RL_05.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### RL Course by David Silver\n",
    "\n",
    "## Lecture 5 Model-Free Control\n",
    "\n",
    "- On-Policy Monte-Carlo Control\n",
    "- On-Policy Temporal-Difference Learing\n",
    "- Off-Policy Learning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "from mpl_toolkits.mplot3d import Axes3D"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1 Monte-Carlo Control\n",
    "\n",
    "<img src=\"img/04_MC control.png\" width=60%>\n",
    "\n",
    "采用$\\epsilon-greedy$方式学习的最终策略, 依然是一个$epsilon-greedy$的策略. 如何保证不会丢到一个更好的策略,同时当我们得到一个当前的最好策略不想继续探索的时候, 得到的这个策略是一个确定性策略,而不包含随机行为? 由此引出了GLIE的概念.\n",
    "\n",
    "GLIE(greedy in limit with Infinite Exploration)要求学习方法有两个条件\n",
    "- 充分探索: 当迭代次数趋向无穷时, 所有状态-动作对都被探索无数次\n",
    "- 最优收敛: 策略收敛在一个贪婪策略,不再具有随机性\n",
    "\n",
    "满足GLIE的方法, 就能够达到我们上述的学习目的. \n",
    "对于$\\epsilon-greedy$方法而言, 当$\\epsilon = \\frac{1}{k}$时, 就满足GLIE."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "def improve_greedy_policy(Q, epsilon, nA):\n",
    "    def policy(state):\n",
    "        prob = np.ones(nA) * epsilon / nA\n",
    "        prob[np.argmax(Q[state])] += 1 - epsilon\n",
    "        return prob\n",
    "    return policy\n",
    "\n",
    "def improve_glie_greedy_policy(Q, nA):\n",
    "    def policy(state, i_episode):\n",
    "        epsilon = 1. / (10 + i_episode/1000)\n",
    "        prob = np.ones(nA) * epsilon / nA\n",
    "        prob[np.argmax(Q[state])] += 1 - epsilon\n",
    "        return prob\n",
    "    return policy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# GLIE Monte-Carlo Control\n",
    "from collections import deque, Counter, defaultdict\n",
    "\n",
    "\n",
    "def GLIE_MC(MDP, episods, gamma = 1.):\n",
    "    '''GLIE Monte-Carlo control method. Use epsilon-greedy for improvement with a decent epsilon.\n",
    "    Params:\n",
    "        MDP: an instance of MDP\n",
    "        episods: number of episod\n",
    "        gamma: decay of reward\n",
    "    \n",
    "    Return:\n",
    "        Q, A defaultdict(np.ndarray)\n",
    "        Q[state][value]: the estimate expect of state-action pair\n",
    "    '''\n",
    "    N = defaultdict(lambda: np.zeros(MDP.action_space.n))\n",
    "    Q = defaultdict(lambda: np.zeros(MDP.action_space.n))\n",
    "    \n",
    "    for i_episod in range(1, episods+1):\n",
    "        if i_episod % 1000 == 0:\n",
    "            print(\"\\ri_episod:%d/%d\"%(i_episod, episods), end='')\n",
    "        episod = deque()\n",
    "        G = 0\n",
    "        s = MDP.reset()\n",
    "#         policy = improve_glie_greedy_policy(Q, MDP.action_space.n)\n",
    "        policy = improve_greedy_policy(Q, 0.1, MDP.action_space.n)\n",
    "        done = False\n",
    "        while not done: # run the simulation\n",
    "            prob = policy(s)\n",
    "#             prob = policy(s, i_episod)\n",
    "            a = np.random.choice(np.arange(len(prob)), p=prob)\n",
    "            s_n, r, done, _ = MDP.step(a)\n",
    "            episod.append((s, a, r))\n",
    "            s = s_n\n",
    "        while len(episod) != 0: # update value evaluation of every-visit\n",
    "            s, a, r = episod.pop()\n",
    "            G = r + gamma * G\n",
    "            N[s][a] += 1\n",
    "            Q[s][a] += (G - Q[s][a])/N[s][a]\n",
    "#         policy = improve_greedy_policy(Q, 1./i_episod, MDP.action_space.n) # update epsilon for descent.\n",
    "    return Q"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2 On-Policy TD Learning\n",
    "\n",
    "TD方法具有低方差, 在线学习, 可以学习不完整的序列的特点, 因此可以利用TD代替MC进行更有效的学习,在TD学习中, 同样使用Q作为估计值, 使用$\\epsilon-greedy$作为策略进行优化, 在每个时间步对Q值进行更新.\n",
    "\n",
    "TD的更新结构如下, 由其状态序列得名Sarsa\n",
    "<img src=\"img/sarsa_structure.png\">\n",
