-height': '30px', + 'align': 'center', + 'color': 'black', + 'width': txtWidth + "px", + 'background-color': bgColor, + 'border-bottom': '2px solid black' + }); + var txtNode = editText.node(); + txtNode.value = that.labelForCurrentLanguage(); + txtNode.focus(); + txtNode.select(); + if ( d3.event.stopPropagation ) d3.event.stopPropagation(); + if ( d3.event.sourceEvent && d3.event.sourceEvent.stopPropagation ) d3.event.sourceEvent.stopPropagation(); + + // add some events that relate to this object + editText.on("click", function (){ + if ( d3.event.stopPropagation ) d3.event.stopPropagation(); + if ( d3.event.sourceEvent && d3.event.sourceEvent.stopPropagation ) d3.event.sourceEvent.stopPropagation(); + + }); + // // remove hover Events for now; + editText.on("mouseout", function (){ + if ( d3.event.stopPropagation ) d3.event.stopPropagation(); + if ( d3.event.sourceEvent && d3.event.sourceEvent.stopPropagation ) d3.event.sourceEvent.stopPropagation(); + }); + editText.on("mousedown", function (){ + if ( d3.event.stopPropagation ) d3.event.stopPropagation(); + if ( d3.event.sourceEvent && d3.event.sourceEvent.stopPropagation ) d3.event.sourceEvent.stopPropagation(); + }) + .on("keydown", function (){ + + if ( d3.event.keyCode === 13 ) { + this.blur(); + that.frozen(false); // << releases the not after selection + that.locked(false); + } + }) + .on("keyup", function (){ + if ( forceIRISync ) { + var labelName = editText.node().value; + var resourceName = labelName.replaceAll(" ", "_"); + var syncedIRI = that.baseIri() + resourceName; + backupFullIri = syncedIRI; + + d3.select("#element_iriEditor").node().title = syncedIRI; + d3.select("#element_iriEditor").node().value = graph.options().prefixModule().getPrefixRepresentationForFullURI(syncedIRI); + } + d3.select("#element_labelEditor").node().value = editText.node().value; + + }) + .on("blur", function (){ + + + that.editingTextElement = false; + ignoreLocalHoverEvents = false; + that.labelElement().selectAll("rect").classed("hoveredForEditing", false); + var newLabel = editText.node().value; + that.labelElement().selectAll(".foreignelements").remove(); + // that.setLabelForCurrentLanguage(classNameConvention(editText.node().value)); + that.label(newLabel); + that.backupLabel(newLabel); + that.redrawLabelText(); + updateHoverElements(true); + graph.showHoverElementsAfterAnimation(that, false); + graph.ignoreOtherHoverEvents(false); + + + that.frozen(graph.paused()); + that.locked(graph.paused()); + that.domain().frozen(graph.paused()); + that.domain().locked(graph.paused()); + that.range().frozen(graph.paused()); + that.range().locked(graph.paused()); + graph.removeEditElements(); + if ( backupFullIri ) { + // console.log("Checking if element is Identical ?"); + var sanityCheckResult = graph.options().editSidebar().checkProperIriChange(that, backupFullIri); + if ( sanityCheckResult !== false ) { + graph.options().warningModule().showWarning("Already seen this property", + "Input IRI: " + backupFullIri + " for element: " + that.labelForCurrentLanguage() + " already been set", + "Continuing with duplicate property!", 1, false, sanityCheckResult); + } + that.iri(backupFullIri); + } + graph.options().focuserModule().handle(undefined); + graph.options().focuserModule().handle(that); + graph.updatePropertyDraggerElements(that); + + + }); // add a foreiner element to this thing; + + }; + + // update hover elements + function updateHoverElements( enable ){ + if ( graph.ignoreOtherHoverEvents() === false ) { + var inversed = false; + if ( that.inverse() ) { + inversed = true; + } + if ( enable === true ) { + graph.activateHoverElementsForProperties(enable, that, inversed); + } + } + } + + that.copyInformation = function ( other ){ + that.label(other.label()); + that.iri(other.iri()); + that.baseIri(other.baseIri()); + if ( other.type() === "owl:ObjectProperty" || + other.type() === "owl:DatatypeProperty" ) { + that.backupLabel(other.label()); + // console.log("copied backup label"+that.backupLabel()); + } + if ( other.backupLabel() !== undefined ) { + that.backupLabel(other.backupLabel()); + } + }; + + forceLayoutNodeFunctions.addTo(this); + }; + + Base.prototype = Object.create(BaseElement.prototype); + Base.prototype.constructor = Base; + + Base.prototype.height = function (){ + return labelHeight; + }; + + Base.prototype.width = function (){ + return labelWidth; + }; + + Base.prototype.actualRadius = function (){ + return smallestRadius; + }; + + Base.prototype.textWidth = Base.prototype.width; + + + return Base; + }()); + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 43 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * Contains a collection of mathematical functions with some additional data + * used for WebVOWL. + */ + module.exports = (function (){ + + var math = {}, + loopFunction = d3.svg.line() + .x(function ( d ){ + return d.x; + }) + .y(function ( d ){ + return d.y; + }) + .interpolate("cardinal") + .tension(-1); + + + /** + * Calculates the normal vector of the path between the two nodes. + * @param source the first node + * @param target the second node + * @param length the length of the calculated normal vector + * @returns {{x: number, y: number}} + */ + math.calculateNormalVector = function ( source, target, length ){ + var dx = target.x - source.x, + dy = target.y - source.y; + + var nx = -dy, + ny = dx; + + var vlength = Math.sqrt(nx * nx + ny * ny); + + var ratio = vlength !== 0 ? length / vlength : 0; + + return { "x": nx * ratio, "y": ny * ratio }; + }; + + /** + * Calculates the path for a link, if it is a loop. Currently only working for circlular nodes. + * @param link the link + * @returns {*} + */ + + + + math.getLoopPoints = function ( link ){ + var node = link.domain(), + label = link.label(); + + var fairShareLoopAngle = 360 / link.loops().length, + fairShareLoopAngleWithMargin = fairShareLoopAngle * 0.8, + loopAngle = Math.min(60, fairShareLoopAngleWithMargin); + + if ( label.increasedLoopAngle === true ) + loopAngle = 120; + + + var dx = label.x - node.x, + dy = label.y - node.y, + labelRadian = Math.atan2(dy, dx), + labelAngle = calculateAngle(labelRadian); + + var startAngle = labelAngle - loopAngle / 2, + endAngle = labelAngle + loopAngle / 2; + + + var arcFrom = calculateRadian(startAngle), + arcTo = calculateRadian(endAngle), + + x1 = Math.cos(arcFrom) * node.actualRadius(), + y1 = Math.sin(arcFrom) * node.actualRadius(), + + x2 = Math.cos(arcTo) * node.actualRadius(), + y2 = Math.sin(arcTo) * node.actualRadius(), + + fixPoint1 = { "x": node.x + x1, "y": node.y + y1 }, + fixPoint2 = { "x": node.x + x2, "y": node.y + y2 }; + + return [fixPoint1, fixPoint2]; + }; + math.calculateLoopPath = function ( link ){ + var node = link.domain(), + label = link.label(); + + + var fairShareLoopAngle = 360 / link.loops().length, + fairShareLoopAngleWithMargin = fairShareLoopAngle * 0.8, + loopAngle = Math.min(60, fairShareLoopAngleWithMargin); + + if ( label.increasedLoopAngle === true ) + loopAngle = 120; + + var dx = label.x - node.x, + dy = label.y - node.y, + labelRadian = Math.atan2(dy, dx), + labelAngle = calculateAngle(labelRadian); + + var startAngle = labelAngle - loopAngle / 2, + endAngle = labelAngle + loopAngle / 2; + + var arcFrom = calculateRadian(startAngle), + arcTo = calculateRadian(endAngle), + + x1 = Math.cos(arcFrom) * node.actualRadius(), + y1 = Math.sin(arcFrom) * node.actualRadius(), + + x2 = Math.cos(arcTo) * node.actualRadius(), + y2 = Math.sin(arcTo) * node.actualRadius(), + + fixPoint1 = { "x": node.x + x1, "y": node.y + y1 }, + fixPoint2 = { "x": node.x + x2, "y": node.y + y2 }; + + return loopFunction([fixPoint1, link.label(), fixPoint2]); + }; + + math.calculateLoopPoints = function ( link ){ + var node = link.domain(), + label = link.label(); + + var fairShareLoopAngle = 360 / link.loops().length, + fairShareLoopAngleWithMargin = fairShareLoopAngle * 0.8, + loopAngle = Math.min(60, fairShareLoopAngleWithMargin); + + var dx = label.x - node.x, + dy = label.y - node.y, + labelRadian = Math.atan2(dy, dx), + labelAngle = calculateAngle(labelRadian); + + var startAngle = labelAngle - loopAngle / 2, + endAngle = labelAngle + loopAngle / 2; + + var arcFrom = calculateRadian(startAngle), + arcTo = calculateRadian(endAngle), + + x1 = Math.cos(arcFrom) * node.actualRadius(), + y1 = Math.sin(arcFrom) * node.actualRadius(), + + x2 = Math.cos(arcTo) * (node.actualRadius()), + y2 = Math.sin(arcTo) * (node.actualRadius()), + + fixPoint1 = { "x": node.x + x1, "y": node.y + y1 }, + fixPoint2 = { "x": node.x + x2, "y": node.y + y2 }; + + return [fixPoint1, link.label(), fixPoint2]; + }; + + /** + * @param angle + * @returns {number} the radian of the angle + */ + function calculateRadian( angle ){ + angle = angle % 360; + if ( angle < 0 ) { + angle = angle + 360; + } + return (Math.PI * angle) / 180; + } + + /** + * @param radian + * @returns {number} the angle of the radian + */ + function calculateAngle( radian ){ + return radian * (180 / Math.PI); + } + + /** + * Calculates the point where the link between the source and target node + * intersects the border of the target node. + * @param source the source node + * @param target the target node + * @param additionalDistance additional distance the + * @returns {{x: number, y: number}} + */ + math.calculateIntersection = function ( source, target, additionalDistance ){ + var dx = target.x - source.x, + dy = target.y - source.y, + length = Math.sqrt(dx * dx + dy * dy); + + if ( length === 0 ) { + return { x: source.x, y: source.y }; + } + + var innerDistance = target.distanceToBorder(dx, dy); + + var ratio = (length - (innerDistance + additionalDistance)) / length, + x = dx * ratio + source.x, + y = dy * ratio + source.y; + + return { x: x, y: y }; + }; + + /** + * Calculates the position between the two points. + * @param firstPoint + * @param secondPoint + * @returns {{x: number, y: number}} + */ + math.calculateCenter = function ( firstPoint, secondPoint ){ + return { + x: (firstPoint.x + secondPoint.x) / 2, + y: (firstPoint.y + secondPoint.y) / 2 + }; + }; + + + return function (){ + /* Use a function here to keep a consistent style like webvowl.path.to.module() + * despite having just a single math object. */ + return math; + }; + })(); + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 44 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.attributes(["datatype"]) + .styleClass("datatypeproperty") + .type("owl:DatatypeProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 45 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.attributes(["deprecated"]) + .styleClass("deprecatedproperty") + .type("owl:DeprecatedProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 46 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + var CenteringTextElement = __webpack_require__(14); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + var label = "Disjoint With"; + var shapeElement; + // Disallow overwriting the label + this.label = function ( p ){ + if ( !arguments.length ) return label; + return this; + }; + + this.linkType("dashed") + .styleClass("disjointwith") + .type("owl:disjointWith"); + + this.drawLabel = function ( labelContainer ){ + shapeElement = this.addRect(labelContainer); + + labelContainer.append("circle") + .classed("symbol", true) + .classed("fineline", true) + .classed("embedded", true) + .attr("cx", -12.5) + .attr("r", 10); + + labelContainer.append("circle") + .classed("symbol", true) + .classed("fineline", true) + .classed("embedded", true) + .attr("cx", 12.5) + .attr("r", 10); + + var textElement = new CenteringTextElement(labelContainer, this.backgroundColor()); + if ( !graph.options().compactNotation() ) { + textElement.addSubText("disjoint"); + } + textElement.translation(0, 20); + }; + this.getShapeElement = function (){ + return shapeElement; + }; + this.markerElement = function (){ + return undefined; + }; + + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 47 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.styleClass("equivalentproperty") + .type("owl:equivalentProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 48 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.attributes(["functional"]) + .styleClass("functionalproperty") + .type("owl:FunctionalProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 49 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.attributes(["inverse functional"]) + .styleClass("inversefunctionalproperty") + .type("owl:InverseFunctionalProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 50 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.attributes(["object"]) + .styleClass("objectproperty") + .type("owl:ObjectProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + + + +/***/ }), +/* 51 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + var superGenerateCardinalityText = this.generateCardinalityText; + + this.linkType("values-from") + .markerType("filled values-from") + .styleClass("somevaluesfromproperty") + .type("owl:someValuesFrom"); + + this.generateCardinalityText = function (){ + var cardinalityText = "E"; + + var superCardinalityText = superGenerateCardinalityText(); + if ( superCardinalityText ) { + cardinalityText += ", " + superCardinalityText; + } + + return cardinalityText; + }; + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + + + +/***/ }), +/* 52 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.attributes(["symmetric"]) + .styleClass("symmetricproperty") + .type("owl:SymmetricProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 53 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.attributes(["transitive"]) + .styleClass("transitiveproperty") + .type("owl:TransitiveProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 54 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.attributes(["rdf"]) + .styleClass("rdfproperty") + .type("rdf:Property"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 55 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + var that = this, + superDrawFunction = that.draw, + label = "Subclass of"; + + this.draw = function ( labelGroup ){ + that.labelVisible(!graph.options().compactNotation()); + return superDrawFunction(labelGroup); + }; + + // Disallow overwriting the label + this.label = function ( p ){ + if ( !arguments.length ) return label; + return this; + }; + + this.linkType("dotted") + .markerType("white") + .styleClass("subclass") + .type("rdfs:subClassOf"); + + that.baseIri("http://www.w3.org/2000/01/rdf-schema#"); + that.iri("http://www.w3.org/2000/01/rdf-schema#subClassOf"); + + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 56 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + + module.exports = (function (){ + + var o = function ( graph ){ + BaseProperty.apply(this, arguments); + + this.labelVisible(false) + .linkType("dashed") + .markerType("white") + .styleClass("setoperatorproperty") + .type("setOperatorProperty"); + }; + o.prototype = Object.create(BaseProperty.prototype); + o.prototype.constructor = o; + + return o; + }()); + + +/***/ }), +/* 57 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var _ = __webpack_require__(58); + var math = __webpack_require__(43)(); + var linkCreator = __webpack_require__(60)(); + var elementTools = __webpack_require__(63)(); + // add some maps for nodes and properties -- used for object generation + var nodePrototypeMap = __webpack_require__(5)(); + var propertyPrototypeMap = __webpack_require__(40)(); + + + module.exports = function ( graphContainerSelector ){ + var graph = {}, + CARDINALITY_HDISTANCE = 20, + CARDINALITY_VDISTANCE = 10, + curveFunction = d3.svg.line() + .x(function ( d ){ + return d.x; + }) + .y(function ( d ){ + return d.y; + }) + .interpolate("cardinal"), + options = __webpack_require__(64)(), + parser = __webpack_require__(65)(graph), + language = "default", + paused = false, + // Container for visual elements + graphContainer, + nodeContainer, + labelContainer, + cardinalityContainer, + linkContainer, + // Visual elements + nodeElements, + initialLoad = true, + updateRenderingDuringSimulation = false, + labelGroupElements, + linkGroups, + linkPathElements, + cardinalityElements, + // Internal data + classNodes, + labelNodes, + links, + properties, + unfilteredData, + // Graph behaviour + force, + dragBehaviour, + zoomFactor = 1.0, + centerGraphViewOnLoad = false, + transformAnimation = false, + graphTranslation = [0, 0], + graphUpdateRequired = false, + pulseNodeIds = [], + nodeArrayForPulse = [], + nodeMap = [], + locationId = 0, + defaultZoom = 1.0, + defaultTargetZoom = 0.8, + global_dof = -1, + touchDevice = false, + last_touch_time, + originalD3_dblClickFunction = null, + originalD3_touchZoomFunction = null, + + // editing elements + deleteGroupElement, + addDataPropertyGroupElement, + editContainer, + draggerLayer = null, + draggerObjectsArray = [], + delayedHider, + nodeFreezer, + hoveredNodeElement = null, + currentlySelectedNode = null, + hoveredPropertyElement = null, + draggingStarted = false, + frozenDomainForPropertyDragger, + frozenRangeForPropertyDragger, + + eP = 0, // id for new properties + eN = 0, // id for new Nodes + editMode = true, + debugContainer = d3.select("#FPS_Statistics"), + finishedLoadingSequence = false, + + ignoreOtherHoverEvents = false, + forceNotZooming = false, + now, then, // used for fps computation + showFPS = false, + seenEditorHint = false, + seenFilterWarning = false, + showFilterWarning = false, + + keepDetailsCollapsedOnLoading = true, + adjustingGraphSize = false, + showReloadButtonAfterLayoutOptimization = false, + zoom; + //var prefixModule=require("./prefixRepresentationModule")(graph); + var NodePrototypeMap = createLowerCasePrototypeMap(nodePrototypeMap); + var PropertyPrototypeMap = createLowerCasePrototypeMap(propertyPrototypeMap); + var classDragger = __webpack_require__(68)(graph); + var rangeDragger = __webpack_require__(69)(graph); + var domainDragger = __webpack_require__(70)(graph); + var shadowClone = __webpack_require__(71)(graph); + + graph.math = function (){ + return math; + }; + /** --------------------------------------------------------- **/ + /** -- getter and setter definitions -- **/ + /** --------------------------------------------------------- **/ + graph.isEditorMode = function (){ + return editMode; + }; + graph.getGlobalDOF = function (){ + return global_dof; + }; + graph.setGlobalDOF = function ( val ){ + global_dof = val; + }; + + graph.updateZoomSliderValueFromOutside = function (){ + graph.options().zoomSlider().updateZoomSliderValue(zoomFactor); + }; + + graph.setDefaultZoom = function ( val ){ + defaultZoom = val; + graph.reset(); + graph.options().zoomSlider().updateZoomSliderValue(defaultZoom); + }; + graph.setTargetZoom = function ( val ){ + defaultTargetZoom = val; + }; + graph.graphOptions = function (){ + return options; + }; + + graph.scaleFactor = function (){ + return zoomFactor; + }; + graph.translation = function (){ + return graphTranslation; + }; + + // Returns the visible nodes + graph.graphNodeElements = function (){ + return nodeElements; + }; + // Returns the visible Label Nodes + graph.graphLabelElements = function (){ + return labelNodes; + }; + + graph.graphLinkElements = function (){ + return links; + }; + + graph.setSliderZoom = function ( val ){ + + var cx = 0.5 * graph.options().width(); + var cy = 0.5 * graph.options().height(); + var cp = getWorldPosFromScreen(cx, cy, graphTranslation, zoomFactor); + var sP = [cp.x, cp.y, graph.options().height() / zoomFactor]; + var eP = [cp.x, cp.y, graph.options().height() / val]; + var pos_intp = d3.interpolateZoom(sP, eP); + + graphContainer.attr("transform", transform(sP, cx, cy)) + .transition() + .duration(1) + .attrTween("transform", function (){ + return function ( t ){ + return transform(pos_intp(t), cx, cy); + }; + }) + .each("end", function (){ + graphContainer.attr("transform", "translate(" + graphTranslation + ")scale(" + zoomFactor + ")"); + zoom.translate(graphTranslation); + zoom.scale(zoomFactor); + graph.options().zoomSlider().updateZoomSliderValue(zoomFactor); + }); + }; + + + graph.setZoom = function ( value ){ + zoom.scale(value); + }; + + graph.setTranslation = function ( translation ){ + zoom.translate([translation[0], translation[1]]); + }; + + graph.options = function (){ + return options; + }; + // search functionality + graph.getUpdateDictionary = function (){ + return parser.getDictionary(); + }; + + graph.language = function ( newLanguage ){ + if ( !arguments.length ) return language; + + // Just update if the language changes + if ( language !== newLanguage ) { + language = newLanguage || "default"; + redrawContent(); + recalculatePositions(); + graph.options().searchMenu().requestDictionaryUpdate(); + graph.resetSearchHighlight(); + } + return graph; + }; + + + /** --------------------------------------------------------- **/ + /** graph / rendering related functions **/ + /** --------------------------------------------------------- **/ + + // Initializes the graph. + function initializeGraph(){ + + options.graphContainerSelector(graphContainerSelector); + var moved = false; + force = d3.layout.force() + .on("tick", hiddenRecalculatePositions); + + dragBehaviour = d3.behavior.drag() + .origin(function ( d ){ + return d; + }) + .on("dragstart", function ( d ){ + d3.event.sourceEvent.stopPropagation(); // Prevent panning + graph.ignoreOtherHoverEvents(true); + if ( d.type && d.type() === "Class_dragger" ) { + classDragger.mouseButtonPressed = true; + clearTimeout(delayedHider); + classDragger.selectedViaTouch(true); + d.parentNode().locked(true); + draggingStarted = true; + } else if ( d.type && d.type() === "Range_dragger" ) { + graph.ignoreOtherHoverEvents(true); + clearTimeout(delayedHider); + frozenDomainForPropertyDragger = shadowClone.parentNode().domain(); + frozenRangeForPropertyDragger = shadowClone.parentNode().range(); + shadowClone.setInitialPosition(); + shadowClone.hideClone(false); + shadowClone.hideParentProperty(true); + shadowClone.updateElement(); + deleteGroupElement.classed("hidden", true); + addDataPropertyGroupElement.classed("hidden", true); + frozenDomainForPropertyDragger.frozen(true); + frozenDomainForPropertyDragger.locked(true); + frozenRangeForPropertyDragger.frozen(true); + frozenRangeForPropertyDragger.locked(true); + domainDragger.updateElement(); + domainDragger.mouseButtonPressed = true; + rangeDragger.updateElement(); + rangeDragger.mouseButtonPressed = true; + // shadowClone.setPosition(d.x, d.y); + + + } else if ( d.type && d.type() === "Domain_dragger" ) { + graph.ignoreOtherHoverEvents(true); + clearTimeout(delayedHider); + frozenDomainForPropertyDragger = shadowClone.parentNode().domain(); + frozenRangeForPropertyDragger = shadowClone.parentNode().range(); + shadowClone.setInitialPosition(); + shadowClone.hideClone(false); + shadowClone.hideParentProperty(true); + shadowClone.updateElement(); + deleteGroupElement.classed("hidden", true); + addDataPropertyGroupElement.classed("hidden", true); + + frozenDomainForPropertyDragger.frozen(true); + frozenDomainForPropertyDragger.locked(true); + frozenRangeForPropertyDragger.frozen(true); + frozenRangeForPropertyDragger.locked(true); + domainDragger.updateElement(); + domainDragger.mouseButtonPressed = true; + rangeDragger.updateElement(); + rangeDragger.mouseButtonPressed = true; + } + else { + d.locked(true); + moved = false; + } + }) + .on("drag", function ( d ){ + + if ( d.type && d.type() === "Class_dragger" ) { + clearTimeout(delayedHider); + classDragger.setPosition(d3.event.x, d3.event.y); + } else if ( d.type && d.type() === "Range_dragger" ) { + clearTimeout(delayedHider); + rangeDragger.setPosition(d3.event.x, d3.event.y); + shadowClone.setPosition(d3.event.x, d3.event.y); + domainDragger.updateElementViaRangeDragger(d3.event.x, d3.event.y); + } + else if ( d.type && d.type() === "Domain_dragger" ) { + clearTimeout(delayedHider); + domainDragger.setPosition(d3.event.x, d3.event.y); + shadowClone.setPositionDomain(d3.event.x, d3.event.y); + rangeDragger.updateElementViaDomainDragger(d3.event.x, d3.event.y); + } + + else { + d.px = d3.event.x; + d.py = d3.event.y; + force.resume(); + updateHaloRadius(); + moved = true; + if ( d.renderType && d.renderType() === "round" ) { + classDragger.setParentNode(d); + } + + } + }) + .on("dragend", function ( d ){ + graph.ignoreOtherHoverEvents(false); + if ( d.type && d.type() === "Class_dragger" ) { + var nX = classDragger.x; + var nY = classDragger.y; + clearTimeout(delayedHider); + classDragger.mouseButtonPressed = false; + classDragger.selectedViaTouch(false); + d.setParentNode(d.parentNode()); + + var draggerEndPos = [nX, nY]; + var targetNode = graph.getTargetNode(draggerEndPos); + if ( targetNode ) { + createNewObjectProperty(d.parentNode(), targetNode, draggerEndPos); + } + if ( touchDevice === false ) { + editElementHoverOut(); + } + draggingStarted = false; + } else if ( d.type && d.type() === "Range_dragger" ) { + graph.ignoreOtherHoverEvents(false); + frozenDomainForPropertyDragger.frozen(false); + frozenDomainForPropertyDragger.locked(false); + frozenRangeForPropertyDragger.frozen(false); + frozenRangeForPropertyDragger.locked(false); + rangeDragger.mouseButtonPressed = false; + domainDragger.mouseButtonPressed = false; + domainDragger.updateElement(); + rangeDragger.updateElement(); + shadowClone.hideClone(true); + var rX = rangeDragger.x; + var rY = rangeDragger.y; + var rangeDraggerEndPos = [rX, rY]; + var targetRangeNode = graph.getTargetNode(rangeDraggerEndPos); + if ( elementTools.isDatatype(targetRangeNode) === true ) { + targetRangeNode = null; + console.log("---------------TARGET NODE IS A DATATYPE/ LITERAL ------------"); + } + + if ( targetRangeNode === null ) { + d.reDrawEverthing(); + shadowClone.hideParentProperty(false); + } + else { + d.updateRange(targetRangeNode); + graph.update(); + shadowClone.hideParentProperty(false); + } + } else if ( d.type && d.type() === "Domain_dragger" ) { + graph.ignoreOtherHoverEvents(false); + frozenDomainForPropertyDragger.frozen(false); + frozenDomainForPropertyDragger.locked(false); + frozenRangeForPropertyDragger.frozen(false); + frozenRangeForPropertyDragger.locked(false); + rangeDragger.mouseButtonPressed = false; + domainDragger.mouseButtonPressed = false; + domainDragger.updateElement(); + rangeDragger.updateElement(); + shadowClone.hideClone(true); + + var dX = domainDragger.x; + var dY = domainDragger.y; + var domainDraggerEndPos = [dX, dY]; + var targetDomainNode = graph.getTargetNode(domainDraggerEndPos); + if ( elementTools.isDatatype(targetDomainNode) === true ) { + targetDomainNode = null; + console.log("---------------TARGET NODE IS A DATATYPE/ LITERAL ------------"); + } + shadowClone.hideClone(true); + if ( targetDomainNode === null ) { + d.reDrawEverthing(); + shadowClone.hideParentProperty(false); + } + else { + d.updateDomain(targetDomainNode); + graph.update(); + shadowClone.hideParentProperty(false); + } + } + + else { + d.locked(false); + var pnp = graph.options().pickAndPinModule(); + if ( pnp.enabled() === true && moved === true ) { + if ( d.id ) { // node + pnp.handle(d, true); + } + if ( d.property ) { + pnp.handle(d.property(), true); + } + } + } + }); + + // Apply the zooming factor. + zoom = d3.behavior.zoom() + .duration(150) + .scaleExtent([options.minMagnification(), options.maxMagnification()]) + .on("zoom", zoomed); + + draggerObjectsArray.push(classDragger); + draggerObjectsArray.push(rangeDragger); + draggerObjectsArray.push(domainDragger); + draggerObjectsArray.push(shadowClone); + force.stop(); + } + + graph.lazyRefresh = function (){ + redrawContent(); + recalculatePositions(); + }; + + graph.adjustingGraphSize = function ( val ){ + adjustingGraphSize = val; + }; + + graph.showReloadButtonAfterLayoutOptimization = function ( show ){ + showReloadButtonAfterLayoutOptimization = show; + }; + + + function hiddenRecalculatePositions(){ + finishedLoadingSequence = false; + if ( graph.options().loadingModule().successfullyLoadedOntology() === false ) { + force.stop(); + d3.select("#progressBarValue").node().innerHTML = ""; + graph.updateProgressBarMode(); + graph.options().loadingModule().showErrorDetailsMessage(hiddenRecalculatePositions); + if ( keepDetailsCollapsedOnLoading && adjustingGraphSize === false ) { + graph.options().loadingModule().collapseDetails("hiddenRecalculatePositions"); + } + return; + } + if ( updateRenderingDuringSimulation === false ) { + var value = 1.0 - 10 * force.alpha(); + var percent = parseInt(200 * value) + "%"; + graph.options().loadingModule().setPercentValue(percent); + d3.select("#progressBarValue").style("width", percent); + d3.select("#progressBarValue").node().innerHTML = percent; + + if ( value > 0.49 ) { + updateRenderingDuringSimulation = true; + // show graph container; + if ( graphContainer ) { + graphContainer.style("opacity", "1"); + percent = "100%"; + d3.select("#progressBarValue").style("width", percent); + d3.select("#progressBarValue").node().innerHTML = percent; + graph.options().ontologyMenu().append_message_toLastBulletPoint("done"); + d3.select("#reloadCachedOntology").classed("hidden", !showReloadButtonAfterLayoutOptimization); + if ( showFilterWarning === true && seenFilterWarning === false ) { + graph.options().warningModule().showFilterHint(); + seenFilterWarning = true; + } + } + + if ( initialLoad ) { + if ( graph.paused() === false ) + force.resume(); // resume force + initialLoad = false; + + } + + + finishedLoadingSequence = true; + if ( showFPS === true ) { + force.on("tick", recalculatePositionsWithFPS); + recalculatePositionsWithFPS(); + } + else { + force.on("tick", recalculatePositions); + recalculatePositions(); + } + + if ( centerGraphViewOnLoad === true && force.nodes().length > 0 ) { + if ( force.nodes().length < 10 ) graph.forceRelocationEvent(true); // uses dynamic zoomer; + else graph.forceRelocationEvent(); + centerGraphViewOnLoad = false; + // console.log("--------------------------------------") + } + + + graph.showEditorHintIfNeeded(); + + if ( graph.options().loadingModule().missingImportsWarning() === false ) { + graph.options().loadingModule().hideLoadingIndicator(); + graph.options().ontologyMenu().append_bulletPoint("Successfully loaded ontology"); + graph.options().loadingModule().setSuccessful(); + } else { + graph.options().loadingModule().showWarningDetailsMessage(); + graph.options().ontologyMenu().append_bulletPoint("Loaded ontology with warnings"); + } + } + } + } + + graph.showEditorHintIfNeeded = function (){ + if ( seenEditorHint === false && editMode === true ) { + seenEditorHint = true; + graph.options().warningModule().showEditorHint(); + } + }; + + graph.setForceTickFunctionWithFPS = function (){ + showFPS = true; + if ( force && finishedLoadingSequence === true ) { + force.on("tick", recalculatePositionsWithFPS); + } + + }; + graph.setDefaultForceTickFunction = function (){ + showFPS = false; + if ( force && finishedLoadingSequence === true ) { + force.on("tick", recalculatePositions); + } + }; + function recalculatePositionsWithFPS(){ + // compute the fps + + recalculatePositions(); + now = Date.now(); + var diff = now - then; + var fps = (1000 / (diff)).toFixed(2); + + debugContainer.node().innerHTML = "FPS: " + fps + "
    " + "Nodes: " + force.nodes().length + "
    " + "Links: " + force.links().length; + then = Date.now(); + + } + + function recalculatePositions(){ + // Set node positions + + + // add switch for edit mode to make this faster; + if ( !editMode ) { + nodeElements.attr("transform", function ( node ){ + return "translate(" + node.x + "," + node.y + ")"; + }); + + // Set label group positions + labelGroupElements.attr("transform", function ( label ){ + var position; + + // force centered positions on single-layered links + var link = label.link(); + if ( link.layers().length === 1 && !link.loops() ) { + var linkDomainIntersection = math.calculateIntersection(link.range(), link.domain(), 0); + var linkRangeIntersection = math.calculateIntersection(link.domain(), link.range(), 0); + position = math.calculateCenter(linkDomainIntersection, linkRangeIntersection); + label.x = position.x; + label.y = position.y; + } + return "translate(" + label.x + "," + label.y + ")"; + }); + // Set link paths and calculate additional information + linkPathElements.attr("d", function ( l ){ + if ( l.isLoop() ) { + return math.calculateLoopPath(l); + } + var curvePoint = l.label(); + var pathStart = math.calculateIntersection(curvePoint, l.domain(), 1); + var pathEnd = math.calculateIntersection(curvePoint, l.range(), 1); + + return curveFunction([pathStart, curvePoint, pathEnd]); + }); + + // Set cardinality positions + cardinalityElements.attr("transform", function ( property ){ + + var label = property.link().label(), + pos = math.calculateIntersection(label, property.range(), CARDINALITY_HDISTANCE), + normalV = math.calculateNormalVector(label, property.range(), CARDINALITY_VDISTANCE); + + return "translate(" + (pos.x + normalV.x) + "," + (pos.y + normalV.y) + ")"; + }); + + + updateHaloRadius(); + return; + } + + // TODO: this is Editor redraw function // we need to make this faster!! + + + nodeElements.attr("transform", function ( node ){ + return "translate(" + node.x + "," + node.y + ")"; + }); + + // Set label group positions + labelGroupElements.attr("transform", function ( label ){ + var position; + + // force centered positions on single-layered links + var link = label.link(); + if ( link.layers().length === 1 && !link.loops() ) { + var linkDomainIntersection = math.calculateIntersection(link.range(), link.domain(), 0); + var linkRangeIntersection = math.calculateIntersection(link.domain(), link.range(), 0); + position = math.calculateCenter(linkDomainIntersection, linkRangeIntersection); + label.x = position.x; + label.y = position.y; + label.linkRangeIntersection = linkRangeIntersection; + label.linkDomainIntersection = linkDomainIntersection; + if ( link.property().focused() === true || hoveredPropertyElement !== undefined ) { + rangeDragger.updateElement(); + domainDragger.updateElement(); + // shadowClone.setPosition(link.property().range().x,link.property().range().y); + // shadowClone.setPositionDomain(link.property().domain().x,link.property().domain().y); + } + } else { + label.linkDomainIntersection = math.calculateIntersection(link.label(), link.domain(), 0); + label.linkRangeIntersection = math.calculateIntersection(link.label(), link.range(), 0); + if ( link.property().focused() === true || hoveredPropertyElement !== undefined ) { + rangeDragger.updateElement(); + domainDragger.updateElement(); + // shadowClone.setPosition(link.property().range().x,link.property().range().y); + // shadowClone.setPositionDomain(link.property().domain().x,link.property().domain().y); + } + + } + return "translate(" + label.x + "," + label.y + ")"; + }); + // Set link paths and calculate additional information + linkPathElements.attr("d", function ( l ){ + if ( l.isLoop() ) { + + var ptrAr = math.getLoopPoints(l); + l.label().linkRangeIntersection = ptrAr[1]; + l.label().linkDomainIntersection = ptrAr[0]; + + if ( l.property().focused() === true || hoveredPropertyElement !== undefined ) { + rangeDragger.updateElement(); + domainDragger.updateElement(); + } + return math.calculateLoopPath(l); + } + var curvePoint = l.label(); + var pathStart = math.calculateIntersection(curvePoint, l.domain(), 1); + var pathEnd = math.calculateIntersection(curvePoint, l.range(), 1); + l.linkRangeIntersection = pathStart; + l.linkDomainIntersection = pathEnd; + if ( l.property().focused() === true || hoveredPropertyElement !== undefined ) { + domainDragger.updateElement(); + rangeDragger.updateElement(); + // shadowClone.setPosition(l.property().range().x,l.property().range().y); + // shadowClone.setPositionDomain(l.property().domain().x,l.property().domain().y); + } + return curveFunction([pathStart, curvePoint, pathEnd]); + }); + + // Set cardinality positions + cardinalityElements.attr("transform", function ( property ){ + + var label = property.link().label(), + pos = math.calculateIntersection(label, property.range(), CARDINALITY_HDISTANCE), + normalV = math.calculateNormalVector(label, property.range(), CARDINALITY_VDISTANCE); + + return "translate(" + (pos.x + normalV.x) + "," + (pos.y + normalV.y) + ")"; + }); + + if ( hoveredNodeElement ) { + setDeleteHoverElementPosition(hoveredNodeElement); + setAddDataPropertyHoverElementPosition(hoveredNodeElement); + if ( draggingStarted === false ) { + classDragger.setParentNode(hoveredNodeElement); + } + } + if ( hoveredPropertyElement ) { + setDeleteHoverElementPositionProperty(hoveredPropertyElement); + } + + updateHaloRadius(); + } + + graph.updatePropertyDraggerElements = function ( property ){ + if ( property.type() !== "owl:DatatypeProperty" ) { + + shadowClone.setParentProperty(property); + rangeDragger.setParentProperty(property); + rangeDragger.hideDragger(false); + rangeDragger.addMouseEvents(); + domainDragger.setParentProperty(property); + domainDragger.hideDragger(false); + domainDragger.addMouseEvents(); + + } + else { + rangeDragger.hideDragger(true); + domainDragger.hideDragger(true); + shadowClone.hideClone(true); + } + }; + + function addClickEvents(){ + function executeModules( selectedElement ){ + options.selectionModules().forEach(function ( module ){ + module.handle(selectedElement); + }); + } + + nodeElements.on("click", function ( clickedNode ){ + + // manaual double clicker // helper for iphone 6 etc... + if ( touchDevice === true && doubletap() === true ) { + d3.event.stopPropagation(); + if ( editMode === true ) { + clickedNode.raiseDoubleClickEdit(defaultIriValue(clickedNode)); + } + } + else { + executeModules(clickedNode); + } + }); + + nodeElements.on("dblclick", function ( clickedNode ){ + + d3.event.stopPropagation(); + if ( editMode === true ) { + clickedNode.raiseDoubleClickEdit(defaultIriValue(clickedNode)); + } + }); + + labelGroupElements.selectAll(".label").on("click", function ( clickedProperty ){ + executeModules(clickedProperty); + + // this is for enviroments that do not define dblClick function; + if ( touchDevice === true && doubletap() === true ) { + d3.event.stopPropagation(); + if ( editMode === true ) { + clickedProperty.raiseDoubleClickEdit(defaultIriValue(clickedProperty)); + } + } + + // currently removed the selection of an element to invoke the dragger + // if (editMode===true && clickedProperty.editingTextElement!==true) { + // return; + // // We say that Datatype properties are not allowed to have domain range draggers + // if (clickedProperty.focused() && clickedProperty.type() !== "owl:DatatypeProperty") { + // shadowClone.setParentProperty(clickedProperty); + // rangeDragger.setParentProperty(clickedProperty); + // rangeDragger.hideDragger(false); + // rangeDragger.addMouseEvents(); + // domainDragger.setParentProperty(clickedProperty); + // domainDragger.hideDragger(false); + // domainDragger.addMouseEvents(); + // + // if (clickedProperty.domain()===clickedProperty.range()){ + // clickedProperty.labelObject().increasedLoopAngle=true; + // recalculatePositions(); + // + // } + // + // } else if (clickedProperty.focused() && clickedProperty.type() === "owl:DatatypeProperty") { + // shadowClone.setParentProperty(clickedProperty); + // rangeDragger.setParentProperty(clickedProperty); + // rangeDragger.hideDragger(true); + // rangeDragger.addMouseEvents(); + // domainDragger.setParentProperty(clickedProperty); + // domainDragger.hideDragger(false); + // domainDragger.addMouseEvents(); + // + // } + // else { + // rangeDragger.hideDragger(true); + // domainDragger.hideDragger(true); + // if (clickedProperty.domain()===clickedProperty.range()){ + // clickedProperty.labelObject().increasedLoopAngle=false; + // recalculatePositions(); + // + // } + // } + // } + }); + labelGroupElements.selectAll(".label").on("dblclick", function ( clickedProperty ){ + d3.event.stopPropagation(); + if ( editMode === true ) { + clickedProperty.raiseDoubleClickEdit(defaultIriValue(clickedProperty)); + } + + }); + } + + function defaultIriValue( element ){ + // get the iri of that element; + if ( graph.options().getGeneralMetaObject().iri ) { + var str2Compare = graph.options().getGeneralMetaObject().iri + element.id(); + return element.iri() === str2Compare; + } + return false; + } + + /** Adjusts the containers current scale and position. */ + function zoomed(){ + if ( forceNotZooming === true ) { + zoom.translate(graphTranslation); + zoom.scale(zoomFactor); + return; + } + + + var zoomEventByMWheel = false; + if ( d3.event.sourceEvent ) { + if ( d3.event.sourceEvent.deltaY ) zoomEventByMWheel = true; + } + if ( zoomEventByMWheel === false ) { + if ( transformAnimation === true ) { + return; + } + zoomFactor = d3.event.scale; + graphTranslation = d3.event.translate; + graphContainer.attr("transform", "translate(" + graphTranslation + ")scale(" + zoomFactor + ")"); + updateHaloRadius(); + graph.options().zoomSlider().updateZoomSliderValue(zoomFactor); + return; + } + /** animate the transition **/ + zoomFactor = d3.event.scale; + graphTranslation = d3.event.translate; + graphContainer.transition() + .tween("attr.translate", function (){ + return function ( t ){ + transformAnimation = true; + var tr = d3.transform(graphContainer.attr("transform")); + graphTranslation[0] = tr.translate[0]; + graphTranslation[1] = tr.translate[1]; + zoomFactor = tr.scale[0]; + updateHaloRadius(); + graph.options().zoomSlider().updateZoomSliderValue(zoomFactor); + }; + }) + .each("end", function (){ + transformAnimation = false; + }) + .attr("transform", "translate(" + graphTranslation + ")scale(" + zoomFactor + ")") + .ease('linear') + .duration(250); + }// end of zoomed function + + function redrawGraph(){ + remove(); + + graphContainer = d3.selectAll(options.graphContainerSelector()) + .append("svg") + .classed("vowlGraph", true) + .attr("width", options.width()) + .attr("height", options.height()) + .call(zoom) + .append("g"); + // add touch and double click functions + + var svgGraph = d3.selectAll(".vowlGraph"); + originalD3_dblClickFunction = svgGraph.on("dblclick.zoom"); + originalD3_touchZoomFunction = svgGraph.on("touchstart"); + svgGraph.on("touchstart", touchzoomed); + if ( editMode === true ) { + svgGraph.on("dblclick.zoom", graph.modified_dblClickFunction); + } + else { + svgGraph.on("dblclick.zoom", originalD3_dblClickFunction); + } + + } + + function generateEditElements(){ + addDataPropertyGroupElement = editContainer.append('g') + .classed("hidden-in-export", true) + .classed("hidden", true) + .classed("addDataPropertyElement", true) + .attr("transform", "translate(" + 0 + "," + 0 + ")"); + + + addDataPropertyGroupElement.append("circle") + // .classed("deleteElement", true) + .attr("r", 12) + .attr("cx", 0) + .attr("cy", 0) + .append("title").text("Add Datatype Property"); + + addDataPropertyGroupElement.append("line") + // .classed("deleteElementIcon ",true) + .attr("x1", -8) + .attr("y1", 0) + .attr("x2", 8) + .attr("y2", 0) + .append("title").text("Add Datatype Property"); + + addDataPropertyGroupElement.append("line") + // .classed("deleteElementIcon",true) + .attr("x1", 0) + .attr("y1", -8) + .attr("x2", 0) + .attr("y2", 8) + .append("title").text("Add Datatype Property"); + + if ( graph.options().useAccuracyHelper() ) { + addDataPropertyGroupElement.append("circle") + .attr("r", 15) + .attr("cx", -7) + .attr("cy", 7) + .classed("superHiddenElement", true) + .classed("superOpacityElement", !graph.options().showDraggerObject()); + } + + + deleteGroupElement = editContainer.append('g') + .classed("hidden-in-export", true) + .classed("hidden", true) + .classed("deleteParentElement", true) + .attr("transform", "translate(" + 0 + "," + 0 + ")"); + + deleteGroupElement.append("circle") + .attr("r", 12) + .attr("cx", 0) + .attr("cy", 0) + .append("title").text("Delete This Node"); + + var crossLen = 5; + deleteGroupElement.append("line") + .attr("x1", -crossLen) + .attr("y1", -crossLen) + .attr("x2", crossLen) + .attr("y2", crossLen) + .append("title").text("Delete This Node"); + + deleteGroupElement.append("line") + .attr("x1", crossLen) + .attr("y1", -crossLen) + .attr("x2", -crossLen) + .attr("y2", crossLen) + .append("title").text("Delete This Node"); + + if ( graph.options().useAccuracyHelper() ) { + deleteGroupElement.append("circle") + .attr("r", 15) + .attr("cx", 7) + .attr("cy", -7) + .classed("superHiddenElement", true) + .classed("superOpacityElement", !graph.options().showDraggerObject()); + } + + + } + + graph.getUnfilteredData = function (){ + return unfilteredData; + }; + + graph.getClassDataForTtlExport = function (){ + var allNodes = unfilteredData.nodes; + var nodeData = []; + for ( var i = 0; i < allNodes.length; i++ ) { + if ( allNodes[i].type() !== "rdfs:Literal" && + allNodes[i].type() !== "rdfs:Datatype" && + allNodes[i].type() !== "owl:Thing" ) { + nodeData.push(allNodes[i]); + } + } + return nodeData; + }; + + graph.getPropertyDataForTtlExport = function (){ + var propertyData = []; + var allProperties = unfilteredData.properties; + for ( var i = 0; i < allProperties.length; i++ ) { + // currently using only the object properties + if ( allProperties[i].type() === "owl:ObjectProperty" || + allProperties[i].type() === "owl:DatatypeProperty" || + allProperties[i].type() === "owl:ObjectProperty" + + ) { + propertyData.push(allProperties[i]); + } else { + if ( allProperties[i].type() === "rdfs:subClassOf" ) { + allProperties[i].baseIri("http://www.w3.org/2000/01/rdf-schema#"); + allProperties[i].iri("http://www.w3.org/2000/01/rdf-schema#subClassOf"); + } + if ( allProperties[i].type() === "owl:disjointWith" ) { + allProperties[i].baseIri("http://www.w3.org/2002/07/owl#"); + allProperties[i].iri("http://www.w3.org/2002/07/owl#disjointWith"); + } + } + } + return propertyData; + }; + + graph.getAxiomsForTtlExport = function (){ + var axioms = []; + var allProperties = unfilteredData.properties; + for ( var i = 0; i < allProperties.length; i++ ) { + // currently using only the object properties + if ( allProperties[i].type() === "owl:ObjectProperty" || + allProperties[i].type() === "owl:DatatypeProperty" || + allProperties[i].type() === "owl:ObjectProperty" || + allProperties[i].type() === "rdfs:subClassOf" + ) { + } else { + } + } + return axioms; + }; + + + graph.getUnfilteredData = function (){ + return unfilteredData; + }; + + graph.getClassDataForTtlExport = function (){ + var allNodes = unfilteredData.nodes; + var nodeData = []; + for ( var i = 0; i < allNodes.length; i++ ) { + if ( allNodes[i].type() !== "rdfs:Literal" && + allNodes[i].type() !== "rdfs:Datatype" && + allNodes[i].type() !== "owl:Thing" ) { + nodeData.push(allNodes[i]); + } + } + return nodeData; + }; + + + function redrawContent(){ + var markerContainer; + + if ( !graphContainer ) { + return; + } + + // Empty the graph container + graphContainer.selectAll("*").remove(); + + // Last container -> elements of this container overlap others + linkContainer = graphContainer.append("g").classed("linkContainer", true); + cardinalityContainer = graphContainer.append("g").classed("cardinalityContainer", true); + labelContainer = graphContainer.append("g").classed("labelContainer", true); + nodeContainer = graphContainer.append("g").classed("nodeContainer", true); + + // adding editing Elements + var draggerPathLayer = graphContainer.append("g").classed("linkContainer", true); + draggerLayer = graphContainer.append("g").classed("editContainer", true); + editContainer = graphContainer.append("g").classed("editContainer", true); + + draggerPathLayer.classed("hidden-in-export", true); + editContainer.classed("hidden-in-export", true); + draggerLayer.classed("hidden-in-export", true); + + // Add an extra container for all markers + markerContainer = linkContainer.append("defs"); + var drElement = draggerLayer.selectAll(".node") + .data(draggerObjectsArray).enter() + .append("g") + .classed("node", true) + .classed("hidden-in-export", true) + .attr("id", function ( d ){ + return d.id(); + }) + .call(dragBehaviour); + drElement.each(function ( node ){ + node.svgRoot(d3.select(this)); + node.svgPathLayer(draggerPathLayer); + if ( node.type() === "shadowClone" ) { + node.drawClone(); + node.hideClone(true); + } else { + node.drawNode(); + node.hideDragger(true); + } + }); + generateEditElements(); + + + // Add an extra container for all markers + markerContainer = linkContainer.append("defs"); + + // Draw nodes + + if ( classNodes === undefined ) classNodes = []; + + nodeElements = nodeContainer.selectAll(".node") + .data(classNodes).enter() + .append("g") + .classed("node", true) + .attr("id", function ( d ){ + return d.id(); + }) + .call(dragBehaviour); + nodeElements.each(function ( node ){ + node.draw(d3.select(this)); + }); + + + if ( labelNodes === undefined ) labelNodes = []; + + // Draw label groups (property + inverse) + labelGroupElements = labelContainer.selectAll(".labelGroup") + .data(labelNodes).enter() + .append("g") + .classed("labelGroup", true) + .call(dragBehaviour); + + labelGroupElements.each(function ( label ){ + var success = label.draw(d3.select(this)); + label.property().labelObject(label); + // Remove empty groups without a label. + if ( !success ) { + d3.select(this).remove(); + } + }); + // Place subclass label groups on the bottom of all labels + labelGroupElements.each(function ( label ){ + // the label might be hidden e.g. in compact notation + if ( !this.parentNode ) { + return; + } + + if ( elementTools.isRdfsSubClassOf(label.property()) ) { + var parentNode = this.parentNode; + parentNode.insertBefore(this, parentNode.firstChild); + } + }); + if ( properties === undefined ) properties = []; + // Draw cardinality elements + cardinalityElements = cardinalityContainer.selectAll(".cardinality") + .data(properties).enter() + .append("g") + .classed("cardinality", true); + + cardinalityElements.each(function ( property ){ + var success = property.drawCardinality(d3.select(this)); + + // Remove empty groups without a label. + if ( !success ) { + d3.select(this).remove(); + } + }); + // Draw links + if ( links === undefined ) links = []; + linkGroups = linkContainer.selectAll(".link") + .data(links).enter() + .append("g") + .classed("link", true); + + linkGroups.each(function ( link ){ + link.draw(d3.select(this), markerContainer); + }); + linkPathElements = linkGroups.selectAll("path"); + // Select the path for direct access to receive a better performance + addClickEvents(); + } + + function remove(){ + if ( graphContainer ) { + // Select the parent element because the graph container is a group (e.g. for zooming) + d3.select(graphContainer.node().parentNode).remove(); + } + } + + initializeGraph(); // << call the initialization function + + graph.updateCanvasContainerSize = function (){ + if ( graphContainer ) { + var svgElement = d3.selectAll(".vowlGraph"); + svgElement.attr("width", options.width()); + svgElement.attr("height", options.height()); + graphContainer.attr("transform", "translate(" + graphTranslation + ")scale(" + zoomFactor + ")"); + } + }; + + // Loads all settings, removes the old graph (if it exists) and draws a new one. + graph.start = function (){ + force.stop(); + loadGraphData(true); + redrawGraph(); + graph.update(true); + + if ( graph.options().loadingModule().successfullyLoadedOntology() === false ) { + graph.options().loadingModule().setErrorMode(); + } + + }; + + // Updates only the style of the graph. + graph.updateStyle = function (){ + refreshGraphStyle(); + if ( graph.options().loadingModule().successfullyLoadedOntology() === false ) { + force.stop(); + } else { + force.start(); + } + }; + + graph.reload = function (){ + loadGraphData(); + graph.update(); + + }; + + graph.load = function (){ + force.stop(); + loadGraphData(); + refreshGraphData(); + for ( var i = 0; i < labelNodes.length; i++ ) { + var label = labelNodes[i]; + if ( label.property().x && label.property().y ) { + label.x = label.property().x; + label.y = label.property().y; + // also set the prev position of the label + label.px = label.x; + label.py = label.y; + } + } + graph.update(); + }; + + graph.fastUpdate = function (){ + // fast update function for editor calls; + // -- experimental ; + quick_refreshGraphData(); + updateNodeMap(); + force.start(); + redrawContent(); + graph.updatePulseIds(nodeArrayForPulse); + refreshGraphStyle(); + updateHaloStyles(); + + }; + + graph.getNodeMapForSearch = function (){ + return nodeMap; + }; + function updateNodeMap(){ + nodeMap = []; + var node; + for ( var j = 0; j < force.nodes().length; j++ ) { + node = force.nodes()[j]; + if ( node.id ) { + nodeMap[node.id()] = j; + // check for equivalents + var eqs = node.equivalents(); + if ( eqs.length > 0 ) { + for ( var e = 0; e < eqs.length; e++ ) { + var eqObject = eqs[e]; + nodeMap[eqObject.id()] = j; + } + } + } + if ( node.property ) { + nodeMap[node.property().id()] = j; + var inverse = node.inverse(); + if ( inverse ) { + nodeMap[inverse.id()] = j; + } + } + } + } + + function updateHaloStyles(){ + var haloElement; + var halo; + var node; + for ( var j = 0; j < force.nodes().length; j++ ) { + node = force.nodes()[j]; + if ( node.id ) { + haloElement = node.getHalos(); + if ( haloElement ) { + halo = haloElement.selectAll(".searchResultA"); + halo.classed("searchResultA", false); + halo.classed("searchResultB", true); + } + } + + if ( node.property ) { + haloElement = node.property().getHalos(); + if ( haloElement ) { + halo = haloElement.selectAll(".searchResultA"); + halo.classed("searchResultA", false); + halo.classed("searchResultB", true); + } + } + } + } + + // Updates the graphs displayed data and style. + graph.update = function ( init ){ + var validOntology = graph.options().loadingModule().successfullyLoadedOntology(); + if ( validOntology === false && (init && init === true) ) { + graph.options().loadingModule().collapseDetails(); + return; + } + if ( validOntology === false ) { + return; + } + + keepDetailsCollapsedOnLoading = false; + refreshGraphData(); + // update node map + updateNodeMap(); + + force.start(); + redrawContent(); + graph.updatePulseIds(nodeArrayForPulse); + refreshGraphStyle(); + updateHaloStyles(); + }; + + graph.paused = function ( p ){ + if ( !arguments.length ) return paused; + paused = p; + graph.updateStyle(); + return graph; + }; + // resetting the graph + graph.reset = function (){ + // window size + var w = 0.5 * graph.options().width(); + var h = 0.5 * graph.options().height(); + // computing initial translation for the graph due tue the dynamic default zoom level + var tx = w - defaultZoom * w; + var ty = h - defaultZoom * h; + zoom.translate([tx, ty]) + .scale(defaultZoom); + }; + + + graph.zoomOut = function (){ + + var minMag = options.minMagnification(), + maxMag = options.maxMagnification(); + var stepSize = (maxMag - minMag) / 10; + var val = zoomFactor - stepSize; + if ( val < minMag ) val = minMag; + + var cx = 0.5 * graph.options().width(); + var cy = 0.5 * graph.options().height(); + var cp = getWorldPosFromScreen(cx, cy, graphTranslation, zoomFactor); + var sP = [cp.x, cp.y, graph.options().height() / zoomFactor]; + var eP = [cp.x, cp.y, graph.options().height() / val]; + var pos_intp = d3.interpolateZoom(sP, eP); + + graphContainer.attr("transform", transform(sP, cx, cy)) + .transition() + .duration(250) + .attrTween("transform", function (){ + return function ( t ){ + return transform(pos_intp(t), cx, cy); + }; + }) + .each("end", function (){ + graphContainer.attr("transform", "translate(" + graphTranslation + ")scale(" + zoomFactor + ")"); + zoom.translate(graphTranslation); + zoom.scale(zoomFactor); + updateHaloRadius(); + options.zoomSlider().updateZoomSliderValue(zoomFactor); + }); + + }; + + graph.zoomIn = function (){ + var minMag = options.minMagnification(), + maxMag = options.maxMagnification(); + var stepSize = (maxMag - minMag) / 10; + var val = zoomFactor + stepSize; + if ( val > maxMag ) val = maxMag; + var cx = 0.5 * graph.options().width(); + var cy = 0.5 * graph.options().height(); + var cp = getWorldPosFromScreen(cx, cy, graphTranslation, zoomFactor); + var sP = [cp.x, cp.y, graph.options().height() / zoomFactor]; + var eP = [cp.x, cp.y, graph.options().height() / val]; + var pos_intp = d3.interpolateZoom(sP, eP); + + graphContainer.attr("transform", transform(sP, cx, cy)) + .transition() + .duration(250) + .attrTween("transform", function (){ + return function ( t ){ + return transform(pos_intp(t), cx, cy); + }; + }) + .each("end", function (){ + graphContainer.attr("transform", "translate(" + graphTranslation + ")scale(" + zoomFactor + ")"); + zoom.translate(graphTranslation); + zoom.scale(zoomFactor); + updateHaloRadius(); + options.zoomSlider().updateZoomSliderValue(zoomFactor); + }); + + + }; + + /** --------------------------------------------------------- **/ + /** -- data related handling -- **/ + /** --------------------------------------------------------- **/ + + var cachedJsonOBJ = null; + graph.clearAllGraphData = function (){ + if ( graph.graphNodeElements() && graph.graphNodeElements().length > 0 ) { + cachedJsonOBJ = graph.options().exportMenu().createJSON_exportObject(); + } else { + cachedJsonOBJ = null; + } + force.stop(); + if ( unfilteredData ) { + unfilteredData.nodes = []; + unfilteredData.properties = []; + } + }; + graph.getCachedJsonObj = function (){ + return cachedJsonOBJ; + }; + + // removes data when data could not be loaded + graph.clearGraphData = function (){ + force.stop(); + var sidebar = graph.options().sidebar(); + if ( sidebar ) + sidebar.clearOntologyInformation(); + if ( graphContainer ) + redrawGraph(); + }; + + function generateDictionary( data ){ + var i; + var originalDictionary = []; + var nodes = data.nodes; + for ( i = 0; i < nodes.length; i++ ) { + // check if node has a label + if ( nodes[i].labelForCurrentLanguage() !== undefined ) + originalDictionary.push(nodes[i]); + } + var props = data.properties; + for ( i = 0; i < props.length; i++ ) { + if ( props[i].labelForCurrentLanguage() !== undefined ) + originalDictionary.push(props[i]); + } + parser.setDictionary(originalDictionary); + + var literFilter = graph.options().literalFilter(); + var idsToRemove = literFilter.removedNodes(); + var originalDict = parser.getDictionary(); + var newDict = []; + + // go through the dictionary and remove the ids; + for ( i = 0; i < originalDict.length; i++ ) { + var dictElement = originalDict[i]; + var dictElementId; + if ( dictElement.property ) + dictElementId = dictElement.property().id(); + else + dictElementId = dictElement.id(); + // compare against the removed ids; + var addToDictionary = true; + for ( var j = 0; j < idsToRemove.length; j++ ) { + var currentId = idsToRemove[j]; + if ( currentId === dictElementId ) { + addToDictionary = false; + } + } + if ( addToDictionary === true ) { + newDict.push(dictElement); + } + } + // tell the parser that the dictionary is updated + parser.setDictionary(newDict); + + } + + graph.updateProgressBarMode = function (){ + var loadingModule = graph.options().loadingModule(); + + var state = loadingModule.getProgressBarMode(); + switch ( state ) { + case 0: + loadingModule.setErrorMode(); + break; + case 1: + loadingModule.setBusyMode(); + break; + case 2: + loadingModule.setPercentMode(); + break; + default: + loadingModule.setPercentMode(); + } + }; + + graph.setFilterWarning = function ( val ){ + showFilterWarning = val; + }; + function loadGraphData( init ){ + // reset the locate button and previously selected locations and other variables + + var loadingModule = graph.options().loadingModule(); + force.stop(); + + force.nodes([]); + force.links([]); + nodeArrayForPulse = []; + pulseNodeIds = []; + locationId = 0; + d3.select("#locateSearchResult").classed("highlighted", false); + d3.select("#locateSearchResult").node().title = "Nothing to locate"; + graph.clearGraphData(); + + if ( init ) { + force.stop(); + return; + } + + showFilterWarning = false; + parser.parse(options.data()); + unfilteredData = { + nodes: parser.nodes(), + properties: parser.properties() + }; + // fixing class and property id counter for the editor + eN = unfilteredData.nodes.length + 1; + eP = unfilteredData.properties.length + 1; + + initialLoad = true; + graph.options().warningModule().closeFilterHint(); + + // loading handler + updateRenderingDuringSimulation = true; + var validOntology = graph.options().loadingModule().successfullyLoadedOntology(); + if ( graphContainer && validOntology === true ) { + + updateRenderingDuringSimulation = false; + graph.options().ontologyMenu().append_bulletPoint("Generating visualization ... "); + loadingModule.setPercentMode(); + + if ( unfilteredData.nodes.length > 0 ) { + graphContainer.style("opacity", "0"); + force.on("tick", hiddenRecalculatePositions); + } else { + graphContainer.style("opacity", "1"); + if ( showFPS === true ) { + force.on("tick", recalculatePositionsWithFPS); + } + else { + force.on("tick", recalculatePositions); + } + } + + force.start(); + } else { + force.stop(); + graph.options().ontologyMenu().append_bulletPoint("Failed to load ontology"); + loadingModule.setErrorMode(); + } + // update prefixList( + // update general MetaOBJECT + graph.options().clearMetaObject(); + graph.options().clearGeneralMetaObject(); + graph.options().editSidebar().clearMetaObjectValue(); + if ( options.data() !== undefined ) { + var header = options.data().header; + if ( header ) { + if ( header.iri ) { + graph.options().addOrUpdateGeneralObjectEntry("iri", header.iri); + } + if ( header.title ) { + graph.options().addOrUpdateGeneralObjectEntry("title", header.title); + } + if ( header.author ) { + graph.options().addOrUpdateGeneralObjectEntry("author", header.author); + } + if ( header.version ) { + graph.options().addOrUpdateGeneralObjectEntry("version", header.version); + } + if ( header.description ) { + graph.options().addOrUpdateGeneralObjectEntry("description", header.description); + } + if ( header.prefixList ) { + var pL = header.prefixList; + for ( var pr in pL ) { + if ( pL.hasOwnProperty(pr) ) { + var val = pL[pr]; + graph.options().addPrefix(pr, val); + } + } + } + // get other metadata; + if ( header.other ) { + var otherObjects = header.other; + for ( var name in otherObjects ) { + if ( otherObjects.hasOwnProperty(name) ) { + var otherObj = otherObjects[name]; + if ( otherObj.hasOwnProperty("identifier") && otherObj.hasOwnProperty("value") ) { + graph.options().addOrUpdateMetaObjectEntry(otherObj.identfier, otherObj.value); + } + } + } + } + } + } + // update more meta OBJECT + // Initialize filters with data to replicate consecutive filtering + var initializationData = _.clone(unfilteredData); + options.filterModules().forEach(function ( module ){ + initializationData = filterFunction(module, initializationData, true); + }); + // generate dictionary here ; + generateDictionary(unfilteredData); + + parser.parseSettings(); + graphUpdateRequired = parser.settingsImported(); + centerGraphViewOnLoad = true; + if ( parser.settingsImportGraphZoomAndTranslation() === true ) { + centerGraphViewOnLoad = false; + } + graph.options().searchMenu().requestDictionaryUpdate(); + graph.options().editSidebar().updateGeneralOntologyInfo(); + graph.options().editSidebar().updatePrefixUi(); + graph.options().editSidebar().updateElementWidth(); + } + + graph.handleOnLoadingError = function (){ + force.stop(); + graph.clearGraphData(); + graph.options().ontologyMenu().append_bulletPoint("Failed to load ontology"); + d3.select("#progressBarValue").node().innherHTML = ""; + d3.select("#progressBarValue").classed("busyProgressBar", false); + graph.options().loadingModule().setErrorMode(); + graph.options().loadingModule().showErrorDetailsMessage(); + }; + + function quick_refreshGraphData(){ + links = linkCreator.createLinks(properties); + labelNodes = links.map(function ( link ){ + return link.label(); + }); + + storeLinksOnNodes(classNodes, links); + setForceLayoutData(classNodes, labelNodes, links); + } + + //Applies the data of the graph options object and parses it. The graph is not redrawn. + function refreshGraphData(){ + var shouldExecuteEmptyFilter = options.literalFilter().enabled(); + graph.executeEmptyLiteralFilter(); + options.literalFilter().enabled(shouldExecuteEmptyFilter); + + var preprocessedData = _.clone(unfilteredData); + + // Filter the data + options.filterModules().forEach(function ( module ){ + preprocessedData = filterFunction(module, preprocessedData); + }); + options.focuserModule().handle(undefined, true); + classNodes = preprocessedData.nodes; + properties = preprocessedData.properties; + links = linkCreator.createLinks(properties); + labelNodes = links.map(function ( link ){ + return link.label(); + }); + storeLinksOnNodes(classNodes, links); + setForceLayoutData(classNodes, labelNodes, links); + // for (var i = 0; i < classNodes.length; i++) { + // if (classNodes[i].setRectangularRepresentation) + // classNodes[i].setRectangularRepresentation(graph.options().rectangularRepresentation()); + // } + } + + function filterFunction( module, data, initializing ){ + links = linkCreator.createLinks(data.properties); + storeLinksOnNodes(data.nodes, links); + + if ( initializing ) { + if ( module.initialize ) { + module.initialize(data.nodes, data.properties); + } + } + module.filter(data.nodes, data.properties); + return { + nodes: module.filteredNodes(), + properties: module.filteredProperties() + }; + } + + + /** --------------------------------------------------------- **/ + /** -- force-layout related functions -- **/ + /** --------------------------------------------------------- **/ + function storeLinksOnNodes( nodes, links ){ + for ( var i = 0, nodesLength = nodes.length; i < nodesLength; i++ ) { + var node = nodes[i], + connectedLinks = []; + + // look for properties where this node is the domain or range + for ( var j = 0, linksLength = links.length; j < linksLength; j++ ) { + var link = links[j]; + + if ( link.domain() === node || link.range() === node ) { + connectedLinks.push(link); + } + } + node.links(connectedLinks); + } + } + + function setForceLayoutData( classNodes, labelNodes, links ){ + var d3Links = []; + links.forEach(function ( link ){ + d3Links = d3Links.concat(link.linkParts()); + }); + + var d3Nodes = [].concat(classNodes).concat(labelNodes); + setPositionOfOldLabelsOnNewLabels(force.nodes(), labelNodes); + + force.nodes(d3Nodes) + .links(d3Links); + } + + // The label nodes are positioned randomly, because they are created from scratch if the data changes and lose + // their position information. With this hack the position of old labels is copied to the new labels. + function setPositionOfOldLabelsOnNewLabels( oldLabelNodes, labelNodes ){ + labelNodes.forEach(function ( labelNode ){ + for ( var i = 0; i < oldLabelNodes.length; i++ ) { + var oldNode = oldLabelNodes[i]; + if ( oldNode.equals(labelNode) ) { + labelNode.x = oldNode.x; + labelNode.y = oldNode.y; + labelNode.px = oldNode.px; + labelNode.py = oldNode.py; + break; + } + } + }); + } + + // Applies all options that don't change the graph data. + function refreshGraphStyle(){ + zoom = zoom.scaleExtent([options.minMagnification(), options.maxMagnification()]); + if ( graphContainer ) { + zoom.event(graphContainer); + } + + force.charge(function ( element ){ + var charge = options.charge(); + if ( elementTools.isLabel(element) ) { + charge *= 0.8; + } + return charge; + }) + .size([options.width(), options.height()]) + .linkDistance(calculateLinkPartDistance) + .gravity(options.gravity()) + .linkStrength(options.linkStrength()); // Flexibility of links + + force.nodes().forEach(function ( n ){ + n.frozen(paused); + }); + } + + function calculateLinkPartDistance( linkPart ){ + var link = linkPart.link(); + + if ( link.isLoop() ) { + return options.loopDistance(); + } + + // divide by 2 to receive the length for a single link part + var linkPartDistance = getVisibleLinkDistance(link) / 2; + linkPartDistance += linkPart.domain().actualRadius(); + linkPartDistance += linkPart.range().actualRadius(); + return linkPartDistance; + } + + function getVisibleLinkDistance( link ){ + if ( elementTools.isDatatype(link.domain()) || elementTools.isDatatype(link.range()) ) { + return options.datatypeDistance(); + } else { + return options.classDistance(); + } + } + + /** --------------------------------------------------------- **/ + /** -- animation functions for the nodes -- **/ + /** --------------------------------------------------------- **/ + + graph.animateDynamicLabelWidth = function (){ + var wantedWidth = options.dynamicLabelWidth(); + var i; + for ( i = 0; i < classNodes.length; i++ ) { + var nodeElement = classNodes[i]; + if ( elementTools.isDatatype(nodeElement) ) { + nodeElement.animateDynamicLabelWidth(wantedWidth); + } + } + for ( i = 0; i < properties.length; i++ ) { + properties[i].animateDynamicLabelWidth(wantedWidth); + } + }; + + + /** --------------------------------------------------------- **/ + /** -- halo and localization functions -- **/ + /** --------------------------------------------------------- **/ + function updateHaloRadius(){ + if ( pulseNodeIds && pulseNodeIds.length > 0 ) { + var forceNodes = force.nodes(); + for ( var i = 0; i < pulseNodeIds.length; i++ ) { + var node = forceNodes[pulseNodeIds[i]]; + if ( node ) { + if ( node.property ) { + // match search strings with property label + if ( node.property().inverse ) { + var searchString = graph.options().searchMenu().getSearchString().toLowerCase(); + var name = node.property().labelForCurrentLanguage().toLowerCase(); + if ( name === searchString ) computeDistanceToCenter(node); + else { + node.property().removeHalo(); + if ( node.property().inverse() ) { + if ( !node.property().inverse().getHalos() ) + node.property().inverse().drawHalo(); + computeDistanceToCenter(node, true); + } + if ( node.property().equivalents() ) { + var eq = node.property().equivalents(); + for ( var e = 0; e < eq.length; e++ ) { + if ( !eq[e].getHalos() ) + eq[e].drawHalo(); + } + if ( !node.property().getHalos() ) + node.property().drawHalo(); + computeDistanceToCenter(node, false); + + } + } + } + } + computeDistanceToCenter(node); + } + } + } + } + + function getScreenCoords( x, y, translate, scale ){ + var xn = translate[0] + x * scale; + var yn = translate[1] + y * scale; + return { x: xn, y: yn }; + } + + function getClickedScreenCoords( x, y, translate, scale ){ + var xn = (x - translate[0]) / scale; + var yn = (y - translate[1]) / scale; + return { x: xn, y: yn }; + } + + + function computeDistanceToCenter( node, inverse ){ + var container = node; + var w = graph.options().width(); + var h = graph.options().height(); + var posXY = getScreenCoords(node.x, node.y, graphTranslation, zoomFactor); + + var highlightOfInv = false; + + if ( inverse && inverse === true ) { + highlightOfInv = true; + posXY = getScreenCoords(node.x, node.y + 20, graphTranslation, zoomFactor); + } + var x = posXY.x; + var y = posXY.y; + var nodeIsRect = false; + var halo; + var roundHalo; + var rectHalo; + var borderPoint_x = 0; + var borderPoint_y = 0; + var defaultRadius; + var offset = 15; + var radius; + + if ( node.property && highlightOfInv === true ) { + if ( node.property().inverse() ) { + rectHalo = node.property().inverse().getHalos().select("rect"); + + } else { + if ( node.property().getHalos() ) + rectHalo = node.property().getHalos().select("rect"); + else { + node.property().drawHalo(); + rectHalo = node.property().getHalos().select("rect"); + } + } + rectHalo.classed("hidden", true); + if ( node.property().inverse() ) { + if ( node.property().inverse().getHalos() ) { + roundHalo = node.property().inverse().getHalos().select("circle"); + } + } else { + roundHalo = node.property().getHalos().select("circle"); + } + if ( roundHalo.node() === null ) { + radius = node.property().inverse().width() + 15; + + roundHalo = node.property().inverse().getHalos().append("circle") + .classed("searchResultB", true) + .classed("searchResultA", false) + .attr("r", radius + 15); + + } + halo = roundHalo; // swap the halo to be round + nodeIsRect = true; + container = node.property().inverse(); + } + + if ( node.id ) { + if ( !node.getHalos() ) return; // something went wrong before + halo = node.getHalos().select("rect"); + if ( halo.node() === null ) { + // this is a round node + nodeIsRect = false; + roundHalo = node.getHalos().select("circle"); + defaultRadius = node.actualRadius(); + roundHalo.attr("r", defaultRadius + offset); + halo = roundHalo; + } else { // this is a rect node + nodeIsRect = true; + rectHalo = node.getHalos().select("rect"); + rectHalo.classed("hidden", true); + roundHalo = node.getHalos().select("circle"); + if ( roundHalo.node() === null ) { + radius = node.width(); + roundHalo = node.getHalos().append("circle") + .classed("searchResultB", true) + .classed("searchResultA", false) + .attr("r", radius + offset); + } + halo = roundHalo; + } + } + if ( node.property && !inverse ) { + if ( !node.property().getHalos() ) return; // something went wrong before + rectHalo = node.property().getHalos().select("rect"); + rectHalo.classed("hidden", true); + + roundHalo = node.property().getHalos().select("circle"); + if ( roundHalo.node() === null ) { + radius = node.property().width(); + + roundHalo = node.property().getHalos().append("circle") + .classed("searchResultB", true) + .classed("searchResultA", false) + .attr("r", radius + 15); + + } + halo = roundHalo; // swap the halo to be round + nodeIsRect = true; + container = node.property(); + } + + if ( x < 0 || x > w || y < 0 || y > h ) { + // node outside viewport; + // check for quadrant and get the correct boarder point (intersection with viewport) + if ( x < 0 && y < 0 ) { + borderPoint_x = 0; + borderPoint_y = 0; + } else if ( x > 0 && x < w && y < 0 ) { + borderPoint_x = x; + borderPoint_y = 0; + } else if ( x > w && y < 0 ) { + borderPoint_x = w; + borderPoint_y = 0; + } else if ( x > w && y > 0 && y < h ) { + borderPoint_x = w; + borderPoint_y = y; + } else if ( x > w && y > h ) { + borderPoint_x = w; + borderPoint_y = h; + } else if ( x > 0 && x < w && y > h ) { + borderPoint_x = x; + borderPoint_y = h; + } else if ( x < 0 && y > h ) { + borderPoint_x = 0; + borderPoint_y = h; + } else if ( x < 0 && y > 0 && y < h ) { + borderPoint_x = 0; + borderPoint_y = y; + } + // kill all pulses of nodes that are outside the viewport + container.getHalos().select("rect").classed("searchResultA", false); + container.getHalos().select("circle").classed("searchResultA", false); + container.getHalos().select("rect").classed("searchResultB", true); + container.getHalos().select("circle").classed("searchResultB", true); + halo.classed("hidden", false); + // compute in pixel coordinates length of difference vector + var borderRadius_x = borderPoint_x - x; + var borderRadius_y = borderPoint_y - y; + + var len = borderRadius_x * borderRadius_x + borderRadius_y * borderRadius_y; + len = Math.sqrt(len); + + var normedX = borderRadius_x / len; + var normedY = borderRadius_y / len; + + len = len + 20; // add 20 px; + + // re-normalized vector + var newVectorX = normedX * len + x; + var newVectorY = normedY * len + y; + // compute world coordinates of this point + var wX = (newVectorX - graphTranslation[0]) / zoomFactor; + var wY = (newVectorY - graphTranslation[1]) / zoomFactor; + + // compute distance in world coordinates + var dx = wX - node.x; + var dy = wY - node.y; + if ( highlightOfInv === true ) + dy = wY - node.y - 20; + + if ( highlightOfInv === false && node.property && node.property().inverse() ) + dy = wY - node.y + 20; + + var newRadius = Math.sqrt(dx * dx + dy * dy); + halo = container.getHalos().select("circle"); + // sanity checks and setting new halo radius + if ( !nodeIsRect ) { + defaultRadius = node.actualRadius() + offset; + if ( newRadius < defaultRadius ) { + newRadius = defaultRadius; + } + halo.attr("r", newRadius); + } else { + defaultRadius = 0.5 * container.width(); + if ( newRadius < defaultRadius ) + newRadius = defaultRadius; + halo.attr("r", newRadius); + } + } else { // node is in viewport , render original; + // reset the halo to original radius + defaultRadius = node.actualRadius() + 15; + if ( !nodeIsRect ) { + halo.attr("r", defaultRadius); + } else { // this is rectangular node render as such + halo = container.getHalos().select("rect"); + halo.classed("hidden", false); + //halo.classed("searchResultB", true); + //halo.classed("searchResultA", false); + var aCircHalo = container.getHalos().select("circle"); + aCircHalo.classed("hidden", true); + + container.getHalos().select("rect").classed("hidden", false); + container.getHalos().select("circle").classed("hidden", true); + } + } + } + + function transform( p, cx, cy ){ + // one iteration step for the locate target animation + zoomFactor = graph.options().height() / p[2]; + graphTranslation = [(cx - p[0] * zoomFactor), (cy - p[1] * zoomFactor)]; + updateHaloRadius(); + // update the values in case the user wants to break the animation + zoom.translate(graphTranslation); + zoom.scale(zoomFactor); + graph.options().zoomSlider().updateZoomSliderValue(zoomFactor); + return "translate(" + graphTranslation[0] + "," + graphTranslation[1] + ")scale(" + zoomFactor + ")"; + } + + graph.zoomToElementInGraph = function ( element ){ + targetLocationZoom(element); + }; + graph.updateHaloRadius = function ( element ){ + computeDistanceToCenter(element); + }; + + function targetLocationZoom( target ){ + // store the original information + var cx = 0.5 * graph.options().width(); + var cy = 0.5 * graph.options().height(); + var cp = getWorldPosFromScreen(cx, cy, graphTranslation, zoomFactor); + var sP = [cp.x, cp.y, graph.options().height() / zoomFactor]; + + var zoomLevel = Math.max(defaultZoom + 0.5 * defaultZoom, defaultTargetZoom); + var eP = [target.x, target.y, graph.options().height() / zoomLevel]; + var pos_intp = d3.interpolateZoom(sP, eP); + + var lenAnimation = pos_intp.duration; + if ( lenAnimation > 2500 ) { + lenAnimation = 2500; + } + + graphContainer.attr("transform", transform(sP, cx, cy)) + .transition() + .duration(lenAnimation) + .attrTween("transform", function (){ + return function ( t ){ + return transform(pos_intp(t), cx, cy); + }; + }) + .each("end", function (){ + graphContainer.attr("transform", "translate(" + graphTranslation + ")scale(" + zoomFactor + ")"); + zoom.translate(graphTranslation); + zoom.scale(zoomFactor); + updateHaloRadius(); + }); + } + + function getWorldPosFromScreen( x, y, translate, scale ){ + var temp = scale[0], xn, yn; + if ( temp ) { + xn = (x - translate[0]) / temp; + yn = (y - translate[1]) / temp; + } else { + xn = (x - translate[0]) / scale; + yn = (y - translate[1]) / scale; + } + return { x: xn, y: yn }; + } + + graph.locateSearchResult = function (){ + if ( pulseNodeIds && pulseNodeIds.length > 0 ) { + // move the center of the viewport to this location + if ( transformAnimation === true ) return; // << prevents incrementing the location id if we are in an animation + var node = force.nodes()[pulseNodeIds[locationId]]; + locationId++; + locationId = locationId % pulseNodeIds.length; + if ( node.id ) node.foreground(); + if ( node.property ) node.property().foreground(); + + targetLocationZoom(node); + } + }; + + graph.resetSearchHighlight = function (){ + // get all nodes (handle also already filtered nodes ) + pulseNodeIds = []; + nodeArrayForPulse = []; + // clear from stored nodes + var nodes = unfilteredData.nodes; + var props = unfilteredData.properties; + var j; + for ( j = 0; j < nodes.length; j++ ) { + var node = nodes[j]; + if ( node.removeHalo ) + node.removeHalo(); + } + for ( j = 0; j < props.length; j++ ) { + var prop = props[j]; + if ( prop.removeHalo ) + prop.removeHalo(); + } + }; + + graph.updatePulseIds = function ( nodeIdArray ){ + pulseNodeIds = []; + for ( var i = 0; i < nodeIdArray.length; i++ ) { + var selectedId = nodeIdArray[i]; + var forceId = nodeMap[selectedId]; + if ( forceId !