pixel-shuffle.ipynb

{
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# pixel-shuffle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# pixel-shuffle lets you rearrange the pixels of one image to create another image\n",
    "# Copyright (C) 2021  Rishi Advani\n",
    "\n",
    "# This program is free software: you can redistribute it and/or modify\n",
    "# it under the terms of the GNU General Public License as published by\n",
    "# the Free Software Foundation, either version 3 of the License, or\n",
    "# (at your option) any later version.\n",
    "\n",
    "# This program is distributed in the hope that it will be useful,\n",
    "# but WITHOUT ANY WARRANTY; without even the implied warranty of\n",
    "# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n",
    "# GNU General Public License for more details.\n",
    "\n",
    "# You should have received a copy of the GNU General Public License\n",
    "# along with this program.  If not, see <https://www.gnu.org/licenses/>."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from PIL import Image\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import animation\n",
    "import scipy\n",
    "from scipy import optimize\n",
    "import numpy as np\n",
    "from tqdm.notebook import trange, tqdm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "rng = np.random.default_rng()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "skeleton_filename = \"woman.jpg\"\n",
    "filler_filename = \"chameleon.jpg\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "skel_img = Image.open(\"input/\" + skeleton_filename)\n",
    "fill_img = Image.open(\"input/\" + filler_filename)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "dims = skel_img.size\n",
    "fill_img = fill_img.resize(dims)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "skel_arr = np.asarray(skel_img)\n",
    "fill_arr = np.asarray(fill_img)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "rows, cols, _ = skel_arr.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## generate pixel shuffle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "precision = 5000  # default to 5000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "total_pixels = skel_arr.size\n",
    "\n",
    "import math\n",
    "O = int(math.sqrt(total_pixels / precision))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "r = rows // O\n",
    "c = cols // O\n",
    "        \n",
    "cost_matrix = np.empty((r,c,r,c))"
   ]
  },
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   "execution_count": 12,
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "for i in trange(r):\n",
    "    for j in trange(c, leave=False):\n",
    "        avg_skel = np.average(skel_arr[i*O:i*O+O, j*O:j*O+O], axis=(0,1))\n",
    "        for i2 in range(r):\n",
    "            for j2 in range(c):\n",
    "                avg_fill = np.average(fill_arr[i2*O:i2*O+O, j2*O:j2*O+O], axis=(0,1))\n",
    "                cost_matrix[i,j,i2,j2] = np.linalg.norm(avg_fill - avg_skel)\n",
    "\n",
    "\n",
    "temp = cost_matrix.reshape(r, c, r*c).transpose(2,0,1).reshape(r*c, r*c).transpose(1,0)\n",
    "_, col_ind = optimize.linear_sum_assignment(temp)\n",
    "\n",
    "coords = col_ind.reshape(r,c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "final_arr = np.full((rows, cols, 3), 255, dtype=int)\n",
    "\n",
    "for i in range(r):\n",
    "    for j in range(c):\n",
    "        temp = coords[i,j]\n",
    "        i2 = temp // c\n",
    "        j2 = temp % c\n",
    "        \n",
    "        final_arr[i*O:i*O+O, j*O:j*O+O] = fill_arr[i2*O:i2*O+O, j2*O:j2*O+O].copy()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### set up interpolation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "interp_mode = \"fixed\"  # default to \"fixed\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "if interp_mode == \"prop\" or interp_mode == \"dissolve\":\n",
    "    interp_coef = 50\n",
    "    interp_arrs = np.full((interp_coef, rows, cols, 3), 255, dtype=int)\n",
    "    interp_domain = np.linspace(0, 1, num=interp_coef)\n",
    "\n",
    "    for k, val in enumerate(tqdm(interp_domain)):\n",
    "        for i in range(r):\n",
    "            for j in range(c):\n",
    "                temp = coords[i,j]\n",
    "                i2 = temp // c\n",
    "                j2 = temp % c\n",
    "\n",
    "                if interp_mode == \"prop\":\n",
    "                    i3 = int(i * (val) + i2 * (1-val))\n",
    "                    j3 = int(j * (val) + j2 * (1-val))\n",
    "                    interp_arrs[k, i3*O:i3*O+O, j3*O:j3*O+O] = fill_arr[i2*O:i2*O+O, j2*O:j2*O+O].copy()\n",
    "\n",
    "                elif interp_mode == \"dissolve\":\n",
    "                    i3 = int(i * (1 - val) + i2 * val)\n",
