1  {
   2   "cells": [
   3    {
   4     "cell_type": "markdown",
   5     "metadata": {},
   6     "source": [
   7      "---\n",
   8      "\n",
   9      "_You are currently looking at **version 1.0** of this notebook. To download notebooks and datafiles, as well as get help on Jupyter notebooks in the Coursera platform, visit the [Jupyter Notebook FAQ](https://www.coursera.org/learn/python-machine-learning/resources/bANLa) course resource._\n",
  10      "\n",
  11      "---"
  12     ]
  13    },
  14    {
  15     "cell_type": "markdown",
  16     "metadata": {
  17      "collapsed": true
  18     },
  19     "source": [
  20      "# Applied Machine Learning: Module 4 (Supervised Learning, Part II)"
  21     ]
  22    },
  23    {
  24     "cell_type": "markdown",
  25     "metadata": {},
  26     "source": [
  27      "## Preamble and Datasets"
  28     ]
  29    },
  30    {
  31     "cell_type": "code",
  32     "execution_count": 1,
  33     "metadata": {
  34      "collapsed": false,
  35      "scrolled": false
  36     },
  37     "outputs": [
  38      {
  39       "data": {
  40        "application/javascript": [
  41         "/* Put everything inside the global mpl namespace */\n",
  42         "window.mpl = {};\n",
  43         "\n",
  44         "\n",
  45         "mpl.get_websocket_type = function() {\n",
  46         "    if (typeof(WebSocket) !== 'undefined') {\n",
  47         "        return WebSocket;\n",
  48         "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
  49         "        return MozWebSocket;\n",
  50         "    } else {\n",
  51         "        alert('Your browser does not have WebSocket support.' +\n",
  52         "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
  53         "              'Firefox 4 and 5 are also supported but you ' +\n",
  54         "              'have to enable WebSockets in about:config.');\n",
  55         "    };\n",
  56         "}\n",
  57         "\n",
  58         "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
  59         "    this.id = figure_id;\n",
  60         "\n",
  61         "    this.ws = websocket;\n",
  62         "\n",
  63         "    this.supports_binary = (this.ws.binaryType != undefined);\n",
  64         "\n",
  65         "    if (!this.supports_binary) {\n",
  66         "        var warnings = document.getElementById(\"mpl-warnings\");\n",
  67         "        if (warnings) {\n",
  68         "            warnings.style.display = 'block';\n",
  69         "            warnings.textContent = (\n",
  70         "                \"This browser does not support binary websocket messages. \" +\n",
  71         "                    \"Performance may be slow.\");\n",
  72         "        }\n",
  73         "    }\n",
  74         "\n",
  75         "    this.imageObj = new Image();\n",
  76         "\n",
  77         "    this.context = undefined;\n",
  78         "    this.message = undefined;\n",
  79         "    this.canvas = undefined;\n",
  80         "    this.rubberband_canvas = undefined;\n",
  81         "    this.rubberband_context = undefined;\n",
  82         "    this.format_dropdown = undefined;\n",
  83         "\n",
  84         "    this.image_mode = 'full';\n",
  85         "\n",
  86         "    this.root = $('<div/>');\n",
  87         "    this._root_extra_style(this.root)\n",
  88         "    this.root.attr('style', 'display: inline-block');\n",
  89         "\n",
  90         "    $(parent_element).append(this.root);\n",
  91         "\n",
  92         "    this._init_header(this);\n",
  93         "    this._init_canvas(this);\n",
  94         "    this._init_toolbar(this);\n",
  95         "\n",
  96         "    var fig = this;\n",
  97         "\n",
  98         "    this.waiting = false;\n",
  99         "\n",
 100         "    this.ws.onopen =  function () {\n",
 101         "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
 102         "            fig.send_message(\"send_image_mode\", {});\n",
 103         "            if (mpl.ratio != 1) {\n",
 104         "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
 105         "            }\n",
 106         "            fig.send_message(\"refresh\", {});\n",
 107         "        }\n",
 108         "\n",
 109         "    this.imageObj.onload = function() {\n",
 110         "            if (fig.image_mode == 'full') {\n",
 111         "                // Full images could contain transparency (where diff images\n",
 112         "                // almost always do), so we need to clear the canvas so that\n",
 113         "                // there is no ghosting.\n",
 114         "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
 115         "            }\n",
 116         "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
 117         "        };\n",
 118         "\n",
 119         "    this.imageObj.onunload = function() {\n",
 120         "        this.ws.close();\n",
 121         "    }\n",
 122         "\n",
 123         "    this.ws.onmessage = this._make_on_message_function(this);\n",
 124         "\n",
 125         "    this.ondownload = ondownload;\n",
 126         "}\n",
 127         "\n",
 128         "mpl.figure.prototype._init_header = function() {\n",
 129         "    var titlebar = $(\n",
 130         "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
 131         "        'ui-helper-clearfix\"/>');\n",
 132         "    var titletext = $(\n",
 133         "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
 134         "        'text-align: center; padding: 3px;\"/>');\n",
 135         "    titlebar.append(titletext)\n",
 136         "    this.root.append(titlebar);\n",
 137         "    this.header = titletext[0];\n",
 138         "}\n",
 139         "\n",
 140         "\n",
 141         "\n",
 142         "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
 143         "\n",
 144         "}\n",
 145         "\n",
 146         "\n",
 147         "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
 148         "\n",
 149         "}\n",
 150         "\n",
 151         "mpl.figure.prototype._init_canvas = function() {\n",
 152         "    var fig = this;\n",
 153         "\n",
 154         "    var canvas_div = $('<div/>');\n",
 155         "\n",
 156         "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
 157         "\n",
 158         "    function canvas_keyboard_event(event) {\n",
 159         "        return fig.key_event(event, event['data']);\n",
 160         "    }\n",
 161         "\n",
 162         "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
 163         "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
 164         "    this.canvas_div = canvas_div\n",
 165         "    this._canvas_extra_style(canvas_div)\n",
 166         "    this.root.append(canvas_div);\n",
 167         "\n",
 168         "    var canvas = $('<canvas/>');\n",
 169         "    canvas.addClass('mpl-canvas');\n",
 170         "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
 171         "\n",
 172         "    this.canvas = canvas[0];\n",
 173         "    this.context = canvas[0].getContext(\"2d\");\n",
 174         "\n",
 175         "    var backingStore = this.context.backingStorePixelRatio ||\n",
 176         "\tthis.context.webkitBackingStorePixelRatio ||\n",
 177         "\tthis.context.mozBackingStorePixelRatio ||\n",
 178         "\tthis.context.msBackingStorePixelRatio ||\n",
 179         "\tthis.context.oBackingStorePixelRatio ||\n",
 180         "\tthis.context.backingStorePixelRatio || 1;\n",
 181         "\n",
 182         "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
 183         "\n",
 184         "    var rubberband = $('<canvas/>');\n",
 185         "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
 186         "\n",
 187         "    var pass_mouse_events = true;\n",
 188         "\n",
 189         "    canvas_div.resizable({\n",
 190         "        start: function(event, ui) {\n",
 191         "            pass_mouse_events = false;\n",
 192         "        },\n",
 193         "        resize: function(event, ui) {\n",
 194         "            fig.request_resize(ui.size.width, ui.size.height);\n",
 195         "        },\n",
 196         "        stop: function(event, ui) {\n",
 197         "            pass_mouse_events = true;\n",
 198         "            fig.request_resize(ui.size.width, ui.size.height);\n",
 199         "        },\n",
 200         "    });\n",
 201         "\n",
 202         "    function mouse_event_fn(event) {\n",
 203         "        if (pass_mouse_events)\n",
 204         "            return fig.mouse_event(event, event['data']);\n",
 205         "    }\n",
 206         "\n",
 207         "    rubberband.mousedown('button_press', mouse_event_fn);\n",
 208         "    rubberband.mouseup('button_release', mouse_event_fn);\n",
 209         "    // Throttle sequential mouse events to 1 every 20ms.\n",
 210         "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
 211         "\n",
 212         "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
 213         "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
 214         "\n",
 215         "    canvas_div.on(\"wheel\", function (event) {\n",
 216         "        event = event.originalEvent;\n",
