Tuto-GUDHI-cover-complex.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Topological Exploratory Data Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mathieu Carrière, https://mathieucarriere.github.io/website/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from gudhi.cover_complex import MapperComplex, GraphInducedComplex, NerveComplex\n",
    "from gudhi import bottleneck_distance\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from tqdm import tqdm\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "verbose = False # set it to True for debug information"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this notebook, we will see how to use Gudhi in order to perform topological dimension reduction: we will compute simplicial complex approximations of point cloud / distance matrices. These complexes will be either [Mapper complexes](https://diglib.eg.org/handle/10.2312/SPBG.SPBG07.091-100) or [Graph Induced complexes](http://web.cse.ohio-state.edu/~dey.8/GIC/gic.html). Both complexes use covers of the initial space (such as Voronoi partitions or preimages of filter functions), and use these covers to generate simplicial complexes, either by taking the nerve (Mapper) or by checking the presence of colored cliques (Graph Induced). "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Gudhi can handle both point clouds and distance matrices. Let's start with a point cloud."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Point cloud"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load an example point cloud."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = np.loadtxt('datasets/human.txt')\n",
    "X = np.hstack([X[:,0:1], X[:,2:3], X[:,1:2]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
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       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "function getModifiers(event) {\n",
       "    var mods = [];\n",
       "    if (event.ctrlKey) {\n",
       "        mods.push('ctrl');\n",
       "    }\n",
       "    if (event.altKey) {\n",
       "        mods.push('alt');\n",
       "    }\n",
       "    if (event.shiftKey) {\n",
       "        mods.push('shift');\n",
       "    }\n",
       "    if (event.metaKey) {\n",
       "        mods.push('meta');\n",
       "    }\n",
       "    return mods;\n",
       "}\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * https://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    // from https://stackoverflow.com/q/1114465\n",
       "    var boundingRect = this.canvas.getBoundingClientRect();\n",
       "    var x = (event.clientX - boundingRect.left) * this.ratio;\n",
       "    var y = (event.clientY - boundingRect.top) * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        modifiers: getModifiers(event),\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def set_axes_equal(ax: plt.Axes):\n",
    "    limits = np.array([\n",
    "        ax.get_xlim3d(),\n",
    "        ax.get_ylim3d(),\n",
    "        ax.get_zlim3d(),\n",
    "    ])\n",
    "    origin = np.mean(limits, axis=1)\n",
    "    radius = 0.5 * np.max(np.abs(limits[:, 1] - limits[:, 0]))\n",
    "    x, y, z = origin\n",
    "    ax.set_xlim3d([x - radius, x + radius])\n",
    "    ax.set_ylim3d([y - radius, y + radius])\n",
    "    ax.set_zlim3d([z - radius, z + radius])\n",
    "    \n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(projection='3d')\n",
    "ax.set_box_aspect([1.0, 1.0, 1.0])\n",
    "ax.scatter(X[::2,1], X[::2,0], X[::2,2], s=1)\n",
    "set_axes_equal(ax)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will use the height function to color the complex nodes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "height = X[:,2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We next provide different configurations for computing cover complexes:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Graph Induced complex with a Voronoi partition with 100 randomly sampled germs and Rips graph obtained with automatic threshold. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "cover_complex = GraphInducedComplex(\n",
    "    input_type='point cloud', cover='voronoi', min_points_per_node=0,\n",
    "    graph=\"rips\", rips_threshold=None, N=100, beta=0., C=10,\n",
    "    voronoi_samples=100, verbose=verbose)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "_ = cover_complex.fit(X, filter=height, color=height)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Graph Induced complex with a preimage partition with automatic resolution and Rips graph obtained with automatic threshold. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "cover_complex = GraphInducedComplex(\n",
    "    input_type='point cloud', cover='functional', min_points_per_node=0,\n",
    "    graph=\"rips\", rips_threshold=None, N=100, beta=0., C=10,\n",
    "    resolution=None, gain=0., verbose=verbose)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "_ = cover_complex.fit(X, filter=height, color=height)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mapper complex with a preimage cover with automatic resolution and hierarchical clustering obtained with automatic threshold. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "cover_complex = MapperComplex(\n",
    "    input_type='point cloud', min_points_per_node=0,\n",
    "    clustering=None, N=100, beta=0., C=10,\n",
    "    filter_bnds=None, resolutions=None, gains=None,\n",
    "    verbose=verbose)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "_ = cover_complex.fit(X, filters=height, colors=height)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Distance matrix"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can actually compute the same complexes using only the pairwise distances between points."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import pairwise_distances"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "D = pairwise_distances(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\n",
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       "        fig.send_message('refresh', {});\n",
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       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute('tabindex', '0');\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;' +\n",
       "            'z-index: 2;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box;' +\n",
       "            'pointer-events: none;' +\n",
       "            'position: relative;' +\n",
       "            'z-index: 0;'\n",
       "    );\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box;' +\n",
       "            'left: 0;' +\n",
       "            'pointer-events: none;' +\n",
       "            'position: absolute;' +\n",
       "            'top: 0;' +\n",
       "            'z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            /* This rescales the canvas back to display pixels, so that it\n",
       "             * appears correct on HiDPI screens. */\n",
       "            canvas.style.width = width + 'px';\n",
       "            canvas.style.height = height + 'px';\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        /* User Agent sniffing is bad, but WebKit is busted:\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=144526\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=181818\n",
       "         * The worst that happens here is that they get an extra browser\n",
       "         * selection when dragging, if this check fails to catch them.\n",
       "         */\n",
       "        var UA = navigator.userAgent;\n",
       "        var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n",
       "        if(isWebKit) {\n",
       "            return function (event) {\n",
       "                /* This prevents the web browser from automatically changing to\n",
