Navigation.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Project: Banana Navigation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Select Device Type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-10T15:54:51.229126Z",
     "start_time": "2018-10-10T15:54:51.054055Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "device(type='cuda', index=0)"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import torch\n",
    "device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n",
    "#device = torch.device(\"cpu\")\n",
    "device"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create UnityEnvironment\n",
    "Create Unity Environment If you have a Linux environment, create an environment without a screen."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-10T16:27:37.383707Z",
     "start_time": "2018-10-10T16:27:36.994043Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:unityagents:\n",
      "'Academy' started successfully!\n",
      "Unity Academy name: Academy\n",
      "        Number of Brains: 1\n",
      "        Number of External Brains : 1\n",
      "        Lesson number : 0\n",
      "        Reset Parameters :\n",
      "\t\t\n",
      "Unity brain name: BananaBrain\n",
      "        Number of Visual Observations (per agent): 0\n",
      "        Vector Observation space type: continuous\n",
      "        Vector Observation space size (per agent): 37\n",
      "        Number of stacked Vector Observation: 1\n",
      "        Vector Action space type: discrete\n",
      "        Vector Action space size (per agent): 4\n",
      "        Vector Action descriptions: , , , \n"
     ]
    }
   ],
   "source": [
    "from unityagents import UnityEnvironment\n",
    "import numpy as np\n",
    "import platform\n",
    "\n",
    "if platform.system() == 'Linux':\n",
    "    env = UnityEnvironment(file_name=\"./Banana_Linux_NoVis/Banana.x86_64\")\n",
    "elif platform.system() == 'Darwin':\n",
    "    env = UnityEnvironment(file_name=\"Banana.app\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-10T16:27:41.168249Z",
     "start_time": "2018-10-10T16:27:41.165910Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('BananaBrain', <unityagents.brain.BrainParameters at 0x7f1c791d99e8>)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get the default brain\n",
    "brain_name = env.brain_names[0]\n",
    "brain = env.brains[brain_name]\n",
    "\n",
    "brain_name, brain"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-10T16:27:43.046671Z",
     "start_time": "2018-10-10T16:27:42.991597Z"
    },
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of agents: 1\n",
      "Number of actions: 4\n",
      "States look like: [1.         0.         0.         0.         0.84408134 0.\n",
      " 0.         1.         0.         0.0748472  0.         1.\n",
      " 0.         0.         0.25755    1.         0.         0.\n",
      " 0.         0.74177343 0.         1.         0.         0.\n",
      " 0.25854847 0.         0.         1.         0.         0.09355672\n",
      " 0.         1.         0.         0.         0.31969345 0.\n",
      " 0.        ]\n",
      "States have length: 37\n"
     ]
    }
   ],
   "source": [
    "# reset the environment\n",
    "env_info = env.reset(train_mode=True)[brain_name]\n",
    "\n",
    "# number of agents in the environment\n",
    "print('Number of agents:', len(env_info.agents))\n",
    "\n",
    "# number of actions\n",
    "action_size = brain.vector_action_space_size\n",
    "print('Number of actions:', action_size)\n",
    "\n",
    "# examine the state space \n",
    "state = env_info.vector_observations[0]\n",
    "print('States look like:', state)\n",
    "state_size = len(state)\n",
    "print('States have length:', state_size)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Implementation DQN\n",
    "\n",
    "Execute learning or agent according to DQN algorithm. Run basic DQN or Dueling DQN by `agent` value\n",
    "If the average score exceeds 13, the network weight value is stored in torch.save."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-10T16:50:28.945601Z",
     "start_time": "2018-10-10T16:50:28.935553Z"
    }
   },
   "outputs": [],
   "source": [
    "from collections import deque\n",
    "import torch\n",
    "\n",
    "def dqn(agent, \n",
    "        n_episodes=4000, max_t=1000, \n",
