{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "recreational-beijing",
   "metadata": {},
   "source": [
    "# Offline pupillometry\n",
    "This notebook provides an example of how to use mEYE models in the Python environment to get pupillometry data from a prerecorded video file.\n",
    "\n",
    "## Installation\n",
    "Follow the requiremets described in the repo [homepage](https://github.com/fabiocarrara/meye).  \n",
    "\n",
    "Download locally the NN model in a location in your computer. \n",
    "\n",
    "For **mEYE** you need Python 3 environment with the following packages installed:\n",
    "- tensorflow >= 2.4\n",
    "- imageio, imageio-ffmpeg\n",
    "- scipy\n",
    "- tqdm\n",
    "\n",
    "For running the rest of this **notebook** you will need:\n",
    "- cv2\n",
    "- numpy\n",
    "- pandas\n",
    "- matplotlib\n",
    "- scikit-image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install -q opencv-python-headless scikit-image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "welcome-prescription",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import required packages for this notebook\n",
    "import os\n",
    "import numpy as np \n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.patches as ptch\n",
    "%matplotlib inline\n",
    "import cv2 as cv\n",
    "from skimage.measure import label, regionprops\n",
    "\n",
    "# Import the NN model\n",
    "from tensorflow.keras.models import load_model\n",
    "\n",
    "### WINDOWS ONLY (Comment if on other OS)\n",
    "# import winsound # makes a beep sound when whole video analysis is finished\n",
    "BEEP_FREQ = 2500  # Set Frequency To 2500 Hertz\n",
    "BEEP_DURATION_MS = 1000  # Set Duration To 1000 ms == 1 second\n",
    "###"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "impressive-youth",
   "metadata": {},
   "source": [
    "### Specify the full paths\n",
    " - **MODELPATH**: the NN model that you downloaded locally on your PC\n",
    " - **VIDEOPATH**: the video file you want to analyze"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "eleven-avatar",
   "metadata": {},
   "outputs": [],
   "source": [
    "MODELPATH = r\"C:\\Users\\Leonardo\\Documents\\Python\\pupilNN\\meye-segmentation_i128_s4_c1_f16_g1_a-relu.hdf5\"\n",
    "VIDEOPATH = r\"D:\\PizzorussoLAB\\proj_Fasting\\exp_acuity-2P\\2P_data\\cage_gNex6\\20210107\\gNex6_postFast_2021-01-07-095936-0000.avi\"\n",
    "\n",
    "model = load_model(MODELPATH)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "offensive-freeware",
   "metadata": {},
   "source": [
    "## Crop the movie\n",
    "\n",
    "The NN makes predition on images of a fixed size. The following section provide some code to interactively and iteratively perform a square region of interest (ROI) around the eye.  \n",
    "You need to specify and eventually adjust 2 parameters:\n",
    "- **TOPLEFT**: tuple containing the XY (columns,rows) coordinates of the top-left corner of the ROI\n",
    "- **ROIWIDTH**: size of the side of the square ROI in pixels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "labeled-gibson",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# EDIT PARAMETERS\n",
    "# Manually select a square ROI for the eye, by specifying the XY coordinates\n",
    "# and the width of the square in pixels\n",
    "# ---------------------------------------------------\n",
    "TOPLEFT = (260,50) # X,Y coordinates\n",
    "ROIWIDTH = 200 # width on the square ROI in pixels\n",
    "# ---------------------------------------------------\n",
    "\n",
    "cap = cv.VideoCapture(VIDEOPATH)\n",
    "try:\n",
    "    numOfFrames = int(cap.get(cv.CAP_PROP_FRAME_COUNT))\n",
    "    chosenFrame = np.random.randint(1, high=numOfFrames)# Choose randomly a frame\n",
    "    \n",
    "    cap.set(cv.CAP_PROP_POS_FRAMES,chosenFrame)\n",
    "    _, frame = cap.read() # Read the frame\n",
    "    frame = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)# Convert to grayscale\n",
    "except:\n",
    "    print('An error occurred while getting a frame for the video.')\n",
    "finally:\n",
    "    cap.release()\n",
    "\n",
    "fHeight, fWidth = frame.shape\n",
    "cropL = TOPLEFT[0]\n",
    "cropR = TOPLEFT[0]+ROIWIDTH\n",
    "cropT = TOPLEFT[1]\n",
    "cropB = TOPLEFT[1]+ROIWIDTH\n",
    "\n",
    "# Default crop is the selected crop is out of the image boundaries\n",
    "if (any(np.array([cropT,cropB])>fHeight)) or (any(np.array([cropL,cropR])>fWidth)):\n",
    "    print('Crop limits exceed image size. Performing a default crop instead.')\n",
    "    cropL = round((fWidth-ROIWIDTH) / 2)\n",
    "    cropR = round((fWidth+ROIWIDTH) / 2)\n",
    "    cropT = round((fHeight-ROIWIDTH) / 2)\n",
    "    cropB = round((fHeight+ROIWIDTH) / 2)                           \n",
    "       \n",
    "# Crop and resize \n",
    "requiredFrameSize = model.input.shape[1:3]\n",
    "crop = frame[cropT:cropB, cropL:cropR]\n",
    "crop = cv.resize(crop,tuple(requiredFrameSize))\n",
    "\n",
    "# Create a Rectangle patch\n",