 217         "        event['data'] = 'scroll'\n",
 218         "        if (event.deltaY < 0) {\n",
 219         "            event.step = 1;\n",
 220         "        } else {\n",
 221         "            event.step = -1;\n",
 222         "        }\n",
 223         "        mouse_event_fn(event);\n",
 224         "    });\n",
 225         "\n",
 226         "    canvas_div.append(canvas);\n",
 227         "    canvas_div.append(rubberband);\n",
 228         "\n",
 229         "    this.rubberband = rubberband;\n",
 230         "    this.rubberband_canvas = rubberband[0];\n",
 231         "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
 232         "    this.rubberband_context.strokeStyle = \"#000000\";\n",
 233         "\n",
 234         "    this._resize_canvas = function(width, height) {\n",
 235         "        // Keep the size of the canvas, canvas container, and rubber band\n",
 236         "        // canvas in synch.\n",
 237         "        canvas_div.css('width', width)\n",
 238         "        canvas_div.css('height', height)\n",
 239         "\n",
 240         "        canvas.attr('width', width * mpl.ratio);\n",
 241         "        canvas.attr('height', height * mpl.ratio);\n",
 242         "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
 243         "\n",
 244         "        rubberband.attr('width', width);\n",
 245         "        rubberband.attr('height', height);\n",
 246         "    }\n",
 247         "\n",
 248         "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
 249         "    // upon first draw.\n",
 250         "    this._resize_canvas(600, 600);\n",
 251         "\n",
 252         "    // Disable right mouse context menu.\n",
 253         "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
 254         "        return false;\n",
 255         "    });\n",
 256         "\n",
 257         "    function set_focus () {\n",
 258         "        canvas.focus();\n",
 259         "        canvas_div.focus();\n",
 260         "    }\n",
 261         "\n",
 262         "    window.setTimeout(set_focus, 100);\n",
 263         "}\n",
 264         "\n",
 265         "mpl.figure.prototype._init_toolbar = function() {\n",
 266         "    var fig = this;\n",
 267         "\n",
 268         "    var nav_element = $('<div/>')\n",
 269         "    nav_element.attr('style', 'width: 100%');\n",
 270         "    this.root.append(nav_element);\n",
 271         "\n",
 272         "    // Define a callback function for later on.\n",
 273         "    function toolbar_event(event) {\n",
 274         "        return fig.toolbar_button_onclick(event['data']);\n",
 275         "    }\n",
 276         "    function toolbar_mouse_event(event) {\n",
 277         "        return fig.toolbar_button_onmouseover(event['data']);\n",
 278         "    }\n",
 279         "\n",
 280         "    for(var toolbar_ind in mpl.toolbar_items) {\n",
 281         "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
 282         "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
 283         "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
 284         "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
 285         "\n",
 286         "        if (!name) {\n",
 287         "            // put a spacer in here.\n",
 288         "            continue;\n",
 289         "        }\n",
 290         "        var button = $('<button/>');\n",
 291         "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
 292         "                        'ui-button-icon-only');\n",
 293         "        button.attr('role', 'button');\n",
 294         "        button.attr('aria-disabled', 'false');\n",
 295         "        button.click(method_name, toolbar_event);\n",
 296         "        button.mouseover(tooltip, toolbar_mouse_event);\n",
 297         "\n",
 298         "        var icon_img = $('<span/>');\n",
 299         "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
 300         "        icon_img.addClass(image);\n",
 301         "        icon_img.addClass('ui-corner-all');\n",
 302         "\n",
 303         "        var tooltip_span = $('<span/>');\n",
 304         "        tooltip_span.addClass('ui-button-text');\n",
 305         "        tooltip_span.html(tooltip);\n",
 306         "\n",
 307         "        button.append(icon_img);\n",
 308         "        button.append(tooltip_span);\n",
 309         "\n",
 310         "        nav_element.append(button);\n",
 311         "    }\n",
 312         "\n",
 313         "    var fmt_picker_span = $('<span/>');\n",
 314         "\n",
 315         "    var fmt_picker = $('<select/>');\n",
 316         "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
 317         "    fmt_picker_span.append(fmt_picker);\n",
 318         "    nav_element.append(fmt_picker_span);\n",
 319         "    this.format_dropdown = fmt_picker[0];\n",
 320         "\n",
 321         "    for (var ind in mpl.extensions) {\n",
 322         "        var fmt = mpl.extensions[ind];\n",
 323         "        var option = $(\n",
 324         "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
 325         "        fmt_picker.append(option)\n",
 326         "    }\n",
 327         "\n",
 328         "    // Add hover states to the ui-buttons\n",
 329         "    $( \".ui-button\" ).hover(\n",
 330         "        function() { $(this).addClass(\"ui-state-hover\");},\n",
 331         "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
 332         "    );\n",
 333         "\n",
 334         "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
 335         "    nav_element.append(status_bar);\n",
 336         "    this.message = status_bar[0];\n",
 337         "}\n",
 338         "\n",
 339         "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
 340         "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
 341         "    // which will in turn request a refresh of the image.\n",
 342         "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
 343         "}\n",
 344         "\n",
 345         "mpl.figure.prototype.send_message = function(type, properties) {\n",
 346         "    properties['type'] = type;\n",
 347         "    properties['figure_id'] = this.id;\n",
 348         "    this.ws.send(JSON.stringify(properties));\n",
 349         "}\n",
 350         "\n",
 351         "mpl.figure.prototype.send_draw_message = function() {\n",
 352         "    if (!this.waiting) {\n",
 353         "        this.waiting = true;\n",
 354         "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
 355         "    }\n",
 356         "}\n",
 357         "\n",
 358         "\n",
 359         "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
 360         "    var format_dropdown = fig.format_dropdown;\n",
 361         "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
 362         "    fig.ondownload(fig, format);\n",
 363         "}\n",
 364         "\n",
 365         "\n",
 366         "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
 367         "    var size = msg['size'];\n",
 368         "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
 369         "        fig._resize_canvas(size[0], size[1]);\n",
 370         "        fig.send_message(\"refresh\", {});\n",
 371         "    };\n",
 372         "}\n",
 373         "\n",
 374         "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
 375         "    var x0 = msg['x0'] / mpl.ratio;\n",
 376         "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
 377         "    var x1 = msg['x1'] / mpl.ratio;\n",
 378         "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
 379         "    x0 = Math.floor(x0) + 0.5;\n",
 380         "    y0 = Math.floor(y0) + 0.5;\n",
 381         "    x1 = Math.floor(x1) + 0.5;\n",
 382         "    y1 = Math.floor(y1) + 0.5;\n",
 383         "    var min_x = Math.min(x0, x1);\n",
 384         "    var min_y = Math.min(y0, y1);\n",
 385         "    var width = Math.abs(x1 - x0);\n",
 386         "    var height = Math.abs(y1 - y0);\n",
 387         "\n",
 388         "    fig.rubberband_context.clearRect(\n",
 389         "        0, 0, fig.canvas.width, fig.canvas.height);\n",
 390         "\n",
 391         "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
 392         "}\n",
 393         "\n",
 394         "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
 395         "    // Updates the figure title.\n",
 396         "    fig.header.textContent = msg['label'];\n",
 397         "}\n",
 398         "\n",
 399         "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
 400         "    var cursor = msg['cursor'];\n",
 401         "    switch(cursor)\n",
 402         "    {\n",
 403         "    case 0:\n",
 404         "        cursor = 'pointer';\n",
 405         "        break;\n",
 406         "    case 1:\n",
 407         "        cursor = 'default';\n",
 408         "        break;\n",
 409         "    case 2:\n",
 410         "        cursor = 'crosshair';\n",
 411         "        break;\n",
 412         "    case 3:\n",
 413         "        cursor = 'move';\n",
 414         "        break;\n",
 415         "    }\n",
 416         "    fig.rubberband_canvas.style.cursor = cursor;\n",
 417         "}\n",
 418         "\n",
 419         "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
