stim_vsync_alignment.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "import datetime\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy import signal, stats\n",
    "from glob import glob\n",
    "import copy\n",
    "import time"
   ]
  },
  {
   "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"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sensory_stim_lag import visual_stim_lag"
   ]
  },
  {
   "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_vis2_2020-06-11_11-42-47\\recording1'\n",
    "dfolder = r'E:\\eeg_pilot\\mouse496220\\audio_vis4_2020-06-18_13-49-17\\recording1'\n",
    "# load experiment metadata and eeg data\n",
    "exp = EEGexp(dfolder, preprocess=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "E:\\eeg_pilot\\mouse496220\\audio_vis4_2020-06-18_13-49-17\\recording1\\mouse496220200618134906.sync\n"
     ]
    }
   ],
   "source": [
    "print(exp.sync_file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "sync_data = exp._load_sync_dataset()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "dir(sync_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['behavior_vsync', 'behavior_sweep', 'fluorescence_camera', 'behavior_camera', 'face_camera', 'eye_camera', 'capacitive_licks', 'barcodes', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '']\n"
     ]
    }
   ],
   "source": [
    "print(sync_data.line_labels)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Get sweep and vsync edges from sync file"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "sweep_edges = sync_data.get_edges(keys=('behavior_sweep',), kind='all', units='seconds')\n",
    "vsync_edges = sync_data.get_edges(keys=('behavior_vsync',), kind='all', units='seconds')"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "print(len(sweep_edges))\n",
    "print(len(vsync_edges))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Let's take a look"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "sweep_step = np.vstack([np.zeros(len(sweep_edges)//2), np.ones(len(sweep_edges)//2)]).T.flatten()\n",
    "vsync_step = np.vstack([np.zeros(len(vsync_edges)//2), np.ones(len(vsync_edges)//2)]).T.flatten()\n",
    "\n",
    "ax.step(sweep_edges, sweep_step, 'b')\n",
    "ax.step(vsync_edges, vsync_step, 'r')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "https://github.com/AllenInstitute/AllenSDK/blob/master/allensdk/brain_observatory/ecephys/stimulus_table/ecephys_visual_coding_time_alignment.ipynb"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load the stim table and log file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "E:\\eeg_pilot\\mouse496220\\audio_vis4_2020-06-18_13-49-17\\recording1\\audio_vis_table.csv\n",
      "E:\\eeg_pilot\\mouse496220\\audio_vis4_2020-06-18_13-49-17\\recording1\\2020-06-18_13-49-55_stimulus_log.csv\n"
     ]
    }
   ],
   "source": [
    "# stimulus table\n",
    "stim_file = glob(exp.data_folder + '/*_table.csv', recursive=True)[0]\n",
    "print(stim_file)\n",
    "\n",
    "# log file\n",
    "log_file = glob(exp.data_folder + '/*_stimulus_log.csv', recursive=True)[0]\n",
    "print(log_file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>type</th>\n",
       "      <th>parameter</th>\n",
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       "      <th>1</th>\n",
       "      <td>auditory</td>\n",
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       "      <td>6</td>\n",
       "      <td>0.25</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>auditory</td>\n",
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       "      <td>auditory</td>\n",
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       "         type   parameter  on_time  duration\n",
       "0  fullscreen       black        1      0.25\n",
       "1    auditory  whitenoise        6      0.25\n",
       "2    auditory  whitenoise       11      0.25\n",
       "3  fullscreen       white       16      0.25\n",
       "4    auditory  whitenoise       21      0.25"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stim_table = pd.read_csv(stim_file)\n",
    "stim_table.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>time</th>\n",
       "      <th>frame</th>\n",
       "      <th>display_stim</th>\n",
       "      <th>stim_type</th>\n",
       "      <th>stim_parameter</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "      <td>none</td>\n",
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       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.266446</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "      <td>gray_screen</td>\n",
       "      <td>none</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.283012</td>\n",
       "      <td>4</td>\n",
       "      <td>False</td>\n",
       "      <td>gray_screen</td>\n",
       "      <td>none</td>\n",
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      "text/plain": [