       "                 * the text insertion cursor when the button is pressed. We\n",
       "                 * want to control all of the cursor setting manually through\n",
       "                 * the 'cursor' event from matplotlib */\n",
       "                event.preventDefault()\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        } else {\n",
       "            return function (event) {\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        }\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    canvas_div.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    canvas_div.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    fig.canvas_div.style.cursor = msg['cursor'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "function getModifiers(event) {\n",
       "    var mods = [];\n",
       "    if (event.ctrlKey) {\n",
       "        mods.push('ctrl');\n",
       "    }\n",
       "    if (event.altKey) {\n",
       "        mods.push('alt');\n",
       "    }\n",
       "    if (event.shiftKey) {\n",
       "        mods.push('shift');\n",
       "    }\n",
       "    if (event.metaKey) {\n",
       "        mods.push('meta');\n",
       "    }\n",
       "    return mods;\n",
       "}\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * https://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    // from https://stackoverflow.com/q/1114465\n",
       "    var boundingRect = this.canvas.getBoundingClientRect();\n",
       "    var x = (event.clientX - boundingRect.left) * this.ratio;\n",
       "    var y = (event.clientY - boundingRect.top) * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        modifiers: getModifiers(event),\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.imshow(D)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This time, color is given by eccentricity."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "ecc = D.max(axis=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Graph Induced complex with a preimage partition with automatic resolution and Rips graph obtained with automatic threshold. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "cover_complex = GraphInducedComplex(\n",
    "    input_type='distance matrix', cover='functional', min_points_per_node=0,\n",
    "    graph=\"rips\", rips_threshold=None, N=100, beta=0., C=10,\n",
    "    resolution=None, gain=0., verbose=verbose)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "_ = cover_complex.fit(D, filter=ecc, color=ecc)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Graph Induced complex with a Voronoi partition with 100 randomly sampled germs and Rips graph obtained with automatic threshold. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "cover_complex = GraphInducedComplex(\n",
    "    input_type='distance matrix', cover='voronoi', min_points_per_node=0,\n",
    "    graph=\"rips\", rips_threshold=None, N=100, beta=0., C=10,\n",
    "    voronoi_samples=100, verbose=verbose)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "_ = cover_complex.fit(D, filter=ecc, color=ecc)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mapper complex with a preimage cover with automatic resolution and hierarchical clustering obtained with automatic threshold. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "cover_complex = MapperComplex(\n",
    "    input_type='distance matrix', min_points_per_node=0,\n",
    "    clustering=None, N=100, beta=0., C=10,\n",
    "    filter_bnds=None, resolutions=None, gains=None, verbose=verbose)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "_ = cover_complex.fit(D, filters=ecc, colors=ecc)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# More than one filter"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mapper complex with a preimage cover with automatic resolution from a 2D function and hierarchical clustering obtained with automatic threshold. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "filt2d = np.hstack([height[:,np.newaxis],X[:,0:1]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "cover_complex = MapperComplex(\n",
    "    input_type='point cloud', min_points_per_node=0,\n",
    "    clustering=None, N=100, beta=0., C=10,\n",
    "    filter_bnds=None, resolutions=[20,2], gains=None, verbose=verbose)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "_ = cover_complex.fit(X, filters=filt2d, colors=filt2d)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualization"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can visualize the complex in three different ways with Gudhi."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. You can use Python package `networkx`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "import networkx as nx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "G = cover_complex.get_networkx()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute('tabindex', '0');\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;' +\n",
       "            'z-index: 2;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box;' +\n",
       "            'pointer-events: none;' +\n",
       "            'position: relative;' +\n",
       "            'z-index: 0;'\n",
       "    );\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box;' +\n",
       "            'left: 0;' +\n",
       "            'pointer-events: none;' +\n",
       "            'position: absolute;' +\n",
       "            'top: 0;' +\n",
       "            'z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            /* This rescales the canvas back to display pixels, so that it\n",
       "             * appears correct on HiDPI screens. */\n",
       "            canvas.style.width = width + 'px';\n",
       "            canvas.style.height = height + 'px';\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        /* User Agent sniffing is bad, but WebKit is busted:\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=144526\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=181818\n",
       "         * The worst that happens here is that they get an extra browser\n",
       "         * selection when dragging, if this check fails to catch them.\n",
       "         */\n",
       "        var UA = navigator.userAgent;\n",
       "        var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n",
       "        if(isWebKit) {\n",
       "            return function (event) {\n",
       "                /* This prevents the web browser from automatically changing to\n",
       "                 * the text insertion cursor when the button is pressed. We\n",
       "                 * want to control all of the cursor setting manually through\n",
       "                 * the 'cursor' event from matplotlib */\n",
       "                event.preventDefault()\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        } else {\n",
       "            return function (event) {\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        }\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    canvas_div.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    canvas_div.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    fig.canvas_div.style.cursor = msg['cursor'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "function getModifiers(event) {\n",
       "    var mods = [];\n",
       "    if (event.ctrlKey) {\n",
       "        mods.push('ctrl');\n",
       "    }\n",
       "    if (event.altKey) {\n",
       "        mods.push('alt');\n",
       "    }\n",
       "    if (event.shiftKey) {\n",
       "        mods.push('shift');\n",
       "    }\n",
       "    if (event.metaKey) {\n",
       "        mods.push('meta');\n",
       "    }\n",
       "    return mods;\n",
       "}\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * https://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    // from https://stackoverflow.com/q/1114465\n",
