test_endovis_gaussian-range.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "import numpy as np\n",
    "np.random.seed(0)\n",
    "import torch\n",
    "torch.manual_seed(0)\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 import SubsetRandomSampler\n",
    "import matplotlib\n",
    "from tqdm import tqdm\n",
    "import torch\n",
    "from matplotlib import pyplot as plt\n",
    "import seaborn as sns\n",
    "sns.set()\n",
    "from tqdm import tqdm\n",
    "from torch.utils.data.sampler import SubsetRandomSampler\n",
    "from data_generator_endovis import EndoVisDataset\n",
    "from models import BreastPathQModel\n",
    "from uce import uceloss\n",
    "from calibration_plots import plot_uncert, plot_frequency, plot_uncert_multi\n",
    "from utils import nll_criterion_gaussian\n",
    "\n",
    "matplotlib.rcParams['font.size'] = 8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "base_model = 'efficientnetb4'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "assert base_model in ['resnet101', 'densenet201', 'efficientnetb4']\n",
    "device = torch.device(\"cuda:0\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2159\n",
      "2232\n"
     ]
    }
   ],
   "source": [
    "batch_size = 16\n",
    "\n",
    "data_dir = '/media/fastdata/laves/EndoVis15_instrument_tracking'\n",
    "data_set_valid = EndoVisDataset(data_dir=data_dir+'/valid', augment=False, scale=0.5)\n",
    "data_set_test = EndoVisDataset(data_dir=data_dir+'/test', augment=False, scale=0.5)\n",
    "\n",
    "assert len(data_set_valid) > 0\n",
    "assert len(data_set_test) > 0\n",
    "print(len(data_set_valid))\n",
    "print(len(data_set_test))\n",
    "\n",
    "calib_loader = torch.utils.data.DataLoader(data_set_valid, batch_size=batch_size, shuffle=False)\n",
    "test_loader = torch.utils.data.DataLoader(data_set_test, batch_size=batch_size, shuffle=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading previous weights at epoch 199 from\n",
      "/media/fastdata/laves/regression_snapshots/efficientnetb4_gaussian_endovis.pth.tar\n"
     ]
    }
   ],
   "source": [
    "from glob import glob\n",
    "model = BreastPathQModel(base_model, out_channels=2).to(device)\n",
    "\n",
    "checkpoint_path = glob(f\"/media/fastdata/laves/regression_snapshots/{base_model}_gaussian_endovis.pth.tar\")[0]\n",
    "\n",
    "checkpoint = torch.load(checkpoint_path, map_location=device)\n",
    "model.load_state_dict(checkpoint['state_dict'])\n",
    "print(\"Loading previous weights at epoch \" + str(checkpoint['epoch']) + \" from\\n\" + checkpoint_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 135/135 [03:50<00:00,  1.71s/it]\n"
     ]
    }
   ],
   "source": [
    "model.eval()\n",
    "y_p_calib = []\n",
    "vars_calib = []\n",
    "logvars_calib = []\n",
    "targets_calib = []\n",
    "\n",
    "with torch.no_grad():\n",
    "    for batch_idx, (data, target) in enumerate(tqdm(calib_loader)):\n",
    "        data, target = data.to(device), target.to(device)\n",
    "\n",
    "        y_p, logvar, var_bayesian = model(data, dropout=True, mc_dropout=True, test=True)\n",
    "\n",
    "        y_p_calib.append(y_p.detach())\n",
    "        vars_calib.append(var_bayesian.detach())\n",
    "        logvars_calib.append(logvar.detach())\n",
    "        targets_calib.append(target.detach())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_p_calib = torch.cat(y_p_calib, dim=1).clamp(0, 1).permute(1,0,2)\n",
    "mu_calib = y_p_calib.mean(dim=1)\n",
    "var_calib = torch.cat(vars_calib, dim=0)\n",
    "logvars_calib = torch.cat(logvars_calib, dim=1).permute(1,0,2)\n",
    "logvar_calib = logvars_calib.mean(dim=1)\n",
    "target_calib = torch.cat(targets_calib, dim=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "err_calib = (target_calib-mu_calib).pow(2).mean(dim=1, keepdim=True).sqrt()\n",
    "errvar_calib = (y_p_calib-target_calib.unsqueeze(1).repeat(1,25,1)).pow(2).mean(dim=(1,2)).unsqueeze(-1)\n",
    "\n",
    "uncertainty = 'total'\n",
    "\n",
    "uncert_calib_aleatoric = logvar_calib.exp().mean(dim=1, keepdim=True)\n",
    "uncert_calib_epistemic = var_calib.mean(dim=1, keepdim=True)\n",
    "\n",
    "if uncertainty == 'aleatoric':\n",
    "    uncert_calib = uncert_calib_aleatoric.sqrt().clamp(0, 1)\n",
    "elif uncertainty == 'epistemic':\n",
    "    uncert_calib = uncert_calib_epistemic.sqrt().clamp(0, 1)\n",
    "else:\n",
    "    uncert_calib = (uncert_calib_aleatoric + uncert_calib_epistemic).sqrt().clamp(0, 1)  # total"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor(0.0011, device='cuda:0')\n",
      "tensor(0.0012, device='cuda:0')\n",
      "tensor(0.0003, device='cuda:0')\n",
      "tensor(0.0147, device='cuda:0')\n",
      "tensor(0.0099, device='cuda:0')\n"
     ]
    }
   ],
   "source": [
    "print((err_calib**2).mean())\n",
    "print(errvar_calib.mean())\n",
    "print((uncert_calib**2).mean())\n",
    "print(uncert_calib_aleatoric.sqrt().mean())\n",
    "print(uncert_calib_epistemic.sqrt().mean())\n",
    "\n",
    "err_calib = errvar_calib.sqrt()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1)\n",
    "ax.plot(uncert_calib.cpu(), err_calib.cpu()[:,0], '.')\n",
    "\n",
    "max_val = max(err_calib.max().item(), uncert_calib.max().item())\n",
    "ax.plot([0, max_val], [0, max_val], '--')\n",
    "ax.set_xlabel('uncert')\n",
    "ax.set_ylabel('err')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor(1.8657, device='cuda:0')\n"
     ]
    }
   ],
   "source": [
    "# calculate optimal T\n",
    "S = (err_calib**2 / uncert_calib**2).mean().sqrt()\n",
    "print(S)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Scaler(torch.nn.Module):\n",
    "    def __init__(self, init_S=1.0):\n",
    "        super().__init__()\n",
    "        self.S = torch.nn.Parameter(torch.tensor([init_S]))\n",
    "\n",
    "    def forward(self, x):\n",
    "        return self.S.mul(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.7898043394088745\n"
     ]
    }
   ],
   "source": [
    "# find optimal S\n",
    "scaler = Scaler(init_S=S).to(device)\n",
    "s_opt = torch.optim.LBFGS([scaler.S], lr=3e-2, max_iter=200)\n",
    "\n",
    "def closure():\n",
    "    s_opt.zero_grad()\n",
    "\n",
    "    loss = nll_criterion_gaussian(mu_calib, scaler(uncert_calib).pow(2).log(), target_calib)\n",
    "\n",
    "    loss.backward()\n",
    "    return loss\n",
    "\n",
    "s_opt.step(closure)\n",
    "print(scaler.S.item())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "class AuxModel(torch.nn.Module):\n",
    "    def __init__(self, channels, hidden=16):\n",
    "        super().__init__()\n",
    "        self.linear1 = torch.nn.Linear(channels, hidden, bias=True)\n",
    "        self.fc = torch.nn.Linear(hidden, channels, bias=True)\n",
    "\n",
    "    def forward(self, x):\n",
    "        x = 2*(x.log())\n",
    "        y = self.linear1(x).relu()\n",
    "        y = self.fc(y)\n",
    "        \n",
    "        if self.training:\n",
    "            return y\n",
    "        else:\n",
    "            return (0.5*y).exp()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-5.907727241516113\n"
     ]
    }
   ],
   "source": [
    "# find optimal aux\n",
    "aux = AuxModel(1).to(device)\n",
    "aux_opt = torch.optim.Adam(aux.parameters(), lr=3e-3, weight_decay=0)\n",
    "lr_scheduler_net = optim.lr_scheduler.ReduceLROnPlateau(aux_opt, patience=100, factor=0.1)\n",
    "\n",
    "aux.train()\n",
    "for i in range(2000):\n",
    "    aux_opt.zero_grad()\n",
    "    loss = nll_criterion_gaussian(mu_calib, aux(uncert_calib), target_calib)\n",
    "    loss.backward()\n",
    "    aux_opt.step()\n",
    "    lr_scheduler_net.step(loss.item())\n",
    "\n",
    "print(loss.item())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-4.881978511810303\n",
      "-5.9086384773254395\n",
      "-5.9123148918151855\n",
      "-5.907743453979492\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "AuxModel(\n",
       "  (linear1): Linear(in_features=1, out_features=16, bias=True)\n",
       "  (fc): Linear(in_features=16, out_features=1, bias=True)\n",
       ")"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aux.train()\n",
    "print(nll_criterion_gaussian(mu_calib, uncert_calib.pow(2).log(), target_calib).item())\n",
    "print(nll_criterion_gaussian(mu_calib, (S*uncert_calib).pow(2).log(), target_calib).item())\n",
    "print(nll_criterion_gaussian(mu_calib, scaler(uncert_calib).pow(2).log(), target_calib).item())\n",
    "print(nll_criterion_gaussian(mu_calib, aux(uncert_calib), target_calib).item())\n",
    "aux.eval()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.008069932460784912\n",
      "0.005666515324264765\n",
      "0.005770913325250149\n",
      "0.005837442819029093\n"
     ]
    }
   ],
   "source": [
