1  {
   2   "cells": [
   3    {
   4     "cell_type": "code",
   5     "execution_count": 1,
   6     "metadata": {
   7      "collapsed": true
   8     },
   9     "outputs": [],
  10     "source": [
  11      "import pandas as pd\n",
  12      "import numpy as np\n",
  13      "from mpl_toolkits.mplot3d import axes3d\n",
  14      "import matplotlib.pyplot as plt\n",
  15      "\n",
  16      "%matplotlib notebook"
  17     ]
  18    },
  19    {
  20     "cell_type": "code",
  21     "execution_count": 2,
  22     "metadata": {},
  23     "outputs": [
  24      {
  25       "data": {
  26        "application/javascript": [
  27         "/* Put everything inside the global mpl namespace */\n",
  28         "window.mpl = {};\n",
  29         "\n",
  30         "\n",
  31         "mpl.get_websocket_type = function() {\n",
  32         "    if (typeof(WebSocket) !== 'undefined') {\n",
  33         "        return WebSocket;\n",
  34         "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
  35         "        return MozWebSocket;\n",
  36         "    } else {\n",
  37         "        alert('Your browser does not have WebSocket support.' +\n",
  38         "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
  39         "              'Firefox 4 and 5 are also supported but you ' +\n",
  40         "              'have to enable WebSockets in about:config.');\n",
  41         "    };\n",
  42         "}\n",
  43         "\n",
  44         "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
  45         "    this.id = figure_id;\n",
  46         "\n",
  47         "    this.ws = websocket;\n",
  48         "\n",
  49         "    this.supports_binary = (this.ws.binaryType != undefined);\n",
  50         "\n",
  51         "    if (!this.supports_binary) {\n",
  52         "        var warnings = document.getElementById(\"mpl-warnings\");\n",
  53         "        if (warnings) {\n",
  54         "            warnings.style.display = 'block';\n",
  55         "            warnings.textContent = (\n",
  56         "                \"This browser does not support binary websocket messages. \" +\n",
  57         "                    \"Performance may be slow.\");\n",
  58         "        }\n",
  59         "    }\n",
  60         "\n",
  61         "    this.imageObj = new Image();\n",
  62         "\n",
  63         "    this.context = undefined;\n",
  64         "    this.message = undefined;\n",
  65         "    this.canvas = undefined;\n",
  66         "    this.rubberband_canvas = undefined;\n",
  67         "    this.rubberband_context = undefined;\n",
  68         "    this.format_dropdown = undefined;\n",
  69         "\n",
  70         "    this.image_mode = 'full';\n",
  71         "\n",
  72         "    this.root = $('<div/>');\n",
  73         "    this._root_extra_style(this.root)\n",
  74         "    this.root.attr('style', 'display: inline-block');\n",
  75         "\n",
  76         "    $(parent_element).append(this.root);\n",
  77         "\n",
  78         "    this._init_header(this);\n",
  79         "    this._init_canvas(this);\n",
  80         "    this._init_toolbar(this);\n",
  81         "\n",
  82         "    var fig = this;\n",
  83         "\n",
  84         "    this.waiting = false;\n",
  85         "\n",
  86         "    this.ws.onopen =  function () {\n",
  87         "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
  88         "            fig.send_message(\"send_image_mode\", {});\n",
  89         "            if (mpl.ratio != 1) {\n",
  90         "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
  91         "            }\n",
  92         "            fig.send_message(\"refresh\", {});\n",
  93         "        }\n",
  94         "\n",
  95         "    this.imageObj.onload = function() {\n",
  96         "            if (fig.image_mode == 'full') {\n",
  97         "                // Full images could contain transparency (where diff images\n",
  98         "                // almost always do), so we need to clear the canvas so that\n",
  99         "                // there is no ghosting.\n",
 100         "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
 101         "            }\n",
 102         "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
 103         "        };\n",
 104         "\n",
 105         "    this.imageObj.onunload = function() {\n",
 106         "        this.ws.close();\n",
 107         "    }\n",
 108         "\n",
 109         "    this.ws.onmessage = this._make_on_message_function(this);\n",
 110         "\n",
 111         "    this.ondownload = ondownload;\n",
 112         "}\n",
 113         "\n",
 114         "mpl.figure.prototype._init_header = function() {\n",
 115         "    var titlebar = $(\n",
 116         "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
 117         "        'ui-helper-clearfix\"/>');\n",
 118         "    var titletext = $(\n",
 119         "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
 120         "        'text-align: center; padding: 3px;\"/>');\n",
 121         "    titlebar.append(titletext)\n",
 122         "    this.root.append(titlebar);\n",
 123         "    this.header = titletext[0];\n",
 124         "}\n",
 125         "\n",
 126         "\n",
 127         "\n",
 128         "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
 129         "\n",
 130         "}\n",
 131         "\n",
 132         "\n",
 133         "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
 134         "\n",
 135         "}\n",
 136         "\n",
 137         "mpl.figure.prototype._init_canvas = function() {\n",
 138         "    var fig = this;\n",
 139         "\n",
 140         "    var canvas_div = $('<div/>');\n",
 141         "\n",
 142         "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
 143         "\n",
 144         "    function canvas_keyboard_event(event) {\n",
 145         "        return fig.key_event(event, event['data']);\n",
 146         "    }\n",
 147         "\n",
 148         "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
 149         "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
 150         "    this.canvas_div = canvas_div\n",
 151         "    this._canvas_extra_style(canvas_div)\n",
 152         "    this.root.append(canvas_div);\n",
 153         "\n",
 154         "    var canvas = $('<canvas/>');\n",
 155         "    canvas.addClass('mpl-canvas');\n",
 156         "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
 157         "\n",
 158         "    this.canvas = canvas[0];\n",
 159         "    this.context = canvas[0].getContext(\"2d\");\n",
 160         "\n",
 161         "    var backingStore = this.context.backingStorePixelRatio ||\n",
 162         "\tthis.context.webkitBackingStorePixelRatio ||\n",
 163         "\tthis.context.mozBackingStorePixelRatio ||\n",
 164         "\tthis.context.msBackingStorePixelRatio ||\n",
 165         "\tthis.context.oBackingStorePixelRatio ||\n",
 166         "\tthis.context.backingStorePixelRatio || 1;\n",
 167         "\n",
 168         "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
 169         "\n",
 170         "    var rubberband = $('<canvas/>');\n",
 171         "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
 172         "\n",
 173         "    var pass_mouse_events = true;\n",
 174         "\n",
 175         "    canvas_div.resizable({\n",
 176         "        start: function(event, ui) {\n",
 177         "            pass_mouse_events = false;\n",
 178         "        },\n",
 179         "        resize: function(event, ui) {\n",
 180         "            fig.request_resize(ui.size.width, ui.size.height);\n",
 181         "        },\n",
 182         "        stop: function(event, ui) {\n",
 183         "            pass_mouse_events = true;\n",
 184         "            fig.request_resize(ui.size.width, ui.size.height);\n",
 185         "        },\n",
 186         "    });\n",
 187         "\n",
 188         "    function mouse_event_fn(event) {\n",
 189         "        if (pass_mouse_events)\n",
 190         "            return fig.mouse_event(event, event['data']);\n",
 191         "    }\n",
 192         "\n",
 193         "    rubberband.mousedown('button_press', mouse_event_fn);\n",
 194         "    rubberband.mouseup('button_release', mouse_event_fn);\n",
 195         "    // Throttle sequential mouse events to 1 every 20ms.\n",
 196         "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
 197         "\n",
 198         "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
 199         "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
 200         "\n",
 201         "    canvas_div.on(\"wheel\", function (event) {\n",
 202         "        event = event.originalEvent;\n",
 203         "        event['data'] = 'scroll'\n",
 204         "        if (event.deltaY < 0) {\n",
 205         "            event.step = 1;\n",
 206         "        } else {\n",
 207         "            event.step = -1;\n",
 208         "        }\n",
 209         "        mouse_event_fn(event);\n",
 210         "    });\n",
 211         "\n",
 212         "    canvas_div.append(canvas);\n",
 213         "    canvas_div.append(rubberband);\n",
 214         "\n",
 215         "    this.rubberband = rubberband;\n",