== undefined ) { + var le_node = force.nodes()[forceId]; + if ( le_node.id ) { + if ( pulseNodeIds.indexOf(forceId) === -1 ) { + pulseNodeIds.push(forceId); + } + } + if ( le_node.property ) { + if ( pulseNodeIds.indexOf(forceId) === -1 ) { + pulseNodeIds.push(forceId); + } + } + } + } + locationId = 0; + if ( pulseNodeIds.length > 0 ) { + d3.select("#locateSearchResult").classed("highlighted", true); + d3.select("#locateSearchResult").node().title = "Locate search term"; + } + else { + d3.select("#locateSearchResult").classed("highlighted", false); + d3.select("#locateSearchResult").node().title = "Nothing to locate"; + } + + }; + + graph.highLightNodes = function ( nodeIdArray ){ + if ( nodeIdArray.length === 0 ) { + return; // nothing to highlight + } + pulseNodeIds = []; + nodeArrayForPulse = nodeIdArray; + var missedIds = []; + + // identify the force id to highlight + for ( var i = 0; i < nodeIdArray.length; i++ ) { + var selectedId = nodeIdArray[i]; + var forceId = nodeMap[selectedId]; + if ( forceId !== undefined ) { + var le_node = force.nodes()[forceId]; + if ( le_node.id ) { + if ( pulseNodeIds.indexOf(forceId) === -1 ) { + pulseNodeIds.push(forceId); + le_node.foreground(); + le_node.drawHalo(); + } + } + if ( le_node.property ) { + if ( pulseNodeIds.indexOf(forceId) === -1 ) { + pulseNodeIds.push(forceId); + le_node.property().foreground(); + le_node.property().drawHalo(); + } + } + } + else { + missedIds.push(selectedId); + } + } + + if ( missedIds.length === nodeIdArray.length ) { + + } + // store the highlight on the missed nodes; + var s_nodes = unfilteredData.nodes; + var s_props = unfilteredData.properties; + for ( i = 0; i < missedIds.length; i++ ) { + var missedId = missedIds[i]; + // search for this in the nodes; + for ( var n = 0; n < s_nodes.length; n++ ) { + var nodeId = s_nodes[n].id(); + if ( nodeId === missedId ) { + s_nodes[n].drawHalo(); + } + } + for ( var p = 0; p < s_props.length; p++ ) { + var propId = s_props[p].id(); + if ( propId === missedId ) { + s_props[p].drawHalo(); + } + } + } + if ( missedIds.length === nodeIdArray.length ) { + d3.select("#locateSearchResult").classed("highlighted", false); + } + else { + d3.select("#locateSearchResult").classed("highlighted", true); + } + locationId = 0; + updateHaloRadius(); + }; + + graph.hideHalos = function (){ + var haloElements = d3.selectAll(".searchResultA,.searchResultB"); + haloElements.classed("hidden", true); + return haloElements; + }; + + function nodeInViewport( node, property ){ + + var w = graph.options().width(); + var h = graph.options().height(); + var posXY = getScreenCoords(node.x, node.y, graphTranslation, zoomFactor); + var x = posXY.x; + var y = posXY.y; + + var retVal = !(x < 0 || x > w || y < 0 || y > h); + return retVal; + } + + graph.getBoundingBoxForTex = function (){ + var halos = graph.hideHalos(); + var bbox = graphContainer.node().getBoundingClientRect(); + halos.classed("hidden", false); + var w = graph.options().width(); + var h = graph.options().height(); + + // get the graph coordinates + var topLeft = getWorldPosFromScreen(0, 0, graphTranslation, zoomFactor); + var botRight = getWorldPosFromScreen(w, h, graphTranslation, zoomFactor); + + + var t_topLeft = getWorldPosFromScreen(bbox.left, bbox.top, graphTranslation, zoomFactor); + var t_botRight = getWorldPosFromScreen(bbox.right, bbox.bottom, graphTranslation, zoomFactor); + + // tighten up the bounding box; + + var tX = Math.max(t_topLeft.x, topLeft.x); + var tY = Math.max(t_topLeft.y, topLeft.y); + + var bX = Math.min(t_botRight.x, botRight.x); + var bY = Math.min(t_botRight.y, botRight.y); + + + // tighten further; + var allForceNodes = force.nodes(); + var numNodes = allForceNodes.length; + var visibleNodes = []; + var bbx; + + + var contentBBox = { tx: 1000000000000, ty: 1000000000000, bx: -1000000000000, by: -1000000000000 }; + + for ( var i = 0; i < numNodes; i++ ) { + var node = allForceNodes[i]; + if ( node ) { + if ( node.property ) { + if ( nodeInViewport(node, true) ) { + if ( node.property().labelElement() === undefined ) continue; + bbx = node.property().labelElement().node().getBoundingClientRect(); + if ( bbx ) { + contentBBox.tx = Math.min(contentBBox.tx, bbx.left); + contentBBox.bx = Math.max(contentBBox.bx, bbx.right); + contentBBox.ty = Math.min(contentBBox.ty, bbx.top); + contentBBox.by = Math.max(contentBBox.by, bbx.bottom); + } + } + } else { + if ( nodeInViewport(node, false) ) { + bbx = node.nodeElement().node().getBoundingClientRect(); + if ( bbx ) { + contentBBox.tx = Math.min(contentBBox.tx, bbx.left); + contentBBox.bx = Math.max(contentBBox.bx, bbx.right); + contentBBox.ty = Math.min(contentBBox.ty, bbx.top); + contentBBox.by = Math.max(contentBBox.by, bbx.bottom); + } + } + } + } + } + + var tt_topLeft = getWorldPosFromScreen(contentBBox.tx, contentBBox.ty, graphTranslation, zoomFactor); + var tt_botRight = getWorldPosFromScreen(contentBBox.bx, contentBBox.by, graphTranslation, zoomFactor); + + tX = Math.max(tX, tt_topLeft.x); + tY = Math.max(tY, tt_topLeft.y); + + bX = Math.min(bX, tt_botRight.x); + bY = Math.min(bY, tt_botRight.y); + // y axis flip for tex + return [tX, -tY, bX, -bY]; + + }; + + var updateTargetElement = function (){ + var bbox = graphContainer.node().getBoundingClientRect(); + + + // get the graph coordinates + var bboxOffset = 50; // default radius of a node; + var topLeft = getWorldPosFromScreen(bbox.left, bbox.top, graphTranslation, zoomFactor); + var botRight = getWorldPosFromScreen(bbox.right, bbox.bottom, graphTranslation, zoomFactor); + + var w = graph.options().width(); + if ( graph.options().leftSidebar().isSidebarVisible() === true ) + w -= 200; + var h = graph.options().height(); + topLeft.x += bboxOffset; + topLeft.y -= bboxOffset; + botRight.x -= bboxOffset; + botRight.y += bboxOffset; + + var g_w = botRight.x - topLeft.x; + var g_h = botRight.y - topLeft.y; + + // endpoint position calculations + var posX = 0.5 * (topLeft.x + botRight.x); + var posY = 0.5 * (topLeft.y + botRight.y); + var cx = 0.5 * w, + cy = 0.5 * h; + + if ( graph.options().leftSidebar().isSidebarVisible() === true ) + cx += 200; + var cp = getWorldPosFromScreen(cx, cy, graphTranslation, zoomFactor); + + // zoom factor calculations and fail safes; + var newZoomFactor = 1.0; // fail save if graph and window are squares + //get the smaller one + var a = w / g_w; + var b = h / g_h; + if ( a < b ) newZoomFactor = a; + else newZoomFactor = b; + + + // fail saves + if ( newZoomFactor > zoom.scaleExtent()[1] ) { + newZoomFactor = zoom.scaleExtent()[1]; + } + if ( newZoomFactor < zoom.scaleExtent()[0] ) { + newZoomFactor = zoom.scaleExtent()[0]; + } + + // apply Zooming + var sP = [cp.x, cp.y, h / zoomFactor]; + var eP = [posX, posY, h / newZoomFactor]; + + + var pos_intp = d3.interpolateZoom(sP, eP); + return [pos_intp, cx, cy]; + + }; + + graph.forceRelocationEvent = function ( dynamic ){ + // we need to kill the halo to determine the bounding box; + var halos = graph.hideHalos(); + var bbox = graphContainer.node().getBoundingClientRect(); + halos.classed("hidden", false); + + // get the graph coordinates + var bboxOffset = 50; // default radius of a node; + var topLeft = getWorldPosFromScreen(bbox.left, bbox.top, graphTranslation, zoomFactor); + var botRight = getWorldPosFromScreen(bbox.right, bbox.bottom, graphTranslation, zoomFactor); + + var w = graph.options().width(); + if ( graph.options().leftSidebar().isSidebarVisible() === true ) + w -= 200; + var h = graph.options().height(); + topLeft.x += bboxOffset; + topLeft.y -= bboxOffset; + botRight.x -= bboxOffset; + botRight.y += bboxOffset; + + var g_w = botRight.x - topLeft.x; + var g_h = botRight.y - topLeft.y; + + // endpoint position calculations + var posX = 0.5 * (topLeft.x + botRight.x); + var posY = 0.5 * (topLeft.y + botRight.y); + var cx = 0.5 * w, + cy = 0.5 * h; + + if ( graph.options().leftSidebar().isSidebarVisible() === true ) + cx += 200; + var cp = getWorldPosFromScreen(cx, cy, graphTranslation, zoomFactor); + + // zoom factor calculations and fail safes; + var newZoomFactor = 1.0; // fail save if graph and window are squares + //get the smaller one + var a = w / g_w; + var b = h / g_h; + if ( a < b ) newZoomFactor = a; + else newZoomFactor = b; + + + // fail saves + if ( newZoomFactor > zoom.scaleExtent()[1] ) { + newZoomFactor = zoom.scaleExtent()[1]; + } + if ( newZoomFactor < zoom.scaleExtent()[0] ) { + newZoomFactor = zoom.scaleExtent()[0]; + } + + // apply Zooming + var sP = [cp.x, cp.y, h / zoomFactor]; + var eP = [posX, posY, h / newZoomFactor]; + + + var pos_intp = d3.interpolateZoom(sP, eP); + var lenAnimation = pos_intp.duration; + if ( lenAnimation > 2500 ) { + lenAnimation = 2500; + } + graphContainer.attr("transform", transform(sP, cx, cy)) + .transition() + .duration(lenAnimation) + .attrTween("transform", function (){ + return function ( t ){ + if ( dynamic ) { + var param = updateTargetElement(); + var nV = param[0](t); + return transform(nV, cx, cy); + } + return transform(pos_intp(t), cx, cy); + }; + }) + .each("end", function (){ + if ( dynamic ) { + return; + } + + graphContainer.attr("transform", "translate(" + graphTranslation + ")scale(" + zoomFactor + ")"); + zoom.translate(graphTranslation); + zoom.scale(zoomFactor); + graph.options().zoomSlider().updateZoomSliderValue(zoomFactor); + + + }); + }; + + + graph.isADraggerActive = function (){ + if ( classDragger.mouseButtonPressed === true || + domainDragger.mouseButtonPressed === true || + rangeDragger.mouseButtonPressed === true ) { + return true; + } + return false; + }; + + /** --------------------------------------------------------- **/ + /** -- VOWL EDITOR create/ edit /delete functions -- **/ + /** --------------------------------------------------------- **/ + + graph.changeNodeType = function ( element ){ + + var typeString = d3.select("#typeEditor").node().value; + + if ( graph.classesSanityCheck(element, typeString) === false ) { + // call reselection to restore previous type selection + graph.options().editSidebar().updateSelectionInformation(element); + return; + } + + var prototype = NodePrototypeMap.get(typeString.toLowerCase()); + var aNode = new prototype(graph); + + aNode.x = element.x; + aNode.y = element.y; + aNode.px = element.x; + aNode.py = element.y; + aNode.id(element.id()); + aNode.copyInformation(element); + + if ( typeString === "owl:Thing" ) { + aNode.label("Thing"); + } + else if ( elementTools.isDatatype(element) === false ) { + if ( element.backupLabel() !== undefined ) { + aNode.label(element.backupLabel()); + } else if ( aNode.backupLabel() !== undefined ) { + aNode.label(aNode.backupLabel()); + } else { + aNode.label("NewClass"); + } + } + + if ( typeString === "rdfs:Datatype" ) { + if ( aNode.dType() === "undefined" ) + aNode.label("undefined"); + else { + var identifier = aNode.dType().split(":")[1]; + aNode.label(identifier); + } + } + var i; + // updates the property domain and range + for ( i = 0; i < unfilteredData.properties.length; i++ ) { + if ( unfilteredData.properties[i].domain() === element ) { + // unfilteredData.properties[i].toString(); + unfilteredData.properties[i].domain(aNode); + } + if ( unfilteredData.properties[i].range() === element ) { + unfilteredData.properties[i].range(aNode); + // unfilteredData.properties[i].toString(); + } + } + + // update for fastUpdate: + for ( i = 0; i < properties.length; i++ ) { + if ( properties[i].domain() === element ) { + // unfilteredData.properties[i].toString(); + properties[i].domain(aNode); + } + if ( properties[i].range() === element ) { + properties[i].range(aNode); + // unfilteredData.properties[i].toString(); + } + } + + var remId = unfilteredData.nodes.indexOf(element); + if ( remId !== -1 ) + unfilteredData.nodes.splice(remId, 1); + remId = classNodes.indexOf(element); + if ( remId !== -1 ) + classNodes.splice(remId, 1); + // very important thing for selection!; + addNewNodeElement(aNode); + // handle focuser! + options.focuserModule().handle(aNode); + generateDictionary(unfilteredData); + graph.getUpdateDictionary(); + element = null; + }; + + + graph.changePropertyType = function ( element ){ + var typeString = d3.select("#typeEditor").node().value; + + // create warning + if ( graph.sanityCheckProperty(element.domain(), element.range(), typeString) === false ) return false; + + var propPrototype = PropertyPrototypeMap.get(typeString.toLowerCase()); + var aProp = new propPrototype(graph); + aProp.copyInformation(element); + aProp.id(element.id()); + + element.domain().removePropertyElement(element); + element.range().removePropertyElement(element); + aProp.domain(element.domain()); + aProp.range(element.range()); + + if ( element.backupLabel() !== undefined ) { + aProp.label(element.backupLabel()); + } else { + aProp.label("newObjectProperty"); + } + + if ( aProp.type() === "rdfs:subClassOf" ) { + aProp.iri("http://www.w3.org/2000/01/rdf-schema#subClassOf"); + } else { + if ( element.iri() === "http://www.w3.org/2000/01/rdf-schema#subClassOf" ) + aProp.iri(graph.options().getGeneralMetaObjectProperty('iri') + aProp.id()); + + } + + + if ( graph.propertyCheckExistenceChecker(aProp, element.domain(), element.range()) === false ) { + graph.options().editSidebar().updateSelectionInformation(element); + return; + } + // // TODO: change its base IRI to proper value + // var ontoIRI="http://someTest.de"; + // aProp.baseIri(ontoIRI); + // aProp.iri(aProp.baseIri()+aProp.id()); + + + // add this to the data; + unfilteredData.properties.push(aProp); + if ( properties.indexOf(aProp) === -1 ) + properties.push(aProp); + var remId = unfilteredData.properties.indexOf(element); + if ( remId !== -1 ) + unfilteredData.properties.splice(remId, 1); + if ( properties.indexOf(aProp) === -1 ) + properties.push(aProp); + remId = properties.indexOf(element); + if ( remId !== -1 ) + properties.splice(remId, 1); + graph.fastUpdate(); + aProp.domain().addProperty(aProp); + aProp.range().addProperty(aProp); + if ( element.labelObject() && aProp.labelObject() ) { + aProp.labelObject().x = element.labelObject().x; + aProp.labelObject().px = element.labelObject().px; + aProp.labelObject().y = element.labelObject().y; + aProp.labelObject().py = element.labelObject().py; + } + + options.focuserModule().handle(aProp); + element = null; + }; + + graph.removeEditElements = function (){ + // just added to be called form outside + removeEditElements(); + }; + + function removeEditElements(){ + rangeDragger.hideDragger(true); + domainDragger.hideDragger(true); + shadowClone.hideClone(true); + + classDragger.hideDragger(true); + if ( addDataPropertyGroupElement ) + addDataPropertyGroupElement.classed("hidden", true); + if ( deleteGroupElement ) + deleteGroupElement.classed("hidden", true); + + + if ( hoveredNodeElement ) { + if ( hoveredNodeElement.pinned() === false ) { + hoveredNodeElement.locked(graph.paused()); + hoveredNodeElement.frozen(graph.paused()); + } + } + if ( hoveredPropertyElement ) { + if ( hoveredPropertyElement.pinned() === false ) { + hoveredPropertyElement.locked(graph.paused()); + hoveredPropertyElement.frozen(graph.paused()); + } + } + + + } + + graph.editorMode = function ( val ){ + var create_entry = d3.select("#empty"); + var create_container = d3.select("#emptyContainer"); + + var modeOfOpString = d3.select("#modeOfOperationString").node(); + if ( !arguments.length ) { + create_entry.node().checked = editMode; + if ( editMode === false ) { + create_container.node().title = "Enable editing in modes menu to create a new ontology"; + create_entry.node().title = "Enable editing in modes menu to create a new ontology"; + create_entry.style("pointer-events", "none"); + } else { + create_container.node().title = "Creates a new empty ontology"; + create_entry.node().title = "Creates a new empty ontology"; + d3.select("#useAccuracyHelper").style("color", "#2980b9"); + d3.select("#useAccuracyHelper").style("pointer-events", "auto"); + create_entry.node().disabled = false; + create_entry.style("pointer-events", "auto"); + } + + return editMode; + } + graph.options().setEditorModeForDefaultObject(val); + + // if (seenEditorHint===false && val===true){ + // seenEditorHint=true; + // graph.options().warningModule().showEditorHint(); + // } + editMode = val; + + if ( create_entry ) { + create_entry.classed("disabled", !editMode); + if ( !editMode ) { + create_container.node().title = "Enable editing in modes menu to create a new ontology"; + create_entry.node().title = "Enable editing in modes menu to create a new ontology"; + create_entry.node().disabled = true; + d3.select("#useAccuracyHelper").style("color", "#979797"); + d3.select("#useAccuracyHelper").style("pointer-events", "none"); + create_entry.style("pointer-events", "none"); + } else { + create_container.node().title = "Creates a new empty ontology"; + create_entry.node().title = "Creates a new empty ontology"; + d3.select("#useAccuracyHelper").style("color", "#2980b9"); + d3.select("#useAccuracyHelper").style("pointer-events", "auto"); + create_entry.style("pointer-events", "auto"); + } + } + + // adjust compact notation + // selector = compactNotationOption; + // box =ModuleCheckbox + var compactNotationContainer = d3.select("#compactnotationModuleCheckbox"); + if ( compactNotationContainer ) { + compactNotationContainer.classed("disabled", !editMode); + if ( !editMode ) { + compactNotationContainer.node().title = ""; + compactNotationContainer.node().disabled = false; + compactNotationContainer.style("pointer-events", "auto"); + d3.select("#compactNotationOption").style("color", ""); + d3.select("#compactNotationOption").node().title = ""; + options.literalFilter().enabled(true); + graph.update(); + } else { + // if editor Mode + //1) uncheck the element + d3.select("#compactNotationOption").node().title = "Compact notation can only be used in view mode"; + compactNotationContainer.node().disabled = true; + compactNotationContainer.node().checked = false; + options.compactNotationModule().enabled(false); + options.literalFilter().enabled(false); + graph.executeCompactNotationModule(); + graph.executeEmptyLiteralFilter(); + graph.lazyRefresh(); + compactNotationContainer.style("pointer-events", "none"); + d3.select("#compactNotationOption").style("color", "#979797"); + } + } + + if ( modeOfOpString ) { + if ( touchDevice === true ) { + modeOfOpString.innerHTML = "touch able device detected"; + } else { + modeOfOpString.innerHTML = "point & click device detected"; + } + } + var svgGraph = d3.selectAll(".vowlGraph"); + + if ( editMode === true ) { + options.leftSidebar().showSidebar(options.leftSidebar().getSidebarVisibility(), true); + options.leftSidebar().hideCollapseButton(false); + graph.options().editSidebar().updatePrefixUi(); + graph.options().editSidebar().updateElementWidth(); + svgGraph.on("dblclick.zoom", graph.modified_dblClickFunction); + + } else { + svgGraph.on("dblclick.zoom", originalD3_dblClickFunction); + options.leftSidebar().showSidebar(0); + options.leftSidebar().hideCollapseButton(true); + // hide hovered edit elements + removeEditElements(); + } + options.sidebar().updateShowedInformation(); + options.editSidebar().updateElementWidth(); + + }; + + function createLowerCasePrototypeMap( prototypeMap ){ + return d3.map(prototypeMap.values(), function ( Prototype ){ + return new Prototype().type().toLowerCase(); + }); + } + + function createNewNodeAtPosition( pos ){ + var aNode, prototype; + var forceUpdate = true; + // create a node of that id; + + var typeToCreate = d3.select("#defaultClass").node().title; + prototype = NodePrototypeMap.get(typeToCreate.toLowerCase()); + aNode = new prototype(graph); + var autoEditElement = false; + if ( typeToCreate === "owl:Thing" ) { + aNode.label("Thing"); + } + else { + aNode.label("NewClass"); + autoEditElement = true; + } + aNode.x = pos.x; + aNode.y = pos.y; + aNode.px = aNode.x; + aNode.py = aNode.y; + aNode.id("Class" + eN++); + // aNode.paused(true); + + aNode.baseIri(d3.select("#iriEditor").node().value); + aNode.iri(aNode.baseIri() + aNode.id()); + addNewNodeElement(aNode, forceUpdate); + options.focuserModule().handle(aNode, true); + aNode.frozen(graph.paused()); + aNode.locked(graph.paused()); + aNode.enableEditing(autoEditElement); + } + + + function addNewNodeElement( element ){ + unfilteredData.nodes.push(element); + if ( classNodes.indexOf(element) === -1 ) + classNodes.push(element); + + generateDictionary(unfilteredData); + graph.getUpdateDictionary(); + graph.fastUpdate(); + } + + graph.getTargetNode = function ( position ){ + var dx = position[0]; + var dy = position[1]; + var tN = null; + var minDist = 1000000000000; + // This is a bit OVERKILL for the computation of one node >> TODO: KD-TREE SEARCH + unfilteredData.nodes.forEach(function ( el ){ + var cDist = Math.sqrt((el.x - dx) * (el.x - dx) + (el.y - dy) * (el.y - dy)); + if ( cDist < minDist ) { + minDist = cDist; + tN = el; + } + }); + if ( hoveredNodeElement ) { + var offsetDist = hoveredNodeElement.actualRadius() + 30; + if ( minDist > offsetDist ) return null; + if ( tN.renderType() === "rect" ) return null; + if ( tN === hoveredNodeElement && minDist <= hoveredNodeElement.actualRadius() ) { + return tN; + } else if ( tN === hoveredNodeElement && minDist > hoveredNodeElement.actualRadius() ) { + return null; + } + return tN; + } + else { + + if ( minDist > (tN.actualRadius() + 30) ) + return null; + else return tN; + + } + }; + + graph.genericPropertySanityCheck = function ( domain, range, typeString, header, action ){ + if ( domain === range && typeString === "rdfs:subClassOf" ) { + graph.options().warningModule().showWarning(header, + "rdfs:subClassOf can not be created as loops (domain == range)", + action, 1, false); + return false; + } + if ( domain === range && typeString === "owl:disjointWith" ) { + graph.options().warningModule().showWarning(header, + "owl:disjointWith can not be created as loops (domain == range)", + action, 1, false); + return false; + } + // allProps[i].type()==="owl:allValuesFrom" || + // allProps[i].type()==="owl:someValuesFrom" + if ( domain.type() === "owl:Thing" && typeString === "owl:allValuesFrom" ) { + graph.options().warningModule().showWarning(header, + "owl:allValuesFrom can not originate from owl:Thing", + action, 1, false); + return false; + } + if ( domain.type() === "owl:Thing" && typeString === "owl:someValuesFrom" ) { + graph.options().warningModule().showWarning(header, + "owl:someValuesFrom can not originate from owl:Thing", + action, 1, false); + return false; + } + + if ( range.type() === "owl:Thing" && typeString === "owl:allValuesFrom" ) { + graph.options().warningModule().showWarning(header, + "owl:allValuesFrom can not be connected to owl:Thing", + action, 1, false); + return false; + } + if ( range.type() === "owl:Thing" && typeString === "owl:someValuesFrom" ) { + graph.options().warningModule().showWarning(header, + "owl:someValuesFrom can not be connected to owl:Thing", + action, 1, false); + return false; + } + + return true; // we can Change the domain or range + }; + + graph.checkIfIriClassAlreadyExist = function ( url ){ + // search for a class node with this url + var allNodes = unfilteredData.nodes; + for ( var i = 0; i < allNodes.length; i++ ) { + if ( elementTools.isDatatype(allNodes[i]) === true || allNodes[i].type() === "owl:Thing" ) + continue; + + // now we are a real class; + //get class IRI + var classIRI = allNodes[i].iri(); + + // this gives me the node for halo + if ( url === classIRI ) { + return allNodes[i]; + } + } + return false; + }; + + graph.classesSanityCheck = function ( classElement, targetType ){ + // this is added due to someValuesFrom properties + // we should not be able to change a classElement to a owl:Thing + // when it has a property attached to it that uses these restrictions + // + + if ( targetType === "owl:Class" ) return true; + + else { + // collect all properties which have that one as a domain or range + var allProps = unfilteredData.properties; + for ( var i = 0; i < allProps.length; i++ ) { + if ( allProps[i].range() === classElement || allProps[i].domain() === classElement ) { + // check for the type of that property + if ( allProps[i].type() === "owl:someValuesFrom" ) { + graph.options().warningModule().showWarning("Can not change class type", + "The element has a property that is of type owl:someValuesFrom", + "Element type not changed!", 1, true); + return false; + } + if ( allProps[i].type() === "owl:allValuesFrom" ) { + graph.options().warningModule().showWarning("Can not change class type", + "The element has a property that is of type owl:allValuesFrom", + "Element type not changed!", 1, true); + return false; + } + } + } + + + } + return true; + }; + + graph.propertyCheckExistenceChecker = function ( property, domain, range ){ + var allProps = unfilteredData.properties; + var i; + if ( property.type() === "rdfs:subClassOf" || property.type() === "owl:disjointWith" ) { + + for ( i = 0; i < allProps.length; i++ ) { + if ( allProps[i] === property ) continue; + if ( allProps[i].domain() === domain && allProps[i].range() === range && allProps[i].type() === property.type() ) { + graph.options().warningModule().showWarning("Warning", + "This triple already exist!", + "Element not created!", 1, false); + return false; + } + if ( allProps[i].domain() === range && allProps[i].range() === domain && allProps[i].type() === property.type() ) { + graph.options().warningModule().showWarning("Warning", + "Inverse assignment already exist! ", + "Element not created!", 1, false); + return false; + } + } + return true; + } + return true; + }; + + // graph.checkForTripleDuplicate=function(property){ + // var domain=property.domain(); + // var range=property.range(); + // console.log("checking for duplicates"); + // var b1= domain.isPropertyAssignedToThisElement(property); + // var b2= range.isPropertyAssignedToThisElement(property); + // + // console.log("test domain results in "+ b1); + // console.log("test range results in "+ b1); + // + // if (b1 && b2 ){ + // graph.options().warningModule().showWarning("Warning", + // "This triple already exist!", + // "Element not created!",1,false); + // return false; + // } + // return true; + // }; + + graph.sanityCheckProperty = function ( domain, range, typeString ){ + + // check for duplicate triple in the element; + + + if ( typeString === "owl:objectProperty" && graph.options().objectPropertyFilter().enabled() === true ) { + graph.options().warningModule().showWarning("Warning", + "Object properties are filtered out in the visualization!", + "Element not created!", 1, false); + return false; + } + + if ( typeString === "owl:disjointWith" && graph.options().disjointPropertyFilter().enabled() === true ) { + graph.options().warningModule().showWarning("Warning", + "owl:disjointWith properties are filtered out in the visualization!", + "Element not created!", 1, false); + return false; + } + + + if ( domain === range && typeString === "rdfs:subClassOf" ) { + graph.options().warningModule().showWarning("Warning", + "rdfs:subClassOf can not be created as loops (domain == range)", + "Element not created!", 1, false); + return false; + } + if ( domain === range && typeString === "owl:disjointWith" ) { + graph.options().warningModule().showWarning("Warning", + "owl:disjointWith can not be created as loops (domain == range)", + "Element not created!", 1, false); + return false; + } + + if ( domain.type() === "owl:Thing" && typeString === "owl:someValuesFrom" ) { + graph.options().warningModule().showWarning("Warning", + "owl:someValuesFrom can not originate from owl:Thing", + "Element not created!", 1, false); + return false; + } + if ( domain.type() === "owl:Thing" && typeString === "owl:allValuesFrom" ) { + graph.options().warningModule().showWarning("Warning", + "owl:allValuesFrom can not originate from owl:Thing", + "Element not created!", 1, false); + return false; + } + + if ( range.type() === "owl:Thing" && typeString === "owl:allValuesFrom" ) { + graph.options().warningModule().showWarning("Warning", + "owl:allValuesFrom can not be connected to owl:Thing", + "Element not created!", 1, false); + return false; + } + if ( range.type() === "owl:Thing" && typeString === "owl:someValuesFrom" ) { + graph.options().warningModule().showWarning("Warning", + "owl:someValuesFrom can not be connected to owl:Thing", + "Element not created!", 1, false); + return false; + } + return true; // we can create a property + }; + + function createNewObjectProperty( domain, range, draggerEndposition ){ + // check type of the property that we want to create; + + var defaultPropertyName = d3.select("#defaultProperty").node().title; + + // check if we are allow to create that property + if ( graph.sanityCheckProperty(domain, range, defaultPropertyName) === false ) return false; + + + var propPrototype = PropertyPrototypeMap.get(defaultPropertyName.toLowerCase()); + var aProp = new propPrototype(graph); + aProp.id("objectProperty" + eP++); + aProp.domain(domain); + aProp.range(range); + aProp.label("newObjectProperty"); + aProp.baseIri(d3.select("#iriEditor").node().value); + aProp.iri(aProp.baseIri() + aProp.id()); + + // check for duplicate; + if ( graph.propertyCheckExistenceChecker(aProp, domain, range) === false ) { + // delete aProp; + // hope for garbage collection here -.- + return false; + } + + var autoEditElement = false; + + if ( defaultPropertyName === "owl:objectProperty" ) { + autoEditElement = true; + } + var pX = 0.49 * (domain.x + range.x); + var pY = 0.49 * (domain.y + range.y); + + if ( domain === range ) { + // we use the dragger endposition to determine an angle to put the loop there; + var dirD_x = draggerEndposition[0] - domain.x; + var dirD_y = draggerEndposition[1] - domain.y; + + // normalize; + var len = Math.sqrt(dirD_x * dirD_x + dirD_y * dirD_y); + // it should be very hard to set the position on the same sport but why not handling this + var nx = dirD_x / len; + var ny = dirD_y / len; + // is Nan in javascript like in c len==len returns false when it is not a number? + if ( isNaN(len) ) { + nx = 0; + ny = -1; + } + + // get domain actual raidus + var offset = 2 * domain.actualRadius() + 50; + pX = domain.x + offset * nx; + pY = domain.y + offset * ny; + } + + // add this property to domain and range; + domain.addProperty(aProp); + range.addProperty(aProp); + + + // add this to the data; + unfilteredData.properties.push(aProp); + if ( properties.indexOf(aProp) === -1 ) + properties.push(aProp); + graph.fastUpdate(); + aProp.labelObject().x = pX; + aProp.labelObject().px = pX; + aProp.labelObject().y = pY; + aProp.labelObject().py = pY; + + aProp.frozen(graph.paused()); + aProp.locked(graph.paused()); + domain.frozen(graph.paused()); + domain.locked(graph.paused()); + range.frozen(graph.paused()); + range.locked(graph.paused()); + + + generateDictionary(unfilteredData); + graph.getUpdateDictionary(); + + options.focuserModule().handle(aProp); + graph.activateHoverElementsForProperties(true, aProp, false, touchDevice); + aProp.labelObject().increasedLoopAngle = true; + aProp.enableEditing(autoEditElement); + } + + graph.createDataTypeProperty = function ( node ){ + // random postion issues; + clearTimeout(nodeFreezer); + // tells user when element is filtered out + if ( graph.options().datatypeFilter().enabled() === true ) { + graph.options().warningModule().showWarning("Warning", + "Datatype properties are filtered out in the visualization!", + "Element not created!", 1, false); + return; + } + + + var aNode, prototype; + + // create a default datatype Node >> HERE LITERAL; + var defaultDatatypeName = d3.select("#defaultDatatype").node().title; + if ( defaultDatatypeName === "rdfs:Literal" ) { + prototype = NodePrototypeMap.get("rdfs:literal"); + aNode = new prototype(graph); + aNode.label("Literal"); + aNode.iri("http://www.w3.org/2000/01/rdf-schema#Literal"); + aNode.baseIri("http://www.w3.org/2000/01/rdf-schema#"); + } else { + prototype = NodePrototypeMap.get("rdfs:datatype"); + aNode = new prototype(graph); + var identifier = ""; + if ( defaultDatatypeName === "undefined" ) { + identifier = "undefined"; + + aNode.label(identifier); + // TODO : HANDLER FOR UNDEFINED DATATYPES!!<<<>>>>>>>>>>>.. + aNode.iri("http://www.undefinedDatatype.org/#" + identifier); + aNode.baseIri("http://www.undefinedDatatype.org/#"); + aNode.dType(defaultDatatypeName); + } else { + identifier = defaultDatatypeName.split(":")[1]; + aNode.label(identifier); + aNode.dType(defaultDatatypeName); + aNode.iri("http://www.w3.org/2001/XMLSchema#" + identifier); + aNode.baseIri("http://www.w3.org/2001/XMLSchema#"); + } + } + + + var nX = node.x - node.actualRadius() - 100; + var nY = node.y + node.actualRadius() + 100; + + aNode.x = nX; + aNode.y = nY; + aNode.px = aNode.x; + aNode.py = aNode.y; + aNode.id("NodeId" + eN++); + // add this property to the nodes; + unfilteredData.nodes.push(aNode); + if ( classNodes.indexOf(aNode) === -1 ) + classNodes.push(aNode); + + + // add also the datatype Property to it + var propPrototype = PropertyPrototypeMap.get("owl:datatypeproperty"); + var aProp = new propPrototype(graph); + aProp.id("datatypeProperty" + eP++); + + // create the connection + aProp.domain(node); + aProp.range(aNode); + aProp.label("newDatatypeProperty"); + + + // TODO: change its base IRI to proper value + var ontoIri = d3.select("#iriEditor").node().value; + aProp.baseIri(ontoIri); + aProp.iri(ontoIri + aProp.id()); + // add this to the data; + unfilteredData.properties.push(aProp); + if ( properties.indexOf(aProp) === -1 ) + properties.push(aProp); + graph.fastUpdate(); + generateDictionary(unfilteredData); + graph.getUpdateDictionary(); + + nodeFreezer = setTimeout(function (){ + if ( node && node.frozen() === true && node.pinned() === false && graph.paused() === false ) { + node.frozen(graph.paused()); + node.locked(graph.paused()); + } + }, 1000); + options.focuserModule().handle(undefined); + if ( node ) { + node.frozen(true); + node.locked(true); + } + }; + + graph.removeNodesViaResponse = function ( nodesToRemove, propsToRemove ){ + var i, remId; + // splice them; + for ( i = 0; i < propsToRemove.length; i++ ) { + remId = unfilteredData.properties.indexOf(propsToRemove[i]); + if ( remId !== -1 ) + unfilteredData.properties.splice(remId, 1); + remId = properties.indexOf(propsToRemove[i]); + if ( remId !== -1 ) + properties.splice(remId, 1); + propsToRemove[i] = null; + } + for ( i = 0; i < nodesToRemove.length; i++ ) { + remId = unfilteredData.nodes.indexOf(nodesToRemove[i]); + if ( remId !== -1 ) { + unfilteredData.nodes.splice(remId, 1); + } + remId = classNodes.indexOf(nodesToRemove[i]); + if ( remId !== -1 ) + classNodes.splice(remId, 1); + nodesToRemove[i] = null; + } + graph.fastUpdate(); + generateDictionary(unfilteredData); + graph.getUpdateDictionary(); + options.focuserModule().handle(undefined); + nodesToRemove = null; + propsToRemove = null; + + }; + + graph.removeNodeViaEditor = function ( node ){ + var propsToRemove = []; + var nodesToRemove = []; + var datatypes = 0; + + var remId; + + nodesToRemove.push(node); + for ( var i = 0; i < unfilteredData.properties.length; i++ ) { + if ( unfilteredData.properties[i].domain() === node || unfilteredData.properties[i].range() === node ) { + propsToRemove.push(unfilteredData.properties[i]); + if ( unfilteredData.properties[i].type().toLocaleLowerCase() === "owl:datatypeproperty" && + unfilteredData.properties[i].range() !== node ) { + nodesToRemove.push(unfilteredData.properties[i].range()); + datatypes++; + } + } + } + var removedItems = propsToRemove.length + nodesToRemove.length; + if ( removedItems > 2 ) { + var text = "You are about to delete 1 class and " + propsToRemove.length + " properties"; + if ( datatypes !== 0 ) { + text = "You are about to delete 1 class, " + datatypes + " datatypes and " + propsToRemove.length + " properties"; + } + + + graph.options().warningModule().responseWarning( + "Removing elements", + text, + "Awaiting response!", graph.removeNodesViaResponse, [nodesToRemove, propsToRemove], false); + + + // + // if (confirm("Remove :\n"+propsToRemove.length + " properties\n"+nodesToRemove.length+" classes? ")===false){ + // return; + // }else{ + // // todo : store for undo delete button ; + // } + } else { + // splice them; + for ( i = 0; i < propsToRemove.length; i++ ) { + remId = unfilteredData.properties.indexOf(propsToRemove[i]); + if ( remId !== -1 ) + unfilteredData.properties.splice(remId, 1); + remId = properties.indexOf(propsToRemove[i]); + if ( remId !== -1 ) + properties.splice(remId, 1); + propsToRemove[i] = null; + } + for ( i = 0; i < nodesToRemove.length; i++ ) { + remId = unfilteredData.nodes.indexOf(nodesToRemove[i]); + if ( remId !== -1 ) + unfilteredData.nodes.splice(remId, 1); + remId = classNodes.indexOf(nodesToRemove[i]); + if ( remId !== -1 ) + classNodes.splice(remId, 1); + nodesToRemove[i] = null; + } + graph.fastUpdate(); + generateDictionary(unfilteredData); + graph.getUpdateDictionary(); + options.focuserModule().handle(undefined); + nodesToRemove = null; + propsToRemove = null; + } + }; + + graph.removePropertyViaEditor = function ( property ){ + property.domain().removePropertyElement(property); + property.range().removePropertyElement(property); + var remId; + + if ( property.type().toLocaleLowerCase() === "owl:datatypeproperty" ) { + var datatype = property.range(); + remId = unfilteredData.nodes.indexOf(property.range()); + if ( remId !== -1 ) + unfilteredData.nodes.splice(remId, 1); + remId = classNodes.indexOf(property.range()); + if ( remId !== -1 ) + classNodes.splice(remId, 1); + datatype = null; + } + remId = unfilteredData.properties.indexOf(property); + if ( remId !== -1 ) + unfilteredData.properties.splice(remId, 1); + remId = properties.indexOf(property); + if ( remId !== -1 ) + properties.splice(remId, 1); + if ( property.inverse() ) { + // so we have inverse + property.inverse().inverse(0); + + } + + + hoveredPropertyElement = undefined; + graph.fastUpdate(); + generateDictionary(unfilteredData); + graph.getUpdateDictionary(); + options.focuserModule().handle(undefined); + property = null; + }; + + graph.executeColorExternalsModule = function (){ + options.colorExternalsModule().filter(unfilteredData.nodes, unfilteredData.properties); + }; + + graph.executeCompactNotationModule = function (){ + if ( unfilteredData ) { + options.compactNotationModule().filter(unfilteredData.nodes, unfilteredData.properties); + } + + }; + graph.executeEmptyLiteralFilter = function (){ + + if ( unfilteredData && unfilteredData.nodes.length > 1 ) { + options.literalFilter().filter(unfilteredData.nodes, unfilteredData.properties); + unfilteredData.nodes = options.literalFilter().filteredNodes(); + unfilteredData.properties = options.literalFilter().filteredProperties(); + } + + }; + + + /** --------------------------------------------------------- **/ + /** -- animation functions for the nodes -- **/ + /** --------------------------------------------------------- **/ + + graph.animateDynamicLabelWidth = function (){ + var wantedWidth = options.dynamicLabelWidth(); + var i; + for ( i = 0; i < classNodes.length; i++ ) { + var nodeElement = classNodes[i]; + if ( elementTools.isDatatype(nodeElement) ) { + nodeElement.animateDynamicLabelWidth(wantedWidth); + } + } + for ( i = 0; i < properties.length; i++ ) { + properties[i].animateDynamicLabelWidth(wantedWidth); + } + }; + + + /** --------------------------------------------------------- **/ + /** -- Touch behaviour functions -- **/ + /** --------------------------------------------------------- **/ + + graph.setTouchDevice = function ( val ){ + touchDevice = val; + }; + + graph.isTouchDevice = function (){ + return touchDevice; + }; + + graph.modified_dblClickFunction = function (){ + + d3.event.stopPropagation(); + d3.event.preventDefault(); + // get position where we want to add the node; + var grPos = getClickedScreenCoords(d3.event.clientX, d3.event.clientY, graph.translation(), graph.scaleFactor()); + createNewNodeAtPosition(grPos); + }; + + function doubletap(){ + var touch_time = d3.event.timeStamp; + var numTouchers = 1; + if ( d3.event && d3.event.touches && d3.event.touches.length ) + numTouchers = d3.event.touches.length; + + if ( touch_time - last_touch_time < 300 && numTouchers === 1 ) { + d3.event.stopPropagation(); + if ( editMode === true ) { + //graph.modified_dblClickFunction(); + d3.event.preventDefault(); + d3.event.stopPropagation(); + last_touch_time = touch_time; + return true; + } + } + last_touch_time = touch_time; + return false; + } + + + function touchzoomed(){ + forceNotZooming = true; + + + var touch_time = d3.event.timeStamp; + if ( touch_time - last_touch_time < 300 && d3.event.touches.length === 1 ) { + d3.event.stopPropagation(); + + if ( editMode === true ) { + //graph.modified_dblClickFunction(); + d3.event.preventDefault(); + d3.event.stopPropagation(); + zoom.translate(graphTranslation); + zoom.scale(zoomFactor); + graph.modified_dblTouchFunction(); + } + else { + forceNotZooming = false; + if ( originalD3_touchZoomFunction ) + originalD3_touchZoomFunction(); + } + return; + } + forceNotZooming = false; + last_touch_time = touch_time; + // TODO: WORK AROUND TO CHECK FOR ORIGINAL FUNCTION + if ( originalD3_touchZoomFunction ) + originalD3_touchZoomFunction(); + } + + graph.modified_dblTouchFunction = function ( d ){ + d3.event.stopPropagation(); + d3.event.preventDefault(); + var xy; + if ( editMode === true ) { + xy = d3.touches(d3.selectAll(".vowlGraph").node()); + } + var grPos = getClickedScreenCoords(xy[0][0], xy[0][1], graph.translation(), graph.scaleFactor()); + createNewNodeAtPosition(grPos); + }; + + /** --------------------------------------------------------- **/ + /** -- Hover and Selection functions, adding edit elements -- **/ + /** --------------------------------------------------------- **/ + + graph.ignoreOtherHoverEvents = function ( val ){ + if ( !arguments.length ) { + return ignoreOtherHoverEvents; + } + else ignoreOtherHoverEvents = val; + }; + + function delayedHiddingHoverElements( tbh ){ + if ( tbh === true ) return; + if ( hoveredNodeElement ) { + if ( hoveredNodeElement.editingTextElement === true ) return; + delayedHider = setTimeout(function (){ + deleteGroupElement.classed("hidden", true); + addDataPropertyGroupElement.classed("hidden", true); + classDragger.hideDragger(true); + if ( hoveredNodeElement && hoveredNodeElement.pinned() === false && graph.paused() === false && hoveredNodeElement.editingTextElement === false ) { + hoveredNodeElement.frozen(false); + hoveredNodeElement.locked(false); + } + }, 1000); + } + if ( hoveredPropertyElement ) { + if ( hoveredPropertyElement.editingTextElement === true ) return; + delayedHider = setTimeout(function (){ + deleteGroupElement.classed("hidden", true); + addDataPropertyGroupElement.classed("hidden", true); + classDragger.hideDragger(true); + rangeDragger.hideDragger(true); + domainDragger.hideDragger(true); + shadowClone.hideClone(true); + if ( hoveredPropertyElement && hoveredPropertyElement.focused() === true && graph.options().drawPropertyDraggerOnHover() === true ) { + hoveredPropertyElement.labelObject().increasedLoopAngle = false; + // lazy update + recalculatePositions(); + } + + if ( hoveredPropertyElement && hoveredPropertyElement.pinned() === false && graph.paused() === false && hoveredPropertyElement.editingTextElement === false ) { + hoveredPropertyElement.frozen(false); + hoveredPropertyElement.locked(false); + } + }, 1000); + } + + } + + + // TODO : experimental code for updating dynamic label with and its hover element + graph.hideHoverPropertyElementsForAnimation = function (){ + deleteGroupElement.classed("hidden", true); + }; + graph.showHoverElementsAfterAnimation = function ( property, inversed ){ + setDeleteHoverElementPositionProperty(property, inversed); + deleteGroupElement.classed("hidden", false); + + }; + + function editElementHoverOnHidden(){ + classDragger.nodeElement.classed("classDraggerNodeHovered", true); + classDragger.nodeElement.classed("classDraggerNode", false); + editElementHoverOn(); + } + + function editElementHoverOutHidden(){ + classDragger.nodeElement.classed("classDraggerNodeHovered", false); + classDragger.nodeElement.classed("classDraggerNode", true); + editElementHoverOut(); + } + + function editElementHoverOn( touch ){ + if ( touch === true ) return; + clearTimeout(delayedHider); // ignore touch behaviour + + } + + graph.killDelayedTimer = function (){ + clearTimeout(delayedHider); + clearTimeout(nodeFreezer); + }; + + + function editElementHoverOut( tbh ){ + if ( hoveredNodeElement ) { + if ( graph.ignoreOtherHoverEvents() === true || tbh === true || hoveredNodeElement.editingTextElement === true ) return; + delayedHider = setTimeout(function (){ + if ( graph.isADraggerActive() === true ) return; + deleteGroupElement.classed("hidden", true); + addDataPropertyGroupElement.classed("hidden", true); + classDragger.hideDragger(true); + if ( hoveredNodeElement && hoveredNodeElement.pinned() === false && graph.paused() === false ) { + hoveredNodeElement.frozen(false); + hoveredNodeElement.locked(false); + } + + }, 1000); + } + if ( hoveredPropertyElement ) { + if ( graph.ignoreOtherHoverEvents() === true || tbh === true || hoveredPropertyElement.editingTextElement === true ) return; + delayedHider = setTimeout(function (){ + if ( graph.isADraggerActive() === true ) return; + deleteGroupElement.classed("hidden", true); + addDataPropertyGroupElement.classed("hidden", true); + classDragger.hideDragger(true); + if ( hoveredPropertyElement && hoveredPropertyElement.pinned() === false && graph.paused() === false ) { + hoveredPropertyElement.frozen(false); + hoveredPropertyElement.locked(false); + } + + }, 1000); + } + } + + graph.activateHoverElementsForProperties = function ( val, property, inversed, touchBehaviour ){ + if ( editMode === false ) return; // nothing to do; + + if ( touchBehaviour === undefined ) + touchBehaviour = false; + + if ( val === true ) { + clearTimeout(delayedHider); + if ( hoveredPropertyElement ) { + if ( hoveredPropertyElement.domain() === hoveredPropertyElement.range() ) { + hoveredPropertyElement.labelObject().increasedLoopAngle = false; + recalculatePositions(); + } + } + + hoveredPropertyElement = property; + if ( graph.options().drawPropertyDraggerOnHover() === true ) { + + + if ( property.type() !== "owl:DatatypeProperty" ) { + if ( property.domain() === property.range() ) { + property.labelObject().increasedLoopAngle = true; + recalculatePositions(); + } + shadowClone.setParentProperty(property, inversed); + rangeDragger.setParentProperty(property, inversed); + rangeDragger.hideDragger(false); + rangeDragger.addMouseEvents(); + domainDragger.setParentProperty(property, inversed); + domainDragger.hideDragger(false); + domainDragger.addMouseEvents(); + + + } else if ( property.type() === "owl:DatatypeProperty" ) { + shadowClone.setParentProperty(property, inversed); + rangeDragger.setParentProperty(property, inversed); + rangeDragger.hideDragger(true); + rangeDragger.addMouseEvents(); + domainDragger.setParentProperty(property, inversed); + domainDragger.hideDragger(false); + domainDragger.addMouseEvents(); + } + } + else { // hide when we dont want that option + if ( graph.options().drawPropertyDraggerOnHover() === true ) { + rangeDragger.hideDragger(true); + domainDragger.hideDragger(true); + shadowClone.hideClone(true); + if ( property.domain() === property.range() ) { + property.labelObject().increasedLoopAngle = false; + recalculatePositions(); + } + } + } + + if ( hoveredNodeElement ) { + if ( hoveredNodeElement && hoveredNodeElement.pinned() === false && graph.paused() === false ) { + hoveredNodeElement.frozen(false); + hoveredNodeElement.locked(false); + } + } + hoveredNodeElement = undefined; + deleteGroupElement.classed("hidden", false); + setDeleteHoverElementPositionProperty(property, inversed); + deleteGroupElement.selectAll("*").on("click", function (){ + if ( touchBehaviour && property.focused() === false ) { + graph.options().focuserModule().handle(property); + return; + } + graph.removePropertyViaEditor(property); + d3.event.stopPropagation(); + }); + classDragger.hideDragger(true); + addDataPropertyGroupElement.classed("hidden", true); + } else { + delayedHiddingHoverElements(); + } + }; + + graph.updateDraggerElements = function (){ + + // set opacity style for all elements + + rangeDragger.draggerObject.classed("superOpacityElement", !graph.options().showDraggerObject()); + domainDragger.draggerObject.classed("superOpacityElement", !graph.options().showDraggerObject()); + classDragger.draggerObject.classed("superOpacityElement", !graph.options().showDraggerObject()); + + nodeContainer.selectAll(".superHiddenElement").classed("superOpacityElement", !graph.options().showDraggerObject()); + labelContainer.selectAll(".superHiddenElement").classed("superOpacityElement", !graph.options().showDraggerObject()); + + deleteGroupElement.selectAll(".superHiddenElement").classed("superOpacityElement", !graph.options().showDraggerObject()); + addDataPropertyGroupElement.selectAll(".superHiddenElement").classed("superOpacityElement", !graph.options().showDraggerObject()); + + + }; + + function setAddDataPropertyHoverElementPosition( node ){ + var delX, delY = 0; + if ( node.renderType() === "round" ) { + var scale = 0.5 * Math.sqrt(2.0); + var oX = scale * node.actualRadius(); + var oY = scale * node.actualRadius(); + delX = node.x - oX; + delY = node.y + oY; + addDataPropertyGroupElement.attr("transform", "translate(" + delX + "," + delY + ")"); + } + } + + function setDeleteHoverElementPosition( node ){ + var delX, delY = 0; + if ( node.renderType() === "round" ) { + var scale = 0.5 * Math.sqrt(2.0); + var oX = scale * node.actualRadius(); + var oY = scale * node.actualRadius(); + delX = node.x + oX; + delY = node.y - oY; + } else { + delX = node.x + 0.5 * node.width() + 6; + delY = node.y - 0.5 * node.height() - 6; + } + deleteGroupElement.attr("transform", "translate(" + delX + "," + delY + ")"); + } + + function setDeleteHoverElementPositionProperty( property, inversed ){ + if ( property && property.labelElement() ) { + var pos = [property.labelObject().x, property.labelObject().y]; + var widthElement = parseFloat(property.getShapeElement().attr("width")); + var heightElement = parseFloat(property.getShapeElement().attr("height")); + var delX = pos[0] + 0.5 * widthElement + 6; + var delY = pos[1] - 0.5 * heightElement - 6; + // this is the lower element + if ( property.labelElement().attr("transform") === "translate(0,15)" ) + delY += 15; + // this is upper element + if ( property.labelElement().attr("transform") === "translate(0,-15)" ) + delY -= 15; + deleteGroupElement.attr("transform", "translate(" + delX + "," + delY + ")"); + } else { + deleteGroupElement.classed("hidden", true);// hide when there is no property + } + + + } + + graph.activateHoverElements = function ( val, node, touchBehaviour ){ + if ( editMode === false ) { + return; // nothing to do; + } + if ( touchBehaviour === undefined ) touchBehaviour = false; + if ( val === true ) { + if ( graph.options().drawPropertyDraggerOnHover() === true ) { + rangeDragger.hideDragger(true); + domainDragger.hideDragger(true); + shadowClone.hideClone(true); + } + // make them visible + clearTimeout(delayedHider); + clearTimeout(nodeFreezer); + if ( hoveredNodeElement && node.pinned() === false && graph.paused() === false ) { + hoveredNodeElement.frozen(false); + hoveredNodeElement.locked(false); + } + hoveredNodeElement = node; + if ( node && node.frozen() === false && node.pinned() === false ) { + node.frozen(true); + node.locked(false); + } + if ( hoveredPropertyElement && hoveredPropertyElement.focused() === false ) { + hoveredPropertyElement.labelObject().increasedLoopAngle = false; + recalculatePositions(); + // update the loopAngles; + + } + hoveredPropertyElement = undefined; + deleteGroupElement.classed("hidden", false); + setDeleteHoverElementPosition(node); + + + deleteGroupElement.selectAll("*").on("click", function (){ + if ( touchBehaviour && node.focused() === false ) { + graph.options().focuserModule().handle(node); + return; + } + graph.removeNodeViaEditor(node); + d3.event.stopPropagation(); + }) + .on("mouseover", function (){ + editElementHoverOn(node, touchBehaviour); + }) + .on("mouseout", function (){ + editElementHoverOut(node, touchBehaviour); + }); + + addDataPropertyGroupElement.classed("hidden", true); + classDragger.nodeElement.on("mouseover", editElementHoverOn) + .on("mouseout", editElementHoverOut); + classDragger.draggerObject.on("mouseover", editElementHoverOnHidden) + .on("mouseout", editElementHoverOutHidden); + + // add the dragger element; + if ( node.renderType() === "round" ) { + classDragger.svgRoot(draggerLayer); + classDragger.setParentNode(node); + classDragger.hideDragger(false); + addDataPropertyGroupElement.classed("hidden", false); + setAddDataPropertyHoverElementPosition(node); + addDataPropertyGroupElement.selectAll("*").on("click", function (){ + if ( touchBehaviour && node.focused() === false ) { + graph.options().focuserModule().handle(node); + return; + } + graph.createDataTypeProperty(node); + d3.event.stopPropagation(); + }) + .on("mouseover", function (){ + editElementHoverOn(node, touchBehaviour); + }) + .on("mouseout", function (){ + editElementHoverOut(node, touchBehaviour); + }); + } else { + classDragger.hideDragger(true); + + } + + } else { + delayedHiddingHoverElements(node, touchBehaviour); + + } + }; + + + return graph; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 58 */ +/***/ (function(module, exports, __webpack_require__) { + + var __WEBPACK_AMD_DEFINE_RESULT__;/* WEBPACK VAR INJECTION */(function(global, module) {/** + * @license + * Lodash (Custom Build) + * Build: `lodash core -o ./dist/lodash.core.js` + * Copyright OpenJS Foundation and other contributors + * Released under MIT license + * Based on Underscore.js 1.8.3 + * Copyright Jeremy Ashkenas, DocumentCloud and Investigative Reporters & Editors + */ + ;(function() { + + /** Used as a safe reference for `undefined` in pre-ES5 environments. */ + var undefined; + + /** Used as the semantic version number. */ + var VERSION = '4.17.15'; + + /** Error message constants. */ + var FUNC_ERROR_TEXT = 'Expected a function'; + + /** Used to compose bitmasks for value comparisons. */ + var COMPARE_PARTIAL_FLAG = 1, + COMPARE_UNORDERED_FLAG = 2; + + /** Used to compose bitmasks for function metadata. */ + var WRAP_BIND_FLAG = 1, + WRAP_PARTIAL_FLAG = 32; + + /** Used as references for various `Number` constants. */ + var INFINITY = 1 / 0, + MAX_SAFE_INTEGER = 9007199254740991; + + /** `Object#toString` result references. */ + var argsTag = '[object Arguments]', + arrayTag = '[object Array]', + asyncTag = '[object AsyncFunction]', + boolTag = '[object Boolean]', + dateTag = '[object Date]', + errorTag = '[object Error]', + funcTag = '[object Function]', + genTag = '[object GeneratorFunction]', + numberTag = '[object Number]', + objectTag = '[object Object]', + proxyTag = '[object Proxy]', + regexpTag = '[object RegExp]', + stringTag = '[object String]'; + + /** Used to match HTML entities and HTML characters. */ + var reUnescapedHtml = /[&<>"']/g, + reHasUnescapedHtml = RegExp(reUnescapedHtml.source); + + /** Used to detect unsigned integer values. */ + var reIsUint = /^(?:0|[1-9]\d*)$/; + + /** Used to map characters to HTML entities. */ + var htmlEscapes = { + '&': '&', + '<': '<', + '>': '>', + '"': '"', + "'": ''' + }; + + /** Detect free variable `global` from Node.js. */ + var freeGlobal = typeof global == 'object' && global && global.Object === Object && global; + + /** Detect free variable `self`. */ + var freeSelf = typeof self == 'object' && self && self.Object === Object && self; + + /** Used as a reference to the global object. */ + var root = freeGlobal || freeSelf || Function('return this')(); + + /** Detect free variable `exports`. */ + var freeExports = typeof exports == 'object' && exports && !exports.nodeType && exports; + + /** Detect free variable `module`. */ + var freeModule = freeExports && typeof module == 'object' && module && !module.nodeType && module; + + /*--------------------------------------------------------------------------*/ + + /** + * Appends the elements of `values` to `array`. + * + * @private + * @param {Array} array The array to modify. + * @param {Array} values The values to append. + * @returns {Array} Returns `array`. + */ + function arrayPush(array, values) { + array.push.apply(array, values); + return array; + } + + /** + * The base implementation of `_.findIndex` and `_.findLastIndex` without + * support for iteratee shorthands. + * + * @private + * @param {Array} array The array to inspect. + * @param {Function} predicate The function invoked per iteration. + * @param {number} fromIndex The index to search from. + * @param {boolean} [fromRight] Specify iterating from right to left. + * @returns {number} Returns the index of the matched value, else `-1`. + */ + function baseFindIndex(array, predicate, fromIndex, fromRight) { + var length = array.length, + index = fromIndex + (fromRight ? 1 : -1); + + while ((fromRight ? index-- : ++index < length)) { + if (predicate(array[index], index, array)) { + return index; + } + } + return -1; + } + + /** + * The base implementation of `_.property` without support for deep paths. + * + * @private + * @param {string} key The key of the property to get. + * @returns {Function} Returns the new accessor function. + */ + function baseProperty(key) { + return function(object) { + return object == null ? undefined : object[key]; + }; + } + + /** + * The base implementation of `_.propertyOf` without support for deep paths. + * + * @private + * @param {Object} object The object to query. + * @returns {Function} Returns the new accessor function. + */ + function basePropertyOf(object) { + return function(key) { + return object == null ? undefined : object[key]; + }; + } + + /** + * The base implementation of `_.reduce` and `_.reduceRight`, without support + * for iteratee shorthands, which iterates over `collection` using `eachFunc`. + * + * @private + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} iteratee The function invoked per iteration. + * @param {*} accumulator The initial value. + * @param {boolean} initAccum Specify using the first or last element of + * `collection` as the initial value. + * @param {Function} eachFunc The function to iterate over `collection`. + * @returns {*} Returns the accumulated value. + */ + function baseReduce(collection, iteratee, accumulator, initAccum, eachFunc) { + eachFunc(collection, function(value, index, collection) { + accumulator = initAccum + ? (initAccum = false, value) + : iteratee(accumulator, value, index, collection); + }); + return accumulator; + } + + /** + * The base implementation of `_.values` and `_.valuesIn` which creates an + * array of `object` property values corresponding to the property names + * of `props`. + * + * @private + * @param {Object} object The object to query. + * @param {Array} props The property names to get values for. + * @returns {Object} Returns the array of property values. + */ + function baseValues(object, props) { + return baseMap(props, function(key) { + return object[key]; + }); + } + + /** + * Used by `_.escape` to convert characters to HTML entities. + * + * @private + * @param {string} chr The matched character to escape. + * @returns {string} Returns the escaped character. + */ + var escapeHtmlChar = basePropertyOf(htmlEscapes); + + /** + * Creates a unary function that invokes `func` with its argument transformed. + * + * @private + * @param {Function} func The function to wrap. + * @param {Function} transform The argument transform. + * @returns {Function} Returns the new function. + */ + function overArg(func, transform) { + return function(arg) { + return func(transform(arg)); + }; + } + + /*--------------------------------------------------------------------------*/ + + /** Used for built-in method references. */ + var arrayProto = Array.prototype, + objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** Used to generate unique IDs. */ + var idCounter = 0; + + /** + * Used to resolve the + * [`toStringTag`](http://ecma-international.org/ecma-262/7.0/#sec-object.prototype.tostring) + * of values. + */ + var nativeObjectToString = objectProto.toString; + + /** Used to restore the original `_` reference in `_.noConflict`. */ + var oldDash = root._; + + /** Built-in value references. */ + var objectCreate = Object.create, + propertyIsEnumerable = objectProto.propertyIsEnumerable; + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeIsFinite = root.isFinite, + nativeKeys = overArg(Object.keys, Object), + nativeMax = Math.max; + + /*------------------------------------------------------------------------*/ + + /** + * Creates a `lodash` object which wraps `value` to enable implicit method + * chain sequences. Methods that operate on and return arrays, collections, + * and functions can be chained together. Methods that retrieve a single value + * or may return a primitive value will automatically end the chain sequence + * and return the unwrapped value. Otherwise, the value must be unwrapped + * with `_#value`. + * + * Explicit chain sequences, which must be unwrapped with `_#value`, may be + * enabled using `_.chain`. + * + * The execution of chained methods is lazy, that is, it's deferred until + * `_#value` is implicitly or explicitly called. + * + * Lazy evaluation allows several methods to support shortcut fusion. + * Shortcut fusion is an optimization to merge iteratee calls; this avoids + * the creation of intermediate arrays and can greatly reduce the number of + * iteratee executions. Sections of a chain sequence qualify for shortcut + * fusion if the section is applied to an array and iteratees accept only + * one argument. The heuristic for whether a section qualifies for shortcut + * fusion is subject to change. + * + * Chaining is supported in custom builds as long as the `_#value` method is + * directly or indirectly included in the build. + * + * In addition to lodash methods, wrappers have `Array` and `String` methods. + * + * The wrapper `Array` methods are: + * `concat`, `join`, `pop`, `push`, `shift`, `sort`, `splice`, and `unshift` + * + * The wrapper `String` methods are: + * `replace` and `split` + * + * The wrapper methods that support shortcut fusion are: + * `at`, `compact`, `drop`, `dropRight`, `dropWhile`, `filter`, `find`, + * `findLast`, `head`, `initial`, `last`, `map`, `reject`, `reverse`, `slice`, + * `tail`, `take`, `takeRight`, `takeRightWhile`, `takeWhile`, and `toArray` + * + * The chainable wrapper methods are: + * `after`, `ary`, `assign`, `assignIn`, `assignInWith`, `assignWith`, `at`, + * `before`, `bind`, `bindAll`, `bindKey`, `castArray`, `chain`, `chunk`, + * `commit`, `compact`, `concat`, `conforms`, `constant`, `countBy`, `create`, + * `curry`, `debounce`, `defaults`, `defaultsDeep`, `defer`, `delay`, + * `difference`, `differenceBy`, `differenceWith`, `drop`, `dropRight`, + * `dropRightWhile`, `dropWhile`, `extend`, `extendWith`, `fill`, `filter`, + * `flatMap`, `flatMapDeep`, `flatMapDepth`, `flatten`, `flattenDeep`, + * `flattenDepth`, `flip`, `flow`, `flowRight`, `fromPairs`, `functions`, + * `functionsIn`, `groupBy`, `initial`, `intersection`, `intersectionBy`, + * `intersectionWith`, `invert`, `invertBy`, `invokeMap`, `iteratee`, `keyBy`, + * `keys`, `keysIn`, `map`, `mapKeys`, `mapValues`, `matches`, `matchesProperty`, + * `memoize`, `merge`, `mergeWith`, `method`, `methodOf`, `mixin`, `negate`, + * `nthArg`, `omit`, `omitBy`, `once`, `orderBy`, `over`, `overArgs`, + * `overEvery`, `overSome`, `partial`, `partialRight`, `partition`, `pick`, + * `pickBy`, `plant`, `property`, `propertyOf`, `pull`, `pullAll`, `pullAllBy`, + * `pullAllWith`, `pullAt`, `push`, `range`, `rangeRight`, `rearg`, `reject`, + * `remove`, `rest`, `reverse`, `sampleSize`, `set`, `setWith`, `shuffle`, + * `slice`, `sort`, `sortBy`, `splice`, `spread`, `tail`, `take`, `takeRight`, + * `takeRightWhile`, `takeWhile`, `tap`, `throttle`, `thru`, `toArray`, + * `toPairs`, `toPairsIn`, `toPath`, `toPlainObject`, `transform`, `unary`, + * `union`, `unionBy`, `unionWith`, `uniq`, `uniqBy`, `uniqWith`, `unset`, + * `unshift`, `unzip`, `unzipWith`, `update`, `updateWith`, `values`, + * `valuesIn`, `without`, `wrap`, `xor`, `xorBy`, `xorWith`, `zip`, + * `zipObject`, `zipObjectDeep`, and `zipWith` + * + * The wrapper methods that are **not** chainable by default are: + * `add`, `attempt`, `camelCase`, `capitalize`, `ceil`, `clamp`, `clone`, + * `cloneDeep`, `cloneDeepWith`, `cloneWith`, `conformsTo`, `deburr`, + * `defaultTo`, `divide`, `each`, `eachRight`, `endsWith`, `eq`, `escape`, + * `escapeRegExp`, `every`, `find`, `findIndex`, `findKey`, `findLast`, + * `findLastIndex`, `findLastKey`, `first`, `floor`, `forEach`, `forEachRight`, + * `forIn`, `forInRight`, `forOwn`, `forOwnRight`, `get`, `gt`, `gte`, `has`, + * `hasIn`, `head`, `identity`, `includes`, `indexOf`, `inRange`, `invoke`, + * `isArguments`, `isArray`, `isArrayBuffer`, `isArrayLike`, `isArrayLikeObject`, + * `isBoolean`, `isBuffer`, `isDate`, `isElement`, `isEmpty`, `isEqual`, + * `isEqualWith`, `isError`, `isFinite`, `isFunction`, `isInteger`, `isLength`, + * `isMap`, `isMatch`, `isMatchWith`, `isNaN`, `isNative`, `isNil`, `isNull`, + * `isNumber`, `isObject`, `isObjectLike`, `isPlainObject`, `isRegExp`, + * `isSafeInteger`, `isSet`, `isString`, `isUndefined`, `isTypedArray`, + * `isWeakMap`, `isWeakSet`, `join`, `kebabCase`, `last`, `lastIndexOf`, + * `lowerCase`, `lowerFirst`, `lt`, `lte`, `max`, `maxBy`, `mean`, `meanBy`, + * `min`, `minBy`, `multiply`, `noConflict`, `noop`, `now`, `nth`, `pad`, + * `padEnd`, `padStart`, `parseInt`, `pop`, `random`, `reduce`, `reduceRight`, + * `repeat`, `result`, `round`, `runInContext`, `sample`, `shift`, `size`, + * `snakeCase`, `some`, `sortedIndex`, `sortedIndexBy`, `sortedLastIndex`, + * `sortedLastIndexBy`, `startCase`, `startsWith`, `stubArray`, `stubFalse`, + * `stubObject`, `stubString`, `stubTrue`, `subtract`, `sum`, `sumBy`, + * `template`, `times`, `toFinite`, `toInteger`, `toJSON`, `toLength`, + * `toLower`, `toNumber`, `toSafeInteger`, `toString`, `toUpper`, `trim`, + * `trimEnd`, `trimStart`, `truncate`, `unescape`, `uniqueId`, `upperCase`, + * `upperFirst`, `value`, and `words` + * + * @name _ + * @constructor + * @category Seq + * @param {*} value The value to wrap in a `lodash` instance. + * @returns {Object} Returns the new `lodash` wrapper instance. + * @example + * + * function square(n) { + * return n * n; + * } + * + * var wrapped = _([1, 2, 3]); + * + * // Returns an unwrapped value. + * wrapped.reduce(_.add); + * // => 6 + * + * // Returns a wrapped value. + * var squares = wrapped.map(square); + * + * _.isArray(squares); + * // => false + * + * _.isArray(squares.value()); + * // => true + */ + function lodash(value) { + return value instanceof LodashWrapper + ? value + : new LodashWrapper(value); + } + + /** + * The base implementation of `_.create` without support for assigning + * properties to the created object. + * + * @private + * @param {Object} proto The object to inherit from. + * @returns {Object} Returns the new object. + */ + var baseCreate = (function() { + function object() {} + return function(proto) { + if (!isObject(proto)) { + return {}; + } + if (objectCreate) { + return objectCreate(proto); + } + object.prototype = proto; + var result = new object; + object.prototype = undefined; + return result; + }; + }()); + + /** + * The base constructor for creating `lodash` wrapper objects. + * + * @private + * @param {*} value The value to wrap. + * @param {boolean} [chainAll] Enable explicit method chain sequences. + */ + function LodashWrapper(value, chainAll) { + this.