       "       time  frame  display_stim    stim_type stim_parameter\n",
       "0  0.228516      0         False  gray_screen           none\n",
       "1  0.232966      1         False  gray_screen           none\n",
       "2  0.249750      2         False  gray_screen           none\n",
       "3  0.266446      3         False  gray_screen           none\n",
       "4  0.283012      4         False  gray_screen           none"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stim_log = pd.read_csv(log_file)\n",
    "stim_log.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of stimuli in stim_table: 240\n",
      "Number of entries in stim_log: 139659\n"
     ]
    }
   ],
   "source": [
    "print('Number of stimuli in stim_table: %d' % (len(stim_table)-1)) # -1 because of \"end\" line\n",
    "print('Number of entries in stim_log: %d' % len(stim_log))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Check rising and falling edges"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "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": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "behavior_sweep info\n",
      "number of rising/falling: 2/2\n",
      "first rising: 49.262640\n",
      "first falling: 1246.283430\n"
     ]
    }
   ],
   "source": [
    "print('behavior_sweep info')\n",
    "print('number of rising/falling: %d/%d' % (len(srising), len(sfalling)))\n",
    "print('first rising: %f' % srising[0])\n",
    "print('first falling: %f' % sfalling[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "behavior_vsync info\n",
      "number of rising/falling: 139659/139659\n",
      "first rising: 49.265840\n",
      "first falling: 49.489790\n"
     ]
    }
   ],
   "source": [
    "print('behavior_vsync info')\n",
    "print('number of rising/falling: %d/%d' % (len(vrising), len(vfalling)))\n",
    "print('first rising: %f' % vrising[0])\n",
    "print('first falling: %f' % vfalling[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Combine log with vsync rising and falling times"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>frame</th>\n",
       "      <th>display_stim</th>\n",
       "      <th>stim_type</th>\n",
       "      <th>stim_parameter</th>\n",
       "      <th>vsync_rising</th>\n",
       "      <th>vsync_falling</th>\n",
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       "      <th>0</th>\n",
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       "      <th>1</th>\n",
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       "      <td>49.49069</td>\n",
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       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "      <td>gray_screen</td>\n",
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       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
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      ],
      "text/plain": [
       "   frame  display_stim    stim_type stim_parameter  vsync_rising  \\\n",
       "0      0         False  gray_screen           none      49.26584   \n",
       "1      1         False  gray_screen           none      49.49069   \n",
       "2      2         False  gray_screen           none      49.49479   \n",
       "3      3         False  gray_screen           none      49.51145   \n",
       "4      4         False  gray_screen           none      49.52813   \n",
       "\n",
       "   vsync_falling  \n",
       "0       49.48979  \n",
       "1       49.49425  \n",
       "2       49.51103  \n",
       "3       49.52773  \n",
       "4       49.54429  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sync_log = stim_log.drop(labels='time', axis='columns')\n",
    "sync_log['vsync_rising'] = vrising\n",
    "sync_log['vsync_falling'] = vfalling\n",
    "sync_log.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Time to loop through stim log: 10.08 seconds\n"
     ]
    }
   ],
   "source": [
    "start = time.time()\n",
    "list_stim_type = []\n",
    "list_stim_param = []\n",
    "list_onset_times = []\n",
    "list_offset_times = []\n",
    "for i in range(1, len(sync_log)):\n",
    "    if sync_log.stim_type.iloc[i-1] == 'gray_screen' and sync_log.stim_type.iloc[i] == 'fullscreen':\n",
    "        list_onset_times.append(sync_log.vsync_falling.iloc[i]) # vsync_falling is visual stim onset\n",
    "        list_stim_type.append(sync_log.stim_type.iloc[i])\n",
    "        list_stim_param.append(sync_log.stim_parameter.iloc[i]) # to make sure order matches stim table\n",
    "    elif sync_log.stim_type.iloc[i-1] == 'fullscreen' and sync_log.stim_type.iloc[i] == 'gray_screen':\n",
    "        list_offset_times.append(sync_log.vsync_falling.iloc[i]) # gray_screen vsync_falling is visual stim offset\n",
    "    elif sync_log.stim_type.iloc[i-1] == 'gray_screen' and sync_log.stim_type.iloc[i] == 'auditory':\n",
