examples/numerical_data/incremental_learner/knefmnn_general_use.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# This example shows how to use the Simpson's Fuzzy Min-Max Neural Network classifier using an enhanced online learning algorithm with k-nearest hyperboxes selection (KNEFMNN)"
   ]
  },
  {
   "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 KNEFMNN classifier 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 Simpson's FMNN classifier using the enhanced online learning algorithm with k-nearest hyperboxes selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\hyperbox-brain\\\\hbbrain\\\\numerical_data\\\\incremental_learner\\\\knefmnn.py'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "knefmnn_file_path = os.path.join(project_dir, Path(\"hbbrain/numerical_data/incremental_learner/knefmnn.py\"))\n",
    "knefmnn_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: knefmnn.py [-h] -training_file TRAINING_FILE -testing_file TESTING_FILE\n",
      "                  [--theta THETA] [--gamma GAMMA] [--k_neighbors K_NEIGHBORS]\n",
      "                  [--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",
      "  --k_neighbors K_NEIGHBORS\n",
      "                        The number of nearest hyperboxes is considered for the\n",
      "                        hyperbox expansion process\n",
      "  --is_draw IS_DRAW     Show the existing hyperboxes during the training\n",
      "                        process on the screen (default: False)\n"
     ]
    }
   ],
   "source": [
    "!python \"{knefmnn_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 = 51\n",
      "Testing accuracy =  86.60%\n"
     ]
    }
   ],
   "source": [
    "!python \"{knefmnn_file_path}\" -training_file \"{training_data_file}\" -testing_file \"{testing_data_file}\" --theta 0.1 --k_neighbors 5 --gamma 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Using the KNEFMNN classifier through its init, fit, and predict functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "from hbbrain.numerical_data.incremental_learner.knefmnn import KNEFMNNClassifier\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",
    "k_neighbors = 5\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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       "    } 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",
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       "        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",
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       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
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       "    this.root = $('<div/>');\n",
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       "    this.root.attr('style', 'display: inline-block');\n",
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       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
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       "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",
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       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
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       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
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       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
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       "\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",
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       "\n",
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       "            pass_mouse_events = false;\n",
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       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
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       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
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       "    this._resize_canvas(600, 600);\n",
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       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
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       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
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       "        }\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",
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       "        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",
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       "        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",
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       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
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       "\n",
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       "    if (!this.waiting) {\n",
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       "        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",
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       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
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       "        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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\" width=\"584.6666666666666\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "KNEFMNNClassifier(C=array([1, 2, 1, 1, 1, 2, 1, 2, 2, 1, 2, 2, 2, 2, 1, 1, 2, 2, 1, 1, 2, 1,\n",
       "       1, 2, 2, 2, 2, 1, 1, 2, 2, 1, 1, 2, 2, 1, 1, 1, 2, 1, 2, 1, 1, 2,\n",
       "       1, 2, 2, 2, 2, 2, 1]),\n",
       "                  V=array([[0.42413   , 0.53516   ],\n",
       "       [0.70577   , 0.397105  ],\n",
       "       [0.82785   , 0.78025   ],\n",
       "       [0.66038   , 0.51128   ],\n",
       "       [0.48794   , 0.672     ],\n",
       "       [0.26651   , 0.18424   ],\n",
       "       [0.32289   , 0.59994   ],\n",
       "       [0.19944   , 0.03      ],\n",
       "       [0.28077   , 0.26124   ],\n",
       "       [0.63683   , 0.6936    ],\n",
       "       [0.28822   , 0.55512   ],\n",
       "       [0.03      , 0.47757   ],\n",
       "       [0...\n",
       "       [0.91185   , 0.5761    ],\n",
       "       [0.2246    , 0.13567   ],\n",
       "       [0.25929   , 0.81558   ],\n",
       "       [0.815     , 0.397095  ],\n",
       "       [0.67906   , 0.83605   ],\n",
       "       [0.52197   , 0.91371   ],\n",
       "       [0.66037   , 0.57837   ],\n",
       "       [0.49408   , 0.66846   ],\n",
       "       [0.80583   , 0.43242   ],\n",
       "       [0.79935   , 0.7757    ],\n",
       "       [0.35813   , 0.58772   ],\n",
       "       [0.79516   , 0.32629   ],\n",
       "       [0.36057   , 0.71561   ],\n",
       "       [0.68469   , 0.29485   ],\n",
       "       [0.70743   , 0.50325   ],\n",
       "       [0.25621   , 0.62174   ],\n",
       "       [0.14737   , 0.28498   ],\n",
       "       [0.56487   , 0.17003   ],\n",
       "       [0.55763   , 0.43813   ]]),\n",
       "                  is_draw=True, theta=0.1)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "knefmnn_clf = KNEFMNNClassifier(theta=theta, k_neighbors=k_neighbors, gamma=gamma, is_draw=is_draw)\n",
    "knefmnn_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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QAACEIAABCAQAQL0n3aDjBizy9eodYrBKE6MQQACEIAABCAAAQh0QYD+026KIMbs8jVqnWIwihNjEIAABCAAAQhAAAKIMU9zADHmKX53kyPG3PFiNAQgAAEIQAACEIBAcgToP5Pj19XZiLGuCPnoc4rBR8HAFQhAAAIQgAAEIBABAvSfdoOMGLPL16h1isEoToxBAAIQgAAEIAABCHRBgP7TboogxuzyNWqdYjCKE2MQgAAEIAABCEAAAogxT3MAMeYpfneTI8bc8WI0BCAAAQhAAAIQgEByBOg/k+PX1dmIsa4I+ehzisFHwcAVCEAAAhCAAAQgEAEC9J92g4wYs8vXqHWKwShOjEEAAhCAAAQgAAEIdEGA/tNuiiDG7PI1ap1iMIoTYxCAAAQgAAEIQAACiDFPcwAx5il+d5MjxtzxYjQEIAABCEAAAhCAQHIE6D+T49fV2Yixrgj56HOKwUfBwBUIQAACEIAABCAQAQL0n3aDjBizy9eodYrBKE6MQQACEIAABCAAAQh0QYD+026KIMbs8jVqnWIwihNjEIAABCAAAQhAAAKIMU9zADHmKX53kyPG3PFiNAQgAAEIQAACEIBAcgToP5Pj19XZiLGuCPnoc4rBR8HAFQhEkMDu3dLmzRFcuKS8PCktLZprZ9UQgEC0CdB/2o0/YswuX6PWKQajODEGAQi4IOAIscZGqanJxUkhGtrQIM2ahSALUUhZCgQgECcB+s84QSU4DDGWIDgvTqMYvKDOnBCAgENg0yapoCDaLFpbpfz8aDNg9RCAQPQI0H/ajTlizC5fo9YpBqM4MQYBCLgg0FmMNTdHR5Q46y4vbweFGHORMAyFAARCQ4D+024oEWN2+Rq1TjEYxYkxCEDABYHOYixKoiSq63aRGgyFAARCToD+026AEWN2+Rq1TjEYxYkxCEDABYGoipKorttFajAUAhAIOQH6T7sBRozZ5WvUOsVgFCfGIAABFwSiKkqium4XqcFQCEAg5AToP+0GGDFml69R6xSDUZwYgwAEXBCIqiiJ6rpdpAZDIQCBkBOg/7QbYMSYXb5GrVMMRnFiDAIQcEEgqqIkqut2kRoMhQAEQk6A/tNugBFjdvkatU4xGMWJMQhAwAWBqIqSqK7bRWowFAIQCDkB+k+7AUaM2eVr1DrFYBQnxiAAARcEoipKorpuF6nBUAhAIOQE6D/tBhgxZpevUesUg1GcGIMABFwQiKooieq6XaQGQyEAgZAToP+0G2DEmF2+Rq1TDEZxYgwCEHBBIKqiJKrrdpEaDIUABEJOgP7TboARY3b5GrVOMRjFiTEIQMAFgaiKkqiu20VqMBQCEAg5AfpPuwFGjNnla9Q6xWAUJ8YgAAEXBKIqSqK6bhepwVAIQCDkBOg/7QYYMWaXr1HrFINRnBiDAARcEIiqKInqul2kBkMhAIGQE6D/tBtgxJhdvkatUwxGcWIMAhBwQSCqoiSq63aRGgyFAARCToD+026AEWN2+Rq1TjEYxYkxCEDABYGoipKorttFajAUAhAIOQH6T7sBRozZ5WvUOsVgFCfGIAABFwSiKkqium4XqcFQCEAg5AToP+0GGDFml69R6xSDUZwYgwAEXBCIqiiJ6rpdpAZDIQCBkBOg/7QbYMSYXb5GrVMMRnFiDAIQcEEgqqIkqut2kRoMhQAEQk6A/tNugBFjdvkatU4xGMWJMQhAwAWBqIqSqK7bRWowFAIQCDkB+k+7AUaM2eVr1DrFYBQnxiAAARcEoipKorpuF6nBUAhAIOQE6D/tBhgxZpevUesUg1GcGIMABFwQiKooieq6XaQGQyEAgZAToP+0G2DEmF2+Rq1TDEZxYgwCEHBBIKqiJKrrdpEaDIUABEJOgP7TboARY3b5GrVOMRjFiTEIQMAFgaiKkqiu20VqMBQCEAg5AfpPuwFGjNnla9Q6xWAUJ8YgAAEXBKIqSqK6bhepwVAIQCDkBOg/7QYYMWaXr1HrFINRnBiDAARcEIiqKInqul2kBkMhAIGQE6D/tBtgxJhdvkatUwxGcWIMAhBwQSCqoiSq63aRGgyFAARCToD+026AEWN2+Rq1TjEYxYkxCEDABYGoipKorttFajAUAhAIOQH6T7sBRozZ5WvUOsVgFCfGIAABFwSiKkqium4XqcFQCEAg5AToP+0GGDFml69R604x7Jb0ymtvGLWLMQikgkBmepoy0tNSMZV275Y2b07JVEYnycuT0lKDyLXfURUlUV236wThBAhAILQEEGN2Q4sYs8vXqHWnGNq279Ktf59l1C7GIJAKAnnZmarrmadehVlKs6g4HCHW2Cg1NaViVWbnaGiQZs3ypyCLqiiJ6rrNZjbWIACBIBNAjNmNHmLMLl+j1p1iaN64Vad/7z6jdjEGgVQQKMzN0Ni+xTqpvpdqeuRaE2Sdm+dUrMv0HK2tUn6+aavJ24uqKInqupPPGCxAAAJhIYAYsxtJxJhdvkatO8Uwf8VGFUz5kVG7GINAKghk52Spvr5MF46t1ukDyzSgLF/pFm5b7Nw8Nzf7U9gcyNvxuby8/V8RY6nIxvjnQIzFz4qREIBAOAkgxuzGFTFml69R604xvP/RBmWedJ1RuxiDQKoIdCvopnHj+uvjo3rrpP491bsk1/jUQWyeg+BzEHw0nkySorpuGyyxCQEIBJMAYsxu3BBjdvkate4Uw7zlG5RxImLMKFiMpYxAZnamho2o00XjqnVafbkGVuQZnzuIzXMQfHau2BUWtocrKFccTSRXEK5amlgnNiAAAQgcjgBizG5uIMbs8jVq3SmGdZu26fyr7jJqF2MQsElgxktLtWRla2yKvWJsmnOr4gDE2F7uQRBjLS37bqW0mS9+tu3XW0j9zAzfIACB4BNAjNmNIWLMLl+j1ikGozgxliICD81epI/f/ERstrT0NPUbUKUp42p09tHlGtWvWDlZGUY9CYKwOXDBQfA56mLMzztdGi0gjEEAAhA4gAD9p92UQIzZ5WvUOsVgFCfGUkTg5QWr1PCthztmcwRZ775lmjy+VhcMrtTI2u7Kz8k05k0QhE0QxZjzyoCVK9s99/P70Iwl0gGGorhmWyyxCwEIBIsA/afdeCHG7PI1ap1iMIoTYykkcP3dL+uH972y34y9Kkt1yvhaXTisUuP7lap7nhlBhhhLYWCZCgIQgAAEQk+A/tNuiBFjdvkatU4xGMWJsRQT+MO/39cXf/OsdjuXWPYc9cf00bkNfXXuoAoNqylShoGt7hFjKQ4s00EAAhCAQKgJ0H/aDS9izC5fo9YpBqM4MeYBgWfeXK7Tr/lHx8x9+ldqSmP77Yoj+nZXTmZ60l4hxpJGiAEIQAACEIBABwH6T7vJgBizy9eodYrBKE6MeUSg8MLbtWNn+9WxvWLs/GPbnx1DjPn3pc8epQvTQgACEICAxwToP+0GADFml69R6xSDUZwY84hA0bQ7tH3Hrtjs+UV5Gj2yVueP7K1J/Xuptmeu0tLSkvKMK2NJ4eNkCEAAAhCAwH4E6D/tJgRizC5fo9YpBqM4MeYRgdFXPKQ3PljdMXtuXo6GDKvRtDF9dNqAcvUv76b0JAQZYsyjwDItBDwi4DyGunlz++TseulREJg21AToP+2GFzFml69R6xSDUZwY84jAirWbNfHKR7W0ZWOHB1nZWTrmuD66YFyNzjiqTEdXFiS8mQdizKPAMi0EPCDgCLHGRqmpqX1y3gfnQRCYMvQE6D/thhgxZpevUesUg1GcGPOQQOuW7Trzhsf0wnstHV4UlRRq0sR6XXJ8lcb3L1WP/KyEPESMJYSNkyAQSAKd633vAlpbpfz8QC4HpyHgSwL0n3bDghizy9eodYrBKE6MeUxg585dqr70z1q3aVvMk/zu+TqxcYAuGVGlxrpS9SrKTshDxFhC2DgJAoEkgBgLZNhwOmAE6D/tBgwxZpevUesUg1GcGPMBgct+8bTufnp+hxg7oXGALh5eqQl1paronpOQh4ixhLBxEgQCSQAxFsiw4XTACNB/2g0YYswuX6PWKQajODHmAwKf/dUz+vOT82KepKenq3dtL00e10/nDa7Q6H7FysvOcO0lYsw1Mk6AQGAJIMYCGzocDxAB+k+7wUKM2eVr1DrFYBQnxnxA4JG5izXth//az5OyqlKdPK5WFw6r1Pi6UnXvlunKU8SYK1wMhkCgCSDGAh0+nA8IAfpPu4FCjNnla9Q6xWAUJ8Z8QuD/Hn9XX/l9k3Y726LtOXqUFWvS+DpddHyVGup6qMTFZh6IMZ8EFjcgkAICiLEUQGaKyBOg/7SbAogxu3yNWqcYjOLEWIoIbNImFaggNlurWpWvg7c5e+L1D/WxG2Zo1652QZaRmaEhI+o0bVy1zhhQrqMq498aDTGWosAyDQR8QAAx5oMg4ELoCdB/2g0xYswuX6PWKQajODGWIgLxiDHHldtnvqsv//a5mFfpGekaPLyfpjnvHRtYpmOq2sVcPAdiLB5KjIFAOAggxvwbx84v4/avl4l7FqUXjNN/Jp4n8ZyJGIuHkk/GUAw+CQRuuCIQrxh79u0VOvU70xFjvCPJVX4xONoEEGP+jP+BL+P2p5fJeRWlF4zTfyaXK12djRjripCPPqcYfBQMXImbAGKsa1RBvJrX9aoYAQH7BBBj9hknMsOh4pKIHb+fE5UXjNN/2s1ExJhdvkatUwxGcWLMEgFHfHU+nP8uV3nsn5rVfNAzY3ufIePKWDu1qPxxt5R+mI0YAcSYPwPeOS7NzVJ+/I/9+nNBnbxy1lbe/ictMt/X9J920xIxZpevUesUg1GcGLNEIE1prizvVvumHYixaP1xd5UkDIbAYQggxvyZGmG+2h/mtR0um+g/7dYZYswuX6PWKQajODFmiQBizD3YKP5xd0+JMyBwMAHEmD+zIszfaWFeG2LMm3qKvBhra2vTTTfdpLvvvltLlixRjx49NHnyZN1www2qrq52FZXHHntMv/jFL/TCCy9o/fr1Kikp0ejRo/X1r39dJ598sitbhxqMGEsaIQZSQIDbFN1DjuIfd/eUOAMCiLGg5ECYv9PCvDbEmDcVFmkx5ggxRyQ1NTWpsrJSEyZM0KJFizR37lz16tVLzz//vPr37x9XZH72s5/piiuuUFpamhoaGtS7d28tXLgwJsyc47e//a2++MUvxmWLYkgKEyf7jEC8G3j84u9v6Nt3zo15z9b2Pgsi7kDApwS4MubPwIRZsIR5bfSf3tRTpMXYNddcoxtvvFHjxo3T448/roKC9ncZ7RVWEydO1NNPP91lZFauXNlxFe2JJ55QY2NjxzkPPPCALrzwQnXr1k3Nzc0dc3Rp9BADuDKWCDXO8ZpAPGLsnlkLdNktT+15ekzKzMrUkNh7xvpo8oAyXvrsdRCZHwI+JYAY82dgwixYwrw2xJg39RRZMbZ9+3aVlZVp3bp1evnll3X88cfvF4GhQ4fq9ddf14svvqgRI0YcMTqPPvqozj777Njtjf/85z8PGjts2DC99tprmjNnTuy2xUQPxFii5DjPSwJHEmO7d+/WD+57Vd+75+X9XOxVVapTG/rpoqFVGtuvREXdMuNeQhD/UAbR57gDwkAIWCTg7D5aWLj/BOxIahF4nKbD/J0W5rUhxuJMcMPDIivGnnzySU2aNCl2G+L8+fMPwupcMXOunF177bW67rrrjoh95syZOu2007oUY/PmzVN9fX3CIUSMJYyOEz0kcCQxdvfT83XZL/ZdfXZu862s6aXJ42t1wZBKjepbrILc+IWYs8wg/qEMos8ephRTQ6CDQEvLvm3G9/4jYsz7BAnzd1qY14YY86Z2IivGfv7zn8c21nBuIfzrX/96EP3p06drypQpOvfcc/Xggw8eMTrO1bXa2lpt2bJFB96m+Le//U0XXHBB7FbI5557LqkoI8aSwsfJPiRw+S+f1l+eav8xJCMjQ7UDKnTWuBqdO6hSw/sWKScrw7XXQfxDGUSfXQeGEyBggcCBYqyhQZo1S0pz94YNC55F22SYv9PCvDbEmDd1G1nt7XrDAAAgAElEQVQx9o1vfEO33HJLTJA5z4gdeDi3FTq3Fw4fPlwvvfRSl9G5//77dckll8i5/XHvBh4ffPBBbAMP5/bFO++8M3ZbZDIHYiwZepzrRwKf+flTuueZBTHX8rvn68TGAbp4eKUm1PVUeffshFwO4h/KIPqcUHA4CQKGCezeLa1c2W40L6/95cIIMcOQEzAX5u+0MK8NMZZAshs4JbJi7POf/7xuvfVWXX311fre9753EErn1sUBAwZo4MCBeu+99+JC/e9//1sXXXSRVq1a1TG+vLxc3/zmN2Oiz/nlP55jr+g6cOyCBQtit1W+9dZb8ZhhDAR8TaBt2w5VfupPatu2cz8xdsmIKjXWlapXEWLM1wHEOQhAAAKHIRBmwRLmtSHGvCnpyIqxz33uc7rtttv0ne98J7aj4oGH83yXI8TiFWM//elP9T//8z+x2xqdZ8zq6upiW9s7z5099NBDOv/88+VcPYvnQIzFQ4kxQSawakObTrp6uuZ/uK5jGd1LizSpsb8uGV6l8XWlKsnPSmiJQfxDGUSfEwoOJ0EAApEgEObvtDCvDTHmTXlGVoyZvE3R2f7+xBNPjN3S6NyWmJ6e3hHNnTt3atSoUXrllVc0Y8aM2EYfiR7cppgoOc7zE4EFy9dr4pWPas2Gtg63snOzNXRYX104ro9OH1Cm+vI8pSd4r1EQ/1AG0Wc/5RS+QAAC/iIQ5u+0MK8NMeZNHUVWjJncwOPyyy/X7bffHrvd0bnt8cDD+ffvfve7uvLKK/WDH/wg4UgjxhJGx4k+InDcf92v+R+t7/AorzBPI4b31cWjq3XygJ6qKe0We3l6okcQ/1AG0edE48N5EIBA+AmE+TstzGtDjHlTm5EVY/Fube/cZnj99dcfMTqnn3567KXRv/zlL/WVr3zloLHOv3/ta1/TF77wBf3ud79LONKIsYTRcaKPCBRNu0Pbd+yKeVRYUqjxo2t1wfBKndi/p3qX5CYlxBybQfxDGUSffZRSuOJDAs7GGps3+9AxAy45G4Uk8XuRAQ/8byLM32lhXhtizJvaiqwY27ZtW2x3w/Xr1x/xpc9z586N3WZ4pOPTn/60/vCHP+hTn/qU7rrrroOGfvKTn9Sf/vQn3XTTTfr2t7+dcKQRYwmj40QfESi44Hbt3LU75lGf/pWa0lir84+t1Mja7srJ3HeLb6IuB/EPZRB9TjQ+nBd+Ao4Qa2yUmprCuVa2z+86rmH+Tgvz2hBjXee2jRGRFWMOTGfzju9///saP3587MpWvrMnrhTb6v6KK65QY2OjZjkvLNlz/PrXv5bzv6lTp8aE1d7DeQ/ZeeedF9st0fn/Z599dsdnDz/8cOwz53j77bd11FFHJRxHxFjC6DjRJwT+9vwHuuTH/+7wZq8Yu2BwpUb0RYw5YHhhrU+SFTcSJtC5WU3YiM9PpE6PHKAwC5Ywrw0x5s0XT6TFWFtbW2zjjTlz5qiyslITJkzQ4sWLY/9dWlqq2bNnq76+viMyzi6Jzi2LzpUw571he4/du3fHtrS/7777Yv80cuRI9evXT857xl588cXYvzmi76qrrkoqyoixpPBxsscEfvy313TNn9rrwTmc58IGDK7R1PE1Oufocg3pU6SM9MSfFdtrN4h/KIPos8fpxPQ+JtA5n5ub29/9FYbDWVd5eftKEGOIsSjlAf2n3W+wSIsxB+2WLVtiV7n+8pe/aOnSpSopKYm9pNnZ7r5Pnz770T+cGHMGOYLsjjvuiN2m+Prrr6u1tVXFxcUaPXp07Dkyx2ayB8WQLEHO94KAUxtf/l2T7pj57n5CrKJPT50+rlYXDK3SmNpiFeRmGnEviMImiD4bCRZGQkkgrPkc1nXZSMIwswrz2g6XC/SfNqpkn83IizG7eM1apxjM8sRaagg8/26zJl31aMdk6RnpqulfobPH12rqseU6vqa7crPieyF6PB4H8Q9lEH2OJxaMiSaBsOZzWNdlI0vDzCrMa0OM2aiGrm0ixrpm5JsRiDHfhAJHXBB4aPYiffzmJ2JnOO/g6z+ot84Z31dTBpZrRG13ZWYkf2tiZ3eC+IcyiD67SAGGRoxAWPM5rOuykZ5hZhXmtSHGbFRD1zYRY10z8s0IxJhvQoEjLgjcO2uBLr3lqdgZmdmZGjaiTheNrdZpA8o1sCLPhaX4hgbxD6VfffbT9uRsJx5f/vthlF/zOVk2YV1XslwOdb7zTF1hYfsnYXpu0FlPFJ8dpP+0USX7bCLG7PI1ap1iMIoTYykgsLZ1qwZ/+T6t2bh1fzE2rlqn15drAGIsxsWPTZ7ftidnO/EUFKyhKfyYzyaWFtZ1mWBzoI2Wln2bndiw7xebUdnIhf7TbsYhxuzyNWqdYjCKE2OWCSxcvl4Tr5qu1eu3dMyUX5Sn8WP76+Ojesde8lxZnGPciyA2TH70ubNPxoOUoMGoND4J4vHNaX7MZxNw3K7LT1eW412/qSvQURBjUfqBiP4z3gpKbBxiLDFunpzlFEPL+i066pKfezI/k0IgXgLbd+zS6x+s3m94t4JuGj68ry4a3UenDOyp2tJuse3tTR9uGybT8ydiz48+d/bJy9uMonhLUCI55Kdz/JjPJvi4WZffrizHu35TAsNZ/8qV7bOaEnjxriFV48K6rkPxQ4zZzSrEmF2+Rq07xTBv+QZlnHidUbsYg4BtAkU9CjVuVK0+PrK3TuhfqvLuOVaEmLMONw2T7XXHa9+PPvvFJ7/4EW8sGRfMGownbm5y0Y9XluNZozOGK9DxkorOOMSY3VgjxuzyNWrdKYb3P9qgzJMQY0bBYswqgZ4VJTpxbD9ddHyVGupKVJKfbXU+Nw2TVUdcGPejz37xyS9+uAhn5IeGNWZu1uWXK8vxJiNXoOMlFc1xiDG7cUeM2eVr1LpTDAtaWtXjvJ8ZtYsxCNgg4NyB2KO0QBOP760LjqvQ6L7Fyjf0Yucj+eumYbKx7kRs+tFnv/jkFz8SiWtUzwlrzNysy81YP+RJ0Pz1A7Mo+YAYsxttxJhdvkatO8WwsnWbLvzJg0btYgwCNgikpUt9S7ppYm0PDetTpByDL3ZGjNmI2P42/dKc+cUP+8TDM0NYY+ZmXW7G+iHyQfPXD8yi5ANizG60EWN2+Rq17hTD1h279Od/Pm/ULsYgYIOAszVHaUG2+pZ2M/5i5yP5G8T32/jxFiG/NGfx+hHEneuOlMdB3hwg3pjZ+N6xadPNutyMtelzvLaD5m+862KcGQKIMTMcD2cFMWaXr1Hre4vhzTffNGoXYxCwRcDGbold+Rr0LZX98vC8X5qzePwI6s51R8plU7vadVUvNj6PJ2Y25rVt08263Iy17Xc89oPmbzxrYow5AogxcywPZQkxZpevUesUg1GcGAspgSCLMT814H5pzuLxo/OYMKW1X4S5W6bxxMytTT+Md7MuN2ODtjY/+IsPqSVA/2mXN2LMLl+j1ikGozgxFlICQX6/jZ9uTfNLMxmPH53HePlONBMl5cdbVt2uK56YubXph/Fu1uVmbNDW5gd/8SG1BOg/7fJGjNnla9S6UwzbduzS3TNmG7ObkS6VFeaqqjjb2nufjDmLIQhAIGUE/NJMxuNHPGNSBi7JicKwljCs4VBhdLMuN2OTTBkjpwfNXyOLxkjcBBBjcaNKaCBiLCFs3pzkFMOqTdt00c8eMuZAZkaaBvbM08TaUh1VWaCMdGfbBQ4IQCDqBPzSnMXjRzxjghLPMKwlDGtAjAWlYvAzFQQQY3YpI8bs8jVq3SmGhS2tKr3wFmN209PTVFFRrDNGVOnsQeUaUl2o7MwMY/YxBAEIBJOAXxrqePyIZ0xQohCGtYRhDYixoFQMfqaCAGLMLmXEmF2+Rq07xfD+RxuUedJ1Ru2mp6erd79ynTW+r84fXKkRfburWzaCzChkjEEgYAT80lDH40c8Y4KCPwxrCcMaEGNBqRj8TAUBxJhdyogxu3yNWneKYd7yDco40awYizmZJpVVlerUcf00bVilxvbroaJumUb9xxgEIBAcAn5pqOPxI54xQSEfhrWEYQ2IsaBUDH6mggBizC5lxJhdvkatO8WwYt0W1V74UyN2N27ZpqUrW/ezVdyzuyaO7adpx1dqQl2pehWxsYcR2BiBQMAI+KWhjsePeMYEBX8Y1hKGNSDGglIx+JkKAogxu5QRY3b5GrVuoxgef2WZLrhpprbv2NXha0H3fI0eWatpo6p0Un0v9SnJZadFo5HEGAT8T8AvDXU8fsQzxv/E2z0Mw1rCsAbEWFAqBj9TQcBG/5kKv4MyB2IsKJGSZKsY3ly8RpOunq6Nm7d10MjJy9GQoTW6cEwfTR5Ypv5leXI2++CAAASiQcAvDXU8fsQzJihRC8NawrAGxFhQKgY/U0HAVv+ZCt+DMAdiLAhR2uOjzWJYsXazTrjyUS1p2dhBJCs7SwOP6a3zxtdoylEVOqaqQM5W+BwQgED4CfiloY7Hj3jGBCViYVhLGNaAGAtKxeBnKgjY7D9T4b/f50CM+T1CnfyzXQyb2rbrrBtmaM67zR2zZmRkqG99hc4e31dTj6nQ0Joi5Wax02KA0gZXIZAQAb801PH4Ec+YhCB4cFIY1hKGNSDGPEh+pvQtAdv9p28XniLHEGMpAm1imlQUw86du3T5r2fp3qfnd7iclpamyj69NNnZ+n5IlUbXFqsgl50WTcQUGxDwKwG/NNTx+BHPGL9yPtCvMKwlDGtAjAWlYvAzFQRS0X+mYh1+nQMx5tfIHMKvVBbDTfe9qhvufmk/L0orSnTimH66aHiVRtWUqCCXK2QBSp8OV3Mz07ndNIiBS7HPfmmo4/EjnjEpxpfwdGFYSxjWgBhLOIU5MYQEUtl/hhBfl0tCjHWJyD8DUl0M9z27UJf+/Cnt2rW7A0JRSaHGjq7VuUPL1TMvxz9w8CRuAiV52RpUUaDSguy4z2Fg9Aj4paGOx494xgQlgmFYSxjWgBgLSsXgZyoIpLr/TMWa/DQHYsxP0ejCFy+KYc57zZp83WNq27qjw7tuBd00+LhqFSDGApQ97a6mpUnlJbk6pb5UJ9T3VFVxDq8tCFwUU+OwXxrqePyIZ0xqqCU/SxjWEoY1IMaSz2UshIeAF/1neOh1vRLEWNeMfDPCq2JY1LxBE698VCvXbelgkZmVqfSMdN+wwZH4CeTm5WjwsVWaNrqPTurfU+VFOVJau1DLy85QJq8wiB9miEf6paGOx494xgQlVGFYSxjWgBgLSsXgZyoIeNV/pmJtfpgDMeaHKMTpg5fFsG7TVp38nX/o7cVr4vSWYX4mkJWTpUGD+2jqmD7q67zUW2nKSE9TdVE3Hde7kA1a/By8FPnml4Y6Hj/iGZMibElPE4a1hGENiLGkUxkDISLgZf8ZIoyHXQpiLEBR9roYtm3fqWk3P6EZLy0NEDVcPRyBjMwM9RtQqbJeBbEh6enp6l+Rr7MGlauhrkQ98nmmLMrZ45eGOh4/4hkTlFiGYS1hWANiLCgVg5+pIOB1/5mKNXo5B2LMS/ou5/ZDMezevVtz3m/RW4vXuvSe4V4T2Llrt+769/t6ef6qDlec1xY4osw5nP+fX5Sn0SNqdPHI3hrTx9kxs/0VBlkZaSrqlhm7esYRDQJ+aajj8SOeMUGJWhjWEoY1IMaCUjH4mQoCfug/U7FOr+ZAjHlFPoF5KYYEoHHKfgQcMX3VH1/Qzx9647BknA1ahh9fo7OGV6k4p12MdcvKUH1pfuwWxhxe+h2JrPJLQx2PH/GMCUrQwrCWMKwBMRaUisHPVBCg/7RLGTFml69R6xSDUZyRNnb7zPf01d8/J+dq2aGO7Jxs1R9dpby89lsVs7MyNLimSFOPrdCovsXK56Xfoc8fvzTU8fgRz5igBCwMawnDGrwUY7t3S5s3pzZjnZiVl7fP2dws5eendn5ntry89o2kOPxHgP7TbkwQY3b5GrVOMRjFGXljqza0afa7zXLkWOuW7brh3le0aMWGDi7ObYvO/5zD2TmzpGd3nTS2ry4cVqVjK4qUtWc3zfycdHXPy1Q6f0VDlVN+aajj8SOeMUEJThjWEoY1eCXGHCHW2Cg1NQUlY8352dAgzZqFIDNH1Jwl+k9zLA9lCTFml69R6xSDUZwYO4CAs0HLBT96QjNfPvwGLUU9CtUwulYnHN1T2XvEWI/cLA2uKNLRlQU8UxZHVgWlUfWLn/H4Ec+YOELjiyFhWEsY1uCVGOvMzhcJmWInWlu9uSqX4mUGbjr6T7shQ4zZ5WvUOsVgFCfGDkHAeabsW3fM0f+b/pacX2gPdeQVdFO/gRXKSGt/z1xBfrbGDSjROcdUakg1z5R1lVhBaVT94mc8fsQzpqu4+OXzMKwlDGvwgxhL5e2CXt6m2HluxJhfvon294P+025cEGN2+Rq1TjEYxYmxIxBoWbdFHzRvjI1YsnKjvnbr81q7ceshz8jMzlRVTS9NaajV+ceWa3hNsXKz23do5DiYQFAaVb/4GY8f8YwJSi6GYS1hWIMfxFgqhYmXMfNy7qB8L3jtJ/2n3QggxuzyNWqdYjCKE2MuCKze2KaTrp6uecvWHfKs3LxcjR7TXx8f3VuT6nuppjTXhfVoDQ1K4+EXP+PxI54xQcmyMKwlDGtAjKWuYsKaL6kjaH8m+k+7jBFjdvkatU4xGMWJMZcE2rbt0Cd/9pSmz10c2/Sj85Gdm62Ro/rr4rG9dUp9L/XrlefSeniHO41G56Or24G82MUs2cbTZvTiadTiGWPTR5O2w7CWMKwh2ZpIlEGi5yWbg17N6/jt5dzJcovK+fSfdiONGLPL16h1isEoTowlSGDNxq3asHmb/m/mu/rJ316PWUGMHR6m200mD/esXoLhSvg0vzRI8fgRz5iEQaT4xDCsJQxrQIylLvHDmi+pI2h/JvpPu4wRY3b5GrVOMRjFibEkCfzf4+/qv373HGKsC46IseQSLZ5GLZ4xyXmRurPDsJYwrAExRs6njoD/Z6L/tBsjxJhdvkatUwxGcWIsSQKIsfgABvU2RWfzgMLC9jWmcle3A6l2vq3zcBsahKn5D8NawrAGxFh8328mRoU1X0yw8YsN+k+7kUCM2eVr1DrFYBQnxpIkgBhLDGBQGo+WFqm8PLE12joLMWaLrFm7Qclxt6t2sy43Yzv7keh5btdyqB89Cgra/zWVuzg683m15mSZRel8+k+70UaM2eVr1DrFYBQnxpIkgBhLDGBQGg+/ibGGBmnWLOlQt30GhWk8GROGtYRhDYeKlZt1uRmLGJO8EoLx1CRjJPpPu1mAGLPL16h1isEoTowlSQAxlhjARJu0xGZL/CxnI5GVK9vPz8s7tAhK3Lr7M4/kQ1CYxrPqMKwlDGtAjMWTrWbGhDVfzNDxhxX6T7txQIzZ5WvUOsVgFCfGkiSAGEsMII1HYtyOdFaYmIZhLWFYA2LMfJ0ezmJY8yV1BO3PRP9plzFizC5fo9YpBqM4MZYkAcRYkgA53RiBMDVzYVhLGNaAGDNWnl0aCmu+dLnwAA2g/7QbLMSYXb5GrVMMRnFiLEkCiLEkAXK6MQJhaubCsJYwrAExZqw8uzQU1nzpcuEBGkD/aTdYiDG7fI1apxiM4sRYkgTCKMac56Q2b04STAhO98MzYm4whqmZC8NawrAGxJibCkxubFjzJTkq/jqb/tNuPBBjdvkatU4xGMWJsSQJhE2MOUKssVFqakoSTAhOP9LOhX5cXpiauTCsJQxrQIylrtLDmi+pI2h/JvpPu4wRY3b5GrVOMRjFibEkCYRNjHVuCJJEE4rTU/2uoWSghamZC8NawrAGxFgyFenu3LDmizsK/h5N/2k3Pogxu3yNWqcYjOLEWJIEOouxzKxMDT6+r6aO6aPT68t0XHWB0g/1Qqgk57R5eueGoLlZys+3OZs/bTsM9r7oGTHmTYzC0Jg6uVNY2M4vTLXkpj4SjWOi5yWbrV7N6/jt5dzJcovK+fSfdiONGLPL16h1isEoTowlSeC+ZxfqUz97ssNKdk62jjmuWuePrdEZR5Xp6MoCZaSnJTlL6k6nIQhuUxSm2IVhLX57YbiNb5GufqxIVJB2FnypFLJuhKZpnmHIedNM/GaP/tNuRBBjdvkatU4xGMWJsSQJbN2+Uydc+YheW7i6w1JGZob6H1Wlc8bV6GPHVGhIdaGyMzOSnCk1p9MQIMZSk2lHniUMeRh2MRbPM5VBZtCV0DRdJ2HIedNM/GaP/tNuRBBjdvkatU4xGMWJMQMEtm3fqWk3P6EZLy3tsJaenq7e/cp05rhanTe4QiNri5WX7X9BRkOAGDNQEkmbCEMeOpvhrFzZjiJoO3PGE8B41hRUMRaP0IyHkZsxYch5N+sN4lj6T7tRQ4zZ5WvUOsVgFCfGDBHYvXu3/veuufrV39/cZzFNKqsq1cnj+mnasEqN69dD3btlGprRjhkaAsSYncxyZ5U8dMfLr6MTFaRe3aa4l2M8QtM0c3LeNFHz9ug/zTPtbBExZpevUesUg1GcGDNM4LbH39VXf/+cnCZk71Hcs0iNY2p18fDeaqwrVVlRttJ8urEHDQFizHBJJGSOPEwIW2hOimL8o7jmoCUs/afdiCHG7PI1ap1iMIoTYxYI/OvVZTrvBzO1fceuDuv5RXkaNaKfLh5dpZPqe6lPj1xfCjIaAsSYhZJwbZI8dI0sVCdEMf5RXHPQkpb+027EEGN2+Rq1TjEYxYkxSwTeXrJWJ109XRs2be2YIadbjoYMq9GFY6p1+sAy1ZflK91nOy3SECDGLJWEK7PkoStcSQ12ruJv3pyUCeMnp/I2RS9uSTwUMHLeeBoZN0j/aRzpfgYRY3b5GrVOMRjFiTGLBJrXbdEJVz6qxc0bOmbJzM7UUcdU67zxNZpyVIWOqSpQZoZ/tr6nIUCMWSyJuE1HKQ+37tilrdv3XUWPG9IBA3My05WTle7qdEeINTZKTU2uTgvVYC8260CMBTOF6D/txg0xZpevUesUg1GcGLNMYPPWHZpywww9/86Kjply83I1ekx/fXx0b02q76Wa0lzLXsRvPkpN8OGoBJVBUP2OamPqbPqzYv1Wvb18o1Zv2R5/kR5mZGm3LB1dXqiqkpy4b4HunDNJOxBgA6nexj6qOR/gFIm5Tv9pN4KIMbt8jVqnGIzixFgKCOzcuUsN//v3jneROVfHho2o00XjqnVafbkGVuSlwIv4pghTQx/fig8eFVQGQfU7io2pI8QWrd6if72/Uv9+f7VWrW9LNF07zivtnqsT6nvo1AFlqivrpvQ4NgnqnDOpfLlyV4tNxW2KnedAjHUVET5HjNnPAcSYfcbGZkCMGUOJoRQSeGj2In385idiM+4VY9PGVuv0AYixFIYhrqmCKmqC6ncUxNi2Hbu0sW2nHBHmbLTavH6rHp+3UvfNXqJ57y3X1rZtceXmkQZl52Sr/4ByXTC2RmcMKtcxlQXK6OKZVL/mjCOOCgvbV2tLJKZC8LkJqt/EoRvfozKW/tNupBFjdvkatU4xGMWJsRQR6CzGnG3tq/r20uTx/TT12AqNrStWfo4/3j/m1+YsRWGKTRNUBkH1O+xibO2m7Xpt2Xot3dCmXY4Y2y0tWL1Jj8xeqgXvfaQd23cYS++MzAz1G1Cpc8bX6GODKjW0T6Fysg7/snm/5kxQXxZtKpB+uFJnai1hskP/aTeaiDG7fI1apxiM4sRYigi8u2ydhn/1gdiv4nuPXpWlmjSuds8LoUtVku+9IPNrc5aiMAVajKXiakKq4hCGqwTOVTDnCtgzC1br0bdbtKRlk3btav8GaG7ZoGUftGjXruQ37jgwJmnpaerdt0yTx9fq/MEVGlV7+B97/FrvURZjftlQJFW1HqR56D/tRgsxZpevUesUg1GcGEshgT/8+3198TfPxm5V2nt0Ly3SxHF1unh4lSb0L1WvwuwUenTwVH5tzlIJJagMwtrApvoqgVOfm7bu1Ia2nUml3fot2/X8ojW6Z+4yvfraUm1u3dJR+7t27i/CzhxVo0tOqFccj3kd5JPzdfJA0wf6W9MH+30Wz489fs11Z00rV7Yvx9bW8367TXFv8GytN6lk5uQYAfpPu4mAGLPL16h1isEoToylmMDTby7Xx26coW3b9zV6dUdX65zGWk0dVKHja4o83erer81ZKsN0OAZ+fB9TZy6OGKurSyUp+3Ol+iqBI8SWrm2L3Vb40UbnHYGdr2W7W++aLdv16Isf6a3Xlxz2mTBHfP30s+P0pTOOcWf8EKMP+WNPjyKNH9NXFw/vrYn1PVVelL3fTotRrvcorz3pZIuoAfpPu4FHjNnla9Q6xWAUJ8Y8IDDvw3Ua8pUHOmbu079SUxprdcHgSo3o213O+4K8OmhQDv3MWJDfxzRunPT440roqotXeejFVQLnFsIFLZv12PstevztFq1cm9wOh5tat2rR/OWHfSasW3am7v7WJJ0+oo8xzM/s+bFna6cfe/IK8zRyeK0uGt1bJw/oqZrSbh2CLMr1HuW1G0u4iBmi/7QbcMSYXb5GrVMMRnFizCMCRdPu0PYd7bcq7RVj5x3T/nyH2xe3mlwCDcqhxVjQ38eU6lv9TOZkKmzt2Llbby9v1fR3V+iBpiWa7+xwuMW5MmbuGDGgl67/+AjlZGfEtp0f3r9UudnmnxN1fuw54arpWrtxn5jM6ZajocfXatqY3jptYLnqy9oFWZTrPcprN5fV0bJE/2k33ogxu3yNWqcYjOLEmEcEul90Z8etirl5ORoyrK8uGN3eKA0oz4vrHUE2XKdB6VqM2dpq23Q8w7AJhmkmh7LnXEV6dckGPfj2Cj3StFiL56/Qzp3JPS924DyXn360fvm58UrvYqt5U+tdtaFNJ139qOZ/uL7DZM/KUp0+oU4XD63S2LoSFeRkIMYK2vHwY4WpzAu3HfpPu/FFjNnla9Q6xWAUJ8Y8InDaNf/QrDeXd8yelZFDvwYAACAASURBVJ2lo46t1nnj+mjK0RUaVFngybNjiLGuxVhQGjdi2XVxt7bt0AuL1+n+1z7SY02LtXzpyv022OnawpFHZGdl6Mb/GKmvnj04WVOuz2/btkMlF9/VcV5Jr2KdOrFenxhWqXH9e6goNxMxhhhznVdRPoH+0270EWN2+Rq1TjEYxYkxjwi0btmuM65/TC++39LhgfOOoPqje2tqQ199bFCFjutdmHJBRgOPGPOoJFI+7cYtOzT7g7W657XlmvncQq38aPV+Pnx5yrH6wuRBSfnVuzRfeR6+Q3DsNx/Sawvb17VXjF04pEIN/UtVkocYK0CMJZXfUTuZ/tNuxBFjdvkatU4xGMWJMQ8J7Ni5S5/55dO6f9bCDi8Kigs0acIAXTKiSo11PdSjILVb3SPGEGMelkRKp563YrMen9+se55fptde+kDbt23vmP+ub5yoaY39U+qPjcka/ufvenl++x7xGRkZqh1QobPG1WjqMZWxnVt3bMtQVAUJ33U2Mi7cNuk/7cYXMWaXr1HrFINRnBjzmICzlfagL92nxS0bY57kd8/XiY17xVipehUhxlIdokM1aUFs3ILocypj/d7yTXpsXovufX6pXn95oXbu2YHwmouH68ppx6fEld3arc3abG2uXz36pq7780vt9rdmKz0tXZV9e2nyuFpdMKRSx/QsVkXP9k1EgnL7rSlY1IcpktGxQ/9pN9aIMbt8jVqnGIzixJgPCFz2i6d199Pz28VYUb4mTqjXtOMrNbGup6qKc1LqIQ0KV8ZSmnAeTnY4Mfa7L0/Qp08eaN0zR4g1qlFNarI+lzNB2jv1yr76f5WmNJX17qnTG/rpYwMqdfbIXoixVik/PyVhYJIAE6D/tBs8xJhdvkatUwxGcWLMBwS++JtZuuuJ99s9SZPKKkt18vh+unBohcbXlap7N/PbXx9u2YgxxJgPSiIlLry/YpNm7Lky5tymuGP7jti8WZnpeu7mc3RcbQ+rfmzSJhVoz0NLVmfaZzzn479R2tYcOVvdjxxdp/OGVOvLk2oQY4ixFGVgsKeh/7QbP8SYXb5GrVMMRnFizAcEnntnhU77zj+0y3mz8J6juGeRGkbX6qIRvTWxrlRlRdkdL2q16TJiDDFmM7/8ZHvVxu16duEq3f3ycj3dtEDrV2/ocC8zI133ffsUTTb4QuYD195ZjDWrWfmyc2nGmadc5bHp94qx7NxsjRhVp6lD++irJx9ajDm3UDvvIgvrwXddWCNrb130n/bYOpYRY3b5GrVOMRjFiTGfEHji9Q819fsztX3PcyuOW0U9CtU4tk6fGFGlif2d58fs37JIg4IY80lJWHfDERurNm7TswvX6N5XluuZ2Qu1duW+93I5OuSR756uk4dVW/GlsxhrVatVMbb3ChxibF8o+a6zktahNkr/aTe8iDG7fI1apxiM4sSYjwi8u3Stxn7rYW3d1v7CWWer++OG12nauGqdMbBMR1fav6WJBuXQYszZ3KCwsD1ZeOmzj4rGgCsbYlvcr9F9r67QzNkfqOXD1R3vGjtvfD/9+ZuTDMxysAm/ijFHpMZ+pQ7xVTFnfXzXWUnrUBul/7QbXsSYXb5GrVMMRnFizGcEHnz+A33ix/+OeZWeka7Bw/tp2riamBg7pgoxlopwHapJa2mRytvv9ArkEbWd8twGqXnDVs1auFp/fWW5nnxmvlrXt8ZMTBndN3a7oo3Dj2IsLy8aQgwxZiOjw2+T/tNujBFjdvkatU4xGMWJMZ8RePbtFTr1O9NjXqWlp+noIX11viPGBpRpWN8ipVv+tZpfiw/9i3mQxVhDgzRrlnOlw2fJ7iN31m7arucWrtEfX/pI/37mfbWuaxdjFSV5WnjbxVauEvlRjEVpR0G+63xUgAFxhf7TbqAQY3b5GrVOMRjFiTGfEXh5wSo1fOvhDq+ycrJ09LHVOn9sjc4cVK5BlQXKTLfXVdOgHFqMOXdurWx/d67y8oIlbILmrxcluW7zDj23cLX+/PJHeuKZedqwpv29f85xztha/fEbJ8V2WTR5IMZM0nRvi+8698yifgb9p90MQIzZ5WvUOsVgFCfGfEZg585dOu2af6rpnRUdnjnPjtXWV+qchhqdM6hCQ/sUKScrw4rnNCg8S2IlsXxudMeu3Xpz2UY9+m6z/ta0WO+/vUw7d7Q/u+kcQ/v31OPXn6GiPHMvYfeDGDt3SLW+dkrf2Bqjdisr33U+L0ofukf/aTcoiDG7fI1apxiM4sSYDwns2LlLn/zZU3ro+Q86vEtPT9fAY/vo/Ma+mnJUuY6rLlSGhStkNCiIMR+WREpc2rlrt95Z3qp/vNei+5sW6923lmn71u0dc1eW5uuZm85WdU8zW9AjxlIS1sNOwnedt/yDODv9p92oIcbs8jVqnWIwihNjPiXg7Gh27V9e0o8feG1fM1hTpjMa+2nacZUa3a9Y3bLNXx2jQUGM+bQkUuKW866/hS1bNHN+i+6dvUyvvbpYbZvaOubOz83SzBvP1PH9eybtj7OdfaHat+j043vGkl6gzw3wXefzAPnQPfpPu0FBjNnla9Q6xWAUJ8Z8TqD7tDu0bceumJcVfXrpjAl1uggxZjVqNGlW8freuPNDyEdrt+qpBat094vLNOeFxR0bejjOZ2Sk6y/fPEkfG1Ob1Fpa1NLxMuakDLk42c17xlyYDeRQ6jyQYfPUafpPu/gRY3b5GrVOMRjFiTGfE6i+9M9avaH9l/mSXsU6aXydzhtSoQn9S1VWZO75lb0YaFC4MubzkkiZe6tat8V2WLz35Y/09OwPtKZl3X5z/+DTo/X1c45L2J9Ui7Hixcdoy9e/rjSlKTs3WyNG1Wnq0D766sk1sTXwzFjCoeTEiBCg/7QbaMSYXb5GrVMMRnFizOcEBn/5Pi1YvqHDy+Ke3TVxbD9NO75SE+pK1aso2+i224gxxJjPSyKl7jkvhH5h0Vrd+/pyzWxapOZlqzpeCO04cumpR+k3X2hQegLPb+7Wbq1U+xadecqLiSQbh7Mp0Jd+95weeGJZxxy5ebkaM7a/zjuuWl84sRox1ipFaVt/G3kWBZv0n3ajjBizy9eodYrBKE6M+ZyA896xM6/7p7bvuVXRcbege75Gj6zVtFFVmlTfS9UlucYEGWIMMebzkki5e23bdurlpev14Fsr9Ohzi7RkYbN27Wy/ddg5Jgyu0sNXn6puOZkp962rCTe1bddZN8zQnHebO4ZmZGSodmClzhnfV6f3q9AJxxYjxhBjXaUSn0ui/7SbBogxu3yNWqcYjOLEWAAIvLl4jSZdPV0bN2/r8LZ7aXdNmtBflwyv1Pi6UpXkZRlZCWIMMWYkkUJmxHlu860PN+iRd1r04Owlmv/Oh9qxfUfHKusqu+vpm6aoZ1Gub1bevG6LTrjyES1u3vfOtMzsTB01qFrnja/RlKPL1bd7oYq7t1+R4zZF34QOR3xKgP7TbmAQY3b5GrVOMRjFibGAEFi+ZrMGfP4eOdtvO0e3gm4aP75el4zqrRP6l6qq2EwTiBhDjAWkJFLuplN781o2acZ7Lbrv+aV6842l2rpla4cfJYW5evoHZ2lA7/YrTV4ebzk/4HznH9qwaZ9/OXk5GjK0RheO6aPTB/ZSfVm+tmxJU0FBu6eIMS8jxtxBIED/aTdKiDG7fI1apxiM4sRYgAh86/bZ+vWjbyHGLMfsQEGalydt3mx50gCYdzik7XmsaffuYDHp7HsyqJ2dFpesbtMT81bq3hc+1IsvLdLmjfuSIzsrQ49ec7omHFuZzDRJnTvzlWU6/6aZ+93anF/UfmvzRaOrdFJ9L/XZc2tzlH98ifLak0qwCJ9M/2k3+Igxu3yNWqcYjOLEWIAIfPePL+gnD76OGLMcs85N2saN0umnS01NlicNgPmGBmnWrHZHGxuDxWSv73vFZDK4HUHWvGGbZi1YpXte+lBNcxdr3ep9m+w47yJb8cf/UGZGejLTJHTu7x97R1+/tUmOWN57HGnTnygLkiivPaHk4iSeGbOcA4gxy4BNmkeMmaQZTVvOLmabldpLHSZ2S0OMpSZfOzdpzc1SeXlq5g3CLM6tbM6x99a2IPi810fTt+Gtad2uWQtX64HXVujJ5z/QqhVrOnAsueMT6tW9W8rwOALxm7fP0f+b3n7lPHakSWVVpTp5XD9dNKxSY/v1UPdu+28yEmVBEuW1pywxQzYR/afdgCLG7PI1ap1iMIozcsYcIdaoRjUptZc6GtSgWZqV1PbVhxJjnxhVpRPqeqp3Cc+MmUrmw4kxR5hFcftrh8deQXqgGPM7kwN9Nxk/5xmy15Zs1MPvLteDTUs0780lnoixbdt3atrNT2jGS0s75k9PT1fvfuU6a3xfnT+4QsP7FisvO+OgEomyIIny2k19V0bNDv2n3YgjxuzyNWqdYjCKM3LGNmmTCrTnifUUr75VrcpXfsKzdhZjGZkZqh/UW2eP6aOzjy7XsJoiZWce3Gy5nYwGZf8NPDpfGTN9ZcVtbLwaf2BOOH4EZdMHm/nsiLHXl2zUQx6KsbWtW3Xyd6brnSVrO9IjIytD/QdW6dzxfXX2oHINqS487HeDTT5e5Wu880Z57fEyYtz+BOg/7WYEYswuX6PWKQajOCNnrLMYa1ZzUuIoHnjOfOVqv88tWTF276wFuvSWp/b9+p2Rrj6xX79rdd7gCo2o6a7cQ/z6HY+fe8fQoCDGDswXxNihK8hrMbaoeYMmXvmoVq7b0uFgdk62jhnSRxeMrdEZA3vpqMoCZRzhhdRRrvcor93N3wTG7iNA/2k3GxBjdvkatU4xGMUZOWOOICpUYWzdQRNjznMhX/3/mnTbjHc74paWlqay3qU6dXw/XTjEeS6kREUHPBfiJsg0KIgxxFh8FePlbYpz3mvW5OseU9vWfe86c153Mfz4Gk0b00en1PdSba9uSu9ix5Io13uU1x5fhjPqQAL0n3ZzAjFml69R6xSDUZyRM9ailo4rValefLJXxvb6+8tH3tT/3jFnP/d7lBVr4ph+uuj4SjXWl6pnQXZCy6NBQYwhxrouHeeHkeXrtuqp+at03ysfqWnuIm1Ys+/lyjY38PjrrIX6zC+e0q497xx0vC0qKdTY0bW6eGRvnVBXqsriHDk/1HR1RLneo7z2rvKCzw9NgP7TbmYgxuzyNWqdYjCKM3LGvBJjJjbw6BysR19Yoo/f/IR27NzV8c8F3fM1ZlStLhrZW5Pqe6pqz7uE3ASZBgUxhhg7csU4Qmzx6i16Yt4q3Tt3mV5y3jXWuu9WwbLibvrgto8r/Qi3B7qpyc5jf3DfK7rx7pf3O720okQnje2nacdXqaGuRD3y4/8hJsr1HuW1J5p/UT+P/tNuBkRejLW1temmm27S3XffrSVLlqhHjx6aPHmybrjhBlVXV7umP3/+fP3oRz/SzJkztWLFChUWFmrAgAGaOnWqvvWtb7m21/kEiiEpfJE/2dlNcaVWxjiY2G4+XqA25npt4Wqd/N3p2rRle4cbuXm5GjrMuVWpWqcNLFddWde3KnVeAw0KYgwxdviqdm5NnNfcqn++t1L3zV6qt15fom1t2zpOKC3K1dM3TVH/yu7xfjXENW7nzl26/NezdO/T8zvGO1e+Kvv00mRnx8QhVRpdW6yC3P23ru/KeJTrPcpr7yov+PzQBOg/7WZGpMWYI8ROPvlkNTU1qbKyUhMmTNCiRYs0d+5c9erVS88//7z69+8fdwQefPBBfeITn9DWrVt1/PHHa+DAgVq9erXeeOMN5efnyxFqyRwUQzL0ODdsBD5cvUknXPmoPly15wVQkrKys3T04GqdN7aPzhpUoUGVBcqM81d6GhTEGGLs0N8S23bs1JsfbtTf32nWQ01LtOC9j7Rj+75ntgZUF+vJ75+l0kIzr5nY68Wmtu0684YZmvtuc4djGRkZ6ltfobPH99XUYys0tE+RcrPc76Ya5XqP8trD9ncwVeuh/7RLOtJi7JprrtGNN96ocePG6fHHH1fBnj2Lf/azn+mKK67QxIkT9fTTT8cVgddee02jR4+OXQl76KGH1NjY2HHerl279PLLL2vkyJFx2TrcIIohKXycHEICG7ds0+RrH9PL89uv+DmHs/V9bX2lzmmo0TmD2pu1nDiaNRoUxBhi7OAviS3bduqlJev1tzeX6x9Ni7X0g2bt6nSL8IlDeuvBq05Rbra7K1NdfR2tWLs5tmPi0pZ9z6M5P7YMPKa3zhtfoylHVeiYqgJlZnT9fNih5opyvUd57V3lHZ8fmgD9p93MiKwY2759u8rKyrRu3bqYUHKuZHU+hg4dqtdff10vvviiRowY0WUUHOE2a9YsPfLII5oyZUqX4xMZQDEkQo1zwk7AeXbsU7c8pQebPuhYalp6mqpqyjR5fK0uOK5Co2qLlZ9z5GaRBgUxhhjbn8CGLTs0+4O1uu/15ZrZ9IFaPlwt57mxvcfnJg/Szz87zvgzYstWbdKobzyoda1bO+bKycvRkKE1unBsH00eUKb+ZXlJzRvleo/y2sP+99DW+ug/bZFttxtZMfbkk09q0qRJsdsQD3X7oHPFzLlydu211+q66647YhTeeecdHXPMMbHbEt977z1rEaMYrKHFcMAJOA3iDfe8rB/e9+p+K+lZ2UOTxtZq2rAqja/roZL8rMOulAYFMYYYayfg1NPq1u2atWC17n1luWbN+UBrWtbth+fHl43Vf0051so3x3V/eUk/un9fLTsb9IweWasLR1VpUn0v9Ulgg56uYpuf+DvprTCwaZTvOpt0w2mb/tNuXCMrxn7+85/r61//ui688EL99a9/PYjy9OnTY1e4zj33XDnPgh3p+PWvf62vfOUr+vKXv6yf/OQnuvfee2NX1JyHjIcMGaJp06apqKgo6UhSDEkjxEDICfz5qfn6/K+e0a5Ov94X9ShUw+haXTSit07oX6ry7ofe+poGBTHWVcPufL7nbna1tkp+buATzWdHiH24tk1Pzl+le174UHNfXKTW9Zs60GRmpOve/z1FZ47sY+3b5Bu3Pa/f/uPtmH1nY54xY/vr/OEVOqm/c0WsW1xb13flXKJ8urIbhM+jvPYgxMePPtJ/2o1KZMXYN77xDd1yyy0xQeY8I3bg4TwDNmzYMA0fPlwvvfTSEaPwpS99Sb/73e/0zW9+M3ab4oFXx3r27KkHHngg9gxaMgfFkAw9zo0KgWffXq4pN8zQ1m07O5acV9BNI0bU6qLR1RrZu7jjGbLcrHRVds+O/bfTXBe2vxNbzc3+brRtxdJp0srL9zHY+//9Ljxs8ugsvsIuxpwfMRY0b9Hj85p135xleu3VxWrbvO9WwYJuWXrie2dpSL9SW8hjdjuLsbzCPDU21OuSkVWaWNdTFcU5RuaOsiCJ8tqNJE8EjdB/2g16ZMXY5z//ed166626+uqr9b3vfe8gys6ti86W9PHcenjxxRfHroZlZmaqpKREv//972O3QDY3N+v666/XX/7yl9i/v/XWW7FdG7s69ib9geMWLFgQu63SscMBAQgcnsCC5etjD/+v2dDWMSg7N1vHDqnRCceVK3PPS2F75GdpeGV3jawt1qZ1GR1CBLbtghQxtv+VsDCLsR27duudj1o1/d0VeuD5pXrvrWXavm3fqyN69yrQMzdNUVUP+/fzIcbsfgMhxuzyDaN1xJjdqEZWjH3uc5/Tbbfdpu985zuxHRUPPObNmxcTYvGIMedWx/vvvz9mYsaMGTrttNP2M+fssvjCCy8cVvgdODdizG7SYz0aBFZvbNNJV0/XvGX7nnXJzMpUr8oecjb4iDXWhbkaPqCnpg2rVH1BqQb2M7sjXFBJNzRIjz2270ohV8YUu3IaVjG2dftOvbp0gx5+e4X+3rRYi+av0M4d+64sDx/QSzOuO0POlbFUHIgxu5QRY3b5htE6YsxuVCMrxkzepnjZZZfpjjvuUO/evbVs2bKDIvbb3/5W//mf/6mGhgY9++yzCUeUYkgYHSdGlEDbth2a+oN/6anXPzwsgeLSIo0f3VcXHF+