ConfidencePenalty.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Temperature Scaling vs. Confidence Penalty\n",
    "\n",
    "Pereyra et al. link label smoothing [Szegedy2016] to *confidence penalty* (CP) and propose a simple way to prevent over-confident networks [Pereyra2017].\n",
    "Low entropy output distributions are penalized by adding the negative entropy $ \\mathcal{H} $ of the softmax output to the negative log-likelihood training objective, weighted by an additional hyperparameter $ \\beta $.\n",
    "This leads to the following optimization function:\n",
    "\n",
    "$ \\mathcal{L}_{\\mathrm{CP}}(\\mathbf{w}) = - \\sum_{\\mathcal{X}, \\mathcal{Y}} \\log \\mathbf{p}_{\\mathbf{w}} (\\mathbf{y} \\vert \\mathbf{x}) - \\beta \\, \\mathcal{H} \\left( \\mathbf{p}_{\\mathbf{w}}(\\mathbf{y} \\vert \\mathbf{x}) \\right) $.\n",
    "\n",
    "We reproduce their experiment on supervised image classification and compare the calibratedness of confidence and uncertainty to our presented approach.\n",
    "DenseNet-121 with dropout is trained on CIFAR-10 as described in § A.3.\n",
    "We fix $ \\beta = 0.1 $ for CP loss and omit data augmentation for this experiment as described in [Pereyra2017]."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "pycharm": {}
   },
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "import numpy as np\n",
    "np.random.seed(0)\n",
    "import torch\n",
    "torch.manual_seed(0)\n",
    "torch.backends.cudnn.deterministic = True\n",
    "torch.backends.cudnn.benchmark = False\n",
    "import torch.nn as nn\n",
    "import torch.nn.functional as F\n",
    "import torch.optim as optim\n",
    "from torchvision import datasets, transforms, models\n",
    "from torch.utils.data.sampler import SubsetRandomSampler\n",
    "import matplotlib\n",
    "from tqdm import tqdm\n",
    "from uce import eceloss, uceloss\n",
    "from utils import accuracy, nentr\n",
    "from models import BayesianNet\n",
    "from matplotlib import pyplot as plt\n",
    "import seaborn as sns\n",
    "sns.set()\n",
    "matplotlib.rcParams['text.usetex'] = True\n",
    "matplotlib.rcParams['font.size'] = 8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "pycharm": {}
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Files already downloaded and verified\n"
     ]
    }
   ],
   "source": [
    "batch_size = 128\n",
    "valid_size = 5000\n",
    "\n",
    "mean = [0.4914, 0.48216, 0.44653]\n",
    "std = [0.2470, 0.2435, 0.26159]\n",
    "valid_set = datasets.CIFAR10('../data', train=True, download=True,\n",
    "                             transform=transforms.Compose([\n",
    "                                 transforms.RandomCrop(32, padding=4),\n",
    "                                 transforms.RandomHorizontalFlip(),\n",
    "                                 transforms.ToTensor(),\n",
    "                                 transforms.Normalize(mean=mean, std=std)]))\n",
    "\n",
    "test_set = datasets.CIFAR10('../data', train=False, download=False,\n",
    "                            transform=transforms.Compose([\n",
    "                                transforms.ToTensor(),\n",
    "                                transforms.Normalize(mean=mean, std=std)]))\n",
    "valid_indices = torch.load('./valid_indices_cifar10.pth')\n",
    "\n",
    "valid_loader = torch.utils.data.DataLoader(valid_set, batch_size=batch_size, pin_memory=True,\n",
    "                                           sampler=SubsetRandomSampler(valid_indices))\n",
    "test_loader = torch.utils.data.DataLoader(test_set, batch_size=batch_size, pin_memory=True, num_workers=4)\n",
    "\n",
    "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "pycharm": {}
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading previous weights at epoch 162\n",
      "Loading previous weights at epoch 170\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<All keys matched successfully>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "conf_penalty_net = BayesianNet(num_classes=10, model='densenet121').to(device)\n",
    "temp_scale_net = BayesianNet(num_classes=10, model='densenet121').to(device)\n",
    "\n",
    "conf_penalty_checkpoint = torch.load(f'../snapshots/densenet121_best_cp.pth.tar', map_location=device)\n",
    "print(\"Loading previous weights at epoch \" + str(conf_penalty_checkpoint['epoch']))\n",
    "conf_penalty_net.load_state_dict(conf_penalty_checkpoint['state_dict'])\n",
    "\n",
    "temp_scale_checkpoint = torch.load(f'../snapshots/densenet121_best_no_cp.pth.tar', map_location=device)\n",
    "print(\"Loading previous weights at epoch \" + str(temp_scale_checkpoint['epoch']))\n",
    "temp_scale_net.load_state_dict(temp_scale_checkpoint['state_dict'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "pycharm": {}
   },
   "outputs": [],
   "source": [
    "def train(net, bayesian):\n",
    "    optimizer = optim.Adam([net.T], lr=1e-2, weight_decay=0)\n",
    "    lr_scheduler = optim.lr_scheduler.ReduceLROnPlateau(optimizer, patience=5, factor=0.1)\n",
    "    train_losses = []\n",
    "    train_accuracies = []\n",
    "    epochs = 30\n",
    "\n",
    "    for e in range(epochs):\n",
    "        net.eval()\n",
    "\n",
    "        epoch_train_loss = []\n",
    "        epoch_train_acc = []\n",
    "        is_best = False\n",
    "\n",
    "        for batch_idx, (data, target) in enumerate(valid_loader):\n",
    "            data, target = data.to(device), target.to(device)\n",
    "            optimizer.zero_grad()\n",
    "            output = net(data, temp_scale=True, bayesian=bayesian)\n",
    "            if bayesian:\n",
    "                output = torch.log_softmax(output, dim=2)\n",
    "                output = output.mean(dim=0)\n",
    "                loss = F.nll_loss(output, target)\n",
    "            else:\n",
    "                loss = F.cross_entropy(output, target)\n",
    "            loss.backward()\n",
    "            epoch_train_loss.append(loss.item())\n",
    "            epoch_train_acc.append(accuracy(output, target))\n",
    "            optimizer.step()\n",
    "\n",
    "        epoch_train_loss = np.mean(epoch_train_loss)\n",
    "        epoch_train_acc = np.mean(epoch_train_acc)\n",
    "        lr_scheduler.step(epoch_train_loss)\n",
    "\n",
    "        # save epoch losses\n",
    "        train_losses.append(epoch_train_loss)\n",
    "        train_accuracies.append(epoch_train_acc)\n",
    "\n",
    "        print(\"Epoch {:2d}, lr: {:.4f}, loss: {:.4f}, acc: {:.4f}, T: {:.4f}\"\n",
    "              .format(e,\n",
    "                      optimizer.param_groups[0]['lr'],\n",
    "                      epoch_train_loss,\n",
    "                      epoch_train_acc,\n",
    "                      net.T.item()\n",
    "                      ))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch  0, lr: 0.0100, loss: 0.4800, acc: 0.8518, T: 1.3314\n",
      "Epoch  1, lr: 0.0100, loss: 0.4507, acc: 0.8578, T: 1.5089\n",
      "Epoch  2, lr: 0.0100, loss: 0.4384, acc: 0.8654, T: 1.5890\n",
      "Epoch  3, lr: 0.0100, loss: 0.4529, acc: 0.8477, T: 1.6101\n",
      "Epoch  4, lr: 0.0100, loss: 0.4481, acc: 0.8547, T: 1.6431\n",
      "Epoch  5, lr: 0.0100, loss: 0.4671, acc: 0.8430, T: 1.6763\n",
