train.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "IPython.OutputArea.prototype._should_scroll = function(lines) {\n",
       "    return false;\n",
       "}"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%javascript\n",
    "IPython.OutputArea.prototype._should_scroll = function(lines) {\n",
    "    return false;\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "try:\n",
    "    import _pickle as cPickle\n",
    "except:\n",
    "    import cPickle\n",
    "import cv2\n",
    "import tensorflow as tf\n",
    "import os, time, sys, math, random\n",
    "from IPython.display import display, clear_output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib\n",
    "%matplotlib notebook\n",
    "from matplotlib import pyplot as plt\n",
    "plt.rcParams['figure.figsize'] = (16, 9)\n",
    "plt.style.use('ggplot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def weight_variable(shape):\n",
    "    initial = tf.truncated_normal(shape, stddev=0.1)\n",
    "    return tf.Variable(initial)\n",
    "\n",
    "def bias_variable(length):\n",
    "    initial = tf.constant(0.1, shape=[length], dtype=tf.float32)\n",
    "    return tf.Variable(initial)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def createConvulationalLayer(input_data, channel_count, filter_size, filter_count, max_pooling=True):\n",
    "    shape = [filter_size, filter_size, channel_count, filter_count]\n",
    "    weights = weight_variable(shape=shape)\n",
    "    bias = bias_variable(length=filter_count)\n",
    "    layer = tf.nn.conv2d(input=input_data,\n",
    "                         filter=weights,\n",
    "                         strides=[1, 1, 1, 1],\n",
    "                         padding='SAME')\n",
    "    layer += bias\n",
    "    if max_pooling:\n",
    "        layer = tf.nn.max_pool(value=layer,\n",
    "                               ksize=[1, 2, 2, 1],\n",
    "                               strides=[1, 2, 2, 1],\n",
    "                               padding='SAME')\n",
    "        layer = tf.layers.dropout(layer, rate=0.25)\n",
    "    layer = tf.nn.relu(layer)\n",
    "    return layer, weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def createFlattenLayer(layer):\n",
    "    layer_shape = layer.get_shape()\n",
    "    # layer_shape is assumed to be in shape [number_of_images, image_height, image_width, channels]\n",
    "    # The channels will be the number of fiter_count in the previous layer\n",
    "    feature_count = layer_shape[1:4].num_elements()\n",
    "    # layer_shape[1:4].num_elements()\n",
    "    flat_layer = tf.reshape(layer, [-1, feature_count])\n",
    "    return flat_layer, feature_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def createFullyConnectedLayer(input_data, input_feature_count, output_feature_count, apply_relu=False):\n",
    "    weights = weight_variable(shape=[input_feature_count, output_feature_count])\n",
    "    bias = bias_variable(length=output_feature_count)\n",
    "    layer = tf.matmul(input_data, weights) + bias\n",
    "    if apply_relu:\n",
    "        layer = tf.nn.relu(layer)\n",
    "    return layer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def splitFilenameAndAngle(row):\n",
    "    filename_and_angle = row.strip().split(',')[0].split()\n",
    "    result = [filename_and_angle[0], (float(filename_and_angle[1]) * math.pi) / 180]\n",
    "    return result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def readDataSetInfo(dataset_id='01'):\n",
    "    info_data = ''\n",
    "    info_data_dict = {}\n",
    "    dataset_path = os.path.join('data', 'dataset_' + dataset_id)\n",
    "    info_file_path = os.path.join(dataset_path, 'data.txt')\n",
    "    xs = []\n",
    "    ys = []\n",
    "    with open(info_file_path, 'r') as f:\n",
    "        for line in f.readlines():\n",
    "            filename_and_angle = line.strip().split(',')[0].split()\n",
    "            x, y = filename_and_angle[0], (float(filename_and_angle[1]) * math.pi) / 180\n",
    "            xs.append(x)\n",
    "            ys.append(y)\n",
    "    \n",
    "    together = list(zip(xs, ys))\n",
    "    \n",
    "    random.shuffle(together)\n",
    "    filenames, angles = zip(*together)\n",
    "    \n",
    "    info_data_dict['path'] = dataset_path\n",
    "    info_data_dict['filenames'] = filenames\n",
    "    info_data_dict['angles'] = angles\n",
    "    return info_data_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def readImages(dataset_info, limit=10000, batch_size=40):\n",
    "    image_data_list = []\n",
    "    rotation_data_list = []\n",
    "    for index, filename in enumerate(dataset_info['filenames']):\n",
    "        image_path = os.path.join(data_info['path'], 'images', filename)\n",