    "print(torch.nn.functional.mse_loss(uncert_calib**2, err_calib**2, reduction='sum').item())\n",
    "print(torch.nn.functional.mse_loss((S*uncert_calib)**2, err_calib**2, reduction='sum').item())\n",
    "print(torch.nn.functional.mse_loss(scaler(uncert_calib)**2, err_calib**2, reduction='sum').item())\n",
    "print(torch.nn.functional.mse_loss(aux(uncert_calib)**2, err_calib**2, reduction='sum').item())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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=\"250\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.09119826718233526\n"
     ]
    }
   ],
   "source": [
    "uce, err_in_bin, avg_sigma_in_bin, freq_in_bin = uceloss(err_calib**2, uncert_calib**2)\n",
    "plot_uncert(err_in_bin.cpu(), avg_sigma_in_bin.cpu())\n",
    "print(uce.item()*100)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"250\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.024160969769582152\n"
     ]
    }
   ],
   "source": [
    "uce, err_in_bin, avg_sigma_in_bin, freq_in_bin = uceloss(err_calib**2, (S*uncert_calib)**2)\n",
    "plot_uncert(err_in_bin.cpu(), avg_sigma_in_bin.cpu())\n",
    "print(uce.item()*100)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"250\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.026022936799563468\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"
    },
    {
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\" width=\"250\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "n_bins = 15\n",
    "uce, err_in_bin, avg_uncert_in_bin, freq_in_bin = uceloss(err_calib**2, scaler(uncert_calib)**2, n_bins=n_bins)\n",
    "plot_uncert(err_in_bin.cpu(), avg_uncert_in_bin.cpu())\n",
    "plt.show()\n",
    "print(uce.item()*100)\n",
    "fig, ax = plot_frequency(scaler(uncert_calib).cpu(), freq_in_bin.cpu(), n_bins=n_bins)\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\" width=\"250\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.030034419614821672\n"
     ]
    }
   ],
   "source": [
    "uce, err_in_bin, avg_uncert_in_bin, freq_in_bin = uceloss(err_calib**2, aux(uncert_calib)**2, n_bins=n_bins)\n",
    "plot_uncert(err_in_bin.cpu(), avg_uncert_in_bin.cpu())\n",
    "plt.show()\n",
    "print(uce.item()*100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 140/140 [03:59<00:00,  1.71s/it]\n",
      "100%|██████████| 140/140 [04:00<00:00,  1.72s/it]\n",
      "100%|██████████| 140/140 [04:00<00:00,  1.72s/it]\n",
      "100%|██████████| 140/140 [03:59<00:00,  1.71s/it]\n",
      "100%|██████████| 140/140 [04:00<00:00,  1.72s/it]\n"
     ]
    }
   ],
   "source": [
    "y_p_test_list = []\n",
    "mu_test_list = []\n",
    "var_test_list = []\n",
    "logvars_test_list = []\n",
    "logvar_test_list = []\n",
    "target_test_list = []\n",
    "\n",
    "for i in range(5):\n",
    "    y_p_test = []\n",
    "    mus_test = []\n",
    "    vars_test = []\n",
    "    logvars_test = []\n",
    "    targets_test = []\n",
    "\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",
    "\n",
    "            y_p, logvar, var_bayesian = model(data, dropout=True, mc_dropout=True, test=True)\n",
    "\n",
    "            y_p_test.append(y_p.detach())\n",
    "            vars_test.append(var_bayesian.detach())\n",
    "            logvars_test.append(logvar.detach())\n",
    "            targets_test.append(target.detach())\n",
    "\n",
    "        y_p_test = torch.cat(y_p_test, dim=1).clamp(0, 1).permute(1,0,2)\n",
    "        mu_test = y_p_test.mean(dim=1)\n",
    "        var_test = torch.cat(vars_test, dim=0)\n",
    "        logvars_test = torch.cat(logvars_test, dim=1).permute(1,0,2)\n",
    "        logvar_test = logvars_test.mean(dim=1)\n",
    "        target_test = torch.cat(targets_test, dim=0)\n",
    "\n",
    "        y_p_test_list.append(y_p_test)\n",
    "        mu_test_list.append(mu_test)\n",
    "        var_test_list.append(var_test)\n",
    "        logvars_test_list.append(logvars_test)\n",
    "        logvar_test_list.append(logvar_test)\n",
    "        target_test_list.append(target_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "err_test = [(target_test-mu_test).pow(2).mean(dim=1, keepdim=True).sqrt() for target_test, mu_test in zip(target_test_list, mu_test_list)]\n",
    "errvar_test = [(y_p_test-target_test.unsqueeze(1).repeat(1,25,1)).pow(2).mean(dim=(1,2)).unsqueeze(-1) for target_test, y_p_test in zip(target_test_list, y_p_test_list)]\n",
    "\n",
    "uncert_aleatoric_test = [logvar_test.exp().mean(dim=1, keepdim=True) for logvar_test in logvar_test_list]\n",
    "uncert_epistemic_test = [var_test.mean(dim=1, keepdim=True) for var_test in var_test_list]\n",
    "\n",
    "if uncertainty == 'aleatoric':\n",
    "    uncert_test = uncert_aleatoric_test.sqrt().clamp(0, 1)\n",
    "elif uncertainty == 'epistemic':\n",
    "    uncert_test = uncert_epistemic_test.sqrt().clamp(0, 1)\n",
    "else:\n",
    "    uncert_test = [(u_a_t + u_e_t).sqrt().clamp(0, 1) for u_a_t, u_e_t in zip(uncert_aleatoric_test, uncert_epistemic_test)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor(0.0009, device='cuda:0')\n",
      "tensor(0.0010, device='cuda:0')\n",
      "tensor(0.0004, device='cuda:0')\n",
      "\n",
      "tensor(0.0009, device='cuda:0')\n",
      "tensor(0.0010, device='cuda:0')\n",
      "tensor(0.0004, device='cuda:0')\n",
      "\n",
      "tensor(0.0009, device='cuda:0')\n",
      "tensor(0.0010, device='cuda:0')\n",
      "tensor(0.0004, device='cuda:0')\n",
      "\n",
      "tensor(0.0009, device='cuda:0')\n",
      "tensor(0.0010, device='cuda:0')\n",
      "tensor(0.0004, device='cuda:0')\n",
      "\n",
      "tensor(0.0009, device='cuda:0')\n",
      "tensor(0.0010, device='cuda:0')\n",
      "tensor(0.0004, device='cuda:0')\n",
      "\n"
     ]
    }
   ],
   "source": [
    "for i in range(len(err_test)):\n",
    "    print((err_test[i]**2).mean())\n",
    "    print(errvar_test[i].mean())\n",
    "    print((uncert_test[i]**2).mean())\n",
    "    print()\n",
    "\n",
    "err_test = [errvar.sqrt() for errvar in errvar_test]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-5.935892581939697\n",
      "-6.135180473327637\n",
      "-6.167741775512695\n",
      "-6.172297477722168\n",
      "\n",
      "-5.946290016174316\n",
      "-6.139063358306885\n",
      "-6.171851634979248\n",
      "-6.176581859588623\n",
      "\n",
      "-5.942417144775391\n",
      "-6.136892795562744\n",
      "-6.16962194442749\n",
      "-6.174119472503662\n",
      "\n",
      "-5.9427947998046875\n",
      "-6.137717247009277\n",
      "-6.170430660247803\n",
      "-6.175024032592773\n",
      "\n",
      "-5.936885833740234\n",
      "-6.136639595031738\n",
      "-6.169184684753418\n",
      "-6.173605442047119\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "AuxModel(\n",
       "  (linear1): Linear(in_features=1, out_features=16, bias=True)\n",
       "  (fc): Linear(in_features=16, out_features=1, bias=True)\n",
       ")"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aux.train()\n",
    "for i in range(len(mu_test_list)):\n",
    "    print(nll_criterion_gaussian(mu_test_list[i], uncert_test[i].pow(2).log(), target_test_list[i]).item())\n",
    "    print(nll_criterion_gaussian(mu_test_list[i], (S*uncert_test[i]).pow(2).log(), target_test_list[i]).item())\n",
    "    print(nll_criterion_gaussian(mu_test_list[i], scaler(uncert_test[i]).pow(2).log(), target_test_list[i]).item())\n",
    "    print(nll_criterion_gaussian(mu_test_list[i], aux(uncert_test[i]), target_test_list[i]).item())\n",
    "    print()\n",
    "aux.eval()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.006106131244450808\n",
      "0.0033148499205708504\n",
      "0.003159784711897373\n",
      "0.0032660779543220997\n",
      "\n",
      "0.005559799261391163\n",
      "0.0026359418407082558\n",
      "0.0025141509249806404\n",
      "0.0026848274283111095\n",
      "\n",
      "0.005749263800680637\n",
      "0.0030668897088617086\n",
      "0.0029285834170877934\n",
      "0.0030460855923593044\n",
      "\n",
      "0.005685101728886366\n",
      "0.0028674104250967503\n",
      "0.0027302505914121866\n",
      "0.0028644041158258915\n",
      "\n",
      "0.005835274234414101\n",
      "0.003215598640963435\n",
      "0.00306911813095212\n",
      "0.0031719196122139692\n",
      "\n"
     ]
    }
   ],
   "source": [
    "for i in range(len(mu_test_list)):\n",
    "    print(torch.nn.functional.mse_loss(uncert_test[i]**2, err_test[i]**2, reduction='sum').item())\n",
    "    print(torch.nn.functional.mse_loss((S*uncert_test[i])**2, err_test[i]**2, reduction='sum').item())\n",
    "    print(torch.nn.functional.mse_loss(scaler(uncert_test[i])**2, err_test[i]**2, reduction='sum').item())\n",
    "    print(torch.nn.functional.mse_loss(aux(uncert_test[i])**2, err_test[i]**2, reduction='sum').item())\n",
    "    print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.004995438270270824\n",