      "Epoch  6, lr: 0.0100, loss: 0.4550, acc: 0.8533, T: 1.6822\n",
      "Epoch  7, lr: 0.0100, loss: 0.4446, acc: 0.8568, T: 1.6605\n",
      "Epoch  8, lr: 0.0010, loss: 0.4624, acc: 0.8414, T: 1.6657\n",
      "Epoch  9, lr: 0.0010, loss: 0.4419, acc: 0.8584, T: 1.6622\n",
      "Epoch 10, lr: 0.0010, loss: 0.4393, acc: 0.8535, T: 1.6569\n",
      "Epoch 11, lr: 0.0010, loss: 0.4520, acc: 0.8529, T: 1.6555\n",
      "Epoch 12, lr: 0.0010, loss: 0.4676, acc: 0.8527, T: 1.6580\n",
      "Epoch 13, lr: 0.0010, loss: 0.4522, acc: 0.8520, T: 1.6608\n",
      "Epoch 14, lr: 0.0001, loss: 0.4628, acc: 0.8518, T: 1.6601\n",
      "Epoch 15, lr: 0.0001, loss: 0.4466, acc: 0.8564, T: 1.6604\n",
      "Epoch 16, lr: 0.0001, loss: 0.4474, acc: 0.8539, T: 1.6601\n",
      "Epoch 17, lr: 0.0001, loss: 0.4510, acc: 0.8523, T: 1.6599\n",
      "Epoch 18, lr: 0.0001, loss: 0.4499, acc: 0.8512, T: 1.6600\n",
      "Epoch 19, lr: 0.0001, loss: 0.4548, acc: 0.8551, T: 1.6601\n",
      "Epoch 20, lr: 0.0000, loss: 0.4411, acc: 0.8607, T: 1.6600\n",
      "Epoch 21, lr: 0.0000, loss: 0.4610, acc: 0.8551, T: 1.6600\n",
      "Epoch 22, lr: 0.0000, loss: 0.4531, acc: 0.8498, T: 1.6600\n",
      "Epoch 23, lr: 0.0000, loss: 0.4470, acc: 0.8549, T: 1.6600\n",
      "Epoch 24, lr: 0.0000, loss: 0.4426, acc: 0.8570, T: 1.6600\n",
      "Epoch 25, lr: 0.0000, loss: 0.4517, acc: 0.8494, T: 1.6599\n",
      "Epoch 26, lr: 0.0000, loss: 0.4644, acc: 0.8480, T: 1.6600\n",
      "Epoch 27, lr: 0.0000, loss: 0.4389, acc: 0.8611, T: 1.6600\n",
      "Epoch 28, lr: 0.0000, loss: 0.4422, acc: 0.8592, T: 1.6600\n",
      "Epoch 29, lr: 0.0000, loss: 0.4677, acc: 0.8496, T: 1.6600\n"
     ]
    }
   ],
   "source": [
    "# train(conf_penalty_net, bayesian=True)\n",
    "train(temp_scale_net, bayesian=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "pycharm": {}
   },
   "outputs": [],
   "source": [
    "def test(net, temp_scale, bayesian):\n",
    "    logits = []\n",
    "    labels = []\n",
    "    with torch.no_grad():\n",
    "        for batch_idx, (data, target) in enumerate(tqdm(test_loader)):\n",
    "            data, target = data.to(device), target.to(device)\n",
    "            output = net(data, temp_scale=temp_scale, bayesian=bayesian)\n",
    "            if bayesian:\n",
    "                output = torch.softmax(output, dim=2).mean(dim=0)\n",
    "            else:\n",
    "                output = torch.softmax(output, dim=1)\n",
    "            logits.append(output.detach())\n",
    "            labels.append(target.detach())\n",
    "    return torch.cat(logits, dim=0), torch.cat(labels, dim=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_conf(acc, conf):\n",
    "    fig, ax = plt.subplots(1, 1, figsize=(2.5, 2.25))\n",
    "    ax.plot([0,1], [0,1], 'k--')\n",
    "    ax.plot(conf.data.cpu().numpy(), acc.data.cpu().numpy(), marker='.')\n",
    "    ax.set_xlabel(r'confidence')\n",
    "    ax.set_ylabel(r'accuracy')\n",
    "    ax.set_xticks((np.arange(0, 1.1, step=0.2)))\n",
    "    ax.set_yticks((np.arange(0, 1.1, step=0.2)))\n",
    "\n",
    "    return fig, ax\n",
    "\n",
    "def plot_uncert(err, entr):\n",
    "    fig, ax = plt.subplots(1, 1, figsize=(2.5, 2.25))\n",
    "    \n",
    "    ax.plot([0,1], [0,1], 'k--') \n",
    "    ax.plot(entr.data.cpu().numpy(), err.data.cpu().numpy(), marker='.')\n",
    "    ax.set_xticks((np.arange(0, 1.1, step=0.2)))\n",
    "    ax.set_ylabel(r'error')\n",
    "    ax.set_xlabel(r'uncertainty')\n",
    "    ax.set_xticks((np.arange(0, 1.1, step=0.2)))\n",
    "    ax.set_yticks((np.arange(0, 1.1, step=0.2)))\n",
    "\n",
    "    return fig, ax"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 79/79 [00:01<00:00, 52.92it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ece = 3.3679887652397156\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
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       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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\" width=\"250\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "logits, labels = test(conf_penalty_net, temp_scale=False, bayesian=False)\n",
    "\n",
    "ece_cp_uc, acc_cp_uc, conf_cp_uc = eceloss(logits, labels)\n",
    "print('ece =', ece_cp_uc.item()*100)\n",
    "\n",
    "fig_cp_uc, ax_cp_uc = plot_conf(acc_cp_uc, conf_cp_uc)\n",
    "\n",
    "textstr_cp_uc = r'ECE\\,=\\,{:.2f}'.format(ece_cp_uc.item()*100)\n",
    "props = dict(boxstyle='round', facecolor='white', alpha=0.75)\n",
    "ax_cp_uc.text(0.075, 0.925, textstr_cp_uc, transform=ax_cp_uc.transAxes, fontsize=14,\n",
    "                verticalalignment='top',\n",
    "                horizontalalignment='left',\n",
    "                bbox=props\n",
    "                )\n",
    "ax_cp_uc.set_title(r'freq. conf. penalty')\n",
    "fig_cp_uc.tight_layout()\n",
    "fig_cp_uc.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 79/79 [00:01<00:00, 50.54it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ece = 4.853932932019234\n",
      "uce = 15.204653143882751\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"250\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\" width=\"250\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "logits, labels = test(conf_penalty_net, temp_scale=False, bayesian=True)\n",
    "\n",
    "ece1, acc1, conf1 = eceloss(logits, labels)\n",
    "uce1, err1, entr1 = uceloss(logits, labels)\n",
    "\n",
    "print('ece =', ece1.item()*100)\n",
    "print(\"uce =\", uce1.item()*100)\n",
    "\n",
    "fig1, ax1 = plot_conf(acc1, conf1)\n",
    "fig2, ax2 = plot_uncert(err1, entr1)\n",
    "\n",
    "textstr1 = r'ECE\\,=\\,{:.2f}'.format(ece1.item()*100)\n",
    "props = dict(boxstyle='round', facecolor='white', alpha=0.75)\n",
    "ax1.text(0.075, 0.925, textstr1, transform=ax1.transAxes, fontsize=14,\n",
    "         verticalalignment='top',\n",
    "         horizontalalignment='left',\n",
    "         bbox=props\n",
    "        )\n",
    "ax1.set_title(r'MC conf. penalty')\n",
    "fig1.tight_layout()\n",
    "fig1.show()\n",
    "\n",
    "textstr2 = r'UCE\\,=\\,{:.2f}'.format(uce1.item()*100)\n",
    "ax2.text(0.075, 0.925, textstr2, transform=ax2.transAxes, fontsize=14,\n",
    "         verticalalignment='top',\n",
    "         horizontalalignment='left',\n",
    "         bbox=props\n",
    "        )\n",
    "ax2.set_title(r'MC conf. penalty')\n",
    "fig2.tight_layout()\n",