    "        eps_start=1.0, eps_end=0.01, eps_decay=0.999, \n",
    "        train=True, checkpoint_filename='checkpoint.pth'):\n",
    "    \"\"\"Deep Q-Learning.\n",
    "    \n",
    "    Args\n",
    "        agent (str): agent type\n",
    "        n_episodes (int): maximum number of training episodes\n",
    "        max_t (int): maximum number of timesteps per episode\n",
    "        eps_start (float): starting value of epsilon, for epsilon-greedy action selection\n",
    "        eps_end (float): minimum value of epsilon\n",
    "        eps_decay (float): multiplicative factor (per episode) for decreasing epsilon\n",
    "        train (bool): flag deciding if the agent will train or just play through the episode\n",
    "        checkpoint_filename (str): filename of checkpoint\n",
    "    \"\"\"\n",
    "    scores = []                        # list containing scores from each episode\n",
    "    scores_window = deque(maxlen=100)  # last 100 scores\n",
    "    eps = eps_start                    # initialize epsilon\n",
    "    for i_episode in range(1, n_episodes+1):\n",
    "        env_info = env.reset(train_mode=train)[brain_name]\n",
    "        state = env_info.vector_observations[0]\n",
    "        score = 0\n",
    "        \n",
    "        for t in range(max_t):\n",
    "            action = agent.act(state, eps if train else 0.0)\n",
    "            env_info = env.step(action)[brain_name]\n",
    "            next_state = env_info.vector_observations[0]   # get the next state\n",
    "            reward = env_info.rewards[0]                   # get the reward\n",
    "            done = env_info.local_done[0]                  # see if episode has finished\n",
    "            if train:\n",
    "                agent.step(state, action, reward, next_state, done)\n",
    "            score += reward                                # update the score\n",
    "            state = next_state                             # roll over the state to next time step\n",
    "            if done:                                       # exit loop if episode finished\n",
    "                break\n",
    "        \n",
    "        scores_window.append(score)       # save most recent score\n",
    "        scores.append(score)              # save most recent score\n",
    "        eps = max(eps_end, eps_decay*eps) # decrease epsilon\n",
    "        \n",
    "        print('\\rEpisode {}\\tAverage Score: {:.2f}'.format(i_episode, np.mean(scores_window)), end=\"\")\n",
    "        if i_episode % 100 == 0:\n",
    "            print('\\rEpisode {}\\tAverage Score: {:.2f}'.format(i_episode, np.mean(scores_window)))\n",
    "            \n",
    "        if np.mean(scores_window) >= 13.0 and train:\n",
    "            print('\\nEnvironment solved in {:d} episodes!\\tAverage Score: {:.2f}'.format(\n",
    "                i_episode-100, \n",
    "                np.mean(scores_window)\n",
    "            ))\n",
    "            torch.save(agent.qnetwork_local.state_dict(), checkpoint_filename)\n",
    "            break\n",
    "            \n",
    "    return scores"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Train agent with Basic DQN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Episode 100\tAverage Score: 0.18\n",
      "Episode 200\tAverage Score: 0.50\n",
      "Episode 300\tAverage Score: 1.42\n",
      "Episode 400\tAverage Score: 2.33\n",
      "Episode 500\tAverage Score: 3.19\n",
      "Episode 600\tAverage Score: 4.05\n",
      "Episode 700\tAverage Score: 5.60\n",
      "Episode 800\tAverage Score: 6.35\n",
      "Episode 900\tAverage Score: 7.29\n",
      "Episode 1000\tAverage Score: 8.16\n",
      "Episode 1100\tAverage Score: 8.58\n",
      "Episode 1400\tAverage Score: 9.642\n",
      "Episode 1500\tAverage Score: 10.49\n",
      "Episode 1600\tAverage Score: 10.17\n",
      "Episode 1700\tAverage Score: 11.01\n",
      "Episode 1800\tAverage Score: 11.11\n",
      "Episode 1900\tAverage Score: 11.04\n",
      "Episode 2000\tAverage Score: 10.78\n",
      "Episode 2100\tAverage Score: 11.11\n",
      "Episode 2200\tAverage Score: 12.78\n",
      "Episode 2300\tAverage Score: 12.28\n",
      "Episode 2400\tAverage Score: 12.60\n",
      "Episode 2438\tAverage Score: 13.01\n",
      "Environment solved in 2338 episodes!\tAverage Score: 13.01\n"
     ]
    }
   ],