 420         "    fig.message.textContent = msg['message'];\n",
 421         "}\n",
 422         "\n",
 423         "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
 424         "    // Request the server to send over a new figure.\n",
 425         "    fig.send_draw_message();\n",
 426         "}\n",
 427         "\n",
 428         "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
 429         "    fig.image_mode = msg['mode'];\n",
 430         "}\n",
 431         "\n",
 432         "mpl.figure.prototype.updated_canvas_event = function() {\n",
 433         "    // Called whenever the canvas gets updated.\n",
 434         "    this.send_message(\"ack\", {});\n",
 435         "}\n",
 436         "\n",
 437         "// A function to construct a web socket function for onmessage handling.\n",
 438         "// Called in the figure constructor.\n",
 439         "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
 440         "    return function socket_on_message(evt) {\n",
 441         "        if (evt.data instanceof Blob) {\n",
 442         "            /* FIXME: We get \"Resource interpreted as Image but\n",
 443         "             * transferred with MIME type text/plain:\" errors on\n",
 444         "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
 445         "             * to be part of the websocket stream */\n",
 446         "            evt.data.type = \"image/png\";\n",
 447         "\n",
 448         "            /* Free the memory for the previous frames */\n",
 449         "            if (fig.imageObj.src) {\n",
 450         "                (window.URL || window.webkitURL).revokeObjectURL(\n",
 451         "                    fig.imageObj.src);\n",
 452         "            }\n",
 453         "\n",
 454         "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
 455         "                evt.data);\n",
 456         "            fig.updated_canvas_event();\n",
 457         "            fig.waiting = false;\n",
 458         "            return;\n",
 459         "        }\n",
 460         "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
 461         "            fig.imageObj.src = evt.data;\n",
 462         "            fig.updated_canvas_event();\n",
 463         "            fig.waiting = false;\n",
 464         "            return;\n",
 465         "        }\n",
 466         "\n",
 467         "        var msg = JSON.parse(evt.data);\n",
 468         "        var msg_type = msg['type'];\n",
 469         "\n",
 470         "        // Call the  \"handle_{type}\" callback, which takes\n",
 471         "        // the figure and JSON message as its only arguments.\n",
 472         "        try {\n",
 473         "            var callback = fig[\"handle_\" + msg_type];\n",
 474         "        } catch (e) {\n",
 475         "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
 476         "            return;\n",
 477         "        }\n",
 478         "\n",
 479         "        if (callback) {\n",
 480         "            try {\n",
 481         "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
 482         "                callback(fig, msg);\n",
 483         "            } catch (e) {\n",
 484         "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
 485         "            }\n",
 486         "        }\n",
 487         "    };\n",
 488         "}\n",
 489         "\n",
 490         "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
 491         "mpl.findpos = function(e) {\n",
 492         "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
 493         "    var targ;\n",
 494         "    if (!e)\n",
 495         "        e = window.event;\n",
 496         "    if (e.target)\n",
 497         "        targ = e.target;\n",
 498         "    else if (e.srcElement)\n",
 499         "        targ = e.srcElement;\n",
 500         "    if (targ.nodeType == 3) // defeat Safari bug\n",
 501         "        targ = targ.parentNode;\n",
 502         "\n",
 503         "    // jQuery normalizes the pageX and pageY\n",
 504         "    // pageX,Y are the mouse positions relative to the document\n",
 505         "    // offset() returns the position of the element relative to the document\n",
 506         "    var x = e.pageX - $(targ).offset().left;\n",
 507         "    var y = e.pageY - $(targ).offset().top;\n",
 508         "\n",
 509         "    return {\"x\": x, \"y\": y};\n",
 510         "};\n",
 511         "\n",
 512         "/*\n",
 513         " * return a copy of an object with only non-object keys\n",
 514         " * we need this to avoid circular references\n",
 515         " * http://stackoverflow.com/a/24161582/3208463\n",
 516         " */\n",
 517         "function simpleKeys (original) {\n",
 518         "  return Object.keys(original).reduce(function (obj, key) {\n",
 519         "    if (typeof original[key] !== 'object')\n",
 520         "        obj[key] = original[key]\n",
 521         "    return obj;\n",
 522         "  }, {});\n",
 523         "}\n",
 524         "\n",
 525         "mpl.figure.prototype.mouse_event = function(event, name) {\n",
 526         "    var canvas_pos = mpl.findpos(event)\n",
 527         "\n",
 528         "    if (name === 'button_press')\n",
 529         "    {\n",
 530         "        this.canvas.focus();\n",
 531         "        this.canvas_div.focus();\n",
 532         "    }\n",
 533         "\n",
 534         "    var x = canvas_pos.x * mpl.ratio;\n",
 535         "    var y = canvas_pos.y * mpl.ratio;\n",
 536         "\n",
 537         "    this.send_message(name, {x: x, y: y, button: event.button,\n",
 538         "                             step: event.step,\n",
 539         "                             guiEvent: simpleKeys(event)});\n",
 540         "\n",
 541         "    /* This prevents the web browser from automatically changing to\n",
 542         "     * the text insertion cursor when the button is pressed.  We want\n",
 543         "     * to control all of the cursor setting manually through the\n",
 544         "     * 'cursor' event from matplotlib */\n",
 545         "    event.preventDefault();\n",
 546         "    return false;\n",
 547         "}\n",
 548         "\n",
 549         "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
 550         "    // Handle any extra behaviour associated with a key event\n",
 551         "}\n",
 552         "\n",
 553         "mpl.figure.prototype.key_event = function(event, name) {\n",
 554         "\n",
 555         "    // Prevent repeat events\n",
 556         "    if (name == 'key_press')\n",
 557         "    {\n",
 558         "        if (event.which === this._key)\n",
 559         "            return;\n",
 560         "        else\n",
 561         "            this._key = event.which;\n",
 562         "    }\n",
 563         "    if (name == 'key_release')\n",
 564         "        this._key = null;\n",
 565         "\n",
 566         "    var value = '';\n",
 567         "    if (event.ctrlKey && event.which != 17)\n",
 568         "        value += \"ctrl+\";\n",
 569         "    if (event.altKey && event.which != 18)\n",
 570         "        value += \"alt+\";\n",
 571         "    if (event.shiftKey && event.which != 16)\n",
 572         "        value += \"shift+\";\n",
 573         "\n",
 574         "    value += 'k';\n",
 575         "    value += event.which.toString();\n",
 576         "\n",
 577         "    this._key_event_extra(event, name);\n",
 578         "\n",
 579         "    this.send_message(name, {key: value,\n",
 580         "                             guiEvent: simpleKeys(event)});\n",
 581         "    return false;\n",
 582         "}\n",
 583         "\n",
 584         "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
 585         "    if (name == 'download') {\n",
 586         "        this.handle_save(this, null);\n",
 587         "    } else {\n",
 588         "        this.send_message(\"toolbar_button\", {name: name});\n",
 589         "    }\n",
 590         "};\n",
 591         "\n",
 592         "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
 593         "    this.message.textContent = tooltip;\n",
 594         "};\n",
 595         "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",
 596         "\n",
 597         "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
 598         "\n",
 599         "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
 600         "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
 601         "    // object with the appropriate methods. Currently this is a non binary\n",
 602         "    // socket, so there is still some room for performance tuning.\n",
 603         "    var ws = {};\n",
 604         "\n",
 605         "    ws.close = function() {\n",
 606         "        comm.close()\n",
 607         "    };\n",
 608         "    ws.send = function(m) {\n",
 609         "        //console.log('sending', m);\n",
 610         "        comm.send(m);\n",
 611         "    };\n",
 612         "    // Register the callback with on_msg.\n",
 613         "    comm.on_msg(function(msg) {\n",
 614         "        //console.log('receiving', msg['content']['data'], msg);\n",
 615         "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
