{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import functools\n",
    "\n",
    "import matplotlib\n",
    "from matplotlib import pyplot\n",
    "import numpy as np\n",
    "\n",
    "import sys\n",
    "sys.path.append(\"..\")\n",
    "from hiora_cartpole import features\n",
    "from hiora_cartpole import fourier_fa\n",
    "from hiora_cartpole import easytile_fa\n",
    "from hiora_cartpole import driver\n",
    "\n",
    "import gym_ext.tools as gym_tools\n",
    "\n",
    "import gym"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[2016-09-23 13:07:02,758] Making new env: CartPole-v0\n"
     ]
    }
   ],
   "source": [
    "env = gym.make('CartPole-v0')\n",
    "clipped_high        = env.observation_space.high\n",
    "clipped_high = np.array([2.5, 3.6, 0.27, 3.7])\n",
    "clipped_low         = -clipped_high\n",
    "state_ranges = np.array([clipped_low, clipped_high])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Tile coding"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "easyt_n_weights, easyt_feature_vec = easytile_fa.make_feature_vec(state_ranges, 2, [5, 7, 5, 7], 8)\n",
    "\n",
    "#fv = feature_vec(cartpole.observation_space.sample(), cartpole.action_space.sample())\n",
    "\n",
    "from hiora_cartpole import linfa\n",
    "eexperience = linfa.init(lmbda=0.9,\n",
    "                        init_alpha=0.05,\n",
    "                        epsi=0.01,\n",
    "                        feature_vec=easyt_feature_vec,\n",
    "                        n_weights=easyt_n_weights,\n",
    "                        act_space=env.action_space,\n",
    "                        theta=None,\n",
    "                        is_use_alpha_bounds=True,\n",
    "                        map_obs=functools.partial(gym_tools.warning_clip_obs, ranges=state_ranges))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZQAAAEACAYAAACUMoD1AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nf0rxeJiGSqL1AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9c4610b410>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "eexperience, steps_per_episode, alpha_per_episode \\\n",
    "    = driver.train(env, linfa, eexperience, n_episodes=700, max_steps=500, is_render=False)\n",
    "# Credits: http://matplotlib.org/examples/api/two_scales.html\n",
    "fig, ax1 = pyplot.subplots()\n",
    "ax1.plot(steps_per_episode, color='b')\n",
    "ax2 = ax1.twinx()\n",
    "ax2.plot(alpha_per_episode, color='r')\n",
    "pyplot.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "steps_per_episode = driver.exec_greedy(env, eexperience, n_episodes=15, max_steps=600, is_render=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('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",
       "            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",
       "        this.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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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;\n",
       "    var y = canvas_pos.y;\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 overriden (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",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "pyplot.plot(eexperience.theta)\n",
    "pyplot.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "eexperience.p_feat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "eexperience, steps_per_episode, alpha_per_episode \\\n",
    "    = driver.train(env, linfa, eexperience, n_episodes=50, max_steps=100, is_render=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sarsa with Fourier basis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "four_n_weights, four_feature_vec \\\n",
    "    = fourier_fa.make_feature_vec(state_ranges,\n",
    "                                  n_acts=2,\n",
    "                                  order=3)\n",
    "\n",
    "#fv = feature_vec(cartpole.observation_space.sample(), cartpole.action_space.sample())\n",
    "\n",
    "from hiora_cartpole import linfa\n",
    "fexperience = linfa.init(lmbda=0.9,\n",
    "                        init_alpha=0.001,\n",
    "                        epsi=0.1,\n",
    "                        feature_vec=four_feature_vec,\n",
    "                        n_weights=four_n_weights,\n",
    "                        act_space=env.action_space,\n",
    "                        theta=None,\n",
    "                        is_use_alpha_bounds=True,\n",
    "                        map_obs=functools.partial(gym_tools.warning_clip_obs, ranges=state_ranges))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('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",
       "            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",
       "        this.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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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;\n",
       "    var y = canvas_pos.y;\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 overriden (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",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fexperience, steps_per_episode, alpha_per_episode \\\n",
    "    = driver.train(env, linfa, fexperience, n_episodes=700, max_steps=500, is_render=False)\n",
    "# Credits: http://matplotlib.org/examples/api/two_scales.html\n",
    "fig, ax1 = pyplot.subplots()\n",
    "ax1.plot(steps_per_episode, color='b')\n",
    "ax2 = ax1.twinx()\n",
    "ax2.plot(alpha_per_episode, color='r')\n",
    "pyplot.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Haha, this just explodes after 30 or so episodes and doesn't diverge, at least not before 700 episodes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "pyplot.plot(fexperience.theta)\n",
    "pyplot.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-100-4b4073f3b212>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0msteps_per_episode\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdriver\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexec_greedy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0menv\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfexperience\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn_episodes\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmax_steps\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m600\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mis_render\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/home/erle/repos/cartpole/hiora_cartpole/driver.py\u001b[0m in \u001b[0;36mexec_greedy\u001b[0;34m(env, experience, n_episodes, max_steps, is_render)\u001b[0m\n\u001b[1;32m     84\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     85\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mt\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mxrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmax_steps\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 86\u001b[0;31m             \u001b[0mis_render\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0menv\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrender\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# pylint: disable=expression-not-assigned\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     87\u001b[0m             \u001b[0maction\u001b[0m                  \u001b[0;34m=\u001b[0m \u001b[0mgreedy_act\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mexperience\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobservation\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     88\u001b[0m             \u001b[0mobservation\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0m_\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0m_\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0menv\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstep\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0maction\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/home/erle/.local/lib/python2.7/site-packages/gym/core.pyc\u001b[0m