    "                    j3 = int(j * (1 - val) + j2 * val)\n",
    "                    interp_arrs[k, i*O:i*O+O, j*O:j*O+O] = fill_arr[i3*O:i3*O+O, j3*O:j3*O+O].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
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   "source": [
    "if interp_mode == \"fixed\":\n",
    "    interp_coef = 0\n",
    "    interp_arrs = []\n",
    "    \n",
    "    curr_locs = np.zeros((r, c), dtype=int)\n",
    "    for i in range(r):\n",
    "        for j in range(c):\n",
    "            curr_locs[i,j] = coords[i,j]\n",
    "    \n",
    "    flag = True\n",
    "    while flag:\n",
    "        flag = False\n",
    "        \n",
    "        arr = np.full((rows, cols, 3), 255, dtype=int)\n",
    "        \n",
    "        occupied = np.zeros((r, c), dtype=bool)\n",
    "        \n",
    "        for i in range(r):\n",
    "            for j in range(c):\n",
    "                temp = coords[i,j]\n",
    "                i4 = temp // c\n",
    "                j4 = temp % c\n",
    "                \n",
    "                temp = curr_locs[i,j]\n",
    "                i2 = temp // c\n",
    "                j2 = temp % c\n",
    "                \n",
    "                # record old position\n",
    "                i3 = i2\n",
    "                j3 = j2\n",
    "                \n",
    "                # move towards target\n",
    "                if i < i2:\n",
    "                    i2 -= 1\n",
    "                elif i > i2:\n",
    "                    i2 += 1\n",
    "                if j < j2:\n",
    "                    j2 -= 1\n",
    "                elif j > j2:\n",
    "                    j2 += 1\n",
    "                \n",
    "                if (i2 != i) or (j2 != j):  # not all pixels have reached target\n",
    "                    flag = True\n",
    "                \n",
    "                curr_locs[i,j] = i2 * c + j2\n",
    "                occupied[i2,j2] = True\n",
    "                \n",
    "                arr[i2*O:i2*O+O, j2*O:j2*O+O] = fill_arr[i4*O:i4*O+O, j4*O:j4*O+O].copy()\n",
    "                \n",
    "                if not occupied[i3,j3]:\n",
    "                    arr[i3*O:i3*O+O, j3*O:j3*O+O] = 255\n",
    "        \n",
    "        interp_arrs.append(arr)\n",
    "        interp_coef += 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## display results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "# %matplotlib inline\n",
    "# plt.imshow(skel_arr);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# %matplotlib inline\n",
    "# plt.imshow(fill_arr);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "plt.imshow(final_arr);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_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",
       "    if (this.ratio !== 1) {\n",
       "        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n",
       "    }\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",
       "    var resizeObserver = new 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 (width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    resizeObserver.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",
       "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.one(\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",
       "\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",
       "    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": {
      "text/html": [
       "<img src=\"data:,\" width=\"0\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "fig = plt.figure()\n",
    "\n",
    "ims = []\n",
    "\n",
    "# start delay\n",
    "for _ in range(20):\n",
    "    im = plt.imshow(fill_arr, animated=True)\n",
    "    ims.append([im])\n",
    "\n",
    "# core animation\n",
    "for k in range(interp_coef):\n",
    "    im = plt.imshow(interp_arrs[k], animated=True)\n",
    "    ims.append([im])\n",
    "\n",
    "# end delay\n",
    "for _ in range(20):\n",
    "    im = plt.imshow(final_arr, animated=True)\n",
    "    ims.append([im])\n",
    "\n",
    "\n",
    "ani = animation.ArtistAnimation(fig, ims, interval=30, repeat_delay=10, blit=True)\n",
    "\n",
    "plt.axis(\"off\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "from datetime import datetime\n",
    "\n",
    "datetime_obj = datetime.now()\n",
    "timestamp = datetime_obj.strftime(\"%Y-%m-%d_%H-%M-%S\")\n",
    "output_filename = \"output/pixel-shuffle_\" + timestamp + \".gif\"\n",
    "\n",
    "ani.save(output_filename, writer=\"pillow\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:test]",
   "language": "python",
   "name": "conda-env-test-py"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.1"
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