 216         "    this.rubberband_canvas = rubberband[0];\n",
 217         "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
 218         "    this.rubberband_context.strokeStyle = \"#000000\";\n",
 219         "\n",
 220         "    this._resize_canvas = function(width, height) {\n",
 221         "        // Keep the size of the canvas, canvas container, and rubber band\n",
 222         "        // canvas in synch.\n",
 223         "        canvas_div.css('width', width)\n",
 224         "        canvas_div.css('height', height)\n",
 225         "\n",
 226         "        canvas.attr('width', width * mpl.ratio);\n",
 227         "        canvas.attr('height', height * mpl.ratio);\n",
 228         "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
 229         "\n",
 230         "        rubberband.attr('width', width);\n",
 231         "        rubberband.attr('height', height);\n",
 232         "    }\n",
 233         "\n",
 234         "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
 235         "    // upon first draw.\n",
 236         "    this._resize_canvas(600, 600);\n",
 237         "\n",
 238         "    // Disable right mouse context menu.\n",
 239         "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
 240         "        return false;\n",
 241         "    });\n",
 242         "\n",
 243         "    function set_focus () {\n",
 244         "        canvas.focus();\n",
 245         "        canvas_div.focus();\n",
 246         "    }\n",
 247         "\n",
 248         "    window.setTimeout(set_focus, 100);\n",
 249         "}\n",
 250         "\n",
 251         "mpl.figure.prototype._init_toolbar = function() {\n",
 252         "    var fig = this;\n",
 253         "\n",
 254         "    var nav_element = $('<div/>')\n",
 255         "    nav_element.attr('style', 'width: 100%');\n",
 256         "    this.root.append(nav_element);\n",
 257         "\n",
 258         "    // Define a callback function for later on.\n",
 259         "    function toolbar_event(event) {\n",
 260         "        return fig.toolbar_button_onclick(event['data']);\n",
 261         "    }\n",
 262         "    function toolbar_mouse_event(event) {\n",
 263         "        return fig.toolbar_button_onmouseover(event['data']);\n",
 264         "    }\n",
 265         "\n",
 266         "    for(var toolbar_ind in mpl.toolbar_items) {\n",
 267         "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
 268         "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
 269         "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
 270         "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
 271         "\n",
 272         "        if (!name) {\n",
 273         "            // put a spacer in here.\n",
 274         "            continue;\n",
 275         "        }\n",
 276         "        var button = $('<button/>');\n",
 277         "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
 278         "                        'ui-button-icon-only');\n",
 279         "        button.attr('role', 'button');\n",
 280         "        button.attr('aria-disabled', 'false');\n",
 281         "        button.click(method_name, toolbar_event);\n",
 282         "        button.mouseover(tooltip, toolbar_mouse_event);\n",
 283         "\n",
 284         "        var icon_img = $('<span/>');\n",
 285         "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
 286         "        icon_img.addClass(image);\n",
 287         "        icon_img.addClass('ui-corner-all');\n",
 288         "\n",
 289         "        var tooltip_span = $('<span/>');\n",
 290         "        tooltip_span.addClass('ui-button-text');\n",
 291         "        tooltip_span.html(tooltip);\n",
 292         "\n",
 293         "        button.append(icon_img);\n",
 294         "        button.append(tooltip_span);\n",
 295         "\n",
 296         "        nav_element.append(button);\n",
 297         "    }\n",
 298         "\n",
 299         "    var fmt_picker_span = $('<span/>');\n",
 300         "\n",
 301         "    var fmt_picker = $('<select/>');\n",
 302         "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
 303         "    fmt_picker_span.append(fmt_picker);\n",
 304         "    nav_element.append(fmt_picker_span);\n",
 305         "    this.format_dropdown = fmt_picker[0];\n",
 306         "\n",
 307         "    for (var ind in mpl.extensions) {\n",
 308         "        var fmt = mpl.extensions[ind];\n",
 309         "        var option = $(\n",
 310         "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
 311         "        fmt_picker.append(option)\n",
 312         "    }\n",
 313         "\n",
 314         "    // Add hover states to the ui-buttons\n",
 315         "    $( \".ui-button\" ).hover(\n",
 316         "        function() { $(this).addClass(\"ui-state-hover\");},\n",
 317         "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
 318         "    );\n",
 319         "\n",
 320         "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
 321         "    nav_element.append(status_bar);\n",
 322         "    this.message = status_bar[0];\n",
 323         "}\n",
 324         "\n",
 325         "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
 326         "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
 327         "    // which will in turn request a refresh of the image.\n",
 328         "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
 329         "}\n",
 330         "\n",
 331         "mpl.figure.prototype.send_message = function(type, properties) {\n",
 332         "    properties['type'] = type;\n",
 333         "    properties['figure_id'] = this.id;\n",
 334         "    this.ws.send(JSON.stringify(properties));\n",
 335         "}\n",
 336         "\n",
 337         "mpl.figure.prototype.send_draw_message = function() {\n",
 338         "    if (!this.waiting) {\n",
 339         "        this.waiting = true;\n",
 340         "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
 341         "    }\n",
 342         "}\n",
 343         "\n",
 344         "\n",
 345         "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
 346         "    var format_dropdown = fig.format_dropdown;\n",
 347         "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
 348         "    fig.ondownload(fig, format);\n",
 349         "}\n",
 350         "\n",
 351         "\n",
 352         "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
 353         "    var size = msg['size'];\n",
 354         "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
 355         "        fig._resize_canvas(size[0], size[1]);\n",
 356         "        fig.send_message(\"refresh\", {});\n",
 357         "    };\n",
 358         "}\n",
 359         "\n",
 360         "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
 361         "    var x0 = msg['x0'] / mpl.ratio;\n",
 362         "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
 363         "    var x1 = msg['x1'] / mpl.ratio;\n",
 364         "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
 365         "    x0 = Math.floor(x0) + 0.5;\n",
 366         "    y0 = Math.floor(y0) + 0.5;\n",
 367         "    x1 = Math.floor(x1) + 0.5;\n",
 368         "    y1 = Math.floor(y1) + 0.5;\n",
 369         "    var min_x = Math.min(x0, x1);\n",
 370         "    var min_y = Math.min(y0, y1);\n",
 371         "    var width = Math.abs(x1 - x0);\n",
 372         "    var height = Math.abs(y1 - y0);\n",
 373         "\n",
 374         "    fig.rubberband_context.clearRect(\n",
 375         "        0, 0, fig.canvas.width, fig.canvas.height);\n",
 376         "\n",
 377         "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
 378         "}\n",
 379         "\n",
 380         "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
 381         "    // Updates the figure title.\n",
 382         "    fig.header.textContent = msg['label'];\n",
 383         "}\n",
 384         "\n",
 385         "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
 386         "    var cursor = msg['cursor'];\n",
 387         "    switch(cursor)\n",
 388         "    {\n",
 389         "    case 0:\n",
 390         "        cursor = 'pointer';\n",
 391         "        break;\n",
 392         "    case 1:\n",
 393         "        cursor = 'default';\n",
 394         "        break;\n",
 395         "    case 2:\n",
 396         "        cursor = 'crosshair';\n",
 397         "        break;\n",
 398         "    case 3:\n",
 399         "        cursor = 'move';\n",
 400         "        break;\n",
 401         "    }\n",
 402         "    fig.rubberband_canvas.style.cursor = cursor;\n",
 403         "}\n",
 404         "\n",
 405         "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
 406         "    fig.message.textContent = msg['message'];\n",
 407         "}\n",
 408         "\n",
 409         "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
 410         "    // Request the server to send over a new figure.\n",
 411         "    fig.send_draw_message();\n",
 412         "}\n",
 413         "\n",
 414         "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
 415         "    fig.image_mode = msg['mode'];\n",
 416         "}\n",
 417         "\n",