lXmlFcnRabjepR0GWqopzlRHne8riQey8OPejdW1at2mHdmtXl6dkZmSooihHJfmZRp6T6XLCPQPy8qTNm4PzfFS863I77sCmNYxibFPbDs1dvE73v7FCM5oW6aMlLdq9a9+Oiec31OnO/z5BzrNiqToQY3ZJI8bs8g2jdfpPu1GNrBgzuYHHDTfcENt1cfz48XruuecOitg///lPnXnmmbHbHt9///2EI0oxJIyOEyNMYNeu3frvW5/XrTPeOSwF57mUkSNqNbhvcWyMc92spiRX42tKNKS6UNmZ7l8qe+Bkzotz31i2Uc8vWatFa9u0r909fHC6ZaVpcHmhGvr1ULWBHeTcpAEN2/4bmoTxytjaTdvVtHCN7n31Iz35/AdatWLtfiny7QuH6ZqLh6f0hwDHAcSYm0p1P5bads8s6mfQf9rNgMiKsXi3tne2t3ee+zrS4Wza8bGPfUxHH320nG3uDzz+9Kc/6ZOf/GTsXWbOO80SPSiGRMlxHgSk2//1nn50/2tat6l9Q4INm7bthyWnW46KSgraxVia1KO0QCcOrdT5gyt0fE135WUnLsi2bN+ll50X576xXE+/tlyrVm/a731Nh4tPVlaG+vXtoakjqnTagHLVlXWLXbnbezg7tto6aNjCK8acHROb12/V0wtW656XPlTT3EXasGbfy5XT09N061cm6hMn1NtKryPaRYzZxU5t2+UbRuv0n3ajGlkxtm3btthLn9evX3/Elz7PnTtXo0aNOmIUNm/eHLPl2HQ22ejTZ/8tfz/72c/q//7v/3T55ZfHnlNL9KAYEiXHeRA4mMDK9Vt0wlXT9cHy9YfGkyaVVZXq5HH9dO7gMpUXdEsYY3Nrmx55s0UzZx/84tyujGZlZ+moY6t13rg+aqjpoZw9V+nyszPVtzRXhd3sPOdGwxZOMeYIsUWrt+iJeat079xlevmlRdrcuqUjDXOzM/XotaerYVBFV6lp7XPEmDW0McPUtl2+YbRO/2k3qpEVYw5WZ/OO73//+7HbCx9//HHl73lpjLPV/RVXXKHGxkbNmjWrIwLO+8Sc/02dOlU33XTTfpG58sor9cMf/lBnnXVWbGfFvbYee+wxnX322dq5c6dmz54tZzOPRA+KIVFynBcmAru1W5u12ciStmzdoWk3P6Gmt1ccZC/2qrKt3WJXy0YMrVbPosS31F69cZtefHWpNqxtlXK2xK68dXlszVZa7IZJKSMzQ7X1FRo/pKrj2Z3ivEyN6VOshroe6lmQ3aU5twNo2MInxpxnFuc1t+qf763Ufc8v0VtvLNW2tn1XiEuLcvX0TVPUv7K723QxOh4xZhTnQcaobbt8w2id/tNuVCMtxtra2nTiiSdqzpw5sS3nJ0yYoMWLF8f+u7S0NCae6uv33aZx3XXXxW5Z/PSnP60777xzv8g4tk455ZTYM2OOrTFjxqilpSVmY9euXTHRd9VVVyUVTYohKXycHAICjhBrVKOa1GR/NS29pPIWO/PsTJfSj/zUWOZ7A5Rx5f90CDJnB8iikkI5t5A5R7e8HB0zsJcuGlGtk+p7qqrk0C+zTnQBNGzhEmNZOTv15rKN+vs7zXro+SVa8N5H2rF9R0d6DKwu1pPfn6IehYn/6JBorh14HmLMFMlD26G27fINo3X6T7tRjbQYc9Bu2bIldpXLeRfY0qVLY+8Dmzx5cmy7+wNvNzySGHNsObcp/uQnP5HzjNjChQuVm5urkSNHxl4s7VwxS/agGJIlyPlBJ7BJm1Sg9ue6rB8eizFnfVff96x+eve7h11qbl6uhh7fVxeNrdap9WV7nimL57Jb1/Ro2MIjxlau2al3V6/X395crn88t1hLFzVr1859u3mePKxaD1x5SsfL0LvODrsjUiHGovyS984vd4/qayvsZnD4rNN/2o1p5MWYXbxmrVMMZnliLXgEOouxZjUrX/ZeQLtizWad8j9P6qPVm4yBquyRp5k/mqSqnnmHtemssVzlsc9b1aq/P7Ncn/3lM3J2hTzUkZWTpaOPrdYF42p05tHlGlRZYGQ7fsRYeMTYwy+06JF5KzTz+YOfWfz85EH6+efGpXzHxCMVVSrEWEvLvpeaGyvwABpCjAUwaB64TP9pFzpizC5fo9YpBqM4MRZAAp3FmCNUbIoxB8+mtu364f2v6ak3lidNa+LgCl15wbAuX5x7qDW+smCVbrr/NS1f0/6s3FuL12jLtn23mDnPlPUbUKlzxtfoY8dUamh1YdJXORBjwRZjra27VVjYfpX0/N++qqZXFmjtyn0vQHeeW/zxZWP15bOOTTq3TRtAjJkmemh7zsvdncfi43qGNTUuMYtPCdB/2g0MYswuX6PWKQajODEWQAKpFmNeIIpnjdt37NInf/akHp69qMNF55my3n3LNHl8rS4YXKmRtd2Vn5P4TouIsWCLsRWrd6iyZ4aUt1kVl07X2jWrOnLFeYHzH79xkk4bXu1Finc557fvnKNbZ7wrbc1WfmG+GhvqdcnIKk2s66mKYjPPtDkb9Kxc2e6K85LzKAqSqK67ywRkwEEE6D/tJgVizC5fo9YpBqM4MRZAAvEIlQAuaz+X412js0X5tX95ST9+4LX9zu9V2UOTxvXTtGGVGtevVCX5iQkyxFiwxdiC5VtVv3CS1JCCzW4sFV3a2wPU/Xs3avy4el00vFKNtaUqNyTGLLl8WLNRFz6O+N1sZhPcVIfuiPNFJa70n3bTDjFml69R6xSDUZwYCyCBeIVKAJfW4bLbNf7h3+/ri795dr+XSHfvUaTxY/rq4uG9NbG+p8qLsl0/E4QYC7YYe3PFWh1X0SPIpdDue36rtNnes6GpAhTlWwIdIdbYKDUF93eBw6ZJVOJK/2n3mwIxZpevUesUg1GcGAsgAbdCJYBLVCJrfObN5frYjTO0UoTvrAAAIABJREFUdfvOjiX3rOih0yf218VDKzWmX4kKc91dIUOMhUeMFX/pVm1Z1/4+sUtPGaifXj7O16Xx1duf0e2XnRkqMeYsJqqbZXT+LvF14iXoXBTiSv+ZYHLEeRpiLE5QfhhGMfghCvjgJYFEhIqX/iYyd6JrnPfhOg35ygMdUxZ0L9AJE+r1HyOq1Ni/1PWLoRFj4RFjJZf9oUOMffb0o/WrLzQkkpopO+eLv39Kv//CSbH5un/yz2oYfVRgb1NkG/n966i5WcoP/oVORS2u9J92v/4QY3b5GrVOMRjFibEAEkhUqARpqcms8eKbn+jY1AMxlnzUDxSkjsWCPa+58/uv4Z1vUwyyGCv+zF2aOG6Q8Q08ks+O+Czwo8bBP2qERYwF5bsgvkw98ij6TxMUD28DMWaXr1HrFINRnBgLIIFkhEpQlpvMGj99y1P666wFsaUixpKPOGIseYaJWOh8ZQwxlghBf50TRkEaxjUdKWvoP+3WFGLMLl+j1ikGozgxFkACyQiVoCw3mTUixsxGGTFmlme81hBj8ZIKxrgwCpcwrgkx5l09Ica8Y+96ZsSYa2ScEDICyQiVoKBIZo2IMbNRRoyZ5RmvNcRYvKSCMS6MwiWMa0KMeVdPiDHv2LueGTHmGhknhIxAMkIlKCiSWSNizGyUEWNmecZrDTEWL6lgjAujcAnjmhBj3tUTYsw79q5nRoy5RsYJISOQjFAJCopk1ogYMxtlxJhZnvFaQ4zFSyoY48IoXMK4JsSYd/WEGPOOveuZEWOukXFCyAgkI1SCgiKZNSLGzEYZMWaWZ7zWEGPxkgrGuDAKlzCuCTH2/7P3HeB1VNfW615JV9JV7727926ruNGxDTHF2KT8JCSQvB8eeQkvySMkoSSE/GmkwEuoKS+hG8LDxsaAsS0sd3DBvcmSbVndsnr/v5lrXV3Jku7M3HNmztzZ8yXfh6Vz1tl77X1m9tKcOce4+URizDjuVY9MYkw1ZdTBzxjwRaiYhQpffCQxxjbKJMbY8qkUjcSYUqbM0c4fhYs/+kRizLj5RGLMOO5Vj0xiTDVl1MHPGPBFqJiFCl98JDHGNsokxtjyqRSNxJhSpszRzh+Fiz/6RGLMuPlEYsw47lWPTGJMNWXUwc8YaEITIhAhe1WJSoQhzM88BCQxloQk2S/JXzU+khhjmw4kxtjyqRSNxJhSpszRzh+Fiz/6RGLMuPlEYsw47lWPTGJMNWXUwc8YqEKVW6j4mWtDukNizNgokxgzhn8SY8bwzmtUfxQu/ugTiTFeM8A7Lokx7xwJ04LEmDChIEMMYsBKYqwQhShGMWywKWab3owppkpRQxJjimhi3ojEGHNKDQX0R+Hijz6RGDNumpAYM4571SOTGFNNGXXwMwZ60YtqVMteOeFUJVTMRoUS/3p7e/H3jcfx4gdH0d7Zjf2na91uhkeFY+H8UfjyzFQU5cUhPtyhigKrFRtDkWNmMbb/fB2mpsbJbkV/7W9oa+iU//sb14/DH79ZqCoX9G5MYkxvxvmO54/3En/0icQY33kwEjqJMeO4Vz0yiTHVlFEHYsBvGejq7sFXf7cZq7eeGtJHSYwtWuASY4W5JMa0JMLggqu3F4hwfbKIykogTNBPFpvbuvDBsfP4cn6WbGvwyudg67TL//2tGyfgqXvytdChWx8SY7pRrctA/ihc/NEnEmO6TIchByExZhz3qkcmMaaaMupADPglA02tnbj+0XX49LjrLeFQV2pWIpYU5WLF5BTMzo5CqCNAFRdWKzaGImcwB9K/k1x7q4h/OZuB5nDZTseKZ2HvdsV/zU9uwNXT0oS2n8SY0OFRbZw/3kv80ScSY6pTm1kHEmPMqOQPRGKMP8c0AjEgIgNrd5/B4698hppLbbJ552ubB5gZ5AhCRLT0msYm/y86xomiqam4Y0oK5mTHICI0ULVbVis2/FqMrXoGgV0heOGBBbhzwSjVuaB3BxJjejPOdzx/vJf4o08kxvjOg5HQSYwZx73qkUmMqaaMOhADpmfgyTf24vFX9gzrR4gzGFOnZWFyTqzcRtruIy0mBPOzYjAjMwohQereiPUNZLViQ4kYczqB6ssvI6X/tinfW4VrHkrfDp6pbcXHJ2uxetdZ7N1bhpauBnS88U153Ki7nsV7D30BBePM8VqPxBjXdNEd3B/vJf7oE4kx3aeGe0ASY8Zxr3pkEmOqKaMOxIBpGeju7sE3ni7Gq5tPDOtDeFQY5szKxopZaRifECGLA+n/MaEOZMaFwBHo+k5Iy2W1YkOJGBPxG7Hunl4crWjC+mPVeHN7GQ4eKEdHWwd6g9vR/sp9slsHLpzDpORULWlgSB8SY4bQzm1Qf7yX+KNPJMa4TQGvwCTGvFIkTgMSY+LEgizxXwb+uekEHn1lD+ouLwk0ytOW9q4BQ9sD7IhLiobd7hJYzrBgTBmTiJXTUzA/Lw5x4UGwMXxVY7Viw4xirKOrGwfONuLdw5X417YynDx6Hl2drrzxFGNqz6szKuf7xiUxZnQE2I7vj/cSf/SJxBjbvFeDRmJMDVsGtyUxZnAAaHi/ZkBa6vXDv+/C7945IJyfgY5AjB2fjgXTUhBod62Niw0NxIzUaMzLiUGkhm/CvDlptWLDbGKstaMbe8404K2DFVi79QzOnq5ET0+P241Fc+Ox/gfL5X+TGPOW7fx+T/MI8EcO/NEnEmP87gPekEmMeWNIoN+TGBMoGJxMkc7RakELJ3TxYJWcpcXLakl89fT0yvCd3T340m8+xnu7yngNpxk3xBmCyVMzsGJuOuZlxCH48tJDZ5AdabEhqndJVGpIU5M5tnFX6o+Wdp67J0p8iLJM8VJrF7afrsMbeyvwwfZSVJ6rAVypLF/fWjIBP/36ZETYXPvwkxjTEn3f+0hHIUjfGPbtwCnycQi+ejvSN5T+KFz80ScSY77OAu39SYxp5073niTGdKdc1wElIVaEIpSgRNdxjRysEIUoRrHuhzcXH6zA1/+wBeXVTUO6HxAYgMTUOAT48M0VC16DHAEYlRGL22YmY/GoBGTEhDBdijiSjVVVJtrGnQXZXjBEEGPSHxBqLnWg+FQtXt9bgS3bT6O+usFtubRK9TffyMe/3TgBzWhGOFxb25MY0yFBBg0hCbGiIqDEIrfzwkKguHjoTW38Ubj4o08kxvS/T/SNSGLMOO5Vj0xiTDVlpurgWTyZynAfjdW7UPzHpuO494/FkArboa6g4CBMmJSBq6alwBGgfQMMH2mRu4cG2TEuPhz52TFIiHToJsSksUmM9UdwpEKTRZyVYEj5Wl7fho9PVOP1Xeexc3cpmhr6jzgIDLRj9X9dg+tmZMhwJMaUsMqvjWexzm8UsZCH+4OFPwoXf/SJxJhx84nEmHHcqx6ZxJhqykzVwbN4qkQlwiCdG+Wfl+RrElzbbPMWY1UXW9HV0wNJe/3m7QP403sHhyXVGR6KadMzccecDMzLiNG8LTyrqAUG2JAY6UBEiPpzwny1oW+JlYQj0jbuvvqlpb/R/vf09uJkZSs2HK/E6zvKsX9vGdpa2t2uRDgd+OhnSzE523W8AYkxLVFm22coMeaPyxSVLOX1R+Hijz6RGGN7D1CDRmJMDVsGtyUxZnAAOA9v5r9kq6VGD19PX7iEm3+2ASfO9y/j8rTTZrchKS0OzrAQ+ceOoADkZUTj1mnJWJQXj5ToYF3fRKnlkNpbg4Gu7l4cqmjC2iMXsLqkDMcOnUNnR6fb+fSEcGx58iakxDoHEKLHHOMVAX/YTXEoMSbCUlfWMVMiSpS0YW0Xbzx/9InEGO+sGR6fxJhx3KsemcSYaspM1cHMxZNaonn7uu1IJZY8uh5tHQO3h++zU/omLGd0Cm6cm4GkyGD5x0F2O0bHOjEnOwZx4Q61LlF7YoA5A+2d3dhbfglvH7yAd0vO4MyJC+ju7naPM3tsIt77yQ0IDw26Ymzec4y5sx6AJMZ4sssWW4koUdKGrVX80fzRJxJj/PNmuBFIjBnHveqRSYyppsxUHcxcPKklmqevrxafxNd/v9m9U+Jg24JDgzFmfCpum5eJa/ISEB3mEl7SXh0JEUFwBuu/JFAtf9Te/xloauvCrjMX8eb+CqwvKUVFWfWA7xxXzM/DXx5YgIBhvmvkOcd4s09ijDfD7PCViBIlbdhZpA+SP/pEYkyf3BlqFBJjxnGvemQSY6opM1UHMxdPaonm4au0wcETb+zFE69+OsCc+OQYJCZHyz+z221IjnPixkmJuG5MEnITQ2FneFCyWh6oPTEwFAP1zR3Yeqoer312Hpu2n0bNhfoBzX60agZ+uGLaiMtoecwxvaJFYkwvpn0fR4koUdLGd0v0RfBHn0iM6ZtDnqORGDOOe9UjkxhTTZmpOpi5eFJLNGtfu7t78LU/bMEbxSfdpthsNqRkJuD6whyMTwqTt8+XdFdGZAhmpkchVcdt4tXyQ+2tyYD0B4ULDe3YfLIWr+4+h207S3GpvtFNhvTHhBe/vRCr5ud5JYj1HPM6IMMGJMYYkskZSokoUdKGs5nM4f3RJxJjzNNEMSCJMcVUGd+QxJjxMeBpgZmLJ7W8sPS1ua0TNz62HruOVrnNCAgIQPboZNyUn4WbxichLSZUFmJ22BDtDES4wt0JpR0FWyxyBrfROwaqzSGztJcEVntXL6QdEUe6pF9LQmzjiWq8tvMsPv30DFqbWt1dQhyBeO/RG5A/zrULqbeL5RzzNhbr35MYY80oPzwlokRJG34W8kH2R59IjPHJFSWoJMaUsCRIGxJjggSCkxlmLp7UUsLS17ue2oTXPd6IBTmCMGZCGm4ryMTSccmYkBIOaYt4tRcd2qqWMWo/mAFpJ8TjF5pxrrEV3T0jizFJrH1e2YS3dpTj0IFydLR1uOHio0Kx5cllyEmOVEwyyzmmeFBGDUmMMSJSBxglokRJGx1MZTqEP/pEYoxpiqgCIzGmii5jG5MYM5Z/3qObuXhSyw1LXyfd/yZOXt6+XtqcY8q0TNw6Jw3Xj07G2BSn5m/C6NBWtVGl9p4MyDshll3Ce8eqcPhCEzo6e7wSdLq8HiePnUd3Z/+OieMzY+QzxGLCXbt+Kr1YzjGlY7JqR2KMFZP8cZSIEiVt+FvKdgR/9InEGNscUYNGYkwNWwa3JTFmcAA4D2/m4kktNSx99RRj8cmxuH5BHlZOScG83FhEhASoNc3d3vNh64+HtfY5quTQVs0kWqRj31LEzm7X26/2rm7sP3cJq/edxwc7y1FT1YBeL2/GpH7S27Cenn7Rds2MdLz5g2sQHKQ+j1nOMb3DSGJMb8a1j6dElChpo90CY3r6o08kxozJJWlUEmPGca96ZBJjqikzVQczF09qiWbp61BibNVUlxgLD1ZfxHqKlPBw17/88bBWq/mpNkeVtpeWF56qasXJ2ia0XH6j1dLRjfWHq/Hx9tOoHbQTolLcf1s6Eb+5e67mg8dZzjGlNrNqR2KMFZP8cZSIEiVt+FvKdgR/9InEGNscUYNGYkwNWwa3JTFmcAA4D2/m4kktNSx9JTGmlv2B7a1WVPjG1sDeXT29OFzRhHVHKrGrtAGNrZ1yg47Obhz8/NyAnRCVjittNPPbbxTgWzeOV9plyHYs55hPhmjo/M0/b8Jz31os94z6yj9ROGcsVs5IQVF2HJKi1S3X1DA8ky6eb5z7AP3xjzpK7h9K2jAhXUcQf/SJxJiOCTRoKBJjxnGvemQSY6opM1UHMxdPaolm6SuJMbXskxjzjTFXb+mbsH3ll/CvwxfwbkkZzpXXur/16untQVdHl3uYoEA7vn7dOCRHh444tCPQjpvmZGFUapTPJrKcYz4boxLg63/YgpceWOjqFdYEtISpRPCxubMZaL78Wpzh+CTG/GeVAYkxH+cYdR/AAIkxEyUEiTETBUuDqWYuntS6y9JXEmNq2Scx5htjQHNbF3aduYg3D1zA+pJSnC+rGvabsIRo106I2UnKd0L01T6pP8s5xsIeNRj+KMYKC4HiYshHbPjTpUSUKGljNk780aeRYkD1J98MJTHGl1+m6DQZmNIpHJiZiye1ZLL0lcSYWvZJjPnCWH1zJ0pO1eH1veexcVspai7UDQs3ISsWH/50ieqdEH2xr68vyznGwh41GM98+Cnuv2am3MWx4lkEdjuRlZuMJfnpWDY2CVPSIzVtajKcDT09vThZ3YwPj9fgk5N1qG69iJIHr5abL/jdxxgXn4Cl4xIwOzsWkaGBilzxXKYobQCUkOB/QkwW/c2At29rlbRRRKpAjfzRJxJjxiUYiTHjuFc9Mokx1ZSZqoOZiye1RLP0lcSYWvZJjGlhTNoxsbKhHZtP1uLVPedQsrMUl+oa3VB2mw13XzcWc0YnyD9Ljw/HgonJCAiwaxnO5z4s55jPxqgEuNTdiKgA15vE4Dufga09GDa7DSmZCbihIAcrJidjdlY0whQe3j7S8NJZcIfON2LNkUq8VVKGUycq0W5rRMvfvyV3C7/rOUQ541A0Jwsrp6eiKCcW8ZEOrxurWKVYV+KnkjYqU8Tw5v7oE4kx49KKxJhx3KsemcSYaspM1cHMxZNaoln6SmJMLfskxtQyJgmxM7Wt8puT13eexZ49pWhpanXDBDsCsOYnN6BoQrJaaG7tWc4xbkYOA+xpe58Y62sanxyDxfk5WDktFQW5sYgJC9JsXltnNz4ra8AbR07jve3lKDt9AT3dPUBIO9r/8l2XGPzab4G2YIRHOjFzRhZun5mC63OzkBETMqIgs0qxrsRPJW00B9Ggjv7oE4kxg5KJtrY3jngtI5MY08KaefqYuXhSyzJLX0mMqWWfxJgaxrp7enG8sgnrjlbjje3lOLi/TD4PrO+KjQyRvwnLS/F90w01dnlry3KOeRuL9e89bX+xeB/+/fe7IS0l7LsiYyNQMCcbq2amYWFeHJKigr2+qRpsY1NbF3aUXpTPgvvTyqmqXHi6+BSuG52EvKTQYQ+Vt0qxrsRPJW1UBUCAxv7oE4kx4xKL3owZx73qkUmMqabMVB3MXDypJZqlr0OJsTumJCNfPvRZ2fcdQ9lvlYetVfxUmqMt7V2ob+mGdH4YentR0dCGdceq8K+SMpw4eh5dnf27JI5Oj8bHTyxFXESIUnjd2rGcY7oZfXmgwbbvPdyIZY+9jzaPHSqd4aGYMTMLd8zJwDWj45EdF6pYkF1s6cK2U7V4bW8FPtp2GmefuVWVi3Of2Ijb8zNx49hEjEsJR4D9yl05rDKvlPippI2qAAjQ2B99IjFmXGKRGDOOe9UjkxhTTZmpOpi5eFJLNEtfJ9//Jk6cb5BNcAQ7MH5yOm6Zm4EbxyRhYtrQhZISe63ysLWKn95iLn8TdqkDn5Y34ExDC3p6AOldzMnaZqzbegblpZWuJWyXr8VT0/DWQ9cgxKFd8HuzyZffs5xjvtihpe9Qtp+saMDCh9ag9lKbG9IR4sDEyRlYIQmjMQkYnex9vktx/vxsE9Yeq8QbJWU4vLcUPQ4XpvTd37P3z8f1BYlIQpL8s1OtZ/Gln5fg0xPV7nEjnfG4av4ofHFGKory4hA7xFJJq8wrJX4qaaMlT4zs448+kRgzLqNIjBnHveqRSYyppsxUHcxcPKklmqWv9/1pK1764IjbhIDAAOSOTcUX8jPxhfHJmJIRAUdggFoTFe0SphpUwA5WKyqGCoFUoJfVtuGj49V49/NKnKtqcr0ZA1BT2Yiq87WQ2vRd91w/Hr+7Jx/2Id6IiBJilnNMb5+Gs72usR2LH16DY2cvuk0KDApE3thULM/PxM3jkzApfeT5LsV1f3kj3j1aidVby3B0f6kb6x8PLsZthblXHAsQ3B2KzK+9jPqmdrltWGQYFs4fjS/PTEVRbhwSIh1XUGSVeaXETyVt9M4xX8fzR59IjPmaFdr7kxjTzp3uPUmM6U65PGAvetGClgGDO+GEDWwPjDFz8aQ2Mix97ejsxqpfbcS63WVuM+x2O9KyE7GkIBu3TkrGrOxoOB3qBJlVHrZW8dMzR9s6ulHd1IG+FYeX2jqx+XQN3tx+Fgc/L0drc//bl8G5/au75+H+ZRPVprzu7VnOMb2NH8l26bDt2578EB/tPTtgvmfkJGFJYRZunZSCmZlRCB1mvo8kxo4+uxKZCeFDntG2/IkNeH9POYmxQcmg5P6hpI3eOebreP7oE4kxX7NCe38SY9q5070niTHdKZeFWBGKUIKSAYMXohDFKGYqyMxcPKmNDGtfpbcWP/jbTvzxfz/vN8UGJKbE4WppK+ypKfLOa1EKzwiSQKzysLWKn32J0dDahV2lF3G0pgltl5cd1rd0Yu3Ocpw4fG7AN2GeeR0YYMdr378aS2Znqk13Q9qznmN6OuHNdmm+f+eFbXh23WG3WTabDYlpcbg2X5rvyZiXM/SZYFrEWPGeOtzyxAb3WGFRYVhUNBpfkt6M5cUhIYLejEnkNDUBYWFXZoo/3mP80ScSY3re5QaORWLMOO5Vj0xiTDVlPnfwLAoGgzWhCWEY4smjcVRvBYhGWCG78fL1+feP4NvPbZX2XXBf0fGRKLy889r83DgkKjgjiMSYkGnjk1FSAV91qQOfnKrFm/sqcPTMRbRf3hCirbUTF8qrB3wT5jlYalwY3v7htZiSE+eTDXp25jXH9PBBqe1Prz2I77+0fcB8j0mIxoJ52a4zwXJjER8x8EwwtWLst+/vwsPP7RswRnJGAm6cn4uVk1MwJyd6yLdwVinWlfippI0eecVyDH/0icQYywxRh0ViTB1fhrYmMaY//Z5FQSUqZQP6PuwmMaY9HkqLLS0jfLjvLG594gN0dvVvthAW6cSsmdlYNScNi0clIDN25DOCSIxpYV6sPh1d3fKGHC3trjzo6OrBnop6vLrjPPZ8WoqmhuZhDV5RlIuffWW2vKGD3Q6kxDgV79QnCgs85xhvH5XafqS8HgsfeheXWjoHmCRtfT9/Xi5WzUzFgjzpDzDB7t+PJMacwYGIiwzB6NQo/PruuXhnxxk89vKefmwbkJQWj2vn5WDFtOHfvtH9Y2CG+KNw8UefSIzxvrMNj09izDjuVY9MYkw1ZT53GFwUSIDhCJdxSYxpp1dpsaV1hENl9bjq4bVoaHZ9cC9dwaHBmDw1E3fMS8d1YxIxOjFsxA0YrPKw9Uc/Wzu6saesAXvPN6Cu1VWod3b3YvPBSuzfW4b21v68GJxjT/yfOfju8slaU0+YftL9KQIRsj3SH5JYvsXn7aR0f/D2R6+h/ujSZ5e0ZHHC9BysKMjA0jHJmJTuumdLl/SG9MDlDTzeLCnDkX39G3h4+hUUaB/wBx3pO9R06bu0/CzcNmXk79IkHH+cV0PFXYmf0vLFCFcqorJy6KWMvHOKNb7kd5Jrw81hl2eyHtNIPKo/+bJPYowvv0zRaTIwpVMRGIkxRTSpbsRbjMkP/YutWPTQGpRWXnLbF+gIxNjx6bilIBNLxyVhUmoEAgOG3ohFSZGh2nEBO/ibn5dau7D9dB3e2HcBe45Vo7HRtRlHb08vKs/XosvjrCrPcCRGh+KP3yzAzXOzBYySepOqUOUWNOp7i9NjqD96vbDhCB54duByZE+LQ8JCMHdOLlbNScdV0pvwuIHnwJXVtmLjiRq8svMsdu48hbYRNmzpw03JTMSNRdlYPiFJPsMw3MsZhv42r4bLCCV+VlX1CxdxMoudJcN9K8duBOORqP7kGwMSY3z5ZYrOejLoURAzJcAAMBJjfEjXK/ekA3yX/fR9bDt0we2IPcCOzLxk3FSQjVsmJmF6ZhRCgq7caVFJkcGHHX1R/cVP6Y1HTaP0TVgdXvusAlu2n0Z9zUXXYWFDXHPHJeGdh6+DtDRNuiRRLr1R8ZfLH8SYtFHS25c+wL1Pf4Kthy7Ib7WknTC7PM57kza1jYmPQpAjSA6dwxGA3Ow43D4rbdjDoCWc0tpWfHi8Bqv3nMPJ07Xo6OiW+3d2dKK+puGKvEnPTcZNRTm4fVIyZmZHIzjQPmKq+Mu88jYflPjpz2KssBAoLgb86NYxZMhZ15/e8spqvycxZqKIs54MehXEJqL4ClNJjPGJnp65193dg2/+9yf458fH3c5IRXdyRjyuz8/G7VNTMTc7+oq/dCspMviwoy+qP/gpFdfn6tuw8UQ1Xtt1Hjt3j/xN2J2LRuH5++YjIGDkgtqXSAx1JIYveGr7SuNXw3VQMY+jONTao8WGc+c6sOiH76H+8tvNwWP2HWGxeHYGIkJcYizMYcek5AjMz4lFUlTwsAJbPuS7oR2fnK7DgQuNaO5wfVvY2NaJj3eX49zpKvRIJ39fvjJHpchi7LaJyZiZFQUHiTGZGSX3D2lDperLZ2Y7nf4lXPzNn+HmNev6U+39w9/bkxgzUYRZTwY9C2IT0TzAVBJjfCJnRO79cvU+PPLP3QMcik2KwWJp57UZaSjMiUFseP8W1UqKDD7s6Itqdj+lDRlOVrZiw/FKvL7jLPbvPYO2loHfhIVefvsV6XTgP2+Zwv2csOGOxNA3smKNpvY4kM2fV+Dmn74P6RzBoS7psOecMSnyYc/XjkpAZIhr7gYF2pAWHYIop+uNp7eroaUL5y62obPL9Qr1UlsHPjhRjXe2leFceR0ycxNRdqoKEyenYeXcDFw3OgF5id43dDH7vPLGW9/vreKnUj78tR3r+tNfedLqF4kxrcwZ0I/1ZDCiIDaANp+GJDHmE33DdjYq91aXnMZdv/0Y3T39a9ciYsKRPzsbK2elYVFePFKiXX9Nt0qRYTY/m1q7UFbfhubL3361d/ag+Ewt3tpWjqMHz8rLzPqu9IRwbHnyJqTEOvkk8jCoIx2Joashgg023KZH0kHO0tvrt7aeGrBphqf50g6JEZGuOEpvNFNTIrF0WgpuHJuIcSnhCLCzWWIq3RuOVDRh/bEq7DpzEfNHxWLL8TosGhOHa0clIjcxVN5l09tltnlLVrEVAAAgAElEQVTlzZ/hfm8VP7Xy4y/9WNef/sILKz9IjLFiUgccXyeDVCB4Xp47Vg2125aZdt/iRf/gHcmkcbzt8qXVFqMEilZ7felnpK+7jlXh+kfWobW9y+1CaFgops/IxB1zMnDN6ATkJISitcWG8MubsPnzB9pmKqZqmjqw9VQddp9tgHR4s3R1dHfjk73nUXriArq7+t+izBqTiHWP3IDwUNfyNT2vwUdiWPle6m1nxNrGNnnn02NnLw4booTUOPkNdma8U/pEDNIKwbxYJ/IzY5GdoEwcqYm/9La1tLoVp2qbMTYpHEcqGzEhKRKpMcMvexyMb6Z5pYYbq/rpC0f+0NfX+tMfOODpA4kxnuwyxvZ1Mtjkx5jyS1pqY/VrpI/gaWt77dlhpBiTrC6rasT8h9agqr7F7YQj2IHxk9JxW34mloxNREZkOKIiXXOGxJj2WLPoKX3fc76+HR+frMFru8/h8PFqtLZ2yNA93T1oqLsk75bYd90+Pxd/eWAhAjl+EzaSX0bnNwvOWWGMxMXJigYsfGgNai+5drwcfAUEBCAlMx43ypvtJCM5MlTeKEF6CRYX5kBseCC3TVeknJPeuoY4AiAdlRDquHKTnxFzoBn0xxxWSUQ4hjPga/1puAOCG0BiTPAAeZrn62QgMaY+2MOJMbXfPygZ2UoFnAi+NjR34Oofv4eDpbXu8AQEBiB3bCq+MC8T12UnY8GkaBJjSpKXYxvpLcWpqlZ8cKIKr20/i33SN2EjbEX+8MoZePiOadyKdCWuipDfSuzUo81wXHxy6AKWPb4e7Zd3MZRscYaHIjEt1v1nw7hYJxZOSMAXJqRgSnoEgofY9VQPH7SMQW/GtLBGfURlwNf6U1S/RLGLxJgokVBgh6+TgZYpKiB5UJPhdiTTsjOYt9GtVMCJ4qu0OcCdv96I93aVucPTt0PbNTNy8KcvTSAx5i1xOf5e+n7ncEUT3jtciTe3l+GI9E1Ye/83YZ5D2+02vPDAAty5YBRHi5RBi5Lfyqzl22ooLl7efAL3/HELejzeZkrfhBXMyca8vFj57Zf0TjoxPBgz06IxnuE3YXy97UcnMaYX0zSOHgz4Wn/qYaOZxyAxZqLosZ4MVDCIFXwrxUMkX6XlSA/9fRd+/86B/oSwAfHxiTj73E3yz85VdyE1XtnubGJllXdrRC0apU0d9p1txP8eqsA7JWU4fbxiwDdhjqAAjEmLkh1MjQ3DI3dOx4y8BO8O69BCpPzWwd0Rh/DkorG3Eb959Sh+8cbeAX3ik2OwOD8Hd0xNxZiEy5tx2IDIkEDERQQp2jDDaD8Hjy/qvGLNk1X8ZM2b2fBY159m85+3vSTGeDPMEJ/1ZKCCgWFwGED5SzyUnK/kbfMYBnSqhvjbR0fx4Is75INlpau3KxAdb94r//e6z2qxcEK06u9GVBthQAcRiynpjcnn55qw5sgFvFVSjsOfn5G/Deu7vjAvG//z3cUI8nLWkwF0ykP6y1xmwZ8nF3/e+Cn+4+lP3bA2uw2pmYm4viAbKyYnY1ZmNGw9YvzRw9fzo0ScVyziaVXRyYM7M2Gyrj/N5LsetpIY04NlRmOwngxUMDAKDCMYf4iHX52v1OwEwl07kL6+vRLXTIpFTJj+O/MxSq9hYUQsGqWNE3aVXsSbn1/Amk9O49zpC277v3fbVDz2xZmGfhPmLSb+MJe9+aj0955c3PH7Nfjfza5YSt9nZo9KxrKCLCyfkIxp6ZG4enEASkqUIvNtV1gIFBdrP6BYxHnFgzGr+MmDOzNhsq4/zeS7HraSGNODZUZjsJ4MVDAwCgwjGH+Ih6cPjGgxDsZDjP3PjtNYOjGdxJhO0Wjr7MHuYcRY61tf18kK7cP4w1zW7v3Anp5crPjdu3h3S6XcIDw6HFctGI1V05NRlBsPp93h3n2Q1di+4oy0i6r09ra7txdBw+zYaRWRYhU/fc0ls/dnXX+anQ/W9pMYY80oRzyaDBzJFQDaHwo4Tx+GOruuj2YRlyn22fbl32zEut3l6A3oRsc//13+MYkxfSdIdWMHPjlVi7f2X8DGklOoq3SdQRUaHIi6V+7S1xgNo/nDXNbg9pBdvImxL81IQWFuHEJs/WKsshIIC2NlgTocSVwkJbn6DCfGpDPujlY0oa2rGzlxTqTHhlzxptYqIsUqfqrLIv9rTfUn35iSGOPLL1N0mgxM6RQOzB8KOKU+KG1nRJBW/OJDrNl5Bj2SGLv8zRiJMX0iIX2vV3OpA8WnavH63gps2X4a9dUN7sFTYsNw6oVV+hjjwygi57cPbmnqqkWMGXmu30jiQsrPqkuuPxRsPFGL5vZuzMqMxLVjEjE6MQzSjp7uPzjROWOa8oU6ickA1Z9840JijC+/TNFpMjClUzgwfyjglPqgtJ0RQSIxZgTrkDdOOVffho9PVOPVXeexc3cpmhpc3+xJV2CgHe/++HosmpxqjIEqRhU5v1W4waSpv4gxKT/Lpfw8Xo1Xd57D/oPn0dnRhcyseNxSkImlY5MwMTXcvamMVd4YWcVPJpPBxCBUf/INHokxvvwyRafJwJRO4cD8oYBT6oPSdkYEicSYEawDDS2d2HaqDi/vrcCHxScGvBGLcDrw0c+WYnJ2rDHGqRxV5PxW6YrPzf1BjEnfh52oasb7x6rxxvZy7N9XhvbWdpkbe4AdmXnJuKkgG7dMTML0zCiEBAXAKiLFKn76PBFMDkD1J98Akhjjyy9TdJoMTOkUDswfCjilPihtZ0SQSIwZwTrk5V9bTtbgn7vPo3jrCTRf6n8rduqFO5ES6zTGMA2jipzfGtzxqYvZxVhwSC8OnW/EmiOVeKukDEcPn0VXR9cATmw2G5Iz4nF9fjZun5KKuTnRsHUHujckMXLZpU/BU9CZxJgCkvygCdWffINIYowvv0zRaTIwpVM4MH8o4JT6oLSdEUEiMWYE60ClLMaq8fLuigFi7MuLR+P5f19gjFEaRxU5vzW6pLmbmcVYTX03jtU24O2DlVhTcgZnTlYMOO9uMCmxidFYlJ+DldNTMS0pFlnJDrkJiTHN6UMdBWGA6k++gSAxxpdfpug0GZjSKRyYPxRwSn1Q2s6IIJEY05/17p5e7D/biHXHKvHO9rM4/Hk5Ojs6ZUPuvnYsnvm3Iv2N8mFEkfPbB7c0dTWzGHt3Tw3WHj+P97edwYXyaveB8BIRdy4ahSUzM/DVpzZByt++KyImHPNmZWP5xHR8fWEaiTFNWUOdRGOA6k++ESExxpdfpug0GZjSKRyYPxRwSn1Q2s6IIJEY05f1jq5u7C9vxDuHL+CdbWU4dfQ8uru63Ub86u55uH/ZRH2N8nE0kfPbR9dUdzezGFv57D588tlJ1FbWD/D7kS/OxH/dPk3+2e7jVbj+kfVoaXP98UC6QsNCMGViDjY/VCD/+1JjLyLC+3daVE2iwB1omaLAwWFoGtWfDMkcAorEGF9+maLTZGBKp3Bg/lDAKfVBaTsjgjSUGPvbjtNYNjEdsWFBRpjEdUwji6mWjm75cOfVn1/AupJSnCutQk9Pj9vfJbOz8Nr3r0LgMAfrciXGB3CR89sHtzR1NZsYO3W+HXlpwbKv8V9/GY3NrjPupCvAbsNz9y/A8vzsAVyUVzXiukfXoaq+1f3zQHsoml/+mvzvtZ9VIjMxCDaB9VgonLDBZaDTEYCw4IArzk4bKgGUnMumKXGok1AMUP3JNxwkxvjyyxSdJgNTOoUD84cCTqkPStsZESS3GLN3o2P1vbIJD755ELdNzMCEtAgEepwlZIR9rMc0qpiSDs4tOVWHN/ZV4KOS06g6XzvAtQdunoRf3DVHUUHImhNf8UTOb199U9vfTGKsrbMHWw7V4/ppcS43m8KAsBa1LrvaVyUASVXa+pq0lz9/G2fSkDAzm+pPZlQOCURijC+/TNFpMjClUzgwfyjglPqgtJ0RQfrl6n145J+70dNrR8e/XH/ZtsqlRzHVd3DullO1eG3POWzdWYqLNZfcFEtvD/7wzUJ847pxpqVd5PzWm1QziTHpEOf1h87h9hmZJMZUJkphIVBcDKHf/ql0iZp7MED1J990IDHGl1+m6DQZmNIpHFgTmhCBCNmuSlQiDGHC2ejNIKnwSkKSVx8820l+i+RrV3cP/s9Tm7B66xlLiTE9iilJiJXVXT7Yeec57N5TiuZL/W8egoIC8PbD1+LqKa6ND8x6qRFjRi4T1YNfM4sxx5f+CFt3AFLjnDjw9ApFdEk5/sjLe/D0uweB9lBXn4BO+TwyIS9HO9r+/H3ZtJC7fw9bezCCggORmZ2IpXPTsXRcEialRcARGDCi+U4nCTEh48vIKKo/GRE5DAyJMb78MkWnycCUTuHAqlDlFjLCGcfRINHEmOSqVFA99NpW/L+rbpU9d/zfn8HWEYy45BgsmpOF26YkY052LGL86Bsy3sWUdHDucfng3Cq8se0sDuzvPzhX4jgqPBibnliKcRkxHLNNH2gSY/08m1qM3f4c7N0BSI8Px/HnVqpKnpc+OIr7/7x1wA6MqgB0atwb3I72V+6TRwu+8xlZjEmX3W5HWk4iluZn49ZJyZiZHS1/S0aXNRmg+pNv3EmM8eWXKTpNBqZ0CgdmRTFWiEIUo9j94bhIQfEsIj2LlMjYCBTOycbKmWlYmBeHpKhgU37XpCfXnV09OFjRhLXywblncOzwuQEH52YnR2Lzz5chMfrymwQ9jeMwFokxEmMSAxv3n8Mdv/gIzR47LXJIN58ghxNjMqgNSEyJw9UFObhjWgryc2IRFRro03jU2ZwMUP3JN24kxvjyyxSdJgNTOoUD60UvqlEt2+X02NlKOENHMEjpMsU+CJH99CyoI+/6Mzoa+4sQZ4QTM2dkYeWcdFw9Oh5ZcaEkyIbJi7bObnxW5jo4992SUpSdvDDg4NyCCcl498fXwxnsP0UeiTESY30MdHR2Y39pHXp6+88iE+me3mprxqLRubJJm46fwobtNXjqX/shmesp1Jb/bTO+PGUUJiZFIjjI9YYsLNiOuHCHvMskXf7NANWffONLYowvv0zRaTIwpZPAODCgpgjlMDxTSE9f9lWcw40PfYy6S23uMYJDHJgwJRMr5mXgxrGJGJ0URkXJoAg0tXVhx+mLeHO/dHBuKS6U1wxYtvWVq8bgz/+3CHY/K+ZGmgfSN2Kel+dulpWVQNigT0UH/5tpkusAZtVlijpQy2SIoXL1w71ncevPP0BHQKt7CWPsvS9h9uTxWDwxHo7L379FBwdiakqkom/KmBhLIIYxQPUnX+pJjPHllyk6TQamdBIYBwb8VYxJ37W1NQZg8cNrcfxs/7lDgUGBGDUuFcvzM3HTeGUfunOgXUjI2qYObD1Vh9c/O4+Pt51GXVU/b5LBj395Fr5361QhbffVqJHmgdqzpgR9oaKYIhJjiqkypOFwuXqorB6LHl+N6hfuke2SlmqH2CORlpUgf08mXVGRwZgzJg63TkrBzMwohNI3ZYbEUI9Bqf7kyzKJMb78MkWnycCUTgLjwIA/izFpx8e2ji7c8vMPsWn/OTd70i5pGTlJWFpw+UP3zCiEWLgokTY/qbjYjk0navDq7nPYvrsUjfVNbr6kJU1/f3Axbs3P4ZCBYkCSGOuPA4kxMXJyOCtGytVTF2uQF53gFmN9m3v0YUn3voSUWFybn4PbpyQjKzYMerzkdgTakRTpIPGnY2pR/cmXbBJjfPllik6TgSmdBMaBAX8XYxJl0q6A335+G154/7CbQZvNhsS0OFxbkIMVU1IwLycGkRb80F36LuZ0dSs+PF6N13eW47NPy9Da3OrmyRkShPcfuwGzRidyyD5xIGmZIokxcbJxZEs8c3XwkSqe3wAHf+23QJtrp8W+q0+cxSREY8G8bExMi9BlMyZncAAmJoRjHm0ooluaUf3Jl2oSY3z5ZYpOk4EpnQTGgQEriLE+2v747uf4/l92DGAxNjEa8+fmYNX0FBSNikN8uIMDy2JCdvf04khFE947WoXV28pw6PNydLZ3uo1NinViy8+XITPRdZYez0vaDKcF/eeXsRhLzWYzauYBnTOWgsLcOITYHAgPd0VKj8PHh8qJwYc+O3zY2p5FzumB4ZmrascLufUFd5fwqDDEJkSqhdDUPiQ4CONyYnH79BQsyI1DYqSDNlDSxKTyTlR/KudKS0sSY1pYM6gPTQaDiKdhFTOgpghVDGpQQyW+rN1VhlW//AjSQdF9l1SUzJ2djZWz0nDVqHikxoT4faEgCbFD55uw9mglVpeU4fDnZeju7HZzMjknDh88vgRRYfzFqSTEilCEEpQwzRw1xzAoyZ0+40iMjSzGpNySlr02tPQLe6aB9QDr6QX2V9Tgy3NdS2hJjI3MdPyX/46mlg5e4RgRNzImAgVzc3HnrFT3ESOGGGKRQan+5BtoEmN8+WWKTpOBKZ0ExoEBNUUoh+GZQir1Zd/pWlzzo7Voau0vFkOcIZg6LRN3zE3HdWOSkJsYCrvanRuYesMXrKm9G9tP1eHVfRV4v/gkairq3AMum5OFl//zKgQFuj7653358pd+b7YpPaBcae5I45EYG16MdXR1Y//ZRuw8W4/yi+3QY3P4ysYm/PWLswaIsZzkSBz67xXe0sOUv1e6THHwEkbJ2YY6YOFDa3C2uv+bUL1IsNltmDgtBysKMrF0TBImpl9+raqXARYbh+pPvgEnMcaXX6boNBmY0klgHBhQU4RyGJ4ppBpfztc1Y/5/rcH5mv6iJMgRhLGT0nHbvAwsHZ+M8SnhCNTj63amLCgDa2zrxvbTdXjls/OyGKurrJc7SucR1b96l65vBkcqLpV5M7CV53czJMbUM6h0A49gOBBxeQWrtMW/LagL285W4L3Dldh6uBoXL7ZCPvyK89Xe2Ybqvy6XRwm65SXYuwPwkztn4Ns3Tx5xZDXLWDm7oAp+xO8b0YxwuETOcLkv/RHq3meKsX5POaS3mDwv6cw292UDJkzLxe0FGVg2NhmTSYzxpB5Uf3KlFyTG+PLLFJ0mA1M6CYwDA2oEDIfhmUKq9aWxtQM3PLIen55wHdwtXQGBAcgelYKbCzOxfHwypmb0H5jK1FiDwWqaOvDJyVqsPlCJD4tP4GJ1g2zR+IwYfPr7W3W1Tm3cvBmnBU9LH292mPX3w4mxsMgwLJg/CiumSd/9xCOoMxhJSX1e9gKfFAGFbJea8uRQzTJWnnaoxfZVjKkdz5f2h8vrMePbb7kgSIz5QqXqvlR/qqZMVQcSY6roMrYxTQZj+afRvTPgT0WoFl+kb8fuemoT3io57SZLWk6TmpmIGwqycfvkZMzOikZYSKB3Mk3S4lJrF7afrscb+yvwYUkpKs/1H+w8PS8eJb/6gq6eaInbSAZqwdPSR1eSdBzMk4uv/Pc6vPFh/7EQ0oY3C+blYNWMVIyJiMWE3MvfFDqbgWbzLTtT+uZUR/q9DkVizCtF1ACgN2Ocs4DEGGeCWcKTGGPJJmHxYMCfilCtvkjnbD3+6qf4xRt7B1AcnxKLq+Zl445pqSjIjUVMWBCPEOiKKb8RO1GL1z6rwJYdVx7s/D//uRi3F+TqapPWuA1npBY8LX10JUnHwTy52HLiNJY89PGgDW/CMXdOFlbOSEdmcDT2X7iIfx07iY0PLJKtdHzlD+4t1WMiHJDOqeN59QR14MKvvw04W1Fpq4R0vqA3sZ4E1ys9K4kx6YiPBp037zhcfhFXP7zGFQ56M