      "0.004116563592106104\n",
      "0.004396152216941118\n",
      "0.004327855072915554\n",
      "0.004065563436597586\n",
      "0.05866248160600662 0.0012024359311908484\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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     "data": {
      "text/plain": [
       "(<Figure size 250x225 with 1 Axes>,\n",
       " <matplotlib.axes._subplots.AxesSubplot at 0x7f769cd6eb70>)"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "if base_model == 'resnet101':\n",
    "    uce_range = [0, 0.0003]\n",
    "elif base_model == 'densenet201':\n",
    "    uce_range = [0, 0.00031]\n",
    "elif base_model == 'efficientnetb4':\n",
    "    uce_range = [0, 0.003]\n",
    "\n",
    "n_bins = 15\n",
    "uce_uncal_list = []\n",
    "err_uncal_list = []\n",
    "uncert_uncal_list = []\n",
    "for i in range(len(err_test)):\n",
    "    print((uncert_test[i]**2).max().item())\n",
    "    uce_uncal, err_uncal, uncert_uncal, _ = uceloss(err_test[i]**2, uncert_test[i]**2, n_bins=n_bins, range=uce_range)\n",
    "    uce_uncal_list.append(uce_uncal.cpu())\n",
    "    err_uncal_list.append(err_uncal.cpu())\n",
    "    uncert_uncal_list.append(uncert_uncal.cpu())\n",
    "\n",
    "print((torch.stack(uce_uncal_list)*100).mean().item(), (torch.stack(uce_uncal_list)*100).var().sqrt().item())\n",
    "plot_uncert_multi(err_uncal_list, uncert_uncal_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.016002384945750237\n",
      "0.013186996802687645\n",
      "0.014082631096243858\n",
      "0.013863849453628063\n",
      "0.013023624196648598\n",
      "0.0357249453663826 0.000580057327169925\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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fLZqt0vTsKf5X/3VV+Utb/mdeFXh9RAS4JB7CBuFRSIBEgg3ARirYa04jOGGVdSxZM1LcFu4Jxtuj5UmXgCqKss8vwjESiPWNSvmWJo2MTEhH/7wB+Xpp38SKyqvhZQABT2kDcNikQAJhJcAeufT07MyPDqlw+jehtvhGrbftaytNc7682zX3CnmNm+I+pe//FdaT28vK/Y5fuaOAAU9d+yZMwmQQJ4SgKCjd55sZzVn9XpdLmFh5NZSn3z+3JlGEMexxBz5YGnaV76yUw3/yoLIlmkGQICCHgBUJkkCJFC4BDDUjiF3CPrA0LhZsualtu7las31VcZK3suzQcVJJOb0ABcU9eDSpaAHx5YpkwAJFCAB9M4ndPh8VF24uo3cElXXHXdBkvXnidLy4x7F3A+K4UqDVu4e22NgYEB27twpzz77rDQ1NUl/f7+cd955sm3bNunoyMyhg19pP/LII7Jr1y556qmnPNXKr3w9ZcZIJFAgBDAE3a9e4eZ2VoveNS1eFbEbmnvIPR2DuHjpp3qdYp4qsfyIzx66h3bau3evXHbZZSbmY489Jg888IDgc/369XL55ZfLk08+6SGV2FEySRuC3NXVJRDy6667Tnbs2GHOY+cUfTWTfKNT4hkJFA8Bu7MajNt6VdR1Gbqn0KdD86rpUSGZh7ioyD6eUMx9hBmypCjoHhpk8+bNpjd+2223RcXeuHGjbN26VW655RbPQhqVgJ6km/YzzzwjF154oWzZskU6OzvlkktScwKRbr7u8vOcBIqJAIbb4e1tYkp3VvPoux183HEbayukojz7xmYU88L+tlLQk7TvXXfdJegJQ7xjhU2bNpnL6B2nGjJJe8OGDfLiiy+a4XW8aJx//vmes88kX8+ZMCIJFCAB9NDRO8cStEHXErRE1XWvP8/FcjWKeaIWKox7FPQk7Xj//febGFdddVXMmJg/xx96zBj+TiUEmXaicuQq30Rl4j0SCDsB9M4xxA5Xr70ePcOhTrP6kLuHnov588cf/wf9N6ozCjOWptGaPQpJXp9Q0BM0H0QaobGxMUEsiRjFpTKXHmTaiQqbq3wTlYn3SCAfCDh3VvPqux31GlBPclPqhMYZcmHhvmXLNnnPezZHikExj6AomANauSdoShiOISSzYm9oaDDxdu/ebT69/C/ItBPln6t8E5WJ90gg7ATgBMbsrDYyKmO6XG3UtWNaovK7e+e11eXqhz37//Ri7fxHPnK7KerTT/+EPfNEjZan99hDT9BwVqCxTC1RaG5uNre7u7sTRYu6F2TaURm5TnKVr6sYPCWBvCJQrgZsczurTeq+596WqtkKnnTFz0Xv3JbFivpDDz3MLVAtlAL6pKAnaMzBwcEEd0/fsj10GM95DUGmnagMuco3UZl4jwTCTgC9c7uzmlff7agT5s/DYBDn5AtRt/9mOa/zOP8JUNB9bEM4mwkqBJl2ojLnKt9EZeI9EsgmAbh6NTurqVU7RH0ihS1Lh3Vo3r0TW9AGcdj6dNOmjbJ///5sYmJeISCQ/YmcEFTaaxFSFbNUeuhBpp2ofrnKN1GZkt3DP6atrXXJovE+CQRGAJ7exqdnBAJdU+N9Q5XDvdE7sWHb07aWWuMLPp3CYu4d69erayqkqmL+OvbDhw/L9u03yIEDB+Sd73ynfPe735UVK1amkxWfyUMCFPQ8bLRiKzKGCMvK1CqJgQRyRKB3UIX51JI1vGB6DSf6ogW9vbkmow1ZkDd+D3O/iegB1kOHDqm/jOuNmKN8EPd3vetd8r3vfU9WrqSoe22zfI5HQU/QesmM4eyjdl462fI2Gx+fQabtzMd9nKt83eVI5RzzkPCbzUACqRKA8A2PTUq19ozLSiGAs57dtdq8kEbv4FjEoYy97uXzuKuH3qaCnsl3Gc/i94C/aR0xsAHiff3174qIub1eX18vlZVVUXHtvbB8wj6BwR8CFPQEHFM1HPEqlsgyyLQTVCln+SYqU7J7+Eesp2c4WTTeJ4EoAhU6JA2xePlgvxHxmqoyqauukDodrobAI+C7BWHEXyyhrawsF8gmtkk9enxQRkcnzHNe/jc2MSVDo5NRURtqylNKI+phPSmZnVEvddMypulOjut8vrqhxZz51q3vnec05qyzzpK//duHpby8LrS/H6weaNEpCAZ/CFDQE3C0y9GSeYDr6+szqaTSQw8y7QRVklzlm6hMvEcCQRAwlukqfFhu1n10UOp17ruhrtJM35Sr0NcbcS83Ig/xn+v1nhZ4lAlp9KnP9ml1DIMNVlIJPQPR8ct12qhJ8/czxBPzM888Sx599FFZsKAttGLuJwemNUeAgp7gm4Dd1BCSGZLZIXdsp+o1BJl2ojLkKt9EZeI9EvCbAIbJjWW6umkdVsv0Yz0jckxGBLPf9bWV0liPvyqpUSMznZHWT+29a88dIl91yukLeuyajAyodXufDrnre0FK4aRr85bWhuq0jeFiZQzf7LF65vAA9/DDD0t7e3uoh9pj1YnXMiNAQU/ADxugICSzXrc9eBs/QZKRWzZuEGlHMolxkKt8YxSFl0ggMALwuw5BhlU6tjm1AZoMX+z4O3hsSC3GS6VJhR3i3qi95+NqdHa6916hLwUyt7OayzmMTS/R5/z151WJoqd0D2L+vi1/NG+Y3bpzhZgzFB8BWiMkaHO4fLU9Wusy1R0dgmwFPdYGLrhn/ac7n/UjbWd6Xo9zla/X8jEeCfhBAEPlgzrcjmF0GLTFC9g1DZbor3b3ya9+c0xeOtCrQj8oR9Rm4+CJIelS0YebV7wApBKQLnr2zuDX+vMTx48mFPO2toXObHlcRAQo6Ekae/v27SbG448/HjOmFetbb7113n2I/eWXX272LMeWpe6QSdrutFI5z1W+qZSRcUkgXQJ2uB0iDEcwEFcvAUPqtue+79WTsufl4/JKV6+81Nnr5fGoOD2ulwisdGtuyHz+vK/nuPzZn2yP2zOnmEc1Q9GdUNCTNDl63dgLHVuO2p64fQSCfccdd5he/LZt2+zlyOeePXsix/v27Ysc24NM0rZp2E/7YoHzeKMJNq6f+do0+UkCYSHgHG6HQVu6AR7h+ocmdKc0by8EznzcBnHNDVWnls05Y6V2PNB/UnbefZscOdQd9aAdZqeYR2EpyhPOoXto9jvvvNMs97ruuuvUC9N2wTw0xHrXrl1yySWXyL333hszFcTDkD1eBGIJPh5KN228TFx22WUmXxw7A8ppLe7jlS/dfJ358JgEwkjA63B7kGV3G8T5MdxeXV0nTa0L5eTxQ5GiU8wjKHigBEp0jilF283i5QbhRE8YAg3BhGBjTtqPkE7aVsiteLvLkew+4qeTrzufoM+xRpjr0IOmXBjpY7i9Rq3Vu48PyZGTI/KbAz1Zr9j0zIw88dNOXS53OuuL1rXLIh/WW5eXTMoju+6U3b/6uSQSc7hKxotN2H875VyHfvpL4sMRBd0HiEwiWAJh/0cp2Noz9VQIYD15qQoZnMl0Hh6Q470jqTzuS1xsl/r0niNRaV190QpjUR91MY0T7KW+anGtPPLQl+VDN9+iHidbY6ZCQY+JpeAvcsi94JuYFSSB4iEQGW7X7jHWjuciuIfbsRwOy+P8CtU1NfLJT35G5+R1SZ16imMgAUvAv2+ZTZGfJEACJJADAlHW7eqi1at1u99FdRvELWhMff35QN8JmRjPzQuJ3zyYXvYIUNCzx5o5kQAJBEgA1u3Y5nR4NNqZTIBZzksaJknuJWupGsT19x6XB750u3zn65+gqM8jzAuJCFDQE9HhPRIggbwhgOF2rDuHqPYNRvtRz1Yl4ExmSv2+O0NrCj10iPmD935Uek8clgMv76aoO0HyOCkBCnpSRIxAAiQQdgLO4XY4h8nVcLvb3WudGrFV645tXoJTzG18iPqT39tpT/lJAgkJUNAT4uFNEiCBfCAQGW5XN625MoYDJ7dBXGtjtSd8scQcD7Yt7pBL3/EeT2kwEglQ0PkdIAESyHsCzuH2Xte2pdmqnJk/d3mm82IQl0jMb7j5c9LQGHtpWrbqxXzyhwAFPX/aiiUlARKIQcA93J6Oq9YYyaZ8CTu7jau7WGdI1kOHmH/rK39q5sydz6FnTjF3EuGxFwLeJne8pMQ4JEACJJADAs7h9kQ7qwVZtH41hvv1KyejsihVr3WJXi7i9cw7Vpwhn/jcX0t5daPZLGZI0x6f5HrzKLg8iUmAgh4TCy+SAAnkCwHjTMZat+dguB1uZn/x0gm1ro8mNqMXfvLrw/KGs9pk+cL6qJvxxHzNmjPl67selNr6FhnRHv+YOo6Z1f8mVNAHVdhzZewXVXiehJYABT20TcOCkQAJJCNgh9sH1LId1u2JesTJ0krnPnrmscTcpgWRx/2G2kppUo9xCPHEHL7Zv/GNb8miRe3GDzvizui6+pHxKSPujXVVKvBTuMxAAjEJUNBjYuFFEiCBfCBgh9vRm+11GaRlo/yvqM94d8/cnS/uv3qoX3vqC+OKOXrm99//oDQ3t8q4CjhCqW6ijtGHmsoyqdcNZxDgOAd1LSsrkVk9ZiABJwEaxTlp8JgESCCvCEDQ0TOP50wG19Frx6ffAWke1h3dvIRDJ0ZMGb7/7XvmGcCtXLVavvWt70hLS1tUUuidT+pQOwR+ROs4NjYpM1qX2irdgAbz81PRBnhRD/OkKAmwh16Uzc5Kk0D+E0APFkPugzp/7h5ux1A4es8QXPRqyzTukgW1smZZU2ToO1MCSBd/XoKN+1/++y3GE9yAWrcjLFcDuK/tfFAWLGgzgp0oLQj8zAyN4xIxKvZ77KEX+zeA9SeBPCWA4ehpdbPqHm6HkdqPf3VI90QfjgguBBXnc9eHfKkxXhL0fcJTQFz8tbYtkc0f+rw0tiyU9iUr5LN3f12WL1ti5so9JcRIJJCAAHvoCeDwFgmQQHgJYLgdPXHncHs6Rmrp1nD/kUHN29vTS9tqzWgCYltRX9LerD3zhVKle7hPTtLYzRtJxkpEgD30RHR4jwRIIJQE4g23p2KklknF9h8ekN2v9nhKAr341UubouJC1JctWaJ+3stMLx8jDQwkkCmBvBH0559/Xr773e/qso5vzKtzd3e3PPvsszI05M9Q2rwMeIEESCBUBGINt6djpJZOpQ5oz/zXKYg51qHbJWvO/OrUcr2mqtz08oMw2nPmxePiIBD6IXeI+N133y0DAwORFrnxxhsjxzh45pln5BOf+ISsX79e/u7v/i7qHk9IgATCRaBKRQyCPKFrqtO11LbD7XDeYr3DWcMzL7VF3OHRSanX9eGphM6jg/Irl0c4PL9qcYPO188IrNmR9sz0hPR2/lwWNczKskv+27wsKitKpUL/IOgz+hwDCfhBINSCfs899+jazPvNHNmGDRtkz549Mjg4OK/e119/vTz88MOyd+9e+elPfyoXX3zxvDi8QAIkkHsCFTpfXKpiDqt0OFsRSV3Uo4bbdQ7dDldbwzMIqpfwo18ekjPV6h1/FTofnyx0HRuSX74c7d4Vz6ztaJa1K5rN42csUN/sX71Deo516fmsHND/l04NyZXXbYvMoSNiXc3ci0SNbq1KQQcRBj8IJP8W+5FLGmlgCH3Xrl3mye9///vyzW9+U5YvXx43pY0bNxrhh7AzkAAJhI8AlphB0HvUAczBE8PSNzQulSpo6K2nEhAfa8uNdfvgWORRpI+laV4DDNpe6u6Xf/nPbnlN58SxLMwZMAxu17B3q5jD45s7nL28KSLm/b0n5KEvf1TFvFOjnU7r5Rd+LuNj0evVMdxeWV5mHMRMa10YSMAPAqHtoUOY8QO988475dxzz01aV/TgEbq68GbMQAIkEDYCGGrHJiMn+sdkTJ2lHOkZEV34JU31lcZ5ildhcw63u/c+X7200SxPS6XuE7pDGgzcXj00IOtWtZhhcBzbNey62kxcWm+SP8sl5g/ee/s8pzF217TqmrqoIsHzG4bbEdwvElEReUICKRAIraDv27fPVOPqq6/2VJ2Ojg4Tzz7n6SFGIgESyAoB9Mzxgg6RHFGPZy+8dlKWL2owgq6XpVH9nI+PT0aGz+MVyg63DwyrM5nh8Xnxky0jQ14LGqvlpL5UnO5Dz+WG7U+fe2HO4Ysz/1hivmZZo5yjw+yoE3rmicTcvZ85ylBTDUEvo5g7QfM4YwKhFXT0tPFjqa+P3qUoXo3ZM49HhtdJILcE8DuGoENER7VnfkD9mkN4u9RaHC5MERCnobZizr1pLAU9VQU73I50emPsrAanMrEC5texFhzLx2BxPqTe5fYd6NFRgtFY0RNeW7awTtatbElLzJFwnYo5qs3584SYeTMNAqEVdPS4sRwNy9W8DLljzh1h3bp1aWDgIyRAAkERMEPtug3oCZ07P3py2Mx927wO6Nw1xBwBQomhaOOzPI6oJxpux9D1QfUG5wyY4z5T/yDoNh/cr9eXhzefu8i8ZOzd36Pz+RPOxxIeo7RIK9WeuU0U8+d4kanUNeiT3D3NYuGnDwRSs0bxIUOvSVxxxRXGyO2+++5L+gh65zt27DA/sk2bNiWNzwgkQALZIRAZatf58hFdJnY4Rg96v/bYewdGjaHcsA7HV2sPFkPr7jBvuN0l+sf6RmXCtWHJ8vZ6KVcjOqeYO9Nd0FQtv/O6JfLGsxY4Lyc8xrRBX8/xlIbZnQnWqXU/5s9RQ2uh77zPYxJIl0BoBf2mm24ydXryySflk5/8ZNz6/fCHP5R3vvOd5j569e9617vixuUNEiCB7BGAAJuhdu2ZY4h8/2Edao+T/Wu6kUofrN+1hw3r9aqq+aKe6nB7S0NVZNvRONmayxD7xQuijdYSxceyOCxN6z1xOCqaNYBzz5lHRdITYxCnvXNMO9ChjJsOzzMhENoh94aGBrNU7X3ve5888sgj8sQTT0TqCW9xu3fvFhjAoXeOHwV+lFjaxkACJBAOAliSNq5D7Zg7P3JiSEZVqOMFCP2rB/tkTUmLidKhPetqFXUMv1vRw3A7hsZnZmfEbd0+qT1z93z4ch3C9xpSWcMOpzFz68xPp+5VzCvVlgD1qKZDmdPweOQbgdD20FFDLEX73ve+J8uWLZP+/n7zh+vwHPeDH/xAOjs7zY8d8+