    "rect = ptch.Rectangle((cropL,cropT),ROIWIDTH,ROIWIDTH,\n",
    "                      linewidth=4,edgecolor=[.2,1,.2],facecolor='none')\n",
    "\n",
    "# Visual plotting\n",
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12,4))\n",
    "ax1.imshow(frame, cmap='gray')\n",
    "ax1.add_patch(rect)\n",
    "ax1.set_title('Raw frame')\n",
    "ax2.imshow(crop, cmap='gray')\n",
    "ax2.set_title('Cropped, resized')\n",
    "ax1.grid(color=[1,.4,.4], linewidth=1, linestyle='-.')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "favorite-bearing",
   "metadata": {},
   "source": [
    "## Load and predict a single frame of the video\n",
    "This section allows to make a prediciton on a single frame of the video.\n",
    "By default the prediction returns: \n",
    "- an **output image** of the same size as the input image, containing a **probability map** (i.e. each pixel value represent the probability for that pizel to be part of a pupil).\n",
    "- the **eye-probability** (i.e., the probability for that frame to be an eye)\n",
    "- the **blink-probability** (i.e., the probability for that frame to be a blink)\n",
    "\n",
    "The output image can be binarized based on a probability threshold to get a binay mask of the pupil.\n",
    "\n",
    "----\n",
    "You need to specify and eventually adjust 2 parameters:\n",
    "- **FRAMENUMBER**: The frame to analyze. If FRAMENUMBER=[], then a random frame will be taken\n",
    "- **THRESHOLD**: The probability threshold to binarize the output image\n",
    "- **IMCLOSING**: Size in pixel for morphological closing (fill pupil areas not detected). Increase to fill more.\n",
    "- **INVERTIMAGE**: bool. Inverts the image (can be useful for tricky 2p images)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "permanent-fifth",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Analyzed image # 20400 / 23236\n",
      "Eye Probability: 99.82%\n",
      "Blink Probability: 2.64%\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.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 = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\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.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* 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",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// 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",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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",
       "        }\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",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\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, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home 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\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"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\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.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 = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\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",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "<img 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width=\"1080\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# EDIT PARAMETERS\n",
    "# ---------------------------------------------------\n",
    "FRAMENUMBER = 20400 # frame number to analyze. If [] a random frame will be taken \n",
    "THRESHOLD = 0.1 # probability threshold for image binarization\n",
    "IMCLOSING = 13 # pixel radius of circular kernel for morphological closing\n",
    "INVERTIMAGE = True\n",
    "# ---------------------------------------------------\n",
    "\n",
    "cap = cv.VideoCapture(VIDEOPATH)\n",
    "try:\n",
    "    numOfFrames = int(cap.get(cv.CAP_PROP_FRAME_COUNT))\n",
    "    if not FRAMENUMBER:\n",
    "        FRAMENUMBER = np.random.randint(1, high=numOfFrames)\n",
    "    if FRAMENUMBER>numOfFrames:\n",
    "        print('requested a frame (#{}) beyond video length ({}).'.format(FRAMENUMBER,numOfFrames),end='')\n",
    "        print(' Analyzing last frame instead')\n",
    "        FRAMENUMBER=numOfFrames\n",
    "    cap.set(cv.CAP_PROP_POS_FRAMES,FRAMENUMBER-1) \n",
    "    # -1 because CAP_PROP_FRAME_COUNT is 1-based while CAP_PROP_POS_FRAMES is 0-based\n",
    "    \n",
    "    # Read a frame from the \n",
    "    _, frame = cap.read()\n",
    "    # Convert to grayscale\n",
    "    frame = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)\n",
    "except:\n",
    "    print('An error occurred while getting a frame for the video.')\n",
    "finally:\n",
    "    cap.release()\n",
    "    \n",
    "def cropResize(sourceImg):\n",
    "    cropped = sourceImg[cropT:cropB, cropL:cropR]\n",
    "    cropped = cv.resize(cropped,tuple(requiredFrameSize))\n",
    "    return cropped\n",
    "\n",
    "def morphProcessing(sourceImg):\n",
    "    # Binarize \n",
    "    binarized = sourceImg > THRESHOLD\n",