 418         "mpl.figure.prototype.updated_canvas_event = function() {\n",
 419         "    // Called whenever the canvas gets updated.\n",
 420         "    this.send_message(\"ack\", {});\n",
 421         "}\n",
 422         "\n",
 423         "// A function to construct a web socket function for onmessage handling.\n",
 424         "// Called in the figure constructor.\n",
 425         "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
 426         "    return function socket_on_message(evt) {\n",
 427         "        if (evt.data instanceof Blob) {\n",
 428         "            /* FIXME: We get \"Resource interpreted as Image but\n",
 429         "             * transferred with MIME type text/plain:\" errors on\n",
 430         "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
 431         "             * to be part of the websocket stream */\n",
 432         "            evt.data.type = \"image/png\";\n",
 433         "\n",
 434         "            /* Free the memory for the previous frames */\n",
 435         "            if (fig.imageObj.src) {\n",
 436         "                (window.URL || window.webkitURL).revokeObjectURL(\n",
 437         "                    fig.imageObj.src);\n",
 438         "            }\n",
 439         "\n",
 440         "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
 441         "                evt.data);\n",
 442         "            fig.updated_canvas_event();\n",
 443         "            fig.waiting = false;\n",
 444         "            return;\n",
 445         "        }\n",
 446         "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
 447         "            fig.imageObj.src = evt.data;\n",
 448         "            fig.updated_canvas_event();\n",
 449         "            fig.waiting = false;\n",
 450         "            return;\n",
 451         "        }\n",
 452         "\n",
 453         "        var msg = JSON.parse(evt.data);\n",
 454         "        var msg_type = msg['type'];\n",
 455         "\n",
 456         "        // Call the  \"handle_{type}\" callback, which takes\n",
 457         "        // the figure and JSON message as its only arguments.\n",
 458         "        try {\n",
 459         "            var callback = fig[\"handle_\" + msg_type];\n",
 460         "        } catch (e) {\n",
 461         "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
 462         "            return;\n",
 463         "        }\n",
 464         "\n",
 465         "        if (callback) {\n",
 466         "            try {\n",
 467         "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
 468         "                callback(fig, msg);\n",
 469         "            } catch (e) {\n",
 470         "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
 471         "            }\n",
 472         "        }\n",
 473         "    };\n",
 474         "}\n",
 475         "\n",
 476         "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
 477         "mpl.findpos = function(e) {\n",
 478         "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
 479         "    var targ;\n",
 480         "    if (!e)\n",
 481         "        e = window.event;\n",
 482         "    if (e.target)\n",
 483         "        targ = e.target;\n",
 484         "    else if (e.srcElement)\n",
 485         "        targ = e.srcElement;\n",
 486         "    if (targ.nodeType == 3) // defeat Safari bug\n",
 487         "        targ = targ.parentNode;\n",
 488         "\n",
 489         "    // jQuery normalizes the pageX and pageY\n",
 490         "    // pageX,Y are the mouse positions relative to the document\n",
 491         "    // offset() returns the position of the element relative to the document\n",
 492         "    var x = e.pageX - $(targ).offset().left;\n",
 493         "    var y = e.pageY - $(targ).offset().top;\n",
 494         "\n",
 495         "    return {\"x\": x, \"y\": y};\n",
 496         "};\n",
 497         "\n",
 498         "/*\n",
 499         " * return a copy of an object with only non-object keys\n",
 500         " * we need this to avoid circular references\n",
 501         " * http://stackoverflow.com/a/24161582/3208463\n",
 502         " */\n",
 503         "function simpleKeys (original) {\n",
 504         "  return Object.keys(original).reduce(function (obj, key) {\n",
 505         "    if (typeof original[key] !== 'object')\n",
 506         "        obj[key] = original[key]\n",
 507         "    return obj;\n",
 508         "  }, {});\n",
 509         "}\n",
 510         "\n",
 511         "mpl.figure.prototype.mouse_event = function(event, name) {\n",
 512         "    var canvas_pos = mpl.findpos(event)\n",
 513         "\n",
 514         "    if (name === 'button_press')\n",
 515         "    {\n",
 516         "        this.canvas.focus();\n",
 517         "        this.canvas_div.focus();\n",
 518         "    }\n",
 519         "\n",
 520         "    var x = canvas_pos.x * mpl.ratio;\n",
 521         "    var y = canvas_pos.y * mpl.ratio;\n",
 522         "\n",
 523         "    this.send_message(name, {x: x, y: y, button: event.button,\n",
 524         "                             step: event.step,\n",
 525         "                             guiEvent: simpleKeys(event)});\n",
 526         "\n",
 527         "    /* This prevents the web browser from automatically changing to\n",
 528         "     * the text insertion cursor when the button is pressed.  We want\n",
 529         "     * to control all of the cursor setting manually through the\n",
 530         "     * 'cursor' event from matplotlib */\n",
 531         "    event.preventDefault();\n",
 532         "    return false;\n",
 533         "}\n",
 534         "\n",
 535         "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
 536         "    // Handle any extra behaviour associated with a key event\n",
 537         "}\n",
 538         "\n",
 539         "mpl.figure.prototype.key_event = function(event, name) {\n",
 540         "\n",
 541         "    // Prevent repeat events\n",
 542         "    if (name == 'key_press')\n",
 543         "    {\n",
 544         "        if (event.which === this._key)\n",
 545         "            return;\n",
 546         "        else\n",
 547         "            this._key = event.which;\n",
 548         "    }\n",
 549         "    if (name == 'key_release')\n",
 550         "        this._key = null;\n",
 551         "\n",
 552         "    var value = '';\n",
 553         "    if (event.ctrlKey && event.which != 17)\n",
 554         "        value += \"ctrl+\";\n",
 555         "    if (event.altKey && event.which != 18)\n",
 556         "        value += \"alt+\";\n",
 557         "    if (event.shiftKey && event.which != 16)\n",
 558         "        value += \"shift+\";\n",
 559         "\n",
 560         "    value += 'k';\n",
 561         "    value += event.which.toString();\n",
 562         "\n",
 563         "    this._key_event_extra(event, name);\n",
 564         "\n",
 565         "    this.send_message(name, {key: value,\n",
 566         "                             guiEvent: simpleKeys(event)});\n",
 567         "    return false;\n",
 568         "}\n",
 569         "\n",
 570         "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
 571         "    if (name == 'download') {\n",
 572         "        this.handle_save(this, null);\n",
 573         "    } else {\n",
 574         "        this.send_message(\"toolbar_button\", {name: name});\n",
 575         "    }\n",
 576         "};\n",
 577         "\n",
 578         "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
 579         "    this.message.textContent = tooltip;\n",
 580         "};\n",
 581         "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",
 582         "\n",
 583         "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
 584         "\n",
 585         "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
 586         "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
 587         "    // object with the appropriate methods. Currently this is a non binary\n",
 588         "    // socket, so there is still some room for performance tuning.\n",
 589         "    var ws = {};\n",
 590         "\n",
 591         "    ws.close = function() {\n",
 592         "        comm.close()\n",
 593         "    };\n",
 594         "    ws.send = function(m) {\n",
 595         "        //console.log('sending', m);\n",
 596         "        comm.send(m);\n",
 597         "    };\n",
 598         "    // Register the callback with on_msg.\n",
 599         "    comm.on_msg(function(msg) {\n",
 600         "        //console.log('receiving', msg['content']['data'], msg);\n",
 601         "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
 602         "        ws.onmessage(msg['content']['data'])\n",
 603         "    });\n",
 604         "    return ws;\n",
 605         "}\n",
 606         "\n",
 607         "mpl.mpl_figure_comm = function(comm, msg) {\n",
 608         "    // This is the function which gets called when the mpl process\n",
 609         "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
 610         "\n",
 611         "    var id = msg.content.data.id;\n",
 612         "    // Get hold of the div created by the display call when the Comm\n",
 613         "    // socket was opened in Python.\n",