    "fig2.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 79/79 [00:01<00:00, 40.46it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ece = 1.0747364722192287\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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5r5zL5SHZSABLxLQ/hWw0vVvxovl9GOZNm7cINdd10/eXfOpY/8feL1jFkyvBu+WzKvEgsoFhdyzZ09jPXUslRochg0bZpxasGBB8CXjWH8IjB071va6V0+yqd2rNcNyeZUAfzPeqZl///ufcsMNg+RgzeZy+iWjjG4RJ6XDEDYvj0unQrepRa1kcSmcZa1vW7Nmjd6VdevWBfb1DqxurIWOZVS1Ja6v4WNg/PjxhhVfWlqqT6fFVjcj6m1aFJqFzBgC+K0tWbLY9jfnRSHxO+FvJfU1c+TIEXnggUky4b57pEHHq6R5l2slK9uZb3i28vK/8qJWqRciQgmcSRIhgUy4BMXao0cPQxTsm0Pfvn0Dy5927dpVZsyYYb4s6PdGszqUdTilPHnyZMEQNqQFix334ENg1qxZYpemJQOPHsRrbTzyyMMyZ87j1ZJqwoT7pH//ATGlgfpZunSJrFixQrAIztatVWvPN23azKibpk2bCj6+Lriga6C+gzNIVdmDy+HFYyhXsGzfvr1rxcNvc9q0R+SFF54PyaOk5EYZOrQ0bN2F3MATviOwffs2GTdulKz/6DPDKq/b4FTHDKDMMQ695clFnvbwp0JXVYrhYq+88opRueGGjgUrevOTMH/+fPOh7f64ceNk+PDhRl87WgCQz5w5cyTa0qq2ifGkYwKot4kT7zOUud1NWrGvX78uEKdXr0vlkUem2UXnORsCkyZNNJQsPrTcUuj4IBs4cIDs3Wv94NbFwUfi0qVLZe7cebZK/fnn58nkyZN09Ji3Dz/8iFx6ae+Y7+MN3iDw1lsr5M47R8vhGkXS9tI7pWbtqhUuzaW77ILmcl7bk2TZO1tk1cav5Yhyfqup+su7tGko/Xq2ltOa1fP8SnpU6MdqNJwi1xUe7bqOF2mLNNLJ8S2SLIm4VlBQqKyqoTEn1aGDs+F9sBrHjBltSR9W5AUXXBD4kIKiQLcKFHosAWUfPrzKPwL3OZ2Qx2nZYylLsuOC2fbtX8rixYtl4cKFUUdxJKJ8ZmXer19/ufHGIUYdoul99uxZxscYPs4Qb+HCRYnIkmlkAAE4Jc6ZM0v++MffS3GL86T1udeoJvZci2Q11WidksvbyfntTzLOD7mivZT8uJ1lLncvT/dqFoYK3UyD+0klgJnx8GJ2Izz++GNG86xOu1279spSnxTWgjQ35zqZDwBlx8cIuh7w0vDDxDKJ6HLQ9RHLFi0A2jK/7bbRlmcGLQJoTdFlg1KHNR7cJYMPObS8xBLQNaM/9HA/Q/oRWLZsscz4w++l6Vn9pGHrH4YIcEJhvtx6dSdpflKB5Roc3/JqZlvOpcMBFXo61BLLGBMBWOboa9UBFt19903Uh7ZbtJ4gDhRGtImAbBPwwUk9AZIWFb4gsNbx51bAh5buM8dHWbgPwNGjxxhN7lDo06ZNC1Ho8FXBXyzhssv6GNHx/LjVlRBLeRg3dgLndb1Eulw1USpqnhhyc7sW9eSmn3aQArXUbaYEerlnSk1SDoMAlIu5md2JMjejg2KnX4OZyPF9WL1z5z4vCxYskg0bNhg+IG4rusWLjzefR+ue6d+/v1FYWPP4qKtOGD36NsNxEpZ5tI/B6uTDe90j8Pn2PXL/U+/YKvNLuzST0QPPyChlDpJU6O49T0w5BQTMljlfxomtAChv/CXzg2fJkiUBITACIVIwN6kvWnT8QyDSPXbX0F2DEREIcIZjSD8CK9Zsl4f+/p7s2HPYUvic7CwZekU7GdTjdMnOyjz1xyZ3S3XzIJ0JwEFKv4ghB7yuGdKbwMqVKwwB4IQYzTHV/KGxfv36uARHC4/+KET3i9stEHEVkjeFEPjqq6/UcLJvpXWbdvL8a5/IklWh3UD1CvLkV307ScvGsa2WFpKZh09QoXu4cli02AjAGUoHWOex9pnqe7n1BgHzUFE9hXK0kqHe0Y+Ov3iC7q5BOuH66+NJl/e4R2DVqrfkjjtGS25+gVw8aLJ8/OW+kMxaNyuWW37WUQrrZE5/eYiQ6kTmtTnYSclzviCwcuXKgJy6PzVwgjtpRwBe5jpg4h8nwRwvVmc9fBBqr/bbbrvNSXaMk0ICGF3yxBOPyU033SgHK/PlxLNvtFXmPzq7iYwddGbGK3NUBS30FD6QzDpxBPDyNltl0fpbE5czU3KLQDyjDTAjow7BXvn6fLgtvOMR4E3PSWTCUfLG+X379ilnxbvUhGBLpV6zc6TF+ddLVo7V+s5Ra7f//NI28oMzTvZGoZNQCir0JEBmFvYE8MKO1Rs53NSsZmsOubnd94myw/FKj0N3MrFMuLLb06laiS8epRYuPfN5jKOP1idtjp/p+xjHrse6R/Omz3QWXpYPa5Fv2LhJ7rpjpGwu2ywnd/6pNGofOoNfcd2a8surOsmpTYq8LE7Cy0aFnnCkTNApAbxAdZ+l03vCTcGpX8ZIBw5UbgfkN2rUqJiyCVd2u0QwBtrc4mAXp7rnHn10tqf9DKx1etzyjiQ3PlR0iOVjSK8vgGeH1rkm6J1t2Vd7DUe3t9Ztk4rKGlLcZaQUnHHQdgrXU5sUGsq8uG6edwRIUkmo0JMEmtm4S8D88ja/1N3N1b3UH310llLoWwNWY6JzguLyutOguU6dym++x/xBEOl+szMlrfNIpFJzbeW67TL7pfVSWfm9KoBatk6F7Jw84884MP1D8/p1vVpLrprO1Y+BCt2Pte4RmeFJnKh5t81K3PxSd0tUlH3ZsqWBJvejRysSmhWGYJmHYSU08TRJzFynsfaHQ0SnLTWPP3589T/zWPY0wZTRxYRlPvvf68TQ5REkVYuhGf3lPzyrSYRYmX/Jn58xmV+vvpPQ/PJ2apn5DlKaCWyu03iKbv4gCHc/5i7QXRtwhvP7R1Q4Tqk6/+yi96Mqc5Stfcv64ndlDg5U6KDAkPYEzMOVIAxe1AzpTcCskJ22upgtebPHezgSixYtDFziSogBFJ7YeeqpObJuy35HZdm0ZZdS/GiS93egQvd3/WeM9LCszBadnmEsYwT0oSBmhRw8iiEcDnM88wdBuPhYQ10HDnXUJLyx3f7V17b95Halw9rlR9Wf3wMVut+fgAySv3fv48NXnn/++QySzJ+imBWyWVFHoqGbzxEn2rC84LkL3B7qGKncvGYlcOhIudRr82PryQhHNXOzJFf9+T3QKc7vT0AGyY/VwPRSm3ixr1ixwvOe3JHwxzrTWaS0gq9BWUZTeMH3JPsY5UOrC3winPhFmHnBaTFa0LPCIR6t82i0knf9s217ZOa/1srXOw86zrRLm4aCNcz9HqjQ/f4EZJD8sLDgpawXaJk8eVLCvOiTjYnj0KuIX3DBBYH6jPaBZlXQF0StsjVr1gTitGvXLrDPndQQQB/4orfK5B//96kaa+68Pzxbubj3UsuhMnDqVz4DGUYAK2RphQ4rfdKkiWm5njXHoVc9mHBU0/WJWQUjjZ2fPXt24Gl2MjmMeUU2ercH0CV159tvv5GJE++VITfdJstWH5T1m3eG5J+rpnAtVwrezucNynyIWg61+UnOJh4KSTzDTtBCz7AK9bs4eDFjRjY9A51ugr/vvomO0WAa0KFDS1PaJA05qGTEmLVNN7ujLrECmh0XjGrQFjriR1L8+kFYu3at3pUOHToG9rmTHALvv/+u3H77KDlS82SZ/o9PJCu3VkjGrU4ulGFXdpBDh8tlqVoSddXGrwUOcOgzRzM7LHMq8+PY6EVwnAX3MoQArDNY6jpAEQwY0D/qUDZYgGjqxjSgTodJ6Ty4jZ0A+rz1X6S7zSuf4UPNvKwq7sPx0KFDAklMnDgxsB9px9wvHzzsMdJ9vFY9Algl7emnn5JhNw2V/BY95dSLhococ/SGX9HtFLnzurOlYXEtQ2kPuaK9/Hn0xfIX9YctjqnMrXVBC93Kg0dJJIAm8dGj41um8pFHqlbGCldcWHJ4SWtLHdbbwIH91blmygHqgoCVt2vXLmXZrRdYa+YXvHk8s10eKPvIkSMDl6qmpQwcRtyJVvaIN6fwIhSntmpz1NSaWJjGzAnKGf3c5hDOUsbHk64b1EmkGQPh7LhkyRLBUETUY58+vQUjGuAzgTz1POzIFz4UTprbzWXEvtcdBIPLm67HBw7sl8mTx8vrKz+U0380TvKLGoWIUr8wT0qVsm7TvF7INTi+5dXMDjnPE1UEqND5JKSUgO4fdaMQeLEvWLBIpk17JNAPC0X8wgtbwmYH5TJhwn2OVmtbvHhx2HQy8QIUqlbCdvJBsZqVK+K8+eaKhCjLWbNmGx9/eF7w4aW7Uszl6Nevv2N/iWAr35wO990h8Pnnn6o6HCH7cppLm17jJCs7NySjc9s0kBsuayt18kOvhUTmiRACVOghSHgikwigvxUWMSw5LMKxcuXKkEVPoMTh5QxLMJxFmUlM0lUW1CP6ymfPnmW0quDjTNcdfB5iGUfOLpXkPgWvvLJEJj3woDTodLU0bdwhJHP0iV/Xs7Vc2Lmx0fITEoEnHBGoofoznI8PcJQkI6UzgZ07D0h5efSFRnJzs6V27Zqim171uuBHj0a/N535mMsOBn6UGwz8Kns8cuM3gi4Z/Db27TtsfoTSar9+/TqSnZ0lFRWVsmNH5ClZMQQNM7fVqFEpf/7TdJm/eIW0OP8Xkpsf6o3eolGBDFeOb43q1/Ysj1hkNwuRk5Mt9eolTy5a6Gb63CcBEiABEoibgF63/J1j3uhSWS4H9zaW0y7+pW2al53fXK76QSvJUR8KDNUnQIUexBB9azNnzjScezCbFprmOnbsKKWlpQFHqqBbHB/qtNFsqJv84Lg1fPhwNWwmtBnKccKMSAIkQAIpJoB1yx9T65ZbJoXJypFaRY1DSlZUJ1eG/qSDdDilfsg1noifABW6iR08eAcPHqyGOA2Q+fPnB67MnTtXevbsKdOnT1cetn0C52PZWb58ucyaNcv4MBg3blzgVpyHtzS8ds3nAxG4QwIkQAIeJwDLPESZhynzmaedKCWXt5UC1WXHkFgCVOgmnlDmsMaDFevAgQOlrKzMULzLli2L2VKHZT516lR54oknQjx+u3XrpjyD50jfvn2lefPmamjVQFOJuEsCJEAC3iewRE36YrHMwxQZE8XcenUnOr6F4VPd0+y4OEZwypQpxgQV4RTqoEGDjJgTJkyImTma8PGhEG6sKzyx0SqAlgAGEiABEkgnAnCAQ5+5k7D1m31CL2wnpOKLQ4V+jJueBzpckzqULv7QRI4hULEETLZhXtvZ7t5OnToFJu2wu85zJEACJOBFAvBmx3SsTgLXLXdCKf44VOiKHZQ0QjgL2rio/kGhIyxatMjYOv2HJvd58+ZFjA4nuWj5R0wgyRc52DHJwJkdCXiMQHl5uWze/JmImqdVrZHiKHDdckeY4o5Eha7Q6ekstcIOR1Nb2atXrw4XxfY80oVSh2NdOOseze2XXXaZ7f1ePKmnL6Bi92LtsExeI4DfSSb9Vnbs+E5uuWWolNz4C5n23DvidLVTrlvu7pNJha74agWNYWqRQnFxsXF569atkaKFXNP98lDmUOrwdjcHHEPhjx071nza0/taoXu6kCwcCXiIQKb8Zt577z0ZNKivvPPe+3JC52tl0xeRJ5nRVcB1yzUJ97ZU6IqteYGJSKi1hQ7lG0tAvzyGpekAj3d4tUPBwxlv4cKFxjC5dGpy14uRZJLVoeuHWxJIFAG1logRoMz1byZRaSc7HciAkTr9+/eTb3fuNiaLKTipjaNicN1yR5iqHYkKPQ6EelKYWG6dMWOGxQJHMz+sdTjMYcx7OilzLTemgMwUq0PLxC0JJJJA1dTAVSk6mVI5kXknMq2DBw+qJYlvk3vuuUcqa+TK6T8cKXUbnGbJolZejgz9cTvp3rGRsV45LqLPHMfjbzhXLmgfurKaJQEeVJsAx6ErhLEq6FgtdF1LaHqHA552wsN5KHZY65i0Jlofvk7HK1vMTY25nRlIgATsCWQpbzFtmZeXO/MEt08pdWfLyjYrY2SEbNq0UXLy6srpl4yUWsVNLAWqWytXxgw8UzAve7dOjaVEKXZ4v+cqhY4lTxmSQ4AKPTmcDcWNiWvQT46JZDCeXY8710odzVmpngK2sDA/JiJ4YZkDFq/wY/Cr3Khrv8ruVO7s7BqSpb57scBHuoWlS5cqy3yU4eOTW6vIsMyD1zAvrpsnk4ZdoJR5YbqJ57i8+j2HrZfrkQpdVWk0Zzhd67qvPdbmcVjkJSUlhiLHzHAIkydPNmaFw7Sv6EuH1Y99zESXylAdixvNi34MfpUbde1X2WOVu+qnkT6/j4qKCmN2S3QVItSsXV9O/9FIyavbwDjW/04sypdf39xdmjSoq09l9Bb1jg80rwYqdFUz2tnNaSU5/QDQ6UFRDx06VLQy1+dhjUOBa2sdil3P967jJHuLfvFYA75a8aD7sT/dr3LjGfGr7LHKDcfRdPpt7NixQ2699VfyxhtvGK8CKHE0s9esY11I5SS13OnkYV0F23jeG7G+Z1IZ3/yO010oTstTHSPJaR46HhW6IqGHo0GhRgq7du0yLsdioaNZHdY3VlQLF2Ct46MCs9XBmsfKbqkKe/YccrQeurl8VWsFV3214sWFFxge+nR6iZnlcbpvbnL10zrw4ONX2SPJDSscyh4vf/wGoOTwO9i375Bx7PS5SmW8NWtWq7UsRsq2bV8axcgvbCSnXTJCataqGrKrywYlPm7QmZKrJnKNtja6viedt/odh/qMRd6cHK6HnvR61/3W0ZzjdJM75mV3GtA/jg+AaB8BWBAGs8lF+6hwmm+q4uEllqU6DKuapapebGbFjhddJga8yP0a/Co7FDcC5DdXP176+MNvYf/+w2mjzCHLf//7ekCZ1ypuKqf98FbJzS/ApUBorhzfbut/hhTV4WppASge2aGFripCN4VH817XylbHd1KH2qp3Erdr164S66Q1TtJNVhy8xODJm33ML67qRVfVHI8ymF96ySpTsvLxcr+a2wz8Kru2xMEXz75uncLxoUNH5fDhcuymVSgtvVk+/PB/8r8NWwxlnlOztqX8pzYtkvuGnC/laSibRZAMPaBCVxWL4WKw0mFN409b7OY6h7LXCt1uARdcw1+wsseiK4sXLzaa3aNZ6evWrbNMQGPOP1329+07bAxly8nJMpplk9l/lGxG5ubXdB2SFC8zv8oeTm4oczwD6HrBePN0bYnKVl/jQ2+9T2a8uEaycvIsj0eb5vVkouozr1UzW3ZQoVvYeOWACv1YTQwbNszwMl+wYIGtQkffNoLd9KxQ9pgkBgHOb+b11DH2/NFHHzU8RtFXHi7gQwJN/pH62sPd67XzaGrEHywUWOWwZLS17rWyVqc8BQX5RtcCrLMDB45UJ6m0u9evspvl1s3pUOZ4BtI1YPlTPWZ8/ead8uiCT0KUedvmxXLf0AsE483x22bwJgEq9GP1AqsbyheOaVj73DzJCxT2+PHjDUVv57C2Zs2aQO3CyjYHWOWYNKakpMRwfDMrex0PHwvwhMc49GhWvL4nXbawVCoq8LJL3xeeE9Z+c4ozM/Gr7OnaKlNZWalG0/xF2nTuJh9/l2esZY5lTXPUcKwKo+vAXLsiHVvWl1/27SS18qkurGS8d8QaMtWJ9jbHzG2w2NF8DmWNoWTo39ZjMk23GLuIh2Z6NLnbKXxcx/SumMMdlryOX1ZWZkz9imFwuG7+iAjOg8ckQAIkUF0Cu3btVNO33i7rthyUU75rLTWyjk8EVW58eFtzOOv0E+Wmn3aUXNWFxuB9AjVUc1Fmm05x1AEscljNUNCwmKGAE6VskSaa17HVffeJSjsOUUNu2bnzQJzD1rKMprhYhnSEZJ5mJ6qGsvhPblSTX2VPZ7nXrVsjY8aMkF0Ha0jbS++0