{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Extract and Visualize Individual Heartbeats"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This example can be referenced by [citing the package](https://github.com/neuropsychology/NeuroKit#citation).\n",
    "\n",
    "This example shows how to use NeuroKit to extract and visualize the QRS complexes (individual heartbeats) from an electrocardiogram (ECG).\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load NeuroKit and other useful packages\n",
    "import neurokit2 as nk\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams['figure.figsize'] = [15, 9]  # Bigger images"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extract the cleaned ECG signal"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this example, we will use a simulated ECG signal. However, you can use any of your signal (for instance, extracted from the dataframe using the [read_acqknowledge()](https://neurokit2.readthedocs.io/en/latest/functions.html#neurokit2.read_acqknowledge>).\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Simulate 30 seconds of ECG Signal (recorded at 250 samples / second)\n",
    "ecg_signal = nk.ecg_simulate(duration=30, sampling_rate=250)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Once you have a raw ECG signal in the shape of a vector (i.e., a one-dimensional array), or a list, you can use [ecg_process()](https://neurokit2.readthedocs.io/en/latest/functions.html#neurokit2.ecg_process>) to process it.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Note: It is critical that you specify the correct sampling rate of your signal throughout many processing functions, as this allows NeuroKit to have a time reference.*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Automatically process the (raw) ECG signal\n",
    "signals, info = nk.ecg_process(ecg_signal, sampling_rate=250)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This function outputs two elements, a *dataframe* containing the different signals (raw, cleaned, etc.) and a *dictionary* containing various additional information (peaks location, ...)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extract R-peaks location"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "The processing function does two important things for our purpose: 1) it cleans the signal and 2) it detects the location of the R-peaks. Let's extract these from the output.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Extract clean ECG and R-peaks location\n",
    "rpeaks = info[\"ECG_R_Peaks\"]\n",
    "cleaned_ecg = signals[\"ECG_Clean\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Great. We can visualize the R-peaks location in the signal to make sure it got detected correctly by marking their location in the signal."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize R-peaks in ECG signal\n",
    "plot = nk.events_plot(rpeaks, cleaned_ecg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "Once that we know where the R-peaks are located, we can create windows of signal around them (of a length of for instance 1 second, ranging from 400 ms before the R-peak), which we can refer to as *epochs*.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Segment the signal around the heart beats"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "You can now epoch all these individual heart beats, synchronized by their R peaks with the [ecg_segment()](https://neurokit2.readthedocs.io/en/latest/functions.html#neurokit2.ecg_segment) function.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting all the heart beats\n",
    "epochs = nk.ecg_segment(cleaned_ecg, rpeaks=None, sampling_rate=250, show=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "This create a dictionary of dataframes for each 'epoch' (in this case, each heart beat).\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Advanced Plotting"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This section is written for a more advanced purpose of plotting and visualizing all the heartbeats segments. The code below uses packages other than *NeuroKit2* to manually set the colour gradient of the signals and to create a more interactive experience for the user - by hovering your cursor over each signal, an annotation of the signal corresponding to the heart beat index is shown."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Custom colors and legend"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here, we define a function to create the epochs. It takes in `cleaned` as the cleaned signal dataframe, and `peaks` as the array of R-peaks locations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Signal</th>\n",
       "      <th>Index</th>\n",
       "      <th>Label</th>\n",
       "      <th>Time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-0.193262</td>\n",
       "      <td>139</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.187513</td>\n",
       "      <td>140</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.295977</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.181679</td>\n",
       "      <td>141</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.291954</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.175692</td>\n",
       "      <td>142</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.287931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.169474</td>\n",
       "      <td>143</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.283908</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Signal  Index Label      Time\n",
       "0 -0.193262    139     1 -0.300000\n",
       "1 -0.187513    140     1 -0.295977\n",
       "2 -0.181679    141     1 -0.291954\n",
       "3 -0.175692    142     1 -0.287931\n",
       "4 -0.169474    143     1 -0.283908"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "plt.rcParams['figure.figsize'] = [10, 6]  # resize\n",
    "\n",
    "# Define a function to create epochs\n",
    "def plot_heartbeats(cleaned, peaks, sampling_rate=None): \n",
    "    heartbeats = nk.epochs_create(cleaned, events=peaks, epochs_start=-0.3, epochs_end=0.4, sampling_rate=sampling_rate)\n",
    "    heartbeats = nk.epochs_to_df(heartbeats)\n",
    "    return heartbeats\n",
    "heartbeats = plot_heartbeats(cleaned_ecg, peaks=rpeaks, sampling_rate=250)\n",
    "heartbeats.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We then pivot the dataframe so that each column corresponds to the signal values of one channel, or *Label*."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Label</th>\n",
       "      <th>1</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>13</th>\n",
       "      <th>14</th>\n",
       "      <th>15</th>\n",
       "      <th>16</th>\n",
       "      <th>17</th>\n",
       "      <th>18</th>\n",
       "      <th>...</th>\n",
       "      <th>31</th>\n",
       "      <th>32</th>\n",
       "      <th>33</th>\n",
       "      <th>34</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Time</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>-0.300000</th>\n",
       "      <td>-0.193262</td>\n",
       "      <td>-0.130034</td>\n",
       "      <td>-0.136912</td>\n",
       "      <td>-0.139149</td>\n",
       "      <td>-0.130810</td>\n",
       "      <td>-0.129424</td>\n",
       "      <td>-0.140368</td>\n",
       "      <td>-0.141949</td>\n",
       "      <td>-0.137200</td>\n",
       "      <td>-0.129263</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.134434</td>\n",
       "      <td>-0.137504</td>\n",
       "      <td>-0.130364</td>\n",
       "      <td>-0.155541</td>\n",
       "      <td>-0.121164</td>\n",
       "      <td>-0.148815</td>\n",
       "      <td>-0.131790</td>\n",
       "      <td>-0.138593</td>\n",
       "      <td>-0.134619</td>\n",
       "      <td>-0.137870</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-0.295977</th>\n",
       "      <td>-0.187513</td>\n",
       "      <td>-0.129303</td>\n",
       "      <td>-0.135751</td>\n",
       "      <td>-0.138231</td>\n",
       "      <td>-0.130387</td>\n",
       "      <td>-0.128518</td>\n",
       "      <td>-0.138962</td>\n",
       "      <td>-0.140974</td>\n",