boqSdap47nGEiABLJDIDLUbubMJ1XQo+e2Y5UCPdZXunulX9enw7gNS9ww/I6XdTvcDoc0A3Am4xpuP6z5OJd/6SNqBOdd0JGH1zXsfV2/0OKfHmvwKuaoM3rnCHMe4k6nYS7yfySQIYHQ9tBtveDO9amnnjIC/vjjj5teOcS9qanJGMBhzvySSy6x0flJAiSQYwJ2qB3rzUe1h445cq/SZUS9q0/OWtEiXTIkK9BTr4Y3tTknL6Pj0zrfftqZjK0qtkZ1hkUtNWYXM+e1ZMfYKx0Ob1CGeAEvCm86/2zp+lmFTE9NSipijjQjDmV0OmJygg5l4nHm9fQIhF7QbbWuvPJKwR8DCZBAuAlgqH3MOdSu8+epBPhnf7mrd07Uj4l0LKo34tw7OG6G2/v10xkwP4+XB2dYvtDbclfnM1jOho1U4BEulqhDzHF/+cJVUr3tDvmXf3hI3v2BT0myOXNnHnVqXU+HMk4iPPaTQN4IurvS2FkNc+uYS4cx3DXXXONpeZs7HZ6TAAn4R2BuqF3kSApD7bFyx5D6S529cvbKVoEP9RXqhMYMt+scunu43d07Ly8rkUWtNbGSTXoNLwLwMf+qjirYjVbca9iRyFnrLpA157xRpwK8z1piqVqN2gXQoUzSZmCENAmEVtBh8PaHf/iHMXdQw70tW7ZE7cCGTVy2bdsmH/nIR9JEwcdIgAQyIRAZatflY6O6vjqVofZY+Z4W9RbBLmfwq253VrPxYTDndiazVC3Wy1IQWpuW/ZzrqS+U81ZNSEmp+prX4XHMsbtDKmKOZ2trdKmaJjM3f87hdjdPnmdOwPvrZeZ5pZQC5svxY401P37LLbcYAzl7H8ZwOMZmLthtjYEESCD7BCJD7erB7bDOaWMoPNMAEUdP/ZiuYz+ufz2uoXUYyA2q1zdnwNrzTEN/73H5+uc/KM//8icxxTyd9Ot1hzW8HMDSnevP0yHIZ5IRCK2gw4odb8UYSneGRx991CxVw70HHnjALFX753/+Z7GOaLjbmpMWj0kgOwTsUDuszYfHJoxHOL9yxpI09Pa7tJfuDu7hdgxnL2isckdL6Rxi/uC9H5WTxw7KYw/dJbt//m8pPR8vMgziqtW+AH19p0V+vPi8TgKpEgitoMOSHcHt9hWOZhAwb+7svVtHNNycxeDh/0ggawQiQ+3aex7TofYDulNZAkNx38o1N9webd2OOfBYw+NeM7Vibp3GzOqad4j6C7szH/mDoGO4HQZ3KDsDCfhNILSCPjAwELOue/bsMT9Yt8U7BB6Bm7TExMaLJBAYATvU3uPjULuXwh7XFwisVXeGVJzJOJ/DsVvM7f0Fi5bJspVn29O0PqvUMxwcyswZxHH+PC2IfCgpgdAKeqySo/dthd7uf27j9fX1mcPGxkZ7iZ8kQAIBE4gaah+dMNbtAWcZSb5brd+dAcZssFBPJ8QT81TXmcfLG71zBAy5c7g9HiVez5RAaAXdDqc7jdxgKGeDvW/PsTMbAhzOMJAACQRPwD3Uvl93TstWgLEcNklxhnR750GLOcoID3FVagwHo7hpLTsDCQRBILTL1tADx5aosGi//vrrTc8cBnGYH8O5Ozz99NPmklvo3fF4TgIk4A8BDLXDkh1D7YfUqn3MB6t2ryU7omLuXo+O7VdTDdkQc5SpTi3csf85AnvoBgP/FwCB0Ao61pTDcQx63lhjjgBDEvTAb7vttnkorNhfddVV8+7xAgmQgL8EsPMZeuhHdCnZkA61Y5/zbAa3dfvC5moznJ1KGbIl5uAEY7i59ec0hkuljRg3NQKhHXJHNb7//e/LjTfeaDZdwVpz9Mzh172+PnqdKZa4Qezdlu+poWBsEiABrwQg6HDvCqO0Q665bK9ppBsPlvTY+9wZOlJ09ZotMUcZ63SDGaxVq9YldTMzHG53thuP/SVQokLIV0Z/mTI1nwlgzrGnJ7s9QJ+rUHDJ1eiccI/6VMfQ969/cywry9QsxFd0Tfre13rtqZmXvvLNHVKuLxleQjbFHOXBXusdixvkrOXNMq7TEtmYQ29tVW95yiPsv53y8jJpaan10myM44GAt1+Ah4QYhQRIoDgIYAgZtizDo5PGv3q2ewTdx6Jf7rDtqVcxHx8bMU5j7Dpz22J+WbPb9JyfZkOWyPw5e+hONjz2lwAF3V+eTI0ECp4Aen4w7MJWpgO6d3k2AzZo6Vd3r86Qys5qVdW18oaLr3A+nvIWqFEPeziBhXt1xKGMhwcYhQTSJBBaozh3fbC7ml1r7r7nPsd8OwMJkEAwBNBDHx6b0mH2WYEv9WwGtzEcloLBIC5eWNRaKw26Pv2I7nM+pCMKCG+9cqP5/Nd/fChwMYdDGbwA0aGMQc7/BUwg1IL+/PPPy86dOwVGb14DhgLp/tUrLcYjgdQJQKCGx9TNq84HT7g8taWemvcnYO7j3lkNS9XiuXqFVfky3Xa1UudpG+qqpOvIgJw4ZUwHUa+tb5S151+U0n7m3ks7FxMbsugEhVmyNqU+6RlIIEgCoRV0iDK2T0Wg3V6QXwGmTQLeCUDMETB/nm7vHL9nrCGPty1pvNJgvTuG+Z2hI8Ha87bmGjO3vmpJgxzvG1Ph161Lq8ul+8igMeK74C1XO5MK5Bge4ior5pb40cI9EMRM1EEgtIJ+9913R4QcTmbwR7eujpbjIQnkgEBZWYlZqjapKw9SnT/H3PcrB/uNhzcr6DBoW7OsSeC2NVnoOh7t6rWhtkIa4zwH8Z6Z0B754RNy5rLfkkUtNeqprdT05uF+9dWDfVnZwtQYxOlIAQIdyiRrYd7PlEBoBd1uwoK155/61KcyrSefJwES8IEAeugDQxMyqz1sGKh5DRgq/8VLJ/Ql/fQTEHXMiR/U+e03nNUmiYzbpnX99iGN5wxw9RpvuF0mB+WO/+9PZGxkWLdZ/raceebZ0lxfZfYiP6Q2AOdWLJBXuvt82bPdWSbnMUYg4B0OfxRzJxkeB0UgtFbudhMWeIxjIAESyD0BiCf+IsvVHOKcqHTombvF3BkfIo/7but1Z5yjPaMyNR2dYbwXgP7eE/LXf/EROXKoWw1pe2XLlj8S2OOMjU2quJbJSp1Xb1RxX7uqVZr0M6hQq8PtcChDg7igCDNdN4HQCvq6detMWWmx7m4ynpNAbghguH1G1Rf+29FL9xowzO7smcd6DvdfVYcxsQLm3DuPDUbdWtBYbVypRl3UE4j5Q1++XY4eORi5hdUxn//8p42TFYg6es4rFtUbMV/T0Wwcv0Qi+3iA5WplpaVmVGDa9TLiYzZMigQiBEIr6HaTlRdeeCFSWB6QAAnkjgCG20d1uRpEfWDY2/pziLF7V7R4NTh0YiRiN4M46LH/52+Oy+M/7ZRjvWNRj3W0z9+IBWL+4L23S8/xw1FxV69eI1/4wl+Z0QW8OEDUZ1Rgl7XVycKmGlnaXi9n6Dx+KSbefQwwiEPvHIEGcT6CZVJxCYRW0G+66Sbjs/3jH/+4YA06AwmQQG4JQNCHVNCxVA1+3L0EzJPjz0tAvJ/uOyr71Qr9Nd2K9ce/OmTm2GM9D2F2Bivmbg9wEPP77ntQ2toWOqPLhPqDn9A6LGiqVmGv188aMwRfUe7fP4l2hzW81LjLG1UYnpCATwRCaxTX0NAgDz74oFm6dtlll8n73/9+Qa8d15ubmxNW3715S8LIvEkCJJCUAIbbEUa0d5vKcDuUDE+69NekFet/WF6Gv2Th16+elOaGKmMdH0/M16xZo34s5ou5TXtqalqLN2P2Kl+pvtZhoHfuGXPGcrATyCTAMxyYcYe1TCjy2VQJhFbQURFslYq5dKxJv+uuuzzVDUY7dCzjCRUjkYBnAuidT6pjFOyu5nW4Hb34554/6lnMPRdGI6LHizn31W0lZpjd3TNfs+ZM2bXrQWltbUuYLOa2MQRfrevTV6moH1RRP3tli3TqKMFJ145uCRNy3cRwOxzKYIe1qUk6lHHh4WlABEIr6F1dXXLFFad9LmPYioEESCA3BErVuGtAl6nhZzjowd0rnM78h4q52xGMn6WH+P74bz4tbjE/44w18tBD/1On7BKP5Nmy4N+WUe2RV2mvukPn04/2jpj5dvSuu49GG+PZZ5J9wiAObl8xL8/582S0eN8vAqEVdKdjGfTSr7nmGjqW8avVmQ4JpEAAtmLGf/volC5Zm0g6J36sd1R+9uKxecvM4mWJ9F+3eoF6dSuRQ7odq1cjOkzN9/eejEq2Y8UZ8q1vf0e35Fwgkym6pcXWppUqwovV/3u1fhqXrSrqr+p69Vjz+FEZu07QQ0caCFyD7oLD08AIhFbQn332WfOWfOWVV8oXv/jFwAAwYRIggcQEMNyOnvmwh/lzGLPtebVn3jB7rQrj+lUtckR7v7Bmh0Bi+djStlpZvfS0p7ilankOq3YvAjo9Na7W6qfnupd3nCH3fu0BWdTerj1u78vqnLWHoRwE2DihUR/wh06UyDk6r/6aepYbUYNALwH1whw658+90GIcPwmEVtDhWAbz4TCGYyABEsgdAbNcTXuvWK7WH2e5Goat9+7v1XntgXkFbVHjtTef026GoJeoYL/+zPi+3PGbhztY965q8xLVC31d/6n/n5uKW7RkhXz2nq/L6hVLzXpzvICkG7CJysyMOqFRUYaxHDzZwQlNl86r281dEqWN3jnCnKBz/jwRK97zl4B/azT8LZdYhzLnnnuuzykzORIggVQIQNDRO4dRHNah2wARn1Kf7pNqLf7cC8diijl64BvWLzJibp+DaJdrmviMFeDbPc6tSHRYpx978V/NedviDvnYZ74iSxYtMiLqx65m6KVbJzQr1QlNa0O1rFjSKKt0NCHZenUIejkcyugSODqUiTQZD7JAILQ9dAy1f/Ob3xQ4ljnnnHOygIJZkAAJuAlg7hwB+58PnuqduzdZcT9jz89e3iRrVzTHFW4bz/2JjVrg2z2eu1iI/evXLJCRfR1ysrpUbrzlL2TlimXG8xteMqb1JcOPgF4+RB3z6thXHTu1Qcxr9RPz6vHW4tfXVhrrdpSBBnF+tATT8EqgRH8AGQxOec0m9XgYcsf689e97nXyjW98I/UE+ETBEMA/0D090RtzFEzlQl6Rigo1DlNRf1ndt76mf7tfORFXaG1VjOCe2WYsxu21dD7x4oClafHm3KemJmV8dETOWLlEVixuNLu2zWDEIEVjOC9lwyhFpW6yMqGjEdgkBu5vD6i9QO/A/DXzr1/bbl4AWnWqAdbzuQitrXW6Dh4jBOH+7ZSrnUJLS20uEBVknqHtoWOr1Iceekg2b95slq9t2rTJOJbp6OhI2hB0LJMUESOQgCcCEIVBiJK+9nfpEq54vWZnYr+lFutY/pVpmOupL4w7515erkPbDU2Cfc/n/KaXyIRrv/RMy2CfhzCOjU3o0rYKM69+tGdELf+bpF63cMXSNtstwrw5RjW4w5olx89sEgitoF900UWGw+DgoOCPjmWy+bVgXiSgG4Xp0PbccrVJM4f+m66+iHAl4nNycEx7zA2Joni61997XH7w2C55x6abpbYudnoQcliUwyodomuF1VMGKUY6PQRfroZ7dWa+HkPwddUVur96v3GJG+1Qxpt73BSLwegkEJdAaAW9vz/2zktxa8IbJEACvhKAMxnMx2H+vF9F2uv6cAyRw5I9ntGbl0JCzB+896PGaUzvySPyng9+Nqaot7XUqPFZmZnXxjrybAT4gZ+ZKTUvEdU6DI8h+HPPKJf9Oj0AQT/tUCaUs5nZQMQ8ckQgtIJ+66235ggJsyUBEgABDLePqUhOz8xI7+C4p7XheA5ryPEHRzHpBKeY4/nDXS/Lt7/6sXmijvXezWp93lRfaXrm6KFnK8CSflrXwFuXsXjZwVassI4/vcMaBT1b7cF85giEVtC3bt3KNiIBEsghAQh6nxqmGX/nKuwQUC8OXxAPf+kEt5jbNCYn9YXC4UQG11t0pzTsN4659unp7A9vw57YuoxdtrBOegbKdWOZUc6f20bjZ9YJhHYdetZJMEMSIIEIAcydYw7deIfT5WrW4UskQoIDrD1PZ7g9nphjnfkNN39OGhpbo3K1xnBY0z6Zww1QMNSPYfjWxipZoWvWsawtm6MFUVB4UtQEQivo99xzj3ziE5+Q7u7uom4gVp4EckHALHmCcxW1GrfbpUKskgW8BMCVa6ohVTHHmvBaNUbDcDuGuXO9+hZD8FizXqXL/DA64Ydzm1QZMj4JhFbQn3zySXn00UcFPt0ZSIAEsksAgo7euUplZLtUGMclChBzOITBEHgqIVUxR9oLdalahZYRRmjY1zwMwXqXwzB8rl8wwsCDZcg+gdAKunX5umfPnuxTYY4kUOQE5parTRkHKnD5ioDtSp3BzpKjR9rRXidv/a2lsnxh8l68M410xBxLxVoaa8yLA8rA3rCTKI+LmUBoBf2mm24yb7nopcP9KwMJkEB2CKB3jjC3u9q4OR7TOeIT/dFe0d54dptcc/EK8/eGsxZmpWeOwjTrXHWZWtA36dpzirlpHv6PBAyB0Ao69kC/4oorjKjfcsstcvDgQTYZCZBAFghA0MfVfSo2XrHz59hxzBnQK8e+4Yk2WXHGdx+n0zO3abQ11xpnLhW6+UlYhttt2fhJArkkEFpBB5R7771XNmzYIAcOHJDLL79c/vIv/9LMqQ8NDeWSGfMmgYImgN7vsM4DY0546NS+4u7hdmxxanvyqcLo7z0RcRrjfDaeNbszTrVulAJ3q82njOFQRgYSIIE5AqFdh25dv6KYWAIDI5Ndu3aZv0SNh7j79u1LFIX3SIAE4hDA7wd/c7urTejvTlTUJ6VvaCLqieW67jrdAA90ZWXR//R4EXPkt0CN4bA1KVy+BrEJS7p14nMkEAYCoe2hw/Wr/bMWo/j08hcGsCwDCeQjAfS60esd0bXVA6e2S4VrU2fAPt9tTTXOSykdNzS1mnXlbYvmNlryKub6niELNN9GtaLHSwfnz1PCzshFQCD6NTlEFb7zzjtDVBoWhQSKgwCG2yHmeHHG/Dk+u13W7Uvb6symLZkQsaL+T4/+tbx94/87z2lMrLSxAUu5vkxg7TnFPBYhXit2AqEV9Ouvv77Y24b1J4GsE0APfXh0TMYnpo1h3IC6fsWQuzPAzakfAaK+advHPSe1QI3hsD0pnLfAiQsDCZBANIHQDrlHF5NnJEACQROwRm5D6kBmYGhuuZrbuh0bj7Q2VHkuyvBgvw7hZ+74pbKi1Ay1o5eOUQMaw3luAkYsIgIU9CJqbFaVBBIRwHD7hDqRmVTPa5g/h3C6rduX6XA75q+9BFiz3/+XH5G//84XMxZ1zJ2jfA1q4c7hdi/0GacYCYR2yD1sjTEwMCA7d+40y+aampqMwd55550n27Ztk46OOeOedMucSdrpPotlgFjrf80118j69etNHZBWV1eXwDvfI488ItjCFssGGYqDAHrog6fmzQeHJ6VHt0wd1aF3Z1jm0RPc3NK02+f2Mz9x2CTx/7z7j3XuvcyZnOdjbMTSUFsp8BI3HhJXr54Lz4gkkCUCFHQPoPfu3SubN28WzOs/9thjkScgehDGL33pS3LVVVdFrqdykEnamTyLFQQ/+MEPzF+s8m7cuJFiHgtMgV47vVxtUoZGdA16jN55gy4Va9QecrLgFHMb91f/91+kqWWh/P473msvefqEN7h2dWBTofPmGG7HLmZaNAYSIIEYBCjoMaC4L0HM0Ru/7bbbom5B9Do7OwWe7J566qm0euqZpJ3Js1EVcZw0NjbKpz/96bRfUBxJ8TCPCGA4G0PsIzp/3q/z55ijdi9XgzFcsuH2WGIODFiaduFb3+GJCLzPYb05NmCpVEcyMIRrUTGHUxkaw3lCyEhFSoBz6Eka/q677hIMRUO8Y4VNmzaZyzt27Ih1O+G1TNLO5FlbqAceeECwPHDr1q3mE+fPPfccxdwCKqJPDLdjuRp65rBsP94/aubTnQgwf54oJBLzWPuZu9PCzmmrljbK+bpjW8eiBmlvqZVVixtlpR5j7hz7jtMYzk2N5yRwmgB76KdZxDy6//77zfV4Q+qYP8ffM888Y+afU5lPzyTtTJ61FeX8uCXBT7NcbWDceF8bU+F0G8PB1SoEN15IV8xhX9eqO6ctbKmRWk2/shxD65Vm4xX4i8cQ+/j4pH5ynD0ee14nAUuAPXRLIsYnRBoBw9CJghVx7OHuNWSSdibPei0f4xUPAWyVioDd1fq1d45NWQ6fHIkCkGhb1HTEvFLnxJe118vrdJe2VUubzDw58jhDe+gtDdUyo2UYVT/y6JVTzKOagickEJcAe+hx0YjA6AzBCna8qA0NDebW7t2740WZdz2TtDN5dl5BeKHoCaB3jj3PscMa1p8f7R2VademJ0vbamNy8irmVTr/XVddYXr56InjGPnC6xuM3eBOFsPpk7pNK5elxUTNiySQlAAFPQEiK9BYppYoNDc3m9vd3d2JokXdyyTtTJ6NKgRPSEAJQFgHRuY2YhnUHrp7uL2tqVoN0ub/UxFPzBcuXiH/46P3yJLFi6T2lIjD6A4BQ+pwToPrmBfHMjQIOIzdOD9uEPF/JJA2gfm/0rSTKrwHBwcHPVXK9tBhPOc1ZJJ2Js+6y4eld08//bS5jBcSvLxg/TnWpjMUPgHMYWPIHburYcvUMe0hH+uNHm6P5eo1npgv7zhDPnvP16Wltc3slQ7L9Bp9GahWEcdLAebFESDeU5MzKubR69wLnzhrSALBEaCg+8gWa7uDCpmkHe/ZLVu2GMc42HfeBmxRe9111xmr93iW/TYuP/OfQLn2mCGuI9pDhnc4zJ07R9uhv9j73BlmZmbk4V2fMk5jnNdXrFwtX/7aN2X50sVGvCt0GB3BumrFvPjkxAx74k5oPCYBHwlQ0BPAjCeE8R5JpYeeSdqZPGvLjnX1WLLmtg+A5zsY3WEZHu6FwRIePcjW1sRLpmy9+JkaAfTQj+uceUkJlq1Ny+Ge0agEluhStaaG+VulbrnpNvniZ/9ERkbmtlY988yzjHfB9vaF5nk6f4nCmPUTa+jI307W0ec0Qwp6TvHnLnOsOY8XsETPijoc5uQ6wJmJnYPNdVkKLX8sCzvRP6ZuXsfMrmrHeqKH21ctaZy3VSpeAjZccpGs/uv75Y//xzZZsmSJPProo9Le3l5oePK+Pvzt5H0TplQBCnoCXMmM4eyjdk472fI2Gx+fmaSdybPOMsQ7tr1y+HWHsNvzePGDvm6HbIPOp9jSN73zvlGzGctRHWo/cHhAnKu9y9WQbfGCunlD5AvUSA4vWJe+dYP8zd/8jSxdukwWLGgza8aLjWFY64ueOcQ8H347MMpk8IcABT0BR2vsliBK1C2vQouHMkk7k2ejChznxFkPLJHLtaBjjrenZ25oN06ReTlFAnCpWlJaKkdODMmh40O6KcuY7D8UbQOyWH2oYxmZe+fxJl0rXqPryKfVoG3VqrVG8Nk+KTZAwNExRYWXrrD/dmDD0aIeARn8IcBXowQc7XI09FQThb6+PnM7lR56Jmln8izqgg1l8JesXqiUlziJ2PBe+AigZ16u/5D2DIyZ9efoncPCvVd3WnMGWLf39x4XbKxiQ0tjtWBNeat+YrgegsFAAiQQDgIU9ATtYJduJTNCs0PuMDTzGjJJO5NnMYQOkcZfKp7tvNaL8cJPADuXwftar26PijlzeIY7eCJ6BASOXipnh+TBez8q3//2PfLcT/7JVGyRWrzDKQyWo02qIxoGEiCB8BCgoCdoCzvUnMx63fZibfwESUZu2bjppJ3Js3Y4HaMJ8fzTO19g7MtDpOA8yGsCtnd+Uo3g4B3uqE5lYJ61+3i0oLc1lMq3vvynkaVp//ToV2X3fzxpHMK0NlaZnjl753n9VWDhC5AABT1Bo2LZlhU0627VHR2CbAU9lkDiHnrF7pBJ2pk8i/rghQC7qiGdWMH23CH6wez3JAAAKjVJREFUV199dawovJanBCoqyk2PvM/0zodNT31A9z8f0iF3Z/jZD++PiLm9/tN/+wdRB62mh87euaXCTxIIDwEKepK22L59u4nx+OOPx4xpxRre1dwBYo+56i3qwAXbnbpDJmmn+yxEHEZ18V5QUMYnnnjCFBX7oqdiF+CuH8/DRWCud16qc+e6q5r2zu0StYNqFOcMU2P9cuSV55yXpH3JCvlz9QC3uK3B9Ogxf85AAiQQLgIU9CTtgV43PKZhu1LbE7ePQLDvuOMO04uHQxZ32LNnT+TSvn37Isf2IJO0M3n2M5/5jNxyyy0xRR0OZSD2qHOsEQdbdn7mH4FI7xwbsJzU3rkatM0Nt0cL+onX/kMrd9rYrW1xh3zs01+RRe2L1P96JefO86/pWeIiIcBlax4aGh7V0KuFS1T0jDFkDbGGm9RLLrlEnK5TnckhHoa48SIQS/ARN920M3kWve7HHntMNm/ebNbD2zl59MxR1i996UsUc2dDFsAx1iSXq6HbUTWCm9TlZvDXjq1S9+3vUf/t0b3tkZ7OSI0h5ts//AU5Y+UytWyvgh9X7oYWocMDEggXgRJ9Qz/9Kh6usoWuNOiRWytxiCKEMN48dKqFzyTtTJ5Ffezwu51fT7XsQcfH8C7XOWdGuVI3RsEP/VV1HtN9dFB+/sJR+cVLJ6DP88LszLTs/+lDUjZxVG64+XOy7uyVsqStXlbr+vNpHarn/Pk8ZKG7MLcOvdQsLQzzb6e8nOvQ/fzyUND9pMm0AiFAQc8MK3rnNboH+RHtnZ9Qz3BP//Kg/J9fHYop5jYniPqbz26UjqWL5Pwz26RdnX/AQ9yIbrPKEH4CFPTwt1EQJeQcehBUmSYJhIgAvMJNaM+6Xx3HHNG585cO9icUcxS9pLRMjuhuwO3qLQ6uOZsbqtgzD1GbsigkEIsABT0WFV4jgQIhAJ/eEOSTugHLhDqCOabrzrFFqpdw6MSItDVXS3N9ldnHnHuXe6HGOCSQOwIU9NyxZ84kEDgBeIWDkA+oAdyRk0O6Bn3WWLd7yXjOCr5EWrR3PqU9/Fjz7V7SYRwSIIHsEKCgZ4czcyGBrBOwvXNsjzoxOWXmz8vQY9c/L6FCreJbdd4cnzSE80KMcUggtwQo6Lnlz9xJIDAC6J2Pa+98UD3BHVZf7ehhw0CuXg3kvIR1Z7RKmwo6jBK5GMYLMcYhgdwSoKDnlj9zJ4FACDh75+O6BepJtW5HgMAPjSa3VEcn/rI3LZcqfSlg7zyQJmKiJOA7AQq670iZIAnknoDpnU+gdz4hB48NRvy+vdjZp3PoicsHF7HX/t4aOW9NGzdhSYyKd0kgVAQo6KFqDhaGBDIn4OydHzp0SD738e3S+epeGdKh9wNHBqMyqK0qj8ypY269o71O3nPVWnnzusWCe+ydR+HiCQmEmgBdv4a6eVg4EkidAHrnY9o7f62zSz5+6/vlxLFD8j//eods2PQX2lM//ZPHsPqG8xdLja5Th0U7BL1efbWvXtYsCxqrTe+cm7Ckzp9PkECuCLCHnivyzJcEAiBge+fPv/Sa/OlHthsxRzaVTctlYPy0mOPa6qVNphdu/LzrWnV8LlpQZ+bNYTjHdeegxEAC+UOAgp4/bcWSkkBSAvDZvv9At9zywffJ0cPdp+KXyPLX/2HUs5UVpXLW8qaoa1XaU4cTmdaGamPVjrXnDCRAAvlDgIKeP23FkpJAQgJlZSVy7NgR3UXv3XLkkBVzkdaVF0pt64qoZ9d2NJv15c6L6J1jR7bGugrOnTvB8JgE8oQABT1PGorFJIFkBE6ePC7vfvd/k0MHuyJRS8oqZPkbro2c4wDD6SsXNURdg/MYbL7Sql7hdLU6t0iNosMTEsgPAhT0/GgnlpIEEhI4fvyYvPe979b97Duj4p3xpmulvDp6aH3dqhbBXLszYBOWcmzCokPunDt3kuExCeQPAQp6/rQVS0oCMQkcPXpEbrzxj6Sz80DU/faOtbLgzN+LugbPb4taaqKuwbq9rbnWiDmEnkvVovDwhATyhgAFPW+aigUlgfkEIOZbt75XxTy6Z962uEPe/Ae3znMig945rNmdoU33Osfc+dwmLNPOWzwmARLIIwIU9DxqLBaVBJwEIObbtr133jA7xPyd2z4jh3smndFl+cI60wt3XoS2Y7i9qa7SDLmzd+6kw2MSyC8CFPT8ai+WlgQMgZ6eHiPmsXrmN9z8OTlwQjdUcbDCUPq5K1scV+YO21vrpLK8zBjDzW3CMi8KL5AACeQJAQp6njQUi0kCTgLt7QvkTRdc6Lwk6JlDzMdnauRo79xmLDbCmqWNUqOuXJ0Ba9GXtNWZofZK9S43od7lGEiABPKXAAU9f9uOJS9SAtXV5TrnXS43fehj8vtv+wNDwYp5fUOL7N3fG0XGOJFZFm3pjgjLFzUKhByGcrBs5xapUdh4QgJ5RyD6lT3vis8Ck0BxEaiurjBD6V3HhmRkfEaufNcHZaqsXi78nbdLQ2Or4Hr/cPT2qOeoExkYvTlDky5Pa9Y157B4xzw6e+dOOjwmgfwkQEHPz3ZjqYuQgBFznRjv0u1Qh0Yn5aWuXhlVUf/9t7/H0JjSfVGfPxDdO4cTmRWLo53IQMA71LFMvb4cNOhmLOPjU0VIk1UmgcIjEP3aXnj1Y41IIO8JwJ3rwECvzMzOSqeK+aCK+W86VczHTgsxhstf7u43u6w5K7weTmRcy9SWtNVLtc6nw7odhnDcUc1JjMckkL8E2EPP37ZjyYuAAMQc68xLS8vks/fcJ9W1TUbMx08ZsGF4/ZWD/XLo5IjZ7tSJBHPj7S4nMtW6AcuiBbXSqtujVuow/Oho9PC883kekwAJ5BcB9tDzq71Y2iIiYMUcS9P2739NbvvQjfLcr18WK+bdx4fkx786JN3Hh+eJOTAtVEF3O5HpWNyo26OW637nVcYjnHbsGUiABAqEAAW9QBqS1SgsAseOHZ3nAe7QwU75X9/5sqkoeua/eOmEWqbHr/cLXX1RBnLolTeoA5lFrXOuX+lEJj473iGBfCRAQc/HVmOZC5rAnJi/J6Y717dv/KCpO4bZE4k5IuH+q4f6TXz4a1+uhnCNagRXp8ZwExOn599NBP6PBEgg7wlQ0PO+CVmBQiIQq2eO+tl15liaBgO4wzpn7iUcOjFi4i9tr5cqnT/HnPqcIVyCrr2XhBmHBEggdARoFBe6JmGBipXAaTE/EIXAKeajusQM1uzTM94EGfEg5At1N7W2phrjr52GcFF4eUICBUOAgl4wTcmK5DMBu9FK98EjWg1dKH7KE7sV89nyep0zP24M4JINtTs5YKj9jKVNZpkaHMlgqD2V551p8ZgESCDcBCjo4W4flq4ICPzy+f3yhV1/Ly1v/rC0lVfJ9NS49HX9QiZO7JVrNt4s+7on1Tf7obRIrFYf7nU6bw6PcLPaW5+amkkrHT5EAiQQfgIU9PC3EUtYwAR+8OyL8vCPOqW6/fxILctU1BeccbGI/v3iVW9z5ZGHHQfwJ/N7b+owW6ZiY5axsejtVB1ReUgCJFAABGgUVwCNyCrkJwH0zCHmJeo0JpWArVBXqTvX9We0GD/ssZ6FmF/x5hWyUi3bFzbXmJ75jMd591jp8RoJkED4CbCHHv42YgkLlMDOR/9NSqo6PNeuQj27nbGkQf/gHGbuJQCGbliaBmt2GMBhznxpW62cv7pN3nzeYiPmcP06OsHeuWfQjEgCeUqAgp6nDcdi5zcB+GWfrVsp4nFOGz7ZV2qvvLwselCtSR3FvOGshfL6M2cjgg4BP3f1AqnVYfam+kquOc/vrwpLTwKeCVDQPaNiRBLwj8Dk5IxMeBRz5BpLzJ2lgYvX8jJYx4v6aq+TmqoK9QhXa1zC0hDOSYrHJFC4BKJf9wu3nqwZCYSKQG1thQ6be/v5YRgdf15CpQ7FL2mrkxb11Y5heW6N6oUa45BAYRDw9i9KYdSVtSCBUBCAURuEt7G+ylN5MCfu3mQl3oPY5xxpY6c1+GqHVzkGEiCB4iBAQS+OdmYtc0gATmM+//lPq8DObVVaWVku/+snr8rx3tGkpYK1+mp1DOMlNOkLQpM6j2lv0RcAfYCbr3ihxjgkUDgEOIdeOG3JmoSQAMQc+5l3dXXK4cOH5Itf/Ir87IUeefSpl5KWFmL+hrPaBIZvyQIM4TrUaK6+pkIadDifQ+3JiPE+CRQegRIdkuOYXOG1a0HVCJuJ9PQM512dnGJuC//WK/5QxtvfJpMugzjsT943NGEs1bE87ZwVLXLBue2yQJelYf24+dOfqvsYS9VgMQ8Rb1N/7VjShul2CrolXpyfra11UqYrIsL+2ykvL5MWHVFi8IcAe+j+cGQqJBBFIJaYV9S2yED9RVLqEvNzVjTLhtctkeXtDcaQDXuWI0C88bptlridEm79MPPiznu4j7BA9zvHywA3XzE4+D8SKDoCFPSia3JWOGgCscS8tLxa1l3+x1JaWR+VfYdua/r7b1ou7brUrKWh2mxvempflrhe4KISOHUCUYfh3JwhXKwYvEYCJFDoBCjohd7CrF9WCcQSc/XtKusvv1nKahdGlQWW6Nf97hpp1WH1Ra01xuc6BDmWMRvm0+dCSUToreW7vYeOOoZYGUiABIqTAAW9ONudtQ6AQEwx13zWX7pVKprPiMoRc95/dOVaWaDz3st03XhtdbmZ944nyKdG1TWNuWH4ucTmhtqjEuYJCZBA0RKgoBdt07PifhKIFvMSKS2rkJnpSTn3kndKVfvro7KCw5cbrjnHeHRbtrBeKtR4CTuhYV6cgQRIgATSJUBBT5ccnyOBUwSsmJ8YnJaVF71XmjveINgCdXZmSkfbo39i8Pj2bu2Zr1zcZHrmSGJsbMIYvxEoCZAACWRCIPpfm0xS4rMkUIQErJgPlbTLOVfcELUVqlvMgee/6pz5b+nacjh/mdH5bi4vK8IvDatMAgERoKe4gMAy2cInYMUcPfNVF0eLeazaX3juInnbhR2ySMV8So3fKOaxKPEaCZBAugQo6OmS43NFT2BwcECGhgalfe1lUT3zeGCwRrxZ3bNOTEzFtGSP9xyvkwAJkIAXAhR0L5QYhwRiEDjzzLNl584HpKXjjTHuzr/08xeOycjohHA70/lseIUESCBzAhT0zBkyhSImsHLVWVJantzXOhCNm2H26SKmxaqTAAkESYCCHiRdpl3wBCp0T/NKj/uaIx7iM5AACZBAEAT4r0sQVJlmwREYHh6KWSfscnbB2vaY99wXL9R4iM9AAiRAAkEQoKAHQZVpFhSBI0cOy6ZN18muXV+LWa/XrVkQ87rzItafw8KdgQRIgASCIkBBD4os0y0IAhDzbdtuMPuZf/WrX5on6vDu9uR/dCasK8T8xnecKysWNSSMx5skQAIkkAkBOpbJhB6fLWgCTjG3FYWoNze3yLvetclceupnXbL/yKC9bT4h4NinHHPmGGZHz5xiHoWIJyRAAgEQoKAHAJVJ5j+BWGKOWq1evUYuvfQyU8ETfaPy2E9ejarsUt1o5dPbLpaJ8SljAMc58yg8PCEBEgiQAAU9QLhMOj8JJBLz++57UNraFqrv9Vn59g9/IxOT0duVbvsv50mJ3quqLMvPyrPUJEACeUuAc+h523QseBAEvIg58v2P54/K7ldPRhXh8gs6ZPUSzpNHQeEJCZBA1ghQ0LOGmhmFnYBXMR8anZS/feqlqOrApevGy86UePuZR0XmCQmQAAkEQICCHgBUJpl/BLyKOWr26L++LIMjk1GV3PL2c6VcjeEYSIAESCBXBCjouSLPfENDIBUxf35/j/z77sNRZb/w3HZ5g26JqlPnDCRAAiSQMwIU9JyhZ8ZhIJCKmE+oL/aHnnwxqtjVavz23qvO4YYrUVR4QgIkkAsCFPRcUGeeoSAwOTkhN930PuM0xlkgLE2z1uzO6//76f1yTJeqOcN/v2Kt1FdzsYiTCY9JgARyQ4CCnhvuzDUEBCoqKuUDH7hZyspOLzGLJ+Zdx4bmeYQ7u6NZ3vpbSznUHoK2ZBFIgARE2LXgt6CoCVx55TWm/n/2Z7fJypWr5vXMZ3RifHx8Wh54fJ/g2AZ4g9v6B+tlZjp6Hbq9z08SIAESyDYBCnq2iTO/0BGAqNfU1Mi6decZpzEoYOfRQfnhc13ysxePzXMeg/v/9a2rZWFTtXEwg3MGEiABEsg1AQp6rluA+YeCwFvfemmkHD/dd0S+8Y/PG3/skYuOg+aGKrnmkpUUcwcTHpIACeSeAOfQc98GLEEWCBw9ekR++tNnkuaEnnkiMUcCA0MT0uXakCVpwoxAAiRAAgEToKAHDJjJ554AxHzr1vfKzTe/X/7933+csEAYZsdOaYkC5tL/WeMxkAAJkECYCFDQw9QaLIvvBKyYd3V1yuTkpHz4wx+MK+oQ6udeOOapDM/p3LrTSM7TQ4xEAiRAAgESoKAHCJdJ55aAU8znSoJ9ykvky1/+K/W5Ph0p3JRaqmPe/LMP/Uwmp7xZrWOXtUnXTmuRBHlAAiRAAjkgQKO4HEBnlsETcIp5TfMyaV97mTR3vEHKyqukorxEHnjiRXnLeYvl5YP98qNfHJQ+nRdPJVRWlJr9zlN5hnFJgARIIEgCFPQg6TLtnBBwinnLigtk1cU3SEnpaecxk1Oz8syeI+Yv3QJeuLZdSku4GUu6/PgcCZCA/wQ45O4/U6aYQwJOMUfP3C3mfhQNTmXedmGHH0kxDRIgARLwjQB76L6hZEK5JnD4yGHZ/v6t6pt9zgIdw+zOnnmy8p2zskWuumiFjE1Mya7/vS+mtTvE/MZ3nCsrFjUkS473SYAESCCrBEpmNWQ1R2ZGAikSmFajtZ6e4bhPYe343//4N/KfvzkuJWWVMj01Ln1dv5SWlW+S0tLk76ylKtKfeN+bZWV7vcycWrKGNLE0DdbsMIDDnDmG2dEzp5jHbQreCAmB1tY63aOgVI0/E/92cl3c8vIyaWmpzXUxCiZ/CnrBNGXhViTRP0qwTr//H+BnPbP6f+0jvytVuhWqO2BpGqzZK1TQOWfupsPzsBKgoIe1ZYItV/LuS7D5M3USSJsAetF+iHkii3WIeCyhT7vQfJAESIAEAiJAQfcIdmBgQHbu3CnPPvusNDU1SX9/v5x33nmybds26ejIzEAqk7Rz9axHbIFGg1e3THvmKCAt1gNtJiZOAiSQJQK0cvcAeu/evXLZZZeZmI899pg88MADgs/169fL5ZdfLk8++aSHVGJHySTtXD0buybZvYqhcOyElmmgxXqmBPk8CZBAWAhwDt1DS1x44YWmNw4hd4e77rpL7r//fnnqqafS6qlnknaunnUzCPo81hz6+MS0fOAv/y2jrK3F+sXrFmeUDh8mgbAR4Bx62FokO+VhDz0JZwg2hrU3btwYM+amTZvM9R07dsS8n+hiJmnn6tlE9cnmPRipYe7bSyhXz3Ab1CucjY9PeIm744YLhGLuhSDjkAAJ5AMB9tCTtNLatWtNjBdffDFuTAy7Y+1zqr30TNLO1bNxIQR4I1YPHdnd/4/7PHl7g3jf+I51ZjMVWqwH2FBMOjQE2EMPTVNktSDeujhZLVJ4Mnvmmbn9sxsbGxMWyhrFpTKXnknauXo2IYQc3LxC14Rj2DxRcM6RW4t1Lj9LRIz3SIAE8pUABT1By8HoDMEKdryoDQ1zXsN2794dL8q865mknatn51Uixxfg4AVe2+KJup0jpyOYHDcUsycBEsgKAS5bS4DZCjSWqSUKzc3N5nZ3d3eiaFH3Mkk7V89GVSAkJ5gDX7qgjl7dQtIeLAYJkEDuCFDQE7AfHBxMcPf0LdtDh/Gc15BJ2rl61mvdsh1vrqe+Tra8/Vx6dcs2fOZHAiQQGgIUdB+bAs5mggqZpJ2rZ4NiES9dO0ce7z6vkwAJkEAhE+AceoLWTVUIU+mhZ5J2rp5NgIq3SIAESIAEckyAPfQcNwCzT04Au6FhGQ4DCZCANwL4zSDwt+ONV6HEoqAnaMlkxnD2UTunnWx5m42Pz0zSztWzzvJn87hEN0gpK0u8PC2b5WFeJJAvBPjbyZeW8qecFPQEHK2xW4IoUbe8Ci0eyiTtXD0bVdksnsyq33a7T3kWs2VWJJC3BNAzh5jnw28H+7Yz+EOAgp6Ao12OBi9wiUJfX5+5nUoPPZO0c/VsIgZB3oOYDwyMBZkF0yaBgiLQ2FhtRrXC/tuBmKOsDP4QoKAn4Ijd1BCSGaHZIXdsp+o1ZJJ2rp71Wje/4+FH39JS63eyTI8ECp4AfzsF38RRFeRYRxSO6JMNGzaYC8ms120P3saPTiX2mY2bTtq5ejZ2TXiVBEiABEggDAQo6AlaAS5fbW/Yult1R4cgW0G/6qqr3LfNPet73Xkzk7Rz9ayz/DwmARIgARIIFwEKepL22L59u4nx+OOPx4xpxfrWW2+ddx9ij53YtmzZItju1B0ySTtXz7rrwHMSIAESIIGQEFArSIYkBO64447Zs88+e7azszMqps6tz15wwQWz1157bdR1e/L000+b5/Ds5s2b7eWoz3TTRiK5ejaqAjwhARIgARIIBYGyT2oIybtFaItx6aWXytjYmOzYscMsBamurpYf/ehHcvvtt8sb3/hGefDBB2OWHUPjiDc+Pi4f+9jHYu7alm7ayDBXz8asLC+SAAmQAAnklEAJXityWoI8yhxD6Bhix5w5lqjBOA2i7UfIJO1cPetHvZkGCZAACZCAPwQo6P5wZCokQAIkQAIkkFMCNIrLKX5mTgIkQAIkQAL+EKCg+8ORqZAACZAACZBATglQ0HOKn5mTAAmQAAmQgD8EKOj+cGQqJEACJEACJJBTAhT0nOJn5iRAAiRAAiTgDwEKuj8cmQoJkAAJkAAJ5JQABT2n+Jk5CZAACZAACfhDgILuD0emQgIkQAIkQAI5JUBBzyl+Zk4CJEACJEAC/hCgoPvDkamQAAmQAAmQQE4JUNBzip+ZkwAJkAAJkIA/BCjo/nBkKiRAAiRAAiSQUwIU9JziZ+YkQAIkQAIk4A8BCro/HJkKCZAACZAACeSUAAU9p/iZOQmQAAmQAAn4Q4CC7g9HpkICJEACJEACOSVAQc8pfmZOAiRAAiRAAv4QoKD7w5GpkAAJkAAJkEBOCZTnNHdmnvcEBgYGZOfOnfLss89KU1OT9Pf3y3nnnSfbtm2Tjo6OjOqXSdqZPJtRofkwCXgkEOR31K+0H3nkEdm1a5c89dRTHmvFaDklMMtAAmkS2LNnz+wFF1ww+4UvfCEqhYcffnj27LPPnn3iiSeirqdykknamTybShkZlwTSJRDkdzSTtPWFfLazs3MWv+Frr73W/I7xW2bIDwKSH8VkKcNIAGK+efPmmEWDyOMfAvzjkE7IJO1Mnk2nrHyGBFIlEOR3NN20n376afObveyyy8xLuv0NU9BTbd3cxeccek7HR/I387vuukswrLdx48aYldi0aZO5vmPHjpj3E13MJO1Mnk1UJt4jAb8IBPkdzSTtDRs2yIsvvmiG12+77TY5//zz/aoy08kSgRK8S2QpL2ZTQATWrl1raoN/AOKFyy+/XLq6usw/EKnMp2eSdibPxqsHr5OAnwSC/I76mfaTTz4pt9xyi6l6ot+5n2yYVmYE2EPPjF9RPv3MM8+Yejc2NiasvxVx/MPgNWSSdibPei0f45FAJgSC/I4GmXYmdeaz2SNAQc8e64LJae/evaYuVrDjVayhocHc2r17d7wo865nknYmz84rCC+QQAAEgvyOBpl2ACiYZAAEKOgBQC30JK1AY5laotDc3Gxud3d3J4oWdS+TtDN5NqoQPCGBgAgE+R0NMu2AcDBZnwlQ0H0GWgzJDQ4Oeqqm7aHDeM5ryCTtTJ71Wj7GI4FMCAT5HQ0y7UzqzGezR4CCnj3WRZsTnM0EFTJJO5Nng6oP0yUBJ4Egv6NBpu2sA4+zR4CCnj3WBZNTqv8QpNJDzyTtTJ4tmMZhRUJNIMjvaJBphxoqCxchQEGPoOABCZAACZAACeQvAQp6/rZdzkqezBjOFszO6SVb3mbj4zOTtDN51lkGHpNAUASC/I4GmXZQPJiuvwQo6P7yLIrUrLGb18p6/YcG6WWSdibPeq0L45FAJgSC/I4GmXYmdeaz2SNAQc8e64LJyS5Hgxe4RKGvr8/cTqWHnknamTybqB68RwJ+EQjyOxpk2n7Vn+kES4CCHizfgkx9/fr1pl7JjHDskDu2U/UaMkk7k2e9lo/xSCATAkF+R4NMO5M689nsEaCgZ491weSETRwQklmv2x68je8FgI2bTtqZPOulbIxDApkSCPI7GmTamdabz2eHAAU9O5wLKhe4fLW9Aetu0l1BCLIV9Kuuusp929yzvqedNzNJO5NnnWXgMQkERcCP7yh+V37/doKqL9PNLgEKenZ5F0xu27dvN3V5/PHHY9bJ/oNz6623zrsPscdObFu2bBFs9+gOmaSdybPucvCcBIIgkMl3NMjfThB1ZZpZJpC7rdiZc74TuOOOO2bPPvvs2c7Ozqiq6Nz67AUXXDB77bXXRl23J08//bR5Ds9u3rzZXo76TDdtJJLJs1GF4AkJBEQg3e9o0L8dZ3VtGfE73bNnj/MWj0NKoOyTGrL8DsHsCoTApZdeKmNjY7Jjxw4pKSmR6upq+dGPfiS33367vPGNb5QHH3wwZk0x7Ih44+Pj8rGPfUxw7g7ppo10MnnWXQ6ek0AQBNL9jgb520Hv/7d/+7dl165dcs8994hzOu2RRx6Rb33rW+aeirtcffXVQWBhmhkSKMGLRoZp8PEiJ4B/CDDEjrk9LFGDcU4skU4HUyZpZ/JsOmXlMySQKoEgv6PppI1nEOItNU12P9X6M76/BCjo/vJkaiRAAiRAAiSQEwI0issJdmZKAiRAAiRAAv4SoKD7y5OpkQAJkAAJkEBOCFDQc4KdmZIACZAACZCAvwQo6P7yZGokQAIkQAIkkBMCFPScYGemJEACJEACJOAvAQq6vzyZGgmQAAmQAAnkhAAFPSfYmSkJkAAJkAAJ+EuAgu4vT6ZGAiRAAiRAAjkhQEHPCXZmSgIkQAIkQAL+EqCg+8uTqZEACZAACZBATghQ0HOCnZmSAAmQAAmQgL8EKOj+8mRqJEACJEACJJATAhT0nGBnpiRAAiRAAiTgLwEKur88mRoJkAAJkAAJ5IQABT0n2JkpCZAACZAACfhLgILuL0+mRgIkQAIkQAI5IUBBzwl2ZkoCJEACJEAC/hKgoPvLk6mRAAnkAYEdO3bI2rVrzd8zzzyTByVmEUkgOQEKenJGjEECJEACJEACoSdQHvoSsoAkQAIk4DOBjo4OwR9CU1OTz6kzORLIDYGSWQ25yZq5kgAJkAAJkAAJ+EWAQ+5+kWQ6JEACGRGw89of+tCHMkonLA8XWn3CwpXliE+Agh6fDe+QAAmQAAmQQN4QoKDnTVOxoCRAAiRAAiQQnwAFPT4b3iEBEiABEiCBvCFAo7i8aSoWNF8J7Nq1S+6++25T/Oeee04aGxvnVSVZHHsfzyKNgYEBkybWUHd1dZk0L7nkErntttsi1tvzMnFceOSRR+TJJ5+UPXv2mLSQLqy+r776atm2bZsj5ulD5Llz5075wQ9+YPJE/HXr1smmTZtkw4YNpyOeOkIemEe2ZcblvXv3mjT27dsnV155paxYscLEmfew68IDDzwwLw+UB3lYBuCAMqEsqIO1YnclZU5t2XDy4osvzouSLm9nuvMSdVz4wAc+IF/72tfMlVh1c0Q19duyZYu59NRTTyWsl/M5HhcfAS5bK742Z43znAAE7JZbbjFCbKsCcYPQ4i/RP/oQPYgDPp0Bz0Ns8YeXD3cayNOKin0OaeAPeW7dutW8TNh7sT5h7Ia4NgwODpolY/YFB2WwwV6z5+6lZXgZAQNnwDMoD0QVf1/60pfkqquuckZJ6zgV3iinLXui+rztbW+T73znO6YN8fIQ64XIFhb3EdavX08xt1D4GZMAh9xjYuFFEggnAYgEhPW8884zoove5WOPPWZ6u7bEVgDsuf3Es9ddd11EzO+8807T27dpQACtsDgFFCJvxRy9auSHZzBSgDQQ7r//fiOiNi/3J563Yr5x40bzHHrREFykgz+kjYBPe81+Qsycob+/3wgnXiSc5UF8WwcIvvvFxZmGl+NUeadSn+3bt5si2BGGWOVB/riPAG4MJJCIAAU9ER3eI4EQEsBQMoZp7ZAyxO7ee+81PTgU94knnohZavS8IRDoQUIEIRC2N4k0IEZIF/fsdSRke8KI78wHcXAN8RHstII5cfzPihLKi7h4CcBztvyOqJ4PMTUA8cYUg1PsUSbUwZY/3suN54w0Yrq8k+UBBjY8/PDD9jDqEyMNNjjj22v8JAEnAQq6kwaPSSAPCMT7hx1z6AgQUHdAL9uKA3qGThF0x3Xew9A2erkQSNsbjxUfvWLki3ziBQitM+148bxct4IdL65lARuBTEM6vL3kiTrYtB999NGYj9g2s/FiRuJFEjhFgHPo/CqQQJ4RsEPK7mI3NzdHLtmeuL1gh21xHs/ozcZ1fj7++OORUwzXxwt2aBsCGku0MTSeSY88Xr7xrtu8Er1gxHvWfT0d3u404p2jLSDaaC98OoUbZbdcndfjpcXrJEBB53eABPKMgBWrVIq9e/duEz3VZ2GNjpCs920inYpnj52fb3nLW5ynvh9D/PAy0dnZadJ+9tlnfcsjVWapZIy08cKAFy63oGNFAQJekGK9JKWSD+MWBwEKenG0M2tZ5ASsMKcqTjA+Q7j11ltT6tm7ccOIz+8AEce8vXP0we88spEeet+og+2R2zZyGhFmoxzMI/8JcA49/9uQNSCBpATsnLMdwk36wKkI1trd9vC9PueOZ/N3X0/3HL1ZTAFACJE2hvRhpY/ldjCWw3m+BBgjWj7WOM75ksLh9nxpydyXk4Ke+zZgCUggcAK2h5yqoMNxDILt4QdeUA8ZoCcLhzUIEG5r7Q5hRO/WiqOHpEITxS5hs71yK+wU89A0UV4UhIKeF83EQhY6gUx7wMn4QOxsSGUpF7zAIeBFABbv2QhwOJMo2N4rhBvL1mKFZGnEeiaoa17KYoUbnGGvYG0A7PWgysZ0C4sABb2w2pO1CSGBZD1G5z/gQRUfhlfWsOq+++6LWE/Hyg/D2VY0nc/dcccdSZ9LdQQgVv5e0wC3eMGWP979bF73Uh98R6x4wxgOdaMxXDZbqTDyoqAXRjuyFiEmYI2cUESIpTPgH/vNmzebf8Cd14M4xhwzhANicfnllwt66hi+xjkEEGXDdQxnO0UIzyHY5xDP3scnzjGf7X4u1TpYTjZN5IfywcvcXXfdFUnOOdqAfBHHBtQD12z57PVcfHqtjy2bXU5o16Rbgbf3+UkCyQjQyj0ZId4ngQwJoJeLf9whMrDKRg8Z5xAsXMMx/vF2i32G2c57HPnAUxsE0pZlXiS9gHh2zh33cQ5jM/ucnb92P4sepfM59/1k59dcc41xIYt4yMOZT0NDQ+RxlAfuYTHfDDGHgLsD4uRa1L3Wx5YdZbZL2HCNgm7J8NMrAfbQvZJiPBLIgAC8pOEfa9tDhpjjH3B4X4NY2uHwDLLw9CjyRH7IF3na6QBch0haS3F3edzP2cwQD8/Fchlr43j9RFooF/JCuXAOUUPacDnrDDh3OqvBM+CL5XWoXxjEMJX62LqhDghhKL8tEz/zhwC3T82ftmJJSYAECpyAnULASApeCBhIIBUC7KGnQotxSYAESCAgApg+wB9GGyjmAUEu8GQp6AXewKweCZBAfhCwrl6tcVx+lJqlDBMBCnqYWoNlIQESKBoCTut8rPGHkR9655w/L5qvgO8V5Ry670iZIAmQAAkkJ4Algm5LfGs8mfxpxiCB+QTYQ5/PhFdIgARIIHACdtUDMoJVP1YYWCv3wDNnBgVJgD30gmxWVooESIAESKDYCLCHXmwtzvqSAAmQAAkUJAEKekE2KytFAiRAAiRQbAQo6MXW4qwvCZAACZBAQRKgoBdks7JSJEACJEACxUaAgl5sLc76kgAJkAAJFCQBCnpBNisrRQIkQAIkUGwEKOjF1uKsLwmQAAmQQEESoKAXZLOyUiRAAiRAAsVGgIJebC3O+pIACZAACRQkAQp6QTYrK0UCJEACJFBsBCjoxdbirC8JkAAJkEBBEqCgF2SzslIkQAIkQALFRoCCXmwtzvqSAAmQAAkUJAEKekE2KytFAiRAAiRQbAQo6MXW4qwvCZAACZBAQRKgoBdks7JSJEACJEACxUaAgl5sLc76kgAJkAAJFCQBCnpBNisrRQIkQAIkUGwEKOjF1uKsLwmQAAmQQEESoKAXZLOyUiRAAiRAAsVGgIJebC3O+pIACZAACRQkAQp6QTYrK0UCJEACJFBsBCjoxdbirC8JkAAJkEBBEvj/AYQ/jDO6QUERAAAAAElFTkSuQmCC\" width=\"250\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(<Figure size 250x225 with 1 Axes>,\n",
       " <matplotlib.axes._subplots.AxesSubplot at 0x7f769cc830f0>)"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "if base_model == 'resnet101':\n",
    "    uce_range = [0, 0.004]\n",
    "elif base_model == 'densenet201':\n",
    "    uce_range = [0, 0.0031]\n",
    "elif base_model == 'efficientnetb4':\n",
    "    uce_range = [0, 0.01]\n",
    "\n",
    "uce_s_list = []\n",
    "err_s_list = []\n",
    "uncert_s_list = []\n",
    "for i in range(len(err_test)):\n",
    "    print((scaler(uncert_test[i])**2).max().item())\n",
    "    uce_s, err_s, uncert_s, _ = uceloss(err_test[i]**2, scaler(uncert_test[i])**2, n_bins=n_bins, range=uce_range)\n",
    "    uce_s_list.append(uce_s.cpu())\n",
    "    err_s_list.append(err_s.cpu())\n",
    "    uncert_s_list.append(uncert_s.cpu())\n",
    "\n",
    "print((torch.stack(uce_s_list)*100).mean().item(), (torch.stack(uce_s_list)*100).var().sqrt().item())\n",
    "plot_uncert_multi(err_s_list, uncert_s_list)\n",
    "\n",
    "#fig, ax = plot_frequency(scaler(uncert_test[0]).cpu(), in_bin.cpu(), n_bins=n_bins)\n",
    "#fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.013426141813397408\n",
      "0.011179763823747635\n",
      "0.011891653761267662\n",
      "0.011718012392520905\n",
      "0.011049605906009674\n",
      "0.035516493022441864 0.0008374509634450078\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": {
      "text/plain": [
       "(<Figure size 250x225 with 1 Axes>,\n",
       " <matplotlib.axes._subplots.AxesSubplot at 0x7f769cc476a0>)"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "if base_model == 'resnet101':\n",
    "    uce_range = [0, 0.0045]\n",
    "elif base_model == 'densenet201':\n",
    "    uce_range = [0, 0.0031]\n",
    "elif base_model == 'efficientnetb4':\n",
    "    uce_range = [0, 0.009]\n",
    "\n",
    "uce_aux_list = []\n",
    "err_aux_list = []\n",
    "uncert_aux_list = []\n",
    "for i in range(len(err_test)):\n",
    "    print((aux(uncert_test[i])**2).max().item())\n",
    "    uce_aux, err_aux, uncert_aux, _ = uceloss(err_test[i]**2, aux(uncert_test[i])**2, n_bins=n_bins, range=uce_range)\n",
    "    uce_aux_list.append(uce_aux.cpu())\n",
    "    err_aux_list.append(err_aux.cpu())\n",