    "    # Divide in regions and keep only the biggest\n",
    "    label_img = label(binarized)\n",
    "    regions = regionprops(label_img)\n",
    "    if len(regions)==0:\n",
    "        morph = np.zeros(sourceImg.shape, dtype='uint8')\n",
    "        centroid = (np.nan, np.nan)\n",
    "        return (morph, centroid)\n",
    "    regions.sort(key=lambda x: x.area, reverse=True)\n",
    "    centroid = regions[0].centroid # centroid coordinates of the biggest object\n",
    "    if len(regions) > 1:\n",
    "        for rg in regions[1:]:\n",
    "            label_img[rg.coords[:,0], rg.coords[:,1]] = 0\n",
    "    label_img[label_img!=0] = 1\n",
    "    biggestRegion = (label_img*255).astype(np.uint8)\n",
    "    # Morphological\n",
    "    kernel = cv.getStructuringElement(cv.MORPH_ELLIPSE,(IMCLOSING,IMCLOSING))\n",
    "    morph = cv.morphologyEx(biggestRegion, cv.MORPH_CLOSE, kernel)\n",
    "    return (morph, centroid)\n",
    "\n",
    "croppedFrame = cropResize(frame)\n",
    "\n",
    "if INVERTIMAGE:\n",
    "    croppedFrame = cv.bitwise_not(croppedFrame)\n",
    "\n",
    "networkInput = croppedFrame.astype(np.float32) / 255.0  # convert from uint8 [0, 255] to float32 [0, 1]\n",
    "networkInput = networkInput[None, :, :, None]  # add batch and channel dimensions\n",
    "mask, info = model(networkInput)\n",
    "\n",
    "# Extract infos\n",
    "prediction = mask[0,:,:,0]\n",
    "eyeProbability = info[0,0]\n",
    "blinkProbability = info[0,1]\n",
    "\n",
    "morphedMask, centroid = morphProcessing(prediction)\n",
    "\n",
    "# Generate falsecolor image\n",
    "falseColor = np.dstack((morphedMask, croppedFrame, croppedFrame))\n",
    "\n",
    "# OUTPUT\n",
    "print('Analyzed image # {} / {}'.format(FRAMENUMBER, numOfFrames))\n",
    "print('Eye Probability: {:4.2%}'.format(eyeProbability))\n",
    "print('Blink Probability: {:4.2%}'.format(blinkProbability))\n",
    "\n",
    "fig, ax = plt.subplots(nrows=1, ncols=5, figsize=(15,5))\n",
    "ax[0].imshow(croppedFrame, cmap='gray')\n",
    "ax[0].set_title('Cropped Frame')\n",
    "\n",
    "ax[1].imshow(prediction, vmin=0, vmax=1)\n",
    "ax[1].set_title('Probability map')\n",
    "\n",
    "ax[2].imshow(prediction > THRESHOLD)\n",
    "ax[2].set_title('Map Binarized')\n",
    "\n",
    "ax[3].imshow(morphedMask)\n",
    "ax[3].set_title('After Morphology')\n",
    "\n",
    "ax[4].imshow(falseColor)\n",
    "ax[4].plot(centroid[1], centroid[0], marker='+', markersize=12, mew=2, mec='g')\n",
    "ax[4].set_title('Binary pupil')\n",
    "\n",
    "for a in ax.reshape(-1):\n",
    "    a.axis('off')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "european-bruce",
   "metadata": {},
   "source": [
    "## Predict pupil size for the whole video\n",
    "\n",
    "After adjusting all the parameters on single images in the previous section you can use this section to measure pupilsize on the whole video.  \n",
    "**This process can be long** (minutes), but having a GPU that tensorflow can use, might shorthen processing time significantly. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "protective-locking",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processing frames... (400/23236)\n",
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      "Processing frames... (22800/23236)\n",
      "Processing frames... (23200/23236)\n"
     ]
    }
   ],
   "source": [
    "cap = cv.VideoCapture(VIDEOPATH)\n",
    "numFrames = int(cap.get(cv.CAP_PROP_FRAME_COUNT))\n",
    "\n",
    "df = pd.DataFrame(columns=['frameN','pupilSize','pupCntr_x','pupCntr_y','eyeProb','blinkProb'])\n",
    "\n",
    "try:\n",
    "    for i in range(numFrames):\n",
    "        _, frame = cap.read()\n",
    "        frame = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)\n",
    "        \n",
    "        croppedFrame = cropResize(frame)\n",
    "        if INVERTIMAGE:\n",
    "            croppedFrame = cv.bitwise_not(croppedFrame)\n",
    "        \n",
    "        networkInput = croppedFrame.astype(np.float32) / 255.0\n",
    "        networkInput = networkInput[None, :, :, None]\n",
    "        mask, info = model(networkInput)\n",
    "        prediction = mask[0,:,:,0]\n",
    "        morphedMask, centroid = morphProcessing(prediction)\n",
    "        \n",
    "        # Extract infos\n",
    "        eyeProbability = info[0,0]\n",
    "        blinkProbability = info[0,1]\n",
    "        \n",
    "        #Save values for the current frame\n",
    "        df = df.append({'frameN':int(i+1),\n",
    "                  'pupilSize':np.sum(morphedMask)/255,\n",
    "                  'pupCntr_x':centroid[1],\n",
    "                  'pupCntr_y':centroid[0],\n",
    "                  'eyeProb':eyeProbability,\n",
    "                  'blinkProb':blinkProbability},\n",
    "                  ignore_index=True)\n",
    "        \n",
    "        if (i!=0) & (i%400==0) :\n",
    "            print('Processing frames... ({}/{})'.format(i,numFrames))\n",
    "finally:\n",
    "    cap.release()\n",