    "        list_onset_times.append(sync_log.vsync_rising.iloc[i]) # vsync_rising is aditory stim onset\n",
    "        list_offset_times.append(sync_log.vsync_falling.iloc[i]) # vsync_falling is aditory stim offset\n",
    "        list_stim_type.append(sync_log.stim_type.iloc[i])\n",
    "        list_stim_param.append(sync_log.stim_parameter.iloc[i])\n",
    "end = time.time()\n",
    "print('Time to loop through stim log: %0.2f seconds' % (end-start))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Now build stim table log with vsync onset/offset times (falling edge for visual stim, rising for auditory) *** These times are not yet corrected for visual/auditory display lag."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>stim_type</th>\n",
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       "      <th>onset</th>\n",
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       "      <td>fullscreen</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>auditory</td>\n",
       "      <td>whitenoise</td>\n",
       "      <td>55.38163</td>\n",
       "      <td>55.65093</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>auditory</td>\n",
       "      <td>whitenoise</td>\n",
       "      <td>60.30197</td>\n",
       "      <td>60.57100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>fullscreen</td>\n",
       "      <td>white</td>\n",
       "      <td>65.29150</td>\n",
       "      <td>65.55837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>auditory</td>\n",
       "      <td>whitenoise</td>\n",
       "      <td>70.29263</td>\n",
       "      <td>70.56114</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    stim_type stim_parameter     onset    offset\n",
       "0  fullscreen          black  50.27826  50.54503\n",
       "1    auditory     whitenoise  55.38163  55.65093\n",
       "2    auditory     whitenoise  60.30197  60.57100\n",
       "3  fullscreen          white  65.29150  65.55837\n",
       "4    auditory     whitenoise  70.29263  70.56114"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vsync_log = pd.DataFrame({\n",
    "    'stim_type': list_stim_type,\n",
    "    'stim_parameter': list_stim_param,\n",
    "    'onset': list_onset_times,\n",
    "    'offset': list_offset_times\n",
    "})\n",
    "vsync_log.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "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>stim_type</th>\n",
       "      <th>stim_parameter</th>\n",
       "      <th>onset</th>\n",
       "      <th>offset</th>\n",
       "      <th>duration</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>fullscreen</td>\n",
       "      <td>black</td>\n",
       "      <td>50.27826</td>\n",
       "      <td>50.54503</td>\n",
       "      <td>0.26677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>auditory</td>\n",
       "      <td>whitenoise</td>\n",
       "      <td>55.38163</td>\n",
       "      <td>55.65093</td>\n",
       "      <td>0.26930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>auditory</td>\n",
       "      <td>whitenoise</td>\n",
       "      <td>60.30197</td>\n",
       "      <td>60.57100</td>\n",
       "      <td>0.26903</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>fullscreen</td>\n",
       "      <td>white</td>\n",
       "      <td>65.29150</td>\n",
       "      <td>65.55837</td>\n",
       "      <td>0.26687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>auditory</td>\n",
       "      <td>whitenoise</td>\n",
       "      <td>70.29263</td>\n",
       "      <td>70.56114</td>\n",
       "      <td>0.26851</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    stim_type stim_parameter     onset    offset  duration\n",
       "0  fullscreen          black  50.27826  50.54503   0.26677\n",
       "1    auditory     whitenoise  55.38163  55.65093   0.26930\n",
       "2    auditory     whitenoise  60.30197  60.57100   0.26903\n",
       "3  fullscreen          white  65.29150  65.55837   0.26687\n",
       "4    auditory     whitenoise  70.29263  70.56114   0.26851"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vsync_log['duration'] = vsync_log['offset'] - vsync_log['onset']\n",
    "vsync_log.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "vis_stim = vsync_log[vsync_log['stim_type'] == 'fullscreen']\n",
    "aud_stim = vsync_log[vsync_log['stim_type'] == 'auditory']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Now what about onset/offset lag??"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10000.0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\lesliec\\AppData\\Local\\Continuum\\miniconda3\\envs\\tbd_eeg\\lib\\site-packages\\allensdk\\brain_observatory\\sync_dataset.py:454: H5pyDeprecationWarning: dataset.value has been deprecated. Use dataset[()] instead.\n",
      "  return eval(self.dfile['analog_meta'].value)\n"
     ]
    }
   ],
   "source": [