 616         "        ws.onmessage(msg['content']['data'])\n",
 617         "    });\n",
 618         "    return ws;\n",
 619         "}\n",
 620         "\n",
 621         "mpl.mpl_figure_comm = function(comm, msg) {\n",
 622         "    // This is the function which gets called when the mpl process\n",
 623         "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
 624         "\n",
 625         "    var id = msg.content.data.id;\n",
 626         "    // Get hold of the div created by the display call when the Comm\n",
 627         "    // socket was opened in Python.\n",
 628         "    var element = $(\"#\" + id);\n",
 629         "    var ws_proxy = comm_websocket_adapter(comm)\n",
 630         "\n",
 631         "    function ondownload(figure, format) {\n",
 632         "        window.open(figure.imageObj.src);\n",
 633         "    }\n",
 634         "\n",
 635         "    var fig = new mpl.figure(id, ws_proxy,\n",
 636         "                           ondownload,\n",
 637         "                           element.get(0));\n",
 638         "\n",
 639         "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
 640         "    // web socket which is closed, not our websocket->open comm proxy.\n",
 641         "    ws_proxy.onopen();\n",
 642         "\n",
 643         "    fig.parent_element = element.get(0);\n",
 644         "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
 645         "    if (!fig.cell_info) {\n",
 646         "        console.error(\"Failed to find cell for figure\", id, fig);\n",
 647         "        return;\n",
 648         "    }\n",
 649         "\n",
 650         "    var output_index = fig.cell_info[2]\n",
 651         "    var cell = fig.cell_info[0];\n",
 652         "\n",
 653         "};\n",
 654         "\n",
 655         "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
 656         "    var width = fig.canvas.width/mpl.ratio\n",
 657         "    fig.root.unbind('remove')\n",
 658         "\n",
 659         "    // Update the output cell to use the data from the current canvas.\n",
 660         "    fig.push_to_output();\n",
 661         "    var dataURL = fig.canvas.toDataURL();\n",
 662         "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
 663         "    // the notebook keyboard shortcuts fail.\n",
 664         "    IPython.keyboard_manager.enable()\n",
 665         "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
 666         "    fig.close_ws(fig, msg);\n",
 667         "}\n",
 668         "\n",
 669         "mpl.figure.prototype.close_ws = function(fig, msg){\n",
 670         "    fig.send_message('closing', msg);\n",
 671         "    // fig.ws.close()\n",
 672         "}\n",
 673         "\n",
 674         "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
 675         "    // Turn the data on the canvas into data in the output cell.\n",
 676         "    var width = this.canvas.width/mpl.ratio\n",
 677         "    var dataURL = this.canvas.toDataURL();\n",
 678         "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
 679         "}\n",
 680         "\n",
 681         "mpl.figure.prototype.updated_canvas_event = function() {\n",
 682         "    // Tell IPython that the notebook contents must change.\n",
 683         "    IPython.notebook.set_dirty(true);\n",
 684         "    this.send_message(\"ack\", {});\n",
 685         "    var fig = this;\n",
 686         "    // Wait a second, then push the new image to the DOM so\n",
 687         "    // that it is saved nicely (might be nice to debounce this).\n",
 688         "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
 689         "}\n",
 690         "\n",
 691         "mpl.figure.prototype._init_toolbar = function() {\n",
 692         "    var fig = this;\n",
 693         "\n",
 694         "    var nav_element = $('<div/>')\n",
 695         "    nav_element.attr('style', 'width: 100%');\n",
 696         "    this.root.append(nav_element);\n",
 697         "\n",
 698         "    // Define a callback function for later on.\n",
 699         "    function toolbar_event(event) {\n",
 700         "        return fig.toolbar_button_onclick(event['data']);\n",
 701         "    }\n",
 702         "    function toolbar_mouse_event(event) {\n",
 703         "        return fig.toolbar_button_onmouseover(event['data']);\n",
 704         "    }\n",
 705         "\n",
 706         "    for(var toolbar_ind in mpl.toolbar_items){\n",
 707         "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
 708         "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
 709         "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
 710         "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
 711         "\n",
 712         "        if (!name) { continue; };\n",
 713         "\n",
 714         "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
 715         "        button.click(method_name, toolbar_event);\n",
 716         "        button.mouseover(tooltip, toolbar_mouse_event);\n",
 717         "        nav_element.append(button);\n",
 718         "    }\n",
 719         "\n",
 720         "    // Add the status bar.\n",
 721         "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
 722         "    nav_element.append(status_bar);\n",
 723         "    this.message = status_bar[0];\n",
 724         "\n",
 725         "    // Add the close button to the window.\n",
 726         "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
 727         "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
 728         "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
 729         "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
 730         "    buttongrp.append(button);\n",
 731         "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
 732         "    titlebar.prepend(buttongrp);\n",
 733         "}\n",
 734         "\n",
 735         "mpl.figure.prototype._root_extra_style = function(el){\n",
 736         "    var fig = this\n",
 737         "    el.on(\"remove\", function(){\n",
 738         "\tfig.close_ws(fig, {});\n",
 739         "    });\n",
 740         "}\n",
 741         "\n",
 742         "mpl.figure.prototype._canvas_extra_style = function(el){\n",
 743         "    // this is important to make the div 'focusable\n",
 744         "    el.attr('tabindex', 0)\n",
 745         "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
 746         "    // off when our div gets focus\n",
 747         "\n",
 748         "    // location in version 3\n",
 749         "    if (IPython.notebook.keyboard_manager) {\n",
 750         "        IPython.notebook.keyboard_manager.register_events(el);\n",
 751         "    }\n",
 752         "    else {\n",
 753         "        // location in version 2\n",
 754         "        IPython.keyboard_manager.register_events(el);\n",
 755         "    }\n",
 756         "\n",
 757         "}\n",
 758         "\n",
 759         "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
 760         "    var manager = IPython.notebook.keyboard_manager;\n",
 761         "    if (!manager)\n",
 762         "        manager = IPython.keyboard_manager;\n",
 763         "\n",
 764         "    // Check for shift+enter\n",
 765         "    if (event.shiftKey && event.which == 13) {\n",
 766         "        this.canvas_div.blur();\n",
 767         "        // select the cell after this one\n",
 768         "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
 769         "        IPython.notebook.select(index + 1);\n",
 770         "    }\n",
 771         "}\n",
 772         "\n",
 773         "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
 774         "    fig.ondownload(fig, null);\n",
 775         "}\n",
 776         "\n",
 777         "\n",
 778         "mpl.find_output_cell = function(html_output) {\n",
 779         "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
 780         "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
 781         "    // IPython event is triggered only after the cells have been serialised, which for\n",
 782         "    // our purposes (turning an active figure into a static one), is too late.\n",
 783         "    var cells = IPython.notebook.get_cells();\n",
 784         "    var ncells = cells.length;\n",
 785         "    for (var i=0; i<ncells; i++) {\n",
 786         "        var cell = cells[i];\n",
 787         "        if (cell.cell_type === 'code'){\n",
 788         "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
 789         "                var data = cell.output_area.outputs[j];\n",
 790         "                if (data.data) {\n",
 791         "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
 792         "                    data = data.data;\n",
 793         "                }\n",
 794         "                if (data['text/html'] == html_output) {\n",
 795         "                    return [cell, data, j];\n",
 796         "                }\n",
 797         "            }\n",
 798         "        }\n",
 799         "    }\n",
 800         "}\n",
 801         "\n",
 802         "// Register the function which deals with the matplotlib target/channel.\n",
 803         "// The kernel may be null if the page has been refreshed.\n",
 804         "if (IPython.notebook.kernel != null) {\n",
