test_gaussian-interval.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "import numpy as np\n",
    "import torch\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, SequentialSampler\n",
    "from data_generator_breast import BreastPathQDataset\n",
    "from data_generator_boneage import BoneAgeDataset\n",
    "from data_generator_endovis import EndoVisDataset\n",
    "from data_generator_oct import OCTDataset\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",
    "from glob import glob\n",
    "\n",
    "matplotlib.rcParams['font.size'] = 8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "base_model = 'efficientnetb4'\n",
    "dataset = 'OCT'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "assert base_model in ['resnet101', 'densenet201', 'efficientnetb4']\n",
    "assert dataset in ['BreastPathQ', 'BoneAge', 'EndoVis', 'OCT']\n",
    "device = torch.device(\"cuda:0\")\n",
    "\n",
    "base_model_caps = {\n",
    "    'resnet101': 'ResNet-101',\n",
    "    'densenet201': 'DenseNet-201',\n",
    "    'efficientnetb4': 'EfficientNet-B4',\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([850])\n",
      "torch.Size([850])\n",
      "Loading previous weights at epoch 499 from\n",
      "/media/fastdata/laves/regression_snapshots/efficientnetb4_gaussian_oct.pth.tar\n"
     ]
    }
   ],
   "source": [
    "resize_to = (256, 256)\n",
    "if dataset == 'BreastPathQ':\n",
    "    batch_size = 16\n",
    "    resize_to = (384, 384)\n",
    "    out_channels = 1\n",
    "\n",
    "    data_set = BreastPathQDataset(data_dir='/media/fastdata/laves/breastpathq/', augment=False, resize_to=resize_to)\n",
    "    assert len(data_set) > 0\n",
    "\n",
    "    calib_indices = torch.load('./data_indices/breastpathq_valid_indices.pth')\n",
    "    test_indices = torch.load('./data_indices/breastpathq_test_indices.pth')\n",
    "\n",
    "    print(calib_indices.shape)\n",
    "    print(test_indices.shape)\n",
    "\n",
    "    calib_loader = torch.utils.data.DataLoader(data_set, batch_size=batch_size,\n",
    "                                               sampler=SubsetRandomSampler(calib_indices))\n",
    "    test_loader = torch.utils.data.DataLoader(data_set, batch_size=batch_size,\n",
    "                                              sampler=SequentialSampler(test_indices))\n",
    "    \n",
    "    model = BreastPathQModel(base_model, out_channels=1).to(device)\n",
    "\n",
    "    checkpoint_path = glob(f\"/media/fastdata/laves/regression_snapshots/{base_model}_gaussian_breastpathq.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)\n",
    "elif dataset == 'BoneAge':\n",
    "    batch_size = 16\n",
    "    out_channels = 1\n",
    "\n",
    "    data_set = BoneAgeDataset(data_dir='/media/fastdata/laves/rsna-bone-age/', augment=False, resize_to=resize_to)\n",
    "    assert len(data_set) > 0\n",
    "\n",
    "    calib_indices = torch.load('./data_indices/boneage_valid_indices.pth')\n",
    "    test_indices = torch.load('./data_indices/boneage_test_indices.pth')\n",
    "\n",
    "    print(calib_indices.shape)\n",
    "    print(test_indices.shape)\n",
    "\n",
    "    calib_loader = torch.utils.data.DataLoader(data_set, batch_size=batch_size,\n",
    "                                               sampler=SubsetRandomSampler(calib_indices))\n",
    "    test_loader = torch.utils.data.DataLoader(data_set, batch_size=batch_size,\n",
    "                                              sampler=SubsetRandomSampler(test_indices))\n",
    "    \n",
    "    model = BreastPathQModel(base_model, in_channels=1, out_channels=1).to(device)\n",
    "\n",
    "    checkpoint_path = glob(f\"/media/fastdata/laves/regression_snapshots/{base_model}_gaussian_boneage.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']))\n",
    "elif dataset == 'EndoVis':\n",
    "    batch_size = 16\n",
    "    out_channels = 2\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)\n",
    "\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)\n",
    "elif dataset == 'OCT':\n",
    "    out_channels = 6\n",
    "    batch_size = 16\n",
    "\n",
    "    data_dir = '/media/fastdata/laves/oct_data_needle/data'\n",
    "    data_set = OCTDataset(data_dir=data_dir, augment=False, resize_to=resize_to)\n",
    "    assert len(data_set) > 0\n",
    "\n",
    "    calib_indices = torch.load('./data_indices/oct_valid_indices.pth')\n",