       "    var boundingRect = this.canvas.getBoundingClientRect();\n",
       "    var x = (event.clientX - boundingRect.left) * this.ratio;\n",
       "    var y = (event.clientY - boundingRect.top) * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        modifiers: getModifiers(event),\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "nx.draw(G, pos=nx.kamada_kawai_layout(G), node_color=[cover_complex.node_info_[v][\"colors\"][0] for v in G.nodes()])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2. You can create a DOT file that can be processed later with `neato` to produce a PDF."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute('tabindex', '0');\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;' +\n",
       "            'z-index: 2;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box;' +\n",
       "            'pointer-events: none;' +\n",
       "            'position: relative;' +\n",
       "            'z-index: 0;'\n",
       "    );\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box;' +\n",
       "            'left: 0;' +\n",
       "            'pointer-events: none;' +\n",
       "            'position: absolute;' +\n",
       "            'top: 0;' +\n",
       "            'z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            /* This rescales the canvas back to display pixels, so that it\n",
       "             * appears correct on HiDPI screens. */\n",
       "            canvas.style.width = width + 'px';\n",
       "            canvas.style.height = height + 'px';\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        /* User Agent sniffing is bad, but WebKit is busted:\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=144526\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=181818\n",
       "         * The worst that happens here is that they get an extra browser\n",
       "         * selection when dragging, if this check fails to catch them.\n",
       "         */\n",
       "        var UA = navigator.userAgent;\n",
       "        var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n",
       "        if(isWebKit) {\n",
       "            return function (event) {\n",
       "                /* This prevents the web browser from automatically changing to\n",
       "                 * the text insertion cursor when the button is pressed. We\n",
       "                 * want to control all of the cursor setting manually through\n",
       "                 * the 'cursor' event from matplotlib */\n",
       "                event.preventDefault()\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        } else {\n",
       "            return function (event) {\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        }\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    canvas_div.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    canvas_div.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    fig.canvas_div.style.cursor = msg['cursor'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "function getModifiers(event) {\n",
       "    var mods = [];\n",
       "    if (event.ctrlKey) {\n",
       "        mods.push('ctrl');\n",
       "    }\n",
       "    if (event.altKey) {\n",
       "        mods.push('alt');\n",
       "    }\n",
       "    if (event.shiftKey) {\n",
       "        mods.push('shift');\n",
       "    }\n",
       "    if (event.metaKey) {\n",
       "        mods.push('meta');\n",
       "    }\n",
       "    return mods;\n",
       "}\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * https://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    // from https://stackoverflow.com/q/1114465\n",
       "    var boundingRect = this.canvas.getBoundingClientRect();\n",
       "    var x = (event.clientX - boundingRect.left) * this.ratio;\n",
       "    var y = (event.clientY - boundingRect.top) * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        modifiers: getModifiers(event),\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"600\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cover_complex.save_to_dot(file_name=\"human\", color_name=\"color\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "!neato -Tpdf human.dot -o human.pdf"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3. You can create an HTML file and visualize it in browser."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'human.html' is generated. You can now use your favorite web browser to visualize it.\n"
     ]
    }
   ],
   "source": [
    "cover_complex.save_to_html(file_name=\"human\", data_name=\"human\", cover_name=\"uniform\", color_name=\"height\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"100%\"\n",
       "            height=\"500px\"\n",
       "            src=\"human.html\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "            \n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x7f5bb0f6b9d0>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import IFrame\n",
    "IFrame(src=\"human.html\", width='100%', height='500px')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Alternatively, you can create a TXT file that you can process later with our KeplerMapper wrapper to produce the HTML file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "cover_complex.save_to_txt(file_name=\"human\", data_name=\"human\", cover_name=\"uniform\", color_name=\"height\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'human.html' is generated. You can now use your favorite web browser to visualize it.\r\n"
     ]
    }
   ],
   "source": [
    "!python ./utils/KeplerMapperVisuFromTxtFile.py -f human.txt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Topological features"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this section, we will do a variety of post-processing, statistical tasks for the computed cover complex, including, e.g., computing the topological features and/or assessing their stability. For these operations, we will need a set of helper functions, which we define below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "cover_complex = MapperComplex(\n",
    "    input_type='point cloud', min_points_per_node=0,\n",
    "    clustering=None, N=100, beta=0., C=10,\n",
    "    filter_bnds=None, resolutions=None, gains=None,\n",
    "    verbose=verbose)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "_ = cover_complex.fit(X, filters=height, colors=height)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "cover_complex.data = X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.sparse.csgraph    import dijkstra, shortest_path, connected_components\n",
    "from scipy.stats             import ks_2samp\n",
    "\n",
    "def find(i, parents):\n",
    "    if parents[i] == i:\n",
    "        return i\n",
    "    else:\n",
    "        return find(parents[i], parents)\n",
    "\n",
    "def union(i, j, parents, f):\n",
    "    if f[i] <= f[j]:\n",
    "        parents[j] = i\n",
    "    else:\n",
    "        parents[i] = j\n",
    "        \n",
    "def compute_topological_features(M, threshold=0.):\n",
    "    \"\"\"\n",
    "    Compute the topological features (connected components, up/down branches, loops) of the 1-skeleton of the cover complex. Connected components and loops are computed with scipy functions, and branches are detected with Union-Find and 0-dimensional persistence of the 1-skeleton.\n",
    "    Parameters:\n",
    "        threshold (float): any topological feature whose size is less than this parameter (relative to the first color function) will be discarded.\n",
    "    Returns:\n",
    "        dgm (list of (dim,(a,b)) tuples): list of feature characteristics. dim is the topological dimension of the feature (0 for CCs and branches, 1 for loops), a,b are the min and max of the first color function along the feature.\n",