    "\n",
    "sarsa的算法流程如下:\n",
    "<img src=\"img/sarsa.png\">"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Sarsa Algorithm\n",
    "from collections import defaultdict\n",
    "\n",
    "def Sarsa(MDP, episods, gamma = 1, alpha = 0.1, epsilon = 0.3):\n",
    "    '''Sarsa Algorithm for On-policy Control\n",
    "    \n",
    "    Params:\n",
    "        MDP: an instance of MDP\n",
    "        episods: number of episod\n",
    "        gamma: decay of reward\n",
    "        alpha: parameter of TD-learning, learning rate\n",
    "        epsilon: parameter of epsilon-greedy\n",
    "        \n",
    "    Return:\n",
    "        Q, A defaultdict(np.ndarray)\n",
    "        Q[state][value]: the estimate expect of state-action pair\n",
    "    '''\n",
    "    Q = defaultdict(lambda: np.zeros(MDP.action_space.n))\n",
    "    policy = improve_greedy_policy(Q, epsilon, MDP.action_space.n)\n",
    "    step = 0\n",
    "    converge = []\n",
    "    step = 0\n",
    "    for i_episod in range(1, episods+1):\n",
    "        if i_episod % 100000 == 0:\n",
    "            print(\"\\ri_episod:%d/%d\"%(i_episod, episods), end=\"\")\n",
    "        s = MDP.reset()\n",
    "        done = False\n",
    "        prob = policy(s)\n",
    "        a = np.random.choice(np.arange(len(prob)), p = prob)\n",
    "        while not done:\n",
    "            step += 1\n",
    "            s_next, r, done, _ = MDP.step(a)\n",
    "            if not done:\n",
    "                prob = policy(s_next)\n",
    "                a_next = np.random.choice(np.arange(len(prob)), p = prob)\n",
    "                Q[s][a] += alpha * (r + gamma * Q[s_next][a_next] - Q[s][a])\n",
    "                s = s_next\n",
    "                a = a_next\n",
    "            else:\n",
    "                Q[s][a] += alpha * (r + gamma * 0 - Q[s][a]) # Q(terminate-state,.) = 0\n",
    "        converge.append(step)\n",
    "        step = 0\n",
    "    return Q, converge"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "有上一讲可知, TD(0)只学习了前一步的估值, 由此可以衍生出n-step的TD, 进而衍生出将0到n步状态估值结合的TD($\\lambda$). 前向的TD($\\lambda$)需要向MC一样知道后面的状态, 而后向的TD($\\lambda$)利用资格轨迹将当前步的TD Error向后传播,达到更新的目的, 以下是加入了后向传播的TD($\\lambda$)的sarsa($\\lambda$)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Sarsa(lambda) Algorithm\n",
    "from collections import defaultdict\n",
    "\n",
    "def Sarsa_lambda(MDP, episods, gamma = 1, alpha = 0.1, epsilon = 0.3, lamda = 0.5):\n",
    "    '''Sarsa Lambda with Backward view\n",
    "    \n",
    "    Params:\n",
    "        MDP: an instance of MDP\n",
    "        episods: number of episod\n",
    "        gamma: decay of reward\n",
    "        alpha: parameter of TD-learning, learning rate\n",
    "        epsilon: parameter of epsilon-greedy\n",
    "        lamda: parameter of sarsa lamda, the decay rate of n-step TD\n",
    "        \n",
    "    Return:\n",
    "        Q, A defaultdict(np.ndarray)\n",
    "        Q[state][value]: the estimate expect of state-action pair\n",
    "    '''\n",
    "    Q = defaultdict(lambda: np.zeros(MDP.action_space.n))\n",
    "    \n",
    "    policy = improve_greedy_policy(Q, epsilon, MDP.action_space.n)\n",
    "    converge = []\n",
    "    step = 0\n",
    "    for i_episod in range(1, episods+1):\n",
    "        E = defaultdict(lambda: np.zeros(MDP.action_space.n)) # eligibility trace\n",
    "        \n",
    "        if i_episod % 1000 == 0:\n",
    "            print(\"\\ri_episod:%d/%d\"%(i_episod, episods), end=\"\")\n",
    "        \n",
    "        s = MDP.reset()\n",
    "        done = False\n",
    "        prob = policy(s)\n",
    "        a = np.random.choice(np.arange(len(prob)), p = prob)\n",
    "        while not done:\n",
    "            step += 1\n",