8ZzGlyBTfUnX7pJjPHllyk6TQamdBIYBwb8qQj11Zd/bjqBe5/eIp9L1ndFxkagYE42Vs1Mc+8AJp1RZsbrYnMnSk7X4eXPKrDxk5Oor77odiMwwI5Xvn81ls3O1N01X+M22GAteFr66E6UTgMO5uL4qVZc8+P30Dx4w5vpWVg8KREf7b+A/UeOoeHFe2QLg+98BpEBEdj4xFJMyorlbrXa2Kltz90BlQNosf/tbaW470+foL6pXeVoDJuTGGNIpncoqj+9c+RLCxJjvrCnc1+aDDoTTsOpZkDLg131IDp1YOHLJ4cuYNnj69He0f/huTM8FDNmZmPlnHRcMzoeWXGhum5wwYq+MzWt+OhENV7ZeRa7dpxCe6urMJO05bZfLcfU3DhWQ6nCYRE3zwG14Gnpo8pJEzUeiouzNc1Y8NC7qKhtdnsSFByElIx4VJTVoMPWhPZX7pN/l/fA3/DJY7cjOcapi9dqY6e2vS5OqBhErf2/emsffvKP3SpG4NPUbrdj4nRpN8UMLJF2U0wz37JWPszwQaX6kw+vfagkxvjyyxSdJgNTOgmMAwNqH+wcTGAGycqXkxUNWPDQGtRdanPb5ghxYOKUTKyYl4EbxyZidFIY9+VXzIi5DHS6phUbj1fhlZ3nsHtnvxh7aMU0/OTOmayHU4zHKm59A2rB09JHsYMmazgcF5daOnDdI+uw72TNFR71Bre7xVhlWz0SQ6J181pt7NS2180RhQMptV96w//N//4E/9h4TCEyv2bSd7gx8VFYmJ+DVdNT5UPD48LNv+ybH2O+I1P96TuHIyGQGOPLL1N0mgxM6SQwDgwofbBzGJo5JEtfahvbsPjhtTh+1mMpX1Ag8samYnlBJm4en4RJaRFwBAYw94MHYE9vLz4/24T3T1Th7R3lOLD3DLo6uuShnronH9+6cQKPYRVhsoybNKAWPC19FDlnwkYjcdHZ1YOv/PZjvLO9dIBnnmJM7++w1MZObXvRQqjE/pb2Ltz00/dRcuiC23x7gB2pWYkICw/R3aUQRwAmZMdgxdRk5OfEIdrpPxsi6U6mwgGp/lRIlMZmJMY0EmdEN5oMRrBOY6phQMmDXQ2ekW1Z+9LW0YVbn/wQH+/r301OKmgycpKwpCALt05KwczMKIQ6xBZk0llCRyuasO5YNd7cXoZD+8vR0d7hDtVL316IOxeOMix0rOOmBU9LH8MI4zywNy6kDW8eeXkPfrV6n9uSH3x5PB67tVD+N4kxvgHyFp+qi61Y+MM1KL1wyW1IoCMQY8anYcmcDMSHXd4Bk6+ZA9CdQQEYHx+G6dLOtILfL3WkhetQVH9ypZfOGWtra8OTTz6JV155BWVlZYiNjcUNN9yAxx9/HOnp6ZrZP378OKZMmQIJ//rrr8f69es1Y/V1pMngM4XCA/SiFy1oEd7O4QyUHuxm3lnM0y9vRYqWIElLff7jhW14fv1hd3dpA4/EtDhcm58j/6V3Xk4sIkPF/EtvR1c39p9txLuHK/FOSRlOHDuHbo+DWCdlx6H4F8sQ4jDOftZx04KnpY+WfDJDH6VcfLj3LP6x6QS+dvUYzJoc5fWwYV6+K7W3b3y17XnZrRV3JPuPlNdj0cNr0eCxUUdwaDAmy0us07EwJwFRBryVCg60Iz4iCEEBdq1uUz+VDFD9qZIwlc0t/WZMEkpXX301SkpKkJKSgvnz56O0tBQ7d+5EQkICtm3bhry8PJWUuppfddVV2LRpE6S/+pEY00Sh5TpJQqwIRSiBeQ46HSlIev9Fm3XC8Cyynl5zEN97afsAk2MSXGcurZyegvl5rm8gRNppUbqXHaloxvrjlXh921kc+PQ0urv6Nya5dkYG3vzB1XAEGftmj3XctOBp6cM6f0XB08KFlj6s/FU7ttr2rOxkhTOc/Rv3n8PyJz5Ap8cfW8IinJg5Kxt3zknD4lEJyIwNEeoexYoTwrmSARJjfLPC0mLsJz/5CX76058iPz8fGzZsQHi4azee3/72t3jwwQexYMECbN68WXUEXnzxRXzjG9/Avffei+eee47EmGoGrdnB86HoDwyQGBs5iu/tKsPKX3406MylMMyZlY1Vs9Nw1ah4pMaIU+xIyxM/K7uEdw5fwNtbz+DkoXK3g1+7diye+VahEIUZ6+JYC56WPv4w54fyQQsXWvqw4k/t2Grbs7KTFc5Q9r+44Qj+/dkS+Y/JfVd0fCQK52Rj5cxULMiNR2KkQ4j5zooHwhmZARJjfDPEsmKss7MTiYmJuHjxIj799FNMnz59ANNTp07F/v37sXv3bsycqXxnsKqqKowbN07u8/DDD2Px4sUkxvjmsN+gez4UK+H9sFHRHPdcoijZRmLMe4T2n67F1T9ai6YBZy4FY+q0LNwxNx3Xjk5CXlIo7AKcRTaSGLvwP19BlAHfjrAq/keKlJZiW0sf79lizhZauNDShxU7asdW256VnaxwPO1v7G3Ez/5+CL9/50A/vA1ITInD1fnZWDEtBQW5cYgSdBk1K04I50oGSIzxzQrLirGPP/5YXkooLUM8ceLEFSxLb8ykN2ePPPIIHn30UcVRWLVqFd555x0cOHAAZ8+eJTGmmDlq6E8PdRJjyvP5fJ105tIanKtucncKcgRh7MR03JafgaXjkjE+NRyBdmMPh77Y0omtJ+vw9ucX8EHJaVSdq3XbS2JsYLzNPpeVZ6/3llq40NLHuyXKWqgdW217ZVbo18rT/pt//Q42lFS7B5fO8krLTsSN+dm4bXIyZmVHw0kbZugXHIFGIjHGNxiWFWO/+93v8J3vfAcrVqzA66+/fgXLa9euxbJly7B8+XK8/fbbiqLw3nvvYenSpfLmHz/+8Y/lb8bozZgi6qiRxi20RSJu8DJLejOmPDrSm7EbHl2HPcf7C6GAwABkj0rGTQVZWD4hGdMyIhFs0PdYtU0d+ORUHV7/7Dw2bTuNuqr+LfpDgwNR9Y+vIFCQj+lZF8da8LT0UZ4t5mqphQstfVixonZste1Z2ckKx9P+4Dufga09WIaW7j+5Y1PxhfxMfGF8MqZkmOfoDVbcEE4/AyTG+GaDZcXYd7/7XTz11FOyIJO+ERt87du3D9OmTcOMGTOwZ88er1Fobm6GlKwhISHy8kaHw0FizCtr1MCTAX96qEt+kRhTl99d3T346u83Y/Unp9wdpcNNUzITcENBDlZMTsZsaSvnEP12KpS+GTl/sR2bT9bg1V3nsFcTXnUAACAASURBVH1XKRov9r/BCwiw4fXvX4MlszPVOcuxNet5pAVPSx+OlBgKPRIXn52sQXVDG66amjpAzBvJn9qx1bb3NRjSm/R1u8vR7rGxhi+YNe0NeOTyMQJ9YswR7MD4SdKb+UwsGZuIcSnhpjuU3hdOqO+VDJAY45sVlhVj0uYazz//vPxd189+9rMrWJaWLo4ePRpjxozB0aNHvUZBEnXS27aNGzfKb8OkS+ubsb6kHzzoyZMn5WWVBw8e9GoPNTAfA3o/1FkzRG/GfGdUEj+Pv/opfvHG3gFg8ckxuCo/B3dMS0VBbixiwoJ8H0wBQnN7N3acrsdr+yqwvvgkqs73L010hgThg8eXYMaoeAVI+jVhPY+04Gnpox9D+o40FBfSEQ8PPFcCaaMI6ZqaG48Nj9+ISKfrzCoj+VM7ttr2vrC/uuQ0vvrUpgGb/viCJ/X1PGBbEmPOwGhMn5GJO+Zk4JrRCchJEOObVV/9pP6+MUBizDf+vPW2rBi755578MILL+BHP/qRvKPi4Es6J0wSYkrEmLTJx7x58/ClL30Jf/vb39xQJMa8pR/93pMBPR/qPJgnMcaO1Zc3n8A9f9wCqWjtuyJjI1AwOxurZqVhYV4ckqKCue9m1tDSha2navHPT8/jo+ITaKjtP/j12HMrkRHv2oFWpIv1PNKCp6WPSByytGUwFwEdwbjl5x9i0/7+w8+l8ZJjw7DlF8vknDKSP+mNfgQiZAqUbKQk2dp3tqKS9lq5fepfB/Cz1z6FvMFhN8O348Ht6Hj2v2Sz4r/9POZMHo3bZqRiQU4ckqNHvsc4nYAAewtppZT6qWCAxJgKsjQ0tawYY7VMsaurC7Nnz5YPjD5y5Ih8PlnfpVWMDRdHmgwaMtxEXYwsQFjQRGKMBYv9GFsPX8Cyx95HW0eX+4fO8FDMmJmNlXPScfXoeGTHhXIVZMOJsYIJyfjoZ0vZOswIjfU80oKnpQ8j94WD8eTiTGMNlv5wE06c6//m0NPgvretY0eFGnbocxWq3OJKODIlIVb0CVBSKIRphYVAcTEJMiGCwdkIqj/5EmxZMcZqAw/pkOicnBwkJydj7NixA6IlbZsvfXsWExODKVOmyOeYrVmzRnNEaTJops4UHc1ewJEYY59mpyoasOCHa1Hb0OoGd4Q4MHFKJlbMy8CNYxMwOonf9xzDibH5E1Ow4adL2DvMAJH1PNKCp6UPA9eFhPDkIvneF3Cxpt/M4BAHgoKD0NTQ7P5hgN2GF743D3fOnSj/TO9vT4UWY81OILyfKxEC3tQEhIWJYAnZwJMBqj95sgtYVowp3dpe2t7+scceGzYKfWJMSZiioqLkc820XjQZtDJnjn5mL+BIjPHJs7rGdlz1ozU4Wt5/7wgMCkTe2FQsL8jEzeOTMCmNz05nZhRjapeZeYua5zI0pcLA7HPZGydqfu/Jhedufc4IJ2bOyEJ8VAg2bx+4Q6fnd0xKOVdj00hte9GLarh2NXXCCRtGPlKC1zLFyoutuOGRdSirauwXqrYQtLxyt/zv5zeVwhnav4zZF//tdiAjPBbjksMRomDH1uZmICnJNSKJMV+YN09fqj/5xsqyYqyjo0M+9LmhoWHEQ5937twpL0PUctEyRS2sWbeP2Qs4EmP8clfaOe22Jz/ER3vPugeRzgDKyEnCksIs3DIxGdmxYbDbbfI3HJEhAQgLDvB5CaMZxRjPNxtKhYFRc3nH0Sq8+MFRNLd38ktGlcjnmuqx+ZHb5V59YiwqNhIFc7KwcmYaYkIdWH2gAh9sK8WF8hpIm9h4irFLPY2IsIv3bWIfDTxifaisHlc9vBYNze1utoNDgzFxfDZKflwk/6yiphsRjGiR7hkhQXbFh8tLYiz88tgkxlROCJM2JzHGN3CWFWMSrdLmHU888QQKCgqwYcMGhF1+1y5tdf/ggw+iqKgIxdKC6MvX008/Den/t9xyC5588kmvkSEx5pUiauDBAI+Hup4Ekxjjy7ZUpH7nhW14dt1h90A2mw2JaXG4Nj8H0zMiIZ0LLf0dPzk8GNPSopEZF+KTICMx1h/TQhSiGMVe35RIPYyYy79cvQ+P/HM33yTUgD54t77E2JTLO4OmID8nDqEOGz4ta8C/Dlbi3ZJSlJ28gO7AVrS/cp882qLHV+O9H9wM6Tw7ES/Wsf5w71nc+vMP0NnV43Y3LNKJWTOzccvkdHxrcYb8cyNFEIkxETORr00kxvjya2kx1tbWhkWLFmHHjh1ISUnB/PnzcebMGfnfcXFx2L59O0aNGuWOwKOPPiovWbzrrrvw17/+1WtkSIx5pYgakBgTNgdYF1msHP3v9w7hP1/c5tpV7fIVkxCNjKw4+V+SQIuPDsG1ExJw/dhEjE4M03xGkBnFmNplZkrjomTJWh8W66WSI9nY3d2D+58rwWubT7LdZU8pMd7aeezWl/3jf+C6mWOwfEISZkpn5l0WWJLwOHT+EtYfr8E728twovQ0Wl7+howsvU3Li03Epp8vRUJUqLfRdP89y/vECxuO4IFntw6Y29HxkSiaky2/RZyRFIe8NNehzCTGdA+1pQckMcY3/JYWYxK1ra2t8luul19+GeXl5fJmGzfccIO83X1GhusvUH0XiTG+yWh1dJYPdSO4pDdj+rG+fk85Vvziw2HPG5KWNOWMTsYt8zJxw5gEJERIb8gA6duQuLAgdxHszWIzijFvPunxe55LJYe0X7Bd9nzm2NkMNLvWwTlWPQN7RzBiIkKw8zfLkR4v1m4RLO7b0lvv7/91J55+9/N+6mxAYkocri7IwR1TU5CfG4vAnkAhlgfSmzGfM9x0ACTG+IbM8mKML71s0WkysOVTNDQWD3UjfSIxpi/7B0rrcNWP1qKppWPIge0BdmTmJmFJfjYyYkLl9YsBNhtyo0MxKzMaiZEOr0sYSYxpi6nuYkzAXfa0MXe5l6cYW/Es7N0B8i/uWzYRv757nk/QrDv7et/u6OzGyl9+BOkPLH2X9D1oWnYilhRk49ZJyZiVHQ2nIwCiiCBR7GAdS8IbngGqP/lmB4kxvvwyRafJwJRO4cB8fagb7RCJMf0jUFHXgmWPr4f0wf9Ql7RkMSE1DlExTvnXgZJAS47E8mlJWDwqAZmxI39TRmJMW0x5LZXss+ZweT2WPLYel5pdQry3KxAdb94r//eP3zmMqRnal6Zq83jkXoF2G3IjYpAR7/S6SYT0lmhPWQ0WTUiUQaO++le0X3KdtXfnwlF46dsLeZioGdOX+/bF5nZc86P3cPBMnXv8gMAAeafUm/Mz8YUJyZiS3r9TqigiSBQ7NAeNOqpmgOpP1ZSp6kBiTBVdxjamyWAs/7xH9+Whzts2JfgkxpSwxKfN2ZpmSDsuStdfPjyK37y9f9iBQsNCMHFyBu6Yl46irHiEh7jeOgx1SZDHqy/htb0V+Kj4JC7VXZKbiXzOGB+GxUH9aN853PLEhgEbPDhDI1D38h2ykQdLWzAqzbUsVZTLbrOp+m7x0IV6TEyOlc2P+frf0VrvEp3+JMZKKy9h4UNrUXWxxR0mR7ADEyan47Z5mbhxbCLGpQw8Q1AUESSKHaLktxXsoPqTb5RJjPHllyk6TQamdAoHRmJMrJCYOR7/u6MUX/z1x5A2dxjqCnQEYuz4dFw3Kw3hXnapq7zUhve3l6H8dCV6LuMtmpKKdY/eKFbALGDNcBs8zJuWi3/dN1NmoLGxF+HhAikxDXHxdzG281iVfIZYa7vrjZ90hYaHYsb0TNwxJwPXjE5AdkLoFW8RRRFBotihIbWoi0YGqP7USJzCbiTGFBIlQjOaDCJEgZ8NZi7+JVbozRi/3NCCvPdUDVb+cuOAQ2M9caRvypLS4hHkGP7NmNS+pbkdtRfq5fOf+q4/3VeEr149VotZ1EcDA942eLh5dApumeNa1mfkLnsaXBuyiz+LsTe3nsJdT21CT0//fIqMicC82dlYOSsVi/LikRIdPOT3nKKIIFHsYJVvhOOdAao/vXPkSwsSY76wp3Nfmgw6E67zcCTGdCbcy3Bmj0efe42triVe3T29+I/nt+G1LSd9IvpXd8/D/csm+oRBndUx8MCzJXj+/f7z5QZv8DA+IRqJsS5RTWJMHbe+tlZzn3h50wl8/Q+bBwwZlxyDxfNycMf0VBTmxiA2zDGsSaKIIFHs8DV21F85A1R/KudKS0sSY1pYM6gPTQaDiNdpWDUPdZ1MUjUMvRlTRZdhjbUeDixt/vH6D67BjbMGHvlhmCMWGjjqjr+gw+MQ4JSsRFwzLxurpiRjXl4sejsDhNjynFVI/PXN2KzvvO3erEPaXCclIwHX52fhtqmpmJsdjfCQkQ+2FkUEiWIHq3wjHO8MUP3pnSNfWpAY84U9nfvSZNCZcJ2HIzGmM+FehjN7PEZy7+1tp/G9v+xEZX3/5gEjtR+THo2/PLAAU3JcB0vTpS8DX/z1Rrxdcto9qLTjXvaoZNxUkIXlE5IxOjYScTH0ZkzfqLhGU3OfmHz/mzhxvkHuF5sYg2uKcnHblCQU5sYhLnz4N2J9fokigkSxw4h4W3VMqj/5Rp7EGF9+maLTZGBKp3Bgah7qwhk/xDdjlahEGMQ6oFUNb1I8kpAkd2lCk6l9UeM3tRWPga7uHnz195ux+pNTbuNsdhtSMhNwQ0EOluYlY+mMeFeuNgFh5p12sg/++mbMU4zFJ8fiuvl5uHNaCublxI64qymJMfHmpNUsovqTb8RJjPHllyk6TQamdAoH5m9iTDiCfTCIxJgP5FFXJgxIm3j89LXP8OTrnw3Ai0+OQdGMPLx6z1QSY0yYVgei5r5NYkwdt9RaHAao/uQbCxJjfPllik6TgSmdwoGpeagLZ/wQb8ZEtFGLTYUoRDGKYYO5twvX4jv1EYsB6TDpv35yAPf9aeuA3fgiwqNR88IXZWO3H6tDVrL3JW9ieTbQmmNVDViYly7/MPpbz6O1wbUJzYqiXPz9vuuFmotq7tskxkTOOrJtJAao/uSbHyTG+PLLFJ0mA1M6hQNT81AXzvhBYuwUTiEBCUIVTVo5c8LpF35o9Z/6icGAJMSKUIQSlFxpUFUCkFQlhqEsrHA2A83hLqTmUCCs1Y0q2h9H1Ny3SYyxSA7CMIIBqj/5sk5ijC+/TNFpMjClUzgwNQ914YxX+SG7iPaTTcSAyAwM3q10gK3+LMak47gGvZQWadmwmvs2iTGRZxjZNhIDVH/yzQ8SY3z5ZYpOk4EpncKBqXmoC2c8iTERQ0I2+REDnveHvs1x6hrbseTx9ThWfhFoD3V5G9CJsAgnAr0c5i0yNb2ONtT88W7ZRMdXfwtbezBCo3pw8c//Lv+MxJixG7XQbooizx4+tlH9yYfXPlQSY3z5ZYpOk4EpncKBkRgTLiRkEDEgDAPD3R/aO7tx25Mf4qO9Z4Wx1VdDeoPb0f7KfTJM8J3PIDE0GuufXIyJSakkxi6v3jRy10wSY75muPn6U/3JN2YkxvjyyxSdJgNTOoUDIzEmXEjIIGJAGAZGuj9IOy1+98XteHHDEURGhKK2vlkYu7UY4inGpv7gZWz6ya0ICutCOFxKhN6M0ZsxLXlFfbQzQPWndu6U9CQxpoQlQdrQZBAkEJzMIDHGiViCJQb8gAEl94fzdc14efNJvLe73NQedwe1Ycujt8s+1HU2ICYoUtXhyno6ryQuffb4+s2Y9DYsIsKFVllp3Hly0puxJNcRjH5xrp2e+WLWsaj+5Bs5EmN8+WWKTpOBKZ3Cgal5qAtnPH0zJmJIyCY/YsDs9wc1oRjKV1H9V2OXpxiLiInAgvxc3DY9GQtyE5AWE+yVoqqqfhHktbFODYxcLqmTizQMAKo/+aYBiTG+/DJFp8nAlE7hwNQ81IUznsSYiCEhm/yIAbPfH9SEwl/F2KIfrsGOI5VuKiJjIjBvdjZWzkrForx4pEQHw2Yb/jxD0cRYYSFQXAyMYLKasFNbgRmg+pNvcEiM8eWXKTpNBqZ0Cgdm9mLL7PYLlxBkEDHgwYCV5pe/irEDpbVY9MO1aGnrdEc2NDwUM6Zn4o45GbhmdAKyE0JhH0bd9PYC1dWurk6n8SJIBBvoJqEPA1R/8uWZxBhffpmi02RgSqdwYGYvtsxuv3AJQQYRAyTG3Jt1iHp/UWvXmcpGLPjhGlTVt7ijGx4djgUFefjSrFTMz4tHQoSDcp8YEIoBqj/5hoPEGF9+maLTZGBKp3Bgah/qojnAw/5e9KIF/UWLaD7zsMcJJ2yDT7nlMRBhmooBHvNLVAL89c1YH98Xm9sx+t7X0NTqekMWHBqM2XNzceecdFw9KgFZ8ZfPjBM1QGSX5Rig+pNvyEmM8eWXKTpNBqZ0Cgdm9mKLtf2SECtCEUpQIlyseBpUiEIUo5gEGU+STYjNen6JTIG/izGJ+9/+az8e/vuuK8RYUXY8kqP0fTMmrYp0OgIQYB/+ezWR84Vs488A1Z98OSYxxpdfpug0GZjSKRyY2Yst1vZ74gkXLM4GiXSOEmdXCV4hA6znl8JhDWkm5X8EXHu4V6ISYQiTt7ZPgms/9b6fGWLcoEE97VIzb59e8zm+99IOGS0gMACjxqXhpvwMTE6K1P29eIAdSIt0YlJaOMKCA0WglWwQjAGqP/kGhMQYX36ZotNkYEqncGBmL7ZY2++JJ1LxxStxtBZ1vOwhXLEYYD2/xPJuoDVVqHILL5HtHGybGjH23u4y3PbzD9wQ9gA7MnOTkJ4ao7vLkhjLTQ7HsvGJyM+JQ0wYCTLdgyD4gFR/8g0QiTG+/DJFp8nAlE7hwMxebLG2nzWecAEf4i/s4QiXf6qmqBPdL7KPDQNWmg9mFGNqlxf39vbi/mdL8NKGI+4Ekba1DwzSXwhJ44ZHOTF3RgZWzUzDnMwYhIcGXZG4dgDhIQFwBEr/RZeVGKD6k2+0SYzx5ZcpOk0GpnQKB2b2You1/azxhAs4iTHRQyKUfVaaD9L3otVw7eHet6GNqMsU+5JE68Y7v/vfz/HQX13LFY2+nBFOzJqRhWUzUhA5xHLFAJsN6ZEhmJoeiZgwfb9rM5obq49P9SffDCAxxpdfpug0GZjSKRyY2Yst1vazxhMu4CTGRA+JUPZZbT4MJt+f/X93xxl86Tcb0dnVY3jOBYc4MGpcKpzOK8WWdP5ZRkIYlk5MxMK8OCRHjXxIteHOkAHMGKD6kxmVQwKRGOPLL1N0mgxM6RQOzOzFBmv7WeMJF3ASY6KHRCj7rDYfrCTGJF+l7e43HahAV7e+gqyxpRNPvPEZztU0uym32W2w24ZYimgDpEOqp05Ox8q56SjKiUPUEMsZhZo4ZIxmBqS9NVOig+X+VH9qplFRRxJjimgSoxFNBjHiwMsKsxdbrO1njccrbqxwreYvK96sgmP1/LC6/zzzvK2jC8t//gE27z+vaBhHiAMTJmfgptlpiBviDZoiEGokPAPSstRv5GeSGNMhUiTGdCCZ1RAkxlgxKSaO2YsN1vazxhMz6v1WWc1f0eMhmn1Wzw+r+887H3t6evHt50vw4vtH0KtgsICgAGTlpSAiIkRBa2piRgakc+e2/mABiTEdgkdiTAeSWQ1BYowVk2LimL3YYG0/azwxo05iTPS4iGKf1ebDYN6t7r9eeXiuthmnLly6Yrj2zm789LW92Hm0Ui9TaByDGbDb7Wh+82skxnSIA4kxHUhmNQSJMVZMiolj9mKDtf2s8cSMOokx0eMiin1Wmw8kxkTJvH47pO34H3xpB/609qB4xpFFzBmQjjxoWX03iTHmzF4JSGJMB5JZDUFijBWTYuKYvdhibT9rPDGjTmJM9LiIYp/V5gOJsYEMSNv9t6CFWzqq2Zr/T+sO47/+ugMdnd3c7CFg4xkIDLCj8Q16M6ZHJEiM6cEyozFIjDEiUlAY6aDfCETI1lWiEmEIE9TSoc2SisUkJMm/ZHFosdWKT6v5a6rkFsBYq+eHlf2XhFgRilCCEm6ZqPbQ6tb2LpRVN3Gzh4CNZ8But2F0apRsCNWffONBYowvv0zRaTIwpVM4sCpUucWMcMapNIjEmErCAFi52FTPlvV6WD0/rOy/p+88M5/FfZunfYRtHANUf/LlnsQYX36ZotNkYEqncGD+IsbU/oV1uEBYrfiymr/CTUDBDbJ6fljZf0/fWa+aYL2iQfBpROZpZIDqT43EKexGYkwhUSI0o8kgQhT42SAtRalGtTyAmvX7/CzShszKdqsVX1bzV1t2WbeX1fPDyv7zXMJOYsy69xQ1nlP9qYYt9W1JjKnnzLAeNBkMo54GNoABqxVfVvPXgJQy9ZBWzw8r+6/XqglapmjqWwRX46n+5EovSIzx5ZcpOk0GpnQSmOAMWK34spq/gqefcOZZPT9E8p/3zoaDk08SY7nI5ZqT+cjHBmyADbZhx2G16oGrIwTOhQGqP7nQ6gYlMcaXX6boNBmY0klggjMgUvGlB1VW81cPTv1pDKvnhyj+67Gzoah5y+p7YFH9I7uGZ4DqT77ZQWKML79M0WkyMKWTwARnQJTiSy+arOavXrz6yzhWzw9R/NdrZ0NR85aWMooaGb52Uf3Jl18SY3z5ZYpOk4EpnQQmOAOiFF960WQ1f/Xi1V/GsXp+iOI/z50NRc1V2uRD1MjoZxfVn3y5JjHGl1+m6DQZmNJJYIIzIErxpRdNVvNXL179ZRyr54co/otih555bUWf9eTXDGNR/ck3SiTG+PLLFJ0mA1M6uYPp/ZE3d4d8GEDLh99WKwCs5q8P6WTJrlbPD1H8F8UOPSeBFX3Wk18zjEX1J98okRjjyy9TdJoMTOnkCmblj7yHIlbLh99WKwCs5i/XCeiH4FbPD1H8F8UOPVPcij7rya8ZxqL6k2+USIzx5ZcpOk0GpnRyBbP6R95Dkav2w2+rFQBW85frBPRDcKvnhyj+i2KHniluRZ/15NcMY1H9yTdKJMb48ssUnSYDUzq5glnxI++hCPXlw2+rFQBW85frBPRDcKvnhyj+i2KHniluRZ/15NcMY1H9yTdKJMb48ssUnSYDUzq5gtHDy0WvLzz40pdrcDmBW81fTjT6LazV80MU/0WxQ89Et6LPevJrhrGo/uQbJRJjfPllik6TgSmdXMHo4UViTG2CUc6oZcxa7a2eH6L4L4odema/FX3Wk18zjEX1J98okRjjyy9TdJoMTOnkCkYPLxJjahOMckYtY9Zqb/X8EMV/UezQM/ut6LOe/JphLKo/+UaJxBhffpmi02RgSidXMHp4kRhTm2CUM2oZs1Z7s+eHr0d9eH5/WolKhCHMawJoOVLDG6jZ4+DNv6F+b0WftfDkz32o/uQbXRJjfPllik6TgSmdXMHo4UViTG2CUc6oZcxa7c2cH0Yd9aHlSA1vWWXmOHjzbbjfW9FnrVz5az+qP/lGlsQYX36ZotNkYEqnZjAlDyYlbTQbYKKOvvDgS18TUeQ21Wr+mjFGRtps5vzwtF1vDtUeqeHNPjPHwZtvJMa0MuT//aj+5BtjEmN8+WWKTpOBKZ2awZQ8jJW00WyAiTr6woMvfU1EEYkxMwbLAJvNPB88bVe6xHAwxWqWKXq2JTHme7KaOfd8954QJAao/uSbByTG+PLLFJ0mA1M6NYMpeTApaaPZABN19IUHX/qaiCISY2YMlgE2m3k+sLBdDYaatmpDyRNbrS16tbeiz3pxa5ZxqP7kGykSY3z5ZYpOk4EpnZrBlDyYlLTRbICJOvrCgy99TUQRiTEzBssAm808H1jYrgZDTVu1oeSJrdYWvdpb0We9uDXLOFR/8o0UiTG+/DJFp8nAlE7FYNKDyPPytlxG2uWLHl4uxnzhwZe+ioMrUEOr+SsQ9aYwxcz5wcJ2NRhq2qoNPk9stbbo1d6KPuvFrVnGofqTb6RIjPHllyk6TQamdCoGs8GmuK3UUNo5jB5eJMZUJY2PwlXtWNTefAyY+Z7CwnY1GGraqs0EnthqbdGrvRV91otbs4xD9SffSJEY48svU3SaDEzpVAxGYkwxVVc09OUh7ktf7RYb19Nq/hrHtDlHNnN+sLBdDYaatmqzgSe2Wlv0am9Fn/Xi1izjUP3JN1IkxvjyyxSdJgNTOhWD0TJFxVSRGNNOFb1N9YE7K3Q1c0HMwnY1GGraqs0dnthqbdGrvRV91otbs4xD9SffSJEY48svU3SaDEzp1Aym5MGkpI1mA0zU0RcefOlrIorcplrNXzPGyEibzZwfLGxXg6GmrdqY8sRWa4te7a3os17cmmUcqj/5RorEGF9+maLTZGBKp2YwJQ8mJW00G2Cijr7w4EtfE1FEYsyMwTLAZjPPBxa2q8FQ01ZtKHliq7VFr/ZW9Fkvbs0yDtWffCNFYowvv0zRaTIwpVMzmJIHk5I2mg0wUUdfePClr4koIjFmxmAZYLOZ5wML29VgqGmrNpQ8sdXaold7K/qsF7dmGYfqT76RIjHGl1+m6DQZmNKpGUzJg0lJG80GmKijLzz40tdEFJEYM2OwDLC5CU2IQIQ8ciUqIR2hYZZLmstJSPLJdk8MiYuR/Od57+CJLWo8reizqLEwyi6qP/kyT2KML79M0WkyMKWTKxg9vFz0+sKDL325BpcTuNX85USj38JWocotaPzWSYWOkRhTSBSjZnRvYkSkiWGo/uQbPBJjfPllik6TgSmdXMHo4UViTG2CUc6oZcxa7UmMueJdiEIUoxgjHTnCcy7xxBY1o63os6ixMMouqj/5Mk9ijC+/TNFpMjClkysYPbxIjKlNMMoZtYxZq710mHw1qmWnnXCOKEZEY4bFMsU+n5T4znMu8cQWLW599ljRZ1FjYZRdVH/yZZ7EGF9+maLTZGBKJ1cweniRGFObYJQzahmj9mZhQO/c5jkeT2xR42lFn0WNhVF2Uf3Jl3kSY3z5ZYpOk4EpnVzB6OFFYkxtglHOqGWM2puFAb1zm+d4PLFFjacVfRY1FkbZRfUnX+ZJjPHlX/bTHwAAIABJREFUlyk6TQamdHIFo4cXiTG1CUY5o5Yxam8WBvTObZ7j8cQWNZ5W9FnUWBhlF9WffJknMcaXX6boNBmY0skVjB5evosxM2/lrSW5PL+r8bZbnBZ86kMMGMWA3vdDnuPxxDYqPt7GtaLP3jix2u+p/uQbcRJjfPllik6TgSmdXMHo4eW7GLPy7nEkxrhOTwLXmQG974c8x+OJrXNYFA9nRZ8Vk2ORhlR/8g00iTG+/DJFp8nAlE6uYPTwIjGmNcGUbN2tFZv6EQNGMKD3/ZDneDyxjYiNkjGt6LMSXqzUhupPvtEmMcaXX6boNBmY0skVjB5evosxM2/l7UtyKdm62xd86ksM6M2A3vdDnuPxxNY7LkrHs6LPSrmxSjuqP/lGmsQYX36ZotNkYEonVzB6ePkuxrgGiMCJAWJANwb0vh/yHI8ntm4BUTmQFX1WSZHfN6f6k2+ISYzx5ZcpOk0GpnRyBaOHF4kxrglG4MSAiRjQ+37Iczye2KKG1Io+ixoLo+yi+pMv8yTG+PLLFJ0mA1M6uYLRw4vEGNcEI3BiwEQM6H0/5DkeT2xRQ2pFn0WNhVF2Uf3Jl3kSY3z5ZYpOk4EpnVzB6OFFYoxrghE4MWAiBvS+H/Icjye2qCG1os+ixsIou6j+5Ms8iTG+/DJFp8nAlE6uYPTwIjHGNcEInBgwEQN63w95jscTW9SQWtFnUWNhlF1Uf/JlnsQYX36ZotNkYEonVzB6eJEY45pgBE4MmIgBve+HPMfjiS1qSK3os6ixMMouqj/5Mk9ijC+/TNFpMjClkysYPbxIjHFNMAInBkzEgN73Q57j8cQWNaRW9FnUWBhlF9WffJknMcaXX6boNBmY0skVjB5eJMa4JhiBEwMmYkDv+yHP8XhiixpSK/osaiyMsovqT77Mkxjjyy9TdJoMTOnkCkYPLxJjXBOMwIkBEzGg9/2Q53g8sUUNqRV9FjUWRtlF9Sdf5kmM8eWXKTpNBqZ0cgWjhxeJMa4JRuDEgIkY0Pt+yHM8ntiihtSKPosaC6PsovqTL/MkxvjyyxSdJgNTOrmC0cOLxBjXBCNwYsBEDOh9P+Q5Hk9sUUNqRZ9FjYVRdv3/9u4F2KqqfuD47wpYcaEU1CsCjskjx2aSZ6k8NAFlClM0tDFTUKE0X3izyTTBB0KOgc/JEhQjQSlSJzFFy5ybiKQkhqSBiZLIBVEZEfGR9z+/9Z9753Iv3HP2Ob919l57ffeMM9Hd+7fX+qy1zlm/s/dem/mnX3mSMb++ptEZDKacXoPx5UUy5rWDERyBgAQq/Xno83w+Y2e1SWOsc1bbIq1yMf/0K08y5tfXNDqDwZTTazC+vEjGvHYwgiMQkEClPw99ns9n7Kw2aYx1zmpbpFUu5p9+5UnG/PqaRmcwmHJ6DcaXF8mY1w5GcAQCEqj056HP8/mMndUmjbHOWW2LtMrF/NOvPMmYX1/T6AwGU06vwfjyIhnz2sEIjkBAApX+PPR5Pp+xs9qkMdY5q22RVrmYf/qVJxnz62sancFgyuk1GF9eJGNeOxjBEQhIoNKfhz7P5zN2Vps0xjpntS3SKhfzT7/yJGN+fU2jMxhMOb0G48uLZMxrByM4AgEJVPrz0Of5fMbOapPGWOestkVa5WL+6VeeZMyvr2l0BoMpp9dgfHmRjHntYARHICCBSn8e+jyfz9hZbdIY65zVtkirXMw//cqTjPn1NY3OYDDl9Bpsm2yTztLZnaNe6qVaqr2eL6vB9Uu8Rmpc8dQkVoestg/lQqASApWezPs8n8/YlWiLUs4RY51LccrzMcw//bYuyZhfX9PoDAZTTq/BNsmmpiTE64kCCk4yFlBjUVQEDAUq/eOUzx+BYkxMYqyzYffPRSjmn36bkWTMr69pdAaDKafXYCRjO/MOkSFSJ3VSJVVe3QmOAALZE0jz89D6R6AYE5MY65y9UZRuiZh/+vUnGfPraxqdwWDK6TVYgzTIZtnsztFROkafhGDgtbsRHIFMC6SVjPn4EajSV/my0LA+rzRmoX6UobAA88/CRuXsQTJWjl6Fj2UwVBic0yGAAAIIlC2Q1o9TPn4ESiuxLLsRjAJYX2k0KhZhPAsw//QLTDLm19c0OoPBlJNgCCCAAAIIJBKIORnzcaUxET47pybA/NMvPcmYX1/T6AwGU06CIYAAAgggkEggrat8iQrpaWcfVxo9FZWwxgLMP41BW4SLPhnbsWOHTJ8+XRYsWCCvv/66dOnSRUaPHi1XX3219OjRoyj9d999Vx5++GF56KGH5Pnnn5fXXntN9thjDzn00EPltNNOk/POO086dOhQVKy2dmIwlE1IgIwI6IRmu2zPSGmSFYMJSTIv9kYAAQQQCFuA+aff9os6GdNEbMSIEbJ06VLp1q2bDBs2TNatWyfLly+XfffdV55++mnp1atXwRa44oorZNq0aS4B69+/v/Tu3Vs2b94sTz31lHz44YcydOhQefTRR6Vjx44FY5GMlUXEwQEIaCI2VIbKUlkaQGlbF5FbdYJsNgqNAAIIIFCiAMlYiXBFHhZ1MnbllVfKNddcI0cccYQsWbJEOnXq5NhmzpwptbW1Mnz4cHnyyScLUs6YMUPee+89dwWse/fuTfuvWbNGRo4c6a64XXbZZXLdddcVjEUyVhYRBwcg0HyZ5ACKu8si8hB7qC1HuRFAAAEEkgqQjCUVS7Z/tMnYxx9/LPvtt5/oLYYrVqxwV7Sab4cddpi88MIL8uyzz8rAgQOTqTbbW29/1FsVDzroIHn11VdLjqMHMhjK4uPgjAg0T8bqpV6qpTojJWu7GCzvHEQzUUgEEEAAAWMB5p/GoC3CRZuMPfHEE3LMMce42xDXrl3bSlmvmOmVsylTpsjUqVNLboXVq1e7JGrPPfd0tyyWszEYytHj2KwIhPoC0VDLnZV2pxwIIIAAAmEKMP/0227RJmM33nijTJ48WcaNGycLFy5spbx48WIZM2aMnHjiiXL//feX3Aq6qMfxxx8vBx54oFvYo5yNwVCOHsdmRSDUpCbUcmel3SkHAggggECYAsw//bZbtMnYJZdcIrNmzXIJmT4j1nJbuXKl9OvXTwYMGCDPPfdcya0watQoefzxx+WCCy6Qm2++ueQ4eiCDoSw+Ds6IQKhJTajlzkizUwwEEEAAgUAFmH/6bbhok7FJkybJHXfcIZdffrlce+21rZT11sU+ffpI37595eWXXy6pFW6//XY599xzZa+99pIXX3xRDjjggKLiNHb6lju/8sor7rZKjcWGQKgCoSY1oZY71H5CuRFAAAEEsiFAMua3HaJNxiZOnCizZ88WXZZenw9ruelKiJqIlZqM6SqMxx57rOhCIYsWLZKxY8cW3ZIkY0VTsWOAAqEmNaGWO8AuQpERQAABBDIkQDLmtzGiTcZ83qaoqzAeddRRbqVGvTVRb1G02BgMForESFsg1KQm1HKn3d6cHwEEEEAgbAHmn37bL9pkzNcCHnorob7keePGjW4VRl2N0WpjMFhJEidNgVCTmlDLnWZbc24EEEAAgfAFmH/6bcNok7Fil7bX5e2vuuqqolphw4YNLhHT94lddNFFogmf5cZgsNQkVloCoSY1oZY7rXbmvAgggAAC+RBg/um3HaNNxj766CP30uetW7e2+dLn5cuXy+DBgwu2wjvvvCPDhw+XVatWyYQJE2TOnDlSVVVV8LgkOzAYkmixb1YFQk1qQi13VvsB5UIAAQQQCEOA+affdoo2GVNWXbxj2rRpcuSRR8qSJUukurraaetS97W1te4qV11dXVML3HrrraL/6WIc06dPb/r/t2/fLiNGjJBly5bJKaecIvPnz5d27dqZtxyDwZyUgCkIhJrUhFruFJqYUyKAAAII5EiA+affxow6GduxY4ccffTR8swzz0i3bt1k2LBh7sXM+u+uXbu65Kp3795NLaDPgOkti2eeeabMnTu36f/Xd5XpLYmagJ166qnSoUOHXbZa82NKaVYGQylqHJM1gVCTmlDLnbX2pzwIIIAAAmEJMP/0215RJ2NK+8EHH7irXHo1a/369bL33nvL6NGj3XL3PXv23El/d8nY+PHj5e677y7YUg0NDQX3aWsHBkNZfBycEYFQk5pQy52RZqcYCCCAAAKBCjD/9Ntw0SdjfnltozMYbD2Jlo7ANtkmnaWzO3m91Eu1/P/twVnfNBmrkRpXTK1DKOXOuivlQwABBBDItgDzT7/tQzLm19c0OoPBlJNgKQlskk1NSU1KRSj7tCRjZRMSAAEEEEAgEAHmn34bimTMr69pdAaDKSfBUhIIPRkbIkOkTuqkSmxXS02pOTgtAggggAACbQow//TbQUjG/PqaRmcwmHISLCWBBmmQzbLZnb2jdAwuqQmxzCk1NadFAAEEEMiBAPNPv41IMubX1zQ6g8GUk2AIIIBAJgVYLCaTzUKhEIhWgPmn36YnGfPraxqdwWDKSTAEEEAgkwIkY5lsFgqFQLQCzD/9Nj3JmF9f0+gMBlNOgiGAAAKZFCAZy2SzUCgEohVg/um36UnG/PqaRmcwmHISDAEEEMikAMlYJpuFQiEQrQDzT79NTzLm19c0OoPBlJNgCCCAQCYENPlqvjV/p92u3sXHO+4y0WwUAoFoBJh/+m1qkjG/vqbRGQymnARDAAEEMiGQ9DUJuiIpGwIIIFApAeaffqVJxvz6mkZnMJhyEgwBBBDIhADJWCaagUIggMBuBJh/+u0aJGN+fU2jMxhMOQmGAAIIZEKA2xQz0QwUAgEESMZS6QMkY6mwl3ZSkrHS3DgKAQQQCEmABTxCai3KikD+BZh/+m1jkjG/vqbRGQymnARDAAEEMilAMpbJZqFQCEQrwPzTb9OTjPn1NY3OYDDlJBgCCCCQSQGSsUw2C4VCIFoB5p9+m55kzK+vaXQGgyknwRBAAIFMCpCMZbJZKBQC0Qow//Tb9CRjfn1NozMYTDkJhgACCCCAAAIIIFBAgPmn3y5CMubX1zQ6g8GUk2AIIIAAAggggAACJGOp9gGSsVT5k52cZCyZF3sjgAACCCCAAAIIlCfA/LM8v0JHk4wVEsrQ3xkMGWoMioIAAggggAACCEQgwPzTbyOTjPn1NY3OYDDlJBgCCCCAAAIIIIBAAQHmn367CMmYX1/T6AwGU06CIYAAAggggAACCJCMpdoHSMZS5U92cpKxZF7sjQACCCCAAAIIIFCeAPPP8vwKHU0yVkgoQ39nMGSoMSgKAggggAACCCAQgQDzT7+NTDLm19c0OoPBlJNgCCCAAAIIIIAAAgUEmH/67SIkY359TaMzGEw5CYYAAggggAACCCBAMpZqHyAZS5U/2clJxpJ5sTcCCCCAAAIIIIBAeQLMP8vzK3Q0yVghoQz9ncGQocagKAgggAACCCCAQAQCzD/9NjLJmF9f0+gMBlNO02AN0iDbZbtpzEoH6ygdpUqqKn1azocAAggggAACGRZg/um3cUjG/PqaRmcwmHKaBdNEbKgMlaWy1CxmGoGGyBCpkzoSsjTwOScCCCCAAAIZFWD+6bdhSMb8+ppGZzCYcpoFe1/el07SySxemoG2yTapluo0i8C5EUAAAQQQQCBDAsw//TYGyZhfX9PoDAZTTrNgzZOxeqkPLpnR8tdIjfMgGTPrFgRCAAEEEEAgFwLMP/02I8mYX1/T6AwGU06zYM2TsRCTmdDLb9aQBEIAAQQQQACBVgLMP/12CpIxv76m0RkMppxmwUJPZkIvv1lDEggBBBBAAAEESMYq3AdIxioMXs7pSMbK0fN3bOjJTOjl99eyREYAAQQQQAAB5p9++wDJmF9f0+gMBlNOs2ChJzOhl9+sIQmEAAIIIIAAAlwZq3AfIBmrMHg5pyMZK0fP37GhJzOhl99fyxIZAQQQQAABBJh/+u0DJGN+fU2jMxhMOc2ChZ7MhF5+s4YkEAIIIIAAAghwZazCfYBkrMLg5ZyOZKwcPX/Hhp7MhF5+fy1LZAQQQAABBBBg/um3D5CM+fU1jc5gMOU0CxZ6MhN6+c0akkAIIIAAAgggwJWxCvcBkrEKg5dzOpKxcvT8HRt6MhN6+f21LJERQAABBBBAgPmn3z5AMubX1zQ6g8GU0yxY6MlM6OU3a0gCIYAAAggggABXxircB0jGKgxezulIxsrR83ds6MlM6OX317JERgABBBBAAAHmn377AMmYX1/T6AwGU06zYNtkm3SWzi5evdRLtVSbxa5EIE3GaqTGnUrrElr5K2HEORBAAAEEEIhVgPmn35YnGfPraxqdwWDKaRZsk2xqSmbMgqYUiGQsJXhOiwACCCCAQEYFmH/6bRiSMb++ptEZDKacZsHykowNkSFSJ3VSJVVmNgRCAAEEEEAAgbAFmH/6bT+SMb++ptEZDKacZsEapEE2y2YXr6N0DDaZCbnsZo1JIAQQQAABBBDYSYD5p98OQTLm19c0OoPBlJNgCCCAAAIIIIAAAgUEmH/67SIkY359TaMzGEw5CYYAAggggAACCCBAMpZqHyAZS5U/2clJxpJ5sTcCCCCAAAIIIIBAeQLMP8vzK3Q0yVghoQz9ncGQocagKAgggAACCCCAQAQCzD/9NjLJmF9f0+gMBlNOgiGAAAIIIIAAAggUEGD+6beLkIz59TWNzmAw5SQYAggggAACCCCAAMlYqn2AZCxV/mQnJxlL5sXeCCCAAAIIIIAAAuUJMP8sz6/Q0SRjhYQy9HcGQ4Yag6IggAACCCCAAAIRCDD/9NvIJGN+fU2jMxhMOQmGAAIIIIAAAgggUECA+affLkIy5tfXNDqDwZQzN8EapEG2y/bc1CdJRTpKR6mSqiSHsC8CCCCAAAIIJBBg/pkAq4RdScZKQEvrEAZDWvLZPa8mYkNlqCyVpdktpMeSDZEhUid1JGQejQmNAAIIIBC3APNPv+1PMubX1zQ6g8GUMxfB3pf3pZN0ykVdSq3ENtkm1VJd6uEchwACCCCAAAJtCDD/9Ns9SMb8+ppGZzCYcuYiWPNkrF7qo0lKtN41UuPakGQsF12ZSiCAAAIIZFSA+affhiEZ8+trGp3BYMqZi2DNk7GYkpJY652LTkslEEAAAQSCEmD+6be5SMb8+ppGZzCYcuYiWKxJSaz1zkWnpRIIIIAAAkEJMP/021wkY359TaMzGEw5cxEs1qQk1nrnotNSCQQQQACBoASYf/ptLpIxv76m0RkMppy5CBZrUhJrvXPRaakEAggggEBQAsw//TYXyZhfX9PoDAZTzlwEizUpibXeuei0VAIBBBBAICgB5p9+m4tkzK+vaXQGgylnLoLFmpTEWu9cdFoqgQACCCAQlADzT7/NRTLm19c0OoPBlDMXwWJNSmKtdy46LZVAAAEEEAhKgPmn3+YiGfPraxqdwWDKmYtgsSYlsdY7F52WSiCAAAIIBCXA/NNvc5GM+fU1jc5gMOXMRbBYk5JY652LTkslEEAAAQSCEmD+6be5SMb8+ppGZzCYcuYiWKxJSaz1zkWnpRIIIIAAAkEJMP/021wkY359TaMzGEw5cxEs1qQk1nrnotNSCQQQQACBoASYf/ptLpIxv76m0RkMppy5CBZrUhJrvXPRaakEAggggEBQAsw//TYXyZhfX9PoDAZTzlwEizUpibXeuei0VAIBBBBAICgB5p9+m4tkzK+vaXQGgylnLoLFmpTEWu9cdFoqgQACCCAQlADzT7/NRTLm19c0OoPBlDMXwWJNSmKtdy46LZVAAAEEEAhKgPmn3+YiGfPraxqdwWDKmYtgsSYlsdY7F52WSiCAAAIIBCXA/NNvc5GM+fU1jc5gMOXMRbBYk5JY652LTkslEEAAAQSCEmD+6be5SMb8+ppGZzCYcuYiWKxJSaz1zkWnpRIIIIAAAkEJMP/021wkY359TaMzGEw5cxEs1qQk1nrnotNSCQQQQACBoASYf/ptLpIxv76m0RkMppy5CBZrUhJrvXPRaakEAggggEBQAsw//TYXyZhfX9PoDAZTzlwEizUpibXeuei0VAIBBBBAICgB5p9+m4tkzK+vaXQGgylnLoLFmpTEWu9cdFoqgQACCCAQlADzT7/NRTLm19c0OoPBlDMXwWJNSmKtdy46LZVAAAEEEAhKgPmn3+YiGfPraxqdwWDKmYtgsSYlsdY7F52WSiCAAAIIBCXA/NNvc5GM+fU1jc5gMOXMRbBYk5JY652LTkslEEAAAQSCEmD+6be5SMb8+ppGZzCYcuYiWKxJSaz1zkWnpRIIIIAAAkEJMP/021wkY359TaMzGEw5cxEs1qQk1nrnotNSCQQQQACBoASYf/ptLpIxv76m0RkMppy5CBZrUhJrvXPRaakEAggggEBQAsw//TYXyZhfX9PoDAZTzlwEizUpibXeuei0VAIBBBBAICgB5p9+m4tkzK+vaXQGgylnLoJtk23SWTq7utRLvVRLdS7qVagSmozVSI3bTQ1iqXchF/6OAAIIIICAtQDzT2vRneORjPn1NY3OYDDlzEWwTbKpKSnJRYVKqATJWAloHIIAAggggECRAsw/i4QqcTeSsRLh0jiMwZCGerbPGXsyNkSGSJ3USZVUZbuhKB0CCCCAAAKBCjD/9NtwJGN+fU2jMxhMOXMRrEEaZLNsdnXpKB2jS0pirHMuOi6VQAABBBAIRoD5p9+mIhnz62sancFgykkwBBBAAAEEEEAAgQICzD/9dhGSMb++ptEZDKacBEMAAQQQQAABBBAgGUu1D5CMpcqf7OQkY8m82BsBBBBAAAEEEECgPAHmn+X5FTqaZKyQUIb+zmDIUGNQFAQQQAABBBBAIAIB5p9+G5lkzK+vaXQGgyknwRBAAAEEEEAAAQQKCDD/9NtFSMb8+ppGZzCYchIMAQQQQAABBBBAgGQs1T5AMpYqf7KTk4wl82JvBBBAAAEEEEAAgfIEmH+W51foaJKxQkIZ+juDIUONQVEQQAABBBBAAIEIBJh/+m3k6JOxHTt2yPTp02XBggXy+uuvS5cuXWT06NFy9dVXS48ePRLpv/vuuzJ16lS5//77ZePGjbL//vvLiSeeKFdddZXstddeiWLtamcGQ9mEBEAAAQQQQAABBBBIIMD8MwFWCbtGnYxpIjZixAhZunSpdOvWTYYNGybr1q2T5cuXy7777itPP/209OrVqyjWLVu2yBFHHCFr1qyRgw8+WAYNGiQvvvii+693796ybNky6dq1a1GxdrcTg6EsPg5GAAEEEEAAAQQQSCjA/DMhWMLdo07GrrzySrnmmmtcErVkyRLp1KmT45s5c6bU1tbK8OHD5cknnyyK9IwzzpB58+bJSSedJPfdd5+0b9/eHXfhhRfKLbfcIvr3u+++u6hYJGNlMXEwAggggAACCCCAgJEAyZgR5G7CRJuMffzxx7LffvuJ3lq4YsUK6d+//05Ehx12mLzwwgvy7LPPysCBA9tsBb0lsXv37tKuXTtZv3691NTUNO3/4YcfSs+ePeXtt9+WN954Y6e/JW1aBkNSMfZHAAEEEEAAAQQQKEeA+Wc5eoWPjTYZe+KJJ+SYY45xtyGuXbu2lZReMdMrZ1OmTHHPgbW13XXXXXLWWWe5Wx4ff/zxVrueffbZcuedd4ruN378+MKtsps9GAwl03EgAggggAACCCCAQAkCzD9LQEtwSLTJ2I033iiTJ0+WcePGycKFC1uRLV68WMaMGeMW4NAFOdraLr74Yrnpppvk0ksvleuvv77Vrrfddpucf/75ovvNmjUrQfPsvCuDoWQ6DkQAAQQQQAABBBAoQYD5ZwloCQ6JNhm75JJLXGKkCZk+I9ZyW7lypfTr108GDBggzz33XJuk+pyYJmyakOkzYi23Bx980CV1ut+iRYsSNA/JWMlYHIgAAggggAACCCBQtgDJWNmEbQaINhmbNGmS3HHHHXL55ZfLtdde2wpJb13s06eP9O3bV15++eU2EY899lh57LHHXLxzzjmn1b566+KoUaNE93v00UcLtmhjp2+540svvSQdOnQoeoXHgidiBwQQQAABBBBAAAEE2hB45ZVX3Pzzvffew8mDQLTJ2MSJE2X27NlyxRVXuBUVW266RL0mYsUkY5poacKl8fT5sJabJmqaiJWbjK1evVr22GMPOeSQQzx0BUKGLKAflLoV+yqGkOtK2YsXoF8UbxXbnvSN2Fq8uPrSL4pzim0vvRhQVVUln3zySWxVr0h9o03GuE2xIv2Lk1RIgFsIKgQd2GnoF4E1WAWLS9+oIHZAp6JfBNRYFSwq/cIvdrTJGAt4+O1YRK+sAB+UlfUO5Wz0i1BaqvLlpG9U3jyEM9IvQmilypeRfuHXPNpkrNil7XV5+6uuuqrNVih2aXtd3n7ChAkltyiDoWS63B9I38h9E5dUQfpFSWxRHETfiKKZE1eSfpGYLIoD6Bd+mznaZOyjjz5yL33eunVrmy99Xr58uQwePLjNVnjzzTelR48e0r59e/fSZ43buDW+9HnLli3upc/7779/yS3KYCiZLvcH0jdy38QlVZB+URJbFAfRN6Jo5sSVpF8kJoviAPqF32aONhlTVl28Y9q0aXLkkUfKkiVLpLq62mnrUve1tbUydOhQqaura2qBW2+9VfS/sWPHyvTp03dqmdNPP13uueceOfnkk+Xee+91iZluF110kdx8882if583b15ZrclgKIsv1wfTN3LdvCVXjn5RMl3uD6Rv5L6JS6og/aIkttwfRL/w28RRJ2M7duyQo48+Wp555hnp1q2bDBs2TF577TX3765du8qyZcukd+/eTS0wdepUd8vimWeeKXPnzt2pZd566y05/PDDRVci0hXtBg0aJC+++KKsWrXK/Vtj7bPPPmW1JoOhLL5cH0zfyHXzllw5+kXJdLk/kL6R+yYuqYL0i5LYcn8Q/cJvE0edjCntBx984K5yzZ8/391iuPfee8vo0aPdcvc9e/bcSb+tZEwNNTQsAAARCklEQVR3fOedd2TKlCnywAMPSH19vdTU1MgJJ5zgErguXbr4bUmiI4AAAggggAACCCCAQFAC0SdjQbUWhUUAAQQQQAABBBBAAIHcCJCM5aYpqQgCCCCAAAIIIIAAAgiEJEAyFlJrUVYEEEAAAQQQQAABBBDIjQDJWG6akooggAACCCCAAAIIIIBASAIkYyG1FmVFAAEEEEAAAQQQQACB3AiQjOWmKakIAggggAACCCCAAAIIhCRAMpZia+l7znRZ/QULFsjrr7/ulr/XZfWvvvpq6dGjR6KSvfvuu6JL799///2yceNG2X///eXEE090y+rvtddeiWKxc/oCFn1D+8TDDz8sDz30kDz//PPuHXp77LGHHHrooXLaaafJeeedJx06dEi/spSgaAGLfrGrk61Zs0a+8pWviMY/7rjj5JFHHim6TOyYvoB1v1i7dq38/Oc/l8cee8x9n3Tu3Fn69OkjY8eOlUsvvTT9ClOCogUs+4Z+Ltx0003y97//XbZu3epeBfTVr35VJk+eLCNGjCi6TOyYrsBzzz3nxvby5cvde3U3bNggn/nMZ9znfykb889S1HY+hmSsfMOSImin1w+vpUuXNr1wet26dW5w7LvvvvL000+7l0UXs23ZskWOOOII0QnVwQcf3PTCaX3ptL60Wl84rS+xZgtDwKpvXHHFFTJt2jSXgPXv39/1hc2bN8tTTz0lH374oQwdOlQeffRR6dixYxgwkZfSql/sivGYY46Rv/71r9LQ0EAyFlg/s+4X+oOe/lijnxH6udG3b1/R75h//vOfUl1dLZqosYUhYNk3Zs6cKbW1tVJVVSVDhgyR7t27y3/+8x+XmOn2y1/+Un7wgx+EARN5KfWH+gcffHAnhVKTMeafNp2JZMzGMXGUK6+80r1YWpOoJUuWSKdOnVyMxg+84cOHy5NPPllU3DPOOEPmzZsnJ510ktx3333Svn17d9yFF14ot9xyi+jf77777qJisVP6AlZ9Y8aMGfLee++5K2D6xdm4adI+cuRIdzX2sssuk+uuuy79SlOCggJW/aLliebMmSPnnHOOTJo0SX7961+TjBVsiWztYNkvVq5c6a506JWwBx54wP1g07h9+umnsmLFCvdjH1sYAlZ9Q3/Ea7xb589//vNO/WLRokUybtw4+dznPif19fVNc5kwhOIspV713r59uwwePNj9p3dSlZqMMf+06UMkYzaOiaJ8/PHHst9++4le2tUvN/31sfl22GGHyQsvvCDPPvusDBw4sM3YeguJTrTbtWsn69evl5qamqb99ZfNnj17yttvvy1vvPHGTn9LVGB2rpiAZd9oq9B6a6z++n3QQQfJq6++WrH6caLSBHz1i02bNskhhxziPmcuv/xy+frXv04yVloTpXKUdb/QHwHr6urkj3/8o4wZMyaVOnFSGwHLvqG3uh9//PHuMYo//elPrQrYr18/0UReb3nTZJ4tLAG92llKMsb8066dScbsLIuO9MQTT4jeFqS3Ie7qlg+9Yqa/aE2ZMsU9B9bWdtddd8lZZ53lbnl8/PHHW+169tlny5133im63/jx44suIzumI2DZN9qqwerVq+XLX/6y7Lnnnu52JLZsC/jqF9/5znfc7Sp6C9p///tfkrFsd4NWpbPsF//617/c86R6W+LLL78cmATFbSlg2Tf0+aJjjz22YDKmd13o7fBsYQmUmowx/7RrZ5IxO8uiI914443ugVe9tL9w4cJWxy1evNj9Kqn39er9+21tF198sXugVh+qvv7661vtetttt8n5558vut+sWbOKLiM7piNg2TfaqkHjL50HHnigW9iDLdsCPvqFLu7yzW9+0y0Y9LOf/cw9M8aVsWz3g5als+wXt956q1xwwQXywx/+UG644QZ3y7venaETNV3c5ZRTTpHPf/7zYQFFXFrLvqF38ehdFB988IG0vE3xD3/4g3z72992j1zo88hs4QmUmowx/7Rra5IxO8uiI11yySUuMdKETJ8Ra7np5X697D9gwADRVW/a2vQ5MU3YNCHTZ8RabvqrtyZ1up/e282WbQHLvtFWTUeNGuWupOrk6+abb842CqUT637x/vvvuyujn/3sZ90t0XqFlGQsvI5m2S/OPfdcuf322+VHP/qRu02x5dWxffbZx32H6K2MbNkXsOwbWtvf//738t3vflf09sfGBTz0FnddwENvX5w7d657/IItPIFSkzHmn3ZtTTJmZ1l0JH1Q/o477nDPaFx77bWtjtNbF3UZ4WJuF9FbB/QWAo2nD+G33HTCrRNv3U9XzmPLtoBl39hdTXXCpRMvfeWBrrh5wAEHZBuF0rnFNaw+M5RTfwjSX87/8pe/uKthupGMhdfRLPuF3rLauACULln+q1/9yt1Or4sy6CtS5s+f75Yy18+Mbt26hYcVWYkt+0YjnX5enHrqqfLWW281aepz6prA62eKPrvOFp5AqckY80+7tiYZs7MsOtLEiRNl9uzZokuP6/NhLTe971oTsWKSscYrHBpPnw9ruTXe600yVnTzpLqjZd/YVUV0hU7tC/rrpv7Kre8NYsu+gGW/0FvPDj/8cPcrd/NVVknGst8PWpbQsl/obfN69UM3/eFOPyeab7owg14F2d2PiOHp5bvEln1DpX7xi1/Ij3/8Y3enjT7Lrq/R0aXt9fl2XXnz5JNPbuo/+ZbNX+1KTcaYf9r1BZIxO8uiI1nePsBl4qLZg9jRsm+0rLDejnbUUUe5VTz11kS9RZEtDAGrfvHJJ5+4pYz1tQYvvfSSe6dh40YyFkZfaF5Kq36hMXUhKH0gX1fn1cVcWm76Hil9TYbeova3v/0tPKzISmzZN/RHvKOPPto9OqEJub67snH73//+5z5T/vGPf+wyiY+MPcjqlpqMMf+0a26SMTvLoiNZPljLA5RFswexo2XfaF7hV155xb0bRpei1V81daVOtnAErPqFvlj+i1/8onuvzJe+9KWdADRJ1+dV9VY0XbBB332oC72wZVfAql9oDXUhF/1cOPLII3e5EIMuaf6Nb3zD3UL/73//O7solMwJWPaNxlWZ9bEKvTLactP/XxcB4r2VYXa+UpMx5p927U0yZmdZdKRil5zVy/96r35bW7FLi+ry9hMmTCi6jOyYjoBl32iswYYNG1wipg9bX3TRRe5Lmi0sAat+0ZiMFVP7L3zhC+4qKlt2Baz6hdZQF+341re+5d47p8vct9x++9vfyve+9z33Xkx9PyZbtgUs+8Zxxx0nS5Ys2e0dFXqnhX63fP/733eLwLCFJVBqMsb8066dScbsLIuO9NFHH7lVh7Zu3drmS5+XL1/uLv+3tb355pvSo0cPad++vXvpc/PVjBpf+rxlyxb30mf9NZwt2wKWfUNr+s4777jVz1atWuWS8Tlz5rilqtnCErDuF7uqPbcphtUntLSW/WL79u3u+0Nj6pX0nj177gSiC0Tp54deJdFnlNmyLWDZN84880z5zW9+I2ecccZOz5k2CmiSrsn69OnT5Sc/+Um2YShdK4FSkzHmn3adiWTMzjJRJF28Y9q0ae6WEP3Fqbq62h2vS93X1ta6Kxl1dXVNMfUdMPqfLrigH3jNt9NPP13uuece9wDtvffe6xIz3fSXKv3FSv8+b968ROVj5/QErPqGTq70ZeDLli1z7wjS1dBY7Sq9di33zFb9YnflIBkrt4XSOd6yX+htZjNmzHDvn9OVFRu/lx555BE5/vjjRZ8P0s8TXcyDLfsCVn1DX5+jzwfp94f+b+0LjZu+Pkf/ptvq1atb3f6cfSVKWCgZY/7pv4+QjPk33uUZduzY4R6IfeaZZ9wywcOGDXMv39V/d+3a1X3hNX+TvT7no7cs6i9U+j6P5psuM6uro+mvmb169ZJBgwa55Yf1aoj+W2PpO2LYwhCw6huNy5frF6guR9yhQ4ddArTsT2EoxVdKq35BMpavvmPZLzTWyJEj3TNj+r30ta99TTZt2uS+Qz799FP3A+JPf/rTfAHmuDZWfaOhocF9h/zud79zWjrH0GdP9dZ3XZ1VN/pGOB1p8eLFO63krfNOTcia/8iizwDqjzK6Mf/037YkY/6Nd3sGfZu9XuXSKxZ6i6E+OK8vT9Tl7lveItLWYNAT6O1o+vC1LjGr74XRd3+ccMIJLoHr0qVLirXk1KUIWPSN8ePH7/KWkpbl0S9atjAELPoFyVgYbZ2klJb9Qm9vu+GGG9xtZ7p0ub4YXCff+uNO4+QsSdnYN10Bq76h3xP6jJC+DkNX5t22bZt7V6VO4HVlXp27sIUhoD/AFlpDQNta5xCFkjHmnzZtTjJm40gUBBBAAAEEEEAAAQQQQCCRAMlYIi52RgABBBBAAAEEEEAAAQRsBEjGbByJggACCCCAAAIIIIAAAggkEiAZS8TFzggggAACCCCAAAIIIICAjQDJmI0jURBAAAEEEEAAAQQQQACBRAIkY4m42BkBBBBAAAEEEEAAAQQQsBEgGbNxJAoCCCCAAAIIIIAAAgggkEiAZCwRFzsjgAACCCCAAAIIIIAAAjYCJGM2jkRBAAEEEEAAAQQQQAABBBIJkIwl4mJnBBBAAAEEEEAAAQQQQMBGgGTMxpEoCCCAAAIIIIAAAggggEAiAZKxRFzsjAACCCCAAAIIIIAAAgjYCJCM2TgSBQEEEEAAAQQQQAABBBBIJEAyloiLnRFAAAEEEEAAAQQQQAABGwGSMRtHoiCAAAIIIIAAAggggAACiQRIxhJxsTMCCCCAAAIIIIAAAgggYCNAMmbjSBQEEEAAAQQQQAABBBBAIJEAyVgiLnZGAAEEEEAAAQQQQAABBGwESMZsHImCAAIIIIAAAggggAACCCQSIBlLxMXOCCCAAAIIIIAAAggggICNAMmYjSNREEAAAQQQQAABBBBAAIFEAiRjibjYGQEEEEAAAQQQQAABBBCwESAZs3EkCgIIIIAAAggggAACCCCQSIBkLBEXOyOAAAIIIIAAAggggAACNgIkYzaOREEAAQQQQAABBBBAAAEEEgmQjCXiYmcEEEAAAQQQQAABBBBAwEaAZMzGkSgIIIAAAggggAACCCCAQCIBkrFEXOyMAAIIIIAAAggggAACCNgIkIzZOBIFAQQQQAABBBBAAAEEEEgkQDKWiIudEUAAAQQQQAABBBBAAAEbAZIxG0eiIIAAAggggAACCCCAAAKJBEjGEnGxMwIIIIAAAggggAACCCBgI0AyZuNIFAQQQAABBBBAAAEEEEAgkQDJWCIudkYAAQQQQAABBBBAAAEEbARIxmwciYIAAggggAACCCCAAAIIJBIgGUvExc4IIIAAAggggAACCCCAgI0AyZiNI1EQQAABBBBAAAEEEEAAgUQCJGOJuNgZAQQQQAABBBBAAAEEELARIBmzcSQKAggggAACCCCAAAIIIJBIgGQsERc7I4AAAggggAACCCCAAAI2AiRjNo5EQQABBBBAAAEEEEAAAQQSCZCMJeJiZwQQQAABBBBAAAEEEEDARoBkzMaRKAgggAACCCCAAAIIIIBAIgGSsURc7IwAAggggAACCCCAAAII2AiQjNk4EgUBBBBAAAEEEEAAAQQQSCRAMpaIi50RQAABBBBAAAEEEEAAARsBkjEbR6IggAACCCCAAAIIIIAAAokESMYScbEzAggggAACCCCAAAIIIGAjQDJm40gUBBBAAAEEEEAAAQQQQCCRAMlYIi52RgABBBBAAAEEEEAAAQRsBEjGbByJggACCCCAAAIIIIAAAggkEiAZS8TFzggggAACCCCAAAIIIICAjQDJmI0jURBAAAEEEEAAAQQQQACBRAL/By1g+S17ro2TAAAAAElFTkSuQmCC\" width=\"578\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "knefmnn_clf.draw_hyperbox_and_boundary(\"The trained KNEFMNN classifier and its decision boundaries\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of existing hyperboxes = 51\n"
     ]
    }
   ],
   "source": [
    "print(\"Number of existing hyperboxes = %d\"%(knefmnn_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 =  86.60%\n"
     ]
    }
   ],
   "source": [
    "y_pred = knefmnn_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 = knefmnn_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 = 0.964263\n",
      "Class 2 has the maximum membership value = 0.990050\n",
      "Class 1 has the representative hyperbox: V = [0.58339 0.3649 ] and W = [0.66091    0.38616125]\n",
      "Class 2 has the representative hyperbox: V = [0.57285 0.27229] and W = [0.66773 0.36489]\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=\"594\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "knefmnn_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",
    "knefmnn_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/knefmnn_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/knefmnn_par_cord.html\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x2bdffd230f0>"
      ]
     },
     "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/knefmnn_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
}