 614         "    var element = $(\"#\" + id);\n",
 615         "    var ws_proxy = comm_websocket_adapter(comm)\n",
 616         "\n",
 617         "    function ondownload(figure, format) {\n",
 618         "        window.open(figure.imageObj.src);\n",
 619         "    }\n",
 620         "\n",
 621         "    var fig = new mpl.figure(id, ws_proxy,\n",
 622         "                           ondownload,\n",
 623         "                           element.get(0));\n",
 624         "\n",
 625         "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
 626         "    // web socket which is closed, not our websocket->open comm proxy.\n",
 627         "    ws_proxy.onopen();\n",
 628         "\n",
 629         "    fig.parent_element = element.get(0);\n",
 630         "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
 631         "    if (!fig.cell_info) {\n",
 632         "        console.error(\"Failed to find cell for figure\", id, fig);\n",
 633         "        return;\n",
 634         "    }\n",
 635         "\n",
 636         "    var output_index = fig.cell_info[2]\n",
 637         "    var cell = fig.cell_info[0];\n",
 638         "\n",
 639         "};\n",
 640         "\n",
 641         "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
 642         "    var width = fig.canvas.width/mpl.ratio\n",
 643         "    fig.root.unbind('remove')\n",
 644         "\n",
 645         "    // Update the output cell to use the data from the current canvas.\n",
 646         "    fig.push_to_output();\n",
 647         "    var dataURL = fig.canvas.toDataURL();\n",
 648         "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
 649         "    // the notebook keyboard shortcuts fail.\n",
 650         "    IPython.keyboard_manager.enable()\n",
 651         "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
 652         "    fig.close_ws(fig, msg);\n",
 653         "}\n",
 654         "\n",
 655         "mpl.figure.prototype.close_ws = function(fig, msg){\n",
 656         "    fig.send_message('closing', msg);\n",
 657         "    // fig.ws.close()\n",
 658         "}\n",
 659         "\n",
 660         "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
 661         "    // Turn the data on the canvas into data in the output cell.\n",
 662         "    var width = this.canvas.width/mpl.ratio\n",
 663         "    var dataURL = this.canvas.toDataURL();\n",
 664         "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
 665         "}\n",
 666         "\n",
 667         "mpl.figure.prototype.updated_canvas_event = function() {\n",
 668         "    // Tell IPython that the notebook contents must change.\n",
 669         "    IPython.notebook.set_dirty(true);\n",
 670         "    this.send_message(\"ack\", {});\n",
 671         "    var fig = this;\n",
 672         "    // Wait a second, then push the new image to the DOM so\n",
 673         "    // that it is saved nicely (might be nice to debounce this).\n",
 674         "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
 675         "}\n",
 676         "\n",
 677         "mpl.figure.prototype._init_toolbar = function() {\n",
 678         "    var fig = this;\n",
 679         "\n",
 680         "    var nav_element = $('<div/>')\n",
 681         "    nav_element.attr('style', 'width: 100%');\n",
 682         "    this.root.append(nav_element);\n",
 683         "\n",
 684         "    // Define a callback function for later on.\n",
 685         "    function toolbar_event(event) {\n",
 686         "        return fig.toolbar_button_onclick(event['data']);\n",
 687         "    }\n",
 688         "    function toolbar_mouse_event(event) {\n",
 689         "        return fig.toolbar_button_onmouseover(event['data']);\n",
 690         "    }\n",
 691         "\n",
 692         "    for(var toolbar_ind in mpl.toolbar_items){\n",
 693         "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
 694         "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
 695         "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
 696         "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
 697         "\n",
 698         "        if (!name) { continue; };\n",
 699         "\n",
 700         "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
 701         "        button.click(method_name, toolbar_event);\n",
 702         "        button.mouseover(tooltip, toolbar_mouse_event);\n",
 703         "        nav_element.append(button);\n",
 704         "    }\n",
 705         "\n",
 706         "    // Add the status bar.\n",
 707         "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
 708         "    nav_element.append(status_bar);\n",
 709         "    this.message = status_bar[0];\n",
 710         "\n",
 711         "    // Add the close button to the window.\n",
 712         "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
 713         "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
 714         "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
 715         "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
 716         "    buttongrp.append(button);\n",
 717         "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
 718         "    titlebar.prepend(buttongrp);\n",
 719         "}\n",
 720         "\n",
 721         "mpl.figure.prototype._root_extra_style = function(el){\n",
 722         "    var fig = this\n",
 723         "    el.on(\"remove\", function(){\n",
 724         "\tfig.close_ws(fig, {});\n",
 725         "    });\n",
 726         "}\n",
 727         "\n",
 728         "mpl.figure.prototype._canvas_extra_style = function(el){\n",
 729         "    // this is important to make the div 'focusable\n",
 730         "    el.attr('tabindex', 0)\n",
 731         "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
 732         "    // off when our div gets focus\n",
 733         "\n",
 734         "    // location in version 3\n",
 735         "    if (IPython.notebook.keyboard_manager) {\n",
 736         "        IPython.notebook.keyboard_manager.register_events(el);\n",
 737         "    }\n",
 738         "    else {\n",
 739         "        // location in version 2\n",
 740         "        IPython.keyboard_manager.register_events(el);\n",
 741         "    }\n",
 742         "\n",
 743         "}\n",
 744         "\n",
 745         "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
 746         "    var manager = IPython.notebook.keyboard_manager;\n",
 747         "    if (!manager)\n",
 748         "        manager = IPython.keyboard_manager;\n",
 749         "\n",
 750         "    // Check for shift+enter\n",
 751         "    if (event.shiftKey && event.which == 13) {\n",
 752         "        this.canvas_div.blur();\n",
 753         "        // select the cell after this one\n",
 754         "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
 755         "        IPython.notebook.select(index + 1);\n",
 756         "    }\n",
 757         "}\n",
 758         "\n",
 759         "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
 760         "    fig.ondownload(fig, null);\n",
 761         "}\n",
 762         "\n",
 763         "\n",
 764         "mpl.find_output_cell = function(html_output) {\n",
 765         "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
 766         "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
 767         "    // IPython event is triggered only after the cells have been serialised, which for\n",
 768         "    // our purposes (turning an active figure into a static one), is too late.\n",
 769         "    var cells = IPython.notebook.get_cells();\n",
 770         "    var ncells = cells.length;\n",
 771         "    for (var i=0; i<ncells; i++) {\n",
 772         "        var cell = cells[i];\n",
 773         "        if (cell.cell_type === 'code'){\n",
 774         "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
 775         "                var data = cell.output_area.outputs[j];\n",
 776         "                if (data.data) {\n",
 777         "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
 778         "                    data = data.data;\n",
 779         "                }\n",
 780         "                if (data['text/html'] == html_output) {\n",
 781         "                    return [cell, data, j];\n",
 782         "                }\n",
 783         "            }\n",
 784         "        }\n",
 785         "    }\n",
 786         "}\n",
 787         "\n",
 788         "// Register the function which deals with the matplotlib target/channel.\n",
 789         "// The kernel may be null if the page has been refreshed.\n",
 790         "if (IPython.notebook.kernel != null) {\n",
 791         "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
 792         "}\n"
 793        ],
 794        "text/plain": [
 795         "<IPython.core.display.Javascript object>"
 796        ]
 797       },
 798       "metadata": {},
 799       "output_type": "display_data"
 800      },
 801      {
 802       "data": {
 803        "text/html": [
 804         "<img src=\"data:image/png;base64,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\" width=\"640\">"
 805        ],
 806        "text/plain": [
 807         "<IPython.core.display.HTML object>"