KHO7n16HU+rJSOXNnnNseud0lt1OvljOxSt7Tg6HrcXC2ZW4UOJ2jm+JyAzK20sKPBEyMQ0SIAFvE/jHP16Qhx6aLEeOHJEW5/8iqjKHNEVqSletzL0tHUunCbAdRZPglgRIgAQyjMDhw4dl0qR7jT8oczV4VIqbneVIync2fi1wmGNIHwLsQ0+fumJJSYAESMAxgS++2GqskrZ+/XFH3azsXMkOGo4WLkE4ysH7PU8NU2NIDwK00NOjnlhKEiABEnBM4M0335Brr71azMocN1dWHFU2urNhZ1jLHMufMqQPAdZW+tQVS0oCJEACEQlgSNrMmX+SX/1qmDGvhTlyrVq1ZfS901Sru7PXfpc2DbmWuRlgGuw7q1mXBUnn6U5dRsPkSYAESMARgd27d8mIETfLX/7yB2MaWvNNp5zSUh6c9pQs35zvaBa7bDUZVK8uzcxJcD8NCHhCoffq1Uv69esnzz//fBogYxFJgARIwFsE9uzZrZrY+xmLqwSXrEePXvLQI0/ICyu+E/SLRwtQ5kOuaCfNT7IuyhLtPl5PPQFPKHQMhcfYbKwL3q5dO5k4caLq+1mfejosAQmQAAmkAYHCwiI1+VV3S0mx6uGoUeNk9J0PyV/+vUkOHq6wXMc4824dGwn6yhGw7a6Ox99wrlzQvpElLg/Sg4AnJpbBJC6YjW3FihUGNcz7jdC+fXtjGtb+/fsbx/znPgFOLOOccbyTTTjPwbsx/Sq7l+XGsLSSkuuUcbRaTfxzgvz2tw9Li9M6y0NPvye791nXGuh86gnyKzWdK8aZm+dyz4qwJKKXZXf7lxKv7MmeWMYTCl1XBtYbf+655yzrgmvljnnW8QcLnsE9AlToztnG+yN3noN3Y/pVdq/LvW3bl/Kb39wvd989UXJrFclDf39PvttzyPIgtWuhZoDr11lZ5LENR/O67BYhE3wQr+y+VujmOsAiJ3/9619lyZIlxmmt2Gm1myklfp8K3TnTeH/kznPwbky/yu4FudFfjib2SGH3/iPyG2WZf7XjgCXaqU0KZczAMyW/ZuxTkHhBdoswSTyIV/ZkK3RP9KHb1QsUNxZD2bBhgzz++OMCx7mCggL2tdvB4jkSIIGMJ1C1Stpf5Sc/uVTKyjaHlXffwaPy8HPvhyjz5g3rym1qbvZ4lHnYzHjBUwQ81eQejQya5GfOnGk0yWMBFQRY7s2bNzfWIWdfezSC0a/TQo/OSMeI96td35/OW7/Kniq5q5ZwvkNef/0147Fp3bqNPPnkc1KrVi3LY3TwcLlMfe5/8tm2qvejvtj4hNpyx3VnS2HtmvpUzNtUyR5zQV24IV7ZaaEHVQbGqD/88MNy6aWXynnnnSePPfaY4OHGCmhjx441+tQ3b95seMj37t1bVq5cGZQCD0mABEggfQls3LhBrruuX0CZQ5JNmzbKr399n2W8+eGjFTL9hQ9DlPmJRfkydtBZ1VLm6UvPXyWPvSMlSXwwJh0OcuhLR9CrvA4YMMBYc1yvWDZ06FAjju5vLykpMZrq0UTPQAIkQALpTODf//6nPPDARDl0yOrYhiFpp556WkC0o+WV8qd/rJZNW3YFzmGnXkGejLvmLGNrucCDjCTgqSZ3WONz584NNKlrJY7lTIcNG2Z4uaMfPVxYtGiRGnc5SoqKiuStt94KF43nIxBgk3sEOEGX4m2GC0omLQ/9Knuy5MYQtClTHlKTbT0b8nzUq1dPebI/Iuef39W4VqGme/3rP9fKu5u+scQtqJ0rd6pm9sYn1LGcj/cgWbLHWz4374tX9mQ3uXvCQsf489mzZwvGoyNoRY5mdQxVQ1O6k6DXMNf9607uYRwSIAES8BKB7du3ybhxo2T16g9CitWp0xlK0f9eGjVqbFzDGPLHX94Qosxr5+UY3uyJUuYhBeEJTxLwhEJHMzmc27QiD25Wj5UcLHoGEiABEkg3Am+9tULuvHO07Ny5M6ToAwZcq/yG7pSaNasc2/C+/PuSTbJi7XZLXCx3etvAMzh1q4WKPw48odCBGk3pTprVI1UL+tvRtw7LnoEESIAE0oUAlPOcObPkj3/8vWB4mjnk5+fLvfdOkiuu+Kkxq9vhIxWSk1NDXnz9U/nP+1+Yo0puTpaMvLqznHpy5HHqlpt4kDEEPKHQp0+f7rhZPRJ5jF1funRppCi8RgIkQAKeIoDhuBMm3CWvvbYspFzNmjWXqVNnSK3iJjL7pXXyzsavjQVWsIBKReX3lvg498urOkpbNRMcgz8JeGJiGfSRwyFu3759UWsB/e3wgOfiLVFRMQIJkEAaEFi06GVbZX7xxZfI00+/IDsriuX+J9+R5Wu2B1ZLC1bmmIJ9+JUdpPOpJ6aBxCyiWwQ8odAhXM+ePY1x5tEU9ZYtW2T8+PGGN7tbUJguCZAACSSLQL9+AwVLnOqAIWm/+tUomTbtT7LrYA157KX1Ida4jqu3P72wpZzbtqE+5NanBDyh0OHhjtC1a9eoi6/AYa5p06Zq6sMyNq/79KGl2CSQSQTgEDxp0kPSosUpUlxcLH/60yw18+VNAsW+ZNWWqMocLL7ZeTCTkFCWOAl4QqEvWLDA8HLHEDUnAc5zcCJ5+eWXnURnHBIgARLwNIG6devK73//Z3n22fmBdc0xJA195k7CKhUP8Rn8TcATTnHoP0fQs79FqxIdT88iFy0+r5MACZBAqgmsWrVSDTnLkzPOOMu2KC1btrKcP3q0MtBnbrlgc3BExUV8DFlj8C8BT1joeiIYp2udd+zY0agx9KczkAAJkICXCaA18YknHpPhw29U48hHyrffWmd0sys75mV//j8f212yPVczN0ty1R+Dvwl44gnQE8E48XJHdWlFru/zdxVSehIgAa8SwDtt7NgRqjl9ijG+/JtvvpY77rhNWdNHwxb54y92y8TH35ZX37OOMQ97g7rQpU1DyYKrO4OvCXiiyR0WN4ajLVy4UJwsgaqniIVzXKIDWguwRCvKgznhd+/eLShfaWmp4y6BaGVC+fXCM/qjBP4DTn0IoqXP6yRAAqkn8PHHH8mYMbfK5s2fWwrz7rvvCBZd6du3v+U8Flj5538/lUVvlSkfIculiAcYf96rS7OIcXjRHwQ8YaFjHDqapSZMmCAbNmyISB7W+dSpUw0nukGDBkWMG+vFtWvXquEjPYzb5s+fr2ZumiPYdujQwRhWh8VfqhtGjBghI0eOFJR92bJlRvrIA177U6ZMqW7yvJ8ESMADBBYvXiDXXz8wRJnDo/2WW0bIz352taWUm7fvlclPrpKFK0OVORR2OOMb14Zc0Y7TvFpo+vfAM6utYRw6nONgFQ8fPlxuvPHGkFrBWuiPPvqoYTU3b95clixZEhKnOie6dOliWONQ5MEByhbD66CEtVNecJxox3379jW6C6DAzWnAYoeSR+vAxo0boyXj6nWutuYcb7wrMDnPwbsx/Sp7NLnRlD5t2hR55pmnQioP77YHH5wq3btfFLhWXlEpC1Zsln8v/9x2eFqrkwtlyI/bCaz3pWoIG7zZ4QCHPnM0s8Myb35S+BUoAxklYCea7AnIwrNJxCt7Tk621KtXO2lyeaLJHdJCiULhoYkbyhN/UHr4g1Wu+81hyeOH8fjjjycUEvKDQg3X7A2LGgodrQh2Cj9aYXAfWgAmT55sUea4D5a/dgzEVjfDR0uT10mABLxDAP3jWCXtf/97L6RQ7dq1N6ZwbdLkeDfhF9/uV5PGrJPPlXUeHGB5/+yiltLn/OaSrcajIwy5or2UQLkrhQ4HOPaZB1PjsWcUOhT3q6++aijyefPmGTWDZmgocihxHTBfO+Z+T3T/uZ7cRi/BqvPTW/1xAWsaZcKx0wBFjnXeoajtPhhwDmlCNipzp1QZjwS8Q+Ddd1fJ7bffJt99921Ioa66qp9aQW285OXlGdcq1RzsmDBm/v99KrDQg0OzhnVlqFLe2AYHKHEOTQumwmNNwDMKHQXCimuwYGENQ3GuXr1aMNYc5+GYdtlllxmzyenCJ2qLvBCiKVPdWgCLGk5yTgOc7BBQfruAPvp4rH67tHiOBEggeQRgbPztb3OUkfGwVFRUWDLGmPOxt98r/a7uF7Cmv9p5QB57eb18vHW3JS4OoKwv79pCrux+iuRke8K9KaSMPOFtAp5S6BoVLFX8JSvAgkaIZnXjwwIBHxpOA5rQFy9ebETnsq5OqTEeCXifABT4XXeNVb48Cy2FxcpoLc78iRQ26SyL1FDyVx95Xc5V/d31CvJk6TtbbCeLaXxCbcMqb9m40JIWD0ggFgKeVOixCJCIuFpBo28+UsA8ywh6ZrtIcfW1NWvW6N2oHwyBiNwhARLwPIHs7Gxp1KiRpZz1mp8rLbsOFqmRpZrTqy7BiQ0rpdkFjByHY1vfH7RSjm6c5c2OEc85J0CFrlhhPWInQVvo2oHNyT1vvvlmIJpusocDHvKEAyA+ItB8T+s9gIk7JJA2BEaMGKOcXdcI+tBhmbfqViLfi7MJXhoU5ysP9vbSulmVoZA2QrOgniVAhR5H1UAROw3mjwU4vmEMPZz6dH89+u9LSkrU6kpDlYfsOKfJMh4JkIAHCOTk5Mhvf/uIMa3r2ZffJp9En9XVKPUPz2oiAy45VfJr8hXsgWrMmCJ46mlCU/asWbMEzdROFl7BJA1O4kWrrVgUNNKKxUKHEtcBznFmZY7zsMzHjh1rKHo06cfibKfTTeS2sDA/5uSy1BAbBGwxXtMvwa9y67rWWz/UOfrL0cRuV+eFRbVkxuy5MnHWWwrJ8RE54X4HuTlZMmLgWYG0wsXz2nk72b1WRrfKky6ye0ahw3Fs1KhRRn2Yh6m5VUGpSBdN7toyN+ePoXKw3PGHIWx2cczx3dzProZ3LT6wsrOdNTe6KUOy0/ar3OCcKbJjKNkRtSAK+rH1y1s/R2+//bbcdtttgomt2rZtawyj3fLVXvnfR9/IB5u+ldWffCsHD5fr6FG3mCSmQuWXm6Z95plS51EryiaC12X3hEKHFYuZ0hCgzLp27Wo4kKE5ev369TJkyBDjGixjzLGO+JgpbsCAAcb56v6L5gyn09fN57EoXN3vjjS6d++uk7Jszd71GK+eSiu9wmZcrKWwNgd4AeJBx4cYXox+CX6VG/WbKbJ/9uVu+dcbn8ryD7cJVjjLU0q2W+fGcuVFreQU5XGOCaweeODXUiOnjtxy5zTp0/dGWfvZLtmx51DcjznywMQx8fzW4s40ATdmSp3Hg6I6slfHSIq1rJ5Q6GhmR4DCw1ewDrBYodBvuukmqVv3+CQLmFEO58NNAqPvd7o1K10n9zj9AEBa2jMe+2bFjWNzwEcCPli0x735WjL396gXVbl2z3WYcdW0iDUMZb5jx36Hd6V/NL/KjZrLBNlXrtuuZmpbb5lyFUr9tXe3yuvvfyF5Bz5Sc7GXyek971QObycbD+wbH9h7q8fyNJ/bpoHs2nUglls8ETcT6jxekPHKnpOT3KlfPTF7AaxuWHjoX7YLu3btspxGnzOswUTN5a6Vrrm/25LhsQNdjlgsdEwao0OkDwF9LRE+ATo/bkmABOwJlKkm82Blbo6JlqaD+adJwzY/Cihz83W7/Yb1aoVdREXHh2XOldE0DW4TTcATFjoUKRSa2QqHoGhWR4CSM0/1qod4YUiY3SIuxk0x/NNKN5pznG5yx6x1ToM5LtKP5WPAaR6MRwIkEBsBTL2KfuzqBEwU0+GU+tL+lHrSTm2L6tQUO6tf5wFlzpXRNA1u3SDgCYWOpmi7yVqgDGGJw+v90ksvDZE/mkUdckOYE/oDIZr3us5Pxw+TnOW0/ljASdwfrtldf0wkc4Y8S0F5QAI+IVCp3invqFXLYg218rKl82kN5KzWDaTTqSdKvpoHBi2L5nBB+0Zy8gl1Ur4ymrlM3PcPAU8pdPSLt2vXLkBfKzc4io0ePTpwXjdLawUbuBDnDpQsFC+mgMWfWQnrJKHsdX52ffe4hj87ZY/13uHFj7TtriNt/TFx+eWX6yy5JQEScIEAVivD7G1Ow8Ud68mFZ8FJrkAanFigRnJkGQ5t4fxFsJwpV0ZzSpfxEknAE33o8GpHWLjQOicyzuEalN0jjzyCQyPce++9xjactXssWkybYcOGGfEXLFhge59ewAX998EB5cN67iUlJcZqccHX9YQxOo3g6/o8lL3dx0JwfB6TAAnETwBLj2I9cSehphozfv2Pz5RTmxQFljF1ch/i6JXRuMypU2KMV10Czp7q6uYS5X6sroamdVjiwUE7wMET/vzzzzcseFjyaOqC5ZuoAEWKMeBYRlVb4jptKOzx48cblrvdkDLzfO269UDfiy0+PCAHFHewjDpt9K1jpTkGEiABdwlAwTYsruUoky5tGwZWSnN0AyORQAoJZE9UIYX5G1ljneDTTz9dzj77bGnRooXUrFkzUKSGDRtKgwYN5LXXXpPDhw8HzkMBJ1oBXnLJJXLo0CGZMGGC8cGQn59v5HvHHXcYZXviiScC+Zt3oLB1+e655x7bfvJzzjlHIAvS/uijj4xWB7RIIG20Qjz55JPGdXO6qdg/dOhozGPJa9WqaYxLxkfZwYNHU1HslOTpV7kBO51lf19NCLPsna1Rnxk4sZVc3k6K6latY57uckcVOEqEdK7zKKJFvRyv7FlZWeq3khs1/URFqKFewtVz9UxUSaKkA8tXN03DMk9kc3tw1rCakRcsdVjOaApPVH7mtJEm0vaS5/tOtV5zfOPQI/crBjPOhOOqsan+kxt1l66yb99xQO5/cpWa2c26dnnw86g90uHkZg7pKrdZhnj3KXvsv/WcnOSOQ/eEU5yTByyZa6RDwbrVl+1m2k44Mg4J+JXAoSPl8qf5q0OU+f7vPpeCE5pJpWQbfetd1NrlGCsO5zYGEkgnAp5Q6A8//LDRBI3+afN483QCybKSAAl4lwAaIp9YuEG++NY6k2GnFnXljPNayA8v+ZHA+x0Oc3Ri8249smSRCXhCoS9atMgYh45x5/37949cYl4lARIgAYcEduz4Tr74Yqt8ebCevL3eOva8aQM1P/vV50heTTWgXAW9dZg0o5GA5wh4wstdjz03e4t7jhQLRAIkkFYEVq/+QK655moZd99v5PnXPraUvVZejvyybycqcQsVHqQ7AU8odCy+giaxefPmyYYNG9KdKctPAiSQQgJV75Jn1bwQPzdWRWvQeaAEz/I67Cft5aR6tVNYSmZNAokn4AmFDoc3TO2KHyKWUf3iiy8SLylTJAESyHgCBw8eVHNG3CkPPjjJmKu9VfdSyc0vtMh9ZfdT5IzTTrSc4wEJZAIBTyh0gJwxY4YxhGvz5s3GrGuYGQ6rsO3bty8TOFMGEiABlwls2VImN9wwSF566f8ZOTU9q5/UObGlJdfOp54gV15oPWeJwAMSSGMCnnCKwwxwOmAGOFjqmBlOr5OurwVvEdduZrbgeDwmARLIbAKvv/6q3HPPHcoA2GsIWr/lBdLg9B9YhG5QnC+lqqmdXuwWLDzIIAKeUOh6pTEzVyh1BhIgARKIRKCiokL+8pc/qCmb/xqIVqueGkN+7jWBY+xgTvZf9e0sdfKTN2uXpQA8IIEkEPCEQk/0FK5J4MYsSIAEUkxg586dctddY2TlyuWBkmTXrCOtLhwmWdlWxX3DZW2lWcO6gXjcIYFMJOAJhT5gwIBMZEuZSIAEXCKwZs1qGTdupGzb9uXxHFQXXMtuN0penROOn1N7Pc9pKl07WKdwtUTgAQlkCAHPOMVlCE+KQQIk4DKBF1+cp4akXWtV5irPpmf8VAobtbPkfnrTIhnwo9Ms53hAAplKwBMWeqbCpVwkQAKJJ/DNN1+raVqtq/o1b3eRnNj2UktmRXVqys0/6yg52bRbLGB4kLEE+KRnbNVSMBLITALDht0i3bsf92A/+4IfSZNzr7MIi9XSbrmqoxSblj61ROABCWQgAU9Y6NUZa163Lh1dMvC5pEgkEJYA1ph+8MHfGdO6XtKjj+wqvEi2fXfAEn9Qj9Pl9KbFlnM8IIFMJ+AJhd6lS5e4OHMcelzYeBMJpD2BgsIieervL8rc/5TJ+k3fWuTp2uEk+dHZTSzneEACfiDgCYXOMed+eNQoIwk4J7Br106ZNGm8lJbeJO3bdwzcWPbVXlmyaou8s/FrOaKWOw0OGJr2iz5tBR/7DCTgNwKeUOhjx451xH316tXGdLB79+4VDHXr0KGDo/sYiQRIIH0IrFu3RsaMGWF4sW/YsE6effZFKS6uJyvXbZfHXlpvzNFuJ02eWsvcWEEtt2o5VLs4PEcCmUzAEwp96NChjhnv2bNHBg8ebCj2SZMmOb6PEUmABLxPYP785+U3v7lfjhw5YhQW48zvvnuc3D7+4YjKHJGPllfKocPl3heSJSQBlwiknZd7YWGhTJ8+XcrKyuT55593CQuTJQESSCaBw4cPqyb2e2Xy5PEBZa7z37hxg/zrjU1hLXMdD0ukLlXN8Qwk4FcCaafQUVHNmjUz/hYtWuTXeqPcJJAxBL74YqtqdbtG/vGPF0JkOvPMs+XpZ16QdWX7Q67ZnVil+tYruQ6EHRqe8wGBtFToqJeCggLZsoVf4z54RiliBhN488035Nprr5b169eFSHnddTeoFReflG17suSIak53EuAod9TGWc7JvYxDAulOwBN96PFA3Lp1q8A5joEESCD9CFRWVipl/Rf561//aCyXbJagVq3act9990vXC3vKYws2ytvrvzZfjrhfUznG5ao/BhLwIwFPKPRYJ5aZO3euwDmuqKjIj3VGmUkgrQns3r3LWLv8v/99PUSOFi1OkalTZ8jWfXXk7llvycEYndy6tGnI9c5DqPKEXwh4QqHHM7EMxpl27Hh8fKpfKoxykkA6E8AwNAxJQ795cOjRo5cMu3W8zPu/Mvnky9DrwfGDjzHda68uzYJP85gEfEPAEwo9noll4BjHYWu+eU4paAYQgBK/4YZrBB7t5oCpXH/5q7FS95SLZMrctbZObXXyc+QcZX2/uXqbrbc7lPmQK9pJ85MKzElznwR8RcATCt3pxDKoGQxbgzLv2rWrryqKwpJAuhNo0qSpXHllXzXc9NmAKPXrnyA3j/udvP2ZyHdv2zu5YirXgT86XQrV6mmY0hVD0+DNDgc49JmjmR2WOZV5ACt3fEqghrKO1ehNBk0AffMzZ840Jq5BH/3u3buN3qNuvQAAOfVJREFUpv3S0lLjQ0LHS+S2Z8+exth6L8x8t3PnASkvr4hJvPr160i2WqKyoqJSduxwNrwopgw8GtmvcqM64pUdE8YMGXK9rF79gXQ+u7uc0esmWbvZ3rn1pHq15PrebaT9KfVDngAMTYM3OxzgspI4zWu8cocIkIYnKHvs77icnGypV6920mrbExZ60qSNktHatWuNWegwrez8+fMDseGEp5Vunz59AucTsTNlyhRj+B0+HBhIIBMJmJVvzZo15Xe/+7386Zml8p20sFXmOdk15PILWsiPu7aQXPVCtAtQ4nk17a/Zxec5EvADAc8odAxDKy4ulmjLoa5YsUIQFw5x7dq1S2gdYUpZpDtu3DhLugMHDjRmphs5cqQsW7YsYZY6PiBmz55tyYsHJJDuBDAkbfPmzyW7dgPLQipoHm/bvJ58s/OgbDvaVIkZ2hLUtnmxYZU3PqFOumNg+Ukg6QQ8o9BhAcM55sUXX4yoqDGZzIQJE6RFixayePHihAGDpYzmdihvuzBo0CBD+SLvOXPm2EWJ+dzUqVNjvoc3kICXCeA3NH78HbJp21Fpcs61ysHteGnR5/3hJ98dP2Haq1srV/WTnybdOjbiSmkmLtwlgVgIeGIGBm2lwtEtmtWN5vCmTZsaFvPSpUtjkTViXF2GcE3qerrZ5cuXJ2SGulmzZgnygpMfAwlkAgHMuX7ddf3k7Q82SaMzB1qUeST5LurcWB4cdoF079SYyjwSKF4jgSgEPKHQFyxYYPyQw1nHwTIMGzbMmF3q5ZdfDr4U1zGUNEI05QqljlDdOeTRyoA8ncprZMp/JJAEAujvPnykwnboWKTs//Wvf8rQm26WPZX1pMX5N0iNrOj927XysuXO686WksvbCSx0BhIggeoR8ESTO/rEEbTCjCaSjrduXej8z9HutbuOvmwEna5dHJzD/PEIWJe9OgHN9pMnT65OEryXBBJKoOyrvSH93eeq4WCX2gwHg9L/4pt98vm2PbLx8+9k6Rvvy94juXJ67/ExlalCtcef1pSzPcYEjZFJIAIBTyh09Lth5rdoze1aDj1DXKIWZ9EKOtpUsnDaQ9AfILo8sWxh3Xfr1i3qx0MsaTIuCVSHwMp120PWGkd/9/I12+WtdV/JVRe1kqK6NWWzUvpl2/fK5q/3GVZ8IM8a9SQnL3DkeEcvpEJvdcfIGJEEIhLwhEJHUzcWWsGc7tG83CGNVuTRmsgjSm666HSRF22h4wMknoD7Hn30UcuQuHjS4T0kkCgCsMwfe2m97exryANW9Auvf5Ko7CzpcCEVCw4ekEC1CXiiD11b3AsXLnQkkO7zhnNcKkK8Y8bvvfdeuf/++1NRZOZJArYElqhZ16C0ExVys7+XIjWjm5PAhVScUGIcEnBOwBMWeu/evQ0nMfQtd+rUSdq2bRtWAljnGO6FJnoMJUtEiFVBx2Oh4yMETfZemA0uErPCwvxIl22vZal5tBGwxWxSfgnpLnelUuTvbvwm7uo6enC3HNi5Rf2VSd2cwzL57pHS7bzORt/62BlvRPxQwNzr/Xq2TrvnJd3rPO7KVjdSdu+/4zyh0OHtjWFc6Ju+4YYbZPjw4XLjjTeGPHuPPfaY0WSNC3Bg69+/f0gcr57AR4h59jmvlhNTuMYb8JGVrWb58ltIV7mPlpfL4aOhk7uEq78jOz6Sb7euVwp8q6HEyw9VdT316tXLmLpY+6Cc1qye3HbN2TLt2fdslTqUOa4jXrqGdK3zRPCm7N59x3lCoeMhw2Qtffv2NeZOxyQv+IPSxh+sct1vjqnn8eJ4/PHHE/FsGmnoF1G0BHVfe6x995AllgVoopXDzeuYjz3WgC93/MhRN7D6/BLSXW4o1rzcbEdKPbtGpaxZ8ntVtcfrF3V+++23y80332JMCmV+di4842Rp0qCO/OuNT2X5h9uMPJBXNzXm/ErlZNfy5CJj7v90e1bSvc6rw5uyx/eOq46RFGt9eUahQ3G/+uqrhiKfN2+eIUdZWZmhyM3rx7Rv396wBhLZf66d3ZzCc/oBgPQwJA4fI/BsT4ewZ8+hOBdnqWEoc/8tzpLecp/d+kRZsfarqI/m+R1OlqKevdTUx0uMuPXq1ZM///nP0r37hWEX5ClSS55e36u1XNfz9JCFVNL1OalaoCS96zxqZYeJQNljr/ecHB8vzgLFivHZ6BtHnzOGk2GsOc7Dce6yyy5zZdlUPRxNtwKEeZ5l165dxqVYLPTx48fLE088ES5JnieBlBKo78BnApY8xqNfc8mD8vHHH0mdOnXVNMizpHnzZo6sbC6kktIqZuY+IuAZC93MHFY4/pIVtKNaNOc43eSuvfKjlQ8fCLDQu3TpEi2qlJSUBOJMnz7dmBY2cII7JOACgaPlVWPNIyUNZT7kinaBtcb/8pfH5IQTTpRGjdK3/zuSvLxGAulMwDMKHQ5xqVptTTeHR/Ne1xa8jh+t4tGNsHHjxrDRkJ9W9vAhcJpu2AR5gQRiIPDGh1/Kzr2HLXeoRkXVS54lGCOOYWW9gmaKa9z4ZEt8HpAACXiHQPwuzQmWAautnXfeebJ+/fqIKUOpohl71KhREePFchGKV1vpehrY4PuhfLVCt1vABdf0+Pjge3lMAl4jcLS8Ql5esdlSrJwj38i7z90qW179tUy6vp2yzNsHLHNLRB6QAAl4koAnFLpe6SyVq61hwRcELBRjF7SytvNWh7LHBwmazeHRzkACXifwfx9sC7HO173xd1Xs7+Wbr7+Uu+4coxzZjnpdDJaPBEjARMATCj3Vq62BB6xujIfHx4W2xDUnKGy0CsCKLy0t1acD2zVr1gT2Y1kwxnxfuJaBQMLcIYEEEaiyzj+3pLb3q42y75uPAufef/9dWbXqrcAxd0iABLxPwBN96HqxEzR9Owk6XizK00m68LCHRz3Gw8NiR582lC4mvUHrwYwZM2yTQTwoe3wI2Cn84Jt0vzk+FHTAxDP4gwc9vOJ1F4C+zi0JJIrAf/73pezad8SS3LY1x5cixrDMBx+cqp7/Cy1xeEACJOBtAp5Q6FBsmKQiVautmato3Lhxxkx1aGLHHxQsHNb0R4Q5rnk/llngXnnlFeNWu+FvYGF33pwX90kgXgJH1MxwLy3/zHL7nq82KOv8Y+Ncu3bt1YflDGnSJDXrJFgKxgMSIIGYCHhCoUOBpXK1tWBiKI+d41twvHiPIynsSNfizY/3kYAm8PeXVsreA+X60NhuW11lnV91VT+5887xkpcXx1qolhR5QAIkkAoCnuhD1+O602W1tVRUFPMkgeoQwGyLTzz1hLz2v68tyezZvl6O7tkiEybcL/fd92sqcwsdHpBAehHwhELHamt44WC1tQ0bNkQkiH7qRK+2FjFDXiSBNCewf/8+Nef6bfLMS29Lbq0iizRHtr2lfDaeUX4j6bPQkUUAHpAACQQIeEKhw7scc7NDqWO1tXALr2C1tX79+hmFR592Oq22FiDOHRJIIoGDBw/K9dcPlGWvviIntetlyTnr4DZ5auZ0NStjR8t5HpAACaQnAU/0oQNdKldbS8+qY6lJIDqBWrVqyUUX/VD25X4eYp3fPvRyNTsjp3CNTpExSCA9CHjCQgcqWNxYbW3AgAGGpQ5rHautwdMcWxzjD3O8v/DCC4ZFnx6IWUoSSC2BYcNHSNNOl1sK0bFVfWmdxuuRW4ThAQmQgEHAMxY6SpOq1db4LJBAJhP4v9XbRXJqWUT86YUtLcc8IAESSH8CnlLoGmeyV1vT+XJLAulMwG4Og0NHymXhyjKLWJ1anSCnnmx1jrNE4AEJkEBaEvBMk3ta0mOhScADBNAV9fTTT8nll/dQ65VvspTo1fe+kH0HrXOy0zq3IOIBCWQMASr0jKlKCuJHAgcO7FeTwYxRiwI9KPv27ZXRo281JmkCi4OHy2XRW1brvPOpJ0irkwv9iIoyk0DGE6BCz/gqpoCZSuDzzz+Vn/98oCxefHyFwLKyzWohoTulsrJSXn1vK63zTK18ykUCNgQ81YeORVqwEAoWRHGy8Armf3cSz0ZuniKBtCbwyitL1ERMd8n+/ftD5Dj99NbKOj8aYp2fedqJ0rIxrfMQYDxBAhlCwDMKffHixTJq1CgDK/oEGUiABEIJlJeXyx/+ME2efPKxkIt16xbIAw/8Vi6++EdqAZbPZf8h65zt7DsPQcYTJJBRBDyh0DGd68iRIw2wWJwES5ViXDrGoK9fv16GDBliXIMX74oVK4xlSps3b26MWc+o2qAwJBCBwHfffSt33DFa3nnn7ZBYrVu3lYcfnqF+N82NvvPFb1v7zs86/URp0agg5D6eIAESyBwCnlDoaGZH6N69u2B6Vx0wZzsU+k033SR169bVp431ynHezRXRAplxhwQ8QOCDD96XsWNHyjffWBdXQdGuuOKncs89EwWzwiEse2cLrXODBP+RgL8IeMIpDlY3+sOnT59uS3/Xrl2W82PHjjVmjVuyZInlPA9IINMIoPvpuef+rlqpfhGizHNycg1Ffv/9vwko8wOqmX3x21ssGM5u3UCan0Tr3AKFBySQgQQ8odDR5I6mdrMVDtZoVkcIdnzr1q2bcf7NN980tvxHAplI4ODBA0ph3y6/+c2vpbzcOpb8pJMaqfUP/q4WKBpkfAxr+WGdH1DD1czhyu6nmA+5TwIkkKEEPKHQ0V+O/vHggHXSYaHA690u4EOAgQQylcBrr70iCxb8O0S88867QJ59dr506nSG5dqBQ0dl8Srrb+IcWucWRjwggUwm4BmFDsjoFzcHTAGLMHfuXPPpgMVOhW7BwoMMI3DZZVfIT37yM4tUN95YKn/+82ypX7++5TwOlihljslkzOFKztluxsF9EshoAp5Q6PBqR1i4cGEIbFyD9f7II48Ert17773GPix7BhLIVALwK4GzW5s27YzuqGnT/iQjRoyRnJxQX9b9yjpfqprbzeHcNg2kWcPjzqTma9wnARLIPAKeUOiDBg0ymtaDLXHg1g5w8IQ///zzpV27doYlj5dd7969M69GKBEJmAjk5+erj9k/qLnaX5BLLulhumLdXaIc4Q4ergicrKH2aJ0HcHCHBHxBwBMKHcumwsN9zJgxaj7qfRbwHTp0kEmTJhkKf/fu3cYW/epQ5ojPQALpTmD16g/k7bdXhhWjSZOm0qLFKbbXK9Vv4bs9h5R1Xma5fm7bhtK0Aa1zCxQekECGEwhtu0uRwJGs7YEDByoHoE7GRDMoHuKyuT1FFcVsE0YAH6bPP/+c/O53D0qdOrUNR7eTT27iKP2yr/YafebvbPxajhyttNxD69yCgwck4BsCnlHo0YhzjfRohHg9nQgcPHhQTdM6UV566f8ZxUbrEyaOmTPnacnLy4soysp12+Wxl9ZLRaX9FMlYTa3JiXUipsGLJEACmUfAE03umYeVEpFAeAJbtpTJDTcMCihzHXPdujUyb94z+tB2C8s8kjLHTZ9t2