__wrapped__ = value; + this.__actions__ = []; + this.__chain__ = !!chainAll; + } + + LodashWrapper.prototype = baseCreate(lodash.prototype); + LodashWrapper.prototype.constructor = LodashWrapper; + + /*------------------------------------------------------------------------*/ + + /** + * Assigns `value` to `key` of `object` if the existing value is not equivalent + * using [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. + * + * @private + * @param {Object} object The object to modify. + * @param {string} key The key of the property to assign. + * @param {*} value The value to assign. + */ + function assignValue(object, key, value) { + var objValue = object[key]; + if (!(hasOwnProperty.call(object, key) && eq(objValue, value)) || + (value === undefined && !(key in object))) { + baseAssignValue(object, key, value); + } + } + + /** + * The base implementation of `assignValue` and `assignMergeValue` without + * value checks. + * + * @private + * @param {Object} object The object to modify. + * @param {string} key The key of the property to assign. + * @param {*} value The value to assign. + */ + function baseAssignValue(object, key, value) { + object[key] = value; + } + + /** + * The base implementation of `_.delay` and `_.defer` which accepts `args` + * to provide to `func`. + * + * @private + * @param {Function} func The function to delay. + * @param {number} wait The number of milliseconds to delay invocation. + * @param {Array} args The arguments to provide to `func`. + * @returns {number|Object} Returns the timer id or timeout object. + */ + function baseDelay(func, wait, args) { + if (typeof func != 'function') { + throw new TypeError(FUNC_ERROR_TEXT); + } + return setTimeout(function() { func.apply(undefined, args); }, wait); + } + + /** + * The base implementation of `_.forEach` without support for iteratee shorthands. + * + * @private + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} iteratee The function invoked per iteration. + * @returns {Array|Object} Returns `collection`. + */ + var baseEach = createBaseEach(baseForOwn); + + /** + * The base implementation of `_.every` without support for iteratee shorthands. + * + * @private + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} predicate The function invoked per iteration. + * @returns {boolean} Returns `true` if all elements pass the predicate check, + * else `false` + */ + function baseEvery(collection, predicate) { + var result = true; + baseEach(collection, function(value, index, collection) { + result = !!predicate(value, index, collection); + return result; + }); + return result; + } + + /** + * The base implementation of methods like `_.max` and `_.min` which accepts a + * `comparator` to determine the extremum value. + * + * @private + * @param {Array} array The array to iterate over. + * @param {Function} iteratee The iteratee invoked per iteration. + * @param {Function} comparator The comparator used to compare values. + * @returns {*} Returns the extremum value. + */ + function baseExtremum(array, iteratee, comparator) { + var index = -1, + length = array.length; + + while (++index < length) { + var value = array[index], + current = iteratee(value); + + if (current != null && (computed === undefined + ? (current === current && !false) + : comparator(current, computed) + )) { + var computed = current, + result = value; + } + } + return result; + } + + /** + * The base implementation of `_.filter` without support for iteratee shorthands. + * + * @private + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} predicate The function invoked per iteration. + * @returns {Array} Returns the new filtered array. + */ + function baseFilter(collection, predicate) { + var result = []; + baseEach(collection, function(value, index, collection) { + if (predicate(value, index, collection)) { + result.push(value); + } + }); + return result; + } + + /** + * The base implementation of `_.flatten` with support for restricting flattening. + * + * @private + * @param {Array} array The array to flatten. + * @param {number} depth The maximum recursion depth. + * @param {boolean} [predicate=isFlattenable] The function invoked per iteration. + * @param {boolean} [isStrict] Restrict to values that pass `predicate` checks. + * @param {Array} [result=[]] The initial result value. + * @returns {Array} Returns the new flattened array. + */ + function baseFlatten(array, depth, predicate, isStrict, result) { + var index = -1, + length = array.length; + + predicate || (predicate = isFlattenable); + result || (result = []); + + while (++index < length) { + var value = array[index]; + if (depth > 0 && predicate(value)) { + if (depth > 1) { + // Recursively flatten arrays (susceptible to call stack limits). + baseFlatten(value, depth - 1, predicate, isStrict, result); + } else { + arrayPush(result, value); + } + } else if (!isStrict) { + result[result.length] = value; + } + } + return result; + } + + /** + * The base implementation of `baseForOwn` which iterates over `object` + * properties returned by `keysFunc` and invokes `iteratee` for each property. + * Iteratee functions may exit iteration early by explicitly returning `false`. + * + * @private + * @param {Object} object The object to iterate over. + * @param {Function} iteratee The function invoked per iteration. + * @param {Function} keysFunc The function to get the keys of `object`. + * @returns {Object} Returns `object`. + */ + var baseFor = createBaseFor(); + + /** + * The base implementation of `_.forOwn` without support for iteratee shorthands. + * + * @private + * @param {Object} object The object to iterate over. + * @param {Function} iteratee The function invoked per iteration. + * @returns {Object} Returns `object`. + */ + function baseForOwn(object, iteratee) { + return object && baseFor(object, iteratee, keys); + } + + /** + * The base implementation of `_.functions` which creates an array of + * `object` function property names filtered from `props`. + * + * @private + * @param {Object} object The object to inspect. + * @param {Array} props The property names to filter. + * @returns {Array} Returns the function names. + */ + function baseFunctions(object, props) { + return baseFilter(props, function(key) { + return isFunction(object[key]); + }); + } + + /** + * The base implementation of `getTag` without fallbacks for buggy environments. + * + * @private + * @param {*} value The value to query. + * @returns {string} Returns the `toStringTag`. + */ + function baseGetTag(value) { + return objectToString(value); + } + + /** + * The base implementation of `_.gt` which doesn't coerce arguments. + * + * @private + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @returns {boolean} Returns `true` if `value` is greater than `other`, + * else `false`. + */ + function baseGt(value, other) { + return value > other; + } + + /** + * The base implementation of `_.isArguments`. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an `arguments` object, + */ + var baseIsArguments = noop; + + /** + * The base implementation of `_.isDate` without Node.js optimizations. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a date object, else `false`. + */ + function baseIsDate(value) { + return isObjectLike(value) && baseGetTag(value) == dateTag; + } + + /** + * The base implementation of `_.isEqual` which supports partial comparisons + * and tracks traversed objects. + * + * @private + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @param {boolean} bitmask The bitmask flags. + * 1 - Unordered comparison + * 2 - Partial comparison + * @param {Function} [customizer] The function to customize comparisons. + * @param {Object} [stack] Tracks traversed `value` and `other` objects. + * @returns {boolean} Returns `true` if the values are equivalent, else `false`. + */ + function baseIsEqual(value, other, bitmask, customizer, stack) { + if (value === other) { + return true; + } + if (value == null || other == null || (!isObjectLike(value) && !isObjectLike(other))) { + return value !== value && other !== other; + } + return baseIsEqualDeep(value, other, bitmask, customizer, baseIsEqual, stack); + } + + /** + * A specialized version of `baseIsEqual` for arrays and objects which performs + * deep comparisons and tracks traversed objects enabling objects with circular + * references to be compared. + * + * @private + * @param {Object} object The object to compare. + * @param {Object} other The other object to compare. + * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. + * @param {Function} customizer The function to customize comparisons. + * @param {Function} equalFunc The function to determine equivalents of values. + * @param {Object} [stack] Tracks traversed `object` and `other` objects. + * @returns {boolean} Returns `true` if the objects are equivalent, else `false`. + */ + function baseIsEqualDeep(object, other, bitmask, customizer, equalFunc, stack) { + var objIsArr = isArray(object), + othIsArr = isArray(other), + objTag = objIsArr ? arrayTag : baseGetTag(object), + othTag = othIsArr ? arrayTag : baseGetTag(other); + + objTag = objTag == argsTag ? objectTag : objTag; + othTag = othTag == argsTag ? objectTag : othTag; + + var objIsObj = objTag == objectTag, + othIsObj = othTag == objectTag, + isSameTag = objTag == othTag; + + stack || (stack = []); + var objStack = find(stack, function(entry) { + return entry[0] == object; + }); + var othStack = find(stack, function(entry) { + return entry[0] == other; + }); + if (objStack && othStack) { + return objStack[1] == other; + } + stack.push([object, other]); + stack.push([other, object]); + if (isSameTag && !objIsObj) { + var result = (objIsArr) + ? equalArrays(object, other, bitmask, customizer, equalFunc, stack) + : equalByTag(object, other, objTag, bitmask, customizer, equalFunc, stack); + stack.pop(); + return result; + } + if (!(bitmask & COMPARE_PARTIAL_FLAG)) { + var objIsWrapped = objIsObj && hasOwnProperty.call(object, '__wrapped__'), + othIsWrapped = othIsObj && hasOwnProperty.call(other, '__wrapped__'); + + if (objIsWrapped || othIsWrapped) { + var objUnwrapped = objIsWrapped ? object.value() : object, + othUnwrapped = othIsWrapped ? other.value() : other; + + var result = equalFunc(objUnwrapped, othUnwrapped, bitmask, customizer, stack); + stack.pop(); + return result; + } + } + if (!isSameTag) { + return false; + } + var result = equalObjects(object, other, bitmask, customizer, equalFunc, stack); + stack.pop(); + return result; + } + + /** + * The base implementation of `_.isRegExp` without Node.js optimizations. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a regexp, else `false`. + */ + function baseIsRegExp(value) { + return isObjectLike(value) && baseGetTag(value) == regexpTag; + } + + /** + * The base implementation of `_.iteratee`. + * + * @private + * @param {*} [value=_.identity] The value to convert to an iteratee. + * @returns {Function} Returns the iteratee. + */ + function baseIteratee(func) { + if (typeof func == 'function') { + return func; + } + if (func == null) { + return identity; + } + return (typeof func == 'object' ? baseMatches : baseProperty)(func); + } + + /** + * The base implementation of `_.lt` which doesn't coerce arguments. + * + * @private + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @returns {boolean} Returns `true` if `value` is less than `other`, + * else `false`. + */ + function baseLt(value, other) { + return value < other; + } + + /** + * The base implementation of `_.map` without support for iteratee shorthands. + * + * @private + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} iteratee The function invoked per iteration. + * @returns {Array} Returns the new mapped array. + */ + function baseMap(collection, iteratee) { + var index = -1, + result = isArrayLike(collection) ? Array(collection.length) : []; + + baseEach(collection, function(value, key, collection) { + result[++index] = iteratee(value, key, collection); + }); + return result; + } + + /** + * The base implementation of `_.matches` which doesn't clone `source`. + * + * @private + * @param {Object} source The object of property values to match. + * @returns {Function} Returns the new spec function. + */ + function baseMatches(source) { + var props = nativeKeys(source); + return function(object) { + var length = props.length; + if (object == null) { + return !length; + } + object = Object(object); + while (length--) { + var key = props[length]; + if (!(key in object && + baseIsEqual(source[key], object[key], COMPARE_PARTIAL_FLAG | COMPARE_UNORDERED_FLAG) + )) { + return false; + } + } + return true; + }; + } + + /** + * The base implementation of `_.pick` without support for individual + * property identifiers. + * + * @private + * @param {Object} object The source object. + * @param {string[]} paths The property paths to pick. + * @returns {Object} Returns the new object. + */ + function basePick(object, props) { + object = Object(object); + return reduce(props, function(result, key) { + if (key in object) { + result[key] = object[key]; + } + return result; + }, {}); + } + + /** + * The base implementation of `_.rest` which doesn't validate or coerce arguments. + * + * @private + * @param {Function} func The function to apply a rest parameter to. + * @param {number} [start=func.length-1] The start position of the rest parameter. + * @returns {Function} Returns the new function. + */ + function baseRest(func, start) { + return setToString(overRest(func, start, identity), func + ''); + } + + /** + * The base implementation of `_.slice` without an iteratee call guard. + * + * @private + * @param {Array} array The array to slice. + * @param {number} [start=0] The start position. + * @param {number} [end=array.length] The end position. + * @returns {Array} Returns the slice of `array`. + */ + function baseSlice(array, start, end) { + var index = -1, + length = array.length; + + if (start < 0) { + start = -start > length ? 0 : (length + start); + } + end = end > length ? length : end; + if (end < 0) { + end += length; + } + length = start > end ? 0 : ((end - start) >>> 0); + start >>>= 0; + + var result = Array(length); + while (++index < length) { + result[index] = array[index + start]; + } + return result; + } + + /** + * Copies the values of `source` to `array`. + * + * @private + * @param {Array} source The array to copy values from. + * @param {Array} [array=[]] The array to copy values to. + * @returns {Array} Returns `array`. + */ + function copyArray(source) { + return baseSlice(source, 0, source.length); + } + + /** + * The base implementation of `_.some` without support for iteratee shorthands. + * + * @private + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} predicate The function invoked per iteration. + * @returns {boolean} Returns `true` if any element passes the predicate check, + * else `false`. + */ + function baseSome(collection, predicate) { + var result; + + baseEach(collection, function(value, index, collection) { + result = predicate(value, index, collection); + return !result; + }); + return !!result; + } + + /** + * The base implementation of `wrapperValue` which returns the result of + * performing a sequence of actions on the unwrapped `value`, where each + * successive action is supplied the return value of the previous. + * + * @private + * @param {*} value The unwrapped value. + * @param {Array} actions Actions to perform to resolve the unwrapped value. + * @returns {*} Returns the resolved value. + */ + function baseWrapperValue(value, actions) { + var result = value; + return reduce(actions, function(result, action) { + return action.func.apply(action.thisArg, arrayPush([result], action.args)); + }, result); + } + + /** + * Compares values to sort them in ascending order. + * + * @private + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @returns {number} Returns the sort order indicator for `value`. + */ + function compareAscending(value, other) { + if (value !== other) { + var valIsDefined = value !== undefined, + valIsNull = value === null, + valIsReflexive = value === value, + valIsSymbol = false; + + var othIsDefined = other !== undefined, + othIsNull = other === null, + othIsReflexive = other === other, + othIsSymbol = false; + + if ((!othIsNull && !othIsSymbol && !valIsSymbol && value > other) || + (valIsSymbol && othIsDefined && othIsReflexive && !othIsNull && !othIsSymbol) || + (valIsNull && othIsDefined && othIsReflexive) || + (!valIsDefined && othIsReflexive) || + !valIsReflexive) { + return 1; + } + if ((!valIsNull && !valIsSymbol && !othIsSymbol && value < other) || + (othIsSymbol && valIsDefined && valIsReflexive && !valIsNull && !valIsSymbol) || + (othIsNull && valIsDefined && valIsReflexive) || + (!othIsDefined && valIsReflexive) || + !othIsReflexive) { + return -1; + } + } + return 0; + } + + /** + * Copies properties of `source` to `object`. + * + * @private + * @param {Object} source The object to copy properties from. + * @param {Array} props The property identifiers to copy. + * @param {Object} [object={}] The object to copy properties to. + * @param {Function} [customizer] The function to customize copied values. + * @returns {Object} Returns `object`. + */ + function copyObject(source, props, object, customizer) { + var isNew = !object; + object || (object = {}); + + var index = -1, + length = props.length; + + while (++index < length) { + var key = props[index]; + + var newValue = customizer + ? customizer(object[key], source[key], key, object, source) + : undefined; + + if (newValue === undefined) { + newValue = source[key]; + } + if (isNew) { + baseAssignValue(object, key, newValue); + } else { + assignValue(object, key, newValue); + } + } + return object; + } + + /** + * Creates a function like `_.assign`. + * + * @private + * @param {Function} assigner The function to assign values. + * @returns {Function} Returns the new assigner function. + */ + function createAssigner(assigner) { + return baseRest(function(object, sources) { + var index = -1, + length = sources.length, + customizer = length > 1 ? sources[length - 1] : undefined; + + customizer = (assigner.length > 3 && typeof customizer == 'function') + ? (length--, customizer) + : undefined; + + object = Object(object); + while (++index < length) { + var source = sources[index]; + if (source) { + assigner(object, source, index, customizer); + } + } + return object; + }); + } + + /** + * Creates a `baseEach` or `baseEachRight` function. + * + * @private + * @param {Function} eachFunc The function to iterate over a collection. + * @param {boolean} [fromRight] Specify iterating from right to left. + * @returns {Function} Returns the new base function. + */ + function createBaseEach(eachFunc, fromRight) { + return function(collection, iteratee) { + if (collection == null) { + return collection; + } + if (!isArrayLike(collection)) { + return eachFunc(collection, iteratee); + } + var length = collection.length, + index = fromRight ? length : -1, + iterable = Object(collection); + + while ((fromRight ? index-- : ++index < length)) { + if (iteratee(iterable[index], index, iterable) === false) { + break; + } + } + return collection; + }; + } + + /** + * Creates a base function for methods like `_.forIn` and `_.forOwn`. + * + * @private + * @param {boolean} [fromRight] Specify iterating from right to left. + * @returns {Function} Returns the new base function. + */ + function createBaseFor(fromRight) { + return function(object, iteratee, keysFunc) { + var index = -1, + iterable = Object(object), + props = keysFunc(object), + length = props.length; + + while (length--) { + var key = props[fromRight ? length : ++index]; + if (iteratee(iterable[key], key, iterable) === false) { + break; + } + } + return object; + }; + } + + /** + * Creates a function that produces an instance of `Ctor` regardless of + * whether it was invoked as part of a `new` expression or by `call` or `apply`. + * + * @private + * @param {Function} Ctor The constructor to wrap. + * @returns {Function} Returns the new wrapped function. + */ + function createCtor(Ctor) { + return function() { + // Use a `switch` statement to work with class constructors. See + // http://ecma-international.org/ecma-262/7.0/#sec-ecmascript-function-objects-call-thisargument-argumentslist + // for more details. + var args = arguments; + var thisBinding = baseCreate(Ctor.prototype), + result = Ctor.apply(thisBinding, args); + + // Mimic the constructor's `return` behavior. + // See https://es5.github.io/#x13.2.2 for more details. + return isObject(result) ? result : thisBinding; + }; + } + + /** + * Creates a `_.find` or `_.findLast` function. + * + * @private + * @param {Function} findIndexFunc The function to find the collection index. + * @returns {Function} Returns the new find function. + */ + function createFind(findIndexFunc) { + return function(collection, predicate, fromIndex) { + var iterable = Object(collection); + if (!isArrayLike(collection)) { + var iteratee = baseIteratee(predicate, 3); + collection = keys(collection); + predicate = function(key) { return iteratee(iterable[key], key, iterable); }; + } + var index = findIndexFunc(collection, predicate, fromIndex); + return index > -1 ? iterable[iteratee ? collection[index] : index] : undefined; + }; + } + + /** + * Creates a function that wraps `func` to invoke it with the `this` binding + * of `thisArg` and `partials` prepended to the arguments it receives. + * + * @private + * @param {Function} func The function to wrap. + * @param {number} bitmask The bitmask flags. See `createWrap` for more details. + * @param {*} thisArg The `this` binding of `func`. + * @param {Array} partials The arguments to prepend to those provided to + * the new function. + * @returns {Function} Returns the new wrapped function. + */ + function createPartial(func, bitmask, thisArg, partials) { + if (typeof func != 'function') { + throw new TypeError(FUNC_ERROR_TEXT); + } + var isBind = bitmask & WRAP_BIND_FLAG, + Ctor = createCtor(func); + + function wrapper() { + var argsIndex = -1, + argsLength = arguments.length, + leftIndex = -1, + leftLength = partials.length, + args = Array(leftLength + argsLength), + fn = (this && this !== root && this instanceof wrapper) ? Ctor : func; + + while (++leftIndex < leftLength) { + args[leftIndex] = partials[leftIndex]; + } + while (argsLength--) { + args[leftIndex++] = arguments[++argsIndex]; + } + return fn.apply(isBind ? thisArg : this, args); + } + return wrapper; + } + + /** + * A specialized version of `baseIsEqualDeep` for arrays with support for + * partial deep comparisons. + * + * @private + * @param {Array} array The array to compare. + * @param {Array} other The other array to compare. + * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. + * @param {Function} customizer The function to customize comparisons. + * @param {Function} equalFunc The function to determine equivalents of values. + * @param {Object} stack Tracks traversed `array` and `other` objects. + * @returns {boolean} Returns `true` if the arrays are equivalent, else `false`. + */ + function equalArrays(array, other, bitmask, customizer, equalFunc, stack) { + var isPartial = bitmask & COMPARE_PARTIAL_FLAG, + arrLength = array.length, + othLength = other.length; + + if (arrLength != othLength && !(isPartial && othLength > arrLength)) { + return false; + } + var index = -1, + result = true, + seen = (bitmask & COMPARE_UNORDERED_FLAG) ? [] : undefined; + + // Ignore non-index properties. + while (++index < arrLength) { + var arrValue = array[index], + othValue = other[index]; + + var compared; + if (compared !== undefined) { + if (compared) { + continue; + } + result = false; + break; + } + // Recursively compare arrays (susceptible to call stack limits). + if (seen) { + if (!baseSome(other, function(othValue, othIndex) { + if (!indexOf(seen, othIndex) && + (arrValue === othValue || equalFunc(arrValue, othValue, bitmask, customizer, stack))) { + return seen.push(othIndex); + } + })) { + result = false; + break; + } + } else if (!( + arrValue === othValue || + equalFunc(arrValue, othValue, bitmask, customizer, stack) + )) { + result = false; + break; + } + } + return result; + } + + /** + * A specialized version of `baseIsEqualDeep` for comparing objects of + * the same `toStringTag`. + * + * **Note:** This function only supports comparing values with tags of + * `Boolean`, `Date`, `Error`, `Number`, `RegExp`, or `String`. + * + * @private + * @param {Object} object The object to compare. + * @param {Object} other The other object to compare. + * @param {string} tag The `toStringTag` of the objects to compare. + * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. + * @param {Function} customizer The function to customize comparisons. + * @param {Function} equalFunc The function to determine equivalents of values. + * @param {Object} stack Tracks traversed `object` and `other` objects. + * @returns {boolean} Returns `true` if the objects are equivalent, else `false`. + */ + function equalByTag(object, other, tag, bitmask, customizer, equalFunc, stack) { + switch (tag) { + + case boolTag: + case dateTag: + case numberTag: + // Coerce booleans to `1` or `0` and dates to milliseconds. + // Invalid dates are coerced to `NaN`. + return eq(+object, +other); + + case errorTag: + return object.name == other.name && object.message == other.message; + + case regexpTag: + case stringTag: + // Coerce regexes to strings and treat strings, primitives and objects, + // as equal. See http://www.ecma-international.org/ecma-262/7.0/#sec-regexp.prototype.tostring + // for more details. + return object == (other + ''); + + } + return false; + } + + /** + * A specialized version of `baseIsEqualDeep` for objects with support for + * partial deep comparisons. + * + * @private + * @param {Object} object The object to compare. + * @param {Object} other The other object to compare. + * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. + * @param {Function} customizer The function to customize comparisons. + * @param {Function} equalFunc The function to determine equivalents of values. + * @param {Object} stack Tracks traversed `object` and `other` objects. + * @returns {boolean} Returns `true` if the objects are equivalent, else `false`. + */ + function equalObjects(object, other, bitmask, customizer, equalFunc, stack) { + var isPartial = bitmask & COMPARE_PARTIAL_FLAG, + objProps = keys(object), + objLength = objProps.length, + othProps = keys(other), + othLength = othProps.length; + + if (objLength != othLength && !isPartial) { + return false; + } + var index = objLength; + while (index--) { + var key = objProps[index]; + if (!(isPartial ? key in other : hasOwnProperty.call(other, key))) { + return false; + } + } + var result = true; + + var skipCtor = isPartial; + while (++index < objLength) { + key = objProps[index]; + var objValue = object[key], + othValue = other[key]; + + var compared; + // Recursively compare objects (susceptible to call stack limits). + if (!(compared === undefined + ? (objValue === othValue || equalFunc(objValue, othValue, bitmask, customizer, stack)) + : compared + )) { + result = false; + break; + } + skipCtor || (skipCtor = key == 'constructor'); + } + if (result && !skipCtor) { + var objCtor = object.constructor, + othCtor = other.constructor; + + // Non `Object` object instances with different constructors are not equal. + if (objCtor != othCtor && + ('constructor' in object && 'constructor' in other) && + !(typeof objCtor == 'function' && objCtor instanceof objCtor && + typeof othCtor == 'function' && othCtor instanceof othCtor)) { + result = false; + } + } + return result; + } + + /** + * A specialized version of `baseRest` which flattens the rest array. + * + * @private + * @param {Function} func The function to apply a rest parameter to. + * @returns {Function} Returns the new function. + */ + function flatRest(func) { + return setToString(overRest(func, undefined, flatten), func + ''); + } + + /** + * Checks if `value` is a flattenable `arguments` object or array. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is flattenable, else `false`. + */ + function isFlattenable(value) { + return isArray(value) || isArguments(value); + } + + /** + * Checks if `value` is a valid array-like index. + * + * @private + * @param {*} value The value to check. + * @param {number} [length=MAX_SAFE_INTEGER] The upper bounds of a valid index. + * @returns {boolean} Returns `true` if `value` is a valid index, else `false`. + */ + function isIndex(value, length) { + var type = typeof value; + length = length == null ? MAX_SAFE_INTEGER : length; + + return !!length && + (type == 'number' || + (type != 'symbol' && reIsUint.test(value))) && + (value > -1 && value % 1 == 0 && value < length); + } + + /** + * Checks if the given arguments are from an iteratee call. + * + * @private + * @param {*} value The potential iteratee value argument. + * @param {*} index The potential iteratee index or key argument. + * @param {*} object The potential iteratee object argument. + * @returns {boolean} Returns `true` if the arguments are from an iteratee call, + * else `false`. + */ + function isIterateeCall(value, index, object) { + if (!isObject(object)) { + return false; + } + var type = typeof index; + if (type == 'number' + ? (isArrayLike(object) && isIndex(index, object.length)) + : (type == 'string' && index in object) + ) { + return eq(object[index], value); + } + return false; + } + + /** + * This function is like + * [`Object.keys`](http://ecma-international.org/ecma-262/7.0/#sec-object.keys) + * except that it includes inherited enumerable properties. + * + * @private + * @param {Object} object The object to query. + * @returns {Array} Returns the array of property names. + */ + function nativeKeysIn(object) { + var result = []; + if (object != null) { + for (var key in Object(object)) { + result.push(key); + } + } + return result; + } + + /** + * Converts `value` to a string using `Object.prototype.toString`. + * + * @private + * @param {*} value The value to convert. + * @returns {string} Returns the converted string. + */ + function objectToString(value) { + return nativeObjectToString.call(value); + } + + /** + * A specialized version of `baseRest` which transforms the rest array. + * + * @private + * @param {Function} func The function to apply a rest parameter to. + * @param {number} [start=func.length-1] The start position of the rest parameter. + * @param {Function} transform The rest array transform. + * @returns {Function} Returns the new function. + */ + function overRest(func, start, transform) { + start = nativeMax(start === undefined ? (func.length - 1) : start, 0); + return function() { + var args = arguments, + index = -1, + length = nativeMax(args.length - start, 0), + array = Array(length); + + while (++index < length) { + array[index] = args[start + index]; + } + index = -1; + var otherArgs = Array(start + 1); + while (++index < start) { + otherArgs[index] = args[index]; + } + otherArgs[start] = transform(array); + return func.apply(this, otherArgs); + }; + } + + /** + * Sets the `toString` method of `func` to return `string`. + * + * @private + * @param {Function} func The function to modify. + * @param {Function} string The `toString` result. + * @returns {Function} Returns `func`. + */ + var setToString = identity; + + /*------------------------------------------------------------------------*/ + + /** + * Creates an array with all falsey values removed. The values `false`, `null`, + * `0`, `""`, `undefined`, and `NaN` are falsey. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to compact. + * @returns {Array} Returns the new array of filtered values. + * @example + * + * _.compact([0, 1, false, 2, '', 3]); + * // => [1, 2, 3] + */ + function compact(array) { + return baseFilter(array, Boolean); + } + + /** + * Creates a new array concatenating `array` with any additional arrays + * and/or values. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to concatenate. + * @param {...*} [values] The values to concatenate. + * @returns {Array} Returns the new concatenated array. + * @example + * + * var array = [1]; + * var other = _.concat(array, 2, [3], [[4]]); + * + * console.log(other); + * // => [1, 2, 3, [4]] + * + * console.log(array); + * // => [1] + */ + function concat() { + var length = arguments.length; + if (!length) { + return []; + } + var args = Array(length - 1), + array = arguments[0], + index = length; + + while (index--) { + args[index - 1] = arguments[index]; + } + return arrayPush(isArray(array) ? copyArray(array) : [array], baseFlatten(args, 1)); + } + + /** + * This method is like `_.find` except that it returns the index of the first + * element `predicate` returns truthy for instead of the element itself. + * + * @static + * @memberOf _ + * @since 1.1.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @param {number} [fromIndex=0] The index to search from. + * @returns {number} Returns the index of the found element, else `-1`. + * @example + * + * var users = [ + * { 'user': 'barney', 'active': false }, + * { 'user': 'fred', 'active': false }, + * { 'user': 'pebbles', 'active': true } + * ]; + * + * _.findIndex(users, function(o) { return o.user == 'barney'; }); + * // => 0 + * + * // The `_.matches` iteratee shorthand. + * _.findIndex(users, { 'user': 'fred', 'active': false }); + * // => 1 + * + * // The `_.matchesProperty` iteratee shorthand. + * _.findIndex(users, ['active', false]); + * // => 0 + * + * // The `_.property` iteratee shorthand. + * _.findIndex(users, 'active'); + * // => 2 + */ + function findIndex(array, predicate, fromIndex) { + var length = array == null ? 0 : array.length; + if (!length) { + return -1; + } + var index = fromIndex == null ? 0 : toInteger(fromIndex); + if (index < 0) { + index = nativeMax(length + index, 0); + } + return baseFindIndex(array, baseIteratee(predicate, 3), index); + } + + /** + * Flattens `array` a single level deep. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to flatten. + * @returns {Array} Returns the new flattened array. + * @example + * + * _.flatten([1, [2, [3, [4]], 5]]); + * // => [1, 2, [3, [4]], 5] + */ + function flatten(array) { + var length = array == null ? 0 : array.length; + return length ? baseFlatten(array, 1) : []; + } + + /** + * Recursively flattens `array`. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to flatten. + * @returns {Array} Returns the new flattened array. + * @example + * + * _.flattenDeep([1, [2, [3, [4]], 5]]); + * // => [1, 2, 3, 4, 5] + */ + function flattenDeep(array) { + var length = array == null ? 0 : array.length; + return length ? baseFlatten(array, INFINITY) : []; + } + + /** + * Gets the first element of `array`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @alias first + * @category Array + * @param {Array} array The array to query. + * @returns {*} Returns the first element of `array`. + * @example + * + * _.head([1, 2, 3]); + * // => 1 + * + * _.head([]); + * // => undefined + */ + function head(array) { + return (array && array.length) ? array[0] : undefined; + } + + /** + * Gets the index at which the first occurrence of `value` is found in `array` + * using [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. If `fromIndex` is negative, it's used as the + * offset from the end of `array`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @param {number} [fromIndex=0] The index to search from. + * @returns {number} Returns the index of the matched value, else `-1`. + * @example + * + * _.indexOf([1, 2, 1, 2], 2); + * // => 1 + * + * // Search from the `fromIndex`. + * _.indexOf([1, 2, 1, 2], 2, 2); + * // => 3 + */ + function indexOf(array, value, fromIndex) { + var length = array == null ? 0 : array.length; + if (typeof fromIndex == 'number') { + fromIndex = fromIndex < 0 ? nativeMax(length + fromIndex, 0) : fromIndex; + } else { + fromIndex = 0; + } + var index = (fromIndex || 0) - 1, + isReflexive = value === value; + + while (++index < length) { + var other = array[index]; + if ((isReflexive ? other === value : other !== other)) { + return index; + } + } + return -1; + } + + /** + * Gets the last element of `array`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to query. + * @returns {*} Returns the last element of `array`. + * @example + * + * _.last([1, 2, 3]); + * // => 3 + */ + function last(array) { + var length = array == null ? 0 : array.length; + return length ? array[length - 1] : undefined; + } + + /** + * Creates a slice of `array` from `start` up to, but not including, `end`. + * + * **Note:** This method is used instead of + * [`Array#slice`](https://mdn.io/Array/slice) to ensure dense arrays are + * returned. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to slice. + * @param {number} [start=0] The start position. + * @param {number} [end=array.length] The end position. + * @returns {Array} Returns the slice of `array`. + */ + function slice(array, start, end) { + var length = array == null ? 0 : array.length; + start = start == null ? 0 : +start; + end = end === undefined ? length : +end; + return length ? baseSlice(array, start, end) : []; + } + + /*------------------------------------------------------------------------*/ + + /** + * Creates a `lodash` wrapper instance that wraps `value` with explicit method + * chain sequences enabled. The result of such sequences must be unwrapped + * with `_#value`. + * + * @static + * @memberOf _ + * @since 1.3.0 + * @category Seq + * @param {*} value The value to wrap. + * @returns {Object} Returns the new `lodash` wrapper instance. + * @example + * + * var users = [ + * { 'user': 'barney', 'age': 36 }, + * { 'user': 'fred', 'age': 40 }, + * { 'user': 'pebbles', 'age': 1 } + * ]; + * + * var youngest = _ + * .chain(users) + * .sortBy('age') + * .map(function(o) { + * return o.user + ' is ' + o.age; + * }) + * .head() + * .value(); + * // => 'pebbles is 1' + */ + function chain(value) { + var result = lodash(value); + result.__chain__ = true; + return result; + } + + /** + * This method invokes `interceptor` and returns `value`. The interceptor + * is invoked with one argument; (value). The purpose of this method is to + * "tap into" a method chain sequence in order to modify intermediate results. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Seq + * @param {*} value The value to provide to `interceptor`. + * @param {Function} interceptor The function to invoke. + * @returns {*} Returns `value`. + * @example + * + * _([1, 2, 3]) + * .tap(function(array) { + * // Mutate input array. + * array.pop(); + * }) + * .reverse() + * .value(); + * // => [2, 1] + */ + function tap(value, interceptor) { + interceptor(value); + return value; + } + + /** + * This method is like `_.tap` except that it returns the result of `interceptor`. + * The purpose of this method is to "pass thru" values replacing intermediate + * results in a method chain sequence. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Seq + * @param {*} value The value to provide to `interceptor`. + * @param {Function} interceptor The function to invoke. + * @returns {*} Returns the result of `interceptor`. + * @example + * + * _(' abc ') + * .chain() + * .trim() + * .thru(function(value) { + * return [value]; + * }) + * .value(); + * // => ['abc'] + */ + function thru(value, interceptor) { + return interceptor(value); + } + + /** + * Creates a `lodash` wrapper instance with explicit method chain sequences enabled. + * + * @name chain + * @memberOf _ + * @since 0.1.0 + * @category Seq + * @returns {Object} Returns the new `lodash` wrapper instance. + * @example + * + * var users = [ + * { 'user': 'barney', 'age': 36 }, + * { 'user': 'fred', 'age': 40 } + * ]; + * + * // A sequence without explicit chaining. + * _(users).head(); + * // => { 'user': 'barney', 'age': 36 } + * + * // A sequence with explicit chaining. + * _(users) + * .chain() + * .head() + * .pick('user') + * .value(); + * // => { 'user': 'barney' } + */ + function wrapperChain() { + return chain(this); + } + + /** + * Executes the chain sequence to resolve the unwrapped value. + * + * @name value + * @memberOf _ + * @since 0.1.0 + * @alias toJSON, valueOf + * @category Seq + * @returns {*} Returns the resolved unwrapped value. + * @example + * + * _([1, 2, 3]).value(); + * // => [1, 2, 3] + */ + function wrapperValue() { + return baseWrapperValue(this.__wrapped__, this.__actions__); + } + + /*------------------------------------------------------------------------*/ + + /** + * Checks if `predicate` returns truthy for **all** elements of `collection`. + * Iteration is stopped once `predicate` returns falsey. The predicate is + * invoked with three arguments: (value, index|key, collection). + * + * **Note:** This method returns `true` for + * [empty collections](https://en.wikipedia.org/wiki/Empty_set) because + * [everything is true](https://en.wikipedia.org/wiki/Vacuous_truth) of + * elements of empty collections. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Collection + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. + * @returns {boolean} Returns `true` if all elements pass the predicate check, + * else `false`. + * @example + * + * _.every([true, 1, null, 'yes'], Boolean); + * // => false + * + * var users = [ + * { 'user': 'barney', 'age': 36, 'active': false }, + * { 'user': 'fred', 'age': 40, 'active': false } + * ]; + * + * // The `_.matches` iteratee shorthand. + * _.every(users, { 'user': 'barney', 'active': false }); + * // => false + * + * // The `_.matchesProperty` iteratee shorthand. + * _.every(users, ['active', false]); + * // => true + * + * // The `_.property` iteratee shorthand. + * _.every(users, 'active'); + * // => false + */ + function every(collection, predicate, guard) { + predicate = guard ? undefined : predicate; + return baseEvery(collection, baseIteratee(predicate)); + } + + /** + * Iterates over elements of `collection`, returning an array of all elements + * `predicate` returns truthy for. The predicate is invoked with three + * arguments: (value, index|key, collection). + * + * **Note:** Unlike `_.remove`, this method returns a new array. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Collection + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @returns {Array} Returns the new filtered array. + * @see _.reject + * @example + * + * var users = [ + * { 'user': 'barney', 'age': 36, 'active': true }, + * { 'user': 'fred', 'age': 40, 'active': false } + * ]; + * + * _.filter(users, function(o) { return !o.active; }); + * // => objects for ['fred'] + * + * // The `_.matches` iteratee shorthand. + * _.filter(users, { 'age': 36, 'active': true }); + * // => objects for ['barney'] + * + * // The `_.matchesProperty` iteratee shorthand. + * _.filter(users, ['active', false]); + * // => objects for ['fred'] + * + * // The `_.property` iteratee shorthand. + * _.filter(users, 'active'); + * // => objects for ['barney'] + */ + function filter(collection, predicate) { + return baseFilter(collection, baseIteratee(predicate)); + } + + /** + * Iterates over elements of `collection`, returning the first element + * `predicate` returns truthy for. The predicate is invoked with three + * arguments: (value, index|key, collection). + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Collection + * @param {Array|Object} collection The collection to inspect. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @param {number} [fromIndex=0] The index to search from. + * @returns {*} Returns the matched element, else `undefined`. + * @example + * + * var users = [ + * { 'user': 'barney', 'age': 36, 'active': true }, + * { 'user': 'fred', 'age': 40, 'active': false }, + * { 'user': 'pebbles', 'age': 1, 'active': true } + * ]; + * + * _.find(users, function(o) { return o.age < 40; }); + * // => object for 'barney' + * + * // The `_.matches` iteratee shorthand. + * _.find(users, { 'age': 1, 'active': true }); + * // => object for 'pebbles' + * + * // The `_.matchesProperty` iteratee shorthand. + * _.find(users, ['active', false]); + * // => object for 'fred' + * + * // The `_.property` iteratee shorthand. + * _.find(users, 'active'); + * // => object for 'barney' + */ + var find = createFind(findIndex); + + /** + * Iterates over elements of `collection` and invokes `iteratee` for each element. + * The iteratee is invoked with three arguments: (value, index|key, collection). + * Iteratee functions may exit iteration early by explicitly returning `false`. + * + * **Note:** As with other "Collections" methods, objects with a "length" + * property are iterated like arrays. To avoid this behavior use `_.forIn` + * or `_.forOwn` for object iteration. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @alias each + * @category Collection + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} [iteratee=_.identity] The function invoked per iteration. + * @returns {Array|Object} Returns `collection`. + * @see _.forEachRight + * @example + * + * _.forEach([1, 2], function(value) { + * console.log(value); + * }); + * // => Logs `1` then `2`. + * + * _.forEach({ 'a': 1, 'b': 2 }, function(value, key) { + * console.log(key); + * }); + * // => Logs 'a' then 'b' (iteration order is not guaranteed). + */ + function forEach(collection, iteratee) { + return baseEach(collection, baseIteratee(iteratee)); + } + + /** + * Creates an array of values by running each element in `collection` thru + * `iteratee`. The iteratee is invoked with three arguments: + * (value, index|key, collection). + * + * Many lodash methods are guarded to work as iteratees for methods like + * `_.every`, `_.filter`, `_.map`, `_.mapValues`, `_.reject`, and `_.some`. + * + * The guarded methods are: + * `ary`, `chunk`, `curry`, `curryRight`, `drop`, `dropRight`, `every`, + * `fill`, `invert`, `parseInt`, `random`, `range`, `rangeRight`, `repeat`, + * `sampleSize`, `slice`, `some`, `sortBy`, `split`, `take`, `takeRight`, + * `template`, `trim`, `trimEnd`, `trimStart`, and `words` + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Collection + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} [iteratee=_.identity] The function invoked per iteration. + * @returns {Array} Returns the new mapped array. + * @example + * + * function square(n) { + * return n * n; + * } + * + * _.map([4, 8], square); + * // => [16, 64] + * + * _.map({ 'a': 4, 'b': 8 }, square); + * // => [16, 64] (iteration order is not guaranteed) + * + * var users = [ + * { 'user': 'barney' }, + * { 'user': 'fred' } + * ]; + * + * // The `_.property` iteratee shorthand. + * _.map(users, 'user'); + * // => ['barney', 'fred'] + */ + function map(collection, iteratee) { + return baseMap(collection, baseIteratee(iteratee)); + } + + /** + * Reduces `collection` to a value which is the accumulated result of running + * each element in `collection` thru `iteratee`, where each successive + * invocation is supplied the return value of the previous. If `accumulator` + * is not given, the first element of `collection` is used as the initial + * value. The iteratee is invoked with four arguments: + * (accumulator, value, index|key, collection). + * + * Many lodash methods are guarded to work as iteratees for methods like + * `_.reduce`, `_.reduceRight`, and `_.transform`. + * + * The guarded methods are: + * `assign`, `defaults`, `defaultsDeep`, `includes`, `merge`, `orderBy`, + * and `sortBy` + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Collection + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} [iteratee=_.identity] The function invoked per iteration. + * @param {*} [accumulator] The initial value. + * @returns {*} Returns the accumulated value. + * @see _.reduceRight + * @example + * + * _.reduce([1, 2], function(sum, n) { + * return sum + n; + * }, 0); + * // => 3 + * + * _.reduce({ 'a': 1, 'b': 2, 'c': 1 }, function(result, value, key) { + * (result[value] || (result[value] = [])).push(key); + * return result; + * }, {}); + * // => { '1': ['a', 'c'], '2': ['b'] } (iteration order is not guaranteed) + */ + function reduce(collection, iteratee, accumulator) { + return baseReduce(collection, baseIteratee(iteratee), accumulator, arguments.length < 3, baseEach); + } + + /** + * Gets the size of `collection` by returning its length for array-like + * values or the number of own enumerable string keyed properties for objects. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Collection + * @param {Array|Object|string} collection The collection to inspect. + * @returns {number} Returns the collection size. + * @example + * + * _.size([1, 2, 3]); + * // => 3 + * + * _.size({ 'a': 1, 'b': 2 }); + * // => 2 + * + * _.size('pebbles'); + * // => 7 + */ + function size(collection) { + if (collection == null) { + return 0; + } + collection = isArrayLike(collection) ? collection : nativeKeys(collection); + return collection.length; + } + + /** + * Checks if `predicate` returns truthy for **any** element of `collection`. + * Iteration is stopped once `predicate` returns truthy. The predicate is + * invoked with three arguments: (value, index|key, collection). + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Collection + * @param {Array|Object} collection The collection to iterate over. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. + * @returns {boolean} Returns `true` if any element passes the predicate check, + * else `false`. + * @example + * + * _.some([null, 0, 'yes', false], Boolean); + * // => true + * + * var users = [ + * { 'user': 'barney', 'active': true }, + * { 'user': 'fred', 'active': false } + * ]; + * + * // The `_.matches` iteratee shorthand. + * _.some(users, { 'user': 'barney', 'active': false }); + * // => false + * + * // The `_.matchesProperty` iteratee shorthand. + * _.some(users, ['active', false]); + * // => true + * + * // The `_.property` iteratee shorthand. + * _.some(users, 'active'); + * // => true + */ + function some(collection, predicate, guard) { + predicate = guard ? undefined : predicate; + return baseSome(collection, baseIteratee(predicate)); + } + + /** + * Creates an array of elements, sorted in ascending order by the results of + * running each element in a collection thru each iteratee. This method + * performs a stable sort, that is, it preserves the original sort order of + * equal elements. The iteratees are invoked with one argument: (value). + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Collection + * @param {Array|Object} collection The collection to iterate over. + * @param {...(Function|Function[])} [iteratees=[_.identity]] + * The iteratees to sort by. + * @returns {Array} Returns the new sorted array. + * @example + * + * var users = [ + * { 'user': 'fred', 'age': 48 }, + * { 'user': 'barney', 'age': 36 }, + * { 'user': 'fred', 'age': 40 }, + * { 'user': 'barney', 'age': 34 } + * ]; + * + * _.sortBy(users, [function(o) { return o.user; }]); + * // => objects for [['barney', 36], ['barney', 34], ['fred', 48], ['fred', 40]] + * + * _.sortBy(users, ['user', 'age']); + * // => objects for [['barney', 34], ['barney', 36], ['fred', 40], ['fred', 48]] + */ + function sortBy(collection, iteratee) { + var index = 0; + iteratee = baseIteratee(iteratee); + + return baseMap(baseMap(collection, function(value, key, collection) { + return { 'value': value, 'index': index++, 'criteria': iteratee(value, key, collection) }; + }).sort(function(object, other) { + return compareAscending(object.criteria, other.criteria) || (object.index - other.index); + }), baseProperty('value')); + } + + /*------------------------------------------------------------------------*/ + + /** + * Creates a function that invokes `func`, with the `this` binding and arguments + * of the created function, while it's called less than `n` times. Subsequent + * calls to the created function return the result of the last `func` invocation. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Function + * @param {number} n The number of calls at which `func` is no longer invoked. + * @param {Function} func The function to restrict. + * @returns {Function} Returns the new restricted function. + * @example + * + * jQuery(element).on('click', _.before(5, addContactToList)); + * // => Allows adding up to 4 contacts to the list. + */ + function before(n, func) { + var result; + if (typeof func != 'function') { + throw new TypeError(FUNC_ERROR_TEXT); + } + n = toInteger(n); + return function() { + if (--n > 0) { + result = func.apply(this, arguments); + } + if (n <= 1) { + func = undefined; + } + return result; + }; + } + + /** + * Creates a function that invokes `func` with the `this` binding of `thisArg` + * and `partials` prepended to the arguments it receives. + * + * The `_.bind.placeholder` value, which defaults to `_` in monolithic builds, + * may be used as a placeholder for partially applied arguments. + * + * **Note:** Unlike native `Function#bind`, this method doesn't set the "length" + * property of bound functions. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Function + * @param {Function} func The function to bind. + * @param {*} thisArg The `this` binding of `func`. + * @param {...*} [partials] The arguments to be partially applied. + * @returns {Function} Returns the new bound function. + * @example + * + * function greet(greeting, punctuation) { + * return greeting + ' ' + this.user + punctuation; + * } + * + * var object = { 'user': 'fred' }; + * + * var bound = _.bind(greet, object, 'hi'); + * bound('!'); + * // => 'hi fred!' + * + * // Bound with placeholders. + * var bound = _.bind(greet, object, _, '!'); + * bound('hi'); + * // => 'hi fred!' + */ + var bind = baseRest(function(func, thisArg, partials) { + return createPartial(func, WRAP_BIND_FLAG | WRAP_PARTIAL_FLAG, thisArg, partials); + }); + + /** + * Defers invoking the `func` until the current call stack has cleared. Any + * additional arguments are provided to `func` when it's invoked. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Function + * @param {Function} func The function to defer. + * @param {...*} [args] The arguments to invoke `func` with. + * @returns {number} Returns the timer id. + * @example + * + * _.defer(function(text) { + * console.log(text); + * }, 'deferred'); + * // => Logs 'deferred' after one millisecond. + */ + var defer = baseRest(function(func, args) { + return baseDelay(func, 1, args); + }); + + /** + * Invokes `func` after `wait` milliseconds. Any additional arguments are + * provided to `func` when it's invoked. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Function + * @param {Function} func The function to delay. + * @param {number} wait The number of milliseconds to delay invocation. + * @param {...*} [args] The arguments to invoke `func` with. + * @returns {number} Returns the timer id. + * @example + * + * _.delay(function(text) { + * console.log(text); + * }, 1000, 'later'); + * // => Logs 'later' after one second. + */ + var delay = baseRest(function(func, wait, args) { + return baseDelay(func, toNumber(wait) || 0, args); + }); + + /** + * Creates a function that negates the result of the predicate `func`. The + * `func` predicate is invoked with the `this` binding and arguments of the + * created function. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Function + * @param {Function} predicate The predicate to negate. + * @returns {Function} Returns the new negated function. + * @example + * + * function isEven(n) { + * return n % 2 == 0; + * } + * + * _.filter([1, 2, 3, 4, 5, 6], _.negate(isEven)); + * // => [1, 3, 5] + */ + function negate(predicate) { + if (typeof predicate != 'function') { + throw new TypeError(FUNC_ERROR_TEXT); + } + return function() { + var args = arguments; + return !predicate.apply(this, args); + }; + } + + /** + * Creates a function that is restricted to invoking `func` once. Repeat calls + * to the function return the value of the first invocation. The `func` is + * invoked with the `this` binding and arguments of the created function. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Function + * @param {Function} func The function to restrict. + * @returns {Function} Returns the new restricted function. + * @example + * + * var initialize = _.once(createApplication); + * initialize(); + * initialize(); + * // => `createApplication` is invoked once + */ + function once(func) { + return before(2, func); + } + + /*------------------------------------------------------------------------*/ + + /** + * Creates a shallow clone of `value`. + * + * **Note:** This method is loosely based on the + * [structured clone algorithm](https://mdn.io/Structured_clone_algorithm) + * and supports cloning arrays, array buffers, booleans, date objects, maps, + * numbers, `Object` objects, regexes, sets, strings, symbols, and typed + * arrays. The own enumerable properties of `arguments` objects are cloned + * as plain objects. An empty object is returned for uncloneable values such + * as error objects, functions, DOM nodes, and WeakMaps. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to clone. + * @returns {*} Returns the cloned value. + * @see _.cloneDeep + * @example + * + * var objects = [{ 'a': 1 }, { 'b': 2 }]; + * + * var shallow = _.clone(objects); + * console.log(shallow[0] === objects[0]); + * // => true + */ + function clone(value) { + if (!isObject(value)) { + return value; + } + return isArray(value) ? copyArray(value) : copyObject(value, nativeKeys(value)); + } + + /** + * Performs a + * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * comparison between two values to determine if they are equivalent. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @returns {boolean} Returns `true` if the values are equivalent, else `false`. + * @example + * + * var object = { 'a': 1 }; + * var other = { 'a': 1 }; + * + * _.eq(object, object); + * // => true + * + * _.eq(object, other); + * // => false + * + * _.eq('a', 'a'); + * // => true + * + * _.eq('a', Object('a')); + * // => false + * + * _.eq(NaN, NaN); + * // => true + */ + function eq(value, other) { + return value === other || (value !== value && other !== other); + } + + /** + * Checks if `value` is likely an `arguments` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an `arguments` object, + * else `false`. + * @example + * + * _.isArguments(function() { return arguments; }()); + * // => true + * + * _.isArguments([1, 2, 3]); + * // => false + */ + var isArguments = baseIsArguments(function() { return arguments; }()) ? baseIsArguments : function(value) { + return isObjectLike(value) && hasOwnProperty.call(value, 'callee') && + !propertyIsEnumerable.call(value, 'callee'); + }; + + /** + * Checks if `value` is classified as an `Array` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an array, else `false`. + * @example + * + * _.isArray([1, 2, 3]); + * // => true + * + * _.isArray(document.body.children); + * // => false + * + * _.isArray('abc'); + * // => false + * + * _.isArray(_.noop); + * // => false + */ + var isArray = Array.isArray; + + /** + * Checks if `value` is array-like. A value is considered array-like if it's + * not a function and has a `value.length` that's an integer greater than or + * equal to `0` and less than or equal to `Number.MAX_SAFE_INTEGER`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is array-like, else `false`. + * @example + * + * _.isArrayLike([1, 2, 3]); + * // => true + * + * _.isArrayLike(document.body.children); + * // => true + * + * _.isArrayLike('abc'); + * // => true + * + * _.isArrayLike(_.noop); + * // => false + */ + function isArrayLike(value) { + return value != null && isLength(value.length) && !isFunction(value); + } + + /** + * Checks if `value` is classified as a boolean primitive or object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a boolean, else `false`. + * @example + * + * _.isBoolean(false); + * // => true + * + * _.isBoolean(null); + * // => false + */ + function isBoolean(value) { + return value === true || value === false || + (isObjectLike(value) && baseGetTag(value) == boolTag); + } + + /** + * Checks if `value` is classified as a `Date` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a date object, else `false`. + * @example + * + * _.isDate(new Date); + * // => true + * + * _.isDate('Mon April 23 2012'); + * // => false + */ + var isDate = baseIsDate; + + /** + * Checks if `value` is an empty object, collection, map, or set. + * + * Objects are considered empty if they have no own enumerable string keyed + * properties. + * + * Array-like values such as `arguments` objects, arrays, buffers, strings, or + * jQuery-like collections are considered empty if they have a `length` of `0`. + * Similarly, maps and sets are considered empty if they have a `size` of `0`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is empty, else `false`. + * @example + * + * _.isEmpty(null); + * // => true + * + * _.isEmpty(true); + * // => true + * + * _.isEmpty(1); + * // => true + * + * _.isEmpty([1, 2, 3]); + * // => false + * + * _.isEmpty({ 'a': 1 }); + * // => false + */ + function isEmpty(value) { + if (isArrayLike(value) && + (isArray(value) || isString(value) || + isFunction(value.splice) || isArguments(value))) { + return !value.length; + } + return !nativeKeys(value).length; + } + + /** + * Performs a deep comparison between two values to determine if they are + * equivalent. + * + * **Note:** This method supports comparing arrays, array buffers, booleans, + * date objects, error objects, maps, numbers, `Object` objects, regexes, + * sets, strings, symbols, and typed arrays. `Object` objects are compared + * by their own, not inherited, enumerable properties. Functions and DOM + * nodes are compared by strict equality, i.e. `===`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @returns {boolean} Returns `true` if the values are equivalent, else `false`. + * @example + * + * var object = { 'a': 1 }; + * var other = { 'a': 1 }; + * + * _.isEqual(object, other); + * // => true + * + * object === other; + * // => false + */ + function isEqual(value, other) { + return baseIsEqual(value, other); + } + + /** + * Checks if `value` is a finite primitive number. + * + * **Note:** This method is based on + * [`Number.isFinite`](https://mdn.io/Number/isFinite). + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a finite number, else `false`. + * @example + * + * _.isFinite(3); + * // => true + * + * _.isFinite(Number.MIN_VALUE); + * // => true + * + * _.isFinite(Infinity); + * // => false + * + * _.isFinite('3'); + * // => false + */ + function isFinite(value) { + return typeof value == 'number' && nativeIsFinite(value); + } + + /** + * Checks if `value` is classified as a `Function` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a function, else `false`. + * @example + * + * _.isFunction(_); + * // => true + * + * _.isFunction(/abc/); + * // => false + */ + function isFunction(value) { + if (!isObject(value)) { + return false; + } + // The use of `Object#toString` avoids issues with the `typeof` operator + // in Safari 9 which returns 'object' for typed arrays and other constructors. + var tag = baseGetTag(value); + return tag == funcTag || tag == genTag || tag == asyncTag || tag == proxyTag; + } + + /** + * Checks if `value` is a valid array-like length. + * + * **Note:** This method is loosely based on + * [`ToLength`](http://ecma-international.org/ecma-262/7.0/#sec-tolength). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a valid length, else `false`. + * @example + * + * _.isLength(3); + * // => true + * + * _.isLength(Number.MIN_VALUE); + * // => false + * + * _.isLength(Infinity); + * // => false + * + * _.isLength('3'); + * // => false + */ + function isLength(value) { + return typeof value == 'number' && + value > -1 && value % 1 == 0 && value <= MAX_SAFE_INTEGER; + } + + /** + * Checks if `value` is the + * [language type](http://www.ecma-international.org/ecma-262/7.0/#sec-ecmascript-language-types) + * of `Object`. (e.g. arrays, functions, objects, regexes, `new Number(0)`, and `new String('')`) + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an object, else `false`. + * @example + * + * _.isObject({}); + * // => true + * + * _.isObject([1, 2, 3]); + * // => true + * + * _.isObject(_.noop); + * // => true + * + * _.isObject(null); + * // => false + */ + function isObject(value) { + var type = typeof value; + return value != null && (type == 'object' || type == 'function'); + } + + /** + * Checks if `value` is object-like. A value is object-like if it's not `null` + * and has a `typeof` result of "object". + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is object-like, else `false`. + * @example + * + * _.isObjectLike({}); + * // => true + * + * _.isObjectLike([1, 2, 3]); + * // => true + * + * _.isObjectLike(_.noop); + * // => false + * + * _.isObjectLike(null); + * // => false + */ + function isObjectLike(value) { + return value != null && typeof value == 'object'; + } + + /** + * Checks if `value` is `NaN`. + * + * **Note:** This method is based on + * [`Number.isNaN`](https://mdn.io/Number/isNaN) and is not the same as + * global [`isNaN`](https://mdn.io/isNaN) which returns `true` for + * `undefined` and other non-number values. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is `NaN`, else `false`. + * @example + * + * _.isNaN(NaN); + * // => true + * + * _.isNaN(new Number(NaN)); + * // => true + * + * isNaN(undefined); + * // => true + * + * _.isNaN(undefined); + * // => false + */ + function isNaN(value) { + // An `NaN` primitive is the only value that is not equal to itself. + // Perform the `toStringTag` check first to avoid errors with some + // ActiveX objects in IE. + return isNumber(value) && value != +value; + } + + /** + * Checks if `value` is `null`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is `null`, else `false`. + * @example + * + * _.isNull(null); + * // => true + * + * _.isNull(void 0); + * // => false + */ + function isNull(value) { + return value === null; + } + + /** + * Checks if `value` is classified as a `Number` primitive or object. + * + * **Note:** To exclude `Infinity`, `-Infinity`, and `NaN`, which are + * classified as numbers, use the `_.isFinite` method. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a number, else `false`. + * @example + * + * _.isNumber(3); + * // => true + * + * _.isNumber(Number.MIN_VALUE); + * // => true + * + * _.isNumber(Infinity); + * // => true + * + * _.isNumber('3'); + * // => false + */ + function isNumber(value) { + return typeof value == 'number' || + (isObjectLike(value) && baseGetTag(value) == numberTag); + } + + /** + * Checks if `value` is classified as a `RegExp` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a regexp, else `false`. + * @example + * + * _.isRegExp(/abc/); + * // => true + * + * _.isRegExp('/abc/'); + * // => false + */ + var isRegExp = baseIsRegExp; + + /** + * Checks if `value` is classified as a `String` primitive or object. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a string, else `false`. + * @example + * + * _.isString('abc'); + * // => true + * + * _.isString(1); + * // => false + */ + function isString(value) { + return typeof value == 'string' || + (!isArray(value) && isObjectLike(value) && baseGetTag(value) == stringTag); + } + + /** + * Checks if `value` is `undefined`. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is `undefined`, else `false`. + * @example + * + * _.isUndefined(void 0); + * // => true + * + * _.isUndefined(null); + * // => false + */ + function isUndefined(value) { + return value === undefined; + } + + /** + * Converts `value` to an array. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Lang + * @param {*} value The value to convert. + * @returns {Array} Returns the converted array. + * @example + * + * _.toArray({ 'a': 1, 'b': 2 }); + * // => [1, 2] + * + * _.toArray('abc'); + * // => ['a', 'b', 'c'] + * + * _.toArray(1); + * // => [] + * + * _.toArray(null); + * // => [] + */ + function toArray(value) { + if (!isArrayLike(value)) { + return values(value); + } + return value.length ? copyArray(value) : []; + } + + /** + * Converts `value` to an integer. + * + * **Note:** This method is loosely based on + * [`ToInteger`](http://www.ecma-international.org/ecma-262/7.0/#sec-tointeger). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to convert. + * @returns {number} Returns the converted integer. + * @example + * + * _.toInteger(3.2); + * // => 3 + * + * _.toInteger(Number.MIN_VALUE); + * // => 0 + * + * _.toInteger(Infinity); + * // => 1.7976931348623157e+308 + * + * _.toInteger('3.2'); + * // => 3 + */ + var toInteger = Number; + + /** + * Converts `value` to a number. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to process. + * @returns {number} Returns the number. + * @example + * + * _.toNumber(3.2); + * // => 3.2 + * + * _.toNumber(Number.MIN_VALUE); + * // => 5e-324 + * + * _.toNumber(Infinity); + * // => Infinity + * + * _.toNumber('3.2'); + * // => 3.2 + */ + var toNumber = Number; + + /** + * Converts `value` to a string. An empty string is returned for `null` + * and `undefined` values. The sign of `-0` is preserved. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to convert. + * @returns {string} Returns the converted string. + * @example + * + * _.toString(null); + * // => '' + * + * _.toString(-0); + * // => '-0' + * + * _.toString([1, 2, 3]); + * // => '1,2,3' + */ + function toString(value) { + if (typeof value == 'string') { + return value; + } + return value == null ? '' : (value + ''); + } + + /*------------------------------------------------------------------------*/ + + /** + * Assigns own enumerable string keyed properties of source objects to the + * destination object. Source objects are applied from left to right. + * Subsequent sources overwrite property assignments of previous sources. + * + * **Note:** This method mutates `object` and is loosely based on + * [`Object.assign`](https://mdn.io/Object/assign). + * + * @static + * @memberOf _ + * @since 0.10.0 + * @category Object + * @param {Object} object The destination object. + * @param {...Object} [sources] The source objects. + * @returns {Object} Returns `object`. + * @see _.assignIn + * @example + * + * function Foo() { + * this.a = 1; + * } + * + * function Bar() { + * this.c = 3; + * } + * + * Foo.prototype.b = 2; + * Bar.prototype.d = 4; + * + * _.assign({ 'a': 0 }, new Foo, new Bar); + * // => { 'a': 1, 'c': 3 } + */ + var assign = createAssigner(function(object, source) { + copyObject(source, nativeKeys(source), object); + }); + + /** + * This method is like `_.assign` except that it iterates over own and + * inherited source properties. + * + * **Note:** This method mutates `object`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @alias extend + * @category Object + * @param {Object} object The destination object. + * @param {...Object} [sources] The source objects. + * @returns {Object} Returns `object`. + * @see _.assign + * @example + * + * function Foo() { + * this.a = 1; + * } + * + * function Bar() { + * this.c = 3; + * } + * + * Foo.prototype.b = 2; + * Bar.prototype.d = 4; + * + * _.assignIn({ 'a': 0 }, new Foo, new Bar); + * // => { 'a': 1, 'b': 2, 'c': 3, 'd': 4 } + */ + var assignIn = createAssigner(function(object, source) { + copyObject(source, nativeKeysIn(source), object); + }); + + /** + * Creates an object that inherits from the `prototype` object. If a + * `properties` object is given, its own enumerable string keyed properties + * are assigned to the created object. + * + * @static + * @memberOf _ + * @since 2.3.0 + * @category Object + * @param {Object} prototype The object to inherit from. + * @param {Object} [properties] The properties to assign to the object. + * @returns {Object} Returns the new object. + * @example + * + * function Shape() { + * this.x = 0; + * this.y = 0; + * } + * + * function Circle() { + * Shape.call(this); + * } + * + * Circle.prototype = _.create(Shape.prototype, { + * 'constructor': Circle + * }); + * + * var circle = new Circle; + * circle instanceof Circle; + * // => true + * + * circle instanceof Shape; + * // => true + */ + function create(prototype, properties) { + var result = baseCreate(prototype); + return properties == null ? result : assign(result, properties); + } + + /** + * Assigns own and inherited enumerable string keyed properties of source + * objects to the destination object for all destination properties that + * resolve to `undefined`. Source objects are applied from left to right. + * Once a property is set, additional values of the same property are ignored. + * + * **Note:** This method mutates `object`. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Object + * @param {Object} object The destination object. + * @param {...Object} [sources] The source objects. + * @returns {Object} Returns `object`. + * @see _.defaultsDeep + * @example + * + * _.defaults({ 'a': 1 }, { 'b': 2 }, { 'a': 3 }); + * // => { 'a': 1, 'b': 2 } + */ + var defaults = baseRest(function(object, sources) { + object = Object(object); + + var index = -1; + var length = sources.length; + var guard = length > 2 ? sources[2] : undefined; + + if (guard && isIterateeCall(sources[0], sources[1], guard)) { + length = 1; + } + + while (++index < length) { + var source = sources[index]; + var props = keysIn(source); + var propsIndex = -1; + var propsLength = props.length; + + while (++propsIndex < propsLength) { + var key = props[propsIndex]; + var value = object[key]; + + if (value === undefined || + (eq(value, objectProto[key]) && !hasOwnProperty.call(object, key))) { + object[key] = source[key]; + } + } + } + + return object; + }); + + /** + * Checks if `path` is a direct property of `object`. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Object + * @param {Object} object The object to query. + * @param {Array|string} path The path to check. + * @returns {boolean} Returns `true` if `path` exists, else `false`. + * @example + * + * var object = { 'a': { 'b': 2 } }; + * var other = _.create({ 'a': _.create({ 'b': 2 }) }); + * + * _.has(object, 'a'); + * // => true + * + * _.has(object, 'a.b'); + * // => true + * + * _.has(object, ['a', 'b']); + * // => true + * + * _.has(other, 'a'); + * // => false + */ + function has(object, path) { + return object != null && hasOwnProperty.call(object, path); + } + + /** + * Creates an array of the own enumerable property names of `object`. + * + * **Note:** Non-object values are coerced to objects. See the + * [ES spec](http://ecma-international.org/ecma-262/7.0/#sec-object.keys) + * for more details. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Object + * @param {Object} object The object to query. + * @returns {Array} Returns the array of property names. + * @example + * + * function Foo() { + * this.a = 1; + * this.b = 2; + * } + * + * Foo.prototype.c = 3; + * + * _.keys(new Foo); + * // => ['a', 'b'] (iteration order is not guaranteed) + * + * _.keys('hi'); + * // => ['0', '1'] + */ + var keys = nativeKeys; + + /** + * Creates an array of the own and inherited enumerable property names of `object`. + * + * **Note:** Non-object values are coerced to objects. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Object + * @param {Object} object The object to query. + * @returns {Array} Returns the array of property names. + * @example + * + * function Foo() { + * this.a = 1; + * this.b = 2; + * } + * + * Foo.prototype.c = 3; + * + * _.keysIn(new Foo); + * // => ['a', 'b', 'c'] (iteration order is not guaranteed) + */ + var keysIn = nativeKeysIn; + + /** + * Creates an object composed of the picked `object` properties. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Object + * @param {Object} object The source object. + * @param {...(string|string[])} [paths] The property paths to pick. + * @returns {Object} Returns the new object. + * @example + * + * var object = { 'a': 1, 'b': '2', 'c': 3 }; + * + * _.pick(object, ['a', 'c']); + * // => { 'a': 1, 'c': 3 } + */ + var pick = flatRest(function(object, paths) { + return object == null ? {} : basePick(object, paths); + }); + + /** + * This method is like `_.get` except that if the resolved value is a + * function it's invoked with the `this` binding of its parent object and + * its result is returned. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Object + * @param {Object} object The object to query. + * @param {Array|string} path The path of the property to resolve. + * @param {*} [defaultValue] The value returned for `undefined` resolved values. + * @returns {*} Returns the resolved value. + * @example + * + * var object = { 'a': [{ 'b': { 'c1': 3, 'c2': _.constant(4) } }] }; + * + * _.result(object, 'a[0].b.c1'); + * // => 3 + * + * _.result(object, 'a[0].b.c2'); + * // => 4 + * + * _.result(object, 'a[0].b.c3', 'default'); + * // => 'default' + * + * _.result(object, 'a[0].b.c3', _.constant('default')); + * // => 'default' + */ + function result(object, path, defaultValue) { + var value = object == null ? undefined : object[path]; + if (value === undefined) { + value = defaultValue; + } + return isFunction(value) ? value.call(object) : value; + } + + /** + * Creates an array of the own enumerable string keyed property values of `object`. + * + * **Note:** Non-object values are coerced to objects. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Object + * @param {Object} object The object to query. + * @returns {Array} Returns the array of property values. + * @example + * + * function Foo() { + * this.a = 1; + * this.b = 2; + * } + * + * Foo.prototype.c = 3; + * + * _.values(new Foo); + * // => [1, 2] (iteration order is not guaranteed) + * + * _.values('hi'); + * // => ['h', 'i'] + */ + function values(object) { + return object == null ? [] : baseValues(object, keys(object)); + } + + /*------------------------------------------------------------------------*/ + + /** + * Converts the characters "&", "<", ">", '"', and "'" in `string` to their + * corresponding HTML entities. + * + * **Note:** No other characters are escaped. To escape additional + * characters use a third-party library like [_he_](https://mths.be/he). + * + * Though the ">" character is escaped for symmetry, characters like + * ">" and "/" don't need escaping in HTML and have no special meaning + * unless they're part of a tag or unquoted attribute value. See + * [Mathias Bynens's article](https://mathiasbynens.be/notes/ambiguous-ampersands) + * (under "semi-related fun fact") for more details. + * + * When working with HTML you should always + * [quote attribute values](http://wonko.com/post/html-escaping) to reduce + * XSS vectors. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category String + * @param {string} [string=''] The string to escape. + * @returns {string} Returns the escaped string. + * @example + * + * _.escape('fred, barney, & pebbles'); + * // => 'fred, barney, & pebbles' + */ + function escape(string) { + string = toString(string); + return (string && reHasUnescapedHtml.test(string)) + ? string.replace(reUnescapedHtml, escapeHtmlChar) + : string; + } + + /*------------------------------------------------------------------------*/ + + /** + * This method returns the first argument it receives. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Util + * @param {*} value Any value. + * @returns {*} Returns `value`. + * @example + * + * var object = { 'a': 1 }; + * + * console.log(_.identity(object) === object); + * // => true + */ + function identity(value) { + return value; + } + + /** + * Creates a function that invokes `func` with the arguments of the created + * function. If `func` is a property name, the created function returns the + * property value for a given element. If `func` is an array or object, the + * created function returns `true` for elements that contain the equivalent + * source properties, otherwise it returns `false`. + * + * @static + * @since 4.0.0 + * @memberOf _ + * @category Util + * @param {*} [func=_.identity] The value to convert to a callback. + * @returns {Function} Returns the callback. + * @example + * + * var users = [ + * { 'user': 'barney', 'age': 36, 'active': true }, + * { 'user': 'fred', 'age': 40, 'active': false } + * ]; + * + * // The `_.matches` iteratee shorthand. + * _.filter(users, _.iteratee({ 'user': 'barney', 'active': true })); + * // => [{ 'user': 'barney', 'age': 36, 'active': true }] + * + * // The `_.matchesProperty` iteratee shorthand. + * _.filter(users, _.iteratee(['user', 'fred'])); + * // => [{ 'user': 'fred', 'age': 40 }] + * + * // The `_.property` iteratee shorthand. + * _.map(users, _.iteratee('user')); + * // => ['barney', 'fred'] + * + * // Create custom iteratee shorthands. + * _.iteratee = _.wrap(_.iteratee, function(iteratee, func) { + * return !_.isRegExp(func) ? iteratee(func) : function(string) { + * return func.test(string); + * }; + * }); + * + * _.filter(['abc', 'def'], /ef/); + * // => ['def'] + */ + var iteratee = baseIteratee; + + /** + * Creates a function that performs a partial deep comparison between a given + * object and `source`, returning `true` if the given object has equivalent + * property values, else `false`. + * + * **Note:** The created function is equivalent to `_.isMatch` with `source` + * partially applied. + * + * Partial comparisons will match empty array and empty object `source` + * values against any array or object value, respectively. See `_.isEqual` + * for a list of supported value comparisons. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Util + * @param {Object} source The object of property values to match. + * @returns {Function} Returns the new spec function. + * @example + * + * var objects = [ + * { 'a': 1, 'b': 2, 'c': 3 }, + * { 'a': 4, 'b': 5, 'c': 6 } + * ]; + * + * _.filter(objects, _.matches({ 'a': 4, 'c': 6 })); + * // => [{ 'a': 4, 'b': 5, 'c': 6 }] + */ + function matches(source) { + return baseMatches(assign({}, source)); + } + + /** + * Adds all own enumerable string keyed function properties of a source + * object to the destination object. If `object` is a function, then methods + * are added to its prototype as well. + * + * **Note:** Use `_.runInContext` to create a pristine `lodash` function to + * avoid conflicts caused by modifying the original. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Util + * @param {Function|Object} [object=lodash] The destination object. + * @param {Object} source The object of functions to add. + * @param {Object} [options={}] The options object. + * @param {boolean} [options.chain=true] Specify whether mixins are chainable. + * @returns {Function|Object} Returns `object`. + * @example + * + * function vowels(string) { + * return _.filter(string, function(v) { + * return /[aeiou]/i.test(v); + * }); + * } + * + * _.mixin({ 'vowels': vowels }); + * _.vowels('fred'); + * // => ['e'] + * + * _('fred').vowels().value(); + * // => ['e'] + * + * _.mixin({ 'vowels': vowels }, { 'chain': false }); + * _('fred').vowels(); + * // => ['e'] + */ + function mixin(object, source, options) { + var props = keys(source), + methodNames = baseFunctions(source, props); + + if (options == null && + !(isObject(source) && (methodNames.length || !props.length))) { + options = source; + source = object; + object = this; + methodNames = baseFunctions(source, keys(source)); + } + var chain = !(isObject(options) && 'chain' in options) || !!options.chain, + isFunc = isFunction(object); + + baseEach(methodNames, function(methodName) { + var func = source[methodName]; + object[methodName] = func; + if (isFunc) { + object.prototype[methodName] = function() { + var chainAll = this.__chain__; + if (chain || chainAll) { + var result = object(this.__wrapped__), + actions = result.__actions__ = copyArray(this.__actions__); + + actions.push({ 'func': func, 'args': arguments, 'thisArg': object }); + result.__chain__ = chainAll; + return result; + } + return func.apply(object, arrayPush([this.value()], arguments)); + }; + } + }); + + return object; + } + + /** + * Reverts the `_` variable to its previous value and returns a reference to + * the `lodash` function. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Util + * @returns {Function} Returns the `lodash` function. + * @example + * + * var lodash = _.noConflict(); + */ + function noConflict() { + if (root._ === this) { + root._ = oldDash; + } + return this; + } + + /** + * This method returns `undefined`. + * + * @static + * @memberOf _ + * @since 2.3.0 + * @category Util + * @example + * + * _.times(2, _.noop); + * // => [undefined, undefined] + */ + function noop() { + // No operation performed. + } + + /** + * Generates a unique ID. If `prefix` is given, the ID is appended to it. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Util + * @param {string} [prefix=''] The value to prefix the ID with. + * @returns {string} Returns the unique ID. + * @example + * + * _.uniqueId('contact_'); + * // => 'contact_104' + * + * _.uniqueId(); + * // => '105' + */ + function uniqueId(prefix) { + var id = ++idCounter; + return toString(prefix) + id; + } + + /*------------------------------------------------------------------------*/ + + /** + * Computes the maximum value of `array`. If `array` is empty or falsey, + * `undefined` is returned. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Math + * @param {Array} array The array to iterate over. + * @returns {*} Returns the maximum value. + * @example + * + * _.max([4, 2, 8, 6]); + * // => 8 + * + * _.max([]); + * // => undefined + */ + function max(array) { + return (array && array.length) + ? baseExtremum(array, identity, baseGt) + : undefined; + } + + /** + * Computes the minimum value of `array`. If `array` is empty or falsey, + * `undefined` is returned. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Math + * @param {Array} array The array to iterate over. + * @returns {*} Returns the minimum value. + * @example + * + * _.min([4, 2, 8, 6]); + * // => 2 + * + * _.min([]); + * // => undefined + */ + function min(array) { + return (array && array.length) + ? baseExtremum(array, identity, baseLt) + : undefined; + } + + /*------------------------------------------------------------------------*/ + + // Add methods that return wrapped values in chain sequences. + lodash.assignIn = assignIn; + lodash.before = before; + lodash.bind = bind; + lodash.chain = chain; + lodash.compact = compact; + lodash.concat = concat; + lodash.create = create; + lodash.defaults = defaults; + lodash.defer = defer; + lodash.delay = delay; + lodash.filter = filter; + lodash.flatten = flatten; + lodash.flattenDeep = flattenDeep; + lodash.iteratee = iteratee; + lodash.keys = keys; + lodash.map = map; + lodash.matches = matches; + lodash.mixin = mixin; + lodash.negate = negate; + lodash.once = once; + lodash.pick = pick; + lodash.slice = slice; + lodash.sortBy = sortBy; + lodash.tap = tap; + lodash.thru = thru; + lodash.toArray = toArray; + lodash.values = values; + + // Add aliases. + lodash.extend = assignIn; + + // Add methods to `lodash.prototype`. + mixin(lodash, lodash); + + /*------------------------------------------------------------------------*/ + + // Add methods that return unwrapped values in chain sequences. + lodash.clone = clone; + lodash.escape = escape; + lodash.every = every; + lodash.find = find; + lodash.forEach = forEach; + lodash.has = has; + lodash.head = head; + lodash.identity = identity; + lodash.indexOf = indexOf; + lodash.isArguments = isArguments; + lodash.isArray = isArray; + lodash.isBoolean = isBoolean; + lodash.isDate = isDate; + lodash.isEmpty = isEmpty; + lodash.isEqual = isEqual; + lodash.isFinite = isFinite; + lodash.isFunction = isFunction; + lodash.isNaN = isNaN; + lodash.isNull = isNull; + lodash.isNumber = isNumber; + lodash.isObject = isObject; + lodash.isRegExp = isRegExp; + lodash.isString = isString; + lodash.isUndefined = isUndefined; + lodash.last = last; + lodash.max = max; + lodash.min = min; + lodash.noConflict = noConflict; + lodash.noop = noop; + lodash.reduce = reduce; + lodash.result = result; + lodash.size = size; + lodash.some = some; + lodash.uniqueId = uniqueId; + + // Add aliases. + lodash.each = forEach; + lodash.first = head; + + mixin(lodash, (function() { + var source = {}; + baseForOwn(lodash, function(func, methodName) { + if (!hasOwnProperty.call(lodash.prototype, methodName)) { + source[methodName] = func; + } + }); + return source; + }()), { 'chain': false }); + + /*------------------------------------------------------------------------*/ + + /** + * The semantic version number. + * + * @static + * @memberOf _ + * @type {string} + */ + lodash.VERSION = VERSION; + + // Add `Array` methods to `lodash.prototype`. + baseEach(['pop', 'join', 'replace', 'reverse', 'split', 'push', 'shift', 'sort', 'splice', 'unshift'], function(methodName) { + var func = (/^(?:replace|split)$/.test(methodName) ? String.prototype : arrayProto)[methodName], + chainName = /^(?:push|sort|unshift)$/.test(methodName) ? 'tap' : 'thru', + retUnwrapped = /^(?:pop|join|replace|shift)$/.test(methodName); + + lodash.prototype[methodName] = function() { + var args = arguments; + if (retUnwrapped && !this.__chain__) { + var value = this.value(); + return func.apply(isArray(value) ? value : [], args); + } + return this[chainName](function(value) { + return func.apply(isArray(value) ? value : [], args); + }); + }; + }); + + // Add chain sequence methods to the `lodash` wrapper. + lodash.prototype.toJSON = lodash.prototype.valueOf = lodash.prototype.value = wrapperValue; + + /*--------------------------------------------------------------------------*/ + + // Some AMD build optimizers, like r.js, check for condition patterns like: + if (true) { + // Expose Lodash on the global object to prevent errors when Lodash is + // loaded by a script tag in the presence of an AMD loader. + // See http://requirejs.org/docs/errors.html#mismatch for more details. + // Use `_.noConflict` to remove Lodash from the global object. + root._ = lodash; + + // Define as an anonymous module so, through path mapping, it can be + // referenced as the "underscore" module. + !(__WEBPACK_AMD_DEFINE_RESULT__ = function() { + return lodash; + }.call(exports, __webpack_require__, exports, module), __WEBPACK_AMD_DEFINE_RESULT__ !== undefined && (module.exports = __WEBPACK_AMD_DEFINE_RESULT__)); + } + // Check for `exports` after `define` in case a build optimizer adds it. + else if (freeModule) { + // Export for Node.js. + (freeModule.exports = lodash)._ = lodash; + // Export for CommonJS support. + freeExports._ = lodash; + } + else { + // Export to the global object. + root._ = lodash; + } + }.call(this)); + + /* WEBPACK VAR INJECTION */}.call(exports, (function() { return this; }()), __webpack_require__(59)(module))) + +/***/ }), +/* 59 */ +/***/ (function(module, exports) { + + module.exports = function(module) { + if(!module.webpackPolyfill) { + module.deprecate = function() {}; + module.paths = []; + // module.parent = undefined by default + module.children = []; + module.webpackPolyfill = 1; + } + return module; + } + + +/***/ }), +/* 60 */ +/***/ (function(module, exports, __webpack_require__) { + + var ArrowLink = __webpack_require__(61); + var BoxArrowLink = __webpack_require__(22); + var PlainLink = __webpack_require__(23); + var OwlDisjointWith = __webpack_require__(46); + var SetOperatorProperty = __webpack_require__(56); + + /** + * Stores the passed properties in links. + * @returns {Function} + */ + module.exports = (function (){ + var linkCreator = {}; + + /** + * Creates links from the passed properties. + * @param properties + */ + linkCreator.createLinks = function ( properties ){ + var links = groupPropertiesToLinks(properties); + + for ( var i = 0, l = links.length; i < l; i++ ) { + var link = links[i]; + + countAndSetLayers(link, links); + countAndSetLoops(link, links); + } + + return links; + }; + + /** + * Creates links of properties and - if existing - their inverses. + * @param properties the properties + * @returns {Array} + */ + function groupPropertiesToLinks( properties ){ + var links = [], + property, + addedProperties = __webpack_require__(62)(); + + for ( var i = 0, l = properties.length; i < l; i++ ) { + property = properties[i]; + + if ( !addedProperties.has(property) ) { + var link = createLink(property); + + property.link(link); + if ( property.inverse() ) { + property.inverse().link(link); + } + + links.push(link); + + addedProperties.add(property); + if ( property.inverse() ) { + addedProperties.add(property.inverse()); + } + } + } + + return links; + } + + function countAndSetLayers( link, allLinks ){ + var layer, + layers, + i, l; + + if ( typeof link.layers() === "undefined" ) { + layers = []; + + // Search for other links that are another layer + for ( i = 0, l = allLinks.length; i < l; i++ ) { + var otherLink = allLinks[i]; + if ( link.domain() === otherLink.domain() && link.range() === otherLink.range() || + link.domain() === otherLink.range() && link.range() === otherLink.domain() ) { + layers.push(otherLink); + } + } + + // Set the results on each of the layers + for ( i = 0, l = layers.length; i < l; ++i ) { + layer = layers[i]; + + layer.layerIndex(i); + layer.layers(layers); + } + } + } + + function countAndSetLoops( link, allLinks ){ + var loop, + loops, + i, l; + + if ( typeof link.loops() === "undefined" ) { + loops = []; + + // Search for other links that are also loops of the same node + for ( i = 0, l = allLinks.length; i < l; i++ ) { + var otherLink = allLinks[i]; + if ( link.domain() === otherLink.domain() && link.domain() === otherLink.range() ) { + loops.push(otherLink); + } + } + + // Set the results on each of the loops + for ( i = 0, l = loops.length; i < l; ++i ) { + loop = loops[i]; + + loop.loopIndex(i); + loop.loops(loops); + } + } + } + + function createLink( property ){ + var domain = property.domain(); + var range = property.range(); + + if ( property instanceof OwlDisjointWith ) { + return new PlainLink(domain, range, property); + } else if ( property instanceof SetOperatorProperty ) { + return new BoxArrowLink(domain, range, property); + } + return new ArrowLink(domain, range, property); + } + + return function (){ + // Return a function to keep module interfaces consistent + return linkCreator; + }; + })(); + + +/***/ }), +/* 61 */ +/***/ (function(module, exports, __webpack_require__) { + + var PlainLink = __webpack_require__(23); + + + module.exports = ArrowLink; + + function ArrowLink( domain, range, property ){ + PlainLink.apply(this, arguments); + } + + ArrowLink.prototype = Object.create(PlainLink.prototype); + ArrowLink.prototype.constructor = ArrowLink; + + + ArrowLink.prototype.draw = function ( linkGroup, markerContainer ){ + var property = this.label().property(); + var inverse = this.label().inverse(); + + createPropertyMarker(markerContainer, property); + if ( inverse ) { + createInverseMarker(markerContainer, inverse); + } + + PlainLink.prototype.draw.apply(this, arguments); + + // attach the markers to the link + linkGroup.attr("marker-end", "url(#" + property.markerId() + ")"); + if ( inverse ) { + linkGroup.attr("marker-start", "url(#" + inverse.markerId() + ")"); + } + }; + + function createPropertyMarker( markerContainer, property ){ + var marker = appendBasicMarker(markerContainer, property); + //marker.attr("refX", 12); + var m1X = -12; + var m1Y = 8; + var m2X = -12; + var m2Y = -8; + marker.append("path") + //.attr("d", "M0,-8L12,0L0,8Z") + .attr("d", "M0,0L " + m1X + "," + m1Y + "L" + m2X + "," + m2Y + "L" + 0 + "," + 0) + .classed(property.markerType(), true); + + property.markerElement(marker); + } + + function createInverseMarker( markerContainer, inverse ){ + var m1X = -12; + var m1Y = 8; + var m2X = -12; + var m2Y = -8; + var inverseMarker = appendBasicMarker(markerContainer, inverse); + inverseMarker.append("path") + //.attr("d", "M12,-8L0,0L12,8Z") + .attr("d", "M0,0L " + -m1X + "," + -m1Y + "L" + -m2X + "," + -m2Y + "L" + 0 + "," + 0) + .classed(inverse.markerType(), true); + + inverse.markerElement(inverseMarker); + } + + function appendBasicMarker( markerContainer, property ){ + return markerContainer.append("marker") + .datum(property) + .attr("id", property.markerId()) + + .attr("viewBox", "-14 -10 28 20") + .attr("markerWidth", 10) + .attr("markerHeight", 10) + //.attr("markerUnits", "userSpaceOnUse") + .attr("orient", "auto"); + } + + +/***/ }), +/* 62 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {/** + * A simple incomplete encapsulation of the d3 set, which is able to store webvowl + * elements by using their id. + */ + module.exports = function ( array ){ + + var set = {}, + d3Set = d3.set(array); + + set.has = function ( webvowlElement ){ + return d3Set.has(webvowlElement.id()); + }; + + set.add = function ( webvowlElement ){ + return d3Set.add(webvowlElement.id()); + }; + + set.remove = function ( webvowlElement ){ + return d3Set.remove(webvowlElement.id()); + }; + + set.empty = function (){ + return d3Set.empty(); + }; + + set.size = function (){ + return d3Set.size(); + }; + + return set; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 63 */ +/***/ (function(module, exports, __webpack_require__) { + + var BaseProperty = __webpack_require__(42); + var BaseNode = __webpack_require__(9); + var DatatypeNode = __webpack_require__(35); + var Thing = __webpack_require__(31); + var ObjectProperty = __webpack_require__(50); + var DatatypeProperty = __webpack_require__(44); + var RdfsSubClassOf = __webpack_require__(55); + var Label = __webpack_require__(24); + + + var tools = {}; + module.exports = function (){ + return tools; + }; + + tools.isLabel = function ( element ){ + return element instanceof Label; + }; + + tools.isNode = function ( element ){ + return element instanceof BaseNode; + }; + + tools.isDatatype = function ( node ){ + return node instanceof DatatypeNode; + }; + + tools.isThing = function ( node ){ + return node instanceof Thing; + }; + + tools.isProperty = function ( element ){ + return element instanceof BaseProperty; + }; + + tools.isObjectProperty = function ( element ){ + return element instanceof ObjectProperty; + }; + + tools.isDatatypeProperty = function ( element ){ + return element instanceof DatatypeProperty; + }; + + tools.isRdfsSubClassOf = function ( property ){ + return property instanceof RdfsSubClassOf; + }; + + +/***/ }), +/* 64 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function (){ + var options = {}, + data, + graphContainerSelector, + classDistance = 200, + datatypeDistance = 120, + loopDistance = 150, + charge = -500, + gravity = 0.025, + linkStrength = 1, + height = 600, + width = 800, + selectionModules = [], + filterModules = [], + minMagnification = 0.01, + maxMagnification = 4, + compactNotation = false, + dynamicLabelWidth = true, + // some filters + literalFilter, + // menus + gravityMenu, + filterMenu, + loadingModule, + modeMenu, + pausedMenu, + pickAndPinModule, + resetMenu, + searchMenu, + ontologyMenu, + sidebar, + leftSidebar, + editSidebar, + navigationMenu, + exportMenu, + graphObject, + zoomSlider, + datatypeFilter, + focuserModule, + colorExternalsModule, + compactNotationModule, + objectPropertyFilter, + subclassFilter, + setOperatorFilter, + maxLabelWidth = 120, + metadataObject = {}, + generalOntologyMetaData = {}, + disjointPropertyFilter, + rectangularRep = false, + warningModule, + prefixModule, + drawPropertyDraggerOnHover = true, + showDraggerObject = false, + directInputModule, + scaleNodesByIndividuals = true, + useAccuracyHelper = true, + showRenderingStatistic = true, + showInputModality = false, + hideDebugOptions = true, + nodeDegreeFilter, + debugMenu, + + supportedDatatypes = ["rdfs:Literal", "xsd:boolean", "xsd:double", "xsd:integer", "xsd:string", "undefined"], + supportedClasses = ["owl:Thing", "owl:Class", "owl:DeprecatedClass"], + supportedProperties = ["owl:objectProperty", + "rdfs:subClassOf", + "owl:disjointWith", + "owl:allValuesFrom", + "owl:someValuesFrom" + ], + prefixList = { + rdf: 'http://www.w3.org/1999/02/22-rdf-syntax-ns#', + rdfs: 'http://www.w3.org/2000/01/rdf-schema#', + owl: 'http://www.w3.org/2002/07/owl#', + xsd: 'http://www.w3.org/2001/XMLSchema#', + dc: 'http://purl.org/dc/elements/1.1/#', + xml: 'http://www.w3.org/XML/1998/namespace' + }; + + options.clearMetaObject = function (){ + generalOntologyMetaData = {}; + }; + options.clearGeneralMetaObject = function (){ + generalOntologyMetaData = {}; + }; + + options.debugMenu = function ( val ){ + if ( !arguments.length ) return debugMenu; + debugMenu = val; + }; + + options.getHideDebugFeatures = function (){ + return hideDebugOptions; + }; + options.executeHiddenDebugFeatuers = function (){ + hideDebugOptions = !hideDebugOptions; + d3.selectAll(".debugOption").classed("hidden", hideDebugOptions); + if ( hideDebugOptions === false ) { + graphObject.setForceTickFunctionWithFPS(); + } + else { + graphObject.setDefaultForceTickFunction(); + } + if ( debugMenu ) { + debugMenu.updateSettings(); + } + options.setHideDebugFeaturesForDefaultObject(hideDebugOptions); + }; + + + options.addOrUpdateGeneralObjectEntry = function ( property, value ){ + if ( generalOntologyMetaData.hasOwnProperty(property) ) { + //console.log("Updating Property:"+ property); + if ( property === "iri" ) { + if ( validURL(value) === false ) { + warningModule.showWarning("Invalid Ontology IRI", "Input IRI does not represent an URL", "Restoring previous IRI for ontology", 1, false); + return false; + } + } + generalOntologyMetaData[property] = value; + } else { + generalOntologyMetaData[property] = value; + } + return true; + }; + + options.getGeneralMetaObjectProperty = function ( property ){ + if ( generalOntologyMetaData.hasOwnProperty(property) ) { + return generalOntologyMetaData[property]; + } + }; + + options.getGeneralMetaObject = function (){ + return generalOntologyMetaData; + }; + + options.addOrUpdateMetaObjectEntry = function ( property, value ){ + + if ( metadataObject.hasOwnProperty(property) ) { + metadataObject[property] = value; + } else { + metadataObject[property] = value; + } + }; + + options.getMetaObjectProperty = function ( property ){ + if ( metadataObject.hasOwnProperty(property) ) { + return metadataObject[property]; + } + }; + options.getMetaObject = function (){ + return metadataObject; + }; + + + options.prefixList = function (){ + return prefixList; + }; + options.addPrefix = function ( prefix, url ){ + prefixList[prefix] = url; + }; + + function validURL( str ){ + var urlregex = /^(https?|ftp):\/\/([a-zA-Z0-9.-]+(:[a-zA-Z0-9.&%$-]+)*@)*((25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9][0-9]?)(\.(25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9]?[0-9])){3}|([a-zA-Z0-9-]+\.)*[a-zA-Z0-9-]+\.(com|edu|gov|int|mil|net|org|biz|arpa|info|name|pro|aero|coop|museum|[a-zA-Z]{2}))(:[0-9]+)*(\/($|[a-zA-Z0-9.,?'\\+&%$#=~_-]+))*$/; + return urlregex.test(str); + } + + options.updatePrefix = function ( oldPrefix, newPrefix, oldURL, newURL ){ + if ( oldPrefix === newPrefix && oldURL === newURL ) { + // console.log("Nothing to update"); + return true; + } + if ( oldPrefix === newPrefix && oldURL !== newURL && validURL(newURL) === true ) { + // console.log("Update URL"); + prefixList[oldPrefix] = newURL; + } else if ( oldPrefix === newPrefix && oldURL !== newURL && validURL(newURL) === false ) { + if ( validURL(newURL) === false ) { + warningModule.showWarning("Invalid Prefix IRI", "Input IRI does not represent an IRI", "You should enter a valid IRI in form of a URL", 1, false); + return false; + } + + return false; + } + if ( oldPrefix !== newPrefix && validURL(newURL) === true ) { + + // sanity check + if ( prefixList.hasOwnProperty(newPrefix) ) { + // console.log("Already have this prefix!"); + warningModule.showWarning("Prefix Already Exist", "Prefix: " + newPrefix + " is already defined", "You should use an other one", 1, false); + return false; + } + options.removePrefix(oldPrefix); + options.addPrefix(newPrefix, newURL); + editSidebar.updateEditDeleteButtonIds(oldPrefix, newPrefix); + return true; + } + + // console.log("Is new URL ("+newURL+") valid? >> "+validURL(newURL)); + if ( validURL(newURL) === false ) { + warningModule.showWarning("Invalid Prefix IRI", "Input IRI does not represent an URL", "You should enter a valid URL", 1, false); + + } + return false; + }; + + options.removePrefix = function ( prefix ){ + delete prefixList[prefix]; + }; + + + options.supportedDatatypes = function (){ + return supportedDatatypes; + }; + options.supportedClasses = function (){ + return supportedClasses; + }; + options.supportedProperties = function (){ + return supportedProperties; + }; + + options.datatypeFilter = function ( val ){ + if ( !arguments.length ) return datatypeFilter; + datatypeFilter = val; + }; + + options.showDraggerObject = function ( val ){ + if ( !arguments.length ) { + return showDraggerObject; + } + showDraggerObject = val; + }; + options.useAccuracyHelper = function ( val ){ + if ( !arguments.length ) { + return useAccuracyHelper; + } + useAccuracyHelper = val; + }; + options.showAccuracyHelper = function ( val ){ + if ( !arguments.length ) { + return options.showDraggerObject(); + } + options.showDraggerObject(val); + }; + options.showRenderingStatistic = function ( val ){ + if ( !arguments.length ) { + return showRenderingStatistic; + } + showRenderingStatistic = val; + }; + options.showInputModality = function ( val ){ + if ( !arguments.length ) { + return showInputModality; + } + showInputModality = val; + }; + + options.drawPropertyDraggerOnHover = function ( val ){ + if ( !arguments.length ) return drawPropertyDraggerOnHover; + drawPropertyDraggerOnHover = val; + }; + + options.warningModule = function ( val ){ + if ( !arguments.length ) return warningModule; + warningModule = val; + }; + options.directInputModule = function ( val ){ + if ( !arguments.length ) return directInputModule; + directInputModule = val; + }; + options.prefixModule = function ( val ){ + if ( !arguments.length ) return prefixModule; + prefixModule = val; + }; + + options.focuserModule = function ( val ){ + if ( !arguments.length ) return focuserModule; + focuserModule = val; + }; + options.colorExternalsModule = function ( val ){ + if ( !arguments.length ) return colorExternalsModule; + colorExternalsModule = val; + }; + options.compactNotationModule = function ( val ){ + if ( !arguments.length ) return compactNotationModule; + compactNotationModule = val; + }; + + options.maxLabelWidth = function ( val ){ + if ( !arguments.length ) return maxLabelWidth; + maxLabelWidth = val; + }; + options.objectPropertyFilter = function ( val ){ + if ( !arguments.length ) return objectPropertyFilter; + objectPropertyFilter = val; + }; + options.disjointPropertyFilter = function ( val ){ + if ( !arguments.length ) return disjointPropertyFilter; + disjointPropertyFilter = val; + }; + options.subclassFilter = function ( val ){ + if ( !arguments.length ) return subclassFilter; + subclassFilter = val; + }; + options.setOperatorFilter = function ( val ){ + if ( !arguments.length ) return setOperatorFilter; + setOperatorFilter = val; + }; + options.leftSidebar = function ( val ){ + if ( !arguments.length ) return leftSidebar; + leftSidebar = val; + }; + options.editSidebar = function ( val ){ + if ( !arguments.length ) return editSidebar; + editSidebar = val; + }; + + options.zoomSlider = function ( val ){ + if ( !arguments.length ) return zoomSlider; + zoomSlider = val; + }; + + options.graphObject = function ( val ){ + if ( !arguments.length ) return graphObject; + graphObject = val; + }; + + + var defaultOptionsConfig = {}; + defaultOptionsConfig.sidebar = "1"; + defaultOptionsConfig.doc = -1; + defaultOptionsConfig.cd = 200; + defaultOptionsConfig.dd = 120; + defaultOptionsConfig.editorMode = "false"; + defaultOptionsConfig.filter_datatypes = "false"; + defaultOptionsConfig.filter_objectProperties = "false"; + defaultOptionsConfig.filter_sco = "false"; + defaultOptionsConfig.filter_disjoint = "true"; + defaultOptionsConfig.filter_setOperator = "false"; + defaultOptionsConfig.mode_dynamic = "true"; + defaultOptionsConfig.mode_scaling = "true"; + defaultOptionsConfig.mode_compact = "false"; + defaultOptionsConfig.mode_colorExt = "true"; + defaultOptionsConfig.mode_multiColor = "false"; + defaultOptionsConfig.debugFeatures = "false"; + defaultOptionsConfig.rect = 0; + + + options.initialConfig = function (){ + var initCfg = {}; + initCfg.sidebar = "1"; + initCfg.doc = -1; + initCfg.cd = 200; + initCfg.dd = 120; + initCfg.editorMode = "false"; + initCfg.filter_datatypes = "false"; + initCfg.filter_objectProperties = "false"; + initCfg.filter_sco = "false"; + initCfg.filter_disjoint = "true"; + initCfg.filter_setOperator = "false"; + initCfg.mode_dynamic = "true"; + initCfg.mode_scaling = "true"; + initCfg.mode_compact = "false"; + initCfg.mode_colorExt = "true"; + initCfg.mode_multiColor = "false"; + initCfg.mode_pnp = "false"; + initCfg.debugFeatures = "false"; + initCfg.rect = 0; + return initCfg; + }; + + options.setEditorModeForDefaultObject = function ( val ){ + defaultOptionsConfig.editorMode = String(val); + }; + options.setHideDebugFeaturesForDefaultObject = function ( val ){ + defaultOptionsConfig.debugFeatures = String(!val); + }; + + function updateConfigObject(){ + defaultOptionsConfig.sidebar = options.sidebar().getSidebarVisibility(); + defaultOptionsConfig.cd = options.classDistance(); + defaultOptionsConfig.dd = options.datatypeDistance(); + defaultOptionsConfig.filter_datatypes = String(options.filterMenu().getCheckBoxValue("datatypeFilterCheckbox")); + defaultOptionsConfig.filter_sco = String(options.filterMenu().getCheckBoxValue("subclassFilterCheckbox")); + defaultOptionsConfig.filter_disjoint = String(options.filterMenu().getCheckBoxValue("disjointFilterCheckbox")); + defaultOptionsConfig.filter_setOperator = String(options.filterMenu().getCheckBoxValue("setoperatorFilterCheckbox")); + defaultOptionsConfig.filter_objectProperties = String(options.filterMenu().getCheckBoxValue("objectPropertyFilterCheckbox")); + defaultOptionsConfig.mode_dynamic = String(options.dynamicLabelWidth()); + defaultOptionsConfig.mode_scaling = String(options.modeMenu().getCheckBoxValue("nodescalingModuleCheckbox")); + defaultOptionsConfig.mode_compact = String(options.modeMenu().getCheckBoxValue("compactnotationModuleCheckbox")); + defaultOptionsConfig.mode_colorExt = String(options.modeMenu().getCheckBoxValue("colorexternalsModuleCheckbox")); + defaultOptionsConfig.mode_multiColor = String(options.modeMenu().colorModeState()); + defaultOptionsConfig.mode_pnp = String(options.modeMenu().getCheckBoxValue("pickandpinModuleCheckbox")); + defaultOptionsConfig.rect = 0; + } + + options.defaultConfig = function (){ + updateConfigObject(); + return defaultOptionsConfig; + }; + + options.exportMenu = function ( val ){ + if ( !arguments.length ) return exportMenu; + exportMenu = val; + }; + + options.rectangularRepresentation = function ( val ){ + if ( !arguments.length ) { + return rectangularRep; + } else { + var intVal = parseInt(val); + if ( intVal === 0 ) { + rectangularRep = false; + } else { + rectangularRep = true; + } + } + }; + + options.dynamicLabelWidth = function ( val ){ + if ( !arguments.length ) + return dynamicLabelWidth; + else { + dynamicLabelWidth = val; + } + }; + options.sidebar = function ( s ){ + if ( !arguments.length ) return sidebar; + sidebar = s; + return options; + + }; + + options.navigationMenu = function ( m ){ + if ( !arguments.length ) return navigationMenu; + navigationMenu = m; + return options; + + }; + + options.ontologyMenu = function ( m ){ + if ( !arguments.length ) return ontologyMenu; + ontologyMenu = m; + return options; + }; + + options.searchMenu = function ( m ){ + if ( !arguments.length ) return searchMenu; + searchMenu = m; + return options; + }; + + options.resetMenu = function ( m ){ + if ( !arguments.length ) return resetMenu; + resetMenu = m; + return options; + }; + + options.pausedMenu = function ( m ){ + if ( !arguments.length ) return pausedMenu; + pausedMenu = m; + return options; + }; + + options.pickAndPinModule = function ( m ){ + if ( !arguments.length ) return pickAndPinModule; + pickAndPinModule = m; + return options; + }; + + options.gravityMenu = function ( m ){ + if ( !arguments.length ) return gravityMenu; + gravityMenu = m; + return options; + }; + + options.filterMenu = function ( m ){ + if ( !arguments.length ) return filterMenu; + filterMenu = m; + return options; + }; + + options.modeMenu = function ( m ){ + if ( !arguments.length ) return modeMenu; + modeMenu = m; + return options; + }; + + options.charge = function ( p ){ + if ( !arguments.length ) return charge; + charge = +p; + return options; + }; + + options.classDistance = function ( p ){ + if ( !arguments.length ) return classDistance; + classDistance = +p; + return options; + }; + + options.compactNotation = function ( p ){ + + if ( !arguments.length ) return compactNotation; + compactNotation = p; + return options; + }; + + options.data = function ( p ){ + if ( !arguments.length ) return data; + data = p; + return options; + }; + + options.datatypeDistance = function ( p ){ + if ( !arguments.length ) return datatypeDistance; + datatypeDistance = +p; + return options; + }; + + options.filterModules = function ( p ){ + if ( !arguments.length ) return filterModules; + filterModules = p; + return options; + }; + + options.graphContainerSelector = function ( p ){ + if ( !arguments.length ) return graphContainerSelector; + graphContainerSelector = p; + return options; + }; + + options.gravity = function ( p ){ + if ( !arguments.length ) return gravity; + gravity = +p; + return options; + }; + + options.height = function ( p ){ + if ( !arguments.length ) return height; + height = +p; + return options; + }; + + options.linkStrength = function ( p ){ + if ( !arguments.length ) return linkStrength; + linkStrength = +p; + return options; + }; + + options.loopDistance = function ( p ){ + if ( !arguments.length ) return loopDistance; + loopDistance = p; + return options; + }; + + options.minMagnification = function ( p ){ + if ( !arguments.length ) return minMagnification; + minMagnification = +p; + return options; + }; + + options.maxMagnification = function ( p ){ + if ( !arguments.length ) return maxMagnification; + maxMagnification = +p; + return options; + }; + + options.scaleNodesByIndividuals = function ( p ){ + if ( !arguments.length ) return scaleNodesByIndividuals; + scaleNodesByIndividuals = p; + return options; + }; + + options.selectionModules = function ( p ){ + if ( !arguments.length ) return selectionModules; + selectionModules = p; + return options; + }; + + options.width = function ( p ){ + if ( !arguments.length ) return width; + width = +p; + return options; + }; + + options.literalFilter = function ( p ){ + if ( !arguments.length ) return literalFilter; + literalFilter = p; + return options; + }; + options.nodeDegreeFilter = function ( p ){ + if ( !arguments.length ) return nodeDegreeFilter; + nodeDegreeFilter = p; + return options; + }; + + options.loadingModule = function ( p ){ + if ( !arguments.length ) return loadingModule; + loadingModule = p; + return options; + }; + + // define url loadable options; + // update all set values in the default object + options.setOptionsFromURL = function ( opts, changeEditFlag ){ + if ( opts.sidebar !== undefined ) sidebar.showSidebar(parseInt(opts.sidebar), true); + if ( opts.doc ) { + var asInt = parseInt(opts.doc); + filterMenu.setDegreeSliderValue(asInt); + graphObject.setGlobalDOF(asInt); + // reset the value to be -1; + defaultOptionsConfig.doc = -1; + } + var settingFlag = false; + if ( opts.editorMode ) { + if ( opts.editorMode === "true" ) settingFlag = true; + d3.select("#editorModeModuleCheckbox").node().checked = settingFlag; + + if ( changeEditFlag && changeEditFlag === true ) { + graphObject.editorMode(settingFlag); + } + + // update config object + defaultOptionsConfig.editorMode = opts.editorMode; + + } + if ( opts.cd ) { // class distance + options.classDistance(opts.cd); // class distance + defaultOptionsConfig.cd = opts.cd; + } + if ( opts.dd ) { // data distance + options.datatypeDistance(opts.dd); + defaultOptionsConfig.cd = opts.cd; + } + if ( opts.cd || opts.dd ) options.gravityMenu().reset(); // reset the values so the slider is updated; + + + settingFlag = false; + if ( opts.filter_datatypes ) { + if ( opts.filter_datatypes === "true" ) settingFlag = true; + filterMenu.setCheckBoxValue("datatypeFilterCheckbox", settingFlag); + defaultOptionsConfig.filter_datatypes = opts.filter_datatypes; + } + if ( opts.debugFeatures ) { + if ( opts.debugFeatures === "true" ) settingFlag = true; + hideDebugOptions = settingFlag; + if ( options.getHideDebugFeatures() === false ) { + options.executeHiddenDebugFeatuers(); + } + defaultOptionsConfig.debugFeatures = opts.debugFeatures; + } + + settingFlag = false; + if ( opts.filter_objectProperties ) { + if ( opts.filter_objectProperties === "true" ) settingFlag = true; + filterMenu.setCheckBoxValue("objectPropertyFilterCheckbox", settingFlag); + defaultOptionsConfig.filter_objectProperties = opts.filter_objectProperties; + } + settingFlag = false; + if ( opts.filter_sco ) { + if ( opts.filter_sco === "true" ) settingFlag = true; + filterMenu.setCheckBoxValue("subclassFilterCheckbox", settingFlag); + defaultOptionsConfig.filter_sco = opts.filter_sco; + } + settingFlag = false; + if ( opts.filter_disjoint ) { + if ( opts.filter_disjoint === "true" ) settingFlag = true; + filterMenu.setCheckBoxValue("disjointFilterCheckbox", settingFlag); + defaultOptionsConfig.filter_disjoint = opts.filter_disjoint; + } + settingFlag = false; + if ( opts.filter_setOperator ) { + if ( opts.filter_setOperator === "true" ) settingFlag = true; + filterMenu.setCheckBoxValue("setoperatorFilterCheckbox", settingFlag); + defaultOptionsConfig.filter_setOperator = opts.filter_setOperator; + } + filterMenu.updateSettings(); + + // modesMenu + settingFlag = false; + if ( opts.mode_dynamic ) { + if ( opts.mode_dynamic === "true" ) settingFlag = true; + modeMenu.setDynamicLabelWidth(settingFlag); + dynamicLabelWidth = settingFlag; + defaultOptionsConfig.mode_dynamic = opts.mode_dynamic; + } + // settingFlag=false; + // THIS SHOULD NOT BE SET USING THE OPTIONS ON THE URL + // if (opts.mode_picnpin) { + // graph.options().filterMenu().setCheckBoxValue("pickandpin ModuleCheckbox", settingFlag); + // } + + settingFlag = false; + if ( opts.mode_pnp ) { + if ( opts.mode_pnp === "true" ) settingFlag = true; + modeMenu.setCheckBoxValue("pickandpinModuleCheckbox", settingFlag); + defaultOptionsConfig.mode_pnp = opts.mode_pnp; + } + + settingFlag = false; + if ( opts.mode_scaling ) { + if ( opts.mode_scaling === "true" ) settingFlag = true; + modeMenu.setCheckBoxValue("nodescalingModuleCheckbox", settingFlag); + defaultOptionsConfig.mode_scaling = opts.mode_scaling; + } + + settingFlag = false; + if ( opts.mode_compact ) { + if ( opts.mode_compact === "true" ) settingFlag = true; + modeMenu.setCheckBoxValue("compactnotationModuleCheckbox", settingFlag); + defaultOptionsConfig.mode_compact = opts.mode_compact; + } + + settingFlag = false; + if ( opts.mode_colorExt ) { + if ( opts.mode_colorExt === "true" ) settingFlag = true; + modeMenu.setCheckBoxValue("colorexternalsModuleCheckbox", settingFlag); + defaultOptionsConfig.mode_colorExt = opts.mode_colorExt; + } + + settingFlag = false; + if ( opts.mode_multiColor ) { + if ( opts.mode_multiColor === "true" ) settingFlag = true; + modeMenu.setColorSwitchStateUsingURL(settingFlag); + defaultOptionsConfig.mode_multiColor = opts.mode_multiColor; + } + modeMenu.updateSettingsUsingURL(); + options.rectangularRepresentation(opts.rect); + }; + + return options; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 65 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var OwlDisjointWith = __webpack_require__(46); + var attributeParser = __webpack_require__(66)(); + var equivalentPropertyMerger = __webpack_require__(67)(); + var nodePrototypeMap = __webpack_require__(5)(); + var propertyPrototypeMap = __webpack_require__(40)(); + + /** + * Encapsulates the parsing and preparation logic of the input data. + * @param graph the graph object that will be passed to the elements + * @returns {{}} + */ + module.exports = function ( graph ){ + var parser = {}, + nodes, + properties, + classMap, + settingsData, + settingsImported = false, + settingsImportGraphZoomAndTranslation = false, + dictionary = [], + propertyMap; + + parser.getDictionary = function (){ + return dictionary; + }; + + parser.setDictionary = function ( d ){ + dictionary = d; + }; + + parser.settingsImported = function (){ + return settingsImported; + }; + parser.settingsImportGraphZoomAndTranslation = function (){ + return settingsImportGraphZoomAndTranslation; + }; + + parser.parseSettings = function (){ + settingsImported = true; + settingsImportGraphZoomAndTranslation = false; + + if ( !settingsData ) { + settingsImported = false; + return; + } + /** global settings **********************************************************/ + if ( settingsData.global ) { + if ( settingsData.global.zoom ) { + var zoomFactor = settingsData.global.zoom; + graph.setZoom(zoomFactor); + settingsImportGraphZoomAndTranslation = true; + } + + if ( settingsData.global.translation ) { + var translation = settingsData.global.translation; + graph.setTranslation(translation); + settingsImportGraphZoomAndTranslation = true; + } + + if ( settingsData.global.paused ) { + var paused = settingsData.global.paused; + graph.options().pausedMenu().setPauseValue(paused); + } + } + /** Gravity Settings **********************************************************/ + if ( settingsData.gravity ) { + if ( settingsData.gravity.classDistance ) { + var classDistance = settingsData.gravity.classDistance; + graph.options().classDistance(classDistance); + } + if ( settingsData.gravity.datatypeDistance ) { + var datatypeDistance = settingsData.gravity.datatypeDistance; + graph.options().datatypeDistance(datatypeDistance); + } + graph.options().gravityMenu().reset(); // reads the options values and sets the gui values + } + + + // shared variable declaration + + var i; + var id; + var checked; + /** Filter Settings **********************************************************/ + if ( settingsData.filter ) { + // checkbox settings + if ( settingsData.filter.checkBox ) { + var filter_cb = settingsData.filter.checkBox; + for ( i = 0; i < filter_cb.length; i++ ) { + id = filter_cb[i].id; + checked = filter_cb[i].checked; + graph.options().filterMenu().setCheckBoxValue(id, checked); + } + } + // node degree filter settings + if ( settingsData.filter.degreeSliderValue ) { + var degreeSliderValue = settingsData.filter.degreeSliderValue; + graph.options().filterMenu().setDegreeSliderValue(degreeSliderValue); + } + graph.options().filterMenu().updateSettings(); + } + + /** Modes Setting **********************************************************/ + if ( settingsData.modes ) { + // checkbox settings + if ( settingsData.modes.checkBox ) { + var modes_cb = settingsData.modes.checkBox; + for ( i = 0; i < modes_cb.length; i++ ) { + id = modes_cb[i].id; + checked = modes_cb[i].checked; + graph.options().modeMenu().setCheckBoxValue(id, checked); + } + } + // color switch settings + var state = settingsData.modes.colorSwitchState; + // state could be undefined + if ( state === true || state === false ) { + graph.options().modeMenu().setColorSwitchState(state); + } + graph.options().modeMenu().updateSettings(); + } + graph.updateStyle(); // updates graph representation(setting charges and distances) + }; + + + /** + * Parses the ontology data and preprocesses it (e.g. connecting inverse properties and so on). + * @param ontologyData the loaded ontology json file + */ + parser.parse = function ( ontologyData ){ + if ( !ontologyData ) { + nodes = []; + properties = []; + dictionary = []; + return; + } + dictionary = []; + if ( ontologyData.settings ) settingsData = ontologyData.settings; + else settingsData = undefined; + + var classes = combineClasses(ontologyData.class, ontologyData.classAttribute), + datatypes = combineClasses(ontologyData.datatype, ontologyData.datatypeAttribute), + combinedClassesAndDatatypes = classes.concat(datatypes), + unparsedProperties = ontologyData.property || [], + combinedProperties; + + // Inject properties for unions, intersections, ... + addSetOperatorProperties(combinedClassesAndDatatypes, unparsedProperties); + combinedProperties = combineProperties(unparsedProperties, ontologyData.propertyAttribute); + classMap = mapElements(combinedClassesAndDatatypes); + propertyMap = mapElements(combinedProperties); + mergeRangesOfEquivalentProperties(combinedProperties, combinedClassesAndDatatypes); + + // Process the graph data + convertTypesToIris(combinedClassesAndDatatypes, ontologyData.namespace); + convertTypesToIris(combinedProperties, ontologyData.namespace); + nodes = createNodeStructure(combinedClassesAndDatatypes, classMap); + properties = createPropertyStructure(combinedProperties, classMap, propertyMap); + }; + + /** + * @return {Array} the preprocessed nodes + */ + parser.nodes = function (){ + return nodes; + }; + + /** + * @returns {Array} the preprocessed properties + */ + parser.properties = function (){ + return properties; + }; + + /** + * Combines the passed objects with its attributes and prototypes. This also applies + * attributes defined in the base of the prototype. + */ + function combineClasses( baseObjects, attributes ){ + var combinations = []; + var prototypeMap = createLowerCasePrototypeMap(nodePrototypeMap); + + if ( baseObjects ) { + baseObjects.forEach(function ( element ){ + var matchingAttribute; + + if ( attributes ) { + // Look for an attribute with the same id and merge them + for ( var i = 0; i < attributes.length; i++ ) { + var attribute = attributes[i]; + if ( element.id === attribute.id ) { + matchingAttribute = attribute; + break; + } + } + addAdditionalAttributes(element, matchingAttribute); + } + + // Then look for a prototype to add its properties + var Prototype = prototypeMap.get(element.type.toLowerCase()); + + if ( Prototype ) { + addAdditionalAttributes(element, Prototype); // TODO might be unnecessary + + var node = new Prototype(graph); + node.annotations(element.annotations) + .baseIri(element.baseIri) + .comment(element.comment) + .complement(element.complement) + .disjointUnion(element.disjointUnion) + .description(element.description) + .equivalents(element.equivalent) + .id(element.id) + .intersection(element.intersection) + .label(element.label) + // .type(element.type) Ignore, because we predefined it + .union(element.union) + .iri(element.iri); + if ( element.pos ) { + node.x = element.pos[0]; + node.y = element.pos[1]; + node.px = node.x; + node.py = node.y; + } + //class element pin + var elementPinned = element.pinned; + if ( elementPinned === true ) { + node.pinned(true); + graph.options().pickAndPinModule().addPinnedElement(node); + } + // Create node objects for all individuals + if ( element.individuals ) { + element.individuals.forEach(function ( individual ){ + var individualNode = new Prototype(graph); + individualNode.label(individual.labels) + .iri(individual.iri); + + node.individuals().push(individualNode); + }); + } + + if ( element.attributes ) { + var deduplicatedAttributes = d3.set(element.attributes.concat(node.attributes())); + node.attributes(deduplicatedAttributes.values()); + } + combinations.push(node); + } else { + console.error("Unknown element type: " + element.type); + } + }); + } + + return combinations; + } + + function combineProperties( baseObjects, attributes ){ + var combinations = []; + var prototypeMap = createLowerCasePrototypeMap(propertyPrototypeMap); + + if ( baseObjects ) { + baseObjects.forEach(function ( element ){ + var matchingAttribute; + + if ( attributes ) { + // Look for an attribute with the same id and merge them + for ( var i = 0; i < attributes.length; i++ ) { + var attribute = attributes[i]; + if ( element.id === attribute.id ) { + matchingAttribute = attribute; + break; + } + } + addAdditionalAttributes(element, matchingAttribute); + } + + // Then look for a prototype to add its properties + var Prototype = prototypeMap.get(element.type.toLowerCase()); + + if ( Prototype ) { + // Create the matching object and set the properties + var property = new Prototype(graph); + property.annotations(element.annotations) + .baseIri(element.baseIri) + .cardinality(element.cardinality) + .comment(element.comment) + .domain(element.domain) + .description(element.description) + .equivalents(element.equivalent) + .id(element.id) + .inverse(element.inverse) + .label(element.label) + .minCardinality(element.minCardinality) + .maxCardinality(element.maxCardinality) + .range(element.range) + .subproperties(element.subproperty) + .superproperties(element.superproperty) + // .type(element.type) Ignore, because we predefined it + .iri(element.iri); + + // adding property position + if ( element.pos ) { + property.x = element.pos[0]; + property.y = element.pos[1]; + property.px = element.pos[0]; + property.py = element.pos[1]; + } + var elementPinned = element.pinned; + if ( elementPinned === true ) { + property.pinned(true); + graph.options().pickAndPinModule().addPinnedElement(property); + } + + + if ( element.attributes ) { + var deduplicatedAttributes = d3.set(element.attributes.concat(property.attributes())); + property.attributes(deduplicatedAttributes.values()); + } + combinations.push(property); + } else { + console.error("Unknown element type: " + element.type); + } + + }); + } + + return combinations; + } + + function createLowerCasePrototypeMap( prototypeMap ){ + return d3.map(prototypeMap.values(), function ( Prototype ){ + return new Prototype().type().toLowerCase(); + }); + } + + function mergeRangesOfEquivalentProperties( properties, nodes ){ + // pass clones of arrays into the merger to keep the current functionality of this module + var newNodes = equivalentPropertyMerger.merge(properties.slice(), nodes.slice(), propertyMap, classMap, graph); + + // replace all the existing nodes and map the nodes again + nodes.length = 0; + Array.prototype.push.apply(nodes, newNodes); + classMap = mapElements(nodes); + } + + /** + * Checks all attributes which have to be rewritten. + * For example: + * equivalent is filled with only ID's of the corresponding nodes. It would be better to used the + * object instead of the ID so we swap the ID's with the correct object reference and can delete it from drawing + * because it is not necessary. + */ + function createNodeStructure( rawNodes, classMap ){ + var nodes = []; + + // Set the default values + var maxIndividualCount = 0; + rawNodes.forEach(function ( node ){ + maxIndividualCount = Math.max(maxIndividualCount, node.individuals().length); + node.visible(true); + }); + + rawNodes.forEach(function ( node ){ + // Merge and connect the equivalent nodes + processEquivalentIds(node, classMap); + + attributeParser.parseClassAttributes(node); + + node.maxIndividualCount(maxIndividualCount); + }); + + // Collect all nodes that should be displayed + rawNodes.forEach(function ( node ){ + if ( node.visible() ) { + nodes.push(node); + } + }); + + return nodes; + } + + /** + * Sets the disjoint attribute of the nodes if a disjoint label is found. + * @param property + */ + function processDisjoints( property ){ + if ( property instanceof OwlDisjointWith === false ) { + return; + } + + var domain = property.domain(), + range = property.range(); + + // Check the domain. + if ( !domain.disjointWith() ) { + domain.disjointWith([]); + } + + // Check the range. + if ( !range.disjointWith() ) { + range.disjointWith([]); + } + + domain.disjointWith().push(property.range()); + range.disjointWith().push(property.domain()); + } + + /** + * Connect all properties and also their sub- and superproperties. + * We iterate over the rawProperties array because it is way faster than iterating + * over an object and its attributes. + * + * @param rawProperties the properties + * @param classMap a map of all classes + * @param propertyMap the properties in a map + */ + function createPropertyStructure( rawProperties, classMap, propertyMap ){ + var properties = []; + // Set default values + rawProperties.forEach(function ( property ){ + property.visible(true); + }); + + // Connect properties + rawProperties.forEach(function ( property ){ + var domain, + range, + domainObject, + rangeObject, + inverse; + + /* Skip properties that have no information about their domain and range, like + inverse properties with optional inverse and optional domain and range attributes */ + if ( (property.domain() && property.range()) || property.inverse() ) { + + var inversePropertyId = findId(property.inverse()); + // Look if an inverse property exists + if ( inversePropertyId ) { + inverse = propertyMap[inversePropertyId]; + if ( !inverse ) { + console.warn("No inverse property was found for id: " + inversePropertyId); + property.inverse(undefined); + } + } + + // Either domain and range are set on this property or at the inverse + if ( typeof property.domain() !== "undefined" && typeof property.range() !== "undefined" ) { + domain = findId(property.domain()); + range = findId(property.range()); + + domainObject = classMap[domain]; + rangeObject = classMap[range]; + } else if ( inverse ) { + // Domain and range need to be switched + domain = findId(inverse.range()); + range = findId(inverse.domain()); + + domainObject = classMap[domain]; + rangeObject = classMap[range]; + } else { + console.warn("Domain and range not found for property: " + property.id()); + } + + // Set the references on this property + property.domain(domainObject); + property.range(rangeObject); + + // Also set the attributes of the inverse property + if ( inverse ) { + property.inverse(inverse); + inverse.inverse(property); + + // Switch domain and range + inverse.domain(rangeObject); + inverse.range(domainObject); + } + } + // Reference sub- and superproperties + referenceSubOrSuperProperties(property.subproperties()); + referenceSubOrSuperProperties(property.superproperties()); + }); + + // Merge equivalent properties and process disjoints. + rawProperties.forEach(function ( property ){ + processEquivalentIds(property, propertyMap); + processDisjoints(property); + + attributeParser.parsePropertyAttributes(property); + }); + // Add additional information to the properties + rawProperties.forEach(function ( property ){ + // Properties of merged classes should point to/from the visible equivalent class + var propertyWasRerouted = false; + + if ( property.domain() === undefined ) { + console.warn("No Domain was found for id:" + property.id()); + return; + } + + if ( wasNodeMerged(property.domain()) ) { + property.domain(property.domain().equivalentBase()); + propertyWasRerouted = true; + } + if ( property.range() === undefined ) { + console.warn("No range was found for id:" + property.id()); + return; + } + if ( wasNodeMerged(property.range()) ) { + property.range(property.range().equivalentBase()); + propertyWasRerouted = true; + } + // But there should not be two equal properties between the same domain and range + var equalProperty = getOtherEqualProperty(rawProperties, property); + + if ( propertyWasRerouted && equalProperty ) { + property.visible(false); + + equalProperty.redundantProperties().push(property); + } + + // Hide property if source or target node is hidden + if ( !property.domain().visible() || !property.range().visible() ) { + property.visible(false); + } + + // Collect all properties that should be displayed + if ( property.visible() ) { + properties.push(property); + } + }); + return properties; + } + + function referenceSubOrSuperProperties( subOrSuperPropertiesArray ){ + var i, l; + + if ( !subOrSuperPropertiesArray ) { + return; + } + + for ( i = 0, l = subOrSuperPropertiesArray.length; i < l; ++i ) { + var subOrSuperPropertyId = findId(subOrSuperPropertiesArray[i]); + var subOrSuperProperty = propertyMap[subOrSuperPropertyId]; + + if ( subOrSuperProperty ) { + // Replace id with object + subOrSuperPropertiesArray[i] = subOrSuperProperty; + } else { + console.warn("No sub-/superproperty was found for id: " + subOrSuperPropertyId); + } + } + } + + function wasNodeMerged( node ){ + return !node.visible() && node.equivalentBase(); + } + + function getOtherEqualProperty( properties, referenceProperty ){ + var i, l, property; + + for ( i = 0, l = properties.length; i < l; i++ ) { + property = properties[i]; + + if ( referenceProperty === property ) { + continue; + } + if ( referenceProperty.domain() !== property.domain() || + referenceProperty.range() !== property.range() ) { + continue; + } + + // Check for an equal IRI, if non existent compare label and type + if ( referenceProperty.iri() && property.iri() ) { + if ( referenceProperty.iri() === property.iri() ) { + return property; + } + } else if ( referenceProperty.type() === property.type() && + referenceProperty.defaultLabel() === property.defaultLabel() ) { + return property; + } + } + + return undefined; + } + + /** + * Generates and adds properties for links to set operators. + * @param classes unprocessed classes + * @param properties unprocessed properties + */ + function addSetOperatorProperties( classes, properties ){ + function addProperties( domainId, rangeIds, operatorType ){ + if ( !rangeIds ) { + return; + } + + rangeIds.forEach(function ( rangeId, index ){ + var property = { + id: "GENERATED-" + operatorType + "-" + domainId + "-" + rangeId + "-" + index, + type: "setOperatorProperty", + domain: domainId, + range: rangeId + }; + + properties.push(property); + }); + } + + classes.forEach(function ( clss ){ + addProperties(clss.id(), clss.complement(), "COMPLEMENT"); + addProperties(clss.id(), clss.intersection(), "INTERSECTION"); + addProperties(clss.id(), clss.union(), "UNION"); + addProperties(clss.id(), clss.disjointUnion(), "DISJOINTUNION"); + }); + } + + /** + * Replaces the ids of equivalent nodes/properties with the matching objects, cross references them + * and tags them as processed. + * @param element a node or a property + * @param elementMap a map where nodes/properties can be looked up + */ + function processEquivalentIds( element, elementMap ){ + var eqIds = element.equivalents(); + + if ( !eqIds || element.equivalentBase() ) { + return; + } + + // Replace ids with the corresponding objects + for ( var i = 0, l = eqIds.length; i < l; ++i ) { + var eqId = findId(eqIds[i]); + var eqObject = elementMap[eqId]; + + if ( eqObject ) { + // Cross reference both objects + eqObject.equivalents(eqObject.equivalents()); + eqObject.equivalents().push(element); + eqObject.equivalentBase(element); + eqIds[i] = eqObject; + + // Hide other equivalent nodes + eqObject.visible(false); + } else { + console.warn("No class/property was found for equivalent id: " + eqId); + } + } + } + + /** + * Tries to convert the type to an iri and sets it. + * @param elements classes or properties + * @param namespaces an array of namespaces + */ + function convertTypesToIris( elements, namespaces ){ + elements.forEach(function ( element ){ + if ( typeof element.iri() === "string" ) { + element.iri(replaceNamespace(element.iri(), namespaces)); + } + }); + } + + /** + * Creates a map by mapping the array with the passed function. + * @param array the array + * @returns {{}} + */ + function mapElements( array ){ + var map = {}; + for ( var i = 0, length = array.length; i < length; i++ ) { + var element = array[i]; + map[element.id()] = element; + } + return map; + } + + /** + * Adds the attributes of the additional object to the base object, but doesn't + * overwrite existing ones. + * + * @param base the base object + * @param addition the object with additional data + * @returns the combination is also returned + */ + function addAdditionalAttributes( base, addition ){ + // Check for an undefined value + addition = addition || {}; + + for ( var addAttribute in addition ) { + // Add the attribute if it doesn't exist + if ( !