 808        ]
 809       },
 810       "metadata": {},
 811       "output_type": "display_data"
 812      }
 813     ],
 814     "source": [
 815      "iris = pd.read_csv('iris.csv')\n",
 816      "\n",
 817      "plt.figure()\n",
 818      "\n",
 819      "for species, irissubset in iris.groupby('Name'):\n",
 820      "    plt.scatter(irissubset['PetalLength'], irissubset['PetalWidth'], alpha=0.8, label=species)\n",
 821      "\n",
 822      "plt.xlabel('PetalLength')\n",
 823      "plt.ylabel('PetalWidth')\n",
 824      "plt.legend();\n"
 825     ]
 826    },
 827    {
 828     "cell_type": "code",
 829     "execution_count": 3,
 830     "metadata": {},
 831     "outputs": [
 832      {
 833       "data": {
 834        "application/javascript": [
 835         "/* Put everything inside the global mpl namespace */\n",
 836         "window.mpl = {};\n",
 837         "\n",
 838         "\n",
 839         "mpl.get_websocket_type = function() {\n",
 840         "    if (typeof(WebSocket) !== 'undefined') {\n",
 841         "        return WebSocket;\n",
 842         "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
 843         "        return MozWebSocket;\n",
 844         "    } else {\n",
 845         "        alert('Your browser does not have WebSocket support.' +\n",
 846         "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
 847         "              'Firefox 4 and 5 are also supported but you ' +\n",
 848         "              'have to enable WebSockets in about:config.');\n",
 849         "    };\n",
 850         "}\n",
 851         "\n",
 852         "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
 853         "    this.id = figure_id;\n",
 854         "\n",
 855         "    this.ws = websocket;\n",
 856         "\n",
 857         "    this.supports_binary = (this.ws.binaryType != undefined);\n",
 858         "\n",
 859         "    if (!this.supports_binary) {\n",
 860         "        var warnings = document.getElementById(\"mpl-warnings\");\n",
 861         "        if (warnings) {\n",
 862         "            warnings.style.display = 'block';\n",
 863         "            warnings.textContent = (\n",
 864         "                \"This browser does not support binary websocket messages. \" +\n",
 865         "                    \"Performance may be slow.\");\n",
 866         "        }\n",
 867         "    }\n",
 868         "\n",
 869         "    this.imageObj = new Image();\n",
 870         "\n",
 871         "    this.context = undefined;\n",
 872         "    this.message = undefined;\n",
 873         "    this.canvas = undefined;\n",
 874         "    this.rubberband_canvas = undefined;\n",
 875         "    this.rubberband_context = undefined;\n",
 876         "    this.format_dropdown = undefined;\n",
 877         "\n",
 878         "    this.image_mode = 'full';\n",
 879         "\n",
 880         "    this.root = $('<div/>');\n",
 881         "    this._root_extra_style(this.root)\n",
 882         "    this.root.attr('style', 'display: inline-block');\n",
 883         "\n",
 884         "    $(parent_element).append(this.root);\n",
 885         "\n",
 886         "    this._init_header(this);\n",
 887         "    this._init_canvas(this);\n",
 888         "    this._init_toolbar(this);\n",
 889         "\n",
 890         "    var fig = this;\n",
 891         "\n",
 892         "    this.waiting = false;\n",
 893         "\n",
 894         "    this.ws.onopen =  function () {\n",
 895         "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
 896         "            fig.send_message(\"send_image_mode\", {});\n",
 897         "            if (mpl.ratio != 1) {\n",
 898         "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
 899         "            }\n",
 900         "            fig.send_message(\"refresh\", {});\n",
 901         "        }\n",
 902         "\n",
 903         "    this.imageObj.onload = function() {\n",
 904         "            if (fig.image_mode == 'full') {\n",
 905         "                // Full images could contain transparency (where diff images\n",
 906         "                // almost always do), so we need to clear the canvas so that\n",
 907         "                // there is no ghosting.\n",
 908         "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
 909         "            }\n",
 910         "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
 911         "        };\n",
 912         "\n",
 913         "    this.imageObj.onunload = function() {\n",
 914         "        this.ws.close();\n",
 915         "    }\n",
 916         "\n",
 917         "    this.ws.onmessage = this._make_on_message_function(this);\n",
 918         "\n",
 919         "    this.ondownload = ondownload;\n",
 920         "}\n",
 921         "\n",
 922         "mpl.figure.prototype._init_header = function() {\n",
 923         "    var titlebar = $(\n",
 924         "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
 925         "        'ui-helper-clearfix\"/>');\n",
 926         "    var titletext = $(\n",
 927         "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
 928         "        'text-align: center; padding: 3px;\"/>');\n",
 929         "    titlebar.append(titletext)\n",
 930         "    this.root.append(titlebar);\n",
 931         "    this.header = titletext[0];\n",
 932         "}\n",
 933         "\n",
 934         "\n",
 935         "\n",
 936         "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
 937         "\n",
 938         "}\n",
 939         "\n",
 940         "\n",
 941         "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
 942         "\n",
 943         "}\n",
 944         "\n",
 945         "mpl.figure.prototype._init_canvas = function() {\n",
 946         "    var fig = this;\n",
 947         "\n",
 948         "    var canvas_div = $('<div/>');\n",
 949         "\n",
 950         "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
 951         "\n",
 952         "    function canvas_keyboard_event(event) {\n",
 953         "        return fig.key_event(event, event['data']);\n",
 954         "    }\n",
 955         "\n",
 956         "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
 957         "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
 958         "    this.canvas_div = canvas_div\n",
 959         "    this._canvas_extra_style(canvas_div)\n",
 960         "    this.root.append(canvas_div);\n",
 961         "\n",
 962         "    var canvas = $('<canvas/>');\n",
 963         "    canvas.addClass('mpl-canvas');\n",
 964         "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
 965         "\n",
 966         "    this.canvas = canvas[0];\n",
 967         "    this.context = canvas[0].getContext(\"2d\");\n",
 968         "\n",
 969         "    var backingStore = this.context.backingStorePixelRatio ||\n",
 970         "\tthis.context.webkitBackingStorePixelRatio ||\n",
 971         "\tthis.context.mozBackingStorePixelRatio ||\n",
 972         "\tthis.context.msBackingStorePixelRatio ||\n",
 973         "\tthis.context.oBackingStorePixelRatio ||\n",
 974         "\tthis.context.backingStorePixelRatio || 1;\n",
 975         "\n",
 976         "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
 977         "\n",
 978         "    var rubberband = $('<canvas/>');\n",
 979         "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
 980         "\n",
 981         "    var pass_mouse_events = true;\n",
 982         "\n",
 983         "    canvas_div.resizable({\n",
 984         "        start: function(event, ui) {\n",
 985         "            pass_mouse_events = false;\n",
 986         "        },\n",
 987         "        resize: function(event, ui) {\n",
 988         "            fig.request_resize(ui.size.width, ui.size.height);\n",
 989         "        },\n",
 990         "        stop: function(event, ui) {\n",
 991         "            pass_mouse_events = true;\n",
 992         "            fig.request_resize(ui.size.width, ui.size.height);\n",
 993         "        },\n",
 994         "    });\n",
 995         "\n",
 996         "    function mouse_event_fn(event) {\n",
 997         "        if (pass_mouse_events)\n",
 998         "            return fig.mouse_event(event, event['data']);\n",
 999         "    }\n",
1000         "\n",
1001         "    rubberband.mousedown('button_press', mouse_event_fn);\n",
1002         "    rubberband.mouseup('button_release', mouse_event_fn);\n",
1003         "    // Throttle sequential mouse events to 1 every 20ms.\n",
1004         "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
1005         "\n",
1006         "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
1007         "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
1008         "\n",
1009         "    canvas_div.on(\"wheel\", function (event) {\n",
1010         "        event = event.originalEvent;\n",
1011         "        event['data'] = 'scroll'\n",
1012         "        if (event.deltaY < 0) {\n",
1013         "            event.step = 1;\n",
1014         "        } else {\n",
1015         "            event.step = -1;\n",
1016         "        }\n",
1017         "        mouse_event_fn(event);\n",
1018         "    });\n",
1019         "\n",
1020         "    canvas_div.append(canvas);\n",