       "      <td>-0.136386</td>\n",
       "      <td>-0.128326</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.133507</td>\n",
       "      <td>-0.136182</td>\n",
       "      <td>-0.128863</td>\n",
       "      <td>-0.154694</td>\n",
       "      <td>-0.120614</td>\n",
       "      <td>-0.147637</td>\n",
       "      <td>-0.130774</td>\n",
       "      <td>-0.137616</td>\n",
       "      <td>-0.133792</td>\n",
       "      <td>-0.137158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-0.291954</th>\n",
       "      <td>-0.181679</td>\n",
       "      <td>-0.128410</td>\n",
       "      <td>-0.134396</td>\n",
       "      <td>-0.137167</td>\n",
       "      <td>-0.129875</td>\n",
       "      <td>-0.127490</td>\n",
       "      <td>-0.137368</td>\n",
       "      <td>-0.139873</td>\n",
       "      <td>-0.135463</td>\n",
       "      <td>-0.127291</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.132467</td>\n",
       "      <td>-0.134675</td>\n",
       "      <td>-0.127122</td>\n",
       "      <td>-0.153670</td>\n",
       "      <td>-0.119863</td>\n",
       "      <td>-0.146230</td>\n",
       "      <td>-0.129614</td>\n",
       "      <td>-0.136513</td>\n",
       "      <td>-0.132834</td>\n",
       "      <td>-0.136297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-0.287931</th>\n",
       "      <td>-0.175692</td>\n",
       "      <td>-0.127313</td>\n",
       "      <td>-0.132779</td>\n",
       "      <td>-0.135925</td>\n",
       "      <td>-0.129223</td>\n",
       "      <td>-0.126319</td>\n",
       "      <td>-0.135557</td>\n",
       "      <td>-0.138622</td>\n",
       "      <td>-0.134400</td>\n",
       "      <td>-0.126087</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.131265</td>\n",
       "      <td>-0.132927</td>\n",
       "      <td>-0.125104</td>\n",
       "      <td>-0.152414</td>\n",
       "      <td>-0.118853</td>\n",
       "      <td>-0.144558</td>\n",
       "      <td>-0.128243</td>\n",
       "      <td>-0.135241</td>\n",
       "      <td>-0.131704</td>\n",
       "      <td>-0.135261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-0.283908</th>\n",
       "      <td>-0.169474</td>\n",
       "      <td>-0.125951</td>\n",
       "      <td>-0.130811</td>\n",
       "      <td>-0.134471</td>\n",
       "      <td>-0.128376</td>\n",
       "      <td>-0.124978</td>\n",
       "      <td>-0.133487</td>\n",
       "      <td>-0.137182</td>\n",
       "      <td>-0.133150</td>\n",
       "      <td>-0.124632</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.129833</td>\n",
       "      <td>-0.130870</td>\n",
       "      <td>-0.122765</td>\n",
       "      <td>-0.150849</td>\n",
       "      <td>-0.117519</td>\n",
       "      <td>-0.142586</td>\n",
       "      <td>-0.126583</td>\n",
       "      <td>-0.133737</td>\n",
       "      <td>-0.130349</td>\n",
       "      <td>-0.134013</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 34 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Label             1        10        11        12        13        14  \\\n",
       "Time                                                                    \n",
       "-0.300000 -0.193262 -0.130034 -0.136912 -0.139149 -0.130810 -0.129424   \n",
       "-0.295977 -0.187513 -0.129303 -0.135751 -0.138231 -0.130387 -0.128518   \n",
       "-0.291954 -0.181679 -0.128410 -0.134396 -0.137167 -0.129875 -0.127490   \n",
       "-0.287931 -0.175692 -0.127313 -0.132779 -0.135925 -0.129223 -0.126319   \n",
       "-0.283908 -0.169474 -0.125951 -0.130811 -0.134471 -0.128376 -0.124978   \n",
       "\n",
       "Label            15        16        17        18  ...        31        32  \\\n",
       "Time                                               ...                       \n",
       "-0.300000 -0.140368 -0.141949 -0.137200 -0.129263  ... -0.134434 -0.137504   \n",
       "-0.295977 -0.138962 -0.140974 -0.136386 -0.128326  ... -0.133507 -0.136182   \n",
       "-0.291954 -0.137368 -0.139873 -0.135463 -0.127291  ... -0.132467 -0.134675   \n",
       "-0.287931 -0.135557 -0.138622 -0.134400 -0.126087  ... -0.131265 -0.132927   \n",
       "-0.283908 -0.133487 -0.137182 -0.133150 -0.124632  ... -0.129833 -0.130870   \n",
       "\n",
       "Label            33        34         4         5         6         7  \\\n",
       "Time                                                                    \n",
       "-0.300000 -0.130364 -0.155541 -0.121164 -0.148815 -0.131790 -0.138593   \n",
       "-0.295977 -0.128863 -0.154694 -0.120614 -0.147637 -0.130774 -0.137616   \n",
       "-0.291954 -0.127122 -0.153670 -0.119863 -0.146230 -0.129614 -0.136513   \n",
       "-0.287931 -0.125104 -0.152414 -0.118853 -0.144558 -0.128243 -0.135241   \n",
       "-0.283908 -0.122765 -0.150849 -0.117519 -0.142586 -0.126583 -0.133737   \n",
       "\n",
       "Label             8         9  \n",
       "Time                           \n",
       "-0.300000 -0.134619 -0.137870  \n",
       "-0.295977 -0.133792 -0.137158  \n",
       "-0.291954 -0.132834 -0.136297  \n",
       "-0.287931 -0.131704 -0.135261  \n",
       "-0.283908 -0.130349 -0.134013  \n",
       "\n",
       "[5 rows x 34 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "heartbeats_pivoted = heartbeats.pivot(index='Time', columns='Label', values='Signal')\n",
    "heartbeats_pivoted.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\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('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",
       "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 = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(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 (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\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 = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\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 nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\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",
       "\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",
       "\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]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.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, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\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",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = 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.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",
       "            /* 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",
       "            evt.data.type = \"image/png\";\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",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\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(\"No handler for the '\" + msg_type + \"' message type: \", msg);\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(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://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",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\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",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             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",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";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.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",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['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 = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\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.get(0);\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",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\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).html('<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/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<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 () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('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",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\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",
