sensory_stim_movie.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import sys\n",
    "import datetime\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.gridspec import GridSpec\n",
    "from matplotlib import animation, rc\n",
    "from scipy import signal, stats\n",
    "from glob import glob\n",
    "import copy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "sys.path.append(r'C:\\Users\\lesliec\\code')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tbd_eeg.tbd_eeg.data_analysis.eegutils import EEGexp\n",
    "from tbd_eeg.tbd_eeg.data_analysis.Utilities.behavior_movies import Movie"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sensory_stim_lag import visual_stim_lag as vislag\n",
    "from sensory_stim_lag import auditory_stim_lag as audlag"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sslog_file not found.\n"
     ]
    }
   ],
   "source": [
    "dfolder = r'C:\\Users\\lesliec\\data\\eeg_pilot\\mouse496220\\audio_vis1_2020-06-10_14-54-43\\recording1'\n",
    "# load experiment metadata and eeg data\n",
    "exp = EEGexp(dfolder, preprocess=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "sync_data = exp._load_sync_dataset()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "eeg_data, eeg_ts = exp.load_eegdata()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Load stimulus log and get correct onset times"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# stimulus table\n",
    "stim_file = glob(exp.data_folder + '/*_table.csv', recursive=True)[0]\n",
    "stim_table = pd.read_csv(stim_file)\n",
    "\n",
    "# log file\n",
    "log_file = glob(exp.data_folder + '/*_stimulus_log.csv', recursive=True)[0]\n",
    "stim_log = pd.read_csv(log_file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# get sweep and vsync rising and falling times\n",
    "srising = sync_data.get_edges(keys=('behavior_sweep',), kind='rising', units='seconds')\n",
    "sfalling = sync_data.get_edges(keys=('behavior_sweep',), kind='falling', units='seconds')\n",
    "\n",
    "vrising = sync_data.get_edges(keys=('behavior_vsync',), kind='rising', units='seconds')\n",
    "vfalling = sync_data.get_edges(keys=('behavior_vsync',), kind='falling', units='seconds')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "sync_log = stim_log.drop(labels='time', axis='columns')\n",
    "sync_log['rising_edge'] = vrising\n",
    "sync_log['falling_edge'] = vfalling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
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       "   frame  display_stim    stim_type stim_parameter  rising_edge  falling_edge\n",
       "0      0         False  gray_screen           none    351.67956     351.76969\n",
       "1      1         False  gray_screen           none    351.77010     351.77705\n",
       "2      2         False  gray_screen           none    351.77747     351.79347\n",
       "3      3         False  gray_screen           none    351.79382     351.81033\n",
       "4      4         False  gray_screen           none    351.81069     351.82709"
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    "sync_log.head()"
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   "execution_count": 13,
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       "      <td>auditory</td>\n",
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       "          type   parameter  on_time  duration\n",
       "10  fullscreen       white       51      0.25\n",
       "11  fullscreen       black       56      0.25\n",
       "12    auditory  whitenoise       61      0.25\n",
       "13    auditory       10000       66      0.25"
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   "source": [
    "stim_table[10:14]"
   ]
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   "execution_count": 14,
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       "      <td>fullscreen</td>\n",
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       "      <th>1</th>\n",
       "      <td>auditory</td>\n",
       "      <td>whitenoise</td>\n",
       "      <td>6</td>\n",
       "      <td>0.25</td>\n",
       "      <td>357.67778</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>auditory</td>\n",
       "      <td>whitenoise</td>\n",
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       "      <td>0.25</td>\n",
       "      <td>367.67778</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>auditory</td>\n",
       "      <td>whitenoise</td>\n",
       "      <td>21</td>\n",
       "      <td>0.25</td>\n",
       "      <td>372.67778</td>\n",
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      "text/plain": [
       "         type   parameter  on_time  duration  onset_masterclock\n",
       "0  fullscreen       black        1      0.25          352.67778\n",
       "1    auditory  whitenoise        6      0.25          357.67778\n",
