{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# MDI 720 : Statistiques\n",
    "## GLM\n",
    "### *Joseph Salmon*\n",
    "\n",
    "This notebook reproduces the pictures for the course \"GLM_fr\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt  # for plots\n",
    "from matplotlib import rc\n",
    "from sklearn.linear_model import RidgeCV\n",
    "import seaborn as sns\n",
    "from os import mkdir, path\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "# interaction mode better for 3D\n",
    "\n",
    "from sklearn.linear_model import LogisticRegression, LinearRegression\n",
    "from sklearn.preprocessing import OneHotEncoder\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn import datasets\n",
    "from functions_classif import class_round, point_plot,\\\n",
    "    frontiere, data_blob_generation, pdf_3D_plot\n",
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dirname = \"../prebuiltimages/\"\n",
    "if not path.exists(dirname):\n",
    "    mkdir(dirname)\n",
    "\n",
    "\n",
    "np.random.seed(seed=44)\n",
    "\n",
    "###############################################################################\n",
    "# Plot initialization\n",
    "\n",
    "plt.close('all')\n",
    "dirname = \"../srcimages/\"\n",
    "imageformat = '.pdf'\n",
    "\n",
    "\n",
    "rc('font', **{'family': 'sans-serif', 'sans-serif': ['Computer Modern Roman']})\n",
    "params = {'axes.labelsize': 12,\n",
    "          'font.size': 16,\n",
    "          'legend.fontsize': 16,\n",
    "          'text.usetex': True,\n",
    "          'figure.figsize': (8, 6)}\n",
    "plt.rcParams.update(params)\n",
    "\n",
    "sns.set_context(\"poster\")\n",
    "sns.set_palette(\"colorblind\")\n",
    "sns.set_style(\"white\")\n",
    "sns.axes_style()\n",
    "\n",
    "\n",
    "###############################################################################\n",
    "# display function:\n",
    "\n",
    "saving = False\n",
    "\n",
    "\n",
    "def my_saving_display(fig, dirname, filename, imageformat):\n",
    "    \"\"\"\"Saving with personal function.\"\"\"\n",
    "    filename = filename.replace('.', 'pt')  # remove \".\" to avoid floats issues\n",
    "    if saving is True:\n",
    "        dirname + filename + imageformat\n",
    "        image_name = dirname + filename + imageformat\n",
    "        fig.savefig(image_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "digits = datasets.load_digits()\n",
    "images_and_labels = list(zip(digits.images, digits.target))\n",
    "fig = plt.figure(figsize=(12, 5))\n",
    "for index, (image, label) in enumerate(images_and_labels[:10]):\n",
    "    plt.subplot(2, 5, index + 1)\n",
    "    plt.axis('off')\n",
    "    plt.imshow(image, cmap=plt.cm.gray_r, interpolation='nearest')\n",
    "    plt.title('Training: %i' % label)\n",
    "plt.show()\n",
    "my_saving_display(fig, dirname, \"digits_plot\", imageformat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "##############################################################################\n",
    "# Limits on a simulated example\n",
    "##############################################################################\n",
    "\n",
    "scenario = 4\n",
    "n_samples = 100\n",
    "n_test = 30\n",
    "if scenario == 3:\n",
    "    # Example with 3 classes\n",
    "    mean_0 = [0, 0]\n",
    "    mean_1 = [1, 0]\n",
    "    mean_2 = [0, 1]\n",
    "    means = [mean_0, mean_1, mean_2]\n",
    "    noise_level = 0.15\n",
    "elif scenario == 4:\n",
    "    # Example with 4 classes\n",
    "    mean_0 = [0, 0]\n",
    "    mean_1 = [1, 0]\n",
    "    mean_2 = [0, 1]\n",
    "    mean_3 = [0.5, 0.5]\n",
    "    means = [mean_0, mean_1, mean_2, mean_3]\n",