1021         "    canvas_div.append(rubberband);\n",
1022         "\n",
1023         "    this.rubberband = rubberband;\n",
1024         "    this.rubberband_canvas = rubberband[0];\n",
1025         "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
1026         "    this.rubberband_context.strokeStyle = \"#000000\";\n",
1027         "\n",
1028         "    this._resize_canvas = function(width, height) {\n",
1029         "        // Keep the size of the canvas, canvas container, and rubber band\n",
1030         "        // canvas in synch.\n",
1031         "        canvas_div.css('width', width)\n",
1032         "        canvas_div.css('height', height)\n",
1033         "\n",
1034         "        canvas.attr('width', width * mpl.ratio);\n",
1035         "        canvas.attr('height', height * mpl.ratio);\n",
1036         "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
1037         "\n",
1038         "        rubberband.attr('width', width);\n",
1039         "        rubberband.attr('height', height);\n",
1040         "    }\n",
1041         "\n",
1042         "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
1043         "    // upon first draw.\n",
1044         "    this._resize_canvas(600, 600);\n",
1045         "\n",
1046         "    // Disable right mouse context menu.\n",
1047         "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
1048         "        return false;\n",
1049         "    });\n",
1050         "\n",
1051         "    function set_focus () {\n",
1052         "        canvas.focus();\n",
1053         "        canvas_div.focus();\n",
1054         "    }\n",
1055         "\n",
1056         "    window.setTimeout(set_focus, 100);\n",
1057         "}\n",
1058         "\n",
1059         "mpl.figure.prototype._init_toolbar = function() {\n",
1060         "    var fig = this;\n",
1061         "\n",
1062         "    var nav_element = $('<div/>')\n",
1063         "    nav_element.attr('style', 'width: 100%');\n",
1064         "    this.root.append(nav_element);\n",
1065         "\n",
1066         "    // Define a callback function for later on.\n",
1067         "    function toolbar_event(event) {\n",
1068         "        return fig.toolbar_button_onclick(event['data']);\n",
1069         "    }\n",
1070         "    function toolbar_mouse_event(event) {\n",
1071         "        return fig.toolbar_button_onmouseover(event['data']);\n",
1072         "    }\n",
1073         "\n",
1074         "    for(var toolbar_ind in mpl.toolbar_items) {\n",
1075         "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
1076         "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
1077         "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
1078         "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
1079         "\n",
1080         "        if (!name) {\n",
1081         "            // put a spacer in here.\n",
1082         "            continue;\n",
1083         "        }\n",
1084         "        var button = $('<button/>');\n",
1085         "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
1086         "                        'ui-button-icon-only');\n",
1087         "        button.attr('role', 'button');\n",
1088         "        button.attr('aria-disabled', 'false');\n",
1089         "        button.click(method_name, toolbar_event);\n",
1090         "        button.mouseover(tooltip, toolbar_mouse_event);\n",
1091         "\n",
1092         "        var icon_img = $('<span/>');\n",
1093         "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
1094         "        icon_img.addClass(image);\n",
1095         "        icon_img.addClass('ui-corner-all');\n",
1096         "\n",
1097         "        var tooltip_span = $('<span/>');\n",
1098         "        tooltip_span.addClass('ui-button-text');\n",
1099         "        tooltip_span.html(tooltip);\n",
1100         "\n",
1101         "        button.append(icon_img);\n",
1102         "        button.append(tooltip_span);\n",
1103         "\n",
1104         "        nav_element.append(button);\n",
1105         "    }\n",
1106         "\n",
1107         "    var fmt_picker_span = $('<span/>');\n",
1108         "\n",
1109         "    var fmt_picker = $('<select/>');\n",
1110         "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
1111         "    fmt_picker_span.append(fmt_picker);\n",
1112         "    nav_element.append(fmt_picker_span);\n",
1113         "    this.format_dropdown = fmt_picker[0];\n",
1114         "\n",
1115         "    for (var ind in mpl.extensions) {\n",
1116         "        var fmt = mpl.extensions[ind];\n",
1117         "        var option = $(\n",
1118         "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
1119         "        fmt_picker.append(option)\n",
1120         "    }\n",
1121         "\n",
1122         "    // Add hover states to the ui-buttons\n",
1123         "    $( \".ui-button\" ).hover(\n",
1124         "        function() { $(this).addClass(\"ui-state-hover\");},\n",
1125         "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
1126         "    );\n",
1127         "\n",
1128         "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
1129         "    nav_element.append(status_bar);\n",
1130         "    this.message = status_bar[0];\n",
1131         "}\n",
1132         "\n",
1133         "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
1134         "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
1135         "    // which will in turn request a refresh of the image.\n",
1136         "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
1137         "}\n",
1138         "\n",
1139         "mpl.figure.prototype.send_message = function(type, properties) {\n",
1140         "    properties['type'] = type;\n",
1141         "    properties['figure_id'] = this.id;\n",
1142         "    this.ws.send(JSON.stringify(properties));\n",
1143         "}\n",
1144         "\n",
1145         "mpl.figure.prototype.send_draw_message = function() {\n",
1146         "    if (!this.waiting) {\n",
1147         "        this.waiting = true;\n",
1148         "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
1149         "    }\n",
1150         "}\n",
1151         "\n",
1152         "\n",
1153         "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
1154         "    var format_dropdown = fig.format_dropdown;\n",
1155         "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
1156         "    fig.ondownload(fig, format);\n",
1157         "}\n",
1158         "\n",
1159         "\n",
1160         "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
1161         "    var size = msg['size'];\n",
1162         "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
1163         "        fig._resize_canvas(size[0], size[1]);\n",
1164         "        fig.send_message(\"refresh\", {});\n",
1165         "    };\n",
1166         "}\n",
1167         "\n",
1168         "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
1169         "    var x0 = msg['x0'] / mpl.ratio;\n",
1170         "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
1171         "    var x1 = msg['x1'] / mpl.ratio;\n",
1172         "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
1173         "    x0 = Math.floor(x0) + 0.5;\n",
1174         "    y0 = Math.floor(y0) + 0.5;\n",
1175         "    x1 = Math.floor(x1) + 0.5;\n",
1176         "    y1 = Math.floor(y1) + 0.5;\n",
1177         "    var min_x = Math.min(x0, x1);\n",
1178         "    var min_y = Math.min(y0, y1);\n",
1179         "    var width = Math.abs(x1 - x0);\n",
1180         "    var height = Math.abs(y1 - y0);\n",
1181         "\n",
1182         "    fig.rubberband_context.clearRect(\n",
1183         "        0, 0, fig.canvas.width, fig.canvas.height);\n",
1184         "\n",
1185         "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
1186         "}\n",
1187         "\n",
1188         "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
1189         "    // Updates the figure title.\n",
1190         "    fig.header.textContent = msg['label'];\n",
1191         "}\n",
1192         "\n",
1193         "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
1194         "    var cursor = msg['cursor'];\n",
1195         "    switch(cursor)\n",
1196         "    {\n",
1197         "    case 0:\n",
1198         "        cursor = 'pointer';\n",
1199         "        break;\n",
1200         "    case 1:\n",
1201         "        cursor = 'default';\n",
1202         "        break;\n",
1203         "    case 2:\n",
1204         "        cursor = 'crosshair';\n",
1205         "        break;\n",
1206         "    case 3:\n",
1207         "        cursor = 'move';\n",
1208         "        break;\n",
1209         "    }\n",
1210         "    fig.rubberband_canvas.style.cursor = cursor;\n",
1211         "}\n",
1212         "\n",
1213         "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
1214         "    fig.message.textContent = msg['message'];\n",
1215         "}\n",
1216         "\n",
1217         "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
1218         "    // Request the server to send over a new figure.\n",
1219         "    fig.send_draw_message();\n",
1220         "}\n",
1221         "\n",
1222         "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