       "2    auditory  whitenoise       11      0.25          362.67778\n",
       "3  fullscreen       white       16      0.25          367.67778\n",
       "4    auditory  whitenoise       21      0.25          372.67778"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "awake_sweep = stim_table.copy()\n",
    "awake_sweep['onset_masterclock'] = awake_sweep['on_time'] + srising[0]\n",
    "awake_sweep.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
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   "outputs": [
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       "      <th></th>\n",
       "      <th>type</th>\n",
       "      <th>parameter</th>\n",
       "      <th>on_time</th>\n",
       "      <th>duration</th>\n",
       "      <th>onset_masterclock</th>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>fullscreen</td>\n",
       "      <td>black</td>\n",
       "      <td>1</td>\n",
       "      <td>0.25</td>\n",
       "      <td>1962.06246</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>auditory</td>\n",
       "      <td>whitenoise</td>\n",
       "      <td>6</td>\n",
       "      <td>0.25</td>\n",
       "      <td>1967.06246</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>auditory</td>\n",
       "      <td>whitenoise</td>\n",
       "      <td>11</td>\n",
       "      <td>0.25</td>\n",
       "      <td>1972.06246</td>\n",
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       "      <th>3</th>\n",
       "      <td>fullscreen</td>\n",
       "      <td>white</td>\n",
       "      <td>16</td>\n",
       "      <td>0.25</td>\n",
       "      <td>1977.06246</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>auditory</td>\n",
       "      <td>whitenoise</td>\n",
       "      <td>21</td>\n",
       "      <td>0.25</td>\n",
       "      <td>1982.06246</td>\n",
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      "text/plain": [
       "         type   parameter  on_time  duration  onset_masterclock\n",
       "0  fullscreen       black        1      0.25         1962.06246\n",
       "1    auditory  whitenoise        6      0.25         1967.06246\n",
       "2    auditory  whitenoise       11      0.25         1972.06246\n",
       "3  fullscreen       white       16      0.25         1977.06246\n",
       "4    auditory  whitenoise       21      0.25         1982.06246"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "anest_sweep = stim_table.copy()\n",
    "anest_sweep['onset_masterclock'] = anest_sweep['on_time'] + srising[1]\n",
    "anest_sweep.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Load movies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "bodymovie = Movie(filepath=exp.bodymovie_file,\n",
    "                 sync_filepath=exp.sync_file,\n",
    "                 sync_channel='behavior_camera'\n",
    "                 )\n",
    "eyemovie = Movie(filepath=exp.pupilmovie_file,\n",
    "                 sync_filepath=exp.sync_file,\n",
    "                 sync_channel='eye_camera'\n",
    "                 )\n",
    "facemovie = Movie(filepath=exp.facemovie_file,\n",
    "                 sync_filepath=exp.sync_file,\n",
    "                 sync_channel='face_camera'\n",
    "                 )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Choose stim presentation to look at movie"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "stim_choice = 1 # index of stim to plot\n",
    "\n",
    "# electrodes to plot\n",
    "ch_ant = eeg_data[:, 13]\n",
    "ch_vis = eeg_data[:, 4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "stim_onset = anest_sweep['onset_masterclock'].iloc[stim_choice]\n",
    "beg_movie = stim_onset - 0.5 # sec, master clock\n",
    "end_movie = stim_onset + 1.5\n",
    "moviets = bodymovie.sync_timestamps[np.argwhere((bodymovie.sync_timestamps >= beg_movie) & (bodymovie.sync_timestamps <= end_movie)).flatten()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "eeginds = np.argwhere((eeg_ts >= beg_movie) & (eeg_ts <= end_movie)).flatten()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "def update(frame):\n",
    "    current_time = moviets[frame]\n",
    "    \n",
    "    # body cam movie\n",
    "    bax.set_data(bodymovie.get_frame(time=current_time))\n",
    "    \n",
    "    # eeg plot\n",
    "    visline.set_data([current_time, current_time], [0,1])\n",
    "    antline.set_data([current_time, current_time], [0,1])\n",
    "    \n",
    "    return fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
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     "text": [
      "C:\\Users\\lesliec\\data\\eeg_pilot\\mouse496220\\audio_vis1_2020-06-10_14-54-43\\recording1\\whitenoise_eeg_anest.mp4\n"
     ]
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       "\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=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "movie_name = os.path.join(exp.data_folder, 'whitenoise_eeg_anest.mp4')\n",