    "        image_data = cv2.imread(image_path)\n",
    "        image_data = cv2.resize(image_data, (0,0), fx=0.4, fy=0.4)\n",
    "        image_data_list.append(image_data)\n",
    "        rotation_data_list.append(dataset_info['angles'][index])\n",
    "        if len(image_data_list) == batch_size:\n",
    "            if batch_size == 1:\n",
    "                image_data_list, rotation_data_list = image_data_list[0], rotation_data_list[0]\n",
    "            yield np.array(image_data_list), np.array(rotation_data_list).reshape(-1, 1)\n",
    "            image_data_list = []\n",
    "            rotation_data_list = []\n",
    "        \n",
    "    if image_data_list:\n",
    "        yield np.array(image_data_list), np.array(rotation_data_list).reshape(-1, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "def preprocessData(x):\n",
    "    mu = np.mean(x, axis=(0, 1, 2), keepdims=1)\n",
    "    sigma = np.std(x, axis=(0, 1, 2), keepdims=1)\n",
    "    x = x - mu\n",
    "    x = x / sigma\n",
    "    return x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_info = readDataSetInfo()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = None\n",
    "b = None\n",
    "for x, y in readImages(data_info):\n",
    "    a = preprocessData(x)\n",
    "    b = y\n",
    "    break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(40, 102, 182, 3)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "sample_image, sample_rotation = readImages(data_info, batch_size=1).next()\n",
    "# plt.imshow(a[3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(102, 182, 3)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sample_image.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "image_height = sample_image.shape[0]\n",
    "image_width = sample_image.shape[1]\n",
    "image_depth = sample_image.shape[2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "55692"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "image_height * image_width * image_depth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "filter_size_2 = 2\n",
    "filter_size_3 = 3\n",
    "filter_size_5 = 5\n",
    "filter_count_24 = 24\n",
    "filter_count_32 = 32\n",
    "filter_count_36 = 36\n",
    "filter_count_48 = 48\n",
    "filter_count_64 = 64\n",
    "filter_count_128 = 128\n",
    "\n",
    "fully_conn_layer_1_out_size = 100\n",
    "fully_conn_layer_2_out_size = 50\n",
    "fully_conn_layer_3_out_size = 10\n",
    "fully_conn_layer_4_out_size = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = tf.placeholder(tf.float32, shape=[None, image_height, image_width, image_depth])\n",
    "y_actual = tf.placeholder(tf.float32, shape=(None, 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "conv_layer_1, conv_weights_1 = createConvulationalLayer(input_data=x,\n",
    "                   channel_count=image_depth,\n",
    "                   filter_size=filter_size_5,\n",
    "                   filter_count=filter_count_24,\n",
    "                   max_pooling=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "conv_layer_2, conv_weights_2 = createConvulationalLayer(input_data=conv_layer_1,\n",
    "                   channel_count=filter_count_24,\n",
    "                   filter_size=filter_size_5,\n",
    "                   filter_count=filter_count_36,\n",
    "                   max_pooling=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "conv_layer_3, conv_weights_3 = createConvulationalLayer(input_data=conv_layer_2,\n",
    "                   channel_count=filter_count_36,\n",
    "                   filter_size=filter_size_5,\n",
    "                   filter_count=filter_count_48,\n",
    "                   max_pooling=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "conv_layer_4, conv_weights_4 = createConvulationalLayer(input_data=conv_layer_3,\n",
    "                   channel_count=filter_count_48,\n",
    "                   filter_size=filter_size_3,\n",
    "                   filter_count=filter_count_64,\n",
    "                   max_pooling=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "conv_layer_5, conv_weights_5 = createConvulationalLayer(input_data=conv_layer_4,\n",
    "                   channel_count=filter_count_64,\n",
    "                   filter_size=filter_size_3,\n",
    "                   filter_count=filter_count_64,\n",
    "                   max_pooling=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "flat_layer, num_features = createFlattenLayer(conv_layer_5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "fully_con_layer_1 = createFullyConnectedLayer(input_data=flat_layer,\n",
    "                         input_feature_count=num_features,\n",
    "                         output_feature_count=fully_conn_layer_1_out_size,\n",
