docs/tutorials/onln_gfmm_general_use.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Original Online Learning Algorithm for GFMM"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This example shows how to use the GFMM classifier using an original online learning algorithm.\n",
    "\n",
    "Note that the numerical features in training and testing datasets must be in the range of [0, 1] because the GFMM classifiers require features in the unit cube."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Execute directly from the python file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Get the path to the this jupyter notebook file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\hyperbox-brain\\\\docs\\\\tutorials'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "this_notebook_dir = os.path.dirname(os.path.abspath(\"__file__\"))\n",
    "this_notebook_dir"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Get the home folder of the Hyperbox-Brain project"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "WindowsPath('C:/hyperbox-brain')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pathlib import Path\n",
    "project_dir = Path(this_notebook_dir).parent.parent\n",
    "project_dir"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Create the path to the Python file containing the implementation of the GFMM classifier using the original online learning algorithm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\hyperbox-brain\\\\hbbrain\\\\numerical_data\\\\incremental_learner\\\\onln_gfmm.py'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "onln_gfmm_file_path = os.path.join(project_dir, Path(\"hbbrain/numerical_data/incremental_learner/onln_gfmm.py\"))\n",
    "onln_gfmm_file_path"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Run the found file by showing the execution directions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "usage: onln_gfmm.py [-h] -training_file TRAINING_FILE -testing_file\n",
      "                    TESTING_FILE [--theta THETA] [--theta_min THETA_MIN]\n",
      "                    [--gamma GAMMA] [--alpha ALPHA] [--is_draw IS_DRAW]\n",
      "\n",
      "The description of parameters\n",
      "\n",
      "required arguments:\n",
      "  -training_file TRAINING_FILE\n",
      "                        A required argument for the path to training data file\n",
      "                        (including file name)\n",
      "  -testing_file TESTING_FILE\n",
      "                        A required argument for the path to testing data file\n",
      "                        (including file name)\n",
      "\n",
      "optional arguments:\n",
      "  --theta THETA         Maximum hyperbox size (in the range of (0, 1])\n",
      "                        (default: 0.5)\n",
      "  --theta_min THETA_MIN\n",
      "                        Mimimum value of the maximum hyperbox size to escape\n",
      "                        the training loop (in the range of (0, 1]) (default:\n",
      "                        0.5)\n",
      "  --gamma GAMMA         A sensitivity parameter describing the speed of\n",
      "                        decreasing of the membership function in each\n",
      "                        dimension (larger than 0) (default: 1)\n",
      "  --alpha ALPHA         Multiplier showing the decrease of theta in each step\n",
      "                        (default: 0.9)\n",
      "  --is_draw IS_DRAW     Show the existing hyperboxes during the training\n",
      "                        process on the screen (default: False)\n"
     ]
    }
   ],
   "source": [
    "!python \"{onln_gfmm_file_path}\" -h"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Create the path to training and testing datasets stored in the dataset folder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\hyperbox-brain\\\\dataset\\\\syn_num_train.csv'"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "training_data_file = os.path.join(project_dir, Path(\"dataset/syn_num_train.csv\"))\n",
    "training_data_file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\hyperbox-brain\\\\dataset\\\\syn_num_test.csv'"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "testing_data_file = os.path.join(project_dir, Path(\"dataset/syn_num_test.csv\"))\n",
    "testing_data_file"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Run a demo program"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of hyperboxes = 53\n",
      "Testing accuracy =  84.50%\n"
     ]
    }
   ],
   "source": [
    "!python \"{onln_gfmm_file_path}\" -training_file \"{training_data_file}\" -testing_file \"{testing_data_file}\" --theta 0.1 --theta_min 0.1 --gamma 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Using the GFMM classifier with original online learning algorithm through its init, fit, and predict functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "from hbbrain.numerical_data.incremental_learner.onln_gfmm import OnlineGFMM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Create training and testing data sets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train = pd.read_csv(training_data_file, header=None)\n",
    "df_test = pd.read_csv(testing_data_file, header=None)\n",
    "\n",
    "Xy_train = df_train.to_numpy()\n",
    "Xy_test = df_test.to_numpy()\n",
    "\n",
    "Xtr = Xy_train[:, :-1]\n",