    "            s_next, r, done, _ = MDP.step(a)\n",
    "            E[s][a] += 1\n",
    "            \n",
    "            if not done:\n",
    "                prob = policy(s_next)\n",
    "                a_next = np.random.choice(np.arange(len(prob)), p = prob)\n",
    "                td_error = r + gamma * Q[s_next][a_next] - Q[s][a]\n",
    "                \n",
    "                for state in E.keys():\n",
    "                    Q[state] += alpha * td_error * E[state]\n",
    "                    E[state] = E[state] * lamda\n",
    "                \n",
    "                s = s_next\n",
    "                a = a_next\n",
    "            else:\n",
    "                td_error = r + gamma * 0 - Q[s][a]\n",
    "                for state in E.keys():\n",
    "                    Q[state] += alpha * td_error * E[state]\n",
    "                    E[state] = E[state] * lamda\n",
    "        converge.append(step)\n",
    "        step = 0\n",
    "    return Q, converge"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3 Off-Policy Learning\n",
    "\n",
    "off-policy指的是通过$\\mu$策略(表现策略)与环境交互,得到S,A,R的序列作为经验, 利用经验评价和优化另一个策略$\\pi$的学习方式.\n",
    "\n",
    "off-policy的重要性:\n",
    "- 从人类经验或其他agent的经验学习和优化自己的策略\n",
    "- 重用旧的策略$\\pi_1$,$\\pi_2$,...,$\\pi_{t-1}$产生的经验\n",
    "- 从一个策略获取经验训练多个策略\n",
    "\n",
    "off-policy的可行性:\n",
    "- 通过重要性采样使用经验\n",
    "- 重要性采样是用于估计不同分布的期望的方法, 表示如下\n",
    "<img src=\"img/importance_sample.png\" width=60%>\n",
    "- 对Monte-Carlo方法使用重要性采样\n",
    "<img src=\"img/mc_is.png\">\n",
    "- 对TD-learning方法使用重要性采样\n",
    "<img src=\"img/td_is.png\">\n",
    "\n",
    "由式可见, 对于MC使用重要性采样,随着序列长度的增加, 方差会急剧增加, 使得采样结果有误甚至毫无意义. 但是对TD使用重要性采样, 只需要进行一次估计, 方差更低, 更有使用价值.\n",
    "\n",
    "### Q-learning\n",
    "- 不使用重要性采样\n",
    "- 使用基于Q值的$\\epsilon-greedy$进行探索\n",
    "- 使用greedy对Q进行优化\n",
    "- greedy策略和$\\epsilon-greedy$一起提高\n",
    "- intuition, 使用$\\epsilon-greedy$方法选择下一个动作, 到达$S'$后, 假设能够从$S'$选择最优的途径继续(即采用Q(S',.)的最大估计)作为更新q(s,a)的依据.\n",
    "<img src=\"img/q_learning_structure.png\">\n",
    "\n",
    "具体算法流程如下:\n",
    "<img src=\"img/Q_learning.png\">"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Q_learning Algorithm\n",
    "from collections import defaultdict\n",
    "\n",
    "def Q_Learning(MDP, episods, gamma = 1, alpha = 0.1, epsilon = 0.3):\n",
    "    '''Q_Learning Algorithm for Off-policy Control\n",
    "    \n",
    "    Params:\n",
    "        MDP: an instance of MDP\n",
    "        episods: number of episod\n",
    "        gamma: decay of reward\n",
    "        alpha: parameter of TD-learning, learning rate\n",
    "        epsilon: parameter of epsilon-greedy\n",
    "        \n",
    "    Return:\n",
    "        Q, A defaultdict(np.ndarray)\n",
    "        Q[state][value]: the estimate expect of state-action pair\n",
    "    '''\n",
    "    Q = defaultdict(lambda: np.zeros(MDP.action_space.n))\n",
    "    policy = improve_greedy_policy(Q, epsilon, MDP.action_space.n)\n",
    "    converge = []\n",
    "    step = 0\n",
    "    for i_episod in range(1, episods+1):\n",
    "        if i_episod % 1000 == 0:\n",
    "            print(\"\\ri_episod:%d/%d\"%(i_episod, episods), end=\"\")\n",
    "        \n",
    "        s = MDP.reset()\n",
    "        done = False\n",
    "        \n",
    "        while not done:\n",
    "            step += 1\n",
    "            prob = policy(s)\n",
    "            a = np.random.choice(np.arange(len(prob)), p = prob)\n",
    "            s_next, r, done, _ = MDP.step(a)\n",
    "            if not done:\n",
    "                Q[s][a] += alpha * (r + gamma * np.max(Q[s_next]) - Q[s][a])\n",
    "                s = s_next\n",
    "            else:\n",
    "                Q[s][a] += alpha * (r + 0 - Q[s][a]) # Q(terminate-state,.) = 0\n",