(addAttribute in base) && addition.hasOwnProperty(addAttribute) ) { + base[addAttribute] = addition[addAttribute]; + } + } + return base; + } + + /** + * Replaces the namespace (and the separator) if one exists and returns the new value. + * @param address the address with a namespace in it + * @param namespaces an array of namespaces + * @returns {string} the processed address with the (possibly) replaced namespace + */ + function replaceNamespace( address, namespaces ){ + var separatorIndex = address.indexOf(":"); + if ( separatorIndex === -1 ) { + return address; + } + var namespaceName = address.substring(0, separatorIndex); + + for ( var i = 0, length = namespaces.length; i < length; ++i ) { + var namespace = namespaces[i]; + if ( namespaceName === namespace.name ) { + return namespace.iri + address.substring(separatorIndex + 1); + } + } + + return address; + } + + /** + * Looks whether the passed object is already the id or if it was replaced + * with the object that belongs to the id. + * @param object an id, a class or a property + * @returns {string} the id of the passed object or undefined + */ + function findId( object ){ + if ( !object ) { + return undefined; + } else if ( typeof object === "string" ) { + return object; + } else if ( "id" in object ) { + return object.id(); + } else { + console.warn("No Id was found for this object: " + object); + return undefined; + } + } + + return parser; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 66 */ +/***/ (function(module, exports) { + + /** + * Parses the attributes an element has and sets the corresponding attributes. + * @returns {Function} + */ + module.exports = (function (){ + var attributeParser = {}, + // Style + ANONYMOUS = "anonymous", + DATATYPE = "datatype", + DEPRECATED = "deprecated", + EXTERNAL = "external", + OBJECT = "object", + RDF = "rdf", + // Representations + ASYMMETRIC = "asymmetric", + FUNCTIONAL = "functional", + INVERSE_FUNCTIONAL = "inverse functional", + IRREFLEXIVE = "irreflexive", + KEY = "key", + REFLEXIVE = "reflexive", + SYMMETRIC = "symmetric", + TRANSITIVE = "transitive", + // Attribute groups + VISUAL_ATTRIBUTE_GROUPS = [ + [DEPRECATED, DATATYPE, OBJECT, RDF], + [ANONYMOUS] + ], + CLASS_INDICATIONS = [DEPRECATED, EXTERNAL], + PROPERTY_INDICATIONS = [ASYMMETRIC, FUNCTIONAL, INVERSE_FUNCTIONAL, IRREFLEXIVE, KEY, REFLEXIVE, SYMMETRIC, + TRANSITIVE]; + + /** + * Parses and sets the attributes of a class. + * @param clazz + */ + attributeParser.parseClassAttributes = function ( clazz ){ + if ( !(clazz.attributes() instanceof Array) ) { + return; + } + + parseVisualAttributes(clazz); + parseClassIndications(clazz); + }; + + function parseVisualAttributes( element ){ + VISUAL_ATTRIBUTE_GROUPS.forEach(function ( attributeGroup ){ + setVisualAttributeOfGroup(element, attributeGroup); + }); + } + + function setVisualAttributeOfGroup( element, group ){ + var i, l, attribute; + + for ( i = 0, l = group.length; i < l; i++ ) { + attribute = group[i]; + if ( element.attributes().indexOf(attribute) >= 0 ) { + element.visualAttributes().push(attribute); + + // Just a single attribute is possible + break; + } + } + } + + function parseClassIndications( clazz ){ + var i, l, indication; + + for ( i = 0, l = CLASS_INDICATIONS.length; i < l; i++ ) { + indication = CLASS_INDICATIONS[i]; + + if ( clazz.attributes().indexOf(indication) >= 0 ) { + clazz.indications().push(indication); + } + } + } + + /** + * Parses and sets the attributes of a property. + * @param property + */ + attributeParser.parsePropertyAttributes = function ( property ){ + if ( !(property.attributes() instanceof Array) ) { + return; + } + + parseVisualAttributes(property); + parsePropertyIndications(property); + }; + + function parsePropertyIndications( property ){ + var i, l, indication; + + for ( i = 0, l = PROPERTY_INDICATIONS.length; i < l; i++ ) { + indication = PROPERTY_INDICATIONS[i]; + + if ( property.attributes().indexOf(indication) >= 0 ) { + property.indications().push(indication); + } + } + } + + + return function (){ + // Return a function to keep module interfaces consistent + return attributeParser; + }; + })(); + + +/***/ }), +/* 67 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var OwlThing = __webpack_require__(31); + var RdfsLiteral = __webpack_require__(38); + var elementTools = __webpack_require__(63)(); + + var equivalentPropertyMerger = {}; + module.exports = function (){ + return equivalentPropertyMerger; + }; + + var PREFIX = "GENERATED-MERGED_RANGE-"; + var OBJECT_PROPERTY_DEFAULT_RANGE_TYPE = "owl:Thing"; + var DATA_PROPERTY_DEFAULT_RANGE_TYPE = "rdfs:Literal"; + + + equivalentPropertyMerger.merge = function ( properties, nodes, propertyMap, nodeMap, graph ){ + var totalNodeIdsToHide = d3.set(); + var processedPropertyIds = d3.set(); + var mergeNodes = []; + + for ( var i = 0; i < properties.length; i++ ) { + var property = properties[i]; + var equivalents = property.equivalents().map(createIdToPropertyMapper(propertyMap)); + + if ( equivalents.length === 0 || processedPropertyIds.has(property.id()) ) { + continue; + } + + var propertyWithEquivalents = equivalents.concat(property); + + var mergeNode = findMergeNode(propertyWithEquivalents, nodeMap); + if ( !mergeNode ) { + if ( mergeNode !== undefined ) { + mergeNode = createDefaultMergeNode(property, graph); + mergeNodes.push(mergeNode); + } + } + + var nodeIdsToHide = replaceRangesAndCollectNodesToHide(propertyWithEquivalents, mergeNode, properties, + processedPropertyIds); + for ( var j = 0; j < nodeIdsToHide.length; j++ ) { + totalNodeIdsToHide.add(nodeIdsToHide[j]); + } + } + + return filterVisibleNodes(nodes.concat(mergeNodes), totalNodeIdsToHide); + }; + + + function createIdToPropertyMapper( propertyMap ){ + return function ( id ){ + return propertyMap[id]; + }; + } + + function findMergeNode( propertyWithEquivalents, nodeMap ){ + var typeMap = mapPropertiesRangesToType(propertyWithEquivalents, nodeMap); + var typeSet = d3.set(typeMap.keys()); + + // default types are the fallback values and should be ignored for the type determination + typeSet.remove(OBJECT_PROPERTY_DEFAULT_RANGE_TYPE); + typeSet.remove(DATA_PROPERTY_DEFAULT_RANGE_TYPE); + + // exactly one type to chose from -> take the node of this type as range + if ( typeSet.size() === 1 ) { + var type = typeSet.values()[0]; + var ranges = typeMap.get(type); + + if ( ranges.length === 1 ) { + return ranges[0]; + } + } + } + + function mapPropertiesRangesToType( properties, nodeMap ){ + var typeMap = d3.map(); + + properties.forEach(function ( property ){ + if ( property === undefined ) //@ WORKAROUND + return; + + var range = nodeMap[property.range()]; + var type = range.type(); + + if ( !typeMap.has(type) ) { + typeMap.set(type, []); + } + + typeMap.get(type).push(range); + }); + + return typeMap; + } + + function createDefaultMergeNode( property, graph ){ + var range; + + if ( elementTools.isDatatypeProperty(property) ) { + range = new RdfsLiteral(graph); + } else { + range = new OwlThing(graph); + } + range.id(PREFIX + property.id()); + + return range; + } + + function replaceRangesAndCollectNodesToHide( propertyWithEquivalents, mergeNode, properties, processedPropertyIds ){ + var nodesToHide = []; + + propertyWithEquivalents.forEach(function ( property ){ + + if ( property === undefined || mergeNode === undefined ) // @ WORKAROUND + return; + var oldRangeId = property.range(); + property.range(mergeNode.id()); + if ( !isDomainOrRangeOfOtherProperty(oldRangeId, properties) ) { + nodesToHide.push(oldRangeId); + } + + processedPropertyIds.add(property.id()); + }); + + return nodesToHide; + } + + function isDomainOrRangeOfOtherProperty( nodeId, properties ){ + for ( var i = 0; i < properties.length; i++ ) { + var property = properties[i]; + if ( property.domain() === nodeId || property.range() === nodeId ) { + return true; + } + } + + return false; + } + + function filterVisibleNodes( nodes, nodeIdsToHide ){ + var filteredNodes = []; + + nodes.forEach(function ( node ){ + if ( !nodeIdsToHide.has(node.id()) ) { + filteredNodes.push(node); + } + }); + + return filteredNodes; + } + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 68 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( graph ){ + /** variable defs **/ + var Class_dragger = {}; + Class_dragger.nodeId = 10001; + Class_dragger.parent = undefined; + Class_dragger.x = 0; + Class_dragger.y = 0; + Class_dragger.rootElement = undefined; + Class_dragger.rootNodeLayer = undefined; + Class_dragger.pathLayer = undefined; + Class_dragger.mouseEnteredVar = false; + Class_dragger.mouseButtonPressed = false; + Class_dragger.nodeElement = undefined; + Class_dragger.draggerObject = undefined; + Class_dragger.pathElement = undefined; + Class_dragger.typus = "Class_dragger"; + + Class_dragger.type = function (){ + return Class_dragger.typus; + }; + + Class_dragger.parentNode = function (){ + return Class_dragger.parent; + }; + + Class_dragger.hideClass_dragger = function ( val ){ + Class_dragger.pathElement.classed("hidden", val); + Class_dragger.nodeElement.classed("hidden", val); + Class_dragger.draggerObject.classed("hidden", val); + }; + + Class_dragger.setParentNode = function ( parentNode ){ + Class_dragger.parent = parentNode; + + if ( Class_dragger.mouseButtonPressed === false ) { + if ( Class_dragger.parent.actualRadius && Class_dragger.parent.actualRadius() ) { + Class_dragger.x = Class_dragger.parent.x + 10 + Class_dragger.parent.actualRadius(); + Class_dragger.y = Class_dragger.parent.y + 10 + Class_dragger.parent.actualRadius(); + } else { + Class_dragger.x = Class_dragger.parent.x + 60; + Class_dragger.y = Class_dragger.parent.y + 60; + } + } + Class_dragger.updateElement(); + }; + + Class_dragger.hideDragger = function ( val ){ + if ( Class_dragger.pathElement ) Class_dragger.pathElement.classed("hidden", val); + if ( Class_dragger.nodeElement ) Class_dragger.nodeElement.classed("hidden", val); + if ( Class_dragger.draggerObject ) Class_dragger.draggerObject.classed("hidden", val); + + }; + /** BASE HANDLING FUNCTIONS ------------------------------------------------- **/ + Class_dragger.id = function ( index ){ + if ( !arguments.length ) { + return Class_dragger.nodeId; + } + Class_dragger.nodeId = index; + }; + + Class_dragger.svgPathLayer = function ( layer ){ + Class_dragger.pathLayer = layer.append('g'); + }; + + Class_dragger.svgRoot = function ( root ){ + if ( !arguments.length ) + return Class_dragger.rootElement; + Class_dragger.rootElement = root; + Class_dragger.rootNodeLayer = Class_dragger.rootElement.append('g'); + Class_dragger.addMouseEvents(); + }; + + /** DRAWING FUNCTIONS ------------------------------------------------- **/ + Class_dragger.drawNode = function (){ + Class_dragger.pathElement = Class_dragger.pathLayer.append('line') + .classed("classNodeDragPath", true); + Class_dragger.pathElement.attr("x1", 0) + .attr("y1", 0) + .attr("x2", 0) + .attr("y2", 0); + + // var lineData = [ + // {"x": 0, "y": 0}, + // {"x": 0, "y": 40}, + // {"x": -40, "y": 0}, + // {"x": 0, "y": -40}, + // {"x": 0, "y": 0} + // ]; + + var lineData = [ + { "x": -40, "y": 0 }, // start + { "x": -20, "y": -10 }, + { "x": 20, "y": -50 }, + { "x": -10, "y": 0 }, // center + { "x": 20, "y": 50 }, + { "x": -20, "y": 10 }, + { "x": -40, "y": 0 } + ]; + + + var lineFunction = d3.svg.line() + .x(function ( d ){ + return d.x; + }) + .y(function ( d ){ + return d.y; + }) + .interpolate("basis-closed"); + var pathData = "M 20,40 C 0,15 0,-15 20,-40 L -40,0 Z"; + // var pathData="M 20,40 C 0,15 0,-15 20,-40 20,-40 -35.22907,-23.905556 -45.113897,0.06313453 -35.22907,20.095453 20,40 20,40 Z"; + // var pathData="M 39.107144,51.25 C 0,17.362169 0,-13.75 39.285715,-49.821429 c 0,0 -69.58321,34.511175 -100.714286,50.35714329 C -22.96643,20.324376 39.107144,51.25 39.107144,51.25 Z"; + + Class_dragger.nodeElement = Class_dragger.rootNodeLayer.append('path').attr("d", pathData); + Class_dragger.nodeElement.classed("classDraggerNode", true); + Class_dragger.draggerObject = Class_dragger.rootNodeLayer.append("circle"); + if ( graph.options().useAccuracyHelper() ) { + Class_dragger.draggerObject.attr("r", 40) + .attr("cx", 0) + .attr("cy", 0) + .classed("superHiddenElement", true); + Class_dragger.draggerObject.classed("superOpacityElement", !graph.options().showDraggerObject()); + } + + + }; + + Class_dragger.updateElement = function (){ + + // Class_dragger.pathLayer.attr("transform", "translate(" + Class_dragger.x + "," + Class_dragger.y + ")"); + // Class_dragger.rootElement.attr("transform", "translate(" + Class_dragger.x + "," + Class_dragger.y + ")"); + if ( Class_dragger.pathElement ) { + + // compute start point ; + + + var sX = Class_dragger.parent.x, + sY = Class_dragger.parent.y, + eX = Class_dragger.x, + eY = Class_dragger.y; + + + // this is used only when you dont have a proper layout ordering; + var dirX = eX - sX; + var dirY = eY - sY; + var len = Math.sqrt((dirX * dirX) + (dirY * dirY)); + + var nX = dirX / len; + var nY = dirY / len; + + var ppX = sX + nX * Class_dragger.parent.actualRadius(); + var ppY = sY + nY * Class_dragger.parent.actualRadius(); + + var ncx = nX * 15; + var ncy = nY * 15; + Class_dragger.draggerObject.attr("cx", ncx) + .attr("cy", ncy); + + Class_dragger.pathElement.attr("x1", ppX) + .attr("y1", ppY) + .attr("x2", eX) + .attr("y2", eY); + } + var angle = Math.atan2(Class_dragger.parent.y - Class_dragger.y, Class_dragger.parent.x - Class_dragger.x) * 180 / Math.PI; + + Class_dragger.nodeElement.attr("transform", "translate(" + Class_dragger.x + "," + Class_dragger.y + ")" + "rotate(" + angle + ")"); + Class_dragger.draggerObject.attr("transform", "translate(" + Class_dragger.x + "," + Class_dragger.y + ")"); + // console.log("update Elmenent root element"+Class_dragger.x + "," + Class_dragger.y ); + // + // Class_dragger.nodeElement.attr("transform", function (d) { + // return "rotate(" + angle + ")"; + // }); + }; + + /** MOUSE HANDLING FUNCTIONS ------------------------------------------------- **/ + + Class_dragger.addMouseEvents = function (){ + // console.log("adding mouse events"); + Class_dragger.rootNodeLayer.selectAll("*").on("mouseover", Class_dragger.onMouseOver) + .on("mouseout", Class_dragger.onMouseOut) + .on("click", function (){ + }) + .on("dblclick", function (){ + }) + .on("mousedown", Class_dragger.mouseDown) + .on("mouseup", Class_dragger.mouseUp); + }; + + Class_dragger.mouseDown = function (){ + Class_dragger.nodeElement.style("cursor", "move"); + Class_dragger.nodeElement.classed("classDraggerNodeHovered", true); + Class_dragger.mouseButtonPressed = true; + console.log("Mouse DOWN from Dragger"); + }; + + Class_dragger.mouseUp = function (){ + Class_dragger.nodeElement.style("cursor", "auto"); + Class_dragger.mouseButtonPressed = false; + console.log("Mouse UP from Dragger"); + }; + + + Class_dragger.mouseEntered = function ( p ){ + if ( !arguments.length ) return Class_dragger.mouseEnteredVar; + Class_dragger.mouseEnteredVar = p; + return Class_dragger; + }; + + Class_dragger.selectedViaTouch = function ( val ){ + Class_dragger.nodeElement.classed("classDraggerNode", !val); + Class_dragger.nodeElement.classed("classDraggerNodeHovered", val); + + }; + + Class_dragger.onMouseOver = function (){ + if ( Class_dragger.mouseEntered() ) { + return; + } + Class_dragger.nodeElement.classed("classDraggerNode", false); + Class_dragger.nodeElement.classed("classDraggerNodeHovered", true); + var selectedNode = Class_dragger.rootElement.node(), + nodeContainer = selectedNode.parentNode; + nodeContainer.appendChild(selectedNode); + + Class_dragger.mouseEntered(true); + + }; + Class_dragger.onMouseOut = function (){ + if ( Class_dragger.mouseButtonPressed === true ) + return; + Class_dragger.nodeElement.classed("classDraggerNodeHovered", false); + Class_dragger.nodeElement.classed("classDraggerNode", true); + Class_dragger.mouseEntered(false); + }; + + Class_dragger.setPosition = function ( x, y ){ + + Class_dragger.x = x; + Class_dragger.y = y; + Class_dragger.updateElement(); + }; + + Class_dragger.setAdditionalClassForClass_dragger = function ( name, val ){ + // console.log("Class_dragger should sett the class here") + // Class_dragger.nodeElement.classed(name,val); + + }; + return Class_dragger; + }; + + + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 69 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( graph ){ + /** variable defs **/ + var Range_dragger = {}; + Range_dragger.nodeId = 10002; + Range_dragger.parent = undefined; + Range_dragger.x = 0; + Range_dragger.y = 0; + Range_dragger.rootElement = undefined; + Range_dragger.rootNodeLayer = undefined; + Range_dragger.pathLayer = undefined; + Range_dragger.mouseEnteredVar = false; + Range_dragger.mouseButtonPressed = false; + Range_dragger.nodeElement = undefined; + Range_dragger.draggerObject = undefined; + + Range_dragger.pathElement = undefined; + Range_dragger.typus = "Range_dragger"; + + Range_dragger.type = function (){ + return Range_dragger.typus; + }; + + // TODO: We need the endPoint of the Link here! + Range_dragger.parentNode = function (){ + return Range_dragger.parent; + }; + + Range_dragger.hide_dragger = function ( val ){ + Range_dragger.pathElement.classed("hidden", val); + Range_dragger.nodeElement.classed("hidden", val); + Range_dragger.draggerObject.classed("hidden", val); + }; + Range_dragger.hideDragger = function ( val ){ + if ( Range_dragger.pathElement ) Range_dragger.pathElement.classed("hidden", val); + if ( Range_dragger.nodeElement ) Range_dragger.nodeElement.classed("hidden", val); + if ( Range_dragger.draggerObject ) Range_dragger.draggerObject.classed("hidden", val); + + + }; + + Range_dragger.reDrawEverthing = function (){ + Range_dragger.setParentProperty(Range_dragger.parent); + }; + Range_dragger.updateRange = function ( newRange ){ + + if ( graph.genericPropertySanityCheck(Range_dragger.parent.domain(), newRange, + Range_dragger.parent.type(), + "Could not update range", "Restoring previous range") === false ) return; + + // check for triple duplicates! + + if ( graph.propertyCheckExistenceChecker(Range_dragger.parent, Range_dragger.parent.domain(), newRange) === false ) + return; + if ( Range_dragger.parent.labelElement() === undefined ) return; + if ( Range_dragger.parent.labelElement().attr("transform") === "translate(0,15)" || + Range_dragger.parent.labelElement().attr("transform") === "translate(0,-15)" ) { + var prop = Range_dragger.parent; + Range_dragger.parent.inverse().inverse(null); + Range_dragger.parent.inverse(null); + prop.range(newRange); + } + + else { + Range_dragger.parent.range(newRange); + } + // update the position of the new range + var rX = newRange.x; + var rY = newRange.y; + + var dX = Range_dragger.parent.domain().x; + var dY = Range_dragger.parent.domain().y; + + + // center + var cX = 0.49 * (dX + rX); + var cY = 0.49 * (dY + rY); + // put position there; + Range_dragger.parent.labelElement().x = cX; + Range_dragger.parent.labelElement().px = cX; + Range_dragger.parent.labelElement().y = cY; + Range_dragger.parent.labelElement().py = cY; + + }; + + Range_dragger.setParentProperty = function ( parentProperty, inversed ){ + Range_dragger.parent = parentProperty; + var iP; + var renElem; + Range_dragger.isLoopProperty = false; + if ( parentProperty.domain() === parentProperty.range() ) Range_dragger.isLoopProperty = true; + Range_dragger.parent = parentProperty; + renElem = parentProperty.labelObject(); + if ( inversed === true ) { + if ( parentProperty.labelElement() && parentProperty.labelElement().attr("transform") === "translate(0,15)" ) { + iP = renElem.linkDomainIntersection; + if ( renElem.linkDomainIntersection ) { + Range_dragger.x = iP.x; + Range_dragger.y = iP.y; + } + } else { + iP = renElem.linkRangeIntersection; + if ( renElem.linkRangeIntersection ) { + Range_dragger.x = iP.x; + Range_dragger.y = iP.y; + } + } + } + else { + iP = renElem.linkRangeIntersection; + if ( renElem.linkRangeIntersection ) { + Range_dragger.x = iP.x; + Range_dragger.y = iP.y; + } + } + + Range_dragger.updateElement(); + }; + + + /** BASE HANDLING FUNCTIONS ------------------------------------------------- **/ + Range_dragger.id = function ( index ){ + if ( !arguments.length ) { + return Range_dragger.nodeId; + } + Range_dragger.nodeId = index; + }; + + Range_dragger.svgPathLayer = function ( layer ){ + Range_dragger.pathLayer = layer.append('g'); + }; + + Range_dragger.svgRoot = function ( root ){ + if ( !arguments.length ) + return Range_dragger.rootElement; + Range_dragger.rootElement = root; + Range_dragger.rootNodeLayer = Range_dragger.rootElement.append('g'); + Range_dragger.addMouseEvents(); + }; + + /** DRAWING FUNCTIONS ------------------------------------------------- **/ + Range_dragger.drawNode = function (){ + Range_dragger.pathElement = Range_dragger.pathLayer.append('line') + .classed("classNodeDragPath", true); + Range_dragger.pathElement.attr("x1", 0) + .attr("y1", 0) + .attr("x2", 0) + .attr("y2", 0); + + // var lineData = [ + // {"x": 0, "y": 0}, + // {"x": 0, "y": 40}, + // {"x": -40, "y": 0}, + // {"x": 0, "y": -40}, + // {"x": 0, "y": 0} + // ]; + + var lineData = [ + { "x": -40, "y": 0 }, // start + { "x": -20, "y": -10 }, + { "x": 20, "y": -50 }, + { "x": -10, "y": 0 }, // center + { "x": 20, "y": 50 }, + { "x": -20, "y": 10 }, + { "x": -40, "y": 0 } + ]; + + + var lineFunction = d3.svg.line() + .x(function ( d ){ + return d.x; + }) + .y(function ( d ){ + return d.y; + }) + .interpolate("basis-closed"); + var pathData = "M 61,40 C 41,15 41,-15 61,-40 L 1,0 Z"; + + Range_dragger.nodeElement = Range_dragger.rootNodeLayer.append('path').attr("d", pathData); + Range_dragger.nodeElement.classed("classDraggerNode", true); + if ( graph.options().useAccuracyHelper() ) { + Range_dragger.draggerObject = Range_dragger.rootNodeLayer.append("circle"); + Range_dragger.draggerObject.attr("r", 40) + .attr("cx", 0) + .attr("cy", 0) + .classed("superHiddenElement", true); + Range_dragger.draggerObject.classed("superOpacityElement", !graph.options().showDraggerObject()); + } + + + }; + + Range_dragger.updateElementViaDomainDragger = function ( x, y ){ + + var range_x = x; + var range_y = y; + + var dex = Range_dragger.parent.range().x; + var dey = Range_dragger.parent.range().y; + + var dir_X = x - dex; + var dir_Y = y - dey; + + var len = Math.sqrt(dir_X * dir_X + dir_Y * dir_Y); + + var nX = dir_X / len; + var nY = dir_Y / len; + + + var ep_range_x = dex + nX * Range_dragger.parent.range().actualRadius(); + var ep_range_y = dey + nY * Range_dragger.parent.range().actualRadius(); + + + var dx = range_x - ep_range_x; + var dy = range_y - ep_range_y; + len = Math.sqrt(dx * dx + dy * dy); + nX = dx / len; + nY = dy / len; + + var angle = Math.atan2(ep_range_y - range_y, ep_range_x - range_x) * 180 / Math.PI + 180; + Range_dragger.nodeElement.attr("transform", "translate(" + ep_range_x + "," + ep_range_y + ")" + "rotate(" + angle + ")"); + var doX = ep_range_x + nX * 40; + var doY = ep_range_y + nY * 40; + Range_dragger.draggerObject.attr("transform", "translate(" + doX + "," + doY + ")"); + + }; + + + Range_dragger.updateElement = function (){ + if ( Range_dragger.mouseButtonPressed === true || Range_dragger.parent === undefined ) return; + + var range = Range_dragger.parent.range(); + var iP = Range_dragger.parent.labelObject().linkRangeIntersection; + if ( Range_dragger.parent.labelElement() === undefined ) return; + var offsetForLoop = 48; + if ( Range_dragger.parent.labelElement().attr("transform") === "translate(0,15)" ) { + range = Range_dragger.parent.inverse().domain(); + iP = Range_dragger.parent.labelObject().linkDomainIntersection; + offsetForLoop = -48; + } + + if ( iP === undefined ) return; + var range_x = range.x; + var range_y = range.y; + + var ep_range_x = iP.x; + var ep_range_y = iP.y; + // offset for dragger object + var dx = range_x - ep_range_x; + var dy = range_y - ep_range_y; + var len = Math.sqrt(dx * dx + dy * dy); + var nX = dx / len; + var nY = dy / len; + var angle = Math.atan2(ep_range_y - range_y, ep_range_x - range_x) * 180 / Math.PI; + + var doX = ep_range_x - nX * 40; + var doY = ep_range_y - nY * 40; + + if ( Range_dragger.isLoopProperty === true ) + angle -= offsetForLoop; + + + Range_dragger.nodeElement.attr("transform", "translate(" + ep_range_x + "," + ep_range_y + ")" + "rotate(" + angle + ")"); + Range_dragger.draggerObject.attr("transform", "translate(" + doX + "," + doY + ")"); + + + }; + + /** MOUSE HANDLING FUNCTIONS ------------------------------------------------- **/ + + Range_dragger.addMouseEvents = function (){ + var rootLayer = Range_dragger.rootNodeLayer.selectAll("*"); + rootLayer.on("mouseover", Range_dragger.onMouseOver) + .on("mouseout", Range_dragger.onMouseOut) + .on("click", function (){ + }) + .on("dblclick", function (){ + }) + .on("mousedown", Range_dragger.mouseDown) + .on("mouseup", Range_dragger.mouseUp); + }; + + Range_dragger.mouseDown = function (){ + Range_dragger.nodeElement.style("cursor", "move"); + Range_dragger.nodeElement.classed("classDraggerNodeHovered", true); + Range_dragger.mouseButtonPressed = true; + }; + + Range_dragger.mouseUp = function (){ + Range_dragger.nodeElement.style("cursor", "auto"); + Range_dragger.nodeElement.classed("classDraggerNodeHovered", false); + Range_dragger.mouseButtonPressed = false; + }; + + + Range_dragger.mouseEntered = function ( p ){ + if ( !arguments.length ) return Range_dragger.mouseEnteredVar; + Range_dragger.mouseEnteredVar = p; + return Range_dragger; + }; + + Range_dragger.selectedViaTouch = function ( val ){ + Range_dragger.nodeElement.classed("classDraggerNode", !val); + Range_dragger.nodeElement.classed("classDraggerNodeHovered", val); + + }; + + Range_dragger.onMouseOver = function (){ + if ( Range_dragger.mouseEntered() ) { + return; + } + Range_dragger.nodeElement.classed("classDraggerNode", false); + Range_dragger.nodeElement.classed("classDraggerNodeHovered", true); + var selectedNode = Range_dragger.rootElement.node(), + nodeContainer = selectedNode.parentNode; + nodeContainer.appendChild(selectedNode); + + Range_dragger.mouseEntered(true); + + }; + Range_dragger.onMouseOut = function (){ + if ( Range_dragger.mouseButtonPressed === true ) + return; + Range_dragger.nodeElement.classed("classDraggerNodeHovered", false); + Range_dragger.nodeElement.classed("classDraggerNode", true); + Range_dragger.mouseEntered(false); + }; + + Range_dragger.setPosition = function ( x, y ){ + var range_x = Range_dragger.parent.domain().x; + var range_y = Range_dragger.parent.domain().y; + + // var position of the rangeEndPoint + var ep_range_x = x; + var ep_range_y = y; + + // offset for dragger object + var dx = range_x - ep_range_x; + var dy = range_y - ep_range_y; + + var len = Math.sqrt(dx * dx + dy * dy); + + var nX = dx / len; + var nY = dy / len; + + + var angle = Math.atan2(dy, dx) * 180 / Math.PI; + var doX = ep_range_x + nX * 40; + var doY = ep_range_y + nY * 40; + Range_dragger.nodeElement.attr("transform", "translate(" + ep_range_x + "," + ep_range_y + ")" + "rotate(" + angle + ")"); + Range_dragger.draggerObject.attr("transform", "translate(" + doX + "," + doY + ")"); + Range_dragger.x = x; + Range_dragger.y = y; + + }; + + Range_dragger.setAdditionalClassForClass_dragger = function ( name, val ){ + + }; + return Range_dragger; + }; + + + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 70 */ +/***/ (function(module, exports) { + + module.exports = function ( graph ){ + /** variable defs **/ + var Domain_dragger = {}; + Domain_dragger.nodeId = 10002; + Domain_dragger.parent = undefined; + Domain_dragger.x = 0; + Domain_dragger.y = 0; + Domain_dragger.rootElement = undefined; + Domain_dragger.rootNodeLayer = undefined; + Domain_dragger.pathLayer = undefined; + Domain_dragger.mouseEnteredVar = false; + Domain_dragger.mouseButtonPressed = false; + Domain_dragger.nodeElement = undefined; + Domain_dragger.draggerObject = undefined; + + Domain_dragger.pathElement = undefined; + Domain_dragger.typus = "Domain_dragger"; + + Domain_dragger.type = function (){ + return Domain_dragger.typus; + }; + + + // TODO: We need the endPoint of the Link here! + Domain_dragger.parentNode = function (){ + return Domain_dragger.parent; + }; + + Domain_dragger.hide_dragger = function ( val ){ + Domain_dragger.pathElement.classed("hidden", val); + Domain_dragger.nodeElement.classed("hidden", val); + Domain_dragger.draggerObject.classed("hidden", val); + }; + + Domain_dragger.reDrawEverthing = function (){ + Domain_dragger.setParentProperty(Domain_dragger.parent); + }; + Domain_dragger.updateDomain = function ( newDomain ){ + + if ( graph.genericPropertySanityCheck(Domain_dragger.parent.range(), newDomain, Domain_dragger.parent.type(), + "Could not update domain", "Restoring previous domain") === false ) { + Domain_dragger.updateElement(); + return; + } + + if ( graph.propertyCheckExistenceChecker(Domain_dragger.parent, newDomain, Domain_dragger.parent.range()) === false ) + return; + + + if ( Domain_dragger.parent.labelElement() === undefined ) { + Domain_dragger.updateElement(); + return; + } + if ( Domain_dragger.parent.labelElement().attr("transform") === "translate(0,15)" || + Domain_dragger.parent.labelElement().attr("transform") === "translate(0,-15)" ) { + var prop = Domain_dragger.parent; + Domain_dragger.parent.inverse().inverse(null); + Domain_dragger.parent.inverse(null); + console.log("SPLITTING ITEMS!"); + prop.domain(newDomain); + } + else { + Domain_dragger.parent.domain(newDomain); + } + + // update the position of the new range + var rX = Domain_dragger.parent.range().x; + var rY = Domain_dragger.parent.range().y; + var dX = newDomain.x; + var dY = newDomain.y; + + // center + var cX = 0.49 * (dX + rX); + var cY = 0.49 * (dY + rY); + // put position there; + Domain_dragger.parent.labelObject().x = cX; + Domain_dragger.parent.labelObject().px = cX; + Domain_dragger.parent.labelObject().y = cY; + Domain_dragger.parent.labelObject().py = cY; + Domain_dragger.updateElement(); + + }; + + Domain_dragger.setParentProperty = function ( parentProperty, inverted ){ + Domain_dragger.invertedProperty = inverted; + var renElem; + var iP; + Domain_dragger.isLoopProperty = false; + if ( parentProperty.domain() === parentProperty.range() ) + Domain_dragger.isLoopProperty = true; + + Domain_dragger.parent = parentProperty; + renElem = parentProperty.labelObject(); + if ( inverted === true ) { + + // this is the lower element + if ( parentProperty.labelElement() && parentProperty.labelElement().attr("transform") === "translate(0,15)" ) { + // console.log("This is the lower element!"); + iP = renElem.linkRangeIntersection; + if ( renElem.linkRangeIntersection ) { + Domain_dragger.x = iP.x; + Domain_dragger.y = iP.y; + } + } + else { + // console.log("This is the upper element"); + iP = renElem.linkDomainIntersection; + if ( renElem.linkDomainIntersection ) { + Domain_dragger.x = iP.x; + Domain_dragger.y = iP.y; + } + } + } + else { + // console.log("This is single element"); + iP = renElem.linkDomainIntersection; + if ( renElem.linkDomainIntersection ) { + Domain_dragger.x = iP.x; + Domain_dragger.y = iP.y; + } + } + Domain_dragger.updateElement(); + + }; + + Domain_dragger.hideDragger = function ( val ){ + if ( Domain_dragger.pathElement ) Domain_dragger.pathElement.classed("hidden", val); + if ( Domain_dragger.nodeElement ) Domain_dragger.nodeElement.classed("hidden", val); + if ( Domain_dragger.draggerObject ) Domain_dragger.draggerObject.classed("hidden", val); + + + }; + /** BASE HANDLING FUNCTIONS ------------------------------------------------- **/ + Domain_dragger.id = function ( index ){ + if ( !arguments.length ) { + return Domain_dragger.nodeId; + } + Domain_dragger.nodeId = index; + }; + + Domain_dragger.svgPathLayer = function ( layer ){ + Domain_dragger.pathLayer = layer.append('g'); + }; + + Domain_dragger.svgRoot = function ( root ){ + if ( !arguments.length ) + return Domain_dragger.rootElement; + Domain_dragger.rootElement = root; + Domain_dragger.rootNodeLayer = Domain_dragger.rootElement.append('g'); + Domain_dragger.addMouseEvents(); + }; + + /** DRAWING FUNCTIONS ------------------------------------------------- **/ + Domain_dragger.drawNode = function (){ + Domain_dragger.pathElement = Domain_dragger.pathLayer.append('line') + .classed("classNodeDragPath", true); + Domain_dragger.pathElement.attr("x1", 0) + .attr("y1", 0) + .attr("x2", 0) + .attr("y2", 0); + + var pathData = "M 10,40 C -10,15 -10,-15 10,-40 -8.8233455,-13.641384 -36.711107,-5.1228436 -50,0 -36.696429,4.9079017 -8.6403157,13.745728 10,40 Z"; + Domain_dragger.nodeElement = Domain_dragger.rootNodeLayer.append('path').attr("d", pathData); + Domain_dragger.nodeElement.classed("classDraggerNode", true); + if ( graph.options().useAccuracyHelper() ) { + Domain_dragger.draggerObject = Domain_dragger.rootNodeLayer.append("circle"); + Domain_dragger.draggerObject.attr("r", 40) + .attr("cx", 0) + .attr("cy", 0) + .classed("superHiddenElement", true); + Domain_dragger.draggerObject.classed("superOpacityElement", !graph.options().showDraggerObject()); + } + + + }; + Domain_dragger.updateElementViaRangeDragger = function ( x, y ){ + var range_x = x; + var range_y = y; + + var dex = Domain_dragger.parent.domain().x; + var dey = Domain_dragger.parent.domain().y; + + var dir_X = x - dex; + var dir_Y = y - dey; + + var len = Math.sqrt(dir_X * dir_X + dir_Y * dir_Y); + + var nX = dir_X / len; + var nY = dir_Y / len; + + + var ep_range_x = dex + nX * Domain_dragger.parent.domain().actualRadius(); + var ep_range_y = dey + nY * Domain_dragger.parent.domain().actualRadius(); + + var angle = Math.atan2(ep_range_y - range_y, ep_range_x - range_x) * 180 / Math.PI; + + Domain_dragger.nodeElement.attr("transform", "translate(" + ep_range_x + "," + ep_range_y + ")" + "rotate(" + angle + ")"); + var dox = ep_range_x + nX * 20; + var doy = ep_range_y + nY * 20; + Domain_dragger.draggerObject.attr("transform", "translate(" + dox + "," + doy + ")"); + }; + + + Domain_dragger.updateElement = function (){ + if ( Domain_dragger.mouseButtonPressed === true || Domain_dragger.parent === undefined ) return; + + var domain = Domain_dragger.parent.domain(); + var iP = Domain_dragger.parent.labelObject().linkDomainIntersection; + if ( Domain_dragger.parent.labelElement() === undefined ) return; + if ( Domain_dragger.parent.labelElement().attr("transform") === "translate(0,15)" ) { + Domain_dragger.parent.inverse().domain(); + iP = Domain_dragger.parent.labelObject().linkRangeIntersection; + + } + var range_x = domain.x; + var range_y = domain.y; + + + if ( iP === undefined ) return; + var ep_range_x = iP.x; + var ep_range_y = iP.y; + + var dx = range_x - ep_range_x; + var dy = range_y - ep_range_y; + var len = Math.sqrt(dx * dx + dy * dy); + + var nX = dx / len; + var nY = dy / len; + + var dox = ep_range_x - nX * 20; + var doy = ep_range_y - nY * 20; + var angle = Math.atan2(ep_range_y - range_y, ep_range_x - range_x) * 180 / Math.PI + 180; + + Domain_dragger.nodeElement.attr("transform", "translate(" + ep_range_x + "," + ep_range_y + ")" + "rotate(" + angle + ")"); + Domain_dragger.draggerObject.attr("transform", "translate(" + dox + "," + doy + ")"); + }; + + /** MOUSE HANDLING FUNCTIONS ------------------------------------------------- **/ + + Domain_dragger.addMouseEvents = function (){ + var rootLayer = Domain_dragger.rootNodeLayer.selectAll("*"); + rootLayer.on("mouseover", Domain_dragger.onMouseOver) + .on("mouseout", Domain_dragger.onMouseOut) + .on("click", function (){ + }) + .on("dblclick", function (){ + }) + .on("mousedown", Domain_dragger.mouseDown) + .on("mouseup", Domain_dragger.mouseUp); + }; + + Domain_dragger.mouseDown = function (){ + Domain_dragger.nodeElement.style("cursor", "move"); + Domain_dragger.nodeElement.classed("classDraggerNodeHovered", true); + Domain_dragger.mouseButtonPressed = true; + }; + + Domain_dragger.mouseUp = function (){ + Domain_dragger.nodeElement.style("cursor", "auto"); + Domain_dragger.nodeElement.classed("classDraggerNodeHovered", false); + Domain_dragger.mouseButtonPressed = false; + }; + + + Domain_dragger.mouseEntered = function ( p ){ + if ( !arguments.length ) return Domain_dragger.mouseEnteredVar; + Domain_dragger.mouseEnteredVar = p; + return Domain_dragger; + }; + + Domain_dragger.selectedViaTouch = function ( val ){ + Domain_dragger.nodeElement.classed("classDraggerNode", !val); + Domain_dragger.nodeElement.classed("classDraggerNodeHovered", val); + + }; + + Domain_dragger.onMouseOver = function (){ + if ( Domain_dragger.mouseEntered() ) { + return; + } + Domain_dragger.nodeElement.classed("classDraggerNode", false); + Domain_dragger.nodeElement.classed("classDraggerNodeHovered", true); + var selectedNode = Domain_dragger.rootElement.node(), + nodeContainer = selectedNode.parentNode; + nodeContainer.appendChild(selectedNode); + + Domain_dragger.mouseEntered(true); + + }; + Domain_dragger.onMouseOut = function (){ + if ( Domain_dragger.mouseButtonPressed === true ) + return; + Domain_dragger.nodeElement.classed("classDraggerNodeHovered", false); + Domain_dragger.nodeElement.classed("classDraggerNode", true); + Domain_dragger.mouseEntered(false); + }; + + Domain_dragger.setPosition = function ( x, y ){ + var range_x = Domain_dragger.parent.range().x; + var range_y = Domain_dragger.parent.range().y; + + // var position of the rangeEndPoint + var ep_range_x = x; + var ep_range_y = y; + + // offset for dragger object + var dx = range_x - ep_range_x; + var dy = range_y - ep_range_y; + + var len = Math.sqrt(dx * dx + dy * dy); + + var nX = dx / len; + var nY = dy / len; + var dox = ep_range_x + nX * 20; + var doy = ep_range_y + nY * 20; + + var angle = Math.atan2(range_y - ep_range_y, range_x - ep_range_x) * 180 / Math.PI + 180; + + Domain_dragger.nodeElement.attr("transform", "translate(" + ep_range_x + "," + ep_range_y + ")" + "rotate(" + angle + ")"); + Domain_dragger.draggerObject.attr("transform", "translate(" + dox + "," + doy + ")"); + + Domain_dragger.x = x; + Domain_dragger.y = y; + + }; + + Domain_dragger.setAdditionalClassForClass_dragger = function ( name, val ){ + // console.log("Class_dragger should sett the class here") + // Class_dragger.nodeElement.classed(name,val); + + }; + return Domain_dragger; + }; + + + + +/***/ }), +/* 71 */ +/***/ (function(module, exports, __webpack_require__) { + + var CenteringTextElement = __webpack_require__(14); + var elementTools = __webpack_require__(63)(); + var math = __webpack_require__(43)(); + module.exports = function ( graph ){ + /** variable defs **/ + var ShadowClone = {}; + ShadowClone.nodeId = 10003; + ShadowClone.parent = undefined; + ShadowClone.s_x = 0; + ShadowClone.s_y = 0; + ShadowClone.e_x = 0; + ShadowClone.e_y = 0; + ShadowClone.rootElement = undefined; + ShadowClone.rootNodeLayer = undefined; + ShadowClone.pathLayer = undefined; + ShadowClone.nodeElement = undefined; + ShadowClone.pathElement = undefined; + ShadowClone.typus = "shadowClone"; + + + ShadowClone.type = function (){ + return ShadowClone.typus; + }; + + // TODO: We need the endPoint of the Link here! + ShadowClone.parentNode = function (){ + return ShadowClone.parent; + }; + + ShadowClone.setParentProperty = function ( parentProperty, inverted ){ + ShadowClone.invertedProperty = inverted; + ShadowClone.parent = parentProperty; + var renElment; + if ( inverted === true ) { + renElment = parentProperty.inverse().labelObject(); + if ( renElment.linkRangeIntersection && renElment.linkDomainIntersection ) { + var iiP_range = renElment.linkDomainIntersection; + var iiP_domain = renElment.linkRangeIntersection; + ShadowClone.s_x = iiP_domain.x; + ShadowClone.s_y = iiP_domain.y; + ShadowClone.e_x = iiP_range.x; + ShadowClone.e_y = iiP_range.y; + } + } + else { + renElment = parentProperty.labelObject(); + + if ( renElment.linkRangeIntersection && renElment.linkDomainIntersection ) { + var iP_range = renElment.linkRangeIntersection; + var iP_domain = renElment.linkDomainIntersection; + ShadowClone.s_x = iP_domain.x; + ShadowClone.s_y = iP_domain.y; + ShadowClone.e_x = iP_range.x; + ShadowClone.e_y = iP_range.y; + } + + } + + ShadowClone.rootNodeLayer.remove(); + ShadowClone.rootNodeLayer = ShadowClone.rootElement.append('g'); + ShadowClone.rootNodeLayer.datum(parentProperty); + + // ShadowClone.pathElement.remove(); + // ShadowClone.pathElement = ShadowClone.pathLayer.append('line'); + // + // ShadowClone.pathElement.attr("x1", ShadowClone.s_x) + // .attr("y1", ShadowClone.s_y) + // .attr("x2", ShadowClone.e_x) + // .attr("y2", ShadowClone.e_y); + ShadowClone.pathElement.remove(); + ShadowClone.pathElement = ShadowClone.pathLayer.append('line'); + ShadowClone.markerElement = ShadowClone.pathLayer.append("marker"); + ShadowClone.markerElement.attr("id", "shadowCloneMarker"); + ShadowClone.pathElement.attr("x1", ShadowClone.e_x) + .attr("y1", ShadowClone.e_y) + .attr("x2", ShadowClone.s_x) + .attr("y2", ShadowClone.s_y); + ShadowClone.pathElement.classed(parentProperty.linkType(), true); + + if ( parentProperty.markerElement() ) { + ShadowClone.markerElement.attr("viewBox", parentProperty.markerElement().attr("viewBox")) + .attr("markerWidth", parentProperty.markerElement().attr("markerWidth")) + .attr("markerHeight", parentProperty.markerElement().attr("markerHeight")) + .attr("orient", parentProperty.markerElement().attr("orient")); + + var markerPath = parentProperty.markerElement().select("path"); + ShadowClone.markerElement.append("path") + .attr("d", markerPath.attr("d")) + .classed(parentProperty.markerType(), true); + + ShadowClone.pathElement.attr("marker-end", "url(#" + "shadowCloneMarker" + ")"); + ShadowClone.markerElement.classed("hidden", !elementTools.isDatatypeProperty(parentProperty)); + } + var rect = ShadowClone.rootNodeLayer.append("rect") + .classed(parentProperty.styleClass(), true) + .classed("property", true) + .attr("x", -parentProperty.width() / 2) + .attr("y", -parentProperty.height() / 2) + .attr("width", parentProperty.width()) + .attr("height", parentProperty.height()); + + if ( parentProperty.visualAttributes() ) { + rect.classed(parentProperty.visualAttributes(), true); + } + rect.classed("datatype", false); + var bgColor = parentProperty.backgroundColor(); + + if ( parentProperty.attributes().indexOf("deprecated") > -1 ) { + bgColor = undefined; + rect.classed("deprecatedproperty", true); + } else { + rect.classed("deprecatedproperty", false); + } + rect.style("fill", bgColor); + + // add Text; + var equivalentsString = parentProperty.equivalentsString(); + var suffixForFollowingEquivalents = equivalentsString ? "," : ""; + + + var textElement = new CenteringTextElement(ShadowClone.rootNodeLayer, bgColor); + textElement.addText(parentProperty.labelForCurrentLanguage(), "", suffixForFollowingEquivalents); + textElement.addEquivalents(equivalentsString); + textElement.addSubText(parentProperty.indicationString()); + + + var cx = 0.5 * (ShadowClone.s_x + ShadowClone.e_x); + var cy = 0.5 * (ShadowClone.s_y + ShadowClone.e_y); + ShadowClone.rootNodeLayer.attr("transform", "translate(" + cx + "," + cy + ")"); + ShadowClone.rootNodeLayer.classed("hidden", true); + ShadowClone.pathElement.classed("hidden", true); + + + }; + + ShadowClone.hideClone = function ( val ){ + if ( ShadowClone.rootNodeLayer ) ShadowClone.rootNodeLayer.classed("hidden", val); + if ( ShadowClone.pathElement ) ShadowClone.pathElement.classed("hidden", val); + }; + + ShadowClone.hideParentProperty = function ( val ){ + + var labelObj = ShadowClone.parent.labelObject(); + if ( labelObj ) { + if ( ShadowClone.parent.labelElement().attr("transform") === "translate(0,15)" || + ShadowClone.parent.labelElement().attr("transform") === "translate(0,-15)" ) + ShadowClone.parent.inverse().hide(val); + + + } + ShadowClone.parent.hide(val); + + + }; + + /** BASE HANDLING FUNCTIONS ------------------------------------------------- **/ + ShadowClone.id = function ( index ){ + if ( !arguments.length ) { + return ShadowClone.nodeId; + } + ShadowClone.nodeId = index; + }; + + ShadowClone.svgPathLayer = function ( layer ){ + ShadowClone.pathLayer = layer.append('g'); + }; + + ShadowClone.svgRoot = function ( root ){ + if ( !arguments.length ) + return ShadowClone.rootElement; + ShadowClone.rootElement = root; + ShadowClone.rootNodeLayer = ShadowClone.rootElement.append('g'); + + }; + + /** DRAWING FUNCTIONS ------------------------------------------------- **/ + ShadowClone.drawClone = function (){ + ShadowClone.pathElement = ShadowClone.pathLayer.append('line'); + + ShadowClone.pathElement.attr("x1", 0) + .attr("y1", 0) + .attr("x2", 0) + .attr("y2", 0); + + }; + + + ShadowClone.updateElement = function (){ + ShadowClone.pathElement.attr("x1", ShadowClone.e_x) + .attr("y1", ShadowClone.e_y) + .attr("x2", ShadowClone.s_x) + .attr("y2", ShadowClone.s_y); + + var cx = 0.5 * (ShadowClone.s_x + ShadowClone.e_x); + var cy = 0.5 * (ShadowClone.s_y + ShadowClone.e_y); + ShadowClone.rootNodeLayer.attr("transform", "translate(" + cx + "," + cy + ")"); + }; + + ShadowClone.setInitialPosition = function (){ + + var renElment = ShadowClone.parent.labelObject(); + if ( renElment.linkRangeIntersection && renElment.linkDomainIntersection ) { + var iP_range = renElment.linkRangeIntersection; + var iP_domain = renElment.linkDomainIntersection; + ShadowClone.e_x = iP_domain.x; + ShadowClone.e_y = iP_domain.y; + ShadowClone.s_x = iP_range.x; + ShadowClone.s_y = iP_range.y; + } + ShadowClone.updateElement(); + return; + // + // var rex=ShadowClone.parent.range().x; + // var rey=ShadowClone.parent.range().y; + // + // + // var dex=ShadowClone.parent.domain().x; + // var dey=ShadowClone.parent.domain().y; + // + // + // var dir_X= rex-dex; + // var dir_Y= rey-dey; + // + // var len=Math.sqrt(dir_X*dir_X+dir_Y*dir_Y); + // var nX=dir_X/len; + // var nY=dir_Y/len; + // ShadowClone.s_x=rex-nX*ShadowClone.parent.range().actualRadius(); + // ShadowClone.s_y=rey-nY*ShadowClone.parent.range().actualRadius(); + // + // ShadowClone.e_x=dex+nX*ShadowClone.parent.domain().actualRadius(); + // ShadowClone.e_y=dey+nY*ShadowClone.parent.domain().actualRadius(); + // ShadowClone.updateElement(); + + }; + ShadowClone.setPositionDomain = function ( e_x, e_y ){ + + var rex = ShadowClone.parent.range().x; + var rey = ShadowClone.parent.range().y; + + + if ( elementTools.isDatatype(ShadowClone.parent.range()) === true ) { + var intersection = math.calculateIntersection({ x: e_x, y: e_y }, ShadowClone.parent.range(), 0); + ShadowClone.s_x = intersection.x; + ShadowClone.s_y = intersection.y; + } else { + var dir_X = rex - e_x; + var dir_Y = rey - e_y; + + var len = Math.sqrt(dir_X * dir_X + dir_Y * dir_Y); + + var nX = dir_X / len; + var nY = dir_Y / len; + ShadowClone.s_x = rex - nX * ShadowClone.parent.range().actualRadius(); + ShadowClone.s_y = rey - nY * ShadowClone.parent.range().actualRadius(); + + } + + + ShadowClone.e_x = e_x; + ShadowClone.e_y = e_y; + ShadowClone.updateElement(); + }; + + ShadowClone.setPosition = function ( s_x, s_y ){ + ShadowClone.s_x = s_x; + ShadowClone.s_y = s_y; + + // add normalized dir; + + var dex = ShadowClone.parent.domain().x; + var dey = ShadowClone.parent.domain().y; + + var dir_X = s_x - dex; + var dir_Y = s_y - dey; + + var len = Math.sqrt(dir_X * dir_X + dir_Y * dir_Y); + + var nX = dir_X / len; + var nY = dir_Y / len; + + + ShadowClone.e_x = dex + nX * ShadowClone.parent.domain().actualRadius(); + ShadowClone.e_y = dey + nY * ShadowClone.parent.domain().actualRadius(); + + + ShadowClone.updateElement(); + + + }; + + + /** MOUSE HANDLING FUNCTIONS ------------------------------------------------- **/ + + return ShadowClone; + }; + + + + +/***/ }), +/* 72 */ +/***/ (function(module, exports) { + + module.exports = function ( graph ){ + /** variable defs **/ + var prefixRepresentationModule = {}; + + var currentPrefixModel; + + prefixRepresentationModule.updatePrefixModel = function (){ + currentPrefixModel = graph.options().prefixList(); + }; + + + prefixRepresentationModule.validURL = function ( url ){ + return validURL(url); + }; + function validURL( str ){ + var urlregex = /^(https?|ftp):\/\/([a-zA-Z0-9.-]+(:[a-zA-Z0-9.&%$-]+)*@)*((25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9][0-9]?)(\.(25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9]?[0-9])){3}|([a-zA-Z0-9-]+\.)*[a-zA-Z0-9-]+\.(com|edu|gov|int|mil|net|org|biz|arpa|info|name|pro|aero|coop|museum|[a-zA-Z]{2}))(:[0-9]+)*(\/($|[a-zA-Z0-9.,?'\\+&%$#=~_-]+))*$/; + return urlregex.test(str); + } + + function splitURLIntoBaseAndResource( fullURL ){ + var splitedURL = { base: "", resource: "" }; + if ( fullURL === undefined ) { + splitedURL = { base: "ERROR", resource: "NOT FOUND" }; + return splitedURL; + } + + var resource, base; + // check if there is a last hashTag + if ( fullURL.indexOf("#") > -1 ) { + resource = fullURL.substring(fullURL.lastIndexOf('#') + 1); + base = fullURL.substring(0, fullURL.length - resource.length); + // overwrite base if it is ontologyIri; + if ( base === graph.options().getGeneralMetaObjectProperty('iri') ) { + base = ":"; + } + splitedURL.base = base; + splitedURL.resource = resource; + } else { + resource = fullURL.substring(fullURL.lastIndexOf('/') + 1); + base = fullURL.substring(0, fullURL.length - resource.length); + // overwrite base if it is ontologyIri; + if ( base === graph.options().getGeneralMetaObjectProperty('iri') ) { + base = ":"; + } + splitedURL.base = base; + splitedURL.resource = resource; + } + return splitedURL; + } + + prefixRepresentationModule.getPrefixRepresentationForFullURI = function ( fullURL ){ + prefixRepresentationModule.updatePrefixModel(); + var splittedURL = splitURLIntoBaseAndResource(fullURL); + + // lazy approach , for + // loop over prefix model + for ( var name in currentPrefixModel ) { + if ( currentPrefixModel.hasOwnProperty(name) ) { + // THIS IS CASE SENSITIVE! + if ( currentPrefixModel[name] === splittedURL.base ) { + return name + ":" + splittedURL.resource; + } + } + } + + if ( splittedURL.base === ":" ) { + return ":" + splittedURL.resource; + } + + return fullURL; + }; + + + return prefixRepresentationModule; + }; + + + + +/***/ }), +/* 73 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var _ = __webpack_require__(58); + + module.exports = function (){ + + var DEFAULT_STATE = true; + var COLOR_MODES = [ + { type: "same", range: [d3.rgb("#36C"), d3.rgb("#36C")] }, + { type: "gradient", range: [d3.rgb("#36C"), d3.rgb("#EE2867")] } // taken from LD-VOWL + ]; + + var filter = {}, + nodes, + properties, + enabled = DEFAULT_STATE, + filteredNodes, + filteredProperties, + colorModeType = "same"; + + + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + + var externalElements = filterExternalElements(nodes.concat(properties)); + + if ( enabled ) { + setColorsForExternals(externalElements); + } else { + resetBackgroundColors(externalElements); + } + + filteredNodes = nodes; + filteredProperties = properties; + }; + + function filterExternalElements( elements ){ + return elements.filter(function ( element ){ + if ( element.visualAttributes().indexOf("deprecated") >= 0 ) { + // deprecated is the only attribute which has preference over external + return false; + } + + return element.attributes().indexOf("external") >= 0; + }); + } + + function setColorsForExternals( elements ){ + var iriMap = mapExternalsToBaseUri(elements); + var entries = iriMap.entries(); + + var colorScale = d3.scale.linear() + .domain([0, entries.length - 1]) + .range(_.find(COLOR_MODES, { type: colorModeType }).range) + .interpolate(d3.interpolateHsl); + + for ( var i = 0; i < entries.length; i++ ) { + var groupedElements = entries[i].value; + setBackgroundColorForElements(groupedElements, colorScale(i)); + } + } + + function mapExternalsToBaseUri( elements ){ + var map = d3.map(); + + elements.forEach(function ( element ){ + var baseIri = element.baseIri(); + + if ( !map.has(baseIri) ) { + map.set(baseIri, []); + } + map.get(baseIri).push(element); + }); + + return map; + } + + function setBackgroundColorForElements( elements, backgroundColor ){ + elements.forEach(function ( element ){ + element.backgroundColor(backgroundColor); + }); + } + + function resetBackgroundColors( elements ){ + console.log("Resetting color"); + elements.forEach(function ( element ){ + element.backgroundColor(null); + }); + } + + filter.colorModeType = function ( p ){ + if ( !arguments.length ) return colorModeType; + colorModeType = p; + return filter; + }; + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + filter.reset = function (){ + enabled = DEFAULT_STATE; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 74 */ +/***/ (function(module, exports) { + + /** + * This module abuses the filter function a bit like the statistics module. Nothing is filtered. + * + * @returns {{}} + */ + + + module.exports = function ( graph ){ + + var DEFAULT_STATE = false; + + var filter = {}, + nodes, + properties, + enabled = DEFAULT_STATE, + filteredNodes, + filteredProperties; + + + /** + * If enabled, redundant details won't be drawn anymore. + * @param untouchedNodes + * @param untouchedProperties + */ + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + graph.options().compactNotation(enabled); + filteredNodes = nodes; + filteredProperties = properties; + }; + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + filter.reset = function (){ + enabled = DEFAULT_STATE; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }), +/* 75 */ +/***/ (function(module, exports, __webpack_require__) { + + var elementTools = __webpack_require__(63)(); + var filterTools = __webpack_require__(76)(); + + module.exports = function (){ + + var filter = {}, + nodes, + properties, + enabled = false, + filteredNodes, + filteredProperties; + + + /** + * If enabled, all datatypes and literals including connected properties are filtered. + * @param untouchedNodes + * @param untouchedProperties + */ + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + + if ( this.enabled() ) { + removeDatatypesAndLiterals(); + } + + filteredNodes = nodes; + filteredProperties = properties; + }; + + function removeDatatypesAndLiterals(){ + var filteredData = filterTools.filterNodesAndTidy(nodes, properties, isNoDatatypeOrLiteral); + + nodes = filteredData.nodes; + properties = filteredData.properties; + } + + function isNoDatatypeOrLiteral( node ){ + return !elementTools.isDatatype(node); + } + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }), +/* 76 */ +/***/ (function(module, exports, __webpack_require__) { + + var elementTools = __webpack_require__(63)(); + + module.exports = (function (){ + + var tools = {}; + + /** + * Filters the passed nodes and removes dangling properties. + * @param nodes + * @param properties + * @param shouldKeepNode function that returns true if the node should be kept + * @returns {{nodes: Array, properties: Array}} the filtered nodes and properties + */ + tools.filterNodesAndTidy = function ( nodes, properties, shouldKeepNode ){ + var removedNodes = __webpack_require__(62)(), + cleanedNodes = [], + cleanedProperties = []; + + nodes.forEach(function ( node ){ + if ( shouldKeepNode(node) ) { + cleanedNodes.push(node); + } else { + removedNodes.add(node); + } + }); + + properties.forEach(function ( property ){ + if ( propertyHasVisibleNodes(removedNodes, property) ) { + cleanedProperties.push(property); + } else if ( elementTools.isDatatypeProperty(property) ) { + // Remove floating datatypes/literals, because they belong to their datatype property + var index = cleanedNodes.indexOf(property.range()); + if ( index >= 0 ) { + cleanedNodes.splice(index, 1); + } + } + }); + + return { + nodes: cleanedNodes, + properties: cleanedProperties + }; + }; + + /** + * Returns true, if the domain and the range of this property have not been removed. + * @param removedNodes + * @param property + * @returns {boolean} true if property isn't dangling + */ + function propertyHasVisibleNodes( removedNodes, property ){ + return !removedNodes.has(property.domain()) && !removedNodes.has(property.range()); + } + + + return function (){ + return tools; + }; + })(); + + +/***/ }), +/* 77 */ +/***/ (function(module, exports, __webpack_require__) { + + var OwlDisjointWith = __webpack_require__(46); + + module.exports = function (){ + + var filter = {}, + nodes, + properties, + // According to the specification enabled by default + enabled = true, + filteredNodes, + filteredProperties; + + + /** + * If enabled, all disjoint with properties are filtered. + * @param untouchedNodes + * @param untouchedProperties + */ + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + + if ( this.enabled() ) { + removeDisjointWithProperties(); + } + + filteredNodes = nodes; + filteredProperties = properties; + }; + + function removeDisjointWithProperties(){ + var cleanedProperties = [], + i, l, property; + + for ( i = 0, l = properties.length; i < l; i++ ) { + property = properties[i]; + + if ( !(property instanceof OwlDisjointWith) ) { + cleanedProperties.push(property); + } + } + + properties = cleanedProperties; + } + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }), +/* 78 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( graph ){ + var focuser = {}, + focusedElement; + var elementTools = webvowl.util.elementTools(); + focuser.handle = function ( selectedElement, forced ){ + // Don't display details on a drag event, which will be prevented + if ( d3.event && d3.event.defaultPrevented && forced === undefined ) { + return; + } + + if ( focusedElement !== undefined ) { + focusedElement.toggleFocus(); + } + + if ( focusedElement !== selectedElement && selectedElement ) { + selectedElement.toggleFocus(); + focusedElement = selectedElement; + } else { + focusedElement = undefined; + } + if ( focusedElement && focusedElement.focused() ) { + graph.options().editSidebar().updateSelectionInformation(focusedElement); + if ( elementTools.isProperty(selectedElement) === true ) { + var inversed = false; + if ( selectedElement.inverse() ) { + inversed = true; + } + graph.activateHoverElementsForProperties(true, selectedElement, inversed, graph.isTouchDevice()); + } + else { + graph.activateHoverElements(true, selectedElement, graph.isTouchDevice()); + } + } + else { + graph.options().editSidebar().updateSelectionInformation(undefined); + graph.removeEditElements(); + } + }; + + /** + * Removes the focus if an element is focussed. + */ + focuser.reset = function (){ + if ( focusedElement ) { + focusedElement.toggleFocus(); + focusedElement = undefined; + } + }; + + return focuser; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 79 */ +/***/ (function(module, exports) { + + /** @WORKAROUND CODE: + * clears empty literals that are provided by owl2vowl: 0.2.2x*/ + + + module.exports = function (){ + + var filter = {}, + enabled = true, + filteredNodes, + removedNodes, + filteredProperties; + + filter.enabled = function ( val ){ + if ( !arguments.length ) { + return enabled; + } + enabled = val; + }; + + filter.filter = function ( nodes, properties ){ + if ( enabled === false ) { + filteredNodes = nodes; + filteredProperties = properties; + removedNodes = []; + return; + } + var literalUsageMap = []; + var thingUsageMap = []; + var node; + for ( var i = 0; i < properties.length; i++ ) { + // get property range; + var prop = properties[i]; + + // checking for literals + if ( prop.range() ) { + node = prop.range(); + if ( node.type() === "rdfs:Literal" ) { + literalUsageMap[node.id()] = 1; + } + } + // checking for thing + if ( prop.range() ) { + node = prop.range(); + if ( node.type() === "owl:Thing" ) { + thingUsageMap[node.id()] = 1; + } + } + if ( prop.domain() ) { + node = prop.domain(); + if ( node.type() === "owl:Thing" ) { + thingUsageMap[node.id()] = 1; + } + } + + } + var nodesToRemove = []; + var newNodes = []; + // todo: test and make it faster + for ( i = 0; i < nodes.length; i++ ) { + var nodeId = nodes[i].id(); + if ( nodes[i].type() === "rdfs:Literal" ) { + if ( literalUsageMap[nodeId] === undefined ) { + nodesToRemove.push(nodeId); + } + else { + newNodes.push(nodes[i]); + } + // check for node type == OWL:THING + } else if ( nodes[i].type() === "owl:Thing" ) { + if ( thingUsageMap[nodeId] === undefined ) { + nodesToRemove.push(nodeId); + } + else { + newNodes.push(nodes[i]); + } + } else { + newNodes.push(nodes[i]); + } + } + + filteredNodes = newNodes; + filteredProperties = properties; + removedNodes = nodesToRemove; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.removedNodes = function (){ + return removedNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }), +/* 80 */ +/***/ (function(module, exports, __webpack_require__) { + + var elementTools = __webpack_require__(63)(); + var filterTools = __webpack_require__(76)(); + + module.exports = function ( menu ){ + + var filter = {}, + nodes, + properties, + enabled = true, + filteredNodes, + filteredProperties, + maxDegreeSetter, + degreeGetter, + lastFiltedDegree, + degreeSetter; + + + var NODE_COUNT_LIMIT_FOR_AUTO_ENABLING = 50; + + + filter.initialize = function ( nodes, properties ){ + lastFiltedDegree = -1; + var maxLinkCount = findMaxLinkCount(nodes); + if ( maxDegreeSetter instanceof Function ) { + maxDegreeSetter(maxLinkCount); + } + + menu.setDefaultDegreeValue(findAutoDefaultDegree(nodes, properties, maxLinkCount)); + var defaultDegree = findDefaultDegree(maxLinkCount); + if ( degreeSetter instanceof Function ) { + degreeSetter(defaultDegree); + if ( defaultDegree > 0 ) { + menu.highlightForDegreeSlider(true); + menu.getGraphObject().setFilterWarning(true); + + } + } else { + console.error("No degree setter function set."); + } + }; + + function findAutoDefaultDegree( nodes, properties, maxDegree ){ + for ( var degree = 0; degree < maxDegree; degree++ ) { + var filteredData = filterByNodeDegree(nodes, properties, degree); + + if ( filteredData.nodes.length <= NODE_COUNT_LIMIT_FOR_AUTO_ENABLING ) { + return degree; + } + } + return 0; + } + + function findDefaultDegree( maxDegree ){ + var globalDegOfFilter = menu.getGraphObject().getGlobalDOF(); + if ( globalDegOfFilter >= 0 ) { + if ( globalDegOfFilter <= maxDegree ) { + return globalDegOfFilter; + } else { + menu.getGraphObject().setGlobalDOF(maxDegree); + return maxDegree; + } + } + return menu.getDefaultDegreeValue(); + } + + /** + * If enabled, all nodes are filter by their node degree. + * @param untouchedNodes + * @param untouchedProperties + */ + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + + if ( this.enabled() ) { + if ( degreeGetter instanceof Function ) { + filterByNodeDegreeAndApply(degreeGetter()); + } else { + console.error("No degree query function set."); + } + } + + filteredNodes = nodes; + filteredProperties = properties; + + if ( filteredNodes.length === 0 ) { + degreeSetter(0); + filteredNodes = untouchedNodes; + filteredProperties = untouchedProperties; + } + lastFiltedDegree = degreeGetter(); + }; + + function findMaxLinkCount( nodes ){ + var maxLinkCount = 0; + for ( var i = 0, l = nodes.length; i < l; i++ ) { + var linksWithoutDatatypes = filterOutDatatypes(nodes[i].links()); + + maxLinkCount = Math.max(maxLinkCount, linksWithoutDatatypes.length); + } + return maxLinkCount; + } + + function filterOutDatatypes( links ){ + return links.filter(function ( link ){ + return !elementTools.isDatatypeProperty(link.property()); + }); + } + + function filterByNodeDegreeAndApply( minDegree ){ + var filteredData = filterByNodeDegree(nodes, properties, minDegree); + nodes = filteredData.nodes; + properties = filteredData.properties; + } + + function filterByNodeDegree( nodes, properties, minDegree ){ + return filterTools.filterNodesAndTidy(nodes, properties, hasRequiredDegree(minDegree)); + } + + function hasRequiredDegree( minDegree ){ + return function ( node ){ + return filterOutDatatypes(node.links()).length >= minDegree; + }; + } + + filter.setMaxDegreeSetter = function ( _maxDegreeSetter ){ + maxDegreeSetter = _maxDegreeSetter; + }; + + filter.setDegreeGetter = function ( _degreeGetter ){ + degreeGetter = _degreeGetter; + }; + + filter.setDegreeSetter = function ( _degreeSetter ){ + degreeSetter = _degreeSetter; + }; + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }), +/* 81 */ +/***/ (function(module, exports) { + + /** + * This module abuses the filter function a bit like the statistics module. Nothing is filtered. + * + * @returns {{}} + */ + module.exports = function ( graph ){ + + var DEFAULT_STATE = true; + + var filter = {}, + nodes, + properties, + enabled = DEFAULT_STATE, + filteredNodes, + filteredProperties; + + + /** + * If enabled, the scaling of nodes according to individuals will be enabled. + * @param untouchedNodes + * @param untouchedProperties + */ + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + + graph.options().scaleNodesByIndividuals(enabled); + + filteredNodes = nodes; + filteredProperties = properties; + }; + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + filter.reset = function (){ + enabled = DEFAULT_STATE; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }), +/* 82 */ +/***/ (function(module, exports, __webpack_require__) { + + var elementTools = __webpack_require__(63)(); + + + module.exports = function (){ + + var filter = {}, + nodes, + properties, + enabled = false, + filteredNodes, + filteredProperties; + + + /** + * If enabled, all object properties and things without any other property are filtered. + * @param untouchedNodes + * @param untouchedProperties + */ + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + + if ( this.enabled() ) { + removeObjectProperties(); + } + + filteredNodes = nodes; + filteredProperties = properties; + }; + + function removeObjectProperties(){ + properties = properties.filter(isNoObjectProperty); + nodes = nodes.filter(isNoFloatingThing); + } + + function isNoObjectProperty( property ){ + return !elementTools.isObjectProperty(property); + } + + function isNoFloatingThing( node ){ + var isNoThing = !elementTools.isThing(node); + var hasNonFilteredProperties = hasPropertiesOtherThanObjectProperties(node, properties); + return isNoThing || hasNonFilteredProperties; + } + + function hasPropertiesOtherThanObjectProperties( node, properties ){ + for ( var i = 0; i < properties.length; i++ ) { + var property = properties[i]; + if ( property.domain() !== node && property.range() !== node ) { + continue; + } + + if ( isNoObjectProperty(property) ) { + return true; + } + } + + return false; + } + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }), +/* 83 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var _ = __webpack_require__(84); + var elementTools = __webpack_require__(63)(); + + module.exports = function (){ + var pap = {}, + enabled = false, + pinnedElements = []; + + pap.addPinnedElement = function ( element ){ + // check if element is already in list + var indexInArray = pinnedElements.indexOf(element); + if ( indexInArray === -1 ) { + pinnedElements.push(element); + } + }; + + pap.handle = function ( selection, forced ){ + if ( !enabled ) { + return; + } + + if ( !forced ) { + if ( wasNotDragged() ) { + return; + } + } + if ( elementTools.isProperty(selection) ) { + if ( selection.inverse() && selection.inverse().pinned() ) { + return; + } else if ( hasNoParallelProperties(selection) ) { + return; + } + } + + if ( !selection.pinned() ) { + selection.drawPin(); + pap.addPinnedElement(selection); + } + }; + + function wasNotDragged(){ + return !d3.event.defaultPrevented; + } + + function hasNoParallelProperties( property ){ + return _.intersection(property.domain().links(), property.range().links()).length === 1; + } + + pap.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return pap; + }; + + pap.reset = function (){ + pinnedElements.forEach(function ( element ){ + element.removePin(); + }); + // Clear the array of stored nodes + pinnedElements.length = 0; + }; + + return pap; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 84 */ +/***/ (function(module, exports, __webpack_require__) { + + module.exports = { + 'chunk': __webpack_require__(85), + 'compact': __webpack_require__(105), + 'concat': __webpack_require__(106), + 'difference': __webpack_require__(114), + 'differenceBy': __webpack_require__(167), + 'differenceWith': __webpack_require__(229), + 'drop': __webpack_require__(230), + 'dropRight': __webpack_require__(231), + 'dropRightWhile': __webpack_require__(232), + 'dropWhile': __webpack_require__(234), + 'fill': __webpack_require__(235), + 'findIndex': __webpack_require__(239), + 'findLastIndex': __webpack_require__(240), + 'first': __webpack_require__(241), + 'flatten': __webpack_require__(243), + 'flattenDeep': __webpack_require__(244), + 'flattenDepth': __webpack_require__(245), + 'fromPairs': __webpack_require__(246), + 'head': __webpack_require__(242), + 'indexOf': __webpack_require__(247), + 'initial': __webpack_require__(248), + 'intersection': __webpack_require__(249), + 'intersectionBy': __webpack_require__(252), + 'intersectionWith': __webpack_require__(253), + 'join': __webpack_require__(254), + 'last': __webpack_require__(228), + 'lastIndexOf': __webpack_require__(255), + 'nth': __webpack_require__(257), + 'pull': __webpack_require__(259), + 'pullAll': __webpack_require__(260), + 'pullAllBy': __webpack_require__(263), + 'pullAllWith': __webpack_require__(264), + 'pullAt': __webpack_require__(265), + 'remove': __webpack_require__(272), + 'reverse': __webpack_require__(273), + 'slice': __webpack_require__(274), + 'sortedIndex': __webpack_require__(275), + 'sortedIndexBy': __webpack_require__(278), + 'sortedIndexOf': __webpack_require__(279), + 'sortedLastIndex': __webpack_require__(280), + 'sortedLastIndexBy': __webpack_require__(281), + 'sortedLastIndexOf': __webpack_require__(282), + 'sortedUniq': __webpack_require__(283), + 'sortedUniqBy': __webpack_require__(285), + 'tail': __webpack_require__(286), + 'take': __webpack_require__(287), + 'takeRight': __webpack_require__(288), + 'takeRightWhile': __webpack_require__(289), + 'takeWhile': __webpack_require__(290), + 'union': __webpack_require__(291), + 'unionBy': __webpack_require__(295), + 'unionWith': __webpack_require__(296), + 'uniq': __webpack_require__(297), + 'uniqBy': __webpack_require__(298), + 'uniqWith': __webpack_require__(299), + 'unzip': __webpack_require__(300), + 'unzipWith': __webpack_require__(301), + 'without': __webpack_require__(302), + 'xor': __webpack_require__(303), + 'xorBy': __webpack_require__(305), + 'xorWith': __webpack_require__(306), + 'zip': __webpack_require__(307), + 'zipObject': __webpack_require__(308), + 'zipObjectDeep': __webpack_require__(312), + 'zipWith': __webpack_require__(314) + }; + + +/***/ }), +/* 85 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86), + isIterateeCall = __webpack_require__(87), + toInteger = __webpack_require__(100); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeCeil = Math.ceil, + nativeMax = Math.max; + + /** + * Creates an array of elements split into groups the length of `size`. + * If `array` can't be split evenly, the final chunk will be the remaining + * elements. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to process. + * @param {number} [size=1] The length of each chunk + * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. + * @returns {Array} Returns the new array of chunks. + * @example + * + * _.chunk(['a', 'b', 'c', 'd'], 2); + * // => [['a', 'b'], ['c', 'd']] + * + * _.chunk(['a', 'b', 'c', 'd'], 3); + * // => [['a', 'b', 'c'], ['d']] + */ + function chunk(array, size, guard) { + if ((guard ? isIterateeCall(array, size, guard) : size === undefined)) { + size = 1; + } else { + size = nativeMax(toInteger(size), 0); + } + var length = array == null ? 0 : array.length; + if (!length || size < 1) { + return []; + } + var index = 0, + resIndex = 0, + result = Array(nativeCeil(length / size)); + + while (index < length) { + result[resIndex++] = baseSlice(array, index, (index += size)); + } + return result; + } + + module.exports = chunk; + + +/***/ }), +/* 86 */ +/***/ (function(module, exports) { + + /** + * The base implementation of `_.slice` without an iteratee call guard. + * + * @private + * @param {Array} array The array to slice. + * @param {number} [start=0] The start position. + * @param {number} [end=array.length] The end position. + * @returns {Array} Returns the slice of `array`. + */ + function baseSlice(array, start, end) { + var index = -1, + length = array.length; + + if (start < 0) { + start = -start > length ? 0 : (length + start); + } + end = end > length ? length : end; + if (end < 0) { + end += length; + } + length = start > end ? 0 : ((end - start) >>> 0); + start >>>= 0; + + var result = Array(length); + while (++index < length) { + result[index] = array[index + start]; + } + return result; + } + + module.exports = baseSlice; + + +/***/ }), +/* 87 */ +/***/ (function(module, exports, __webpack_require__) { + + var eq = __webpack_require__(88), + isArrayLike = __webpack_require__(89), + isIndex = __webpack_require__(99), + isObject = __webpack_require__(97); + + /** + * Checks if the given arguments are from an iteratee call. + * + * @private + * @param {*} value The potential iteratee value argument. + * @param {*} index The potential iteratee index or key argument. + * @param {*} object The potential iteratee object argument. + * @returns {boolean} Returns `true` if the arguments are from an iteratee call, + * else `false`. + */ + function isIterateeCall(value, index, object) { + if (!isObject(object)) { + return false; + } + var type = typeof index; + if (type == 'number' + ? (isArrayLike(object) && isIndex(index, object.length)) + : (type == 'string' && index in object) + ) { + return eq(object[index], value); + } + return false; + } + + module.exports = isIterateeCall; + + +/***/ }), +/* 88 */ +/***/ (function(module, exports) { + + /** + * Performs a + * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * comparison between two values to determine if they are equivalent. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @returns {boolean} Returns `true` if the values are equivalent, else `false`. + * @example + * + * var object = { 'a': 1 }; + * var other = { 'a': 1 }; + * + * _.eq(object, object); + * // => true + * + * _.eq(object, other); + * // => false + * + * _.eq('a', 'a'); + * // => true + * + * _.eq('a', Object('a')); + * // => false + * + * _.eq(NaN, NaN); + * // => true + */ + function eq(value, other) { + return value === other || (value !== value && other !== other); + } + + module.exports = eq; + + +/***/ }), +/* 89 */ +/***/ (function(module, exports, __webpack_require__) { + + var isFunction = __webpack_require__(90), + isLength = __webpack_require__(98); + + /** + * Checks if `value` is array-like. A value is considered array-like if it's + * not a function and has a `value.length` that's an integer greater than or + * equal to `0` and less than or equal to `Number.MAX_SAFE_INTEGER`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is array-like, else `false`. + * @example + * + * _.isArrayLike([1, 2, 3]); + * // => true + * + * _.isArrayLike(document.body.children); + * // => true + * + * _.isArrayLike('abc'); + * // => true + * + * _.isArrayLike(_.noop); + * // => false + */ + function isArrayLike(value) { + return value != null && isLength(value.length) && !isFunction(value); + } + + module.exports = isArrayLike; + + +/***/ }), +/* 90 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseGetTag = __webpack_require__(91), + isObject = __webpack_require__(97); + + /** `Object#toString` result references. */ + var asyncTag = '[object AsyncFunction]', + funcTag = '[object Function]', + genTag = '[object GeneratorFunction]', + proxyTag = '[object Proxy]'; + + /** + * Checks if `value` is classified as a `Function` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a function, else `false`. + * @example + * + * _.isFunction(_); + * // => true + * + * _.isFunction(/abc/); + * // => false + */ + function isFunction(value) { + if (!isObject(value)) { + return false; + } + // The use of `Object#toString` avoids issues with the `typeof` operator + // in Safari 9 which returns 'object' for typed arrays and other constructors. + var tag = baseGetTag(value); + return tag == funcTag || tag == genTag || tag == asyncTag || tag == proxyTag; + } + + module.exports = isFunction; + + +/***/ }), +/* 91 */ +/***/ (function(module, exports, __webpack_require__) { + + var Symbol = __webpack_require__(92), + getRawTag = __webpack_require__(95), + objectToString = __webpack_require__(96); + + /** `Object#toString` result references. */ + var nullTag = '[object Null]', + undefinedTag = '[object Undefined]'; + + /** Built-in value references. */ + var symToStringTag = Symbol ? Symbol.toStringTag : undefined; + + /** + * The base implementation of `getTag` without fallbacks for buggy environments. + * + * @private + * @param {*} value The value to query. + * @returns {string} Returns the `toStringTag`. + */ + function baseGetTag(value) { + if (value == null) { + return value === undefined ? undefinedTag : nullTag; + } + return (symToStringTag && symToStringTag in Object(value)) + ? getRawTag(value) + : objectToString(value); + } + + module.exports = baseGetTag; + + +/***/ }), +/* 92 */ +/***/ (function(module, exports, __webpack_require__) { + + var root = __webpack_require__(93); + + /** Built-in value references. */ + var Symbol = root.Symbol; + + module.exports = Symbol; + + +/***/ }), +/* 93 */ +/***/ (function(module, exports, __webpack_require__) { + + var freeGlobal = __webpack_require__(94); + + /** Detect free variable `self`. */ + var freeSelf = typeof self == 'object' && self && self.Object === Object && self; + + /** Used as a reference to the global object. */ + var root = freeGlobal || freeSelf || Function('return this')(); + + module.exports = root; + + +/***/ }), +/* 94 */ +/***/ (function(module, exports) { + + /* WEBPACK VAR INJECTION */(function(global) {/** Detect free variable `global` from Node.js. */ + var freeGlobal = typeof global == 'object' && global && global.Object === Object && global; + + module.exports = freeGlobal; + + /* WEBPACK VAR INJECTION */}.call(exports, (function() { return this; }()))) + +/***/ }), +/* 95 */ +/***/ (function(module, exports, __webpack_require__) { + + var Symbol = __webpack_require__(92); + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * Used to resolve the + * [`toStringTag`](http://ecma-international.org/ecma-262/7.0/#sec-object.prototype.tostring) + * of values. + */ + var nativeObjectToString = objectProto.toString; + + /** Built-in value references. */ + var symToStringTag = Symbol ? Symbol.toStringTag : undefined; + + /** + * A specialized version of `baseGetTag` which ignores `Symbol.toStringTag` values. + * + * @private + * @param {*} value The value to query. + * @returns {string} Returns the raw `toStringTag`. + */ + function getRawTag(value) { + var isOwn = hasOwnProperty.call(value, symToStringTag), + tag = value[symToStringTag]; + + try { + value[symToStringTag] = undefined; + var unmasked = true; + } catch (e) {} + + var result = nativeObjectToString.call(value); + if (unmasked) { + if (isOwn) { + value[symToStringTag] = tag; + } else { + delete value[symToStringTag]; + } + } + return result; + } + + module.exports = getRawTag; + + +/***/ }), +/* 96 */ +/***/ (function(module, exports) { + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** + * Used to resolve the + * [`toStringTag`](http://ecma-international.org/ecma-262/7.0/#sec-object.prototype.tostring) + * of values. + */ + var nativeObjectToString = objectProto.toString; + + /** + * Converts `value` to a string using `Object.prototype.toString`. + * + * @private + * @param {*} value The value to convert. + * @returns {string} Returns the converted string. + */ + function objectToString(value) { + return nativeObjectToString.call(value); + } + + module.exports = objectToString; + + +/***/ }), +/* 97 */ +/***/ (function(module, exports) { + + /** + * Checks if `value` is the + * [language type](http://www.ecma-international.org/ecma-262/7.0/#sec-ecmascript-language-types) + * of `Object`. (e.g. arrays, functions, objects, regexes, `new Number(0)`, and `new String('')`) + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an object, else `false`. + * @example + * + * _.isObject({}); + * // => true + * + * _.isObject([1, 2, 3]); + * // => true + * + * _.isObject(_.noop); + * // => true + * + * _.isObject(null); + * // => false + */ + function isObject(value) { + var type = typeof value; + return value != null && (type == 'object' || type == 'function'); + } + + module.exports = isObject; + + +/***/ }), +/* 98 */ +/***/ (function(module, exports) { + + /** Used as references for various `Number` constants. */ + var MAX_SAFE_INTEGER = 9007199254740991; + + /** + * Checks if `value` is a valid array-like length. + * + * **Note:** This method is loosely based on + * [`ToLength`](http://ecma-international.org/ecma-262/7.0/#sec-tolength). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a valid length, else `false`. + * @example + * + * _.isLength(3); + * // => true + * + * _.isLength(Number.MIN_VALUE); + * // => false + * + * _.isLength(Infinity); + * // => false + * + * _.isLength('3'); + * // => false + */ + function isLength(value) { + return typeof value == 'number' && + value > -1 && value % 1 == 0 && value <= MAX_SAFE_INTEGER; + } + + module.exports = isLength; + + +/***/ }), +/* 99 */ +/***/ (function(module, exports) { + + /** Used as references for various `Number` constants. */ + var MAX_SAFE_INTEGER = 9007199254740991; + + /** Used to detect unsigned integer values. */ + var reIsUint = /^(?:0|[1-9]\d*)$/; + + /** + * Checks if `value` is a valid array-like index. + * + * @private + * @param {*} value The value to check. + * @param {number} [length=MAX_SAFE_INTEGER] The upper bounds of a valid index. + * @returns {boolean} Returns `true` if `value` is a valid index, else `false`. + */ + function isIndex(value, length) { + var type = typeof value; + length = length == null ? MAX_SAFE_INTEGER : length; + + return !!length && + (type == 'number' || + (type != 'symbol' && reIsUint.test(value))) && + (value > -1 && value % 1 == 0 && value < length); + } + + module.exports = isIndex; + + +/***/ }), +/* 100 */ +/***/ (function(module, exports, __webpack_require__) { + + var toFinite = __webpack_require__(101); + + /** + * Converts `value` to an integer. + * + * **Note:** This method is loosely based on + * [`ToInteger`](http://www.ecma-international.org/ecma-262/7.0/#sec-tointeger). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to convert. + * @returns {number} Returns the converted integer. + * @example + * + * _.toInteger(3.2); + * // => 3 + * + * _.toInteger(Number.MIN_VALUE); + * // => 0 + * + * _.toInteger(Infinity); + * // => 1.7976931348623157e+308 + * + * _.toInteger('3.2'); + * // => 3 + */ + function toInteger(value) { + var result = toFinite(value), + remainder = result % 1; + + return result === result ? (remainder ? result - remainder : result) : 0; + } + + module.exports = toInteger; + + +/***/ }), +/* 101 */ +/***/ (function(module, exports, __webpack_require__) { + + var toNumber = __webpack_require__(102); + + /** Used as references for various `Number` constants. */ + var INFINITY = 1 / 0, + MAX_INTEGER = 1.7976931348623157e+308; + + /** + * Converts `value` to a finite number. + * + * @static + * @memberOf _ + * @since 4.12.0 + * @category Lang + * @param {*} value The value to convert. + * @returns {number} Returns the converted number. + * @example + * + * _.toFinite(3.2); + * // => 3.2 + * + * _.toFinite(Number.MIN_VALUE); + * // => 5e-324 + * + * _.toFinite(Infinity); + * // => 1.7976931348623157e+308 + * + * _.toFinite('3.2'); + * // => 3.2 + */ + function toFinite(value) { + if (!value) { + return value === 0 ? value : 0; + } + value = toNumber(value); + if (value === INFINITY || value === -INFINITY) { + var sign = (value < 0 ? -1 : 1); + return sign * MAX_INTEGER; + } + return value === value ? value : 0; + } + + module.exports = toFinite; + + +/***/ }), +/* 102 */ +/***/ (function(module, exports, __webpack_require__) { + + var isObject = __webpack_require__(97), + isSymbol = __webpack_require__(103); + + /** Used as references for various `Number` constants. */ + var NAN = 0 / 0; + + /** Used to match leading and trailing whitespace. */ + var reTrim = /^\s+|\s+$/g; + + /** Used to detect bad signed hexadecimal string values. */ + var reIsBadHex = /^[-+]0x[0-9a-f]+$/i; + + /** Used to detect binary string values. */ + var reIsBinary = /^0b[01]+$/i; + + /** Used to detect octal string values. */ + var reIsOctal = /^0o[0-7]+$/i; + + /** Built-in method references without a dependency on `root`. */ + var freeParseInt = parseInt; + + /** + * Converts `value` to a number. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to process. + * @returns {number} Returns the number. + * @example + * + * _.toNumber(3.2); + * // => 3.2 + * + * _.toNumber(Number.MIN_VALUE); + * // => 5e-324 + * + * _.toNumber(Infinity); + * // => Infinity + * + * _.toNumber('3.2'); + * // => 3.2 + */ + function toNumber(value) { + if (typeof value == 'number') { + return value; + } + if (isSymbol(value)) { + return NAN; + } + if (isObject(value)) { + var other = typeof value.valueOf == 'function' ? value.valueOf() : value; + value = isObject(other) ? (other + '') : other; + } + if (typeof value != 'string') { + return value === 0 ? value : +value; + } + value = value.replace(reTrim, ''); + var isBinary = reIsBinary.test(value); + return (isBinary || reIsOctal.test(value)) + ? freeParseInt(value.slice(2), isBinary ? 2 : 8) + : (reIsBadHex.test(value) ? NAN : +value); + } + + module.exports = toNumber; + + +/***/ }), +/* 103 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseGetTag = __webpack_require__(91), + isObjectLike = __webpack_require__(104); + + /** `Object#toString` result references. */ + var symbolTag = '[object Symbol]'; + + /** + * Checks if `value` is classified as a `Symbol` primitive or object. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a symbol, else `false`. + * @example + * + * _.isSymbol(Symbol.iterator); + * // => true + * + * _.isSymbol('abc'); + * // => false + */ + function isSymbol(value) { + return typeof value == 'symbol' || + (isObjectLike(value) && baseGetTag(value) == symbolTag); + } + + module.exports = isSymbol; + + +/***/ }), +/* 104 */ +/***/ (function(module, exports) { + + /** + * Checks if `value` is object-like. A value is object-like if it's not `null` + * and has a `typeof` result of "object". + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is object-like, else `false`. + * @example + * + * _.isObjectLike({}); + * // => true + * + * _.isObjectLike([1, 2, 3]); + * // => true + * + * _.isObjectLike(_.noop); + * // => false + * + * _.isObjectLike(null); + * // => false + */ + function isObjectLike(value) { + return value != null && typeof value == 'object'; + } + + module.exports = isObjectLike; + + +/***/ }), +/* 105 */ +/***/ (function(module, exports) { + + /** + * Creates an array with all falsey values removed. The values `false`, `null`, + * `0`, `""`, `undefined`, and `NaN` are falsey. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to compact. + * @returns {Array} Returns the new array of filtered values. + * @example + * + * _.compact([0, 1, false, 2, '', 3]); + * // => [1, 2, 3] + */ + function compact(array) { + var index = -1, + length = array == null ? 0 : array.length, + resIndex = 0, + result = []; + + while (++index < length) { + var value = array[index]; + if (value) { + result[resIndex++] = value; + } + } + return result; + } + + module.exports = compact; + + +/***/ }), +/* 106 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayPush = __webpack_require__(107), + baseFlatten = __webpack_require__(108), + copyArray = __webpack_require__(113), + isArray = __webpack_require__(112); + + /** + * Creates a new array concatenating `array` with any additional arrays + * and/or values. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to concatenate. + * @param {...*} [values] The values to concatenate. + * @returns {Array} Returns the new concatenated array. + * @example + * + * var array = [1]; + * var other = _.concat(array, 2, [3], [[4]]); + * + * console.log(other); + * // => [1, 2, 3, [4]] + * + * console.log(array); + * // => [1] + */ + function concat() { + var length = arguments.length; + if (!length) { + return []; + } + var args = Array(length - 1), + array = arguments[0], + index = length; + + while (index--) { + args[index - 1] = arguments[index]; + } + return arrayPush(isArray(array) ? copyArray(array) : [array], baseFlatten(args, 1)); + } + + module.exports = concat; + + +/***/ }), +/* 107 */ +/***/ (function(module, exports) { + + /** + * Appends the elements of `values` to `array`. + * + * @private + * @param {Array} array The array to modify. + * @param {Array} values The values to append. + * @returns {Array} Returns `array`. + */ + function arrayPush(array, values) { + var index = -1, + length = values.length, + offset = array.length; + + while (++index < length) { + array[offset + index] = values[index]; + } + return array; + } + + module.exports = arrayPush; + + +/***/ }), +/* 108 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayPush = __webpack_require__(107), + isFlattenable = __webpack_require__(109); + + /** + * The base implementation of `_.flatten` with support for restricting flattening. + * + * @private + * @param {Array} array The array to flatten. + * @param {number} depth The maximum recursion depth. + * @param {boolean} [predicate=isFlattenable] The function invoked per iteration. + * @param {boolean} [isStrict] Restrict to values that pass `predicate` checks. + * @param {Array} [result=[]] The initial result value. + * @returns {Array} Returns the new flattened array. + */ + function baseFlatten(array, depth, predicate, isStrict, result) { + var index = -1, + length = array.length; + + predicate || (predicate = isFlattenable); + result || (result = []); + + while (++index < length) { + var value = array[index]; + if (depth > 0 && predicate(value)) { + if (depth > 1) { + // Recursively flatten arrays (susceptible to call stack limits). + baseFlatten(value, depth - 1, predicate, isStrict, result); + } else { + arrayPush(result, value); + } + } else if (!isStrict) { + result[result.length] = value; + } + } + return result; + } + + module.exports = baseFlatten; + + +/***/ }), +/* 109 */ +/***/ (function(module, exports, __webpack_require__) { + + var Symbol = __webpack_require__(92), + isArguments = __webpack_require__(110), + isArray = __webpack_require__(112); + + /** Built-in value references. */ + var spreadableSymbol = Symbol ? Symbol.isConcatSpreadable : undefined; + + /** + * Checks if `value` is a flattenable `arguments` object or array. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is flattenable, else `false`. + */ + function isFlattenable(value) { + return isArray(value) || isArguments(value) || + !!(spreadableSymbol && value && value[spreadableSymbol]); + } + + module.exports = isFlattenable; + + +/***/ }), +/* 110 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIsArguments = __webpack_require__(111), + isObjectLike = __webpack_require__(104); + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** Built-in value references. */ + var propertyIsEnumerable = objectProto.propertyIsEnumerable; + + /** + * Checks if `value` is likely an `arguments` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an `arguments` object, + * else `false`. + * @example + * + * _.isArguments(function() { return arguments; }()); + * // => true + * + * _.isArguments([1, 2, 3]); + * // => false + */ + var isArguments = baseIsArguments(function() { return arguments; }()) ? baseIsArguments : function(value) { + return isObjectLike(value) && hasOwnProperty.call(value, 'callee') && + !propertyIsEnumerable.call(value, 'callee'); + }; + + module.exports = isArguments; + + +/***/ }), +/* 111 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseGetTag = __webpack_require__(91), + isObjectLike = __webpack_require__(104); + + /** `Object#toString` result references. */ + var argsTag = '[object Arguments]'; + + /** + * The base implementation of `_.isArguments`. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an `arguments` object, + */ + function baseIsArguments(value) { + return isObjectLike(value) && baseGetTag(value) == argsTag; + } + + module.exports = baseIsArguments; + + +/***/ }), +/* 112 */ +/***/ (function(module, exports) { + + /** + * Checks if `value` is classified as an `Array` object. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an array, else `false`. + * @example + * + * _.isArray([1, 2, 3]); + * // => true + * + * _.isArray(document.body.children); + * // => false + * + * _.isArray('abc'); + * // => false + * + * _.isArray(_.noop); + * // => false + */ + var isArray = Array.isArray; + + module.exports = isArray; + + +/***/ }), +/* 113 */ +/***/ (function(module, exports) { + + /** + * Copies the values of `source` to `array`. + * + * @private + * @param {Array} source The array to copy values from. + * @param {Array} [array=[]] The array to copy values to. + * @returns {Array} Returns `array`. + */ + function copyArray(source, array) { + var index = -1, + length = source.length; + + array || (array = Array(length)); + while (++index < length) { + array[index] = source[index]; + } + return array; + } + + module.exports = copyArray; + + +/***/ }), +/* 114 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseDifference = __webpack_require__(115), + baseFlatten = __webpack_require__(108), + baseRest = __webpack_require__(157), + isArrayLikeObject = __webpack_require__(166); + + /** + * Creates an array of `array` values not included in the other given arrays + * using [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. The order and references of result values are + * determined by the first array. + * + * **Note:** Unlike `_.pullAll`, this method returns a new array. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {...Array} [values] The values to exclude. + * @returns {Array} Returns the new array of filtered values. + * @see _.without, _.xor + * @example + * + * _.difference([2, 1], [2, 3]); + * // => [1] + */ + var difference = baseRest(function(array, values) { + return isArrayLikeObject(array) + ? baseDifference(array, baseFlatten(values, 1, isArrayLikeObject, true)) + : []; + }); + + module.exports = difference; + + +/***/ }), +/* 115 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetCache = __webpack_require__(116), + arrayIncludes = __webpack_require__(148), + arrayIncludesWith = __webpack_require__(153), + arrayMap = __webpack_require__(154), + baseUnary = __webpack_require__(155), + cacheHas = __webpack_require__(156); + + /** Used as the size to enable large array optimizations. */ + var LARGE_ARRAY_SIZE = 200; + + /** + * The base implementation of methods like `_.difference` without support + * for excluding multiple arrays or iteratee shorthands. + * + * @private + * @param {Array} array The array to inspect. + * @param {Array} values The values to exclude. + * @param {Function} [iteratee] The iteratee invoked per element. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new array of filtered values. + */ + function baseDifference(array, values, iteratee, comparator) { + var index = -1, + includes = arrayIncludes, + isCommon = true, + length = array.length, + result = [], + valuesLength = values.length; + + if (!length) { + return result; + } + if (iteratee) { + values = arrayMap(values, baseUnary(iteratee)); + } + if (comparator) { + includes = arrayIncludesWith; + isCommon = false; + } + else if (values.length >= LARGE_ARRAY_SIZE) { + includes = cacheHas; + isCommon = false; + values = new SetCache(values); + } + outer: + while (++index < length) { + var value = array[index], + computed = iteratee == null ? value : iteratee(value); + + value = (comparator || value !== 0) ? value : 0; + if (isCommon && computed === computed) { + var valuesIndex = valuesLength; + while (valuesIndex--) { + if (values[valuesIndex] === computed) { + continue outer; + } + } + result.push(value); + } + else if (!includes(values, computed, comparator)) { + result.push(value); + } + } + return result; + } + + module.exports = baseDifference; + + +/***/ }), +/* 116 */ +/***/ (function(module, exports, __webpack_require__) { + + var MapCache = __webpack_require__(117), + setCacheAdd = __webpack_require__(146), + setCacheHas = __webpack_require__(147); + + /** + * + * Creates an array cache object to store unique values. + * + * @private + * @constructor + * @param {Array} [values] The values to cache. + */ + function SetCache(values) { + var index = -1, + length = values == null ? 0 : values.length; + + this.__data__ = new MapCache; + while (++index < length) { + this.add(values[index]); + } + } + + // Add methods to `SetCache`. + SetCache.prototype.add = SetCache.prototype.push = setCacheAdd; + SetCache.prototype.has = setCacheHas; + + module.exports = SetCache; + + +/***/ }), +/* 117 */ +/***/ (function(module, exports, __webpack_require__) { + + var mapCacheClear = __webpack_require__(118), + mapCacheDelete = __webpack_require__(140), + mapCacheGet = __webpack_require__(143), + mapCacheHas = __webpack_require__(144), + mapCacheSet = __webpack_require__(145); + + /** + * Creates a map cache object to store key-value pairs. + * + * @private + * @constructor + * @param {Array} [entries] The key-value pairs to cache. + */ + function MapCache(entries) { + var index = -1, + length = entries == null ? 0 : entries.length; + + this.clear(); + while (++index < length) { + var entry = entries[index]; + this.set(entry[0], entry[1]); + } + } + + // Add methods to `MapCache`. + MapCache.prototype.clear = mapCacheClear; + MapCache.prototype['delete'] = mapCacheDelete; + MapCache.prototype.get = mapCacheGet; + MapCache.prototype.has = mapCacheHas; + MapCache.prototype.set = mapCacheSet; + + module.exports = MapCache; + + +/***/ }), +/* 118 */ +/***/ (function(module, exports, __webpack_require__) { + + var Hash = __webpack_require__(119), + ListCache = __webpack_require__(132), + Map = __webpack_require__(139); + + /** + * Removes all key-value entries from the map. + * + * @private + * @name clear + * @memberOf MapCache + */ + function mapCacheClear() { + this.size = 0; + this.__data__ = { + 'hash': new Hash, + 'map': new (Map || ListCache), + 'string': new Hash + }; + } + + module.exports = mapCacheClear; + + +/***/ }), +/* 119 */ +/***/ (function(module, exports, __webpack_require__) { + + var hashClear = __webpack_require__(120), + hashDelete = __webpack_require__(128), + hashGet = __webpack_require__(129), + hashHas = __webpack_require__(130), + hashSet = __webpack_require__(131); + + /** + * Creates a hash object. + * + * @private + * @constructor + * @param {Array} [entries] The key-value pairs to cache. + */ + function Hash(entries) { + var index = -1, + length = entries == null ? 0 : entries.length; + + this.clear(); + while (++index < length) { + var entry = entries[index]; + this.set(entry[0], entry[1]); + } + } + + // Add methods to `Hash`. + Hash.prototype.clear = hashClear; + Hash.prototype['delete'] = hashDelete; + Hash.prototype.get = hashGet; + Hash.prototype.has = hashHas; + Hash.prototype.set = hashSet; + + module.exports = Hash; + + +/***/ }), +/* 120 */ +/***/ (function(module, exports, __webpack_require__) { + + var nativeCreate = __webpack_require__(121); + + /** + * Removes all key-value entries from the hash. + * + * @private + * @name clear + * @memberOf Hash + */ + function hashClear() { + this.__data__ = nativeCreate ? nativeCreate(null) : {}; + this.size = 0; + } + + module.exports = hashClear; + + +/***/ }), +/* 121 */ +/***/ (function(module, exports, __webpack_require__) { + + var getNative = __webpack_require__(122); + + /* Built-in method references that are verified to be native. */ + var nativeCreate = getNative(Object, 'create'); + + module.exports = nativeCreate; + + +/***/ }), +/* 122 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIsNative = __webpack_require__(123), + getValue = __webpack_require__(127); + + /** + * Gets the native function at `key` of `object`. + * + * @private + * @param {Object} object The object to query. + * @param {string} key The key of the method to get. + * @returns {*} Returns the function if it's native, else `undefined`. + */ + function getNative(object, key) { + var value = getValue(object, key); + return baseIsNative(value) ? value : undefined; + } + + module.exports = getNative; + + +/***/ }), +/* 123 */ +/***/ (function(module, exports, __webpack_require__) { + + var isFunction = __webpack_require__(90), + isMasked = __webpack_require__(124), + isObject = __webpack_require__(97), + toSource = __webpack_require__(126); + + /** + * Used to match `RegExp` + * [syntax characters](http://ecma-international.org/ecma-262/7.0/#sec-patterns). + */ + var reRegExpChar = /[\\^$.*+?()[\]{}|]/g; + + /** Used to detect host constructors (Safari). */ + var reIsHostCtor = /^\[object .+?Constructor\]$/; + + /** Used for built-in method references. */ + var funcProto = Function.prototype, + objectProto = Object.prototype; + + /** Used to resolve the decompiled source of functions. */ + var funcToString = funcProto.toString; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** Used to detect if a method is native. */ + var reIsNative = RegExp('^' + + funcToString.call(hasOwnProperty).replace(reRegExpChar, '\\$&') + .replace(/hasOwnProperty|(function).*?(?=\\\()| for .+?(?=\\\])/g, '$1.*?') + '$' + ); + + /** + * The base implementation of `_.isNative` without bad shim checks. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a native function, + * else `false`. + */ + function baseIsNative(value) { + if (!isObject(value) || isMasked(value)) { + return false; + } + var pattern = isFunction(value) ? reIsNative : reIsHostCtor; + return pattern.test(toSource(value)); + } + + module.exports = baseIsNative; + + +/***/ }), +/* 124 */ +/***/ (function(module, exports, __webpack_require__) { + + var coreJsData = __webpack_require__(125); + + /** Used to detect methods masquerading as native. */ + var maskSrcKey = (function() { + var uid = /[^.]+$/.exec(coreJsData && coreJsData.keys && coreJsData.keys.IE_PROTO || ''); + return uid ? ('Symbol(src)_1.' + uid) : ''; + }()); + + /** + * Checks if `func` has its source masked. + * + * @private + * @param {Function} func The function to check. + * @returns {boolean} Returns `true` if `func` is masked, else `false`. + */ + function isMasked(func) { + return !!maskSrcKey && (maskSrcKey in func); + } + + module.exports = isMasked; + + +/***/ }), +/* 125 */ +/***/ (function(module, exports, __webpack_require__) { + + var root = __webpack_require__(93); + + /** Used to detect overreaching core-js shims. */ + var coreJsData = root['__core-js_shared__']; + + module.exports = coreJsData; + + +/***/ }), +/* 126 */ +/***/ (function(module, exports) { + + /** Used for built-in method references. */ + var funcProto = Function.prototype; + + /** Used to resolve the decompiled source of functions. */ + var funcToString = funcProto.toString; + + /** + * Converts `func` to its source code. + * + * @private + * @param {Function} func The function to convert. + * @returns {string} Returns the source code. + */ + function toSource(func) { + if (func != null) { + try { + return funcToString.call(func); + } catch (e) {} + try { + return (func + ''); + } catch (e) {} + } + return ''; + } + + module.exports = toSource; + + +/***/ }), +/* 127 */ +/***/ (function(module, exports) { + + /** + * Gets the value at `key` of `object`. + * + * @private + * @param {Object} [object] The object to query. + * @param {string} key The key of the property to get. + * @returns {*} Returns the property value. + */ + function getValue(object, key) { + return object == null ? undefined : object[key]; + } + + module.exports = getValue; + + +/***/ }), +/* 128 */ +/***/ (function(module, exports) { + + /** + * Removes `key` and its value from the hash. + * + * @private + * @name delete + * @memberOf Hash + * @param {Object} hash The hash to modify. + * @param {string} key The key of the value to remove. + * @returns {boolean} Returns `true` if the entry was removed, else `false`. + */ + function hashDelete(key) { + var result = this.has(key) && delete this.__data__[key]; + this.size -= result ? 1 : 0; + return result; + } + + module.exports = hashDelete; + + +/***/ }), +/* 129 */ +/***/ (function(module, exports, __webpack_require__) { + + var nativeCreate = __webpack_require__(121); + + /** Used to stand-in for `undefined` hash values. */ + var HASH_UNDEFINED = '__lodash_hash_undefined__'; + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * Gets the hash value for `key`. + * + * @private + * @name get + * @memberOf Hash + * @param {string} key The key of the value to get. + * @returns {*} Returns the entry value. + */ + function hashGet(key) { + var data = this.__data__; + if (nativeCreate) { + var result = data[key]; + return result === HASH_UNDEFINED ? undefined : result; + } + return hasOwnProperty.call(data, key) ? data[key] : undefined; + } + + module.exports = hashGet; + + +/***/ }), +/* 130 */ +/***/ (function(module, exports, __webpack_require__) { + + var nativeCreate = __webpack_require__(121); + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * Checks if a hash value for `key` exists. + * + * @private + * @name has + * @memberOf Hash + * @param {string} key The key of the entry to check. + * @returns {boolean} Returns `true` if an entry for `key` exists, else `false`. + */ + function hashHas(key) { + var data = this.__data__; + return nativeCreate ? (data[key] !== undefined) : hasOwnProperty.call(data, key); + } + + module.exports = hashHas; + + +/***/ }), +/* 131 */ +/***/ (function(module, exports, __webpack_require__) { + + var nativeCreate = __webpack_require__(121); + + /** Used to stand-in for `undefined` hash values. */ + var HASH_UNDEFINED = '__lodash_hash_undefined__'; + + /** + * Sets the hash `key` to `value`. + * + * @private + * @name set + * @memberOf Hash + * @param {string} key The key of the value to set. + * @param {*} value The value to set. + * @returns {Object} Returns the hash instance. + */ + function hashSet(key, value) { + var data = this.__data__; + this.size += this.has(key) ? 0 : 1; + data[key] = (nativeCreate && value === undefined) ? HASH_UNDEFINED : value; + return this; + } + + module.exports = hashSet; + + +/***/ }), +/* 132 */ +/***/ (function(module, exports, __webpack_require__) { + + var listCacheClear = __webpack_require__(133), + listCacheDelete = __webpack_require__(134), + listCacheGet = __webpack_require__(136), + listCacheHas = __webpack_require__(137), + listCacheSet = __webpack_require__(138); + + /** + * Creates an list cache object. + * + * @private + * @constructor + * @param {Array} [entries] The key-value pairs to cache. + */ + function ListCache(entries) { + var index = -1, + length = entries == null ? 0 : entries.length; + + this.clear(); + while (++index < length) { + var entry = entries[index]; + this.set(entry[0], entry[1]); + } + } + + // Add methods to `ListCache`. + ListCache.prototype.clear = listCacheClear; + ListCache.prototype['delete'] = listCacheDelete; + ListCache.prototype.get = listCacheGet; + ListCache.prototype.has = listCacheHas; + ListCache.prototype.set = listCacheSet; + + module.exports = ListCache; + + +/***/ }), +/* 133 */ +/***/ (function(module, exports) { + + /** + * Removes all key-value entries from the list cache. + * + * @private + * @name clear + * @memberOf ListCache + */ + function listCacheClear() { + this.__data__ = []; + this.size = 0; + } + + module.exports = listCacheClear; + + +/***/ }), +/* 134 */ +/***/ (function(module, exports, __webpack_require__) { + + var assocIndexOf = __webpack_require__(135); + + /** Used for built-in method references. */ + var arrayProto = Array.prototype; + + /** Built-in value references. */ + var splice = arrayProto.splice; + + /** + * Removes `key` and its value from the list cache. + * + * @private + * @name delete + * @memberOf ListCache + * @param {string} key The key of the value to remove. + * @returns {boolean} Returns `true` if the entry was removed, else `false`. + */ + function listCacheDelete(key) { + var data = this.__data__, + index = assocIndexOf(data, key); + + if (index < 0) { + return false; + } + var lastIndex = data.length - 1; + if (index == lastIndex) { + data.pop(); + } else { + splice.call(data, index, 1); + } + --this.size; + return true; + } + + module.exports = listCacheDelete; + + +/***/ }), +/* 135 */ +/***/ (function(module, exports, __webpack_require__) { + + var eq = __webpack_require__(88); + + /** + * Gets the index at which the `key` is found in `array` of key-value pairs. + * + * @private + * @param {Array} array The array to inspect. + * @param {*} key The key to search for. + * @returns {number} Returns the index of the matched value, else `-1`. + */ + function assocIndexOf(array, key) { + var length = array.length; + while (length--) { + if (eq(array[length][0], key)) { + return length; + } + } + return -1; + } + + module.exports = assocIndexOf; + + +/***/ }), +/* 136 */ +/***/ (function(module, exports, __webpack_require__) { + + var assocIndexOf = __webpack_require__(135); + + /** + * Gets the list cache value for `key`. + * + * @private + * @name get + * @memberOf ListCache + * @param {string} key The key of the value to get. + * @returns {*} Returns the entry value. + */ + function listCacheGet(key) { + var data = this.__data__, + index = assocIndexOf(data, key); + + return index < 0 ? undefined : data[index][1]; + } + + module.exports = listCacheGet; + + +/***/ }), +/* 137 */ +/***/ (function(module, exports, __webpack_require__) { + + var assocIndexOf = __webpack_require__(135); + + /** + * Checks if a list cache value for `key` exists. + * + * @private + * @name has + * @memberOf ListCache + * @param {string} key The key of the entry to check. + * @returns {boolean} Returns `true` if an entry for `key` exists, else `false`. + */ + function listCacheHas(key) { + return assocIndexOf(this.__data__, key) > -1; + } + + module.exports = listCacheHas; + + +/***/ }), +/* 138 */ +/***/ (function(module, exports, __webpack_require__) { + + var assocIndexOf = __webpack_require__(135); + + /** + * Sets the list cache `key` to `value`. + * + * @private + * @name set + * @memberOf ListCache + * @param {string} key The key of the value to set. + * @param {*} value The value to set. + * @returns {Object} Returns the list cache instance. + */ + function listCacheSet(key, value) { + var data = this.__data__, + index = assocIndexOf(data, key); + + if (index < 0) { + ++this.size; + data.push([key, value]); + } else { + data[index][1] = value; + } + return this; + } + + module.exports = listCacheSet; + + +/***/ }), +/* 139 */ +/***/ (function(module, exports, __webpack_require__) { + + var getNative = __webpack_require__(122), + root = __webpack_require__(93); + + /* Built-in method references that are verified to be native. */ + var Map = getNative(root, 'Map'); + + module.exports = Map; + + +/***/ }), +/* 140 */ +/***/ (function(module, exports, __webpack_require__) { + + var getMapData = __webpack_require__(141); + + /** + * Removes `key` and its value from the map. + * + * @private + * @name delete + * @memberOf MapCache + * @param {string} key The key of the value to remove. + * @returns {boolean} Returns `true` if the entry was removed, else `false`. + */ + function mapCacheDelete(key) { + var result = getMapData(this, key)['delete'](key); + this.size -= result ? 1 : 0; + return result; + } + + module.exports = mapCacheDelete; + + +/***/ }), +/* 141 */ +/***/ (function(module, exports, __webpack_require__) { + + var isKeyable = __webpack_require__(142); + + /** + * Gets the data for `map`. + * + * @private + * @param {Object} map The map to query. + * @param {string} key The reference key. + * @returns {*} Returns the map data. + */ + function getMapData(map, key) { + var data = map.__data__; + return isKeyable(key) + ? data[typeof key == 'string' ? 'string' : 'hash'] + : data.map; + } + + module.exports = getMapData; + + +/***/ }), +/* 142 */ +/***/ (function(module, exports) { + + /** + * Checks if `value` is suitable for use as unique object key. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is suitable, else `false`. + */ + function isKeyable(value) { + var type = typeof value; + return (type == 'string' || type == 'number' || type == 'symbol' || type == 'boolean') + ? (value !== '__proto__') + : (value === null); + } + + module.exports = isKeyable; + + +/***/ }), +/* 143 */ +/***/ (function(module, exports, __webpack_require__) { + + var getMapData = __webpack_require__(141); + + /** + * Gets the map value for `key`. + * + * @private + * @name get + * @memberOf MapCache + * @param {string} key The key of the value to get. + * @returns {*} Returns the entry value. + */ + function mapCacheGet(key) { + return getMapData(this, key).get(key); + } + + module.exports = mapCacheGet; + + +/***/ }), +/* 144 */ +/***/ (function(module, exports, __webpack_require__) { + + var getMapData = __webpack_require__(141); + + /** + * Checks if a map value for `key` exists. + * + * @private + * @name has + * @memberOf MapCache + * @param {string} key The key of the entry to check. + * @returns {boolean} Returns `true` if an entry for `key` exists, else `false`. + */ + function mapCacheHas(key) { + return getMapData(this, key).has(key); + } + + module.exports = mapCacheHas; + + +/***/ }), +/* 145 */ +/***/ (function(module, exports, __webpack_require__) { + + var getMapData = __webpack_require__(141); + + /** + * Sets the map `key` to `value`. + * + * @private + * @name set + * @memberOf MapCache + * @param {string} key The key of the value to set. + * @param {*} value The value to set. + * @returns {Object} Returns the map cache instance. + */ + function mapCacheSet(key, value) { + var data = getMapData(this, key), + size = data.size; + + data.set(key, value); + this.size += data.size == size ? 0 : 1; + return this; + } + + module.exports = mapCacheSet; + + +/***/ }), +/* 146 */ +/***/ (function(module, exports) { + + /** Used to stand-in for `undefined` hash values. */ + var HASH_UNDEFINED = '__lodash_hash_undefined__'; + + /** + * Adds `value` to the array cache. + * + * @private + * @name add + * @memberOf SetCache + * @alias push + * @param {*} value The value to cache. + * @returns {Object} Returns the cache instance. + */ + function setCacheAdd(value) { + this.__data__.set(value, HASH_UNDEFINED); + return this; + } + + module.exports = setCacheAdd; + + +/***/ }), +/* 147 */ +/***/ (function(module, exports) { + + /** + * Checks if `value` is in the array cache. + * + * @private + * @name has + * @memberOf SetCache + * @param {*} value The value to search for. + * @returns {number} Returns `true` if `value` is found, else `false`. + */ + function setCacheHas(value) { + return this.__data__.has(value); + } + + module.exports = setCacheHas; + + +/***/ }), +/* 148 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIndexOf = __webpack_require__(149); + + /** + * A specialized version of `_.includes` for arrays without support for + * specifying an index to search from. + * + * @private + * @param {Array} [array] The array to inspect. + * @param {*} target The value to search for. + * @returns {boolean} Returns `true` if `target` is found, else `false`. + */ + function arrayIncludes(array, value) { + var length = array == null ? 0 : array.length; + return !!length && baseIndexOf(array, value, 0) > -1; + } + + module.exports = arrayIncludes; + + +/***/ }), +/* 149 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFindIndex = __webpack_require__(150), + baseIsNaN = __webpack_require__(151), + strictIndexOf = __webpack_require__(152); + + /** + * The base implementation of `_.indexOf` without `fromIndex` bounds checks. + * + * @private + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @param {number} fromIndex The index to search from. + * @returns {number} Returns the index of the matched value, else `-1`. + */ + function baseIndexOf(array, value, fromIndex) { + return value === value + ? strictIndexOf(array, value, fromIndex) + : baseFindIndex(array, baseIsNaN, fromIndex); + } + + module.exports = baseIndexOf; + + +/***/ }), +/* 150 */ +/***/ (function(module, exports) { + + /** + * The base implementation of `_.findIndex` and `_.findLastIndex` without + * support for iteratee shorthands. + * + * @private + * @param {Array} array The array to inspect. + * @param {Function} predicate The function invoked per iteration. + * @param {number} fromIndex The index to search from. + * @param {boolean} [fromRight] Specify iterating from right to left. + * @returns {number} Returns the index of the matched value, else `-1`. + */ + function baseFindIndex(array, predicate, fromIndex, fromRight) { + var length = array.length, + index = fromIndex + (fromRight ? 1 : -1); + + while ((fromRight ? index-- : ++index < length)) { + if (predicate(array[index], index, array)) { + return index; + } + } + return -1; + } + + module.exports = baseFindIndex; + + +/***/ }), +/* 151 */ +/***/ (function(module, exports) { + + /** + * The base implementation of `_.isNaN` without support for number objects. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is `NaN`, else `false`. + */ + function baseIsNaN(value) { + return value !== value; + } + + module.exports = baseIsNaN; + + +/***/ }), +/* 152 */ +/***/ (function(module, exports) { + + /** + * A specialized version of `_.indexOf` which performs strict equality + * comparisons of values, i.e. `===`. + * + * @private + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @param {number} fromIndex The index to search from. + * @returns {number} Returns the index of the matched value, else `-1`. + */ + function strictIndexOf(array, value, fromIndex) { + var index = fromIndex - 1, + length = array.length; + + while (++index < length) { + if (array[index] === value) { + return index; + } + } + return -1; + } + + module.exports = strictIndexOf; + + +/***/ }), +/* 153 */ +/***/ (function(module, exports) { + + /** + * This function is like `arrayIncludes` except that it accepts a comparator. + * + * @private + * @param {Array} [array] The array to inspect. + * @param {*} target The value to search for. + * @param {Function} comparator The comparator invoked per element. + * @returns {boolean} Returns `true` if `target` is found, else `false`. + */ + function arrayIncludesWith(array, value, comparator) { + var index = -1, + length = array == null ? 0 : array.length; + + while (++index < length) { + if (comparator(value, array[index])) { + return true; + } + } + return false; + } + + module.exports = arrayIncludesWith; + + +/***/ }), +/* 154 */ +/***/ (function(module, exports) { + + /** + * A specialized version of `_.map` for arrays without support for iteratee + * shorthands. + * + * @private + * @param {Array} [array] The array to iterate over. + * @param {Function} iteratee The function invoked per iteration. + * @returns {Array} Returns the new mapped array. + */ + function arrayMap(array, iteratee) { + var index = -1, + length = array == null ? 0 : array.length, + result = Array(length); + + while (++index < length) { + result[index] = iteratee(array[index], index, array); + } + return result; + } + + module.exports = arrayMap; + + +/***/ }), +/* 155 */ +/***/ (function(module, exports) { + + /** + * The base implementation of `_.unary` without support for storing metadata. + * + * @private + * @param {Function} func The function to cap arguments for. + * @returns {Function} Returns the new capped function. + */ + function baseUnary(func) { + return function(value) { + return func(value); + }; + } + + module.exports = baseUnary; + + +/***/ }), +/* 156 */ +/***/ (function(module, exports) { + + /** + * Checks if a `cache` value for `key` exists. + * + * @private + * @param {Object} cache The cache to query. + * @param {string} key The key of the entry to check. + * @returns {boolean} Returns `true` if an entry for `key` exists, else `false`. + */ + function cacheHas(cache, key) { + return cache.has(key); + } + + module.exports = cacheHas; + + +/***/ }), +/* 157 */ +/***/ (function(module, exports, __webpack_require__) { + + var identity = __webpack_require__(158), + overRest = __webpack_require__(159), + setToString = __webpack_require__(161); + + /** + * The base implementation of `_.rest` which doesn't validate or coerce arguments. + * + * @private + * @param {Function} func The function to apply a rest parameter to. + * @param {number} [start=func.length-1] The start position of the rest parameter. + * @returns {Function} Returns the new function. + */ + function baseRest(func, start) { + return setToString(overRest(func, start, identity), func + ''); + } + + module.exports = baseRest; + + +/***/ }), +/* 158 */ +/***/ (function(module, exports) { + + /** + * This method returns the first argument it receives. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Util + * @param {*} value Any value. + * @returns {*} Returns `value`. + * @example + * + * var object = { 'a': 1 }; + * + * console.log(_.identity(object) === object); + * // => true + */ + function identity(value) { + return value; + } + + module.exports = identity; + + +/***/ }), +/* 159 */ +/***/ (function(module, exports, __webpack_require__) { + + var apply = __webpack_require__(160); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeMax = Math.max; + + /** + * A specialized version of `baseRest` which transforms the rest array. + * + * @private + * @param {Function} func The function to apply a rest parameter to. + * @param {number} [start=func.length-1] The start position of the rest parameter. + * @param {Function} transform The rest array transform. + * @returns {Function} Returns the new function. + */ + function overRest(func, start, transform) { + start = nativeMax(start === undefined ? (func.length - 1) : start, 0); + return function() { + var args = arguments, + index = -1, + length = nativeMax(args.length - start, 0), + array = Array(length); + + while (++index < length) { + array[index] = args[start + index]; + } + index = -1; + var otherArgs = Array(start + 1); + while (++index < start) { + otherArgs[index] = args[index]; + } + otherArgs[start] = transform(array); + return apply(func, this, otherArgs); + }; + } + + module.exports = overRest; + + +/***/ }), +/* 160 */ +/***/ (function(module, exports) { + + /** + * A faster alternative to `Function#apply`, this function invokes `func` + * with the `this` binding of `thisArg` and the arguments of `args`. + * + * @private + * @param {Function} func The function to invoke. + * @param {*} thisArg The `this` binding of `func`. + * @param {Array} args The arguments to invoke `func` with. + * @returns {*} Returns the result of `func`. + */ + function apply(func, thisArg, args) { + switch (args.length) { + case 0: return func.call(thisArg); + case 1: return func.call(thisArg, args[0]); + case 2: return func.call(thisArg, args[0], args[1]); + case 3: return func.call(thisArg, args[0], args[1], args[2]); + } + return func.apply(thisArg, args); + } + + module.exports = apply; + + +/***/ }), +/* 161 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSetToString = __webpack_require__(162), + shortOut = __webpack_require__(165); + + /** + * Sets the `toString` method of `func` to return `string`. + * + * @private + * @param {Function} func The function to modify. + * @param {Function} string The `toString` result. + * @returns {Function} Returns `func`. + */ + var setToString = shortOut(baseSetToString); + + module.exports = setToString; + + +/***/ }), +/* 162 */ +/***/ (function(module, exports, __webpack_require__) { + + var constant = __webpack_require__(163), + defineProperty = __webpack_require__(164), + identity = __webpack_require__(158); + + /** + * The base implementation of `setToString` without support for hot loop shorting. + * + * @private + * @param {Function} func The function to modify. + * @param {Function} string The `toString` result. + * @returns {Function} Returns `func`. + */ + var baseSetToString = !defineProperty ? identity : function(func, string) { + return defineProperty(func, 'toString', { + 'configurable': true, + 'enumerable': false, + 'value': constant(string), + 'writable': true + }); + }; + + module.exports = baseSetToString; + + +/***/ }), +/* 163 */ +/***/ (function(module, exports) { + + /** + * Creates a function that returns `value`. + * + * @static + * @memberOf _ + * @since 2.4.0 + * @category Util + * @param {*} value The value to return from the new function. + * @returns {Function} Returns the new constant function. + * @example + * + * var objects = _.times(2, _.constant({ 'a': 1 })); + * + * console.log(objects); + * // => [{ 'a': 1 }, { 'a': 1 }] + * + * console.log(objects[0] === objects[1]); + * // => true + */ + function constant(value) { + return function() { + return value; + }; + } + + module.exports = constant; + + +/***/ }), +/* 164 */ +/***/ (function(module, exports, __webpack_require__) { + + var getNative = __webpack_require__(122); + + var defineProperty = (function() { + try { + var func = getNative(Object, 'defineProperty'); + func({}, '', {}); + return func; + } catch (e) {} + }()); + + module.exports = defineProperty; + + +/***/ }), +/* 165 */ +/***/ (function(module, exports) { + + /** Used to detect hot functions by number of calls within a span of milliseconds. */ + var HOT_COUNT = 800, + HOT_SPAN = 16; + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeNow = Date.now; + + /** + * Creates a function that'll short out and invoke `identity` instead + * of `func` when it's called `HOT_COUNT` or more times in `HOT_SPAN` + * milliseconds. + * + * @private + * @param {Function} func The function to restrict. + * @returns {Function} Returns the new shortable function. + */ + function shortOut(func) { + var count = 0, + lastCalled = 0; + + return function() { + var stamp = nativeNow(), + remaining = HOT_SPAN - (stamp - lastCalled); + + lastCalled = stamp; + if (remaining > 0) { + if (++count >= HOT_COUNT) { + return arguments[0]; + } + } else { + count = 0; + } + return func.apply(undefined, arguments); + }; + } + + module.exports = shortOut; + + +/***/ }), +/* 166 */ +/***/ (function(module, exports, __webpack_require__) { + + var isArrayLike = __webpack_require__(89), + isObjectLike = __webpack_require__(104); + + /** + * This method is like `_.isArrayLike` except that it also checks if `value` + * is an object. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is an array-like object, + * else `false`. + * @example + * + * _.isArrayLikeObject([1, 2, 3]); + * // => true + * + * _.isArrayLikeObject(document.body.children); + * // => true + * + * _.isArrayLikeObject('abc'); + * // => false + * + * _.isArrayLikeObject(_.noop); + * // => false + */ + function isArrayLikeObject(value) { + return isObjectLike(value) && isArrayLike(value); + } + + module.exports = isArrayLikeObject; + + +/***/ }), +/* 167 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseDifference = __webpack_require__(115), + baseFlatten = __webpack_require__(108), + baseIteratee = __webpack_require__(168), + baseRest = __webpack_require__(157), + isArrayLikeObject = __webpack_require__(166), + last = __webpack_require__(228); + + /** + * This method is like `_.difference` except that it accepts `iteratee` which + * is invoked for each element of `array` and `values` to generate the criterion + * by which they're compared. The order and references of result values are + * determined by the first array. The iteratee is invoked with one argument: + * (value). + * + * **Note:** Unlike `_.pullAllBy`, this method returns a new array. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {...Array} [values] The values to exclude. + * @param {Function} [iteratee=_.identity] The iteratee invoked per element. + * @returns {Array} Returns the new array of filtered values. + * @example + * + * _.differenceBy([2.1, 1.2], [2.3, 3.4], Math.floor); + * // => [1.2] + * + * // The `_.property` iteratee shorthand. + * _.differenceBy([{ 'x': 2 }, { 'x': 1 }], [{ 'x': 1 }], 'x'); + * // => [{ 'x': 2 }] + */ + var differenceBy = baseRest(function(array, values) { + var iteratee = last(values); + if (isArrayLikeObject(iteratee)) { + iteratee = undefined; + } + return isArrayLikeObject(array) + ? baseDifference(array, baseFlatten(values, 1, isArrayLikeObject, true), baseIteratee(iteratee, 2)) + : []; + }); + + module.exports = differenceBy; + + +/***/ }), +/* 168 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseMatches = __webpack_require__(169), + baseMatchesProperty = __webpack_require__(211), + identity = __webpack_require__(158), + isArray = __webpack_require__(112), + property = __webpack_require__(225); + + /** + * The base implementation of `_.iteratee`. + * + * @private + * @param {*} [value=_.identity] The value to convert to an iteratee. + * @returns {Function} Returns the iteratee. + */ + function baseIteratee(value) { + // Don't store the `typeof` result in a variable to avoid a JIT bug in Safari 9. + // See https://bugs.webkit.org/show_bug.cgi?id=156034 for more details. + if (typeof value == 'function') { + return value; + } + if (value == null) { + return identity; + } + if (typeof value == 'object') { + return isArray(value) + ? baseMatchesProperty(value[0], value[1]) + : baseMatches(value); + } + return property(value); + } + + module.exports = baseIteratee; + + +/***/ }), +/* 169 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIsMatch = __webpack_require__(170), + getMatchData = __webpack_require__(208), + matchesStrictComparable = __webpack_require__(210); + + /** + * The base implementation of `_.matches` which doesn't clone `source`. + * + * @private + * @param {Object} source The object of property values to match. + * @returns {Function} Returns the new spec function. + */ + function baseMatches(source) { + var matchData = getMatchData(source); + if (matchData.length == 1 && matchData[0][2]) { + return matchesStrictComparable(matchData[0][0], matchData[0][1]); + } + return function(object) { + return object === source || baseIsMatch(object, source, matchData); + }; + } + + module.exports = baseMatches; + + +/***/ }), +/* 170 */ +/***/ (function(module, exports, __webpack_require__) { + + var Stack = __webpack_require__(171), + baseIsEqual = __webpack_require__(177); + + /** Used to compose bitmasks for value comparisons. */ + var COMPARE_PARTIAL_FLAG = 1, + COMPARE_UNORDERED_FLAG = 2; + + /** + * The base implementation of `_.isMatch` without support for iteratee shorthands. + * + * @private + * @param {Object} object The object to inspect. + * @param {Object} source The object of property values to match. + * @param {Array} matchData The property names, values, and compare flags to match. + * @param {Function} [customizer] The function to customize comparisons. + * @returns {boolean} Returns `true` if `object` is a match, else `false`. + */ + function baseIsMatch(object, source, matchData, customizer) { + var index = matchData.length, + length = index, + noCustomizer = !customizer; + + if (object == null) { + return !length; + } + object = Object(object); + while (index--) { + var data = matchData[index]; + if ((noCustomizer && data[2]) + ? data[1] !== object[data[0]] + : !(data[0] in object) + ) { + return false; + } + } + while (++index < length) { + data = matchData[index]; + var key = data[0], + objValue = object[key], + srcValue = data[1]; + + if (noCustomizer && data[2]) { + if (objValue === undefined && !(key in object)) { + return false; + } + } else { + var stack = new Stack; + if (customizer) { + var result = customizer(objValue, srcValue, key, object, source, stack); + } + if (!(result === undefined + ? baseIsEqual(srcValue, objValue, COMPARE_PARTIAL_FLAG | COMPARE_UNORDERED_FLAG, customizer, stack) + : result + )) { + return false; + } + } + } + return true; + } + + module.exports = baseIsMatch; + + +/***/ }), +/* 171 */ +/***/ (function(module, exports, __webpack_require__) { + + var ListCache = __webpack_require__(132), + stackClear = __webpack_require__(172), + stackDelete = __webpack_require__(173), + stackGet = __webpack_require__(174), + stackHas = __webpack_require__(175), + stackSet = __webpack_require__(176); + + /** + * Creates a stack cache object to store key-value pairs. + * + * @private + * @constructor + * @param {Array} [entries] The key-value pairs to cache. + */ + function Stack(entries) { + var data = this.__data__ = new ListCache(entries); + this.size = data.size; + } + + // Add methods to `Stack`. + Stack.prototype.clear = stackClear; + Stack.prototype['delete'] = stackDelete; + Stack.prototype.get = stackGet; + Stack.prototype.has = stackHas; + Stack.prototype.set = stackSet; + + module.exports = Stack; + + +/***/ }), +/* 172 */ +/***/ (function(module, exports, __webpack_require__) { + + var ListCache = __webpack_require__(132); + + /** + * Removes all key-value entries from the stack. + * + * @private + * @name clear + * @memberOf Stack + */ + function stackClear() { + this.__data__ = new ListCache; + this.size = 0; + } + + module.exports = stackClear; + + +/***/ }), +/* 173 */ +/***/ (function(module, exports) { + + /** + * Removes `key` and its value from the stack. + * + * @private + * @name delete + * @memberOf Stack + * @param {string} key The key of the value to remove. + * @returns {boolean} Returns `true` if the entry was removed, else `false`. + */ + function stackDelete(key) { + var data = this.__data__, + result = data['delete'](key); + + this.size = data.size; + return result; + } + + module.exports = stackDelete; + + +/***/ }), +/* 174 */ +/***/ (function(module, exports) { + + /** + * Gets the stack value for `key`. + * + * @private + * @name get + * @memberOf Stack + * @param {string} key The key of the value to get. + * @returns {*} Returns the entry value. + */ + function stackGet(key) { + return this.__data__.get(key); + } + + module.exports = stackGet; + + +/***/ }), +/* 175 */ +/***/ (function(module, exports) { + + /** + * Checks if a stack value for `key` exists. + * + * @private + * @name has + * @memberOf Stack + * @param {string} key The key of the entry to check. + * @returns {boolean} Returns `true` if an entry for `key` exists, else `false`. + */ + function stackHas(key) { + return this.__data__.has(key); + } + + module.exports = stackHas; + + +/***/ }), +/* 176 */ +/***/ (function(module, exports, __webpack_require__) { + + var ListCache = __webpack_require__(132), + Map = __webpack_require__(139), + MapCache = __webpack_require__(117); + + /** Used as the size to enable large array optimizations. */ + var LARGE_ARRAY_SIZE = 200; + + /** + * Sets the stack `key` to `value`. + * + * @private + * @name set + * @memberOf Stack + * @param {string} key The key of the value to set. + * @param {*} value The value to set. + * @returns {Object} Returns the stack cache instance. + */ + function stackSet(key, value) { + var data = this.__data__; + if (data instanceof ListCache) { + var pairs = data.__data__; + if (!Map || (pairs.length < LARGE_ARRAY_SIZE - 1)) { + pairs.push([key, value]); + this.size = ++data.size; + return this; + } + data = this.__data__ = new MapCache(pairs); + } + data.set(key, value); + this.size = data.size; + return this; + } + + module.exports = stackSet; + + +/***/ }), +/* 177 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIsEqualDeep = __webpack_require__(178), + isObjectLike = __webpack_require__(104); + + /** + * The base implementation of `_.isEqual` which supports partial comparisons + * and tracks traversed objects. + * + * @private + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @param {boolean} bitmask The bitmask flags. + * 1 - Unordered comparison + * 2 - Partial comparison + * @param {Function} [customizer] The function to customize comparisons. + * @param {Object} [stack] Tracks traversed `value` and `other` objects. + * @returns {boolean} Returns `true` if the values are equivalent, else `false`. + */ + function baseIsEqual(value, other, bitmask, customizer, stack) { + if (value === other) { + return true; + } + if (value == null || other == null || (!isObjectLike(value) && !isObjectLike(other))) { + return value !== value && other !== other; + } + return baseIsEqualDeep(value, other, bitmask, customizer, baseIsEqual, stack); + } + + module.exports = baseIsEqual; + + +/***/ }), +/* 178 */ +/***/ (function(module, exports, __webpack_require__) { + + var Stack = __webpack_require__(171), + equalArrays = __webpack_require__(179), + equalByTag = __webpack_require__(181), + equalObjects = __webpack_require__(185), + getTag = __webpack_require__(203), + isArray = __webpack_require__(112), + isBuffer = __webpack_require__(194), + isTypedArray = __webpack_require__(196); + + /** Used to compose bitmasks for value comparisons. */ + var COMPARE_PARTIAL_FLAG = 1; + + /** `Object#toString` result references. */ + var argsTag = '[object Arguments]', + arrayTag = '[object Array]', + objectTag = '[object Object]'; + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * A specialized version of `baseIsEqual` for arrays and objects which performs + * deep comparisons and tracks traversed objects enabling objects with circular + * references to be compared. + * + * @private + * @param {Object} object The object to compare. + * @param {Object} other The other object to compare. + * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. + * @param {Function} customizer The function to customize comparisons. + * @param {Function} equalFunc The function to determine equivalents of values. + * @param {Object} [stack] Tracks traversed `object` and `other` objects. + * @returns {boolean} Returns `true` if the objects are equivalent, else `false`. + */ + function baseIsEqualDeep(object, other, bitmask, customizer, equalFunc, stack) { + var objIsArr = isArray(object), + othIsArr = isArray(other), + objTag = objIsArr ? arrayTag : getTag(object), + othTag = othIsArr ? arrayTag : getTag(other); + + objTag = objTag == argsTag ? objectTag : objTag; + othTag = othTag == argsTag ? objectTag : othTag; + + var objIsObj = objTag == objectTag, + othIsObj = othTag == objectTag, + isSameTag = objTag == othTag; + + if (isSameTag && isBuffer(object)) { + if (!isBuffer(other)) { + return false; + } + objIsArr = true; + objIsObj = false; + } + if (isSameTag && !objIsObj) { + stack || (stack = new Stack); + return (objIsArr || isTypedArray(object)) + ? equalArrays(object, other, bitmask, customizer, equalFunc, stack) + : equalByTag(object, other, objTag, bitmask, customizer, equalFunc, stack); + } + if (!(bitmask & COMPARE_PARTIAL_FLAG)) { + var objIsWrapped = objIsObj && hasOwnProperty.call(object, '__wrapped__'), + othIsWrapped = othIsObj && hasOwnProperty.call(other, '__wrapped__'); + + if (objIsWrapped || othIsWrapped) { + var objUnwrapped = objIsWrapped ? object.value() : object, + othUnwrapped = othIsWrapped ? other.value() : other; + + stack || (stack = new Stack); + return equalFunc(objUnwrapped, othUnwrapped, bitmask, customizer, stack); + } + } + if (!isSameTag) { + return false; + } + stack || (stack = new Stack); + return equalObjects(object, other, bitmask, customizer, equalFunc, stack); + } + + module.exports = baseIsEqualDeep; + + +/***/ }), +/* 179 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetCache = __webpack_require__(116), + arraySome = __webpack_require__(180), + cacheHas = __webpack_require__(156); + + /** Used to compose bitmasks for value comparisons. */ + var COMPARE_PARTIAL_FLAG = 1, + COMPARE_UNORDERED_FLAG = 2; + + /** + * A specialized version of `baseIsEqualDeep` for arrays with support for + * partial deep comparisons. + * + * @private + * @param {Array} array The array to compare. + * @param {Array} other The other array to compare. + * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. + * @param {Function} customizer The function to customize comparisons. + * @param {Function} equalFunc The function to determine equivalents of values. + * @param {Object} stack Tracks traversed `array` and `other` objects. + * @returns {boolean} Returns `true` if the arrays are equivalent, else `false`. + */ + function equalArrays(array, other, bitmask, customizer, equalFunc, stack) { + var isPartial = bitmask & COMPARE_PARTIAL_FLAG, + arrLength = array.length, + othLength = other.length; + + if (arrLength != othLength && !(isPartial && othLength > arrLength)) { + return false; + } + // Assume cyclic values are equal. + var stacked = stack.get(array); + if (stacked && stack.get(other)) { + return stacked == other; + } + var index = -1, + result = true, + seen = (bitmask & COMPARE_UNORDERED_FLAG) ? new SetCache : undefined; + + stack.set(array, other); + stack.set(other, array); + + // Ignore non-index properties. + while (++index < arrLength) { + var arrValue = array[index], + othValue = other[index]; + + if (customizer) { + var compared = isPartial + ? customizer(othValue, arrValue, index, other, array, stack) + : customizer(arrValue, othValue, index, array, other, stack); + } + if (compared !== undefined) { + if (compared) { + continue; + } + result = false; + break; + } + // Recursively compare arrays (susceptible to call stack limits). + if (seen) { + if (!arraySome(other, function(othValue, othIndex) { + if (!cacheHas(seen, othIndex) && + (arrValue === othValue || equalFunc(arrValue, othValue, bitmask, customizer, stack))) { + return seen.push(othIndex); + } + })) { + result = false; + break; + } + } else if (!