 805         "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
 806         "}\n"
 807        ],
 808        "text/plain": [
 809         "<IPython.core.display.Javascript object>"
 810        ]
 811       },
 812       "metadata": {},
 813       "output_type": "display_data"
 814      },
 815      {
 816       "data": {
 817        "text/html": [
 818         "<img 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\" width=\"800\">"
 819        ],
 820        "text/plain": [
 821         "<IPython.core.display.HTML object>"
 822        ]
 823       },
 824       "metadata": {},
 825       "output_type": "display_data"
 826      },
 827      {
 828       "data": {
 829        "application/javascript": [
 830         "/* Put everything inside the global mpl namespace */\n",
 831         "window.mpl = {};\n",
 832         "\n",
 833         "\n",
 834         "mpl.get_websocket_type = function() {\n",
 835         "    if (typeof(WebSocket) !== 'undefined') {\n",
 836         "        return WebSocket;\n",
 837         "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
 838         "        return MozWebSocket;\n",
 839         "    } else {\n",
 840         "        alert('Your browser does not have WebSocket support.' +\n",
 841         "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
 842         "              'Firefox 4 and 5 are also supported but you ' +\n",
 843         "              'have to enable WebSockets in about:config.');\n",
 844         "    };\n",
 845         "}\n",
 846         "\n",
 847         "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
 848         "    this.id = figure_id;\n",
 849         "\n",
 850         "    this.ws = websocket;\n",
 851         "\n",
 852         "    this.supports_binary = (this.ws.binaryType != undefined);\n",
 853         "\n",
 854         "    if (!this.supports_binary) {\n",
 855         "        var warnings = document.getElementById(\"mpl-warnings\");\n",
 856         "        if (warnings) {\n",
 857         "            warnings.style.display = 'block';\n",
 858         "            warnings.textContent = (\n",
 859         "                \"This browser does not support binary websocket messages. \" +\n",
 860         "                    \"Performance may be slow.\");\n",
 861         "        }\n",
 862         "    }\n",
 863         "\n",
 864         "    this.imageObj = new Image();\n",
 865         "\n",
 866         "    this.context = undefined;\n",
 867         "    this.message = undefined;\n",
 868         "    this.canvas = undefined;\n",
 869         "    this.rubberband_canvas = undefined;\n",
 870         "    this.rubberband_context = undefined;\n",
 871         "    this.format_dropdown = undefined;\n",
 872         "\n",
 873         "    this.image_mode = 'full';\n",
 874         "\n",
 875         "    this.root = $('<div/>');\n",
 876         "    this._root_extra_style(this.root)\n",
 877         "    this.root.attr('style', 'display: inline-block');\n",
 878         "\n",
 879         "    $(parent_element).append(this.root);\n",
 880         "\n",
 881         "    this._init_header(this);\n",
 882         "    this._init_canvas(this);\n",
 883         "    this._init_toolbar(this);\n",
 884         "\n",
 885         "    var fig = this;\n",
 886         "\n",
 887         "    this.waiting = false;\n",
 888         "\n",
 889         "    this.ws.onopen =  function () {\n",
 890         "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
 891         "            fig.send_message(\"send_image_mode\", {});\n",
 892         "            if (mpl.ratio != 1) {\n",
 893         "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
 894         "            }\n",
 895         "            fig.send_message(\"refresh\", {});\n",
 896         "        }\n",
 897         "\n",
 898         "    this.imageObj.onload = function() {\n",
 899         "            if (fig.image_mode == 'full') {\n",
 900         "                // Full images could contain transparency (where diff images\n",
 901         "                // almost always do), so we need to clear the canvas so that\n",
 902         "                // there is no ghosting.\n",
 903         "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
 904         "            }\n",
 905         "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
 906         "        };\n",
 907         "\n",
 908         "    this.imageObj.onunload = function() {\n",
 909         "        this.ws.close();\n",
 910         "    }\n",
 911         "\n",
 912         "    this.ws.onmessage = this._make_on_message_function(this);\n",
 913         "\n",
 914         "    this.ondownload = ondownload;\n",
 915         "}\n",
 916         "\n",
 917         "mpl.figure.prototype._init_header = function() {\n",
 918         "    var titlebar = $(\n",
 919         "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
 920         "        'ui-helper-clearfix\"/>');\n",
 921         "    var titletext = $(\n",
 922         "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
 923         "        'text-align: center; padding: 3px;\"/>');\n",
 924         "    titlebar.append(titletext)\n",
 925         "    this.root.append(titlebar);\n",
 926         "    this.header = titletext[0];\n",
 927         "}\n",
 928         "\n",
 929         "\n",
 930         "\n",
 931         "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
 932         "\n",
 933         "}\n",
 934         "\n",
 935         "\n",
 936         "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
 937         "\n",
 938         "}\n",
 939         "\n",
 940         "mpl.figure.prototype._init_canvas = function() {\n",
 941         "    var fig = this;\n",
 942         "\n",
 943         "    var canvas_div = $('<div/>');\n",
 944         "\n",
 945         "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
 946         "\n",
 947         "    function canvas_keyboard_event(event) {\n",
 948         "        return fig.key_event(event, event['data']);\n",
 949         "    }\n",
 950         "\n",
 951         "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
 952         "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
 953         "    this.canvas_div = canvas_div\n",
 954         "    this._canvas_extra_style(canvas_div)\n",
 955         "    this.root.append(canvas_div);\n",
 956         "\n",
 957         "    var canvas = $('<canvas/>');\n",
 958         "    canvas.addClass('mpl-canvas');\n",
 959         "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
 960         "\n",
 961         "    this.canvas = canvas[0];\n",
 962         "    this.context = canvas[0].getContext(\"2d\");\n",
 963         "\n",
 964         "    var backingStore = this.context.backingStorePixelRatio ||\n",
 965         "\tthis.context.webkitBackingStorePixelRatio ||\n",
 966         "\tthis.context.mozBackingStorePixelRatio ||\n",
 967         "\tthis.context.msBackingStorePixelRatio ||\n",
 968         "\tthis.context.oBackingStorePixelRatio ||\n",
 969         "\tthis.context.backingStorePixelRatio || 1;\n",
 970         "\n",
 971         "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
 972         "\n",
 973         "    var rubberband = $('<canvas/>');\n",
 974         "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
 975         "\n",
 976         "    var pass_mouse_events = true;\n",
 977         "\n",
 978         "    canvas_div.resizable({\n",
 979         "        start: function(event, ui) {\n",
 980         "            pass_mouse_events = false;\n",
 981         "        },\n",
 982         "        resize: function(event, ui) {\n",
 983         "            fig.request_resize(ui.size.width, ui.size.height);\n",
 984         "        },\n",
 985         "        stop: function(event, ui) {\n",
 986         "            pass_mouse_events = true;\n",
 987         "            fig.request_resize(ui.size.width, ui.size.height);\n",
 988         "        },\n",
 989         "    });\n",
 990         "\n",
 991         "    function mouse_event_fn(event) {\n",
 992         "        if (pass_mouse_events)\n",
 993         "            return fig.mouse_event(event, event['data']);\n",
 994         "    }\n",
 995         "\n",
 996         "    rubberband.mousedown('button_press', mouse_event_fn);\n",
 997         "    rubberband.mouseup('button_release', mouse_event_fn);\n",
 998         "    // Throttle sequential mouse events to 1 every 20ms.\n",
 999         "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
1000         "\n",
1001         "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
1002         "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
1003         "\n",
1004         "    canvas_div.on(\"wheel\", function (event) {\n",
1005         "        event = event.originalEvent;\n",
1006         "        event['data'] = 'scroll'\n",
1007         "        if (event.deltaY < 0) {\n",
1008         "            event.step = 1;\n",
1009         "        } else {\n",
1010         "            event.step = -1;\n",
1011         "        }\n",
1012         "        mouse_event_fn(event);\n",
1013         "    });\n",
1014         "\n",
1015         "    canvas_div.append(canvas);\n",
