examples/numerical_data/incremental_learner/efmnn_general_use.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# This example shows how to use the Simpson's Fuzzy Min-Max Neural Network trained by an enhanced online learning algorithm (EFMNN)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that the numerical features in training and testing datasets must be in the range of [0, 1] because the EFMNN 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\\\\examples\\\\numerical_data\\\\incremental_learner'"
      ]
     },
     "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.parent\n",
    "project_dir"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Create the path to the Python file containing the implementation of the FMNN using the enhanced online learning algorithm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\hyperbox-brain\\\\hbbrain\\\\numerical_data\\\\incremental_learner\\\\efmnn.py'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "efmnn_file_path = os.path.join(project_dir, Path(\"hbbrain/numerical_data/incremental_learner/efmnn.py\"))\n",
    "efmnn_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: efmnn.py [-h] -training_file TRAINING_FILE -testing_file TESTING_FILE\n",
      "                [--theta THETA] [--gamma GAMMA] [--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",
      "  --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",
      "  --is_draw IS_DRAW     Show the existing hyperboxes during the training\n",
      "                        process on the screen (default: False)\n"
     ]
    }
   ],
   "source": [
    "!python \"{efmnn_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 = 77\n",
      "Testing accuracy =  85.80%\n"
     ]
    }
   ],
   "source": [
    "!python \"{efmnn_file_path}\" -training_file \"{training_data_file}\" -testing_file \"{testing_data_file}\" --theta 0.1 --gamma 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Using the EFMNN through its init, fit, and predict functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "from hbbrain.numerical_data.incremental_learner.efmnn import EFMNNClassifier\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Create training and testing data sets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "theta = 0.1\n",
    "gamma = 1\n",
    "is_draw = True"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
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       "/* 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",
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       "\n",
       "    this.imageObj.onload = function() {\n",
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       "                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",
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       "            event.step = -1;\n",
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       "        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": {
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lKpR7FKciEEAAhCAAAQgAIEsCdATatOGAdLylKpR7FKciEEAAhCAAAQgAIEsCdATatOGAdLylKpR7FKciEEAAhCAAAQgAIEsCdATatOGAdLylKpR7FKciEEAAhCAAAQgAIEsCdATatOGAdLylKpR7FKciEEAAhCAAAQgAIEsCdATatOGAdLylKpR7FKciEHAPYG5ObPZWV8YhofNhoZ8xUy0EIBA+wjQE2pzigHS8pSqUexSnIhBwDWBwvyMj5tNTvrCMDZmNjGBCfKVdaKFQPsI0BNqc4oB0vKUqlHsUpyIQcA1gc2bzVat8olgZsZsZMRn7EQNAQi0gwA9oTaPGCAtT6kaxS7FiRgEXBPoNkBTU+03BEW8o6PzKccAuS59godAKwjQE2rTiAHS8pSqUexSnIhBwDWBbgPkwRB4i9d1cRM8BBwQoCfUJhkDpOUpVaPYpTgRg4BrAt4Mgbd4XRc3wUPAAQF6Qm2SMUBanlI1il2KEzEIuCbgzRB4i9d1cRM8BBwQoCfUJhkDpOUpVaPYpTgRg4BrAt4Mgbd4XRc3wUPAAQF6Qm2SMUBanlI1il2KEzEIuCbgzRB4i9d1cRM8BBwQoCfUJhkDpOUpVaPYpTgRg4BrAt4Mgbd4XRc3wUPAAQF6Qm2SMUBanlI1il2KEzEIuCbgzRB4i9d1cRM8BBwQoCfUJhkDpOUpVaPYpTgRg4BrAt4Mgbd4XRc3wUPAAQF6Qm2SMUBanlI1il2KEzEIuCbgzRB4i9d1cRM8BBwQoCfUJhkDpOUpVaPYpTgRg4BrAt4Mgbd4XRc3wUPAAQF6Qm2SMUBanlI1il2KEzEIuCbgzRB4i9d1cRM8BBwQoCfUJhkDpOUpVaPYpTgRg4BrAt4Mgbd4XRc3wUPAAQF6Qm2SMUBanlI1il2KEzEIuCbgzRB4i9d1cRM8BBwQoCfUJhkDpOUpVaPYpTgRg4BrAt4Mgbd4XRc3wUPAAQF6Qm2SMUBanlI1il2KEzEIuCbgzRB4i9d1cRM8BBwQoCfUJhkDpOUpVaPYpTgRg4BrAt4Mgbd4XRc3wUPAAQF6Qm2SMUBanlI1il2KEzEIuCbgzRB4i9d1cRM8BBwQoCfUJhkDpOUpVaPYpTgRg4BrAt4Mgbd4XRc3wUPAAQF6Qm2SMUBanlI1il2KEzEIuCbgzRB4i9d1cRM8BBwQoCfUJhkDpOUpVaPYpTgRg4BrAt4Mgbd4XRc3wUPAAQF6Qm2SMUBanlI1il2KEzEIuCbgzRB4i9d1cRM8BBwQoCfUJhkDpOUpVaPYpTgRg4BrAt4Mgbd4XRc3wUPAAQF6Qm2SMUBanlI1il2KEzEIuCbgzRB4i9d1cRM8BBwQoCfUJhkDpOUpVaPYpTgRg4BrAt4Mgbd4XRc3wUPAAQF6Qm2SMUBanlI1il2KEzEIuCbgzRB4i9d1cRM8BBwQoCfUJhkDpOUpVaPYpTgRg4BrAt4Mgbd4XRc3wUPAAQF6Qm2SMUBanlI1il2KE7FMCczNmc3Oht/88LDZ0FD4dZta0Zsh8BZvU3WDLgQgkAYBekJtHjBAWp5SNYpdihOxDAkU5md83GxyMvzmx8bMJibaY4K8GQJv8Ya/QlgRAhAISYCeUEsbA6TlKVWj2KU4EcuQQHcTG2P7MzNmIyMxVtav6c0QeItXXzEoQgACKRGgJ9RmAwOk5SlVo9ilOBHLkEB3Ezs1FcaMFGuOjs7DwgBlWDS/3DIGKN/csXMIQGApAXpCbVVggLQ8pWoUuxQnYhkSiNHExlgzRGoKM7d69fxKocxkiLiWW6OtRjYmU9aGAATiEaAn1LLHAGl5StUodilOxDIkEMOMxFgzRGqmp7d9shVivZTWaNMneSlxZS8QgEA4AvSEWtYYIC1PqRrFLsWJWIYEYpiRGGuGSI1XA9S2wyxC1AprQAAC6RGgJ9TmBAOk5SlVo9ilOBHLkEAMMxJjzRCpKU7U27RpfqW2HfG9Ej9PsYaoI9aAAATiEKAn1HLHAGl5StUodilOxDIkEMOMxFgzw9SwZQhAAAIQCEiAnlALGwOk5SlVo9ilOBHLkEAMMxJjzQxTw5YhAAEIQCAgAXpCLWwMkJanVI1il+JELEMCMU4u4/SwDAuFLUMAAhBoOQF6Qm2CMUBanlI1il2KE7EMCcT+4j6nh2VYNGwZAhCAQAsJ0BNqk4oB0vKUqlHsUpyIZUggpgHi9LAMC4YtQwACEGgpAXpCbWIxQFqeUjWKXYoTsQwJxDy5jNPDMiwYtlyJQHGdzc5WmiqZxLUmwYhIywnQE2oTjAHS8pSqUexSnIhBAAIQgMAiAoX5GR83m5yMh4ZPW+OxZ+V8CNATanOFAdLylKpR7FKciEEAAhCAwCIC3acexoTD9+1i0mftHAjQE2qzhAHS8pSqUexSnIhBAAIQgMAKBmhqymxkJBwiTlwMx5qV8idAT6jNIQZIy1OqRrFLcSIGAQhAAAIrGKDQn8LwzC3KUUHASx3REyqqZZsGBkjLU6pGsUtxIgYBCEAAAhggaqBlBDBALUtooHAwQIFAV1kGA1SFGnMgAAEIQKAsgZjNY8y1y/JhXPoEvNQRPaG2FjFAWp5SNYpdihMxEYHNttlW2aqO2ozN2IgF/NKAKAZkIACBeQIxm8eYa5P/9hDwUkf0hNqaxQBpeUrVKHYpTsREBDBAIpDIQCABAjGbx5hrJ4CeLVQkUNRN96v7MI1eB3mEPNijYkilptETlsJUehAGqDSq8AMp9vDMWbE/AQxQf0aMgEAuBGKakJhr55If9rmUwNDQYFSKZ1214UVPqM0iBkjLU6pGsUtxIiYigAESgUQGAgkQiGlCYq6dAHq2UJEABuiuiuSY1k0AA5RwPWCAEk6Oo60Vhqf7Vfx51EY7fzVlU0u+A8R3ghwVB6FmTyCmCYm5dvaJcxwAt8BhgBTljwFSUGxIAwPUEFhkByIwZIPdbzBnLbnfYCBKDIZAngRimpCYa+eZLXbdi4CXOqIn1NY/BkjLU6pGsUtxIlaRAAaoIjimQSADAjGbx5hrZ5AatliSgJc6oicsWRAlh7kzQFu2bLENGzbYlVdeaQ899JDtuOOOdswxx9g555xju+22W0ls88O+8pWv2Ec+8hH71re+ZY8++qjtsMMOdsghh9ipp55qRx111EBavQZT7LURIiAgwC1wAohIQCBRAjGbx5hrJ5oOtlWBgJc6oiesUBwrTHFlgArzUxiTyclJ22WXXWzt2rX2wAMP2MaNG23nnXe2m266yfbcc89ShC+44AJbt26dDQ0N2djYmO266652//33d8xQ8frYxz5mf/RHf1RKa7lBFHstfExuiACHIDQEFlkIRCAQs3mMuXYE1CzZEAEvdURPqC0gVwbozDPPtHPPPdcOPfRQu/76623VqvmHOS6YmcMPP9xuvPHGvoQ3bdq09dOif/3Xf7Xx8fGtc66++mo78cQT7ZnPfKZNTU1tXaOvaI8BFHsVasxpmgAGqGnC6EMgHIGYzWPMtcMRZiUIaAjQE2o4Lqi4MUBPPvmkrVmzxh555BG7/fbbbf/999+O5L777mt33nmn3XrrrXbggQeuSPmLX/yiHXfccZ1b57785S8vGbvffvvZHXfcYbfcckvnlriqL4q9KjnmNUkAA9QkXbQhEJZATBMSc+2wlFkNAvUJ0BPWZ9it4MYA3XDDDXbkkUd2bnG79957l1AsPhkqPiE666yzbP369StS/upXv2pHH310XwN0zz332F577VU5YxR7ZXRMbJAABqhBuEhDIDCBmCYk5tqBMbMcBGoToCesjXA7ATcG6KKLLuocTlDcnnbVVVctoXjttdfasccea8cff7xdc801K1IuPkV63vOeZ48//rgtvgXun//5n+33f//3O7fZffOb36yVLYq9Fj4mQwACEIBAHwIxTUjMtSkMCORGgJ5QmzE3Bui0006zCy+8sGOCiu/8LH4Vt6wVt64dcMABdtttt/Wl/LnPfc5e//rXW3Fr3cIhCN///vc7hyAUt8ZddtllnVvu6rwo9jr0mAsBCEAAAv0IxDQhMdfux4V/h0BqBOgJtRlxY4BOOeUUu+SSS+z000+38847bwnF4ra4vffe2/bZZx+7++67S1H++te/bq95zWvsxz/+8dbxo6Oj9u53v7tjtJ761KeW0lko6sWD77vvvs4te3fdxVN/S4FkEAQgAAEIDEQgpgmJufZAkBgMgQQIYIC0SXBjgE4++WS79NJL7YwzzuicBLf4VXxfpzA/ZQ3QX/3VX9mf//mfd26ZK74ztMcee3SOwS6+R/T5z3/eXvWqV1nxKVGZFwaoDCXGQAACEICAmkBMExJzbTVH9CDQNAEMkJawGwOkvAWuOCr7iCOO6NwuV9zy9pSnPGVrVn7+85/bwQcfbP/+7/9u1113XeewhKovir0qOeZBAAIQgEAZAjFNSMy1y7BhDARSIkBPqM2GGwOkPAThrW99q33yk5/s3EpX3FK3+FX8/fvf/35773vfax/4wAcqZ4xir4yOiRCAAAQgUIJATBMSc+0SaBgCgaQI0BNq0+HGAJU9Bru4he3ss89ekfLLX/7yzoNUP/rRj9o73/nOJWOLv3/Xu95lf/iHf2gf//jHK2eMYq+MjokQgAAEIFCCQEwTEnPtEmgYAoGkCNATatPhxgA98cQTnVPZHn300RUfhLpx48bOLWwrvU466ST7+7//e3vjG99ol19++ZKhb3jDG+wzn/mMbdiwwf7iL/6icsYo9sromAgBCEAAAiUIxDQhMdcugYYhEEiKAD2hNh1uDFCBrTgA4fzzz7fDDjus8wnOyMhIh2ZxLPa6detsfHzcJiYmthK++OKLrfjvhBNO6JiZhVfxnKBXvvKVnVPeiv8/7rjjtv7bF77whc6/Fa/vfve79oIXvKByxij2yuiYCAEIQAACJQjENCEx1y6BhiEQSIoAPaE2Ha4M0JYtWzqHF9xyyy22yy672Nq1a+3BBx/s/HmnnXaym2++2fbaa6+thIvT3Yrb4YpPfIrn+iy85ubmOsdf/9M//VPnrw466CB7/vOfb8VzgG699dbO3xVG633ve1+tbFHstfAxGQIQgAAE+hCIaUJirk1hQCA3AvSE2oy5MkAFuscff7zzac4VV1xhDz/8sO2www6dB5cWR2Pvvvvu29FdzgAVgwoT9KlPfapzC9ydd95pMzMz9qxnPcsOOeSQzveCCs26L4q9LkHmQwACEIDASgRimpCYa1MVEMiNAD2hNmPuDJAWX7NqFHuzfFGHAAQg4J1ATBMSc23veSf+/AjQE2pzhgHS8pSqUexSnIhBwCWBuTmz2dnwoQ8Pmw0NhV+XFQcjENOExFx7MErxRyuvY67N+PmssgN6wirUlp+DAdLylKpR7FKciEHAHYGiaRofN5ucDB/62JhZcaYMJig8+0FWjGlCYq49CKPYY9XXMddm7IxWW5+esBq35WZhgLQ8pWoUuxQnYhBwR6C7wYwR/MyM2S8P24yxPGuWIBDThMRcuwSaZIY0cR1zbSaT3tIboScsjarUQAxQKUxxBlHscbizKgTaQqC7cZqaCmNGijVHR+cJ0mSlX0kxTUjMtdPPzLYdFtfR6tXzf77//urXccF7jz24NnPKffde6Qm1mcMAaXlK1Sh2KU7EIFCbQNn78FO5xz5GgxljzdqJdSwQM18x184p5dPT236poNo3v5xQkQynQ0+oZY0B0vKUqlHsUpyIQaAWgUHuw0/lHvsYDWaMNWsl1vnkmPmKuXZOaVcboFR+PuWUgxT2Sk+ozQIGSMtTqkaxS3EiBoFaBAa9Dz+F37DGaDBjrFkrsc4nx8xXzLVzSnvxy5dNm+Z3rPh0WaGRE7+27JWeUJtJDJCWp1SNYpfiRAwCtQiU+T5Nat9/idFgxlizVmKdT46Zr5hrO0874WdIgJ5QmzQMkJanVI1il+JEDAK1CHR/EXm5AwUwQGZljGKtRCQ8OcffrMc0ITHXTriM2BoEehKgJ9QWBgZIy1OqRrFLcSIGgVoEBr0Pn1sFOcrgAAAgAElEQVTgauHOcnKO362IaUJirp1lgbFp1wToCbXpxwBpeUrVKHYpTsQgUIvAIAYolUY4RoM56HelaiUlwckpGN9BsMSokYX9xVx7EEaMhUAKBOgJtVnAAGl5StUodilOxCBQi8AgX0RO5VaoGA3mYgMU6vlDtZJbc3Jqtz4OEk6MGsnJAJU9+n4Q5jmNTeVnWU7MmtorPaGWLAZIy1OqRrFLcSIGAXcEynxvSQ2l2wwU2rl9IlKFR0wTUWW/3XNi7j3m2mW4DXL0fRm9HMek8ml2juzUe6Yn1BLFAGl5StUodilOxCDgjsAgt+01BQcD1BRZjW5MExJz7TL0vN/OucDIwzVcph5ij6En1GYAA6TlKVWj2KU4EYOAOwIYoDApT72RX4lCzL3HXLtMZXg+0TDn2zrL5DbHMfSE2qxhgLQ8pWoUuxQnYhBwR2CQ7y0p4XhrnlJv5DFA1ao757xWi3jbLM+x12XX1Hx6Qi1ZDJCWp1SNYpfiRAwCEAhEwFvzlHO8Mfcec+0yl0Lq+ysTQ9UxnmOvyqzpefSEWsIYIC1PqRrFLsWJGAQgEIiAt+Yp53hj7j3m2mUuhdT3VyaGqmM8x16VWdPz6Am1hDFAWp5SNYpdihMxCEAgEAFvzVPO8cbce8y1y1wKqe+vTAxVx3iOvSqzpufRE2oJY4C0PKVqFLsUJ2IQgEAgAt6ap5zjjbn3mGuXuRRS31+ZGKqO8Rx7VWZNz6Mn1BLGAGl5StUodilOxCAAgUAEvDVPOccbc+8x1y5zKaS+vzIxVB3jOfaqzJqeR0+oJYwB0vKUqlHsUpyIQQACQgIrNUjemqec443xsNyFMiy4jY7O/ynFZ83knNe6l7rn2Ouya2o+PaGWLAZIy1OqRrFLcSIGAQgICWCAtsHMuVlM4VlRGCDhhSmSyrmmRQiSk6En1KYEA6TlKVWj2KU4EYMABIQEMEAYIFU5jY2ZTUyYDQ2pFDU6nk2A59g11aNXoSfUMsUAaXlK1Sh2KU7EIAABIQEMUDsMUKyH5XaX4vBweuan2J9nE+A5duGPSakUPaEUp2GAtDylahS7FCdiEIBADQJFQ9T96v7+xtSU2cjI9oYg5e921MDQcyrNoppoGnqe8+o59jSqb+ku6Am1mcEAaXlK1Sh2KU7EIACBGgSq3p6U4pfba2DAAKnhJazn2QR4jj3VkqQn1GYGA6TlKVWj2KU4EYMABGoQwAAtD49msUZhJTzVc149x55qSdITajODAdLylKpR7FKciEEAAjUIcAscBqhG+WQ51bMJ8Bx7qsVKT6jNDAZIy1OqRrFLcSIGAQgICXAIwjaYNIvCwkpIynNePceeUAlutxV6Qm1mMEBanlI1il2KEzEIQEBIAAOEARKWU5JSnk2A59iTLEYzoyfUZgYDpOUpVaPYpTgRgwAEhAQwQBggYTklKeXZBHiOPclixADJ04IBkiPVCWKAdCxRgoCagPcGAQOEAVJfU6npeb7GPceeWh0u7IeeUJsZDJCWp1SNYpfiRAwCUgI0CMvj9MbGW7zSCylhMc959Rx7qiVJT6jNDAZIy1OqRrFLcSIGASmBtjYIc3Nms7P9UQ0Pmy13NHZb2SxHxVu8/asjnxF8ktk7V9R0ejVMT6jNCQZIy1OqRrFLcSIGASmBNjYIhfkZHzebnOyPamzMbGKitwlqI5uViHiLt3915DMCA4QByqVa6Qm1mcIAaXlK1Sh2KU7EIFCLwCDPwSkWGhmptVyUyd3NYJkNzMz0jtObIfAWb5nayGUMBggDlEut0hNqM4UB0vKUqlHsUpyIQaAWgeVu91pOtPg0JbdXdzM4NbW8uRkdnY8MAzTPAQOUW6Vv2y8GCAOUS/XSE2ozhQHS8pSqUexSnIhBoBYBbwaojrnxZgi8xVvrQoo8eZBPcoux/cx+5HAaW56abgxtZWF6wsroek7EAGl5StUodilOxCBQi8AgjVOxUI63wBWmZ/XqeUx8AlS+XGgWy7OKPXLQX2Qs7He5XwjEjqep9anppshW16UnrM6u10wMkJanVI1il+JEDAJSAm1sEKant/3GuwysOp8SldHPZUwbayEX9oPuEwNUjhg1XY5TyFH0hFraGCAtT6kaxS7FiRgEpATa2CAMYoA4BW5bObWxFqQXS0Jig3ySyy1w84nz9ulXQuW63VboCbWZwQBpeUrVKHYpTsQgICXQxqa3OLhh06Z5TCs956ffv7eRzUrF4y1e6YUUWYxDEHongJqOXJg9lqcn1OYEA6TlKVWj2KU4EYOAlAANwvI4vbHxFq/0QooshgHCAEUuwdLL0xOWRlVqIAaoFKY4gyj2ONxZFQIQqEfAmyHwFm+96khrNgYIA5RWRS6/G3pCbaYwQFqeUjWKXYoTMQhAIBABb4bAW7yByijIMhggDFCQQhMsQk8ogNglgQHS8pSqUexSnIg5I1B8n2V21lnQXeH2+w5Pk2S8GQJv8TZZO4u1m76OV7pOPOfVc+wh63uQtegJB6HVfywGqD+jaCMo9mjoWThzAkXTND5uNjmZeSA1tr/SKW01ZEtN9dY8eYu3VBEIBoW4jjnNkE+ABKUaRIKeUIsZA6TlKVWj2KU4EXNEoLshdRT2klBjHV/rzRB4izfUNRXqOuZ5VkszSk2HqvLy69ATlmdVZiQGqAylSGMo9kjgWTZ7At1v3lNTZiMj2YdUOoAUnl3irXnyFm/pYqw5sMnruMx14jmvnmOvWbaNTacn1KLFAGl5StUodilOxBwR8PzmnULsKewhZLl7izcU2ya5ltEuMyYUi9DreI49NOuy69ETliVVbhwGqBynKKMo9ijYWbQFBDy/eacQewp7CFnG3uINxbZJrmW0y4wJxSL0Op5jD8267Hr0hGVJlRuHASrHKcooij0KdhZtAQHPb94pxJ7CHkKWsbd4Q7FtkmsZ7TJjQrEIvY7n2EOzLrsePWFZUuXGYYDKcYoyimKPgp1FW0DA85t3CrGnsIeQZewt3lBsm+RaRrvMmFAsQq/jOfbQrMuuR09YllS5cRigcpyijKLYo2Bn0RYQ8PzmnULsKewhZBl7izcU2ya5ltEuMyYUi9DreI49NOuy69ETliVVbhwGqBynKKMo9ijYWbQFBDy/eacQewp7CFnG3uINxbZJrmW0y4wJxSL0Op5jD8267Hr0hGVJlRuHASrHKcooij0KdhZtAQHPb94pxJ7CHkKWsbd4Q7FtkmsZ7TJjQrEIvY7n2EOzLrsePWFZUuXGYYDKcYoyimKPgp1FW0DA85t3CrGnsIeQZewt3lBsm+RaRrvMmFAsQq/jOfbQrMuuR09YllS5cRigcpyijKLYo2Bn0RYQ8PzmvTj2Ip2rVs0ndbkn3qtT7o2/t3jV9bKcXpNcy2iXGROKReh1PMcemnXZ9egJy5IqNw4DVI5TlFEUexTsLNoCAp7fvPsZoBCGyBt/b/GG+hHRJNcy2sUvDFavno92aspsZCRU5PHXKfiMjob9xUn8qNPeAT2hNj8YIC1PqRrFLsWJmCMCZZqbtuJIwQB5axxpFpu5mpq8jstoT09vMwHNRJiHaqhPjvOgEW+X9IRa9hggLU+pGsUuxYmYIwJlmpu24kjBAHluHGkWdVdWk9dxGW3PdbyQxbExs4kJs6EhXV5RqkaAnrAat+VmYYC0PKVqFLsUJ2KOCJRpbtqKo7tpK27bKV4Lt7L0+vOaNXoSXhtHmkVtLTV5HZfRnpsz27RpPqbhYZ8mwGvc2krWqNETajguqGCAtDylahS7FCdijgiUaW7aimPQ39QWn1h0vxTfc/DaONIsaq+qJq/jJrW1FFCDwDwBekJtJWCAtDylahS7FCdijgh4bm4GNUCLy6IwL7wgkAKBJq/jJrVTYMce2keAnlCbUwyQlqdUjWKX4kTMEQHPzc3iW+AWbn8rm34MUFlSjGuaQJPXcZPaTXNB3ycBekJt3jFAWp5SNYpdihMxRwQ8NzeLY+8+oazXd4AW3/KmuAXOUakRaoMEmryOm9RuEAnSjgnQE2qTjwHS8pSqUexSnIg5IuC5uUnhFDhHpUaoDRJo8jpuUrtBJEg7JkBPqE0+BkjLU6pGsUtxIuaIgOfmJncD5Dl3ji7RUqE2WQtNapcKjkEQGJAAPeGAwPoMxwBpeUrVKHYpTsQcEfDc3GCAHBV6oFDnbM5mbbbR1YZt2IZs+4fNNHkdN6ndKCjE3RKgJ9SmHgOk5SlVo9ilOBFzRMBzc9Mv9n7/XpRJmTFNlVPMtZuKKWfdwvyM27hN2mSjYYzZmE3YxHYmqMlaaFK7UVCIuyVAT6hNPQZIy1OqRrFLcSLmiIDn5kYRu0KjarnFXLvqnts8b7NttlW2KkiIMzZjIzayda0ma6FJ7SCwWMQdAXpCbcoxQFqeUjWKXYoTMUcEPDc3itgVGmXLrVir+1X8eeHo7uLUOk6pK0uymXHdBmjKprYzKIoVC/1RG+1IYYAURNFoKwF6Qm1mMUBanlI1il2KEzFHBEI28KlhVcSu0CjLZdAHt/KcorJkNeO6DdBig6JYYSX9JuuwSW0FFzQgsJgAPaG2JjBAWp5SNYpdihMxRwQ8NzdVYo/5KQwGKO0LEwOUdn7YnR8C9ITaXGOAtDylahS7FCdijghUMQFtwVMl9pgmJKb5akvOm4wDA9QkXbQhUJ4APWF5VmVGYoDKUIo0hmKPBJ5lsydQxQRkH/QvA6gSe0wDtJh7lf23JXcpxhHTAM3MmK1ePU+l1/fB6vDq/q5Zsc7i75rV0WYuBJogQE+opYoB0vKUqlHsUpyIOSLguYmuEntKn8JU2b+j0g4eakwDND297UCMJgPHADVJF20VAXpCFcl5HQyQlqdUjWKX4kTMEQHPTbQidoVG1XKLuXbVPbd5XtsN0NiY2cSE2aCfgrY558SWJgF6Qm1eMEBanlI1il2KEzFHBDw30YrYFRpVyy3m2lX33OZ5MQ1QceLfpk3zdIeHmzEpTem2uSaILQ4BekItdwyQlqdUjWKX4kTMEQHPTbQidoWGo3JrdajF0derbf6LOKGfA9RqsAQHgQEJ0BMOCKzPcAyQlqdUjWKX4kTMEQHPDbwidoWGo3JrdajTNr31QaVNB9rEc4aa3jP6EAhFgJ5QSxoDpOUpVaPYpTgRc0TAcwPvOXZHJR4s1FAGaMzGbMImbMiGgsXGQhDIiQA9oTZbGCAtT6kaxS7FiZgjAp5NgOfYHZV4sFDnbM422fwXcYZtuDGD0qR2MFgsBIEGCdATauFigLQ8pWoUuxQnYo4IeDYBnmN3VOKECgEIOCNAT6hNOAZIy1OqRrFLcSLmiIBnE+A5dkclTqgQgIAzAvSE2oRjgLQ8pWoUuxQnYo4IeDYBnmN3VOKECgEIOCNAT6hNOAZIy1OqRrFLcSLmiIBnE7A49uI5J7OzjpLfFWrKz3gpnnHTKy8p79lnFRE1BNIgQE+ozQMGSMtTqkaxS3G2Wqz4ovKshelyc/iyMgZovtwfe8zs5S83m5xsdfkvG9zYmNnERDMP0KxDtDA/4+O985LqnuvEy1wIQKA+AXrC+gy7FTBAWp5SNYpdirO1YoX5Gbdxm7QwXW4Ox9VigObLfWrKbHS0taVfKrCZGbORkVJDgw3qrs9ei6a452BwWAgCEOhJgJ5QWxgYIC1PqRrFLsXZWrHNttlW2aqg8aX+wEIM0FIDVJih1IxAU0Vb5H/B+KVoJrrrcyEvqe+5qVwpdD1f7wp+aORBgJ5QmycMkJanVI1il+JsrVi3AZqyKRuxZn7dXawzavMfJ2CA0i2nxc11ykagKYqpN8S99pf6npvKlUIXdgqKaKROgJ5QmyEMkJanVI1il+JsrVhhRlbb6k58GKD5NHtuiDBA6ecfA6T9cez5eteSRC1lAvSE2uxggLQ8pWoUuxRna8WmbXrrJzOhguQToFCkB18HA4QBGrxq8p6BAco7f+y+HAF6wnKcyo5yZ4C2bNliGzZssCuvvNIeeugh23HHHe2YY46xc845x3bbbbey3LaOu/fee+1DH/qQffWrX7Uf/ehHtnr1att7773thBNOsPe85z0D63VPoNhr4XMzObQB4hCEtEsLA4QBSrtC6++uqPHuV/f3p3p9183Ld9/qk0UhZQL0hNrsuDJAhfk56qijbHJy0nbZZRdbu3atPfDAA7Zx40bbeeed7aabbrI999yzNOFrrrnGXve619nPfvYz23///W2fffaxn/zkJ/btb3/bRkZGrDBHdV4Uex16fuYWp8Btsk2dgEMcUR1ijbrZ8/wbYQwQBqju9ZP6/KGhwXZYHDu+8Fru+UuDKTY/mudBNc84txXoCbUZc2WAzjzzTDv33HPt0EMPteuvv95WrZo/OeuCCy6wdevW2eGHH2433nhjKcJ33HGHHXLIIZ1PfD7/+c/bePFQh1++fvGLX9jtt99uBx10UCmt5QZR7LXwMdkxAQzQfPK7j8FO8TS0pko09fzzHaB6ma9qgFZ6/lK9Heln8zwoPdPcFekJtRl0Y4CefPJJW7NmjT3yyCMdc1J8YtP92nfffe3OO++0W2+91Q488MC+lAuzNDExYf/yL/9ixx57bN/xVQZQ7FWoMQcC6X8C0GSO+AQo/fxjgOpdAVVvgev3/KV6u9LP9vRLCz299inSE2pz6sYA3XDDDXbkkUd2bnHrdWta8clQ8QnRWWedZevXr1+R8n/+53/ai170os4tb3fffbc2I11qFHtjaBFuOYHUPwFoEj8GCAPUZH2lqF32eu/1/KXU4uF5UKllJJ390BNqc+HGAF100UV26qmn2oknnmhXXXXVEorXXntt55Oc448/3orv9qz0uvjii+2d73yn/fEf/7F9+MMfts9+9rOdT46GhobsxS9+sb361a+2X/u1X6udKYq9NkIEnBIo2xC1EQ8GaKkBKvL8yzueLYXfqvMJkPbKK3u9lx2n3d1gajnscbCIGK0iQE+oIjmv48YAnXbaaXbhhRd2TFDxnZ/Fr+I7Pfvtt58dcMABdtttt61I+e1vf7t9/OMft3e/+92dW+AWfwr07Gc/266++urOd4rqvCj2OvSY65lA0eSunn80Uud7MJ5OgVp8IhYPQp2vAwxQe38ilDUNZcfFJJXDHmPy8bw2PaE2+24M0CmnnGKXXHKJnX766XbeeectoVjcFlccX13mtrbXvva1nU99nva0p9kOO+xgf/u3f9u5vW5qasrOPvtsu+KKKzp/f9ddd3VOm+v3WijqxePuu+++zi17hQ4vCECgPIHpabOFxr/8rPaN5BAE63zigwFqX213R1TWNJQdF5NWDnuMycfz2hggbfbdGKCTTz7ZLr30UjvjjDM6J8Etft1zzz0d81PGABW30X3uc5/rSFx33XV29NFHbydXnA73rW99a1mztXhtDJC2qFGDAAbIrDhF6itf2fZJWAq3foWqzMVNJAYoFPm018nBXOSwx7Sz3N7dYYC0uXVjgJS3wL3lLW+xT33qU7brrrvaD37wgyUZ+djHPmbveMc7bGxszL7xjW9UzhjFXhkdE50TKI673TT/aCQrnqcxO7vtEyEvt8QtxJ3SrV+hyrLbABf5Ll4Lnwim8KBMvgMUqhK2XycHc5HDHuNkj1XpCbU14MYAKQ9BOOecczqnxR122GH2zW9+c0lGvvzlL9vv/M7vdG6p+6//+q/KGaPYK6NjIgS2I6BsKpRaTacpp70qWVR9ToxyDytpYYBCkcYAxSHNqk0QoCfUUnVjgMoeg10chV18j2elV3Hwwe/+7u/aC1/4QiuOxF78+sxnPmNveMMbOs8aKp45VPVFsVclxzwINNf45GQqctqrsmYxQEqa7dHK4XrIYY/tqYi8IqEn1ObLjQF64oknOg9CffTRR1d8EOrGjRvt4IMPXpHy7OxsR6vQLA4q2H333bcb/7a3vc0+8YlP2Fvf+tbO946qvij2quSYBwEMUEHAazPFLXD8BOhFIIfrIYc9Ul1xCNATarm7MUAFtuIAhPPPP79z69r1119vI788G7c4FnvdunU2Pj5uExMTWwkXz/sp/jvhhBNsw4YN25F/73vfax/84AftFa94RedEuAWtr3zlK3bcccfZz3/+c7v55putOBCh6otir0qOeTkRmLM5m7VZ6ZaLJqL7Vfx5j+fP/8393196LPYgx2R3jpleNdLRmprZ3PeI7WEbtiEbksZXVsxrM8UhCGUrxNe4HK6HHPboq2rSiZaeUJsLVwZoy5YtdsQRR9gtt9zSOZ567dq19uCDD3b+vNNOO3UMy1577bWV8Pr16zu3w5100kl22WWXbUe+0HrpS1/a+Q5QofVbv/VbNj093dH4xS9+0TFa73vf+2pli2KvhY/JGRAozM+4jdukTaa7283Di9zUiNno9PzfTa0xG1nktka2N3NjNmYTNhHFBHltpjBA6V5OMXeWw/WQwx5j5tDz2vSE2uy7MkAFuscff7zzaU7xrJ6HH36487yeY445pnM09uJb2VYyQIVWcQvchz/8YSu+83P//ffbM57xDDvooIM6D1stPhmq+6LY6xJkfuoENttmW2Wr0t7m0Nxg+5tb+mnPjM3YiM1/ahTy5bWZwgCFrLJ81srheshhj/lkvF07pSfU5tOdAdLia1aNYm+WL+rxCXQboCmbkpkE5S1wq4YGMy4zc/OfCBWxjdpo5/8xQGFrDQNUjXfbm+/iWVirV8+zSfU4/M4ttvM/NjoP8R3k9txBs972fA/KI/Xx9ITaDGGAtDylahS7FCdiCRLoNkBNmoQ6b/S9zFSZZ8qEim2ltNaJO8FyKb2l1ONO9Rjs1LmVLoBlBub2gGQMUN2Mt2s+PaE2nxggLU+pGsUuxYlYggRCmQRlY1dWK1RsGKClBMrmKNYlsbwBmjMbnrWp6W2/+Q95iEbq3OrmKycDNDZmVpzJNOiR7oMwanu+B2GRw1h6Qm2WMEBanlI1il2KE7EECYQyCco3+rJaoWLDALXDAM1snrPV/zFuNrb9gSAhD9EoW9sJ/igptaW5ObNNm+aHDg83ay5KbWiFQSH21/Z8181BavPpCbUZwQBpeUrVKHYpTsQSJBDKJCjf6MtqhYoNA9QOAzS9ebONjvQ+EKSp20Or3t6Z4I8StlSCAPkuASnhIfSE2uRggLQ8pWoUuxQnYgkSSMEkDIoFAzQosfDjy+Yo/M7mV+y1v24DdP/mqc6X35s+RGPQ26uKT1B45UuAfOebu2Ln9ITa/GGAtDylahS7FCdiCRLI0QCVxZhCbKkbgbIsBx2Xetz9DNDU5pmOAVo4Ir6pT4BoiAetrLzHk++880dPqM0fBkjLU6pGsUtxIpYggRRMQlNYUogtdSPQGPvNZqt+eTdZ0ydpVYkhFQPELVFVspfvHPKdb+74BEifOwyQnqlMEQMkQ4lQogRSMAlNoUkhNgxQ889SqVI/qRigxXv3Wi9VctiGOeQ7ryzSE2rzhQHS8pSqUexSnIglSCAFk9AUlhRi89rgpB43Bqipqw7dQQikfp0MEouHsfSE2ixjgLQ8pWoUuxQnYgkSSMEkNIUlhdi8Njipx52LASqOYp6dbeoKSVc3xBHUKUSf+nWSAqOU9kBPqM0GBkjLU6pGsUtxIpYggRRMQlNYUojNa4OTetw5GKDHHjN7+cvNJrd/LFFTl0tSuiEeQppCwKlfJykwSmkP9ITabGCAtDylahS7FCdiCRJIwSQ0hSWF2Lw2OKnHnaoB6r4WuvfY1DWSsm6Kh2ekzIu9NU+AnlDLGAOk5SlVo9ilOBFLkEAKJqEpLCnElroRaIw9p8DVRttdO1NT1jmWu+2vIubR0fkoMUBtz3Z+8dETanOGAdLylKpR7FKciCVIIAWT0BSWFGLDAKXZyOb2CZAXM+D1emnqZyC6WgL0hFqeGCAtT6kaxS7FiViCBIoHPK621Z2dTdmUjVh7fs1cGKBRm/91clMPsuyXUq8NXepxY4D6VW6cf0+9buJQYdVUCNATajOBAdLylKpR7FKciCVIYNqmt5qEBLcn2xIGSIaylFDqjSwGqFQagw9KvW6CA2HBpAjQE2rTgQHS8pSqUexSnIglSMCDARqzMZuwCRuyoeAZ8NrQpR43Bij4pVBqwdTrplQQDGotAXpCbWoxQFqeUjWKXYoTsQQJzNmcbbJNnZ0N23AUk9A0lphxeW3oUo8bA9T0VVdNP/W6qRYVs9pCgJ5Qm0kMkJanVI1il+JEDALuCHht6FKPuzhUYPX8V99s4YS16c2bbY81q+b/bvNM59S1VTb/5xi3UKbOsImL2WPMTXBEsxkC9IRarhggLU+pGsUuxYkYBNwR8NrQpR739PS245a3FuXwZrPNGKCYF2nqdROTDWvHJ0BPqM0BBkjLU6pGsUtxIgYBdwS8NnSpx93PAD02N2NDQ3wCFPqCTb1uQvNgvbQI0BNq84EB0vKUqlHsUpyIQcAdAa8NXepxz82ZbZr/6psND1vH7HSOTR/Zdstb8W/cAhf2km2ibprQDEuF1VIhQE+ozQQGSMtTqkaxS3EiBgF3BLw2XznGvfiZWEWxxnyOVI4M617gTcTchGbdOJmfJwF6Qm3eMEBanlI1il2KEzEIuCPgtfnKMe6VjoTnEIQwl24TddOEZhgarJIaAXpCbUYwQFqeUjWKXYoTMQi4I+C1+cox7uUMUKznSOXIsO4F3kTMTWjWjZP5eRKgJ9TmDQOk5SlVo9ilOKOKFc+7mbXZqHsIsXjMZ96EiC+3Nbw2XznGvdwzsWJdUzkyrHt9KmIuNLpfxZ9HR+f/ZuHI8+5/L4475wWBMgToCctQKj8GA1SeVfCRFHtw5I0sWDQ24zZukzbZiH5KorF+W50Sg5T20ut5Myntr6m9dDedBQOazMFJK8zA4KvGnaGIuTjQYpBXcSAGLwiUIUBPWIZS+TEYoPKsgo+k2IMjb2TB4nSnhdOcGlkgMdEY31dIDEEy21giiTgAACAASURBVOl53HIyuwuzEQxQNc4KM1Bt5XizFDFjgOLlr+0r0xNqM4wB0vKUqlHsUpzRxLoN0JRN2Yi1756HzhG+Nn+fBwYoWqktWdi7ARobM5uYmD9mmtdgBBRmYLAV449WxMwtcPHz2NYd0BNqM4sB0vKUqlHsUpzRxLoNUFvNgYcYoxVQjYV7PW+mhlx2UxeesZPdxhPYsMIMJBDGQFtoIuYmNAcKisGtIUBPqE0lBkjLU6pGsUtxRhPzYA48xBitgFgYAhEIeGzcm4i5Cc0I5cCSCRCgJ9QmAQOk5SlVo9ilOKOJeTAHHmKMVkAsDIEIBDw27k3E3IRmhHJgyQQI0BNqk4AB0vKUqlHsUpzRxDyYAw8xRisgFoZABAIeG/cmYm5CM0I5sGQCBOgJtUnAAGl5StUodinOaGIezEEqMdJsRCtzFm4ZAY/XkseYW1a2rQ6HnlCbXgyQlqdUjWKX4owmloo5aBJAKjHGbmCKQwdmAzzvli/3N1nNaBcEYl9LMbLgMeYYnFmzGgF6wmrclpuFAdLylKpR7FKc0cRSMQdNAkglxpgNTGF+xsfNJgM875bjnZusZrQxQGY8P4rrIDUC9ITajGCAtDylahS7FGc0sVTMQZMAUokxpgHqXrtJ1gvaNGghKPtdI+a1FIu6x5hjsWbdwQnQEw7ObKUZGCAtT6kaxS7FGU0sFXPQJIBYMab00MHu5mlqymykgefdFmuMzj9vlt9QN1nQaHML3Ewz1zClBYGqBOgJq5LrPQ8DpOUpVaPYpTijicUyByEDjhXj0NBgURa3qTX1CvHb4xBrNMUH3bwIeKw1jzHnVZW+d0tPqM0/BkjLU6pGsUtxRhOLZQ5CBhwrRgxQyCyzlicCHs2Ax5g91XTusdITajOIAdLylKpR7FKc0cRimYOQAceKMdVb4Jr6fg4NWsiq9r2Wx1rzGLPvKs8renpCbb4wQFqeUjWKXYozmlgscxAy4FRijNnAhFg7xBoh64a10iVQmPjVq+f3V3ynbXhkzmYtwBnvQiTDNmxDVv4+Wb5jJ4SPlJwAPaEWKQZIy1OqRrFLcUYTS8UcNAkglRhjGoQQa4dYo8k6QTsfAtPT2w7cMJsz+8a42ViAM96ViL4xZrZ2wmwAE7SwfFOf4irDQ8sXAXpCbb4xQFqeUjWKXYozmlgq5qBJAKnEGNMghFg7xBpN1gna+RDYzgANbzbbvCqfzXfvdGTGbHawIxl5zlaeqW77rukJtRnGAGl5StUodinOaGKpmIMmAaQSY0yDEGLtEGs0WSdo50OgODFx06b5/c4Nb7bnrJo3QPdvnrIRG8xQhI66+Hm0x8j8efFTm2cG3u/wsNmgB6yEjpH1/BGgJ9TmHAOk5SlVo9ilOKOJpWIOmgTgIcZ+/EKYkxBr9IuTf/dHILfrW7lfrjl/9Z5qxPSE2sxggLQ8pWoUuxRnNDHlm3G0IPos7CHGfuxDNEoh1ugXJ//uj0Bu17dyv1xz/uo91YjpCbWZwQBpeUrVKHYpzmhiyjfjaEFggPqiD9EohVijb6AMcEcgt59hyv1yzbkr92QDpifUpgYDpOUpVaPYpTiXFZuzpce7Dnp86ko7Vb4ZhyEy+CoeYuxHJUSjFGKNfnHy7/4I5HZ9K/fLNZd+vXvJET2hthYxQFqeUjWKXYqzp1hhfsZt3CZt++Ndx2zMJmxioGdILLdb5Ztx80SqreAhxn5kQrwJh1ijX5z8uz8CuV3fdfab0sOV/VVatYi9/FykJ6xWH8vNwgBpeUrVKHYpzp5i3W+UiwfM2OCnB/VapM6bcfMENCt4iLEfqRBvwiHW6Bcn/+6PQG7Xd539Dnr6W3FaHq+4BLz8XKQn1NYZBkjLU6pGsUtx9jVAUzbVGTNq88enYoDK86/TcJRfJe2RId6EQ6yRNmV2F4NAbtd3nf1igGJUWL01vfxcpCesVyeLZ2OAtDylahS7FGdfA1QYnuK1yuafd4EBKs+/TsNRfpW0R4Z4Ew6xRtqU2V0MArld33X2yy1wMSpssDW95oiecLA66TcaA9SPUMR/p9ibh7/4jRIDVI15nYaj2orpzQphTkKskR5ZdhSbQG7Xt3K/XHOxq2/p+l4/paMn1NYiBkjLU6qmKnblm4E0wATEMECaJFBjZiEapRBraCoClTYRyO36HmS/xXd4ZmeXz1ZxzY3O3xVtU1NmIyPbjx0eNhu0IW9TbcSIZVDebfmelqonjJGzFNfEAKWYlV/uSVXsg7wZJIyjka1hgDRYqTEMkKaS4qv0OhY//q7C7mDxYwByu77L7rdojMfHzSa3PwR0INhjY2YTE5iggaDVHMwtcHfVJMj0ggAGKOE6wAA1nxwMkIZx2YZDs1qaKiE+nQmxRpp0w+xquWPxw6yeziqLHwOQ2/Vddr/d11Md+jMzSz8ZqqPH3MEIePm5qOoJB6Pb3tEYoIRzqyr2sm8GCaNobGvFQQerbXVHn1PgqmOmxvgEqHr1pDNzpWPx09llmJ10HwKT2/Vddr/djXOv29tWIt19axwGKExNLrcKBigu/1xXxwAlnLmqBqj44d/9Kv68cLRz0eSP2PY3MS/+c8JI5FubtumtbBaLcwpcedxlG47yivmNLJqg1fNeuud3BRQR0XQpKC6v0V3HvX5WNrt6fPXu9woPBqjXNVv2FsjiWtxjdP69dGpm85LvBoXI5uJbFUOsmeIaGKAUs5L+njBACeeoqgEasqGBoip+4Ht9LWeAFt8CUoePB3NQJcYqc+rkoem509Pbvizd9FqFPr911lNuW00OSmi5+HPjUna/smt2ZsRsZIWTFAZNRMnxyvepkksmOQwDlGRakt8UBijhFGGAmk9OYf422abOQt2/TVP+Zq3sm3Hz0Ta3QpUYq8xpLoL6yrJmqsRW+OJ1CUgVhrStJgdFgAEalJiZjX3DbGKtDfh7xwoL9Z6iulNBtiGEGiNQtSdsbEOZC2OAEk5g1WLnFri0kuqhqaoSY5U5aWV2+90UJ0ptmvfS1vTRuE3rp8y5yb21rSYHZeXNAC2+ZmeHitvF13Sw3W/fX3K7eC+eMa7F5W5VHDTfjM+LQNWeMK8ow+0WAxSO9cArqYrd+5v6wODFEzzwrxJjlTni1CAHge0IeK9JbwZocfnnkv9c9smPFy0BVU+o3VW+ahighHOnKnZ+WMZNsgf+ZWLkk8m4dcjq/QmUqeP+KvmOwABttlW2qpPAlG8t816n+V5h9Xau6gnr7aI9szFACedSVez8sIybZA/8y8TI4Rxx65DV+xMoU8f9VfIdgQHCAOVbve3fuaonbD+pchFigMpxijJKVeze39SjJK9rUQ/8y8SIAYpdiazfj0CZOu6nkfO/Y4AwQDnXb9v3ruoJ286pbHwYoLKkIoyj2CNAb2BJD01VmRi5Ba6B4kJSSqBMHUsXTEwMA4QBSqwk2U4XAXpCbTlggLQ8pWoUuxRnNDEPTVWVGKvMiZZEFnZBwHtNYoAwQC4u9EyDpCfUJg4DpOUpVaPYpTijiXloqqrEWGVOtCSysAsC3msSA4QBcnGhZxokPaE2cRggLU+pGsUuxRlNzENTVSXGKnOiJZGFXRDwXpMYIAyQiws90yDpCbWJwwBpeUrVKHYpzmhiHpqqKjFWmTNoEudszmZttu+0YRu2QQ9p6CvKgOwIhKjJlKFggDBAKden973RE2orAAOk5SlVo9ilOKOJeWiqUoyxMD/jNm6TNtk392M2ZhM2gQnqS6rdA1Ks45DEMUAYoJD1xlqDEaAnHIxXv9EYoH6EIv47xR4RvnBpD01VijF276lMOlN+8GGZ/TOmPoEU67h+VOUVMEAYoPLVwsjQBOgJtcQxQFqeUjWKXYozmpiHpirFGLv3NGVTNmIjS2qgGDNqo52/xwBFu0SSWTjFOg4JBwOEAQpZb6w1GAF6wsF49RuNAepHKOK/U+wR4QuX9tBUpRhjmT2VGSMsBaQSJ+C9HjBAGKDEL1HX26Mn1KYfA6TlKVWj2KU4o4l5aKpSjLHMnsqMiVY4LBycgPd6wABhgIJfdCxYmgA9YWlUpQZigEphijOIYo/DXb1qcWvValvdkV3uViz1mqH1UryVrAz3FPcdOnest40ABqi3AciNS9X9Vp0X+hrKZZ+hubR9PXpCbYYxQFqeUjWKXYozmti0TW/9nkm0TQRcOJXv0gzKPZV9V0nV5s1mq1bNz5yZMRtZ+nWnKrLu5nhvLPkEiE+A3F30GQVMT6hNFgZIy1OqRrFLcUYTG7QRj7ZRwcIpHSc9CPeU9l0lDRigKtSWzsEA8QnQKpv/TULKvxDxXqeaqz0/FXpCbc4wQFqeUjWKXYozmljxPJpNtqmzftsfuJlSfINwT2nfVQq1LQYodmNX5rbJKvnJZc5yt4TGzsug/Krut+q8QfdXd3wu+6wbJ/O3J0BPqK0IDJCWp1SNYpfiRAwCrSWAAdKkdpBPDW3OzGaH6y08PGs2VE+iqdndn4Dk1nBX3W/VeU3lYDndXPYZmkvb16Mn1GYYA6TlKVWj2KU4EYNAawgUhqf7Vfx5dP5xRjY1tfQ7QLl8Jyh2Y1faABXmZ/wbZpNj9Wpq7BtmE2uTM0GLbwmNnZdBIVfdb9V5g+6v7vhc9lk3TuZvT4CeUFsRGCAtT6kaxS7FiZiIAG++IpA1ZIYG/NRgrmjYM3jFrq2yt012DOcqzUkTUzObkzu0YvEtobHzMmjpVt1v3Vsgi+tsdnbQ3Q4+vohvj5H533hMbZ7p+ZDn4t+Gh80G/Vkx+G6YEYoAPaGWNAZIy1OqRrFLcSImIlC1uRAtj4wN3tSkaoCKWup+dX8HpdeR8SOmMR11i6j7lsNen7j10+/+xC6HU/tyu+ar7rf0J4D9Ehzy30dmzGZ7XxdjY2YTE4P/vAi5fdYqT4CesDyrMiMxQGUoRRpDsUcCz7IrEqjaXIBVR6Att8ANDfgFmOITmhRedb9zVXd+aAa5XfNV95udAfrGmNnaieJXIsuWRA4GO3Q957oePaE2cxggLU+pGsUuxYmYiEDV5kK0PDI9COTWUC+EgAHK47lNuV3zVfdb9hbIXj+EOp/qrZn/l/u/H+ZZXMudXpnbJ4z8UC9HgJ6wHKeyozBAZUlFGEexR4DOkksI5HqbkqdU5mqAcq2turzrzg9d21UNReh9LqwXY78p5TSlvcSqgTauS0+ozSoGSMtTqkaxS3EiVpFArr+lrxhultPa0vDEaFyrJLwu77rzq+y5zpxc8oIBmieQW33VqU1Pc+kJtdnGAGl5StUodilOxCoSwABVBBdwWlsanlwa7bq8684PWFqdpRafjjY8N7LiaWdNnj7WfavZ1HTvW826D9Pofp5Rk9xSymlKe2mSuTdtekJtxjFAWp5SNYpdihOxigRyvU2pYrhMi0gAAxQR/gpLZ3c4QFcsGKAw30dKs3LbtSt6Qm0+MUBanlI1il2KEzERgVyaVFG4yAQkkEtt1f0Ne935AVPSWSpXA7T4ga5NcksppyntpUnm3rTpCbUZxwBpeUrVKHYpzqzFUmoMU9pL1kll89kSqNtg1p0fGlz36Whzm4ftOWvmj11efNpZEdcez5/f3XK3p9Xde5lb4BbWWO6UtLp76DU/pZymtJcmWHvVpCfUZh4DpOUpVaPYpTizFkvJdKS0l6yTyuazJVC3waw7Pya4lfbeRFyFZver+4jnXg+hHYn0rNwmYq+a55T2UjUG5i0lQE+orQoMkJanVI1il+LMWiwl05HSXrJOKpvPlkDdBrPu/JjgQhugoeWf8dkTw1ykZ+WmlNOU9hKzVtu2Nj2hNqMYIC1PqRrFLsWZtRimI+v0sflABIpbtWZtdutqTd0CVbfBrDs/EM6ey2CAetNPKacp7SVmrbZtbXpCbUbdGaAtW7bYhg0b7Morr7SHHnrIdtxxRzvmmGPsnHPOsd12260y3Xvuucde/OIXW6H/8pe/3L7yla9U1lqYSLHXRpitACevZZs6Nh6JQGF+xm3cJm1y6w6a+hJ83Qaz7vxIiDvLhjZA3AI3eLZzrq/Bo/Uzg55Qm2tXBqgwJ0cddZRNTk7aLrvsYmvXrrUHHnjANm7caDvvvLPddNNNtueee1YifOSRR9q//du/2dzcHAaoEkEmdRPg2TvUAwQGI9D9KWn3zCaOQa7bYNadPxgZ7ejQBmjx7lNll9K+UtqLtvp8q2GAtPl3ZYDOPPNMO/fcc+3QQw+166+/3latWtWhecEFF9i6devs8MMPtxtvvHFgwp/4xCfsbW97m51yyin2d3/3dxiggQn6mLD49pyVol5l87VZ9lU0eSm8mrrlKIXY2EPaBLoN0P12v+1he3Q2jAHS5g0D1JtnSqYjpb1oq8+3GgZIm383BujJJ5+0NWvW2COPPGK333677b///tuR3Hfffe3OO++0W2+91Q488MDSlKenp+2FL3xhZ87pp59u/+///T8MUGl6fgb2uj2njdE3dctRG1kRk5ZAtwGasikbtdHGDNDMjNnq1fP773USWb/Iuk8yK7RinVzWb5+9/h0DhAGqUjfMqU8AA1SfYbeCGwN0ww03WHGbWnGL27333ruEYvHJUPEJ0VlnnWXr168vTfm1r32tfeELX7Bvf/vb9oMf/AADVJqcr4HL3Z7TRgpN/Ma