    "        bnds (list of lists): list of feature points. Each element of this list is the list of point IDs forming the corresponding feature. \n",
    "    \"\"\"\n",
    "    st = M.simplex_tree_\n",
    "    num_nodes = st.num_vertices()\n",
    "    function, namefunc, invnamefunc = {}, {}, {}\n",
    "    nodeID = 0\n",
    "    for (s,_) in st.get_skeleton(0):\n",
    "        namefunc[s[0]] = nodeID\n",
    "        invnamefunc[nodeID] = s[0]\n",
    "        function[s[0]] = M.node_info_[s[0]][\"colors\"][0]\n",
    "        nodeID += 1\n",
    "    dgm, bnd = [], []\n",
    "\n",
    "    # connected_components\n",
    "    A = np.zeros([num_nodes, num_nodes])\n",
    "    for (splx,_) in st.get_skeleton(1):\n",
    "        if len(splx) == 2:\n",
    "            A[namefunc[splx[0]], namefunc[splx[1]]] = 1\n",
    "            A[namefunc[splx[1]], namefunc[splx[0]]] = 1\n",
    "    _, ccs = connected_components(A, directed=False)\n",
    "    for ccID in np.unique(ccs):\n",
    "        pts = np.argwhere(ccs == ccID).flatten()\n",
    "        vals = [function[invnamefunc[p]] for p in pts]\n",
    "        if np.abs(min(vals) - max(vals)) >= threshold:\n",
    "            dgm.append((0, (min(vals), max(vals))))\n",
    "            bnd.append([invnamefunc[p] for p in pts])\n",
    "\n",
    "    # loops\n",
    "    G = M.get_networkx()\n",
    "    try:\n",
    "        from networkx import cycle_basis\n",
    "        bndall = cycle_basis(G)\n",
    "        for pts in bndall:\n",
    "            vals = [function[p] for p in pts]\n",
    "            if np.abs(min(vals) - max(vals)) >= threshold:\t\n",
    "                dgm.append((1,(min(vals), max(vals))))\n",
    "                bnd.append(pts)\n",
    "    except ImportError:\n",
    "        print(\"Networkx not found, loops not computed\")\n",
    "        \n",
    "    # branches\n",
    "    for topo_type in [\"downbranch\", \"upbranch\"]:\n",
    "\n",
    "        lfunction = []\n",
    "        for i in range(num_nodes):\n",
    "            lfunction.append(function[invnamefunc[i]])\n",
    "\n",
    "        # upranch is downbranch of opposite function\n",
    "        if topo_type == \"upbranch\":\n",
    "            lfunction = [-f for f in lfunction]\n",
    "\n",
    "        # sort vertices according to function values and compute inverse function \n",
    "        sorted_idxs = np.argsort(np.array(lfunction))\n",
    "        inv_sorted_idxs = np.zeros(num_nodes)\n",
    "        for i in range(num_nodes):\n",
    "            inv_sorted_idxs[sorted_idxs[i]] = i\n",
    "\n",
    "        # go through all vertices in ascending function order\n",
    "        persistence_diag, persistence_set, parents, visited = {}, {}, -np.ones(num_nodes, dtype=np.int32), {}\n",
    "        for i in range(num_nodes):\n",
    "\n",
    "            current_pt = sorted_idxs[i]\n",
    "            neighbors = np.ravel(np.argwhere(A[current_pt,:] == 1))\n",
    "            lower_neighbors = [n for n in neighbors if inv_sorted_idxs[n] <= i] if len(neighbors) > 0 else []\n",
    "\n",
    "            # no lower neighbors: current point is a local minimum\n",
    "            if lower_neighbors == []:\n",
    "                parents[current_pt] = current_pt\n",
    "\n",
    "            # some lower neighbors exist\n",
    "            else:\n",
    "\n",
    "                # find parent pg of lower neighbors with lowest function value\n",
    "                neigh_parents = [find(n, parents) for n in lower_neighbors]\n",
    "                pg = neigh_parents[np.argmin([lfunction[n] for n in neigh_parents])]\n",
    "\n",
    "                # set parent of current point to pg\n",
    "                parents[current_pt] = pg\n",
    "\n",
    "                # for each lower neighbor, we will create a persistence diagram point and corresponding set of nodes\n",
    "                for neighbor in lower_neighbors:\n",
    "\n",
    "                    # get parent pn\n",
    "                    pn = find(neighbor, parents)\n",
    "                    val = lfunction[pn]\n",
    "                    persistence_set[pn] = []\n",
    "\n",
    "                    # we will create persistence set only if parent pn is not local minimum pg\n",
    "                    if pn != pg:\n",
    "                        # go through all strictly lower nodes with parent pn\n",
    "                        for v in sorted_idxs[:i]:\n",
    "                            if find(v, parents) == pn:\n",
    "                                # if it is already part of another persistence set, continue\n",
    "                                try:\n",
    "                                    visited[v]\n",
    "                                # else, mark visited and include it in current persistence set\n",
    "                                except KeyError:\n",
    "                                    visited[v] = True\n",
    "                                    persistence_set[pn].append(v)\n",
    "\n",
    "                        # add current point to persistence set\n",
    "                        persistence_set[pn].append(current_pt)\n",
    "\n",
    "                        # do union and create persistence point corresponding to persistence set if persistence is sufficiently large\n",
    "                        if np.abs(lfunction[pn]-lfunction[current_pt]) >= threshold:\n",
    "                            persistence_diag[pn] = current_pt\n",
    "                            union(pg, pn, parents, lfunction)\n",
    "\n",
    "        for key, val in iter(persistence_diag.items()):\n",
    "            if topo_type == \"downbranch\":\n",
    "                dgm.append((0, (lfunction[key],  lfunction[val])))\n",
    "            elif topo_type == \"upbranch\":\n",
    "                dgm.append((0, (-lfunction[val], -lfunction[key])))\n",
    "            bnd.append([invnamefunc[v] for v in persistence_set[key]])\n",
    "\n",
    "    bnd = [list(b) for b in bnd]\n",
    "    M.persistence_diagram, M.persistence_sets = dgm, bnd \n",
    "    return dgm, bnd\n",
    "\n",
    "def bootstrap_topological_features(M, N):\n",
    "    \"\"\"\n",
    "    Use bootstrap to empirically assess stability of the features. This function computes a distribution of bottleneck distances, that can used afterwards to run tests on each topological feature.\n",
    "    Parameters:\n",
    "        N (int): number of bootstrap iterations.\n",
    "    \"\"\"\n",
    "\n",
    "    dgm = M.persistence_diagram\n",
    "    num_pts, distribution = len(M.data), []\n",
    "    for bootstrap_id in tqdm(range(N)):\n",
    "\n",
    "        # Randomly select points\n",
    "        idxs = np.random.choice(num_pts, size=num_pts, replace=True)\n",
    "        Xboot = M.data[idxs,:] if M.input_type == \"point cloud\" else M.data[idxs,:][:,idxs]\n",
    "        f_boot, c_boot = M.filters[idxs,:], M.colors[idxs,:]\n",
    "        Mboot = M.__class__(filter_bnds=M.filter_bnds, resolutions=M.resolutions, gains=M.gains, \n",
    "                            input_type=M.input_type, clustering=M.clustering).fit(Xboot, filters=f_boot, colors=c_boot)\n",
    "\n",
    "        # Compute the corresponding persistence diagrams\n",
    "        dgm_boot, _ = compute_topological_features(Mboot)\n",
    "\n",
    "        # Compute the bottleneck distance\n",
    "        npts, npts_boot = len(dgm), len(dgm_boot)\n",
    "        D1 = np.array([[dgm[pt][1][0], dgm[pt][1][1]] for pt in range(npts)]) \n",
    "        D2 = np.array([[dgm_boot[pt][1][0], dgm_boot[pt][1][1]] for pt in range(npts_boot)])\n",
    "        bottle = bottleneck_distance(D1, D2)\n",
    "        distribution.append(bottle)\n",
