examples/numerical_data/batch_learner/accel_agglo_gfmm_general_use.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# This example shows how to use the GFMM classifier using an accelerated agglomerative learning algorithm (AGGLO-2)"
   ]
  },
  {
   "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 AGGLO-2-GFMM classifiers require features in the unit cube."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Execute directly from the python file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Get the path to the this jupyter notebook file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\hyperbox-brain\\\\examples\\\\numerical_data\\\\batch_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 GFMM classifier using the accelerated agglomerative learning algorithm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\hyperbox-brain\\\\hbbrain\\\\numerical_data\\\\batch_learner\\\\accel_agglo_gfmm.py'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "accel_agglo_file_path = os.path.join(project_dir, Path(\"hbbrain/numerical_data/batch_learner/accel_agglo_gfmm.py\"))\n",
    "accel_agglo_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: accel_agglo_gfmm.py [-h] -training_file TRAINING_FILE -testing_file\n",
      "                           TESTING_FILE [--theta THETA] [--gamma GAMMA]\n",
      "                           [--min_simil MIN_SIMIL]\n",
      "                           [--simil_measure {mid,long,short}]\n",
      "                           [--asimil_type {min,max}] [--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",
      "  --min_simil MIN_SIMIL\n",
      "                        Mimimum similarity value so that two hyperboxes can be\n",
      "                        merged (in the range of [0, 1])(default: 0.5)\n",
      "  --simil_measure {mid,long,short}\n",
      "                        Type of similarity measure (default: mid)\n",
      "  --asimil_type {min,max}\n",
      "                        Type of handling asymmetric similarity matrix\n",
      "                        (default: max)\n",
      "  --is_draw IS_DRAW     Show the existing hyperboxes during the training\n",
      "                        process on the screen (default: False)\n"
     ]
    }
   ],
   "source": [
    "!python \"{accel_agglo_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 = 61\n",
      "Testing accuracy (using a probability measure for samples on the boundary) =  85.00%\n",
      "Testing accuracy (using a Manhattan distance for samples on the boundary) =  85.00%\n"
     ]
    }
   ],
   "source": [
    "!python \"{accel_agglo_file_path}\" -training_file \"{training_data_file}\" -testing_file \"{testing_data_file}\" --theta 0.1 --min_simil 0.5 --simil_measure \"short\" --asimil_type \"max\" --gamma 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Using the GFMM classifier with the accelerated agglomerative learning algorithm through its init, fit, and predict functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "from hbbrain.numerical_data.batch_learner.accel_agglo_gfmm import AccelAgglomerativeLearningGFMM\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",
    "min_simil = 0.5\n",
    "simil_measure = 'short'\n",
    "asimil_type = 'max'\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",
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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",
       "            fig.send_message(\"send_image_mode\", {});\n",
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       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\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",
       "    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",
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       "\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",
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       "            fig.request_resize(ui.size.width, ui.size.height);\n",
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       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
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       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
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       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
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       "            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",
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       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
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       "    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",
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       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"540.6666666666666\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "AccelAgglomerativeLearningGFMM(is_draw=True, simil_measure='short', theta=0.1)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "accel_agglo_gfmm_clf = AccelAgglomerativeLearningGFMM(theta=theta, min_simil=min_simil, simil_measure=simil_measure, asimil_type=asimil_type, gamma=gamma, is_draw=is_draw)\n",
    "accel_agglo_gfmm_clf.fit(Xtr, ytr)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### The code below shows how to display decision boundaries among classes if input data are 2-dimensional"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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    }
   ],
   "source": [
    "accel_agglo_gfmm_clf.draw_hyperbox_and_boundary(\"The trained GFMM classifier and its decision boundaries\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of existing hyperboxes = 61\n"
     ]
    }
   ],
   "source": [
    "print(\"Number of existing hyperboxes = %d\"%(accel_agglo_gfmm_clf.get_n_hyperboxes()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training time = 4.640643 (s)\n"
     ]
    }
   ],
   "source": [
    "print(\"Training time = %f (s)\"%accel_agglo_gfmm_clf.elapsed_training_time)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import accuracy_score\n",
    "from hbbrain.constants import MANHATTAN_DIS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy (using a probability measure for samples on the boundary) =  85.00%\n"
     ]
    }
   ],
   "source": [
    "y_pred = accel_agglo_gfmm_clf.predict(Xtest)\n",
    "acc = accuracy_score(ytest, y_pred)\n",
    "print(f'Accuracy (using a probability measure for samples on the boundary) = {acc * 100: .2f}%')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy (using a Manhattan distance for samples on the boundary) =  85.00%\n"
     ]
    }
   ],
   "source": [
    "y_pred = accel_agglo_gfmm_clf.predict(Xtest, MANHATTAN_DIS)\n",
    "acc = accuracy_score(ytest, y_pred)\n",
    "print(f'Accuracy (using a Manhattan distance for samples on the boundary) = {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": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "sample_need_explain = 10\n",
    "y_pred_input_0, mem_val_classes, min_points_classes, max_points_classes = accel_agglo_gfmm_clf.get_sample_explanation(Xtest[sample_need_explain], Xtest[sample_need_explain])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "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": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Membership values:\n",
      "Class 1 has the maximum membership value = 0.870180\n",
      "Class 2 has the maximum membership value = 0.961410\n",
      "Class 1 has the representative hyperbox: V = [0.66562 0.36352] and W = [0.66562 0.36352]\n",
      "Class 2 has the representative hyperbox: V = [0.57285 0.27229] and W = [0.61106 0.28476]\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": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"558.6666666666666\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "accel_agglo_gfmm_clf.show_sample_explanation(Xtest[sample_need_explain], Xtest[sample_need_explain], min_points_classes, max_points_classes, y_pred_input_0, \"2D\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Using parallel coordinates. This mode best fits for any dimensions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a parallel coordinates graph\n",
    "accel_agglo_gfmm_clf.show_sample_explanation(Xtest[sample_need_explain], Xtest[sample_need_explain], min_points_classes, max_points_classes, y_pred_input_0, file_path=\"iframe_figures/accel_agglo_gfmm_par_cord.html\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"820\"\n",
       "            height=\"500\"\n",
       "            src=\"iframe_figures/accel_agglo_gfmm_par_cord.html\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x12ef57cd048>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load result\n",
    "from IPython.display import IFrame\n",
    "IFrame('iframe_figures/accel_agglo_gfmm_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
}