9jZyISUsgpAGanjYbnfdXtV8YoMEQpvrpRkr7Smkvg2WX0SsRwABp68ONAbrooovs1FNPtRNPPNGuuuqqJRSvvfZaO/bYY+3444+3a665phTlL33pS/aKV7yic4DC+9///s53gPgEqBQ6d4MWN2cjNtjDKor5C7/RLn67Pej8poF37w8D1DRt9HsRyNEAjY2ZTUyYDXrUc8wKiP0JUMzYV1o7JdOR0l5SzVeO+8IAabPmxgCddtppduGFF3ZMUPGdn8WvO+64w/bbbz874IAD7LbbbutLefPmzVYU4zOe8YzOrXO/8iu/ggHqS83vgLrHWNed3zT51PfXdPzoxycQ0gAVz5qZ3jR/5PbwcHUDU2duLOKd2/fWmNnssM3MDG13+16vxrvMdx/b8N3BlExHSnuJVadtXBcDpM2qGwNUHFBwySWXdL6nc9555y2hWNwWt/fee9s+++xjd999d1/KhZEqPlX6+te/3vnUp3hV/QRooagXL3rfffd1btm76667+u6HAWkTqGsQ6s5vmk7q+2s6fvTjEwhqgHocuR2fQOAdfGPMHtt/wlaNbHtS6eLGe3hk6dHkvXbZhu8OpmQ6UtpL4Kps9XIYIG163Rigk08+2S699FI744wzOifBLX4Vz/EpzE8ZA1QclPCSl7zEXv/619vll1++VQoDpC3ONqm13SC0Pb421WJbYwlpgDx9p2+lepnaPGNruk5wWNx428hmK3uiZe63zqZkOlLaS1t/3sSICwOkpe7GAKlugfu///s/O/jggzsPUf3e977XeX7QwquqAVoupRS7tthjqrXdILQ9vpi1w9rlCMQyQCl+J68csWqjpjdvtj1G5k+AGMQA9eLUpu8OpmQ6UtpLtSpjVi8C9ITaunBjgFSHIBQPTn3+859vz3nOc+wFL3jBdtkojtguvku0ww472Itf/OLOc4a++MUvVs4YxV4ZXXIT224Q2h5fcgXFhpYQiGWAcv/kYtBSKgzQ6Mj8c8oGMUC9OLXp50ZKpiOlvQxaX4xfngA9obY63BigssdgF0dhn3322ctSXjBAZdLw67/+653nDlV9UexVyaU3r01v9L3otj2+9CqKHS0mUDTYq23+4TyNPwjVtt3ahQHadqLlSrfAYYDCXbMYoHCsQ65ET6il7cYAPfHEE50HoT766KMrPgh148aNnVvcqry4Ba4KNR9z2m4Q2h6fjyrNO8ppm956VHx3JE0YFM/1zidAva+TlExHSnvJ+6dKWrvHAGnz4cYAFdiKAxDOP/98O+yww+z666+3kV9+ebM4FnvdunU2Pj5uE8VDGX75uvjii63474QTTrANGzb0JY8B6ovI7YC2N0xtj89t4WYUeC8D1NTpYp7rfRADNDey7VM5vgMU7mLCAIVjHXIlDJCWtisDtGXLFjviiCPslltusV122cXWrl1rDz74YOfPO+20k91888221157bSW8fv36zu1wJ510kl122WV9yWOA+iJyO6DtDVPb43NbuBkFXjxvZpNt6ux44bkyTT1fxnO9D2KANo/0/lSuV1k18UldyPJNyXSktJeQOWj7WhggbYZdGaAC3eOPP975NOeKK66whx9+uHNgwTHHHNM5Gnv33Xffji4GSFtsntXa3jC1PT7PtUvsSwl4rvcmDFBTn9SFrN2UTEdKewmZg7avhQHSZtidAdLia1aNYm+Wb0j1tjdMbY8vZK2wVvoEPNf7IAaoeBDq4k/lemW3qU/qQlZSSqYjpb2EzEHb16In1GYYA6TlKVWj2KU4o4q1vWFqe3xRi4fFkyPgud4HMUBdz0hNLofqDaVkOlLai5qzZz16Qm32MUBanlI1il2KM6pY2xumtscXtXhYPDkCnusdA9S7HFMyHSntJbmLN+MN0RNqk4cB0vKUqlHsUpxRxdreMDUdX9P6UYuDxbMj4LkeMUAYoOwu2JZsmJ5Qm0gMkJanVI1il+KMKtb2hqnp+JrWj1ocLJ4dAc/1iAHCAGV3wbZkw/SE2kRigLQ8pWoUuxRnVLG2N0xNx9e0ftTiYPHsCHiuRwwQBii7C7YlG6Yn1CYSA6TlKVWj2KU4o4q1vWFqOr6m9aMWB4tnR8BzPWKAMEDZXbAt2TA9oTaRGCAtT6kaxS7FGVWs7Q2TOr5Cr/tV/HnURjt/1euJ8iM2EjW/LO6LgLrec6KHAcIA5VSvbdorPaE2mxggLU+pGsUuxRlVrO0Nkzq+IRsaKF9zNjfQeAZDoA4Bdb3X2UvouRggDFDommO9eQL0hNpKwABpeUrVKHYpzqhibW+Y1PFhgKKWK4v3ITBjM7baVndG9fpEss0ACwO0x8gvP43dPGNruh724/n45ZRiT2kvbb4WQsdGT6gljgHS8pSqUexSnFHF1AYhajA9FlfHxy1wqWWY/XQTmLbprbdkeiZz//RSAzQ6741sZsaMB6HGqQ4MUBzuTa9KT6gljAHS8pSqUexSnFHF1AYhajABDNDiJdrOL7V8sp+VCWCAzOwbY2ZrJ8yWuV0VAxTvKsIAxWPf5Mr0hFq6GCAtT6kaxS7FGVWs7Q180/E1rR+1OFg8OwLFd8422abOvodt2Aa9ZTO7gLs2PD1ttsfzzWx2eFnzMzZmNjFhNjTYV/lyxmIpmY6U9pJ1UhPbPD2hNiEYIC1PqRrFLsUZVaztDXzT8TWtH7U4WBwCGRGYmzPbNO/9bHi4t8lZ7u8zCnPgraZkOlLay8AgmbAsAXpCbXFggLQ8pWoUuxRnVLG2N/BNx9e0ftTiYHEIQCB7AimZjpT2kn1iEwqAnlCbDAyQlqdUjWKX4owq1vYGvu3xRS0eFocABJInUHznafX8wYA2NRX3AIjCAHk9jCL5QqmxQXrCGvB6TMUAaXlK1Sh2Kc6oYm03CG2PL2rxsDgEIJA8geK7UQumI6XNejuMIiX26r3QE2qJYoC0PKVqFLsUZ1SxthuEtscXtXhYHAIQSJ5AigbI42EUyRdKjQ3SE9aAxydAWnhNq1HsTRMOp992g9D2+MJVCitBwDeB4oS9WZttBEKTJ/aVORyikaBWEPV4GEVoxiHXoyfU0uYTIC1PqRrFLsUZVaztBqFsfE02N1ET3GPxJput1GJlPxBQECh+PozbuE3apEJuicaYjdmETbg6trwRkIhGIUBPqMWOAdLylKpR7FKcUcXKGoSom6yxeJn4mm5uamy/kak0W41gRbTFBLp/jjQV5ozN2IiNNCWPLgQaI0BPqEWLAdLylKpR7FKcUcXKGISoG6y5eJn4QjQ3NcOQT6fZkiNFsMUEiutltc0fpXa/3S8zKsXPnj1sj44u12SLC6jlodETahOMAdLylKpR7FKcUcXKGISoG6y5eJn4usdM2ZSsuam5dfn0Is5RG6XZkpNFsO0Epm1667XTVKwYoKbIots0AXpCLWEMkJanVI1il+KMKlbGIETdYM3Fy8RXZkzNbSQx3UucScBmE60i0LQB4rbUVpWLu2DoCbUpxwBpeUrVKHYpzqhibW+Ky8RXZkzUJIkW9xKnCBcyENhKoPie4Cbb1PlzE4eINKFJ+iAQigA9oZY0BkjLU6pGsUtxRhVre1NcJr4yY6ImSbS4lzhFuJCBAAQgAIESBOgJS0AaYAgGaABYoYdS7KGJN7de25viMvGVGdNcBsIpe4kzHFFWggAEIAABekJtDWCAtDylahS7FGdUsbY3xWXiKzMmapJEi3uJU4QLGQhkTYDrPev0ZbV5ekJtujBAWp5SNYpdijOqWNvfJMvEV2ZM1CSJFvcSpwgXMhDImgDXe9bpy2rz9ITadGGAtDylahS7FGdUsba/SZaJr8yYqEkSLe4lThEuZCCQNQGu96zTl9Xm6Qm16cIAaXlK1Sh2Kc6oYm1/kywTX5kxUZMkWtxLnCJcyEAgawJc71mnL6vN0xNq04UB0vKUqlHsUpxRxdr+JlkmvjJjoiZJtLiXOEW4kIFAVgSK67v7Vfx54cHHvR7wPGIjleLj50glbK2eRE+oTS8GSMtTqkaxS3FGFSuePr7aVnf20OtNMurmBIt3NwHLPWndyxu6lzgFZYMEBLIjMGRDA+25eLZRlRc/R6pQa/ccekJtfjFAWp5SNYpdijOqWNNPOI8a3KLFMUCbbZWt6lBZjkVK+WIvEIBAeQIYoPKsGKklQE+o5YkB0vKUqlHsUpxRxbwYoDEbswmbsF5NgpffaHqJM+oFxeIQiESAW+AigWdZoyfUFgEGSMtTqkaxS3FGFStug9hkmzp7GLbhngYh6gZFi68Umxdj4CVOUckgA4GsCaiu91DGKmvYzjdPT6gtAAyQ1fAGFAAAIABJREFUlqdUjWKX4kQsMgFVoxA5jL7Le4mzLwgGdAgUv/yYtVl3NGL+oick836HIJRN/MJts2XHF7fXLrxisi67X8bVJ0BPWJ9htwIGSMtTqkaxS3EiFpmAF2PgJc7I5ZTF8kUjPm7jNmmTWexXucmVbodVrrNYyyPzWKybzCPaSwnQE2qrAgOk5SlVo9ilOBGLTMCLMfASZ+RyymL57lrIYsPiTcY4BMQr8xisxeWCXB8C9ITaEsEAaXlK1Sh2KU7EIhPwYgy8xBm5nLJYvrsW2nj8fa8klDkSv8nktYV5mVvrYrNuMo9o8wlQ0zWAAWqacA19DFANeExNjoAXY+AlzuQKLMENeayF2DHHXl9VhmXiKDNGtR904hOgJ9TmAAOk5SlVo9ilOBGLTMDLm7WXOCOXUxbLe6yF2DHHXl9VmGXiKDNGtR904hOgJ9TmAAOk5SlVo9ilOOViIU8akm9eIDjoyUNe3qy9xCkoodZLeKyF2DHHXl9V1GXiKDNGtR904hOgJ9TmAAOk5SlVo9ilOKViHk8aWgxw0JOHvLxZe4lTekG1VMxjLcSOOfb6IUvZU6whuaa6Fj2hNjMYIC1PqRrFLsUpFet+45EKZyY2yMlDXt6svcSZWalG2a7HWuiOuTj4YdRGO+wH+VlRJ1memHuKtU5NtGUuPaE2kxggLU+pGsUuxSkVW/wmP2IjUv2UxYrYqzQ1Xt6svcSZco2msjePtYABCld9HusrHN30VqIn1OYEA6TlKVWj2KU4pWKe33iqxl51njRxAcS8xBkAZfZLeKwFDFC4svVYX+HoprcSPaE2JxggLU+pGsUuxSkV8/zGUzX2qvOkiQsg5iXOACizX8JjLWCAwpWtx/oKRze9legJtTnBAGl5StUodilOqZjnN56qsVedJ01cADEvcQZAmf0S3mqhiLf7Ftn77X7bw/bo5LHXg2CbuHXYE3NPsWb/w0AQAD2hAGKXBAZIy1OqRrFLcUrFPL/xVI296jxp4gKIeYkzAMrsl/BWC0M2NFDOitM01S9PzD3Fqq6THPXoCbVZwwBpeUrVKHYpztJiZd5UyowpvWBmA6vGXnVeZng6vwFfZas62w518lVujLzs11stYIDCVra3+gpLN73V6Am1OcEAaXlK1Sh2Kc7SYmXeVMqMKb1gZgOrxl51XmZ4MEC5JazB/Xqp+QWE3ALXYDH1kPZWX2HpprcaPaE2JxggLU+pGsUuxVlarMybSpkxpRfMbGDV2KvOywwPBii3hDW4Xy81342wO2aeA9RgcZnxs6ZZvMmp0xNqU4IB0vKUqlHsUpylxco0LWXGlF4ws4FVY686LzM8NCW5JazB/XqpeQxQg0W0grTH+opDOo1V6Qm1ecAAaXlK1Sh2Kc5lxYo3kcVv4AsP+lzu5CLPbzxVY686L0wV6FbxEqeOWHuVPNYCnwCFq2eP9RWObnor0RNqc4IB0vKUqlHsUpzLilX54q7nN56qsVedF6YKdKt4iVNHrL1KHmsBAxSunj3WVzi66a1ET6jNCQZIy1OqRrFLcWKARDirvulWnSfadjAZL3EGA5rxQh5rIXbMsdcPWa6eYg3JNdW16Am1mcEAaXlK1Sh2Kc5lxbgFbjDOVd90q84bbHfxR3uJMz7p9HfgsRZixxx7/ZBV6SnWkFxTXYueUJsZDJCWp1SNYpfiLC1W5k2lzJjSC2Y2sGrsVedlhodDEHJLWIP79VLz3Qhjxxx7/QbLaYm0p1hDck11LXpCbWYwQFqeUjWKXYqztFiZN5UyY0ovmNnAqrFXnZcZHgxQbglrcL9eah4D1GARrSDtsb7ikE5jVXpCbR4wQFqeUjWKXYqztFiZN5UyY0ovmNnAqrFXnZcZHgxQbglrcL9eah4D1GARYYDiwE1wVXpCbVIwQFqeUjWKXYqztFiZpqXMmNILZjawauxV52WGBwOUW8Ia3K+XmscANVhEGKA4cBNclZ5QmxQMkJanVI1il+KUinlsbBYAVo296jxp4gKIeYkzAMrsl/BYC7Fjjr1+yKL1FGtIrqmuRU+ozQwGSMtTqkaxS3FKxTy/8VSNveo8aeICiHmJMwDK7JfwWAuxY469fsii9RRrSK6prkVPqM0MBkjLU6pGsUtxSsU8v/FUjb3qPGniAoh5iTMAyuyX8FgLsWOOvX7IovUUa0iuqa5FT6jNDAZIy1OqRrFLcUrFPL/xVI296jxp4gKIeYkzAMrsl/BYC7Fjjr1+yKL1FGtIrqmuRU+ozQwGSMtTqkaxS3FKxTy/8VSNveo8aeICiHmJMwDK7JfwWAuxY469fsii9RRrSK6prkVPqM0MBkjLU6pGsUtxSsU8v/FUjX3GZmy1re7kYcqmbMRGpDlJRazgM2qjne0UMbc1zlR4p7yPqtdKyjH121vsmGOv34+P8t89xarklqsWPaE2cxggLU+pGsUuxSkV8/zGUzX2aZveagykyUhYDAOUcHICbK3qtRJga40tETvm2Os3BraHsKdYQ3JNdS16Qm1mMEBanlI1il2KUyrm+Y2nauzeDNCYjdmETdiQDUlrD7F8CFS9VvKJcOlOY8cce/2QufMUa0iuqa5FT6jNDAZIy1OqRrFLcUrFPL/xVI19zuZsk23q5GHYhltvDDzEKL2oWihW9VrJGUXsmGOvHzJ3nmINyTXVtegJtZnBAGl5StUodilOqZjnNx7PsUuLCLHWE/B4rcSOOfb6IYvaU6whuaa6Fj2hNjMYIC1PqRrFLsUpFfP8xuM5dmkRIdZ6Ah6vldgxx14/ZFF7ijUk11TXoifUZgYDpOUpVaPYpTilYp7feDzHLi0ixFpPwOO1Ejvm2OuHLGpPsYbkmupa9ITazGCAtDylahS7FKdUzPMbj+fYpUWEWOsJeDn6vTuRxc+HmMfAe/r55CnW1v+wKBEgPWEJSAMMwQANACv0UIo9NPHy63l+4/Ece/kKYSQEzLydfLg45zGOgff088lTrPw8MaMn1FYBBkjLU6pGsUtxSsU8v/F4jl1aRIi1noBnAxTrGHhPP588xdr6HxYlAqQnLAFpgCEYoAFghR5KsYcmXn49z288nmMvXyGMhICZt6Pfu3Me6xh4Tz+fPMXKzxM+AVLXAAZITVSohwESwhRLeX7j8Ry7uIyQgwAExAQ8/XzyFKu4TLKUoyfUpg0DpOUpVaPYpTilYp7feDzHLi0ixCAAATkBTz+fPMUqL5QMBekJtUnDAGl5StUodilOqZjnNx7PsUuLCDEIQEBOwNPPJ0+xygslQ0F6Qm3SMEBanlI1il2KUyrm+Y3Hc+zSIkIMAhCQE/D088lTrPJCyVCQnlCbNAyQlqdUjWKX4pSKeX7j8Ry7tIgQgwAE5AQ8/XzyFKu8UDIUpCfUJg0DpOUpVaPYpTilYp7feDzHLi0ixCAAATkBTz+fPMUqL5QMBekJtUnDAGl5StUodilOqZjnNx7PsUuLCDEIQEBOwNPPJ0+xygslQ0F6Qm3SMEBanlI1il2KUyrm+Y3Hc+zSIkIMAs4JNPGzpAnNVNPkKdZUcxByX/SEWtoYIC1PqRrFLsUpFfP8xuM5dmkRIQYB5wSa+FnShGaqafIUa6o5CLkvekItbQyQlqdUjWKX4pSKeX7j8Ry7tIgQg4BzAk38LGlCM9U0eYo11RyE3Bc9oZY2BkjLU6pGsUtxSsVmbMZW2+qO5pRN2YiNSPVTFivedEdttLPFgoOn2FPOC3uDQG4Emmjgm9BMlaunWFPNQch90RNqaWOAtDylahS7FKdUbNqmt5oAqXBmYhigzBLGdiEQkUDRsHe/un+Z0usXSVV+ueLJFHiKNWLZJrM0PaE2FRggLU+pGsUuxSkVwwCZjdmYTdiEDdmQlC1iEIBAOwkM+rNizuYGBuHJFHiKdeBCaOEEekJtUjFAWp5SNYpdilMqVrwxb7JNHc1hG3ZpArzGLS0kxCDgiAAGSJtsDJCWZ+pq9ITaDGGAtDylahS7FCdiEIAABCAQkUCIW+A8fT+T72NGLOYIS9MTaqFjgLQ8pWoUuxQnYhCAAAQgkBCBJj7B8Hp7Mt/HTKiwG9oKPaEWLAZIy1OqRrFLcSIGAQhAAAIJEcAAaZLB9zE1HFNXoSfUZsidAdqyZYtt2LDBrrzySnvooYdsxx13tGOOOcbOOecc22233UrRfeSRR+xLX/qSffGLX7T/+I//sAcffNCe8pSn2Ite9CJ73eteZ+94xzvs6U9/eimtlQZR7LURIhCQQPG9qFmbbWRFvm/UCFZEIRCVQBMGyOP3M/n5GLWMgy1OT6hF7coAFebnqKOOssnJSdtll11s7dq19sADD9jGjRtt5513tptuusn23HPPvoTPOOMMO//88zumZ//997e99trLNm3aZN/85jftZz/7mY2Pj9t1111nw8PDfbUwQLUQMTkRAkXTMW7jNmmTjeyI33A2ghVRCEQl0IQBihoQi0OgQQIYIC1cVwbozDPPtHPPPdcOPfRQu/76623VqlUdmhdccIGtW7fODj/8cLvxxhv7Ev7gBz9ojz32WOeTnl133XXr+Hvuucde+tKXdj5Zeu9732sf+MAH+mphgGohYnIiBLobmaa2xD3uTZFFFwIQgAAEUieAAdJmyI0BevLJJ23NmjVW3L52++23dz656X7tu+++duedd9qtt95qBx54YGXKxa11xW1wz3ve8+z73/9+ZZ1iIsVeCx+TAxLoNkC9HmhYdSucclSVHPMgAAEIQKBNBOgJtdl0Y4BuuOEGO/LIIzu3uN17771LKBafDBWfEJ111lm2fv36ypS/+93vdozLr/zKr3Ruh6vzotjr0GNuSAJN3crSlG5INqwFAQhAAAIQqEuAnrAuwe3nuzFAF110kZ166ql24okn2lVXXbWE4rXXXmvHHnusHX/88XbNNddUplwcjHDcccfZc5/73M7hCHVeFHsdeswNSaApo9KUbkg2rAUBCEAAAhCoS4CesC5BpwbotNNOswsvvLBjgorv/Cx+3XHHHbbffvvZAQccYLfddltlyi972cvsa1/7mr3zne+0j370o5V1iokUey18TA5IoCmj0pRuQDQsBQEIQAACEKhNgJ6wNsLtBNx8AnTKKafYJZdcYqeffrqdd955SygWt8Xtvffets8++9jdd99difLHP/5xe/vb327Petaz7K677rLf+I3fKKWzUNSLB993332dW/YKLV4QSJlAU0alKd2UWbI3CEAAAhCAwGICGCBtTbgxQCeffLJdeumlVhxhXXzfZ/GrOMGtMD9VDVBxetzRRx9txWELV199tZ1wwgmlM4UBKo2KgYkSaMqoNKWbKEa2BQEIQAACEOhJAAOkLQw3BqjJW+CK0+N++7d/u3PCXHHbW3H7m+JFsSsoohGCQFNGpSndEExYAwIQgAAEIKAiQE+oIjmv48YANXUIQnGbWvHg0x/96Eed0+OKU+RUL4pdRRKdpgk0ZVSa0m2aB/oQgAAEIAABJQF6QiVNRwao7DHYxVHYZ599dinKP/zhDzvmp3jez7ve9S4rTJbyRbEraaLVJIHiIaWrbXVniRyeA4SxarIa0IYABCAAATUBekItUTefAD3xxBOdB6E++uijKz4IdePGjXbwwQf3pfzTn/7UDj/8cPvOd75jb37zm+0Tn/iEDQ0N9Z03yACKfRBajI1JYNqmbdRGG91CYbJGbESyBgZIghERCEAAAhAIRICeUAvajQEqsBUHIJx//vl22GGH2fXXX28jI/PNVHEs9rp16zqf5kxMTGwlfPHFF1vxX3GgwYYNG7b+/ezsrB111FF2880326tf/Wq74oor7KlPfao2MxyDLeeJYHMEmjZAYzZmEzZhQ6b5JQMGqLlaQBkCEIAABPQEMEBapq4M0JYtW+yII46wW265xXbZZRdbu3Zt52GlxZ932mmnjqHZa6+9thIuvtNT3A530kkn2WWXXbb174tnCRW3uxWm5zWveY09/elP75mV7jlV0kaxV6HGnBgE5mzONtmmztLDNiwzKguxqDUxQDGqhDUhAAEIQKAqAXrCquR6z3NlgAoEjz/+eOfTnOJTm4cffth22GEHO+aYYzpHY+++++7bUVrOAL3pTW+yyy+/vG8m5ubm+o5ZaQDFXgsfkyGwlUBheLpfxZ8Xbtnr9Z0l1a12pAACEIAABCCgIEBPqKC4TcOdAdLia1aNYm+WL+p+CAx661zxiRYvCEAAAhCAQCoE6Am1mcAAaXlK1Sh2KU7EHBPAADlOPqFDAAIQaAEBekJtEjFAWp5SNYpdihMxxwS4Bc5x8gkdAhCAQAsI0BNqk4gB0vKUqlHsUpyIQWArAQ5BoBjUBKgpNVH0IACBbgL0hNp6wABpeUrVKHYpTsQggAGiBhojgAFqDC3CEIAAj0aR1wAGSI5UJ4gB0rFECQLdBGhWqQc1AWpKTRQ9CECAT4CaqwEMUHNsaytjgGojRAACPQnQrFIYagLUlJooehCAAAaouRrAADXHtrYyBqg2QgQgAAEINEKAgzUawYooBCCwDAF6Qm1pYIC0PKVqFLsUJ2IQgAAEZAQ4Wl2GEiEIQKAEAXrCEpAGGIIBGgBW6KEUe2jirAcBCECgHAEMUDlOjIIABDQE6Ak1HBdUMEBanlI1il2KEzEIQAACMgLcAidDiRAEIFCCAD1hCUgDDMEADQAr9FCKPTRx1oMABCBQjQCHIFTjxiwIQKAcAXrCcpzKjsIAlSUVYRzFHgE6S0IAAhCoQAADVAEaUyAAgdIE6AlLoyo1EANUClOcQRR7HO6sCgEIQGBQAhigQYkxHgIQGIQAPeEgtPqPxQD1ZxRtBMUeDT0LQwACEBiIAAZoIFwMhgAEBiRATzggsD7DMUBanlI1il2KEzEIQAACEIAABCCQJQF6Qm3aMEBanlI1il2KEzEIQAACEIAABCCQJQF6Qm3aMEBanlI1il2KEzEIQAACEIAABCCQJQF6Qm3aMEBanlI1il2KEzEIQAACEIAABCCQJQF6Qm3aMEBanlI1il2KEzEIQAACEIAABCCQJQF6Qm3aMEBanlI1il2KEzEIQAACEIAABCCQJQF6Qm3aMEBanlI1il2KEzEIQAACEIAABCCQJQF6Qm3aMEBanlI1il2KEzEIQAACEIAABCCQJQF6Qm3aMEBanlI1il2KEzEIQAACEIAABCCQJQF6Qm3aMEBanlI1il2KEzEIQAACEIAABCCQJQF6Qm3aMEBanlI1il2KEzEIQAACEIAABCCQJQF6Qm3aMEBanlI1il2Ks5bYnM3ZrM3W0og1ediGbciGYi3PuhCAAAQgAAEI1CRAT1gT4KLpGCAtT6kaxS7FWVmsMD/jNm6TNllZI+bEMRuzCZvABMVMAmtDAAIQgAAEahCgJ6wBr8dUDJCWp1SNYpfirCy22TbbKltVeX4KE2dsxkZsJIWtsAcIQAACEIAABAYkQE84ILA+wzFAWp5SNYpdirOyWLcBmrKpbIxEse9RG+3EjQGqnH4mQgACEIAABKIToCfUpgADpOUpVaPYpTgri3UboJyMRK77rpwoJkIAAhCAAARaSoCeUJtYDJCWp1SNYpfirCyWq5HIdd+VE8VECEAAAhCAQEsJ0BNqE4sB0vKUqlHsUpyVxXI1Ernuu3KimAgBCEAAAhBoKQF6Qm1iMUBanlI1il2Ks7JYrkYi131XThQTIQABCEAAAi0lQE+oTSwGSMtTqkaxS3FWFsvVSOS678qJYiIEIAABCECgpQToCbWJxQBpeUrVKHYpzspiuRqJXPddOVFMhAAEIAABCLSUAD2hNrEYIC1PqRrFLsVZWSxXI5HrvisniokQgAAEIACBlhKgJ9QmFgOk5SlVo9ilOCuL5Wokct135UQxEQIQgAAEINBSAvSE2sRigP5/e/cBY0XVBXD80D7LoiIgCwJGKUo0ka6iYENKFAXBFkWk2xAUxKggSBMlSCc2qogdgSgKWJCgNAFFBQtglyY1oIAgfDk3eWQby3t3z76d+/Y/iYnIzHl3fue4e8+8mTu2nqbRKHZTTu9goTYSoY7bO1EciAACCCCAQIoKMCe0TSwNkK2naTSK3ZTTO1iojUSo4/ZOFAcigAACCCCQogLMCW0TSwNk62kajWI35fQOtlf2yilyijt+i2yRNEnzjpXMA7UBSpd095F6DqGMO5lGfBYCCCCAAAIhCDAntM0SDZCtp2k0it2U0zvYVtl6tJHwDlLAB9IAFXAC+HgEEEAAAQTyIMCcMA94ORxKA2TraRqNYjfl9A4WegN0mVwmi2SRFJEi3gYciAACCCCAAAIFJ8Cc0NaeBsjW0zQaxW7K6R3siByRv+Qvd/zJcnJwjUSIY/ZOFgcigAACCCCQggLMCW2TSgNk62kajWI35SQYAggggAACCCAQpABzQtu00QDZeppGo9hNOQmGAAIIIIAAAggEKcCc0DZtNEC2nqbRKHZTToIhgAACCCCAAAJBCjAntE0bDZCtp2k0it2Uk2AIIIAAAggggECQAswJbdNGA2TraRqNYjflJBgCCCCAAAIIIBCkAHNC27TRANl6mkaj2E05CRZhAX1pa0kp6UbIO4sinCiGhgACCCBQIALMCW3ZaYBsPU2jUeymnASLsAANUISTw9AQQAABBApcgDmhbQpogGw9TaNR7KacBIuwAA1QhJPD0BBAAAEEClyAOaFtCmiAbD1No1HsppwEi7AADVCEk8PQEEAAAQQKXIA5oW0KaIBsPU2jUeymnASLkIA2PBk3/XO6pLv/tEW2SJqkZfr7rH+O0KkwFAQQQAABBPJdgDmhLTENkK2naTSK3ZSTYBESKCJFEhrNETmS0P7sjAACCCCAQCoJMCe0zSYNkK2naTSK3ZSTYBESoAGKUDIYCgIIIIBA5AWYE9qmiAbI1tM0GsVuykmwCAlwC1yEksFQEEAAAQQiL8Cc0DZFNEC2nqbRKHZTToJFWIBFECKcHIaGAAIIIFDgAswJbVNAA2TraRqNYjflJFiEBWiAIpwchoYAAgggUOACzAltU0ADZOtpGo1iN+UkWIQFaIAinByGhgACCCBQ4ALMCW1TQANk62kajWI35SRYhAVogCKcHIaGAAIIIFDgAswJbVNAA2TraRqNYjflJBgCCCCAAAIIIBCkAHNC27TRANl6mkaj2E05CYYAAggggAACCAQpwJzQNm00QLaeptEodlNOgiGAAAIIIIAAAkEKMCe0TRsNkK2naTSK3ZSTYAgggAACCCCAQJACzAlt00YDZOtpGo1iN+UkGAIIIIAAAgggEKQAc0LbtNEA2XqaRqPYTTkJhgACCCCAAAIIBCnAnNA2bTRAtp6m0Sh2U06CIYAAAggggAACQQowJ7RNGw2QradpNIrdlJNgCCCAAAIIIIBAkALMCW3TRgNk62kajWI35SQYAggggAACCCAQpABzQtu00QDZeppGo9hNOQmGAAIIIIAAAggEKcCc0DZtNEC2nqbRKHZTToIhgAACCCCAAAJBCjAntE0bDZCtp2k0it2Uk2AIIIAAAggggECQAswJbdNGA2TraRqNYjflJBgCCCCAAAIIIBCkAHNC27TRANl6mkaj2E05CYYAAggggAACCAQpwJzQNm00QLaeptEodlNOgiGAAAIIIIAAAkEKMCe0TRsNkK2naTSK3ZSTYAgggAACCCCAQJACzAlt00YDZOtpGo1iN+UkGAIIIIAAAgggEKQAc0LbtNEA2XqaRqPYTTkJhgACCCCAAAIIBCnAnNA2bTRAtp6m0Sh2U06CIYAAAggggAACQQowJ7RNGw2QradpNIrdlJNgCCCAAAIIIIBAkALMCW3TRgNk62kajWI35Qwu2N/yt5SUkm7ce2WvpElacOfAgBFAAAEEEEAg7wLMCfNumDECDZCtp2k0it2UM7hgNEDBpYwBI4AAAgggkC8CzAltWWmAbD1No1HsppzBBaMBCi5lDBgBBBBAAIF8EWBOaMtKA2TraRqNYjflDC4YDVBwKWPACCCAAAII5IsAc0JbVhogW0/TaBS7KWfkg2nDk3HTP6dLuvtPW2RLtmeAeCYo8illgAgggAACCJgIMCc0YTwahAbI1tM0GsVuyhn5YEWkSEJjPCJHEtqfnRFAAAEEEEAgTAHmhLZ5owGy9TSNRrGbckY+GA1Q5FPEABFAAAEEECgQAeaEtuw0QLaeptEodlPOyAfjFrjIp4gBIoAAAgggUCACzAlt2WmAbD1No1HsppzBBWMRhOBSxoARQAABBBDIFwHmhLasNEC2nqbRKHZTzuCC0QAFlzIGjAACCCCAQL4IMCe0ZaUBsvU0jUaxm3IGF4wGKLiUMWAEEEAAAQTyRYA5oS0rDZCtp2k0it2UM7hgNEDBpYwBI4AAAgggkC8CzAltWWmAbD1No1HsppwEQwABBBBAAAEEghRgTmibNhogW0/TaBS7KSfBEEAAAQQQQACBIAWYE9qmrdA1QPv375ehQ4fKa6+9Jr/99puULl1amjdvLgMHDpRKlSolpLtr1y558sknZebMmbJ582YpX768tGrVSgYMGCClSpVKKFZOO1PseSYkAAIIIIAAAgggELwAc0LbFBaqBkibn8aNG8vixYulQoUK0qhRI/nll19k+fLlcsYZZ8iSJUukatWqcQlv375dGjRoIOvWrZMqVapIvXr1ZM2aNe6fatWqydKlS6VMmTJxxTrWThR7nvg4GAEEEEAAAQQQSAkB5oS2aSxUDVC/fv1k0KBBrnGZP3++lCxZ0mmOGDFCevXqJZdffrksXLgwLuF27drJtGnTpHXr1vLGG29I8eLF3XHdu3eXsWPHiv791KlT44pFA5QnJg5GAAEEEEAAAQRSWoAGyDa9haYBOnjwoJQrV070trVVq1ZJ7dq1M0nWrFlTvv76a1mxYoXUrVs3V2W93a1ixYpSrFgx+f333yU9Pf3o/gcOHJDKlSvLjh075M9HCLotAAAUo0lEQVQ//8z0d4mmjmJPVIz9EUAAAQQQQACB1BNgTmib00LTAC1YsECuvvpqd4vb+vXrsynqN0P6DVH//v3dcz25bZMnT5aOHTu62+k++uijbLt26tRJJk2aJLpf+/btvTNGsXvTcSACCCCAAAIIIJAyAswJbVNZaBqgUaNGyUMPPSQ333yzvPnmm9kU58yZIy1atHCLGOiiBrltDz74oIwePVp69+4tw4YNy7br+PHjpVu3bqL7jRw50jtjFLs3HQcigAACCCCAAAIpI8Cc0DaVhaYB6tmzp2tGtAnSZ36ybqtXr5ZatWpJnTp1ZOXKlbkq63M/2iRpE6TP/GTdZs+e7Rop3W/GjBneGaPYvek4EAEEEEAAAQQQSBkB5oS2qSw0DVDXrl3lpZdekj59+sjgwYOzKeptcdWrV5dzzz1Xfvjhh1yVmzZtKh9++KGL17lz52z76m1xTZo0Ed1v3rx5x81YrKiz7vj9999LiRIl4l6Z7rgfxA4IIIAAAggggAACwQls2LDBzQn37NkT3NijOOBC0wB16dJFJkyYIH379nUrwWXddDlrbX7iaYC0udEmR+Pp8z5ZN22OtPnJawO0du1aKVq0qNSoUSOKtcOYkiCgP/B0i3d59iQMiY9IsgA1kGTwCH4cNRDBpCR5SNRAksEj+HF6UbxIkSJy6NChCI4uvCEVmgaIW+DCK05GLMJX3lQBNUANUAPUADVADVADtjVQaBogFkGwLRyiJUeAH3jJcY7yp1ADUc5OcsZGDSTHOcqfQg1EOTvJGRs1YOtcaBqgeJfB1qWwBwwYkKtyvMtg61LYHTp08M4Yxe5NlzIHUgMpk0rvE6EGvOlS5kBqIGVS6X0i1IA3XcocSA3YprLQNED//vuvexHq7t27c30R6vLly6V+/fq5Km/atEkqVaokxYsXdy9C1bixLfYi1O3bt7sXoZYvX947YxS7N13KHEgNpEwqvU+EGvCmS5kDqYGUSaX3iVAD3nQpcyA1YJvKQtMAKZsugDBkyBC59NJLZf78+ZKWluY0dVnsXr16ScOGDWXRokVHhceNGyf6z4033ihDhw7NJN+2bVuZPn26tGnTRl5//XXXDOnWo0cPGTNmjOjfT5s2LU/ZotjzxJcSB1MDKZHGPJ0ENZAnvpQ4mBpIiTTm6SSogTzxpcTB1IBtGgtVA7R//3658sorZdmyZVKhQgVp1KiR/Prrr+7PZcqUkaVLl0q1atWOCj/55JPudri77rpLpkyZkkl+27Ztcskll4iuzKIrdNWrV0/WrFkj3377rfuzxipbtmyeskWx54kvJQ6mBlIijXk6CWogT3wpcTA1kBJpzNNJUAN54kuJg6kB2zQWqgZI6fbt2+e+zXn11Vfd7Wunn366NG/e3C2NXbly5Uy6uTVAuuPOnTulf//+MmvWLNmyZYukp6dLy5YtXdNUunRp20wRDQEEEEAAAQQQQAABBPIsUOgaoDyLEQABBBBAAAEEEEAAAQSCFaABCjZ1DBwBBBBAAAEEEEAAAQQSFaABSlSM/RFAAAEEEEAAAQQQQCBYARqgYFPHwBFAAAEEEEAAAQQQQCBRARqgRMXYHwEEEEAAAQQQQAABBIIVoAEKNnUMHAEEEEAAAQQQQAABBBIVoAFKVIz9EUAAAQQQQAABBBBAIFgBGqAkpk5fxKrvIHrttdfkt99+c+8K0ncQDRw4UCpVqpTQSHbt2iX6nqKZM2fK5s2bpXz58tKqVSv3DqJSpUolFIudkydgUQOa+/fff1/ee+89+eqrr9zLfIsWLSrnn3++3H777XLfffdJiRIlkndSfFJCAhY1kNMHrlu3Ti688ELR+M2aNZO5c+cmNC52Tp6AdQ2sX79ennnmGfnwww/d74NTTjlFqlevLjfeeKP07t07eSfGJ8UtYFkD+v/66NGj5YsvvpDdu3e79xtedNFF8tBDD0njxo3jHhM7Jk9g5cqV7v/X5cuXy7Jly2Tjxo1ywgknuJ/fPhtzwsTVaIASN/M6QotafxAtXrxYKlSoII0aNZJffvnFFf8ZZ5whS5YskapVq8YVe/v27dKgQQPRCU+VKlWkXr16smbNGvdPtWrVZOnSpVKmTJm4YrFT8gSsaqBv374yZMgQ1/TUrl3b5fyvv/6Szz//XA4cOCANGzaUefPmycknn5y8k+OT4hKwqoGcPuzqq6+WTz/9VI4cOUIDFFc2CmYn6xrQi2B64UP/39efB+eee67o74hvvvlG0tLSRJsjtmgJWNbAiBEjpFevXlKkSBG57LLLpGLFivLTTz+5Zki35557Tu65555oATAad8F69uzZmSR8GyDmhH4FRQPk55bwUf369ZNBgwa5xmX+/PlSsmRJFyP2w+vyyy+XhQsXxhW3Xbt2Mm3aNGndurW88cYbUrx4cXdc9+7dZezYsaJ/P3Xq1LhisVPyBKxq4Omnn5Y9e/a4b3r0l11s04b4mmuucd8uPvbYY/LUU08l7+T4pLgErGog64dNnDhROnfuLF27dpUXX3yRBiiubBTMTpY1sHr1anelX7/xmTVrlrv4EdsOHz4sq1atchfI2KIlYFUDeuErdvfIxx9/nCn/M2bMkJtvvllOOukk2bJly9E5R7QkCu9o9Bvbf/75R+rXr+/+0bt4fBsg5oR+dUQD5OeW0FEHDx6UcuXKiX5Fqb+Q9Cpdxq1mzZry9ddfy4oVK6Ru3bq5xtbbG3TSW6xYMfn9998lPT396P56BbBy5cqyY8cO+fPPPzP9XUIDZmdzAcsayG1wenulXg0+++yz5eeffzY/DwL6C+RXDWzdulVq1Kjhfnb06dNHrrrqKhog/zTl65HWNaAXzhYtWiTvvvuutGjRIl/HTnAbAcsa0Nugr7/+encr/QcffJBtgLVq1RJtkvUWK22U2aIroN/g+TRAzAn9c0oD5G8X95ELFiwQvT1Fb3HL6XYE/WZIrwj179/fPdeT2zZ58mTp2LGju53uo48+yrZrp06dZNKkSaL7tW/fPu4xsmP+CljWQG4jXbt2rVxwwQXyv//9z90SwxYdgfyqgdtuu83dSqG3PP3xxx80QNFJebaRWNbAd999557701vefvjhhwifNUPLKGBZA/oMSdOmTY/bAOndAXqrNFt0BXwbIOaE/jmlAfK3i/vIUaNGuYcR9evoN998M9txc+bMcVfv9J5QvZ87t+3BBx90Dzvqg63Dhg3Ltuv48eOlW7duovuNHDky7jGyY/4KWNZAbiONXRE866yz3OIIbNERyI8a0MUwrrvuOreQyhNPPOGeAeIboOjkPOtILGtg3Lhx8sADD8j9998vw4cPd7dD610EOpHSxTBuueUWOfXUU6OLUUhHZlkDeleJftu/b98+yXoL3DvvvCM33XSTu+1enw9li7aAbwPEnNA/rzRA/nZxH9mzZ0/XjGgTpM/8ZN30K2r9qrpOnTqiK4PktulzP9okaROkz/xk3fRKsDZSup/eA8wWDQHLGsjtjJo0aeK+GdSJ0ZgxY6Jx8ozCCVjXwN9//+2+7TvxxBPdLbT6rR8NULSLzbIG7r33Xnn++efl4YcfdrfAZf0WqGzZsu53gN4mxxYdAcsa0LN6++235Y477hC9tS62CILe/qyLIOitcVOmTHG34LNFW8C3AWJO6J9XGiB/u7iP1AeTX3rpJXd//uDBg7Mdp7fF6ZKl8dzKoF9369feGk8fes666eRXJ8G6n64ExhYNAcsaONYZ6WRIJ0W6DLquCHjmmWdG4+QZhROwrgG9oKJXkz/55BP3rY9uNEDRLjbLGtBbH2OL4Oiyxy+88IK71VofeNfXIbz66qtuOWT9WaArj7JFQ8CyBmJnpD8Dbr31Vtm2bdvRk9Tng7U51p8T+swwW7QFfBsg5oT+eaUB8reL+8guXbrIhAkTRJcv1ud9sm56f642P/E0QLEr/BpPn/fJusXuCaYBijs9SdnRsgZyGrCuIKg516uAetVX3//BFi0ByxrQW50uueQSd+U344qPNEDRynnW0VjWgN5SrVf/ddOLXfr/f8ZNH3rXbwGOdeEt2lKpOzrLGlClZ599Vh555BF354c+Q6yvxtBlsPW5Yl0ZsE2bNkfrJHVVwz8z3waIOaF/7mmA/O3iPtLyK2++7oybPVI7WtZA1hPT25+uuOIKt8qg3vamt7+xRU/AqgYOHTrklk3V5c6///579x6x2EYDFL28ZxyRVQ1oTF0MRx+A1lVBdfGLrJu+/0WXytfboj777LNowxSi0VnWgF74uvLKK93t89rs6rvhYtt///3nfk58+eWXOTbIhYg8iFP1bYCYE/qnlwbI3y7uIy0feuSBt7jZI7WjZQ1kPLENGza4dz/oUph69U9XEmSLpoBVDegLlM855xz33ojzzjsv08lqE6zPFOqtT/ogvL5vTBfGYIuGgFUN6Nnowhf6//ull16a40Puuizytdde626v/vHHH6MBwCjcbatWiyLFVn3VW+v1m76sm/53XRyF98JFv/B8GyDmhP65pQHyt4v7yHiXvdSvrPXe7dy2eJc81KWwO3ToEPcY2TF/BSxrIDbSjRs3uuZHH3jt0aOH+8XKFl0BqxqINUDxnOlpp53mvhlki4aAVQ3o2ejCBzfccIN7B5QuiZ11e+WVV+TOO+90753T98+xRUPAsgaaNWvmXqx+rG/+9b/r74a7777bLZjBFl0B3waIOaF/TmmA/O3iPvLff/91q7Ds3r071xehLl++3H1