test_endovis_levi.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "import numpy as np\n",
    "np.random.seed(1)\n",
    "import torch\n",
    "torch.manual_seed(1)\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:1\")"
   ]
  },
  {
   "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 [06:33<00:00,  2.92s/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 = 'aleatoric'\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:1')\n",
      "tensor(0.0012, device='cuda:1')\n",
      "tensor(0.0002, device='cuda:1')\n",
      "tensor(0.0147, device='cuda:1')\n",
      "tensor(0.0099, device='cuda:1')\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(2.2468, device='cuda:1')\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": [
      "2.2468433380126953\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": [
      "-5.82411527633667\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": [
      "-3.402578353881836\n",
      "-5.831831455230713\n",
      "-5.831831455230713\n",
      "-5.824117183685303\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": [
      "0.00809614546597004\n",
      "0.0060811033472418785\n",
      "0.0060811033472418785\n",
      "0.006124907173216343\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"
    },
    {
     "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": [
      "0.09151273407042027\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": [
      "0.027724314713850617\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"
    },
    {
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\" width=\"250\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.027724314713850617\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"
    }
   ],
   "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"
    },
    {
     "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": [
      "0.019011176482308656\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 [07:01<00:00,  3.01s/it]\n",
      "100%|██████████| 140/140 [07:03<00:00,  3.02s/it]\n",
      "100%|██████████| 140/140 [07:15<00:00,  3.11s/it]\n",
      "100%|██████████| 140/140 [06:52<00:00,  2.95s/it]\n",
      "100%|██████████| 140/140 [06:42<00:00,  2.87s/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_t.sqrt().clamp(0, 1) for uncert_aleatoric_t in uncert_aleatoric_test]\n",
    "elif uncertainty == 'epistemic':\n",
    "    uncert_test = [uncert_epistemic_t.sqrt().clamp(0, 1) for uncert_epistemic_t in uncert_epistemic_test]\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:1')\n",
      "tensor(0.0010, device='cuda:1')\n",
      "tensor(0.0003, device='cuda:1')\n",
      "\n",
      "tensor(0.0009, device='cuda:1')\n",
      "tensor(0.0010, device='cuda:1')\n",
      "tensor(0.0003, device='cuda:1')\n",
      "\n",
      "tensor(0.0009, device='cuda:1')\n",
      "tensor(0.0011, device='cuda:1')\n",
      "tensor(0.0003, device='cuda:1')\n",
      "\n",
      "tensor(0.0009, device='cuda:1')\n",
      "tensor(0.0011, device='cuda:1')\n",
      "tensor(0.0003, device='cuda:1')\n",
      "\n",
      "tensor(0.0009, device='cuda:1')\n",
      "tensor(0.0010, device='cuda:1')\n",
      "tensor(0.0003, device='cuda:1')\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": [
      "-5.100878715515137\n",
      "-6.071095943450928\n",
      "-6.071095943450928\n",
      "-6.06516695022583\n",
      "\n",
      "-5.1109843254089355\n",
      "-6.072808265686035\n",
      "-6.072808265686035\n",
      "-6.067253112792969\n",
      "\n",
      "-5.090693473815918\n",
      "-6.069219589233398\n",
      "-6.069219589233398\n",
      "-6.063063621520996\n",
      "\n",
      "-5.063291549682617\n",
      "-6.06412410736084\n",
      "-6.06412410736084\n",
      "-6.057292938232422\n",
      "\n",
      "-5.117093563079834\n",
      "-6.073911666870117\n",
      "-6.073911666870117\n",
      "-6.068565368652344\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": [
      "0.0060752579011023045\n",
      "0.004984304774552584\n",
      "0.004984304774552584\n",
      "0.005025542341172695\n",
      "\n",
      "0.005926176905632019\n",
      "0.004866382107138634\n",
      "0.004866382107138634\n",
      "0.004900814965367317\n",
      "\n",
      "0.006261334754526615\n",
      "0.005155482795089483\n",
      "0.005155482795089483\n",
      "0.005196657031774521\n",
      "\n",
      "0.0065700155682861805\n",
      "0.005395398009568453\n",
      "0.005395398009568453\n",
      "0.00545024499297142\n",
      "\n",
      "0.005808508954942226\n",
      "0.00475730188190937\n",
      "0.00475730188190937\n",
      "0.004792450927197933\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": 64,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0006469095242209733\n",
      "0.0006401223363354802\n",
      "0.0006620410713367164\n",
      "0.0006521455361507833\n",
      "0.0006550634279847145\n",
      "0.06392474472522736 0.0007318038842640817\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 0x7ff520fec0f0>)"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "if base_model == 'resnet101':\n",
    "    uce_range = [0, 0.00025]\n",
    "elif base_model == 'densenet201':\n",
    "    uce_range = [0, 0.0005]\n",
    "elif base_model == 'efficientnetb4':\n",
    "    uce_range = [0, 0.0008]\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": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.003265796694904566\n",
      "0.0032315326388925314\n",
      "0.003342185402289033\n",
      "0.0032922294922173023\n",
      "0.0033069599885493517\n",
