spiketools
is a collection of tools and utilities for analyzing spiking data.
WARNING: This module is in early development, and may change at any time.
spiketools
is an open-source module for processing and analyzing single-unit activity from neuro-electrophysiological recordings.
Available sub-modules in spiketools
include:
measures
: measures and conversions that can be applied to spiking dataobjects
: objects that can be used to manage spiking dataspatial
: space related functionality and measuresstats
: statistical measures for analyzing spiking datasim
: simulations of spiking activity and related functionalityplts
: plotting functions for visualizing spike data and related measuresutils
: additional utilities for working with spiking data
In terms of scope, note that spiketools
is currently organized around analyses of single cell activity, and is not focused on
population measures (though this may be extended in the future).
Note that spiketools
does not cover spike sorting. Check out
spikeinterface for spike sorting.
Documentation for spiketools
is available
here.
The documentation includes:
- Tutorials: which describe and work through each sub-module
- Examples: demonstrating example applications and workflows
- API List: which lists and describes everything available in the module
- Glossary: which defines key terms used in the module
If you have a question about using SpikeTools that doesn't seem to be covered by the documentation, feel free to open an issue and ask!
spiketools
is written in Python, and requires Python >= 3.6 to run.
It has the following required dependencies:
There are also optional dependencies, that offer extra functionality:
- pytest is needed to run the test suite locally
We recommend using the Anaconda distribution to manage these requirements.
This module is currently in development, with no stable release version yet.
Development Version
To get the current development version, first clone this repository:
$ git clone https://github.com/spiketools/spiketools
To install this cloned copy, move into the directory you just cloned, and run:
$ pip install .
Editable Version
To install an editable version, download the development version as above, and run:
$ pip install -e .
This project welcomes and encourages contributions from the community!
To file bug reports and/or ask questions about this project, please use the Github issue tracker.
To see and get involved in discussions about the module, check out:
- the issues board for topics relating to code updates, bugs, and fixes
- the development page for discussion of potential major updates to the module
When interacting with this project, please use the contribution guidelines and follow the code of conduct.