1016         "    canvas_div.append(rubberband);\n",
1017         "\n",
1018         "    this.rubberband = rubberband;\n",
1019         "    this.rubberband_canvas = rubberband[0];\n",
1020         "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
1021         "    this.rubberband_context.strokeStyle = \"#000000\";\n",
1022         "\n",
1023         "    this._resize_canvas = function(width, height) {\n",
1024         "        // Keep the size of the canvas, canvas container, and rubber band\n",
1025         "        // canvas in synch.\n",
1026         "        canvas_div.css('width', width)\n",
1027         "        canvas_div.css('height', height)\n",
1028         "\n",
1029         "        canvas.attr('width', width * mpl.ratio);\n",
1030         "        canvas.attr('height', height * mpl.ratio);\n",
1031         "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
1032         "\n",
1033         "        rubberband.attr('width', width);\n",
1034         "        rubberband.attr('height', height);\n",
1035         "    }\n",
1036         "\n",
1037         "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
1038         "    // upon first draw.\n",
1039         "    this._resize_canvas(600, 600);\n",
1040         "\n",
1041         "    // Disable right mouse context menu.\n",
1042         "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
1043         "        return false;\n",
1044         "    });\n",
1045         "\n",
1046         "    function set_focus () {\n",
1047         "        canvas.focus();\n",
1048         "        canvas_div.focus();\n",
1049         "    }\n",
1050         "\n",
1051         "    window.setTimeout(set_focus, 100);\n",
1052         "}\n",
1053         "\n",
1054         "mpl.figure.prototype._init_toolbar = function() {\n",
1055         "    var fig = this;\n",
1056         "\n",
1057         "    var nav_element = $('<div/>')\n",
1058         "    nav_element.attr('style', 'width: 100%');\n",
1059         "    this.root.append(nav_element);\n",
1060         "\n",
1061         "    // Define a callback function for later on.\n",
1062         "    function toolbar_event(event) {\n",
1063         "        return fig.toolbar_button_onclick(event['data']);\n",
1064         "    }\n",
1065         "    function toolbar_mouse_event(event) {\n",
1066         "        return fig.toolbar_button_onmouseover(event['data']);\n",
1067         "    }\n",
1068         "\n",
1069         "    for(var toolbar_ind in mpl.toolbar_items) {\n",
1070         "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
1071         "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
1072         "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
1073         "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
1074         "\n",
1075         "        if (!name) {\n",
1076         "            // put a spacer in here.\n",
1077         "            continue;\n",
1078         "        }\n",
1079         "        var button = $('<button/>');\n",
1080         "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
1081         "                        'ui-button-icon-only');\n",
1082         "        button.attr('role', 'button');\n",
1083         "        button.attr('aria-disabled', 'false');\n",
1084         "        button.click(method_name, toolbar_event);\n",
1085         "        button.mouseover(tooltip, toolbar_mouse_event);\n",
1086         "\n",
1087         "        var icon_img = $('<span/>');\n",
1088         "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
1089         "        icon_img.addClass(image);\n",
1090         "        icon_img.addClass('ui-corner-all');\n",
1091         "\n",
1092         "        var tooltip_span = $('<span/>');\n",
1093         "        tooltip_span.addClass('ui-button-text');\n",
1094         "        tooltip_span.html(tooltip);\n",
1095         "\n",
1096         "        button.append(icon_img);\n",
1097         "        button.append(tooltip_span);\n",
1098         "\n",
1099         "        nav_element.append(button);\n",
1100         "    }\n",
1101         "\n",
1102         "    var fmt_picker_span = $('<span/>');\n",
1103         "\n",
1104         "    var fmt_picker = $('<select/>');\n",
1105         "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
1106         "    fmt_picker_span.append(fmt_picker);\n",
1107         "    nav_element.append(fmt_picker_span);\n",
1108         "    this.format_dropdown = fmt_picker[0];\n",
1109         "\n",
1110         "    for (var ind in mpl.extensions) {\n",
1111         "        var fmt = mpl.extensions[ind];\n",
1112         "        var option = $(\n",
1113         "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
1114         "        fmt_picker.append(option)\n",
1115         "    }\n",
1116         "\n",
1117         "    // Add hover states to the ui-buttons\n",
1118         "    $( \".ui-button\" ).hover(\n",
1119         "        function() { $(this).addClass(\"ui-state-hover\");},\n",
1120         "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
1121         "    );\n",
1122         "\n",
1123         "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
1124         "    nav_element.append(status_bar);\n",
1125         "    this.message = status_bar[0];\n",
1126         "}\n",
1127         "\n",
1128         "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
1129         "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
1130         "    // which will in turn request a refresh of the image.\n",
1131         "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
1132         "}\n",
1133         "\n",
1134         "mpl.figure.prototype.send_message = function(type, properties) {\n",
1135         "    properties['type'] = type;\n",
1136         "    properties['figure_id'] = this.id;\n",
1137         "    this.ws.send(JSON.stringify(properties));\n",
1138         "}\n",
1139         "\n",
1140         "mpl.figure.prototype.send_draw_message = function() {\n",
1141         "    if (!this.waiting) {\n",
1142         "        this.waiting = true;\n",
1143         "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
1144         "    }\n",
1145         "}\n",
1146         "\n",
1147         "\n",
1148         "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
1149         "    var format_dropdown = fig.format_dropdown;\n",
1150         "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
1151         "    fig.ondownload(fig, format);\n",
1152         "}\n",
1153         "\n",
1154         "\n",
1155         "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
1156         "    var size = msg['size'];\n",
1157         "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
1158         "        fig._resize_canvas(size[0], size[1]);\n",
1159         "        fig.send_message(\"refresh\", {});\n",
1160         "    };\n",
1161         "}\n",
1162         "\n",
1163         "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
1164         "    var x0 = msg['x0'] / mpl.ratio;\n",
1165         "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
1166         "    var x1 = msg['x1'] / mpl.ratio;\n",
1167         "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
1168         "    x0 = Math.floor(x0) + 0.5;\n",
1169         "    y0 = Math.floor(y0) + 0.5;\n",
1170         "    x1 = Math.floor(x1) + 0.5;\n",
1171         "    y1 = Math.floor(y1) + 0.5;\n",
1172         "    var min_x = Math.min(x0, x1);\n",
1173         "    var min_y = Math.min(y0, y1);\n",
1174         "    var width = Math.abs(x1 - x0);\n",
1175         "    var height = Math.abs(y1 - y0);\n",
1176         "\n",
1177         "    fig.rubberband_context.clearRect(\n",
1178         "        0, 0, fig.canvas.width, fig.canvas.height);\n",
1179         "\n",
1180         "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
1181         "}\n",
1182         "\n",
1183         "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
1184         "    // Updates the figure title.\n",
1185         "    fig.header.textContent = msg['label'];\n",
1186         "}\n",
1187         "\n",
1188         "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
1189         "    var cursor = msg['cursor'];\n",
1190         "    switch(cursor)\n",
1191         "    {\n",
1192         "    case 0:\n",
1193         "        cursor = 'pointer';\n",
1194         "        break;\n",
1195         "    case 1:\n",
1196         "        cursor = 'default';\n",
1197         "        break;\n",
1198         "    case 2:\n",
1199         "        cursor = 'crosshair';\n",
1200         "        break;\n",
1201         "    case 3:\n",
1202         "        cursor = 'move';\n",
1203         "        break;\n",
1204         "    }\n",
1205         "    fig.rubberband_canvas.style.cursor = cursor;\n",
1206         "}\n",
1207         "\n",
1208         "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
1209         "    fig.message.textContent = msg['message'];\n",
1210         "}\n",
1211         "\n",
1212         "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
1213         "    // Request the server to send over a new figure.\n",
1214         "    fig.send_draw_message();\n",
1215         "}\n",
1216         "\n",
1217         "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