      "0.059204451739788055 0.002205593278631568\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
    {
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\" width=\"250\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(<Figure size 250x225 with 1 Axes>,\n",
       " <matplotlib.axes._subplots.AxesSubplot at 0x7ff520fe5940>)"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "if base_model == 'resnet101':\n",
    "    uce_range = [0, 0.003]\n",
    "elif base_model == 'densenet201':\n",
    "    uce_range = [0, 0.0045]\n",
    "elif base_model == 'efficientnetb4':\n",
    "    uce_range = [0, 0.003]\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": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0024832915514707565\n",
      "0.0024637419264763594\n",
      "0.0025266986340284348\n",
      "0.0024983410257846117\n",
      "0.0025067131500691175\n",
      "0.05463606119155884 0.0007770112133584917\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 0x7ff5624440b8>)"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "if base_model == 'resnet101':\n",
    "    uce_range = [0, 0.003]\n",
    "elif base_model == 'densenet201':\n",
    "    uce_range = [0, 0.0045]\n",
    "elif base_model == 'efficientnetb4':\n",
    "    uce_range = [0, 0.003]\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": 74,
   "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": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "def save_log(base_model):\n",
    "    with open(f\"results_levi_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": 76,
   "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([0.0, 0.0032])\n",
    "    ax[1].set_ylim([0.0, 0.0032])\n",
    "    ax[1].set_xticks([0.001, 0.003])\n",
    "    ax[1].set_yticks([0.001, 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(0.6, 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, 0.2], [0, 0.2], '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([0.0, 0.0032])\n",
    "    ax[2].set_ylim([0.0, 0.0032])\n",
    "    ax[2].set_xticks([0.001, 0.003])\n",
    "    ax[2].set_yticks([0.001, 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(0.6, 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_levi_endovis_{base_model}.pdf\", bbox_inches='tight', pad_inches=0.01)\n",
    "    save_log(base_model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "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, 0.004], [0, 0.004], '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, 0.0042])\n",
    "    ax[0].set_ylim([-0.0002, 0.0042])\n",
    "    ax[0].set_xticks([0, 0.004])\n",
    "    ax[0].set_yticks([0, 0.004])\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, 0.005], [0, 0.005], '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([-0.0003, 0.0053])\n",
    "    ax[1].set_ylim([-0.0003, 0.0053])\n",
    "    ax[1].set_xticks([0, 0.005])\n",
    "    ax[1].set_yticks([0, 0.005])\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, 0.005], [0, 0.005], '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([-0.0003, 0.0053])\n",
    "    ax[2].set_ylim([-0.0003, 0.0053])\n",
    "    ax[2].set_xticks([0, 0.005])\n",
    "    ax[2].set_yticks([0, 0.005])\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/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_levi_endovis_{base_model}.pdf\", bbox_inches='tight', pad_inches=0.01)\n",
    "    save_log(base_model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "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=\"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, 0.004], [0, 0.004], '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, 0.0042])\n",
    "    ax[0].set_ylim([-0.0002, 0.0042])\n",
    "    ax[0].set_xticks([0, 0.002, 0.004])\n",
    "    ax[0].set_yticks([0, 0.002, 0.004])\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, 0.004], [0, 0.004], '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, 0.0042])\n",
    "    ax[1].set_ylim([-0.0002, 0.0042])\n",
    "    ax[1].set_xticks([0, 0.002, 0.004])\n",
    "    ax[1].set_yticks([0, 0.002, 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(0.925, 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, 0.004], [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, 0.002, 0.004])\n",
    "    ax[2].set_yticks([0, 0.002, 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(0.925, 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_levi_endovis_{base_model}.pdf\", bbox_inches='tight', pad_inches=0.01)\n",
    "    save_log(base_model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.save(f\"uce_uncal_levi_endovis_{base_model}\", np.array([i.detach().numpy() for i in uce_uncal_list]))\n",
    "np.save(f\"err_uncal_levi_endovis_{base_model}\", np.array([i.detach().numpy() for i in err_uncal_list]))\n",
    "np.save(f\"uncert_uncal_levi_endovis_{base_model}\", np.array([i.detach().numpy() for i in uncert_uncal_list]))\n",
    "\n",
    "np.save(f\"uce_s_levi_endovis_{base_model}\", np.array([i.detach().numpy() for i in uce_s_list]))\n",
    "np.save(f\"err_s_levi_endovis_{base_model}\", np.array([i.detach().numpy() for i in err_s_list]))\n",
    "np.save(f\"uncert_s_levi_endovis_{base_model}\", np.array([i.detach().numpy() for i in uncert_s_list]))\n",
    "\n",
    "np.save(f\"uce_aux_levi_endovis_{base_model}\", np.array([i.detach().numpy() for i in uce_aux_list]))\n",
    "np.save(f\"err_aux_levi_endovis_{base_model}\", np.array([i.detach().numpy() for i in err_aux_list]))\n",
    "np.save(f\"uncert_aux_levi_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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