compute_fom_snmachine.ipynb

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  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The autoreload extension is already loaded. To reload it, use:\n",
      "  %reload_ext autoreload\n"
     ]
    }
   ],
   "source": [
    "#from __future__ import division, print_function\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import glob\n",
    "import os\n",
    "import pandas as pd\n",
    "from scipy.integrate import trapz\n",
    "%matplotlib nbagg\n",
    "%load_ext autoreload\n",
    "\n",
    "plt.rcParams['nbagg.transparent'] = False\n",
    "plt.rcParams['figure.facecolor'] = 'w'\n",
    "\n",
    "prop_cycle = plt.rcParams['axes.prop_cycle']\n",
    "plot_colors = prop_cycle.by_key()['color']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def roc(pr, Yt, true_class=0):\n",
    "    \"\"\"\n",
    "    Produce the false positive rate and true positive rate required to plot\n",
    "    a ROC curve, and the area under that curve.\n",
    "    Parameters\n",
    "    ----------\n",
    "    pr : array\n",
    "        An array of probability scores, either a 1d array of size N_samples or an nd array,\n",
    "\tin which case the column corresponding to the true class will be used.\n",
    "    Yt : array\n",
    "        An array of class labels, of size (N_samples,)\n",
    "    true_class : int\n",
    "        which class is taken to be the \"true class\" (e.g. Ia vs everything else)\n",
    "    Returns\n",
    "    -------\n",
    "    fpr : array\n",
    "        An array containing the false positive rate at each probability threshold\n",
    "    tpr : array\n",
    "        An array containing the true positive rate at each probability threshold\n",
    "    auc : float\n",
    "        The area under the ROC curve\n",
    "    \"\"\"\n",
    "    probs = pr.copy()\n",
    "    Y_test = Yt.copy()\n",
    "    min_class = (int)(Y_test.min())  # This is to deal with starting class assignment at 1.\n",
    "    Y_test = Y_test.squeeze()\n",
    "    \n",
    "    if len(pr.shape)>1:\n",
    "        probs_1 = probs[:, true_class-min_class]\n",
    "    else:\n",
    "        probs_1 = probs\n",
    "    \n",
    "    threshold = np.linspace(0., 1., 50)  # 50 evenly spaced numbers between 0,1\n",
    "\n",
    "    # This creates an array where each column is the prediction for each threshold\n",
    "    preds = np.tile(probs_1, (len(threshold), 1)).T >= np.tile(threshold, (len(probs_1), 1))\n",
    "    Y_bool = (Y_test == true_class)\n",
    "    Y_bool = np.tile(Y_bool, (len(threshold), 1)).T\n",
    "    \n",
    "    TP = (preds & Y_bool).sum(axis=0)\n",
    "    FP = (preds & ~Y_bool).sum(axis=0)\n",
    "    TN = (~preds & ~Y_bool).sum(axis=0)\n",
    "    FN = (~preds & Y_bool).sum(axis=0)\n",
    "    \n",
    "    tpr = np.zeros(len(TP))\n",
    "    tpr[TP != 0] = TP[TP != 0]/(TP[TP != 0] + FN[TP != 0])\n",
    "    fpr = FP/(FP+TN)\n",
    "    \n",
    "    fpr = np.array(fpr)[::-1]\n",
    "    tpr = np.array(tpr)[::-1]\n",
    "    \n",
    "    auc = trapz(tpr, fpr)\n",
    "\n",
    "    return fpr, tpr, auc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def compute_fom(true_classes, preds):\n",
    "    \"\"\"Computes the FoM from Kessler et al. (2010)\n",
    "    \"\"\"\n",
    "    \n",
    "    N_tot_Ia = np.sum(true_classes==1)\n",
    "    N_true_Ia = np.sum((true_classes==1)&(preds==1))\n",
    "    N_false_Ia = np.sum((true_classes!=1)&(preds==1))\n",
    "    W_false_Ia = 3\n",
    "    \n",
    "    return N_true_Ia**2/(N_true_Ia + W_false_Ia*N_false_Ia)/N_tot_Ia"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def compute_brier(true_classes, probs):\n",
    "    \"\"\"\n",
    "    Computes the population Brier score (just the average, equal weighted per object score)\n",
    "    \"\"\"\n",
    "    tau = np.zeros((len(true_classes), len(np.unique(true_classes))))\n",
    "    true_classes = true_classes-np.min(true_classes) # Since often the first class is \"1\" not \"0\"\n",
    "    tau[range(len(tau)), true_classes] = 1\n",
    "    per_object =  np.sum((tau-probs)**2, axis=1)\n",
    "    return np.mean(per_object)/len(np.unique(true_classes))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def compute_logloss(true_classes, probs):\n",