1218         "    fig.image_mode = msg['mode'];\n",
1219         "}\n",
1220         "\n",
1221         "mpl.figure.prototype.updated_canvas_event = function() {\n",
1222         "    // Called whenever the canvas gets updated.\n",
1223         "    this.send_message(\"ack\", {});\n",
1224         "}\n",
1225         "\n",
1226         "// A function to construct a web socket function for onmessage handling.\n",
1227         "// Called in the figure constructor.\n",
1228         "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
1229         "    return function socket_on_message(evt) {\n",
1230         "        if (evt.data instanceof Blob) {\n",
1231         "            /* FIXME: We get \"Resource interpreted as Image but\n",
1232         "             * transferred with MIME type text/plain:\" errors on\n",
1233         "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
1234         "             * to be part of the websocket stream */\n",
1235         "            evt.data.type = \"image/png\";\n",
1236         "\n",
1237         "            /* Free the memory for the previous frames */\n",
1238         "            if (fig.imageObj.src) {\n",
1239         "                (window.URL || window.webkitURL).revokeObjectURL(\n",
1240         "                    fig.imageObj.src);\n",
1241         "            }\n",
1242         "\n",
1243         "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
1244         "                evt.data);\n",
1245         "            fig.updated_canvas_event();\n",
1246         "            fig.waiting = false;\n",
1247         "            return;\n",
1248         "        }\n",
1249         "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
1250         "            fig.imageObj.src = evt.data;\n",
1251         "            fig.updated_canvas_event();\n",
1252         "            fig.waiting = false;\n",
1253         "            return;\n",
1254         "        }\n",
1255         "\n",
1256         "        var msg = JSON.parse(evt.data);\n",
1257         "        var msg_type = msg['type'];\n",
1258         "\n",
1259         "        // Call the  \"handle_{type}\" callback, which takes\n",
1260         "        // the figure and JSON message as its only arguments.\n",
1261         "        try {\n",
1262         "            var callback = fig[\"handle_\" + msg_type];\n",
1263         "        } catch (e) {\n",
1264         "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
1265         "            return;\n",
1266         "        }\n",
1267         "\n",
1268         "        if (callback) {\n",
1269         "            try {\n",
1270         "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
1271         "                callback(fig, msg);\n",
1272         "            } catch (e) {\n",
1273         "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
1274         "            }\n",
1275         "        }\n",
1276         "    };\n",
1277         "}\n",
1278         "\n",
1279         "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
1280         "mpl.findpos = function(e) {\n",
1281         "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
1282         "    var targ;\n",
1283         "    if (!e)\n",
1284         "        e = window.event;\n",
1285         "    if (e.target)\n",
1286         "        targ = e.target;\n",
1287         "    else if (e.srcElement)\n",
1288         "        targ = e.srcElement;\n",
1289         "    if (targ.nodeType == 3) // defeat Safari bug\n",
1290         "        targ = targ.parentNode;\n",
1291         "\n",
1292         "    // jQuery normalizes the pageX and pageY\n",
1293         "    // pageX,Y are the mouse positions relative to the document\n",
1294         "    // offset() returns the position of the element relative to the document\n",
1295         "    var x = e.pageX - $(targ).offset().left;\n",
1296         "    var y = e.pageY - $(targ).offset().top;\n",
1297         "\n",
1298         "    return {\"x\": x, \"y\": y};\n",
1299         "};\n",
1300         "\n",
1301         "/*\n",
1302         " * return a copy of an object with only non-object keys\n",
1303         " * we need this to avoid circular references\n",
1304         " * http://stackoverflow.com/a/24161582/3208463\n",
1305         " */\n",
1306         "function simpleKeys (original) {\n",
1307         "  return Object.keys(original).reduce(function (obj, key) {\n",
1308         "    if (typeof original[key] !== 'object')\n",
1309         "        obj[key] = original[key]\n",
1310         "    return obj;\n",
1311         "  }, {});\n",
1312         "}\n",
1313         "\n",
1314         "mpl.figure.prototype.mouse_event = function(event, name) {\n",
1315         "    var canvas_pos = mpl.findpos(event)\n",
1316         "\n",
1317         "    if (name === 'button_press')\n",
1318         "    {\n",
1319         "        this.canvas.focus();\n",
1320         "        this.canvas_div.focus();\n",
1321         "    }\n",
1322         "\n",
1323         "    var x = canvas_pos.x * mpl.ratio;\n",
1324         "    var y = canvas_pos.y * mpl.ratio;\n",
1325         "\n",
1326         "    this.send_message(name, {x: x, y: y, button: event.button,\n",
1327         "                             step: event.step,\n",
1328         "                             guiEvent: simpleKeys(event)});\n",
1329         "\n",
1330         "    /* This prevents the web browser from automatically changing to\n",
1331         "     * the text insertion cursor when the button is pressed.  We want\n",
1332         "     * to control all of the cursor setting manually through the\n",
1333         "     * 'cursor' event from matplotlib */\n",
1334         "    event.preventDefault();\n",
1335         "    return false;\n",
1336         "}\n",
1337         "\n",
1338         "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
1339         "    // Handle any extra behaviour associated with a key event\n",
1340         "}\n",
1341         "\n",
1342         "mpl.figure.prototype.key_event = function(event, name) {\n",
1343         "\n",
1344         "    // Prevent repeat events\n",
1345         "    if (name == 'key_press')\n",
1346         "    {\n",
1347         "        if (event.which === this._key)\n",
1348         "            return;\n",
1349         "        else\n",
1350         "            this._key = event.which;\n",
1351         "    }\n",
1352         "    if (name == 'key_release')\n",
1353         "        this._key = null;\n",
1354         "\n",
1355         "    var value = '';\n",
1356         "    if (event.ctrlKey && event.which != 17)\n",
1357         "        value += \"ctrl+\";\n",
1358         "    if (event.altKey && event.which != 18)\n",
1359         "        value += \"alt+\";\n",
1360         "    if (event.shiftKey && event.which != 16)\n",
1361         "        value += \"shift+\";\n",
1362         "\n",
1363         "    value += 'k';\n",
1364         "    value += event.which.toString();\n",
1365         "\n",
1366         "    this._key_event_extra(event, name);\n",
1367         "\n",
1368         "    this.send_message(name, {key: value,\n",
1369         "                             guiEvent: simpleKeys(event)});\n",
1370         "    return false;\n",
1371         "}\n",
1372         "\n",
1373         "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
1374         "    if (name == 'download') {\n",
1375         "        this.handle_save(this, null);\n",
1376         "    } else {\n",
1377         "        this.send_message(\"toolbar_button\", {name: name});\n",
1378         "    }\n",
1379         "};\n",
1380         "\n",
1381         "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
1382         "    this.message.textContent = tooltip;\n",
1383         "};\n",
1384         "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",
1385         "\n",
1386         "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
1387         "\n",
1388         "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
1389         "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
1390         "    // object with the appropriate methods. Currently this is a non binary\n",
1391         "    // socket, so there is still some room for performance tuning.\n",
1392         "    var ws = {};\n",
1393         "\n",
1394         "    ws.close = function() {\n",
1395         "        comm.close()\n",
1396         "    };\n",
1397         "    ws.send = function(m) {\n",
1398         "        //console.log('sending', m);\n",
1399         "        comm.send(m);\n",
1400         "    };\n",
1401         "    // Register the callback with on_msg.\n",
1402         "    comm.on_msg(function(msg) {\n",
1403         "        //console.log('receiving', msg['content']['data'], msg);\n",
1404         "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
1405         "        ws.onmessage(msg['content']['data'])\n",
1406         "    });\n",
1407         "    return ws;\n",
1408         "}\n",
1409         "\n",
1410         "mpl.mpl_figure_comm = function(comm, msg) {\n",
1411         "    // This is the function which gets called when the mpl process\n",
1412         "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
1413         "\n",
1414         "    var id = msg.content.data.id;\n",