    "    noise_level = 0.10\n",
    "elif scenario == 2:\n",
    "    # Example with 4 classes\n",
    "    mean_0 = [0, 0]\n",
    "    mean_1 = [1, 1]\n",
    "    noise_level = 0.10\n",
    "    means = [mean_0, mean_1]\n",
    "\n",
    "n_class = len(means)  # get the number of classes considered\n",
    "\n",
    "X, y = data_blob_generation(n_samples, means, noise_level)\n",
    "X_test, y_test = data_blob_generation(n_test, means, noise_level)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "##############################################################################\n",
    "# Naive linear regression on raw observations\n",
    "##############################################################################\n",
    "\n",
    "resolution_param = 500  # 500 for nice plotting, 50 for fast version\n",
    "\n",
    "regr = LinearRegression()\n",
    "regr.fit(X, y)\n",
    "y_pred_test = class_round(regr.predict(X_test), n_class)\n",
    "\n",
    "# Plotting part\n",
    "fig0 = plt.figure(figsize=(12, 8))\n",
    "title = \"Left out accuracy (regression w./o. dummy variables)\" + \\\n",
    "        \": {:.2f}\".format(accuracy_score(y_test, y_pred_test))\n",
    "plt.title(title)\n",
    "\n",
    "\n",
    "def f(xx):\n",
    "    \"\"\"Classifier\"\"\"\n",
    "    return class_round(regr.predict(xx.reshape(1, -1)), n_class)\n",
    "frontiere(f, X, y, step=resolution_param)\n",
    "\n",
    "# reshape needed for sklearn convention on point to predict evaluations\n",
    "display1 = np.asarray([0, 0]).reshape(1, -1)\n",
    "display2 = np.asarray([0.5, 0.5]).reshape(1, -1)\n",
    "display3 = np.asarray([1, 1]).reshape(1, -1)\n",
    "\n",
    "point_plot(fig0, display1, np.zeros(n_class), (90, -60), color_txt='black')\n",
    "point_plot(fig0, display2, np.zeros(n_class), (-200, -15), color_txt='black')\n",
    "point_plot(fig0, display3, np.zeros(n_class), (-100, -60), color_txt='black')\n",
    "\n",
    "plt.show()\n",
    "my_saving_display(fig0, dirname, 'RawRegression' + 'n_class' +\n",
    "                  str(n_class), imageformat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\" width=\"1200\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "##############################################################################\n",
    "# Naive linear regression on dummy variables\n",
    "##############################################################################\n",
    "\n",
    "# performing class estimation by performing multi-task learning with dummy\n",
    "# variables\n",
    "enc = OneHotEncoder()\n",
    "enc.fit(y.reshape(-1, 1))\n",
    "Y = enc.transform(y.reshape(-1, 1)).toarray()\n",
    "regr_multi = LinearRegression()\n",
    "regr_multi.fit(X, Y)\n",
    "proba_vector_test = regr_multi.predict(X_test)\n",
    "y_pred_test = class_round(regr.predict(X_test), n_class)\n",
    "\n",
    "# performance evaluation on new dataset\n",
    "y_pred_test = np.argmax(proba_vector_test, axis=1)\n",
    "title = \"Left out accuracy (regression w. dummy variables)\" + \\\n",
    "        \": {:.2f}\".format(accuracy_score(y_test, y_pred_test))\n",
    "\n",
    "# Plotting part\n",
    "fig1 = plt.figure(figsize=(12, 8))\n",
    "plt.title(title)\n",
    "\n",
    "\n",
    "def f(xx):\n",
    "    \"\"\"Classifier\"\"\"\n",
    "    return np.argmax(regr_multi.predict(xx.reshape(1, -1)))\n",
    "frontiere(f, X, y, step=resolution_param)\n",
    "\n",
    "# naive method: estimate probability with linear model over indicators\n",
    "proba_vector1 = regr_multi.predict(display1)\n",
    "label_pred1 = np.argmax(proba_vector1)\n",
    "\n",
    "proba_vector2 = regr_multi.predict(display2)\n",
    "label_pred2 = np.argmax(proba_vector2)\n",
