docs/tutorials/efmnn_general_use.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Enhanced Online Learning Algorithm for FMNN"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This example shows how to use the Simpson's Fuzzy Min-Max Neural Network trained by an enhanced online learning algorithm (EFMNN)\n",
    "\n",
    "Note that the numerical features in training and testing datasets must be in the range of [0, 1] because the EFMNN classifiers require features in the unit cube."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Execute directly from the python file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Get the path to the this jupyter notebook file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\hyperbox-brain\\\\docs\\\\tutorials'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "this_notebook_dir = os.path.dirname(os.path.abspath(\"__file__\"))\n",
    "this_notebook_dir"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Get the home folder of the Hyperbox-Brain project"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "WindowsPath('C:/hyperbox-brain')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pathlib import Path\n",
    "project_dir = Path(this_notebook_dir).parent.parent\n",
    "project_dir"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Create the path to the Python file containing the implementation of the FMNN using the enhanced online learning algorithm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\hyperbox-brain\\\\hbbrain\\\\numerical_data\\\\incremental_learner\\\\efmnn.py'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "efmnn_file_path = os.path.join(project_dir, Path(\"hbbrain/numerical_data/incremental_learner/efmnn.py\"))\n",
    "efmnn_file_path"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Run the found file by showing the execution directions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "usage: efmnn.py [-h] -training_file TRAINING_FILE -testing_file TESTING_FILE\n",
      "                [--theta THETA] [--gamma GAMMA] [--is_draw IS_DRAW]\n",
      "\n",
      "The description of parameters\n",
      "\n",
      "required arguments:\n",
      "  -training_file TRAINING_FILE\n",
      "                        A required argument for the path to training data file\n",
      "                        (including file name)\n",
      "  -testing_file TESTING_FILE\n",
      "                        A required argument for the path to testing data file\n",
      "                        (including file name)\n",
      "\n",
      "optional arguments:\n",
      "  --theta THETA         Maximum hyperbox size (in the range of (0, 1])\n",
      "                        (default: 0.5)\n",
      "  --gamma GAMMA         A sensitivity parameter describing the speed of\n",
      "                        decreasing of the membership function in each\n",
      "                        dimension (larger than 0) (default: 1)\n",
      "  --is_draw IS_DRAW     Show the existing hyperboxes during the training\n",
      "                        process on the screen (default: False)\n"
     ]
    }
   ],
   "source": [
    "!python \"{efmnn_file_path}\" -h"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Create the path to training and testing datasets stored in the dataset folder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\hyperbox-brain\\\\dataset\\\\syn_num_train.csv'"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "training_data_file = os.path.join(project_dir, Path(\"dataset/syn_num_train.csv\"))\n",
    "training_data_file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\hyperbox-brain\\\\dataset\\\\syn_num_test.csv'"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "testing_data_file = os.path.join(project_dir, Path(\"dataset/syn_num_test.csv\"))\n",
    "testing_data_file"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Run a demo program"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of hyperboxes = 77\n",
      "Testing accuracy =  85.80%\n"
     ]
    }
   ],
   "source": [
    "!python \"{efmnn_file_path}\" -training_file \"{training_data_file}\" -testing_file \"{testing_data_file}\" --theta 0.1 --gamma 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Using the EFMNN through its init, fit, and predict functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "from hbbrain.numerical_data.incremental_learner.efmnn import EFMNNClassifier\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Create training and testing data sets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train = pd.read_csv(training_data_file, header=None)\n",
    "df_test = pd.read_csv(testing_data_file, header=None)\n",
    "\n",
    "Xy_train = df_train.to_numpy()\n",
    "Xy_test = df_test.to_numpy()\n",
    "\n",
    "Xtr = Xy_train[:, :-1]\n",
    "ytr = Xy_train[:, -1]\n",
    "\n",
    "Xtest = Xy_test[:, :-1]\n",
    "ytest = Xy_test[:, -1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Initializing parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "theta = 0.1\n",
    "gamma = 1\n",
    "is_draw = True"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
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       "    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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       "\n",
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       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
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       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
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       "\n",
       "\n",
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       "\n",
       "\n",
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       "\n",
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       "    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=\"538\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "EFMNNClassifier(C=array([1, 2, 1, 1, 1, 2, 1, 2, 2, 1, 2, 2, 2, 2, 1, 1, 2, 2, 1, 1, 2, 1,\n",