    "samp_rate = sync_data.analog_meta_data['analog_sample_rate']\n",
    "print(samp_rate)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's look at the photodiode for visual stim lags."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "photodiode = sync_data.get_analog_channel('photodiode')\n",
    "speaker_input = sync_data.get_analog_channel('speaker_input')\n",
    "synctime = np.arange(0, len(photodiode))/samp_rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "window.mpl = {};\n",
       "\n",
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       "    } 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",
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       "    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",
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       "    this.canvas = undefined;\n",
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       "    this.rubberband_context = undefined;\n",
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       "\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",
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       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
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       "            if (fig.image_mode == 'full') {\n",
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       "\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",
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       "\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",
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       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
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       "\n",
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       "    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",
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       "\n",
       "    canvas_div.resizable({\n",
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       "            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",
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       "\n",
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       "            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",
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       "        event['data'] = 'scroll'\n",
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       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
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       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
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       "        // Keep the size of the canvas, canvas container, and rubber band\n",
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       "        canvas_div.css('width', width)\n",
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       "\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",
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       "\n",
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       "        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",
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       "        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",
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       "        tooltip_span.addClass('ui-button-text');\n",
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       "\n",
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       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
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       "\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",
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       "    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",
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       "\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=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.plot(synctime, photodiode, 'b')\n",
    "\n",
    "for ind, row in vis_stim.iterrows():\n",
    "    ax.axvspan(row.onset, row.offset, alpha=0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "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": {
      "text/html": [
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.plot(synctime, speaker_input, 'r')\n",
    "\n",
    "for ind, row in aud_stim.iterrows():\n",
    "    ax.axvspan(row.onset, row.offset, alpha=0.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Loop through all stim and look through photodiode or speaker signal to find real onset/offset times."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "search_window = 0.1 # s, before and after\n",
    "search_sample = int(search_window * samp_rate)\n",
    "\n",
    "onset_delays = np.zeros(len(vsync_log)) # initialize array to hold delays\n",
    "offset_delays = np.zeros(len(vsync_log)) # initialize array to hold delays\n",