    "        converge.append(step)\n",
    "        step = 0\n",
    "    return Q, converge"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4 实验\n",
    "\n",
    "### 4.1 利用MC Control学习Blackjack中的最优策略"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(21, 2, True)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from lib.envs.blackjack import BlackjackEnv\n",
    "import matplotlib\n",
    "matplotlib.style.use('ggplot')\n",
    "\n",
    "def plot_bj_value_function(Q, title):\n",
    "    V = defaultdict(float)\n",
    "    for s in Q.keys():\n",
    "        V[s] = np.max(Q[s])\n",
    "    max_x = max(x[0] for x in V)\n",
    "    min_x = min(x[0] for x in V)\n",
    "    max_y = max(x[1] for x in V)\n",
    "    min_y = min(x[1] for x in V)\n",
    "    \n",
    "    x = np.arange(min_x, max_x+1)           # 生成 x 坐标，表示玩家此刻的点数\n",
    "    y = np.arange(min_y, max_y+1)             # 生成 y 坐标，表示庄家的明牌\n",
    "    X, Y = np.meshgrid(x, y)        # 生成 meshgrid\n",
    "    # 画图\n",
    "    Z_nace = np.apply_along_axis(lambda _: V[(_[0], _[1], False)], 2, np.dstack([X, Y]))\n",
    "    Z_ace = np.apply_along_axis(lambda _: V[(_[0], _[1], True)], 2, np.dstack([X, Y]))\n",
    "    fig = plt.figure()\n",
    "    ax1 = fig.add_subplot(211, projection='3d')\n",
    "    ax1.plot_surface(X, Y, Z_nace, cmap=matplotlib.cm.coolwarm, vmin=-1, vmax=1,rstride = 1 , cstride = 1)\n",
    "    ax1.view_init(ax1.elev, -120)\n",
    "    ax1.set_title(\"No usable ace\")\n",
    "    ax1.set_xlabel('Player\\'s point')\n",
    "    ax1.set_ylabel('Deal\\'s face-up card')\n",
    "    ax2 = fig.add_subplot(212, projection='3d')\n",
    "    ax2.plot_surface(X, Y, Z_ace, cmap=matplotlib.cm.coolwarm, vmin=-1, vmax=1,rstride = 1 , cstride = 1)\n",
    "    ax2.view_init(ax1.elev, -120)\n",
    "    ax2.set_title(\"Usable ace\")\n",
    "    ax2.set_xlabel('Player\\'s point')\n",
    "    ax2.set_ylabel('Deal\\'s face-up card')\n",
    "    fig.show()    \n",
    "\n",
    "def plot_policy(Q, tittle):\n",
    "    V = defaultdict(float)\n",
    "    for s in Q.keys():\n",
    "        V[s] = np.argmax(Q[s])\n",
    "    max_x = max(x[0] for x in V)\n",
    "    min_x = min(x[0] for x in V)\n",
    "    max_y = max(x[1] for x in V)\n",
    "    min_y = min(x[1] for x in V)\n",
    "    x = np.arange(min_x, max_x+1)\n",
    "    y = np.arange(min_y, max_y+1)\n",
    "    print('No Usable')\n",
    "    print('  ', end='')\n",
    "    for n in y:\n",
    "        print(n, end=' ')\n",
    "    print()\n",
    "    for m in x:\n",
    "        print(m, end=' ')\n",
    "        for n in y:\n",
    "            print('x' if V[(m, n, False)] == 1 else 'o', end=' ')\n",
    "        print()\n",
    "    print('\\nUsable')\n",
    "    print('  ', end='')\n",
    "    for n in y:\n",
    "        print(n, end=' ')\n",
    "    print()\n",
    "    for m in x:\n",
    "        print(m, end = ' ')\n",
    "        for n in y:\n",
    "            print('x' if V[(m, n, True)] == 1 else 'o', end=' ')\n",
    "        print()\n",
    "\n",
    "env = BlackjackEnv()\n",
    "env.reset()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "i_episod:500000/500000"
     ]
    }
   ],
   "source": [
    "Q_glie = GLIE_MC(env, 500000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
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       "\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": [
    "plot_bj_value_function(Q_glie, 'mc_100k')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No Usable\n",
      "  1 2 3 4 5 6 7 8 9 10 \n",
      "12 x o o o o x x x x x \n",
      "13 x o o o o o x x x x \n",
      "14 x o o x o o x x x x \n",
      "15 x o o o o o x x x x \n",
      "16 x o o o o o x x o o \n",
      "17 o o o o o o o o o o \n",