    "\n",
    "proba_vector3 = regr_multi.predict(display3)\n",
    "label_pred3 = np.argmax(proba_vector3)\n",
    "\n",
    "point_plot(fig0, display1, proba_vector1[0], (90, -60), color_txt='black')\n",
    "point_plot(fig0, display2, proba_vector2[0], (-200, -15), color_txt='black')\n",
    "point_plot(fig0, display3, proba_vector3[0], (-100, -60), color_txt='black')\n",
    "\n",
    "plt.show()\n",
    "my_saving_display(fig1, dirname, 'DummyRegression' + 'n_class' +\n",
    "                  str(n_class), imageformat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
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     },
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     "output_type": "display_data"
    },
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\" width=\"1200\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "##############################################################################\n",
    "# Logistic regression\n",
    "##############################################################################\n",
    "\n",
    "clf = LogisticRegression()\n",
    "clf.fit(X, y)\n",
    "y_logit_test = clf.predict(X_test)\n",
    "title = \"Left out accuracy (logistic regression) \" + \\\n",
    "        \": {:.2f}\".format(accuracy_score(y_test, y_logit_test))\n",
    "fig2 = plt.figure(figsize=(12, 8))\n",
    "plt.title(title)\n",
    "\n",
    "\n",
    "def f(xx):\n",
    "    \"\"\"Classifier\"\"\"\n",
    "    return int(clf.predict(xx.reshape(1, -1)))\n",
    "frontiere(f, X, y, step=resolution_param)\n",
    "\n",
    "proba_vector_logit1 = np.exp(clf.predict_log_proba(display1))[0]\n",
    "proba_vector_logit2 = np.exp(clf.predict_log_proba(display2))[0]\n",
    "proba_vector_logit3 = np.exp(clf.predict_log_proba(display3))[0]\n",
    "\n",
    "point_plot(fig0, display1, proba_vector_logit1, (90, -60), color_txt='black')\n",
    "point_plot(fig0, display2, proba_vector_logit2, (-200, -15), color_txt='black')\n",
    "point_plot(fig0, display3, proba_vector_logit3, (-100, -60), color_txt='black')\n",
    "\n",
    "plt.show()\n",
    "my_saving_display(fig2, dirname, 'LogisticRegression' + 'n_class' +\n",
    "                  str(n_class), imageformat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"810\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "##############################################################################\n",
    "# Plotting the underlying distribution: mixture of isotropic Gaussian\n",
    "##############################################################################\n",
    "step = 250\n",
    "\n",
    "fig3 = pdf_3D_plot(means, n_class, noise_level, step)\n",
    "my_saving_display(fig2, dirname, 'mixt_of_iso_gaussian' + 'n_class' +\n",
    "                  str(n_class), imageformat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "##############################################################################\n",
    "# Plotting the logistic function\n",
    "##############################################################################\n",
    "\n",
    "t = np.arange(-10, 10, step=0.01)\n",
    "\n",
    "\n",
    "def logistic(t):\n",
    "    \"\"\"logistic\"\"\"\n",
    "    return np.exp(t) / (1 + np.exp(t))\n",
    "\n",
    "\n",
    "fig0 = plt.figure(figsize=(8, 8))\n",
    "ax1 = plt.subplot(111)\n",
    "ax1.plot(t, logistic(t), label='logistique')\n",
    "\n",
    "ax1.set_ylim(-0.1, 1.1)\n",
    "ax1.set_xlim(-10, 10)\n",
    "plt.legend(loc=\"upper left\", fontsize=14)\n",
    "\n",
    "plt.show()\n",
    "my_saving_display(fig2, dirname, 'logistic', imageformat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
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