1415         "    // Get hold of the div created by the display call when the Comm\n",
1416         "    // socket was opened in Python.\n",
1417         "    var element = $(\"#\" + id);\n",
1418         "    var ws_proxy = comm_websocket_adapter(comm)\n",
1419         "\n",
1420         "    function ondownload(figure, format) {\n",
1421         "        window.open(figure.imageObj.src);\n",
1422         "    }\n",
1423         "\n",
1424         "    var fig = new mpl.figure(id, ws_proxy,\n",
1425         "                           ondownload,\n",
1426         "                           element.get(0));\n",
1427         "\n",
1428         "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
1429         "    // web socket which is closed, not our websocket->open comm proxy.\n",
1430         "    ws_proxy.onopen();\n",
1431         "\n",
1432         "    fig.parent_element = element.get(0);\n",
1433         "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
1434         "    if (!fig.cell_info) {\n",
1435         "        console.error(\"Failed to find cell for figure\", id, fig);\n",
1436         "        return;\n",
1437         "    }\n",
1438         "\n",
1439         "    var output_index = fig.cell_info[2]\n",
1440         "    var cell = fig.cell_info[0];\n",
1441         "\n",
1442         "};\n",
1443         "\n",
1444         "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
1445         "    var width = fig.canvas.width/mpl.ratio\n",
1446         "    fig.root.unbind('remove')\n",
1447         "\n",
1448         "    // Update the output cell to use the data from the current canvas.\n",
1449         "    fig.push_to_output();\n",
1450         "    var dataURL = fig.canvas.toDataURL();\n",
1451         "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
1452         "    // the notebook keyboard shortcuts fail.\n",
1453         "    IPython.keyboard_manager.enable()\n",
1454         "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
1455         "    fig.close_ws(fig, msg);\n",
1456         "}\n",
1457         "\n",
1458         "mpl.figure.prototype.close_ws = function(fig, msg){\n",
1459         "    fig.send_message('closing', msg);\n",
1460         "    // fig.ws.close()\n",
1461         "}\n",
1462         "\n",
1463         "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
1464         "    // Turn the data on the canvas into data in the output cell.\n",
1465         "    var width = this.canvas.width/mpl.ratio\n",
1466         "    var dataURL = this.canvas.toDataURL();\n",
1467         "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
1468         "}\n",
1469         "\n",
1470         "mpl.figure.prototype.updated_canvas_event = function() {\n",
1471         "    // Tell IPython that the notebook contents must change.\n",
1472         "    IPython.notebook.set_dirty(true);\n",
1473         "    this.send_message(\"ack\", {});\n",
1474         "    var fig = this;\n",
1475         "    // Wait a second, then push the new image to the DOM so\n",
1476         "    // that it is saved nicely (might be nice to debounce this).\n",
1477         "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
1478         "}\n",
1479         "\n",
1480         "mpl.figure.prototype._init_toolbar = function() {\n",
1481         "    var fig = this;\n",
1482         "\n",
1483         "    var nav_element = $('<div/>')\n",
1484         "    nav_element.attr('style', 'width: 100%');\n",
1485         "    this.root.append(nav_element);\n",
1486         "\n",
1487         "    // Define a callback function for later on.\n",
1488         "    function toolbar_event(event) {\n",
1489         "        return fig.toolbar_button_onclick(event['data']);\n",
1490         "    }\n",
1491         "    function toolbar_mouse_event(event) {\n",
1492         "        return fig.toolbar_button_onmouseover(event['data']);\n",
1493         "    }\n",
1494         "\n",
1495         "    for(var toolbar_ind in mpl.toolbar_items){\n",
1496         "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
1497         "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
1498         "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
1499         "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
1500         "\n",
1501         "        if (!name) { continue; };\n",
1502         "\n",
1503         "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
1504         "        button.click(method_name, toolbar_event);\n",
1505         "        button.mouseover(tooltip, toolbar_mouse_event);\n",
1506         "        nav_element.append(button);\n",
1507         "    }\n",
1508         "\n",
1509         "    // Add the status bar.\n",
1510         "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
1511         "    nav_element.append(status_bar);\n",
1512         "    this.message = status_bar[0];\n",
1513         "\n",
1514         "    // Add the close button to the window.\n",
1515         "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
1516         "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
1517         "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
1518         "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
1519         "    buttongrp.append(button);\n",
1520         "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
1521         "    titlebar.prepend(buttongrp);\n",
1522         "}\n",
1523         "\n",
1524         "mpl.figure.prototype._root_extra_style = function(el){\n",
1525         "    var fig = this\n",
1526         "    el.on(\"remove\", function(){\n",
1527         "\tfig.close_ws(fig, {});\n",
1528         "    });\n",
1529         "}\n",
1530         "\n",
1531         "mpl.figure.prototype._canvas_extra_style = function(el){\n",
1532         "    // this is important to make the div 'focusable\n",
1533         "    el.attr('tabindex', 0)\n",
1534         "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
1535         "    // off when our div gets focus\n",
1536         "\n",
1537         "    // location in version 3\n",
1538         "    if (IPython.notebook.keyboard_manager) {\n",
1539         "        IPython.notebook.keyboard_manager.register_events(el);\n",
1540         "    }\n",
1541         "    else {\n",
1542         "        // location in version 2\n",
1543         "        IPython.keyboard_manager.register_events(el);\n",
1544         "    }\n",
1545         "\n",
1546         "}\n",
1547         "\n",
1548         "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
1549         "    var manager = IPython.notebook.keyboard_manager;\n",
1550         "    if (!manager)\n",
1551         "        manager = IPython.keyboard_manager;\n",
1552         "\n",
1553         "    // Check for shift+enter\n",
1554         "    if (event.shiftKey && event.which == 13) {\n",
1555         "        this.canvas_div.blur();\n",
1556         "        // select the cell after this one\n",
1557         "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
1558         "        IPython.notebook.select(index + 1);\n",
1559         "    }\n",
1560         "}\n",
1561         "\n",
1562         "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
1563         "    fig.ondownload(fig, null);\n",
1564         "}\n",
1565         "\n",
1566         "\n",
1567         "mpl.find_output_cell = function(html_output) {\n",
1568         "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
1569         "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
1570         "    // IPython event is triggered only after the cells have been serialised, which for\n",
1571         "    // our purposes (turning an active figure into a static one), is too late.\n",
1572         "    var cells = IPython.notebook.get_cells();\n",
1573         "    var ncells = cells.length;\n",
1574         "    for (var i=0; i<ncells; i++) {\n",
1575         "        var cell = cells[i];\n",
1576         "        if (cell.cell_type === 'code'){\n",
1577         "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
1578         "                var data = cell.output_area.outputs[j];\n",
1579         "                if (data.data) {\n",
1580         "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
1581         "                    data = data.data;\n",
1582         "                }\n",
1583         "                if (data['text/html'] == html_output) {\n",
1584         "                    return [cell, data, j];\n",
1585         "                }\n",
1586         "            }\n",
1587         "        }\n",
1588         "    }\n",
1589         "}\n",
1590         "\n",
1591         "// Register the function which deals with the matplotlib target/channel.\n",
1592         "// The kernel may be null if the page has been refreshed.\n",
1593         "if (IPython.notebook.kernel != null) {\n",
1594         "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
1595         "}\n"
1596        ],
1597        "text/plain": [
1598         "<IPython.core.display.Javascript object>"
1599        ]
1600       },
1601       "metadata": {},
1602       "output_type": "display_data"
1603      },
1604      {
1605       "data": {
1606        "text/html": [
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