    "    uncert_aux_list.append(uncert_aux.cpu())\n",
    "\n",
    "print((torch.stack(uce_aux_list)*100).mean().item(), (torch.stack(uce_aux_list)*100).var().sqrt().item())\n",
    "plot_uncert_multi(err_aux_list, uncert_aux_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "\n",
    "sns.set()\n",
    "matplotlib.rcParams['text.usetex'] = True\n",
    "matplotlib.rcParams['font.size'] = 8\n",
    "matplotlib.rcParams['text.latex.preamble'] = [\n",
    "    r'\\usepackage{bm}']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [],
   "source": [
    "def save_log(base_model):\n",
    "    with open(f\"results_endovis_{base_model}.log\", \"w\") as f:\n",
    "        print(\"MSE\", file=f)\n",
    "        print([(e**2).mean().item() for e in err_test], file=f)\n",
    "        print(\"mean\", np.mean([(e**2).mean().item() for e in err_test]), file=f)\n",
    "        print(\"std \", np.std([(e**2).mean().item() for e in err_test]), file=f)\n",
    "        print(\"\", file=f)\n",
    "        \n",
    "        print(\"uncal\", file=f)\n",
    "        print(\"NLL\", file=f)\n",
    "        nll = [nll_criterion_gaussian(mu_test_list[i], uncert_test[i].pow(2).log(), target_test_list[i]).item() for i in range(len(mu_test_list))]\n",
    "        print(nll, file=f)\n",
    "        print(\"mean\", np.mean(nll), file=f)\n",
    "        print(\"std \", np.std(nll), file=f)\n",
    "        print(\"UCE\", file=f)\n",
    "        print([u.item() for u in uce_uncal_list], file=f)\n",
    "        print(\"mean\", (torch.stack(uce_uncal_list)*100).mean().item(), file=f)\n",
    "        print(\"std \", (torch.stack(uce_uncal_list)*100).var().sqrt().item(), file=f)\n",
    "        print(\"\", file=f)\n",
    "        \n",
    "        print(\"aux\", file=f)\n",
    "        print(\"NLL\", file=f)\n",
    "        aux.train()\n",
    "        nll = [nll_criterion_gaussian(mu_test_list[i], aux(uncert_test[i]), target_test_list[i]).item() for i in range(len(mu_test_list))]\n",
    "        aux.eval()\n",
    "        print(nll, file=f)\n",
    "        print(\"mean\", np.mean(nll), file=f)\n",
    "        print(\"std \", np.std(nll), file=f)\n",
    "        print(\"UCE\", file=f)\n",
    "        print([u.item() for u in uce_aux_list], file=f)\n",
    "        print(\"mean\", (torch.stack(uce_aux_list)*100).mean().item(), file=f)\n",
    "        print(\"std \", (torch.stack(uce_aux_list)*100).var().sqrt().item(), file=f)\n",
    "        print(\"\", file=f)\n",
    "        \n",
    "        print(\"s\", file=f)\n",
    "        print(\"NLL\", file=f)\n",
    "        nll = [nll_criterion_gaussian(mu_test_list[i], scaler(uncert_test[i]).pow(2).log(), target_test_list[i]).item() for i in range(len(mu_test_list))]\n",
    "        print(nll, file=f)\n",
    "        print(\"mean\", np.mean(nll), file=f)\n",
    "        print(\"std \", np.std(nll), file=f)\n",
    "        print(\"UCE\", file=f)\n",
    "        print([u.item() for u in uce_s_list], file=f)\n",
    "        print(\"mean\", (torch.stack(uce_s_list)*100).mean().item(), file=f)\n",
    "        print(\"std \", (torch.stack(uce_s_list)*100).var().sqrt().item(), file=f)\n",
    "        print(\"S =\", scaler.S.item(), file=f)\n",
    "        print(\"\", file=f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [],
   "source": [
    "if base_model == 'resnet101':\n",
    "    fig, ax = plt.subplots(1, 3, figsize=(6.8, 2.75))\n",
    "\n",
    "    alpha = 0.4\n",
    "    props = dict(boxstyle='round', facecolor='white', alpha=0.75)\n",
    "\n",
    "    err_uncal = torch.stack(err_uncal_list).mean(dim=0).cpu()\n",
    "    err_uncal_var = torch.stack(err_uncal_list).var(dim=0).sqrt().cpu()\n",
    "    uncert_uncal = torch.stack(uncert_uncal_list).mean(dim=0).cpu()\n",
    "    ax[0].plot([0, 0.2], [0, 0.2], 'k--')\n",
    "    ax[0].plot(uncert_uncal, err_uncal, marker='.', label='uncal')\n",
    "    ax[0].fill_between(uncert_uncal, err_uncal-err_uncal_var, err_uncal+err_uncal_var, alpha=alpha)\n",
    "    ax[0].set_ylabel(r'observed uncertainty', fontsize=11)\n",
    "    ax[0].set_xlabel(r'expected uncertainty', fontsize=11)\n",
    "    ax[0].set_xlim([-0.0002, 0.0022])\n",
    "    ax[0].set_ylim([-0.0002, 0.0022])\n",
    "    ax[0].set_xticks([0, 0.002])\n",
    "    ax[0].set_yticks([0, 0.002])\n",
    "    ax[0].set_aspect(1)\n",
    "    ax[0].set_title(r'uncalibrated')\n",
    "    textstr0 = r'UCE\\,=\\,{:.2f}'.format((torch.stack(uce_uncal_list)*100).mean().item())\n",
    "    ax[0].text(0.925, 0.075, textstr0, transform=ax[0].transAxes, fontsize=10,\n",
    "                    verticalalignment='bottom',\n",
    "                    horizontalalignment='right',\n",
    "                    bbox=props\n",
    "                    )\n",
    "\n",
    "    err_aux = torch.stack(err_aux_list).mean(dim=0).cpu()\n",
    "    err_aux_var = torch.stack(err_aux_list).var(dim=0).sqrt().cpu()\n",
    "    uncert_aux = torch.stack(uncert_aux_list).mean(dim=0).cpu()\n",
    "    ax[1].plot([0, 0.2], [0, 0.2], 'k--')\n",
    "    ax[1].plot(uncert_aux, err_aux, marker='.', label='uncal')\n",
    "    ax[1].fill_between(uncert_aux, err_aux-err_aux_var, err_aux+err_aux_var, alpha=alpha)\n",
    "    ax[1].set_ylabel(r'observed uncertainty', fontsize=11)\n",
    "    ax[1].set_xlabel(r'expected uncertainty', fontsize=11)\n",
    "    ax[1].set_xlim([-0.0002, 0.0052])\n",
    "    ax[1].set_ylim([-0.0002, 0.0052])\n",
    "    ax[1].set_xticks([0.0, 0.004])\n",
    "    ax[1].set_yticks([0.0, 0.004])\n",
    "    ax[1].set_aspect(1)\n",
    "    ax[1].set_title(r'aux scaling')\n",
    "    textstr1 = r'UCE\\,=\\,{:.2f}'.format((torch.stack(uce_aux_list)*100).mean().item())\n",
    "    ax[1].text(0.6, 0.825, textstr1, transform=ax[1].transAxes, fontsize=10,\n",
    "                    verticalalignment='bottom',\n",
    "                    horizontalalignment='right',\n",
    "                    bbox=props\n",
    "                    )\n",
    "\n",
    "    err_s = torch.stack(err_s_list).mean(dim=0).cpu()\n",
    "    err_s_var = torch.stack(err_s_list).var(dim=0).sqrt().cpu()\n",
    "    uncert_s = torch.stack(uncert_s_list).mean(dim=0).cpu()\n",
    "    ax[2].plot([0, 0.004], [0, 0.004], 'k--')\n",
    "    ax[2].plot(uncert_s, err_s, marker='.', label='uncal')\n",
    "    ax[2].fill_between(uncert_s, err_s-err_s_var, err_s+err_s_var, alpha=alpha)\n",
    "    ax[2].set_ylabel(r'observed uncertainty', fontsize=11)\n",
    "    ax[2].set_xlabel(r'expected uncertainty', fontsize=11)\n",
    "    ax[2].set_xlim([-0.0002, 0.0042])\n",
    "    ax[2].set_ylim([-0.0002, 0.0042])\n",
    "    ax[2].set_xticks([0.0, 0.004])\n",
    "    ax[2].set_yticks([0.0, 0.004])\n",
    "    ax[2].set_aspect(1)\n",
    "    ax[2].set_title(r'$ \\sigma $ scaling')\n",
    "    textstr2 = r'UCE\\,=\\,{:.2f}'.format((torch.stack(uce_s_list)*100).mean().item())\n",
    "    ax[2].text(0.6, 0.825, textstr2, transform=ax[2].transAxes, fontsize=10,\n",
    "                    verticalalignment='bottom',\n",
    "                    horizontalalignment='right',\n",
    "                    bbox=props\n",
    "                    )\n",
    "\n",
    "    ax[0].annotate(r'EndoVis/ResNet-101', xy=(0, 0.5), xytext=(-ax[0].yaxis.labelpad - 5, 0),\n",
    "                   xycoords=ax[0].yaxis.label, textcoords='offset points',\n",
    "                   size='large', ha='right', va='center', fontsize=10, rotation=90)\n",
    "    fig.tight_layout()\n",
    "    fig.show()\n",
    "\n",
    "    fig.savefig(f\"results_endovis_{base_model}.pdf\", bbox_inches='tight', pad_inches=0.01)\n",
    "    save_log(base_model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [],
   "source": [
    "if base_model == 'densenet201':\n",
    "    fig, ax = plt.subplots(1, 3, figsize=(6.8, 2.75))\n",
    "\n",
    "    alpha = 0.4\n",
    "    props = dict(boxstyle='round', facecolor='white', alpha=0.75)\n",
    "\n",
    "    err_uncal = torch.stack(err_uncal_list).mean(dim=0).cpu()\n",
    "    err_uncal_var = torch.stack(err_uncal_list).var(dim=0).sqrt().cpu()\n",
    "    uncert_uncal = torch.stack(uncert_uncal_list).mean(dim=0).cpu()\n",
    "    ax[0].plot([0, 0.006], [0, 0.006], 'k--')\n",
    "    ax[0].plot(uncert_uncal, err_uncal, marker='.', label='uncal')\n",
    "    ax[0].fill_between(uncert_uncal, err_uncal-err_uncal_var, err_uncal+err_uncal_var, alpha=alpha)\n",
    "    ax[0].set_ylabel(r'observed uncertainty', fontsize=11)\n",
    "    ax[0].set_xlabel(r'expected uncertainty', fontsize=11)\n",
    "    ax[0].set_xlim([-0.0002, 0.0022])\n",
    "    ax[0].set_ylim([-0.0002, 0.0022])\n",
    "    ax[0].set_xticks([0, 0.002])\n",
    "    ax[0].set_yticks([0, 0.002])\n",
    "    ax[0].set_aspect(1)\n",
    "    ax[0].set_title(r'uncalibrated')\n",
    "    textstr0 = r'UCE\\,=\\,{:.2f}'.format((torch.stack(uce_uncal_list)*100).mean().item())\n",