   "source": [
    "from agent import Agent\n",
    "from model import *\n",
    "qnet_agent = Agent(network_type=QNetwork.net_type,\n",
    "                  state_size=state_size, \n",
    "                  action_size=action_size, \n",
    "                  seed=0,\n",
    "                  device=device)\n",
    "qnet_scores = dqn(qnet_agent, n_episodes=4000, train=True, checkpoint_filename='qnetwork_checkpoint.pth')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Train agent with Dueling DQN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "start_time": "2018-10-10T16:50:30.114Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Episode 100\tAverage Score: -0.01\n",
      "Episode 200\tAverage Score: 0.591\n",
      "Episode 300\tAverage Score: 1.29\n",
      "Episode 400\tAverage Score: 1.72\n",
      "Episode 500\tAverage Score: 2.65\n",
      "Episode 600\tAverage Score: 4.27\n",
      "Episode 700\tAverage Score: 5.37\n",
      "Episode 800\tAverage Score: 6.06\n",
      "Episode 900\tAverage Score: 6.46\n",
      "Episode 1000\tAverage Score: 7.73\n",
      "Episode 1100\tAverage Score: 7.74\n",
      "Episode 1200\tAverage Score: 7.95\n",
      "Episode 1300\tAverage Score: 9.32\n",
      "Episode 1400\tAverage Score: 9.930\n",
      "Episode 1500\tAverage Score: 10.76\n",
      "Episode 1600\tAverage Score: 12.05\n",
      "Episode 1700\tAverage Score: 10.76\n",
      "Episode 1800\tAverage Score: 11.27\n",
      "Episode 1900\tAverage Score: 11.63\n",
      "Episode 2000\tAverage Score: 11.86\n",
      "Episode 2100\tAverage Score: 12.63\n",
      "Episode 2200\tAverage Score: 12.97\n",
      "Episode 2204\tAverage Score: 13.02\n",
      "Environment solved in 2104 episodes!\tAverage Score: 13.02\n"
     ]
    }
   ],
   "source": [
    "from agent import Agent\n",
    "from model import *\n",
    "duel_agent = Agent(network_type=DuelingQNetwork.net_type,\n",
    "                  state_size=state_size, \n",
    "                  action_size=action_size, \n",
    "                  seed=0,\n",
    "                  device=device)\n",
    "duel_scores = dqn(duel_agent, n_episodes=4000, train=True, checkpoint_filename='duel_checkpoint.pth')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
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       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
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       "    }\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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        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": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib notebook\n",
    "\n",
    "# plot the scores\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "plt.plot(np.arange(len(qnet_scores)), qnet_scores)\n",
    "plt.ylabel('QNetwork Score')\n",
    "plt.xlabel('Episode #')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-10T16:23:58.147170Z",
     "start_time": "2018-10-10T16:23:58.089675Z"
    }
   },
   "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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        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=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib notebook\n",
    "\n",
    "# plot the dueling network scores\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "plt.plot(np.arange(len(duel_scores)), duel_scores)\n",
    "plt.ylabel('Dueling QNetowrk Score')\n",
    "plt.xlabel('Episode #')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Run Trained Agent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-10T16:50:21.839332Z",
     "start_time": "2018-10-10T16:49:32.339203Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Episode 100\tAverage Score: 14.29\n"
     ]
    }
   ],
   "source": [
    "from agent import Agent\n",
    "from model import *\n",
    "agent = Agent(network_type=QNetwork.net_type,\n",
    "              state_size=state_size,\n",
    "              action_size=action_size, \n",
    "              seed=0,\n",
    "              device=device,\n",
    "              checkpoint_filename='qnetwork_checkpoint.pth')\n",
    "\n",
    "scores = dqn(agent, n_episodes=100, train=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Close environment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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