yuIx0ACJOAvAlTo/qpvSptiAq+//qpcc83VsmnTxpCSDB48VF27PuS8+QSGpoWzzHU89KsvDRqPrq9xSwIkkLkEqNAzt24pmYcIVFRUyB//+Hu1CNEtyvHTaj3XqVPHWFhl1KixtkPStBhQ1OgzdxJWqXiIz0ACJOAfAmnTh56sKsGY95kzZxqruhUVFQn6NjFjXWlpabUd8bB6nF7vHfnAgz9RaSeLD/OJncDOnTvlrrvGyMqVy0NubtXqNDUsbYacckqrkGvBJ44q57dgB7jgOPoY8RA/r2a2PsUtCZBAhhOghW6q4LVr10qPHlVjfefPn68clOYItlC8PXv2lEWLFplix7Y7ZcoUQ5ljXP2qVatk2bJlAu99jL1H2nrFudhSZWyvE1izZrVce+3Vtsq8T5/L5e9/n+tImUPO3Nwsqan+nATEQ3wGEiAB/xDgL95U14MHDzYs5nHjxpnOiqF4hw4daqzZHs90s1DauA8fCPg4QMCwOyh0nEPAUrHV+WAwEuE/zxDAkLQXXpgrJSXXyrZtX1rKhZnebr/9bnnooYeldm3n3uhZajKlc9s0tKQV7qCLiof4DCRAAv4hQIV+rK5hQaMZHErWLmA2O4QJEybYXQ57DmnC+p4xY4ZtHKwcp1ePGzlypO0iNbY38qRnCUCZT548Xn796/tUs7d1lbQGDRqo5+EpZbX/wrJKmlNhLjkr+jj17Kwa0qsLp0V2ypTxSCBTCFChH6vJ2bNnG3t9+vSxrVtY1PhDP3gsVjpWikP8Ll26CJr07YL5I8JuPnu7e3jOuwQwLXGjRo1DCnjOOecak8ecddbZIdecnvjgk28jRoUyH3JFO65/HpESL5JAZhKgQlf1CiWNgDXZIwU9O10sTeNa+WtnO7v0dbq4Fk7p293Hc94lUFp6s1x44cWBAv7iFyXy17/OkRNPbBA4F+vOVzsOyKK3yiy36VZ19Jl379hIxt9wrlzQvpElDg9IgAT8QYBe7qqetRI1K1a76sec8wirV6+2u2x7Dl7sOnTv3l3vWrbRPiQskXmQFgSysrLkwQd/J0OH/kKNkLhZevWyb/lxKgya8Z9Z9pGUVxwfigZrfMLgc6VhcW3DAY595k5pMh4JZCYBKnRVr1pBY5hapFBcXGxc3rp1a6RolmtwgoNXO4a/hftg0B8UuFE7zVkS4YFnCWB8uYi981lhYZE899w/BMq9uuF/H38rqz/9zpJMj3OaquVRqz4yLRd4QAIk4EsC1X/TZAC2vXutE32EE0lb6Gg+jyXAAg+nzJGObvLHvnaQwz6Dtwl8+OGHaknTS+SDD/4XtqCJUOZHjlbIs8o6N4eiOjXlpxe2NJ/iPgmQgM8JUKHH8QDA2k5k0I5wcI6LpPgTmSfTqh6Bf/zjBbn66r7yySefyE033SSYPMatsGDlZvl29yFL8gN+dJrUymMDmwUKD0jA5wT4RlAPQKwKOlYLPdIzpofLQZFj0plUh8LC/JiLkKX6chGwrV/f+bjqmDPywA2HDh1SQxfHq6b05wKl+eKLL9S52+Wpp/4m2dmJnZlt+3f7ZWGQI1z7lvXl8gtbxTXsLVDoau74qc7NqPwqNxhQdu+/46jQzb/WJO/DAx7D5dAkjwlmvOAcl50df6MNhmtlZ9v3JycZrSvZob6GDRsmaGoPDlD0Bw7sF+1nEXw93uM5L62To+XH1zvHS/Wmvp3VnO+J/XCIt3yZXufhuPhVbvCg7N59x1Ghqwc0mjOc/lHrvvZEKd6SkhJDiWN6Wa80tVdUHFceWu5oWygZ/MjhiV0ZZo3uaGl4/fp//vOajBgxQnbt2hVSVMwieNdddytP81yJh19IgsdOvLP+K3lr7XbL5cu7nmKMMU9kPpYMHB74oc7tUPhVbrCg7PG946pjJNk9g5HOUaErOtrZLRIo8zWnHwDme4L3oRzQ1O8lZY4y7tlzSMrL4bntPKCZHZY5lPmOHfud35gGMSsrK9XMbn9RY8j/aHywmItcu3ZtY8reK674yTG5j5gvV2v/qKqDR/9hHR5ZWDtX+nRp6gnGmVznkSrOr3KDCWWP/R2HlrR69WpHeqQSeo0KXeHUzaRoUo0UtHVWXQsd/ebr1q3znDKPJLsfr+3Zs1vuvvt2+e9/Xw8R/5RTWhpT+rZv3y6hVrnOaNHbW+TrXQf1obHt98PTpHZ+ruUcD0iABEhAE4i/w1SnkAFbPfY7mnOcbnI3TxYTq/hYqGXx4sW2yhzOdrHMQhdr3ozvnMCGDevkmmuutlXmPXr0UqukPS9t2rRxnmAMMb/dfVBeXv655Y5TmxRKt06cAc4ChQckQAIWArTQFQ499jua97q24HV8C0kHBxhvjoVa0MxuZ+Xred8dJMUoLhL45z9fVCuhTZbDhw9bcsGY8hEjxsgNN9zoqof53Fc+liMmRzi44Py8VxuunmapDR6QAAkEE6CFrojAIU1b6eZZ28ywoOy1QrdbwAXXzBPEmO/FPq5jidRwyhxx3nzzTc84x6E8fgyrV38gEyfeE6LM69c/QWbOfFwGDx7iqjJf89l38u6mbyzof6hWWGvRiDPCWaDwgARIIIQALfRjSDAcCcuXLliwIKDczbS0srYbKw5l37NnTyM6PJ6D11PH9b59+8qAAQNETyJjThv7ZWVlMm/ePNHLtAZf53FyCHTqdIZaQvdamTv3mUCGnTufKVOmTJeTTjopcM6NnXI1wuCZpdYZ4erWypWrftDKjeyYJgmQQIYRoEI/VqGwujFTG8aFQ6mah5FBIY8fP95Q9KWlpSGPAJrKdYCzW3AYPHiwsc65XqI1+Lr52Jyv+Tz3k0dg7Ng7Zf36tWq8+QeqH/3nMnr07WpIWk3XC7Bk1RbZrlZUM4d+PzxVoNQZSIAESCAaASp0E6HJkycbQ9hgTcNiR185lDX6vbt27SozZswwxT6+i3hoskezerDChxNcuGb84ylU7dn1qwfH4bH7BKC8YZG///670qfPj93PUOWwQw0X/Pebn1vyatm4QC7sHLquuiUSD0iABEjgGIEaajKQ4+sxEotBABY5mtihoKFkobD9Yjnv3HkgznHoWcbwrXQZh446/uSTj+Wss86O+6mvGpebGLn/+v/WyNvrvw6UBY5w96q1zVs2Lgyc89JOImX3klzRyuJXucGFssf+W8/J4Tj0aL8p169Dids5vrmeMTNICoGNGzfImDG3qlnfdsrTTz8vLVq0TEq+4TJZv3mnRZkj3kVnnOxZZR5ODp4nARJILQF6uaeWP3NPMoF///uf8otfDJStW7fIvn37lGIfIQcPWvutk1kkOMI9vXSTJcs6+Tly9cV0hLNA4QEJkEBUAlToURExQiYQOHLkiDzwwCTl3HinZUjaxx9/JI88MiVlIr7y7lb58lvrdLl9lVd7QW33nfBSJjQzJgEScIUAneJcwcpEvURg+/ZtaijhKMEY8+CAYWpDhgwLPp2U4137Dsv/++9nlrxanFQgF5/ZxHKOByRAAiTghAAtdCeUGCdtCbz11go19KyvrTIfMOBaeeyxv0mjRqnxJJ/32sdy6Ih1IZzrLm0dWHc6baGz4CRAAikhQAs9JdiZqdsEMHhjzpxZ8sc//l6tAmddEjY/P1/uvXeSXHHFT90uRtj0N5btlJVrv7Jc767maj+tSZHlHA9IgARIwCkBKnSnpBgvbQhgEZ0JE+6S115bFlLmZs2aqyl4Z6iFVdqGXEvWiQr1gRHsCFcrL0f6q9XUGEiABEggXgJU6PGS432eJPDRRxsNz/Wyss0h5bv44kvk/vt/a7swTkhkl05UqpYDzAi39RurI9xVF7WUwjp0hHMJO5MlAV8QoEL3RTX7Q8iFC1+SSZPGy6FD1nXEsUraLbeMkBtvHKb6p1PjNlL21V5Dkb+z4WvLSmqomaYN6solZ9MRzh9PKaUkAfcIUKG7x5YpJ5nAt99+E6LMi4uL1VKoD6upe7snuTTHs1u5brs89tJ6qai0n5Tx7NYnSnaKPjSOl5J7JEAC6U4gNeZKulNj+T1J4Oc/H6xWvesdKFuHDp3k2Wfnp1SZwzKPpMxR2JdXbBbEYyABEiCB6hCgQq8OPd7rKQI1atRQTe4PSMuWraRfv4HKy/1padz45JSWEf3l4SxzXTBcX6riMZAACZBAdQiwyb069Hiv5wjUqVNX/va3eVK3bt2Ulw0OcO9sPL7gSqQCrVLxSn7cTrLURwkDCZAACcRDgBZ6PNR4T8oIYP71O+4YLe++uypsGbygzFG4o0cr5Yj6cxIQD/EZSIAESCBeAlTo8ZLjfUkngHnXf/7z/rJ48QJDqX/zjTPrN+kFPZZhbm6W1FR/TgLiIT4DCZAACcRLgG+QeMnxvqQSgBK//vqB8vnnVXOfw6Md87MfPXo0qeWIJTM0n5/bpqGjW7qoeGxud4SKkUiABMIQoEIPA4anvUEACnvKlIcMizx4mdPPPvtENm/+3BsFDVOKS7s0U0PSIveL43ovFY+BBEiABKpDgAq9OvR4r6sE0KQ+bNhgefrpJ0Pyad++gzzzzIty2mmnh1zz0onmavW0IVe0C6vUocxxHfEYSIAESKA6BOjlXh16vNc1AnB6u/322+S7774NyeOqq/rLnXfeK3l5eSHXvHjigvaN5OQT6hhD0+DNDgc49JmjmR2WOZW5F2uNZSKB9CNAhZ5+dZbRJcYqaX/72xyZPv1hqaiwLi1as2ZNueuuCXLVVf3SjkGVpd7eGJoGb3Y4wLHPPO2qkQUmAU8ToEL3dPX4q3D79++T++67R5YtWxwiOCaIefjhGdK+fceQa+l0Ako8r2Z2OhWZZSUBEkgTAlToaVJRmV7MTz/9RK2Sdqt89tmnIaJ2736RPPDA76S4uF7INZ4gARIgARKoIkCFzich5QQwBO366wfI/v3WJUVRsOHDf6kc426R7GxatSmvKBaABEjA0wTo5e7p6vFH4U48sYEMGHCtRdiCgkL5wx9mys0330plbiHDAxIgARKwJ0CFbs+FZ5NM4Je/HCldupxv5NqmTTu1StqLctFFFye5FMyOBEiABNKXAJvc07fuMqrkOTk58tvfPqJWSJslv/zlKMnPz88o+SgMCZAACbhNgAo9iPCePXtk5syZsmLFCikqKpLdu3dLx44dpbS0VJo1q95sXm6mHSSGJw8xJA1Tt2J5U7tQv/4JyjHuTrtLPEcCJEACJBCFAJvcTYDWrl0rPXr0MM7Mnz9fWYtzBNsOHTpIz549ZdGiRabYse26mXZsJUlN7AMH9qvJYMbINdf0lU2bNqamEMyVBEiABDKYABW6qXIHDx5sWOPjxo0znRUZOHCgDB06VEaOHClbtmyxXHN64GbaTsuQqniff/6pWiVtoLFK2qFDh5QVPkLQWsFAAiRAAiSQOAJU6MdYTpkyxVAyUN52YdCgQcbpCRMm2F2OeM7NtCNm7IGLr7yyRK67rr98+unHgdJs2bJZTSBzt6AJnoEESIAESCAxBKjQj3GcPXu2sdenTx9bsug/x9/y5ctjttLdTNu2sB44WV5eLtOmTTGs8eDx5XXrFqjpW6+WGmrWNAYSIAESIIHEEKBCVxyhpBEKCwuNbbh/2ikulr50N9MOV85Un8eCKjfddKM8+eRjIUVp3bqtMSTtBz+4JOQaT5AACZAACcRPgApdsYPDGoJW2MaBzb+CgqolLlevXm1z1f6Um2nb55jasx988L4MGtRX3nnn7ZCCXHHFT5WSf1Zxbh5yjSdIgARIgASqR4DD1hQ/raAxTC1SKC4uNi5v3bo1UjTLNTfTtmSU4gP0hz/xxBMyefJkKS8/ailNTk6u3HHHPdKv30A2s1vI8IAESIAEEkeACl2x3Lt3ryOi2kKPxUPbzbQdFToJkQ4cOCB3332XMcQvOLuTTmokU6dOl06dzgi+xGMSIAESIIEEEqBCjwMmJptxK7iZthtl3rz5c2V9j5INGzaEJH/++V3loYcelvr164dc4wkSIAESIIHEEqBCVzxjVaKxWOhupp3YRyG+1N59d5WtMr/xxmFqCteRXFglPqy8iwRIgARiJkCFHjOyzL6hsDC2OdSHDLlBKfTVMm/ePAMMuiWmTZsml17aO7NBKemysqqG3WFbv36djJfXLKBfZfer3Kh7yl7FwMu/dSp09aBGc4bTLzLdHx5teJuOj62baZvzSdR+dnbsAx8efPBBY6RARUWFzJo1S1q1apWo4qRFOhhPn53tzzH1fpXdr3LjB0nZvftbp0JXD6h2dnOqPZwqaaTnZtpOyxtLvIqKyliiG3GxMtqTTz5pjOPPz68l8aQRc6YeuAEWC15u8PCvrPTXrHd+ld2vcuPnRtnj+63HYyTF+3qjQlfk9HC0aPO079q1y+Aci4XuZtrxVnqk+/bsOaSGnVVEihJyDU1QjRs3NhT5jh37Q65n6gnIDcscytxPcqM+/Sq7X+X2c51XR/acnGypV682kkhKiL19NSnFSm4mWE0NIZoDm25yx3KqToObaTstA+ORAAmQAAlkPgEqdFXH3bp1M2o6mve6tuB1fCePh47rRtpO8mccEiABEiABfxCgQlf1jClftSWtp2oNrn4oZK3Q7RZwwTU9b7v53kSkbU6P+yRAAiRAAiRgR4AK/RiVYcOGGXsLFiyw4xRQ1mPHjg25DmXfs2dPKSkpESyVGhyqk3ZwWjwmARIgARIgATsCVOjHqMDqxlroWOpUW+IaGBT2+PHjDSu+tLRUnw5s16xZE9hft25dYF/vVCdtnQa3JEACJEACJBCJAL3cTXSwsAiGmfXt21dgVaP/G8oaY6u7du0qM2bMMMU+vot4aLLHh4CdwkfMeNM+ngv3SIAESIAESCA8gRpqDK2/BtCGZxG4Aosc/eFQ0BiiBoUdbWnVwM1RdtxMO0rWji7v3HkgrmFrGGuJ8ed+Gr5VNYTJf3LjQfKr7H6V2891Xh3Zc5I8bI0WOmorKECJ2zm+BUWL69DNtOMqUNBN1Z0EAQ+wH4Nf5UZd+1V2v8rt5zqPVfbqvk+RXyyBFnostBiXBEiABEiABDxKgE5xHq0YFosESIAESIAEYiFAhR4LLcYlARIgARIgAY8SoEL3aMWwWCRAAiRAAiQQCwEq9FhoMS4JkAAJkAAJeJQAFbpHK4bFIgESIAESIIFYCFChx0KLcUmABEiABEjAowSo0D1aMSwWCZAACZAACcRCgAo9FlqMSwIkQAIkQAIeJUCF7tGKYbFIgARIgARIIBYCVOix0GJcEiABEiABEvAoASp0j1YMi0UCJEACJEACsRCgQo+FFuOSAAmQAAmQgEcJUKF7tGJYLBIgARIgARKIhQAVeiy0GJcESIAESIAEPEqACt2jFcNikQAJkAAJkEAsBKjQY6HFuCRAAiRAAiTgUQJU6B6tGBaLBEiABEiABGIhQIUeCy3GJQESIAESIAGPEqBC92jFsFgkQAIkQAIkEAsBKvRYaDEuCZAACZAACXiUABW6RyuGxSIBEiABEiCBWAhQocdCi3FJgARIgARIwKMEqNA9WjEsFgmQAAmQAAnEQoAKPRZajEsCJEACJEACHiVAhe7RimGxSIAESIAESCAWAjmxRGbczCSwZ88emTlzpqxYsUKKiopk9+7d0rFjRyktLZVmzZpVS2g3065WwY7d7Gb5li9fLrNmzZI1a9YI8unQoUPCuFZXdjflDle2nj17yvTp0w0O4eIk43wyZEfdP/fcc7Ju3TopLCw0xBo4cKDgL1XBTbl12pAX7w+Epk2byvDhw1Ne32bec+fONX6Ty5YtM5+Oe1/L7ca7M65Cfc/gawJK2Xx/7rnnfv+73/3OwkG9jL5v3br19wsXLrScj+XAzbRjKUe4uG6WDzwHDx78PfJAKCsr+14zBddHH300XLFcP++m3OEKDx6Q+8033wwXJSnnkyH7rbfeavymgmUFg+DfWVKEVpm4KTfkxLMeLC+Oe/TokTKZwVZ9XAR+e1dddZXxDOI5TERwk2m85ZN4b+R9mUEAyhw/RrugX8JQRvEEN9OOpzzB97hVPihuvNTtAl5yeKHgrzofS3ZpOz3nltzh8seLT8sc/NIPd49b592WHUoDeQT/ZiA3zidKmcTKxy25oTAhM7Z2ARyQN34TyQ76t6Y/KvT7LFF14BbT6nBiH3pc7RqZcdOUKVOMpuBwzYCDBg0yBJ0wYULMAruZdsyFsbnBrfKhCQ7N7DNmzLDJVaRbt27GHy6OHDnS4G8b0aWTbskdqbhTp06NdDlp19yWHb+TtWvXytixY0O6qhYtWhSoazwjyQxuyo2uOnTP6W6FYLnQZTdgwABBU3eyA35rGzduFDSvjxs3Tjp16pSwIrjJtDqFpEKvDr00v3f27NmGBH369LGVBD9G/KE/cMuWLbZxwp10M+1wecZy3q3yKWvUYNWlSxfj5W5XJvMHlLLS7aK4ds4tucMVGB83eL7CvfDD3efGeTdlhyKH0oKc5vrVcuAcFMzQoUOTzsJNudF3XFBQoMW03UKRgk8mBTeZVocTFXp16KXxvVDSCNFetNopDhaG0+Bm2k7LECmem+XTHz7aWcauHJopriXzReem3HZyggXytFNwdvHdPOe27LBUES677DJbMeAQOWfOHMNStI3g0km35cZzPm/evIilh5NctPdMxAQ8dtFtptURlwq9OvTS+F6tSMzKxU4c/fW9evVqu8u259xM2zbDGE+6WT40P+rQvXt3vWvZpurl5qbcFgGPHaAJevLkyXaXkn7OTdmh1BYvXmzIBCvcS8FNuSEn3h+QHyMY9MdssPxouQj3oRMcNx2O3WZaHQZU6NWhl8b3agWNYWqRQnFxsXF569atkaJZrrmZtiWjOA/cLB8ssVWrVhn9duEsU/1CQPERP1nBTbmDZUCLDpRbtA/G4PvcOnZTdnSz6OAVeXV53JQbeehnHMocSh1dLOaAYyh8+BVkSnCbaXU4cRx6deil8b179+51VHptoeNH6TS4mbbTMkSK53b5YIFHssJ1kx3KmEyLzm25NXM8K2pYnsyfP1+fSvnWTdmVN3VAPih0KDc4TSFPNDfjoxlzOiSzrnWB3JQbecA/onfv3oEWCjhAwi8E8w0oz3Zjbgs8B5F+D7qs6bJ1m2l1OFChV4eej+7Fi8mt4GbaiShzosunHeFg3XjNojPzilfue++9V+6//35zUmm3H4vs5hc8lDmUGhSaVmL4gCspKTEc4uBt7eUQi9xaDozogCWuRzOgBQrWOlqfvPRRp8ub7G08TOMtI5vc4yWX5vfF+pDFYqG7mXYisKeyfHq4CxR5spshkyE3lBe6aZLZleDkmXBTdnPfMZzjzMocZYNljrqGZ3Rwk7STslcnjptym8uFj9PgFggo9r59+4btWzffn077yWIaDxMq9Hio8R4SiIMAXvx4qcNyg8eztuDiSMqzt8BK84ojXCog4UPNrl710FDwieXjOBUyxJonFLeavMVofse4b92vjnS0UseWwX0CVOjuM/ZkDtGc4XShdXOi3UtKxwneupl2cF7xHKeqfGh2BUc0Q6aiqd1tudH6kOxWB6f176bs2s8EZQk3ssFc38mcZMVNuSEvWmRghaNVQityfNCZn3F8wGASpUwJbjOtDicq9OrQS+N7zS8hJ2I4fYiRlptpOylrtDipKN+IESMMBynziy5aORN93U25YYGhBSK42TXRMsSbnpuy65EgKJtZcf//9s6eN4odCsN7pVsDPwDaIAXo0oQWJCBdKIAySBBKGiiTAlEBDSUfRVoaygASNQ0lHxJt+AN8/IDcfUf3rLwTe2dnxvass48lmC/7+JzHmXnHHs9s3Ve7KbZZ0vXjKbZTxi1/JdT6WE693fXIRV9oM5HX30buxw0peMpmaqZ9/EbQ+9AruKxdhNznf75wfv36Ve22i5EvT31fStv1urps5/ZPPVf9CtWQYi5OKePe2dkZPX78uEtzZCmTMnZ3vsCsG187pr+FXCll3BppUO9bv6gWSuqtS/CV3Lc7QvlL2J+Sad/4meXel2Ch5e0i1DTBw4bc3Q+mNIWc0nZT3fMcz+mfLnr66IjEvH5TpIuhLnL2fHUe3/vkSRW3bgrVQ9fnbpuSHjtY0jBt6bErFvfc0PlUb2eLd4hlqjZXLGpzxdoUr2b262tyTZ2HIfh0qTMl0y7+uGUQdJfGEq3bEFnTBB07CS3/PIgsbwrb89TflCeXfxJrDTP6xFw+2nffm/yNdTxV3Bpm1mSoUNLfgYm9JgOaH6H8KfZbnSn+Ju0CL791voSG3e3meXV1NUWIXpsp47bRO2/FtZ3r6+ujNh+nqhVfqM2UTPsGypB7X4KFltdFxy5EoRmouviZoPt6UjrmG0aLYTsl1hj+hWI3v3VcM5pDYq58+iBJ6OJvdmIuc8Qd09+YtlLHro+rKM06l+xmYmNjI2ZoM22ljFs/uqKYLK5Zjugxg0S9pBQ6x2MwTcUBQU9FtgC729vblZf7+/teb02sfTOXdRLr4xEaQtUz4nrqY7tuK8V2H/+aYtdxzfzVBUwfkdGwe/2fmGkY0m6qUsTos5kybl99i7QvZez2wRg7Z+px23717nw3x/X8MbdTxa0Jbxputw/KhHzWTY5GJ2Y9aw+VHWp/0zneh2nSmPr8mDplyycwnsx0uLKycnhwcDAVzPgEPFxbWzvc3Nyc2m8b495lVU5lt7a2bPfUsqvtKSMJN7r61xS7mInLPP8Shhc0nSruUIUur/EnYUPZsuxPGbtiU5uPP3k6FYudSzqf6ufZVMaEG6nitrZ98uSJ13sdV9zjx0ve4zl3GgO1UZM/FpfylnR9+0dAk94xYHzhCVhvUXed6kHo2a6e/epZnz7rGEr2FShNbrLnSvW8XW3X7aTa7upfKHb1xPUrY/Mk9W70Qy5DpNhx+2Kw5+bq7dSTYt/b28s+QiE/UsZu7a8heL2TPhbwaiRGozV6C6BpAlmdU8ztVHGrB65euoaodR3QqJPi1m+la2a/ZrprmDp30t+dPnijFPob1DG1je86FzrHVcZSV6ZWPvYSQY9NtFB7+oPXsKBOSl10dGLGOglT2o6Be9H9ixGjz0bquGVfySdiOubb7/Mzxb6Usbu2dQ7pXBoyVpef61vs81zXDom7lvacOdY1xI2hzbriVQrxbzo+T10pmc5Tv5sHQXdpsA4BCEAAAhAolACT4gptONyGAAQgAAEIuAQQdJcG6xCAAAQgAIFCCSDohTYcbkMAAhCAAARcAgi6S4N1CEAAAhCAQKEEEPRCGw63IQABCEAAAi4BBN2lwToEIAABCECgUAIIeqENh9sQgAAEIAABlwCC7tJgHQIQgAAEIFAoAQS90IbDbQhAAAIQgIBLAEF3abAOAQhAAAIQKJQAgl5ow+E2BCAAAQhAwCWAoLs0WIcABCAAAQgUSgBBL7ThcBsCEIAABCDgEkDQXRqsQwACEIAABAolgKAX2nC4DQEIQAACEHAJIOguDdYhAAEIQAAChRJA0AttONyGAAQgAAEIuAQQdJcG6xCAQBICnz59Gt2+fXt09uzZ6t/Tp08n9Vy+fLnap2WX9ObNm4ndLuUpA4HjQuDf4xIIcUAAAotJQIK7u7s75dzfv3+nttmAAAT6E0DQ+zPEAgQgECDw58+fiZg/evRodPPmzdHPnz+ncl+5cqXad+bMman9bEAAAu0IIOjteJEbAhBoQUC9cyWJtcTc1quV//97+PChu8k6BCDQkQDP0DuCoxgEINBMwHrjq6urzZnJAQEI9CKAoPfCR2EIQGAWARP0WXk4BgEIxCGAoMfhiBUIQAACEIDAoAQQ9EHxUzkEIAABCEAgDgEmxcXhiBUIJCegCWbv378fff36daTZ4ydOnKgmm127dm109+7dYP0qp38a/lY5TVDTzPJ79+5VNnwFX716NXr27Fl1/PPnz1U5bet9ctlR3evr6yNNaKvPTtfx+jvlHz58qN4Vt7o0QU6z3pX0frrsnjt3bvT27VvLMrXUcfmkpeo+f/786OLFi5OJdlOZAxuK/cWLFyP5Ih/lt57t37p1q7JVL9aHQd2Wtru0X1ufffWyb3kI/HM4TssTLpFCoDwCEh+Jnpaz0sePH6fE9du3b6P79+/PLPf8+fPR1atXj5h1xUx5ZEfi4kv1euXn9evXq6xuGQmxpRs3blQ3A9puEnR9hOb169dWdGpp4i6hV/rx48fUcdvQcdUTSnfu3Jn4Y3n6MDAbWnZtvy4+u/WyvnwEGHJfvjYn4oIISBAljibm6tWqxyzhUm9WYqueqtLJkycnkZmoaqmeqPK55ayMhFq9/lBS/RJC9Ygl3FaveviWJHxuUn2qS/+sHvW+bZ+W876qJt9cMX/w4MGUH/LLxNz1wV3XjY2JufwWN8UhP2yUQHWoB+1LXRiYna7t19dnq5/lkhFQD50EAQgsJoGdnZ3DlZWVw7W1tcPxUHvQyfqxS5cuVeW0DCWzLfu/f/+eyvby5cuqvI6FbGxubk58myrsbGxtbVV5lDeUZuWxOOTHwcGB14SVVx5fMhuK15fETmXF2E0xGBjjru3X1mfXf9aXjwA99CW7gSPccgiol2a9xu3t7eoZc8h79YAtqVdrPXr1zENJvVMbBtfz8VCyD8LUj+sZupJ6oSmSG4d8rT+rtzptFMC23aXZUJzWG3ePa13sZENxiLkvdWHQt/36+uyLg33HmwCT4o53+xJdwQTcoeRZk97qIdpNgATQFfp6Pm1rQp3yv3v3Lih4IcE8derUxKTE0G4OJjt7rnz58mViISSokwyBlf39/ckRe64/2eGs2A2QJhz6mHVh0LX9YvnshMfqkhBA0JekoQmzPAImaKGeaSgiiZLSPF9nM/GSINvz9rrdtvXXy3fd/v79e1XUfOxix2zM6n27dpXPl7ow6Np+sXz2xcG+400AQT/e7Ut0BROwC3tbMTFRcnvQIQzuRDorF8qbe//4uX5VpetjWx/MhibTtRnlaFuPL3/X9hvSZ18c7CuHAM/Qy2krPF0yAjaEbcPB84bfppxr28rNW0/qfCbkro9t6zQb1ltuW75PfuPZ1v8hfe4TL2WHJ4CgD98GeAABLwG9kqXUVhCsRz9POVforJzXmQF22iODeeIIuWc2rLccypdif9f2G9LnFBywmY8Agp6PNTVBoBUB94Mv9Xe9ZxmyCWQSQndiVr2Mhtj11TQl973yer6hti9cuDCpWrPVuyR9BU5JLLra6FKvynRtvyF97hor5RaDAIK+GO2AFxA4QkAzq21C2Pid6Jk9dc1UN/GWoNtw7+7ubvC1Mn1UxtK8H3qx/DmWEkQbNRi/j+2NQzclYhNKLkPZmNXbF8NZx0N1hPa7dbdpP7dcbp9DsbC/DAIIehnthJdLSkDvkUucJVz6Prp66nq/WdsScImQ9ku4XTHa29uriGnf+MMqVT6tq5x6qipjNwCz3vEeGrsmsynJb8Uh37WuJP/1KpptVzs9/9m7+MqnuF3hFhNty06docdU611d229In1sHSYGFIcAs94VpChyBwFEC6qHqU6X6dKnEJ/QBGOWzZ7ayop69yo2/olYJnsTKlyTmNkTvOz70PvXS5Z9EV4LsjirIN8Vpx0O+io0+W2sMQyxky2UYstdmf9f2G9LnNvGRd7EIIOiL1R54A4EjBOziLlGz3qXETfs1gWpjY2Pqea0ZkEDpe+Xq1evDMfYVNJVr+rU1s7EIS910aBhaw9aKQSMWEl4JuQR/nvkFdYbGQoxOnz4d/MW1GPHX67aRkqb2q5fL6XOMuLGRnwC/tpafOTVCAAIQgAAEohPgGXp0pBiEAAQgAAEI5CeAoOdnTo0QgAAEIACB6AQQ9OhIMQgBCEAAAhDITwBBz8+cGiEAAQhAAALRCSDo0ZFiEAIQgAAEIJCfAIKenzk1QgACEIAABKITQNCjI8UgBCAAAQhAID8BBD0/c2qEAAQgAAEIRCeAoEdHikEIQAACEIBAfgIIen7m1AgBCEAAAhCITgBBj44UgxCAAAQgAIH8BBD0/MypEQIQgAAEIBCdAIIeHSkGIQABCEAAAvkJIOj5mVMjBCAAAQhAIDoBBD06UgxCAAIQgAAE8hNA0PMzp0YIQAACEIBAdAIIenSkGIQABCAAAQjkJ4Cg52dOjRCAAAQgAIHoBBD06EgxCAEIQAACEMhPAEHPz5waIQABCEAAAtEJIOjRkWIQAhCAAAQgkJ8Agp6fOTVCAAIQgAAEohNA0KMjxSAEIAABCEAgPwEEPT9zaoQABCAAAQhEJ4CgR0eKQQhAAAIQgEB+Agh6fubUCAEIQAACEIhOAEGPjhSDEIAABCAAgfwEEPT8zKkRAhCAAAQgEJ0Agh4dKQYhAAEIQAAC+Qn8BwDp/FEESAQ2AAAAAElFTkSuQmCC\" width=\"250\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "logits, labels = test(temp_scale_net, temp_scale=True, bayesian=False)\n",
    "\n",
    "ece_freq_ts, acc_freq_ts, conf_freq_ts = eceloss(logits, labels)\n",
    "print('ece =', ece_freq_ts.item()*100)\n",
    "\n",
