fruitTest.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "fruits = pd.read_table('fruit_data_with_colors.txt')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>fruit_label</th>\n",
       "      <th>fruit_name</th>\n",
       "      <th>fruit_subtype</th>\n",
       "      <th>mass</th>\n",
       "      <th>width</th>\n",
       "      <th>height</th>\n",
       "      <th>color_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>apple</td>\n",
       "      <td>granny_smith</td>\n",
       "      <td>192</td>\n",
       "      <td>8.4</td>\n",
       "      <td>7.3</td>\n",
       "      <td>0.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>apple</td>\n",
       "      <td>granny_smith</td>\n",
       "      <td>180</td>\n",
       "      <td>8.0</td>\n",
       "      <td>6.8</td>\n",
       "      <td>0.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>apple</td>\n",
       "      <td>granny_smith</td>\n",
       "      <td>176</td>\n",
       "      <td>7.4</td>\n",
       "      <td>7.2</td>\n",
       "      <td>0.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>mandarin</td>\n",
       "      <td>mandarin</td>\n",
       "      <td>86</td>\n",
       "      <td>6.2</td>\n",
       "      <td>4.7</td>\n",
       "      <td>0.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2</td>\n",
       "      <td>mandarin</td>\n",
       "      <td>mandarin</td>\n",
       "      <td>84</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.6</td>\n",
       "      <td>0.79</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   fruit_label fruit_name fruit_subtype  mass  width  height  color_score\n",
       "0            1      apple  granny_smith   192    8.4     7.3         0.55\n",
       "1            1      apple  granny_smith   180    8.0     6.8         0.59\n",
       "2            1      apple  granny_smith   176    7.4     7.2         0.60\n",
       "3            2   mandarin      mandarin    86    6.2     4.7         0.80\n",
       "4            2   mandarin      mandarin    84    6.0     4.6         0.79"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fruits.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{1: 'apple', 2: 'mandarin', 3: 'orange', 4: 'lemon'}"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#create a mapping from fruit label to fruit name to make results easier to interpret\n",
    "lookup_fruit_name = dict(zip(fruits.fruit_label.unique(), fruits.fruit_name.unique()))\n",
    "lookup_fruit_name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Create train-test split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = fruits[['mass', 'width', 'height']]\n",
    "y = fruits['fruit_label']\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Examining the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\User\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:7: FutureWarning: pandas.scatter_matrix is deprecated, use pandas.plotting.scatter_matrix instead\n",
      "  import sys\n"
     ]
    },
    {
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       "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=\"899.9999804930258\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plotting a scatter matrix\n",
    "from matplotlib import cm\n",
    "X = fruits[['height', 'width', 'mass', 'color_score']]\n",
    "y = fruits['fruit_label']\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)\n",
    "cmap = cm.get_cmap('gnuplot')\n",
    "scatter = pd.scatter_matrix(X_train, c=y_train, marker='o', s=40, hist_kwds={'bins':15}, figsize=(9,9), cmap=cmap)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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": {
      "text/html": [
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\" width=\"639.9999861283738\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'color_score')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#plotting a 3d scatter plot\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "\n",
    "fig=plt.figure()\n",
    "ax=fig.add_subplot(111, projection = '3d')\n",
    "ax.scatter(X_train['width'], X_train['height'], X_train['color_score'], c=y_train, marker='o', s=100)\n",
    "ax.set_xlabel('width')\n",
    "ax.set_ylabel('height')\n",
    "ax.set_zlabel('color_score')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Create train_test split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "#For this example, we use the mass, width and height features of each fruit instance\n",
    "X = fruits[['mass', 'width', 'height']]\n",
    "y = fruits['fruit_label']\n",
    "\n",
    "#default is 75% / 25% train_test split\n",
    "X_train, X_test, y_test, y_train = train_test_split(X, y, random_state=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Create classifier object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',\n",
       "           metric_params=None, n_jobs=None, n_neighbors=5, p=2,\n",
       "           weights='uniform')"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "\n",