1223         "    fig.image_mode = msg['mode'];\n",
1224         "}\n",
1225         "\n",
1226         "mpl.figure.prototype.updated_canvas_event = function() {\n",
1227         "    // Called whenever the canvas gets updated.\n",
1228         "    this.send_message(\"ack\", {});\n",
1229         "}\n",
1230         "\n",
1231         "// A function to construct a web socket function for onmessage handling.\n",
1232         "// Called in the figure constructor.\n",
1233         "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
1234         "    return function socket_on_message(evt) {\n",
1235         "        if (evt.data instanceof Blob) {\n",
1236         "            /* FIXME: We get \"Resource interpreted as Image but\n",
1237         "             * transferred with MIME type text/plain:\" errors on\n",
1238         "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
1239         "             * to be part of the websocket stream */\n",
1240         "            evt.data.type = \"image/png\";\n",
1241         "\n",
1242         "            /* Free the memory for the previous frames */\n",
1243         "            if (fig.imageObj.src) {\n",
1244         "                (window.URL || window.webkitURL).revokeObjectURL(\n",
1245         "                    fig.imageObj.src);\n",
1246         "            }\n",
1247         "\n",
1248         "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
1249         "                evt.data);\n",
1250         "            fig.updated_canvas_event();\n",
1251         "            fig.waiting = false;\n",
1252         "            return;\n",
1253         "        }\n",
1254         "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
1255         "            fig.imageObj.src = evt.data;\n",
1256         "            fig.updated_canvas_event();\n",
1257         "            fig.waiting = false;\n",
1258         "            return;\n",
1259         "        }\n",
1260         "\n",
1261         "        var msg = JSON.parse(evt.data);\n",
1262         "        var msg_type = msg['type'];\n",
1263         "\n",
1264         "        // Call the  \"handle_{type}\" callback, which takes\n",
1265         "        // the figure and JSON message as its only arguments.\n",
1266         "        try {\n",
1267         "            var callback = fig[\"handle_\" + msg_type];\n",
1268         "        } catch (e) {\n",
1269         "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
1270         "            return;\n",
1271         "        }\n",
1272         "\n",
1273         "        if (callback) {\n",
1274         "            try {\n",
1275         "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
1276         "                callback(fig, msg);\n",
1277         "            } catch (e) {\n",
1278         "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
1279         "            }\n",
1280         "        }\n",
1281         "    };\n",
1282         "}\n",
1283         "\n",
1284         "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
1285         "mpl.findpos = function(e) {\n",
1286         "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
1287         "    var targ;\n",
1288         "    if (!e)\n",
1289         "        e = window.event;\n",
1290         "    if (e.target)\n",
1291         "        targ = e.target;\n",
1292         "    else if (e.srcElement)\n",
1293         "        targ = e.srcElement;\n",
1294         "    if (targ.nodeType == 3) // defeat Safari bug\n",
1295         "        targ = targ.parentNode;\n",
1296         "\n",
1297         "    // jQuery normalizes the pageX and pageY\n",
1298         "    // pageX,Y are the mouse positions relative to the document\n",
1299         "    // offset() returns the position of the element relative to the document\n",
1300         "    var x = e.pageX - $(targ).offset().left;\n",
1301         "    var y = e.pageY - $(targ).offset().top;\n",
1302         "\n",
1303         "    return {\"x\": x, \"y\": y};\n",
1304         "};\n",
1305         "\n",
1306         "/*\n",
1307         " * return a copy of an object with only non-object keys\n",
1308         " * we need this to avoid circular references\n",
1309         " * http://stackoverflow.com/a/24161582/3208463\n",
1310         " */\n",
1311         "function simpleKeys (original) {\n",
1312         "  return Object.keys(original).reduce(function (obj, key) {\n",
1313         "    if (typeof original[key] !== 'object')\n",
1314         "        obj[key] = original[key]\n",
1315         "    return obj;\n",
1316         "  }, {});\n",
1317         "}\n",
1318         "\n",
1319         "mpl.figure.prototype.mouse_event = function(event, name) {\n",
1320         "    var canvas_pos = mpl.findpos(event)\n",
1321         "\n",
1322         "    if (name === 'button_press')\n",
1323         "    {\n",
1324         "        this.canvas.focus();\n",
1325         "        this.canvas_div.focus();\n",
1326         "    }\n",
1327         "\n",
1328         "    var x = canvas_pos.x * mpl.ratio;\n",
1329         "    var y = canvas_pos.y * mpl.ratio;\n",
1330         "\n",
1331         "    this.send_message(name, {x: x, y: y, button: event.button,\n",
1332         "                             step: event.step,\n",
1333         "                             guiEvent: simpleKeys(event)});\n",
1334         "\n",
1335         "    /* This prevents the web browser from automatically changing to\n",
1336         "     * the text insertion cursor when the button is pressed.  We want\n",
1337         "     * to control all of the cursor setting manually through the\n",
1338         "     * 'cursor' event from matplotlib */\n",
1339         "    event.preventDefault();\n",
1340         "    return false;\n",
1341         "}\n",
1342         "\n",
1343         "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
1344         "    // Handle any extra behaviour associated with a key event\n",
1345         "}\n",
1346         "\n",
1347         "mpl.figure.prototype.key_event = function(event, name) {\n",
1348         "\n",
1349         "    // Prevent repeat events\n",
1350         "    if (name == 'key_press')\n",
1351         "    {\n",
1352         "        if (event.which === this._key)\n",
1353         "            return;\n",
1354         "        else\n",
1355         "            this._key = event.which;\n",
1356         "    }\n",
1357         "    if (name == 'key_release')\n",
1358         "        this._key = null;\n",
1359         "\n",
1360         "    var value = '';\n",
1361         "    if (event.ctrlKey && event.which != 17)\n",
1362         "        value += \"ctrl+\";\n",
1363         "    if (event.altKey && event.which != 18)\n",
1364         "        value += \"alt+\";\n",
1365         "    if (event.shiftKey && event.which != 16)\n",
1366         "        value += \"shift+\";\n",
1367         "\n",
1368         "    value += 'k';\n",
1369         "    value += event.which.toString();\n",
1370         "\n",
1371         "    this._key_event_extra(event, name);\n",
1372         "\n",
1373         "    this.send_message(name, {key: value,\n",
1374         "                             guiEvent: simpleKeys(event)});\n",
1375         "    return false;\n",
1376         "}\n",
1377         "\n",
1378         "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
1379         "    if (name == 'download') {\n",
1380         "        this.handle_save(this, null);\n",
1381         "    } else {\n",
1382         "        this.send_message(\"toolbar_button\", {name: name});\n",
1383         "    }\n",
1384         "};\n",
1385         "\n",
1386         "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
1387         "    this.message.textContent = tooltip;\n",
1388         "};\n",
1389         "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",
1390         "\n",
1391         "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
1392         "\n",
1393         "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
1394         "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
1395         "    // object with the appropriate methods. Currently this is a non binary\n",
1396         "    // socket, so there is still some room for performance tuning.\n",
1397         "    var ws = {};\n",
1398         "\n",
1399         "    ws.close = function() {\n",
1400         "        comm.close()\n",
1401         "    };\n",
1402         "    ws.send = function(m) {\n",
1403         "        //console.log('sending', m);\n",
1404         "        comm.send(m);\n",
1405         "    };\n",
1406         "    // Register the callback with on_msg.\n",
1407         "    comm.on_msg(function(msg) {\n",
1408         "        //console.log('receiving', msg['content']['data'], msg);\n",
1409         "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
1410         "        ws.onmessage(msg['content']['data'])\n",
1411         "    });\n",
1412         "    return ws;\n",
1413         "}\n",
1414         "\n",
1415         "mpl.mpl_figure_comm = function(comm, msg) {\n",
1416         "    // This is the function which gets called when the mpl process\n",
1417         "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
1418         "\n",
1419         "    var id = msg.content.data.id;\n",