    "    \"\"\"\n",
    "    Computes the population Brier score (just the average, equal weighted per object score)\n",
    "    \"\"\"\n",
    "    tau = np.zeros((len(true_classes), len(np.unique(true_classes))))\n",
    "    true_classes = true_classes-np.min(true_classes) # Since often the first class is \"1\" not \"0\"\n",
    "    tau[range(len(tau)), true_classes] = 1\n",
    "    probs[probs==0] = 0.0005\n",
    "    per_object =  -np.sum((1-tau)*np.log(probs), axis=1)\n",
    "    return np.mean(per_object)/len(np.unique(true_classes))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "fls = glob.glob('classifications/*')\n",
    "nms = [s.split(os.path.sep)[-1].split('.')[0] for s in fls]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "true_classes = pd.read_csv('key.txt', delim_whitespace=True)\n",
    "true_classes = true_classes.sort_values('Object')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "fom = []\n",
    "auc_results = []\n",
    "brier = []\n",
    "logloss = []\n",
    "\n",
    "for f in fls:\n",
    "    probs = pd.read_csv(f, delim_whitespace=True)\n",
    "    preds = pd.DataFrame(data={'Object': probs['Object'], 'Prediction': probs[[1,2,3]].idxmax(axis=1)})\n",
    "    preds = preds.sort_values('Object')\n",
    "    preds['Prediction'] = preds['Prediction'].astype('float')\n",
    "    df = pd.merge(preds, true_classes)\n",
    "    prob_df = pd.merge(probs, true_classes)\n",
    "    fom.append(compute_fom(df['Type'], df['Prediction']))\n",
    "    \n",
    "\n",
    "    fpr, tpr, auc = roc(prob_df['1'].values, prob_df['Type'].values, true_class=1)\n",
    "    auc_results.append(auc)\n",
    "    \n",
    "    brier.append(compute_brier(prob_df['Type'].values, prob_df[['1','2','3']].values))\n",
    "    logloss.append(compute_logloss(prob_df['Type'].values, prob_df[['1','2','3']].values))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "results = pd.DataFrame(index=nms, data={'FoM': fom, 'AUC':auc_results, 'Brier':brier, 'Logloss':logloss})\n",
    "results = results.sort_values('FoM')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AUC</th>\n",
       "      <th>Brier</th>\n",
       "      <th>FoM</th>\n",
       "      <th>Logloss</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>wavelets_nb</th>\n",
       "      <td>0.850239</td>\n",
       "      <td>0.177849</td>\n",
       "      <td>0.036490</td>\n",
       "      <td>2.191487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>wavelets_knn</th>\n",
       "      <td>0.893876</td>\n",
       "      <td>0.132220</td>\n",
       "      <td>0.114470</td>\n",
       "      <td>1.434053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>templates_nb</th>\n",
       "      <td>0.879452</td>\n",
       "      <td>0.104994</td>\n",
       "      <td>0.339890</td>\n",
       "      <td>2.855753</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>templates_knn</th>\n",
       "      <td>0.942365</td>\n",
       "      <td>0.078729</td>\n",
       "      <td>0.383945</td>\n",
       "      <td>1.795642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>wavelets_neural_network</th>\n",
       "      <td>0.945560</td>\n",
       "      <td>0.074970</td>\n",
       "      <td>0.480036</td>\n",
       "      <td>3.158033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>templates_neural_network</th>\n",
       "      <td>0.954455</td>\n",
       "      <td>0.064977</td>\n",
       "      <td>0.496158</td>\n",
       "      <td>2.351954</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>wavelets_svm</th>\n",
       "      <td>0.967807</td>\n",
       "      <td>0.072987</td>\n",
       "      <td>0.498791</td>\n",
       "      <td>2.319222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>templates_svm</th>\n",
       "      <td>0.968613</td>\n",
       "      <td>0.058338</td>\n",
       "      <td>0.514055</td>\n",
       "      <td>2.116697</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>wavelets_boost_forest</th>\n",
       "      <td>0.978034</td>\n",
       "      <td>0.068945</td>\n",
       "      <td>0.591208</td>\n",
