05.1 Trees and Forests.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Trees and Forests"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "from preamble import *"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Decision Tree Classification\n",
    "==================\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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       "/* 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",
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       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
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       "    this.imageObj.onunload = function() {\n",
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       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
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       "\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",
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       "\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>"
      ]
     },
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     "output_type": "display_data"
    },
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from plots import plot_tree_interactive\n",
    "plot_tree_interactive()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Random Forests"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from plots import plot_forest_interactive\n",
    "plot_forest_interactive()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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"
    },
    {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7fae5c55d278>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.datasets import make_moons\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "X, y = make_moons(n_samples=100, noise=0.25, random_state=3)\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, stratify=y, random_state=42)\n",
    "\n",
    "forest = RandomForestClassifier(n_estimators=5, random_state=2)\n",
    "forest.fit(X_train, y_train)\n",
    "\n",
    "fig, axes = plt.subplots(2, 3, figsize=(20, 10))\n",
    "for i, (ax, tree) in enumerate(zip(axes.ravel(), forest.estimators_)):\n",
    "    ax.set_title(\"tree %d\" % i)\n",
    "    mglearn.plots.plot_tree_partition(X_train, y_train, tree, ax=ax)\n",
    "mglearn.plots.plot_2d_separator(forest, X_train, fill=True, ax=axes[-1, -1], alpha=.4)\n",
    "axes[-1, -1].set_title(\"random forest\")\n",
    "plt.scatter(X_train[:, 0], X_train[:, 1], c=y_train, s=60, cmap=mglearn.cm2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Selecting the Optimal Estimator via Cross-Validation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GridSearchCV(cv=5, error_score='raise',\n",
       "       estimator=RandomForestRegressor(bootstrap=True, criterion='mse', max_depth=None,\n",
       "           max_features='auto', max_leaf_nodes=None, min_samples_leaf=1,\n",
       "           min_samples_split=2, min_weight_fraction_leaf=0.0,\n",
       "           n_estimators=200, n_jobs=-1, oob_score=False, random_state=None,\n",
       "           verbose=0, warm_start=False),\n",
       "       fit_params={}, iid=True, n_jobs=1,\n",
       "       param_grid={'max_depth': [5, 7, 9], 'max_features': ['sqrt', 'log2']},\n",
       "       pre_dispatch='2*n_jobs', refit=True, scoring=None, verbose=0)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.datasets import load_boston\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "\n",
    "boston = load_boston()\n",
    "X, y = boston.data, boston.target\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)\n",
    "\n",
    "rf = RandomForestRegressor(n_estimators=200, n_jobs=-1)\n",
    "parameters = {'max_features':['sqrt', 'log2'],\n",
    "              'max_depth':[5, 7, 9]}\n",
    "\n",
    "grid = GridSearchCV(rf, parameters, cv=5)\n",
    "grid.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.97946287860156334"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grid.score(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.71472766354731021"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grid.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.078,  0.014,  0.081,  0.007,  0.068,  0.287,  0.036,  0.056,\n",
       "        0.011,  0.048,  0.084,  0.026,  0.203])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grid.best_estimator_.feature_importances_"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# Exercises\n",
    "Compare training and test performance of the decision tree (``sklearn.tree.DecisionTreeRegressor``) and random forest on the bike dataset.\n",
    "What is the effect of changing ``max_depth`` to training and test set score?\n",
    "How do the feature importances of trees and forest differ?\n",
    "Use ``mglearn.tools.get_tree`` to visualize a decision tree."
   ]
  }
 ],
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