    "    ax[0].text(0.925, 0.075, textstr0, transform=ax[0].transAxes, fontsize=10,\n",
    "                    verticalalignment='bottom',\n",
    "                    horizontalalignment='right',\n",
    "                    bbox=props\n",
    "                    )\n",
    "\n",
    "    err_aux = torch.stack(err_aux_list).mean(dim=0).cpu()\n",
    "    err_aux_var = torch.stack(err_aux_list).var(dim=0).sqrt().cpu()\n",
    "    uncert_aux = torch.stack(uncert_aux_list).mean(dim=0).cpu()\n",
    "    ax[1].plot([0, 0.006], [0, 0.006], 'k--')\n",
    "    ax[1].plot(uncert_aux, err_aux, marker='.', label='uncal')\n",
    "    ax[1].fill_between(uncert_aux, err_aux-err_aux_var, err_aux+err_aux_var, alpha=alpha)\n",
    "    ax[1].set_ylabel(r'observed uncertainty', fontsize=11)\n",
    "    ax[1].set_xlabel(r'expected uncertainty', fontsize=11)\n",
    "    ax[1].set_xlim([-0.0002, 0.0032])\n",
    "    ax[1].set_ylim([-0.0002, 0.0032])\n",
    "    ax[1].set_xticks([0, 0.003])\n",
    "    ax[1].set_yticks([0, 0.003])\n",
    "    ax[1].set_aspect(1)\n",
    "    ax[1].set_title(r'aux scaling')\n",
    "    textstr1 = r'UCE\\,=\\,{:.2f}'.format((torch.stack(uce_aux_list)*100).mean().item())\n",
    "    ax[1].text(0.925, 0.075, textstr1, transform=ax[1].transAxes, fontsize=10,\n",
    "                    verticalalignment='bottom',\n",
    "                    horizontalalignment='right',\n",
    "                    bbox=props\n",
    "                    )\n",
    "\n",
    "    err_s = torch.stack(err_s_list).mean(dim=0).cpu()\n",
    "    err_s_var = torch.stack(err_s_list).var(dim=0).sqrt().cpu()\n",
    "    uncert_s = torch.stack(uncert_s_list).mean(dim=0).cpu()\n",
    "    ax[2].plot([0, 0.006], [0, 0.006], 'k--')\n",
    "    ax[2].plot(uncert_s, err_s, marker='.', label='uncal')\n",
    "    ax[2].fill_between(uncert_s, err_s-err_s_var, err_s+err_s_var, alpha=alpha)\n",
    "    ax[2].set_ylabel(r'observed uncertainty', fontsize=11)\n",
    "    ax[2].set_xlabel(r'expected uncertainty', fontsize=11)\n",
    "    ax[2].set_xlim([-0.0002, 0.0032])\n",
    "    ax[2].set_ylim([-0.0002, 0.0032])\n",
    "    ax[2].set_xticks([0, 0.003])\n",
    "    ax[2].set_yticks([0, 0.003])\n",
    "    ax[2].set_aspect(1)\n",
    "    ax[2].set_title(r'$ \\sigma $ scaling')\n",
    "    textstr2 = r'UCE\\,=\\,{:.2f}'.format((torch.stack(uce_s_list)*100).mean().item())\n",
    "    ax[2].text(0.925, 0.075, textstr2, transform=ax[2].transAxes, fontsize=10,\n",
    "                    verticalalignment='bottom',\n",
    "                    horizontalalignment='right',\n",
    "                    bbox=props\n",
    "                    )\n",
    "\n",
    "    ax[0].annotate(r'EndoVis/DenseNet-201', xy=(0, 0.5), xytext=(-ax[0].yaxis.labelpad - 5, 0),\n",
    "                   xycoords=ax[0].yaxis.label, textcoords='offset points',\n",
    "                   size='large', ha='right', va='center', fontsize=10, rotation=90)\n",
    "    fig.tight_layout()\n",
    "    fig.show()\n",
    "\n",
    "    fig.savefig(f\"results_endovis_{base_model}.pdf\", bbox_inches='tight', pad_inches=0.01)\n",
    "    save_log(base_model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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\" width=\"680\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "if base_model == 'efficientnetb4':\n",
    "    fig, ax = plt.subplots(1, 3, figsize=(6.8, 2.75))\n",
    "\n",
    "    alpha = 0.4\n",
    "    props = dict(boxstyle='round', facecolor='white', alpha=0.75)\n",
    "\n",
    "    err_uncal = torch.stack(err_uncal_list).mean(dim=0).cpu()\n",
    "    err_uncal_var = torch.stack(err_uncal_list).std(dim=0).cpu()\n",
    "    uncert_uncal = torch.stack(uncert_uncal_list).mean(dim=0).cpu()\n",
    "    ax[0].plot([0, 0.012], [0, 0.012], 'k--')\n",
    "    ax[0].plot(uncert_uncal, err_uncal, marker='.', label='uncal')\n",
    "    ax[0].fill_between(uncert_uncal, err_uncal-err_uncal_var, err_uncal+err_uncal_var, alpha=alpha)\n",
    "    ax[0].set_ylabel(r'observed uncertainty', fontsize=11)\n",
    "    ax[0].set_xlabel(r'expected uncertainty', fontsize=11)\n",
    "    ax[0].set_xlim([-0.0005, 0.0125])\n",
    "    ax[0].set_ylim([-0.0005, 0.0125])\n",
    "    ax[0].set_xticks([0, 0.006, 0.012])\n",
    "    ax[0].set_yticks([0, 0.006, 0.012])\n",
    "    ax[0].set_aspect(1)\n",
    "    ax[0].set_title(r'uncalibrated')\n",
    "    textstr0 = r'UCE\\,=\\,{:.2f}'.format((torch.stack(uce_uncal_list)*100).mean().item())\n",
    "    ax[0].text(0.925, 0.075, textstr0, transform=ax[0].transAxes, fontsize=10,\n",
    "                    verticalalignment='bottom',\n",
    "                    horizontalalignment='right',\n",
    "                    bbox=props\n",
    "                    )\n",
    "\n",
    "    err_aux = torch.stack(err_aux_list).mean(dim=0).cpu()\n",
    "    err_aux_var = torch.stack(err_aux_list).std(dim=0).cpu()\n",
    "    uncert_aux = torch.stack(uncert_aux_list).mean(dim=0).cpu()\n",
    "    ax[1].plot([0, 0.012], [0, 0.012], 'k--')\n",
    "    ax[1].plot(uncert_aux, err_aux, marker='.', label='uncal')\n",
    "    ax[1].fill_between(uncert_aux, err_aux-err_aux_var, err_aux+err_aux_var, alpha=alpha)\n",
    "    ax[1].set_ylabel(r'observed uncertainty', fontsize=11)\n",
    "    ax[1].set_xlabel(r'expected uncertainty', fontsize=11)\n",
    "    ax[1].set_xlim([-0.0005, 0.0125])\n",
    "    ax[1].set_ylim([-0.0005, 0.0125])\n",
    "    ax[1].set_xticks([0, 0.006, 0.012])\n",
    "    ax[1].set_yticks([0, 0.006, 0.012])\n",
    "    ax[1].set_aspect(1)\n",
    "    ax[1].set_title(r'aux scaling')\n",
    "    textstr1 = r'UCE\\,=\\,{:.2f}'.format((torch.stack(uce_aux_list)*100).mean().item())\n",
    "    ax[1].text(0.925, 0.075, textstr1, transform=ax[1].transAxes, fontsize=10,\n",
    "                    verticalalignment='bottom',\n",
    "                    horizontalalignment='right',\n",
    "                    bbox=props\n",
    "                    )\n",
    "\n",
    "    err_s = torch.stack(err_s_list).mean(dim=0).cpu()\n",
    "    err_s_var = torch.stack(err_s_list).std(dim=0).cpu()\n",
    "    uncert_s = torch.stack(uncert_s_list).mean(dim=0).cpu()\n",
    "    ax[2].plot([0, 0.012], [0, 0.012], 'k--')\n",
    "    ax[2].plot(uncert_s, err_s, marker='.', label='uncal')\n",
    "    ax[2].fill_between(uncert_s, err_s-err_s_var, err_s+err_s_var, alpha=alpha)\n",
    "    ax[2].set_ylabel(r'observed uncertainty', fontsize=11)\n",
    "    ax[2].set_xlabel(r'expected uncertainty', fontsize=11)\n",
    "    ax[2].set_xlim([-0.0005, 0.0125])\n",
    "    ax[2].set_ylim([-0.0005, 0.0125])\n",
    "    ax[2].set_xticks([0, 0.006, 0.012])\n",
    "    ax[2].set_yticks([0, 0.006, 0.012])\n",
    "    ax[2].set_aspect(1)\n",
    "    ax[2].set_title(r'$ \\sigma $ scaling')\n",
    "    textstr2 = r'UCE\\,=\\,{:.2f}'.format((torch.stack(uce_s_list)*100).mean().item())\n",
    "    ax[2].text(0.925, 0.075, textstr2, transform=ax[2].transAxes, fontsize=10,\n",
    "                    verticalalignment='bottom',\n",
    "                    horizontalalignment='right',\n",
    "                    bbox=props\n",
    "                    )\n",
    "\n",
    "    ax[0].annotate(r'EndoVis/EfficientNet-B4', xy=(0, 0.5), xytext=(-ax[0].yaxis.labelpad - 5, 0),\n",
    "                   xycoords=ax[0].yaxis.label, textcoords='offset points',\n",
    "                   size='large', ha='right', va='center', fontsize=10, rotation=90)\n",
    "    fig.tight_layout()\n",
    "    fig.show()\n",
    "\n",
    "    fig.savefig(f\"results_endovis_{base_model}.pdf\", bbox_inches='tight', pad_inches=0.01)\n",
    "    save_log(base_model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.save(f\"uce_uncal_endovis_{base_model}\", np.array([i.detach().numpy() for i in uce_uncal_list]))\n",
    "np.save(f\"err_uncal_endovis_{base_model}\", np.array([i.detach().numpy() for i in err_uncal_list]))\n",
    "np.save(f\"uncert_uncal_endovis_{base_model}\", np.array([i.detach().numpy() for i in uncert_uncal_list]))\n",
    "\n",
    "np.save(f\"uce_s_endovis_{base_model}\", np.array([i.detach().numpy() for i in uce_s_list]))\n",
    "np.save(f\"err_s_endovis_{base_model}\", np.array([i.detach().numpy() for i in err_s_list]))\n",
    "np.save(f\"uncert_s_endovis_{base_model}\", np.array([i.detach().numpy() for i in uncert_s_list]))\n",
    "\n",
    "np.save(f\"uce_aux_endovis_{base_model}\", np.array([i.detach().numpy() for i in uce_aux_list]))\n",
    "np.save(f\"err_aux_endovis_{base_model}\", np.array([i.detach().numpy() for i in err_aux_list]))\n",
    "np.save(f\"uncert_aux_endovis_{base_model}\", np.array([i.detach().numpy() for i in uncert_aux_list]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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