       "      <td>1.750274</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>templates_boost_forest</th>\n",
       "      <td>0.982376</td>\n",
       "      <td>0.048551</td>\n",
       "      <td>0.635263</td>\n",
       "      <td>6.199345</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               AUC     Brier       FoM   Logloss\n",
       "wavelets_nb               0.850239  0.177849  0.036490  2.191487\n",
       "wavelets_knn              0.893876  0.132220  0.114470  1.434053\n",
       "templates_nb              0.879452  0.104994  0.339890  2.855753\n",
       "templates_knn             0.942365  0.078729  0.383945  1.795642\n",
       "wavelets_neural_network   0.945560  0.074970  0.480036  3.158033\n",
       "templates_neural_network  0.954455  0.064977  0.496158  2.351954\n",
       "wavelets_svm              0.967807  0.072987  0.498791  2.319222\n",
       "templates_svm             0.968613  0.058338  0.514055  2.116697\n",
       "wavelets_boost_forest     0.978034  0.068945  0.591208  1.750274\n",
       "templates_boost_forest    0.982376  0.048551  0.635263  6.199345"
      ]
     },
     "execution_count": 168,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results"
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  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "results.to_csv('FoM_results_snmachine.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
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       "\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 overriden (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",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\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": [
       "<img 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\" width=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(10,6))\n",
    "plt.plot(range(len(results)), results.FoM, 'o')\n",
    "plt.xticks(range(len(results)), results.index, rotation=90);\n",
    "plt.ylabel('FoM (blue circle)')\n",
    "\n",
    "ax2 = plt.gca().twinx()\n",
    "ax2.plot(range(len(results)), results.AUC,'^r')\n",
    "plt.ylabel('AUC (red triangle)')\n",
    "\n",
    "plt.tight_layout()\n",
    "\n",
    "fig.savefig('fom_vs_auc.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "metadata": {
    "collapsed": false
   },
   "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",
       "        this.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 overriden (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",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\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"
    },
    {
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\" width=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(10,6))\n",
    "plt.plot(range(len(results)), results.FoM, 'o')\n",
    "plt.xticks(range(len(results)), results.index, rotation=90);\n",
    "plt.ylabel('FoM (blue circle)')\n",
    "\n",
    "ax2 = plt.gca().twinx()\n",
    "ax2.plot(range(len(results)), results.Brier,'^r')\n",
    "plt.ylabel('Brier Score (red triangle)')\n",
    "\n",
    "plt.tight_layout()\n",
    "fig.savefig('fom_vs_brier.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {
    "collapsed": false
   },
   "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",
       "        this.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 overriden (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",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\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"
    },
    {
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width=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig =plt.figure(figsize=(10,6))\n",
    "plt.plot(range(len(results)), results.FoM, 'o')\n",
    "plt.xticks(range(len(results)), results.index, rotation=90);\n",
    "plt.ylabel('FoM (blue circle)')\n",
    "\n",
    "ax2 = plt.gca().twinx()\n",
    "ax2.plot(range(len(results)), results.Logloss,'^r')\n",
    "plt.ylabel('Log loss (red triangle)')\n",
    "\n",
    "plt.tight_layout()\n",
    "fig.savefig('fom_vs_logloss.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:py3]",
   "language": "python",
   "name": "conda-env-py3-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}