    "for ind, row in vsync_log.iterrows():\n",
    "    onset_ind = int(row.onset * samp_rate)\n",
    "    offset_ind = int(row.offset * samp_rate)\n",
    "    \n",
    "    if row.stim_type == 'fullscreen':\n",
    "        onset_chunk = photodiode[onset_ind - search_sample:onset_ind + search_sample]\n",
    "        offset_chunk = photodiode[offset_ind - search_sample:offset_ind + search_sample]\n",
    "    elif row.stim_type == 'auditory':\n",
    "        onset_chunk = speaker_input[onset_ind - search_sample:onset_ind + search_sample]\n",
    "        offset_chunk = speaker_input[offset_ind - search_sample:offset_ind + search_sample]\n",
    "    \n",
    "    # TIME stamps for chunks\n",
    "    onset_t = synctime[onset_ind - search_sample:onset_ind + search_sample] - row.onset\n",
    "    offset_t = synctime[offset_ind - search_sample:offset_ind + search_sample] - row.offset\n",
    "    \n",
    "    # ONSET DELAY\n",
    "    onset_z = np.abs((onset_chunk - np.mean(onset_chunk[0:search_sample]))/np.std(onset_chunk[0:search_sample]))\n",
    "    onset_z_thresh = (np.max(onset_z) - np.min(onset_z))*0.5\n",
    "    onset_delays[ind] = onset_t[np.argwhere(onset_z > onset_z_thresh)[0]]\n",
    "    \n",
    "    # OFFSET DELAY\n",
    "    offset_z = np.abs((offset_chunk - np.mean(offset_chunk[0:search_sample]))/np.std(offset_chunk[0:search_sample]))\n",
    "    offset_z_thresh = (np.max(offset_z) - np.min(offset_z))*0.5\n",
    "    offset_delays[ind] = offset_t[np.argwhere(offset_z > offset_z_thresh)[0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "vsync_log['onset_delay'] = onset_delays\n",
    "vsync_log['offset_delay'] = offset_delays"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        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>stim_type</th>\n",
       "      <th>stim_parameter</th>\n",
       "      <th>onset</th>\n",
       "      <th>offset</th>\n",
       "      <th>duration</th>\n",
       "      <th>onset_delay</th>\n",
       "      <th>offset_delay</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>fullscreen</td>\n",
       "      <td>black</td>\n",
       "      <td>50.27826</td>\n",
       "      <td>50.54503</td>\n",
       "      <td>0.26677</td>\n",
       "      <td>0.03224</td>\n",
       "      <td>0.03717</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>auditory</td>\n",
       "      <td>whitenoise</td>\n",
       "      <td>55.38163</td>\n",
       "      <td>55.65093</td>\n",
       "      <td>0.26930</td>\n",
       "      <td>0.02017</td>\n",
       "      <td>-0.10003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>auditory</td>\n",
       "      <td>whitenoise</td>\n",
       "      <td>60.30197</td>\n",
       "      <td>60.57100</td>\n",
       "      <td>0.26903</td>\n",
       "      <td>0.02073</td>\n",
       "      <td>-0.10000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>fullscreen</td>\n",
       "      <td>white</td>\n",
       "      <td>65.29150</td>\n",
       "      <td>65.55837</td>\n",
       "      <td>0.26687</td>\n",
       "      <td>0.03100</td>\n",
       "      <td>0.03123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>auditory</td>\n",
       "      <td>whitenoise</td>\n",
       "      <td>70.29263</td>\n",
       "      <td>70.56114</td>\n",
       "      <td>0.26851</td>\n",
       "      <td>0.01947</td>\n",
       "      <td>-0.09984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>475</th>\n",
       "      <td>fullscreen</td>\n",
       "      <td>white</td>\n",
       "      <td>2575.05393</td>\n",
       "      <td>2575.32079</td>\n",
       "      <td>0.26686</td>\n",
       "      <td>0.03097</td>\n",
       "      <td>0.03121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>476</th>\n",
       "      <td>fullscreen</td>\n",
       "      <td>black</td>\n",
       "      <td>2580.05778</td>\n",
       "      <td>2580.32464</td>\n",
       "      <td>0.26686</td>\n",
       "      <td>0.03022</td>\n",
       "      <td>0.03546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>477</th>\n",
       "      <td>auditory</td>\n",
       "      <td>10000</td>\n",
       "      <td>2585.04611</td>\n",
       "      <td>2585.31515</td>\n",
       "      <td>0.26904</td>\n",
       "      <td>0.02249</td>\n",
       "      <td>-0.00155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>478</th>\n",
       "      <td>auditory</td>\n",
       "      <td>10000</td>\n",
       "      <td>2590.05005</td>\n",
       "      <td>2590.31534</td>\n",
       "      <td>0.26529</td>\n",
       "      <td>0.01855</td>\n",
       "      <td>-0.00174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>479</th>\n",
       "      <td>auditory</td>\n",
       "      <td>10000</td>\n",
       "      <td>2595.05397</td>\n",
       "      <td>2595.31528</td>\n",
       "      <td>0.26131</td>\n",