    "    test_indices = torch.load('./data_indices/oct_test_indices.pth')\n",
    "\n",
    "    print(calib_indices.shape)\n",
    "    print(test_indices.shape)\n",
    "\n",
    "    calib_loader = torch.utils.data.DataLoader(data_set, batch_size=batch_size,\n",
    "                                               sampler=SubsetRandomSampler(calib_indices))\n",
    "    test_loader = torch.utils.data.DataLoader(data_set, batch_size=batch_size,\n",
    "                                              sampler=SequentialSampler(test_indices))\n",
    "\n",
    "    model = BreastPathQModel(base_model, out_channels=6).to(device)\n",
    "\n",
    "    checkpoint_path = glob(f\"/media/fastdata/laves/regression_snapshots/{base_model}_gaussian_oct.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)\n",
    "else:\n",
    "    assert False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 54/54 [01:07<00:00,  1.25s/it]\n"
     ]
    }
   ],
   "source": [
    "model.eval()\n",
    "mus_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",
    "        mu, logvar, var_bayesian = model(data, dropout=True, mc_dropout=True)\n",
    "\n",
    "        mus_calib.append(mu.detach())\n",
    "        vars_calib.append(var_bayesian.detach())\n",
    "        logvars_calib.append(logvar.detach())\n",
    "        targets_calib.append(target.detach()) \n",
    "\n",
    "mu_calib = torch.cat(mus_calib, dim=0).clamp(0, 1)\n",
    "var_calib = torch.cat(vars_calib, dim=0)\n",
    "logvar_calib = torch.cat(logvars_calib, dim=0)\n",
    "target_calib = torch.cat(targets_calib, dim=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "err_calib = torch.pow(target_calib-mu_calib, 2).sqrt()\n",
    "\n",
    "uncertainty = 'total'\n",
    "\n",
    "uncert_calib_aleatoric = logvar_calib.exp()\n",
    "uncert_calib_epistemic = var_calib\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": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor(0.0015, device='cuda:0')\n",
      "tensor(0.0004, device='cuda:0')\n",
      "tensor(0.0144, device='cuda:0')\n",
      "tensor(0.0133, device='cuda:0')\n"
     ]
    }
   ],
   "source": [
    "print((err_calib**2).mean())\n",
    "print((uncert_calib**2).mean())\n",
    "print(uncert_calib_aleatoric.sqrt().mean())\n",
    "print(uncert_calib_epistemic.sqrt().mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
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       "    }\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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       "<img 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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": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor(1.9323, device='cuda:0')\n"
     ]
    }
   ],
   "source": [
    "# calculate optimal T\n",
    "S = (err_calib**2 / uncert_calib**2).mean().sqrt()\n",
    "print(S)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.9527008533477783\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": 12,
   "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": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-5.540228366851807\n"
     ]
    }
   ],
   "source": [
    "# find optimal aux\n",
    "aux = AuxModel(out_channels).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": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-4.036839485168457\n",
      "-5.525126934051514\n",
      "-5.525455474853516\n",
      "-5.540229797363281\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "AuxModel(\n",
       "  (linear1): Linear(in_features=6, out_features=16, bias=True)\n",
       "  (fc): Linear(in_features=16, out_features=6, bias=True)\n",
       ")"
      ]
     },
     "execution_count": 14,
     "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": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.049244679510593414\n",
      "0.04326901212334633\n",
      "0.04328388720750809\n",
      "0.04366026073694229\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": 16,
   "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": [
      "0.10585729032754898\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": 17,
   "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": [
      "0.017450192535761744\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": 18,
   "metadata": {
    "scrolled": true
   },
   "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": [