    "        M.distribution = np.sort(distribution)\n",
    "\n",
    "def get_distance_from_confidence_level(M, alpha=.95, complex_type='mapper'):\n",
    "    \"\"\"\n",
    "    Compute the bottleneck distance threshold corresponding to a specific confidence level.\n",
    "    Parameters:\n",
    "        alpha (float): confidence level.\n",
    "    Returns:\n",
    "        distance value (float); each feature whose size is above this distance is sure at confidence level alpha.\n",
    "    \"\"\"\n",
    "    return M.distribution[int(alpha*len(M.distribution))]\n",
    "\n",
    "def get_confidence_level_from_distance(M, distance):\n",
    "    \"\"\"\n",
    "    Compute the confidence level of a specific bottleneck distance threshold.\n",
    "    Parameters:\n",
    "        distance (float): bottleneck distance threshold.\n",
    "    Returns:\n",
    "        confidence level (float); each feature whose size is above the distance threshold is sure at this confidence level.\n",
    "    \"\"\"\n",
    "    return len(np.argwhere(M.distribution <= distance))/len(M.distribution)\n",
    "\n",
    "def get_pvalue(M):\n",
    "    \"\"\"\n",
    "    Compute the p-value, i.e. the opposite of the confidence level of the largest bottleneck distance preserving the topological features.\n",
    "    Returns:\n",
    "        p-value (float)\n",
    "    \"\"\"\n",
    "    distancemin = min([np.abs(pt[1][0]-pt[1][1]) for pt in M.persistence_diagram])\n",
    "    return 1.-M.compute_confidence_from_distance(distancemin)\n",
    "\n",
    "def compute_differential_coordinates(M, nodes=None, features=None, sparse=False):\n",
    "    \"\"\"\n",
    "    Compute the coordinates that best explain a set of nodes VS the rest of the nodes (in the 1-skeleton of the cover complex) with a Kolmogorov-Smirnov test. Only works if input_type is \"point cloud\".\n",
    "    Parameters:\n",
    "        nodes (list of integers): list of nodes to try. For instance, one can take the list of nodes obtained after calling \"compute_topological_features\"\n",
    "        features (list of integers): the coordinates to try. All coordinates are tested if None.\n",
    "        sparse (bool): set to True if your data is sparse and there will be speedup, otherwise use False.\n",
    "    Returns:\n",
    "        features (list of integers): the list of coordinates, ranked from smallest to largest p-values.\n",
    "        p-values (list of float): the corresponding p-values. \n",
    "    \"\"\"\n",
    "    if M.input_type == \"distance matrix\":\n",
    "        print(\"Need coordinates for running differential coordinates!\")\n",
    "        raise\n",
    "\n",
    "    node_info = M.node_info_\n",
    "    X = M.data\n",
    "    nodes = [s[0] for s,_ in self.simplex_tree_.get_skeleton(0)] if nodes is None else nodes\n",
    "\n",
    "    if features is None:\n",
    "        features = np.arange(X.shape[1])\n",
    "\n",
    "    list_idxs1 = list(np.unique(np.concatenate([node_info[node_name][\"indices\"] for node_name in nodes])))\n",
    "    list_idxs2 = list(set(np.arange(X.shape[0]))-set(list_idxs1))\n",
    "    pvals = []\n",
    "    for f in features:\n",
    "        if sparse:\n",
    "            Xsp = csr_matrix(X)\n",
    "            group1 = np.squeeze(np.array(Xsp[list_idxs1,f].todense()))\n",
    "            group2 = np.squeeze(np.array(Xsp[list_idxs2,f].todense()))\n",
    "        else:\n",
    "            group1, group2 = X[list_idxs1,f], X[list_idxs2,f]\n",
    "        _,pval = ks_2samp(group1, group2)\n",
    "        pvals.append(pval)\n",
    "    pvals = np.array(pvals)\n",
    "    F, P = features[np.argsort(pvals)], np.sort(pvals) \n",
    "    return F, P"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are various postprocessing one can do on a cover complex. For instance, one can compute the topological features in the complex. For our human shape, the topological features (identified by computing the persistence of the color function on the complex) are the three branches corresponding to the arms and legs (the lower leg correspond to the whole connected component)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "dgm, bnd = compute_topological_features(cover_complex, threshold=0.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
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       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        /* User Agent sniffing is bad, but WebKit is busted:\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=144526\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=181818\n",
       "         * The worst that happens here is that they get an extra browser\n",
       "         * selection when dragging, if this check fails to catch them.\n",
       "         */\n",
       "        var UA = navigator.userAgent;\n",
       "        var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n",
       "        if(isWebKit) {\n",
       "            return function (event) {\n",
       "                /* This prevents the web browser from automatically changing to\n",
       "                 * the text insertion cursor when the button is pressed. We\n",
       "                 * want to control all of the cursor setting manually through\n",
       "                 * the 'cursor' event from matplotlib */\n",
       "                event.preventDefault()\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        } else {\n",
       "            return function (event) {\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        }\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    canvas_div.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    canvas_div.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    fig.canvas_div.style.cursor = msg['cursor'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "function getModifiers(event) {\n",
       "    var mods = [];\n",
       "    if (event.ctrlKey) {\n",
       "        mods.push('ctrl');\n",
       "    }\n",
       "    if (event.altKey) {\n",
       "        mods.push('alt');\n",
       "    }\n",
       "    if (event.shiftKey) {\n",
       "        mods.push('shift');\n",
       "    }\n",
       "    if (event.metaKey) {\n",
       "        mods.push('meta');\n",
       "    }\n",
       "    return mods;\n",
       "}\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * https://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    // from https://stackoverflow.com/q/1114465\n",
       "    var boundingRect = this.canvas.getBoundingClientRect();\n",
       "    var x = (event.clientX - boundingRect.left) * this.ratio;\n",
       "    var y = (event.clientY - boundingRect.top) * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        modifiers: getModifiers(event),\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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Bw2ZllU3MCYR3KNHD0ybNg1//PEHUqdOrYvVsgNcvHhxVbRY3g1ix2Yacl0G4jNC6YAYZSSoR4QJnD9/Xm31ywOvd+/eEe7vazsQJ6hGjRrYt28fzp07h6RJk35tF/y8ExCQB67sfB0+fBj582ufdODFixfKAfby8lK1Sdzc3JyAKk34WgLVq1eH1GOQ3bgYMWJ87eUR/rzIlt2Pfv36YcCAARHujx04HgE/Pz8VBiihoFIjRI82evRo9T7w+++/q0VKNuMQoANinLGgJjYg0K1bN1Wc8NKlS6pSupZtwYIFaNasGdauXQt5+LOZk4CsuMkDV9qxY8c0dwAk1l7CwMQJljAcNnMSkAKtcv6sTZs2GDdO24xTr1+/VuE3EoZ44MABuLuz6KA5ZyGwatUqdebCx8cH5cuX1xSDhP1JQcTOnTtDHBE2YxGgA2Ks8aA2ESTw6tUrteIiK8/r1q2LYG9ffvmNGzfUqnPNmjUhjgibuQkcPXoUBQoUUOeA2rfXLjPbypUrVciNHLgUR4TN3AQkBO/nn39W5y8kNFSr1qpVKyxduhRnzpxB+vTptRJLOQYkIJEBpUuXhjwjJStf1KjaZJ0KCAjAt99+i0iRIkHux3qFZRtwSAyjEh0QwwwFFbEVAclyUa9ePWzdulUdBrd3Cw4OVlu79+/fVzGmMWPGtLdI9u8ABOQlTFb/JAQmUSL7F4S7e/euesmUh738H9Dz8LEDDI8pVAwKClILIwkSJICcC9JiTmzatAlVqlRRGa/k/wAbCcg9UO5NP/30E+RckBZNdj0kGuLkyZPw9vbWQiRlfCUBOiBfCYwfNz4BWXEpWbIkJPOFrLjYO/3osGHD0L9/f/WAl5hnNhIQAr6+vupAesWKFbFo0SK7QpGc++J4XL58WYVexY0b167y2LnjEJBzQHI/lDkoaUjt2R49eqReNGUHeuPGjZo4PPa0h33bjkDfvn1VKKBkx0qbNq3tOv5MT7t27VL3wwkTJqjwKzZjEqADYsxxoVYRJCAvYpJ2T2569jwAKfUVJNRGMg2JI8JGAh8TkExYsgosiQm+++47u8GRdLtdunQxRBpquxnJjsNNQMLy5BCurETbKwuQLPxUrlxZnXuShCAJEyYMt7680PkI+Pv7I3PmzGo3Qs6D2Gs3TlI+ixMssnbs2GGteO7qfDCdxCI6IE4ykDTjvwn06dNHrYBICsA0adLYHJFUO8+VKxc8PT1VxqPIkSPbXAY7dGwCsjNRsGBByMNXilJKPLKtm+zySaxz27Zt1XxnI4G/E7h37546Gyd1auRckj2ahFzJgXdJgCC7fmwk8HcCGzZsQLVq1VRGrKpVq9ockDjBcuBd6t+IE5wsWTKby2CHtiNAB8R2LNmTwQiErbjIaog8FG214nL97C0cXH8MO/dtx9pDy3HqNKudG2zoDaWOOB558uTB2LFj1S6FrdqhTcdx6ehVzFgxFW+j+rHaua3AOmk/48ePh9RlkMKUsnBii2axBAEBa/D08VWUrDAB+QvXZbVzW4B10j7EQRDnVBZNZGFQFu9s0XwfPMeOBb/j3IWzGLt8OJatXIratWvbomv2YUcCdEDsCJdd609AVlokJa6svMjByIi2G+duo33e3ggJDoEl1ILUhZJizv5JEe2W1zs5AakLsnjxYnVGwxb1YbbM2oVJbWcDLlZwFqDh6Bpo1F2/gnNOPnxOYZ5UJQ/bsT106JBNQlNCn/8IS+AOhIYAb62+iFt8H0SLwaxXTjFh7GTE9evXVRhW165dMXz48AhL8X/1Bi2ydIXv/WeQHedIcVyx5fFyzdOfR9gQE3ZAB8SEg24mk2XFpUKFCrh18i56teuL3CWyIUvhTP+IQDLHSEYrCVv4+/fDwy/gdsfT+t4nb35A5KiR4eO/1ExIaWs4CEhxwIwZMqKg1/eoW+MHFKmVH0m8/jkzltRS+NwclH97/us7uL/2UJpYrF/5KuTCsM0/hUMzXmImAvv370eJIiXRqXYPFC5SGKWbfI+onu/n0eea3D8lpv6z98KHd7Fh9rUPl1k/Ckv0n+Eew74H3c00Xs5q66BBg7BhzWhs39QbCZN8C0Qp+48RClJbSRIcfPZ+eO4RXM5+Wmhz3h8TkfIbhl8Zff7QATH6CFG/CBNYPHIFfvlp7fvVYmtrNrEO4maI8dmbmaQyffLkyScyJW+5xJLKd9ygxPA7Yl3u+8+Lnz9eIV39ROqge7p06SKsKztwXgItC3bCrSP3rQ9awCO6Bzotawb/EL9P5qHMv7CHrNS0+bjJ4eGweehxIy7e3AhWux/igDyMdBs1+1RQIV6xYsVyXoi0LEIEAl4HoFqSxgj2D1WLKF45UqLR5Op48OD/F1w+noOyEPP27dsPMiWMVQ6Xv5+HSbFo3E3E8Ayy7qa8/0iL7iH4vvQA1K9fnyvQERop57448PUpWJ7Xgbubi5o7zwLr4PyN4v/zXvjw4UOIExLWpLCl7CTLPEwcIxn8dr3/jdwLLZZQhBR8jmGjh6JQoULODdLBraMD4uADSPX/nUDn737GxYNX3t+grMt0j3EP53FE/V3y48tNLHny5B9e7sJe8sL+lBe/sPMjssU7o8tC7Fy0BwlSxEe6Kokxef5EPH78WFVBl6JfWldg/3cC/ITeBN4FvUN5jx8+qCHz8ApO4y5uqBe1JEmS/OM8lIftx/HSL568xLC6E3Hl+DVkKpQeQeleYObcGarIl2Rk+/HHH20WX603O8q3HYHjO87gp3KfZus7ZNmON3it0pX/271Q5unHiRQsQWdhedkDCH2Gx69Lo233P6zhrhvVgffBgwejRo0aNgn1sh0B9mQEAqF+YxDqN886N0KVOo+eBCNptpvq548XWv7+LA77uzy3P85u5TN7Fxb0WwH3yO7I3zgbFm6Zo2pylS1bFkOHDkXu3LmNYDZ1+BsBOiCcEk5PYGi9Cdiz8qBa8XNxdUHeGtnRYlR99dJni+qoUnF1+vTpkKrDsmrdunVrVXApceLETs+WBn4ZAXE4qidoCr9nrz+E7zUaVwMl6xZVK8rihES0yWq1pIKW1L9x4sRRc1Dmor3r4ERUb16vHYGbF+6gVbZuHwS6WlegB/3eHRkyp1NzxhaJOiQ1eb9+/bB9+3bkyJEDQ4YMUWGwtuhbO1KUZE8CFv/FCH01VO0Gh4a64HVgSjx+N005wLY4mC4LhWvWrFH1uST1tGTeEoc4S5Ys9jSLfX8lATogXwmMH3c8AiMHj8bagdsRzz0Bsn3vjf6ruiF6bNtk3/iYhp+fHyZPnowxY8ZAzpHIKrSsRseLF8/xoFFjmxJQ2V8KV4H/UcAzcnRUaV8WLUc3tMtL2a1bt9RL38KFC1WYgrwMNm3a1C4pgG0KiZ3ZncDLly9RMGUxJA1IgxgxY6DTjFYoWquAXeTKeRPZEZYaOFKYUFaiS5QoYRdZ7NSxCBw+tA/XTtdGnapxrLsWqeESZwpc3G0fwhwcHIxly5ap6utyX6xXr576OX16JkowwoyhA2KEUaAOdiMQlv9eKgBPmzbNbnI+7vj58+eq4qsUh5OVbcn2IbH5MWPG1EQ+hRiPQFj+e1mVk7AULdrVq1fV2aQVK1aoOjjy4P3hhx9sstuihf6UYXsCHTt2xPz583Hp0iWkSJHC9gL+1qM43lKTQRwRKVBYrFgx5YhIbRw2cxIQp0BCoqRu1pEjRzS5H8mC4IIFC9TCjJwnkXo4sjvCcGl95yAdEH35U7qdCUgucFmBk/Sn9qoA/L9MkHMho0aNUo6PbCvLboikY5Wfg98FW1NXhiKyB4sX2nkK6N69ZLOSqrxSj2bLli122fX4JyPPnTunHrYbN25EpkyZVCiCpKaWGOrAgEC4R3KHm3vEQ8B0B00F/pFAWD2a0aNHo1u3/w/D0gKbOCJSi0l242Q+litXTjkikhZYfgfLG2uSkGia/9/QwnbK+JRAWD0acUi1Ppsh4dJSMFPS/8puYKtWrVSoqoRjS9hWYEDQP2aF41jalgAdENvyZG8GIrBjxw51CG3JkiUqK4teTXZhwmLzJRyrQYlmuLj2pqolUqdnVTQf/v+Hk/XSkXLtR0AcT6k+ffHiRbUToVeTAnTyAij/L3LmyImiicriws4/4eEZBX2WdELBKnn0Uo1y7UxAMggVKFBAZbQ6efKkbuF48pK3evVqtTMnsflNGlXG1GHWlz7369YiIimsoTjzrKE4qe1Mg93rRUAyrMkiiOxAyD1RryaLQiJfnPHAwEA0rd4CD3b4wc/3NfKWy4kBa7tzcVCDwaEDogFkitCegKx0yIpzqlSpVAiAEQ5A3rx5EwP7DsK9FX7Wg8j/yVtpRTP58HBkyseYVO1nif0lSsXfnDlzqvCnvn372l/gF0iQHcH+bYcg0qXYHz4tTsiGF4s0CYf4AhX5ERsTmDFjBtq1a4cDBw4YIjWphOEsXboUIS8Go0ENV7i7S4506z0xchG4xrUW2GRzSgI1a9bEwYMHVUSCEdKFS30m2ZH5bdhxeFj+U9/LOhXbjm+C6p0qOOUYGMkoOiBGGg3qYjMCssI2YsQItd0vKSGN0h7dfoIGXu0+UWfo5t7WQnJME2iUMbKVHrLaW7RoUVVXRlJC2iLjmq102z7/N4xrMeOT7rb4L0GUqFFsJYL9GISAFHDLmDEj5OVv7ty5BtHqvRrBz7oAgVvh6mINw5IWKRtc460xlI5UxjYEtm3bhvLly6tD4XIY3Eitevwm1gyF/kolVzdX1OtdDU2G1DWSik6pCx0QpxxWcxslh29l96NHjx4qzthITeKd+1UeiaM+p5RaKazVWqcdH8m4UyMNko10kUOPUhtm9+7dKF68uI16tU03L5++QpucPfD03jPVYbkWJdB1dhvbdM5eDEWgYcOGkJc/CXkyWkY+S9BxWJ41FlfE+m1Nkx5rLFyiVjIUPyoTcQISkSApcL28vLBr1y5DRCR8bNXyEesxv+8y9U9RY3hg+vFRSJ4hacQNZw//SIAOCCeIUxGQF/zSpUvj+vXrKuZeCrMZrckB9IMbjiPIeuCtYNU88IwZzWgqUp8IEvD19VWrzmFnkCLYnV0uFyfk8OaTiBkvOvJXzM2CcXahrG+nv//+u3J+582bp5xhIzZL8DUg6CTg/g1cImc3oorUKYIE5OyZnLc4f/48MmTIEMHe7HP5qd3n8fDmY3xbOhsSpkxgHyHs9RMCdEA4IZyKwPLly1WqUR8fH7Xdy0YCehBo2bKlOmwrq86JEiXSQwXKNDkBOVybPXt2SNXovXv30sE0+XzQy3w575EtWzb06dMHgwYN0ksNyjUgATogBhwUqhQ+ApJWT857FCpUSFVBZSMBPQgcOnRIzUFJvywHf9lIQA8CknlPkh+cPn2aFaD1GADKVCmWpfjknTt3IAk5PDw8SIUEPhCgA8LJ4DQEpPK4VH+WIlvJkyd3GrtoiOMQ0KPIluPQoaZaEbhx4wa8vb0h90QJfWEjAT0ISKazBg0aYPv27ShTpoweKlCmgQnQATHw4FC1Lycgue3z5s2LMWPGqMrjbCSgBwE9i2zpYS9lGo+ArDpXrFhRxdv/8ccfiB49uvGUpEZOT0BS3Mo5OMkEuGrVKqe3lwZ+PQE6IF/PjFcYiMD5/Zewd/UhrNiwDH6xnuLk6ZPWnPLuBtKQqjg7AXnh27FwD87sP4fpyyejSovyuhbZcnbetO/zBAJeB2DdpK04deQ0Zm+Zil/WL0TVqlWJiwQ0JXD/+kNsmbkTu/fsxs5Lm3HhynkkS5ZMUx0ozDEI0AFxjHGilp8h8MfhK+j8XT/rbywIDbEgV8UsGL15IFmRgKYEVozagHl9llqziFprGVhc0HlOS1RoXlpTHSiMBHqUHISzey5C6s+4WGv6Lbw8BcnSJSEYEtCMgGTWa/pNJ/i/9EdISAhiJPLEmrsLWOBUsxFwLEF0QBxrvKjtRwQW/Lwc8vIXGhKq/tUzVjRseL6IjEhAUwLt8/bG1RPX38u0VtEtWqsAfl7BMEBNBx9AOs0AACAASURBVMHkwgIDAlHRs8EnFDrPbIUKrUqZnAzN15LAkS0nVZ2rj9uiP6cgadrEWqpBWQ5CgA6IgwwU1fxvArt+2YvRjaeqX0j10gzfpsWUw8OJigQ0JTD0h/HYs+KQlFGzrjy7oH7fGmg8qI6mOlCYuQlIGGCNRE3x6qmfdRZatz+sbdyeQchWJLO5wdB6TQncuXwPzb07q+xXri4u8PD0wMoHc1hoV9NRcBxhdEAcZ6yo6d8ILFmyBAMbjkTWBLmRNosXus9vh8SpE5ITCWhKoGmDZji38hrSJcyIvOVy4cepzRHZI7KmOlCYuQlIpem8mQoggW9KJI2fHDW6VES1jqyDZO5Zob31Uvy3bI5KyB4zP5KmSIL2k5ohe1Fv7RWhRIcgQAfEIYaJSv6dwMOHD1WaSal6LsUH2UhADwI7duxQ1c7nzJmDFi1a6KECZZIAevXqhYkTJ6qaH5kzc9eDU0J7ApKCXOofvXr1Ss1D1vzQfgwcTSIdEEcbMeqrtndr1qyJ/fv3qzST8ePHJxUS0JyAPGizZMmiil+KI+JiDTlgIwGtCRw7dgwFChTA0KFDVbVpNhLQg4CkwBdH+ODBg2o+spHAvxGgA/JvhPh7wxFYvXo1ateurXKL16pVy3D6USFzEGjbti0kDFAq/KZKlcocRtNKQxEIDAxE7ty51WrzkSNHmILcUKNjHmWuXLmC7Nmzo3379hg3bpx5DKelESJAByRC+Hix1gSePHmiQq+KFCmCNWvWaC2e8khAEfjtt99QokQJTJ8+HeKIsJGAHgT69euHUaNGQQqxZs2aVQ8VKNPkBCTdrhQbfPToEc6ePYto0aKZnAjN/1ICdEC+lBQ/ZwgC9erVw86dO1XoVaJEiQyhE5UwF4HXr18jW7Zsatdj9+7dcHV9n3WIjQS0JCBx9nny5EH//v3VNxsJ6EFg0qRJ6Ny5M/bt24fvvvtODxUo00EJ0AFx0IEzo9obNmxAtWrVVNhL/fr1zYiANhuAQMeOHTFv3jycO3cOadOmNYBGVMFsBIKCgpA3b151Hu748eOIHJlZ18w2B4xg7/Xr19XOW/PmzTFlyhQjqEQdHIgAHRAHGiwzq/rs2TMVeiUrfhs3buSBXzNPBh1tl8QHEv4nGYc6deqkoyYUbWYCQ4YMwaBBgyAH0HPlymVmFLRdJwKhoaEqDPX27dtqMSZ69Og6aUKxjkqADoijjpzJ9G7cuDE2bdoEyTOeNGlSk1lPc41A4M2bN8iRIwcSJkyowg0YemWEUTGfDufPn1cHz3v27KkyX7GRgB4EZsyYgXbt2qkw1OLFi+uhAmU6OAE6IA4+gGZQ38fHBxUrVsSCBQvQpEkTM5hMGw1IoHv37pg2bZo6aJkhQwYDakiVnJ2A1FrInz8/pPDgqVOnECVKFGc3mfYZkIDsekgKcgmFnjlzpgE1pEqOQIAOiCOMkol1fPnypQq9kpvdtm3bGHpl4rmgp+mS4lSKbI0cORI9evTQUxXKNjEBmX99+/bF4cOH1RkQNhLQmoCcOypTpgwuX76sUpDHjBlTaxUoz0kI0AFxkoF0NjNO7DyLhf1X4NatmzjldwhHLx9EihQpnM1M2mNgAvKgXTNuM3Ys2oPLty8iOK0fDp7YDzc3NwNrTdWcjUDA6wBM67QAZ/dfxIkbh1GxUwmMGTfG2cykPQYn8NeVe5jacT5uXL6Jg3d+w4Lts5QjwkYC4SVAByS85Hid3Qg8veeLhmk7IPhdMCyhFrhHcceah/MQPban3WSyYxL4O4F9aw5jSO3x6p8tCEXa3F6YdXwsQZGApgQmtZ2NrXN3IzQk1DoPLWg4oBYaD6ijqQ4UZm4CshjTKF0HPL79BCHWw+cu1q+JB4bCu2BGc4Oh9REiQAckQvh4sT0InPn9AnqUGPRJ1zNPj0Ha7KntIY59ksBnCSz4eTmWj1yvnGBp0WJGxcYXi0mLBDQl0D5vb1w9cf29TBegSM0C6Leyq6Y6UJi5CQQGBKKiZ4NPIHSa0QoVW5cyNxhaHyECdEAihI8X24OA3/PXqJm0GUICQ6zhLu6IkygWFv05BVGi8sClPXizz88TOL7rNPqUGaZ+KRmvitTIj5/54sfpojGBcR2mYdv039+ff7P6wl1mt0H5FiU01oLizE6gbvqWeHrtGVytIahubq6YeWYsUmVKbnYstD8CBOiARAAeL7UPge3bt6NGuVpoUKQ5smTNglrdKyNx6oT2EcZeSeB/EJA0p4snLEezCq3xTY4MqN2zCjyi0QnmhNGOgGS9KlSwEIJvu6FGydrIXSo7Sjf+nsk4tBsCSrISuHPnDrJ750Axr3Io+G0hlLM6wAy/4tSIKAE6IBElyOttSuDFixcq41XmzJmxY8cOPmhtSpedfSmBQ4cOoXDhwhgxYgR69er1pZfxcyRgUwJhWa8OHjyo0u+ykYDWBOT8R+nSpT9kvYoVK5bWKlCekxKgA+KkA+uoZjVt2hTr1q1T6f2Y9cpRR9Gx9Q4rOBg3blwcOHAA7u7ujm0QtXdIAnIPlIKDXbp0Uemf2UhADwJS56Nt27ZqQVAcETYSsBUBOiC2Isl+Ikxgy5YtqFSpEubPnw9xRNhIQA8CXbt2hVT5PXPmDDJmZJYXPcbA7DLfvXundjzevn2LkydPwsPDw+xIaL8OBG7evImsWbOqgoOzZs3SQQOKdGYCdECceXQdyLZnz56pgoO5cuWCOCLqwCUbCWhMYP/+/ShatCjGjh0LcUTYSEAPAkOGDMGgQYMgBTC//fZbPVSgTJMTCLWm2y1RogTECTl//jxixIhhciI039YE6IDYmij7CxeBBg0awMfHR4VeJUuWLFx98CISiAgBf39/ZMuWDUmSJMHevXtZcDAiMHltuAnIzluePHnQu3dviCPCRgJ6EJg6dSp+/PFH7N69G8WLF9dDBcp0cgJ0QJx8gB3BvPXr16N69epYvHgxGjZs6AgqU0cnJCAP23nz5uHs2bNInz69E1pIk4xOICgoSDkf0o4fP47IkSMbXWXq54QErl27huzZs6tQaHFE2EjAHgTogNiDKvv8YgJPnz5VoVcFChSAOCIMvfpidPygDQn8/vvvapVv8uTJatWPjQT0INC/f3+Vee3YsWPImTOnHipQpskJhISEqDDUBw8eqMWY6NGjm5wIzbcXATog9iLLfr+IQN26dbFr1y5cvHgRiRMn/qJr+CESsCUBPz8/FXqVKlUq/Pbbb6roIBsJaE1ADpvny5cP/fr1w4ABA7QWT3kkoAhMmDAB3bp1w549e1CkSBFSIQG7EaADYje07PjfCKxevRq1a9fG8uXLIY4IGwnoQaBNmzZYsmQJzp07hzRp0uihAmWanEBgYKBKuSshV0ePHkWkSJFMToTm60HgypUryJEjB+SeKI4IGwnYkwAdEHvSZd+fJfDw1mPcvXUXZWuUxvfFvoc4Igy94mTRkoBkeLl98S+cOH0CtRvXxPTp01WuezYS0JJAYEAg7ly6h9mLZ2LS9Ikq5a6kPWUjAS0JvHz6Cg9uPkbTDg3h+9xXpSCPFi2alipQlgkJ0AEx4aDrafKKURswr89SpcKrSM+w/sYSJE2WRE+VKNtkBILfBaNf5ZE4seOsstySJgA7r25i6JXJ5oHe5j7+6yk6FfoZT+/6IsT6latpRoydN0JvtSjfZASObTuNgdVH411gMALgj34bOqNMZRYcNNk00MVcOiC6YDen0Dd+AagapzEsoZYPAAat74mCVd5nfWEjAS0IHNlyUjkgYU1239Y/WwDPWJ5aiKcMElAEZnZdiPVTtiE0JBQW61f6nF6YcXIM6ZCApgSae3fBnct3rSsxVrHW8lt1e1VD8+E/aKoDhZmTAB0Qc467Llb7v3qjHBB1o/tPG7C2OwpXy6eLPhRqTgKHNh3HgKqj/99460N3ve9CRI9NB8ScM0Ifq6d3XmB1QLZ+ePFLmy01Zp6mA6LPaJhXatNvOuKvq/etvocLXN1cUatbJbQY2cC8QGi5ZgTogGiGmoIsFgvKZqiG0OvvD1h6F8qI0b8OQOQoPHDJ2aEdgccPH6NqqgbwfBdLCa3XpxqaDeOKn3YjQElCYNPKLRhXbxYiwwPukdww0LobnK98LsIhAU0JdPqhOy6suAlX61fcJHEw5fAwJEyZQFMdKMycBOiAmHPcdbF6/vz5aN68ORZOW4w8OfMiY550cHN300UXCjUvgfr162OrzzZs/GUzUqZJidTeKcwLg5brQuD169eq0FuSBEkxdeQMJE+fBPGTxdNFFwo1LwE5bC6FLzu37YqGNRsjnTUMMFqMqOYFQss1JUAHRFPc5hV2+/Ztld2lZs2aEEeEjQT0ILB27Vo1ByXtrjgibCSgB4F27dph0aJFqtBbunTp9FCBMk1OQFI/i/MhZ+COHz+uUkCzkYCWBOiAaEnbpLIk5Wnp0qVx9epVnD9/HrFivQ99YSMBLQk8fvwY3t7e+O677yCOCFM/a0mfssII/PrrryhVqhSmTJmCDh06EAwJ6EKgb9++GDNmjHI+ZDeOjQS0JkAHRGviJpQnNRbat2+vKp6XLFnShARost4E5PyR7Hzs27cPFy9eRMKECfVWifJNSODly5dqJzh9+vTqfujq6mpCCjRZbwJS7LJgwYIYPHgwxBFhIwE9CNAB0YO6iWReu3ZNra40btxYFXtjIwE9CCxduhQNGjTAmjVrUKNGDT1UoEwSQLNmzdQclJ3gVKlSkQgJaE4gICAAOXPmRMyYMXHo0CG4u7trrgMFkoAQoAPCeWA3AiEhIfj+++9x//59FescPXp0u8lixyTwvwjI/JPQq/Lly0McETYS0IPAli1bUKlSJcydO1cl42AjAT0IdO3aVS0Gnj59GpkyZdJDBcokAUWADggngt0IjBs3Dj169MDevXtV3D0bCWhNQEKvKlSoAMn2cuHCBcSNG1drFSiPBODr64ssWbIgV65cEEeE5484KfQgICGosigoZz+6deumhwqUSQIfCNAB4WSwC4FLly6pbV45+yGOCBsJ6EFg3rx5aNGihXrpE0eEjQT0IPDDDz9g+/btyglOmjSpHipQpskJSOrnbNmyIVmyZNizZw/c3JgC3+RTQnfz6YDoPgTOp0BwcLA64Obn54dTp04halTmFXe+UTa+RWGpn2vVqgVxRNhIQA8CcuZD5qCE/4kjwkYCehAIS/187tw5pE2bVg8VKJMEPiFAB4QTwuYEhg0bhv79+6sDbvny5bN5/+yQBP6NgKR+llSnf/75J1M//xss/t5uBMJSPxcpUkQdPmfold1Qs+N/ICAZ1yQV/tSpU1VUAhsJGIEAHRAjjIIT6SCHzaW4kZz9EEeEjQT0IDBt2jRVY4Gpn/WgT5lCQM4fVa9eHQcPHlShV0z9zHmhBwFJ/SznjzJmzIidO3cy9bMeg0CZnyVAB8TEE+PCgUuY23spgoND0HhQHeQpkyNcNORBu7DfCmycth0vA17gZfIHOHxxP6JEiRKu/niRuQhsnrkTW6zf8ZPFRYcpzZEkTaJwAbCE+sHyshtC3x7B/sMvsP1wGYwaMydcffEicxEIehuEWT0W4+yeP5Cl8DdoO74xokQN3/3r5vnbGFZvIu7feIjrAZcwfHU/1KjJ1M/mmlHhs/bR7SeY0mEuHt95ivItSqLqj+XC15H1qt9XHMSMrgvx8sVL/Gk5iz1XdiFlypTh7o8XkoCtCdABsTVRB+nP7/lr1EvRGkEB72Cxfrm6uaLxrGrwjBtVrdxJCMvH33//t4//fvfMIxycfkZZbr0SMePFwNrHCxhu4CBzQU81T+w8gz5l3++Uubi6IG7yWKg/pfIXz72wOSrzMU+m3fD2OmVd4bMgOMQCRKmEyPHH62keZTsIgTm9fsHqcZthCbWoeZizciYUapJbzcN/uvd97vfbBhyA36M3cjNUreeiDijVsKiDkKCaehJonbM7bl24g1C5f1lb5X7FkSp3sq+6H8p89X/2Blv67LPO5/c7cTKnl9yYjkSpEuhpHmWTwCcE6IA46IR4/NdTnNx5Vq0W5yiW5bNWyI3n4cOHkGKAYd/Xr19XP9+78hBZ/At8ct1Jy148x5OvJpLCJS0yIAdcrF9hbVvgcrhHYoGjr4bpYBdcOXEd18/cUqvGKb9J9lntJSmBHAgPm3sy/8J+fnvVAq/gzB+cVZmzu7E2XBTWzEuCKmU9rQ7If+ZhpNxwjbc8XH3xIschIE7AUZ9TeOXrhwKVvlULIJ9rb968wY0bN9T97+9zMdatZIhnSfRhHvpaHuE09ocLQjGXqnDD+3ufvPg1GlAbDfrVDFdfvMhxCLzxC8ChjcetO2eRUbBKHri5fz7L1LNnzz57L5R56f2oEFxdXJXRci+8hgu4jStfDSGmSxzkRYlPrpt4YCi8C2b86r54AQnYiwAdEHuRtWO/d/98gHbf9kKA9YYnrXrP8shQKuV/ORnykJWHblhLnjw50qVLp75Tp/TC8UmXEfDyrTwmETWGB8YfHogYcaOrGNGPv+Xg5P/6u/zuwc1HaJ29OwL836qbZsEq32Lw+t52JMCujUDgt+UHMKLBJLXS6x7JDe3nNYYlVvB/PVxv3bplDfMLVipHihQJXl5eKguLzMMEHomxf/z73TNpmQtlwE+rO36Yb/8098LmpHxGvi1vt8PyoiOs9S+tKSatszrmELhEq2MEVNTBjgQmtJ6JrXN2KwnxksZB+8WN8ODp/f9yNKQgZVjz9PT8cC+UuRh6OxLOrLqiHAbZBanbryoqdyit5tXX3Avl85PazbaGFO76sLM86/RYeGVh6Isdp4DuXb99E4j2eXrhzqV7SpecpbOg8s8lPutoPH/+/IO+CRIk+HAvlPvhrY1PcO/cY+u8s95WrbsXA326IX3uNF98Pwy7Fwa/C0brHD1w98o96+6JxbqzHBu/XJ0W7rBC3QFTAackQAfEAYd1Yf8VWD5ivXWb1nqHsrYgSyD2YbPK650qVaoPD1a5oYW96MlL39/T4T689Rirx25CSHAoqneu8D9XsL8EkThFm+dsx4hxw9BjQif82PHHL7mMn3FgAj8W+AmXj/6pLJDQu4eWv3ARx9U8C5t3YX+GzcUUKVLA3f3TnbGzey5i5+I9iJs4Dur2rgrPmNHCTcUSeAgXzyxCr75LMHbKCVb6DTdJx7gwMCAQFT0bfKLsRctxPLCuG8eJE+ez90KZi3Ig/OOMVLJwsnXOr7hw8DIy5cuAim1KhfuwbojVA961eB/mT1uAU3eP4Mq9S6y54BjTKdxaHt16Cj9XHPHJ9fstPghEgKq78fGzOOxnuTfGihXrk2sCXgdgxcgNeHLPFyXrF0GuktnCrdOrZ37YNu83jB41Gt8U98LSVUvC3RcvJAF7EKADYg+qdu5z3UQfzOy2SO02SNRTnKSxMPz33sr5kBVmPVu1atVUmINUnmbKST1Hwv6y+1YcjhM7zipHWKIG8lTLjnYTmyJJkiThfnmzhdaBgYGQ3b5GjRqxCKYtgBq4jxBrAo2qcRrjrX/gBy0bjqmGik3L6l71/sSJEyojIItgGngC2Ui1P45cRaeCfT/0JjtpQ/f1QJYc3ogWLfwLKrZQb9SoURgwYABkBzBu3Li26JJ9kIBNCNABsQlGbTuRVb+B1ceol7+Y8aJj8Mbehont3Lp1q6o4ffToUeTNm1dbMJSmKYG7V++jd9mheHTrCdLl9MKI7X0RO8GnK3qaKvSRsO7du2PhwoW4d+8es7HpNQgayT2w/ihGNpyMwDdBKNO0GLrOaaOrAxxmtiwQ5cqVS2Ue2rhxo0Y0KEYPAjLWklFy9diNcLOefew0vSXKNiuuhyr/JfPRo0dqQWbcuHHo2LGjIXSiEiQgBOiAOPA8kO3aKNGiGOJhG4ZRwg8k3KtMmTKYM4cpUB14en2R6vLgDXj9FlGjexhqx+vyZWsoTaZMWL58OerWrftFtvBDjktAdkKCAt8hqqeHoYyYPn26eum7c+cOkiZNaijdqIztCcjioGSUjBRZ30iEv1tWo0YNXL16FVIFnZEJth939hg+AnRAwseNV/0DgUGDBmHMmDF48OABYsT4fEYaAiQBexOQ6tMSkrh79/sDymwkoDUBKQInIYl9+/ZV32wkoAeB7du3o1y5cjh8+DDy58+vhwqUSQL/RYAOCCeFzQn89ddfSJ06NWbOnImWLVvavH92SAJfQmDJkiVo2LChyoYkBz7ZSEAPAk2bNsXevXvVPJSMWmwkoDUBiUyQe2CJEiUwb948rcVTHgl8lgAdEE4MuxCQcyBPnjzBsWPH7NI/OyWBfyMQEBCgwl7atGmDESM+zVDzb9fy9yRgKwKHDh1CoUKFsHPnTpQqVcpW3bIfEvgqAkOGDMHIkSNVZELMmDG/6lp+mATsQYAOiD2osk916LJq1ao4ffo0cuTIQSIkoAsBib9ftWoVZFdO7wxxugCgUN0JyDmpLFmywNvbW81FNhLQg8Ddu3dVpkw5l9S6dWs9VKBMEviEAB0QTgi7EJDCc5L9RdLyTps2zS4y2CkJ/BuB8+fPI1u2bFi7di2qV6/+bx/n70nALgQmTpyInj17Ql4CpQYJGwnoQaBSpUoqHe/Jkyf1EE+ZJEAHhHNAGwJy6FKcD7nh6Z0LXRuLKcWIBAoUKIDYsWNj27ZtRlSPOpmAgK+vrypIJ2EwPXr0MIHFNNGIBDZv3ozKlSsrB0RSRLORgJ4EuAOiJ30nly0FCeXgm9RjaNy4sZNbS/OMSmD+/Plo0aIFbt68qUIQ2EhADwL169eHFCeUFNFMharHCFCmRCbIPVCckBkzZhAICehKgA6IrvidX3jp0qXx5s0bHDhwwPmNpYWGJODv769SoXbp0gWSIpqNBPQgsGfPHhQrVgzyZ9GiRfVQgTJJAP369cOkSZPUYXRPT08SIQHdCNAB0Q29OQSvXr0atWvXxsWLF5E5c2ZzGE0rDUdAMmH5+PioXRB3d3fD6UeFnJ+AHEbPmDEj8ubNC0kRzUYCehC4desW0qRJo9LxSopoNhLQiwAdEL3Im0RuUFAQMiTKjALpvkPDVvVRplkxuLm5mcR6mmkUAidPnsD44cUxsF89pMvUCC5RChlFNephIgIjho7A3EG/oFvH7qjcuiySZ2B1dBMNv2FMLV2kLAJvWNC2QxtUalcGnjGjGUY3KmIeAnRAzDPWulh68dAVdP7uZ1gsoXCBK6p1Ko92E7jqostgmFio5fUsWF6Pg7Uel9UBBlxiz4CLRwkTE6HpWhOQHZDORX7GxYNX4OrigqgxomLuhQlIkDye1qpQnokJvHjyEg3StsNbv7fWwphuyPBtWkw+PIxFMk08J/QynQ6IXuRNInd2j8VYO9EHoSGhyuLYCWNh9cO5JrGeZhqFQOjTikDwVaWOxeoIu3hUhmvs0UZRj3qYgMDrF/6oFrfJJ5b2XNgBpRrxPIgJht8wJu5fewSDa437RJ/lf81E/GR0hA0zSCZRhA6ISQZaLzM3z9yJye3mvBfvAngXyIiJB4bqpQ7lmpRA6PMfYXm7y5p9KNS6G2fdi4vxI1yidzApDZqtB4GQ4BDUStwCfs9fixes2oR9g5GlcCY91KFMkxK4dvom2ubu+Z/FGAuiRY+K1Y/mIkrUKCYlQrP1IkAHRC/yJpEbYo15mdF5ITbP24EA+GPlhflIkiaRSaynmUYhYAl5CsvL7nj2+CCu3UmKfKV2Wp0RPnCNMj5m0UNCUkc1mYxbf95B8aYFMXB+H7OYTjsNREAWBuf0WYynL59i1IYB+K5yAQNpR1XMQoAOiFlGWmc7ly1bBsmD/+jRI1YC1nkszCy+efPmOHbsGKRCOhsJ6EXAy8sLVapUgVRIZyMBPQiE1enatGkTpEI6GwloTYAOiNbETSrv3r17SJ48OSQtb82aNU1KgWbrTWDx4sWqKOaTJ08QP358vdWhfJMSaNKkCc6ePYvTp0+blADN1puAJEVImTIl6tSpg7Fjx+qtDuWbkAAdEBMOul4mp0uXDuXKlcOUKVP0UoFyTU7g9u3bSJ06NdatW4dq1aqZnAbN14vAggULILtxvr6+iBMnjl5qUK7JCTRo0ABXrlzB8ePHTU6C5utBgA6IHtRNKlMeuHKjO3funEkJ0GwjEBAHpGrVqgx/McJgmFQHhr+YdOANZvacOXMgRVqfP3+OmDFjGkw7quPsBOiAOPsIG8i+sPCXp0+fIl48pvwz0NCYShUJwRInmOEvphp2QxnL8BdDDYdplbl69SoyZsyIrVu3qugENhLQkgAdEC1pm1xWWPjL+vXr1Qo0GwnoQWD+/Plo0aIFw1/0gE+ZHwgw/IWTQW8C4ggnTZpUnYsbOXKk3upQvskI0AEx2YDrba6Ev0js/YQJE/RWhfJNSuD69euQ80jM/mLSCWAQsxn+YpCBMLkadevWhSwOHj582OQkaL7WBOiAaE3c5PIk+4uEv5w6dcrkJGi+XgQY/qIXecr9mADDXzgfjEBgxowZ6NixI168eAFPT08jqEQdTEKADohJBtooZjL7i1FGwtx6MPzF3ONvBOsZ/mKEUaAOf/zxB7y9vbFz506UKlWKQEhAMwJ0QDRDTUFCgNlfOA+MQIDhL0YYBerA8BfOAb0JiCOcKFEitGrVCkOHDtVbHco3EQE6ICYabCOYyvAXI4wCdWD4C+eAEQgw/MUIo0AdpDjwo0ePsH//fsIgAc0I0AHRDDUFhRFg+Avngt4EGP6i9whQvhBg+AvngREISHHg7t27q3MgUaNGNYJK1MEEBOiAmGCQjWbimIHjMW/wL+jWqyt+6F0dnrF48M1oY2QGfcYMLQuvZPdQo05fIGptuLi4msFs2mggAu+C3iF7vLzImfFbdBv5I3KVzGYg7aiKWQgc3HMYjYu1Qp1addBueHMkS5fELKbTTh0J0AHREb4ZRT+89RjNvTvj7ZtAuLm54Zt86THpoR0c5AAABItJREFUwFDry5+LGXHQZp0IWN5uh+VFR7wLtiCSu3XueXaAa4yOOmlDsWYlMLHtbPjM2gmLFYDcA8fuHojs33ubFQft1oFA8LtgtMjaFXev3ldzMEac6Fh4ZTJixouhgzYUaSYCdEDMNNoGsHXnoj0Y03TaJ5qs812gbnpsJKAVgdAXPWEJ2GR94Ia+F+meHq7xfbQSTzkkoAjUStwCLx6/VD+7ubuieqcKaDWmEemQgGYE/rpyD80ydf5E3jCfn5C3XE7NdKAgcxKgA2LOcdfN6ktH/0THAj8p+a6uLmqVZcX92Wo3hI0EtCJgeT0TltdSDFPWnq1zz6MsXGOzOKZW/CnnPYFuxQbgwoHLCA157wh3m9sWZZsVJx4S0IzAG78A1EnSEoEBQZCzcS7W5/L8S5OQPD3DsDQbBJMKogNi0oHX02yf2buwasxGxIgbHZ1mtEL6XGn0VIeyTUjAYrE+bF8NBwL3AJG84RLLGgboGseEJGiyngSe3PXFuBYzVPhLsTqF0HRYPevCDM8i6TkmZpR9ds9FTO+yAO/evkPjQXVQtHZBM2KgzRoToAOiMXCKIwESIAESIAESIAESIAEzE6ADYubRp+0kQAIkQAIkQAIkQAIkoDEBOiAaA6c4EiABEiABEiABEiABEjAzATogZh592k4CJEACJEACJEACJEACGhOgA6IxcIojARIgARIgARIgARIgATMToANi5tGn7SRAAiRAAiRAAiRAAiSgMQE6IBoDpzgSIAESIAESIAESIAESMDMBOiBmHn3aTgIkQAIkQAIkQAIkQAIaE6ADojFwiiMBEiABEiABEiABEiABMxOgA2Lm0aftJEACJEACJEACJEACJKAxATogGgOnOBIgARIgARIgARIgARIwMwE6IGYefdpOAiRAAiRAAiRAAiRAAhoToAOiMXCKIwESIAESIAESIAESIAEzE6ADYubRp+0kQAIkQAIkQAIkQAIkoDEBOiAaA6c4EiABEiABEiABEiABEjAzATogZh592k4CJEACJEACJEACJEACGhOgA6IxcIojARIgARIgARIgARIgATMToANi5tGn7SRAAiRAAiRAAiRAAiSgMQE6IBoDpzgSIAESIAESIAESIAESMDMBOiBmHn3aTgIkQAIkQAIkQAIkQAIaE6ADojFwiiMBEiABEiABEiABEiABMxOgA2Lm0aftJEACJEACJEACJEACJKAxATogGgOnOBIgARIgARIgARIgARIwMwE6IGYefdpOAiRAAiRAAiRAAiRAAhoToAOiMXCKIwESIAESIAESIAESIAEzE6ADYubRp+0kQAIkQAIkQAIkQAIkoDEBOiAaA6c4EiABEiABEiABEiABEjAzATogZh592k4CJEACJEACJEACJEACGhOgA6IxcIojARIgARIgARIgARIgATMToANi5tGn7SRAAiRAAiRAAiRAAiSgMQE6IBoDpzgSIAESIAESIAESIAESMDMBOiBmHn3aTgIkQAIkQAIkQAIkQAIaE6ADojFwiiMBEiABEiABEiABEiABMxP4P/52dRE1ONvvAAAAAElFTkSuQmCC\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "G = cover_complex.get_networkx()\n",
    "plt.figure(figsize=(8,2))\n",
    "for idx, bd in enumerate(bnd):\n",
    "    plt.subplot(1,len(bnd),idx+1)\n",
    "    nx.draw(G, pos=nx.kamada_kawai_layout(G), \n",
    "            node_color=[1 if node in bd else 0 for node in G.nodes()], node_size=5)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can also identify the robust topological features by bootstrapping, and select those associated to 95% confidence."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 100/100 [00:39<00:00,  2.55it/s]\n"
     ]
    }
   ],
   "source": [
    "bootstrap_topological_features(cover_complex, 100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "dist = get_distance_from_confidence_level(cover_complex, .85)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "bnd_boot = [b for idx, b in enumerate(bnd) if np.abs(.5 * (dgm[idx][1][1]-dgm[idx][1][0])) >= dist]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute('tabindex', '0');\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;' +\n",
       "            'z-index: 2;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box;' +\n",
       "            'pointer-events: none;' +\n",
       "            'position: relative;' +\n",
       "            'z-index: 0;'\n",
       "    );\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box;' +\n",
       "            'left: 0;' +\n",
       "            'pointer-events: none;' +\n",
       "            'position: absolute;' +\n",
       "            'top: 0;' +\n",
       "            'z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            /* This rescales the canvas back to display pixels, so that it\n",
       "             * appears correct on HiDPI screens. */\n",
       "            canvas.style.width = width + 'px';\n",
       "            canvas.style.height = height + 'px';\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        /* User Agent sniffing is bad, but WebKit is busted:\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=144526\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=181818\n",
       "         * The worst that happens here is that they get an extra browser\n",
       "         * selection when dragging, if this check fails to catch them.\n",
       "         */\n",
       "        var UA = navigator.userAgent;\n",
       "        var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n",
       "        if(isWebKit) {\n",
       "            return function (event) {\n",
       "                /* This prevents the web browser from automatically changing to\n",
       "                 * the text insertion cursor when the button is pressed. We\n",
       "                 * want to control all of the cursor setting manually through\n",
       "                 * the 'cursor' event from matplotlib */\n",
       "                event.preventDefault()\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        } else {\n",
       "            return function (event) {\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        }\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    canvas_div.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    canvas_div.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    fig.canvas_div.style.cursor = msg['cursor'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "function getModifiers(event) {\n",
       "    var mods = [];\n",
       "    if (event.ctrlKey) {\n",
       "        mods.push('ctrl');\n",
       "    }\n",
       "    if (event.altKey) {\n",
       "        mods.push('alt');\n",
       "    }\n",
       "    if (event.shiftKey) {\n",
       "        mods.push('shift');\n",
       "    }\n",
       "    if (event.metaKey) {\n",
       "        mods.push('meta');\n",
       "    }\n",
       "    return mods;\n",
       "}\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * https://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    // from https://stackoverflow.com/q/1114465\n",
       "    var boundingRect = this.canvas.getBoundingClientRect();\n",
       "    var x = (event.clientX - boundingRect.left) * this.ratio;\n",
       "    var y = (event.clientY - boundingRect.top) * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        modifiers: getModifiers(event),\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "G = cover_complex.get_networkx()\n",
    "plt.figure(figsize=(8,2))\n",
    "for idx, bd in enumerate(bnd_boot):\n",
    "    plt.subplot(1,len(bnd_boot),idx+1)\n",
    "    nx.draw(G, pos=nx.kamada_kawai_layout(G), \n",
    "            node_color=[1 if node in bd else 0 for node in G.nodes()], node_size=5)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, one can identify the coordinates that best explain a topological feature VS the rest of the complex with a Kolmogorov-Smirnov test. In particular, for each topological feature, we can rank the coordinates with respect to their p-values. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For instance, coordinate 0 (height) is the one that best distinguishes the topological structures from the rest."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([0, 1, 2]), array([0., 0., 0.]))"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "compute_differential_coordinates(cover_complex, nodes=bnd[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([1, 2, 0]), array([0.00000000e+000, 0.00000000e+000, 4.87710222e-147]))"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "compute_differential_coordinates(cover_complex, nodes=bnd[2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([0, 2, 1]), array([0.00000000e+000, 0.00000000e+000, 3.13211519e-128]))"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "compute_differential_coordinates(cover_complex, nodes=bnd[3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "language": "python",
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   "file_extension": ".py",
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