      "18 o o o o o o o o o o \n",
      "19 o o o o o o o o o o \n",
      "20 o o o o o o o o o o \n",
      "21 o o o o o o o o o o \n",
      "\n",
      "Usable\n",
      "  1 2 3 4 5 6 7 8 9 10 \n",
      "12 x x x x x o x x x x \n",
      "13 x x x x x x x x x x \n",
      "14 x x x x x x x x x x \n",
      "15 x x x x x x x x x x \n",
      "16 x x x x x x x x x x \n",
      "17 x o x x x x x x x x \n",
      "18 x o o o o o o o x x \n",
      "19 o o o o o o o o o o \n",
      "20 o o o o o o o o o o \n",
      "21 o o o o o o o o o o \n"
     ]
    }
   ],
   "source": [
    "plot_policy(Q_glie, 'title')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.2 利用sarsa学习blackjack"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "i_episod:1000000/1000000"
     ]
    }
   ],
   "source": [
    "Q_sarsa,_ = Sarsa(env, 1000000, epsilon = 0.1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "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\", \"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": [
    "plot_bj_value_function(Q_sarsa, 'sarsa_1kk')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No Usable\n",
      "  1 2 3 4 5 6 7 8 9 10 \n",
      "12 x x x x x x x x x x \n",
      "13 x o x o x x x x o x \n",
      "14 x o x o x x o x x x \n",
      "15 x x o o o o x x o x \n",
      "16 o o o x o o o x x o \n",
      "17 o o o o o o o o o o \n",
      "18 o o o o o o o o o o \n",
      "19 o o o o o o o o o o \n",
      "20 o o o o o o o o o o \n",
      "21 o o o o o o o o o o \n",
      "\n",
      "Usable\n",
      "  1 2 3 4 5 6 7 8 9 10 \n",
      "12 x x x x x x x x x x \n",
      "13 x x x x x x x x x x \n",
      "14 x x x x x x x x x x \n",
      "15 x x x x x o x x x x \n",
      "16 x x x x x x x x x x \n",
      "17 x x o x x x x x x x \n",
      "18 x o x x o x o o x x \n",
      "19 x x x o o o o o x x \n",
      "20 o o o o o o o o o o \n",
      "21 o o o o o o o o o o \n"
     ]
    }
   ],
   "source": [
    "plot_policy(Q_sarsa, 'sarsa_1kk')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "i_episod:100000/100000"
     ]
    }
   ],
   "source": [
    "Q_sarsa_lambda, _ = Sarsa_lambda(env, 100000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "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\", \"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": [
    "plot_bj_value_function(Q_sarsa_lambda, 'sarsa_lambda_100k')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No Usable\n",
      "  1 2 3 4 5 6 7 8 9 10 \n",
      "12 x o o o o x x x x x \n",
      "13 x o o x x o x x x x \n",
      "14 x o x x o x x o x x \n",
      "15 x x o x o o x x x o \n",
      "16 x x x o o o x x x x \n",
      "17 x o o o o o o o o o \n",
      "18 o o o o o o o o o o \n",
      "19 o o o o o o o o o o \n",
      "20 o o o o o o o o o o \n",
      "21 o o o o o o o o o o \n",
      "\n",
      "Usable\n",
      "  1 2 3 4 5 6 7 8 9 10 \n",
      "12 x x x x x x x x x x \n",
      "13 x x x x x x x x x x \n",
      "14 x o x x x x x x x x \n",
      "15 x o x x o x x x x x \n",
      "16 x x x x x o x x x x \n",
      "17 x x x x x x x x x x \n",
      "18 x o o o x o o x o x \n",
      "19 o o o o o o o o o o \n",
      "20 o o o o o o o o o o \n",
      "21 o o o o o o o o o o \n"
     ]
    }
   ],
   "source": [
    "plot_policy(Q_sarsa_lambda, 'sarsa_lambda')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.3 利用Q-learning 学习blackjack"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "i_episod:500000/500000"
     ]
    }
   ],
   "source": [
    "Q_ql,_ = Q_Learning(env, 500000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "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\", \"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>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_bj_value_function(Q_ql, 'q_learning_1kk')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No Usable\n",