      "0.018578150775283575\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": 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"
    },
    {
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\" width=\"250\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.012800641707144678\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": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 54/54 [01:07<00:00,  1.24s/it]\n"
     ]
    }
   ],
   "source": [
    "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",
    "        mu, logvar, var_bayesian = model(data, dropout=True, mc_dropout=True)\n",
    "\n",
    "        mus_test.append(mu.detach())\n",
    "        vars_test.append(var_bayesian.detach())\n",
    "        logvars_test.append(logvar.detach())\n",
    "        targets_test.append(target.detach())\n",
    "\n",
    "    mu_test = torch.cat(mus_test, dim=0).clamp(0, 1)\n",
    "    var_test = torch.cat(vars_test, dim=0)\n",
    "    logvar_test = torch.cat(logvars_test, dim=0)\n",
    "    target_test = torch.cat(targets_test, dim=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "err_test = torch.pow(target_test-mu_test, 2).sqrt()\n",
    "\n",
    "uncert_aleatoric_test = logvar_test.exp()\n",
    "uncert_epistemic_test = var_test\n",
    "\n",
    "if uncertainty == 'aleatoric':\n",
    "    uncert_test = uncert_aleatoric_test.sqrt().clamp(0, 1)\n",
    "elif uncertainty == 'epistemic':\n",
    "    uncert_test = uncert_epistemic_test.sqrt().clamp(0, 1)\n",
    "else:\n",
    "    uncert_test = (uncert_aleatoric_test + uncert_epistemic_test).sqrt().clamp(0, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor(0.0007, device='cuda:0')\n",
      "tensor(0.0004, device='cuda:0')\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print((err_test**2).mean())\n",
    "print((uncert_test**2).mean())\n",
    "print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-5.991395950317383\n",
      "-6.076413154602051\n",
      "-6.0660505294799805\n",
      "-6.072226524353027\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "AuxModel(\n",
       "  (linear1): Linear(in_features=6, out_features=16, bias=True)\n",
       "  (fc): Linear(in_features=16, out_features=6, bias=True)\n",
       ")"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aux.train()\n",
    "print(nll_criterion_gaussian(mu_test, uncert_test.pow(2).log(), target_test).item())\n",
    "print(nll_criterion_gaussian(mu_test, (S*uncert_test).pow(2).log(), target_test).item())\n",
    "print(nll_criterion_gaussian(mu_test, scaler(uncert_test).pow(2).log(), target_test).item())\n",
    "print(nll_criterion_gaussian(mu_test, aux(uncert_test), target_test).item())\n",
    "print()\n",
    "aux.eval()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.022006645798683167\n",
      "0.023863403126597404\n",
      "0.024092555046081543\n",
      "0.023842252790927887\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(torch.nn.functional.mse_loss(uncert_test**2, err_test**2, reduction='sum').item())\n",
    "print(torch.nn.functional.mse_loss((S*uncert_test)**2, err_test**2, reduction='sum').item())\n",
    "print(torch.nn.functional.mse_loss(scaler(uncert_test)**2, err_test**2, reduction='sum').item())\n",
    "print(torch.nn.functional.mse_loss(aux(uncert_test)**2, err_test**2, reduction='sum').item())\n",
    "print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([850, 6])\n",
      "torch.Size([850, 6])\n",
      "torch.Size([850, 6])\n"
     ]
    }
   ],
   "source": [
    "print(target_test.shape)\n",
    "print(mu_test.shape)\n",
    "print(uncert_test.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Compute prediction intervals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.5, 0.6, 0.7, 0.8, 0.9, 0.95, 0.99]\n",
      "[0.6744897501960817, 0.8416212335729143, 1.0364333894937898, 1.2815515655446004, 1.6448536269514722, 1.959963984540054, 2.5758293035489004]\n"
     ]
    }
   ],
   "source": [
    "# compute sigma boundaries for 50%, 90%, 95% and 99% intervals\n",
    "\n",
    "from scipy.special import erfinv\n",
    "\n",
    "def probit(p):\n",
    "    return erfinv(p)*np.sqrt(2)\n",
    "\n",
    "expected_gamma = [0.5, 0.6, 0.7, 0.8, 0.9, 0.95, 0.99] #np.arange(0.1, 1.0, step=0.05)\n",
    "#expected_gamma = np.arange(0.9, 1.0, step=0.01)\n",
    "print(expected_gamma)\n",
    "stds = [probit(i) for i in expected_gamma]\n",
    "print(stds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([0., 0., 0., 0., 0., 0.], device='cuda:0')\n",