    "knn = KNeighborsClassifier(n_neighbors = 5)\n",
    "knn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Train the classifier fit the estimator using the training data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "#For this example, we use the mass, width and height features of each fruit instance\n",
    "X = fruits[['mass', 'width', 'height']]\n",
    "y = fruits['fruit_label']\n",
    "\n",
    "#default is 75% / 25% train_test split\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',\n",
       "           metric_params=None, n_jobs=None, n_neighbors=5, p=2,\n",
       "           weights='uniform')"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "\n",
    "knn = KNeighborsClassifier(n_neighbors = 5)\n",
    "knn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',\n",
       "           metric_params=None, n_jobs=None, n_neighbors=5, p=2,\n",
       "           weights='uniform')"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "knn.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5333333333333333"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "knn.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "#let's use the trained classifier model to classify new, previously unseen objects"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'mandarin'"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fruit_prediction = knn.predict([[18, 5, 4.3]])\n",
    "lookup_fruit_name[fruit_prediction[0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'mandarin'"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fruit_prediction = knn.predict([[25, 8, 5.5]])\n",
    "lookup_fruit_name[fruit_prediction[0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'mandarin'"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fruit_prediction = knn.predict([[15, 8, 5.5]])\n",
    "lookup_fruit_name[fruit_prediction[0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'mandarin'"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fruit_prediction = knn.predict([[45, 15, 20]])\n",
    "lookup_fruit_name[fruit_prediction[0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'mandarin'"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fruit_prediction = knn.predict([[75, 25, 25]])\n",
    "lookup_fruit_name[fruit_prediction[0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'lemon'"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fruit_prediction = knn.predict([[125, 65, 70]])\n",
    "lookup_fruit_name[fruit_prediction[0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'lemon'"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fruit_prediction = knn.predict([[200, 125, 145]])\n",
    "lookup_fruit_name[fruit_prediction[0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'orange'"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fruit_prediction = knn.predict([[400, 500, 600]])\n",
    "lookup_fruit_name[fruit_prediction[0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "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=\"639.9999861283738\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "([<matplotlib.axis.XTick at 0x13e311cb4a8>,\n",
       "  <matplotlib.axis.XTick at 0x13e311c1d68>,\n",
       "  <matplotlib.axis.XTick at 0x13e311b9be0>,\n",
       "  <matplotlib.axis.XTick at 0x13e311ea518>,\n",
       "  <matplotlib.axis.XTick at 0x13e311ea9b0>],\n",
       " <a list of 5 Text xticklabel objects>)"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "k_range = range(1, 20)\n",
    "scores=[]\n",
    "\n",
    "for k in k_range:\n",
    "    knn = KNeighborsClassifier(n_neighbors = k)\n",
    "    knn.fit(X_train, y_train)\n",
    "    scores.append(knn.score(X_test, y_test))\n",
    "    \n",
    "plt.figure()\n",
    "plt.xlabel('k')\n",
    "plt.ylabel('accuracy')\n",
    "plt.scatter(k_range, scores)\n",
    "plt.xticks([0, 5, 10, 15, 20])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "#How sensitive is k-NN classification accuracy to the train/test split proportion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "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=\"639.9999861283738\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'accuracy')"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t = [0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2]\n",
    "\n",
    "knn = KNeighborsClassifier(n_neighbors = 5)\n",
    "\n",
    "plt.figure()\n",
    "\n",
    "for s in t:\n",
    "    scores = []\n",
    "    for i in range(1, 1000):\n",
    "        X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 1-s)\n",
    "        knn.fit(X_train, y_train)\n",
    "        scores.append(knn.score(X_test, y_test))\n",
    "    plt.plot(s, np.mean(scores), 'bo')\n",
    "plt.xlabel('Training set proportion (%)')\n",
    "plt.ylabel('accuracy')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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",
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