examples/numerical_data/batch_learner/agglo_gfmm_general_use.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# This example shows how to use the GFMM classifier using an agglomerative learning algorithm with full similarity matrix (AGGLO-SM)"
   ]
  },
  {
   "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 GFMM classifiers with AGGLO-SM algorithm 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 agglomerative learning algorithm with full similarity matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\hyperbox-brain\\\\hbbrain\\\\numerical_data\\\\batch_learner\\\\agglo_gfmm.py'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agglo_sm_file_path = os.path.join(project_dir, Path(\"hbbrain/numerical_data/batch_learner/agglo_gfmm.py\"))\n",
    "agglo_sm_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: 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 \"{agglo_sm_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 = 63\n",
      "Testing accuracy (using a probability measure for samples on the boundary) =  85.10%\n",
      "Testing accuracy (using a Manhattan distance for samples on the boundary) =  85.10%\n"
     ]
    }
   ],
   "source": [
    "!python \"{agglo_sm_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 agglomerative learning algorithm with full similarity matrix through its init, fit, and predict functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "from hbbrain.numerical_data.batch_learner.agglo_gfmm import AgglomerativeLearningGFMM\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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       "        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",
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       "mpl.figure.prototype._init_header = function() {\n",
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       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
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       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
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       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
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       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
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       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
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       "\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",
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       "\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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       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
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       "        button.click(method_name, toolbar_event);\n",
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       "\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",
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       "        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",
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       "        var fmt = mpl.extensions[ind];\n",
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       "\n",
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       "    );\n",
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       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
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       "\n",
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       "\n",
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       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
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       "    fig.ondownload(fig, format);\n",
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       "\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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "AgglomerativeLearningGFMM(is_draw=True, simil_measure='short', theta=0.1)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agglo_gfmm_clf = AgglomerativeLearningGFMM(theta=theta, min_simil=min_simil, simil_measure=simil_measure, asimil_type=asimil_type, gamma=gamma, is_draw=is_draw)\n",
    "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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\" width=\"564\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "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 = 63\n"
     ]
    }
   ],
   "source": [
    "print(\"Number of existing hyperboxes = %d\"%(agglo_gfmm_clf.get_n_hyperboxes()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training time = 107.447257 (s)\n"
     ]
    }
   ],
   "source": [
    "print(\"Training time = %f (s)\"%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) =  85.10%\n"
     ]
    }
   ],
   "source": [
    "y_pred = 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) =  85.10%\n"
     ]
    }
   ],
   "source": [
    "y_pred = 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 = 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 = [0.57285 0.27229]\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": [
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\" width=\"568\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "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",
    "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/agglo_gfmm_par_cord.html\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"820\"\n",
       "            height=\"500\"\n",
       "            src=\"iframe_figures/agglo_gfmm_par_cord.html\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x1c3c8342390>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load result\n",
    "from IPython.display import IFrame\n",
    "IFrame('iframe_figures/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
}