lndu2adMm9+bn4sWLuxehZlzdJfYi1O3bt7sXoeoVYrZoCFjWgJ7Rzp073epO3377rWt0J06c6Ja/ZYuugHUN5HSm3AIX3fzryCxrQN8irz//NaZ+E6wvwc646SI5+nNBvyXQZ0bZoiFgWQN33XWXvPzyy9KuXbtMzwLGzlQbYG2Ehw4dKo8++mg0ABhFjgK+DRBzQv+CogHyt0voSF0AYciQIe52Bb1ik5aW5o7XZbF79erlruTrG71jm77jQf/Rh9n1h1fGrW3btjJ9+nT3cOPrr7/umiHd9EqPXvHRv582bVpC42Pn/BewqgGd+OiLcJcuXere9aGrPbHKT/7nz+ITrGrgWGOhAbLIUv7GsKwBvbXp6aefdu+C0hXhYr9X5s6dK9dff73ocyD6c0IXRGCLjoBVDegrMfQZEP35r/+uOY9t+koM/Tvd9AXZWW+XjY4GI1GB4zVAzAnt64QGyN40x4j79+93DysuW7bMLUnaqFEj96JK/XOZMmXcL6mMb2rW5zn0dji9wqPr+GfcdKlLXQFKr/pVrVpV6tWr55Y61W8D9M8aS98BwRYtAasaiC1/rL/0dOnTEiVK5HiiWesmWhqFczRWNUADFG79WNaAxrrmmmvcM0D6e+Xiiy+WrVu3ut8Bhw8fdhfdHn/88XCxUnTkVjVw5MgR9zvgrbfeclI6F9DnA/W2aF0pUjdqIJpFNGfOnEyrAutcUJugjBcr9PktvbihG3NC+zzSANmbHjOivq1Zv83RK/Z6+5o+qKwvKtOlsbPevpBbsesH6C1Q+gCsLnOp733QNf9btmzpmqbSpUsn8az4qEQELGqgffv2Od7ukHUc+suRLXoCFjVAAxS9vCYyIssa0Fuqhg8f7m510uWP9cW4OhHWCyWxyVMiY2Pf5AhY1YD+nNfnQHQ5fF0RdO/eve5dcDqR1hVBdY7BFj0BvUB5vOe0Na/6+/54DRBzQr/80gD5uXEUAggggAACCCCAAAIIBChAAxRg0hgyAggggAACCCCAAAII+AnQAPm5cRQCCCCAAAIIIIAAAggEKEADFGDSGDICCCCAAAIIIIAAAgj4CdAA+blxFAIIIIAAAggggAACCAQoQAMUYNIYMgIIIIAAAggggAACCPgJ0AD5uXEUAggggAACCCCAAAIIBChAAxRg0hgyAggggAACCCCAAAII+AnQAPm5cRQCCCCAAAIIIIAAAggEKEADFGDSGDICCCCAAAIIIIAAAgj4CdAA+blxFAIIIIAAAggggAACCAQoQAMUYNIYMgIIIIAAAggggAACCPgJ0AD5uXEUAggggAACCCCAAAIIBChAAxRg0hgyAggggAACCCCAAAII+AnQAPm5cRQCCCCAAAIIIIAAAggEKEADFGDSGDICCCCAAAIIIIAAAgj4CdAA+blxFAIIIIAAAggggAACCAQoQAMUYNIYMgIIIIAAAggggAACCPgJ0AD5uXEUAggggAACCCCAAAIIBChAAxRg0hgyAggggAACCCCAAAII+AnQAPm5cRQCCCCAAAIIIIAAAggEKEADFGDSGDICCCCAAAIIIIAAAgj4CdAA+blxFAIIIIAAAggggAACCAQoQAMUYNIYMgIIIIAAAggggAACCPgJ0AD5uXEUAggggAACCCCAAAIIBChAAxRg0hgyAggggAACCCCAAAII+AnQAPm5cRQCCCCAAAIIIIAAAggEKEADFGDSGDICCCCAAAIIIIAAAgj4CdAA+blxFAIIIIAAAggggAACCAQoQAMUYNIYMgIIIIAAAggggAACCPgJ0AD5uXEUAggggAACCCCAAAIIBChAAxRg0hgyAggggAACCCCAAAII+AnQAPm5cRQCCCCAAAIIIIAAAggEKEADFGDSGDICCCCAAAIIIIAAAgj4CdAA+blxFAIIIIAAAggggAACCAQoQAMUYNIYMgIIIIAAAggggAACCPgJ0AD5uXEUAggggAACCCCAAAIIBChAAxRg0hgyAggggAACCCCAAAII+AnQAPm5cRQCCCCAAAIIIIAAAggEKEADFGDSGDICCCCAAAIIIIAAAgj4CdAA+blxFAIIIIAAAggggAACCAQoQAMUYNIYMgIIIIAAAggggAACCPgJ0AD5uXEUAggggAACCCCAAAIIBChAAxRg0hgyAggggAACCCCAAAII+AnQAPm5cRQCCCCAAAIIIIAAAggEKEADFGDSGDICCCCAAAIIIIAAAgj4CdAA+blxFAIIIIAAAggggAACCAQoQAMUYNIYMgIIIIAAAggggAACCPgJ0AD5uXEUAggggAACCCCAAAIIBCjwf3/5f2VKZPBkAAAAAElFTkSuQmCC\" 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      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "EFMNNClassifier(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, 2, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2,\n",
       "       1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 2, 2, 2, 1, 2,\n",
       "       2, 1, 1, 2, 1, 2, 2, 1, 2, 1, 2]),\n",
       "                V=array([[0.42413   , 0.53516   ],\n",
       "       [0.74088   , 0.43310562],\n",
       "       [0.91059   , 0.82085   ],\n",
       "       [0.64586   , 0.50818437],\n",
       "       [0.4713    , 0.672     ],\n",
       "       [0.33484   , 0.18424   ],\n",
       "       [0.32289   , 0.59994   ],\n",
       "       [0.19944   , 0.03      ],\n",
       "       [0.28077   , 0.26124...\n",
       "       [0.36842   , 0.77238   ],\n",
       "       [0.36057   , 0.71561   ],\n",
       "       [0.6733    , 0.29485   ],\n",
       "       [0.25621   , 0.62174   ],\n",
       "       [0.14737   , 0.28498   ],\n",
       "       [0.72496   , 0.34978   ],\n",
       "       [0.73681   , 0.71261   ],\n",
       "       [0.76138   , 0.32629   ],\n",
       "       [0.52124   , 0.41288   ],\n",
       "       [0.42647   , 0.66846   ],\n",
       "       [0.91185   , 0.48697   ],\n",
       "       [0.29163   , 0.086547  ],\n",
       "       [0.35813   , 0.58584   ],\n",
       "       [0.56487   , 0.17003   ],\n",
       "       [0.287     , 0.46814   ],\n",
       "       [0.44575   , 0.64683   ],\n",
       "       [0.25924   , 0.42696   ],\n",
       "       [0.77398   , 0.5357    ],\n",
       "       [0.68469   , 0.2221    ]]),\n",
       "                is_draw=True, theta=0.1)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "efmnn_clf = EFMNNClassifier(theta=theta, gamma=gamma, is_draw=is_draw)\n",
    "efmnn_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": 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>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"588\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "efmnn_clf.draw_hyperbox_and_boundary(\"The trained FMNNN and its decision boundaries\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of existing hyperboxes = 77\n"
     ]
    }
   ],
   "source": [
    "print(\"Number of existing hyperboxes = %d\"%(efmnn_clf.get_n_hyperboxes()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import accuracy_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy =  85.80%\n"
     ]
    }
   ],
   "source": [
    "y_pred = efmnn_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": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "sample_need_explain = 10\n",
    "y_pred_input_0, mem_val_classes, min_points_classes, max_points_classes = efmnn_clf.get_sample_explanation(Xtest[sample_need_explain])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Membership values:\n",
      "Class 1 has the maximum membership value = 0.957157\n",
      "Class 2 has the maximum membership value = 0.995862\n",
      "Class 1 has the representative hyperbox: V = [0.55763 0.40507] and W = [0.58339 0.43813]\n",
      "Class 2 has the representative hyperbox: V = [0.57285 0.24904] and W = [0.66773 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": 21,
   "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>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"570\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "efmnn_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": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create the parallel coordinates graph\n",
    "efmnn_clf.show_sample_explanation(Xtest[sample_need_explain], Xtest[sample_need_explain], min_points_classes, max_points_classes, y_pred_input_0, file_path=\"iframe_figures/efmnn_par_cord.html\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"820\"\n",
       "            height=\"500\"\n",
       "            src=\"iframe_figures/efmnn_par_cord.html\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x25f102b6d68>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load the result to show on the notebook\n",
    "from IPython.display import IFrame\n",
    "IFrame('iframe_figures/efmnn_par_cord.html', width=820, height=500)"
   ]
  }
 ],
 "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
}