    "ytr = Xy_train[:, -1]\n",
    "\n",
    "Xtest = Xy_test[:, :-1]\n",
    "ytest = Xy_test[:, -1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Initializing parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "theta = 0.1\n",
    "theta_min = 0.1\n",
    "gamma = 1\n",
    "is_draw = True"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "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",
       "        fig.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 overridden (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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"594.6666666666666\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "OnlineGFMM(C=array([1, 2, 1, 1, 1, 2, 1, 2, 2, 1, 2, 2, 2, 2, 1, 1, 2, 2, 1, 1, 2, 1,\n",
       "       1, 2, 2, 2, 2, 1, 1, 2, 2, 1, 1, 2, 2, 1, 1, 2, 1, 2, 1, 2, 1, 1,\n",
       "       2, 2, 1, 2, 2, 2, 2, 2, 1]),\n",
       "           V=array([[0.42413   , 0.53516   ],\n",
       "       [0.70577   , 0.397105  ],\n",
       "       [0.82785   , 0.78025   ],\n",
       "       [0.66038   , 0.51128   ],\n",
       "       [0.48794   , 0.672     ],\n",
       "       [0.26651   , 0.18424   ],\n",
       "       [0.32289   , 0.60194   ],\n",
       "       [0.19944   , 0.03      ],\n",
       "       [0.29343   , 0.28975   ],\n",
       "       [0.63683   , 0.6936    ],\n",
       "       [0.32906   , 0.55512   ],\n",
       "       [0.03      , 0.47757   ],\n",
       "       [0.54...\n",
       "       [0.815     , 0.397095  ],\n",
       "       [0.67906   , 0.83605   ],\n",
       "       [0.37033   , 0.26124   ],\n",
       "       [0.52197   , 0.91371   ],\n",
       "       [0.66037   , 0.57837   ],\n",
       "       [0.52621   , 0.66846   ],\n",
       "       [0.80583   , 0.43242   ],\n",
       "       [0.79935   , 0.7757    ],\n",
       "       [0.35813   , 0.58772   ],\n",
       "       [0.79516   , 0.32629   ],\n",
       "       [0.70743   , 0.50325   ],\n",
       "       [0.36057   , 0.71561   ],\n",
       "       [0.72496   , 0.38674   ],\n",
       "       [0.28822   , 0.62174   ],\n",
       "       [0.14737   , 0.28498   ],\n",
       "       [0.56487   , 0.17003   ],\n",
       "       [0.68469   , 0.2221    ],\n",
       "       [0.55763   , 0.43813   ]]),\n",
       "           is_draw=True, theta=0.1, theta_min=0.1)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "onln_gfmm_clf = OnlineGFMM(theta=theta, theta_min=theta_min, gamma=gamma, is_draw=is_draw)\n",
    "onln_gfmm_clf.fit(Xtr, ytr)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### The code below shows how to display decision boundaries among classes if input data are 2-dimensional"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "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",
       "        fig.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 overridden (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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"572\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "onln_gfmm_clf.draw_hyperbox_and_boundary(\"The trained GFMM classifier and its decision boundaries\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of existing hyperboxes = 53\n"
     ]
    }
   ],
   "source": [
    "print(\"Number of existing hyperboxes = %d\"%(onln_gfmm_clf.get_n_hyperboxes()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import accuracy_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy =  84.50%\n"
     ]
    }
   ],
   "source": [
    "y_pred = onln_gfmm_clf.predict(Xtest)\n",
    "acc = accuracy_score(ytest, y_pred)\n",
    "print(f'Accuracy = {acc * 100: .2f}%')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Explaining the predicted result for the input sample by showing membership values and hyperboxes for each class"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "sample_need_explain = 10\n",
    "y_pred_input_0, mem_val_classes, min_points_classes, max_points_classes = onln_gfmm_clf.get_sample_explanation(Xtest[sample_need_explain], Xtest[sample_need_explain])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted class for sample X = [0.571640, 0.233700] is 2 and real class is 2\n"
     ]
    }
   ],
   "source": [
    "print(\"Predicted class for sample X = [%f, %f] is %d and real class is %d\" % (Xtest[sample_need_explain, 0], Xtest[sample_need_explain, 1], y_pred_input_0, ytest[sample_need_explain]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Membership values:\n",
      "Class 1 has the maximum membership value = 0.870180\n",
      "Class 2 has the maximum membership value = 0.984660\n",
      "Class 1 has the representative hyperbox: V = [0.58339 0.36352] and W = [0.66562    0.38375437]\n",
      "Class 2 has the representative hyperbox: V = [0.57285 0.24904] and W = [0.65695 0.31638]\n"
     ]
    }
   ],
   "source": [
    "print(\"Membership values:\")\n",
    "for key, val in mem_val_classes.items():\n",
    "    print(\"Class %d has the maximum membership value = %f\" % (key, val))\n",
    "    \n",
    "for key in min_points_classes:\n",