in \u001b[0;36mrender\u001b[0;34m(self, mode, close)\u001b[0m\n\u001b[1;32m    190\u001b[0m             \u001b[0;32mraise\u001b[0m \u001b[0merror\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mUnsupportedMode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Unsupported rendering mode: {}. (Supported modes for {}: {})'\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmode\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmodes\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    191\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 192\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_render\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmode\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmode\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mclose\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mclose\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    193\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    194\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mclose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/home/erle/.local/lib/python2.7/site-packages/gym/envs/classic_control/cartpole.pyc\u001b[0m in \u001b[0;36m_render\u001b[0;34m(self, mode, close)\u001b[0m\n\u001b[1;32m    147\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpoletrans\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_rotation\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    148\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 149\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mviewer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrender\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreturn_rgb_array\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmode\u001b[0m\u001b[0;34m==\u001b[0m\u001b[0;34m'rgb_array'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/home/erle/.local/lib/python2.7/site-packages/gym/envs/classic_control/rendering.pyc\u001b[0m in \u001b[0;36mrender\u001b[0;34m(self, return_rgb_array)\u001b[0m\n\u001b[1;32m     80\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mrender\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mreturn_rgb_array\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     81\u001b[0m         \u001b[0mglClearColor\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 82\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwindow\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclear\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     83\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwindow\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mswitch_to\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     84\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwindow\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdispatch_events\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/home/erle/.local/lib/python2.7/site-packages/pyglet/window/__init__.pyc\u001b[0m in \u001b[0;36mclear\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m   1149\u001b[0m         \u001b[0mbuffer\u001b[0m\u001b[0;34m.\u001b[0m  \u001b[0mThe\u001b[0m \u001b[0mwindow\u001b[0m \u001b[0mmust\u001b[0m \u001b[0mbe\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mactive\u001b[0m \u001b[0mcontext\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0msee\u001b[0m \u001b[0;34m`\u001b[0m\u001b[0mswitch_to\u001b[0m\u001b[0;34m`\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1150\u001b[0m         '''\n\u001b[0;32m-> 1151\u001b[0;31m         \u001b[0mgl\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mglClear\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgl\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mGL_COLOR_BUFFER_BIT\u001b[0m \u001b[0;34m|\u001b[0m \u001b[0mgl\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mGL_DEPTH_BUFFER_BIT\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1152\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1153\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mdispatch_event\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/home/erle/.local/lib/python2.7/site-packages/pyglet/gl/lib.pyc\u001b[0m in \u001b[0;36merrcheck\u001b[0;34m(result, func, arguments)\u001b[0m\n\u001b[1;32m     82\u001b[0m     \u001b[0;32mpass\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     83\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 84\u001b[0;31m \u001b[0;32mdef\u001b[0m \u001b[0merrcheck\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0marguments\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     85\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0m_debug_gl_trace\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     86\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "steps_per_episode = driver.exec_greedy(env, fexperience, n_episodes=10, max_steps=600, is_render=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Q-learning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "qfour_n_weights, qfour_feature_vec \\\n",
    "    = fourier_fa.make_feature_vec(state_ranges,\n",
    "                                  n_acts=2,\n",
    "                                  order=3)\n",
    "\n",
    "#fv = feature_vec(cartpole.observation_space.sample(), cartpole.action_space.sample())\n",
    "\n",
    "from hiora_cartpole import linfa\n",
    "qfexperience = linfa.init(lmbda=0.9,\n",
    "                        init_alpha=0.001,\n",
    "                        epsi=0.1,\n",
    "                        feature_vec=qfour_feature_vec,\n",
    "                        n_weights=qfour_n_weights,\n",
    "                        act_space=env.action_space,\n",
    "                        theta=None,\n",
    "                        is_use_alpha_bounds=True,\n",
    "                        map_obs=functools.partial(gym_tools.warning_clip_obs, ranges=state_ranges),\n",
    "                        choose_action=linfa.choose_action_Q)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('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",
       "            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",
       "        this.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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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;\n",
       "    var y = canvas_pos.y;\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 overriden (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",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "qfexperience, steps_per_episode, alpha_per_episode \\\n",
    "    = driver.train(env, linfa, qfexperience, n_episodes=300, max_steps=500, is_render=False)\n",
    "# Credits: http://matplotlib.org/examples/api/two_scales.html\n",
    "fig, ax1 = pyplot.subplots()\n",
    "ax1.plot(steps_per_episode, color='b')\n",
    "ax2 = ax1.twinx()\n",
    "ax2.plot(alpha_per_episode, color='r')\n",
    "pyplot.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "steps_per_episode = driver.exec_greedy(env, qfexperience, n_episodes=10, max_steps=600, is_render=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('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",
       "            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",
       "        this.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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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;\n",
       "    var y = canvas_pos.y;\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 overriden (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",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = pyplot.subplots()\n",
    "ax.plot(qfexperience.theta)\n",
    "pyplot.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12+"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}