       "       1, 2, 2, 2, 2, 2, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2,\n",
       "       1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 2, 2, 2, 1, 2,\n",
       "       2, 1, 1, 2, 1, 2, 2, 1, 2, 1, 2]),\n",
       "                V=array([[0.42413   , 0.53516   ],\n",
       "       [0.74088   , 0.43310562],\n",
       "       [0.91059   , 0.82085   ],\n",
       "       [0.64586   , 0.50818437],\n",
       "       [0.4713    , 0.672     ],\n",
       "       [0.33484   , 0.18424   ],\n",
       "       [0.32289   , 0.59994   ],\n",
       "       [0.19944   , 0.03      ],\n",
       "       [0.28077   , 0.26124...\n",
       "       [0.36842   , 0.77238   ],\n",
       "       [0.36057   , 0.71561   ],\n",
       "       [0.6733    , 0.29485   ],\n",
       "       [0.25621   , 0.62174   ],\n",
       "       [0.14737   , 0.28498   ],\n",
       "       [0.72496   , 0.34978   ],\n",
       "       [0.73681   , 0.71261   ],\n",
       "       [0.76138   , 0.32629   ],\n",
       "       [0.52124   , 0.41288   ],\n",
       "       [0.42647   , 0.66846   ],\n",
       "       [0.91185   , 0.48697   ],\n",
       "       [0.29163   , 0.086547  ],\n",
       "       [0.35813   , 0.58584   ],\n",
       "       [0.56487   , 0.17003   ],\n",
       "       [0.287     , 0.46814   ],\n",
       "       [0.44575   , 0.64683   ],\n",
       "       [0.25924   , 0.42696   ],\n",
       "       [0.77398   , 0.5357    ],\n",
       "       [0.68469   , 0.2221    ]]),\n",
       "                is_draw=True, theta=0.1)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "efmnn_clf = EFMNNClassifier(theta=theta, gamma=gamma, is_draw=is_draw)\n",
    "efmnn_clf.fit(Xtr, ytr)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### The code below shows how to display decision boundaries among classes if input data are 2-dimensional"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"560.6666666666666\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "efmnn_clf.draw_hyperbox_and_boundary(\"The trained FMNNN and its decision boundaries\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of existing hyperboxes = 77\n"
     ]
    }
   ],
   "source": [
    "print(\"Number of existing hyperboxes = %d\"%(efmnn_clf.get_n_hyperboxes()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import accuracy_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy =  85.80%\n"
     ]
    }
   ],
   "source": [
    "y_pred = efmnn_clf.predict(Xtest)\n",
    "acc = accuracy_score(ytest, y_pred)\n",
    "print(f'Accuracy = {acc * 100: .2f}%')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Explaining the predicted result for the input sample by showing membership values and hyperboxes for each class"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "sample_need_explain = 10\n",
    "y_pred_input_0, mem_val_classes, min_points_classes, max_points_classes = efmnn_clf.get_sample_explanation(Xtest[sample_need_explain])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted class for sample X = [0.571640, 0.233700] is 2 and real class is 2\n"
     ]
    }
   ],
   "source": [
    "print(\"Predicted class for sample X = [%f, %f] is %d and real class is %d\" % (Xtest[sample_need_explain, 0], Xtest[sample_need_explain, 1], y_pred_input_0, ytest[sample_need_explain]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Membership values:\n",
      "Class 1 has the maximum membership value = 0.957157\n",
      "Class 2 has the maximum membership value = 0.995862\n",
      "Class 1 has the representative hyperbox: V = [0.55763 0.40507] and W = [0.58339 0.43813]\n",
      "Class 2 has the representative hyperbox: V = [0.57285 0.24904] and W = [0.66773 0.31638]\n"
     ]
    }
   ],
   "source": [
    "print(\"Membership values:\")\n",
    "for key, val in mem_val_classes.items():\n",
    "    print(\"Class %d has the maximum membership value = %f\" % (key, val))\n",
    "    \n",
    "for key in min_points_classes:\n",
    "    print(\"Class %d has the representative hyperbox: V = %s and W = %s\" % (key, min_points_classes[key], max_points_classes[key]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Show input sample and hyperboxes belonging to each class. In 2D, we can show rectangles or use parallel coordinates"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Using rectangles to show explanations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
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     "output_type": "display_data"
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\" width=\"568.6666666666666\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "efmnn_clf.show_sample_explanation(Xtest[sample_need_explain], Xtest[sample_need_explain], min_points_classes, max_points_classes, y_pred_input_0, \"2D\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Using parallel coordinates. This mode best fits for any dimensions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a parallel coordinates graph\n",
    "efmnn_clf.show_sample_explanation(Xtest[sample_need_explain], Xtest[sample_need_explain], min_points_classes, max_points_classes, y_pred_input_0, file_path=\"par_cord/efmnn_par_cord.html\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"820\"\n",
       "            height=\"520\"\n",
       "            src=\"https://uts-caslab.github.io/hyperbox-brain/docs/tutorials/par_cord/efmnn_par_cord.html\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x210cf663c18>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load parallel coordinates to display on the notebook\n",
    "from IPython.display import IFrame\n",
    "# We load the parallel coordinates from GitHub here for demostration in readthedocs\n",
    "# On the local notebook, we only need to load from the graph storing at 'par_cord/efmnn_par_cord.html'\n",
    "IFrame('https://uts-caslab.github.io/hyperbox-brain/docs/tutorials/par_cord/efmnn_par_cord.html', width=820, height=520)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}