      "  1 2 3 4 5 6 7 8 9 10 \n",
      "12 x o x o x x x o o x \n",
      "13 x o x o o x x x x x \n",
      "14 x o o x o x x x x x \n",
      "15 x o o o x x o x x o \n",
      "16 o o o o o o x x x x \n",
      "17 x o o o o o o o x o \n",
      "18 o o o o o o o o o o \n",
      "19 o o o o o o o o o o \n",
      "20 o o o o o o o o o o \n",
      "21 o o o o o o o o o o \n",
      "\n",
      "Usable\n",
      "  1 2 3 4 5 6 7 8 9 10 \n",
      "12 x x x x x x x x x x \n",
      "13 x x x x o x x x x x \n",
      "14 x x x x x x x x x x \n",
      "15 x x x x x x x x x x \n",
      "16 x x x x o x x x x x \n",
      "17 x x x x x x x o x x \n",
      "18 o o o o o x o o x x \n",
      "19 x x x o x o o o x x \n",
      "20 o o x o o o o o o o \n",
      "21 o o o o o o o o o o \n"
     ]
    }
   ],
   "source": [
    "plot_policy(Q_ql, 'qlearning')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4.4 Windy Gridworld Example\n",
    "\n",
    "通过该示例比较sarsa的学习速度\n",
    "\n",
    "**问题描述**\n",
    "\n",
    "- 当agent进入某个格子时， 会受到箭头方向的风，向箭头方向移动k格\n",
    "- agent不知边界的存在， 不知前后格之间相对关系， 不清楚起始点二维位置\n",
    "- 能够记住曾经在什么时间步经过某一个格子\n",
    "\n",
    "<img src=\"img/WindyGridWorld.png\">"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [],
   "source": [
    "from lib.envs.windy_gridworld import WindyGridworldEnv\n",
    "env = WindyGridworldEnv()\n",
    "def plot_convergence(convergence, title, fig=None, *arg):\n",
    "    if fig == None:\n",
    "        fig = plt.figure()\n",
    "        fig.clear()\n",
    "        fig.suptitle(title)\n",
    "        ax = fig.add_subplot(111)\n",
    "    else:\n",
    "        ax = fig.add_subplot(arg[0])\n",
    "    x = np.arange(0, len(convergence))\n",
    "    y = np.asarray(convergence)\n",
    "    ax.plot(x, y)\n",
    "    ax.set_xlabel(\"Num of episodes\")\n",
    "    ax.set_ylabel(\"Steps per episode\")\n",
    "    ax.set_title(\"Convergence\")\n",
    "\n",
    "def plot_step(convergence, title, fig = None, *arg):\n",
    "    arr = np.array(convergence).cumsum(0)\n",
    "    z = np.zeros(arr[-1])\n",
    "    arr_i = 0\n",
    "    for i in range(z.size):\n",
    "        if i < arr[arr_i]:\n",
    "            z[i] = arr_i\n",
    "        else:\n",
    "            arr_i += 1\n",
    "            z[i] = arr_i\n",
    "    if fig is None:\n",
    "        fig = plt.figure()\n",
    "        fig.suptitle(title)\n",
    "        ax = fig.add_subplot(111)\n",
    "    else:\n",
    "        ax = fig.add_subplot(arg[0])\n",
    "    ax.plot(np.arange(z.size), z)\n",
    "    ax.set_xlabel(\"Time Step\")\n",
    "    ax.set_ylabel(\"Episodes\")\n",
    "    ax.set_title(\"Episodes per step\")\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [],
   "source": [
    "Q, converge0 = Sarsa(env, 200, epsilon=0.1)\n",
    "Q, converge1 = Sarsa_lambda(env, 200, epsilon=0.1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {
    "scrolled": false
   },
   "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=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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"
    },
    {
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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig =plt.figure(figsize = (8,4))\n",
    "fig.suptitle('sarsa')\n",
    "plot_convergence(converge0, 'sarsa', fig, 121)\n",
    "plot_step(converge0, 'sarsa', fig, 122)\n",
    "fig1 = plt.figure(figsize = (8,4))\n",
    "fig1.suptitle('sarsa_lambda')\n",
    "plot_convergence(converge1, 'sarsa', fig1, 121)\n",
    "plot_step(converge1, 'sarsa', fig1, 122)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
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