       "      <td>0.01503</td>\n",
       "      <td>-0.00148</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>480 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      stim_type stim_parameter       onset      offset  duration  onset_delay  \\\n",
       "0    fullscreen          black    50.27826    50.54503   0.26677      0.03224   \n",
       "1      auditory     whitenoise    55.38163    55.65093   0.26930      0.02017   \n",
       "2      auditory     whitenoise    60.30197    60.57100   0.26903      0.02073   \n",
       "3    fullscreen          white    65.29150    65.55837   0.26687      0.03100   \n",
       "4      auditory     whitenoise    70.29263    70.56114   0.26851      0.01947   \n",
       "..          ...            ...         ...         ...       ...          ...   \n",
       "475  fullscreen          white  2575.05393  2575.32079   0.26686      0.03097   \n",
       "476  fullscreen          black  2580.05778  2580.32464   0.26686      0.03022   \n",
       "477    auditory          10000  2585.04611  2585.31515   0.26904      0.02249   \n",
       "478    auditory          10000  2590.05005  2590.31534   0.26529      0.01855   \n",
       "479    auditory          10000  2595.05397  2595.31528   0.26131      0.01503   \n",
       "\n",
       "     offset_delay  \n",
       "0         0.03717  \n",
       "1        -0.10003  \n",
       "2        -0.10000  \n",
       "3         0.03123  \n",
       "4        -0.09984  \n",
       "..            ...  \n",
       "475       0.03121  \n",
       "476       0.03546  \n",
       "477      -0.00155  \n",
       "478      -0.00174  \n",
       "479      -0.00148  \n",
       "\n",
       "[480 rows x 7 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vsync_log"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### From previous analysis:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Get analog speaker_input to check auditory delay"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### How to threshold analog speaker signal?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What about a rolling z-score? Window should be longer than stimuli duration, 250 ms."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# AUDITORY SIGNAL\n",
    "\n",
    "search_window = 0.1 # s, before and after\n",
    "search_sample = int(search_window * samp_rate)\n",
    "\n",
    "aud_delays = np.zeros(len(aud_stim)) # initialize array to hold delays\n",
    "for ind, sync_aud_onset in enumerate(aud_stim['onset']):\n",
    "    onset_ind = int(sync_aud_onset * samp_rate)\n",
    "    \n",
    "    speaker_input_chunk = speaker_input[onset_ind - search_sample:onset_ind + search_sample]\n",
    "    BL = np.mean(speaker_input_chunk[0:search_sample])\n",
    "    STD = np.std(speaker_input_chunk[0:search_sample])\n",
    "    chunk_z = np.abs((speaker_input_chunk - BL)/STD)\n",
    "    timex = synctime[onset_ind - search_sample:onset_ind + search_sample] - sync_aud_onset\n",
    "    \n",
    "    z_thresh = (np.max(chunk_z) - np.min(chunk_z))*0.5\n",
    "\n",
    "    aud_delays[ind] = timex[np.argwhere(chunk_z > z_thresh)[0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# VISUAL SIGNAL\n",
    "\n",
    "search_window = 0.1 # s, before and after\n",
    "search_sample = int(search_window * samp_rate)\n",
    "\n",
    "vis_delays = np.zeros(len(vis_stim)) # initialize array to hold delays\n",
    "for ind, sync_vis_onset in enumerate(vis_stim['onset']):\n",
    "    onset_ind = int(sync_vis_onset * samp_rate)\n",
    "    \n",
    "    photodiode_chunk = photodiode[onset_ind - search_sample:onset_ind + search_sample]\n",
    "    BL = np.mean(photodiode_chunk[0:search_sample])\n",
    "    STD = np.std(photodiode_chunk[0:search_sample])\n",
    "    chunk_z = np.abs((photodiode_chunk - BL)/STD)\n",
    "    timex = synctime[onset_ind - search_sample:onset_ind + search_sample] - sync_vis_onset\n",
    "    \n",
    "    z_thresh = (np.max(chunk_z) - np.min(chunk_z))*0.5\n",
    "\n",
    "    vis_delays[ind] = timex[np.argwhere(chunk_z > z_thresh)[0]]"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "print('Mean auditory delay = %0.3f ms' % (np.mean(aud_delays)*1000))\n",
    "print('Auditory delay standard deviation = %0.5f ms' % (np.std(aud_delays)*1000))\n",
    "print('Auditory delay max = %0.3f ms' % (np.max(aud_delays)*1000))\n",
    "print('Auditory delay min = %0.3f ms' % (np.min(aud_delays)*1000))"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.hist(aud_delays)"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.plot(synctime, speaker_input, 'b')\n",
    "\n",
    "for ind, val in enumerate(aud_stim['pulse_rising']):\n",
    "    if aud_delays[ind] < 0.008:\n",
    "        ax.axvline(x=val+aud_delays[ind], c='orange')\n",
    "        ax.axvline(x=val, c='black')\n",
    "        print(ind)\n",