1420         "    // Get hold of the div created by the display call when the Comm\n",
1421         "    // socket was opened in Python.\n",
1422         "    var element = $(\"#\" + id);\n",
1423         "    var ws_proxy = comm_websocket_adapter(comm)\n",
1424         "\n",
1425         "    function ondownload(figure, format) {\n",
1426         "        window.open(figure.imageObj.src);\n",
1427         "    }\n",
1428         "\n",
1429         "    var fig = new mpl.figure(id, ws_proxy,\n",
1430         "                           ondownload,\n",
1431         "                           element.get(0));\n",
1432         "\n",
1433         "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
1434         "    // web socket which is closed, not our websocket->open comm proxy.\n",
1435         "    ws_proxy.onopen();\n",
1436         "\n",
1437         "    fig.parent_element = element.get(0);\n",
1438         "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
1439         "    if (!fig.cell_info) {\n",
1440         "        console.error(\"Failed to find cell for figure\", id, fig);\n",
1441         "        return;\n",
1442         "    }\n",
1443         "\n",
1444         "    var output_index = fig.cell_info[2]\n",
1445         "    var cell = fig.cell_info[0];\n",
1446         "\n",
1447         "};\n",
1448         "\n",
1449         "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
1450         "    var width = fig.canvas.width/mpl.ratio\n",
1451         "    fig.root.unbind('remove')\n",
1452         "\n",
1453         "    // Update the output cell to use the data from the current canvas.\n",
1454         "    fig.push_to_output();\n",
1455         "    var dataURL = fig.canvas.toDataURL();\n",
1456         "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
1457         "    // the notebook keyboard shortcuts fail.\n",
1458         "    IPython.keyboard_manager.enable()\n",
1459         "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
1460         "    fig.close_ws(fig, msg);\n",
1461         "}\n",
1462         "\n",
1463         "mpl.figure.prototype.close_ws = function(fig, msg){\n",
1464         "    fig.send_message('closing', msg);\n",
1465         "    // fig.ws.close()\n",
1466         "}\n",
1467         "\n",
1468         "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
1469         "    // Turn the data on the canvas into data in the output cell.\n",
1470         "    var width = this.canvas.width/mpl.ratio\n",
1471         "    var dataURL = this.canvas.toDataURL();\n",
1472         "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
1473         "}\n",
1474         "\n",
1475         "mpl.figure.prototype.updated_canvas_event = function() {\n",
1476         "    // Tell IPython that the notebook contents must change.\n",
1477         "    IPython.notebook.set_dirty(true);\n",
1478         "    this.send_message(\"ack\", {});\n",
1479         "    var fig = this;\n",
1480         "    // Wait a second, then push the new image to the DOM so\n",
1481         "    // that it is saved nicely (might be nice to debounce this).\n",
1482         "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
1483         "}\n",
1484         "\n",
1485         "mpl.figure.prototype._init_toolbar = function() {\n",
1486         "    var fig = this;\n",
1487         "\n",
1488         "    var nav_element = $('<div/>')\n",
1489         "    nav_element.attr('style', 'width: 100%');\n",
1490         "    this.root.append(nav_element);\n",
1491         "\n",
1492         "    // Define a callback function for later on.\n",
1493         "    function toolbar_event(event) {\n",
1494         "        return fig.toolbar_button_onclick(event['data']);\n",
1495         "    }\n",
1496         "    function toolbar_mouse_event(event) {\n",
1497         "        return fig.toolbar_button_onmouseover(event['data']);\n",
1498         "    }\n",
1499         "\n",
1500         "    for(var toolbar_ind in mpl.toolbar_items){\n",
1501         "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
1502         "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
1503         "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
1504         "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
1505         "\n",
1506         "        if (!name) { continue; };\n",
1507         "\n",
1508         "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
1509         "        button.click(method_name, toolbar_event);\n",
1510         "        button.mouseover(tooltip, toolbar_mouse_event);\n",
1511         "        nav_element.append(button);\n",
1512         "    }\n",
1513         "\n",
1514         "    // Add the status bar.\n",
1515         "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
1516         "    nav_element.append(status_bar);\n",
1517         "    this.message = status_bar[0];\n",
1518         "\n",
1519         "    // Add the close button to the window.\n",
1520         "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
1521         "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
1522         "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
1523         "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
1524         "    buttongrp.append(button);\n",
1525         "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
1526         "    titlebar.prepend(buttongrp);\n",
1527         "}\n",
1528         "\n",
1529         "mpl.figure.prototype._root_extra_style = function(el){\n",
1530         "    var fig = this\n",
1531         "    el.on(\"remove\", function(){\n",
1532         "\tfig.close_ws(fig, {});\n",
1533         "    });\n",
1534         "}\n",
1535         "\n",
1536         "mpl.figure.prototype._canvas_extra_style = function(el){\n",
1537         "    // this is important to make the div 'focusable\n",
1538         "    el.attr('tabindex', 0)\n",
1539         "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
1540         "    // off when our div gets focus\n",
1541         "\n",
1542         "    // location in version 3\n",
1543         "    if (IPython.notebook.keyboard_manager) {\n",
1544         "        IPython.notebook.keyboard_manager.register_events(el);\n",
1545         "    }\n",
1546         "    else {\n",
1547         "        // location in version 2\n",
1548         "        IPython.keyboard_manager.register_events(el);\n",
1549         "    }\n",
1550         "\n",
1551         "}\n",
1552         "\n",
1553         "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
1554         "    var manager = IPython.notebook.keyboard_manager;\n",
1555         "    if (!manager)\n",
1556         "        manager = IPython.keyboard_manager;\n",
1557         "\n",
1558         "    // Check for shift+enter\n",
1559         "    if (event.shiftKey && event.which == 13) {\n",
1560         "        this.canvas_div.blur();\n",
1561         "        // select the cell after this one\n",
1562         "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
1563         "        IPython.notebook.select(index + 1);\n",
1564         "    }\n",
1565         "}\n",
1566         "\n",
1567         "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
1568         "    fig.ondownload(fig, null);\n",
1569         "}\n",
1570         "\n",
1571         "\n",
1572         "mpl.find_output_cell = function(html_output) {\n",
1573         "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
1574         "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
1575         "    // IPython event is triggered only after the cells have been serialised, which for\n",
1576         "    // our purposes (turning an active figure into a static one), is too late.\n",
1577         "    var cells = IPython.notebook.get_cells();\n",
1578         "    var ncells = cells.length;\n",
1579         "    for (var i=0; i<ncells; i++) {\n",
1580         "        var cell = cells[i];\n",
1581         "        if (cell.cell_type === 'code'){\n",
1582         "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
1583         "                var data = cell.output_area.outputs[j];\n",
1584         "                if (data.data) {\n",
1585         "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
1586         "                    data = data.data;\n",
1587         "                }\n",
1588         "                if (data['text/html'] == html_output) {\n",
1589         "                    return [cell, data, j];\n",
1590         "                }\n",
1591         "            }\n",
1592         "        }\n",
1593         "    }\n",
1594         "}\n",
1595         "\n",
1596         "// Register the function which deals with the matplotlib target/channel.\n",
1597         "// The kernel may be null if the page has been refreshed.\n",
1598         "if (IPython.notebook.kernel != null) {\n",
1599         "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
1600         "}\n"
1601        ],
1602        "text/plain": [
1603         "<IPython.core.display.Javascript object>"
1604        ]
1605       },
1606       "metadata": {},
1607       "output_type": "display_data"
1608      },
1609      {
1610       "data": {
1611        "text/html": [
1612         "<img src=\"data:image/png;base64,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