( + arrValue === othValue || + equalFunc(arrValue, othValue, bitmask, customizer, stack) + )) { + result = false; + break; + } + } + stack['delete'](array); + stack['delete'](other); + return result; + } + + module.exports = equalArrays; + + +/***/ }), +/* 180 */ +/***/ (function(module, exports) { + + /** + * A specialized version of `_.some` for arrays without support for iteratee + * shorthands. + * + * @private + * @param {Array} [array] The array to iterate over. + * @param {Function} predicate The function invoked per iteration. + * @returns {boolean} Returns `true` if any element passes the predicate check, + * else `false`. + */ + function arraySome(array, predicate) { + var index = -1, + length = array == null ? 0 : array.length; + + while (++index < length) { + if (predicate(array[index], index, array)) { + return true; + } + } + return false; + } + + module.exports = arraySome; + + +/***/ }), +/* 181 */ +/***/ (function(module, exports, __webpack_require__) { + + var Symbol = __webpack_require__(92), + Uint8Array = __webpack_require__(182), + eq = __webpack_require__(88), + equalArrays = __webpack_require__(179), + mapToArray = __webpack_require__(183), + setToArray = __webpack_require__(184); + + /** Used to compose bitmasks for value comparisons. */ + var COMPARE_PARTIAL_FLAG = 1, + COMPARE_UNORDERED_FLAG = 2; + + /** `Object#toString` result references. */ + var boolTag = '[object Boolean]', + dateTag = '[object Date]', + errorTag = '[object Error]', + mapTag = '[object Map]', + numberTag = '[object Number]', + regexpTag = '[object RegExp]', + setTag = '[object Set]', + stringTag = '[object String]', + symbolTag = '[object Symbol]'; + + var arrayBufferTag = '[object ArrayBuffer]', + dataViewTag = '[object DataView]'; + + /** Used to convert symbols to primitives and strings. */ + var symbolProto = Symbol ? Symbol.prototype : undefined, + symbolValueOf = symbolProto ? symbolProto.valueOf : undefined; + + /** + * A specialized version of `baseIsEqualDeep` for comparing objects of + * the same `toStringTag`. + * + * **Note:** This function only supports comparing values with tags of + * `Boolean`, `Date`, `Error`, `Number`, `RegExp`, or `String`. + * + * @private + * @param {Object} object The object to compare. + * @param {Object} other The other object to compare. + * @param {string} tag The `toStringTag` of the objects to compare. + * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. + * @param {Function} customizer The function to customize comparisons. + * @param {Function} equalFunc The function to determine equivalents of values. + * @param {Object} stack Tracks traversed `object` and `other` objects. + * @returns {boolean} Returns `true` if the objects are equivalent, else `false`. + */ + function equalByTag(object, other, tag, bitmask, customizer, equalFunc, stack) { + switch (tag) { + case dataViewTag: + if ((object.byteLength != other.byteLength) || + (object.byteOffset != other.byteOffset)) { + return false; + } + object = object.buffer; + other = other.buffer; + + case arrayBufferTag: + if ((object.byteLength != other.byteLength) || + !equalFunc(new Uint8Array(object), new Uint8Array(other))) { + return false; + } + return true; + + case boolTag: + case dateTag: + case numberTag: + // Coerce booleans to `1` or `0` and dates to milliseconds. + // Invalid dates are coerced to `NaN`. + return eq(+object, +other); + + case errorTag: + return object.name == other.name && object.message == other.message; + + case regexpTag: + case stringTag: + // Coerce regexes to strings and treat strings, primitives and objects, + // as equal. See http://www.ecma-international.org/ecma-262/7.0/#sec-regexp.prototype.tostring + // for more details. + return object == (other + ''); + + case mapTag: + var convert = mapToArray; + + case setTag: + var isPartial = bitmask & COMPARE_PARTIAL_FLAG; + convert || (convert = setToArray); + + if (object.size != other.size && !isPartial) { + return false; + } + // Assume cyclic values are equal. + var stacked = stack.get(object); + if (stacked) { + return stacked == other; + } + bitmask |= COMPARE_UNORDERED_FLAG; + + // Recursively compare objects (susceptible to call stack limits). + stack.set(object, other); + var result = equalArrays(convert(object), convert(other), bitmask, customizer, equalFunc, stack); + stack['delete'](object); + return result; + + case symbolTag: + if (symbolValueOf) { + return symbolValueOf.call(object) == symbolValueOf.call(other); + } + } + return false; + } + + module.exports = equalByTag; + + +/***/ }), +/* 182 */ +/***/ (function(module, exports, __webpack_require__) { + + var root = __webpack_require__(93); + + /** Built-in value references. */ + var Uint8Array = root.Uint8Array; + + module.exports = Uint8Array; + + +/***/ }), +/* 183 */ +/***/ (function(module, exports) { + + /** + * Converts `map` to its key-value pairs. + * + * @private + * @param {Object} map The map to convert. + * @returns {Array} Returns the key-value pairs. + */ + function mapToArray(map) { + var index = -1, + result = Array(map.size); + + map.forEach(function(value, key) { + result[++index] = [key, value]; + }); + return result; + } + + module.exports = mapToArray; + + +/***/ }), +/* 184 */ +/***/ (function(module, exports) { + + /** + * Converts `set` to an array of its values. + * + * @private + * @param {Object} set The set to convert. + * @returns {Array} Returns the values. + */ + function setToArray(set) { + var index = -1, + result = Array(set.size); + + set.forEach(function(value) { + result[++index] = value; + }); + return result; + } + + module.exports = setToArray; + + +/***/ }), +/* 185 */ +/***/ (function(module, exports, __webpack_require__) { + + var getAllKeys = __webpack_require__(186); + + /** Used to compose bitmasks for value comparisons. */ + var COMPARE_PARTIAL_FLAG = 1; + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * A specialized version of `baseIsEqualDeep` for objects with support for + * partial deep comparisons. + * + * @private + * @param {Object} object The object to compare. + * @param {Object} other The other object to compare. + * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. + * @param {Function} customizer The function to customize comparisons. + * @param {Function} equalFunc The function to determine equivalents of values. + * @param {Object} stack Tracks traversed `object` and `other` objects. + * @returns {boolean} Returns `true` if the objects are equivalent, else `false`. + */ + function equalObjects(object, other, bitmask, customizer, equalFunc, stack) { + var isPartial = bitmask & COMPARE_PARTIAL_FLAG, + objProps = getAllKeys(object), + objLength = objProps.length, + othProps = getAllKeys(other), + othLength = othProps.length; + + if (objLength != othLength && !isPartial) { + return false; + } + var index = objLength; + while (index--) { + var key = objProps[index]; + if (!(isPartial ? key in other : hasOwnProperty.call(other, key))) { + return false; + } + } + // Assume cyclic values are equal. + var stacked = stack.get(object); + if (stacked && stack.get(other)) { + return stacked == other; + } + var result = true; + stack.set(object, other); + stack.set(other, object); + + var skipCtor = isPartial; + while (++index < objLength) { + key = objProps[index]; + var objValue = object[key], + othValue = other[key]; + + if (customizer) { + var compared = isPartial + ? customizer(othValue, objValue, key, other, object, stack) + : customizer(objValue, othValue, key, object, other, stack); + } + // Recursively compare objects (susceptible to call stack limits). + if (!(compared === undefined + ? (objValue === othValue || equalFunc(objValue, othValue, bitmask, customizer, stack)) + : compared + )) { + result = false; + break; + } + skipCtor || (skipCtor = key == 'constructor'); + } + if (result && !skipCtor) { + var objCtor = object.constructor, + othCtor = other.constructor; + + // Non `Object` object instances with different constructors are not equal. + if (objCtor != othCtor && + ('constructor' in object && 'constructor' in other) && + !(typeof objCtor == 'function' && objCtor instanceof objCtor && + typeof othCtor == 'function' && othCtor instanceof othCtor)) { + result = false; + } + } + stack['delete'](object); + stack['delete'](other); + return result; + } + + module.exports = equalObjects; + + +/***/ }), +/* 186 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseGetAllKeys = __webpack_require__(187), + getSymbols = __webpack_require__(188), + keys = __webpack_require__(191); + + /** + * Creates an array of own enumerable property names and symbols of `object`. + * + * @private + * @param {Object} object The object to query. + * @returns {Array} Returns the array of property names and symbols. + */ + function getAllKeys(object) { + return baseGetAllKeys(object, keys, getSymbols); + } + + module.exports = getAllKeys; + + +/***/ }), +/* 187 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayPush = __webpack_require__(107), + isArray = __webpack_require__(112); + + /** + * The base implementation of `getAllKeys` and `getAllKeysIn` which uses + * `keysFunc` and `symbolsFunc` to get the enumerable property names and + * symbols of `object`. + * + * @private + * @param {Object} object The object to query. + * @param {Function} keysFunc The function to get the keys of `object`. + * @param {Function} symbolsFunc The function to get the symbols of `object`. + * @returns {Array} Returns the array of property names and symbols. + */ + function baseGetAllKeys(object, keysFunc, symbolsFunc) { + var result = keysFunc(object); + return isArray(object) ? result : arrayPush(result, symbolsFunc(object)); + } + + module.exports = baseGetAllKeys; + + +/***/ }), +/* 188 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayFilter = __webpack_require__(189), + stubArray = __webpack_require__(190); + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Built-in value references. */ + var propertyIsEnumerable = objectProto.propertyIsEnumerable; + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeGetSymbols = Object.getOwnPropertySymbols; + + /** + * Creates an array of the own enumerable symbols of `object`. + * + * @private + * @param {Object} object The object to query. + * @returns {Array} Returns the array of symbols. + */ + var getSymbols = !nativeGetSymbols ? stubArray : function(object) { + if (object == null) { + return []; + } + object = Object(object); + return arrayFilter(nativeGetSymbols(object), function(symbol) { + return propertyIsEnumerable.call(object, symbol); + }); + }; + + module.exports = getSymbols; + + +/***/ }), +/* 189 */ +/***/ (function(module, exports) { + + /** + * A specialized version of `_.filter` for arrays without support for + * iteratee shorthands. + * + * @private + * @param {Array} [array] The array to iterate over. + * @param {Function} predicate The function invoked per iteration. + * @returns {Array} Returns the new filtered array. + */ + function arrayFilter(array, predicate) { + var index = -1, + length = array == null ? 0 : array.length, + resIndex = 0, + result = []; + + while (++index < length) { + var value = array[index]; + if (predicate(value, index, array)) { + result[resIndex++] = value; + } + } + return result; + } + + module.exports = arrayFilter; + + +/***/ }), +/* 190 */ +/***/ (function(module, exports) { + + /** + * This method returns a new empty array. + * + * @static + * @memberOf _ + * @since 4.13.0 + * @category Util + * @returns {Array} Returns the new empty array. + * @example + * + * var arrays = _.times(2, _.stubArray); + * + * console.log(arrays); + * // => [[], []] + * + * console.log(arrays[0] === arrays[1]); + * // => false + */ + function stubArray() { + return []; + } + + module.exports = stubArray; + + +/***/ }), +/* 191 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayLikeKeys = __webpack_require__(192), + baseKeys = __webpack_require__(199), + isArrayLike = __webpack_require__(89); + + /** + * Creates an array of the own enumerable property names of `object`. + * + * **Note:** Non-object values are coerced to objects. See the + * [ES spec](http://ecma-international.org/ecma-262/7.0/#sec-object.keys) + * for more details. + * + * @static + * @since 0.1.0 + * @memberOf _ + * @category Object + * @param {Object} object The object to query. + * @returns {Array} Returns the array of property names. + * @example + * + * function Foo() { + * this.a = 1; + * this.b = 2; + * } + * + * Foo.prototype.c = 3; + * + * _.keys(new Foo); + * // => ['a', 'b'] (iteration order is not guaranteed) + * + * _.keys('hi'); + * // => ['0', '1'] + */ + function keys(object) { + return isArrayLike(object) ? arrayLikeKeys(object) : baseKeys(object); + } + + module.exports = keys; + + +/***/ }), +/* 192 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseTimes = __webpack_require__(193), + isArguments = __webpack_require__(110), + isArray = __webpack_require__(112), + isBuffer = __webpack_require__(194), + isIndex = __webpack_require__(99), + isTypedArray = __webpack_require__(196); + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * Creates an array of the enumerable property names of the array-like `value`. + * + * @private + * @param {*} value The value to query. + * @param {boolean} inherited Specify returning inherited property names. + * @returns {Array} Returns the array of property names. + */ + function arrayLikeKeys(value, inherited) { + var isArr = isArray(value), + isArg = !isArr && isArguments(value), + isBuff = !isArr && !isArg && isBuffer(value), + isType = !isArr && !isArg && !isBuff && isTypedArray(value), + skipIndexes = isArr || isArg || isBuff || isType, + result = skipIndexes ? baseTimes(value.length, String) : [], + length = result.length; + + for (var key in value) { + if ((inherited || hasOwnProperty.call(value, key)) && + !(skipIndexes && ( + // Safari 9 has enumerable `arguments.length` in strict mode. + key == 'length' || + // Node.js 0.10 has enumerable non-index properties on buffers. + (isBuff && (key == 'offset' || key == 'parent')) || + // PhantomJS 2 has enumerable non-index properties on typed arrays. + (isType && (key == 'buffer' || key == 'byteLength' || key == 'byteOffset')) || + // Skip index properties. + isIndex(key, length) + ))) { + result.push(key); + } + } + return result; + } + + module.exports = arrayLikeKeys; + + +/***/ }), +/* 193 */ +/***/ (function(module, exports) { + + /** + * The base implementation of `_.times` without support for iteratee shorthands + * or max array length checks. + * + * @private + * @param {number} n The number of times to invoke `iteratee`. + * @param {Function} iteratee The function invoked per iteration. + * @returns {Array} Returns the array of results. + */ + function baseTimes(n, iteratee) { + var index = -1, + result = Array(n); + + while (++index < n) { + result[index] = iteratee(index); + } + return result; + } + + module.exports = baseTimes; + + +/***/ }), +/* 194 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(module) {var root = __webpack_require__(93), + stubFalse = __webpack_require__(195); + + /** Detect free variable `exports`. */ + var freeExports = typeof exports == 'object' && exports && !exports.nodeType && exports; + + /** Detect free variable `module`. */ + var freeModule = freeExports && typeof module == 'object' && module && !module.nodeType && module; + + /** Detect the popular CommonJS extension `module.exports`. */ + var moduleExports = freeModule && freeModule.exports === freeExports; + + /** Built-in value references. */ + var Buffer = moduleExports ? root.Buffer : undefined; + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeIsBuffer = Buffer ? Buffer.isBuffer : undefined; + + /** + * Checks if `value` is a buffer. + * + * @static + * @memberOf _ + * @since 4.3.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a buffer, else `false`. + * @example + * + * _.isBuffer(new Buffer(2)); + * // => true + * + * _.isBuffer(new Uint8Array(2)); + * // => false + */ + var isBuffer = nativeIsBuffer || stubFalse; + + module.exports = isBuffer; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(59)(module))) + +/***/ }), +/* 195 */ +/***/ (function(module, exports) { + + /** + * This method returns `false`. + * + * @static + * @memberOf _ + * @since 4.13.0 + * @category Util + * @returns {boolean} Returns `false`. + * @example + * + * _.times(2, _.stubFalse); + * // => [false, false] + */ + function stubFalse() { + return false; + } + + module.exports = stubFalse; + + +/***/ }), +/* 196 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIsTypedArray = __webpack_require__(197), + baseUnary = __webpack_require__(155), + nodeUtil = __webpack_require__(198); + + /* Node.js helper references. */ + var nodeIsTypedArray = nodeUtil && nodeUtil.isTypedArray; + + /** + * Checks if `value` is classified as a typed array. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Lang + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a typed array, else `false`. + * @example + * + * _.isTypedArray(new Uint8Array); + * // => true + * + * _.isTypedArray([]); + * // => false + */ + var isTypedArray = nodeIsTypedArray ? baseUnary(nodeIsTypedArray) : baseIsTypedArray; + + module.exports = isTypedArray; + + +/***/ }), +/* 197 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseGetTag = __webpack_require__(91), + isLength = __webpack_require__(98), + isObjectLike = __webpack_require__(104); + + /** `Object#toString` result references. */ + var argsTag = '[object Arguments]', + arrayTag = '[object Array]', + boolTag = '[object Boolean]', + dateTag = '[object Date]', + errorTag = '[object Error]', + funcTag = '[object Function]', + mapTag = '[object Map]', + numberTag = '[object Number]', + objectTag = '[object Object]', + regexpTag = '[object RegExp]', + setTag = '[object Set]', + stringTag = '[object String]', + weakMapTag = '[object WeakMap]'; + + var arrayBufferTag = '[object ArrayBuffer]', + dataViewTag = '[object DataView]', + float32Tag = '[object Float32Array]', + float64Tag = '[object Float64Array]', + int8Tag = '[object Int8Array]', + int16Tag = '[object Int16Array]', + int32Tag = '[object Int32Array]', + uint8Tag = '[object Uint8Array]', + uint8ClampedTag = '[object Uint8ClampedArray]', + uint16Tag = '[object Uint16Array]', + uint32Tag = '[object Uint32Array]'; + + /** Used to identify `toStringTag` values of typed arrays. */ + var typedArrayTags = {}; + typedArrayTags[float32Tag] = typedArrayTags[float64Tag] = + typedArrayTags[int8Tag] = typedArrayTags[int16Tag] = + typedArrayTags[int32Tag] = typedArrayTags[uint8Tag] = + typedArrayTags[uint8ClampedTag] = typedArrayTags[uint16Tag] = + typedArrayTags[uint32Tag] = true; + typedArrayTags[argsTag] = typedArrayTags[arrayTag] = + typedArrayTags[arrayBufferTag] = typedArrayTags[boolTag] = + typedArrayTags[dataViewTag] = typedArrayTags[dateTag] = + typedArrayTags[errorTag] = typedArrayTags[funcTag] = + typedArrayTags[mapTag] = typedArrayTags[numberTag] = + typedArrayTags[objectTag] = typedArrayTags[regexpTag] = + typedArrayTags[setTag] = typedArrayTags[stringTag] = + typedArrayTags[weakMapTag] = false; + + /** + * The base implementation of `_.isTypedArray` without Node.js optimizations. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a typed array, else `false`. + */ + function baseIsTypedArray(value) { + return isObjectLike(value) && + isLength(value.length) && !!typedArrayTags[baseGetTag(value)]; + } + + module.exports = baseIsTypedArray; + + +/***/ }), +/* 198 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(module) {var freeGlobal = __webpack_require__(94); + + /** Detect free variable `exports`. */ + var freeExports = typeof exports == 'object' && exports && !exports.nodeType && exports; + + /** Detect free variable `module`. */ + var freeModule = freeExports && typeof module == 'object' && module && !module.nodeType && module; + + /** Detect the popular CommonJS extension `module.exports`. */ + var moduleExports = freeModule && freeModule.exports === freeExports; + + /** Detect free variable `process` from Node.js. */ + var freeProcess = moduleExports && freeGlobal.process; + + /** Used to access faster Node.js helpers. */ + var nodeUtil = (function() { + try { + // Use `util.types` for Node.js 10+. + var types = freeModule && freeModule.require && freeModule.require('util').types; + + if (types) { + return types; + } + + // Legacy `process.binding('util')` for Node.js < 10. + return freeProcess && freeProcess.binding && freeProcess.binding('util'); + } catch (e) {} + }()); + + module.exports = nodeUtil; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(59)(module))) + +/***/ }), +/* 199 */ +/***/ (function(module, exports, __webpack_require__) { + + var isPrototype = __webpack_require__(200), + nativeKeys = __webpack_require__(201); + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * The base implementation of `_.keys` which doesn't treat sparse arrays as dense. + * + * @private + * @param {Object} object The object to query. + * @returns {Array} Returns the array of property names. + */ + function baseKeys(object) { + if (!isPrototype(object)) { + return nativeKeys(object); + } + var result = []; + for (var key in Object(object)) { + if (hasOwnProperty.call(object, key) && key != 'constructor') { + result.push(key); + } + } + return result; + } + + module.exports = baseKeys; + + +/***/ }), +/* 200 */ +/***/ (function(module, exports) { + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** + * Checks if `value` is likely a prototype object. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` is a prototype, else `false`. + */ + function isPrototype(value) { + var Ctor = value && value.constructor, + proto = (typeof Ctor == 'function' && Ctor.prototype) || objectProto; + + return value === proto; + } + + module.exports = isPrototype; + + +/***/ }), +/* 201 */ +/***/ (function(module, exports, __webpack_require__) { + + var overArg = __webpack_require__(202); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeKeys = overArg(Object.keys, Object); + + module.exports = nativeKeys; + + +/***/ }), +/* 202 */ +/***/ (function(module, exports) { + + /** + * Creates a unary function that invokes `func` with its argument transformed. + * + * @private + * @param {Function} func The function to wrap. + * @param {Function} transform The argument transform. + * @returns {Function} Returns the new function. + */ + function overArg(func, transform) { + return function(arg) { + return func(transform(arg)); + }; + } + + module.exports = overArg; + + +/***/ }), +/* 203 */ +/***/ (function(module, exports, __webpack_require__) { + + var DataView = __webpack_require__(204), + Map = __webpack_require__(139), + Promise = __webpack_require__(205), + Set = __webpack_require__(206), + WeakMap = __webpack_require__(207), + baseGetTag = __webpack_require__(91), + toSource = __webpack_require__(126); + + /** `Object#toString` result references. */ + var mapTag = '[object Map]', + objectTag = '[object Object]', + promiseTag = '[object Promise]', + setTag = '[object Set]', + weakMapTag = '[object WeakMap]'; + + var dataViewTag = '[object DataView]'; + + /** Used to detect maps, sets, and weakmaps. */ + var dataViewCtorString = toSource(DataView), + mapCtorString = toSource(Map), + promiseCtorString = toSource(Promise), + setCtorString = toSource(Set), + weakMapCtorString = toSource(WeakMap); + + /** + * Gets the `toStringTag` of `value`. + * + * @private + * @param {*} value The value to query. + * @returns {string} Returns the `toStringTag`. + */ + var getTag = baseGetTag; + + // Fallback for data views, maps, sets, and weak maps in IE 11 and promises in Node.js < 6. + if ((DataView && getTag(new DataView(new ArrayBuffer(1))) != dataViewTag) || + (Map && getTag(new Map) != mapTag) || + (Promise && getTag(Promise.resolve()) != promiseTag) || + (Set && getTag(new Set) != setTag) || + (WeakMap && getTag(new WeakMap) != weakMapTag)) { + getTag = function(value) { + var result = baseGetTag(value), + Ctor = result == objectTag ? value.constructor : undefined, + ctorString = Ctor ? toSource(Ctor) : ''; + + if (ctorString) { + switch (ctorString) { + case dataViewCtorString: return dataViewTag; + case mapCtorString: return mapTag; + case promiseCtorString: return promiseTag; + case setCtorString: return setTag; + case weakMapCtorString: return weakMapTag; + } + } + return result; + }; + } + + module.exports = getTag; + + +/***/ }), +/* 204 */ +/***/ (function(module, exports, __webpack_require__) { + + var getNative = __webpack_require__(122), + root = __webpack_require__(93); + + /* Built-in method references that are verified to be native. */ + var DataView = getNative(root, 'DataView'); + + module.exports = DataView; + + +/***/ }), +/* 205 */ +/***/ (function(module, exports, __webpack_require__) { + + var getNative = __webpack_require__(122), + root = __webpack_require__(93); + + /* Built-in method references that are verified to be native. */ + var Promise = getNative(root, 'Promise'); + + module.exports = Promise; + + +/***/ }), +/* 206 */ +/***/ (function(module, exports, __webpack_require__) { + + var getNative = __webpack_require__(122), + root = __webpack_require__(93); + + /* Built-in method references that are verified to be native. */ + var Set = getNative(root, 'Set'); + + module.exports = Set; + + +/***/ }), +/* 207 */ +/***/ (function(module, exports, __webpack_require__) { + + var getNative = __webpack_require__(122), + root = __webpack_require__(93); + + /* Built-in method references that are verified to be native. */ + var WeakMap = getNative(root, 'WeakMap'); + + module.exports = WeakMap; + + +/***/ }), +/* 208 */ +/***/ (function(module, exports, __webpack_require__) { + + var isStrictComparable = __webpack_require__(209), + keys = __webpack_require__(191); + + /** + * Gets the property names, values, and compare flags of `object`. + * + * @private + * @param {Object} object The object to query. + * @returns {Array} Returns the match data of `object`. + */ + function getMatchData(object) { + var result = keys(object), + length = result.length; + + while (length--) { + var key = result[length], + value = object[key]; + + result[length] = [key, value, isStrictComparable(value)]; + } + return result; + } + + module.exports = getMatchData; + + +/***/ }), +/* 209 */ +/***/ (function(module, exports, __webpack_require__) { + + var isObject = __webpack_require__(97); + + /** + * Checks if `value` is suitable for strict equality comparisons, i.e. `===`. + * + * @private + * @param {*} value The value to check. + * @returns {boolean} Returns `true` if `value` if suitable for strict + * equality comparisons, else `false`. + */ + function isStrictComparable(value) { + return value === value && !isObject(value); + } + + module.exports = isStrictComparable; + + +/***/ }), +/* 210 */ +/***/ (function(module, exports) { + + /** + * A specialized version of `matchesProperty` for source values suitable + * for strict equality comparisons, i.e. `===`. + * + * @private + * @param {string} key The key of the property to get. + * @param {*} srcValue The value to match. + * @returns {Function} Returns the new spec function. + */ + function matchesStrictComparable(key, srcValue) { + return function(object) { + if (object == null) { + return false; + } + return object[key] === srcValue && + (srcValue !== undefined || (key in Object(object))); + }; + } + + module.exports = matchesStrictComparable; + + +/***/ }), +/* 211 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIsEqual = __webpack_require__(177), + get = __webpack_require__(212), + hasIn = __webpack_require__(222), + isKey = __webpack_require__(215), + isStrictComparable = __webpack_require__(209), + matchesStrictComparable = __webpack_require__(210), + toKey = __webpack_require__(221); + + /** Used to compose bitmasks for value comparisons. */ + var COMPARE_PARTIAL_FLAG = 1, + COMPARE_UNORDERED_FLAG = 2; + + /** + * The base implementation of `_.matchesProperty` which doesn't clone `srcValue`. + * + * @private + * @param {string} path The path of the property to get. + * @param {*} srcValue The value to match. + * @returns {Function} Returns the new spec function. + */ + function baseMatchesProperty(path, srcValue) { + if (isKey(path) && isStrictComparable(srcValue)) { + return matchesStrictComparable(toKey(path), srcValue); + } + return function(object) { + var objValue = get(object, path); + return (objValue === undefined && objValue === srcValue) + ? hasIn(object, path) + : baseIsEqual(srcValue, objValue, COMPARE_PARTIAL_FLAG | COMPARE_UNORDERED_FLAG); + }; + } + + module.exports = baseMatchesProperty; + + +/***/ }), +/* 212 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseGet = __webpack_require__(213); + + /** + * Gets the value at `path` of `object`. If the resolved value is + * `undefined`, the `defaultValue` is returned in its place. + * + * @static + * @memberOf _ + * @since 3.7.0 + * @category Object + * @param {Object} object The object to query. + * @param {Array|string} path The path of the property to get. + * @param {*} [defaultValue] The value returned for `undefined` resolved values. + * @returns {*} Returns the resolved value. + * @example + * + * var object = { 'a': [{ 'b': { 'c': 3 } }] }; + * + * _.get(object, 'a[0].b.c'); + * // => 3 + * + * _.get(object, ['a', '0', 'b', 'c']); + * // => 3 + * + * _.get(object, 'a.b.c', 'default'); + * // => 'default' + */ + function get(object, path, defaultValue) { + var result = object == null ? undefined : baseGet(object, path); + return result === undefined ? defaultValue : result; + } + + module.exports = get; + + +/***/ }), +/* 213 */ +/***/ (function(module, exports, __webpack_require__) { + + var castPath = __webpack_require__(214), + toKey = __webpack_require__(221); + + /** + * The base implementation of `_.get` without support for default values. + * + * @private + * @param {Object} object The object to query. + * @param {Array|string} path The path of the property to get. + * @returns {*} Returns the resolved value. + */ + function baseGet(object, path) { + path = castPath(path, object); + + var index = 0, + length = path.length; + + while (object != null && index < length) { + object = object[toKey(path[index++])]; + } + return (index && index == length) ? object : undefined; + } + + module.exports = baseGet; + + +/***/ }), +/* 214 */ +/***/ (function(module, exports, __webpack_require__) { + + var isArray = __webpack_require__(112), + isKey = __webpack_require__(215), + stringToPath = __webpack_require__(216), + toString = __webpack_require__(219); + + /** + * Casts `value` to a path array if it's not one. + * + * @private + * @param {*} value The value to inspect. + * @param {Object} [object] The object to query keys on. + * @returns {Array} Returns the cast property path array. + */ + function castPath(value, object) { + if (isArray(value)) { + return value; + } + return isKey(value, object) ? [value] : stringToPath(toString(value)); + } + + module.exports = castPath; + + +/***/ }), +/* 215 */ +/***/ (function(module, exports, __webpack_require__) { + + var isArray = __webpack_require__(112), + isSymbol = __webpack_require__(103); + + /** Used to match property names within property paths. */ + var reIsDeepProp = /\.|\[(?:[^[\]]*|(["'])(?:(?!\1)[^\\]|\\.)*?\1)\]/, + reIsPlainProp = /^\w*$/; + + /** + * Checks if `value` is a property name and not a property path. + * + * @private + * @param {*} value The value to check. + * @param {Object} [object] The object to query keys on. + * @returns {boolean} Returns `true` if `value` is a property name, else `false`. + */ + function isKey(value, object) { + if (isArray(value)) { + return false; + } + var type = typeof value; + if (type == 'number' || type == 'symbol' || type == 'boolean' || + value == null || isSymbol(value)) { + return true; + } + return reIsPlainProp.test(value) || !reIsDeepProp.test(value) || + (object != null && value in Object(object)); + } + + module.exports = isKey; + + +/***/ }), +/* 216 */ +/***/ (function(module, exports, __webpack_require__) { + + var memoizeCapped = __webpack_require__(217); + + /** Used to match property names within property paths. */ + var rePropName = /[^.[\]]+|\[(?:(-?\d+(?:\.\d+)?)|(["'])((?:(?!\2)[^\\]|\\.)*?)\2)\]|(?=(?:\.|\[\])(?:\.|\[\]|$))/g; + + /** Used to match backslashes in property paths. */ + var reEscapeChar = /\\(\\)?/g; + + /** + * Converts `string` to a property path array. + * + * @private + * @param {string} string The string to convert. + * @returns {Array} Returns the property path array. + */ + var stringToPath = memoizeCapped(function(string) { + var result = []; + if (string.charCodeAt(0) === 46 /* . */) { + result.push(''); + } + string.replace(rePropName, function(match, number, quote, subString) { + result.push(quote ? subString.replace(reEscapeChar, '$1') : (number || match)); + }); + return result; + }); + + module.exports = stringToPath; + + +/***/ }), +/* 217 */ +/***/ (function(module, exports, __webpack_require__) { + + var memoize = __webpack_require__(218); + + /** Used as the maximum memoize cache size. */ + var MAX_MEMOIZE_SIZE = 500; + + /** + * A specialized version of `_.memoize` which clears the memoized function's + * cache when it exceeds `MAX_MEMOIZE_SIZE`. + * + * @private + * @param {Function} func The function to have its output memoized. + * @returns {Function} Returns the new memoized function. + */ + function memoizeCapped(func) { + var result = memoize(func, function(key) { + if (cache.size === MAX_MEMOIZE_SIZE) { + cache.clear(); + } + return key; + }); + + var cache = result.cache; + return result; + } + + module.exports = memoizeCapped; + + +/***/ }), +/* 218 */ +/***/ (function(module, exports, __webpack_require__) { + + var MapCache = __webpack_require__(117); + + /** Error message constants. */ + var FUNC_ERROR_TEXT = 'Expected a function'; + + /** + * Creates a function that memoizes the result of `func`. If `resolver` is + * provided, it determines the cache key for storing the result based on the + * arguments provided to the memoized function. By default, the first argument + * provided to the memoized function is used as the map cache key. The `func` + * is invoked with the `this` binding of the memoized function. + * + * **Note:** The cache is exposed as the `cache` property on the memoized + * function. Its creation may be customized by replacing the `_.memoize.Cache` + * constructor with one whose instances implement the + * [`Map`](http://ecma-international.org/ecma-262/7.0/#sec-properties-of-the-map-prototype-object) + * method interface of `clear`, `delete`, `get`, `has`, and `set`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Function + * @param {Function} func The function to have its output memoized. + * @param {Function} [resolver] The function to resolve the cache key. + * @returns {Function} Returns the new memoized function. + * @example + * + * var object = { 'a': 1, 'b': 2 }; + * var other = { 'c': 3, 'd': 4 }; + * + * var values = _.memoize(_.values); + * values(object); + * // => [1, 2] + * + * values(other); + * // => [3, 4] + * + * object.a = 2; + * values(object); + * // => [1, 2] + * + * // Modify the result cache. + * values.cache.set(object, ['a', 'b']); + * values(object); + * // => ['a', 'b'] + * + * // Replace `_.memoize.Cache`. + * _.memoize.Cache = WeakMap; + */ + function memoize(func, resolver) { + if (typeof func != 'function' || (resolver != null && typeof resolver != 'function')) { + throw new TypeError(FUNC_ERROR_TEXT); + } + var memoized = function() { + var args = arguments, + key = resolver ? resolver.apply(this, args) : args[0], + cache = memoized.cache; + + if (cache.has(key)) { + return cache.get(key); + } + var result = func.apply(this, args); + memoized.cache = cache.set(key, result) || cache; + return result; + }; + memoized.cache = new (memoize.Cache || MapCache); + return memoized; + } + + // Expose `MapCache`. + memoize.Cache = MapCache; + + module.exports = memoize; + + +/***/ }), +/* 219 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseToString = __webpack_require__(220); + + /** + * Converts `value` to a string. An empty string is returned for `null` + * and `undefined` values. The sign of `-0` is preserved. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to convert. + * @returns {string} Returns the converted string. + * @example + * + * _.toString(null); + * // => '' + * + * _.toString(-0); + * // => '-0' + * + * _.toString([1, 2, 3]); + * // => '1,2,3' + */ + function toString(value) { + return value == null ? '' : baseToString(value); + } + + module.exports = toString; + + +/***/ }), +/* 220 */ +/***/ (function(module, exports, __webpack_require__) { + + var Symbol = __webpack_require__(92), + arrayMap = __webpack_require__(154), + isArray = __webpack_require__(112), + isSymbol = __webpack_require__(103); + + /** Used as references for various `Number` constants. */ + var INFINITY = 1 / 0; + + /** Used to convert symbols to primitives and strings. */ + var symbolProto = Symbol ? Symbol.prototype : undefined, + symbolToString = symbolProto ? symbolProto.toString : undefined; + + /** + * The base implementation of `_.toString` which doesn't convert nullish + * values to empty strings. + * + * @private + * @param {*} value The value to process. + * @returns {string} Returns the string. + */ + function baseToString(value) { + // Exit early for strings to avoid a performance hit in some environments. + if (typeof value == 'string') { + return value; + } + if (isArray(value)) { + // Recursively convert values (susceptible to call stack limits). + return arrayMap(value, baseToString) + ''; + } + if (isSymbol(value)) { + return symbolToString ? symbolToString.call(value) : ''; + } + var result = (value + ''); + return (result == '0' && (1 / value) == -INFINITY) ? '-0' : result; + } + + module.exports = baseToString; + + +/***/ }), +/* 221 */ +/***/ (function(module, exports, __webpack_require__) { + + var isSymbol = __webpack_require__(103); + + /** Used as references for various `Number` constants. */ + var INFINITY = 1 / 0; + + /** + * Converts `value` to a string key if it's not a string or symbol. + * + * @private + * @param {*} value The value to inspect. + * @returns {string|symbol} Returns the key. + */ + function toKey(value) { + if (typeof value == 'string' || isSymbol(value)) { + return value; + } + var result = (value + ''); + return (result == '0' && (1 / value) == -INFINITY) ? '-0' : result; + } + + module.exports = toKey; + + +/***/ }), +/* 222 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseHasIn = __webpack_require__(223), + hasPath = __webpack_require__(224); + + /** + * Checks if `path` is a direct or inherited property of `object`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Object + * @param {Object} object The object to query. + * @param {Array|string} path The path to check. + * @returns {boolean} Returns `true` if `path` exists, else `false`. + * @example + * + * var object = _.create({ 'a': _.create({ 'b': 2 }) }); + * + * _.hasIn(object, 'a'); + * // => true + * + * _.hasIn(object, 'a.b'); + * // => true + * + * _.hasIn(object, ['a', 'b']); + * // => true + * + * _.hasIn(object, 'b'); + * // => false + */ + function hasIn(object, path) { + return object != null && hasPath(object, path, baseHasIn); + } + + module.exports = hasIn; + + +/***/ }), +/* 223 */ +/***/ (function(module, exports) { + + /** + * The base implementation of `_.hasIn` without support for deep paths. + * + * @private + * @param {Object} [object] The object to query. + * @param {Array|string} key The key to check. + * @returns {boolean} Returns `true` if `key` exists, else `false`. + */ + function baseHasIn(object, key) { + return object != null && key in Object(object); + } + + module.exports = baseHasIn; + + +/***/ }), +/* 224 */ +/***/ (function(module, exports, __webpack_require__) { + + var castPath = __webpack_require__(214), + isArguments = __webpack_require__(110), + isArray = __webpack_require__(112), + isIndex = __webpack_require__(99), + isLength = __webpack_require__(98), + toKey = __webpack_require__(221); + + /** + * Checks if `path` exists on `object`. + * + * @private + * @param {Object} object The object to query. + * @param {Array|string} path The path to check. + * @param {Function} hasFunc The function to check properties. + * @returns {boolean} Returns `true` if `path` exists, else `false`. + */ + function hasPath(object, path, hasFunc) { + path = castPath(path, object); + + var index = -1, + length = path.length, + result = false; + + while (++index < length) { + var key = toKey(path[index]); + if (!(result = object != null && hasFunc(object, key))) { + break; + } + object = object[key]; + } + if (result || ++index != length) { + return result; + } + length = object == null ? 0 : object.length; + return !!length && isLength(length) && isIndex(key, length) && + (isArray(object) || isArguments(object)); + } + + module.exports = hasPath; + + +/***/ }), +/* 225 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseProperty = __webpack_require__(226), + basePropertyDeep = __webpack_require__(227), + isKey = __webpack_require__(215), + toKey = __webpack_require__(221); + + /** + * Creates a function that returns the value at `path` of a given object. + * + * @static + * @memberOf _ + * @since 2.4.0 + * @category Util + * @param {Array|string} path The path of the property to get. + * @returns {Function} Returns the new accessor function. + * @example + * + * var objects = [ + * { 'a': { 'b': 2 } }, + * { 'a': { 'b': 1 } } + * ]; + * + * _.map(objects, _.property('a.b')); + * // => [2, 1] + * + * _.map(_.sortBy(objects, _.property(['a', 'b'])), 'a.b'); + * // => [1, 2] + */ + function property(path) { + return isKey(path) ? baseProperty(toKey(path)) : basePropertyDeep(path); + } + + module.exports = property; + + +/***/ }), +/* 226 */ +/***/ (function(module, exports) { + + /** + * The base implementation of `_.property` without support for deep paths. + * + * @private + * @param {string} key The key of the property to get. + * @returns {Function} Returns the new accessor function. + */ + function baseProperty(key) { + return function(object) { + return object == null ? undefined : object[key]; + }; + } + + module.exports = baseProperty; + + +/***/ }), +/* 227 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseGet = __webpack_require__(213); + + /** + * A specialized version of `baseProperty` which supports deep paths. + * + * @private + * @param {Array|string} path The path of the property to get. + * @returns {Function} Returns the new accessor function. + */ + function basePropertyDeep(path) { + return function(object) { + return baseGet(object, path); + }; + } + + module.exports = basePropertyDeep; + + +/***/ }), +/* 228 */ +/***/ (function(module, exports) { + + /** + * Gets the last element of `array`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to query. + * @returns {*} Returns the last element of `array`. + * @example + * + * _.last([1, 2, 3]); + * // => 3 + */ + function last(array) { + var length = array == null ? 0 : array.length; + return length ? array[length - 1] : undefined; + } + + module.exports = last; + + +/***/ }), +/* 229 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseDifference = __webpack_require__(115), + baseFlatten = __webpack_require__(108), + baseRest = __webpack_require__(157), + isArrayLikeObject = __webpack_require__(166), + last = __webpack_require__(228); + + /** + * This method is like `_.difference` except that it accepts `comparator` + * which is invoked to compare elements of `array` to `values`. The order and + * references of result values are determined by the first array. The comparator + * is invoked with two arguments: (arrVal, othVal). + * + * **Note:** Unlike `_.pullAllWith`, this method returns a new array. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {...Array} [values] The values to exclude. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new array of filtered values. + * @example + * + * var objects = [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }]; + * + * _.differenceWith(objects, [{ 'x': 1, 'y': 2 }], _.isEqual); + * // => [{ 'x': 2, 'y': 1 }] + */ + var differenceWith = baseRest(function(array, values) { + var comparator = last(values); + if (isArrayLikeObject(comparator)) { + comparator = undefined; + } + return isArrayLikeObject(array) + ? baseDifference(array, baseFlatten(values, 1, isArrayLikeObject, true), undefined, comparator) + : []; + }); + + module.exports = differenceWith; + + +/***/ }), +/* 230 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86), + toInteger = __webpack_require__(100); + + /** + * Creates a slice of `array` with `n` elements dropped from the beginning. + * + * @static + * @memberOf _ + * @since 0.5.0 + * @category Array + * @param {Array} array The array to query. + * @param {number} [n=1] The number of elements to drop. + * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. + * @returns {Array} Returns the slice of `array`. + * @example + * + * _.drop([1, 2, 3]); + * // => [2, 3] + * + * _.drop([1, 2, 3], 2); + * // => [3] + * + * _.drop([1, 2, 3], 5); + * // => [] + * + * _.drop([1, 2, 3], 0); + * // => [1, 2, 3] + */ + function drop(array, n, guard) { + var length = array == null ? 0 : array.length; + if (!length) { + return []; + } + n = (guard || n === undefined) ? 1 : toInteger(n); + return baseSlice(array, n < 0 ? 0 : n, length); + } + + module.exports = drop; + + +/***/ }), +/* 231 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86), + toInteger = __webpack_require__(100); + + /** + * Creates a slice of `array` with `n` elements dropped from the end. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to query. + * @param {number} [n=1] The number of elements to drop. + * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. + * @returns {Array} Returns the slice of `array`. + * @example + * + * _.dropRight([1, 2, 3]); + * // => [1, 2] + * + * _.dropRight([1, 2, 3], 2); + * // => [1] + * + * _.dropRight([1, 2, 3], 5); + * // => [] + * + * _.dropRight([1, 2, 3], 0); + * // => [1, 2, 3] + */ + function dropRight(array, n, guard) { + var length = array == null ? 0 : array.length; + if (!length) { + return []; + } + n = (guard || n === undefined) ? 1 : toInteger(n); + n = length - n; + return baseSlice(array, 0, n < 0 ? 0 : n); + } + + module.exports = dropRight; + + +/***/ }), +/* 232 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + baseWhile = __webpack_require__(233); + + /** + * Creates a slice of `array` excluding elements dropped from the end. + * Elements are dropped until `predicate` returns falsey. The predicate is + * invoked with three arguments: (value, index, array). + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to query. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @returns {Array} Returns the slice of `array`. + * @example + * + * var users = [ + * { 'user': 'barney', 'active': true }, + * { 'user': 'fred', 'active': false }, + * { 'user': 'pebbles', 'active': false } + * ]; + * + * _.dropRightWhile(users, function(o) { return !o.active; }); + * // => objects for ['barney'] + * + * // The `_.matches` iteratee shorthand. + * _.dropRightWhile(users, { 'user': 'pebbles', 'active': false }); + * // => objects for ['barney', 'fred'] + * + * // The `_.matchesProperty` iteratee shorthand. + * _.dropRightWhile(users, ['active', false]); + * // => objects for ['barney'] + * + * // The `_.property` iteratee shorthand. + * _.dropRightWhile(users, 'active'); + * // => objects for ['barney', 'fred', 'pebbles'] + */ + function dropRightWhile(array, predicate) { + return (array && array.length) + ? baseWhile(array, baseIteratee(predicate, 3), true, true) + : []; + } + + module.exports = dropRightWhile; + + +/***/ }), +/* 233 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86); + + /** + * The base implementation of methods like `_.dropWhile` and `_.takeWhile` + * without support for iteratee shorthands. + * + * @private + * @param {Array} array The array to query. + * @param {Function} predicate The function invoked per iteration. + * @param {boolean} [isDrop] Specify dropping elements instead of taking them. + * @param {boolean} [fromRight] Specify iterating from right to left. + * @returns {Array} Returns the slice of `array`. + */ + function baseWhile(array, predicate, isDrop, fromRight) { + var length = array.length, + index = fromRight ? length : -1; + + while ((fromRight ? index-- : ++index < length) && + predicate(array[index], index, array)) {} + + return isDrop + ? baseSlice(array, (fromRight ? 0 : index), (fromRight ? index + 1 : length)) + : baseSlice(array, (fromRight ? index + 1 : 0), (fromRight ? length : index)); + } + + module.exports = baseWhile; + + +/***/ }), +/* 234 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + baseWhile = __webpack_require__(233); + + /** + * Creates a slice of `array` excluding elements dropped from the beginning. + * Elements are dropped until `predicate` returns falsey. The predicate is + * invoked with three arguments: (value, index, array). + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to query. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @returns {Array} Returns the slice of `array`. + * @example + * + * var users = [ + * { 'user': 'barney', 'active': false }, + * { 'user': 'fred', 'active': false }, + * { 'user': 'pebbles', 'active': true } + * ]; + * + * _.dropWhile(users, function(o) { return !o.active; }); + * // => objects for ['pebbles'] + * + * // The `_.matches` iteratee shorthand. + * _.dropWhile(users, { 'user': 'barney', 'active': false }); + * // => objects for ['fred', 'pebbles'] + * + * // The `_.matchesProperty` iteratee shorthand. + * _.dropWhile(users, ['active', false]); + * // => objects for ['pebbles'] + * + * // The `_.property` iteratee shorthand. + * _.dropWhile(users, 'active'); + * // => objects for ['barney', 'fred', 'pebbles'] + */ + function dropWhile(array, predicate) { + return (array && array.length) + ? baseWhile(array, baseIteratee(predicate, 3), true) + : []; + } + + module.exports = dropWhile; + + +/***/ }), +/* 235 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFill = __webpack_require__(236), + isIterateeCall = __webpack_require__(87); + + /** + * Fills elements of `array` with `value` from `start` up to, but not + * including, `end`. + * + * **Note:** This method mutates `array`. + * + * @static + * @memberOf _ + * @since 3.2.0 + * @category Array + * @param {Array} array The array to fill. + * @param {*} value The value to fill `array` with. + * @param {number} [start=0] The start position. + * @param {number} [end=array.length] The end position. + * @returns {Array} Returns `array`. + * @example + * + * var array = [1, 2, 3]; + * + * _.fill(array, 'a'); + * console.log(array); + * // => ['a', 'a', 'a'] + * + * _.fill(Array(3), 2); + * // => [2, 2, 2] + * + * _.fill([4, 6, 8, 10], '*', 1, 3); + * // => [4, '*', '*', 10] + */ + function fill(array, value, start, end) { + var length = array == null ? 0 : array.length; + if (!length) { + return []; + } + if (start && typeof start != 'number' && isIterateeCall(array, value, start)) { + start = 0; + end = length; + } + return baseFill(array, value, start, end); + } + + module.exports = fill; + + +/***/ }), +/* 236 */ +/***/ (function(module, exports, __webpack_require__) { + + var toInteger = __webpack_require__(100), + toLength = __webpack_require__(237); + + /** + * The base implementation of `_.fill` without an iteratee call guard. + * + * @private + * @param {Array} array The array to fill. + * @param {*} value The value to fill `array` with. + * @param {number} [start=0] The start position. + * @param {number} [end=array.length] The end position. + * @returns {Array} Returns `array`. + */ + function baseFill(array, value, start, end) { + var length = array.length; + + start = toInteger(start); + if (start < 0) { + start = -start > length ? 0 : (length + start); + } + end = (end === undefined || end > length) ? length : toInteger(end); + if (end < 0) { + end += length; + } + end = start > end ? 0 : toLength(end); + while (start < end) { + array[start++] = value; + } + return array; + } + + module.exports = baseFill; + + +/***/ }), +/* 237 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseClamp = __webpack_require__(238), + toInteger = __webpack_require__(100); + + /** Used as references for the maximum length and index of an array. */ + var MAX_ARRAY_LENGTH = 4294967295; + + /** + * Converts `value` to an integer suitable for use as the length of an + * array-like object. + * + * **Note:** This method is based on + * [`ToLength`](http://ecma-international.org/ecma-262/7.0/#sec-tolength). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Lang + * @param {*} value The value to convert. + * @returns {number} Returns the converted integer. + * @example + * + * _.toLength(3.2); + * // => 3 + * + * _.toLength(Number.MIN_VALUE); + * // => 0 + * + * _.toLength(Infinity); + * // => 4294967295 + * + * _.toLength('3.2'); + * // => 3 + */ + function toLength(value) { + return value ? baseClamp(toInteger(value), 0, MAX_ARRAY_LENGTH) : 0; + } + + module.exports = toLength; + + +/***/ }), +/* 238 */ +/***/ (function(module, exports) { + + /** + * The base implementation of `_.clamp` which doesn't coerce arguments. + * + * @private + * @param {number} number The number to clamp. + * @param {number} [lower] The lower bound. + * @param {number} upper The upper bound. + * @returns {number} Returns the clamped number. + */ + function baseClamp(number, lower, upper) { + if (number === number) { + if (upper !== undefined) { + number = number <= upper ? number : upper; + } + if (lower !== undefined) { + number = number >= lower ? number : lower; + } + } + return number; + } + + module.exports = baseClamp; + + +/***/ }), +/* 239 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFindIndex = __webpack_require__(150), + baseIteratee = __webpack_require__(168), + toInteger = __webpack_require__(100); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeMax = Math.max; + + /** + * This method is like `_.find` except that it returns the index of the first + * element `predicate` returns truthy for instead of the element itself. + * + * @static + * @memberOf _ + * @since 1.1.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @param {number} [fromIndex=0] The index to search from. + * @returns {number} Returns the index of the found element, else `-1`. + * @example + * + * var users = [ + * { 'user': 'barney', 'active': false }, + * { 'user': 'fred', 'active': false }, + * { 'user': 'pebbles', 'active': true } + * ]; + * + * _.findIndex(users, function(o) { return o.user == 'barney'; }); + * // => 0 + * + * // The `_.matches` iteratee shorthand. + * _.findIndex(users, { 'user': 'fred', 'active': false }); + * // => 1 + * + * // The `_.matchesProperty` iteratee shorthand. + * _.findIndex(users, ['active', false]); + * // => 0 + * + * // The `_.property` iteratee shorthand. + * _.findIndex(users, 'active'); + * // => 2 + */ + function findIndex(array, predicate, fromIndex) { + var length = array == null ? 0 : array.length; + if (!length) { + return -1; + } + var index = fromIndex == null ? 0 : toInteger(fromIndex); + if (index < 0) { + index = nativeMax(length + index, 0); + } + return baseFindIndex(array, baseIteratee(predicate, 3), index); + } + + module.exports = findIndex; + + +/***/ }), +/* 240 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFindIndex = __webpack_require__(150), + baseIteratee = __webpack_require__(168), + toInteger = __webpack_require__(100); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeMax = Math.max, + nativeMin = Math.min; + + /** + * This method is like `_.findIndex` except that it iterates over elements + * of `collection` from right to left. + * + * @static + * @memberOf _ + * @since 2.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @param {number} [fromIndex=array.length-1] The index to search from. + * @returns {number} Returns the index of the found element, else `-1`. + * @example + * + * var users = [ + * { 'user': 'barney', 'active': true }, + * { 'user': 'fred', 'active': false }, + * { 'user': 'pebbles', 'active': false } + * ]; + * + * _.findLastIndex(users, function(o) { return o.user == 'pebbles'; }); + * // => 2 + * + * // The `_.matches` iteratee shorthand. + * _.findLastIndex(users, { 'user': 'barney', 'active': true }); + * // => 0 + * + * // The `_.matchesProperty` iteratee shorthand. + * _.findLastIndex(users, ['active', false]); + * // => 2 + * + * // The `_.property` iteratee shorthand. + * _.findLastIndex(users, 'active'); + * // => 0 + */ + function findLastIndex(array, predicate, fromIndex) { + var length = array == null ? 0 : array.length; + if (!length) { + return -1; + } + var index = length - 1; + if (fromIndex !== undefined) { + index = toInteger(fromIndex); + index = fromIndex < 0 + ? nativeMax(length + index, 0) + : nativeMin(index, length - 1); + } + return baseFindIndex(array, baseIteratee(predicate, 3), index, true); + } + + module.exports = findLastIndex; + + +/***/ }), +/* 241 */ +/***/ (function(module, exports, __webpack_require__) { + + module.exports = __webpack_require__(242); + + +/***/ }), +/* 242 */ +/***/ (function(module, exports) { + + /** + * Gets the first element of `array`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @alias first + * @category Array + * @param {Array} array The array to query. + * @returns {*} Returns the first element of `array`. + * @example + * + * _.head([1, 2, 3]); + * // => 1 + * + * _.head([]); + * // => undefined + */ + function head(array) { + return (array && array.length) ? array[0] : undefined; + } + + module.exports = head; + + +/***/ }), +/* 243 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFlatten = __webpack_require__(108); + + /** + * Flattens `array` a single level deep. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to flatten. + * @returns {Array} Returns the new flattened array. + * @example + * + * _.flatten([1, [2, [3, [4]], 5]]); + * // => [1, 2, [3, [4]], 5] + */ + function flatten(array) { + var length = array == null ? 0 : array.length; + return length ? baseFlatten(array, 1) : []; + } + + module.exports = flatten; + + +/***/ }), +/* 244 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFlatten = __webpack_require__(108); + + /** Used as references for various `Number` constants. */ + var INFINITY = 1 / 0; + + /** + * Recursively flattens `array`. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to flatten. + * @returns {Array} Returns the new flattened array. + * @example + * + * _.flattenDeep([1, [2, [3, [4]], 5]]); + * // => [1, 2, 3, 4, 5] + */ + function flattenDeep(array) { + var length = array == null ? 0 : array.length; + return length ? baseFlatten(array, INFINITY) : []; + } + + module.exports = flattenDeep; + + +/***/ }), +/* 245 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFlatten = __webpack_require__(108), + toInteger = __webpack_require__(100); + + /** + * Recursively flatten `array` up to `depth` times. + * + * @static + * @memberOf _ + * @since 4.4.0 + * @category Array + * @param {Array} array The array to flatten. + * @param {number} [depth=1] The maximum recursion depth. + * @returns {Array} Returns the new flattened array. + * @example + * + * var array = [1, [2, [3, [4]], 5]]; + * + * _.flattenDepth(array, 1); + * // => [1, 2, [3, [4]], 5] + * + * _.flattenDepth(array, 2); + * // => [1, 2, 3, [4], 5] + */ + function flattenDepth(array, depth) { + var length = array == null ? 0 : array.length; + if (!length) { + return []; + } + depth = depth === undefined ? 1 : toInteger(depth); + return baseFlatten(array, depth); + } + + module.exports = flattenDepth; + + +/***/ }), +/* 246 */ +/***/ (function(module, exports) { + + /** + * The inverse of `_.toPairs`; this method returns an object composed + * from key-value `pairs`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} pairs The key-value pairs. + * @returns {Object} Returns the new object. + * @example + * + * _.fromPairs([['a', 1], ['b', 2]]); + * // => { 'a': 1, 'b': 2 } + */ + function fromPairs(pairs) { + var index = -1, + length = pairs == null ? 0 : pairs.length, + result = {}; + + while (++index < length) { + var pair = pairs[index]; + result[pair[0]] = pair[1]; + } + return result; + } + + module.exports = fromPairs; + + +/***/ }), +/* 247 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIndexOf = __webpack_require__(149), + toInteger = __webpack_require__(100); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeMax = Math.max; + + /** + * Gets the index at which the first occurrence of `value` is found in `array` + * using [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. If `fromIndex` is negative, it's used as the + * offset from the end of `array`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @param {number} [fromIndex=0] The index to search from. + * @returns {number} Returns the index of the matched value, else `-1`. + * @example + * + * _.indexOf([1, 2, 1, 2], 2); + * // => 1 + * + * // Search from the `fromIndex`. + * _.indexOf([1, 2, 1, 2], 2, 2); + * // => 3 + */ + function indexOf(array, value, fromIndex) { + var length = array == null ? 0 : array.length; + if (!length) { + return -1; + } + var index = fromIndex == null ? 0 : toInteger(fromIndex); + if (index < 0) { + index = nativeMax(length + index, 0); + } + return baseIndexOf(array, value, index); + } + + module.exports = indexOf; + + +/***/ }), +/* 248 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86); + + /** + * Gets all but the last element of `array`. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to query. + * @returns {Array} Returns the slice of `array`. + * @example + * + * _.initial([1, 2, 3]); + * // => [1, 2] + */ + function initial(array) { + var length = array == null ? 0 : array.length; + return length ? baseSlice(array, 0, -1) : []; + } + + module.exports = initial; + + +/***/ }), +/* 249 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayMap = __webpack_require__(154), + baseIntersection = __webpack_require__(250), + baseRest = __webpack_require__(157), + castArrayLikeObject = __webpack_require__(251); + + /** + * Creates an array of unique values that are included in all given arrays + * using [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. The order and references of result values are + * determined by the first array. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @returns {Array} Returns the new array of intersecting values. + * @example + * + * _.intersection([2, 1], [2, 3]); + * // => [2] + */ + var intersection = baseRest(function(arrays) { + var mapped = arrayMap(arrays, castArrayLikeObject); + return (mapped.length && mapped[0] === arrays[0]) + ? baseIntersection(mapped) + : []; + }); + + module.exports = intersection; + + +/***/ }), +/* 250 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetCache = __webpack_require__(116), + arrayIncludes = __webpack_require__(148), + arrayIncludesWith = __webpack_require__(153), + arrayMap = __webpack_require__(154), + baseUnary = __webpack_require__(155), + cacheHas = __webpack_require__(156); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeMin = Math.min; + + /** + * The base implementation of methods like `_.intersection`, without support + * for iteratee shorthands, that accepts an array of arrays to inspect. + * + * @private + * @param {Array} arrays The arrays to inspect. + * @param {Function} [iteratee] The iteratee invoked per element. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new array of shared values. + */ + function baseIntersection(arrays, iteratee, comparator) { + var includes = comparator ? arrayIncludesWith : arrayIncludes, + length = arrays[0].length, + othLength = arrays.length, + othIndex = othLength, + caches = Array(othLength), + maxLength = Infinity, + result = []; + + while (othIndex--) { + var array = arrays[othIndex]; + if (othIndex && iteratee) { + array = arrayMap(array, baseUnary(iteratee)); + } + maxLength = nativeMin(array.length, maxLength); + caches[othIndex] = !comparator && (iteratee || (length >= 120 && array.length >= 120)) + ? new SetCache(othIndex && array) + : undefined; + } + array = arrays[0]; + + var index = -1, + seen = caches[0]; + + outer: + while (++index < length && result.length < maxLength) { + var value = array[index], + computed = iteratee ? iteratee(value) : value; + + value = (comparator || value !== 0) ? value : 0; + if (!(seen + ? cacheHas(seen, computed) + : includes(result, computed, comparator) + )) { + othIndex = othLength; + while (--othIndex) { + var cache = caches[othIndex]; + if (!(cache + ? cacheHas(cache, computed) + : includes(arrays[othIndex], computed, comparator)) + ) { + continue outer; + } + } + if (seen) { + seen.push(computed); + } + result.push(value); + } + } + return result; + } + + module.exports = baseIntersection; + + +/***/ }), +/* 251 */ +/***/ (function(module, exports, __webpack_require__) { + + var isArrayLikeObject = __webpack_require__(166); + + /** + * Casts `value` to an empty array if it's not an array like object. + * + * @private + * @param {*} value The value to inspect. + * @returns {Array|Object} Returns the cast array-like object. + */ + function castArrayLikeObject(value) { + return isArrayLikeObject(value) ? value : []; + } + + module.exports = castArrayLikeObject; + + +/***/ }), +/* 252 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayMap = __webpack_require__(154), + baseIntersection = __webpack_require__(250), + baseIteratee = __webpack_require__(168), + baseRest = __webpack_require__(157), + castArrayLikeObject = __webpack_require__(251), + last = __webpack_require__(228); + + /** + * This method is like `_.intersection` except that it accepts `iteratee` + * which is invoked for each element of each `arrays` to generate the criterion + * by which they're compared. The order and references of result values are + * determined by the first array. The iteratee is invoked with one argument: + * (value). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @param {Function} [iteratee=_.identity] The iteratee invoked per element. + * @returns {Array} Returns the new array of intersecting values. + * @example + * + * _.intersectionBy([2.1, 1.2], [2.3, 3.4], Math.floor); + * // => [2.1] + * + * // The `_.property` iteratee shorthand. + * _.intersectionBy([{ 'x': 1 }], [{ 'x': 2 }, { 'x': 1 }], 'x'); + * // => [{ 'x': 1 }] + */ + var intersectionBy = baseRest(function(arrays) { + var iteratee = last(arrays), + mapped = arrayMap(arrays, castArrayLikeObject); + + if (iteratee === last(mapped)) { + iteratee = undefined; + } else { + mapped.pop(); + } + return (mapped.length && mapped[0] === arrays[0]) + ? baseIntersection(mapped, baseIteratee(iteratee, 2)) + : []; + }); + + module.exports = intersectionBy; + + +/***/ }), +/* 253 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayMap = __webpack_require__(154), + baseIntersection = __webpack_require__(250), + baseRest = __webpack_require__(157), + castArrayLikeObject = __webpack_require__(251), + last = __webpack_require__(228); + + /** + * This method is like `_.intersection` except that it accepts `comparator` + * which is invoked to compare elements of `arrays`. The order and references + * of result values are determined by the first array. The comparator is + * invoked with two arguments: (arrVal, othVal). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new array of intersecting values. + * @example + * + * var objects = [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }]; + * var others = [{ 'x': 1, 'y': 1 }, { 'x': 1, 'y': 2 }]; + * + * _.intersectionWith(objects, others, _.isEqual); + * // => [{ 'x': 1, 'y': 2 }] + */ + var intersectionWith = baseRest(function(arrays) { + var comparator = last(arrays), + mapped = arrayMap(arrays, castArrayLikeObject); + + comparator = typeof comparator == 'function' ? comparator : undefined; + if (comparator) { + mapped.pop(); + } + return (mapped.length && mapped[0] === arrays[0]) + ? baseIntersection(mapped, undefined, comparator) + : []; + }); + + module.exports = intersectionWith; + + +/***/ }), +/* 254 */ +/***/ (function(module, exports) { + + /** Used for built-in method references. */ + var arrayProto = Array.prototype; + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeJoin = arrayProto.join; + + /** + * Converts all elements in `array` into a string separated by `separator`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to convert. + * @param {string} [separator=','] The element separator. + * @returns {string} Returns the joined string. + * @example + * + * _.join(['a', 'b', 'c'], '~'); + * // => 'a~b~c' + */ + function join(array, separator) { + return array == null ? '' : nativeJoin.call(array, separator); + } + + module.exports = join; + + +/***/ }), +/* 255 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFindIndex = __webpack_require__(150), + baseIsNaN = __webpack_require__(151), + strictLastIndexOf = __webpack_require__(256), + toInteger = __webpack_require__(100); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeMax = Math.max, + nativeMin = Math.min; + + /** + * This method is like `_.indexOf` except that it iterates over elements of + * `array` from right to left. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @param {number} [fromIndex=array.length-1] The index to search from. + * @returns {number} Returns the index of the matched value, else `-1`. + * @example + * + * _.lastIndexOf([1, 2, 1, 2], 2); + * // => 3 + * + * // Search from the `fromIndex`. + * _.lastIndexOf([1, 2, 1, 2], 2, 2); + * // => 1 + */ + function lastIndexOf(array, value, fromIndex) { + var length = array == null ? 0 : array.length; + if (!length) { + return -1; + } + var index = length; + if (fromIndex !== undefined) { + index = toInteger(fromIndex); + index = index < 0 ? nativeMax(length + index, 0) : nativeMin(index, length - 1); + } + return value === value + ? strictLastIndexOf(array, value, index) + : baseFindIndex(array, baseIsNaN, index, true); + } + + module.exports = lastIndexOf; + + +/***/ }), +/* 256 */ +/***/ (function(module, exports) { + + /** + * A specialized version of `_.lastIndexOf` which performs strict equality + * comparisons of values, i.e. `===`. + * + * @private + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @param {number} fromIndex The index to search from. + * @returns {number} Returns the index of the matched value, else `-1`. + */ + function strictLastIndexOf(array, value, fromIndex) { + var index = fromIndex + 1; + while (index--) { + if (array[index] === value) { + return index; + } + } + return index; + } + + module.exports = strictLastIndexOf; + + +/***/ }), +/* 257 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseNth = __webpack_require__(258), + toInteger = __webpack_require__(100); + + /** + * Gets the element at index `n` of `array`. If `n` is negative, the nth + * element from the end is returned. + * + * @static + * @memberOf _ + * @since 4.11.0 + * @category Array + * @param {Array} array The array to query. + * @param {number} [n=0] The index of the element to return. + * @returns {*} Returns the nth element of `array`. + * @example + * + * var array = ['a', 'b', 'c', 'd']; + * + * _.nth(array, 1); + * // => 'b' + * + * _.nth(array, -2); + * // => 'c'; + */ + function nth(array, n) { + return (array && array.length) ? baseNth(array, toInteger(n)) : undefined; + } + + module.exports = nth; + + +/***/ }), +/* 258 */ +/***/ (function(module, exports, __webpack_require__) { + + var isIndex = __webpack_require__(99); + + /** + * The base implementation of `_.nth` which doesn't coerce arguments. + * + * @private + * @param {Array} array The array to query. + * @param {number} n The index of the element to return. + * @returns {*} Returns the nth element of `array`. + */ + function baseNth(array, n) { + var length = array.length; + if (!length) { + return; + } + n += n < 0 ? length : 0; + return isIndex(n, length) ? array[n] : undefined; + } + + module.exports = baseNth; + + +/***/ }), +/* 259 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseRest = __webpack_require__(157), + pullAll = __webpack_require__(260); + + /** + * Removes all given values from `array` using + * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. + * + * **Note:** Unlike `_.without`, this method mutates `array`. Use `_.remove` + * to remove elements from an array by predicate. + * + * @static + * @memberOf _ + * @since 2.0.0 + * @category Array + * @param {Array} array The array to modify. + * @param {...