    "    winsound.Beep(BEEP_FREQ, BEEP_DURATION_MS)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "quarterly-cocktail",
   "metadata": {},
   "source": [
    "## Preprocessing of pupil size\n",
    "In the following section the estimated pupil size for the whole video will undergo two preprocessing steps:\n",
    "1. **Blink removal**: Blink events can generate artifacts in the pupil size prediction. We can correct for this by looking at the blink probability for each frame. Frames with a blink probability higher that a threshold (*BLINK_THRESH*) will be rejected and pupil size will be linearly interpolated between the points.\n",
    "2. **Curve smoothing**: Ofthen the video FrameRate is much higher than the typical timecourse of pupil dilations. The resulting pupil size signal can thus be filtered to increase the saliency of biological fluctuations and remove noise. We implemented a simple *moving median filter*. Users can select an appropiate window size (in frames).\n",
    "----\n",
    "You need to specify and eventually adjust 2 parameters:\n",
    "- **BLINK_THRESH**: Probability threshold for each frame to be classified as a blink\n",
    "- **MEDIAN_WINDOW**: Window size (in frames) for median filtering. (Usually between 300-900ms works)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "activated-father",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
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       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\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.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* 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",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// 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",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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",
       "        }\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",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\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, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home 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\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"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\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.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 = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\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",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"1008\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# EDIT PARAMETERS\n",
    "# ---------------------------------------------------\n",
    "BLINK_THRESH = 0.01\n",
    "MEDIAN_WINDOW = 7\n",
    "# ---------------------------------------------------\n",
    "\n",
    "%matplotlib notebook\n",
    "# Remove blinks and interpolate the curve\n",
    "isBlinking = df['blinkProb'] > BLINK_THRESH\n",
    "processedPupil = df['pupilSize']\n",
    "processedPupil[isBlinking] = np.nan\n",
    "processedPupil.interpolate(inplace=True)\n",
    "# Moving median filter\n",
    "processedPupil = processedPupil.rolling(MEDIAN_WINDOW,min_periods=1, center=True).median()\n",
    "df['processedPupil'] = processedPupil\n",
    "\n",
    "# Plotting\n",
    "f, ax = plt.subplots(figsize=(14,4))\n",
    "ax.plot(df['pupilSize'],label='Raw pupil')\n",
    "ax.plot(processedPupil, label='Preprocessed Pupil')\n",
    "ax.fill_between(df['frameN'], ax.get_ylim()[0], ax.get_ylim()[1],\n",
    "                where=isBlinking, interpolate=True,\n",
    "                facecolor='red', alpha=1,label='Blinking')\n",
    "ax.set_title('Pupil Area Preprocessing')\n",
    "ax.set_xlabel('Frame Number')\n",
    "ax.set_ylabel('Pupil Area (px)')\n",
    "ax.autoscale(enable=True, axis='x', tight=True)\n",
    "ax.legend(loc=0)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "owned-pierce",
   "metadata": {},
   "source": [
    "## Export data as a csv file\n",
    "The following section will export pupillometry data in a .CSV file.  \n",
    "By default the file will be saved in the same folder as the movie, with the same filename and `_pupil` appended at the end. If you wish to give a custom name to the output file, you can edit the parameter `CUSTOM_NAME`. Doing this will use this name as the output filename instead."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "id": "light-clinic",
   "metadata": {},
   "outputs": [],
   "source": [
    "# EDIT PARAMETERS\n",
    "# ---------------------------------------------------\n",
    "CUSTOM_NAME = []\n",
    "# ---------------------------------------------------\n",
    "\n",
    "path, fN = os.path.split(VIDEOPATH)\n",
    "fN, ext =  os.path.splitext(fN)\n",
    "fN = fN + '_pupil'\n",
    "\n",
    "if CUSTOM_NAME:\n",
    "    fN = CUSTOM_NAME\n",
    "\n",
    "newFileName = path + os.path.sep + fN + '.csv'\n",
    "df.to_csv(newFileName, index=False) # Export to csv file"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}