       "\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('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img 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\" width=\"720\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\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('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",
       "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 = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(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 (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\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 = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\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 nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\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",
       "\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",
       "\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]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.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, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\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",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = 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.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",
       "            /* 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",
       "            evt.data.type = \"image/png\";\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",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\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(\"No handler for the '\" + msg_type + \"' message type: \", msg);\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(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://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",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\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",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             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",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";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.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",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['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 = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\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.get(0);\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",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\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).html('<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/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<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 () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('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",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\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",
       "\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('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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\" width=\"720\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Import dependencies\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Prepare figure\n",
    "fig, ax = plt.subplots()\n",
    "plt.close(fig)\n",
    "ax.set_title(\"Individual Heart Beats\")\n",
    "ax.set_xlabel(\"Time (seconds)\")\n",
    "\n",
    "# Aesthetics\n",
    "labels = list(heartbeats_pivoted)\n",
    "labels = ['Channel ' + x for x in labels] # Set labels for each signal\n",
    "cmap = iter(plt.cm.YlOrRd(np.linspace(0,1, int(heartbeats[\"Label\"].nunique())))) # Get color map\n",
    "lines = [] # Create empty list to contain the plot of each signal\n",
    "\n",
    "for i, x, color in zip(labels, heartbeats_pivoted, cmap):\n",
    "    line, = ax.plot(heartbeats_pivoted[x], label='%s' % i, color=color)\n",
    "    lines.append(line)\n",
    "\n",
    "# Show figure\n",
    "fig"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Interactivity"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This section of the code incorporates the aesthetics and interactivity of the plot produced. Unfortunately, the interactivity is not active in this example but it should work in your console! As you hover your cursor over each signal, annotation of the channel that produced it is shown. The below figure that you see is a standstill image."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Note: you need to install the `mplcursors` package for the interactive part (`pip install mplcursors`)*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import packages\n",
    "import ipywidgets as widgets\n",
    "from ipywidgets import interact, interact_manual\n",
    "\n",
    "import mplcursors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\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('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",
       "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 = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(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 (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\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 = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\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 nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\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",
       "\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",
       "\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]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.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, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\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",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = 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.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",
       "            /* 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",
       "            evt.data.type = \"image/png\";\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",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\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(\"No handler for the '\" + msg_type + \"' message type: \", msg);\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(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://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",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\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",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             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",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";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.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",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['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 = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\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.get(0);\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",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\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).html('<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/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<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 () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('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",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\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",
       "\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('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"720\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Obtain hover cursor\n",
    "mplcursors.cursor(lines, hover=True, highlight=True).connect(\"add\", lambda sel: sel.annotation.set_text(sel.artist.get_label())) \n",
    "# Return figure\n",
    "fig"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}