    "    print(\"Class %d has the representative hyperbox: V = %s and W = %s\" % (key, min_points_classes[key], max_points_classes[key]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Show input sample and hyperboxes belonging to each class. In 2D, we can show rectangles or use parallel coordinates"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Using rectangles to show explanations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "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",
       "        fig.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 overridden (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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"552.6666666666666\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "onln_gfmm_clf.show_sample_explanation(Xtest[sample_need_explain], Xtest[sample_need_explain], min_points_classes, max_points_classes, y_pred_input_0, \"2D\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Using parallel coordinates. This mode best fits for any dimensions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a parallel coordinates graph\n",
    "onln_gfmm_clf.show_sample_explanation(Xtest[sample_need_explain], Xtest[sample_need_explain], min_points_classes, max_points_classes, y_pred_input_0, file_path=\"par_cord/onln_gfmm_par_cord_1.html\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"820\"\n",
       "            height=\"520\"\n",
       "            src=\"https://uts-caslab.github.io/hyperbox-brain/docs/tutorials/par_cord/onln_gfmm_par_cord_1.html\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x1e6eeeab9b0>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load parallel coordinates to display on the notebook\n",
    "from IPython.display import IFrame\n",
    "# We load the parallel coordinates from GitHub here for demostration in readthedocs\n",
    "# On the local notebook, we only need to load from the graph storing at 'par_cord/onln_gfmm_par_cord_1.html'\n",
    "IFrame('https://uts-caslab.github.io/hyperbox-brain/docs/tutorials/par_cord/onln_gfmm_par_cord_1.html', width=820, height=520)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### An example for the wrong prediction case with the demonstration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Try another sample\n",
    "sample_need_explain = 1\n",
    "y_pred_input_0, mem_val_classes, min_points_classes, max_points_classes = onln_gfmm_clf.get_sample_explanation(Xtest[sample_need_explain], Xtest[sample_need_explain])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted class for sample X = [0.485900, 0.476500] is 2 and real class is 1\n"
     ]
    }
   ],
   "source": [
    "print(\"Predicted class for sample X = [%f, %f] is %d and real class is %d\" % (Xtest[sample_need_explain, 0], Xtest[sample_need_explain, 1], y_pred_input_0, ytest[sample_need_explain]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Membership values:\n",
      "Class 1 has the maximum membership value = 0.941340\n",
      "Class 2 has the maximum membership value = 0.955140\n",
      "Hyperboxes:\n",
      "Class 1 has the representative hyperbox: V = [0.42413 0.53516] and W = [0.52084 0.60972]\n",
      "Class 2 has the representative hyperbox: V = [0.49255 0.39125] and W = [0.52124 0.43164]\n"
     ]
    }
   ],
   "source": [
    "print(\"Membership values:\")\n",
    "for key, val in mem_val_classes.items():\n",
    "    print(\"Class %d has the maximum membership value = %f\" % (key, val))\n",
    "print(\"Hyperboxes:\")\n",
    "for key in min_points_classes:\n",
    "    print(\"Class %d has the representative hyperbox: V = %s and W = %s\" % (key, min_points_classes[key], max_points_classes[key]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "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",
       "        fig.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 overridden (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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"555.3333333333334\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "onln_gfmm_clf.show_sample_explanation(Xtest[sample_need_explain], Xtest[sample_need_explain], min_points_classes, max_points_classes, y_pred_input_0, \"2D\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Using parallel coordinates. This mode best fits for any dimensions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a parallel coordinates graph\n",
    "onln_gfmm_clf.show_sample_explanation(Xtest[sample_need_explain], Xtest[sample_need_explain], min_points_classes, max_points_classes, y_pred_input_0, file_path=\"par_cord/onln_gfmm_par_cord_2.html\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"820\"\n",
       "            height=\"520\"\n",
       "            src=\"https://uts-caslab.github.io/hyperbox-brain/docs/tutorials/par_cord/onln_gfmm_par_cord_2.html\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x1e6ee6da4e0>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load parallel coordinates to display on the notebook\n",
    "from IPython.display import IFrame\n",
    "# We load the parallel coordinates from GitHub here for demostration in readthedocs\n",
    "# On the local notebook, we only need to load from the graph storing at 'par_cord/onln_gfmm_par_cord_2.html'\n",
    "IFrame('https://uts-caslab.github.io/hyperbox-brain/docs/tutorials/par_cord/onln_gfmm_par_cord_2.html', width=820, height=520)"
   ]
  }
 ],
 "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",
   "pygments_lexer": "ipython3",
   "version": "3.6.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}