    "print(movie_name)\n",
    "\n",
    "fig = plt.figure(figsize=(8, 4))\n",
    "fig.patch.set_facecolor('whitesmoke')\n",
    "\n",
    "timezero = moviets[0]\n",
    "\n",
    "# make grid for subplots\n",
    "gs = GridSpec(2, 2, figure=fig)\n",
    "ax_body = fig.add_subplot(gs[:, 0])\n",
    "ax_ant = fig.add_subplot(gs[0, 1])\n",
    "ax_vis = fig.add_subplot(gs[1, 1])\n",
    "\n",
    "# body cam movie\n",
    "bax = ax_body.imshow(bodymovie.get_frame(time=timezero))\n",
    "ax_body.get_xaxis().set_visible(False)\n",
    "ax_body.get_yaxis().set_visible(False)\n",
    "\n",
    "# EEG plot (vis)\n",
    "ax_vis.plot(eeg_ts[eeginds], ch_vis[eeginds], 'b', linewidth=1)\n",
    "ax_vis.set_xlim((eeg_ts[eeginds[0]], eeg_ts[eeginds[-1]]))\n",
    "ax_vis.set_ylim((-200, 200))\n",
    "ax_vis.set_ylabel('Visp EEG')\n",
    "ax_vis.axvspan(stim_onset, stim_onset+0.25, color='orange', alpha=0.5)\n",
    "visline = ax_vis.axvline(x=timezero, color='green', linewidth=3)\n",
    "\n",
    "# EEG plot (ant)\n",
    "ax_ant.plot(eeg_ts[eeginds], ch_ant[eeginds], 'm', linewidth=1)\n",
    "ax_ant.set_xlim((eeg_ts[eeginds[0]], eeg_ts[eeginds[-1]]))\n",
    "ax_ant.set_ylim((-200, 200))\n",
    "ax_ant.set_ylabel('MOs EEG\\n(microvolts)')\n",
    "ax_ant.axvspan(stim_onset, stim_onset+0.25, color='orange', alpha=0.5)\n",
    "antline = ax_ant.axvline(x=timezero, color='green', linewidth=3)\n",
    "\n",
    "gs.tight_layout(fig)\n",
    "\n",
    "anim = animation.FuncAnimation(fig, update, init_func=None, frames=len(moviets), interval=200, blit=False)\n",
    "# anim.save(movie_name, writer='ffmpeg', fps=5, extra_args=['-vcodec', 'libx264'], dpi=300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "563\n",
      "399.67778\n",
      "419.67778\n"
     ]
    }
   ],
   "source": [
    "# time to investigate\n",
    "inv_time = awake_sweep['onset_masterclock'].iloc[10] - 3 # sec, master clock\n",
    "end_time = awake_sweep['onset_masterclock'].iloc[13] + 2 # sec\n",
    "inv_movietimes = bodymovie.sync_timestamps[np.argwhere((bodymovie.sync_timestamps >= inv_time) & (bodymovie.sync_timestamps <= end_time)).flatten()]\n",
    "print(len(inv_movietimes))\n",
    "print(inv_time)\n",
    "print(end_time)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "563\n"
     ]
    }
   ],
   "source": [
    "stim_list = []\n",
    "for ttime in inv_movietimes:\n",
    "    if (ttime > awake_sweep['onset_masterclock'].iloc[10]) & (ttime < awake_sweep['onset_masterclock'].iloc[10]+0.25):\n",
    "        stim_list.append('white screen')\n",
    "    elif (ttime > awake_sweep['onset_masterclock'].iloc[11]) & (ttime < awake_sweep['onset_masterclock'].iloc[11]+0.25):\n",
    "        stim_list.append('black screen')\n",
    "    elif (ttime > awake_sweep['onset_masterclock'].iloc[12]) & (ttime < awake_sweep['onset_masterclock'].iloc[12]+0.25):\n",
    "        stim_list.append('whitenoise')\n",
    "    elif (ttime > awake_sweep['onset_masterclock'].iloc[13]) & (ttime < awake_sweep['onset_masterclock'].iloc[13]+0.25):\n",
    "        stim_list.append('10 kHz tone')\n",
    "    else:\n",
    "        stim_list.append('')\n",
    "print(len(stim_list))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "def update(frame):\n",
    "    current_time = inv_movietimes[frame]\n",
    "    \n",
    "    # body cam movie\n",
    "    bax.set_data(bodymovie.get_frame(time=current_time))\n",
    "    \n",
    "    # update text\n",
    "    time_text.set_text(stim_list[frame])\n",
    "    \n",
    "    return fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "C:\\Users\\lesliec\\data\\eeg_pilot\\mouse496220\\audio_vis1_2020-06-10_14-54-43\\recording1\\stim_sample_awake.mp4\n"
     ]
    }
   ],
   "source": [
    "movie_name = os.path.join(exp.data_folder, 'stim_sample_awake.mp4')\n",
    "print(movie_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "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=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(8, 6))\n",
    "# fig.patch.set_facecolor('whitesmoke')\n",
    "\n",
    "timezero = inv_movietimes[0]\n",
    "\n",
    "ax_body = fig.add_subplot()\n",
    "\n",
    "# body cam movie\n",
    "bax = ax_body.imshow(bodymovie.get_frame(time=timezero))\n",
    "ax_body.get_xaxis().set_visible(False)\n",
    "ax_body.get_yaxis().set_visible(False)\n",
    "\n",
    "# add text\n",
    "time_text = ax_body.text(0.02, 0.05, 'STIMULUS', color='white', fontsize=14, transform=ax_body.transAxes)\n",
    "\n",
    "anim = animation.FuncAnimation(fig, update, init_func=None, frames=len(inv_movietimes), interval=35, blit=False)\n",
    "# anim.save(movie_name, writer='ffmpeg', fps=28, extra_args=['-vcodec', 'libx264'], dpi=300) # fps=30"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "tbd_eeg",
   "language": "python",
   "name": "tbd_eeg"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}