*} [values] The values to remove. + * @returns {Array} Returns `array`. + * @example + * + * var array = ['a', 'b', 'c', 'a', 'b', 'c']; + * + * _.pull(array, 'a', 'c'); + * console.log(array); + * // => ['b', 'b'] + */ + var pull = baseRest(pullAll); + + module.exports = pull; + + +/***/ }), +/* 260 */ +/***/ (function(module, exports, __webpack_require__) { + + var basePullAll = __webpack_require__(261); + + /** + * This method is like `_.pull` except that it accepts an array of values to remove. + * + * **Note:** Unlike `_.difference`, this method mutates `array`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to modify. + * @param {Array} values The values to remove. + * @returns {Array} Returns `array`. + * @example + * + * var array = ['a', 'b', 'c', 'a', 'b', 'c']; + * + * _.pullAll(array, ['a', 'c']); + * console.log(array); + * // => ['b', 'b'] + */ + function pullAll(array, values) { + return (array && array.length && values && values.length) + ? basePullAll(array, values) + : array; + } + + module.exports = pullAll; + + +/***/ }), +/* 261 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayMap = __webpack_require__(154), + baseIndexOf = __webpack_require__(149), + baseIndexOfWith = __webpack_require__(262), + baseUnary = __webpack_require__(155), + copyArray = __webpack_require__(113); + + /** Used for built-in method references. */ + var arrayProto = Array.prototype; + + /** Built-in value references. */ + var splice = arrayProto.splice; + + /** + * The base implementation of `_.pullAllBy` without support for iteratee + * shorthands. + * + * @private + * @param {Array} array The array to modify. + * @param {Array} values The values to remove. + * @param {Function} [iteratee] The iteratee invoked per element. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns `array`. + */ + function basePullAll(array, values, iteratee, comparator) { + var indexOf = comparator ? baseIndexOfWith : baseIndexOf, + index = -1, + length = values.length, + seen = array; + + if (array === values) { + values = copyArray(values); + } + if (iteratee) { + seen = arrayMap(array, baseUnary(iteratee)); + } + while (++index < length) { + var fromIndex = 0, + value = values[index], + computed = iteratee ? iteratee(value) : value; + + while ((fromIndex = indexOf(seen, computed, fromIndex, comparator)) > -1) { + if (seen !== array) { + splice.call(seen, fromIndex, 1); + } + splice.call(array, fromIndex, 1); + } + } + return array; + } + + module.exports = basePullAll; + + +/***/ }), +/* 262 */ +/***/ (function(module, exports) { + + /** + * This function is like `baseIndexOf` except that it accepts a comparator. + * + * @private + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @param {number} fromIndex The index to search from. + * @param {Function} comparator The comparator invoked per element. + * @returns {number} Returns the index of the matched value, else `-1`. + */ + function baseIndexOfWith(array, value, fromIndex, comparator) { + var index = fromIndex - 1, + length = array.length; + + while (++index < length) { + if (comparator(array[index], value)) { + return index; + } + } + return -1; + } + + module.exports = baseIndexOfWith; + + +/***/ }), +/* 263 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + basePullAll = __webpack_require__(261); + + /** + * This method is like `_.pullAll` except that it accepts `iteratee` which is + * invoked for each element of `array` and `values` to generate the criterion + * by which they're compared. The iteratee is invoked with one argument: (value). + * + * **Note:** Unlike `_.differenceBy`, this method mutates `array`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to modify. + * @param {Array} values The values to remove. + * @param {Function} [iteratee=_.identity] The iteratee invoked per element. + * @returns {Array} Returns `array`. + * @example + * + * var array = [{ 'x': 1 }, { 'x': 2 }, { 'x': 3 }, { 'x': 1 }]; + * + * _.pullAllBy(array, [{ 'x': 1 }, { 'x': 3 }], 'x'); + * console.log(array); + * // => [{ 'x': 2 }] + */ + function pullAllBy(array, values, iteratee) { + return (array && array.length && values && values.length) + ? basePullAll(array, values, baseIteratee(iteratee, 2)) + : array; + } + + module.exports = pullAllBy; + + +/***/ }), +/* 264 */ +/***/ (function(module, exports, __webpack_require__) { + + var basePullAll = __webpack_require__(261); + + /** + * This method is like `_.pullAll` except that it accepts `comparator` which + * is invoked to compare elements of `array` to `values`. The comparator is + * invoked with two arguments: (arrVal, othVal). + * + * **Note:** Unlike `_.differenceWith`, this method mutates `array`. + * + * @static + * @memberOf _ + * @since 4.6.0 + * @category Array + * @param {Array} array The array to modify. + * @param {Array} values The values to remove. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns `array`. + * @example + * + * var array = [{ 'x': 1, 'y': 2 }, { 'x': 3, 'y': 4 }, { 'x': 5, 'y': 6 }]; + * + * _.pullAllWith(array, [{ 'x': 3, 'y': 4 }], _.isEqual); + * console.log(array); + * // => [{ 'x': 1, 'y': 2 }, { 'x': 5, 'y': 6 }] + */ + function pullAllWith(array, values, comparator) { + return (array && array.length && values && values.length) + ? basePullAll(array, values, undefined, comparator) + : array; + } + + module.exports = pullAllWith; + + +/***/ }), +/* 265 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayMap = __webpack_require__(154), + baseAt = __webpack_require__(266), + basePullAt = __webpack_require__(267), + compareAscending = __webpack_require__(270), + flatRest = __webpack_require__(271), + isIndex = __webpack_require__(99); + + /** + * Removes elements from `array` corresponding to `indexes` and returns an + * array of removed elements. + * + * **Note:** Unlike `_.at`, this method mutates `array`. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to modify. + * @param {...(number|number[])} [indexes] The indexes of elements to remove. + * @returns {Array} Returns the new array of removed elements. + * @example + * + * var array = ['a', 'b', 'c', 'd']; + * var pulled = _.pullAt(array, [1, 3]); + * + * console.log(array); + * // => ['a', 'c'] + * + * console.log(pulled); + * // => ['b', 'd'] + */ + var pullAt = flatRest(function(array, indexes) { + var length = array == null ? 0 : array.length, + result = baseAt(array, indexes); + + basePullAt(array, arrayMap(indexes, function(index) { + return isIndex(index, length) ? +index : index; + }).sort(compareAscending)); + + return result; + }); + + module.exports = pullAt; + + +/***/ }), +/* 266 */ +/***/ (function(module, exports, __webpack_require__) { + + var get = __webpack_require__(212); + + /** + * The base implementation of `_.at` without support for individual paths. + * + * @private + * @param {Object} object The object to iterate over. + * @param {string[]} paths The property paths to pick. + * @returns {Array} Returns the picked elements. + */ + function baseAt(object, paths) { + var index = -1, + length = paths.length, + result = Array(length), + skip = object == null; + + while (++index < length) { + result[index] = skip ? undefined : get(object, paths[index]); + } + return result; + } + + module.exports = baseAt; + + +/***/ }), +/* 267 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseUnset = __webpack_require__(268), + isIndex = __webpack_require__(99); + + /** Used for built-in method references. */ + var arrayProto = Array.prototype; + + /** Built-in value references. */ + var splice = arrayProto.splice; + + /** + * The base implementation of `_.pullAt` without support for individual + * indexes or capturing the removed elements. + * + * @private + * @param {Array} array The array to modify. + * @param {number[]} indexes The indexes of elements to remove. + * @returns {Array} Returns `array`. + */ + function basePullAt(array, indexes) { + var length = array ? indexes.length : 0, + lastIndex = length - 1; + + while (length--) { + var index = indexes[length]; + if (length == lastIndex || index !== previous) { + var previous = index; + if (isIndex(index)) { + splice.call(array, index, 1); + } else { + baseUnset(array, index); + } + } + } + return array; + } + + module.exports = basePullAt; + + +/***/ }), +/* 268 */ +/***/ (function(module, exports, __webpack_require__) { + + var castPath = __webpack_require__(214), + last = __webpack_require__(228), + parent = __webpack_require__(269), + toKey = __webpack_require__(221); + + /** + * The base implementation of `_.unset`. + * + * @private + * @param {Object} object The object to modify. + * @param {Array|string} path The property path to unset. + * @returns {boolean} Returns `true` if the property is deleted, else `false`. + */ + function baseUnset(object, path) { + path = castPath(path, object); + object = parent(object, path); + return object == null || delete object[toKey(last(path))]; + } + + module.exports = baseUnset; + + +/***/ }), +/* 269 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseGet = __webpack_require__(213), + baseSlice = __webpack_require__(86); + + /** + * Gets the parent value at `path` of `object`. + * + * @private + * @param {Object} object The object to query. + * @param {Array} path The path to get the parent value of. + * @returns {*} Returns the parent value. + */ + function parent(object, path) { + return path.length < 2 ? object : baseGet(object, baseSlice(path, 0, -1)); + } + + module.exports = parent; + + +/***/ }), +/* 270 */ +/***/ (function(module, exports, __webpack_require__) { + + var isSymbol = __webpack_require__(103); + + /** + * Compares values to sort them in ascending order. + * + * @private + * @param {*} value The value to compare. + * @param {*} other The other value to compare. + * @returns {number} Returns the sort order indicator for `value`. + */ + function compareAscending(value, other) { + if (value !== other) { + var valIsDefined = value !== undefined, + valIsNull = value === null, + valIsReflexive = value === value, + valIsSymbol = isSymbol(value); + + var othIsDefined = other !== undefined, + othIsNull = other === null, + othIsReflexive = other === other, + othIsSymbol = isSymbol(other); + + if ((!othIsNull && !othIsSymbol && !valIsSymbol && value > other) || + (valIsSymbol && othIsDefined && othIsReflexive && !othIsNull && !othIsSymbol) || + (valIsNull && othIsDefined && othIsReflexive) || + (!valIsDefined && othIsReflexive) || + !valIsReflexive) { + return 1; + } + if ((!valIsNull && !valIsSymbol && !othIsSymbol && value < other) || + (othIsSymbol && valIsDefined && valIsReflexive && !valIsNull && !valIsSymbol) || + (othIsNull && valIsDefined && valIsReflexive) || + (!othIsDefined && valIsReflexive) || + !othIsReflexive) { + return -1; + } + } + return 0; + } + + module.exports = compareAscending; + + +/***/ }), +/* 271 */ +/***/ (function(module, exports, __webpack_require__) { + + var flatten = __webpack_require__(243), + overRest = __webpack_require__(159), + setToString = __webpack_require__(161); + + /** + * A specialized version of `baseRest` which flattens the rest array. + * + * @private + * @param {Function} func The function to apply a rest parameter to. + * @returns {Function} Returns the new function. + */ + function flatRest(func) { + return setToString(overRest(func, undefined, flatten), func + ''); + } + + module.exports = flatRest; + + +/***/ }), +/* 272 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + basePullAt = __webpack_require__(267); + + /** + * Removes all elements from `array` that `predicate` returns truthy for + * and returns an array of the removed elements. The predicate is invoked + * with three arguments: (value, index, array). + * + * **Note:** Unlike `_.filter`, this method mutates `array`. Use `_.pull` + * to pull elements from an array by value. + * + * @static + * @memberOf _ + * @since 2.0.0 + * @category Array + * @param {Array} array The array to modify. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @returns {Array} Returns the new array of removed elements. + * @example + * + * var array = [1, 2, 3, 4]; + * var evens = _.remove(array, function(n) { + * return n % 2 == 0; + * }); + * + * console.log(array); + * // => [1, 3] + * + * console.log(evens); + * // => [2, 4] + */ + function remove(array, predicate) { + var result = []; + if (!(array && array.length)) { + return result; + } + var index = -1, + indexes = [], + length = array.length; + + predicate = baseIteratee(predicate, 3); + while (++index < length) { + var value = array[index]; + if (predicate(value, index, array)) { + result.push(value); + indexes.push(index); + } + } + basePullAt(array, indexes); + return result; + } + + module.exports = remove; + + +/***/ }), +/* 273 */ +/***/ (function(module, exports) { + + /** Used for built-in method references. */ + var arrayProto = Array.prototype; + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeReverse = arrayProto.reverse; + + /** + * Reverses `array` so that the first element becomes the last, the second + * element becomes the second to last, and so on. + * + * **Note:** This method mutates `array` and is based on + * [`Array#reverse`](https://mdn.io/Array/reverse). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to modify. + * @returns {Array} Returns `array`. + * @example + * + * var array = [1, 2, 3]; + * + * _.reverse(array); + * // => [3, 2, 1] + * + * console.log(array); + * // => [3, 2, 1] + */ + function reverse(array) { + return array == null ? array : nativeReverse.call(array); + } + + module.exports = reverse; + + +/***/ }), +/* 274 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86), + isIterateeCall = __webpack_require__(87), + toInteger = __webpack_require__(100); + + /** + * Creates a slice of `array` from `start` up to, but not including, `end`. + * + * **Note:** This method is used instead of + * [`Array#slice`](https://mdn.io/Array/slice) to ensure dense arrays are + * returned. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to slice. + * @param {number} [start=0] The start position. + * @param {number} [end=array.length] The end position. + * @returns {Array} Returns the slice of `array`. + */ + function slice(array, start, end) { + var length = array == null ? 0 : array.length; + if (!length) { + return []; + } + if (end && typeof end != 'number' && isIterateeCall(array, start, end)) { + start = 0; + end = length; + } + else { + start = start == null ? 0 : toInteger(start); + end = end === undefined ? length : toInteger(end); + } + return baseSlice(array, start, end); + } + + module.exports = slice; + + +/***/ }), +/* 275 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSortedIndex = __webpack_require__(276); + + /** + * Uses a binary search to determine the lowest index at which `value` + * should be inserted into `array` in order to maintain its sort order. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The sorted array to inspect. + * @param {*} value The value to evaluate. + * @returns {number} Returns the index at which `value` should be inserted + * into `array`. + * @example + * + * _.sortedIndex([30, 50], 40); + * // => 1 + */ + function sortedIndex(array, value) { + return baseSortedIndex(array, value); + } + + module.exports = sortedIndex; + + +/***/ }), +/* 276 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSortedIndexBy = __webpack_require__(277), + identity = __webpack_require__(158), + isSymbol = __webpack_require__(103); + + /** Used as references for the maximum length and index of an array. */ + var MAX_ARRAY_LENGTH = 4294967295, + HALF_MAX_ARRAY_LENGTH = MAX_ARRAY_LENGTH >>> 1; + + /** + * The base implementation of `_.sortedIndex` and `_.sortedLastIndex` which + * performs a binary search of `array` to determine the index at which `value` + * should be inserted into `array` in order to maintain its sort order. + * + * @private + * @param {Array} array The sorted array to inspect. + * @param {*} value The value to evaluate. + * @param {boolean} [retHighest] Specify returning the highest qualified index. + * @returns {number} Returns the index at which `value` should be inserted + * into `array`. + */ + function baseSortedIndex(array, value, retHighest) { + var low = 0, + high = array == null ? low : array.length; + + if (typeof value == 'number' && value === value && high <= HALF_MAX_ARRAY_LENGTH) { + while (low < high) { + var mid = (low + high) >>> 1, + computed = array[mid]; + + if (computed !== null && !isSymbol(computed) && + (retHighest ? (computed <= value) : (computed < value))) { + low = mid + 1; + } else { + high = mid; + } + } + return high; + } + return baseSortedIndexBy(array, value, identity, retHighest); + } + + module.exports = baseSortedIndex; + + +/***/ }), +/* 277 */ +/***/ (function(module, exports, __webpack_require__) { + + var isSymbol = __webpack_require__(103); + + /** Used as references for the maximum length and index of an array. */ + var MAX_ARRAY_LENGTH = 4294967295, + MAX_ARRAY_INDEX = MAX_ARRAY_LENGTH - 1; + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeFloor = Math.floor, + nativeMin = Math.min; + + /** + * The base implementation of `_.sortedIndexBy` and `_.sortedLastIndexBy` + * which invokes `iteratee` for `value` and each element of `array` to compute + * their sort ranking. The iteratee is invoked with one argument; (value). + * + * @private + * @param {Array} array The sorted array to inspect. + * @param {*} value The value to evaluate. + * @param {Function} iteratee The iteratee invoked per element. + * @param {boolean} [retHighest] Specify returning the highest qualified index. + * @returns {number} Returns the index at which `value` should be inserted + * into `array`. + */ + function baseSortedIndexBy(array, value, iteratee, retHighest) { + value = iteratee(value); + + var low = 0, + high = array == null ? 0 : array.length, + valIsNaN = value !== value, + valIsNull = value === null, + valIsSymbol = isSymbol(value), + valIsUndefined = value === undefined; + + while (low < high) { + var mid = nativeFloor((low + high) / 2), + computed = iteratee(array[mid]), + othIsDefined = computed !== undefined, + othIsNull = computed === null, + othIsReflexive = computed === computed, + othIsSymbol = isSymbol(computed); + + if (valIsNaN) { + var setLow = retHighest || othIsReflexive; + } else if (valIsUndefined) { + setLow = othIsReflexive && (retHighest || othIsDefined); + } else if (valIsNull) { + setLow = othIsReflexive && othIsDefined && (retHighest || !othIsNull); + } else if (valIsSymbol) { + setLow = othIsReflexive && othIsDefined && !othIsNull && (retHighest || !othIsSymbol); + } else if (othIsNull || othIsSymbol) { + setLow = false; + } else { + setLow = retHighest ? (computed <= value) : (computed < value); + } + if (setLow) { + low = mid + 1; + } else { + high = mid; + } + } + return nativeMin(high, MAX_ARRAY_INDEX); + } + + module.exports = baseSortedIndexBy; + + +/***/ }), +/* 278 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + baseSortedIndexBy = __webpack_require__(277); + + /** + * This method is like `_.sortedIndex` except that it accepts `iteratee` + * which is invoked for `value` and each element of `array` to compute their + * sort ranking. The iteratee is invoked with one argument: (value). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The sorted array to inspect. + * @param {*} value The value to evaluate. + * @param {Function} [iteratee=_.identity] The iteratee invoked per element. + * @returns {number} Returns the index at which `value` should be inserted + * into `array`. + * @example + * + * var objects = [{ 'x': 4 }, { 'x': 5 }]; + * + * _.sortedIndexBy(objects, { 'x': 4 }, function(o) { return o.x; }); + * // => 0 + * + * // The `_.property` iteratee shorthand. + * _.sortedIndexBy(objects, { 'x': 4 }, 'x'); + * // => 0 + */ + function sortedIndexBy(array, value, iteratee) { + return baseSortedIndexBy(array, value, baseIteratee(iteratee, 2)); + } + + module.exports = sortedIndexBy; + + +/***/ }), +/* 279 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSortedIndex = __webpack_require__(276), + eq = __webpack_require__(88); + + /** + * This method is like `_.indexOf` except that it performs a binary + * search on a sorted `array`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @returns {number} Returns the index of the matched value, else `-1`. + * @example + * + * _.sortedIndexOf([4, 5, 5, 5, 6], 5); + * // => 1 + */ + function sortedIndexOf(array, value) { + var length = array == null ? 0 : array.length; + if (length) { + var index = baseSortedIndex(array, value); + if (index < length && eq(array[index], value)) { + return index; + } + } + return -1; + } + + module.exports = sortedIndexOf; + + +/***/ }), +/* 280 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSortedIndex = __webpack_require__(276); + + /** + * This method is like `_.sortedIndex` except that it returns the highest + * index at which `value` should be inserted into `array` in order to + * maintain its sort order. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The sorted array to inspect. + * @param {*} value The value to evaluate. + * @returns {number} Returns the index at which `value` should be inserted + * into `array`. + * @example + * + * _.sortedLastIndex([4, 5, 5, 5, 6], 5); + * // => 4 + */ + function sortedLastIndex(array, value) { + return baseSortedIndex(array, value, true); + } + + module.exports = sortedLastIndex; + + +/***/ }), +/* 281 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + baseSortedIndexBy = __webpack_require__(277); + + /** + * This method is like `_.sortedLastIndex` except that it accepts `iteratee` + * which is invoked for `value` and each element of `array` to compute their + * sort ranking. The iteratee is invoked with one argument: (value). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The sorted array to inspect. + * @param {*} value The value to evaluate. + * @param {Function} [iteratee=_.identity] The iteratee invoked per element. + * @returns {number} Returns the index at which `value` should be inserted + * into `array`. + * @example + * + * var objects = [{ 'x': 4 }, { 'x': 5 }]; + * + * _.sortedLastIndexBy(objects, { 'x': 4 }, function(o) { return o.x; }); + * // => 1 + * + * // The `_.property` iteratee shorthand. + * _.sortedLastIndexBy(objects, { 'x': 4 }, 'x'); + * // => 1 + */ + function sortedLastIndexBy(array, value, iteratee) { + return baseSortedIndexBy(array, value, baseIteratee(iteratee, 2), true); + } + + module.exports = sortedLastIndexBy; + + +/***/ }), +/* 282 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSortedIndex = __webpack_require__(276), + eq = __webpack_require__(88); + + /** + * This method is like `_.lastIndexOf` except that it performs a binary + * search on a sorted `array`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {*} value The value to search for. + * @returns {number} Returns the index of the matched value, else `-1`. + * @example + * + * _.sortedLastIndexOf([4, 5, 5, 5, 6], 5); + * // => 3 + */ + function sortedLastIndexOf(array, value) { + var length = array == null ? 0 : array.length; + if (length) { + var index = baseSortedIndex(array, value, true) - 1; + if (eq(array[index], value)) { + return index; + } + } + return -1; + } + + module.exports = sortedLastIndexOf; + + +/***/ }), +/* 283 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSortedUniq = __webpack_require__(284); + + /** + * This method is like `_.uniq` except that it's designed and optimized + * for sorted arrays. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @returns {Array} Returns the new duplicate free array. + * @example + * + * _.sortedUniq([1, 1, 2]); + * // => [1, 2] + */ + function sortedUniq(array) { + return (array && array.length) + ? baseSortedUniq(array) + : []; + } + + module.exports = sortedUniq; + + +/***/ }), +/* 284 */ +/***/ (function(module, exports, __webpack_require__) { + + var eq = __webpack_require__(88); + + /** + * The base implementation of `_.sortedUniq` and `_.sortedUniqBy` without + * support for iteratee shorthands. + * + * @private + * @param {Array} array The array to inspect. + * @param {Function} [iteratee] The iteratee invoked per element. + * @returns {Array} Returns the new duplicate free array. + */ + function baseSortedUniq(array, iteratee) { + var index = -1, + length = array.length, + resIndex = 0, + result = []; + + while (++index < length) { + var value = array[index], + computed = iteratee ? iteratee(value) : value; + + if (!index || !eq(computed, seen)) { + var seen = computed; + result[resIndex++] = value === 0 ? 0 : value; + } + } + return result; + } + + module.exports = baseSortedUniq; + + +/***/ }), +/* 285 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + baseSortedUniq = __webpack_require__(284); + + /** + * This method is like `_.uniqBy` except that it's designed and optimized + * for sorted arrays. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {Function} [iteratee] The iteratee invoked per element. + * @returns {Array} Returns the new duplicate free array. + * @example + * + * _.sortedUniqBy([1.1, 1.2, 2.3, 2.4], Math.floor); + * // => [1.1, 2.3] + */ + function sortedUniqBy(array, iteratee) { + return (array && array.length) + ? baseSortedUniq(array, baseIteratee(iteratee, 2)) + : []; + } + + module.exports = sortedUniqBy; + + +/***/ }), +/* 286 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86); + + /** + * Gets all but the first element of `array`. + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to query. + * @returns {Array} Returns the slice of `array`. + * @example + * + * _.tail([1, 2, 3]); + * // => [2, 3] + */ + function tail(array) { + var length = array == null ? 0 : array.length; + return length ? baseSlice(array, 1, length) : []; + } + + module.exports = tail; + + +/***/ }), +/* 287 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86), + toInteger = __webpack_require__(100); + + /** + * Creates a slice of `array` with `n` elements taken from the beginning. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to query. + * @param {number} [n=1] The number of elements to take. + * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. + * @returns {Array} Returns the slice of `array`. + * @example + * + * _.take([1, 2, 3]); + * // => [1] + * + * _.take([1, 2, 3], 2); + * // => [1, 2] + * + * _.take([1, 2, 3], 5); + * // => [1, 2, 3] + * + * _.take([1, 2, 3], 0); + * // => [] + */ + function take(array, n, guard) { + if (!(array && array.length)) { + return []; + } + n = (guard || n === undefined) ? 1 : toInteger(n); + return baseSlice(array, 0, n < 0 ? 0 : n); + } + + module.exports = take; + + +/***/ }), +/* 288 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSlice = __webpack_require__(86), + toInteger = __webpack_require__(100); + + /** + * Creates a slice of `array` with `n` elements taken from the end. + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to query. + * @param {number} [n=1] The number of elements to take. + * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. + * @returns {Array} Returns the slice of `array`. + * @example + * + * _.takeRight([1, 2, 3]); + * // => [3] + * + * _.takeRight([1, 2, 3], 2); + * // => [2, 3] + * + * _.takeRight([1, 2, 3], 5); + * // => [1, 2, 3] + * + * _.takeRight([1, 2, 3], 0); + * // => [] + */ + function takeRight(array, n, guard) { + var length = array == null ? 0 : array.length; + if (!length) { + return []; + } + n = (guard || n === undefined) ? 1 : toInteger(n); + n = length - n; + return baseSlice(array, n < 0 ? 0 : n, length); + } + + module.exports = takeRight; + + +/***/ }), +/* 289 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + baseWhile = __webpack_require__(233); + + /** + * Creates a slice of `array` with elements taken from the end. Elements are + * taken until `predicate` returns falsey. The predicate is invoked with + * three arguments: (value, index, array). + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to query. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @returns {Array} Returns the slice of `array`. + * @example + * + * var users = [ + * { 'user': 'barney', 'active': true }, + * { 'user': 'fred', 'active': false }, + * { 'user': 'pebbles', 'active': false } + * ]; + * + * _.takeRightWhile(users, function(o) { return !o.active; }); + * // => objects for ['fred', 'pebbles'] + * + * // The `_.matches` iteratee shorthand. + * _.takeRightWhile(users, { 'user': 'pebbles', 'active': false }); + * // => objects for ['pebbles'] + * + * // The `_.matchesProperty` iteratee shorthand. + * _.takeRightWhile(users, ['active', false]); + * // => objects for ['fred', 'pebbles'] + * + * // The `_.property` iteratee shorthand. + * _.takeRightWhile(users, 'active'); + * // => [] + */ + function takeRightWhile(array, predicate) { + return (array && array.length) + ? baseWhile(array, baseIteratee(predicate, 3), false, true) + : []; + } + + module.exports = takeRightWhile; + + +/***/ }), +/* 290 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + baseWhile = __webpack_require__(233); + + /** + * Creates a slice of `array` with elements taken from the beginning. Elements + * are taken until `predicate` returns falsey. The predicate is invoked with + * three arguments: (value, index, array). + * + * @static + * @memberOf _ + * @since 3.0.0 + * @category Array + * @param {Array} array The array to query. + * @param {Function} [predicate=_.identity] The function invoked per iteration. + * @returns {Array} Returns the slice of `array`. + * @example + * + * var users = [ + * { 'user': 'barney', 'active': false }, + * { 'user': 'fred', 'active': false }, + * { 'user': 'pebbles', 'active': true } + * ]; + * + * _.takeWhile(users, function(o) { return !o.active; }); + * // => objects for ['barney', 'fred'] + * + * // The `_.matches` iteratee shorthand. + * _.takeWhile(users, { 'user': 'barney', 'active': false }); + * // => objects for ['barney'] + * + * // The `_.matchesProperty` iteratee shorthand. + * _.takeWhile(users, ['active', false]); + * // => objects for ['barney', 'fred'] + * + * // The `_.property` iteratee shorthand. + * _.takeWhile(users, 'active'); + * // => [] + */ + function takeWhile(array, predicate) { + return (array && array.length) + ? baseWhile(array, baseIteratee(predicate, 3)) + : []; + } + + module.exports = takeWhile; + + +/***/ }), +/* 291 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFlatten = __webpack_require__(108), + baseRest = __webpack_require__(157), + baseUniq = __webpack_require__(292), + isArrayLikeObject = __webpack_require__(166); + + /** + * Creates an array of unique values, in order, from all given arrays using + * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @returns {Array} Returns the new array of combined values. + * @example + * + * _.union([2], [1, 2]); + * // => [2, 1] + */ + var union = baseRest(function(arrays) { + return baseUniq(baseFlatten(arrays, 1, isArrayLikeObject, true)); + }); + + module.exports = union; + + +/***/ }), +/* 292 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetCache = __webpack_require__(116), + arrayIncludes = __webpack_require__(148), + arrayIncludesWith = __webpack_require__(153), + cacheHas = __webpack_require__(156), + createSet = __webpack_require__(293), + setToArray = __webpack_require__(184); + + /** Used as the size to enable large array optimizations. */ + var LARGE_ARRAY_SIZE = 200; + + /** + * The base implementation of `_.uniqBy` without support for iteratee shorthands. + * + * @private + * @param {Array} array The array to inspect. + * @param {Function} [iteratee] The iteratee invoked per element. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new duplicate free array. + */ + function baseUniq(array, iteratee, comparator) { + var index = -1, + includes = arrayIncludes, + length = array.length, + isCommon = true, + result = [], + seen = result; + + if (comparator) { + isCommon = false; + includes = arrayIncludesWith; + } + else if (length >= LARGE_ARRAY_SIZE) { + var set = iteratee ? null : createSet(array); + if (set) { + return setToArray(set); + } + isCommon = false; + includes = cacheHas; + seen = new SetCache; + } + else { + seen = iteratee ? [] : result; + } + outer: + while (++index < length) { + var value = array[index], + computed = iteratee ? iteratee(value) : value; + + value = (comparator || value !== 0) ? value : 0; + if (isCommon && computed === computed) { + var seenIndex = seen.length; + while (seenIndex--) { + if (seen[seenIndex] === computed) { + continue outer; + } + } + if (iteratee) { + seen.push(computed); + } + result.push(value); + } + else if (!includes(seen, computed, comparator)) { + if (seen !== result) { + seen.push(computed); + } + result.push(value); + } + } + return result; + } + + module.exports = baseUniq; + + +/***/ }), +/* 293 */ +/***/ (function(module, exports, __webpack_require__) { + + var Set = __webpack_require__(206), + noop = __webpack_require__(294), + setToArray = __webpack_require__(184); + + /** Used as references for various `Number` constants. */ + var INFINITY = 1 / 0; + + /** + * Creates a set object of `values`. + * + * @private + * @param {Array} values The values to add to the set. + * @returns {Object} Returns the new set. + */ + var createSet = !(Set && (1 / setToArray(new Set([,-0]))[1]) == INFINITY) ? noop : function(values) { + return new Set(values); + }; + + module.exports = createSet; + + +/***/ }), +/* 294 */ +/***/ (function(module, exports) { + + /** + * This method returns `undefined`. + * + * @static + * @memberOf _ + * @since 2.3.0 + * @category Util + * @example + * + * _.times(2, _.noop); + * // => [undefined, undefined] + */ + function noop() { + // No operation performed. + } + + module.exports = noop; + + +/***/ }), +/* 295 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFlatten = __webpack_require__(108), + baseIteratee = __webpack_require__(168), + baseRest = __webpack_require__(157), + baseUniq = __webpack_require__(292), + isArrayLikeObject = __webpack_require__(166), + last = __webpack_require__(228); + + /** + * This method is like `_.union` except that it accepts `iteratee` which is + * invoked for each element of each `arrays` to generate the criterion by + * which uniqueness is computed. Result values are chosen from the first + * array in which the value occurs. The iteratee is invoked with one argument: + * (value). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @param {Function} [iteratee=_.identity] The iteratee invoked per element. + * @returns {Array} Returns the new array of combined values. + * @example + * + * _.unionBy([2.1], [1.2, 2.3], Math.floor); + * // => [2.1, 1.2] + * + * // The `_.property` iteratee shorthand. + * _.unionBy([{ 'x': 1 }], [{ 'x': 2 }, { 'x': 1 }], 'x'); + * // => [{ 'x': 1 }, { 'x': 2 }] + */ + var unionBy = baseRest(function(arrays) { + var iteratee = last(arrays); + if (isArrayLikeObject(iteratee)) { + iteratee = undefined; + } + return baseUniq(baseFlatten(arrays, 1, isArrayLikeObject, true), baseIteratee(iteratee, 2)); + }); + + module.exports = unionBy; + + +/***/ }), +/* 296 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseFlatten = __webpack_require__(108), + baseRest = __webpack_require__(157), + baseUniq = __webpack_require__(292), + isArrayLikeObject = __webpack_require__(166), + last = __webpack_require__(228); + + /** + * This method is like `_.union` except that it accepts `comparator` which + * is invoked to compare elements of `arrays`. Result values are chosen from + * the first array in which the value occurs. The comparator is invoked + * with two arguments: (arrVal, othVal). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new array of combined values. + * @example + * + * var objects = [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }]; + * var others = [{ 'x': 1, 'y': 1 }, { 'x': 1, 'y': 2 }]; + * + * _.unionWith(objects, others, _.isEqual); + * // => [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }, { 'x': 1, 'y': 1 }] + */ + var unionWith = baseRest(function(arrays) { + var comparator = last(arrays); + comparator = typeof comparator == 'function' ? comparator : undefined; + return baseUniq(baseFlatten(arrays, 1, isArrayLikeObject, true), undefined, comparator); + }); + + module.exports = unionWith; + + +/***/ }), +/* 297 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseUniq = __webpack_require__(292); + + /** + * Creates a duplicate-free version of an array, using + * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons, in which only the first occurrence of each element + * is kept. The order of result values is determined by the order they occur + * in the array. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to inspect. + * @returns {Array} Returns the new duplicate free array. + * @example + * + * _.uniq([2, 1, 2]); + * // => [2, 1] + */ + function uniq(array) { + return (array && array.length) ? baseUniq(array) : []; + } + + module.exports = uniq; + + +/***/ }), +/* 298 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseIteratee = __webpack_require__(168), + baseUniq = __webpack_require__(292); + + /** + * This method is like `_.uniq` except that it accepts `iteratee` which is + * invoked for each element in `array` to generate the criterion by which + * uniqueness is computed. The order of result values is determined by the + * order they occur in the array. The iteratee is invoked with one argument: + * (value). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {Function} [iteratee=_.identity] The iteratee invoked per element. + * @returns {Array} Returns the new duplicate free array. + * @example + * + * _.uniqBy([2.1, 1.2, 2.3], Math.floor); + * // => [2.1, 1.2] + * + * // The `_.property` iteratee shorthand. + * _.uniqBy([{ 'x': 1 }, { 'x': 2 }, { 'x': 1 }], 'x'); + * // => [{ 'x': 1 }, { 'x': 2 }] + */ + function uniqBy(array, iteratee) { + return (array && array.length) ? baseUniq(array, baseIteratee(iteratee, 2)) : []; + } + + module.exports = uniqBy; + + +/***/ }), +/* 299 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseUniq = __webpack_require__(292); + + /** + * This method is like `_.uniq` except that it accepts `comparator` which + * is invoked to compare elements of `array`. The order of result values is + * determined by the order they occur in the array.The comparator is invoked + * with two arguments: (arrVal, othVal). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new duplicate free array. + * @example + * + * var objects = [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }, { 'x': 1, 'y': 2 }]; + * + * _.uniqWith(objects, _.isEqual); + * // => [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }] + */ + function uniqWith(array, comparator) { + comparator = typeof comparator == 'function' ? comparator : undefined; + return (array && array.length) ? baseUniq(array, undefined, comparator) : []; + } + + module.exports = uniqWith; + + +/***/ }), +/* 300 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayFilter = __webpack_require__(189), + arrayMap = __webpack_require__(154), + baseProperty = __webpack_require__(226), + baseTimes = __webpack_require__(193), + isArrayLikeObject = __webpack_require__(166); + + /* Built-in method references for those with the same name as other `lodash` methods. */ + var nativeMax = Math.max; + + /** + * This method is like `_.zip` except that it accepts an array of grouped + * elements and creates an array regrouping the elements to their pre-zip + * configuration. + * + * @static + * @memberOf _ + * @since 1.2.0 + * @category Array + * @param {Array} array The array of grouped elements to process. + * @returns {Array} Returns the new array of regrouped elements. + * @example + * + * var zipped = _.zip(['a', 'b'], [1, 2], [true, false]); + * // => [['a', 1, true], ['b', 2, false]] + * + * _.unzip(zipped); + * // => [['a', 'b'], [1, 2], [true, false]] + */ + function unzip(array) { + if (!(array && array.length)) { + return []; + } + var length = 0; + array = arrayFilter(array, function(group) { + if (isArrayLikeObject(group)) { + length = nativeMax(group.length, length); + return true; + } + }); + return baseTimes(length, function(index) { + return arrayMap(array, baseProperty(index)); + }); + } + + module.exports = unzip; + + +/***/ }), +/* 301 */ +/***/ (function(module, exports, __webpack_require__) { + + var apply = __webpack_require__(160), + arrayMap = __webpack_require__(154), + unzip = __webpack_require__(300); + + /** + * This method is like `_.unzip` except that it accepts `iteratee` to specify + * how regrouped values should be combined. The iteratee is invoked with the + * elements of each group: (...group). + * + * @static + * @memberOf _ + * @since 3.8.0 + * @category Array + * @param {Array} array The array of grouped elements to process. + * @param {Function} [iteratee=_.identity] The function to combine + * regrouped values. + * @returns {Array} Returns the new array of regrouped elements. + * @example + * + * var zipped = _.zip([1, 2], [10, 20], [100, 200]); + * // => [[1, 10, 100], [2, 20, 200]] + * + * _.unzipWith(zipped, _.add); + * // => [3, 30, 300] + */ + function unzipWith(array, iteratee) { + if (!(array && array.length)) { + return []; + } + var result = unzip(array); + if (iteratee == null) { + return result; + } + return arrayMap(result, function(group) { + return apply(iteratee, undefined, group); + }); + } + + module.exports = unzipWith; + + +/***/ }), +/* 302 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseDifference = __webpack_require__(115), + baseRest = __webpack_require__(157), + isArrayLikeObject = __webpack_require__(166); + + /** + * Creates an array excluding all given values using + * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. + * + * **Note:** Unlike `_.pull`, this method returns a new array. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {Array} array The array to inspect. + * @param {...*} [values] The values to exclude. + * @returns {Array} Returns the new array of filtered values. + * @see _.difference, _.xor + * @example + * + * _.without([2, 1, 2, 3], 1, 2); + * // => [3] + */ + var without = baseRest(function(array, values) { + return isArrayLikeObject(array) + ? baseDifference(array, values) + : []; + }); + + module.exports = without; + + +/***/ }), +/* 303 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayFilter = __webpack_require__(189), + baseRest = __webpack_require__(157), + baseXor = __webpack_require__(304), + isArrayLikeObject = __webpack_require__(166); + + /** + * Creates an array of unique values that is the + * [symmetric difference](https://en.wikipedia.org/wiki/Symmetric_difference) + * of the given arrays. The order of result values is determined by the order + * they occur in the arrays. + * + * @static + * @memberOf _ + * @since 2.4.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @returns {Array} Returns the new array of filtered values. + * @see _.difference, _.without + * @example + * + * _.xor([2, 1], [2, 3]); + * // => [1, 3] + */ + var xor = baseRest(function(arrays) { + return baseXor(arrayFilter(arrays, isArrayLikeObject)); + }); + + module.exports = xor; + + +/***/ }), +/* 304 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseDifference = __webpack_require__(115), + baseFlatten = __webpack_require__(108), + baseUniq = __webpack_require__(292); + + /** + * The base implementation of methods like `_.xor`, without support for + * iteratee shorthands, that accepts an array of arrays to inspect. + * + * @private + * @param {Array} arrays The arrays to inspect. + * @param {Function} [iteratee] The iteratee invoked per element. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new array of values. + */ + function baseXor(arrays, iteratee, comparator) { + var length = arrays.length; + if (length < 2) { + return length ? baseUniq(arrays[0]) : []; + } + var index = -1, + result = Array(length); + + while (++index < length) { + var array = arrays[index], + othIndex = -1; + + while (++othIndex < length) { + if (othIndex != index) { + result[index] = baseDifference(result[index] || array, arrays[othIndex], iteratee, comparator); + } + } + } + return baseUniq(baseFlatten(result, 1), iteratee, comparator); + } + + module.exports = baseXor; + + +/***/ }), +/* 305 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayFilter = __webpack_require__(189), + baseIteratee = __webpack_require__(168), + baseRest = __webpack_require__(157), + baseXor = __webpack_require__(304), + isArrayLikeObject = __webpack_require__(166), + last = __webpack_require__(228); + + /** + * This method is like `_.xor` except that it accepts `iteratee` which is + * invoked for each element of each `arrays` to generate the criterion by + * which by which they're compared. The order of result values is determined + * by the order they occur in the arrays. The iteratee is invoked with one + * argument: (value). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @param {Function} [iteratee=_.identity] The iteratee invoked per element. + * @returns {Array} Returns the new array of filtered values. + * @example + * + * _.xorBy([2.1, 1.2], [2.3, 3.4], Math.floor); + * // => [1.2, 3.4] + * + * // The `_.property` iteratee shorthand. + * _.xorBy([{ 'x': 1 }], [{ 'x': 2 }, { 'x': 1 }], 'x'); + * // => [{ 'x': 2 }] + */ + var xorBy = baseRest(function(arrays) { + var iteratee = last(arrays); + if (isArrayLikeObject(iteratee)) { + iteratee = undefined; + } + return baseXor(arrayFilter(arrays, isArrayLikeObject), baseIteratee(iteratee, 2)); + }); + + module.exports = xorBy; + + +/***/ }), +/* 306 */ +/***/ (function(module, exports, __webpack_require__) { + + var arrayFilter = __webpack_require__(189), + baseRest = __webpack_require__(157), + baseXor = __webpack_require__(304), + isArrayLikeObject = __webpack_require__(166), + last = __webpack_require__(228); + + /** + * This method is like `_.xor` except that it accepts `comparator` which is + * invoked to compare elements of `arrays`. The order of result values is + * determined by the order they occur in the arrays. The comparator is invoked + * with two arguments: (arrVal, othVal). + * + * @static + * @memberOf _ + * @since 4.0.0 + * @category Array + * @param {...Array} [arrays] The arrays to inspect. + * @param {Function} [comparator] The comparator invoked per element. + * @returns {Array} Returns the new array of filtered values. + * @example + * + * var objects = [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }]; + * var others = [{ 'x': 1, 'y': 1 }, { 'x': 1, 'y': 2 }]; + * + * _.xorWith(objects, others, _.isEqual); + * // => [{ 'x': 2, 'y': 1 }, { 'x': 1, 'y': 1 }] + */ + var xorWith = baseRest(function(arrays) { + var comparator = last(arrays); + comparator = typeof comparator == 'function' ? comparator : undefined; + return baseXor(arrayFilter(arrays, isArrayLikeObject), undefined, comparator); + }); + + module.exports = xorWith; + + +/***/ }), +/* 307 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseRest = __webpack_require__(157), + unzip = __webpack_require__(300); + + /** + * Creates an array of grouped elements, the first of which contains the + * first elements of the given arrays, the second of which contains the + * second elements of the given arrays, and so on. + * + * @static + * @memberOf _ + * @since 0.1.0 + * @category Array + * @param {...Array} [arrays] The arrays to process. + * @returns {Array} Returns the new array of grouped elements. + * @example + * + * _.zip(['a', 'b'], [1, 2], [true, false]); + * // => [['a', 1, true], ['b', 2, false]] + */ + var zip = baseRest(unzip); + + module.exports = zip; + + +/***/ }), +/* 308 */ +/***/ (function(module, exports, __webpack_require__) { + + var assignValue = __webpack_require__(309), + baseZipObject = __webpack_require__(311); + + /** + * This method is like `_.fromPairs` except that it accepts two arrays, + * one of property identifiers and one of corresponding values. + * + * @static + * @memberOf _ + * @since 0.4.0 + * @category Array + * @param {Array} [props=[]] The property identifiers. + * @param {Array} [values=[]] The property values. + * @returns {Object} Returns the new object. + * @example + * + * _.zipObject(['a', 'b'], [1, 2]); + * // => { 'a': 1, 'b': 2 } + */ + function zipObject(props, values) { + return baseZipObject(props || [], values || [], assignValue); + } + + module.exports = zipObject; + + +/***/ }), +/* 309 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseAssignValue = __webpack_require__(310), + eq = __webpack_require__(88); + + /** Used for built-in method references. */ + var objectProto = Object.prototype; + + /** Used to check objects for own properties. */ + var hasOwnProperty = objectProto.hasOwnProperty; + + /** + * Assigns `value` to `key` of `object` if the existing value is not equivalent + * using [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) + * for equality comparisons. + * + * @private + * @param {Object} object The object to modify. + * @param {string} key The key of the property to assign. + * @param {*} value The value to assign. + */ + function assignValue(object, key, value) { + var objValue = object[key]; + if (!(hasOwnProperty.call(object, key) && eq(objValue, value)) || + (value === undefined && !(key in object))) { + baseAssignValue(object, key, value); + } + } + + module.exports = assignValue; + + +/***/ }), +/* 310 */ +/***/ (function(module, exports, __webpack_require__) { + + var defineProperty = __webpack_require__(164); + + /** + * The base implementation of `assignValue` and `assignMergeValue` without + * value checks. + * + * @private + * @param {Object} object The object to modify. + * @param {string} key The key of the property to assign. + * @param {*} value The value to assign. + */ + function baseAssignValue(object, key, value) { + if (key == '__proto__' && defineProperty) { + defineProperty(object, key, { + 'configurable': true, + 'enumerable': true, + 'value': value, + 'writable': true + }); + } else { + object[key] = value; + } + } + + module.exports = baseAssignValue; + + +/***/ }), +/* 311 */ +/***/ (function(module, exports) { + + /** + * This base implementation of `_.zipObject` which assigns values using `assignFunc`. + * + * @private + * @param {Array} props The property identifiers. + * @param {Array} values The property values. + * @param {Function} assignFunc The function to assign values. + * @returns {Object} Returns the new object. + */ + function baseZipObject(props, values, assignFunc) { + var index = -1, + length = props.length, + valsLength = values.length, + result = {}; + + while (++index < length) { + var value = index < valsLength ? values[index] : undefined; + assignFunc(result, props[index], value); + } + return result; + } + + module.exports = baseZipObject; + + +/***/ }), +/* 312 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseSet = __webpack_require__(313), + baseZipObject = __webpack_require__(311); + + /** + * This method is like `_.zipObject` except that it supports property paths. + * + * @static + * @memberOf _ + * @since 4.1.0 + * @category Array + * @param {Array} [props=[]] The property identifiers. + * @param {Array} [values=[]] The property values. + * @returns {Object} Returns the new object. + * @example + * + * _.zipObjectDeep(['a.b[0].c', 'a.b[1].d'], [1, 2]); + * // => { 'a': { 'b': [{ 'c': 1 }, { 'd': 2 }] } } + */ + function zipObjectDeep(props, values) { + return baseZipObject(props || [], values || [], baseSet); + } + + module.exports = zipObjectDeep; + + +/***/ }), +/* 313 */ +/***/ (function(module, exports, __webpack_require__) { + + var assignValue = __webpack_require__(309), + castPath = __webpack_require__(214), + isIndex = __webpack_require__(99), + isObject = __webpack_require__(97), + toKey = __webpack_require__(221); + + /** + * The base implementation of `_.set`. + * + * @private + * @param {Object} object The object to modify. + * @param {Array|string} path The path of the property to set. + * @param {*} value The value to set. + * @param {Function} [customizer] The function to customize path creation. + * @returns {Object} Returns `object`. + */ + function baseSet(object, path, value, customizer) { + if (!isObject(object)) { + return object; + } + path = castPath(path, object); + + var index = -1, + length = path.length, + lastIndex = length - 1, + nested = object; + + while (nested != null && ++index < length) { + var key = toKey(path[index]), + newValue = value; + + if (index != lastIndex) { + var objValue = nested[key]; + newValue = customizer ? customizer(objValue, key, nested) : undefined; + if (newValue === undefined) { + newValue = isObject(objValue) + ? objValue + : (isIndex(path[index + 1]) ? [] : {}); + } + } + assignValue(nested, key, newValue); + nested = nested[key]; + } + return object; + } + + module.exports = baseSet; + + +/***/ }), +/* 314 */ +/***/ (function(module, exports, __webpack_require__) { + + var baseRest = __webpack_require__(157), + unzipWith = __webpack_require__(301); + + /** + * This method is like `_.zip` except that it accepts `iteratee` to specify + * how grouped values should be combined. The iteratee is invoked with the + * elements of each group: (...group). + * + * @static + * @memberOf _ + * @since 3.8.0 + * @category Array + * @param {...Array} [arrays] The arrays to process. + * @param {Function} [iteratee=_.identity] The function to combine + * grouped values. + * @returns {Array} Returns the new array of grouped elements. + * @example + * + * _.zipWith([1, 2], [10, 20], [100, 200], function(a, b, c) { + * return a + b + c; + * }); + * // => [111, 222] + */ + var zipWith = baseRest(function(arrays) { + var length = arrays.length, + iteratee = length > 1 ? arrays[length - 1] : undefined; + + iteratee = typeof iteratee == 'function' ? (arrays.pop(), iteratee) : undefined; + return unzipWith(arrays, iteratee); + }); + + module.exports = zipWith; + + +/***/ }), +/* 315 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {module.exports = function ( handlerFunction ){ + var viewer = {}, + lastSelectedElement; + + viewer.handle = function ( selectedElement ){ + // Don't display details on a drag event, which will be prevented + if ( d3.event.defaultPrevented ) { + return; + } + + var isSelection = true; + + // Deselection of the focused element + if ( lastSelectedElement === selectedElement ) { + isSelection = false; + } + + if ( handlerFunction instanceof Function ) { + if ( isSelection ) { + handlerFunction(selectedElement); + } else { + handlerFunction(undefined); + } + } + + if ( isSelection ) { + lastSelectedElement = selectedElement; + } else { + lastSelectedElement = undefined; + } + }; + + /** + * Resets the displayed information to its default. + */ + viewer.reset = function (){ + if ( lastSelectedElement ) { + handlerFunction(undefined); + lastSelectedElement = undefined; + } + }; + + return viewer; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 316 */ +/***/ (function(module, exports, __webpack_require__) { + + var SetOperatorNode = __webpack_require__(20); + + module.exports = function (){ + + var filter = {}, + nodes, + properties, + enabled = false, + filteredNodes, + filteredProperties, + filterTools = __webpack_require__(76)(); + + + /** + * If enabled, all set operators including connected properties are filtered. + * @param untouchedNodes + * @param untouchedProperties + */ + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + + if ( this.enabled() ) { + removeSetOperators(); + } + + filteredNodes = nodes; + filteredProperties = properties; + }; + + function removeSetOperators(){ + var filteredData = filterTools.filterNodesAndTidy(nodes, properties, isNoSetOperator); + + nodes = filteredData.nodes; + properties = filteredData.properties; + } + + function isNoSetOperator( node ){ + return !(node instanceof SetOperatorNode); + } + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }), +/* 317 */ +/***/ (function(module, exports, __webpack_require__) { + + /* WEBPACK VAR INJECTION */(function(d3) {var SetOperatorNode = __webpack_require__(20); + var OwlThing = __webpack_require__(31); + var OwlNothing = __webpack_require__(30); + var elementTools = __webpack_require__(63)(); + + module.exports = function (){ + + var statistics = {}, + nodeCount, + occurencesOfClassAndDatatypeTypes = {}, + edgeCount, + occurencesOfPropertyTypes = {}, + classCount, + datatypeCount, + datatypePropertyCount, + objectPropertyCount, + propertyCount, + totalIndividualCount, + filteredNodes, + filteredProperties; + + + statistics.filter = function ( classesAndDatatypes, properties ){ + resetStoredData(); + + storeTotalCounts(classesAndDatatypes, properties); + storeClassAndDatatypeCount(classesAndDatatypes); + storePropertyCount(properties); + + storeOccurencesOfTypes(classesAndDatatypes, occurencesOfClassAndDatatypeTypes); + storeOccurencesOfTypes(properties, occurencesOfPropertyTypes); + + storeTotalIndividualCount(classesAndDatatypes); + + filteredNodes = classesAndDatatypes; + filteredProperties = properties; + }; + + function resetStoredData(){ + nodeCount = 0; + edgeCount = 0; + classCount = 0; + datatypeCount = 0; + datatypePropertyCount = 0; + objectPropertyCount = 0; + propertyCount = 0; + totalIndividualCount = 0; + } + + function storeTotalCounts( classesAndDatatypes, properties ){ + nodeCount = classesAndDatatypes.length; + + var seenProperties = __webpack_require__(62)(), i, l, property; + for ( i = 0, l = properties.length; i < l; i++ ) { + property = properties[i]; + if ( !seenProperties.has(property) ) { + edgeCount += 1; + } + + seenProperties.add(property); + if ( property.inverse() ) { + seenProperties.add(property.inverse()); + } + } + } + + function storeClassAndDatatypeCount( classesAndDatatypes ){ + // Each datatype should be counted just a single time + var datatypeSet = d3.set(), + hasThing = false, + hasNothing = false; + classCount = 0; + var old = 0, newcc = 0; + classesAndDatatypes.forEach(function ( node ){ + if ( elementTools.isDatatype(node) ) { + datatypeSet.add(node.defaultLabel()); + } else if ( !(node instanceof SetOperatorNode) ) { + if ( node instanceof OwlThing ) { + hasThing = true; + } else if ( node instanceof OwlNothing ) { + hasNothing = true; + } else { + old = classCount; + var adds = 1 + countElementArray(node.equivalents()); + classCount += adds; + newcc = classCount; + } + } else if ( node instanceof SetOperatorNode ) { + old = classCount; + classCount += 1; + newcc = classCount; + } + }); + + // count things and nothings just a single time + // classCount += hasThing ? 1 : 0; + // classCount += hasNothing ? 1 : 0; + + datatypeCount = datatypeSet.size(); + } + + function storePropertyCount( properties ){ + for ( var i = 0, l = properties.length; i < l; i++ ) { + var property = properties[i]; + var attr; + var result = false; + if ( property.attributes ) { + attr = property.attributes(); + if ( attr && attr.indexOf("datatype") !== -1 ) { + result = true; + } + } + if ( result === true ) { + datatypePropertyCount += getExtendedPropertyCount(property); + } else if ( elementTools.isObjectProperty(property) ) { + objectPropertyCount += getExtendedPropertyCount(property); + } + } + propertyCount = objectPropertyCount + datatypePropertyCount; + } + + function getExtendedPropertyCount( property ){ + // count the property itself + var count = 1; + + // and count properties this property represents + count += countElementArray(property.equivalents()); + count += countElementArray(property.redundantProperties()); + + return count; + } + + function countElementArray( properties ){ + if ( properties ) { + return properties.length; + } + return 0; + } + + function storeOccurencesOfTypes( elements, storage ){ + elements.forEach(function ( element ){ + var type = element.type(), + typeCount = storage[type]; + + if ( typeof typeCount === "undefined" ) { + typeCount = 0; + } else { + typeCount += 1; + } + storage[type] = typeCount; + }); + } + + function storeTotalIndividualCount( nodes ){ + var sawIndividuals = {}; + var totalCount = 0; + for ( var i = 0, l = nodes.length; i < l; i++ ) { + var individuals = nodes[i].individuals(); + + var tempCount = 0; + for ( var iA = 0; iA < individuals.length; iA++ ) { + if ( sawIndividuals[individuals[iA].iri()] === undefined ) { + sawIndividuals[individuals[iA].iri()] = 1; // this iri for that individual is now set to 1 >> seen it + tempCount++; + } + } + totalCount += tempCount; + } + totalIndividualCount = totalCount; + sawIndividuals = {}; // clear the object + + } + + + statistics.nodeCount = function (){ + return nodeCount; + }; + + statistics.occurencesOfClassAndDatatypeTypes = function (){ + return occurencesOfClassAndDatatypeTypes; + }; + + statistics.edgeCount = function (){ + return edgeCount; + }; + + statistics.occurencesOfPropertyTypes = function (){ + return occurencesOfPropertyTypes; + }; + + statistics.classCount = function (){ + return classCount; + }; + + statistics.datatypeCount = function (){ + return datatypeCount; + }; + + statistics.datatypePropertyCount = function (){ + return datatypePropertyCount; + }; + + statistics.objectPropertyCount = function (){ + return objectPropertyCount; + }; + + statistics.propertyCount = function (){ + return propertyCount; + }; + + statistics.totalIndividualCount = function (){ + return totalIndividualCount; + }; + + + // Functions a filter must have + statistics.filteredNodes = function (){ + return filteredNodes; + }; + + statistics.filteredProperties = function (){ + return filteredProperties; + }; + + + return statistics; + }; + + /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(6))) + +/***/ }), +/* 318 */ +/***/ (function(module, exports, __webpack_require__) { + + var elementTools = __webpack_require__(63)(); + + module.exports = function (){ + + var filter = {}, + nodes, + properties, + enabled = false, + filteredNodes, + filteredProperties; + + + /** + * If enabled subclasses that have only subclass properties are filtered. + * @param untouchedNodes + * @param untouchedProperties + */ + filter.filter = function ( untouchedNodes, untouchedProperties ){ + nodes = untouchedNodes; + properties = untouchedProperties; + + if ( this.enabled() ) { + hideSubclassesWithoutOwnProperties(); + } + + filteredNodes = nodes; + filteredProperties = properties; + }; + + function hideSubclassesWithoutOwnProperties(){ + var unneededProperties = [], + unneededClasses = [], + subclasses = [], + connectedProperties, + subclass, + property, + i, // index, + l; // length + + + for ( i = 0, l = properties.length; i < l; i++ ) { + property = properties[i]; + if ( elementTools.isRdfsSubClassOf(property) ) { + subclasses.push(property.domain()); + } + } + + for ( i = 0, l = subclasses.length; i < l; i++ ) { + subclass = subclasses[i]; + connectedProperties = findRelevantConnectedProperties(subclass, properties); + + // Only remove the node and its properties, if they're all subclassOf properties + if ( areOnlySubclassProperties(connectedProperties) && + doesNotInheritFromMultipleClasses(subclass, connectedProperties) ) { + + unneededProperties = unneededProperties.concat(connectedProperties); + unneededClasses.push(subclass); + } + } + + nodes = removeUnneededElements(nodes, unneededClasses); + properties = removeUnneededElements(properties, unneededProperties); + } + + /** + * Looks recursively for connected properties. Because just subclasses are relevant, + * we just look recursively for their properties. + * + * @param node + * @param allProperties + * @param visitedNodes a visited nodes which is used on recursive invocation + * @returns {Array} + */ + function findRelevantConnectedProperties( node, allProperties, visitedNodes ){ + var connectedProperties = [], + property, + i, + l; + + for ( i = 0, l = allProperties.length; i < l; i++ ) { + property = allProperties[i]; + if ( property.domain() === node || + property.range() === node ) { + + connectedProperties.push(property); + + + /* Special case: SuperClass <-(1) Subclass <-(2) Subclass ->(3) e.g. Datatype + * We need to find the last property recursively. Otherwise, we would remove the subClassOf + * property (1) because we didn't see the datatype property (3). + */ + + // Look only for subclass properties, because these are the relevant properties + if ( elementTools.isRdfsSubClassOf(property) ) { + var domain = property.domain(); + visitedNodes = visitedNodes || __webpack_require__(62)(); + + // If we have the range, there might be a nested property on the domain + if ( node === property.range() && !visitedNodes.has(domain) ) { + visitedNodes.add(domain); + var nestedConnectedProperties = findRelevantConnectedProperties(domain, allProperties, visitedNodes); + connectedProperties = connectedProperties.concat(nestedConnectedProperties); + } + } + } + } + + return connectedProperties; + } + + function areOnlySubclassProperties( connectedProperties ){ + var onlySubclassProperties = true, + property, + i, + l; + + for ( i = 0, l = connectedProperties.length; i < l; i++ ) { + property = connectedProperties[i]; + + if ( !elementTools.isRdfsSubClassOf(property) ) { + onlySubclassProperties = false; + break; + } + } + + return onlySubclassProperties; + } + + function doesNotInheritFromMultipleClasses( subclass, connectedProperties ){ + var superClassCount = 0; + + for ( var i = 0, l = connectedProperties.length; i < l; i++ ) { + var property = connectedProperties[i]; + + if ( property.domain() === subclass ) { + superClassCount += 1; + } + + if ( superClassCount > 1 ) { + return false; + } + } + + return true; + } + + function removeUnneededElements( array, removableElements ){ + var disjoint = [], + element, + i, + l; + + for ( i = 0, l = array.length; i < l; i++ ) { + element = array[i]; + if ( removableElements.indexOf(element) === -1 ) { + disjoint.push(element); + } + } + return disjoint; + } + + filter.enabled = function ( p ){ + if ( !arguments.length ) return enabled; + enabled = p; + return filter; + }; + + + // Functions a filter must have + filter.filteredNodes = function (){ + return filteredNodes; + }; + + filter.filteredProperties = function (){ + return filteredProperties; + }; + + + return filter; + }; + + +/***/ }) +/******/ ]); \ No newline at end of file diff --git a/doc/releases/0.1.0/steps/webvowl/license.txt b/doc/releases/0.1.0/steps/webvowl/license.txt new file mode 100644 index 0000000..008e54c --- /dev/null +++ b/doc/releases/0.1.0/steps/webvowl/license.txt @@ -0,0 +1,21 @@ +The MIT License (MIT) + +Copyright (c) 2014-2019 Vincent Link, Steffen Lohmann, Eduard Marbach, Stefan Negru, Vitalis Wiens + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in +all copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN +THE SOFTWARE. diff --git a/doc/run_full_build.sh b/doc/run_full_build.sh new file mode 100755 index 0000000..43ff2d0 --- /dev/null +++ b/doc/run_full_build.sh @@ -0,0 +1,10 @@ +#!/bin/bash -x + +rm -rf releases +rm ../src/neao_merge.owl + +./build_doc.sh 0.1.0 + +cd docker +./build.sh + diff --git a/doc/source/base/config-base.properties b/doc/source/base/config-base.properties index 6a024fd..88fa56e 100644 --- a/doc/source/base/config-base.properties +++ b/doc/source/base/config-base.properties @@ -7,9 +7,9 @@ ontologyName=NEAO Base classes thisVersionURI=http://purl.org/neao/0.1.0/base# latestVersionURI=http://purl.org/neao/base# previousVersionURI= -dateCreated=2024-XX-XX +dateCreated=2024-12-06 dateModified= -dateIssued=2024-XX-XX +dateIssued=2024-12-06 ontologyRevisionNumber=0.1.0 licenseURI=https://creativecommons.org/licenses/by/4.0/ licenseName=CC-BY 4.0 International diff --git a/doc/source/bibliography/config-bibliography.properties b/doc/source/bibliography/config-bibliography.properties index 65bba04..28d817f 100644 --- a/doc/source/bibliography/config-bibliography.properties +++ b/doc/source/bibliography/config-bibliography.properties @@ -6,9 +6,9 @@ ontologyName=NEAO Bibliography thisVersionURI=http://purl.org/neao/0.1.0/bibliography# latestVersionURI=http://purl.org/neao/bibliography# previousVersionURI= -dateCreated=2024-XX-XX +dateCreated=2024-12-06 dateModified= -dateIssued=2024-XX-XX +dateIssued=2024-12-06 ontologyRevisionNumber=0.1.0 licenseURI=https://creativecommons.org/licenses/by/4.0/ licenseName=CC-BY 4.0 International diff --git a/doc/source/config.properties b/doc/source/config.properties index a2e7b8c..59afcb9 100644 --- a/doc/source/config.properties +++ b/doc/source/config.properties @@ -7,9 +7,9 @@ ontologyName=NEAO thisVersionURI=http://purl.org/neao/0.1.0/ latestVersionURI=http://purl.org/neao/ previousVersionURI= -dateCreated=2024-XX-XX +dateCreated=2024-12-06 dateModified= -dateIssued=2024-XX-XX +dateIssued=2024-12-06 ontologyRevisionNumber=0.1.0 licenseURI=https://creativecommons.org/licenses/by/4.0/ licenseName=CC-BY 4.0 International diff --git a/doc/source/data/config-data.properties b/doc/source/data/config-data.properties index 22bef79..0d56da1 100644 --- a/doc/source/data/config-data.properties +++ b/doc/source/data/config-data.properties @@ -7,9 +7,9 @@ ontologyName=NEAO Data thisVersionURI=http://purl.org/neao/0.1.0/data# latestVersionURI=http://purl.org/neao/data# previousVersionURI= -dateCreated=2024-XX-XX +dateCreated=2024-12-06 dateModified= -dateIssued=2024-XX-XX +dateIssued=2024-12-06 ontologyRevisionNumber=0.1.0 licenseURI=https://creativecommons.org/licenses/by/4.0/ licenseName=CC-BY 4.0 International diff --git a/doc/source/parameters/config-parameters.properties b/doc/source/parameters/config-parameters.properties index 9bf40bd..50aa41e 100644 --- a/doc/source/parameters/config-parameters.properties +++ b/doc/source/parameters/config-parameters.properties @@ -7,9 +7,9 @@ ontologyName=NEAO Analysis Parameters thisVersionURI=http://purl.org/neao/0.1.0/parameters# latestVersionURI=http://purl.org/neao/parameters# previousVersionURI= -dateCreated=2024-XX-XX +dateCreated=2024-12-06 dateModified= -dateIssued=2024-XX-XX +dateIssued=2024-12-06 ontologyRevisionNumber=0.1.0 licenseURI=https://creativecommons.org/licenses/by/4.0/ licenseName=CC-BY 4.0 International diff --git a/doc/source/steps/config-steps.properties b/doc/source/steps/config-steps.properties index b0f6cda..cc03f6a 100644 --- a/doc/source/steps/config-steps.properties +++ b/doc/source/steps/config-steps.properties @@ -7,9 +7,9 @@ ontologyName=NEAO Analysis Steps thisVersionURI=http://purl.org/neao/0.1.0/steps# latestVersionURI=http://purl.org/neao/steps# previousVersionURI= -dateCreated=2024-XX-XX +dateCreated=2024-12-06 dateModified= -dateIssued=2024-XX-XX +dateIssued=2024-12-06 ontologyRevisionNumber=0.1.0 licenseURI=https://creativecommons.org/licenses/by/4.0/ licenseName=CC-BY 4.0 International