    "                         apply_relu=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "fully_con_layer_2 = createFullyConnectedLayer(input_data=fully_con_layer_1,\n",
    "                         input_feature_count=fully_conn_layer_1_out_size,\n",
    "                         output_feature_count=fully_conn_layer_2_out_size,\n",
    "                         apply_relu=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "fully_con_layer_3 = createFullyConnectedLayer(input_data=fully_con_layer_2,\n",
    "                         input_feature_count=fully_conn_layer_2_out_size,\n",
    "                         output_feature_count=fully_conn_layer_3_out_size,\n",
    "                         apply_relu=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "fully_con_layer_4 = createFullyConnectedLayer(input_data=fully_con_layer_3,\n",
    "                         input_feature_count=fully_conn_layer_3_out_size,\n",
    "                         output_feature_count=fully_conn_layer_4_out_size,\n",
    "                         apply_relu=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_predicted = fully_con_layer_4 # tf.nn.softmax(fully_con_layer_4)\n",
    "cross_entropy = tf.reduce_mean(tf.square(tf.subtract(y_actual, y_predicted)))\n",
    "# cross_entropy = tf.reduce_mean(-tf.reduce_sum(y_actual * tf.log(y_predicted), reduction_indices=[1]))\n",
    "optimizer = tf.train.AdamOptimizer(1e-4).minimize(cross_entropy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "is_correct = tf.equal(tf.argmax(y_predicted, 1), tf.argmax(y_actual, 1))\n",
    "accuracy = tf.reduce_mean(tf.cast(is_correct, tf.float32))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "epochs = 20\n",
    "session = tf.Session(config=tf.ConfigProto(log_device_placement=True))\n",
    "init = tf.global_variables_initializer()\n",
    "session.run(init)\n",
    "\n",
    "highest_test_accuracy = 0\n",
    "highest_train_accuracy = 0\n",
    "train_ac, test_ac = 0, 0\n",
    "training_done = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "def draw(fig, ax, entropy):    \n",
    "    ax.clear()\n",
    "    ax.plot(entropy)\n",
    "    fig.canvas.draw()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"1600\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 0\n",
      "Iteration 1\n",
      "Iteration 2\n",
      "Iteration 3\n",
      "Iteration 4\n",
      "Iteration 5\n",
      "Iteration 6\n",
      "Iteration 7\n",
      "Iteration 8\n",
      "Iteration 9\n",
      "Iteration 10\n",
      "Iteration 11\n",
      "Iteration 12\n",
      "Iteration 13\n",
      "Iteration 14\n",
      "Iteration 15\n",
      "Iteration 16\n",
      "Iteration 17\n",
      "Iteration 18\n",
      "Iteration 19\n",
      "Training done in 331.087612 mins\n"
     ]
    }
   ],
   "source": [
    "start_time = time.time()\n",
    "entropy = []\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "plt.ion()\n",
    "\n",
    "fig.show()\n",
    "fig.canvas.draw()\n",
    "\n",
    "for i in range(epochs):\n",
    "    counter = 0\n",
    "    if training_done:\n",
    "        break\n",
    "    for batch_X, batch_Y in readImages(data_info, batch_size=10):\n",
    "        batch_X = preprocessData(batch_X)\n",
    "        train_data = {x: batch_X, y_actual: batch_Y}\n",
    "        \n",
    "        # Training Step\n",
    "        session.run(optimizer, feed_dict=train_data)\n",
    "        \n",
    "        entropy_value = session.run(cross_entropy, feed_dict=train_data)\n",
    "        \n",
    "#         if counter % 500 == 0:\n",
    "#             clear_output(wait=True)\n",
    "#             display('Iteration '+str(i)+ ' Batch counter ' + str(counter) + ' Entropy: '+ str(entropy_value))\n",
    "#         counter += 1\n",
    "        \n",
    "    if not np.isnan(entropy_value):\n",
    "        entropy.append(entropy_value)\n",
    "        draw(fig, ax, entropy)\n",
    "        print('Iteration '+str(i))\n",
    "        \n",
    "print(\"Training done in %f mins\"%((time.time() - start_time)/60))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = os.path.join(os.getcwd(), 'model')\n",
    "if not os.path.exists(model):\n",
    "    os.makedirs(model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model saved in path: /home/amit/notebooks/self-driving/model/model.ckpt\n"
     ]
    }
   ],
   "source": [
    "flag = True\n",
    "if flag or raw_input('Do you want to save this model ? (y/n)').strip() == 'y':\n",
    "    saver = tf.train.Saver()\n",
    "    save_path = saver.save(session, os.path.join(model, \"model.ckpt\"))\n",
    "    print(\"Model saved in path: %s\" % save_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.15rc1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}