    "fig_ts_uc, ax_ts_uc = plot_conf(acc_freq_ts, conf_freq_ts)\n",
    "\n",
    "textstr_freq_ts = r'ECE\\,=\\,{:.2f}'.format(ece_freq_ts.item()*100)\n",
    "props = dict(boxstyle='round', facecolor='white', alpha=0.75)\n",
    "ax_ts_uc.text(0.075, 0.925, textstr_freq_ts, transform=ax_ts_uc.transAxes, fontsize=14,\n",
    "                verticalalignment='top',\n",
    "                horizontalalignment='left',\n",
    "                bbox=props\n",
    "                )\n",
    "ax_ts_uc.set_title(r'freq. TS')\n",
    "fig_ts_uc.tight_layout()\n",
    "fig_ts_uc.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 79/79 [00:02<00:00, 38.91it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ece = 0.6901661865413189\n",
      "uce = 3.8130737841129303\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"250\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"250\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "logits2, labels2 = test(temp_scale_net, temp_scale=True, bayesian=True)\n",
    "\n",
    "ece2, acc2, conf2 = eceloss(logits2, labels2)\n",
    "uce2, err2, entr2 = uceloss(logits2, labels2)\n",
    "\n",
    "print('ece =', ece2.item()*100)\n",
    "print(\"uce =\", uce2.item()*100)\n",
    "\n",
    "fig3, ax3 = plot_conf(acc2, conf2)\n",
    "fig4, ax4 = plot_uncert(err2, entr2)\n",
    "\n",
    "textstr3 = r'ECE\\,=\\,{:.2f}'.format(ece2.item()*100)\n",
    "props = dict(boxstyle='round', facecolor='white', alpha=0.75)\n",
    "ax3.text(0.075, 0.925, textstr3, transform=ax3.transAxes, fontsize=14,\n",
    "        verticalalignment='top',\n",
    "        horizontalalignment='left',\n",
    "        bbox=props\n",
    "        )\n",
    "ax3.set_title(r'MC Dropout TS')\n",
    "fig3.tight_layout()\n",
    "fig3.show()\n",
    "\n",
    "textstr4 = r'UCE\\,=\\,{:.2f}'.format(uce2.item()*100)\n",
    "ax4.text(0.925, 0.075, textstr4, transform=ax4.transAxes, fontsize=14,\n",
    "         verticalalignment='bottom',\n",
    "         horizontalalignment='right',\n",
    "         bbox=props\n",
    "         )\n",
    "ax4.set_title(r'MC Dropout TS')\n",
    "fig4.tight_layout()\n",
    "fig4.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\" width=\"750\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# compose final figure\n",
    "fig_uc, ax_uc = plt.subplots(2, 3, figsize=(7.5, 3.75), sharex=True, sharey=False)\n",
    "\n",
    "ax_uc[0,0].plot([0,1], [0,1], 'k--')\n",
    "ax_uc[0,0].plot(conf_cp_uc.data.cpu().numpy(), acc_cp_uc.data.cpu().numpy(), marker='.')\n",
    "#ax_uc[0,0].set_xlabel(r'confidence')\n",
    "ax_uc[0,0].set_ylabel(r'accuracy')\n",
    "ax_uc[0,0].set_xticks((np.arange(0, 1.1, step=0.2)))\n",
    "ax_uc[0,0].set_yticks((np.arange(0, 1.1, step=0.2)))\n",
    "ax_uc[0,0].set_title(r'Frequentist Confidence')\n",
    "ax_uc[0,0].text(0.075, 0.925, textstr_cp_uc, transform=ax_uc[0,0].transAxes, fontsize=14,\n",
    "                verticalalignment='top',\n",
    "                horizontalalignment='left',\n",
    "                bbox=props\n",
    "                )\n",
    "\n",
    "ax_uc[0,1].plot([0,1], [0,1], 'k--')\n",
    "ax_uc[0,1].plot(conf1.data.cpu().numpy(), acc1.data.cpu().numpy(), marker='.')\n",
    "ax_uc[0,1].set_xticks((np.arange(0, 1.1, step=0.2)))\n",
    "ax_uc[0,1].set_yticks((np.arange(0, 1.1, step=0.2)))\n",
    "ax_uc[0,1].set_ylabel(r'accuracy')\n",
    "#ax_uc[0,1].set_xlabel(r'confidence')\n",
    "ax_uc[0,1].set_title(r'MC Dropout Confidence')\n",
    "ax_uc[0,1].text(0.075, 0.925, textstr1, transform=ax_uc[0,1].transAxes, fontsize=14,\n",
    "                verticalalignment='top',\n",
    "                horizontalalignment='left',\n",
    "                bbox=props\n",
    "                )\n",
    "\n",
    "ax_uc[0,2].plot([0,1], [0,1], 'k--')\n",
    "ax_uc[0,2].plot(entr1.data.cpu().numpy(), err1.data.cpu().numpy(), marker='.')\n",
    "ax_uc[0,2].set_xticks((np.arange(0, 1.1, step=0.2)))\n",
    "ax_uc[0,2].set_yticks((np.arange(0, 1.1, step=0.2)))\n",
    "ax_uc[0,2].set_ylabel(r'error')\n",
    "#ax_uc[0,2].set_xlabel(r'uncertainty')\n",
    "ax_uc[0,2].set_title(r'MC Dropout Uncertainty')\n",
    "ax_uc[0,2].text(0.075, 0.925, textstr2, transform=ax_uc[0,2].transAxes, fontsize=14,\n",
    "                verticalalignment='top',\n",
    "                horizontalalignment='left',\n",
    "                bbox=props\n",
    "                )\n",
    "\n",
    "\n",
    "ax_uc[0,0].annotate(r'Confidence Penalty', xy=(0, 0.5), xytext=(-ax_uc[0,0].yaxis.labelpad - 5, 0),\n",
    "                    xycoords=ax_uc[0,0].yaxis.label, textcoords='offset points',\n",
    "                    size='large', ha='right', va='center', fontsize=14, rotation=90)\n",
    "\n",
    "\n",
    "ax_uc[1,0].plot([0,1], [0,1], 'k--')\n",
    "ax_uc[1,0].plot(conf_freq_ts.data.cpu().numpy(), acc_freq_ts.data.cpu().numpy(), marker='.')\n",
    "ax_uc[1,0].set_xlabel(r'confidence')\n",
    "ax_uc[1,0].set_ylabel(r'accuracy')\n",
    "ax_uc[1,0].set_xticks((np.arange(0, 1.1, step=0.2)))\n",
    "ax_uc[1,0].set_yticks((np.arange(0, 1.1, step=0.2)))\n",
    "#ax_uc[1,0].set_title(r'frequentist')\n",
    "ax_uc[1,0].text(0.075, 0.925, textstr_freq_ts, transform=ax_uc[1,0].transAxes, fontsize=14,\n",
    "                verticalalignment='top',\n",
    "                horizontalalignment='left',\n",
    "                bbox=props\n",
    "                )\n",
    "\n",
    "ax_uc[1,1].plot([0,1], [0,1], 'k--')\n",
    "ax_uc[1,1].plot(conf2.data.cpu().numpy(), acc2.data.cpu().numpy(), marker='.')\n",
    "ax_uc[1,1].set_xticks((np.arange(0, 1.1, step=0.2)))\n",
    "ax_uc[1,1].set_yticks((np.arange(0, 1.1, step=0.2)))\n",
    "ax_uc[1,1].set_ylabel(r'accuracy')\n",
    "ax_uc[1,1].set_xlabel(r'confidence')\n",
    "#ax_uc[1,1].set_title(r'MC dropout')\n",
    "ax_uc[1,1].text(0.075, 0.925, textstr3, transform=ax_uc[1,1].transAxes, fontsize=14,\n",
    "                verticalalignment='top',\n",
    "                horizontalalignment='left',\n",
    "                bbox=props\n",
    "                )\n",
    "\n",
    "ax_uc[1,2].plot([0,1], [0,1], 'k--')\n",
    "ax_uc[1,2].plot(entr2.data.cpu().numpy(), err2.data.cpu().numpy(), marker='.')\n",
    "ax_uc[1,2].set_xticks((np.arange(0, 1.1, step=0.2)))\n",
    "ax_uc[1,2].set_yticks((np.arange(0, 1.1, step=0.2)))\n",
    "ax_uc[1,2].set_ylabel(r'error')\n",
    "ax_uc[1,2].set_xlabel(r'uncertainty')\n",
    "#ax_uc[1,2].set_title(r'MC dropout')\n",
    "ax_uc[1,2].text(0.075, 0.925, textstr4, transform=ax_uc[1,2].transAxes, fontsize=14,\n",
    "                verticalalignment='top',\n",
    "                horizontalalignment='left',\n",
    "                bbox=props\n",
    "                )\n",
    "\n",
    "ax_uc[1,0].annotate(r'TS Calibrated', xy=(0, 0.5), xytext=(-ax_uc[1,0].yaxis.labelpad - 5, 0),\n",
    "                    xycoords=ax_uc[1,0].yaxis.label, textcoords='offset points',\n",
    "                    size='large', ha='right', va='center', fontsize=14, rotation=90)\n",
    "\n",
    "fig_uc.tight_layout()\n",
    "fig_uc.show()\n",
    "fig_uc.savefig(f'conf_penalty_composed.pdf', bbox_inches='tight', pad_inches=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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