      "tensor([0.0699, 0.0449, 0.1196, 0.2461, 0.1240, 0.0320], device='cuda:0')\n",
      "tensor([0.0214, 0.0243, 0.0263, 0.0301, 0.0253, 0.0220], device='cuda:0')\n"
     ]
    }
   ],
   "source": [
    "# let's look at a sample\n",
    "print(target_test[0])\n",
    "print(mu_test[0])\n",
    "print(uncert_test[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "uncal\n",
      "0.6441176470588236\n",
      "0.6892156862745098\n",
      "0.7321568627450981\n",
      "0.7790196078431373\n",
      "0.8337254901960784\n",
      "0.8715686274509804\n",
      "0.9217647058823529\n"
     ]
    }
   ],
   "source": [
    "observed_gamma_uncal = []\n",
    "\n",
    "print('uncal')\n",
    "for std in stds:\n",
    "    within = torch.logical_and(\n",
    "        ((mu_test-std*uncert_test) < target_test),\n",
    "        (target_test < (mu_test+std*uncert_test))\n",
    "    ).sum().item()\n",
    "    print(within/(target_test.shape[0]*target_test.shape[1]))\n",
    "    observed_gamma_uncal.append(within/(target_test.shape[0]*target_test.shape[1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "temp\n",
      "0.7843137254901961\n",
      "0.8337254901960784\n",
      "0.8792156862745099\n",
      "0.917843137254902\n",
      "0.9531372549019608\n",
      "0.9701960784313726\n",
      "0.9915686274509804\n",
      "\n",
      "temp\n",
      "0.7843137254901961\n",
      "0.8337254901960784\n",
      "0.8792156862745099\n",
      "0.917843137254902\n",
      "0.9531372549019608\n",
      "0.9701960784313726\n",
      "0.9915686274509804\n",
      "\n",
      "aux\n",
      "0.7860784313725491\n",
      "0.8337254901960784\n",
      "0.8764705882352941\n",
      "0.9164705882352941\n",
      "0.9525490196078431\n",
      "0.9707843137254902\n",
      "0.9907843137254903\n"
     ]
    }
   ],
   "source": [
    "observed_gamma_cal = {}\n",
    "\n",
    "print('temp')\n",
    "obs_gamma_current = []\n",
    "for std in stds:\n",
    "    within = torch.logical_and(\n",
    "        ((mu_test-std*scaler(uncert_test)) < target_test),\n",
    "        (target_test < (mu_test+std*scaler(uncert_test)))\n",
    "    ).sum().item()\n",
    "    print(within/(target_test.shape[0]*target_test.shape[1]))\n",
    "    obs_gamma_current.append(within/(target_test.shape[0]*target_test.shape[1]))\n",
    "observed_gamma_cal['temp'] = obs_gamma_current\n",
    "print()\n",
    "\n",
    "print('temp')\n",
    "obs_gamma_current = []\n",
    "for std in stds:\n",
    "    within = torch.logical_and(\n",
    "        ((mu_test-std*scaler(uncert_test)) < target_test),\n",
    "        (target_test < (mu_test+std*scaler(uncert_test)))\n",
    "    ).sum().item()\n",
    "    print(within/(target_test.shape[0]*target_test.shape[1]))\n",
    "    obs_gamma_current.append(within/(target_test.shape[0]*target_test.shape[1]))\n",
    "observed_gamma_cal['temp'] = obs_gamma_current\n",
    "print()\n",
    "\n",
    "print('aux')\n",
    "obs_gamma_current = []\n",
    "for std in stds:\n",
    "    within = torch.logical_and(\n",
    "        ((mu_test-std*aux(uncert_test)) < target_test),\n",
    "        (target_test < (mu_test+std*aux(uncert_test)))\n",
    "    ).sum().item()\n",
    "    print(within/(target_test.shape[0]*target_test.shape[1]))\n",
    "    obs_gamma_current.append(within/(target_test.shape[0]*target_test.shape[1]))\n",
    "observed_gamma_cal['aux'] = obs_gamma_current"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "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": 31,
   "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=\"275\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, figsize=(2.75, 2.75))\n",
    "plt.plot([0.5, 0.99], [0.5, 0.99], 'k--')\n",
    "plt.plot(expected_gamma, observed_gamma_uncal, '.-', label=r'uncal.')\n",
    "plt.plot(expected_gamma, observed_gamma_cal['temp'], '.-', label=r'$ \\sigma $ sc.')\n",
    "plt.plot(expected_gamma, observed_gamma_cal['aux'], '.-', label='aux')\n",
    "#if base_model == 'resnet101':\n",
    "ax.legend(labelspacing=0.15, prop={'size': 10})\n",
    "ax.set_xlabel(r'estimated interval')\n",
    "ax.set_ylabel(r'observed interval')\n",
    "ax.set_title(base_model_caps[base_model] + '/' + dataset)\n",
    "fig.tight_layout()\n",
    "fig.savefig(\"prediction_interval_\"+ dataset +\"_\"+base_model+\".pdf\", bbox_inches='tight')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}