    "    elif aud_delays[ind] > 0.025:\n",
    "        ax.axvline(x=val+aud_delays[ind], c='red')\n",
    "        ax.axvline(x=val, c='black')\n",
    "        print(ind)"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "# check length of aud stim\n",
    "fig, ax = plt.subplots()\n",
    "ax.plot(analogx, speaker_input, 'b')\n",
    "\n",
    "for ind, val in enumerate(aud_stim['pulse_rising']):\n",
    "    aon = val + aud_delays[ind]\n",
    "    aoff = aon + 0.25\n",
    "    ax.axvspan(aon, aoff, facecolor='orange', alpha=0.6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
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       "    } 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",
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       "        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",
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       "\n",
       "    this.root = $('<div/>');\n",
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       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
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       "    this.ws.onmessage = this._make_on_message_function(this);\n",
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       "\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",
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       "\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",
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       "\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=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x222961198d0>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "numind = 32\n",
    "test_onset = aud_stim['onset'].iloc[numind]\n",
    "\n",
    "onset_sample = int(test_onset * samp_rate)\n",
    "search_window = 0.1 # s, before and after\n",
    "search_sample = int(search_window * samp_rate)\n",
    "\n",
    "speaker_chunk = speaker_input[onset_sample - search_sample:onset_sample + search_sample]\n",
    "BL = np.mean(speaker_chunk[0:search_sample])\n",
    "STD = np.std(speaker_chunk[0:search_sample])\n",
    "chunkz = np.abs((speaker_chunk-BL)/STD)\n",
    "timex = synctime[onset_sample - search_sample:onset_sample + search_sample] - test_onset\n",
    "z_thresh = (np.max(chunkz) - np.min(chunkz))/2\n",
    "delay = timex[np.argwhere(chunkz > z_thresh)[0]]\n",
    "\n",
    "half_window = 10\n",
    "rolling_std = np.zeros(len(speaker_chunk))\n",
    "amp = np.zeros(len(speaker_chunk))\n",
    "for ii in range(len(rolling_std)):\n",
    "    center_sample = onset_sample + ii\n",
    "    rolling_std[ii] = np.std(speaker_input[center_sample - half_window:center_sample + half_window])\n",
    "    amp[ii] = np.max(speaker_input[center_sample - half_window:center_sample + half_window]) - np.min(speaker_input[center_sample - half_window:center_sample + half_window])\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "ax.plot(timex, speaker_chunk, 'b', alpha=0.6, label='speaker signal')\n",
    "ax1 = ax.twinx()\n",
    "ax1.plot(timex, chunkz, 'm', alpha=0.75)\n",
    "# ax1.set_ylim([0, 0.02])\n",
    "ax.axvline(x=0, c='black', label='vsync onset')\n",
    "ax.axvline(x=delay, c='red', label='est. delay')\n",
    "ax1.axhline(y=STD, c='green', label='baseline std')\n",
    "ax1.axhline(y=z_thresh, c='teal', label='threshold')\n",
    "ax.set_title('Auditory stim #%d\\nEstimated delay = %0.4f ms' % (numind, delay))\n",
    "ax.set_xlabel('Time from vsync pulse onset (s)')\n",
    "ax.set_ylabel('Speaker signal (V)')\n",
    "ax.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# aud_delays[32] = 0.023\n",
    "# aud_delays[144] = 0.015"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean auditory delay = 17.343 ms\n",
      "Auditory delay standard deviation = 3.25681 ms\n",
      "Auditory delay max = 27.330 ms\n",
      "Auditory delay min = 10.970 ms\n"
     ]
    }
   ],
   "source": [
    "print('Mean auditory delay = %0.3f ms' % (np.mean(aud_delays)*1000))\n",
    "print('Auditory delay standard deviation = %0.5f ms' % (np.std(aud_delays)*1000))\n",
    "print('Auditory delay max = %0.3f ms' % (np.max(aud_delays)*1000))\n",
    "print('Auditory delay min = %0.3f ms' % (np.min(aud_delays)*1000))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Testing Irene's visual_stim_lag function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "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=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vislagmean, vislagstd = visual_stim_lag(photodiode, log_file, vfalling, flag_plot=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "30.60616666672592\n",
      "0.04827323849252103\n"
     ]
    }
   ],
   "source": [
    "print(vislagmean)\n",
    "print(vislagstd)"
   ]
  },
  {
   "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",
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